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+26
-7
@@ -17,6 +17,23 @@ NODE_ENV=production
|
||||
# The title displayed on the info page.
|
||||
# SERVER_TITLE=Coom Tunnel
|
||||
|
||||
# URL for the image displayed on the login page.
|
||||
# If not set, no image will be displayed.
|
||||
# LOGIN_IMAGE_URL=https://example.com/your-logo.png
|
||||
|
||||
# Whether to enable the token-based or password-based login for the main info page.
|
||||
# Defaults to true. Set to false to disable login and make the info page public.
|
||||
# ENABLE_INFO_PAGE_LOGIN=true
|
||||
|
||||
# Authentication mode for the service info page. (token | password)
|
||||
# If 'token', any valid user token is used (requires GATEKEEPER='user_token' mode).
|
||||
# If 'password', SERVICE_INFO_PASSWORD is used.
|
||||
# Defaults to 'token' if ENABLE_INFO_PAGE_LOGIN is true.
|
||||
# SERVICE_INFO_AUTH_MODE=token
|
||||
|
||||
# Password for the service info page if SERVICE_INFO_AUTH_MODE is 'password'.
|
||||
# SERVICE_INFO_PASSWORD=your-service-info-password
|
||||
|
||||
# The route name used to proxy requests to APIs, relative to the Web site root.
|
||||
# PROXY_ENDPOINT_ROUTE=/proxy
|
||||
|
||||
@@ -48,15 +65,14 @@ NODE_ENV=production
|
||||
# | mistral-small | mistral-medium | mistral-large | aws-claude |
|
||||
# | aws-claude-opus | gcp-claude | gcp-claude-opus | azure-turbo | azure-gpt4
|
||||
# | azure-gpt4-32k | azure-gpt4-turbo | azure-gpt4o | azure-o1 | azure-dall-e
|
||||
|
||||
# By default, all models are allowed except for dall-e and o1.
|
||||
# To allow DALL-E image generation, uncomment the line below and add 'dall-e' or
|
||||
# 'azure-dall-e' to the list of allowed model families.
|
||||
# ALLOWED_MODEL_FAMILIES=turbo,gpt4,gpt4-32k,gpt4-turbo,gpt4o,claude,claude-opus,gemini-flash,gemini-pro,gemini-ultra,mistral-tiny,mistral-small,mistral-medium,mistral-large,aws-claude,aws-claude-opus,gcp-claude,gcp-claude-opus,azure-turbo,azure-gpt4,azure-gpt4-32k,azure-gpt4-turbo,azure-gpt4o
|
||||
# | azure-gpt45 | azure-o1-mini | azure-o3-mini | deepseek | xai | o3 | o4-mini | gpt41 | gpt41-mini | gpt41-nano
|
||||
# By default, all models are allowed
|
||||
# To dissalow any, uncomment line below and edit
|
||||
# ALLOWED_MODEL_FAMILIES=turbo,gpt4,gpt4-32k,gpt45,gpt4-turbo,gpt4o,claude,claude-opus,gemini-flash,gemini-pro,gemini-ultra,mistral-tiny,mistral-small,mistral-medium,mistral-large,aws-claude,aws-claude-opus,gcp-claude,gcp-claude-opus,azure-turbo,azure-gpt4,azure-gpt4-32k,azure-gpt4-turbo,azure-gpt4o,azure-gpt45,azure-o1-mini,azure-o3-mini,deepseek
|
||||
|
||||
# Which services can be used to process prompts containing images via multimodal
|
||||
# models. The following services are recognized:
|
||||
# openai | anthropic | aws | gcp | azure | google-ai | mistral-ai
|
||||
# openai | anthropic | aws | gcp | azure | google-ai | mistral-ai | xai
|
||||
# Do not enable this feature unless all users are trusted, as you will be liable
|
||||
# for any user-submitted images containing illegal content.
|
||||
# By default, no image services are allowed and image prompts are rejected.
|
||||
@@ -120,8 +136,11 @@ NODE_ENV=production
|
||||
|
||||
# Which access control method to use. (none | proxy_key | user_token)
|
||||
# GATEKEEPER=none
|
||||
# Which persistence method to use. (memory | firebase_rtdb)
|
||||
# Which persistence method to use. (memory | firebase_rtdb | sqlite)
|
||||
# GATEKEEPER_STORE=memory
|
||||
# If using sqlite store, path to the SQLite database file for user data.
|
||||
# Defaults to data/user-store.sqlite in the project directory.
|
||||
# SQLITE_USER_STORE_PATH=data/user-store.sqlite3
|
||||
|
||||
# Maximum number of unique IPs a user can connect from. (0 for unlimited)
|
||||
# MAX_IPS_PER_USER=0
|
||||
|
||||
+1
-1
@@ -7,5 +7,5 @@
|
||||
build
|
||||
greeting.md
|
||||
node_modules
|
||||
|
||||
.windsurfrules
|
||||
http-client.private.env.json
|
||||
|
||||
@@ -0,0 +1,33 @@
|
||||
You are a Senior Full Stack Developer and an Expert in ReactJS, NextJS, JavaScript, TypeScript, HTML, CSS and modern UI/UX frameworks (e.g., TailwindCSS, Shadcn, Radix). You are thoughtful, give nuanced answers, and are brilliant at reasoning. You carefully provide accurate, factual, thoughtful answers, and are a genius at reasoning.
|
||||
|
||||
- Follow the user’s requirements carefully & to the letter.
|
||||
- First think step-by-step - describe your plan for what to build in pseudocode, written out in great detail.
|
||||
- Confirm, then write code!
|
||||
- Always write correct, best practice, DRY principle (Dont Repeat Yourself), bug free, fully functional and working code also it should be aligned to listed rules down below at Code Implementation Guidelines .
|
||||
- Focus on easy and readability code, over being performant.
|
||||
- Fully implement all requested functionality.
|
||||
- Leave NO todo’s, placeholders or missing pieces.
|
||||
- Ensure code is complete! Verify thoroughly finalised.
|
||||
- Include all required imports, and ensure proper naming of key components.
|
||||
- Be concise Minimize any other prose.
|
||||
- If you think there might not be a correct answer, you say so.
|
||||
- If you do not know the answer, say so, instead of guessing.
|
||||
|
||||
### Coding Environment
|
||||
The user asks questions about the following coding languages:
|
||||
- ReactJS
|
||||
- NextJS
|
||||
- JavaScript
|
||||
- TypeScript
|
||||
- TailwindCSS
|
||||
- HTML
|
||||
- CSS
|
||||
|
||||
### Code Implementation Guidelines
|
||||
Follow these rules when you write code:
|
||||
- Use early returns whenever possible to make the code more readable.
|
||||
- Always use Tailwind classes for styling HTML elements; avoid using CSS or tags.
|
||||
- Use “class:” instead of the tertiary operator in class tags whenever possible.
|
||||
- Use descriptive variable and function/const names. Also, event functions should be named with a “handle” prefix, like “handleClick” for onClick and “handleKeyDown” for onKeyDown.
|
||||
- Implement accessibility features on elements. For example, a tag should have a tabindex=“0”, aria-label, on:click, and on:keydown, and similar attributes.
|
||||
- Use consts instead of functions, for example, “const toggle = () =>”. Also, define a type if possible.
|
||||
@@ -0,0 +1,321 @@
|
||||
# Project Codebase Guide
|
||||
|
||||
This document serves as a guide and index for the project codebase, designed to help developers and AI agents quickly understand its structure, components, and how to contribute.
|
||||
|
||||
## Table of Contents
|
||||
|
||||
1. [Project Overview](#project-overview)
|
||||
2. [Directory Structure](#directory-structure)
|
||||
3. [Core Components](#core-components)
|
||||
* [Configuration (`src/config.ts`)](#configuration)
|
||||
* [Server Entry Point (`src/server.ts`)](#server-entry-point)
|
||||
* [Proxy Layer (`src/proxy/`)](#proxy-layer)
|
||||
* [User Management (`src/user/`)](#user-management)
|
||||
* [Admin Interface (`src/admin/`)](#admin-interface)
|
||||
* [Shared Utilities (`src/shared/`)](#shared-utilities)
|
||||
4. [Proxy Functionality](#proxy-functionality)
|
||||
* [Routing (`src/proxy/routes.ts`)](#proxy-routing)
|
||||
* [Supported Models & Providers](#supported-models--providers)
|
||||
* [Middleware (`src/proxy/middleware/`)](#proxy-middleware)
|
||||
* [Adding New Models](#adding-new-models)
|
||||
* [Adding New APIs/Providers](#adding-new-apisproviders)
|
||||
5. [Model Management](#model-management)
|
||||
* [Model Family Definitions](#model-family-definitions)
|
||||
* [Adding OpenAI Models](#adding-openai-models)
|
||||
* [Model Mapping & Routing](#model-mapping--routing)
|
||||
* [Service Information](#service-information)
|
||||
* [Step-by-Step Guide for Adding a New Model](#step-by-step-guide-for-adding-a-new-model)
|
||||
* [Model Patterns and Versioning](#model-patterns-and-versioning)
|
||||
* [Response Format Handling](#response-format-handling)
|
||||
6. [Key Management](#key-management)
|
||||
* [Key Pool System](#key-pool-system)
|
||||
* [Provider-Specific Key Management](#provider-specific-key-management)
|
||||
* [Key Rotation and Health Checks](#key-rotation-and-health-checks)
|
||||
7. [Data Management](#data-management)
|
||||
* [Database (`src/shared/database/`)](#database)
|
||||
* [File Storage (`src/shared/file-storage/`)](#file-storage)
|
||||
8. [Authentication & Authorization](#authentication--authorization)
|
||||
9. [Logging & Monitoring](#logging--monitoring)
|
||||
10. [Deployment](#deployment)
|
||||
11. [Contributing](#contributing)
|
||||
|
||||
## Project Overview
|
||||
|
||||
This project provides a proxy layer for various Large Language Models (LLMs) and potentially other AI APIs. It aims to offer a unified interface, manage API keys securely, handle rate limiting, usage tracking, and potentially add features like response caching or prompt modification.
|
||||
|
||||
## Directory Structure
|
||||
|
||||
```
|
||||
.
|
||||
├── .env.example # Example environment variables
|
||||
├── .gitattributes # Git attributes
|
||||
├── .gitignore # Git ignore rules
|
||||
├── .husky/ # Git hooks
|
||||
├── .prettierrc # Code formatting rules
|
||||
├── CODEBASE_GUIDE.md # This file
|
||||
├── README.md # Project README
|
||||
├── data/ # Data files (e.g., SQLite DB)
|
||||
├── docker/ # Docker configuration
|
||||
├── docs/ # Documentation files
|
||||
├── http-client.env.json # HTTP client environment
|
||||
├── package-lock.json # NPM lock file
|
||||
├── package.json # Project dependencies and scripts
|
||||
├── patches/ # Patches for dependencies
|
||||
├── public/ # Static assets served by the web server
|
||||
├── render.yaml # Render deployment configuration
|
||||
├── scripts/ # Utility scripts
|
||||
├── src/ # Source code
|
||||
│ ├── admin/ # Admin interface logic
|
||||
│ ├── config.ts # Application configuration
|
||||
│ ├── info-page.ts # Logic for the info page
|
||||
│ ├── logger.ts # Logging setup
|
||||
│ ├── proxy/ # Core proxy logic for different providers
|
||||
│ ├── server.ts # Express server setup and main entry point
|
||||
│ ├── service-info.ts # Service information logic
|
||||
│ ├── shared/ # Shared utilities, types, and modules
|
||||
│ └── user/ # User management logic
|
||||
├── tsconfig.json # TypeScript configuration
|
||||
```
|
||||
|
||||
## Core Components
|
||||
|
||||
### Configuration (`src/config.ts`)
|
||||
|
||||
* Loads environment variables and defines application settings.
|
||||
* Contains configuration for database connections, API keys (placeholders/retrieval methods), logging levels, rate limits, etc.
|
||||
* Uses `dotenv` and potentially a schema validation library (like Zod) to ensure required variables are present.
|
||||
|
||||
### Server Entry Point (`src/server.ts`)
|
||||
|
||||
* Initializes the Express application.
|
||||
* Sets up core middleware (e.g., body parsing, CORS, logging).
|
||||
* Mounts routers for different parts of the application (admin, user, proxy).
|
||||
* Starts the HTTP server.
|
||||
|
||||
### Proxy Layer (`src/proxy/`)
|
||||
|
||||
* The heart of the application, handling requests to downstream AI APIs.
|
||||
* Contains individual modules for each supported provider (e.g., `openai.ts`, `anthropic.ts`).
|
||||
* Handles request transformation, authentication against the target API, and response handling.
|
||||
* Uses middleware for common proxy tasks.
|
||||
|
||||
### User Management (`src/user/`)
|
||||
|
||||
* Handles user registration, login, session management, and potentially API key generation/management for end-users.
|
||||
* Likely interacts with the database (`src/shared/database/`).
|
||||
|
||||
### Admin Interface (`src/admin/`)
|
||||
|
||||
* Provides an interface for administrators to manage users, monitor usage, configure settings, etc.
|
||||
* May have its own set of routes and views.
|
||||
|
||||
### Shared Utilities (`src/shared/`)
|
||||
|
||||
* Contains reusable code across different modules.
|
||||
* `api-schemas/`: Zod schemas for API request/response validation.
|
||||
* `database/`: Database connection, schemas (e.g., Prisma), and query logic.
|
||||
* `errors.ts`: Custom error classes.
|
||||
* `key-management/`: Logic for managing API keys (if applicable).
|
||||
* `models.ts`: Core data models/types used throughout the application.
|
||||
* `prompt-logging/`: Logic for logging prompts and responses.
|
||||
* `tokenization/`: Utilities for counting tokens.
|
||||
* `utils.ts`: General utility functions.
|
||||
|
||||
## Proxy Functionality
|
||||
|
||||
### Proxy Routing (`src/proxy/routes.ts`)
|
||||
|
||||
* Defines the API endpoints for the proxy service (e.g., `/v1/chat/completions`).
|
||||
* Maps incoming requests to the appropriate provider-specific handler based on the request path, headers, or body content (e.g., model requested).
|
||||
* Applies relevant middleware (authentication, rate limiting, queuing, etc.).
|
||||
|
||||
### Supported Models & Providers
|
||||
|
||||
* **OpenAI:** Handled in `src/proxy/openai.ts`. Supports models like GPT-4, GPT-3.5-turbo, as well as o-series models (o1, o1-mini, o1-pro, o3, o3-mini, o3-pro, o4-mini). Handles chat completions and potentially image generation (`src/proxy/openai-image.ts`).
|
||||
* **Anthropic:** Handled in `src/proxy/anthropic.ts`. Supports Claude models. May use AWS Bedrock (`src/proxy/aws-claude.ts`) or Anthropic's direct API.
|
||||
* **Google AI / Vertex AI:** Handled in `src/proxy/google-ai.ts` and `src/proxy/gcp.ts`. Supports Gemini models (gemini-flash, gemini-pro, gemini-ultra).
|
||||
* **Mistral AI:** Handled in `src/proxy/mistral-ai.ts`. Supports Mistral models via their API or potentially AWS (`src/proxy/aws-mistral.ts`).
|
||||
* **Azure OpenAI:** Handled in `src/proxy/azure.ts`. Provides an alternative endpoint for OpenAI models via Azure.
|
||||
* **Deepseek:** Handled in `src/proxy/deepseek.ts`.
|
||||
* **Xai:** Handled in `src/proxy/xai.ts`.
|
||||
* **AWS (General):** `src/proxy/aws.ts` might contain shared AWS logic (e.g., authentication).
|
||||
|
||||
### Middleware (`src/proxy/middleware/`)
|
||||
|
||||
* **`gatekeeper.ts`:** Likely handles initial request validation, authentication, and authorization checks before hitting provider logic. Checks origin (`check-origin.ts`), potentially custom tokens (`check-risu-token.ts`).
|
||||
* **`rate-limit.ts`:** Implements rate limiting logic, potentially per-user or per-key.
|
||||
* **`queue.ts`:** Manages request queuing, possibly to handle concurrency limits or prioritize requests.
|
||||
|
||||
### Adding New Models
|
||||
|
||||
1. **Identify the Provider:** Determine if the new model belongs to an existing provider (e.g., a new OpenAI model) or a new one.
|
||||
2. **Update Provider Logic (if existing):**
|
||||
* Modify the relevant provider file (e.g., `src/proxy/openai.ts`).
|
||||
* Update model lists or logic that selects/validates models.
|
||||
* Adjust any request/response transformations if the new model has a different API schema.
|
||||
* Update model information in shared files like `src/shared/models.ts` if necessary.
|
||||
3. **Update Routing (if necessary):** Modify `src/proxy/routes.ts` if the new model requires a different endpoint or routing logic.
|
||||
4. **Configuration:** Add any new API keys or configuration parameters to `.env.example` and `src/config.ts`.
|
||||
5. **Testing:** Add unit or integration tests for the new model.
|
||||
|
||||
### Adding New APIs/Providers
|
||||
|
||||
1. **Create Provider Module:** Create a new file in `src/proxy/` (e.g., `src/proxy/new-provider.ts`).
|
||||
2. **Implement Handler:**
|
||||
* Write the core logic to handle requests for this provider. This typically involves:
|
||||
* Receiving the standardized request from the router.
|
||||
* Transforming the request into the format expected by the new provider's API.
|
||||
* Authenticating with the new provider's API (fetching keys from config).
|
||||
* Making the API call (consider using a robust HTTP client like `axios` or `node-fetch`).
|
||||
* Handling streaming responses if applicable (using helpers from `src/shared/streaming.ts`).
|
||||
* Transforming the provider's response back into a standardized format.
|
||||
* Handling errors gracefully.
|
||||
3. **Add Routing:**
|
||||
* Import the new handler in `src/proxy/routes.ts`.
|
||||
* Add new routes or modify existing routing logic to direct requests to the new handler based on model name, path, or other criteria.
|
||||
* Apply necessary middleware (gatekeeper, rate limiter, queue).
|
||||
4. **Create Key Management:**
|
||||
* Create a new directory in `src/shared/key-management/` for the provider.
|
||||
* Implement provider-specific key management (key checkers, token counters).
|
||||
5. **Configuration:**
|
||||
* Add configuration variables (API keys, base URLs) to `.env.example` and `src/config.ts`.
|
||||
* Update `src/config.ts` to load and validate the new variables.
|
||||
6. **Model Information:** Add details about the new provider and its models to `src/shared/models.ts` or similar shared locations.
|
||||
7. **Tokenization (if applicable):** If token counting is needed, add or update tokenization logic in `src/shared/tokenization/`.
|
||||
8. **Testing:** Implement thorough tests for the new provider integration.
|
||||
9. **Documentation:** Update this guide and any other relevant documentation.
|
||||
|
||||
## Model Management
|
||||
|
||||
### Model Family Definitions
|
||||
|
||||
* **Model Family Definitions:** The project uses a family-based approach to group similar models together. These are defined in `src/shared/models.ts`.
|
||||
* Each model is part of a model family (e.g., "gpt4", "claude", "gemini-pro") which helps with routing, key management, and feature support.
|
||||
* The `MODEL_FAMILIES` array contains all supported model families, and the `MODEL_FAMILY_SERVICE` mapping connects each family to its provider service.
|
||||
|
||||
### Adding OpenAI Models
|
||||
|
||||
When adding new OpenAI models to the codebase, there are several files that must be updated:
|
||||
|
||||
1. **Update Model Types (`src/shared/models.ts`):**
|
||||
- Add the new model to the `OpenAIModelFamily` type
|
||||
- Add the model to the `MODEL_FAMILIES` array
|
||||
- Add the Azure variants for the model if applicable
|
||||
- Add the model to `MODEL_FAMILY_SERVICE` mapping
|
||||
- Update `OPENAI_MODEL_FAMILY_MAP` with regex patterns to match the model names
|
||||
|
||||
2. **Update Context Size Limits (`src/proxy/middleware/request/preprocessors/validate-context-size.ts`):**
|
||||
- Add regex matching for the new model
|
||||
- Set the appropriate context token limit for the model
|
||||
|
||||
3. **Update Token Cost Tracking (`src/shared/stats.ts`):**
|
||||
- Add pricing information for the new model in the `getTokenCostUsd` function
|
||||
- Include both input and output prices in the comments for clarity
|
||||
|
||||
4. **Update Feature Support Checks (`src/proxy/openai.ts`):**
|
||||
- If the model supports special features like the reasoning API parameter (`isO1Model` function), update the appropriate function
|
||||
- For model feature detection, prefer using regex patterns over explicit lists when possible, as this handles date-stamped versions better
|
||||
|
||||
5. **Update Display Names (`src/info-page.ts`):**
|
||||
- Add friendly display names for the new models in the `MODEL_FAMILY_FRIENDLY_NAME` object
|
||||
|
||||
6. **Update Key Management Provider Files:**
|
||||
- For OpenAI keys in `src/shared/key-management/openai/provider.ts`, add token counters for the new models
|
||||
- For Azure OpenAI keys in `src/shared/key-management/azure/provider.ts`, add token counters for the Azure versions
|
||||
|
||||
### Model Patterns and Versioning
|
||||
|
||||
The codebase handles several patterns for model naming and versioning:
|
||||
|
||||
1. **Date-stamped Models:** Many models include date stamps (e.g., `gpt-4-0125-preview`). The regex patterns in `OPENAI_MODEL_FAMILY_MAP` account for these with patterns like `^gpt-4o(-\\d{4}-\\d{2}-\\d{2})?$`.
|
||||
|
||||
2. **O-Series Models:** OpenAI's o-series models (o1, o1-mini, o1-pro, o3, o3-mini, o3-pro, o4-mini) follow a different naming convention. The codebase handles these with dedicated model families and regex patterns.
|
||||
|
||||
3. **Preview/Non-Preview Variants:** Some models have preview variants (e.g., `gpt-4.5-preview`). The regex patterns in `OPENAI_MODEL_FAMILY_MAP` account for these with patterns like `^gpt-4\\.5(-preview)?(-\\d{4}-\\d{2}-\\d{2})?$`.
|
||||
|
||||
When adding new models, try to follow the existing patterns for consistency.
|
||||
|
||||
### Response Format Handling
|
||||
|
||||
The codebase includes special handling for different API response formats:
|
||||
|
||||
1. **Chat vs. Text Completions:** There's transformation logic in `openai.ts` to convert between chat completions and text completions formats (`transformTurboInstructResponse`).
|
||||
|
||||
2. **Newer API Formats:** For newer APIs like the Responses API, there's transformation logic (`transformResponsesApiResponse`) to convert responses to a format compatible with existing clients.
|
||||
|
||||
When adding support for new models or APIs, consider whether transformation is needed to maintain compatibility with existing clients.
|
||||
|
||||
## Key Management
|
||||
|
||||
### Key Pool System
|
||||
|
||||
The project uses a sophisticated key pool system (`src/shared/key-management/key-pool.ts`) to manage API keys for different providers. Key features include:
|
||||
|
||||
* **Key Selection:** The system selects the appropriate key based on model family, region preferences, and other criteria.
|
||||
* **Rotation:** Keys are rotated to distribute usage and avoid hitting rate limits.
|
||||
* **Health Checks:** Keys are checked periodically to ensure they're still valid and within rate limits.
|
||||
|
||||
### Provider-Specific Key Management
|
||||
|
||||
Each provider has its own key management module in `src/shared/key-management/`:
|
||||
|
||||
* **Key Checkers:** Each provider implements key checkers to validate keys and check their status.
|
||||
* **Token Counters:** Providers implement token counting logic specific to their pricing model.
|
||||
* **Models Support:** Keys are associated with specific model families they support.
|
||||
|
||||
When adding a new model or provider, you'll need to update or create the appropriate key management files.
|
||||
|
||||
### Key Rotation and Health Checks
|
||||
|
||||
The key pool system includes logic for:
|
||||
|
||||
* **Rotation Strategy:** Keys are selected based on a prioritization strategy (`prioritize-keys.ts`).
|
||||
* **Disabling Unhealthy Keys:** Keys that fail health checks are temporarily disabled.
|
||||
* **Rate Limit Awareness:** The system tracks usage to avoid hitting provider rate limits.
|
||||
|
||||
## Data Management
|
||||
|
||||
### Database (`src/shared/database/`)
|
||||
|
||||
* Likely uses Prisma or a similar ORM.
|
||||
* Defines database schemas (e.g., for users, API keys, usage logs).
|
||||
* Provides functions for interacting with the database.
|
||||
* Configuration is managed in `src/config.ts`.
|
||||
|
||||
### File Storage (`src/shared/file-storage/`)
|
||||
|
||||
* May be used for storing logs, cached data, or user-uploaded files.
|
||||
* Could integrate with local storage or cloud providers (e.g., S3, GCS).
|
||||
|
||||
## Authentication & Authorization
|
||||
|
||||
* **User Auth:** Handled in `src/user/` potentially using sessions (`src/shared/with-session.ts`) or JWTs.
|
||||
* **Proxy Auth:** The `gatekeeper.ts` middleware likely verifies incoming requests to the proxy endpoints. This could involve checking:
|
||||
* Custom API keys stored in the database (`src/shared/database/`).
|
||||
* Specific tokens (`check-risu-token.ts`).
|
||||
* HMAC signatures (`src/shared/hmac-signing.ts`).
|
||||
* Origin checks (`check-origin.ts`).
|
||||
* **Downstream Auth:** Each provider module (`src/proxy/*.ts`) handles authentication with the actual AI service API using keys from the configuration.
|
||||
|
||||
## Logging & Monitoring
|
||||
|
||||
* **Logging:** Configured in `src/logger.ts`, likely using a library like `pino` or `winston`. Logs requests, errors, and important events.
|
||||
* **Prompt Logging:** Specific logic for logging prompts and responses might exist in `src/shared/prompt-logging/`.
|
||||
* **Stats/Monitoring:** `src/shared/stats.ts` might handle collecting and exposing application metrics.
|
||||
|
||||
## Deployment
|
||||
|
||||
* **Docker:** The project likely includes Docker configuration for containerized deployment.
|
||||
* **Render:** The `render.yaml` file suggests the project is or can be deployed on Render.
|
||||
* **Environment Variables:** The `.env.example` file provides a template for required environment variables in production.
|
||||
|
||||
## Contributing
|
||||
|
||||
When contributing to this project:
|
||||
|
||||
1. **Follow Coding Standards:** Use the established patterns and standards in the codebase. The `.prettierrc` file defines code formatting rules.
|
||||
2. **Update Documentation:** Keep this guide updated when adding new components or changing existing ones.
|
||||
3. **Add Tests:** Ensure your changes are tested appropriately.
|
||||
4. **Update Configuration:** If your changes require new environment variables, update `.env.example`.
|
||||
|
||||
*This guide provides a high-level overview. For detailed information, refer to the specific source code files.*
|
||||
@@ -1,4 +1,4 @@
|
||||
# OAI Reverse Proxy
|
||||
# OAI Reverse Proxy - just a shitty fork
|
||||
Reverse proxy server for various LLM APIs.
|
||||
|
||||
### Table of Contents
|
||||
@@ -23,7 +23,7 @@ This project allows you to run a reverse proxy server for various LLM APIs.
|
||||
- [x] Support for multiple APIs
|
||||
- [x] [OpenAI](https://openai.com/)
|
||||
- [x] [Anthropic](https://www.anthropic.com/)
|
||||
- [x] [AWS Bedrock](https://aws.amazon.com/bedrock/)
|
||||
- [x] [AWS Bedrock](https://aws.amazon.com/bedrock/) (Claude4 is fucked, dont care)
|
||||
- [x] [Vertex AI (GCP)](https://cloud.google.com/vertex-ai/)
|
||||
- [x] [Google MakerSuite/Gemini API](https://ai.google.dev/)
|
||||
- [x] [Azure OpenAI](https://azure.microsoft.com/en-us/products/ai-services/openai-service)
|
||||
|
||||
@@ -12,6 +12,7 @@ Several of these features require you to set secrets in your environment. If usi
|
||||
- [Memory](#memory)
|
||||
- [Firebase Realtime Database](#firebase-realtime-database)
|
||||
- [Firebase setup instructions](#firebase-setup-instructions)
|
||||
- [SQLite Database](#sqlite-database)
|
||||
- [Whitelisting admin IP addresses](#whitelisting-admin-ip-addresses)
|
||||
|
||||
## No user management (`GATEKEEPER=none`)
|
||||
@@ -63,6 +64,17 @@ To use Firebase Realtime Database to persist user data, set the following enviro
|
||||
|
||||
The proxy server will attempt to connect to your Firebase Realtime Database at startup and will throw an error if it cannot connect. If you see this error, check that your `FIREBASE_RTDB_URL` and `FIREBASE_KEY` secrets are set correctly.
|
||||
|
||||
### SQLite Database
|
||||
|
||||
To use a local SQLite database file to persist user data, set the following environment variables:
|
||||
|
||||
- `GATEKEEPER_STORE`: Set this to `sqlite`.
|
||||
- `SQLITE_USER_STORE_PATH` (Optional): Specifies the path to the SQLite database file.
|
||||
- If not set, it defaults to `data/user-store.sqlite` within the project directory.
|
||||
- Ensure that the directory where the SQLite file will be created (e.g., the `data/` directory) is writable by the application process.
|
||||
|
||||
Using SQLite provides a simple way to persist user data locally without relying on external services. User data will be saved to the specified file and will be available across server restarts.
|
||||
|
||||
## Whitelisting admin IP addresses
|
||||
You can add your own IP ranges to the `ADMIN_WHITELIST` environment variable for additional security.
|
||||
|
||||
|
||||
Generated
+499
-325
File diff suppressed because it is too large
Load Diff
+2
-2
@@ -53,7 +53,7 @@
|
||||
"pino-http": "^8.3.3",
|
||||
"proxy-agent": "^6.4.0",
|
||||
"sanitize-html": "^2.13.0",
|
||||
"sharp": "^0.32.6",
|
||||
"sharp": "^0.34.2",
|
||||
"showdown": "^2.1.0",
|
||||
"source-map-support": "^0.5.21",
|
||||
"stream-json": "^1.8.0",
|
||||
@@ -78,7 +78,7 @@
|
||||
"@types/stream-json": "^1.7.7",
|
||||
"@types/uuid": "^9.0.1",
|
||||
"concurrently": "^8.0.1",
|
||||
"esbuild": "^0.17.16",
|
||||
"esbuild": "^0.25.5",
|
||||
"esbuild-register": "^3.4.2",
|
||||
"husky": "^8.0.3",
|
||||
"nodemon": "^3.0.1",
|
||||
|
||||
@@ -13,6 +13,7 @@ import { eventsApiRouter } from "./api/events";
|
||||
import { usersApiRouter } from "./api/users";
|
||||
import { usersWebRouter as webRouter } from "./web/manage";
|
||||
import { logger } from "../logger";
|
||||
import { keyPool } from "../shared/key-management";
|
||||
|
||||
const adminRouter = Router();
|
||||
|
||||
@@ -36,6 +37,43 @@ adminRouter.use(injectCsrfToken);
|
||||
adminRouter.use("/users", authorize({ via: "header" }), usersApiRouter);
|
||||
adminRouter.use("/events", authorize({ via: "header" }), eventsApiRouter);
|
||||
|
||||
// Special endpoint to validate organization verification status for all OpenAI keys
|
||||
// This checks both gpt-image-1 and o3 streaming access which require verified organizations
|
||||
adminRouter.post("/validate-gpt-image-keys", authorize({ via: "header" }), async (req, res) => {
|
||||
try {
|
||||
logger.info("Manual validation of organization verification status initiated");
|
||||
|
||||
// Use the specialized validation function that tests each key's organization verification
|
||||
// status using o3 streaming and waits for the results
|
||||
const results = await keyPool.validateGptImageAccess();
|
||||
|
||||
logger.info({
|
||||
total: results.total,
|
||||
verified: results.verified.length,
|
||||
removed: results.removed.length,
|
||||
errors: results.errors.length
|
||||
}, "Manual organization verification check completed");
|
||||
|
||||
return res.json({
|
||||
success: true,
|
||||
message: "Organization verification check completed",
|
||||
results: {
|
||||
total: results.total,
|
||||
verified: results.verified.length,
|
||||
removed: results.removed.length,
|
||||
errors: results.errors.length,
|
||||
// Only include hashes, not full keys
|
||||
verified_keys: results.verified,
|
||||
removed_keys: results.removed,
|
||||
error_details: results.errors
|
||||
}
|
||||
});
|
||||
} catch (error) {
|
||||
logger.error({ error }, "Error validating organization verification status for OpenAI keys");
|
||||
return res.status(500).json({ error: "Failed to validate keys", details: error.message });
|
||||
}
|
||||
});
|
||||
|
||||
adminRouter.use(checkCsrfToken);
|
||||
adminRouter.use(injectLocals);
|
||||
adminRouter.use("/", loginRouter);
|
||||
|
||||
+76
-7
@@ -132,10 +132,11 @@ router.post("/create-user", (req, res) => {
|
||||
)
|
||||
.transform((data: any) => {
|
||||
const expiresAt = Date.now() + data.temporaryUserDuration * 60 * 1000;
|
||||
const tokenLimits = MODEL_FAMILIES.reduce((limits, model) => {
|
||||
limits[model] = data[`temporaryUserQuota_${model}`];
|
||||
const tokenLimits = MODEL_FAMILIES.reduce((limits, modelFamily) => {
|
||||
const quotaValue = data[`temporaryUserQuota_${modelFamily}`];
|
||||
limits[modelFamily] = typeof quotaValue === 'number' ? quotaValue : 0;
|
||||
return limits;
|
||||
}, {} as UserTokenCounts);
|
||||
}, {} as any);
|
||||
return { ...data, expiresAt, tokenLimits };
|
||||
});
|
||||
|
||||
@@ -189,7 +190,70 @@ router.post("/import-users", upload.single("users"), (req, res) => {
|
||||
if (!req.file) throw new HttpError(400, "No file uploaded");
|
||||
|
||||
const data = JSON.parse(req.file.buffer.toString());
|
||||
const result = z.array(UserPartialSchema).safeParse(data.users);
|
||||
|
||||
// Transform old token count format to new format
|
||||
const transformedUsers = data.users.map((user: any) => {
|
||||
if (user.tokenCounts) {
|
||||
const transformedTokenCounts: any = {};
|
||||
for (const [family, value] of Object.entries(user.tokenCounts)) {
|
||||
if (typeof value === 'number') {
|
||||
// Old format: just a number (legacy_total)
|
||||
transformedTokenCounts[family] = {
|
||||
input: 0,
|
||||
output: 0,
|
||||
legacy_total: value
|
||||
};
|
||||
} else if (typeof value === 'object' && value !== null) {
|
||||
// New format or partially new format
|
||||
const transformedCounts: { input: number; output: number; legacy_total?: number } = {
|
||||
input: (value as any).input || 0,
|
||||
output: (value as any).output || 0
|
||||
};
|
||||
if ((value as any).legacy_total !== undefined) {
|
||||
transformedCounts.legacy_total = (value as any).legacy_total;
|
||||
}
|
||||
transformedTokenCounts[family] = transformedCounts;
|
||||
}
|
||||
}
|
||||
user.tokenCounts = transformedTokenCounts;
|
||||
}
|
||||
|
||||
// Handle tokenLimits - should be flat numbers
|
||||
if (user.tokenLimits) {
|
||||
const transformedTokenLimits: any = {};
|
||||
for (const [family, value] of Object.entries(user.tokenLimits)) {
|
||||
if (typeof value === 'number') {
|
||||
// Already in correct format
|
||||
transformedTokenLimits[family] = value;
|
||||
} else if (typeof value === 'object' && value !== null) {
|
||||
// Old format with input/output/legacy_total - sum them up
|
||||
const val = value as any;
|
||||
transformedTokenLimits[family] = (val.input ?? 0) + (val.output ?? 0) + (val.legacy_total ?? 0);
|
||||
}
|
||||
}
|
||||
user.tokenLimits = transformedTokenLimits;
|
||||
}
|
||||
|
||||
// Handle tokenRefresh - should be flat numbers
|
||||
if (user.tokenRefresh) {
|
||||
const transformedTokenRefresh: any = {};
|
||||
for (const [family, value] of Object.entries(user.tokenRefresh)) {
|
||||
if (typeof value === 'number') {
|
||||
// Already in correct format
|
||||
transformedTokenRefresh[family] = value;
|
||||
} else if (typeof value === 'object' && value !== null) {
|
||||
// Old format with input/output/legacy_total - sum them up
|
||||
const val = value as any;
|
||||
transformedTokenRefresh[family] = (val.input ?? 0) + (val.output ?? 0) + (val.legacy_total ?? 0);
|
||||
}
|
||||
}
|
||||
user.tokenRefresh = transformedTokenRefresh;
|
||||
}
|
||||
|
||||
return user;
|
||||
});
|
||||
|
||||
const result = z.array(UserPartialSchema).safeParse(transformedUsers);
|
||||
if (!result.success) throw new HttpError(400, result.error.toString());
|
||||
|
||||
const upserts = result.data.map((user) => userStore.upsertUser(user));
|
||||
@@ -547,9 +611,14 @@ router.post("/generate-stats", (req, res) => {
|
||||
function getSumsForUser(user: User) {
|
||||
const sums = MODEL_FAMILIES.reduce(
|
||||
(s, model) => {
|
||||
const tokens = user.tokenCounts[model] ?? 0;
|
||||
s.sumTokens += tokens;
|
||||
s.sumCost += getTokenCostUsd(model, tokens);
|
||||
const counts = user.tokenCounts[model] ?? { input: 0, output: 0 };
|
||||
// Ensure inputTokens and outputTokens are numbers, defaulting to 0 if NaN or undefined
|
||||
const inputTokens = Number(counts.input) || 0;
|
||||
const outputTokens = Number(counts.output) || 0;
|
||||
// We could also consider legacy_total here if input and output are 0
|
||||
// For now, sumTokens and sumCost will be based on current input/output.
|
||||
s.sumTokens += inputTokens + outputTokens;
|
||||
s.sumCost += getTokenCostUsd(model, inputTokens, outputTokens);
|
||||
return s;
|
||||
},
|
||||
{ sumTokens: 0, sumCost: 0, prettyUsage: "" }
|
||||
|
||||
@@ -18,13 +18,19 @@
|
||||
</li>
|
||||
<li>
|
||||
<code>tokenCounts</code> (optional): the number of tokens the user has
|
||||
consumed. This should be an object with keys <code>turbo</code>,
|
||||
<code>gpt4</code>, and <code>claude</code>.
|
||||
consumed. This should be an object with model family keys (e.g. <code>turbo</code>,
|
||||
<code>gpt4</code>, <code>claude</code>), each containing an object with
|
||||
<code>input</code> and <code>output</code> token counts.
|
||||
</li>
|
||||
<li>
|
||||
<code>tokenLimits</code> (optional): the number of tokens the user can
|
||||
consume. This should be an object with keys <code>turbo</code>,
|
||||
<code>gpt4</code>, and <code>claude</code>.
|
||||
<code>tokenLimits</code> (optional): the maximum number of tokens the user can
|
||||
consume. This should be an object with model family keys (e.g. <code>turbo</code>,
|
||||
<code>gpt4</code>, <code>claude</code>), each containing a single number
|
||||
representing the total token quota.
|
||||
</li>
|
||||
<li>
|
||||
<code>tokenRefresh</code> (optional): the amount of tokens to refresh when quotas
|
||||
are reset. Same format as <code>tokenLimits</code>.
|
||||
</li>
|
||||
<li>
|
||||
<code>createdAt</code> (optional): the timestamp when the user was created
|
||||
|
||||
+97
-11
@@ -29,10 +29,40 @@ type Config = {
|
||||
* same but the APIs are different. Vertex is the GCP product for enterprise.
|
||||
**/
|
||||
googleAIKey?: string;
|
||||
/**
|
||||
* Comma-delimited list of Google AI experimental model names that are
|
||||
* allowed to bypass the experimental model block. By default, all models
|
||||
* containing "exp" are blocked, but specific models listed here will be
|
||||
* permitted.
|
||||
*
|
||||
* @example "gemini-2.0-flash-exp,gemini-exp-1206"
|
||||
*/
|
||||
allowedExpModels?: string;
|
||||
/**
|
||||
* Comma-delimited list of Mistral AI API keys.
|
||||
*/
|
||||
mistralAIKey?: string;
|
||||
/**
|
||||
* Comma-delimited list of Deepseek API keys.
|
||||
*/
|
||||
deepseekKey?: string;
|
||||
/**
|
||||
* Comma-delimited list of Xai (Grok) API keys.
|
||||
*/
|
||||
xaiKey?: string;
|
||||
/**
|
||||
* Comma-delimited list of Cohere API keys.
|
||||
*/
|
||||
cohereKey?: string;
|
||||
/**
|
||||
* Comma-delimited list of Qwen API keys.
|
||||
*/
|
||||
qwenKey?: string;
|
||||
/**
|
||||
* Comma-delimited list of Moonshot API keys.
|
||||
*/
|
||||
moonshotKey?: string;
|
||||
|
||||
/**
|
||||
* Comma-delimited list of AWS credentials. Each credential item should be a
|
||||
* colon-delimited list of access key, secret key, and AWS region.
|
||||
@@ -73,11 +103,6 @@ type Config = {
|
||||
* management mode is set to 'user_token'.
|
||||
*/
|
||||
adminKey?: string;
|
||||
/**
|
||||
* The password required to view the service info/status page. If not set, the
|
||||
* info page will be publicly accessible.
|
||||
*/
|
||||
serviceInfoPassword?: string;
|
||||
/**
|
||||
* Which user management mode to use.
|
||||
* - `none`: No user management. Proxy is open to all requests with basic
|
||||
@@ -94,10 +119,14 @@ type Config = {
|
||||
* - `memory`: Users are stored in memory and are lost on restart (default)
|
||||
* - `firebase_rtdb`: Users are stored in a Firebase Realtime Database;
|
||||
* requires `firebaseKey` and `firebaseRtdbUrl` to be set.
|
||||
* - `sqlite`: Users are stored in an SQLite database; requires
|
||||
* `sqliteUserStorePath` to be set.
|
||||
*/
|
||||
gatekeeperStore: "memory" | "firebase_rtdb";
|
||||
gatekeeperStore: "memory" | "firebase_rtdb" | "sqlite";
|
||||
/** URL of the Firebase Realtime Database if using the Firebase RTDB store. */
|
||||
firebaseRtdbUrl?: string;
|
||||
/** Path to the SQLite database file for storing user data. */
|
||||
sqliteUserStorePath?: string;
|
||||
/**
|
||||
* Base64-encoded Firebase service account key if using the Firebase RTDB
|
||||
* store. Note that you should encode the *entire* JSON key file, not just the
|
||||
@@ -356,7 +385,7 @@ type Config = {
|
||||
*
|
||||
* Defaults to no services, meaning image prompts are disabled. Use a comma-
|
||||
* separated list. Available services are:
|
||||
* openai,anthropic,google-ai,mistral-ai,aws,gcp,azure
|
||||
* openai,anthropic,google-ai,mistral-ai,aws,gcp,azure,xai
|
||||
*/
|
||||
allowedVisionServices: LLMService[];
|
||||
/**
|
||||
@@ -415,6 +444,14 @@ type Config = {
|
||||
*/
|
||||
proxyUrl?: string;
|
||||
};
|
||||
/** URL for the image on the login page. Defaults to empty string (no image). */
|
||||
loginImageUrl?: string;
|
||||
/** Whether to enable the token-based login page for the service info page. Defaults to true. */
|
||||
enableInfoPageLogin?: boolean;
|
||||
/** Authentication mode for the service info page. (token | password) */
|
||||
serviceInfoAuthMode: "token" | "password";
|
||||
/** Password for the service info page if serviceInfoAuthMode is 'password'. */
|
||||
serviceInfoPassword?: string;
|
||||
};
|
||||
|
||||
// To change configs, create a file called .env in the root directory.
|
||||
@@ -424,14 +461,19 @@ export const config: Config = {
|
||||
bindAddress: getEnvWithDefault("BIND_ADDRESS", "0.0.0.0"),
|
||||
openaiKey: getEnvWithDefault("OPENAI_KEY", ""),
|
||||
anthropicKey: getEnvWithDefault("ANTHROPIC_KEY", ""),
|
||||
qwenKey: getEnvWithDefault("QWEN_KEY", ""),
|
||||
googleAIKey: getEnvWithDefault("GOOGLE_AI_KEY", ""),
|
||||
allowedExpModels: getEnvWithDefault("ALLOWED_EXP_MODELS", ""),
|
||||
mistralAIKey: getEnvWithDefault("MISTRAL_AI_KEY", ""),
|
||||
deepseekKey: getEnvWithDefault("DEEPSEEK_KEY", ""),
|
||||
xaiKey: getEnvWithDefault("XAI_KEY", ""),
|
||||
cohereKey: getEnvWithDefault("COHERE_KEY", ""),
|
||||
moonshotKey: getEnvWithDefault("MOONSHOT_KEY", ""),
|
||||
awsCredentials: getEnvWithDefault("AWS_CREDENTIALS", ""),
|
||||
gcpCredentials: getEnvWithDefault("GCP_CREDENTIALS", ""),
|
||||
azureCredentials: getEnvWithDefault("AZURE_CREDENTIALS", ""),
|
||||
proxyKey: getEnvWithDefault("PROXY_KEY", ""),
|
||||
adminKey: getEnvWithDefault("ADMIN_KEY", ""),
|
||||
serviceInfoPassword: getEnvWithDefault("SERVICE_INFO_PASSWORD", ""),
|
||||
sqliteDataPath: getEnvWithDefault(
|
||||
"SQLITE_DATA_PATH",
|
||||
path.join(DATA_DIR, "database.sqlite")
|
||||
@@ -439,7 +481,11 @@ export const config: Config = {
|
||||
eventLogging: getEnvWithDefault("EVENT_LOGGING", false),
|
||||
eventLoggingTrim: getEnvWithDefault("EVENT_LOGGING_TRIM", 5),
|
||||
gatekeeper: getEnvWithDefault("GATEKEEPER", "none"),
|
||||
gatekeeperStore: getEnvWithDefault("GATEKEEPER_STORE", "memory"),
|
||||
gatekeeperStore: getEnvWithDefault("GATEKEEPER_STORE", "memory") as Config["gatekeeperStore"],
|
||||
sqliteUserStorePath: getEnvWithDefault(
|
||||
"SQLITE_USER_STORE_PATH",
|
||||
path.join(DATA_DIR, "user-store.sqlite")
|
||||
),
|
||||
maxIpsPerUser: getEnvWithDefault("MAX_IPS_PER_USER", 0),
|
||||
maxIpsAutoBan: getEnvWithDefault("MAX_IPS_AUTO_BAN", false),
|
||||
captchaMode: getEnvWithDefault("CAPTCHA_MODE", "none"),
|
||||
@@ -525,6 +571,10 @@ export const config: Config = {
|
||||
interface: getEnvWithDefault("HTTP_AGENT_INTERFACE", undefined),
|
||||
proxyUrl: getEnvWithDefault("HTTP_AGENT_PROXY_URL", undefined),
|
||||
},
|
||||
loginImageUrl: getEnvWithDefault("LOGIN_IMAGE_URL", ""),
|
||||
enableInfoPageLogin: getEnvWithDefault("ENABLE_INFO_PAGE_LOGIN", true),
|
||||
serviceInfoAuthMode: getEnvWithDefault("SERVICE_INFO_AUTH_MODE", "token") as Config["serviceInfoAuthMode"],
|
||||
serviceInfoPassword: getEnvWithDefault("SERVICE_INFO_PASSWORD", undefined),
|
||||
} as const;
|
||||
|
||||
function generateSigningKey() {
|
||||
@@ -541,6 +591,8 @@ function generateSigningKey() {
|
||||
config.anthropicKey,
|
||||
config.googleAIKey,
|
||||
config.mistralAIKey,
|
||||
config.deepseekKey,
|
||||
config.xaiKey,
|
||||
config.awsCredentials,
|
||||
config.gcpCredentials,
|
||||
config.azureCredentials,
|
||||
@@ -644,6 +696,12 @@ export async function assertConfigIsValid() {
|
||||
);
|
||||
}
|
||||
|
||||
if (config.gatekeeperStore === "sqlite" && !config.sqliteUserStorePath) {
|
||||
throw new Error(
|
||||
"SQLite user store requires `SQLITE_USER_STORE_PATH` to be set."
|
||||
);
|
||||
}
|
||||
|
||||
if (Object.values(config.httpAgent || {}).filter(Boolean).length === 0) {
|
||||
delete config.httpAgent;
|
||||
} else if (config.httpAgent) {
|
||||
@@ -654,6 +712,25 @@ export async function assertConfigIsValid() {
|
||||
}
|
||||
}
|
||||
|
||||
if (config.enableInfoPageLogin) {
|
||||
if (!["token", "password"].includes(config.serviceInfoAuthMode)) {
|
||||
throw new Error(
|
||||
`Invalid SERVICE_INFO_AUTH_MODE: ${config.serviceInfoAuthMode}. Must be 'token' or 'password'.`
|
||||
);
|
||||
}
|
||||
if (config.serviceInfoAuthMode === "password" && !config.serviceInfoPassword) {
|
||||
throw new Error(
|
||||
"SERVICE_INFO_AUTH_MODE is 'password' but SERVICE_INFO_PASSWORD is not set."
|
||||
);
|
||||
}
|
||||
// If service info login is token-based, gatekeeper must be 'user_token' mode for getUser() to be effective.
|
||||
if (config.serviceInfoAuthMode === "token" && config.gatekeeper !== "user_token") {
|
||||
throw new Error(
|
||||
"SERVICE_INFO_AUTH_MODE is 'token' for info page login, but GATEKEEPER is not 'user_token'. User token authentication will not work."
|
||||
);
|
||||
}
|
||||
}
|
||||
|
||||
// Ensure forks which add new secret-like config keys don't unwittingly expose
|
||||
// them to users.
|
||||
for (const key of getKeys(config)) {
|
||||
@@ -689,13 +766,17 @@ export const OMITTED_KEYS = [
|
||||
"openaiKey",
|
||||
"anthropicKey",
|
||||
"googleAIKey",
|
||||
"deepseekKey",
|
||||
"xaiKey",
|
||||
"cohereKey",
|
||||
"qwenKey",
|
||||
"moonshotKey",
|
||||
"mistralAIKey",
|
||||
"awsCredentials",
|
||||
"gcpCredentials",
|
||||
"azureCredentials",
|
||||
"proxyKey",
|
||||
"adminKey",
|
||||
"serviceInfoPassword",
|
||||
"rejectPhrases",
|
||||
"rejectMessage",
|
||||
"showTokenCosts",
|
||||
@@ -704,6 +785,7 @@ export const OMITTED_KEYS = [
|
||||
"firebaseKey",
|
||||
"firebaseRtdbUrl",
|
||||
"sqliteDataPath",
|
||||
"sqliteUserStorePath",
|
||||
"eventLogging",
|
||||
"eventLoggingTrim",
|
||||
"gatekeeperStore",
|
||||
@@ -722,6 +804,9 @@ export const OMITTED_KEYS = [
|
||||
"adminWhitelist",
|
||||
"ipBlacklist",
|
||||
"powTokenPurgeHours",
|
||||
"loginImageUrl",
|
||||
"enableInfoPageLogin",
|
||||
"serviceInfoPassword",
|
||||
] satisfies (keyof Config)[];
|
||||
type OmitKeys = (typeof OMITTED_KEYS)[number];
|
||||
|
||||
@@ -784,6 +869,7 @@ function getEnvWithDefault<T>(env: string | string[], defaultValue: T): T {
|
||||
"AWS_CREDENTIALS",
|
||||
"GCP_CREDENTIALS",
|
||||
"AZURE_CREDENTIALS",
|
||||
"QWEN_KEY",
|
||||
].includes(String(env))
|
||||
) {
|
||||
return value as unknown as T;
|
||||
@@ -810,6 +896,6 @@ function parseCsv(val: string): string[] {
|
||||
|
||||
function getDefaultModelFamilies(): ModelFamily[] {
|
||||
return MODEL_FAMILIES.filter(
|
||||
(f) => !f.includes("dall-e") && !f.includes("o1")
|
||||
(f) => !f.includes("o1-pro") && !f.includes("o3-pro")
|
||||
) as ModelFamily[];
|
||||
}
|
||||
|
||||
+239
-127
@@ -1,4 +1,8 @@
|
||||
/** This whole module kinda sucks */
|
||||
/* ──────────────────────────────────────────────────────────────
|
||||
Login-gated info page
|
||||
drop-in replacement for src/info-page.ts
|
||||
──────────────────────────────────────────────────────────── */
|
||||
|
||||
import fs from "fs";
|
||||
import express, { Router, Request, Response } from "express";
|
||||
import showdown from "showdown";
|
||||
@@ -8,18 +12,49 @@ import { getLastNImages } from "./shared/file-storage/image-history";
|
||||
import { keyPool } from "./shared/key-management";
|
||||
import { MODEL_FAMILY_SERVICE, ModelFamily } from "./shared/models";
|
||||
import { withSession } from "./shared/with-session";
|
||||
import { checkCsrfToken, injectCsrfToken } from "./shared/inject-csrf";
|
||||
import { injectCsrfToken, checkCsrfToken } from "./shared/inject-csrf";
|
||||
import { getUser } from "./shared/users/user-store";
|
||||
|
||||
/* ──────────────── TYPES: extend express-session ──────────── */
|
||||
declare module "express-session" {
|
||||
interface Session {
|
||||
infoPageAuthed?: boolean;
|
||||
}
|
||||
}
|
||||
|
||||
/* ──────────────── misc constants ─────────────────────────── */
|
||||
const INFO_PAGE_TTL = 2_000; // ms
|
||||
const LOGIN_ROUTE = "/";
|
||||
|
||||
const INFO_PAGE_TTL = 2000;
|
||||
const MODEL_FAMILY_FRIENDLY_NAME: { [f in ModelFamily]: string } = {
|
||||
qwen: "Qwen",
|
||||
cohere: "Cohere",
|
||||
deepseek: "Deepseek",
|
||||
xai: "Grok",
|
||||
moonshot: "Moonshot",
|
||||
turbo: "GPT-4o Mini / 3.5 Turbo",
|
||||
gpt4: "GPT-4",
|
||||
"gpt4-32k": "GPT-4 32k",
|
||||
"gpt4-turbo": "GPT-4 Turbo",
|
||||
gpt4o: "GPT-4o",
|
||||
gpt41: "GPT-4.1",
|
||||
"gpt41-mini": "GPT-4.1 Mini",
|
||||
"gpt41-nano": "GPT-4.1 Nano",
|
||||
gpt5: "GPT-5",
|
||||
"gpt5-mini": "GPT-5 Mini",
|
||||
"gpt5-nano": "GPT-5 Nano",
|
||||
"gpt5-chat-latest": "GPT-5 Chat Latest",
|
||||
gpt45: "GPT-4.5",
|
||||
o1: "OpenAI o1",
|
||||
"o1-mini": "OpenAI o1 mini",
|
||||
"o1-pro": "OpenAI o1 pro",
|
||||
"o3-pro": "OpenAI o3 pro",
|
||||
"o3-mini": "OpenAI o3 mini",
|
||||
"o3": "OpenAI o3",
|
||||
"o4-mini": "OpenAI o4 mini",
|
||||
"codex-mini": "OpenAI Codex Mini",
|
||||
"dall-e": "DALL-E",
|
||||
"gpt-image": "GPT Image",
|
||||
claude: "Claude (Sonnet)",
|
||||
"claude-opus": "Claude (Opus)",
|
||||
"gemini-flash": "Gemini Flash",
|
||||
@@ -42,19 +77,101 @@ const MODEL_FAMILY_FRIENDLY_NAME: { [f in ModelFamily]: string } = {
|
||||
"azure-gpt4-32k": "Azure GPT-4 32k",
|
||||
"azure-gpt4-turbo": "Azure GPT-4 Turbo",
|
||||
"azure-gpt4o": "Azure GPT-4o",
|
||||
"azure-gpt45": "Azure GPT-4.5",
|
||||
"azure-gpt41": "Azure GPT-4.1",
|
||||
"azure-gpt41-mini": "Azure GPT-4.1 Mini",
|
||||
"azure-gpt41-nano": "Azure GPT-4.1 Nano",
|
||||
"azure-gpt5": "Azure GPT-5",
|
||||
"azure-gpt5-mini": "Azure GPT-5 Mini",
|
||||
"azure-gpt5-nano": "Azure GPT-5 Nano",
|
||||
"azure-gpt5-chat-latest": "Azure GPT-5 Chat Latest",
|
||||
"azure-o1": "Azure o1",
|
||||
"azure-o1-mini": "Azure o1 mini",
|
||||
"azure-o1-pro": "Azure o1 pro",
|
||||
"azure-o3-pro": "Azure o3 pro",
|
||||
"azure-o3-mini": "Azure o3 mini",
|
||||
"azure-o3": "Azure o3",
|
||||
"azure-o4-mini": "Azure o4 mini",
|
||||
"azure-codex-mini": "Azure Codex Mini",
|
||||
"azure-dall-e": "Azure DALL-E",
|
||||
"azure-gpt-image": "Azure GPT Image",
|
||||
};
|
||||
|
||||
const converter = new showdown.Converter();
|
||||
|
||||
/* optional markdown greeting */
|
||||
const customGreeting = fs.existsSync("greeting.md")
|
||||
? `<div id="servergreeting">${fs.readFileSync("greeting.md", "utf8")}</div>`
|
||||
: "";
|
||||
|
||||
/* ──────────────── Login page ──────────────────────── */
|
||||
function renderLoginPage(csrf: string, error?: string) {
|
||||
const errBlock = error
|
||||
? `<div class="error-message">${escapeHtml(error)}</div>`
|
||||
: "";
|
||||
const pageTitle = getServerTitle();
|
||||
return `<!DOCTYPE html>
|
||||
<html>
|
||||
<head>
|
||||
<title>${pageTitle} – Login</title>
|
||||
<style>
|
||||
body{font-family:Arial, sans-serif;display:flex;justify-content:center;
|
||||
align-items:center;height:100vh;margin:0;padding:20px;background:#f5f5f5;}
|
||||
.login-container{background:#fff;border-radius:8px;box-shadow:0 4px 8px rgba(0,0,0,.1);
|
||||
padding:30px;width:100%;max-width:400px;text-align:center;}
|
||||
.logo-image{max-width:200px;margin-bottom:20px;}
|
||||
.form-group{margin-bottom:20px;}
|
||||
input[type=text], input[type=password]{width:100%;padding:10px;border:1px solid #ddd;border-radius:4px;
|
||||
box-sizing:border-box;font-size:16px;}
|
||||
button{background:#4caf50;color:#fff;border:none;padding:12px 20px;border-radius:4px;
|
||||
cursor:pointer;font-size:16px;width:100%;}
|
||||
button:hover{background:#45a049;}
|
||||
.error-message{color:#f44336;margin-bottom:15px;}
|
||||
|
||||
@media (prefers-color-scheme: dark) {
|
||||
body { background: #2c2c2c; color: #e0e0e0; }
|
||||
.login-container { background: #383838; box-shadow: 0 4px 12px rgba(0,0,0,0.4); border: 1px solid #4a4a4a; }
|
||||
input[type=text], input[type=password] { background: #4a4a4a; color: #e0e0e0; border: 1px solid #5a5a5a; }
|
||||
input[type=text]::placeholder, input[type=password]::placeholder { color: #999; }
|
||||
button { background: #007bff; } /* Using a blue for dark mode button */
|
||||
button:hover { background: #0056b3; }
|
||||
.error-message { color: #ff8a80; } /* Lighter red for errors in dark mode */
|
||||
}
|
||||
</style>
|
||||
</head>
|
||||
<body>
|
||||
<div class="login-container">
|
||||
${config.loginImageUrl ? `<img src="${config.loginImageUrl}" alt="Logo" class="logo-image">` : ''}
|
||||
${errBlock}
|
||||
<form method="POST" action="${LOGIN_ROUTE}">
|
||||
<div class="form-group">
|
||||
${config.serviceInfoAuthMode === "password"
|
||||
? `<input type="password" id="password" name="password" required placeholder="Service Password">`
|
||||
: `<input type="text" id="token" name="token" required placeholder="Your token">`}
|
||||
<input type="hidden" name="_csrf" value="${csrf}">
|
||||
</div>
|
||||
<button type="submit">Access Dashboard</button>
|
||||
</form>
|
||||
</div>
|
||||
</body>
|
||||
</html>`;
|
||||
}
|
||||
|
||||
/* ──────────────── login-required middleware ──────────────── */
|
||||
function requireLogin(
|
||||
req: Request,
|
||||
res: Response,
|
||||
next: express.NextFunction
|
||||
) {
|
||||
if (req.session?.infoPageAuthed) return next();
|
||||
return res.send(renderLoginPage(res.locals.csrfToken));
|
||||
}
|
||||
|
||||
/* ──────────────── INFO PAGE CACHING ──────────────────────── */
|
||||
let infoPageHtml: string | undefined;
|
||||
let infoPageLastUpdated = 0;
|
||||
|
||||
export const handleInfoPage = (req: Request, res: Response) => {
|
||||
export function handleInfoPage(req: Request, res: Response) {
|
||||
if (infoPageLastUpdated + INFO_PAGE_TTL > Date.now()) {
|
||||
return res.send(infoPageHtml);
|
||||
}
|
||||
@@ -69,60 +186,46 @@ export const handleInfoPage = (req: Request, res: Response) => {
|
||||
infoPageLastUpdated = Date.now();
|
||||
|
||||
res.send(infoPageHtml);
|
||||
};
|
||||
}
|
||||
|
||||
/* ──────────────── RENDER FULL INFO PAGE ──────────────────── */
|
||||
export function renderPage(info: ServiceInfo) {
|
||||
const title = getServerTitle();
|
||||
const headerHtml = buildInfoPageHeader(info);
|
||||
|
||||
return `<!doctype html>
|
||||
<html lang="en">
|
||||
<head>
|
||||
<meta charset="utf-8" />
|
||||
<meta name="robots" content="noindex" />
|
||||
<title>${title}</title>
|
||||
<link rel="stylesheet" href="/res/css/reset.css" media="screen" />
|
||||
<link rel="stylesheet" href="/res/css/sakura.css" media="screen" />
|
||||
<link rel="stylesheet" href="/res/css/sakura-dark.css" media="screen and (prefers-color-scheme: dark)" />
|
||||
<style>
|
||||
body {
|
||||
font-family: sans-serif;
|
||||
padding: 1em;
|
||||
max-width: 900px;
|
||||
margin: 0;
|
||||
}
|
||||
|
||||
.self-service-links {
|
||||
display: flex;
|
||||
justify-content: center;
|
||||
margin-bottom: 1em;
|
||||
padding: 0.5em;
|
||||
font-size: 0.8em;
|
||||
}
|
||||
|
||||
.self-service-links a {
|
||||
margin: 0 0.5em;
|
||||
}
|
||||
</style>
|
||||
</head>
|
||||
<body>
|
||||
${headerHtml}
|
||||
<hr />
|
||||
${getSelfServiceLinks()}
|
||||
<h2>Service Info</h2>
|
||||
<pre>${JSON.stringify(info, null, 2)}</pre>
|
||||
</body>
|
||||
<head>
|
||||
<meta charset="utf-8" />
|
||||
<meta name="robots" content="noindex" />
|
||||
<title>${title}</title>
|
||||
<link rel="stylesheet" href="/res/css/reset.css" />
|
||||
<link rel="stylesheet" href="/res/css/sakura.css" />
|
||||
<link rel="stylesheet" href="/res/css/sakura-dark.css"
|
||||
media="screen and (prefers-color-scheme: dark)" />
|
||||
<style>
|
||||
body{font-family:sans-serif;padding:1em;max-width:900px;margin:0;}
|
||||
.self-service-links{display:flex;justify-content:center;margin-bottom:1em;
|
||||
padding:0.5em;font-size:0.8em;}
|
||||
.self-service-links a{margin:0 0.5em;}
|
||||
</style>
|
||||
</head>
|
||||
<body>
|
||||
${headerHtml}
|
||||
<hr/>
|
||||
${getSelfServiceLinks()}
|
||||
<h2>Service Info</h2>
|
||||
<pre>${JSON.stringify(info, null, 2)}</pre>
|
||||
</body>
|
||||
</html>`;
|
||||
}
|
||||
|
||||
/**
|
||||
* If the server operator provides a `greeting.md` file, it will be included in
|
||||
* the rendered info page.
|
||||
**/
|
||||
/* ──────────────── header & helper functions ──────────────── */
|
||||
/* (all copied verbatim from original file) */
|
||||
function buildInfoPageHeader(info: ServiceInfo) {
|
||||
const title = getServerTitle();
|
||||
// TODO: use some templating engine instead of this mess
|
||||
let infoBody = `# ${title}`;
|
||||
|
||||
if (config.promptLogging) {
|
||||
infoBody += `\n## Prompt Logging Enabled
|
||||
This proxy keeps full logs of all prompts and AI responses. Prompt logs are anonymous and do not contain IP addresses or timestamps.
|
||||
@@ -141,9 +244,9 @@ This proxy keeps full logs of all prompts and AI responses. Prompt logs are anon
|
||||
for (const modelFamily of config.allowedModelFamilies) {
|
||||
const service = MODEL_FAMILY_SERVICE[modelFamily];
|
||||
|
||||
const hasKeys = keyPool.list().some((k) => {
|
||||
return k.service === service && k.modelFamilies.includes(modelFamily);
|
||||
});
|
||||
const hasKeys = keyPool.list().some(
|
||||
(k) => k.service === service && k.modelFamilies.includes(modelFamily)
|
||||
);
|
||||
|
||||
const wait = info[modelFamily]?.estimatedQueueTime;
|
||||
if (hasKeys && wait) {
|
||||
@@ -154,9 +257,7 @@ This proxy keeps full logs of all prompts and AI responses. Prompt logs are anon
|
||||
}
|
||||
|
||||
infoBody += "\n\n" + waits.join(" / ");
|
||||
|
||||
infoBody += customGreeting;
|
||||
|
||||
infoBody += buildRecentImageSection();
|
||||
|
||||
return converter.makeHtml(infoBody);
|
||||
@@ -164,63 +265,60 @@ This proxy keeps full logs of all prompts and AI responses. Prompt logs are anon
|
||||
|
||||
function getSelfServiceLinks() {
|
||||
if (config.gatekeeper !== "user_token") return "";
|
||||
|
||||
const links = [["Check your user token", "/user/lookup"]];
|
||||
if (config.captchaMode !== "none") {
|
||||
links.unshift(["Request a user token", "/user/captcha"]);
|
||||
}
|
||||
|
||||
return `<div class="self-service-links">${links
|
||||
.map(([text, link]) => `<a href="${link}">${text}</a>`)
|
||||
.map(([t, l]) => `<a href="${l}">${t}</a>`)
|
||||
.join(" | ")}</div>`;
|
||||
}
|
||||
|
||||
function getServerTitle() {
|
||||
// Use manually set title if available
|
||||
if (process.env.SERVER_TITLE) {
|
||||
return process.env.SERVER_TITLE;
|
||||
}
|
||||
|
||||
// Huggingface
|
||||
if (process.env.SPACE_ID) {
|
||||
if (process.env.SERVER_TITLE) return process.env.SERVER_TITLE;
|
||||
if (process.env.SPACE_ID)
|
||||
return `${process.env.SPACE_AUTHOR_NAME} / ${process.env.SPACE_TITLE}`;
|
||||
}
|
||||
|
||||
// Render
|
||||
if (process.env.RENDER) {
|
||||
if (process.env.RENDER)
|
||||
return `Render / ${process.env.RENDER_SERVICE_NAME}`;
|
||||
}
|
||||
|
||||
return "OAI Reverse Proxy";
|
||||
return "Tunnel";
|
||||
}
|
||||
|
||||
function buildRecentImageSection() {
|
||||
const dalleModels: ModelFamily[] = ["azure-dall-e", "dall-e"];
|
||||
const imageModels: ModelFamily[] = [
|
||||
"azure-dall-e",
|
||||
"dall-e",
|
||||
"gpt-image",
|
||||
"azure-gpt-image",
|
||||
];
|
||||
// Condition 1: Is the feature enabled via config?
|
||||
// Condition 2: Is at least one relevant image model family allowed in config?
|
||||
if (
|
||||
!config.showRecentImages ||
|
||||
dalleModels.every((f) => !config.allowedModelFamilies.includes(f))
|
||||
imageModels.every((f) => !config.allowedModelFamilies.includes(f))
|
||||
) {
|
||||
return ""; // Exit if feature is disabled or no relevant models are allowed
|
||||
}
|
||||
|
||||
// Condition 3: Are there any actual images to display?
|
||||
const recentImages = getLastNImages(12).reverse();
|
||||
if (recentImages.length === 0) {
|
||||
// If the feature is enabled and models are allowed, but no images exist,
|
||||
// do not render the section, including its title.
|
||||
return "";
|
||||
}
|
||||
|
||||
let html = `<h2>Recent DALL-E Generations</h2>`;
|
||||
const recentImages = getLastNImages(12).reverse();
|
||||
if (recentImages.length === 0) {
|
||||
html += `<p>No images yet.</p>`;
|
||||
return html;
|
||||
}
|
||||
|
||||
html += `<div style="display: flex; flex-wrap: wrap;" id="recent-images">`;
|
||||
// If all conditions pass (feature enabled, models allowed, images exist), build and return the HTML
|
||||
let html = `<h2>Recent Image Generations</h2>`;
|
||||
html += `<div style="display:flex;flex-wrap:wrap;" id="recent-images">`;
|
||||
for (const { url, prompt } of recentImages) {
|
||||
const thumbUrl = url.replace(/\.png$/, "_t.jpg");
|
||||
const escapedPrompt = escapeHtml(prompt);
|
||||
html += `<div style="margin: 0.5em;" class="recent-image">
|
||||
<a href="${url}" target="_blank"><img src="${thumbUrl}" title="${escapedPrompt}" alt="${escapedPrompt}" style="max-width: 150px; max-height: 150px;" /></a>
|
||||
</div>`;
|
||||
html += `<div style="margin:0.5em" class="recent-image">
|
||||
<a href="${url}" target="_blank"><img src="${thumbUrl}" title="${escapedPrompt}"
|
||||
alt="${escapedPrompt}" style="max-width:150px;max-height:150px;"/></a></div>`;
|
||||
}
|
||||
html += `</div>`;
|
||||
html += `<p style="clear: both; text-align: center;"><a href="/user/image-history">View all recent images</a></p>`;
|
||||
|
||||
html += `</div><p style="clear:both;text-align:center;">
|
||||
<a href="/user/image-history">View all recent images</a></p>`;
|
||||
return html;
|
||||
}
|
||||
|
||||
@@ -235,57 +333,71 @@ function escapeHtml(unsafe: string) {
|
||||
.replace(/]/g, "]");
|
||||
}
|
||||
|
||||
|
||||
function getExternalUrlForHuggingfaceSpaceId(spaceId: string) {
|
||||
try {
|
||||
const [username, spacename] = spaceId.split("/");
|
||||
return `https://${username}-${spacename.replace(/_/g, "-")}.hf.space`;
|
||||
} catch (e) {
|
||||
const [u, s] = spaceId.split("/");
|
||||
return `https://${u}-${s.replace(/_/g, "-")}.hf.space`;
|
||||
} catch {
|
||||
return "";
|
||||
}
|
||||
}
|
||||
|
||||
function checkIfUnlocked(
|
||||
req: Request,
|
||||
res: Response,
|
||||
next: express.NextFunction
|
||||
) {
|
||||
if (config.serviceInfoPassword?.length && !req.session?.unlocked) {
|
||||
return res.redirect("/unlock-info");
|
||||
}
|
||||
next();
|
||||
}
|
||||
|
||||
/* ──────────────── ROUTER ─────────────────────────────────── */
|
||||
const infoPageRouter = Router();
|
||||
if (config.serviceInfoPassword?.length) {
|
||||
infoPageRouter.use(
|
||||
express.json({ limit: "1mb" }),
|
||||
express.urlencoded({ extended: true, limit: "1mb" })
|
||||
);
|
||||
infoPageRouter.use(withSession);
|
||||
infoPageRouter.use(injectCsrfToken, checkCsrfToken);
|
||||
infoPageRouter.post("/unlock-info", (req, res) => {
|
||||
if (req.body.password !== config.serviceInfoPassword) {
|
||||
return res.status(403).send("Incorrect password");
|
||||
}
|
||||
req.session!.unlocked = true;
|
||||
res.redirect("/");
|
||||
});
|
||||
infoPageRouter.get("/unlock-info", (_req, res) => {
|
||||
if (_req.session?.unlocked) return res.redirect("/");
|
||||
|
||||
res.send(`
|
||||
<form method="post" action="/unlock-info">
|
||||
<h1>Unlock Service Info</h1>
|
||||
<input type="hidden" name="_csrf" value="${res.locals.csrfToken}" />
|
||||
<input type="password" name="password" placeholder="Password" />
|
||||
<button type="submit">Unlock</button>
|
||||
</form>
|
||||
`);
|
||||
});
|
||||
infoPageRouter.use(checkIfUnlocked);
|
||||
}
|
||||
infoPageRouter.get("/", handleInfoPage);
|
||||
infoPageRouter.get("/status", (req, res) => {
|
||||
res.json(buildInfo(req.protocol + "://" + req.get("host"), false));
|
||||
infoPageRouter.use(
|
||||
express.json({ limit: "1mb" }),
|
||||
express.urlencoded({ extended: true, limit: "1mb" }),
|
||||
withSession,
|
||||
injectCsrfToken,
|
||||
checkCsrfToken
|
||||
);
|
||||
|
||||
/* login attempt */
|
||||
infoPageRouter.post(LOGIN_ROUTE, (req, res) => {
|
||||
if (config.serviceInfoAuthMode === "password") {
|
||||
const password = (req.body.password || "").trim();
|
||||
// Simple string comparison; for production, consider a timing-safe comparison library
|
||||
if (config.serviceInfoPassword && password === config.serviceInfoPassword) {
|
||||
req.session!.infoPageAuthed = true;
|
||||
return res.redirect("/");
|
||||
} else {
|
||||
return res
|
||||
.status(401)
|
||||
.send(renderLoginPage(res.locals.csrfToken, "Invalid password. Please try again."));
|
||||
}
|
||||
} else {
|
||||
// Token-based authentication (using any valid user token)
|
||||
const token = (req.body.token || "").trim();
|
||||
const user = getUser(token); // returns undefined if invalid
|
||||
|
||||
if (user && !user.disabledAt) {
|
||||
// Only allow access if user exists AND is not disabled
|
||||
req.session!.infoPageAuthed = true;
|
||||
return res.redirect("/");
|
||||
} else if (user && user.disabledAt) {
|
||||
// User exists but is disabled
|
||||
const reason = user.disabledReason || "Your account has been disabled";
|
||||
return res
|
||||
.status(401)
|
||||
.send(renderLoginPage(res.locals.csrfToken, `Access denied: ${reason}`));
|
||||
} else {
|
||||
// User doesn't exist
|
||||
return res
|
||||
.status(401)
|
||||
.send(renderLoginPage(res.locals.csrfToken, "Invalid token. Please try again."));
|
||||
}
|
||||
}
|
||||
});
|
||||
|
||||
/* GET / – either login form or info page */
|
||||
if (config.enableInfoPageLogin) {
|
||||
infoPageRouter.get(LOGIN_ROUTE, requireLogin, handleInfoPage);
|
||||
} else {
|
||||
infoPageRouter.get(LOGIN_ROUTE, handleInfoPage);
|
||||
}
|
||||
|
||||
/* ─── Removed the public /status route : simply not added ─── */
|
||||
|
||||
export { infoPageRouter };
|
||||
|
||||
+1
-1
@@ -2,7 +2,7 @@ import { NextFunction, Request, Response } from "express";
|
||||
|
||||
export function addV1(req: Request, res: Response, next: NextFunction) {
|
||||
// Clients don't consistently use the /v1 prefix so we'll add it for them.
|
||||
if (!req.path.startsWith("/v1/") && !req.path.startsWith("/v1beta/")) {
|
||||
if (!req.path.startsWith("/v1/") && !req.path.match(/^\/(v1alpha|v1beta)\//)) {
|
||||
req.url = `/v1${req.url}`;
|
||||
}
|
||||
next();
|
||||
|
||||
+144
-60
@@ -9,6 +9,8 @@ import {
|
||||
import { ProxyResHandlerWithBody } from "./middleware/response";
|
||||
import { createQueuedProxyMiddleware } from "./middleware/request/proxy-middleware-factory";
|
||||
import { ProxyReqManager } from "./middleware/request/proxy-req-manager";
|
||||
import { claudeModels } from "../shared/claude-models";
|
||||
import { validateClaude41OpusParameters } from "../shared/claude-4-1-validation";
|
||||
|
||||
let modelsCache: any = null;
|
||||
let modelsCacheTime = 0;
|
||||
@@ -18,45 +20,32 @@ const getModelsResponse = () => {
|
||||
return modelsCache;
|
||||
}
|
||||
|
||||
if (!config.anthropicKey) return { object: "list", data: [] };
|
||||
if (!config.anthropicKey) return { object: "list", data: [], has_more: false, first_id: null, last_id: null };
|
||||
|
||||
const claudeVariants = [
|
||||
"claude-v1",
|
||||
"claude-v1-100k",
|
||||
"claude-instant-v1",
|
||||
"claude-instant-v1-100k",
|
||||
"claude-v1.3",
|
||||
"claude-v1.3-100k",
|
||||
"claude-v1.2",
|
||||
"claude-v1.0",
|
||||
"claude-instant-v1.1",
|
||||
"claude-instant-v1.1-100k",
|
||||
"claude-instant-v1.0",
|
||||
"claude-2",
|
||||
"claude-2.0",
|
||||
"claude-2.1",
|
||||
"claude-3-haiku-20240307",
|
||||
"claude-3-5-haiku-20241022",
|
||||
"claude-3-opus-20240229",
|
||||
"claude-3-opus-latest",
|
||||
"claude-3-sonnet-20240229",
|
||||
"claude-3-5-sonnet-20240620",
|
||||
"claude-3-5-sonnet-20241022",
|
||||
"claude-3-5-sonnet-latest",
|
||||
];
|
||||
|
||||
const models = claudeVariants.map((id) => ({
|
||||
id,
|
||||
object: "model",
|
||||
created: new Date().getTime(),
|
||||
const date = new Date()
|
||||
const models = claudeModels.map(model => ({
|
||||
// Common
|
||||
id: model.anthropicId,
|
||||
owned_by: "anthropic",
|
||||
permission: [],
|
||||
root: "claude",
|
||||
parent: null,
|
||||
}));
|
||||
// Anthropic
|
||||
type: "model",
|
||||
display_name: model.displayName,
|
||||
created_at: date.toISOString(),
|
||||
// OpenAI
|
||||
object: "model",
|
||||
created: date.getTime(),
|
||||
}));
|
||||
|
||||
modelsCache = { object: "list", data: models };
|
||||
modelsCacheTime = new Date().getTime();
|
||||
modelsCache = {
|
||||
// Common
|
||||
object: "list",
|
||||
data: models,
|
||||
// Anthropic
|
||||
has_more: false,
|
||||
first_id: models[0]?.id,
|
||||
last_id: models[models.length - 1]?.id,
|
||||
};
|
||||
modelsCacheTime = date.getTime();
|
||||
|
||||
return modelsCache;
|
||||
};
|
||||
@@ -182,12 +171,91 @@ function maybeReassignModel(req: Request) {
|
||||
* If client requests more than 4096 output tokens the request must have a
|
||||
* particular version header.
|
||||
* https://docs.anthropic.com/en/release-notes/api#july-15th-2024
|
||||
*
|
||||
* Also adds the required beta header for 1-hour cache duration if requested.
|
||||
* Also validates Claude 4.1 Opus parameters (temperature/top_p).
|
||||
*/
|
||||
function setAnthropicBetaHeader(req: Request) {
|
||||
// Validate Claude 4.1 Opus parameters before processing
|
||||
validateClaude41OpusParameters(req);
|
||||
|
||||
const { max_tokens_to_sample } = req.body;
|
||||
|
||||
// Initialize beta headers array
|
||||
const betaHeaders: string[] = [];
|
||||
|
||||
// Add max tokens beta header if needed
|
||||
if (max_tokens_to_sample > 4096) {
|
||||
req.headers["anthropic-beta"] = "max-tokens-3-5-sonnet-2024-07-15";
|
||||
betaHeaders.push("max-tokens-3-5-sonnet-2024-07-15");
|
||||
}
|
||||
|
||||
// Add extended cache TTL beta header if 1h cache is requested
|
||||
if (req.body.cache_control?.ttl === "1h") {
|
||||
betaHeaders.push("extended-cache-ttl-2025-04-11");
|
||||
}
|
||||
|
||||
// Set the combined beta headers if any were added
|
||||
if (betaHeaders.length > 0) {
|
||||
req.headers["anthropic-beta"] = betaHeaders.join(",");
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Adds web search tool for Claude-3.5 and Claude-3.7 models when enable_web_search is true
|
||||
*
|
||||
* Supports all optional parameters documented in the Claude API:
|
||||
* - max_uses: Limit the number of searches per request
|
||||
* - allowed_domains: Only include results from these domains
|
||||
* - blocked_domains: Never include results from these domains
|
||||
* - user_location: Localize search results
|
||||
*/
|
||||
function addWebSearchTool(req: Request) {
|
||||
// Check if this is a Claude model that supports web search and if web search is enabled
|
||||
const isClaude35 = req.body.model?.includes("claude-3-5") || req.body.model?.includes("claude-3.5");
|
||||
const isClaude37 = req.body.model?.includes("claude-3-7") || req.body.model?.includes("claude-3.7");
|
||||
const isClaude4 = req.body.model?.includes("claude-sonnet-4") || req.body.model?.includes("claude-opus-4");
|
||||
const useWebSearch = (isClaude35 || isClaude37 || isClaude4) && Boolean(req.body.enable_web_search);
|
||||
|
||||
if (useWebSearch) {
|
||||
// Create the base web search tool
|
||||
const webSearchTool: any = {
|
||||
'type': 'web_search_20250305',
|
||||
'name': 'web_search',
|
||||
};
|
||||
|
||||
// Add optional parameters if provided by the client
|
||||
|
||||
// max_uses: Limit the number of searches per request
|
||||
if (typeof req.body.web_search_max_uses === 'number') {
|
||||
webSearchTool.max_uses = req.body.web_search_max_uses;
|
||||
delete req.body.web_search_max_uses;
|
||||
}
|
||||
|
||||
// allowed_domains: Only include results from these domains
|
||||
if (Array.isArray(req.body.web_search_allowed_domains)) {
|
||||
webSearchTool.allowed_domains = req.body.web_search_allowed_domains;
|
||||
delete req.body.web_search_allowed_domains;
|
||||
}
|
||||
|
||||
// blocked_domains: Never include results from these domains
|
||||
if (Array.isArray(req.body.web_search_blocked_domains)) {
|
||||
webSearchTool.blocked_domains = req.body.web_search_blocked_domains;
|
||||
delete req.body.web_search_blocked_domains;
|
||||
}
|
||||
|
||||
// user_location: Localize search results
|
||||
if (req.body.web_search_user_location) {
|
||||
webSearchTool.user_location = req.body.web_search_user_location;
|
||||
delete req.body.web_search_user_location;
|
||||
}
|
||||
|
||||
// Add the web search tool to the tools array
|
||||
req.body.tools = [...(req.body.tools || []), webSearchTool];
|
||||
}
|
||||
|
||||
// Delete custom parameters as they're not standard Claude API parameters
|
||||
delete req.body.enable_web_search;
|
||||
delete req.body.reasoning_effort;
|
||||
}
|
||||
|
||||
function selectUpstreamPath(manager: ProxyReqManager) {
|
||||
@@ -218,44 +286,58 @@ const anthropicProxy = createQueuedProxyMiddleware({
|
||||
|
||||
const nativeAnthropicChatPreprocessor = createPreprocessorMiddleware(
|
||||
{ inApi: "anthropic-chat", outApi: "anthropic-chat", service: "anthropic" },
|
||||
{ afterTransform: [setAnthropicBetaHeader] }
|
||||
{ afterTransform: [setAnthropicBetaHeader, addWebSearchTool] }
|
||||
);
|
||||
|
||||
const nativeTextPreprocessor = createPreprocessorMiddleware({
|
||||
inApi: "anthropic-text",
|
||||
outApi: "anthropic-text",
|
||||
service: "anthropic",
|
||||
});
|
||||
const nativeTextPreprocessor = createPreprocessorMiddleware(
|
||||
{
|
||||
inApi: "anthropic-text",
|
||||
outApi: "anthropic-text",
|
||||
service: "anthropic",
|
||||
},
|
||||
{ afterTransform: [setAnthropicBetaHeader, addWebSearchTool] }
|
||||
);
|
||||
|
||||
const textToChatPreprocessor = createPreprocessorMiddleware({
|
||||
inApi: "anthropic-text",
|
||||
outApi: "anthropic-chat",
|
||||
service: "anthropic",
|
||||
});
|
||||
const textToChatPreprocessor = createPreprocessorMiddleware(
|
||||
{
|
||||
inApi: "anthropic-text",
|
||||
outApi: "anthropic-chat",
|
||||
service: "anthropic",
|
||||
},
|
||||
{ afterTransform: [setAnthropicBetaHeader, addWebSearchTool] }
|
||||
);
|
||||
|
||||
/**
|
||||
* Routes text completion prompts to anthropic-chat if they need translation
|
||||
* (claude-3 based models do not support the old text completion endpoint).
|
||||
*/
|
||||
const preprocessAnthropicTextRequest: RequestHandler = (req, res, next) => {
|
||||
if (req.body.model?.startsWith("claude-3")) {
|
||||
const model = req.body.model;
|
||||
const isClaude4Model = model?.includes("claude-sonnet-4") || model?.includes("claude-opus-4");
|
||||
if (model?.startsWith("claude-3") || isClaude4Model) {
|
||||
textToChatPreprocessor(req, res, next);
|
||||
} else {
|
||||
nativeTextPreprocessor(req, res, next);
|
||||
}
|
||||
};
|
||||
|
||||
const oaiToTextPreprocessor = createPreprocessorMiddleware({
|
||||
inApi: "openai",
|
||||
outApi: "anthropic-text",
|
||||
service: "anthropic",
|
||||
});
|
||||
const oaiToTextPreprocessor = createPreprocessorMiddleware(
|
||||
{
|
||||
inApi: "openai",
|
||||
outApi: "anthropic-text",
|
||||
service: "anthropic",
|
||||
},
|
||||
{ afterTransform: [setAnthropicBetaHeader] }
|
||||
);
|
||||
|
||||
const oaiToChatPreprocessor = createPreprocessorMiddleware({
|
||||
inApi: "openai",
|
||||
outApi: "anthropic-chat",
|
||||
service: "anthropic",
|
||||
});
|
||||
const oaiToChatPreprocessor = createPreprocessorMiddleware(
|
||||
{
|
||||
inApi: "openai",
|
||||
outApi: "anthropic-chat",
|
||||
service: "anthropic",
|
||||
},
|
||||
{ afterTransform: [setAnthropicBetaHeader, addWebSearchTool] }
|
||||
);
|
||||
|
||||
/**
|
||||
* Routes an OpenAI prompt to either the legacy Claude text completion endpoint
|
||||
@@ -263,7 +345,9 @@ const oaiToChatPreprocessor = createPreprocessorMiddleware({
|
||||
*/
|
||||
const preprocessOpenAICompatRequest: RequestHandler = (req, res, next) => {
|
||||
maybeReassignModel(req);
|
||||
if (req.body.model?.includes("claude-3")) {
|
||||
const model = req.body.model;
|
||||
const isClaude4 = model?.includes("claude-sonnet-4") || model?.includes("claude-opus-4");
|
||||
if (model?.includes("claude-3") || isClaude4) {
|
||||
oaiToChatPreprocessor(req, res, next);
|
||||
} else {
|
||||
oaiToTextPreprocessor(req, res, next);
|
||||
|
||||
+93
-9
@@ -12,6 +12,8 @@ import {
|
||||
} from "./middleware/request";
|
||||
import { ProxyResHandlerWithBody } from "./middleware/response";
|
||||
import { createQueuedProxyMiddleware } from "./middleware/request/proxy-middleware-factory";
|
||||
import { ProxyReqManager } from "./middleware/request/proxy-req-manager";
|
||||
import { validateClaude41OpusParameters } from "../shared/claude-4-1-validation";
|
||||
|
||||
const awsBlockingResponseHandler: ProxyResHandlerWithBody = async (
|
||||
_proxyRes,
|
||||
@@ -167,6 +169,9 @@ awsClaudeRouter.post(
|
||||
* strategies are used to try to map a non-AWS model name to AWS model ID.
|
||||
*/
|
||||
function maybeReassignModel(req: Request) {
|
||||
// Validate Claude 4.1 Opus parameters before processing
|
||||
validateClaude41OpusParameters(req);
|
||||
|
||||
const model = req.body.model;
|
||||
|
||||
// If it looks like an AWS model, use it as-is
|
||||
@@ -177,25 +182,72 @@ function maybeReassignModel(req: Request) {
|
||||
// Anthropic model names can look like:
|
||||
// - claude-v1
|
||||
// - claude-2.1
|
||||
// - claude-3-5-sonnet-20240620
|
||||
// - claude-3-opus-latest
|
||||
// - claude-3-5-sonnet-20240620 (old format: number-model)
|
||||
// - claude-3-opus-latest (old format: number-model)
|
||||
// - claude-sonnet-4-20250514 (new format: model-number)
|
||||
// - claude-opus-4-latest (new format: model-number)
|
||||
// - anthropic.claude-3-sonnet-20240229-v1:0 (AWS format with old naming)
|
||||
// - anthropic.claude-sonnet-4-20250514-v1:0 (AWS format with new naming)
|
||||
const pattern =
|
||||
/^(claude-)?(instant-)?(v)?(\d+)([.-](\d))?(-\d+k)?(-sonnet-|-opus-|-haiku-)?(latest|\d*)/i;
|
||||
/^(?:anthropic\.)?claude-(?:(?:(instant-)?(v)?(\d+)([.-](\d))?(-\d+k)?(-sonnet-|-opus-|-haiku-)?(latest|\d*))|(?:(sonnet-|opus-|haiku-)(\d+)([.-](\d))?(-\d+k)?-(latest|\d+)))(?:-v\d+(?::\d+)?)?$/i;
|
||||
const match = model.match(pattern);
|
||||
|
||||
if (!match) {
|
||||
throw new Error(`Provided model name (${model}) doesn't resemble a Claude model ID.`);
|
||||
}
|
||||
|
||||
const [_, _cl, instant, _v, major, _sep, minor, _ctx, rawName, rev] = match;
|
||||
|
||||
if (instant) {
|
||||
req.body.model = "anthropic.claude-instant-v1";
|
||||
return;
|
||||
// Check which format matched (old or new)
|
||||
// New format: claude-sonnet-4-20250514 or anthropic.claude-sonnet-4-20250514-v1:0
|
||||
// Old format: claude-3-sonnet-20240229 or anthropic.claude-3-sonnet-20240229-v1:0
|
||||
const isNewFormat = !!match[9];
|
||||
|
||||
let major, minor, name, rev;
|
||||
|
||||
if (isNewFormat) {
|
||||
// New format: claude-sonnet-4-20250514
|
||||
// match[9] = sonnet-/opus-/haiku-
|
||||
// match[10] = 4 (major version)
|
||||
// match[12] = minor version (if any, from [.-](\d) pattern)
|
||||
// match[14] = revision (latest or date)
|
||||
const modelType = match[9]?.match(/([a-z]+)/)?.[1] || "";
|
||||
name = modelType;
|
||||
major = match[10];
|
||||
minor = match[12];
|
||||
rev = match[14];
|
||||
|
||||
// Special case: if revision is a single digit and no minor version,
|
||||
// treat revision as minor version (e.g., claude-opus-4-1 -> version 4.1)
|
||||
if (!minor && rev && /^\d$/.test(rev)) {
|
||||
minor = rev;
|
||||
rev = undefined;
|
||||
}
|
||||
|
||||
// Handle instant case for completeness
|
||||
const instant = match[1];
|
||||
if (instant) {
|
||||
req.body.model = "anthropic.claude-instant-v1";
|
||||
return;
|
||||
}
|
||||
} else {
|
||||
// Old format: claude-3-sonnet-20240229
|
||||
// match[1] = instant- (if any)
|
||||
// match[3] = 3 (major version)
|
||||
// match[5] = minor version (if any)
|
||||
// match[7] = -sonnet-/-opus-/-haiku- (if any)
|
||||
// match[8] = revision (latest or date)
|
||||
const instant = match[1];
|
||||
if (instant) {
|
||||
req.body.model = "anthropic.claude-instant-v1";
|
||||
return;
|
||||
}
|
||||
|
||||
major = match[3];
|
||||
minor = match[5];
|
||||
name = match[7]?.match(/([a-z]+)/)?.[1] || "";
|
||||
rev = match[8];
|
||||
}
|
||||
|
||||
const ver = minor ? `${major}.${minor}` : major;
|
||||
const name = rawName?.match(/([a-z]+)/)?.[1] || "";
|
||||
|
||||
switch (ver) {
|
||||
case "1":
|
||||
@@ -249,6 +301,38 @@ function maybeReassignModel(req: Request) {
|
||||
// Add after model id is announced never
|
||||
break;
|
||||
}
|
||||
case "3.7":
|
||||
switch (name) {
|
||||
case "sonnet":
|
||||
req.body.model = "anthropic.claude-3-7-sonnet-20250219-v1:0";
|
||||
return;
|
||||
}
|
||||
break;
|
||||
case "4":
|
||||
case "4.0":
|
||||
// Mapping "claude-4-..." variants to their actual AWS Bedrock IDs
|
||||
// as defined in src/shared/claude-models.ts.
|
||||
switch (name) {
|
||||
case "sonnet":
|
||||
req.body.model = "anthropic.claude-sonnet-4-20250514-v1:0";
|
||||
return;
|
||||
case "opus":
|
||||
req.body.model = "anthropic.claude-opus-4-20250514-v1:0";
|
||||
return;
|
||||
// No case for "haiku" here, as "claude-4-haiku" is not defined
|
||||
// in claude-models.ts. It will fall through and throw an error.
|
||||
}
|
||||
break;
|
||||
case "4.1":
|
||||
// Mapping "claude-4.1-..." variants to their actual AWS Bedrock IDs
|
||||
// as defined in src/shared/claude-models.ts.
|
||||
switch (name) {
|
||||
case "opus":
|
||||
req.body.model = "anthropic.claude-opus-4-1-20250805-v1:0";
|
||||
return;
|
||||
// No sonnet or haiku variants for 4.1 yet
|
||||
}
|
||||
break;
|
||||
}
|
||||
|
||||
throw new Error(`Provided model name (${model}) could not be mapped to a known AWS Claude model ID.`);
|
||||
|
||||
+47
-26
@@ -6,6 +6,7 @@ import { addV1 } from "./add-v1";
|
||||
import { awsClaude } from "./aws-claude";
|
||||
import { awsMistral } from "./aws-mistral";
|
||||
import { AwsBedrockKey, keyPool } from "../shared/key-management";
|
||||
import { claudeModels, findByAwsId } from "../shared/claude-models";
|
||||
|
||||
const awsRouter = Router();
|
||||
awsRouter.get(["/:vendor?/v1/models", "/:vendor?/models"], handleModelsRequest);
|
||||
@@ -29,47 +30,67 @@ function handleModelsRequest(req: Request, res: Response) {
|
||||
return res.json(modelsCache[vendor]);
|
||||
}
|
||||
|
||||
const availableModelIds = new Set<string>();
|
||||
const availableAwsModelIds = new Set<string>();
|
||||
for (const key of keyPool.list()) {
|
||||
if (key.isDisabled || key.service !== "aws") continue;
|
||||
(key as AwsBedrockKey).modelIds.forEach((id) => availableModelIds.add(id));
|
||||
(key as AwsBedrockKey).modelIds.forEach((id) => availableAwsModelIds.add(id));
|
||||
}
|
||||
|
||||
// https://docs.aws.amazon.com/bedrock/latest/userguide/model-ids.html
|
||||
const models = [
|
||||
"anthropic.claude-v2",
|
||||
"anthropic.claude-v2:1",
|
||||
"anthropic.claude-3-haiku-20240307-v1:0",
|
||||
"anthropic.claude-3-5-haiku-20241022-v1:0",
|
||||
"anthropic.claude-3-sonnet-20240229-v1:0",
|
||||
"anthropic.claude-3-5-sonnet-20240620-v1:0",
|
||||
"anthropic.claude-3-5-sonnet-20241022-v2:0",
|
||||
"anthropic.claude-3-opus-20240229-v1:0",
|
||||
"mistral.mistral-7b-instruct-v0:2",
|
||||
"mistral.mixtral-8x7b-instruct-v0:1",
|
||||
"mistral.mistral-large-2402-v1:0",
|
||||
"mistral.mistral-large-2407-v1:0",
|
||||
"mistral.mistral-small-2402-v1:0",
|
||||
]
|
||||
.filter((id) => availableModelIds.has(id))
|
||||
.map((id) => {
|
||||
const vendor = id.match(/^(.*)\./)?.[1];
|
||||
const mistralMappings = new Map([
|
||||
["mistral.mistral-7b-instruct-v0:2", "Mistral 7B Instruct"],
|
||||
["mistral.mixtral-8x7b-instruct-v0:1", "Mixtral 8x7B Instruct"],
|
||||
["mistral.mistral-large-2402-v1:0", "Mistral Large 2402"],
|
||||
["mistral.mistral-large-2407-v1:0", "Mistral Large 2407"],
|
||||
["mistral.mistral-small-2402-v1:0", "Mistral Small 2402"],
|
||||
]);
|
||||
|
||||
const date = new Date();
|
||||
|
||||
const claudeModelsList = claudeModels
|
||||
.filter(model => availableAwsModelIds.has(model.awsId))
|
||||
.map(model => ({
|
||||
id: model.anthropicId,
|
||||
owned_by: "anthropic",
|
||||
type: "model",
|
||||
display_name: model.displayName,
|
||||
created_at: date.toISOString(),
|
||||
object: "model",
|
||||
created: date.getTime(),
|
||||
permission: [],
|
||||
root: "anthropic",
|
||||
parent: null,
|
||||
}));
|
||||
|
||||
const mistralModelsList = Array.from(mistralMappings.keys())
|
||||
.filter(id => availableAwsModelIds.has(id))
|
||||
.map(id => {
|
||||
return {
|
||||
id,
|
||||
owned_by: "mistral",
|
||||
type: "model",
|
||||
display_name: mistralMappings.get(id) || id.split('.')[1],
|
||||
created_at: date.toISOString(),
|
||||
object: "model",
|
||||
created: new Date().getTime(),
|
||||
owned_by: vendor,
|
||||
created: date.getTime(),
|
||||
permission: [],
|
||||
root: vendor,
|
||||
root: "mistral",
|
||||
parent: null,
|
||||
};
|
||||
});
|
||||
|
||||
const allModels = [...claudeModelsList, ...mistralModelsList];
|
||||
const filteredModels = vendor === "all"
|
||||
? allModels
|
||||
: allModels.filter(m => m.root === vendor);
|
||||
|
||||
modelsCache[vendor] = {
|
||||
object: "list",
|
||||
data: models.filter((m) => vendor === "all" || m.root === vendor),
|
||||
data: filteredModels,
|
||||
has_more: false,
|
||||
first_id: filteredModels[0]?.id,
|
||||
last_id: filteredModels[filteredModels.length - 1]?.id,
|
||||
};
|
||||
modelsCacheTime[vendor] = new Date().getTime();
|
||||
modelsCacheTime[vendor] = date.getTime();
|
||||
|
||||
return res.json(modelsCache[vendor]);
|
||||
}
|
||||
|
||||
@@ -0,0 +1,222 @@
|
||||
import { Request, RequestHandler, Router } from "express";
|
||||
import { createPreprocessorMiddleware } from "./middleware/request";
|
||||
import { ipLimiter } from "./rate-limit";
|
||||
import { createQueuedProxyMiddleware } from "./middleware/request/proxy-middleware-factory";
|
||||
import { addKey, finalizeBody } from "./middleware/request";
|
||||
import { ProxyResHandlerWithBody } from "./middleware/response";
|
||||
import axios from "axios";
|
||||
import { CohereKey, keyPool } from "../shared/key-management";
|
||||
import { isCohereModel, normalizeMessages } from "../shared/api-schemas/cohere";
|
||||
import { logger } from "../logger";
|
||||
|
||||
const log = logger.child({ module: "proxy", service: "cohere" });
|
||||
let modelsCache: any = null;
|
||||
let modelsCacheTime = 0;
|
||||
|
||||
const cohereResponseHandler: ProxyResHandlerWithBody = async (
|
||||
_proxyRes,
|
||||
req,
|
||||
res,
|
||||
body
|
||||
) => {
|
||||
if (typeof body !== "object") {
|
||||
throw new Error("Expected body to be an object");
|
||||
}
|
||||
|
||||
res.status(200).json({ ...body, proxy: body.proxy });
|
||||
};
|
||||
|
||||
const getModelsResponse = async () => {
|
||||
// Return cache if less than 1 minute old
|
||||
if (new Date().getTime() - modelsCacheTime < 1000 * 60) {
|
||||
return modelsCache;
|
||||
}
|
||||
|
||||
try {
|
||||
// Get a Cohere key directly
|
||||
const modelToUse = "command"; // Use any Cohere model here - just for key selection
|
||||
const cohereKey = keyPool.get(modelToUse, "cohere") as CohereKey;
|
||||
|
||||
if (!cohereKey || !cohereKey.key) {
|
||||
log.warn("No valid Cohere key available for model listing");
|
||||
throw new Error("No valid Cohere API key available");
|
||||
}
|
||||
|
||||
// Fetch models directly from Cohere API
|
||||
const response = await axios.get("https://api.cohere.com/v1/models", {
|
||||
headers: {
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": `Bearer ${cohereKey.key}`,
|
||||
"Cohere-Version": "2022-12-06"
|
||||
},
|
||||
});
|
||||
|
||||
if (!response.data || !response.data.models) {
|
||||
throw new Error("Unexpected response format from Cohere API");
|
||||
}
|
||||
|
||||
// Extract models and filter by those that support the chat endpoint
|
||||
const filteredModels = response.data.models
|
||||
.filter((model: any) => {
|
||||
return model.endpoints && model.endpoints.includes("chat");
|
||||
})
|
||||
.map((model: any) => ({
|
||||
id: model.name,
|
||||
name: model.name,
|
||||
// Adding additional OpenAI-compatible fields
|
||||
context_window: model.context_window_size || 4096,
|
||||
max_tokens: model.max_tokens || 4096
|
||||
}));
|
||||
|
||||
log.debug({ modelCount: filteredModels.length, models: filteredModels.map((m: any) => m.id) }, "Filtered models from Cohere API");
|
||||
|
||||
// Format response to ensure OpenAI compatibility
|
||||
const models = {
|
||||
object: "list",
|
||||
data: filteredModels.map((model: any) => ({
|
||||
id: model.id,
|
||||
object: "model",
|
||||
created: Math.floor(Date.now() / 1000),
|
||||
owned_by: "cohere",
|
||||
permission: [],
|
||||
root: model.id,
|
||||
parent: null,
|
||||
context_length: model.context_window,
|
||||
})),
|
||||
};
|
||||
|
||||
log.debug({ modelCount: filteredModels.length }, "Retrieved models from Cohere API");
|
||||
|
||||
// Cache the response
|
||||
modelsCache = models;
|
||||
modelsCacheTime = new Date().getTime();
|
||||
return models;
|
||||
} catch (error) {
|
||||
// Provide detailed logging for better troubleshooting
|
||||
if (error instanceof Error) {
|
||||
log.error(
|
||||
{ errorMessage: error.message, stack: error.stack },
|
||||
"Error fetching Cohere models"
|
||||
);
|
||||
} else {
|
||||
log.error({ error }, "Unknown error fetching Cohere models");
|
||||
}
|
||||
|
||||
// Return empty list as fallback
|
||||
return {
|
||||
object: "list",
|
||||
data: [],
|
||||
};
|
||||
}
|
||||
};
|
||||
|
||||
const handleModelRequest: RequestHandler = async (_req, res) => {
|
||||
try {
|
||||
const models = await getModelsResponse();
|
||||
res.status(200).json(models);
|
||||
} catch (error) {
|
||||
if (error instanceof Error) {
|
||||
log.error(
|
||||
{ errorMessage: error.message, stack: error.stack },
|
||||
"Error handling model request"
|
||||
);
|
||||
} else {
|
||||
log.error({ error }, "Unknown error handling model request");
|
||||
}
|
||||
res.status(500).json({ error: "Failed to fetch models" });
|
||||
}
|
||||
};
|
||||
|
||||
// Function to prepare messages for Cohere API
|
||||
function prepareMessages(req: Request) {
|
||||
if (req.body.messages && Array.isArray(req.body.messages)) {
|
||||
req.body.messages = normalizeMessages(req.body.messages);
|
||||
}
|
||||
}
|
||||
|
||||
// Function to remove parameters not supported by Cohere models
|
||||
function removeUnsupportedParameters(req: Request) {
|
||||
const model = req.body.model;
|
||||
|
||||
// Remove parameters that Cohere doesn't support
|
||||
if (req.body.logit_bias !== undefined) {
|
||||
delete req.body.logit_bias;
|
||||
}
|
||||
|
||||
if (req.body.top_logprobs !== undefined) {
|
||||
delete req.body.top_logprobs;
|
||||
}
|
||||
|
||||
if (req.body.max_completion_tokens !== undefined) {
|
||||
delete req.body.max_completion_tokens;
|
||||
}
|
||||
|
||||
// Handle structured output format
|
||||
if (req.body.response_format && req.body.response_format.schema) {
|
||||
// Transform to Cohere's format if needed
|
||||
const jsonSchema = req.body.response_format.schema;
|
||||
req.body.response_format = {
|
||||
type: "json_object",
|
||||
schema: jsonSchema
|
||||
};
|
||||
}
|
||||
|
||||
// Logging for debugging
|
||||
if (process.env.NODE_ENV !== 'production') {
|
||||
log.debug({ body: req.body }, "Request after parameter cleanup");
|
||||
}
|
||||
}
|
||||
|
||||
// Set up count token functionality for Cohere models
|
||||
function countCohereTokens(req: Request) {
|
||||
const model = req.body.model;
|
||||
|
||||
if (isCohereModel(model)) {
|
||||
// Count tokens using prompt tokens (simplified)
|
||||
if (req.promptTokens) {
|
||||
req.log.debug(
|
||||
{ tokens: req.promptTokens },
|
||||
"Estimated token count for Cohere prompt"
|
||||
);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
const cohereProxy = createQueuedProxyMiddleware({
|
||||
mutations: [
|
||||
addKey,
|
||||
// Add Cohere-Version header to every request
|
||||
(manager) => {
|
||||
manager.setHeader("Cohere-Version", "2022-12-06");
|
||||
},
|
||||
finalizeBody
|
||||
],
|
||||
target: "https://api.cohere.ai/compatibility",
|
||||
blockingResponseHandler: cohereResponseHandler,
|
||||
});
|
||||
|
||||
const cohereRouter = Router();
|
||||
|
||||
cohereRouter.post(
|
||||
"/v1/chat/completions",
|
||||
ipLimiter,
|
||||
createPreprocessorMiddleware(
|
||||
{ inApi: "openai", outApi: "openai", service: "cohere" },
|
||||
{ afterTransform: [ prepareMessages, removeUnsupportedParameters, countCohereTokens ] }
|
||||
),
|
||||
cohereProxy
|
||||
);
|
||||
|
||||
cohereRouter.post(
|
||||
"/v1/embeddings",
|
||||
ipLimiter,
|
||||
createPreprocessorMiddleware(
|
||||
{ inApi: "openai", outApi: "openai", service: "cohere" },
|
||||
{ afterTransform: [] }
|
||||
),
|
||||
cohereProxy
|
||||
);
|
||||
|
||||
cohereRouter.get("/v1/models", handleModelRequest);
|
||||
|
||||
export const cohere = cohereRouter;
|
||||
@@ -0,0 +1,135 @@
|
||||
import { Request, RequestHandler, Router } from "express";
|
||||
import { createPreprocessorMiddleware } from "./middleware/request";
|
||||
import { ipLimiter } from "./rate-limit";
|
||||
import { createQueuedProxyMiddleware } from "./middleware/request/proxy-middleware-factory";
|
||||
import { addKey, finalizeBody } from "./middleware/request";
|
||||
import { ProxyResHandlerWithBody } from "./middleware/response";
|
||||
import axios from "axios";
|
||||
import { DeepseekKey, keyPool } from "../shared/key-management";
|
||||
|
||||
let modelsCache: any = null;
|
||||
let modelsCacheTime = 0;
|
||||
|
||||
const deepseekResponseHandler: ProxyResHandlerWithBody = async (
|
||||
_proxyRes,
|
||||
req,
|
||||
res,
|
||||
body
|
||||
) => {
|
||||
if (typeof body !== "object") {
|
||||
throw new Error("Expected body to be an object");
|
||||
}
|
||||
|
||||
let newBody = body;
|
||||
|
||||
res.status(200).json({ ...newBody, proxy: body.proxy });
|
||||
};
|
||||
|
||||
const getModelsResponse = async () => {
|
||||
// Return cache if less than 1 minute old
|
||||
if (new Date().getTime() - modelsCacheTime < 1000 * 60) {
|
||||
return modelsCache;
|
||||
}
|
||||
|
||||
try {
|
||||
// Get a Deepseek key directly using keyPool.get()
|
||||
const modelToUse = "deepseek-chat"; // Use any Deepseek model here - just for key selection
|
||||
const deepseekKey = keyPool.get(modelToUse, "deepseek") as DeepseekKey;
|
||||
|
||||
if (!deepseekKey || !deepseekKey.key) {
|
||||
throw new Error("Failed to get valid Deepseek key");
|
||||
}
|
||||
|
||||
// Fetch models from Deepseek API with authorization
|
||||
const response = await axios.get("https://api.deepseek.com/models", {
|
||||
headers: {
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": `Bearer ${deepseekKey.key}`
|
||||
},
|
||||
});
|
||||
|
||||
// If successful, update the cache
|
||||
if (response.data && response.data.data) {
|
||||
modelsCache = {
|
||||
object: "list",
|
||||
data: response.data.data.map((model: any) => ({
|
||||
id: model.id,
|
||||
object: "model",
|
||||
owned_by: "deepseek",
|
||||
})),
|
||||
};
|
||||
} else {
|
||||
throw new Error("Unexpected response format from Deepseek API");
|
||||
}
|
||||
} catch (error) {
|
||||
console.error("Error fetching Deepseek models:", error);
|
||||
throw error; // No fallback - error will be passed to caller
|
||||
}
|
||||
|
||||
modelsCacheTime = new Date().getTime();
|
||||
return modelsCache;
|
||||
};
|
||||
|
||||
const handleModelRequest: RequestHandler = async (_req, res) => {
|
||||
try {
|
||||
const modelsResponse = await getModelsResponse();
|
||||
res.status(200).json(modelsResponse);
|
||||
} catch (error) {
|
||||
console.error("Error in handleModelRequest:", error);
|
||||
res.status(500).json({ error: "Failed to fetch models" });
|
||||
}
|
||||
};
|
||||
|
||||
const deepseekProxy = createQueuedProxyMiddleware({
|
||||
mutations: [addKey, finalizeBody],
|
||||
target: "https://api.deepseek.com/beta",
|
||||
blockingResponseHandler: deepseekResponseHandler,
|
||||
});
|
||||
|
||||
const deepseekRouter = Router();
|
||||
|
||||
// combines all the assistant messages at the end of the context and adds the
|
||||
// beta 'prefix' option, makes prefills work the same way they work for Claude
|
||||
function enablePrefill(req: Request) {
|
||||
// If you want to disable
|
||||
if (process.env.NO_DEEPSEEK_PREFILL) return
|
||||
|
||||
const msgs = req.body.messages;
|
||||
if (msgs.at(-1)?.role !== 'assistant') return;
|
||||
|
||||
let i = msgs.length - 1;
|
||||
let content = '';
|
||||
|
||||
while (i >= 0 && msgs[i].role === 'assistant') {
|
||||
// maybe we should also add a newline between messages? no for now.
|
||||
content = msgs[i--].content + content;
|
||||
}
|
||||
|
||||
msgs.splice(i + 1, msgs.length, { role: 'assistant', content, prefix: true });
|
||||
}
|
||||
|
||||
function removeReasonerStuff(req: Request) {
|
||||
if (req.body.model === "deepseek-reasoner") {
|
||||
// https://api-docs.deepseek.com/guides/reasoning_model
|
||||
delete req.body.presence_penalty;
|
||||
delete req.body.frequency_penalty;
|
||||
delete req.body.temperature;
|
||||
delete req.body.top_p;
|
||||
delete req.body.logprobs;
|
||||
delete req.body.top_logprobs;
|
||||
}
|
||||
}
|
||||
|
||||
deepseekRouter.post(
|
||||
"/v1/chat/completions",
|
||||
ipLimiter,
|
||||
createPreprocessorMiddleware(
|
||||
{ inApi: "openai", outApi: "openai", service: "deepseek" },
|
||||
{ afterTransform: [ enablePrefill, removeReasonerStuff ] }
|
||||
),
|
||||
deepseekProxy
|
||||
);
|
||||
|
||||
deepseekRouter.get("/v1/models", handleModelRequest);
|
||||
|
||||
export const deepseek = deepseekRouter;
|
||||
@@ -25,6 +25,12 @@ function getProxyAuthorizationFromRequest(req: Request): string | undefined {
|
||||
delete req.headers["x-api-key"];
|
||||
return token;
|
||||
}
|
||||
|
||||
if (req.headers["x-goog-api-key"]) {
|
||||
const token = req.headers["x-goog-api-key"]?.toString();
|
||||
delete req.headers["x-goog-api-key"];
|
||||
return token;
|
||||
}
|
||||
|
||||
if (req.query.key) {
|
||||
const token = req.query.key?.toString();
|
||||
|
||||
+100
-39
@@ -9,6 +9,7 @@ import {
|
||||
} from "./middleware/request";
|
||||
import { ProxyResHandlerWithBody } from "./middleware/response";
|
||||
import { createQueuedProxyMiddleware } from "./middleware/request/proxy-middleware-factory";
|
||||
import { validateClaude41OpusParameters } from "../shared/claude-4-1-validation";
|
||||
|
||||
const LATEST_GCP_SONNET_MINOR_VERSION = "20240229";
|
||||
|
||||
@@ -26,10 +27,12 @@ const getModelsResponse = () => {
|
||||
const variants = [
|
||||
"claude-3-haiku@20240307",
|
||||
"claude-3-5-haiku@20241022",
|
||||
"claude-3-sonnet@20240229",
|
||||
"claude-3-5-sonnet@20240620",
|
||||
"claude-3-5-sonnet-v2@20241022",
|
||||
"claude-3-opus@20240229",
|
||||
"claude-3-7-sonnet@20250219",
|
||||
"claude-sonnet-4@20250514",
|
||||
"claude-opus-4@20250514",
|
||||
"claude-opus-4-1@20250805",
|
||||
];
|
||||
|
||||
const models = variants.map((id) => ({
|
||||
@@ -128,69 +131,127 @@ gcpRouter.post(
|
||||
* strategies are used to try to map a non-GCP model name to GCP model ID.
|
||||
*/
|
||||
function maybeReassignModel(req: Request) {
|
||||
// Validate Claude 4.1 Opus parameters before processing
|
||||
validateClaude41OpusParameters(req);
|
||||
|
||||
const model = req.body.model;
|
||||
const DEFAULT_MODEL = "claude-3-5-sonnet-v2@20241022";
|
||||
|
||||
// If it looks like an GCP model, use it as-is
|
||||
// if (model.includes("anthropic.claude")) {
|
||||
if (model.startsWith("claude-") && model.includes("@")) {
|
||||
return;
|
||||
}
|
||||
|
||||
// Anthropic model names can look like:
|
||||
// - claude-v1
|
||||
// - claude-2.1
|
||||
// - claude-3-5-sonnet-20240620-v1:0
|
||||
const pattern =
|
||||
/^(claude-)?(instant-)?(v)?(\d+)([.-](\d{1}))?(-\d+k)?(-sonnet-|-opus-|-haiku-)?(\d*)/i;
|
||||
// - claude-3-sonnet
|
||||
// - claude-3.5-sonnet
|
||||
// - claude-3-5-haiku
|
||||
// - claude-3-5-haiku-latest
|
||||
// - claude-3-5-sonnet-20240620
|
||||
// - claude-opus-4-1 (new format)
|
||||
// - claude-4.1-opus (alternative format)
|
||||
const pattern = /^claude-(?:(\d+)[.-]?(\d)?-(sonnet|opus|haiku)(?:-(latest|\d+))?|(opus|sonnet|haiku)-(\d+)[.-]?(\d)?(?:-(latest|\d+))?)/i;
|
||||
const match = model.match(pattern);
|
||||
|
||||
// If there's no match, fallback to Claude3 Sonnet as it is most likely to be
|
||||
// available on GCP.
|
||||
if (!match) {
|
||||
req.body.model = `claude-3-sonnet@${LATEST_GCP_SONNET_MINOR_VERSION}`;
|
||||
req.body.model = DEFAULT_MODEL;
|
||||
return;
|
||||
}
|
||||
|
||||
const [_, _cl, instant, _v, major, _sep, minor, _ctx, name, rev] = match;
|
||||
|
||||
// TODO: rework this to function similarly to aws-claude.ts maybeReassignModel
|
||||
// Handle both formats: claude-3-5-sonnet and claude-opus-4-1
|
||||
const [_, major1, minor1, flavor1, rev1, flavor2, major2, minor2, rev2] = match;
|
||||
|
||||
let major, minor, flavor, rev;
|
||||
if (major1) {
|
||||
// Old format: claude-3-5-sonnet
|
||||
major = major1;
|
||||
minor = minor1;
|
||||
flavor = flavor1;
|
||||
rev = rev1;
|
||||
} else {
|
||||
// New format: claude-opus-4-1
|
||||
major = major2;
|
||||
minor = minor2;
|
||||
flavor = flavor2;
|
||||
rev = rev2;
|
||||
}
|
||||
|
||||
const ver = minor ? `${major}.${minor}` : major;
|
||||
|
||||
switch (ver) {
|
||||
case "3":
|
||||
case "3.0":
|
||||
if (name.includes("opus")) {
|
||||
req.body.model = "claude-3-opus@20240229";
|
||||
} else if (name.includes("haiku")) {
|
||||
req.body.model = "claude-3-haiku@20240307";
|
||||
} else {
|
||||
req.body.model = "claude-3-sonnet@20240229";
|
||||
switch (flavor) {
|
||||
case "haiku":
|
||||
req.body.model = "claude-3-haiku@20240307";
|
||||
break;
|
||||
case "opus":
|
||||
req.body.model = "claude-3-opus@20240229";
|
||||
break;
|
||||
case "sonnet":
|
||||
req.body.model = "claude-3-sonnet@20240229";
|
||||
break;
|
||||
default:
|
||||
req.body.model = "claude-3-sonnet@20240229";
|
||||
}
|
||||
return;
|
||||
|
||||
case "3.5":
|
||||
switch (name) {
|
||||
case "sonnet":
|
||||
switch (rev) {
|
||||
case "20241022":
|
||||
case "latest":
|
||||
req.body.model = "claude-3-5-sonnet-v2@20241022";
|
||||
return;
|
||||
case "20240620":
|
||||
req.body.model = "claude-3-5-sonnet@20240620";
|
||||
return;
|
||||
}
|
||||
break;
|
||||
switch (flavor) {
|
||||
case "haiku":
|
||||
req.body.model = "claude-3-5-haiku@20241022";
|
||||
return;
|
||||
case "opus":
|
||||
// Add after model ids are announced late 2024
|
||||
break;
|
||||
// no 3.5 opus yet
|
||||
req.body.model = DEFAULT_MODEL;
|
||||
return;
|
||||
case "sonnet":
|
||||
if (rev === "20240620") {
|
||||
req.body.model = "claude-3-5-sonnet@20240620";
|
||||
} else {
|
||||
// includes -latest, edit if anthropic actually releases 3.5 sonnet v3
|
||||
req.body.model = DEFAULT_MODEL;
|
||||
}
|
||||
return;
|
||||
default:
|
||||
req.body.model = DEFAULT_MODEL;
|
||||
}
|
||||
}
|
||||
return;
|
||||
|
||||
case "3.7":
|
||||
switch (flavor) {
|
||||
case "sonnet":
|
||||
req.body.model = "claude-3-7-sonnet@20250219";
|
||||
return;
|
||||
}
|
||||
break;
|
||||
|
||||
// Fallback to Claude3 Sonnet
|
||||
req.body.model = `claude-3-sonnet@${LATEST_GCP_SONNET_MINOR_VERSION}`;
|
||||
return;
|
||||
case "4":
|
||||
case "4.0":
|
||||
switch (flavor) {
|
||||
case "opus":
|
||||
req.body.model = "claude-opus-4@20250514";
|
||||
return;
|
||||
case "sonnet":
|
||||
req.body.model = "claude-sonnet-4@20250514";
|
||||
return;
|
||||
default:
|
||||
req.body.model = DEFAULT_MODEL;
|
||||
}
|
||||
break;
|
||||
|
||||
case "4.1":
|
||||
switch (flavor) {
|
||||
case "opus":
|
||||
req.body.model = "claude-opus-4-1@20250805";
|
||||
return;
|
||||
default:
|
||||
req.body.model = DEFAULT_MODEL;
|
||||
}
|
||||
break;
|
||||
|
||||
default:
|
||||
req.body.model = DEFAULT_MODEL;
|
||||
}
|
||||
}
|
||||
|
||||
export const gcp = gcpRouter;
|
||||
|
||||
+161
-41
@@ -1,4 +1,4 @@
|
||||
import { Request, RequestHandler, Router } from "express";
|
||||
import { Request, RequestHandler, Router, Response, NextFunction } from "express";
|
||||
import { v4 } from "uuid";
|
||||
import { GoogleAIKey, keyPool } from "../shared/key-management";
|
||||
import { config } from "../config";
|
||||
@@ -10,10 +10,15 @@ import {
|
||||
import { ProxyResHandlerWithBody } from "./middleware/response";
|
||||
import { addGoogleAIKey } from "./middleware/request/mutators/add-google-ai-key";
|
||||
import { createQueuedProxyMiddleware } from "./middleware/request/proxy-middleware-factory";
|
||||
import axios from "axios";
|
||||
|
||||
let modelsCache: any = null;
|
||||
let modelsCacheTime = 0;
|
||||
|
||||
// Cache for native Google AI models
|
||||
let nativeModelsCache: any = null;
|
||||
let nativeModelsCacheTime = 0;
|
||||
|
||||
// https://ai.google.dev/models/gemini
|
||||
// TODO: list models https://ai.google.dev/tutorials/rest_quickstart#list_models
|
||||
|
||||
@@ -33,11 +38,15 @@ const getModelsResponse = () => {
|
||||
return modelsCache;
|
||||
}
|
||||
|
||||
// Get all model IDs from keys, excluding any with "bard" in the name
|
||||
const modelIds = Array.from(
|
||||
new Set(keys.map((k) => k.modelIds).flat())
|
||||
).filter((id) => id.startsWith("models/gemini"));
|
||||
).filter((id) => id.startsWith("models/") && !id.includes("bard"));
|
||||
|
||||
// Strip "models/" prefix from IDs before creating model objects
|
||||
const models = modelIds.map((id) => ({
|
||||
id,
|
||||
// Strip "models/" prefix from ID for consistency with request processing
|
||||
id: id.startsWith("models/") ? id.slice("models/".length) : id,
|
||||
object: "model",
|
||||
created: new Date().getTime(),
|
||||
owned_by: "google",
|
||||
@@ -52,10 +61,50 @@ const getModelsResponse = () => {
|
||||
return modelsCache;
|
||||
};
|
||||
|
||||
const handleModelRequest: RequestHandler = (_req, res) => {
|
||||
// Function to fetch native models from Google AI API
|
||||
const getNativeModelsResponse = async () => {
|
||||
// Return cached value if it was refreshed in the last minute
|
||||
if (new Date().getTime() - nativeModelsCacheTime < 1000 * 60) {
|
||||
return nativeModelsCache;
|
||||
}
|
||||
|
||||
/*
|
||||
* The official Google API requires an API key. However SillyTavern only needs
|
||||
* a list of model IDs and does not care about any other model metadata. We
|
||||
* can therefore generate a **synthetic** response from the keys already
|
||||
* loaded into the proxy (same source we use for the OpenAI-compatible
|
||||
* endpoint) and completely avoid the outbound request. This removes the
|
||||
* need for the frontend to supply the proxy password as an API key and
|
||||
* prevents 4xx/5xx errors when the real Google API is unreachable or the key
|
||||
* is missing.
|
||||
*/
|
||||
const openaiStyle = getModelsResponse();
|
||||
const models = (openaiStyle.data || []).map((m: any) => ({
|
||||
// Google AI Studio returns names in the format "models/<id>"
|
||||
name: `models/${m.id}`,
|
||||
supportedGenerationMethods: ["generateContent"],
|
||||
}));
|
||||
|
||||
nativeModelsCache = { models };
|
||||
nativeModelsCacheTime = new Date().getTime();
|
||||
return nativeModelsCache;
|
||||
};
|
||||
|
||||
const handleModelRequest: RequestHandler = (_req: Request, res: any) => {
|
||||
res.status(200).json(getModelsResponse());
|
||||
};
|
||||
|
||||
// Native Gemini API model list request
|
||||
const handleNativeModelRequest: RequestHandler = async (_req: Request, res: any) => {
|
||||
try {
|
||||
const modelsResponse = await getNativeModelsResponse();
|
||||
res.status(200).json(modelsResponse);
|
||||
} catch (error) {
|
||||
console.error("Error in handleNativeModelRequest:", error);
|
||||
res.status(500).json({ error: "Failed to fetch models" });
|
||||
}
|
||||
};
|
||||
|
||||
const googleAIBlockingResponseHandler: ProxyResHandlerWithBody = async (
|
||||
_proxyRes,
|
||||
req,
|
||||
@@ -80,8 +129,30 @@ function transformGoogleAIResponse(
|
||||
req: Request
|
||||
): Record<string, any> {
|
||||
const totalTokens = (req.promptTokens ?? 0) + (req.outputTokens ?? 0);
|
||||
const parts = resBody.candidates[0].content?.parts ?? [{ text: "" }];
|
||||
const content = parts[0].text.replace(/^(.{0,50}?): /, () => "");
|
||||
|
||||
// Handle the case where content might have different structures
|
||||
let content = "";
|
||||
|
||||
// Check if the response has the expected structure
|
||||
if (resBody.candidates && resBody.candidates[0]) {
|
||||
const candidate = resBody.candidates[0];
|
||||
|
||||
// Extract content text with multiple fallbacks
|
||||
if (candidate.content?.parts && candidate.content.parts[0]?.text) {
|
||||
// Regular format with parts array containing text
|
||||
content = candidate.content.parts[0].text;
|
||||
} else if (candidate.content?.text) {
|
||||
// Alternate format with direct text property
|
||||
content = candidate.content.text;
|
||||
} else if (typeof candidate.content?.parts?.[0] === 'string') {
|
||||
// Some formats might have string parts
|
||||
content = candidate.content.parts[0];
|
||||
}
|
||||
|
||||
// Apply cleanup to the content if needed
|
||||
content = content.replace(/^(.{0,50}?): /, () => "");
|
||||
}
|
||||
|
||||
return {
|
||||
id: "goo-" + v4(),
|
||||
object: "chat.completion",
|
||||
@@ -95,7 +166,7 @@ function transformGoogleAIResponse(
|
||||
choices: [
|
||||
{
|
||||
message: { role: "assistant", content },
|
||||
finish_reason: resBody.candidates[0].finishReason,
|
||||
finish_reason: resBody.candidates?.[0]?.finishReason || "STOP",
|
||||
index: 0,
|
||||
},
|
||||
],
|
||||
@@ -103,7 +174,7 @@ function transformGoogleAIResponse(
|
||||
}
|
||||
|
||||
const googleAIProxy = createQueuedProxyMiddleware({
|
||||
target: ({ signedRequest }) => {
|
||||
target: ({ signedRequest }: { signedRequest: any }) => {
|
||||
if (!signedRequest) throw new Error("Must sign request before proxying");
|
||||
const { protocol, hostname} = signedRequest;
|
||||
return `${protocol}//${hostname}`;
|
||||
@@ -114,28 +185,16 @@ const googleAIProxy = createQueuedProxyMiddleware({
|
||||
|
||||
const googleAIRouter = Router();
|
||||
googleAIRouter.get("/v1/models", handleModelRequest);
|
||||
googleAIRouter.get("/:apiVersion(v1alpha|v1beta)/models", handleNativeModelRequest);
|
||||
|
||||
// Native Google AI chat completion endpoint
|
||||
googleAIRouter.post(
|
||||
"/v1beta/models/:modelId:(generateContent|streamGenerateContent)",
|
||||
ipLimiter,
|
||||
createPreprocessorMiddleware(
|
||||
{ inApi: "google-ai", outApi: "google-ai", service: "google-ai" },
|
||||
{ beforeTransform: [maybeReassignModel], afterTransform: [setStreamFlag] }
|
||||
),
|
||||
googleAIProxy
|
||||
);
|
||||
|
||||
// OpenAI-to-Google AI compatibility endpoint.
|
||||
googleAIRouter.post(
|
||||
"/v1/chat/completions",
|
||||
ipLimiter,
|
||||
createPreprocessorMiddleware(
|
||||
{ inApi: "openai", outApi: "google-ai", service: "google-ai" },
|
||||
{ afterTransform: [maybeReassignModel] }
|
||||
),
|
||||
googleAIProxy
|
||||
);
|
||||
/**
|
||||
* Processes the thinking budget for Gemini 2.5 Flash model.
|
||||
* Validation has been disabled - budget is passed through without limits.
|
||||
*/
|
||||
function processThinkingBudget(req: Request) {
|
||||
// Validation disabled - budget is passed through without any range limits
|
||||
// Previously enforced 0-24576 token limit
|
||||
}
|
||||
|
||||
function setStreamFlag(req: Request) {
|
||||
const isStreaming = req.url.includes("streamGenerateContent");
|
||||
@@ -149,8 +208,8 @@ function setStreamFlag(req: Request) {
|
||||
}
|
||||
|
||||
/**
|
||||
* Replaces requests for non-Google AI models with gemini-1.5-pro-latest.
|
||||
* Also strips models/ from the beginning of the model IDs.
|
||||
* Strips 'models/' prefix from the beginning of model IDs if present.
|
||||
* No longer forces redirection to gemini-1.5-pro-latest for non-Gemini models.
|
||||
**/
|
||||
function maybeReassignModel(req: Request) {
|
||||
// Ensure model is on body as a lot of middleware will expect it.
|
||||
@@ -160,17 +219,78 @@ function maybeReassignModel(req: Request) {
|
||||
}
|
||||
req.body.model = model;
|
||||
|
||||
const requested = model;
|
||||
if (requested.startsWith("models/")) {
|
||||
req.body.model = requested.slice("models/".length);
|
||||
// Only strip the 'models/' prefix if present
|
||||
if (model.startsWith("models/")) {
|
||||
req.body.model = model.slice("models/".length);
|
||||
req.log.info({ originalModel: model, updatedModel: req.body.model }, "Stripped 'models/' prefix from model ID");
|
||||
}
|
||||
|
||||
if (requested.includes("gemini")) {
|
||||
return;
|
||||
}
|
||||
|
||||
req.log.info({ requested }, "Reassigning model to gemini-1.5-pro-latest");
|
||||
req.body.model = "gemini-1.5-pro-latest";
|
||||
|
||||
// No longer redirecting non-Gemini models to gemini-1.5-pro-latest
|
||||
// This allows the original model to be passed through to the API
|
||||
// If it's an invalid model, the Google AI API will return the appropriate error
|
||||
}
|
||||
|
||||
/**
|
||||
* Middleware to check for and block requests to experimental models.
|
||||
* This function is intended to be used as a RequestPreprocessor.
|
||||
* It throws an error if an experimental model is detected, which should be
|
||||
* caught by the proxy's onError handler.
|
||||
*
|
||||
* Models can be allowed through the ALLOWED_EXP_MODELS environment variable.
|
||||
*/
|
||||
function checkAndBlockExperimentalModels(req: Request) { // Changed signature
|
||||
const modelId = req.body.model as string | undefined;
|
||||
|
||||
// Check if the model ID contains "exp" (case-insensitive)
|
||||
if (modelId && modelId.toLowerCase().includes("exp")) {
|
||||
// Check if this specific model is in the allowlist
|
||||
const allowedModels = config.allowedExpModels
|
||||
?.split(",")
|
||||
.map(model => model.trim())
|
||||
.filter(model => model.length > 0) || [];
|
||||
|
||||
const isAllowed = allowedModels.some(allowedModel =>
|
||||
modelId.toLowerCase() === allowedModel.toLowerCase()
|
||||
);
|
||||
|
||||
if (isAllowed) {
|
||||
req.log.info({ modelId }, "Allowing experimental Google AI model via allowlist.");
|
||||
return; // Allow the request to proceed
|
||||
}
|
||||
|
||||
req.log.warn({ modelId }, "Blocking request to experimental Google AI model.");
|
||||
const err: any = new Error("Experimental models are too unstable to be supported in proxy code. Please use preview models instead.");
|
||||
err.statusCode = 400;
|
||||
throw err;
|
||||
}
|
||||
// If no experimental model, do nothing, allowing request to proceed.
|
||||
}
|
||||
|
||||
// Native Google AI chat completion endpoint
|
||||
googleAIRouter.post(
|
||||
"/:apiVersion(v1alpha|v1beta)/models/:modelId:(generateContent|streamGenerateContent)",
|
||||
ipLimiter,
|
||||
createPreprocessorMiddleware(
|
||||
{ inApi: "google-ai", outApi: "google-ai", service: "google-ai" },
|
||||
{
|
||||
beforeTransform: [maybeReassignModel],
|
||||
afterTransform: [checkAndBlockExperimentalModels, setStreamFlag, processThinkingBudget]
|
||||
}
|
||||
),
|
||||
googleAIProxy
|
||||
);
|
||||
|
||||
// OpenAI-to-Google AI compatibility endpoint.
|
||||
googleAIRouter.post(
|
||||
"/v1/chat/completions",
|
||||
ipLimiter,
|
||||
createPreprocessorMiddleware(
|
||||
{ inApi: "openai", outApi: "google-ai", service: "google-ai" },
|
||||
{
|
||||
afterTransform: [maybeReassignModel, checkAndBlockExperimentalModels, processThinkingBudget]
|
||||
}
|
||||
),
|
||||
googleAIProxy
|
||||
);
|
||||
|
||||
export const googleAI = googleAIRouter;
|
||||
|
||||
@@ -12,11 +12,13 @@ const OPENAI_CHAT_COMPLETION_ENDPOINT = "/v1/chat/completions";
|
||||
const OPENAI_TEXT_COMPLETION_ENDPOINT = "/v1/completions";
|
||||
const OPENAI_EMBEDDINGS_ENDPOINT = "/v1/embeddings";
|
||||
const OPENAI_IMAGE_COMPLETION_ENDPOINT = "/v1/images/generations";
|
||||
const OPENAI_RESPONSES_ENDPOINT = "/v1/responses";
|
||||
const ANTHROPIC_COMPLETION_ENDPOINT = "/v1/complete";
|
||||
const ANTHROPIC_MESSAGES_ENDPOINT = "/v1/messages";
|
||||
const ANTHROPIC_SONNET_COMPAT_ENDPOINT = "/v1/sonnet";
|
||||
const ANTHROPIC_OPUS_COMPAT_ENDPOINT = "/v1/opus";
|
||||
const GOOGLE_AI_COMPLETION_ENDPOINT = "/v1beta/models";
|
||||
const GOOGLE_AI_ALPHA_COMPLETION_ENDPOINT = "/v1alpha/models";
|
||||
const GOOGLE_AI_BETA_COMPLETION_ENDPOINT = "/v1beta/models";
|
||||
|
||||
export function isTextGenerationRequest(req: Request) {
|
||||
return (
|
||||
@@ -24,11 +26,13 @@ export function isTextGenerationRequest(req: Request) {
|
||||
[
|
||||
OPENAI_CHAT_COMPLETION_ENDPOINT,
|
||||
OPENAI_TEXT_COMPLETION_ENDPOINT,
|
||||
OPENAI_RESPONSES_ENDPOINT,
|
||||
ANTHROPIC_COMPLETION_ENDPOINT,
|
||||
ANTHROPIC_MESSAGES_ENDPOINT,
|
||||
ANTHROPIC_SONNET_COMPAT_ENDPOINT,
|
||||
ANTHROPIC_OPUS_COMPAT_ENDPOINT,
|
||||
GOOGLE_AI_COMPLETION_ENDPOINT,
|
||||
GOOGLE_AI_ALPHA_COMPLETION_ENDPOINT,
|
||||
GOOGLE_AI_BETA_COMPLETION_ENDPOINT,
|
||||
].some((endpoint) => req.path.startsWith(endpoint))
|
||||
);
|
||||
}
|
||||
@@ -234,6 +238,22 @@ export function getCompletionFromBody(req: Request, body: Record<string, any>) {
|
||||
// - choices[0].message.content
|
||||
// - choices[0].message with no content if model is invoking a tool
|
||||
return body.choices?.[0]?.message?.content || "";
|
||||
case "openai-responses":
|
||||
// Handle the original Responses API format
|
||||
if (body.output && Array.isArray(body.output)) {
|
||||
// Look for a message type in the output array
|
||||
for (const item of body.output) {
|
||||
if (item.type === "message" && item.content && Array.isArray(item.content)) {
|
||||
// Extract text content from each content item
|
||||
return item.content
|
||||
.filter((contentItem: any) => contentItem.type === "output_text")
|
||||
.map((contentItem: any) => contentItem.text)
|
||||
.join("");
|
||||
}
|
||||
}
|
||||
}
|
||||
// If we've been transformed to chat completion format already
|
||||
return body.choices?.[0]?.message?.content || "";
|
||||
case "mistral-text":
|
||||
return body.outputs?.[0]?.text || "";
|
||||
case "openai-text":
|
||||
@@ -285,6 +305,7 @@ export function getModelFromBody(req: Request, resBody: Record<string, any>) {
|
||||
switch (format) {
|
||||
case "openai":
|
||||
case "openai-text":
|
||||
case "openai-responses":
|
||||
return resBody.model;
|
||||
case "mistral-ai":
|
||||
case "mistral-text":
|
||||
|
||||
@@ -25,6 +25,9 @@ export const addGoogleAIKey: ProxyReqMutator = (manager) => {
|
||||
// https://generativelanguage.googleapis.com/v1beta/models/$MODEL_ID:streamGenerateContent?key=${API_KEY}
|
||||
const payload = { ...req.body, stream: undefined, model: undefined };
|
||||
|
||||
// For OpenAI -> Google conversion we don't actually have the API version
|
||||
const apiVersion = req.params.apiVersion || "v1beta"
|
||||
|
||||
// TODO: this isn't actually signed, so the manager api is a little unclear
|
||||
// with the ProxyReqManager refactor, it's probably no longer necesasry to
|
||||
// do this because we can modify the path using Manager.setPath.
|
||||
@@ -32,7 +35,7 @@ export const addGoogleAIKey: ProxyReqMutator = (manager) => {
|
||||
method: "POST",
|
||||
protocol: "https:",
|
||||
hostname: "generativelanguage.googleapis.com",
|
||||
path: `/v1beta/models/${model}:${
|
||||
path: `/${apiVersion}/models/${model}:${
|
||||
req.isStreaming ? "streamGenerateContent?alt=sse&" : "generateContent?"
|
||||
}key=${key.key}`,
|
||||
headers: {
|
||||
|
||||
@@ -31,7 +31,9 @@ export const addKey: ProxyReqMutator = (manager) => {
|
||||
}
|
||||
|
||||
if (inboundApi === outboundApi) {
|
||||
assignedKey = keyPool.get(body.model, service, needsMultimodal);
|
||||
// Pass streaming information for GPT-5 models that require verified keys for streaming
|
||||
const isStreaming = body.stream === true;
|
||||
assignedKey = keyPool.get(body.model, service, needsMultimodal, isStreaming);
|
||||
} else {
|
||||
switch (outboundApi) {
|
||||
// If we are translating between API formats we may need to select a model
|
||||
@@ -49,7 +51,12 @@ export const addKey: ProxyReqMutator = (manager) => {
|
||||
assignedKey = keyPool.get("gpt-3.5-turbo-instruct", service);
|
||||
break;
|
||||
case "openai-image":
|
||||
assignedKey = keyPool.get("dall-e-3", service);
|
||||
// Use the actual model from the request body instead of defaulting to dall-e-3
|
||||
// This ensures that gpt-image-1 requests get keys that are verified for gpt-image-1
|
||||
assignedKey = keyPool.get(body.model, service);
|
||||
break;
|
||||
case "openai-responses":
|
||||
assignedKey = keyPool.get(body.model, service);
|
||||
break;
|
||||
case "openai":
|
||||
throw new Error(
|
||||
@@ -88,6 +95,21 @@ export const addKey: ProxyReqMutator = (manager) => {
|
||||
const azureKey = assignedKey.key;
|
||||
manager.setHeader("api-key", azureKey);
|
||||
break;
|
||||
case "deepseek":
|
||||
manager.setHeader("Authorization", `Bearer ${assignedKey.key}`);
|
||||
break;
|
||||
case "xai":
|
||||
manager.setHeader("Authorization", `Bearer ${assignedKey.key}`);
|
||||
break;
|
||||
case "cohere":
|
||||
manager.setHeader("Authorization", `Bearer ${assignedKey.key}`);
|
||||
break;
|
||||
case "qwen":
|
||||
manager.setHeader("Authorization", `Bearer ${assignedKey.key}`);
|
||||
break;
|
||||
case "moonshot":
|
||||
manager.setHeader("Authorization", `Bearer ${assignedKey.key}`);
|
||||
break;
|
||||
case "aws":
|
||||
case "gcp":
|
||||
case "google-ai":
|
||||
|
||||
@@ -13,6 +13,51 @@ export const finalizeBody: ProxyReqMutator = (manager) => {
|
||||
if (req.outboundApi === "anthropic-chat") {
|
||||
delete req.body.prompt;
|
||||
}
|
||||
// For OpenAI Responses API, ensure messages is in the correct format
|
||||
if (req.outboundApi === "openai-responses") {
|
||||
// Format messages for the Responses API
|
||||
if (req.body.messages) {
|
||||
req.log.info("Formatting messages for Responses API in finalizeBody");
|
||||
// The Responses API expects input to be an array, not an object
|
||||
req.body.input = req.body.messages;
|
||||
delete req.body.messages;
|
||||
} else if (req.body.input && req.body.input.messages) {
|
||||
req.log.info("Reformatting input.messages for Responses API in finalizeBody");
|
||||
// If input already exists but contains a messages object, replace input with the messages array
|
||||
req.body.input = req.body.input.messages;
|
||||
}
|
||||
|
||||
// Final check to ensure max_completion_tokens is converted to max_output_tokens
|
||||
if (req.body.max_completion_tokens) {
|
||||
req.log.info("Converting max_completion_tokens to max_output_tokens in finalizeBody");
|
||||
if (!req.body.max_output_tokens) {
|
||||
req.body.max_output_tokens = req.body.max_completion_tokens;
|
||||
}
|
||||
delete req.body.max_completion_tokens;
|
||||
}
|
||||
|
||||
// Final check to ensure max_tokens is converted to max_output_tokens
|
||||
if (req.body.max_tokens) {
|
||||
req.log.info("Converting max_tokens to max_output_tokens in finalizeBody");
|
||||
if (!req.body.max_output_tokens) {
|
||||
req.body.max_output_tokens = req.body.max_tokens;
|
||||
}
|
||||
delete req.body.max_tokens;
|
||||
}
|
||||
|
||||
// Remove all parameters not supported by Responses API
|
||||
const unsupportedParams = [
|
||||
'frequency_penalty',
|
||||
'presence_penalty',
|
||||
];
|
||||
|
||||
for (const param of unsupportedParams) {
|
||||
if (req.body[param] !== undefined) {
|
||||
req.log.info(`Removing unsupported parameter for Responses API: ${param}`);
|
||||
delete req.body[param];
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
const serialized =
|
||||
typeof req.body === "string" ? req.body : JSON.stringify(req.body);
|
||||
|
||||
@@ -27,6 +27,14 @@ export const signAwsRequest: ProxyReqMutator = async (manager) => {
|
||||
const key = keyPool.get(model, "aws") as AwsBedrockKey;
|
||||
manager.setKey(key);
|
||||
|
||||
let system = req.body.system ?? "";
|
||||
if (Array.isArray(system)) {
|
||||
system = system
|
||||
.map((m: { type: string; text: string }) => m.text)
|
||||
.join("\n");
|
||||
req.body.system = system;
|
||||
}
|
||||
|
||||
const credential = getCredentialParts(req);
|
||||
const host = AMZ_HOST.replace("%REGION%", credential.region);
|
||||
|
||||
@@ -130,6 +138,9 @@ function getStrictlyValidatedBodyForAws(req: Readonly<Request>): unknown {
|
||||
temperature: true,
|
||||
top_k: true,
|
||||
top_p: true,
|
||||
tools: true,
|
||||
tool_choice: true,
|
||||
thinking: true
|
||||
})
|
||||
.strip()
|
||||
.parse(req.body);
|
||||
|
||||
@@ -48,6 +48,9 @@ export const signGcpRequest: ProxyReqMutator = async (manager) => {
|
||||
top_k: true,
|
||||
top_p: true,
|
||||
stream: true,
|
||||
tools: true,
|
||||
tool_choice: true,
|
||||
thinking: true
|
||||
})
|
||||
.strip()
|
||||
.parse(req.body);
|
||||
|
||||
@@ -34,4 +34,4 @@ export const applyQuotaLimits: RequestPreprocessor = (req) => {
|
||||
}
|
||||
);
|
||||
}
|
||||
};
|
||||
};
|
||||
@@ -1,6 +1,6 @@
|
||||
import { RequestPreprocessor } from "../index";
|
||||
|
||||
const DISALLOWED_ORIGIN_SUBSTRINGS = "janitorai.com,janitor.ai".split(",");
|
||||
const DISALLOWED_ORIGIN_SUBSTRINGS = "janitorai.com,janitor.ai,vip.jewproxy.tech,jewproxy.tech".split(",");
|
||||
|
||||
class ZoomerForbiddenError extends Error {
|
||||
constructor(message: string) {
|
||||
@@ -14,7 +14,7 @@ class ZoomerForbiddenError extends Error {
|
||||
* stop getting emails asking for tech support.
|
||||
*/
|
||||
export const blockZoomerOrigins: RequestPreprocessor = (req) => {
|
||||
const origin = req.headers.origin || req.headers.referer;
|
||||
const origin = req.headers.origin || req.headers.referer || req.headers.host;
|
||||
if (origin && DISALLOWED_ORIGIN_SUBSTRINGS.some((s) => origin.includes(s))) {
|
||||
// Venus-derivatives send a test prompt to check if the proxy is working.
|
||||
// We don't want to block that just yet.
|
||||
|
||||
@@ -1,11 +1,18 @@
|
||||
import { RequestPreprocessor } from "../index";
|
||||
import { countTokens } from "../../../../shared/tokenization";
|
||||
import { assertNever } from "../../../../shared/utils";
|
||||
import { OpenAIChatMessage } from "../../../../shared/api-schemas";
|
||||
import { GoogleAIChatMessage } from "../../../../shared/api-schemas/google-ai";
|
||||
import {
|
||||
GoogleAIChatMessage,
|
||||
MistralAIChatMessage,
|
||||
OpenAIChatMessage,
|
||||
} from "../../../../shared/api-schemas";
|
||||
AnthropicChatMessage,
|
||||
flattenAnthropicMessages,
|
||||
} from "../../../../shared/api-schemas/anthropic";
|
||||
import {
|
||||
MistralAIChatMessage,
|
||||
ContentItem,
|
||||
isMistralVisionModel
|
||||
} from "../../../../shared/api-schemas/mistral-ai";
|
||||
import { isGrokVisionModel } from "../../../../shared/api-schemas/xai";
|
||||
|
||||
/**
|
||||
* Given a request with an already-transformed body, counts the number of
|
||||
@@ -22,6 +29,12 @@ export const countPromptTokens: RequestPreprocessor = async (req) => {
|
||||
result = await countTokens({ req, prompt, service });
|
||||
break;
|
||||
}
|
||||
case "openai-responses": {
|
||||
req.outputTokens = req.body.max_completion_tokens || req.body.max_tokens;
|
||||
const prompt: OpenAIChatMessage[] = req.body.messages;
|
||||
result = await countTokens({ req, prompt, service });
|
||||
break;
|
||||
}
|
||||
case "openai-text": {
|
||||
req.outputTokens = req.body.max_tokens;
|
||||
const prompt: string = req.body.prompt;
|
||||
@@ -55,9 +68,47 @@ export const countPromptTokens: RequestPreprocessor = async (req) => {
|
||||
case "mistral-ai":
|
||||
case "mistral-text": {
|
||||
req.outputTokens = req.body.max_tokens;
|
||||
const prompt: string | MistralAIChatMessage[] =
|
||||
req.body.messages ?? req.body.prompt;
|
||||
|
||||
// Handle multimodal content (vision) in Mistral models
|
||||
const isVisionModel = isMistralVisionModel(req.body.model);
|
||||
const messages = req.body.messages;
|
||||
|
||||
// Check if this is a vision request with images
|
||||
const hasImageContent = Array.isArray(messages) && messages.some(
|
||||
(msg: MistralAIChatMessage) => Array.isArray(msg.content) &&
|
||||
msg.content.some((item: ContentItem) => item.type === "image_url")
|
||||
);
|
||||
|
||||
// For vision content, we add a fixed token count per image
|
||||
// This is an estimate as the actual token count depends on image size and complexity
|
||||
const TOKENS_PER_IMAGE = 1200; // Conservative estimate
|
||||
let imageTokens = 0;
|
||||
|
||||
if (hasImageContent && Array.isArray(messages)) {
|
||||
// Count images in the request
|
||||
for (const msg of messages) {
|
||||
if (Array.isArray(msg.content)) {
|
||||
const imageCount = msg.content.filter(
|
||||
(item: ContentItem) => item.type === "image_url"
|
||||
).length;
|
||||
imageTokens += imageCount * TOKENS_PER_IMAGE;
|
||||
}
|
||||
}
|
||||
|
||||
req.log.debug(
|
||||
{ imageCount: imageTokens / TOKENS_PER_IMAGE, tokenEstimate: imageTokens },
|
||||
"Estimated token count for Mistral vision images"
|
||||
);
|
||||
}
|
||||
|
||||
const prompt: string | MistralAIChatMessage[] = messages ?? req.body.prompt;
|
||||
result = await countTokens({ req, prompt, service });
|
||||
|
||||
// Add the image tokens to the total count
|
||||
if (imageTokens > 0) {
|
||||
result.token_count += imageTokens;
|
||||
}
|
||||
|
||||
break;
|
||||
}
|
||||
case "openai-image": {
|
||||
@@ -65,6 +116,10 @@ export const countPromptTokens: RequestPreprocessor = async (req) => {
|
||||
result = await countTokens({ req, service });
|
||||
break;
|
||||
}
|
||||
|
||||
// Handle XAI (Grok) vision models
|
||||
// Since it uses the OpenAI API format, it's caught in the "openai" case,
|
||||
// but we need to add additional handling for image tokens after that
|
||||
default:
|
||||
assertNever(service);
|
||||
}
|
||||
|
||||
@@ -78,14 +78,15 @@ function getPromptFromRequest(req: Request) {
|
||||
.join("\n\n");
|
||||
case "anthropic-text":
|
||||
case "openai-text":
|
||||
case "openai-responses":
|
||||
case "openai-image":
|
||||
case "mistral-text":
|
||||
return body.prompt;
|
||||
case "google-ai": {
|
||||
const b = body as z.infer<typeof GoogleAIV1GenerateContentSchema>;
|
||||
return [
|
||||
b.systemInstruction?.parts.map((p) => p.text),
|
||||
...b.contents.flatMap((c) => c.parts.map((p) => p.text)),
|
||||
b.systemInstruction?.parts.filter(p => 'text' in p).map((p) => (p as { text: string }).text),
|
||||
...b.contents.flatMap((c) => c.parts.filter(p => 'text' in p).map((p) => (p as { text: string }).text)),
|
||||
].join("\n");
|
||||
}
|
||||
default:
|
||||
|
||||
@@ -4,7 +4,7 @@ import {
|
||||
API_REQUEST_TRANSFORMERS,
|
||||
} from "../../../../shared/api-schemas";
|
||||
import { BadRequestError } from "../../../../shared/errors";
|
||||
import { fixMistralPrompt } from "../../../../shared/api-schemas/mistral-ai";
|
||||
import { fixMistralPrompt, isMistralVisionModel } from "../../../../shared/api-schemas/mistral-ai";
|
||||
import {
|
||||
isImageGenerationRequest,
|
||||
isTextGenerationRequest,
|
||||
@@ -30,6 +30,8 @@ export const transformOutboundPayload: RequestPreprocessor = async (req) => {
|
||||
}
|
||||
|
||||
applyMistralPromptFixes(req);
|
||||
applyGoogleAIKeyTransforms(req);
|
||||
applyOpenAIResponsesTransform(req);
|
||||
|
||||
// Native prompts are those which were already provided by the client in the
|
||||
// target API format. We don't need to transform them.
|
||||
@@ -55,6 +57,58 @@ export const transformOutboundPayload: RequestPreprocessor = async (req) => {
|
||||
);
|
||||
};
|
||||
|
||||
// Handle OpenAI Responses API transformation
|
||||
function applyOpenAIResponsesTransform(req: Request): void {
|
||||
if (req.outboundApi === "openai-responses") {
|
||||
req.log.info("Transforming request to OpenAI Responses API format");
|
||||
|
||||
// Store the original body for reference if needed
|
||||
const originalBody = { ...req.body };
|
||||
|
||||
// Map standard OpenAI chat completions format to Responses API format
|
||||
// The main differences are:
|
||||
// 1. Endpoint is /v1/responses instead of /v1/chat/completions
|
||||
// 2. 'messages' field moves to 'input.messages'
|
||||
|
||||
// Move messages to input.messages
|
||||
if (req.body.messages && !req.body.input) {
|
||||
req.body.input = {
|
||||
messages: req.body.messages
|
||||
};
|
||||
delete req.body.messages;
|
||||
}
|
||||
|
||||
// Keep all the original properties of the request but ensure compatibility
|
||||
// with Responses API specifics
|
||||
if (!req.body.previousResponseId && req.body.conversation_id) {
|
||||
req.body.previousResponseId = req.body.conversation_id;
|
||||
delete req.body.conversation_id;
|
||||
}
|
||||
|
||||
// Convert max_tokens to max_output_tokens if present and not already set
|
||||
if (req.body.max_tokens && !req.body.max_output_tokens) {
|
||||
req.body.max_output_tokens = req.body.max_tokens;
|
||||
delete req.body.max_tokens;
|
||||
}
|
||||
|
||||
// Set the correct tools format if needed
|
||||
if (req.body.tools) {
|
||||
// Tools structure is maintained but might need conversion if non-standard
|
||||
if (!req.body.tools.some((tool: any) => tool.type === "function" || tool.type === "web_search")) {
|
||||
req.body.tools = req.body.tools.map((tool: any) => ({
|
||||
...tool,
|
||||
type: tool.type || "function"
|
||||
}));
|
||||
}
|
||||
}
|
||||
|
||||
req.log.info({
|
||||
originalModel: originalBody.model,
|
||||
newFormat: "openai-responses"
|
||||
}, "Successfully transformed request to Responses API format");
|
||||
}
|
||||
}
|
||||
|
||||
// handles weird cases that don't fit into our abstractions
|
||||
function applyMistralPromptFixes(req: Request): void {
|
||||
if (req.inboundApi === "mistral-ai") {
|
||||
@@ -63,12 +117,66 @@ function applyMistralPromptFixes(req: Request): void {
|
||||
// mistral prompt and try to fix it if it fails. It will be re-validated
|
||||
// after this function returns.
|
||||
const result = API_REQUEST_VALIDATORS["mistral-ai"].parse(req.body);
|
||||
|
||||
// Check if this is a vision model request
|
||||
const isVisionModel = isMistralVisionModel(req.body.model);
|
||||
|
||||
// Check if the request contains image content
|
||||
const hasImageContent = result.messages?.some((msg: {content: string | any[]}) =>
|
||||
Array.isArray(msg.content) &&
|
||||
msg.content.some((item: any) => item.type === "image_url")
|
||||
);
|
||||
|
||||
// For vision requests, normalize the image_url format
|
||||
if (hasImageContent && Array.isArray(result.messages)) {
|
||||
// Process each message with image content
|
||||
result.messages.forEach((msg: any) => {
|
||||
if (Array.isArray(msg.content)) {
|
||||
// Process each content item
|
||||
msg.content.forEach((item: any) => {
|
||||
if (item.type === "image_url") {
|
||||
// Normalize the image_url field to a string format that Mistral expects
|
||||
if (typeof item.image_url === "object") {
|
||||
// If it's an object, extract the URL or base64 data
|
||||
if (item.image_url.url) {
|
||||
item.image_url = item.image_url.url;
|
||||
} else if (item.image_url.data) {
|
||||
item.image_url = item.image_url.data;
|
||||
}
|
||||
|
||||
req.log.info(
|
||||
{ model: req.body.model },
|
||||
"Normalized object-format image_url to string format"
|
||||
);
|
||||
}
|
||||
}
|
||||
});
|
||||
}
|
||||
});
|
||||
}
|
||||
|
||||
// Apply Mistral prompt fixes while preserving multimodal content
|
||||
req.body.messages = fixMistralPrompt(result.messages);
|
||||
req.log.info(
|
||||
{ n: req.body.messages.length, prev: result.messages.length },
|
||||
{
|
||||
n: req.body.messages.length,
|
||||
prev: result.messages.length,
|
||||
isVisionModel,
|
||||
hasImageContent
|
||||
},
|
||||
"Applied Mistral chat prompt fixes."
|
||||
);
|
||||
|
||||
// If this is a vision model with image content, it MUST use the chat API
|
||||
// and cannot be converted to text completions
|
||||
if (hasImageContent) {
|
||||
req.log.info(
|
||||
{ model: req.body.model },
|
||||
"Detected Mistral vision request with image content. Keeping as chat format."
|
||||
);
|
||||
return;
|
||||
}
|
||||
|
||||
// If the prompt relies on `prefix: true` for the last message, we need to
|
||||
// convert it to a text completions request because AWS Mistral support for
|
||||
// this feature is broken.
|
||||
@@ -87,3 +195,43 @@ function applyMistralPromptFixes(req: Request): void {
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
function toCamelCase(str: string): string {
|
||||
return str.replace(/_([a-z])/g, (_, letter) => letter.toUpperCase());
|
||||
}
|
||||
|
||||
function transformKeysToCamelCase(obj: any, hasTransformed = { value: false }): any {
|
||||
if (Array.isArray(obj)) {
|
||||
return obj.map(item => transformKeysToCamelCase(item, hasTransformed));
|
||||
}
|
||||
|
||||
if (obj !== null && typeof obj === 'object') {
|
||||
return Object.fromEntries(
|
||||
Object.entries(obj).map(([key, value]) => {
|
||||
const camelKey = toCamelCase(key);
|
||||
if (camelKey !== key) {
|
||||
hasTransformed.value = true;
|
||||
}
|
||||
return [
|
||||
camelKey,
|
||||
transformKeysToCamelCase(value, hasTransformed)
|
||||
];
|
||||
})
|
||||
);
|
||||
}
|
||||
|
||||
return obj;
|
||||
}
|
||||
|
||||
function applyGoogleAIKeyTransforms(req: Request): void {
|
||||
// Google (Gemini) API in their infinite wisdom accepts both snake_case and camelCase
|
||||
// for some params even though in the docs they use snake_case.
|
||||
// Some frontends (e.g. ST) use snake_case and camelCase so we normalize all keys to camelCase
|
||||
if (req.outboundApi === "google-ai") {
|
||||
const hasTransformed = { value: false };
|
||||
req.body = transformKeysToCamelCase(req.body, hasTransformed);
|
||||
if (hasTransformed.value) {
|
||||
req.log.info("Applied Gemini camelCase -> snake_case transform");
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@@ -28,6 +28,7 @@ export const validateContextSize: RequestPreprocessor = async (req) => {
|
||||
switch (req.outboundApi) {
|
||||
case "openai":
|
||||
case "openai-text":
|
||||
case "openai-responses":
|
||||
proxyMax = OPENAI_MAX_CONTEXT;
|
||||
break;
|
||||
case "anthropic-chat":
|
||||
@@ -58,6 +59,22 @@ export const validateContextSize: RequestPreprocessor = async (req) => {
|
||||
modelMax = 16384;
|
||||
} else if (model.match(/^gpt-4o/)) {
|
||||
modelMax = 128000;
|
||||
} else if (model.match(/^gpt-4.5/)) {
|
||||
modelMax = 128000;
|
||||
} else if (model.match(/^gpt-4\.1(-\d{4}-\d{2}-\d{2})?$/)) {
|
||||
modelMax = 1000000;
|
||||
} else if (model.match(/^gpt-4\.1-mini(-\d{4}-\d{2}-\d{2})?$/)) {
|
||||
modelMax = 1000000;
|
||||
} else if (model.match(/^gpt-4\.1-nano(-\d{4}-\d{2}-\d{2})?$/)) {
|
||||
modelMax = 1000000;
|
||||
} else if (model.match(/^gpt-5(-\d{4}-\d{2}-\d{2})?$/)) {
|
||||
modelMax = 400000;
|
||||
} else if (model.match(/^gpt-5-mini(-\d{4}-\d{2}-\d{2})?$/)) {
|
||||
modelMax = 400000;
|
||||
} else if (model.match(/^gpt-5-nano(-\d{4}-\d{2}-\d{2})?$/)) {
|
||||
modelMax = 400000;
|
||||
} else if (model.match(/^gpt-5-chat-latest$/)) {
|
||||
modelMax = 400000;
|
||||
} else if (model.match(/^chatgpt-4o/)) {
|
||||
modelMax = 128000;
|
||||
} else if (model.match(/gpt-4-turbo(-\d{4}-\d{2}-\d{2})?$/)) {
|
||||
@@ -68,9 +85,23 @@ export const validateContextSize: RequestPreprocessor = async (req) => {
|
||||
modelMax = 131072;
|
||||
} else if (model.match(/^gpt-4(-\d{4})?-vision(-preview)?$/)) {
|
||||
modelMax = 131072;
|
||||
} else if (model.match(/^o3-mini(-\d{4}-\d{2}-\d{2})?$/)) {
|
||||
modelMax = 200000;
|
||||
} else if (model.match(/^o3(-\d{4}-\d{2}-\d{2})?$/)) {
|
||||
modelMax = 200000;
|
||||
} else if (model.match(/^o4-mini(-\d{4}-\d{2}-\d{2})?$/)) {
|
||||
modelMax = 200000;
|
||||
} else if (model.match(/^codex-mini(-latest|-\d{4}-\d{2}-\d{2})?$/)) {
|
||||
modelMax = 200000; // 200k context window for codex-mini-latest
|
||||
} else if (model.match(/^o1(-\d{4}-\d{2}-\d{2})?$/)) {
|
||||
modelMax = 200000;
|
||||
} else if (model.match(/^o1-mini(-\d{4}-\d{2}-\d{2})?$/)) {
|
||||
modelMax = 128000;
|
||||
} else if (model.match(/^o1(-preview)?(-\d{4}-\d{2}-\d{2})?$/)) {
|
||||
} else if (model.match(/^o1-pro(-\d{4}-\d{2}-\d{2})?$/)) {
|
||||
modelMax = 200000;
|
||||
} else if (model.match(/^o3-pro(-\d{4}-\d{2}-\d{2})?$/)) {
|
||||
modelMax = 200000;
|
||||
} else if (model.match(/^o1-preview(-\d{4}-\d{2}-\d{2})?$/)) {
|
||||
modelMax = 128000;
|
||||
} else if (model.match(/gpt-3.5-turbo/)) {
|
||||
modelMax = 16384;
|
||||
@@ -88,14 +119,38 @@ export const validateContextSize: RequestPreprocessor = async (req) => {
|
||||
modelMax = 200000;
|
||||
} else if (model.match(/^claude-3/)) {
|
||||
modelMax = 200000;
|
||||
} else if (model.match(/^claude-(?:sonnet|opus)-4/)) {
|
||||
modelMax = 200000;
|
||||
} else if (model.match(/^gemini-/)) {
|
||||
modelMax = 1024000;
|
||||
} else if (model.match(/^anthropic\.claude-3/)) {
|
||||
modelMax = 200000;
|
||||
} else if (model.match(/^anthropic\.claude-(?:sonnet|opus)-4/)) {
|
||||
modelMax = 200000;
|
||||
} else if (model.match(/^anthropic\.claude-v2:\d/)) {
|
||||
modelMax = 200000;
|
||||
} else if (model.match(/^anthropic\.claude/)) {
|
||||
modelMax = 100000;
|
||||
} else if (model.match(/^deepseek/)) {
|
||||
modelMax = 64000;
|
||||
} else if (model.match(/^kimi-k2/)) {
|
||||
// Kimi K2 models have 131k context window
|
||||
modelMax = 131000;
|
||||
} else if (model.match(/moonshot/)) {
|
||||
// Moonshot models typically have 200k context window
|
||||
modelMax = 200000;
|
||||
} else if (model.match(/command[\w-]*-03-202[0-9]/)) {
|
||||
// Cohere's command-a-03 models have 256k context window
|
||||
modelMax = 256000;
|
||||
} else if (model.match(/command/) || model.match(/cohere/)) {
|
||||
// Default for all other Cohere models
|
||||
modelMax = 128000;
|
||||
} else if (model.match(/^grok-4/)) {
|
||||
modelMax = 256000;
|
||||
} else if (model.match(/^grok/)) {
|
||||
modelMax = 128000;
|
||||
} else if (model.match(/^magistral/)) {
|
||||
modelMax = 40000;
|
||||
} else if (model.match(/tral/)) {
|
||||
// catches mistral, mixtral, codestral, mathstral, etc. mistral models have
|
||||
// no name convention and wildly different context windows so this is a
|
||||
@@ -136,4 +191,4 @@ function assertRequestHasTokenCounts(
|
||||
})
|
||||
.nonstrict()
|
||||
.parse({ promptTokens: req.promptTokens, outputTokens: req.outputTokens });
|
||||
}
|
||||
}
|
||||
@@ -3,6 +3,7 @@ import { assertNever } from "../../../../shared/utils";
|
||||
import { RequestPreprocessor } from "../index";
|
||||
import { containsImageContent as containsImageContentOpenAI } from "../../../../shared/api-schemas/openai";
|
||||
import { containsImageContent as containsImageContentAnthropic } from "../../../../shared/api-schemas/anthropic";
|
||||
import { containsImageContent as containsImageContentGoogleAI } from "../../../../shared/api-schemas/google-ai";
|
||||
import { ForbiddenError } from "../../../../shared/errors";
|
||||
|
||||
/**
|
||||
@@ -22,11 +23,16 @@ export const validateVision: RequestPreprocessor = async (req) => {
|
||||
case "openai":
|
||||
hasImage = containsImageContentOpenAI(req.body.messages);
|
||||
break;
|
||||
case "openai-responses":
|
||||
hasImage = containsImageContentOpenAI(req.body.messages);
|
||||
break;
|
||||
case "anthropic-chat":
|
||||
hasImage = containsImageContentAnthropic(req.body.messages);
|
||||
break;
|
||||
case "anthropic-text":
|
||||
case "google-ai":
|
||||
hasImage = containsImageContentGoogleAI(req.body.contents);
|
||||
break;
|
||||
case "anthropic-text":
|
||||
case "mistral-ai":
|
||||
case "mistral-text":
|
||||
case "openai-image":
|
||||
|
||||
@@ -194,6 +194,21 @@ export function buildSpoofedCompletion({
|
||||
|
||||
switch (format) {
|
||||
case "openai":
|
||||
case "openai-responses":
|
||||
return {
|
||||
id: "error-" + id,
|
||||
object: "chat.completion",
|
||||
created: Date.now(),
|
||||
model,
|
||||
usage: { prompt_tokens: 0, completion_tokens: 0, total_tokens: 0 },
|
||||
choices: [
|
||||
{
|
||||
message: { role: "assistant", content },
|
||||
finish_reason: title,
|
||||
index: 0,
|
||||
},
|
||||
],
|
||||
};
|
||||
case "mistral-ai":
|
||||
return {
|
||||
id: "error-" + id,
|
||||
@@ -283,6 +298,15 @@ export function buildSpoofedSSE({
|
||||
|
||||
switch (format) {
|
||||
case "openai":
|
||||
case "openai-responses":
|
||||
event = {
|
||||
id: "chatcmpl-" + id,
|
||||
object: "chat.completion.chunk",
|
||||
created: Date.now(),
|
||||
model,
|
||||
choices: [{ delta: { content }, index: 0, finish_reason: title }],
|
||||
};
|
||||
break;
|
||||
case "mistral-ai":
|
||||
event = {
|
||||
id: "chatcmpl-" + id,
|
||||
|
||||
@@ -4,8 +4,9 @@ import { Request, Response } from "express";
|
||||
import * as http from "http";
|
||||
import { config } from "../../../config";
|
||||
import { HttpError, RetryableError } from "../../../shared/errors";
|
||||
import { keyPool } from "../../../shared/key-management";
|
||||
import { getOpenAIModelFamily } from "../../../shared/models";
|
||||
import { keyPool, GoogleAIKey } from "../../../shared/key-management";
|
||||
import { logger } from "../../../logger";
|
||||
import { getOpenAIModelFamily, GoogleAIModelFamily } from "../../../shared/models";
|
||||
import { countTokens } from "../../../shared/tokenization";
|
||||
import {
|
||||
incrementPromptCount,
|
||||
@@ -246,6 +247,12 @@ const handleUpstreamErrors: ProxyResHandlerWithBody = async (
|
||||
errorPayload.proxy_note = `The upstream API rejected the request. Check the error message for details.`;
|
||||
}
|
||||
break;
|
||||
case "deepseek":
|
||||
await handleDeepseekBadRequestError(req, errorPayload);
|
||||
break;
|
||||
case "xai":
|
||||
await handleXaiBadRequestError(req, errorPayload);
|
||||
break;
|
||||
case "anthropic":
|
||||
case "aws":
|
||||
case "gcp":
|
||||
@@ -254,13 +261,37 @@ const handleUpstreamErrors: ProxyResHandlerWithBody = async (
|
||||
case "google-ai":
|
||||
await handleGoogleAIBadRequestError(req, errorPayload);
|
||||
break;
|
||||
case "cohere":
|
||||
errorPayload.proxy_note = `The upstream Cohere API rejected the request. Check the error message for details.`;
|
||||
break;
|
||||
case "qwen":
|
||||
// No special handling yet
|
||||
break;
|
||||
case "moonshot":
|
||||
errorPayload.proxy_note = `The Moonshot API rejected the request. Check the error message for details.`;
|
||||
break;
|
||||
default:
|
||||
assertNever(service);
|
||||
}
|
||||
} else if (statusCode === 401) {
|
||||
// Key is invalid or was revoked
|
||||
// Universal 401 handling - authentication failed, retry with different key
|
||||
keyPool.disable(req.key!, "revoked");
|
||||
errorPayload.proxy_note = `Assigned API key is invalid or revoked, please try again.`;
|
||||
await reenqueueRequest(req);
|
||||
throw new RetryableError(`${service} key authentication failed, retrying with different key.`);
|
||||
} else if (statusCode === 402) {
|
||||
// Deepseek specific - insufficient balance
|
||||
if (service === "deepseek") {
|
||||
keyPool.disable(req.key!, "quota");
|
||||
await reenqueueRequest(req);
|
||||
throw new RetryableError("Deepseek key has insufficient balance, retrying with different key.");
|
||||
}
|
||||
} else if (statusCode === 405) {
|
||||
// Xai specific - insufficient balance
|
||||
if (service === "xai") {
|
||||
keyPool.disable(req.key!, "quota");
|
||||
await reenqueueRequest(req);
|
||||
throw new RetryableError("XAI key has insufficient balance, retrying with different key.");
|
||||
}
|
||||
} else if (statusCode === 403) {
|
||||
switch (service) {
|
||||
case "anthropic":
|
||||
@@ -283,7 +314,8 @@ const handleUpstreamErrors: ProxyResHandlerWithBody = async (
|
||||
case "UnrecognizedClientException":
|
||||
// Key is invalid.
|
||||
keyPool.disable(req.key!, "revoked");
|
||||
errorPayload.proxy_note = `Assigned API key is invalid or revoked, please try again.`;
|
||||
await reenqueueRequest(req);
|
||||
throw new RetryableError("AWS key is invalid, retrying with different key.");
|
||||
break;
|
||||
case "AccessDeniedException":
|
||||
const isModelAccessError =
|
||||
@@ -304,8 +336,12 @@ const handleUpstreamErrors: ProxyResHandlerWithBody = async (
|
||||
case "mistral-ai":
|
||||
case "gcp":
|
||||
keyPool.disable(req.key!, "revoked");
|
||||
errorPayload.proxy_note = `Assigned API key is invalid or revoked, please try again.`;
|
||||
return;
|
||||
await reenqueueRequest(req);
|
||||
throw new RetryableError("GCP key is invalid, retrying with different key.");
|
||||
case "moonshot":
|
||||
keyPool.disable(req.key!, "revoked");
|
||||
await reenqueueRequest(req);
|
||||
throw new RetryableError("Moonshot key is invalid, retrying with different key.");
|
||||
}
|
||||
} else if (statusCode === 429) {
|
||||
switch (service) {
|
||||
@@ -328,8 +364,24 @@ const handleUpstreamErrors: ProxyResHandlerWithBody = async (
|
||||
case "google-ai":
|
||||
await handleGoogleAIRateLimitError(req, errorPayload);
|
||||
break;
|
||||
case "deepseek":
|
||||
await handleDeepseekRateLimitError(req, errorPayload);
|
||||
break;
|
||||
case "xai":
|
||||
await handleXaiRateLimitError(req, errorPayload);
|
||||
break;
|
||||
case "cohere":
|
||||
await handleCohereRateLimitError(req, errorPayload);
|
||||
break;
|
||||
case "qwen":
|
||||
// Similar handling to OpenAI for rate limits
|
||||
await handleOpenAIRateLimitError(req, errorPayload);
|
||||
break;
|
||||
case "moonshot":
|
||||
await handleMoonshotRateLimitError(req, errorPayload);
|
||||
break;
|
||||
default:
|
||||
assertNever(service);
|
||||
assertNever(service as never);
|
||||
}
|
||||
} else if (statusCode === 404) {
|
||||
// Most likely model not found
|
||||
@@ -351,21 +403,27 @@ const handleUpstreamErrors: ProxyResHandlerWithBody = async (
|
||||
case "aws":
|
||||
case "gcp":
|
||||
case "azure":
|
||||
case "deepseek":
|
||||
case "xai":
|
||||
case "cohere":
|
||||
case "qwen":
|
||||
errorPayload.proxy_note = `The key assigned to your prompt does not support the requested model.`;
|
||||
break;
|
||||
default:
|
||||
assertNever(service);
|
||||
assertNever(service as never);
|
||||
}
|
||||
} else if (statusCode === 503) {
|
||||
switch (service) {
|
||||
case "aws":
|
||||
if (
|
||||
errorType === "ServiceUnavailableException" &&
|
||||
errorPayload.error?.message?.match(/too many connections/i)
|
||||
) {
|
||||
errorPayload.proxy_note = `The requested AWS Bedrock model is overloaded. Try again in a few minutes, or try another model.`;
|
||||
}
|
||||
break;
|
||||
// Re-enqueue on any 503 from AWS Bedrock
|
||||
req.log.warn(
|
||||
{ key: req.key?.hash, errorType, errorPayload },
|
||||
`AWS Bedrock service unavailable (503). Re-enqueueing request.`
|
||||
);
|
||||
await reenqueueRequest(req);
|
||||
throw new RetryableError(
|
||||
"AWS Bedrock service unavailable (503), re-enqueued request."
|
||||
);
|
||||
default:
|
||||
errorPayload.proxy_note = `Upstream service unavailable. Try again later.`;
|
||||
break;
|
||||
@@ -413,27 +471,32 @@ async function handleAnthropicAwsBadRequestError(
|
||||
// {"type":"error","error":{"type":"invalid_request_error","message":"Your credit balance is too low to access the Claude API. Please go to Plans & Billing to upgrade or purchase credits."}}
|
||||
const isOverQuota =
|
||||
error?.message?.match(/usage blocked until/i) ||
|
||||
error?.message?.match(/credit balance is too low/i);
|
||||
error?.message?.match(/credit balance is too low/i) ||
|
||||
error?.message?.match(/You will regain access on/i) ||
|
||||
error?.message?.match(/reached your specified API usage limits/i);
|
||||
if (isOverQuota) {
|
||||
req.log.warn(
|
||||
{ key: req.key?.hash, message: error?.message },
|
||||
"Anthropic key has hit spending limit and will be disabled."
|
||||
);
|
||||
keyPool.disable(req.key!, "quota");
|
||||
errorPayload.proxy_note = `Assigned key has hit its spending limit. ${error?.message}`;
|
||||
await reenqueueRequest(req);
|
||||
throw new RetryableError("Claude key hit spending limit, retrying with different key.");
|
||||
return;
|
||||
}
|
||||
|
||||
const isDisabled =
|
||||
error?.message?.match(/organization has been disabled/i) ||
|
||||
error?.message?.match(/^operation not allowed/i);
|
||||
error?.message?.match(/^operation not allowed/i) ||
|
||||
error?.message?.match(/credential is only authorized for use with Claude Code/i);
|
||||
if (isDisabled) {
|
||||
req.log.warn(
|
||||
{ key: req.key?.hash, message: error?.message },
|
||||
"Anthropic/AWS key has been disabled."
|
||||
);
|
||||
keyPool.disable(req.key!, "revoked");
|
||||
errorPayload.proxy_note = `Assigned key has been disabled. (${error?.message})`;
|
||||
await reenqueueRequest(req);
|
||||
throw new RetryableError("Claude key has been disabled, retrying with different key.");
|
||||
return;
|
||||
}
|
||||
|
||||
@@ -484,6 +547,106 @@ async function handleGcpRateLimitError(
|
||||
}
|
||||
}
|
||||
|
||||
async function handleDeepseekRateLimitError(
|
||||
req: Request,
|
||||
errorPayload: ProxiedErrorPayload
|
||||
) {
|
||||
keyPool.markRateLimited(req.key!);
|
||||
await reenqueueRequest(req);
|
||||
throw new RetryableError("Deepseek rate-limited request re-enqueued.");
|
||||
}
|
||||
|
||||
async function handleDeepseekBadRequestError(
|
||||
req: Request,
|
||||
errorPayload: ProxiedErrorPayload
|
||||
) {
|
||||
// Based on the checker code, a 400 response means the key is valid but there was some other error
|
||||
errorPayload.proxy_note = `The API rejected the request. Check the error message for details.`;
|
||||
}
|
||||
|
||||
async function handleXaiRateLimitError(
|
||||
req: Request,
|
||||
errorPayload: ProxiedErrorPayload
|
||||
) {
|
||||
keyPool.markRateLimited(req.key!);
|
||||
await reenqueueRequest(req);
|
||||
throw new RetryableError("Xai rate-limited request re-enqueued.");
|
||||
}
|
||||
|
||||
async function handleXaiBadRequestError(
|
||||
req: Request,
|
||||
errorPayload: ProxiedErrorPayload
|
||||
) {
|
||||
// Based on the checker code, a 400 response means the key is valid but there was some other error
|
||||
errorPayload.proxy_note = `The API rejected the request. Check the error message for details.`;
|
||||
}
|
||||
|
||||
async function handleCohereRateLimitError(
|
||||
req: Request,
|
||||
errorPayload: ProxiedErrorPayload
|
||||
) {
|
||||
// Mark the current key as rate limited
|
||||
keyPool.markRateLimited(req.key!);
|
||||
|
||||
// Store the original request attempt count or initialize it
|
||||
req.retryCount = (req.retryCount || 0) + 1;
|
||||
|
||||
// Only retry up to 3 times
|
||||
if (req.retryCount <= 3) {
|
||||
try {
|
||||
// Add a small delay before retrying (1-5 seconds)
|
||||
const delayMs = 1000 + Math.floor(Math.random() * 4000);
|
||||
await new Promise(resolve => setTimeout(resolve, delayMs));
|
||||
|
||||
// Re-enqueue the request to try with a different key
|
||||
await reenqueueRequest(req);
|
||||
req.log.info({ attempt: req.retryCount }, "Cohere rate-limited request re-enqueued");
|
||||
throw new RetryableError(`Cohere rate-limited request re-enqueued (attempt ${req.retryCount}/3).`);
|
||||
} catch (error) {
|
||||
if (error instanceof RetryableError) {
|
||||
throw error; // Rethrow RetryableError to continue the flow
|
||||
}
|
||||
req.log.error({ error }, "Failed to re-enqueue rate-limited Cohere request");
|
||||
}
|
||||
}
|
||||
|
||||
// If we've already retried 3 times, show the error to the user
|
||||
errorPayload.proxy_note = "Too many requests to the Cohere API. Please try again later.";
|
||||
}
|
||||
|
||||
async function handleMoonshotRateLimitError(
|
||||
req: Request,
|
||||
errorPayload: ProxiedErrorPayload
|
||||
) {
|
||||
// Mark the current key as rate limited
|
||||
keyPool.markRateLimited(req.key!);
|
||||
|
||||
// Store the original request attempt count or initialize it
|
||||
req.retryCount = (req.retryCount || 0) + 1;
|
||||
|
||||
// Only retry up to 3 times with different keys
|
||||
if (req.retryCount <= 3) {
|
||||
try {
|
||||
// Add a small delay before retrying (2-6 seconds for Moonshot)
|
||||
const delayMs = 2000 + Math.floor(Math.random() * 4000);
|
||||
await new Promise(resolve => setTimeout(resolve, delayMs));
|
||||
|
||||
// Re-enqueue the request to try with a different key
|
||||
await reenqueueRequest(req);
|
||||
req.log.info({ attempt: req.retryCount }, "Moonshot rate-limited request re-enqueued");
|
||||
throw new RetryableError(`Moonshot rate-limited request re-enqueued (attempt ${req.retryCount}/3).`);
|
||||
} catch (error) {
|
||||
if (error instanceof RetryableError) {
|
||||
throw error; // Rethrow RetryableError to continue the flow
|
||||
}
|
||||
req.log.error({ error }, "Failed to re-enqueue rate-limited Moonshot request");
|
||||
}
|
||||
}
|
||||
|
||||
// If we've already retried 3 times, show the error to the user
|
||||
errorPayload.proxy_note = "Too many requests to the Moonshot API. Please try again later.";
|
||||
}
|
||||
|
||||
async function handleOpenAIRateLimitError(
|
||||
req: Request,
|
||||
errorPayload: ProxiedErrorPayload
|
||||
@@ -494,17 +657,20 @@ async function handleOpenAIRateLimitError(
|
||||
case "invalid_request_error": // this is the billing_hard_limit_reached error seen in some cases
|
||||
// Billing quota exceeded (key is dead, disable it)
|
||||
keyPool.disable(req.key!, "quota");
|
||||
errorPayload.proxy_note = `Assigned key's quota has been exceeded. Please try again.`;
|
||||
await reenqueueRequest(req);
|
||||
throw new RetryableError("Google AI key quota exceeded, retrying with different key.");
|
||||
break;
|
||||
case "access_terminated":
|
||||
// Account banned (key is dead, disable it)
|
||||
keyPool.disable(req.key!, "revoked");
|
||||
errorPayload.proxy_note = `Assigned key has been banned by OpenAI for policy violations. Please try again.`;
|
||||
await reenqueueRequest(req);
|
||||
throw new RetryableError("Google AI key banned for policy violations, retrying with different key.");
|
||||
break;
|
||||
case "billing_not_active":
|
||||
// Key valid but account billing is delinquent
|
||||
keyPool.disable(req.key!, "quota");
|
||||
errorPayload.proxy_note = `Assigned key has been disabled due to delinquent billing. Please try again.`;
|
||||
await reenqueueRequest(req);
|
||||
throw new RetryableError("Google AI key billing not active, retrying with different key.");
|
||||
break;
|
||||
case "requests":
|
||||
case "tokens":
|
||||
@@ -563,7 +729,8 @@ async function handleGoogleAIBadRequestError(
|
||||
"Google API key appears to be inoperative."
|
||||
);
|
||||
keyPool.disable(req.key!, "revoked");
|
||||
errorPayload.proxy_note = `Assigned API key cannot be used.`;
|
||||
await reenqueueRequest(req);
|
||||
throw new RetryableError("Google API key inoperative, retrying with different key.");
|
||||
} else {
|
||||
req.log.warn(
|
||||
{ key: req.key?.hash, error: text },
|
||||
@@ -609,6 +776,7 @@ async function handleGoogleAIRateLimitError(
|
||||
) {
|
||||
const status = errorPayload.error?.status;
|
||||
const text = JSON.stringify(errorPayload.error);
|
||||
const errorMessage = errorPayload.error?.message?.toLowerCase() || '';
|
||||
|
||||
// sometimes they block keys by rate limiting them to 0 requests per minute
|
||||
// for some indefinite period of time
|
||||
@@ -617,19 +785,112 @@ async function handleGoogleAIRateLimitError(
|
||||
/"quota_limit_value":"0"/i,
|
||||
];
|
||||
|
||||
// Quota exhaustion indicators in error messages
|
||||
const quotaExhaustedMsgs = [
|
||||
/quota exceeded/i,
|
||||
/free tier|free_tier/i,
|
||||
/quota limit/i
|
||||
];
|
||||
|
||||
// If we don't have a key in the request, we can't process rate limits
|
||||
if (!req.key) {
|
||||
errorPayload.proxy_note = `Rate limit error but no key was found in the request.`;
|
||||
return;
|
||||
}
|
||||
|
||||
switch (status) {
|
||||
case "RESOURCE_EXHAUSTED": {
|
||||
if (keyDeadMsgs.every((msg) => text.match(msg))) {
|
||||
// Hard disabled keys - these are completely blocked
|
||||
if (keyDeadMsgs.some((msg) => msg.test(text))) {
|
||||
req.log.warn(
|
||||
{ key: req.key?.hash, error: text },
|
||||
"Google API key appears to be temporarily inoperative and will be disabled."
|
||||
{ key: req.key.hash, error: text },
|
||||
"Google API key appears to be completely disabled and will be removed from rotation."
|
||||
);
|
||||
keyPool.disable(req.key!, "revoked");
|
||||
keyPool.disable(req.key, "revoked");
|
||||
errorPayload.proxy_note = `Assigned API key cannot be used.`;
|
||||
return;
|
||||
}
|
||||
|
||||
keyPool.markRateLimited(req.key!);
|
||||
// Check if this is a quota exhaustion error rather than just a rate limit
|
||||
const isQuotaExhausted = quotaExhaustedMsgs.some(pattern => pattern.test(text) || pattern.test(errorMessage));
|
||||
|
||||
if (isQuotaExhausted && req.body?.model) {
|
||||
// Get model family for the current request
|
||||
const modelName = req.body.model;
|
||||
const isPro = modelName.includes('pro');
|
||||
const isFlash = modelName.includes('flash');
|
||||
const isUltra = modelName.includes('ultra');
|
||||
|
||||
req.log.warn(
|
||||
{ key: req.key.hash, model: modelName, error: text },
|
||||
"Google API key has exhausted its quota for this model family and will be marked as overquota."
|
||||
);
|
||||
|
||||
// Create a filtered list of model families that excludes the over-quota family
|
||||
let familyToRemove: GoogleAIModelFamily | null = null;
|
||||
if (isPro) {
|
||||
familyToRemove = 'gemini-pro';
|
||||
errorPayload.proxy_note = `Assigned API key has exhausted quota for Gemini Pro models.`;
|
||||
} else if (isFlash) {
|
||||
familyToRemove = 'gemini-flash';
|
||||
errorPayload.proxy_note = `Assigned API key has exhausted quota for Gemini Flash models.`;
|
||||
} else if (isUltra) {
|
||||
familyToRemove = 'gemini-ultra';
|
||||
errorPayload.proxy_note = `Assigned API key has exhausted quota for Gemini Ultra models.`;
|
||||
} else {
|
||||
// If model family can't be determined, just mark as rate limited
|
||||
keyPool.markRateLimited(req.key);
|
||||
errorPayload.proxy_note = `Assigned API key has exhausted quota but model family couldn't be determined.`;
|
||||
}
|
||||
|
||||
// Update the modelFamilies in the key if we identified a family to remove
|
||||
if (familyToRemove) {
|
||||
// Get current model families, filter out the one that's over quota
|
||||
const updatedFamilies = [...req.key.modelFamilies].filter(f => f !== familyToRemove);
|
||||
|
||||
// Cast the key to GoogleAIKey type to access its specific properties
|
||||
const googleKey = req.key as GoogleAIKey;
|
||||
|
||||
// Track which families are over quota for future rechecking
|
||||
const overQuotaFamilies = googleKey.overQuotaFamilies || [];
|
||||
if (!overQuotaFamilies.includes(familyToRemove)) {
|
||||
overQuotaFamilies.push(familyToRemove);
|
||||
}
|
||||
|
||||
// Mark the key as over quota but still usable for other model families
|
||||
req.log.info(
|
||||
{ key: req.key.hash, family: familyToRemove },
|
||||
"Marking Google AI key as over quota for specific model family"
|
||||
);
|
||||
|
||||
// First make a typed update object that includes only the properties we want to update
|
||||
interface GoogleAIPartialUpdate {
|
||||
modelFamilies: GoogleAIModelFamily[];
|
||||
isOverQuota: boolean;
|
||||
overQuotaFamilies: GoogleAIModelFamily[];
|
||||
}
|
||||
|
||||
// Create a properly typed update
|
||||
const update: GoogleAIPartialUpdate = {
|
||||
modelFamilies: updatedFamilies as GoogleAIModelFamily[],
|
||||
isOverQuota: true,
|
||||
overQuotaFamilies
|
||||
};
|
||||
|
||||
// Use the standard KeyPool interface
|
||||
// This gets around the TypeScript issues by letting KeyPool handle routing
|
||||
const clonedKey = { ...req.key }; // Make a clone since we'll be modifying it
|
||||
keyPool.update(clonedKey, update as any);
|
||||
}
|
||||
|
||||
// Re-enqueue with a different key
|
||||
await reenqueueRequest(req);
|
||||
throw new RetryableError("Quota-exhausted request re-enqueued with a different key.");
|
||||
}
|
||||
|
||||
// Standard rate limiting - just mark as rate limited temporarily
|
||||
req.log.debug({ key: req.key.hash, error: text }, "Google API request rate limited, will retry.");
|
||||
keyPool.markRateLimited(req.key);
|
||||
await reenqueueRequest(req);
|
||||
throw new RetryableError("Rate-limited request re-enqueued.");
|
||||
}
|
||||
@@ -652,10 +913,12 @@ const incrementUsage: ProxyResHandlerWithBody = async (_proxyRes, req) => {
|
||||
},
|
||||
`Incrementing usage for model`
|
||||
);
|
||||
keyPool.incrementUsage(req.key!, model, tokensUsed);
|
||||
// Get modelFamily for the key usage log
|
||||
const modelFamilyForKeyPool = req.modelFamily!; // Should be set by getModelFamilyForRequest earlier
|
||||
keyPool.incrementUsage(req.key!, modelFamilyForKeyPool, { input: req.promptTokens!, output: req.outputTokens! });
|
||||
if (req.user) {
|
||||
incrementPromptCount(req.user.token);
|
||||
incrementTokenCount(req.user.token, model, req.outboundApi, tokensUsed);
|
||||
incrementTokenCount(req.user.token, model, req.outboundApi, { input: req.promptTokens!, output: req.outputTokens! });
|
||||
}
|
||||
}
|
||||
};
|
||||
@@ -681,8 +944,8 @@ const countResponseTokens: ProxyResHandlerWithBody = async (
|
||||
const service = req.outboundApi;
|
||||
const completion = getCompletionFromBody(req, body);
|
||||
const tokens = await countTokens({ req, completion, service });
|
||||
|
||||
if (req.service === "openai" || req.service === "azure") {
|
||||
|
||||
if (req.service === "openai" || req.service === "azure" || req.service === "deepseek" || req.service === "cohere" || req.service === "qwen") {
|
||||
// O1 consumes (a significant amount of) invisible tokens for the chain-
|
||||
// of-thought reasoning. We have no way to count these other than to check
|
||||
// the response body.
|
||||
@@ -723,6 +986,8 @@ const omittedHeaders = new Set<string>([
|
||||
"set-cookie",
|
||||
"openai-organization",
|
||||
"x-request-id",
|
||||
"x-ds-request-id",
|
||||
"x-ds-trace-id",
|
||||
"cf-ray",
|
||||
]);
|
||||
const copyHttpHeaders: ProxyResHandlerWithBody = async (
|
||||
@@ -730,6 +995,9 @@ const copyHttpHeaders: ProxyResHandlerWithBody = async (
|
||||
_req,
|
||||
res
|
||||
) => {
|
||||
// Hack: we don't copy headers since with chunked transfer we've already sent them.
|
||||
if (_req.isChunkedTransfer) return;
|
||||
|
||||
Object.keys(proxyRes.headers).forEach((key) => {
|
||||
if (omittedHeaders.has(key)) return;
|
||||
res.setHeader(key, proxyRes.headers[key] as string);
|
||||
|
||||
@@ -72,6 +72,8 @@ const getPromptForRequest = (
|
||||
// format.
|
||||
switch (req.outboundApi) {
|
||||
case "openai":
|
||||
case "openai-responses":
|
||||
return req.body.messages;
|
||||
case "mistral-ai":
|
||||
return req.body.messages;
|
||||
case "anthropic-chat":
|
||||
@@ -120,7 +122,7 @@ const flattenMessages = (
|
||||
if (isGoogleAIChatPrompt(val)) {
|
||||
return val.contents
|
||||
.map(({ parts, role }) => {
|
||||
const text = parts.map((p) => p.text).join("\n");
|
||||
const text = parts.filter(p => 'text' in p).map((p) => (p as { text: string }).text).join("\n");
|
||||
return `${role}: ${text}`;
|
||||
})
|
||||
.join("\n");
|
||||
|
||||
@@ -84,7 +84,8 @@ export class EventAggregator {
|
||||
getFinalResponse() {
|
||||
switch (this.responseFormat) {
|
||||
case "openai":
|
||||
case "google-ai": // TODO: this is probably wrong now that we support native Google Makersuite prompts
|
||||
case "openai-responses":
|
||||
case "google-ai":
|
||||
return mergeEventsForOpenAIChat(this.events);
|
||||
case "openai-text":
|
||||
return mergeEventsForOpenAIText(this.events);
|
||||
|
||||
@@ -158,6 +158,8 @@ function getTransformer(
|
||||
: mistralAIToOpenAI;
|
||||
case "openai-image":
|
||||
throw new Error(`SSE transformation not supported for ${responseApi}`);
|
||||
case "openai-responses":
|
||||
return passthroughToOpenAI;
|
||||
default:
|
||||
assertNever(responseApi);
|
||||
}
|
||||
|
||||
+53
-27
@@ -20,40 +20,66 @@ import { createQueuedProxyMiddleware } from "./middleware/request/proxy-middlewa
|
||||
// months of releasing them so this list is hard to keep up to date. 2024-07-28
|
||||
// https://docs.mistral.ai/platform/endpoints
|
||||
export const KNOWN_MISTRAL_AI_MODELS = [
|
||||
/*
|
||||
Mistral Nemo
|
||||
"A 12B model built with the partnership with Nvidia. It is easy to use and a
|
||||
drop-in replacement in any system using Mistral 7B that it supersedes."
|
||||
*/
|
||||
/* Premier models */
|
||||
// Mistral Large (top-tier reasoning model)
|
||||
"mistral-large-latest",
|
||||
"mistral-large-2411",
|
||||
"mistral-large-2407",
|
||||
"mistral-large-2402", // older version
|
||||
|
||||
// Pixtral Large (multimodal/vision model)
|
||||
"pixtral-large-latest",
|
||||
"pixtral-large-2411",
|
||||
|
||||
// Mistral Saba (language-specialized model)
|
||||
"mistral-saba-latest",
|
||||
"mistral-saba-2502",
|
||||
|
||||
// Codestral (code model)
|
||||
"codestral-latest",
|
||||
"codestral-2501",
|
||||
"codestral-2405",
|
||||
|
||||
// Ministral models (edge models)
|
||||
"ministral-8b-latest",
|
||||
"ministral-8b-2410",
|
||||
"ministral-3b-latest",
|
||||
"ministral-3b-2410",
|
||||
|
||||
// Embedding & Moderation
|
||||
"mistral-embed",
|
||||
"mistral-embed-2312",
|
||||
"mistral-moderation-latest",
|
||||
"mistral-moderation-2411",
|
||||
|
||||
/* Free models */
|
||||
// Mistral Small (with vision in latest version)
|
||||
"mistral-small-latest",
|
||||
"mistral-small-2503", // v3.1 with vision
|
||||
"mistral-small-2402", // older version
|
||||
"magistral-small-latest",
|
||||
|
||||
// Pixtral 12B (vision model)
|
||||
"pixtral-12b-latest",
|
||||
"pixtral-12b-2409",
|
||||
|
||||
/* Research & Open Models */
|
||||
// Mistral Nemo
|
||||
"open-mistral-nemo",
|
||||
"open-mistral-nemo-2407",
|
||||
/*
|
||||
Mistral Large
|
||||
"Our flagship model with state-of-the-art reasoning, knowledge, and coding
|
||||
capabilities."
|
||||
*/
|
||||
"mistral-large-latest",
|
||||
"mistral-large-2407",
|
||||
"mistral-large-2402", // deprecated
|
||||
/*
|
||||
Codestral
|
||||
"A cutting-edge generative model that has been specifically designed and
|
||||
optimized for code generation tasks, including fill-in-the-middle and code
|
||||
completion."
|
||||
note: this uses a separate bidi completion endpoint that is not implemented
|
||||
*/
|
||||
"codestral-latest",
|
||||
"codestral-2405",
|
||||
/* So-called "Research Models" */
|
||||
|
||||
// Earlier Mixtral & Mistral models
|
||||
"open-mistral-7b",
|
||||
"open-mixtral-8x7b",
|
||||
"open-mistral-8x22b",
|
||||
"open-mixtral-8x22b",
|
||||
"open-codestral-mamba",
|
||||
/* Deprecated production models */
|
||||
"mistral-small-latest",
|
||||
"mistral-small-2402",
|
||||
"mathstral",
|
||||
|
||||
/* Other, too lazy to do it properly now */
|
||||
"mistral-medium-latest",
|
||||
"mistral-medium-2312",
|
||||
"mistral-medium-2505",
|
||||
"magistral-medium-latest",
|
||||
"mistral-tiny",
|
||||
"mistral-tiny-2312",
|
||||
];
|
||||
|
||||
@@ -0,0 +1,219 @@
|
||||
import { Request, RequestHandler, Router } from "express";
|
||||
import { createPreprocessorMiddleware } from "./middleware/request";
|
||||
import { ipLimiter } from "./rate-limit";
|
||||
import { createQueuedProxyMiddleware } from "./middleware/request/proxy-middleware-factory";
|
||||
import { addKey, finalizeBody } from "./middleware/request";
|
||||
import { ProxyResHandlerWithBody } from "./middleware/response";
|
||||
import axios from "axios";
|
||||
import { MoonshotKey, keyPool } from "../shared/key-management";
|
||||
import { isMoonshotModel, isMoonshotVisionModel } from "../shared/api-schemas/moonshot";
|
||||
import { logger } from "../logger";
|
||||
|
||||
const log = logger.child({ module: "proxy", service: "moonshot" });
|
||||
let modelsCache: any = null;
|
||||
let modelsCacheTime = 0;
|
||||
|
||||
const moonshotResponseHandler: ProxyResHandlerWithBody = async (
|
||||
_proxyRes,
|
||||
req,
|
||||
res,
|
||||
body
|
||||
) => {
|
||||
if (typeof body !== "object") {
|
||||
throw new Error("Expected body to be an object");
|
||||
}
|
||||
|
||||
res.status(200).json({ ...body, proxy: body.proxy });
|
||||
};
|
||||
|
||||
const getModelsResponse = async () => {
|
||||
// Return cache if less than 1 minute old
|
||||
if (new Date().getTime() - modelsCacheTime < 1000 * 60) {
|
||||
return modelsCache;
|
||||
}
|
||||
|
||||
try {
|
||||
const modelToUse = "moonshot-v1-8k";
|
||||
const moonshotKey = keyPool.get(modelToUse, "moonshot") as MoonshotKey;
|
||||
|
||||
if (!moonshotKey || !moonshotKey.key) {
|
||||
log.warn("No valid Moonshot key available for model listing");
|
||||
throw new Error("No valid Moonshot API key available");
|
||||
}
|
||||
|
||||
// Fetch models from Moonshot API
|
||||
const response = await axios.get("https://api.moonshot.cn/v1/models", {
|
||||
headers: {
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": `Bearer ${moonshotKey.key}`
|
||||
},
|
||||
});
|
||||
|
||||
if (!response.data || !response.data.data) {
|
||||
throw new Error("Unexpected response format from Moonshot API");
|
||||
}
|
||||
|
||||
// Format response to ensure OpenAI compatibility
|
||||
const models = {
|
||||
object: "list",
|
||||
data: response.data.data.map((model: any) => ({
|
||||
id: model.id,
|
||||
object: "model",
|
||||
created: model.created || Math.floor(Date.now() / 1000),
|
||||
owned_by: model.owned_by || "moonshot",
|
||||
permission: model.permission || [],
|
||||
root: model.root || model.id,
|
||||
parent: model.parent || null,
|
||||
})),
|
||||
};
|
||||
|
||||
log.debug({ modelCount: models.data.length }, "Retrieved models from Moonshot API");
|
||||
|
||||
// Cache the response
|
||||
modelsCache = models;
|
||||
modelsCacheTime = new Date().getTime();
|
||||
return models;
|
||||
} catch (error) {
|
||||
if (error instanceof Error) {
|
||||
log.error(
|
||||
{ errorMessage: error.message, stack: error.stack },
|
||||
"Error fetching Moonshot models"
|
||||
);
|
||||
} else {
|
||||
log.error({ error }, "Unknown error fetching Moonshot models");
|
||||
}
|
||||
|
||||
// Return a default list of known Moonshot models as fallback
|
||||
return {
|
||||
object: "list",
|
||||
data: [
|
||||
{ id: "moonshot-v1-8k", object: "model", created: 1678888000, owned_by: "moonshot" },
|
||||
{ id: "moonshot-v1-32k", object: "model", created: 1678888000, owned_by: "moonshot" },
|
||||
{ id: "moonshot-v1-128k", object: "model", created: 1678888000, owned_by: "moonshot" },
|
||||
],
|
||||
};
|
||||
}
|
||||
};
|
||||
|
||||
const handleModelRequest: RequestHandler = async (_req, res) => {
|
||||
try {
|
||||
const models = await getModelsResponse();
|
||||
res.status(200).json(models);
|
||||
} catch (error) {
|
||||
if (error instanceof Error) {
|
||||
log.error(
|
||||
{ errorMessage: error.message, stack: error.stack },
|
||||
"Error handling model request"
|
||||
);
|
||||
} else {
|
||||
log.error({ error }, "Unknown error handling model request");
|
||||
}
|
||||
res.status(500).json({ error: "Failed to fetch models" });
|
||||
}
|
||||
};
|
||||
|
||||
// Function to handle partial mode for Moonshot
|
||||
function handlePartialMode(req: Request) {
|
||||
if (!process.env.NO_MOONSHOT_PARTIAL && req.body.messages && Array.isArray(req.body.messages)) {
|
||||
const msgs = req.body.messages;
|
||||
if (msgs.at(-1)?.role !== 'assistant') return;
|
||||
|
||||
let i = msgs.length - 1;
|
||||
let content = '';
|
||||
|
||||
while (i >= 0 && msgs[i].role === 'assistant') {
|
||||
// Consolidate consecutive assistant messages
|
||||
content = msgs[i--].content + content;
|
||||
}
|
||||
|
||||
// Replace consecutive assistant messages with single message with partial: true
|
||||
msgs.splice(i + 1, msgs.length, { role: 'assistant', content, partial: true });
|
||||
log.debug("Consolidated assistant messages and enabled partial mode for Moonshot request");
|
||||
}
|
||||
}
|
||||
|
||||
// Function to handle vision model content transformation
|
||||
function handleVisionContent(req: Request) {
|
||||
const model = req.body.model;
|
||||
|
||||
if (isMoonshotVisionModel(model) && req.body.messages) {
|
||||
// Ensure vision content is properly formatted
|
||||
req.body.messages = req.body.messages.map((msg: any) => {
|
||||
if (msg.content && typeof msg.content === 'string') {
|
||||
// Keep string content as is for non-vision requests
|
||||
return msg;
|
||||
}
|
||||
return msg;
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
// Function to count tokens for Moonshot models
|
||||
function countMoonshotTokens(req: Request) {
|
||||
const model = req.body.model;
|
||||
|
||||
if (isMoonshotModel(model)) {
|
||||
if (req.promptTokens) {
|
||||
log.debug(
|
||||
{ tokens: req.promptTokens, model },
|
||||
"Estimated token count for Moonshot prompt"
|
||||
);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Handle rate limit errors for Moonshot
|
||||
async function handleMoonshotRateLimitError(req: Request, error: any) {
|
||||
if (error.response?.status === 429) {
|
||||
log.warn({ model: req.body.model }, "Moonshot rate limit hit, rotating key");
|
||||
|
||||
const currentKey = req.key as MoonshotKey;
|
||||
keyPool.markRateLimited(currentKey);
|
||||
|
||||
// Try to get a new key
|
||||
const newKey = keyPool.get(req.body.model, "moonshot") as MoonshotKey;
|
||||
if (newKey.hash !== currentKey.hash) {
|
||||
req.key = newKey;
|
||||
return true; // Retry with new key
|
||||
}
|
||||
}
|
||||
return false;
|
||||
}
|
||||
|
||||
const moonshotProxy = createQueuedProxyMiddleware({
|
||||
mutations: [
|
||||
addKey,
|
||||
finalizeBody
|
||||
],
|
||||
target: "https://api.moonshot.cn",
|
||||
blockingResponseHandler: moonshotResponseHandler,
|
||||
});
|
||||
|
||||
const moonshotRouter = Router();
|
||||
|
||||
// Chat completions endpoint
|
||||
moonshotRouter.post(
|
||||
"/v1/chat/completions",
|
||||
ipLimiter,
|
||||
createPreprocessorMiddleware(
|
||||
{ inApi: "openai", outApi: "openai", service: "moonshot" },
|
||||
{ afterTransform: [ handlePartialMode, handleVisionContent, countMoonshotTokens ] }
|
||||
),
|
||||
moonshotProxy
|
||||
);
|
||||
|
||||
// Embeddings endpoint
|
||||
moonshotRouter.post(
|
||||
"/v1/embeddings",
|
||||
ipLimiter,
|
||||
createPreprocessorMiddleware(
|
||||
{ inApi: "openai", outApi: "openai", service: "moonshot" },
|
||||
{ afterTransform: [ countMoonshotTokens ] }
|
||||
),
|
||||
moonshotProxy
|
||||
);
|
||||
|
||||
// Models endpoint
|
||||
moonshotRouter.get("/v1/models", handleModelRequest);
|
||||
|
||||
export const moonshot = moonshotRouter;
|
||||
+102
-9
@@ -11,7 +11,7 @@ import { ProxyResHandlerWithBody } from "./middleware/response";
|
||||
import { ProxyReqManager } from "./middleware/request/proxy-req-manager";
|
||||
import { createQueuedProxyMiddleware } from "./middleware/request/proxy-middleware-factory";
|
||||
|
||||
const KNOWN_MODELS = ["dall-e-2", "dall-e-3"];
|
||||
const KNOWN_MODELS = ["dall-e-2", "dall-e-3", "gpt-image-1"];
|
||||
|
||||
let modelListCache: any = null;
|
||||
let modelListValid = 0;
|
||||
@@ -58,27 +58,46 @@ function transformResponseForChat(
|
||||
req: Request
|
||||
): Record<string, any> {
|
||||
const prompt = imageBody.data[0].revised_prompt ?? req.body.prompt;
|
||||
const isGptImage = req.body.model?.includes("gpt-image") || false;
|
||||
|
||||
const content = imageBody.data
|
||||
.map((item) => {
|
||||
const { url, b64_json } = item;
|
||||
// The gpt-image-1 model always returns b64_json
|
||||
// Format will depend on output_format parameter (defaults to png)
|
||||
// For simplicity, we'll assume png if not specified
|
||||
const format = req.body.output_format || "png";
|
||||
|
||||
if (b64_json) {
|
||||
return ``;
|
||||
return ``;
|
||||
} else {
|
||||
return ``;
|
||||
}
|
||||
})
|
||||
.join("\n\n");
|
||||
|
||||
// Prepare the usage information - gpt-image-1 includes detailed token usage
|
||||
let usage = {
|
||||
prompt_tokens: 0,
|
||||
completion_tokens: req.outputTokens,
|
||||
total_tokens: req.outputTokens,
|
||||
};
|
||||
|
||||
// If this is a gpt-image-1 response, it includes detailed usage info
|
||||
if (imageBody.usage) {
|
||||
usage = {
|
||||
prompt_tokens: imageBody.usage.input_tokens || 0,
|
||||
completion_tokens: imageBody.usage.output_tokens || 0,
|
||||
total_tokens: imageBody.usage.total_tokens || 0,
|
||||
};
|
||||
}
|
||||
|
||||
return {
|
||||
id: "dalle-" + req.id,
|
||||
id: req.body.model?.includes("gpt-image") ? "gptimage-" + req.id : "dalle-" + req.id,
|
||||
object: "chat.completion",
|
||||
created: Date.now(),
|
||||
model: req.body.model,
|
||||
usage: {
|
||||
prompt_tokens: 0,
|
||||
completion_tokens: req.outputTokens,
|
||||
total_tokens: req.outputTokens,
|
||||
},
|
||||
usage,
|
||||
choices: [
|
||||
{
|
||||
message: { role: "assistant", content },
|
||||
@@ -89,6 +108,69 @@ function transformResponseForChat(
|
||||
};
|
||||
}
|
||||
|
||||
// Filter parameters based on the model being used to avoid sending unsupported parameters
|
||||
function filterModelParameters(manager: ProxyReqManager) {
|
||||
const req = manager.request;
|
||||
const originalBody = req.body;
|
||||
const modelName = originalBody?.model || "";
|
||||
|
||||
// Skip if no body or it's not an object
|
||||
if (!originalBody || typeof originalBody !== 'object') return;
|
||||
|
||||
// Create a deep copy of the body to filter
|
||||
const filteredBody = { ...originalBody };
|
||||
|
||||
// Define allowed parameters for each model
|
||||
if (modelName.includes('dall-e-2')) {
|
||||
// DALL-E 2 parameters
|
||||
const allowedParams = [
|
||||
'model', 'prompt', 'n', 'size', 'response_format', 'user'
|
||||
];
|
||||
|
||||
// Remove any parameter not in the allowed list
|
||||
Object.keys(filteredBody).forEach(key => {
|
||||
if (!allowedParams.includes(key)) {
|
||||
delete filteredBody[key];
|
||||
}
|
||||
});
|
||||
|
||||
req.log.info({ model: 'dall-e-2', params: Object.keys(filteredBody) }, "Filtered parameters for DALL-E 2");
|
||||
} else if (modelName.includes('dall-e-3')) {
|
||||
// DALL-E 3 parameters
|
||||
const allowedParams = [
|
||||
'model', 'prompt', 'n', 'quality', 'size', 'style', 'response_format', 'user'
|
||||
];
|
||||
|
||||
// Remove any parameter not in the allowed list
|
||||
Object.keys(filteredBody).forEach(key => {
|
||||
if (!allowedParams.includes(key)) {
|
||||
delete filteredBody[key];
|
||||
}
|
||||
});
|
||||
|
||||
req.log.info({ model: 'dall-e-3', params: Object.keys(filteredBody) }, "Filtered parameters for DALL-E 3");
|
||||
} else if (modelName.includes('gpt-image')) {
|
||||
// Define allowed parameters for gpt-image-1
|
||||
const allowedParams = [
|
||||
'model', 'prompt', 'background', 'moderation', 'n', 'output_compression',
|
||||
'output_format', 'quality', 'size', 'user', 'image', 'mask'
|
||||
];
|
||||
|
||||
// Remove any parameter not in the allowed list, especially 'style' which is only for DALL-E 3
|
||||
Object.keys(filteredBody).forEach(key => {
|
||||
if (!allowedParams.includes(key)) {
|
||||
req.log.info({ model: 'gpt-image-1', removedParam: key }, "Removing unsupported parameter for GPT Image");
|
||||
delete filteredBody[key];
|
||||
}
|
||||
});
|
||||
|
||||
req.log.info({ model: 'gpt-image-1', params: Object.keys(filteredBody) }, "Filtered parameters for GPT Image");
|
||||
}
|
||||
|
||||
// Use the proper method to update the body
|
||||
manager.setBody(filteredBody);
|
||||
}
|
||||
|
||||
function replacePath(manager: ProxyReqManager) {
|
||||
const req = manager.request;
|
||||
const pathname = req.url.split("?")[0];
|
||||
@@ -100,7 +182,7 @@ function replacePath(manager: ProxyReqManager) {
|
||||
|
||||
const openaiImagesProxy = createQueuedProxyMiddleware({
|
||||
target: "https://api.openai.com",
|
||||
mutations: [replacePath, addKey, finalizeBody],
|
||||
mutations: [replacePath, filterModelParameters, addKey, finalizeBody],
|
||||
blockingResponseHandler: openaiImagesResponseHandler,
|
||||
});
|
||||
|
||||
@@ -116,6 +198,17 @@ openaiImagesRouter.post(
|
||||
}),
|
||||
openaiImagesProxy
|
||||
);
|
||||
// Add support for the /v1/images/edits endpoint (used by gpt-image-1 for image editing)
|
||||
openaiImagesRouter.post(
|
||||
"/v1/images/edits",
|
||||
ipLimiter,
|
||||
createPreprocessorMiddleware({
|
||||
inApi: "openai-image",
|
||||
outApi: "openai-image",
|
||||
service: "openai",
|
||||
}),
|
||||
openaiImagesProxy
|
||||
);
|
||||
openaiImagesRouter.post(
|
||||
"/v1/chat/completions",
|
||||
ipLimiter,
|
||||
|
||||
+299
-5
@@ -1,5 +1,6 @@
|
||||
import { Request, RequestHandler, Router } from "express";
|
||||
import { config } from "../config";
|
||||
import { BadRequestError } from "../shared/errors";
|
||||
import { AzureOpenAIKey, keyPool, OpenAIKey } from "../shared/key-management";
|
||||
import { getOpenAIModelFamily } from "../shared/models";
|
||||
import { ipLimiter } from "./rate-limit";
|
||||
@@ -38,7 +39,7 @@ export function generateModelList(service: "openai" | "azure") {
|
||||
.flatMap((k) => k.modelIds)
|
||||
.filter((id) => {
|
||||
const allowed = modelFamilies.has(getOpenAIModelFamily(id));
|
||||
const known = ["gpt", "o1", "dall-e", "chatgpt", "text-embedding"].some(
|
||||
const known = ["gpt", "o", "dall-e", "chatgpt", "text-embedding", "codex"].some(
|
||||
(prefix) => id.startsWith(prefix)
|
||||
);
|
||||
const isFinetune = id.includes("ft");
|
||||
@@ -109,10 +110,21 @@ const openaiResponseHandler: ProxyResHandlerWithBody = async (
|
||||
throw new Error("Expected body to be an object");
|
||||
}
|
||||
|
||||
const interval = (req as any)._keepAliveInterval
|
||||
if (interval) {
|
||||
clearInterval(interval);
|
||||
res.write(JSON.stringify(body));
|
||||
res.end();
|
||||
return;
|
||||
}
|
||||
|
||||
let newBody = body;
|
||||
if (req.outboundApi === "openai-text" && req.inboundApi === "openai") {
|
||||
req.log.info("Transforming Turbo-Instruct response to Chat format");
|
||||
newBody = transformTurboInstructResponse(body);
|
||||
} else if (req.outboundApi === "openai-responses" && req.inboundApi === "openai") {
|
||||
req.log.info("Transforming Responses API response to Chat format");
|
||||
newBody = transformResponsesApiResponse(body);
|
||||
}
|
||||
|
||||
res.status(200).json({ ...newBody, proxy: body.proxy });
|
||||
@@ -135,6 +147,135 @@ function transformTurboInstructResponse(
|
||||
return transformed;
|
||||
}
|
||||
|
||||
function transformResponsesApiResponse(
|
||||
responsesBody: Record<string, any>
|
||||
): Record<string, any> {
|
||||
// If the response is already in chat completion format, return it as is
|
||||
if (responsesBody.choices && responsesBody.choices[0]?.message) {
|
||||
return responsesBody;
|
||||
}
|
||||
|
||||
// Create a compatible format for clients expecting chat completions format
|
||||
const transformed: Record<string, any> = {
|
||||
id: responsesBody.id || `chatcmpl-${Date.now()}`,
|
||||
object: "chat.completion",
|
||||
created: responsesBody.created_at || Math.floor(Date.now() / 1000),
|
||||
model: responsesBody.model || "o1-pro",
|
||||
choices: [],
|
||||
usage: responsesBody.usage || {
|
||||
prompt_tokens: 0,
|
||||
completion_tokens: 0,
|
||||
total_tokens: 0
|
||||
}
|
||||
};
|
||||
|
||||
// Extract content from the Responses API format - multiple possible structures
|
||||
|
||||
// Structure 1: output array with message objects
|
||||
if (responsesBody.output && Array.isArray(responsesBody.output)) {
|
||||
// Look for a message type in the output array
|
||||
let messageOutput = null;
|
||||
for (const output of responsesBody.output) {
|
||||
if (output.type === "message") {
|
||||
messageOutput = output;
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
if (messageOutput) {
|
||||
if (messageOutput.content && Array.isArray(messageOutput.content) && messageOutput.content.length > 0) {
|
||||
// Handle text content
|
||||
let content = "";
|
||||
const toolCalls: any[] = [];
|
||||
|
||||
for (const contentItem of messageOutput.content) {
|
||||
if (contentItem.type === "output_text") {
|
||||
content += contentItem.text;
|
||||
} else if (contentItem.type === "tool_calls" && Array.isArray(contentItem.tool_calls)) {
|
||||
toolCalls.push(...contentItem.tool_calls);
|
||||
}
|
||||
}
|
||||
|
||||
const message: Record<string, any> = {
|
||||
role: messageOutput.role || "assistant",
|
||||
content: content
|
||||
};
|
||||
|
||||
if (toolCalls.length > 0) {
|
||||
message.tool_calls = toolCalls;
|
||||
}
|
||||
|
||||
transformed.choices.push({
|
||||
index: 0,
|
||||
message,
|
||||
finish_reason: "stop"
|
||||
});
|
||||
} else if (typeof messageOutput.content === 'string') {
|
||||
// Simple string content
|
||||
transformed.choices.push({
|
||||
index: 0,
|
||||
message: {
|
||||
role: messageOutput.role || "assistant",
|
||||
content: messageOutput.content
|
||||
},
|
||||
finish_reason: "stop"
|
||||
});
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Structure 2: response object with content
|
||||
else if (responsesBody.response && responsesBody.response.content) {
|
||||
transformed.choices.push({
|
||||
index: 0,
|
||||
message: {
|
||||
role: "assistant",
|
||||
content: typeof responsesBody.response.content === 'string'
|
||||
? responsesBody.response.content
|
||||
: JSON.stringify(responsesBody.response.content)
|
||||
},
|
||||
finish_reason: responsesBody.response.finish_reason || "stop"
|
||||
});
|
||||
}
|
||||
|
||||
// Structure 3: look for 'content' field directly
|
||||
else if (responsesBody.content) {
|
||||
transformed.choices.push({
|
||||
index: 0,
|
||||
message: {
|
||||
role: "assistant",
|
||||
content: typeof responsesBody.content === 'string'
|
||||
? responsesBody.content
|
||||
: JSON.stringify(responsesBody.content)
|
||||
},
|
||||
finish_reason: "stop"
|
||||
});
|
||||
}
|
||||
|
||||
// If we couldn't extract content, create a basic response
|
||||
if (transformed.choices.length === 0) {
|
||||
transformed.choices.push({
|
||||
index: 0,
|
||||
message: {
|
||||
role: "assistant",
|
||||
content: ""
|
||||
},
|
||||
finish_reason: "stop"
|
||||
});
|
||||
}
|
||||
|
||||
// Copy usage information if available
|
||||
if (responsesBody.usage) {
|
||||
transformed.usage = {
|
||||
prompt_tokens: responsesBody.usage.input_tokens || 0,
|
||||
completion_tokens: responsesBody.usage.output_tokens || 0,
|
||||
total_tokens: responsesBody.usage.total_tokens || 0
|
||||
};
|
||||
}
|
||||
|
||||
return transformed;
|
||||
}
|
||||
|
||||
const openaiProxy = createQueuedProxyMiddleware({
|
||||
mutations: [addKey, finalizeBody],
|
||||
target: "https://api.openai.com",
|
||||
@@ -146,6 +287,13 @@ const openaiEmbeddingsProxy = createQueuedProxyMiddleware({
|
||||
target: "https://api.openai.com",
|
||||
});
|
||||
|
||||
// New proxy middleware for the Responses API
|
||||
const openaiResponsesProxy = createQueuedProxyMiddleware({
|
||||
mutations: [addKey, finalizeBody],
|
||||
target: "https://api.openai.com",
|
||||
blockingResponseHandler: openaiResponseHandler,
|
||||
});
|
||||
|
||||
const openaiRouter = Router();
|
||||
openaiRouter.get("/v1/models", handleModelRequest);
|
||||
// Native text completion endpoint, only for turbo-instruct.
|
||||
@@ -172,16 +320,120 @@ openaiRouter.post(
|
||||
),
|
||||
openaiProxy
|
||||
);
|
||||
|
||||
const setupChunkedTransfer: RequestHandler = (req, res, next) => {
|
||||
req.log.info("Setting chunked transfer for o1 to prevent Cloudflare timeouts")
|
||||
|
||||
// Check if user is trying to use streaming with codex-mini models
|
||||
if (req.body.model?.startsWith("codex-mini") && req.body.stream === true) {
|
||||
return res.status(400).json({
|
||||
error: {
|
||||
message: "The codex-mini models do not support streaming. Please set 'stream: false' in your request.",
|
||||
type: "invalid_request_error",
|
||||
param: "stream",
|
||||
code: "streaming_not_supported"
|
||||
}
|
||||
});
|
||||
}
|
||||
|
||||
// Only o1 doesn't support streaming
|
||||
if (req.body.model === "o1" || req.body.model === "o1-2024-12-17") {
|
||||
req.isChunkedTransfer = true;
|
||||
res.writeHead(200, {
|
||||
'Content-Type': 'application/json',
|
||||
'Transfer-Encoding': 'chunked'
|
||||
});
|
||||
|
||||
// Higher values are required - otherwise Cloudflare will buffer and not pass
|
||||
// the separate chunks, which means that a >100s response will get terminated anyway
|
||||
const keepAlive = setInterval(() => {
|
||||
res.write(' '.repeat(4096));
|
||||
}, 48_000);
|
||||
|
||||
(req as any)._keepAliveInterval = keepAlive;
|
||||
}
|
||||
next();
|
||||
};
|
||||
|
||||
// Functions to handle model-specific API routing
|
||||
function shouldUseResponsesApi(model: string): boolean {
|
||||
return model === "o1-pro" || model.startsWith("o1-pro-") ||
|
||||
model === "o3-pro" || model.startsWith("o3-pro-") ||
|
||||
model === "codex-mini-latest" || model.startsWith("codex-mini-");
|
||||
}
|
||||
|
||||
// Preprocessor to redirect requests to the responses API
|
||||
const routeToResponsesApi: RequestPreprocessor = (req) => {
|
||||
if (shouldUseResponsesApi(req.body.model)) {
|
||||
req.log.info(`Routing ${req.body.model} to OpenAI Responses API`);
|
||||
req.url = "/v1/responses";
|
||||
req.outboundApi = "openai-responses";
|
||||
}
|
||||
};
|
||||
|
||||
// General chat completion endpoint. Turbo-instruct is not supported here.
|
||||
openaiRouter.post(
|
||||
"/v1/chat/completions",
|
||||
ipLimiter,
|
||||
createPreprocessorMiddleware(
|
||||
{ inApi: "openai", outApi: "openai", service: "openai" },
|
||||
{ afterTransform: [fixupMaxTokens] }
|
||||
{
|
||||
afterTransform: [
|
||||
fixupMaxTokens,
|
||||
filterGPT5UnsupportedParams,
|
||||
routeToResponsesApi
|
||||
]
|
||||
}
|
||||
),
|
||||
setupChunkedTransfer,
|
||||
(req, _res, next) => {
|
||||
// Route to the responses endpoint if needed
|
||||
if (req.outboundApi === "openai-responses") {
|
||||
// Ensure messages is moved to input properly
|
||||
req.log.info("Final check for Responses API format in chat completions");
|
||||
if (req.body.messages) {
|
||||
req.log.info("Moving 'messages' to 'input' for Responses API");
|
||||
req.body.input = req.body.messages;
|
||||
delete req.body.messages;
|
||||
} else if (req.body.input && req.body.input.messages) {
|
||||
req.log.info("Reformatting input.messages for Responses API");
|
||||
req.body.input = req.body.input.messages;
|
||||
}
|
||||
|
||||
return openaiResponsesProxy(req, _res, next);
|
||||
}
|
||||
next();
|
||||
},
|
||||
openaiProxy
|
||||
);
|
||||
|
||||
// New endpoint for OpenAI Responses API
|
||||
openaiRouter.post(
|
||||
"/v1/responses",
|
||||
ipLimiter,
|
||||
createPreprocessorMiddleware(
|
||||
{ inApi: "openai", outApi: "openai-responses", service: "openai" },
|
||||
{ afterTransform: [fixupMaxTokens, filterGPT5UnsupportedParams] }
|
||||
),
|
||||
// Add final check to ensure the body is in the correct format for Responses API
|
||||
(req, _res, next) => {
|
||||
req.log.info("Final check for Responses API format");
|
||||
|
||||
// Ensure messages is properly formatted for input
|
||||
if (req.body.messages) {
|
||||
req.log.info("Moving 'messages' to 'input' for Responses API");
|
||||
req.body.input = req.body.messages;
|
||||
delete req.body.messages;
|
||||
} else if (req.body.input && req.body.input.messages) {
|
||||
req.log.info("Reformatting input.messages for Responses API");
|
||||
req.body.input = req.body.input.messages;
|
||||
}
|
||||
|
||||
next();
|
||||
},
|
||||
openaiResponsesProxy
|
||||
);
|
||||
|
||||
// Embeddings endpoint.
|
||||
openaiRouter.post(
|
||||
"/v1/embeddings",
|
||||
@@ -195,10 +447,52 @@ function forceModel(model: string): RequestPreprocessor {
|
||||
}
|
||||
|
||||
function fixupMaxTokens(req: Request) {
|
||||
if (!req.body.max_completion_tokens) {
|
||||
req.body.max_completion_tokens = req.body.max_tokens;
|
||||
// For Responses API, use max_output_tokens instead of max_completion_tokens
|
||||
if (req.outboundApi === "openai-responses") {
|
||||
if (!req.body.max_output_tokens) {
|
||||
req.body.max_output_tokens = req.body.max_tokens || req.body.max_completion_tokens;
|
||||
}
|
||||
// Remove the other token params to avoid API errors
|
||||
delete req.body.max_tokens;
|
||||
delete req.body.max_completion_tokens;
|
||||
|
||||
// Remove other parameters not supported by Responses API
|
||||
const unsupportedParams = ['frequency_penalty', 'presence_penalty'];
|
||||
for (const param of unsupportedParams) {
|
||||
if (req.body[param] !== undefined) {
|
||||
req.log.info(`Removing unsupported parameter for Responses API: ${param}`);
|
||||
delete req.body[param];
|
||||
}
|
||||
}
|
||||
} else {
|
||||
// Original behavior for other APIs
|
||||
if (!req.body.max_completion_tokens) {
|
||||
req.body.max_completion_tokens = req.body.max_tokens;
|
||||
}
|
||||
delete req.body.max_tokens;
|
||||
}
|
||||
}
|
||||
|
||||
// GPT-5, GPT-5-mini, and GPT-5-nano don't support certain parameters
|
||||
// Remove them if present to prevent API errors
|
||||
function filterGPT5UnsupportedParams(req: Request) {
|
||||
const model = req.body.model;
|
||||
|
||||
// Only apply filtering to these specific models (gpt5-chat-latest supports all params)
|
||||
const restrictedModels = /^gpt-5(-mini|-nano)?(-\d{4}-\d{2}-\d{2})?$/;
|
||||
|
||||
if (!restrictedModels.test(model)) {
|
||||
return; // Not a restricted model, no filtering needed
|
||||
}
|
||||
|
||||
// Remove unsupported parameters if they exist
|
||||
const unsupportedParams = ['temperature', 'top_p', 'presence_penalty', 'frequency_penalty'];
|
||||
|
||||
for (const param of unsupportedParams) {
|
||||
if (req.body[param] !== undefined) {
|
||||
delete req.body[param];
|
||||
}
|
||||
}
|
||||
delete req.body.max_tokens;
|
||||
}
|
||||
|
||||
export const openai = openaiRouter;
|
||||
|
||||
+2
-2
@@ -77,8 +77,8 @@ async function enqueue(req: Request) {
|
||||
}
|
||||
|
||||
const enqueuedRequestCount = queue.filter(sharesIdentifierWith(req)).length;
|
||||
|
||||
if (enqueuedRequestCount >= USER_CONCURRENCY_LIMIT) {
|
||||
// Do not apply concurrency limit to "special" users
|
||||
if (enqueuedRequestCount >= USER_CONCURRENCY_LIMIT && req.user?.type !== "special") {
|
||||
throw new TooManyRequestsError(
|
||||
"Your IP or user token already has another request in the queue."
|
||||
);
|
||||
|
||||
@@ -0,0 +1,361 @@
|
||||
import { Request, RequestHandler, Router } from "express";
|
||||
import { createPreprocessorMiddleware } from "./middleware/request";
|
||||
import { ipLimiter } from "./rate-limit";
|
||||
import { createQueuedProxyMiddleware } from "./middleware/request/proxy-middleware-factory";
|
||||
import { addKey, finalizeBody } from "./middleware/request";
|
||||
import { ProxyResHandlerWithBody } from "./middleware/response";
|
||||
import axios from "axios";
|
||||
import { QwenKey, keyPool } from "../shared/key-management";
|
||||
import {
|
||||
isQwenModel,
|
||||
isQwenThinkingModel,
|
||||
normalizeMessages,
|
||||
isQwen3Model,
|
||||
isThinkingVariant,
|
||||
isNonThinkingVariant,
|
||||
getBaseModelName
|
||||
} from "../shared/api-schemas/qwen";
|
||||
import { logger } from "../logger";
|
||||
|
||||
const log = logger.child({ module: "proxy", service: "qwen" });
|
||||
let modelsCache: any = null;
|
||||
let modelsCacheTime = 0;
|
||||
|
||||
const qwenResponseHandler: ProxyResHandlerWithBody = async (
|
||||
_proxyRes,
|
||||
req,
|
||||
res,
|
||||
body
|
||||
) => {
|
||||
if (typeof body !== "object") {
|
||||
throw new Error("Expected body to be an object");
|
||||
}
|
||||
|
||||
res.status(200).json({ ...body, proxy: body.proxy });
|
||||
};
|
||||
|
||||
const getModelsResponse = async () => {
|
||||
// Return cache if less than 1 minute old
|
||||
if (new Date().getTime() - modelsCacheTime < 1000 * 60) {
|
||||
return modelsCache;
|
||||
}
|
||||
|
||||
try {
|
||||
// Get a Qwen key directly
|
||||
const modelToUse = "qwen-plus"; // Use any Qwen model here - just for key selection
|
||||
const qwenKey = keyPool.get(modelToUse, "qwen") as QwenKey;
|
||||
|
||||
if (!qwenKey || !qwenKey.key) {
|
||||
log.warn("No valid Qwen key available for model listing");
|
||||
throw new Error("No valid Qwen API key available");
|
||||
}
|
||||
|
||||
// Fetch models directly from Qwen API
|
||||
const response = await axios.get("https://dashscope-intl.aliyuncs.com/compatible-mode/v1/models", {
|
||||
headers: {
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": `Bearer ${qwenKey.key}`
|
||||
},
|
||||
});
|
||||
|
||||
if (!response.data || !response.data.data) {
|
||||
throw new Error("Unexpected response format from Qwen API");
|
||||
}
|
||||
|
||||
// Extract models
|
||||
const models = response.data;
|
||||
|
||||
// Ensure we have all known Qwen models in the list
|
||||
const knownQwenModels = [
|
||||
"qwen-max",
|
||||
"qwen-max-latest",
|
||||
"qwen-max-2025-01-25",
|
||||
"qwen-plus",
|
||||
"qwen-plus-latest",
|
||||
"qwen-plus-2025-01-25",
|
||||
"qwen-turbo",
|
||||
"qwen-turbo-latest",
|
||||
"qwen-turbo-2024-11-01",
|
||||
"qwen3-235b-a22b",
|
||||
"qwen3-32b",
|
||||
"qwen3-30b-a3b"
|
||||
];
|
||||
|
||||
// Add thinking capability flag to models that support it
|
||||
if (models.data && Array.isArray(models.data)) {
|
||||
// Create a set of existing model IDs for quick lookup
|
||||
const existingModelIds = new Set(models.data.map((model: any) => model.id));
|
||||
|
||||
// Filter out base Qwen3 models since we'll add variants instead
|
||||
models.data = models.data.filter((model: any) => {
|
||||
return !isQwen3Model(model.id) || isThinkingVariant(model.id) || isNonThinkingVariant(model.id);
|
||||
});
|
||||
|
||||
// Add any missing models from our known list
|
||||
knownQwenModels.forEach(modelId => {
|
||||
if (!existingModelIds.has(modelId)) {
|
||||
models.data.push({
|
||||
id: modelId,
|
||||
object: "model",
|
||||
created: Date.now(),
|
||||
owned_by: "qwen",
|
||||
capabilities: isQwenThinkingModel(modelId) ? { thinking: true } : {}
|
||||
});
|
||||
}
|
||||
});
|
||||
|
||||
// Add thinking capability flag to existing models
|
||||
const processedModelIds = new Set();
|
||||
const originalModelsData = [...models.data];
|
||||
|
||||
models.data = originalModelsData.flatMap((model: any) => {
|
||||
const modelId = model.id;
|
||||
processedModelIds.add(modelId);
|
||||
|
||||
// Apply capabilities to all models
|
||||
if (isQwenThinkingModel(modelId)) {
|
||||
model.capabilities = model.capabilities || {};
|
||||
model.capabilities.thinking = true;
|
||||
}
|
||||
|
||||
// For Qwen3 models, add thinking and non-thinking variants, but not the original
|
||||
if (isQwen3Model(modelId) &&
|
||||
!isThinkingVariant(modelId) &&
|
||||
!isNonThinkingVariant(modelId)) {
|
||||
|
||||
// Create thinking variant
|
||||
const thinkingModel = {
|
||||
id: `${modelId}-thinking`,
|
||||
object: "model",
|
||||
created: model.created || Date.now(),
|
||||
owned_by: model.owned_by || "qwen",
|
||||
capabilities: { thinking: true },
|
||||
proxy_managed: true,
|
||||
display_name: `${model.display_name || modelId} (Thinking Mode)`
|
||||
};
|
||||
|
||||
// Create non-thinking variant
|
||||
const nonThinkingModel = {
|
||||
id: `${modelId}-nonthinking`,
|
||||
object: "model",
|
||||
created: model.created || Date.now(),
|
||||
owned_by: model.owned_by || "qwen",
|
||||
capabilities: { thinking: true },
|
||||
proxy_managed: true,
|
||||
display_name: `${model.display_name || modelId} (Standard Mode)`
|
||||
};
|
||||
|
||||
// Only add variants, not the original model
|
||||
return [thinkingModel, nonThinkingModel];
|
||||
}
|
||||
|
||||
return [model];
|
||||
});
|
||||
} else {
|
||||
// If the API response didn't include models, create our own list
|
||||
models.data = knownQwenModels.flatMap(modelId => {
|
||||
// For Qwen3 models, add only thinking and non-thinking variants (not the base model)
|
||||
if (isQwen3Model(modelId) &&
|
||||
!isThinkingVariant(modelId) &&
|
||||
!isNonThinkingVariant(modelId)) {
|
||||
|
||||
return [
|
||||
{
|
||||
id: `${modelId}-thinking`,
|
||||
object: "model",
|
||||
created: Date.now(),
|
||||
owned_by: "qwen",
|
||||
capabilities: { thinking: true },
|
||||
proxy_managed: true,
|
||||
display_name: `${modelId} (Thinking Mode)`
|
||||
},
|
||||
{
|
||||
id: `${modelId}-nonthinking`,
|
||||
object: "model",
|
||||
created: Date.now(),
|
||||
owned_by: "qwen",
|
||||
capabilities: { thinking: true },
|
||||
proxy_managed: true,
|
||||
display_name: `${modelId} (Standard Mode)`
|
||||
}
|
||||
];
|
||||
}
|
||||
|
||||
// For non-Qwen3 models, return the base model
|
||||
const baseModel = {
|
||||
id: modelId,
|
||||
object: "model",
|
||||
created: Date.now(),
|
||||
owned_by: "qwen",
|
||||
capabilities: isQwenThinkingModel(modelId) ? { thinking: true } : {}
|
||||
};
|
||||
|
||||
return [baseModel];
|
||||
});
|
||||
}
|
||||
|
||||
log.debug({ modelCount: models.data?.length }, "Retrieved models from Qwen API");
|
||||
|
||||
// Cache the response
|
||||
modelsCache = models;
|
||||
modelsCacheTime = new Date().getTime();
|
||||
return models;
|
||||
} catch (error) {
|
||||
// Provide detailed logging for better troubleshooting
|
||||
if (error instanceof Error) {
|
||||
log.error(
|
||||
{ errorMessage: error.message, stack: error.stack },
|
||||
"Error fetching Qwen models"
|
||||
);
|
||||
} else {
|
||||
log.error({ error }, "Unknown error fetching Qwen models");
|
||||
}
|
||||
|
||||
// Return empty list as fallback
|
||||
return {
|
||||
object: "list",
|
||||
data: [],
|
||||
};
|
||||
}
|
||||
};
|
||||
|
||||
const handleModelRequest: RequestHandler = async (_req, res) => {
|
||||
try {
|
||||
const models = await getModelsResponse();
|
||||
res.status(200).json(models);
|
||||
} catch (error) {
|
||||
if (error instanceof Error) {
|
||||
log.error(
|
||||
{ errorMessage: error.message, stack: error.stack },
|
||||
"Error handling model request"
|
||||
);
|
||||
} else {
|
||||
log.error({ error }, "Unknown error handling model request");
|
||||
}
|
||||
res.status(500).json({ error: "Failed to fetch models" });
|
||||
}
|
||||
};
|
||||
|
||||
// Function to prepare messages for Qwen API
|
||||
function prepareMessages(req: Request) {
|
||||
if (req.body.messages && Array.isArray(req.body.messages)) {
|
||||
req.body.messages = normalizeMessages(req.body.messages);
|
||||
}
|
||||
}
|
||||
|
||||
// Function to handle thinking capability for Qwen models
|
||||
function handleThinkingCapability(req: Request) {
|
||||
const model = req.body.model;
|
||||
|
||||
// Special handling for our proxy-managed variants
|
||||
if (isThinkingVariant(model)) {
|
||||
// Set the base model name without the suffix
|
||||
req.body.model = getBaseModelName(model);
|
||||
// Force enable thinking for the -thinking variant
|
||||
req.body.enable_thinking = true;
|
||||
|
||||
// Log the transformation
|
||||
log.debug(
|
||||
{ originalModel: model, transformedModel: req.body.model, enableThinking: true },
|
||||
"Transformed request for thinking variant"
|
||||
);
|
||||
return;
|
||||
}
|
||||
|
||||
if (isNonThinkingVariant(model)) {
|
||||
// Set the base model name without the suffix
|
||||
req.body.model = getBaseModelName(model);
|
||||
// Force disable thinking for the -nonthinking variant
|
||||
req.body.enable_thinking = false;
|
||||
|
||||
// Log the transformation
|
||||
log.debug(
|
||||
{ originalModel: model, transformedModel: req.body.model, enableThinking: false },
|
||||
"Transformed request for non-thinking variant"
|
||||
);
|
||||
return;
|
||||
}
|
||||
|
||||
// For standard models with thinking capability
|
||||
if (isQwenThinkingModel(model) && req.body.stream === true) {
|
||||
// Only add enable_thinking if it's not already set
|
||||
if (req.body.enable_thinking === undefined) {
|
||||
req.body.enable_thinking = false; // Default to false, let users explicitly enable it
|
||||
}
|
||||
|
||||
// If thinking_budget is provided but enable_thinking is false, enable thinking
|
||||
if (req.body.thinking_budget !== undefined && req.body.enable_thinking === false) {
|
||||
req.body.enable_thinking = true;
|
||||
}
|
||||
} else if (isQwenThinkingModel(model) && req.body.stream !== true) {
|
||||
// For non-streaming requests with thinking-capable models, always disable thinking
|
||||
req.body.enable_thinking = false;
|
||||
}
|
||||
}
|
||||
|
||||
// Function to remove parameters not supported by Qwen models
|
||||
function removeUnsupportedParameters(req: Request) {
|
||||
// Remove parameters that Qwen doesn't support
|
||||
if (req.body.logit_bias !== undefined) {
|
||||
delete req.body.logit_bias;
|
||||
}
|
||||
|
||||
if (req.body.top_logprobs !== undefined) {
|
||||
delete req.body.top_logprobs;
|
||||
}
|
||||
|
||||
// Logging for debugging
|
||||
if (process.env.NODE_ENV !== 'production') {
|
||||
log.debug({ body: req.body }, "Request after parameter cleanup");
|
||||
}
|
||||
}
|
||||
|
||||
// Set up count token functionality for Qwen models
|
||||
function countQwenTokens(req: Request) {
|
||||
const model = req.body.model;
|
||||
|
||||
if (isQwenModel(model)) {
|
||||
// Count tokens using prompt tokens (simplified)
|
||||
if (req.promptTokens) {
|
||||
req.log.debug(
|
||||
{ tokens: req.promptTokens },
|
||||
"Estimated token count for Qwen prompt"
|
||||
);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
const qwenProxy = createQueuedProxyMiddleware({
|
||||
mutations: [
|
||||
addKey,
|
||||
finalizeBody
|
||||
],
|
||||
target: "https://dashscope-intl.aliyuncs.com/compatible-mode",
|
||||
blockingResponseHandler: qwenResponseHandler,
|
||||
});
|
||||
|
||||
const qwenRouter = Router();
|
||||
|
||||
qwenRouter.post(
|
||||
"/v1/chat/completions",
|
||||
ipLimiter,
|
||||
createPreprocessorMiddleware(
|
||||
{ inApi: "openai", outApi: "openai", service: "qwen" },
|
||||
{ afterTransform: [ prepareMessages, handleThinkingCapability, removeUnsupportedParameters, countQwenTokens ] }
|
||||
),
|
||||
qwenProxy
|
||||
);
|
||||
|
||||
qwenRouter.post(
|
||||
"/v1/embeddings",
|
||||
ipLimiter,
|
||||
createPreprocessorMiddleware(
|
||||
{ inApi: "openai", outApi: "openai", service: "qwen" },
|
||||
{ afterTransform: [] }
|
||||
),
|
||||
qwenProxy
|
||||
);
|
||||
|
||||
qwenRouter.get("/v1/models", handleModelRequest);
|
||||
|
||||
export const qwen = qwenRouter;
|
||||
@@ -10,6 +10,11 @@ import { googleAI } from "./google-ai";
|
||||
import { mistralAI } from "./mistral-ai";
|
||||
import { openai } from "./openai";
|
||||
import { openaiImage } from "./openai-image";
|
||||
import { deepseek } from "./deepseek";
|
||||
import { xai } from "./xai";
|
||||
import { cohere } from "./cohere";
|
||||
import { qwen } from "./qwen";
|
||||
import { moonshot } from "./moonshot";
|
||||
import { sendErrorToClient } from "./middleware/response/error-generator";
|
||||
|
||||
const proxyRouter = express.Router();
|
||||
@@ -49,6 +54,11 @@ proxyRouter.use("/mistral-ai", addV1, mistralAI);
|
||||
proxyRouter.use("/aws", aws);
|
||||
proxyRouter.use("/gcp/claude", addV1, gcp);
|
||||
proxyRouter.use("/azure/openai", addV1, azure);
|
||||
proxyRouter.use("/deepseek", addV1, deepseek);
|
||||
proxyRouter.use("/xai", addV1, xai);
|
||||
proxyRouter.use("/cohere", addV1, cohere);
|
||||
proxyRouter.use("/qwen", addV1, qwen);
|
||||
proxyRouter.use("/moonshot", addV1, moonshot);
|
||||
|
||||
// Redirect browser requests to the homepage.
|
||||
proxyRouter.get("*", (req, res, next) => {
|
||||
|
||||
@@ -0,0 +1,394 @@
|
||||
import { Request, RequestHandler, Router } from "express";
|
||||
import { createPreprocessorMiddleware } from "./middleware/request";
|
||||
import { ipLimiter } from "./rate-limit";
|
||||
import { createQueuedProxyMiddleware } from "./middleware/request/proxy-middleware-factory";
|
||||
import { addKey, finalizeBody } from "./middleware/request";
|
||||
import { ProxyResHandlerWithBody } from "./middleware/response";
|
||||
import axios from "axios";
|
||||
import { XaiKey, keyPool } from "../shared/key-management";
|
||||
import { isGrokVisionModel, isGrokImageGenModel, isGrokReasoningModel, isGrokReasoningEffortModel, isGrokReasoningContentModel } from "../shared/api-schemas/xai";
|
||||
|
||||
let modelsCache: any = null;
|
||||
let modelsCacheTime = 0;
|
||||
|
||||
const xaiResponseHandler: ProxyResHandlerWithBody = async (
|
||||
_proxyRes,
|
||||
req,
|
||||
res,
|
||||
body
|
||||
) => {
|
||||
if (typeof body !== "object") {
|
||||
throw new Error("Expected body to be an object");
|
||||
}
|
||||
|
||||
// Preserve the original body (including potential reasoning_content) for grok-3-mini models
|
||||
// which support the reasoning feature
|
||||
let newBody = body;
|
||||
|
||||
// Check if this is an image generation response (data array with url or b64_json)
|
||||
if (body.data && Array.isArray(body.data)) {
|
||||
req.log.debug(
|
||||
{ imageCount: body.data.length },
|
||||
"Grok image generation response detected"
|
||||
);
|
||||
|
||||
// Transform the image generation response into a chat completion format
|
||||
// that SillyTavern can display
|
||||
const images = body.data;
|
||||
|
||||
// Create a chat completion style response
|
||||
newBody = {
|
||||
id: `grok-image-${Date.now()}`,
|
||||
object: "chat.completion",
|
||||
created: Math.floor(Date.now() / 1000),
|
||||
model: req.body.model,
|
||||
choices: images.map((image, index) => {
|
||||
// Create markdown image content for each generated image
|
||||
let content = '';
|
||||
|
||||
// Add the image using data URL for b64_json
|
||||
if (image.b64_json) {
|
||||
// If it doesn't start with data:image/, add the prefix
|
||||
const imgData = image.b64_json.startsWith('data:image/')
|
||||
? image.b64_json
|
||||
: `data:image/jpeg;base64,${image.b64_json}`;
|
||||
|
||||
content = ``;
|
||||
}
|
||||
// Fall back to URL if b64_json isn't available
|
||||
else if (image.url) {
|
||||
content = ``;
|
||||
}
|
||||
|
||||
return {
|
||||
index,
|
||||
message: {
|
||||
role: "assistant",
|
||||
content
|
||||
},
|
||||
finish_reason: "stop"
|
||||
};
|
||||
}),
|
||||
usage: body.usage || { prompt_tokens: 0, completion_tokens: 0, total_tokens: 0 }
|
||||
};
|
||||
|
||||
req.log.debug("Transformed image generation response to chat format");
|
||||
}
|
||||
// Check if this is a chat completion response with choices
|
||||
else if (body.choices && Array.isArray(body.choices) && body.choices.length > 0) {
|
||||
// Make sure each choice's message is preserved, especially reasoning_content
|
||||
// Only grok-3-mini models return reasoning_content
|
||||
const model = req.body.model;
|
||||
if (isGrokReasoningContentModel(model)) {
|
||||
body.choices.forEach(choice => {
|
||||
if (choice.message && choice.message.reasoning_content) {
|
||||
req.log.debug(
|
||||
{ reasoning_length: choice.message.reasoning_content.length },
|
||||
"Grok reasoning content detected"
|
||||
);
|
||||
}
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
res.status(200).json({ ...newBody, proxy: body.proxy });
|
||||
};
|
||||
|
||||
const getModelsResponse = async () => {
|
||||
// Return cache if less than 1 minute old
|
||||
if (new Date().getTime() - modelsCacheTime < 1000 * 60) {
|
||||
return modelsCache;
|
||||
}
|
||||
|
||||
try {
|
||||
// Get an XAI key directly using keyPool.get()
|
||||
const modelToUse = "grok-3"; // Use any XAI model here - just for key selection
|
||||
const xaiKey = keyPool.get(modelToUse, "xai") as XaiKey;
|
||||
|
||||
if (!xaiKey || !xaiKey.key) {
|
||||
throw new Error("Failed to get valid XAI key");
|
||||
}
|
||||
|
||||
// Fetch models from XAI API with authorization
|
||||
const response = await axios.get("https://api.x.ai/v1/models", {
|
||||
headers: {
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": `Bearer ${xaiKey.key}`
|
||||
},
|
||||
});
|
||||
|
||||
// If successful, update the cache
|
||||
if (response.data && response.data.data) {
|
||||
modelsCache = {
|
||||
object: "list",
|
||||
data: response.data.data.map((model: any) => ({
|
||||
id: model.id,
|
||||
object: "model",
|
||||
owned_by: "xai",
|
||||
})),
|
||||
};
|
||||
} else {
|
||||
throw new Error("Unexpected response format from XAI API");
|
||||
}
|
||||
} catch (error) {
|
||||
console.error("Error fetching XAI models:", error);
|
||||
throw error; // No fallback - error will be passed to caller
|
||||
}
|
||||
|
||||
modelsCacheTime = new Date().getTime();
|
||||
return modelsCache;
|
||||
};
|
||||
|
||||
const handleModelRequest: RequestHandler = async (_req, res) => {
|
||||
try {
|
||||
const modelsResponse = await getModelsResponse();
|
||||
res.status(200).json(modelsResponse);
|
||||
} catch (error) {
|
||||
console.error("Error in handleModelRequest:", error);
|
||||
res.status(500).json({ error: "Failed to fetch models" });
|
||||
}
|
||||
};
|
||||
|
||||
const xaiProxy = createQueuedProxyMiddleware({
|
||||
mutations: [addKey, finalizeBody],
|
||||
target: "https://api.x.ai",
|
||||
blockingResponseHandler: xaiResponseHandler,
|
||||
});
|
||||
|
||||
const xaiRouter = Router();
|
||||
|
||||
// combines all the assistant messages at the end of the context and adds the
|
||||
// beta 'prefix' option, makes prefills work the same way they work for Claude
|
||||
function enablePrefill(req: Request) {
|
||||
// If you want to disable
|
||||
if (process.env.NO_XAI_PREFILL) return
|
||||
|
||||
// Skip if no messages (e.g., for image generation requests)
|
||||
if (!req.body.messages || !Array.isArray(req.body.messages)) return;
|
||||
|
||||
const msgs = req.body.messages;
|
||||
if (msgs.length === 0 || msgs.at(-1)?.role !== 'assistant') return;
|
||||
|
||||
let i = msgs.length - 1;
|
||||
let content = '';
|
||||
|
||||
while (i >= 0 && msgs[i].role === 'assistant') {
|
||||
// maybe we should also add a newline between messages? no for now.
|
||||
content = msgs[i--].content + content;
|
||||
}
|
||||
|
||||
msgs.splice(i + 1, msgs.length, { role: 'assistant', content, prefix: true });
|
||||
}
|
||||
|
||||
// Function to redirect image model requests to the image generations endpoint
|
||||
function redirectImageRequests(req: Request) {
|
||||
const model = req.body.model;
|
||||
|
||||
// If this is an image generation model but the endpoint is chat/completions,
|
||||
// we need to transform the request to match the image generations endpoint format
|
||||
if (isGrokImageGenModel(model) && req.path === "/v1/chat/completions") {
|
||||
req.log.info(`Redirecting ${model} request to /v1/images/generations endpoint`);
|
||||
|
||||
// Save original URL and path for later
|
||||
const originalUrl = req.url;
|
||||
const originalPath = req.path;
|
||||
|
||||
// Change the request URL and path to the images endpoint
|
||||
req.url = req.url.replace("/v1/chat/completions", "/v1/images/generations");
|
||||
Object.defineProperty(req, 'path', { value: "/v1/images/generations" });
|
||||
|
||||
// Extract the prompt from the messages if present
|
||||
if (req.body.messages && Array.isArray(req.body.messages)) {
|
||||
// Find the last user message and use its content as the prompt
|
||||
for (let i = req.body.messages.length - 1; i >= 0; i--) {
|
||||
const msg = req.body.messages[i];
|
||||
if (msg.role === 'user') {
|
||||
// Extract text content
|
||||
let prompt = "";
|
||||
if (typeof msg.content === 'string') {
|
||||
prompt = msg.content;
|
||||
} else if (Array.isArray(msg.content)) {
|
||||
// Collect all text content items
|
||||
prompt = msg.content
|
||||
.filter((item: any) => item.type === 'text')
|
||||
.map((item: any) => item.text)
|
||||
.join(" ");
|
||||
}
|
||||
|
||||
if (prompt) {
|
||||
// Create a new request body for image generation
|
||||
req.body = {
|
||||
model: model,
|
||||
prompt: prompt,
|
||||
n: req.body.n || 1,
|
||||
response_format: "b64_json", // Always use b64_json for better client compatibility
|
||||
user: req.body.user
|
||||
};
|
||||
req.log.debug({ newBody: req.body }, "Transformed request for image generation");
|
||||
break;
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Log transformation
|
||||
req.log.info(`Request transformed from ${originalUrl} to ${req.url}`);
|
||||
}
|
||||
}
|
||||
|
||||
// Function to remove parameters not supported by X.AI/Grok models and handle special cases
|
||||
function removeUnsupportedParameters(req: Request) {
|
||||
const model = req.body.model;
|
||||
|
||||
// Check if this is a reasoning model (grok-3-mini or grok-4-0709)
|
||||
const isReasoningModel = isGrokReasoningModel(model);
|
||||
const isReasoningEffortModel = isGrokReasoningEffortModel(model);
|
||||
|
||||
if (isReasoningModel) {
|
||||
// List of parameters not supported by reasoning models
|
||||
const unsupportedParams = [
|
||||
'presence_penalty',
|
||||
'frequency_penalty',
|
||||
'stop' // stop parameter is not supported by reasoning models
|
||||
];
|
||||
|
||||
for (const param of unsupportedParams) {
|
||||
if (req.body[param] !== undefined) {
|
||||
req.log.info(`Removing unsupported parameter for reasoning model ${model}: ${param}`);
|
||||
delete req.body[param];
|
||||
}
|
||||
}
|
||||
|
||||
// Handle reasoning_effort parameter - only supported by grok-3-mini
|
||||
if (isReasoningEffortModel) {
|
||||
// This is grok-3-mini, handle reasoning_effort
|
||||
if (req.body.reasoning_effort) {
|
||||
// If reasoning_effort is already present in the request, validate it
|
||||
if (!['low', 'medium', 'high'].includes(req.body.reasoning_effort)) {
|
||||
req.log.warn(`Invalid reasoning_effort value: ${req.body.reasoning_effort}, removing it`);
|
||||
delete req.body.reasoning_effort;
|
||||
}
|
||||
} else {
|
||||
// Default to low reasoning effort if not specified
|
||||
req.body.reasoning_effort = 'low';
|
||||
req.log.debug(`Setting default reasoning_effort=low for Grok-3-mini model`);
|
||||
}
|
||||
} else {
|
||||
// This is grok-4-0709 or other reasoning model that doesn't support reasoning_effort
|
||||
if (req.body.reasoning_effort !== undefined) {
|
||||
req.log.info(`Removing unsupported reasoning_effort parameter for model ${model}`);
|
||||
delete req.body.reasoning_effort;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Special handling for vision models
|
||||
if (isGrokVisionModel(model)) {
|
||||
req.log.debug(`Detected Grok vision model: ${model}`);
|
||||
|
||||
// Check that messages have proper format for vision models
|
||||
if (req.body.messages && Array.isArray(req.body.messages)) {
|
||||
req.body.messages.forEach((msg: { content: string | any[] }) => {
|
||||
// If content is a string but the model is vision-capable,
|
||||
// convert it to an array with a single text item for consistency
|
||||
if (typeof msg.content === 'string') {
|
||||
req.log.debug('Converting string content to array format for vision model');
|
||||
msg.content = [{ type: 'text', text: msg.content }];
|
||||
}
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
// Special handling for image generation models is handled by separate endpoint
|
||||
}
|
||||
|
||||
// Handler for image generation requests
|
||||
const handleImageGenerationRequest: RequestHandler = async (req, res) => {
|
||||
try {
|
||||
// Get an XAI key directly for image generation
|
||||
const modelToUse = req.body.model || "grok-2-image"; // Default model
|
||||
const xaiKey = keyPool.get(modelToUse, "xai") as XaiKey;
|
||||
|
||||
if (!xaiKey || !xaiKey.key) {
|
||||
throw new Error("Failed to get valid XAI key for image generation");
|
||||
}
|
||||
|
||||
// Forward the request to XAI API
|
||||
const response = await axios.post("https://api.x.ai/v1/images/generations", req.body, {
|
||||
headers: {
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": `Bearer ${xaiKey.key}`
|
||||
},
|
||||
});
|
||||
|
||||
// Return the response directly
|
||||
res.status(200).json(response.data);
|
||||
} catch (error) {
|
||||
req.log.error({ error }, "Error in image generation request");
|
||||
// Pass through the error response if available
|
||||
if (error.response && error.response.data) {
|
||||
res.status(error.response.status || 500).json(error.response.data);
|
||||
} else {
|
||||
res.status(500).json({ error: "Failed to generate image", message: error.message });
|
||||
}
|
||||
}
|
||||
};
|
||||
|
||||
// Set up count token functionality for XAI models
|
||||
function countXaiTokens(req: Request) {
|
||||
const model = req.body.model;
|
||||
|
||||
// For vision models, estimate image token usage
|
||||
if (isGrokVisionModel(model) && req.body.messages && Array.isArray(req.body.messages)) {
|
||||
// Initialize image count
|
||||
let imageCount = 0;
|
||||
|
||||
// Count images in the request
|
||||
for (const msg of req.body.messages) {
|
||||
if (Array.isArray(msg.content)) {
|
||||
const imagesInMessage = msg.content.filter(
|
||||
(item: any) => item.type === "image_url"
|
||||
).length;
|
||||
imageCount += imagesInMessage;
|
||||
}
|
||||
}
|
||||
|
||||
// Apply token estimations for images
|
||||
// Each image is approximately 1500 tokens based on documentation
|
||||
const TOKENS_PER_IMAGE = 1500;
|
||||
const imageTokens = imageCount * TOKENS_PER_IMAGE;
|
||||
|
||||
if (imageTokens > 0) {
|
||||
req.log.debug(
|
||||
{ imageCount, tokenEstimate: imageTokens },
|
||||
"Estimated token count for Grok vision images"
|
||||
);
|
||||
|
||||
// Add the image tokens to the existing token count if available
|
||||
if (req.promptTokens) {
|
||||
req.promptTokens += imageTokens;
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
xaiRouter.post(
|
||||
"/v1/chat/completions",
|
||||
ipLimiter,
|
||||
createPreprocessorMiddleware(
|
||||
{ inApi: "openai", outApi: "openai", service: "xai" },
|
||||
{ afterTransform: [ redirectImageRequests, enablePrefill, removeUnsupportedParameters, countXaiTokens ] }
|
||||
),
|
||||
xaiProxy
|
||||
);
|
||||
|
||||
// Add endpoint for image generation
|
||||
xaiRouter.post(
|
||||
"/v1/images/generations",
|
||||
ipLimiter,
|
||||
handleImageGenerationRequest
|
||||
);
|
||||
|
||||
xaiRouter.get("/v1/models", handleModelRequest);
|
||||
|
||||
export const xai = xaiRouter;
|
||||
+1
-1
@@ -92,7 +92,7 @@ app.use("/admin", adminRouter);
|
||||
app.use((req, _, next) => {
|
||||
// For whatever reason SillyTavern just ignores the path a user provides
|
||||
// when using Google AI with reverse proxy. We'll fix it here.
|
||||
if (req.path.startsWith("/v1beta/models/")) {
|
||||
if (req.path.match(/^\/v1(alpha|beta)\/models(\/|$)/)) {
|
||||
req.url = `${config.proxyEndpointRoute}/google-ai${req.url}`;
|
||||
return next();
|
||||
}
|
||||
|
||||
+328
-32
@@ -2,9 +2,14 @@ import { config, listConfig } from "./config";
|
||||
import {
|
||||
AnthropicKey,
|
||||
AwsBedrockKey,
|
||||
DeepseekKey,
|
||||
GcpKey,
|
||||
keyPool,
|
||||
OpenAIKey,
|
||||
XaiKey,
|
||||
CohereKey,
|
||||
QwenKey,
|
||||
MoonshotKey,
|
||||
} from "./shared/key-management";
|
||||
import {
|
||||
AnthropicModelFamily,
|
||||
@@ -19,6 +24,11 @@ import {
|
||||
MODEL_FAMILY_SERVICE,
|
||||
ModelFamily,
|
||||
OpenAIModelFamily,
|
||||
DeepseekModelFamily,
|
||||
XaiModelFamily,
|
||||
CohereModelFamily,
|
||||
QwenModelFamily,
|
||||
MoonshotModelFamily,
|
||||
} from "./shared/models";
|
||||
import { getCostSuffix, getTokenCostUsd, prettyTokens } from "./shared/stats";
|
||||
import { getUniqueIps } from "./proxy/rate-limit";
|
||||
@@ -27,6 +37,87 @@ import { getEstimatedWaitTime, getQueueLength } from "./proxy/queue";
|
||||
|
||||
const CACHE_TTL = 2000;
|
||||
|
||||
// Define the preferred order for model families in the service info display
|
||||
// This ensures logical grouping (GPT-4 models together, then GPT-4.1, then GPT-5, etc.)
|
||||
const MODEL_FAMILY_ORDER: ModelFamily[] = [
|
||||
// OpenAI models in logical order
|
||||
"turbo",
|
||||
"gpt4",
|
||||
"gpt4-32k",
|
||||
"gpt4-turbo",
|
||||
"gpt4o",
|
||||
"gpt41",
|
||||
"gpt41-mini",
|
||||
"gpt41-nano",
|
||||
"gpt45",
|
||||
"gpt5",
|
||||
"gpt5-mini",
|
||||
"gpt5-nano",
|
||||
"gpt5-chat-latest",
|
||||
"o1",
|
||||
"o1-mini",
|
||||
"o1-pro",
|
||||
"o3",
|
||||
"o3-mini",
|
||||
"o3-pro",
|
||||
"o4-mini",
|
||||
"codex-mini",
|
||||
"dall-e",
|
||||
"gpt-image",
|
||||
// Azure OpenAI models (same order as OpenAI)
|
||||
"azure-turbo",
|
||||
"azure-gpt4",
|
||||
"azure-gpt4-32k",
|
||||
"azure-gpt4-turbo",
|
||||
"azure-gpt4o",
|
||||
"azure-gpt41",
|
||||
"azure-gpt41-mini",
|
||||
"azure-gpt41-nano",
|
||||
"azure-gpt45",
|
||||
"azure-gpt5",
|
||||
"azure-gpt5-mini",
|
||||
"azure-gpt5-nano",
|
||||
"azure-gpt5-chat-latest",
|
||||
"azure-o1",
|
||||
"azure-o1-mini",
|
||||
"azure-o1-pro",
|
||||
"azure-o3",
|
||||
"azure-o3-mini",
|
||||
"azure-o3-pro",
|
||||
"azure-o4-mini",
|
||||
"azure-codex-mini",
|
||||
"azure-dall-e",
|
||||
"azure-gpt-image",
|
||||
// Anthropic models
|
||||
"claude",
|
||||
"claude-opus",
|
||||
// Google AI models
|
||||
"gemini-flash",
|
||||
"gemini-pro",
|
||||
"gemini-ultra",
|
||||
// Mistral AI models
|
||||
"mistral-tiny",
|
||||
"mistral-small",
|
||||
"mistral-medium",
|
||||
"mistral-large",
|
||||
// AWS Bedrock models
|
||||
"aws-claude",
|
||||
"aws-claude-opus",
|
||||
"aws-mistral-tiny",
|
||||
"aws-mistral-small",
|
||||
"aws-mistral-medium",
|
||||
"aws-mistral-large",
|
||||
// GCP models
|
||||
"gcp-claude",
|
||||
"gcp-claude-opus",
|
||||
// Other services
|
||||
"deepseek",
|
||||
"xai",
|
||||
"cohere",
|
||||
"qwen",
|
||||
"moonshot"
|
||||
];
|
||||
|
||||
type KeyPoolKey = ReturnType<typeof keyPool.list>[0];
|
||||
const keyIsOpenAIKey = (k: KeyPoolKey): k is OpenAIKey =>
|
||||
k.service === "openai";
|
||||
@@ -34,6 +125,16 @@ const keyIsAnthropicKey = (k: KeyPoolKey): k is AnthropicKey =>
|
||||
k.service === "anthropic";
|
||||
const keyIsAwsKey = (k: KeyPoolKey): k is AwsBedrockKey => k.service === "aws";
|
||||
const keyIsGcpKey = (k: KeyPoolKey): k is GcpKey => k.service === "gcp";
|
||||
const keyIsDeepseekKey = (k: KeyPoolKey): k is DeepseekKey =>
|
||||
k.service === "deepseek";
|
||||
const keyIsXaiKey = (k: KeyPoolKey): k is XaiKey =>
|
||||
k.service === "xai";
|
||||
const keyIsCohereKey = (k: KeyPoolKey): k is CohereKey =>
|
||||
k.service === "cohere";
|
||||
const keyIsQwenKey = (k: KeyPoolKey): k is QwenKey =>
|
||||
k.service === "qwen";
|
||||
const keyIsMoonshotKey = (k: KeyPoolKey): k is MoonshotKey =>
|
||||
k.service === "moonshot";
|
||||
|
||||
/** Stats aggregated across all keys for a given service. */
|
||||
type ServiceAggregate = "keys" | "uncheckedKeys" | "orgs";
|
||||
@@ -49,19 +150,27 @@ type ModelAggregates = {
|
||||
awsClaude2?: number;
|
||||
awsSonnet3?: number;
|
||||
awsSonnet3_5?: number;
|
||||
awsSonnet3_7?: number;
|
||||
awsSonnet4?: number;
|
||||
awsOpus3?: number;
|
||||
awsOpus4?: number;
|
||||
awsHaiku: number;
|
||||
gcpSonnet?: number;
|
||||
gcpSonnet35?: number;
|
||||
gcpHaiku?: number;
|
||||
queued: number;
|
||||
tokens: number;
|
||||
inputTokens: number; // Changed from tokens
|
||||
outputTokens: number; // Added
|
||||
legacyTokens?: number; // Added for migrated totals
|
||||
};
|
||||
/** All possible combinations of model family and aggregate type. */
|
||||
type ModelAggregateKey = `${ModelFamily}__${keyof ModelAggregates}`;
|
||||
|
||||
type AllStats = {
|
||||
proompts: number;
|
||||
tokens: number;
|
||||
inputTokens: number; // Changed from tokens
|
||||
outputTokens: number; // Added
|
||||
legacyTokens?: number; // Added
|
||||
tokenCost: number;
|
||||
} & { [modelFamily in ModelFamily]?: ModelAggregates } & {
|
||||
[service in LLMService as `${service}__${ServiceAggregate}`]?: number;
|
||||
@@ -96,6 +205,8 @@ export type ServiceInfo = {
|
||||
uptime: number;
|
||||
endpoints: {
|
||||
openai?: string;
|
||||
deepseek?: string;
|
||||
xai?: string;
|
||||
anthropic?: string;
|
||||
"google-ai"?: string;
|
||||
"mistral-ai"?: string;
|
||||
@@ -116,8 +227,13 @@ export type ServiceInfo = {
|
||||
& { [f in AwsBedrockModelFamily]?: AwsInfo }
|
||||
& { [f in GcpModelFamily]?: GcpInfo }
|
||||
& { [f in AzureOpenAIModelFamily]?: BaseFamilyInfo; }
|
||||
& { [f in GoogleAIModelFamily]?: BaseFamilyInfo }
|
||||
& { [f in MistralAIModelFamily]?: BaseFamilyInfo };
|
||||
& { [f in GoogleAIModelFamily]?: BaseFamilyInfo & { overQuotaKeys?: number } }
|
||||
& { [f in MistralAIModelFamily]?: BaseFamilyInfo }
|
||||
& { [f in DeepseekModelFamily]?: BaseFamilyInfo }
|
||||
& { [f in XaiModelFamily]?: BaseFamilyInfo }
|
||||
& { [f in CohereModelFamily]?: BaseFamilyInfo }
|
||||
& { [f in QwenModelFamily]?: BaseFamilyInfo }
|
||||
& { [f in MoonshotModelFamily]?: BaseFamilyInfo };
|
||||
|
||||
// https://stackoverflow.com/a/66661477
|
||||
// type DeepKeyOf<T> = (
|
||||
@@ -159,6 +275,21 @@ const SERVICE_ENDPOINTS: { [s in LLMService]: Record<string, string> } = {
|
||||
azure: `%BASE%/azure/openai`,
|
||||
"azure-image": `%BASE%/azure/openai`,
|
||||
},
|
||||
deepseek: {
|
||||
deepseek: `%BASE%/deepseek`,
|
||||
},
|
||||
xai: {
|
||||
xai: `%BASE%/xai`,
|
||||
},
|
||||
cohere: {
|
||||
cohere: `%BASE%/cohere`,
|
||||
},
|
||||
qwen: {
|
||||
qwen: `%BASE%/qwen`,
|
||||
},
|
||||
moonshot: {
|
||||
moonshot: `%BASE%/moonshot`,
|
||||
},
|
||||
};
|
||||
|
||||
const familyStats = new Map<ModelAggregateKey, number>();
|
||||
@@ -250,11 +381,14 @@ function getEndpoints(baseUrl: string, accessibleFamilies: Set<ModelFamily>) {
|
||||
type TrafficStats = Pick<ServiceInfo, "proompts" | "tookens" | "proomptersNow">;
|
||||
|
||||
function getTrafficStats(): TrafficStats {
|
||||
const tokens = serviceStats.get("tokens") || 0;
|
||||
const inputTokens = serviceStats.get("inputTokens") || 0;
|
||||
const outputTokens = serviceStats.get("outputTokens") || 0;
|
||||
// const legacyTokens = serviceStats.get("legacyTokens") || 0; // Optional: include in total if desired
|
||||
const totalTokens = inputTokens + outputTokens; // + legacyTokens;
|
||||
const tokenCost = serviceStats.get("tokenCost") || 0;
|
||||
return {
|
||||
proompts: serviceStats.get("proompts") || 0,
|
||||
tookens: `${prettyTokens(tokens)}${getCostSuffix(tokenCost)}`,
|
||||
tookens: `${prettyTokens(totalTokens)}${getCostSuffix(tokenCost)}`, // Simplified to show aggregate and cost
|
||||
...(config.textModelRateLimit ? { proomptersNow: getUniqueIps() } : {}),
|
||||
};
|
||||
}
|
||||
@@ -270,16 +404,18 @@ function getServiceModelStats(accessibleFamilies: Set<ModelFamily>) {
|
||||
if (!hasKeys) continue;
|
||||
|
||||
serviceInfo[`${service}Keys`] = hasKeys;
|
||||
accessibleFamilies.forEach((f) => {
|
||||
if (MODEL_FAMILY_SERVICE[f] === service) {
|
||||
modelFamilyInfo[f] = getInfoForFamily(f);
|
||||
}
|
||||
});
|
||||
|
||||
if (service === "openai" && config.checkKeys) {
|
||||
serviceInfo.openaiOrgs = getUniqueOpenAIOrgs(keyPool.list());
|
||||
}
|
||||
}
|
||||
|
||||
// Build model family info in the defined order for logical grouping
|
||||
for (const family of MODEL_FAMILY_ORDER) {
|
||||
if (accessibleFamilies.has(family)) {
|
||||
modelFamilyInfo[family] = getInfoForFamily(family);
|
||||
}
|
||||
}
|
||||
return { serviceInfo, modelFamilyInfo };
|
||||
}
|
||||
|
||||
@@ -309,15 +445,45 @@ function addKeyToAggregates(k: KeyPoolKey) {
|
||||
addToService("aws__keys", k.service === "aws" ? 1 : 0);
|
||||
addToService("gcp__keys", k.service === "gcp" ? 1 : 0);
|
||||
addToService("azure__keys", k.service === "azure" ? 1 : 0);
|
||||
addToService("deepseek__keys", k.service === "deepseek" ? 1 : 0);
|
||||
addToService("xai__keys", k.service === "xai" ? 1 : 0);
|
||||
addToService("cohere__keys", k.service === "cohere" ? 1 : 0);
|
||||
addToService("qwen__keys", k.service === "qwen" ? 1 : 0);
|
||||
addToService("moonshot__keys", k.service === "moonshot" ? 1 : 0);
|
||||
|
||||
let sumTokens = 0;
|
||||
let sumInputTokens = 0;
|
||||
let sumOutputTokens = 0;
|
||||
let sumLegacyTokens = 0; // Optional
|
||||
let sumCost = 0;
|
||||
|
||||
const incrementGenericFamilyStats = (f: ModelFamily) => {
|
||||
const tokens = (k as any)[`${f}Tokens`];
|
||||
sumTokens += tokens;
|
||||
sumCost += getTokenCostUsd(f, tokens);
|
||||
addToFamily(`${f}__tokens`, tokens);
|
||||
const usage = k.tokenUsage?.[f];
|
||||
let familyInputTokens = 0;
|
||||
let familyOutputTokens = 0;
|
||||
let familyLegacyTokens = 0;
|
||||
|
||||
if (usage) {
|
||||
familyInputTokens = usage.input || 0;
|
||||
familyOutputTokens = usage.output || 0;
|
||||
if (usage.legacy_total && familyInputTokens === 0 && familyOutputTokens === 0) {
|
||||
// This is a migrated key with no new usage, use legacy_total as input for cost
|
||||
familyLegacyTokens = usage.legacy_total;
|
||||
sumCost += getTokenCostUsd(f, usage.legacy_total, 0);
|
||||
} else {
|
||||
sumCost += getTokenCostUsd(f, familyInputTokens, familyOutputTokens);
|
||||
}
|
||||
}
|
||||
// If no k.tokenUsage[f], tokens are 0, cost is 0.
|
||||
|
||||
sumInputTokens += familyInputTokens;
|
||||
sumOutputTokens += familyOutputTokens;
|
||||
sumLegacyTokens += familyLegacyTokens; // Optional
|
||||
|
||||
addToFamily(`${f}__inputTokens`, familyInputTokens);
|
||||
addToFamily(`${f}__outputTokens`, familyOutputTokens);
|
||||
if (familyLegacyTokens > 0) {
|
||||
addToFamily(`${f}__legacyTokens`, familyLegacyTokens); // Optional
|
||||
}
|
||||
addToFamily(`${f}__revoked`, k.isRevoked ? 1 : 0);
|
||||
addToFamily(`${f}__active`, k.isDisabled ? 0 : 1);
|
||||
};
|
||||
@@ -351,10 +517,21 @@ function addKeyToAggregates(k: KeyPoolKey) {
|
||||
k.modelIds.forEach((id) => {
|
||||
if (id.includes("claude-3-sonnet")) {
|
||||
addToFamily(`aws-claude__awsSonnet3`, 1);
|
||||
// not ideal but whatever
|
||||
} else if (id.includes("claude-3-5-sonnet")) {
|
||||
addToFamily(`aws-claude__awsSonnet3_5`, 1);
|
||||
} else if (id.includes("claude-3-7-sonnet")) {
|
||||
addToFamily(`aws-claude__awsSonnet3_7`, 1);
|
||||
} else if (id.includes("claude-3-haiku")) {
|
||||
addToFamily(`aws-claude__awsHaiku`, 1);
|
||||
} else if (id.includes("sonnet-4")) {
|
||||
addToFamily(`aws-claude__awsSonnet4`, 1);
|
||||
} else if (id.includes("claude-3-opus")) {
|
||||
addToFamily(`aws-claude__awsOpus3`, 1);
|
||||
addToFamily(`aws-claude-opus__awsOpus3`, 1);
|
||||
} else if (id.includes("opus-4")) {
|
||||
addToFamily(`aws-claude__awsOpus4`, 1);
|
||||
addToFamily(`aws-claude-opus__awsOpus4`, 1);
|
||||
} else if (id.includes("claude-v2")) {
|
||||
addToFamily(`aws-claude__awsClaude2`, 1);
|
||||
}
|
||||
@@ -372,25 +549,111 @@ function addKeyToAggregates(k: KeyPoolKey) {
|
||||
k.modelFamilies.forEach(incrementGenericFamilyStats);
|
||||
// TODO: add modelIds to GcpKey
|
||||
break;
|
||||
case "deepseek":
|
||||
if (!keyIsDeepseekKey(k)) throw new Error("Invalid key type");
|
||||
k.modelFamilies.forEach((f) => {
|
||||
incrementGenericFamilyStats(f);
|
||||
addToFamily(`${f}__overQuota`, k.isOverQuota ? 1 : 0);
|
||||
});
|
||||
break;
|
||||
case "xai":
|
||||
if (!keyIsXaiKey(k)) throw new Error("Invalid key type");
|
||||
k.modelFamilies.forEach((f) => {
|
||||
incrementGenericFamilyStats(f);
|
||||
if ('isOverQuota' in k) {
|
||||
addToFamily(`${f}__overQuota`, k.isOverQuota ? 1 : 0);
|
||||
}
|
||||
});
|
||||
break;
|
||||
case "cohere":
|
||||
if (!keyIsCohereKey(k)) throw new Error("Invalid key type");
|
||||
k.modelFamilies.forEach((f) => {
|
||||
incrementGenericFamilyStats(f);
|
||||
if ('isOverQuota' in k) {
|
||||
addToFamily(`${f}__overQuota`, k.isOverQuota ? 1 : 0);
|
||||
}
|
||||
});
|
||||
break;
|
||||
// These services don't have any additional stats to track.
|
||||
case "azure":
|
||||
case "google-ai":
|
||||
case "mistral-ai":
|
||||
k.modelFamilies.forEach(incrementGenericFamilyStats);
|
||||
break;
|
||||
case "google-ai":
|
||||
// Cast to GoogleAIKey to access GoogleAI-specific properties
|
||||
const googleKey = k as unknown as { overQuotaFamilies?: string[] };
|
||||
|
||||
// First handle general stats for all model families
|
||||
k.modelFamilies.forEach((f) => {
|
||||
incrementGenericFamilyStats(f);
|
||||
});
|
||||
|
||||
// Create a set of model families that are over quota for this key
|
||||
let overQuotaModelFamilies = new Set<string>();
|
||||
|
||||
// Add any model family that's listed in overQuotaFamilies
|
||||
if (googleKey.overQuotaFamilies && Array.isArray(googleKey.overQuotaFamilies)) {
|
||||
googleKey.overQuotaFamilies.forEach(family => {
|
||||
overQuotaModelFamilies.add(family);
|
||||
});
|
||||
}
|
||||
// If key is generally over quota and we don't have specific families, add all families
|
||||
else if ('isOverQuota' in k && k.isOverQuota) {
|
||||
k.modelFamilies.forEach(family => {
|
||||
overQuotaModelFamilies.add(family);
|
||||
});
|
||||
}
|
||||
|
||||
// Now increment the over-quota counter for each affected family
|
||||
// These model families are valid and already defined in the enum
|
||||
overQuotaModelFamilies.forEach(family => {
|
||||
if (family === 'gemini-pro' || family === 'gemini-flash' || family === 'gemini-ultra') {
|
||||
addToFamily(`${family}__overQuota` as any, 1);
|
||||
}
|
||||
});
|
||||
break;
|
||||
case "qwen":
|
||||
k.modelFamilies.forEach(incrementGenericFamilyStats);
|
||||
break;
|
||||
case "moonshot":
|
||||
k.modelFamilies.forEach(incrementGenericFamilyStats);
|
||||
break;
|
||||
default:
|
||||
assertNever(k.service);
|
||||
}
|
||||
|
||||
addToService("tokens", sumTokens);
|
||||
addToService("inputTokens", sumInputTokens);
|
||||
addToService("outputTokens", sumOutputTokens);
|
||||
if (sumLegacyTokens > 0) { // Optional
|
||||
addToService("legacyTokens", sumLegacyTokens);
|
||||
}
|
||||
addToService("tokenCost", sumCost);
|
||||
}
|
||||
|
||||
function getInfoForFamily(family: ModelFamily): BaseFamilyInfo {
|
||||
const tokens = familyStats.get(`${family}__tokens`) || 0;
|
||||
const cost = getTokenCostUsd(family, tokens);
|
||||
const inputTokens = familyStats.get(`${family}__inputTokens`) || 0;
|
||||
const outputTokens = familyStats.get(`${family}__outputTokens`) || 0;
|
||||
const legacyTokens = familyStats.get(`${family}__legacyTokens`) || 0; // Optional
|
||||
|
||||
let cost = 0;
|
||||
let displayTokens = 0;
|
||||
let usageString = "";
|
||||
|
||||
if (inputTokens > 0 || outputTokens > 0) {
|
||||
cost = getTokenCostUsd(family, inputTokens, outputTokens);
|
||||
displayTokens = inputTokens + outputTokens;
|
||||
usageString = `${prettyTokens(displayTokens)} (In: ${prettyTokens(inputTokens)}, Out: ${prettyTokens(outputTokens)})${getCostSuffix(cost)}`;
|
||||
} else if (legacyTokens > 0) {
|
||||
// Only show legacy if no new input/output has been recorded for this family aggregate
|
||||
cost = getTokenCostUsd(family, legacyTokens, 0); // Cost legacy as all input
|
||||
displayTokens = legacyTokens;
|
||||
usageString = `${prettyTokens(displayTokens)} tokens (legacy total)${getCostSuffix(cost)}`;
|
||||
} else {
|
||||
usageString = `${prettyTokens(0)} tokens${getCostSuffix(0)}`;
|
||||
}
|
||||
|
||||
let info: BaseFamilyInfo & OpenAIInfo & AnthropicInfo & AwsInfo & GcpInfo = {
|
||||
usage: `${prettyTokens(tokens)} tokens${getCostSuffix(cost)}`,
|
||||
usage: usageString,
|
||||
activeKeys: familyStats.get(`${family}__active`) || 0,
|
||||
revokedKeys: familyStats.get(`${family}__revoked`) || 0,
|
||||
};
|
||||
@@ -418,25 +681,40 @@ function getInfoForFamily(family: ModelFamily): BaseFamilyInfo {
|
||||
break;
|
||||
case "aws":
|
||||
if (family === "aws-claude") {
|
||||
// Original behavior: get logged count from the same family
|
||||
const logged = familyStats.get(`${family}__awsLogged`) || 0;
|
||||
const variants = new Set<string>();
|
||||
if (familyStats.get(`${family}__awsClaude2`) || 0)
|
||||
variants.add("claude2");
|
||||
if (familyStats.get(`${family}__awsSonnet3`) || 0)
|
||||
variants.add("sonnet3");
|
||||
if (familyStats.get(`${family}__awsSonnet3_5`) || 0)
|
||||
variants.add("sonnet3.5");
|
||||
if (familyStats.get(`${family}__awsHaiku`) || 0)
|
||||
variants.add("haiku");
|
||||
info.enabledVariants = variants.size
|
||||
? `${Array.from(variants).join(",")}`
|
||||
: undefined;
|
||||
if (familyStats.get(`${family}__awsClaude2`) || 0) variants.add("claude2");
|
||||
if (familyStats.get(`${family}__awsSonnet3`) || 0) variants.add("sonnet3");
|
||||
if (familyStats.get(`${family}__awsSonnet3_5`) || 0) variants.add("sonnet3.5");
|
||||
if (familyStats.get(`${family}__awsSonnet3_7`) || 0) variants.add("sonnet3.7");
|
||||
if (familyStats.get(`${family}__awsHaiku`) || 0) variants.add("haiku");
|
||||
if (familyStats.get(`${family}__awsSonnet4`) || 0) variants.add("sonnet4");
|
||||
|
||||
info.enabledVariants = variants.size ? Array.from(variants).join(",") : undefined;
|
||||
|
||||
if (logged > 0) {
|
||||
info.privacy = config.allowAwsLogging
|
||||
? `AWS logging verification inactive. Prompts could be logged.`
|
||||
: `${logged} active keys are potentially logged and can't be used. Set ALLOW_AWS_LOGGING=true to override.`;
|
||||
}
|
||||
} else if (family === "aws-claude-opus") {
|
||||
// Get logging info from aws-claude family since that's where it's collected
|
||||
const awsLogged = familyStats.get(`aws-claude__awsLogged`) || 0;
|
||||
const variants = new Set<string>();
|
||||
if (familyStats.get(`${family}__awsOpus3`) || 0) variants.add("opus3");
|
||||
if (familyStats.get(`${family}__awsOpus4`) || 0) variants.add("opus4");
|
||||
|
||||
info.enabledVariants = variants.size ? Array.from(variants).join(",") : undefined;
|
||||
|
||||
// Show privacy warning for Opus if there are active Opus keys AND some AWS keys are logged
|
||||
if (awsLogged > 0 && info.activeKeys > 0) {
|
||||
info.privacy = config.allowAwsLogging
|
||||
? `AWS logging verification inactive. Prompts could be logged.`
|
||||
: `Some AWS keys are potentially logged. Set ALLOW_AWS_LOGGING=true to override.`;
|
||||
}
|
||||
}
|
||||
// TODO: Consider if aws-mistral-* families need similar enabledVariant listings
|
||||
break;
|
||||
case "gcp":
|
||||
if (family === "gcp-claude") {
|
||||
@@ -444,6 +722,24 @@ function getInfoForFamily(family: ModelFamily): BaseFamilyInfo {
|
||||
info.enabledVariants = "not implemented";
|
||||
}
|
||||
break;
|
||||
case "deepseek":
|
||||
info.overQuotaKeys = familyStats.get(`${family}__overQuota`) || 0;
|
||||
break;
|
||||
case "xai":
|
||||
info.overQuotaKeys = familyStats.get(`${family}__overQuota`) || 0;
|
||||
break;
|
||||
case "cohere":
|
||||
info.overQuotaKeys = familyStats.get(`${family}__overQuota`) || 0;
|
||||
break;
|
||||
case "google-ai":
|
||||
info.overQuotaKeys = familyStats.get(`${family}__overQuota`) || 0;
|
||||
break;
|
||||
case "qwen":
|
||||
info.overQuotaKeys = familyStats.get(`${family}__overQuota`) || 0;
|
||||
break;
|
||||
case "moonshot":
|
||||
info.overQuotaKeys = familyStats.get(`${family}__overQuota`) || 0;
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
@@ -19,6 +19,13 @@ const AnthropicV1BaseSchema = z
|
||||
top_k: z.coerce.number().optional(),
|
||||
top_p: z.coerce.number().optional(),
|
||||
metadata: z.object({ user_id: z.string().optional() }).optional(),
|
||||
tools: z.array(z.any()).optional(),
|
||||
tool_choice: z.any().optional(),
|
||||
service_tier: z.enum(["auto", "standard_only"]).optional(),
|
||||
cache_control: z.object({
|
||||
type: z.literal("ephemeral"),
|
||||
ttl: z.enum(["5m", "1h"]).optional()
|
||||
}).optional(),
|
||||
})
|
||||
.strip();
|
||||
|
||||
@@ -33,16 +40,35 @@ export const AnthropicV1TextSchema = AnthropicV1BaseSchema.merge(
|
||||
})
|
||||
);
|
||||
|
||||
const AnthropicV1BaseContentSchema = z.union([
|
||||
z.object({ type: z.literal("text"), text: z.string() }),
|
||||
z.object({
|
||||
type: z.literal("image"),
|
||||
source: z.object({
|
||||
type: z.literal("base64"),
|
||||
media_type: z.string().max(100),
|
||||
data: z.string(),
|
||||
}),
|
||||
})
|
||||
]);
|
||||
|
||||
const AnthropicV1MessageMultimodalContentSchema = z.array(
|
||||
z.union([
|
||||
z.object({ type: z.literal("text"), text: z.string() }),
|
||||
AnthropicV1BaseContentSchema,
|
||||
z.object({
|
||||
type: z.literal("image"),
|
||||
source: z.object({
|
||||
type: z.literal("base64"),
|
||||
media_type: z.string().max(100),
|
||||
data: z.string(),
|
||||
}),
|
||||
type: z.literal("tool_use"),
|
||||
id: z.string(),
|
||||
name: z.string(),
|
||||
input: z.object({}).passthrough(),
|
||||
}),
|
||||
z.object({
|
||||
type: z.literal("tool_result"),
|
||||
tool_use_id: z.string(),
|
||||
is_error: z.boolean().optional(),
|
||||
content: z.union([
|
||||
z.string(),
|
||||
z.array(AnthropicV1BaseContentSchema)
|
||||
]).optional(),
|
||||
}),
|
||||
])
|
||||
);
|
||||
@@ -69,6 +95,10 @@ export const AnthropicV1MessagesSchema = AnthropicV1BaseSchema.merge(
|
||||
z.array(z.object({ type: z.literal("text"), text: z.string() })),
|
||||
])
|
||||
.optional(),
|
||||
thinking: z.object({
|
||||
type: z.literal("enabled"),
|
||||
budget_tokens: z.number().min(1024),
|
||||
}).optional(),
|
||||
})
|
||||
);
|
||||
export type AnthropicChatMessage = z.infer<
|
||||
@@ -82,7 +112,7 @@ function openAIMessagesToClaudeTextPrompt(messages: OpenAIChatMessage[]) {
|
||||
let role: string = m.role;
|
||||
if (role === "assistant") {
|
||||
role = "Assistant";
|
||||
} else if (role === "system") {
|
||||
} else if (role === "system" || role === "developer") {
|
||||
role = "System";
|
||||
} else if (role === "user") {
|
||||
role = "Human";
|
||||
@@ -109,6 +139,10 @@ export const transformOpenAIToAnthropicChat: APIFormatTransformer<
|
||||
);
|
||||
throw result.error;
|
||||
}
|
||||
if (result.data.max_tokens > 8192) {
|
||||
result.data.max_tokens = 4096;
|
||||
}
|
||||
|
||||
|
||||
const { messages, ...rest } = result.data;
|
||||
const { messages: newMessages, system } =
|
||||
@@ -365,7 +399,7 @@ function openAIMessagesToClaudeChatPrompt(messages: OpenAIChatMessage[]): {
|
||||
// Here we will lose the original name if it was a system message, but that
|
||||
// is generally okay because the system message is usually a prompt and not
|
||||
// a character in the chat.
|
||||
const name = msg.role === "system" ? "System" : msg.name?.trim();
|
||||
const name = (msg.role === "system" || msg.role === "developer") ? "System" : msg.name?.trim();
|
||||
const content = convertOpenAIContent(msg.content);
|
||||
|
||||
// Prepend the display name to the first text content in the current message
|
||||
@@ -395,8 +429,8 @@ function openAIMessagesToClaudeChatPrompt(messages: OpenAIChatMessage[]): {
|
||||
|
||||
function isSystemOpenAIRole(
|
||||
role: OpenAIChatMessage["role"]
|
||||
): role is "system" | "function" | "tool" {
|
||||
return ["system", "function", "tool"].includes(role);
|
||||
): role is "developer" | "system" | "function" | "tool" {
|
||||
return ["developer", "system", "function", "tool"].includes(role);
|
||||
}
|
||||
|
||||
function getFirstTextContent(content: OpenAIChatMessage["content"]) {
|
||||
@@ -439,9 +473,25 @@ function convertOpenAIContent(
|
||||
});
|
||||
}
|
||||
|
||||
export function containsImageContent(messages: AnthropicChatMessage[]) {
|
||||
return messages.some(
|
||||
({ content }) =>
|
||||
typeof content !== "string" && content.some((c) => c.type === "image")
|
||||
);
|
||||
export function containsImageContent(messages: AnthropicChatMessage[]): boolean {
|
||||
const isImage = (item: any) => item?.type === 'image';
|
||||
|
||||
return messages.some(msg => {
|
||||
if (typeof msg.content === 'string') return false;
|
||||
|
||||
return msg.content.some(item => {
|
||||
if (isImage(item)) return true;
|
||||
|
||||
if (item.type === 'tool_result') {
|
||||
const content = item.content;
|
||||
if (!content) return false;
|
||||
|
||||
if (typeof content === 'string') return false;
|
||||
if (Array.isArray(content)) return content.some(isImage);
|
||||
return isImage(content);
|
||||
}
|
||||
|
||||
return false;
|
||||
});
|
||||
});
|
||||
}
|
||||
|
||||
@@ -0,0 +1,69 @@
|
||||
import { z } from "zod";
|
||||
import { OPENAI_OUTPUT_MAX } from "./openai";
|
||||
|
||||
/**
|
||||
* Helper function to check if a model is from Cohere
|
||||
*/
|
||||
export function isCohereModel(model: string): boolean {
|
||||
// Cohere's command model family
|
||||
return model.includes("command") || model.includes("cohere");
|
||||
}
|
||||
|
||||
// Basic chat message schema
|
||||
const CohereChatMessageSchema = z.object({
|
||||
role: z.enum(["user", "assistant", "system", "developer"]),
|
||||
content: z.string().nullable(),
|
||||
name: z.string().optional(),
|
||||
});
|
||||
|
||||
const CohereMessagesSchema = z.array(CohereChatMessageSchema);
|
||||
|
||||
// Schema for Cohere chat completions
|
||||
export const CohereV1ChatCompletionsSchema = z.object({
|
||||
model: z.string(),
|
||||
messages: CohereMessagesSchema,
|
||||
temperature: z.number().optional().default(1),
|
||||
top_p: z.number().optional().default(1),
|
||||
max_tokens: z.coerce
|
||||
.number()
|
||||
.int()
|
||||
.nullish()
|
||||
.transform((v) => Math.min(v ?? OPENAI_OUTPUT_MAX, OPENAI_OUTPUT_MAX)),
|
||||
stream: z.boolean().optional().default(false),
|
||||
stop: z
|
||||
.union([z.string(), z.array(z.string())])
|
||||
.optional()
|
||||
.default([])
|
||||
.transform((v) => (Array.isArray(v) ? v : [v])),
|
||||
seed: z.number().int().min(0).optional(),
|
||||
response_format: z
|
||||
.object({
|
||||
type: z.enum(["text", "json_object"]),
|
||||
schema: z.any().optional()
|
||||
})
|
||||
.optional(),
|
||||
// Structured output with schema
|
||||
tools: z.array(z.any()).optional(),
|
||||
frequency_penalty: z.number().optional().default(0),
|
||||
presence_penalty: z.number().optional().default(0),
|
||||
});
|
||||
|
||||
// Schema for Cohere embeddings
|
||||
export const CohereV1EmbeddingsSchema = z.object({
|
||||
model: z.string(),
|
||||
input: z.union([z.string(), z.array(z.string())]),
|
||||
encoding_format: z.enum(["float", "base64"]).optional()
|
||||
});
|
||||
|
||||
// Helper function to convert between different message formats if needed
|
||||
export function normalizeMessages(messages: any[]): any[] {
|
||||
// From documentation, Cohere supports roles: developer, user, assistant
|
||||
// The 'developer' role is equivalent to 'system' in OpenAI API
|
||||
return messages.map((msg) => {
|
||||
// Convert system role to developer role for Cohere compatibility
|
||||
if (msg.role === "system") {
|
||||
return { ...msg, role: "developer" };
|
||||
}
|
||||
return msg;
|
||||
});
|
||||
}
|
||||
@@ -5,19 +5,28 @@ import {
|
||||
} from "./openai";
|
||||
import { APIFormatTransformer } from "./index";
|
||||
|
||||
const TextPartSchema = z.object({
|
||||
text: z.string(),
|
||||
thought: z.boolean().optional()
|
||||
});
|
||||
|
||||
const InlineDataPartSchema = z.object({
|
||||
inlineData: z.object({
|
||||
mimeType: z.string(),
|
||||
data: z.string(),
|
||||
}),
|
||||
});
|
||||
|
||||
const PartSchema = z.union([TextPartSchema, InlineDataPartSchema]);
|
||||
|
||||
const GoogleAIV1ContentSchema = z.object({
|
||||
parts: z
|
||||
.union([
|
||||
z.array(z.object({ text: z.string() })),
|
||||
z.object({ text: z.string() }),
|
||||
])
|
||||
// Google allows parts to be an array or a single object, which is really
|
||||
// annoying for downstream code. We will coerce it to an array here.
|
||||
.union([PartSchema, z.array(PartSchema)])
|
||||
.transform((val) => (Array.isArray(val) ? val : [val])),
|
||||
// TODO: add other media types
|
||||
role: z.enum(["user", "model"]).optional(),
|
||||
});
|
||||
|
||||
|
||||
const SafetySettingsSchema = z
|
||||
.array(
|
||||
z.object({
|
||||
@@ -40,18 +49,21 @@ const SafetySettingsSchema = z
|
||||
)
|
||||
.optional();
|
||||
|
||||
// https://developers.generativeai.google/api/rest/generativelanguage/models/generateContent
|
||||
const GoogleSearchToolSchema = z.object({
|
||||
googleSearch: z.object({}),
|
||||
});
|
||||
|
||||
// Corrected: Directly assign the schema since there's only one tool type for now
|
||||
const ToolSchema = GoogleSearchToolSchema;
|
||||
|
||||
export const GoogleAIV1GenerateContentSchema = z
|
||||
.object({
|
||||
model: z.string().max(100), //actually specified in path but we need it for the router
|
||||
stream: z.boolean().optional().default(false), // also used for router
|
||||
model: z.string().max(100),
|
||||
stream: z.boolean().optional().default(false),
|
||||
contents: z.array(GoogleAIV1ContentSchema),
|
||||
tools: z.array(z.object({})).max(0).optional(),
|
||||
tools: z.array(ToolSchema).optional(), // Uses the corrected ToolSchema
|
||||
safetySettings: SafetySettingsSchema,
|
||||
systemInstruction: GoogleAIV1ContentSchema.optional(),
|
||||
// quick fix for SillyTavern, which uses camel case field names for everything
|
||||
// except for system_instruction where it randomly uses snake case.
|
||||
// google api evidently accepts either case.
|
||||
system_instruction: GoogleAIV1ContentSchema.optional(),
|
||||
generationConfig: z
|
||||
.object({
|
||||
@@ -61,11 +73,22 @@ export const GoogleAIV1GenerateContentSchema = z
|
||||
.int()
|
||||
.optional()
|
||||
.default(16)
|
||||
.transform((v) => Math.min(v, 4096)), // TODO: Add config
|
||||
.transform((v) => Math.min(v, 65536)),
|
||||
candidateCount: z.literal(1).optional(),
|
||||
topP: z.number().min(0).max(1).optional(),
|
||||
topK: z.number().min(1).max(40).optional(),
|
||||
topK: z.number().min(0).max(500).optional(),
|
||||
stopSequences: z.array(z.string().max(500)).max(5).optional(),
|
||||
seed: z.number().int().optional(),
|
||||
frequencyPenalty: z.number().optional().default(0),
|
||||
presencePenalty: z.number().optional().default(0),
|
||||
thinkingConfig: z.object({
|
||||
includeThoughts: z.boolean().optional(),
|
||||
thinkingBudget: z.union([
|
||||
z.literal("auto"),
|
||||
z.number().int()
|
||||
]).optional()
|
||||
}).optional(),
|
||||
responseModalities: z.any().optional(), // responseModalities: z.array(z.enum(["TEXT"])).optional()
|
||||
})
|
||||
.default({}),
|
||||
})
|
||||
@@ -91,15 +114,11 @@ export const transformOpenAIToGoogleAI: APIFormatTransformer<
|
||||
}
|
||||
|
||||
const { messages, ...rest } = result.data;
|
||||
|
||||
const foundNames = new Set<string>();
|
||||
const contents = messages
|
||||
.map((m) => {
|
||||
const role = m.role === "assistant" ? "model" : "user";
|
||||
// Detects character names so we can set stop sequences for them as Gemini
|
||||
// is prone to continuing as the next character.
|
||||
// If names are not available, we'll still try to prefix the message
|
||||
// with generic names so we can set stops for them but they don't work
|
||||
// as well as real names.
|
||||
const text = flattenOpenAIMessageContent(m.content);
|
||||
const propName = m.name?.trim();
|
||||
const textName =
|
||||
@@ -109,12 +128,6 @@ export const transformOpenAIToGoogleAI: APIFormatTransformer<
|
||||
|
||||
foundNames.add(name);
|
||||
|
||||
// Prefixing messages with their character name seems to help avoid
|
||||
// Gemini trying to continue as the next character, or at the very least
|
||||
// ensures it will hit the stop sequence. Otherwise it will start a new
|
||||
// paragraph and switch perspectives.
|
||||
// The response will be very likely to include this prefix so frontends
|
||||
// will need to strip it out.
|
||||
const textPrefix = textName ? "" : `${name}: `;
|
||||
return {
|
||||
parts: [{ text: textPrefix + text }],
|
||||
@@ -123,7 +136,7 @@ export const transformOpenAIToGoogleAI: APIFormatTransformer<
|
||||
})
|
||||
.reduce<GoogleAIChatMessage[]>((acc, msg) => {
|
||||
const last = acc[acc.length - 1];
|
||||
if (last?.role === msg.role) {
|
||||
if (last?.role === msg.role && 'text' in last.parts[0] && 'text' in msg.parts[0]) {
|
||||
last.parts[0].text += "\n\n" + msg.parts[0].text;
|
||||
} else {
|
||||
acc.push(msg);
|
||||
@@ -139,17 +152,36 @@ export const transformOpenAIToGoogleAI: APIFormatTransformer<
|
||||
stops.push(...Array.from(foundNames).map((name) => `\n${name}:`));
|
||||
stops = [...new Set(stops)].slice(0, 5);
|
||||
|
||||
let tools: z.infer<typeof ToolSchema>[] | undefined = undefined;
|
||||
let responseModalities: string[] | undefined = undefined;
|
||||
|
||||
if (req.body.use_google_search === true) {
|
||||
req.log.info("Google Search tool requested.");
|
||||
tools = [{ googleSearch: {} }];
|
||||
responseModalities = ["TEXT"];
|
||||
}
|
||||
|
||||
let thinkingConfig = undefined;
|
||||
if (body.generationConfig?.thinkingConfig || body.thinkingConfig) {
|
||||
thinkingConfig = body.generationConfig?.thinkingConfig || body.thinkingConfig;
|
||||
}
|
||||
|
||||
return {
|
||||
model: req.body.model,
|
||||
stream: rest.stream,
|
||||
contents,
|
||||
tools: [],
|
||||
tools: tools,
|
||||
generationConfig: {
|
||||
maxOutputTokens: rest.max_tokens,
|
||||
stopSequences: stops,
|
||||
topP: rest.top_p,
|
||||
topK: 40, // openai schema doesn't have this, google ai defaults to 40
|
||||
topK: 40,
|
||||
temperature: rest.temperature,
|
||||
seed: rest.seed,
|
||||
frequencyPenalty: rest.frequency_penalty,
|
||||
presencePenalty: rest.presence_penalty,
|
||||
responseModalities: responseModalities,
|
||||
...(thinkingConfig ? { thinkingConfig } : {})
|
||||
},
|
||||
safetySettings: [
|
||||
{ category: "HARM_CATEGORY_HARASSMENT", threshold: "BLOCK_NONE" },
|
||||
@@ -158,5 +190,14 @@ export const transformOpenAIToGoogleAI: APIFormatTransformer<
|
||||
{ category: "HARM_CATEGORY_DANGEROUS_CONTENT", threshold: "BLOCK_NONE" },
|
||||
{ category: "HARM_CATEGORY_CIVIC_INTEGRITY", threshold: "BLOCK_NONE" },
|
||||
],
|
||||
...(req.body.system_instruction && { system_instruction: req.body.system_instruction }),
|
||||
...(req.body.systemInstruction && { systemInstruction: req.body.systemInstruction }),
|
||||
};
|
||||
};
|
||||
|
||||
export function containsImageContent(contents: GoogleAIChatMessage[]): boolean {
|
||||
return contents.some(content => {
|
||||
const parts = Array.isArray(content.parts) ? content.parts : [content.parts];
|
||||
return parts.some(part => 'inlineData' in part);
|
||||
});
|
||||
}
|
||||
|
||||
@@ -17,6 +17,10 @@ import {
|
||||
OpenAIV1ImagesGenerationSchema,
|
||||
transformOpenAIToOpenAIImage,
|
||||
} from "./openai-image";
|
||||
import {
|
||||
OpenAIV1ResponsesSchema,
|
||||
transformOpenAIToOpenAIResponses,
|
||||
} from "./openai-responses";
|
||||
import {
|
||||
GoogleAIV1GenerateContentSchema,
|
||||
transformOpenAIToGoogleAI,
|
||||
@@ -52,6 +56,7 @@ export const API_REQUEST_TRANSFORMERS: TransformerMap = {
|
||||
"openai->anthropic-text": transformOpenAIToAnthropicText,
|
||||
"openai->openai-text": transformOpenAIToOpenAIText,
|
||||
"openai->openai-image": transformOpenAIToOpenAIImage,
|
||||
"openai->openai-responses": transformOpenAIToOpenAIResponses,
|
||||
"openai->google-ai": transformOpenAIToGoogleAI,
|
||||
"mistral-ai->mistral-text": transformMistralChatToText,
|
||||
};
|
||||
@@ -62,6 +67,7 @@ export const API_REQUEST_VALIDATORS: Record<APIFormat, z.ZodSchema<any>> = {
|
||||
openai: OpenAIV1ChatCompletionSchema,
|
||||
"openai-text": OpenAIV1TextCompletionSchema,
|
||||
"openai-image": OpenAIV1ImagesGenerationSchema,
|
||||
"openai-responses": OpenAIV1ResponsesSchema,
|
||||
"google-ai": GoogleAIV1GenerateContentSchema,
|
||||
"mistral-ai": MistralAIV1ChatCompletionsSchema,
|
||||
"mistral-text": MistralAIV1TextCompletionsSchema,
|
||||
|
||||
@@ -4,9 +4,61 @@ import { Template } from "@huggingface/jinja";
|
||||
import { APIFormatTransformer } from "./index";
|
||||
import { logger } from "../../logger";
|
||||
|
||||
// Define the content types for multimodal messages
|
||||
export const TextContentSchema = z.object({
|
||||
type: z.literal("text"),
|
||||
text: z.string()
|
||||
});
|
||||
|
||||
export const ImageUrlContentSchema = z.object({
|
||||
type: z.literal("image_url"),
|
||||
image_url: z.union([
|
||||
// URL format (https://...)
|
||||
z.string().url(),
|
||||
// Base64 format (data:image/jpeg;base64,...)
|
||||
z.string().regex(/^data:image\/(jpeg|png|gif|webp);base64,/),
|
||||
// Object format (might contain detail or url properties)
|
||||
z.record(z.any()),
|
||||
// Allow any string for maximum compatibility
|
||||
z.string()
|
||||
])
|
||||
});
|
||||
|
||||
export const ContentItemSchema = z.union([TextContentSchema, ImageUrlContentSchema]);
|
||||
|
||||
// Export types for the content schemas
|
||||
export type TextContent = z.infer<typeof TextContentSchema>;
|
||||
export type ImageUrlContent = z.infer<typeof ImageUrlContentSchema>;
|
||||
export type ContentItem = z.infer<typeof ContentItemSchema>;
|
||||
|
||||
// List of Mistral models with vision capabilities
|
||||
export const MISTRAL_VISION_MODELS = [
|
||||
"pixtral-12b-2409",
|
||||
"pixtral-12b-latest",
|
||||
"pixtral-large-2411",
|
||||
"pixtral-large-latest",
|
||||
"mistral-small-2503",
|
||||
"mistral-small-latest",
|
||||
"mistral-medium-latest",
|
||||
"mistral-medium-2505"
|
||||
];
|
||||
|
||||
// Helper function to check if a model supports vision
|
||||
export function isMistralVisionModel(model: string): boolean {
|
||||
return MISTRAL_VISION_MODELS.some(visionModel =>
|
||||
model === visionModel ||
|
||||
model.startsWith(`${visionModel}-`)
|
||||
);
|
||||
}
|
||||
|
||||
// Main Mistral chat message schema
|
||||
const MistralChatMessageSchema = z.object({
|
||||
role: z.enum(["system", "user", "assistant", "tool"]), // TODO: implement tools
|
||||
content: z.string(),
|
||||
// Support both string content (for backwards compatibility) and array of content items (for multimodal)
|
||||
content: z.union([
|
||||
z.string(),
|
||||
z.array(ContentItemSchema)
|
||||
]),
|
||||
prefix: z.boolean().optional(),
|
||||
});
|
||||
|
||||
@@ -107,7 +159,26 @@ export function fixMistralPrompt(
|
||||
// Consolidate multiple messages from the same role
|
||||
const last = acc[acc.length - 1];
|
||||
if (last.role === copy.role) {
|
||||
last.content += "\n\n" + copy.content;
|
||||
// Handle different content types for consolidation
|
||||
if (typeof last.content === "string" && typeof copy.content === "string") {
|
||||
// Both are strings, concatenate them
|
||||
last.content += "\n\n" + copy.content;
|
||||
} else if (Array.isArray(last.content) && typeof copy.content === "string") {
|
||||
// Add the string content as a new text content item
|
||||
last.content.push({
|
||||
type: "text",
|
||||
text: copy.content
|
||||
});
|
||||
} else if (typeof last.content === "string" && Array.isArray(copy.content)) {
|
||||
// Convert last.content to array and append copy.content items
|
||||
last.content = [
|
||||
{ type: "text", text: last.content },
|
||||
...copy.content
|
||||
];
|
||||
} else if (Array.isArray(last.content) && Array.isArray(copy.content)) {
|
||||
// Both are arrays, concatenate them
|
||||
last.content = [...last.content, ...copy.content];
|
||||
}
|
||||
} else {
|
||||
acc.push(copy);
|
||||
}
|
||||
@@ -125,18 +196,41 @@ export function fixMistralPrompt(
|
||||
|
||||
let jinjaTemplate: Template;
|
||||
let renderTemplate: (messages: MistralAIChatMessage[]) => string;
|
||||
|
||||
// Helper function to convert multimodal content to string format for text-only models
|
||||
function contentToString(content: string | any[]): string {
|
||||
if (typeof content === "string") {
|
||||
return content;
|
||||
} else if (Array.isArray(content)) {
|
||||
// For multimodal content, extract only the text parts
|
||||
// Images are not supported in text-only templates
|
||||
return content
|
||||
.filter(item => item.type === "text")
|
||||
.map(item => (item as any).text)
|
||||
.join("\n\n");
|
||||
}
|
||||
return "";
|
||||
}
|
||||
|
||||
function renderMistralPrompt(messages: MistralAIChatMessage[]) {
|
||||
if (!jinjaTemplate) {
|
||||
logger.warn("Lazy loading mistral chat template...");
|
||||
const { chatTemplate, bosToken, eosToken } =
|
||||
require("./templates/mistral-template").MISTRAL_TEMPLATE;
|
||||
jinjaTemplate = new Template(chatTemplate);
|
||||
renderTemplate = (messages) =>
|
||||
jinjaTemplate.render({
|
||||
messages,
|
||||
renderTemplate = (messages) => {
|
||||
// We need to convert any multimodal content to string format for the template
|
||||
const textOnlyMessages = messages.map(msg => ({
|
||||
...msg,
|
||||
content: contentToString(msg.content)
|
||||
}));
|
||||
|
||||
return jinjaTemplate.render({
|
||||
messages: textOnlyMessages,
|
||||
bos_token: bosToken,
|
||||
eos_token: eosToken,
|
||||
});
|
||||
};
|
||||
}
|
||||
|
||||
return renderTemplate(messages);
|
||||
@@ -145,6 +239,9 @@ function renderMistralPrompt(messages: MistralAIChatMessage[]) {
|
||||
/**
|
||||
* Attempts to convert a Mistral chat completions request to a text completions,
|
||||
* using the official prompt template published by Mistral.
|
||||
*
|
||||
* Note: This transformation is only applicable for text-only models.
|
||||
* Multimodal/vision models (Pixtral, etc.) cannot use this transformation.
|
||||
*/
|
||||
export const transformMistralChatToText: APIFormatTransformer<
|
||||
typeof MistralAIV1TextCompletionsSchema
|
||||
@@ -159,8 +256,24 @@ export const transformMistralChatToText: APIFormatTransformer<
|
||||
throw result.error;
|
||||
}
|
||||
|
||||
const { messages, ...rest } = result.data;
|
||||
const prompt = renderMistralPrompt(messages);
|
||||
// Check if this is a vision request (contains any image_url content items)
|
||||
const { messages, model, ...rest } = result.data;
|
||||
const hasVisionContent = messages.some(msg =>
|
||||
Array.isArray(msg.content) &&
|
||||
msg.content.some(item => item.type === "image_url")
|
||||
);
|
||||
|
||||
return { ...rest, prompt, messages: undefined };
|
||||
// Cannot transform vision requests to text completions
|
||||
if (hasVisionContent) {
|
||||
req.log.warn(
|
||||
{ model },
|
||||
"Cannot transform Mistral vision request to text completions format"
|
||||
);
|
||||
throw new Error(
|
||||
"Vision requests (with image_url content) cannot be transformed to text completions format"
|
||||
);
|
||||
}
|
||||
|
||||
const prompt = renderMistralPrompt(messages);
|
||||
return { ...rest, model, prompt, messages: undefined };
|
||||
};
|
||||
|
||||
@@ -0,0 +1,87 @@
|
||||
import { z } from "zod";
|
||||
import { OPENAI_OUTPUT_MAX } from "./openai";
|
||||
|
||||
/**
|
||||
* Helper function to check if a model is from Moonshot
|
||||
*/
|
||||
export function isMoonshotModel(model: string): boolean {
|
||||
return model.includes("moonshot");
|
||||
}
|
||||
|
||||
/**
|
||||
* Helper function to check if a model is a Moonshot vision model
|
||||
*/
|
||||
export function isMoonshotVisionModel(model: string): boolean {
|
||||
return model.includes("moonshot") && model.includes("vision");
|
||||
}
|
||||
|
||||
// Content schema for vision models
|
||||
const MoonshotVisionContentSchema = z.union([
|
||||
z.string(),
|
||||
z.array(
|
||||
z.union([
|
||||
z.object({
|
||||
type: z.literal("text"),
|
||||
text: z.string(),
|
||||
}),
|
||||
z.object({
|
||||
type: z.literal("image_url"),
|
||||
image_url: z.object({
|
||||
url: z.string(),
|
||||
detail: z.enum(["low", "high", "auto"]).optional(),
|
||||
}),
|
||||
}),
|
||||
])
|
||||
),
|
||||
]);
|
||||
|
||||
// Basic chat message schema
|
||||
const MoonshotChatMessageSchema = z.object({
|
||||
role: z.enum(["user", "assistant", "system"]),
|
||||
content: z.union([z.string(), MoonshotVisionContentSchema]).nullable(),
|
||||
name: z.string().optional(),
|
||||
// Support for partial mode
|
||||
partial: z.boolean().optional(),
|
||||
});
|
||||
|
||||
const MoonshotMessagesSchema = z.array(MoonshotChatMessageSchema);
|
||||
|
||||
// Schema for Moonshot chat completions
|
||||
export const MoonshotV1ChatCompletionsSchema = z.object({
|
||||
model: z.string(),
|
||||
messages: MoonshotMessagesSchema,
|
||||
temperature: z.number().optional().default(0.3),
|
||||
top_p: z.number().optional().default(1),
|
||||
max_tokens: z.coerce
|
||||
.number()
|
||||
.int()
|
||||
.nullish()
|
||||
.transform((v) => Math.min(v ?? OPENAI_OUTPUT_MAX, OPENAI_OUTPUT_MAX)),
|
||||
stream: z.boolean().optional().default(false),
|
||||
stop: z
|
||||
.union([z.string(), z.array(z.string()).max(5)])
|
||||
.optional()
|
||||
.default([])
|
||||
.transform((v) => (Array.isArray(v) ? v : [v])),
|
||||
seed: z.number().int().min(0).optional(),
|
||||
response_format: z
|
||||
.object({
|
||||
type: z.enum(["text", "json_object"])
|
||||
})
|
||||
.optional(),
|
||||
tools: z.array(z.any()).optional(),
|
||||
tool_choice: z.any().optional(),
|
||||
frequency_penalty: z.number().min(-2).max(2).optional().default(0),
|
||||
presence_penalty: z.number().min(-2).max(2).optional().default(0),
|
||||
n: z.number().int().min(1).max(5).optional().default(1),
|
||||
});
|
||||
|
||||
// Schema for Moonshot embeddings
|
||||
export const MoonshotV1EmbeddingsSchema = z.object({
|
||||
model: z.string(),
|
||||
input: z.union([z.string(), z.array(z.string())]),
|
||||
encoding_format: z.enum(["float", "base64"]).optional()
|
||||
});
|
||||
|
||||
// Note: Partial mode handling is implemented directly in the proxy middleware
|
||||
// to follow the Deepseek-style consolidation pattern
|
||||
@@ -1,20 +1,58 @@
|
||||
import { z } from "zod";
|
||||
import { Request } from "express";
|
||||
import { OpenAIV1ChatCompletionSchema } from "./openai";
|
||||
import { APIFormatTransformer } from "./index";
|
||||
|
||||
// Extend the Express Request type to include multimodal content
|
||||
declare global {
|
||||
namespace Express {
|
||||
interface Request {
|
||||
multimodalContent?: {
|
||||
prompt?: string;
|
||||
images?: string[];
|
||||
};
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// https://platform.openai.com/docs/api-reference/images/create
|
||||
export const OpenAIV1ImagesGenerationSchema = z
|
||||
.object({
|
||||
prompt: z.string().max(4000),
|
||||
prompt: z.string().max(32000), // gpt-image-1 supports up to 32000 chars
|
||||
model: z.string().max(100).optional(),
|
||||
quality: z.enum(["standard", "hd"]).optional().default("standard"),
|
||||
n: z.number().int().min(1).max(4).optional().default(1),
|
||||
response_format: z.enum(["url", "b64_json"]).optional(),
|
||||
// Support for image inputs (multimodal capability of gpt-image-1)
|
||||
image: z.union([
|
||||
z.string(), // single image (base64 or URL)
|
||||
z.array(z.string()) // array of images
|
||||
]).optional(),
|
||||
mask: z.string().optional(), // mask image for editing
|
||||
// Different quality options based on model
|
||||
quality: z
|
||||
.union([
|
||||
z.enum(["standard", "hd"]), // dall-e-3 options
|
||||
z.enum(["high", "medium", "low"]), // gpt-image-1 options
|
||||
z.literal("auto") // default for gpt-image-1
|
||||
])
|
||||
.optional()
|
||||
.default("standard"),
|
||||
n: z.number().int().min(1).max(10).optional().default(1), // gpt-image-1 supports up to 10
|
||||
response_format: z.enum(["url", "b64_json"]).optional(), // Note: gpt-image-1 always returns b64_json
|
||||
// Enhanced size options for gpt-image-1
|
||||
size: z
|
||||
.enum(["256x256", "512x512", "1024x1024", "1792x1024", "1024x1792"])
|
||||
.union([
|
||||
// dalle models
|
||||
z.enum(["256x256", "512x512", "1024x1024", "1792x1024", "1024x1792"]),
|
||||
// gpt-image-1 models (adds landscape, portrait, auto)
|
||||
z.enum(["1024x1024", "1536x1024", "1024x1536", "auto"])
|
||||
])
|
||||
.optional()
|
||||
.default("1024x1024"),
|
||||
style: z.enum(["vivid", "natural"]).optional().default("vivid"),
|
||||
style: z.enum(["vivid", "natural"]).optional().default("vivid"), // dall-e-3 only
|
||||
// New gpt-image-1 specific parameters
|
||||
background: z.enum(["transparent", "opaque", "auto"]).optional(), // gpt-image-1 only
|
||||
moderation: z.enum(["low", "auto"]).optional(), // gpt-image-1 only
|
||||
output_compression: z.number().int().min(0).max(100).optional(), // gpt-image-1 only
|
||||
output_format: z.enum(["png", "jpeg", "webp"]).optional(), // gpt-image-1 only
|
||||
user: z.string().max(500).optional(),
|
||||
})
|
||||
.strip();
|
||||
@@ -34,9 +72,41 @@ export const transformOpenAIToOpenAIImage: APIFormatTransformer<
|
||||
}
|
||||
|
||||
const { messages } = result.data;
|
||||
const prompt = messages.filter((m) => m.role === "user").pop()?.content;
|
||||
if (Array.isArray(prompt)) {
|
||||
throw new Error("Image generation prompt must be a text message.");
|
||||
const userMessage = messages.filter((m) => m.role === "user").pop();
|
||||
if (!userMessage) {
|
||||
throw new Error("No user message found in the request.");
|
||||
}
|
||||
|
||||
const content = userMessage.content;
|
||||
|
||||
// Handle array content (multimodal content with text and images)
|
||||
if (Array.isArray(content)) {
|
||||
const textParts: string[] = [];
|
||||
const imageParts: string[] = [];
|
||||
|
||||
// Process content parts, extracting text and images
|
||||
content.forEach(part => {
|
||||
if (typeof part === 'string') {
|
||||
textParts.push(part);
|
||||
} else if (part.type === 'image_url') {
|
||||
// Extract image URL or base64 data from the content
|
||||
const imageUrl = typeof part.image_url === 'string'
|
||||
? part.image_url
|
||||
: part.image_url.url;
|
||||
imageParts.push(imageUrl);
|
||||
}
|
||||
});
|
||||
|
||||
// Join all text parts to form the prompt
|
||||
const prompt = textParts.join('\n');
|
||||
|
||||
// For gpt-image-1, we'll pass both the text prompt and image(s)
|
||||
req.multimodalContent = {
|
||||
prompt,
|
||||
images: imageParts
|
||||
};
|
||||
} else if (typeof content !== 'string') {
|
||||
throw new Error("Image generation prompt must be a text message or multimodal content.");
|
||||
}
|
||||
|
||||
if (body.stream) {
|
||||
@@ -49,20 +119,206 @@ export const transformOpenAIToOpenAIImage: APIFormatTransformer<
|
||||
// character name or wrapping the entire thing in quotes. We will look for
|
||||
// the index of "Image:" and use everything after that as the prompt.
|
||||
|
||||
const index = prompt?.toLowerCase().indexOf("image:");
|
||||
if (index === -1 || !prompt) {
|
||||
throw new Error(
|
||||
`Start your prompt with 'Image:' followed by a description of the image you want to generate (received: ${prompt}).`
|
||||
);
|
||||
// Determine if this is a multimodal request (with images)
|
||||
const isMultimodalRequest = Array.isArray(content) && req.multimodalContent?.images && req.multimodalContent.images.length > 0;
|
||||
|
||||
// Check if this is a request for gpt-image-1
|
||||
const isGptImageRequest = body.model?.includes("gpt-image") || false;
|
||||
|
||||
// Only enforce the "Image:" prefix for non-multimodal, non-gpt-image-1 requests
|
||||
if (!isMultimodalRequest && !isGptImageRequest && typeof content === 'string') {
|
||||
const textIndex = content.toLowerCase().indexOf("image:");
|
||||
if (textIndex === -1) {
|
||||
throw new Error(
|
||||
`Start your prompt with 'Image:' followed by a description of the image you want to generate (received: ${content}).`
|
||||
);
|
||||
}
|
||||
}
|
||||
|
||||
// TODO: Add some way to specify parameters via chat message
|
||||
// Determine which model to use (gpt-image-1 or dall-e-3)
|
||||
const isGptImage = body.model?.includes("gpt-image") || false;
|
||||
|
||||
// For gpt-image-1, add the 'Image:' prefix if it's missing but only for string content
|
||||
let modifiedStringContent = typeof content === 'string' ? content : '';
|
||||
if (isGptImageRequest && typeof content === 'string' && !content.toLowerCase().includes("image:")) {
|
||||
req.log.info("Adding 'Image:' prefix to gpt-image-1 prompt");
|
||||
modifiedStringContent = `Image: ${content}`;
|
||||
// Store this in the request object for later use
|
||||
req.multimodalContent = req.multimodalContent || {};
|
||||
req.multimodalContent.prompt = modifiedStringContent;
|
||||
}
|
||||
|
||||
// TODO: Add some way to specify parameters via chat message
|
||||
const transformed = {
|
||||
model: body.model.includes("dall-e") ? body.model : "dall-e-3",
|
||||
quality: "standard",
|
||||
size: "1024x1024",
|
||||
response_format: "url",
|
||||
prompt: prompt.slice(index! + 6).trim(),
|
||||
// Get the correct text prompt either from multimodal content or plain string content
|
||||
let textPrompt: string | undefined;
|
||||
let index = -1;
|
||||
|
||||
if (Array.isArray(content)) {
|
||||
// For array content, use the prompt from multimodal content if available
|
||||
textPrompt = req.multimodalContent?.prompt;
|
||||
} else if (typeof content === 'string') {
|
||||
// For string content, use the modified content which might have the Image: prefix for gpt-image-1
|
||||
const contentToProcess = isGptImageRequest ? modifiedStringContent : content;
|
||||
|
||||
// Find the "Image:" prefix in the content
|
||||
index = contentToProcess.toLowerCase().indexOf("image:");
|
||||
|
||||
// For gpt-image-1, we might have just added the prefix, so we need to handle both cases
|
||||
if (index !== -1) {
|
||||
textPrompt = contentToProcess.slice(index + 6).trim();
|
||||
} else if (isGptImageRequest) {
|
||||
// For gpt-image-1, use the whole content if no prefix is found
|
||||
textPrompt = content; // Use the original content without prefix
|
||||
} else {
|
||||
// For other models, default to the content as-is
|
||||
textPrompt = contentToProcess;
|
||||
}
|
||||
}
|
||||
|
||||
// Validate that we have a text prompt
|
||||
if (!textPrompt) {
|
||||
throw new Error("No text prompt found in the request.");
|
||||
}
|
||||
|
||||
// Determine the exact model being used
|
||||
let modelName = "dall-e-2"; // Default
|
||||
|
||||
if (isGptImage) {
|
||||
modelName = "gpt-image-1";
|
||||
} else if (body.model?.includes("dall-e-3")) {
|
||||
modelName = "dall-e-3";
|
||||
} else if (body.model?.includes("dall-e-2")) {
|
||||
modelName = "dall-e-2";
|
||||
} else {
|
||||
// If no specific model requested, default to dall-e-3
|
||||
modelName = "dall-e-3";
|
||||
}
|
||||
|
||||
// Start with basic parameters common to all models
|
||||
const transformed: any = {
|
||||
model: modelName,
|
||||
prompt: textPrompt,
|
||||
};
|
||||
|
||||
// Add model-specific parameters
|
||||
if (modelName === "gpt-image-1") {
|
||||
// GPT Image specific parameters - Ensure we only include parameters that are valid for gpt-image-1
|
||||
transformed.quality = "auto"; // Default quality for gpt-image-1
|
||||
transformed.size = "1024x1024"; // Default size (square)
|
||||
transformed.moderation = "low"; // Always set moderation to low for gpt-image-1
|
||||
|
||||
// Optional GPT Image parameters
|
||||
if (body.background) transformed.background = body.background;
|
||||
if (body.output_format) transformed.output_format = body.output_format;
|
||||
if (body.output_compression) transformed.output_compression = body.output_compression;
|
||||
|
||||
// Handle specific quality settings for gpt-image-1
|
||||
if (body.quality && ["high", "medium", "low", "auto"].includes(body.quality)) {
|
||||
transformed.quality = body.quality;
|
||||
}
|
||||
|
||||
// Handle specific size settings for gpt-image-1
|
||||
if (body.size && ["1024x1024", "1536x1024", "1024x1536", "auto"].includes(body.size)) {
|
||||
transformed.size = body.size;
|
||||
}
|
||||
|
||||
// IMPORTANT: Remove any style parameter as it's not supported by gpt-image-1
|
||||
delete transformed.style;
|
||||
|
||||
// Log what we're sending for debugging
|
||||
req.log.info({ model: "gpt-image-1", allowedParams: Object.keys(transformed) }, "Filtered parameters for gpt-image-1");
|
||||
|
||||
// No response_format for gpt-image-1 as it always returns b64_json
|
||||
} else if (modelName === "dall-e-3") {
|
||||
// DALL-E 3 specific parameters
|
||||
transformed.size = "1024x1024"; // Default size
|
||||
transformed.response_format = "url"; // Default format
|
||||
transformed.quality = "standard"; // Default quality
|
||||
|
||||
// Handle DALL-E 3 style parameter
|
||||
if (body.style && ["vivid", "natural"].includes(body.style)) {
|
||||
transformed.style = body.style;
|
||||
} else {
|
||||
transformed.style = "vivid"; // Default style
|
||||
}
|
||||
|
||||
// Handle specific quality settings for dall-e-3
|
||||
if (body.quality && ["standard", "hd"].includes(body.quality)) {
|
||||
transformed.quality = body.quality;
|
||||
}
|
||||
|
||||
// Handle specific size settings for dall-e-3
|
||||
if (body.size && ["1024x1024", "1792x1024", "1024x1792"].includes(body.size)) {
|
||||
transformed.size = body.size;
|
||||
}
|
||||
} else {
|
||||
// DALL-E 2 specific parameters
|
||||
transformed.size = "1024x1024"; // Default size
|
||||
transformed.response_format = "url"; // Default format
|
||||
|
||||
// NO quality parameter for dall-e-2
|
||||
// Explicitly remove the quality parameter before sending
|
||||
delete transformed.quality;
|
||||
|
||||
// Handle specific size settings for dall-e-2
|
||||
if (body.size && ["256x256", "512x512", "1024x1024"].includes(body.size)) {
|
||||
transformed.size = body.size;
|
||||
}
|
||||
}
|
||||
|
||||
// Handle common parameters
|
||||
if (body.n && !isNaN(parseInt(body.n))) {
|
||||
// For dall-e-3, only n=1 is supported
|
||||
if (modelName === "dall-e-3" && parseInt(body.n) > 1) {
|
||||
transformed.n = 1;
|
||||
} else {
|
||||
transformed.n = parseInt(body.n);
|
||||
}
|
||||
}
|
||||
|
||||
// Handle response_format for non-gpt-image models
|
||||
if (!isGptImage && body.response_format && ["url", "b64_json"].includes(body.response_format)) {
|
||||
transformed.response_format = body.response_format;
|
||||
}
|
||||
|
||||
// If this is gpt-image-1 and we have image content, add it to the transformed request
|
||||
if (isGptImage && req.multimodalContent?.images && req.multimodalContent.images.length > 0) {
|
||||
// For the edit endpoint, we need to format the images properly
|
||||
transformed.image = req.multimodalContent.images.length === 1
|
||||
? req.multimodalContent.images[0]
|
||||
: req.multimodalContent.images;
|
||||
|
||||
// Any request with images for gpt-image-1 should use the edits endpoint
|
||||
req.log.info(`${req.multimodalContent.images.length} image(s) detected for gpt-image-1, using images/edits endpoint`);
|
||||
if (req.path.startsWith("/v1/chat/completions")) {
|
||||
req.url = req.url.replace("/v1/chat/completions", "/v1/images/edits");
|
||||
}
|
||||
}
|
||||
// For dall-e-2, we need to make sure we don't introduce unsupported parameters
|
||||
// due to default values in the schema. Let's bypass Zod schema validation here
|
||||
// for dall-e-2 and only include the supported parameters.
|
||||
if (modelName === "dall-e-2") {
|
||||
// Only include parameters that dall-e-2 supports
|
||||
const filteredTransformed: any = {};
|
||||
|
||||
// List of parameters supported by dall-e-2
|
||||
const supportedParams = [
|
||||
"model", "prompt", "n", "size", "response_format", "user"
|
||||
];
|
||||
|
||||
// Copy only supported parameters
|
||||
for (const param of supportedParams) {
|
||||
if (transformed[param] !== undefined) {
|
||||
filteredTransformed[param] = transformed[param];
|
||||
}
|
||||
}
|
||||
|
||||
// Log what we're sending
|
||||
req.log.info({ model: "dall-e-2", params: Object.keys(filteredTransformed) }, "Filtered parameters for dall-e-2");
|
||||
|
||||
return filteredTransformed;
|
||||
}
|
||||
|
||||
// For other models, use the schema as normal
|
||||
return OpenAIV1ImagesGenerationSchema.parse(transformed);
|
||||
};
|
||||
|
||||
@@ -0,0 +1,61 @@
|
||||
import { z } from "zod";
|
||||
import { Request } from "express";
|
||||
import { OpenAIChatMessage, OpenAIV1ChatCompletionSchema } from "./openai";
|
||||
|
||||
// Schema for the OpenAI Responses API based on the chat completion schema
|
||||
// with some additional fields specific to the Responses API
|
||||
export const OpenAIV1ResponsesSchema = z.object({
|
||||
model: z.string(),
|
||||
input: z.object({
|
||||
messages: z.array(z.any())
|
||||
}).optional(),
|
||||
previousResponseId: z.string().optional(),
|
||||
max_output_tokens: z.number().int().positive().optional(),
|
||||
temperature: z.number().min(0).max(2).optional(),
|
||||
top_p: z.number().min(0).max(1).optional(),
|
||||
n: z.number().int().positive().optional(),
|
||||
stream: z.boolean().optional(),
|
||||
stop: z.union([z.string(), z.array(z.string())]).optional(),
|
||||
presence_penalty: z.number().min(-2).max(2).optional(),
|
||||
frequency_penalty: z.number().min(-2).max(2).optional(),
|
||||
user: z.string().optional(),
|
||||
tools: z.array(z.any()).optional(),
|
||||
reasoning_effort: z.enum(["low", "medium", "high"]).optional(),
|
||||
});
|
||||
|
||||
// Allow transforming from OpenAI Chat to Responses format
|
||||
export async function transformOpenAIToOpenAIResponses(
|
||||
req: Request
|
||||
): Promise<z.infer<typeof OpenAIV1ResponsesSchema>> {
|
||||
const body = { ...req.body };
|
||||
|
||||
// Move 'messages' to 'input.messages' as required by the Responses API
|
||||
if (body.messages && !body.input) {
|
||||
body.input = {
|
||||
messages: body.messages
|
||||
};
|
||||
delete body.messages;
|
||||
}
|
||||
|
||||
// Convert max_tokens to max_output_tokens if present and not set
|
||||
if (body.max_tokens && !body.max_output_tokens) {
|
||||
body.max_output_tokens = body.max_tokens;
|
||||
delete body.max_tokens;
|
||||
}
|
||||
|
||||
// Map conversation_id to previousResponseId if present
|
||||
if (body.conversation_id && !body.previousResponseId) {
|
||||
body.previousResponseId = body.conversation_id;
|
||||
delete body.conversation_id;
|
||||
}
|
||||
|
||||
// Ensure tools have the right format if present
|
||||
if (body.tools) {
|
||||
body.tools = body.tools.map((tool: any) => ({
|
||||
...tool,
|
||||
type: tool.type || "function"
|
||||
}));
|
||||
}
|
||||
|
||||
return body;
|
||||
}
|
||||
@@ -21,11 +21,11 @@ export const OpenAIV1ChatCompletionSchema = z
|
||||
model: z.string().max(100),
|
||||
messages: z.array(
|
||||
z.object({
|
||||
role: z.enum(["system", "user", "assistant", "tool", "function"]),
|
||||
role: z.enum(["system", "developer", "user", "assistant", "tool", "function"]),
|
||||
content: z.union([z.string(), OpenAIV1ChatContentArraySchema]),
|
||||
name: z.string().optional(),
|
||||
tool_calls: z.array(z.any()).optional(),
|
||||
function_call: z.array(z.any()).optional(),
|
||||
function_call: z.any().optional(),
|
||||
tool_call_id: z.string().optional(),
|
||||
}),
|
||||
{
|
||||
@@ -77,12 +77,14 @@ export const OpenAIV1ChatCompletionSchema = z
|
||||
functions: z.array(z.any()).optional(),
|
||||
tool_choice: z.any().optional(),
|
||||
function_choice: z.any().optional(),
|
||||
reasoning_effort: z.enum(["minimal", "low", "medium", "high"]).optional(),
|
||||
verbosity: z.enum(["low", "medium", "high"]).optional(),
|
||||
response_format: z.any(),
|
||||
})
|
||||
// Tool usage must be enabled via config because we currently have no way to
|
||||
// track quota usage for them or enforce limits.
|
||||
.omit(
|
||||
Boolean(config.allowOpenAIToolUsage) ? {} : { tools: true, functions: true }
|
||||
!Boolean(config.allowOpenAIToolUsage) ? { tools: true, functions: true } : {}
|
||||
)
|
||||
.strip();
|
||||
export type OpenAIChatMessage = z.infer<
|
||||
|
||||
@@ -0,0 +1,118 @@
|
||||
import { z } from "zod";
|
||||
import { OPENAI_OUTPUT_MAX } from "./openai";
|
||||
|
||||
/**
|
||||
* Helper function to check if a model is from Qwen
|
||||
*/
|
||||
export function isQwenModel(model: string): boolean {
|
||||
// Remove any suffix like -thinking or -nonthinking for checking
|
||||
const baseModel = model.replace(/-thinking$|-nonthinking$/, '');
|
||||
return baseModel.startsWith("qwen") || baseModel.includes("qwen");
|
||||
}
|
||||
|
||||
/**
|
||||
* Helper function to check if a model supports thinking capability
|
||||
*/
|
||||
export function isQwenThinkingModel(model: string): boolean {
|
||||
// Remove any suffix like -thinking or -nonthinking for checking
|
||||
const baseModel = model.replace(/-thinking$|-nonthinking$/, '');
|
||||
|
||||
// All Qwen3 models support thinking
|
||||
if (baseModel.startsWith("qwen3")) {
|
||||
return true;
|
||||
}
|
||||
|
||||
// Other models that support thinking
|
||||
return (
|
||||
baseModel === "qwen-plus-latest" ||
|
||||
baseModel === "qwen-plus-2025-04-28" ||
|
||||
baseModel === "qwen-turbo-latest" ||
|
||||
baseModel === "qwen-turbo-2025-04-28"
|
||||
);
|
||||
}
|
||||
|
||||
// Basic chat message schema
|
||||
const QwenChatMessageSchema = z.object({
|
||||
role: z.enum(["user", "assistant", "system"]),
|
||||
content: z.string().nullable(),
|
||||
name: z.string().optional(),
|
||||
});
|
||||
|
||||
const QwenMessagesSchema = z.array(QwenChatMessageSchema);
|
||||
|
||||
// Schema for Qwen chat completions
|
||||
export const QwenV1ChatCompletionsSchema = z.object({
|
||||
model: z.string(),
|
||||
messages: QwenMessagesSchema,
|
||||
temperature: z.number().optional().default(1),
|
||||
top_p: z.number().optional().default(1),
|
||||
max_tokens: z.coerce
|
||||
.number()
|
||||
.int()
|
||||
.nullish()
|
||||
.transform((v) => Math.min(v ?? OPENAI_OUTPUT_MAX, OPENAI_OUTPUT_MAX)),
|
||||
stream: z.boolean().optional().default(false),
|
||||
stop: z
|
||||
.union([z.string(), z.array(z.string())])
|
||||
.optional()
|
||||
.default([])
|
||||
.transform((v) => (Array.isArray(v) ? v : [v])),
|
||||
seed: z.number().int().min(0).optional(),
|
||||
response_format: z
|
||||
.object({
|
||||
type: z.enum(["text", "json_object"]),
|
||||
schema: z.any().optional()
|
||||
})
|
||||
.optional(),
|
||||
tools: z.array(z.any()).optional(),
|
||||
frequency_penalty: z.number().optional().default(0),
|
||||
presence_penalty: z.number().optional().default(0),
|
||||
// Qwen-specific parameters
|
||||
enable_thinking: z.boolean().optional(),
|
||||
thinking_budget: z.number().optional(),
|
||||
});
|
||||
|
||||
// Schema for Qwen embeddings
|
||||
export const QwenV1EmbeddingsSchema = z.object({
|
||||
model: z.string(),
|
||||
input: z.union([z.string(), z.array(z.string())]),
|
||||
encoding_format: z.enum(["float", "base64"]).optional()
|
||||
});
|
||||
|
||||
/**
|
||||
* Helper function to normalize messages for Qwen API
|
||||
* Qwen uses the standard OpenAI message format, so no transformation is needed
|
||||
*/
|
||||
export function normalizeMessages(messages: any[]): any[] {
|
||||
return messages;
|
||||
}
|
||||
|
||||
/**
|
||||
* Helper function to check if a model is a Qwen3 model
|
||||
*/
|
||||
export function isQwen3Model(model: string): boolean {
|
||||
// Remove any suffix like -thinking or -nonthinking for checking
|
||||
const baseModel = model.replace(/-thinking$|-nonthinking$/, '');
|
||||
return baseModel.startsWith("qwen3");
|
||||
}
|
||||
|
||||
/**
|
||||
* Helper function to check if a model name has the thinking variant suffix
|
||||
*/
|
||||
export function isThinkingVariant(model: string): boolean {
|
||||
return model.endsWith("-thinking");
|
||||
}
|
||||
|
||||
/**
|
||||
* Helper function to check if a model name has the non-thinking variant suffix
|
||||
*/
|
||||
export function isNonThinkingVariant(model: string): boolean {
|
||||
return model.endsWith("-nonthinking");
|
||||
}
|
||||
|
||||
/**
|
||||
* Get the base model name without any thinking/nonthinking suffix
|
||||
*/
|
||||
export function getBaseModelName(model: string): string {
|
||||
return model.replace(/-thinking$|-nonthinking$/, '');
|
||||
}
|
||||
@@ -0,0 +1,167 @@
|
||||
import { z } from "zod";
|
||||
import { OPENAI_OUTPUT_MAX } from "./openai";
|
||||
|
||||
// Define the content types for multimodal messages
|
||||
export const TextContentSchema = z.object({
|
||||
type: z.literal("text"),
|
||||
text: z.string()
|
||||
});
|
||||
|
||||
export const ImageUrlContentSchema = z.object({
|
||||
type: z.literal("image_url"),
|
||||
image_url: z.union([
|
||||
// URL format (https://...)
|
||||
z.string().url(),
|
||||
// Base64 format (data:image/jpeg;base64,...)
|
||||
z.string().regex(/^data:image\/(jpeg|png|gif|webp);base64,/),
|
||||
// Object format (might contain detail or url properties)
|
||||
z.object({
|
||||
url: z.string(),
|
||||
detail: z.enum(["low", "high"]).optional()
|
||||
}),
|
||||
// Allow any string for maximum compatibility
|
||||
z.string()
|
||||
])
|
||||
});
|
||||
|
||||
export const ContentItemSchema = z.union([TextContentSchema, ImageUrlContentSchema]);
|
||||
|
||||
// Export types for the content schemas
|
||||
export type TextContent = z.infer<typeof TextContentSchema>;
|
||||
export type ImageUrlContent = z.infer<typeof ImageUrlContentSchema>;
|
||||
export type ContentItem = z.infer<typeof ContentItemSchema>;
|
||||
|
||||
// Helper function to check if a model supports vision
|
||||
export function isGrokVisionModel(model: string): boolean {
|
||||
// Check if the model name contains '-vision' anywhere in the name
|
||||
// This makes it future-proof for new vision models
|
||||
return model.toLowerCase().includes("-vision");
|
||||
}
|
||||
|
||||
// Helper function to check if a model supports image generation
|
||||
export function isGrokImageGenModel(model: string): boolean {
|
||||
// Check if the model name contains '-image' anywhere in the name
|
||||
// This makes it future-proof for new image generation models
|
||||
return model.toLowerCase().includes("-image");
|
||||
}
|
||||
|
||||
// Helper function to check if a model supports reasoning
|
||||
export function isGrokReasoningModel(model: string): boolean {
|
||||
// grok-3-mini variants and grok-4-0709 support reasoning
|
||||
const modelLower = model.toLowerCase();
|
||||
return (modelLower.includes("-mini") && modelLower.includes("grok-3")) ||
|
||||
modelLower.includes("grok-4");
|
||||
}
|
||||
|
||||
// Helper function to check if a model supports reasoning_effort parameter
|
||||
export function isGrokReasoningEffortModel(model: string): boolean {
|
||||
// Only grok-3-mini variants support reasoning_effort parameter
|
||||
// grok-4-0709 does NOT support reasoning_effort
|
||||
const modelLower = model.toLowerCase();
|
||||
return modelLower.includes("-mini") && modelLower.includes("grok-3");
|
||||
}
|
||||
|
||||
// Helper function to check if a model returns reasoning_content
|
||||
export function isGrokReasoningContentModel(model: string): boolean {
|
||||
// Only grok-3-mini variants return reasoning_content
|
||||
// grok-4-0709 does NOT return reasoning_content
|
||||
const modelLower = model.toLowerCase();
|
||||
return modelLower.includes("-mini") && modelLower.includes("grok-3");
|
||||
}
|
||||
|
||||
// Main Grok chat message schema
|
||||
const XaiChatMessageSchema = z.object({
|
||||
role: z.enum(["system", "user", "assistant", "tool", "function"]),
|
||||
// Support both string content (for backwards compatibility) and array of content items (for multimodal)
|
||||
content: z.union([
|
||||
z.string().nullable(),
|
||||
z.array(ContentItemSchema)
|
||||
]),
|
||||
// Reasoning content field (for grok-3-mini models)
|
||||
reasoning_content: z.string().optional(),
|
||||
// Tool call fields
|
||||
tool_call_id: z.string().optional(),
|
||||
name: z.string().optional(),
|
||||
tool_calls: z.array(z.any()).optional(),
|
||||
});
|
||||
|
||||
const XaiMessagesSchema = z.array(XaiChatMessageSchema);
|
||||
|
||||
// Basic chat completions schema
|
||||
export const XaiV1ChatCompletionsSchema = z.object({
|
||||
model: z.string(),
|
||||
messages: XaiMessagesSchema,
|
||||
temperature: z.number().optional().default(1),
|
||||
top_p: z.number().optional().default(1),
|
||||
max_completion_tokens: z.coerce
|
||||
.number()
|
||||
.int()
|
||||
.nullish()
|
||||
.transform((v) => Math.min(v ?? OPENAI_OUTPUT_MAX, OPENAI_OUTPUT_MAX)),
|
||||
max_tokens: z.coerce // Deprecated parameter, but kept for backward compatibility
|
||||
.number()
|
||||
.int()
|
||||
.nullish()
|
||||
.transform((v) => Math.min(v ?? OPENAI_OUTPUT_MAX, OPENAI_OUTPUT_MAX)),
|
||||
stream: z.boolean().optional().default(false),
|
||||
// Grok docs say that `stop` can be a string or array
|
||||
stop: z
|
||||
.union([z.string(), z.array(z.string())])
|
||||
.optional()
|
||||
.default([])
|
||||
.transform((v) => (Array.isArray(v) ? v : [v])),
|
||||
seed: z.number().int().min(0).optional(),
|
||||
response_format: z
|
||||
.object({ type: z.enum(["text", "json_object", "json_schema"]), json_schema: z.any().optional() })
|
||||
.optional(),
|
||||
// reasoning_effort parameter for grok-3-mini models
|
||||
reasoning_effort: z.enum(["low", "medium", "high"]).optional().default("low"),
|
||||
stream_options: z.object({
|
||||
include_usage: z.boolean()
|
||||
}).optional(),
|
||||
user: z.string().optional(),
|
||||
// Fields to support function calling
|
||||
tools: z.array(z.any()).optional(),
|
||||
tool_choice: z.union([
|
||||
z.string(),
|
||||
z.object({
|
||||
type: z.literal("function"),
|
||||
function: z.object({
|
||||
name: z.string()
|
||||
})
|
||||
})
|
||||
]).optional(),
|
||||
// Advanced parameters
|
||||
frequency_penalty: z.number().optional().default(0),
|
||||
presence_penalty: z.number().optional().default(0),
|
||||
logprobs: z.boolean().optional().default(false),
|
||||
top_logprobs: z.number().int().min(0).max(8).optional(),
|
||||
});
|
||||
|
||||
// Image Generation schema
|
||||
export const XaiV1ImageGenerationsSchema = z.object({
|
||||
model: z.string().optional(),
|
||||
prompt: z.string(),
|
||||
n: z.number().int().min(1).max(10).optional().default(1),
|
||||
response_format: z.enum(["url", "b64_json"]).optional().default("url"),
|
||||
user: z.string().optional(),
|
||||
// These are marked as not supported in the documentation but included for compatibility
|
||||
quality: z.string().optional(),
|
||||
size: z.string().optional(),
|
||||
style: z.string().optional(),
|
||||
});
|
||||
|
||||
// Helper function to convert multimodal content to string format for text-only models
|
||||
export function contentToString(content: string | any[] | null): string {
|
||||
if (typeof content === "string") {
|
||||
return content || "";
|
||||
} else if (Array.isArray(content)) {
|
||||
// For multimodal content, extract only the text parts
|
||||
// Images are not supported in text-only templates
|
||||
return content
|
||||
.filter(item => item.type === "text")
|
||||
.map(item => (item as any).text)
|
||||
.join("\n\n");
|
||||
}
|
||||
return "";
|
||||
}
|
||||
@@ -0,0 +1,82 @@
|
||||
import { Request } from "express";
|
||||
|
||||
/**
|
||||
* Claude Opus 4.1 has stricter API validation that doesn't allow both temperature
|
||||
* and top_p parameters to be specified simultaneously. This function validates and
|
||||
* adjusts the request parameters for Claude Opus 4.1 models ONLY.
|
||||
*
|
||||
* Rules:
|
||||
* - If both parameters are at default values (1.0), omit top_p
|
||||
* - If only one parameter is at default, omit the default one
|
||||
* - If both are non-default, throw an error
|
||||
*/
|
||||
export function validateClaude41OpusParameters(req: Request): void {
|
||||
const model = req.body.model;
|
||||
|
||||
// Only apply this validation to Claude Opus 4.1 models
|
||||
if (!isClaude41OpusModel(model)) {
|
||||
return;
|
||||
}
|
||||
|
||||
const temperature = req.body.temperature;
|
||||
const topP = req.body.top_p;
|
||||
|
||||
// If neither parameter is specified, no validation needed
|
||||
if (temperature === undefined && topP === undefined) {
|
||||
return;
|
||||
}
|
||||
|
||||
// Default values for Claude API
|
||||
const DEFAULT_TEMPERATURE = 1.0;
|
||||
const DEFAULT_TOP_P = 1.0;
|
||||
|
||||
const tempIsDefault = temperature === undefined || temperature === DEFAULT_TEMPERATURE;
|
||||
const topPIsDefault = topP === undefined || topP === DEFAULT_TOP_P;
|
||||
|
||||
// If both are at default values, omit top_p (keep temperature)
|
||||
if (tempIsDefault && topPIsDefault) {
|
||||
delete req.body.top_p;
|
||||
req.log?.info("Claude Opus 4.1: Both temperature and top_p at default, omitting top_p");
|
||||
return;
|
||||
}
|
||||
|
||||
// If only one is at default, omit the default one
|
||||
if (tempIsDefault && !topPIsDefault) {
|
||||
delete req.body.temperature;
|
||||
req.log?.info("Claude Opus 4.1: Temperature at default, omitting temperature");
|
||||
return;
|
||||
}
|
||||
|
||||
if (!tempIsDefault && topPIsDefault) {
|
||||
delete req.body.top_p;
|
||||
req.log?.info("Claude Opus 4.1: top_p at default, omitting top_p");
|
||||
return;
|
||||
}
|
||||
|
||||
// If both are non-default, throw an error
|
||||
if (!tempIsDefault && !topPIsDefault) {
|
||||
throw new Error(
|
||||
"Claude Opus 4.1 does not support both temperature and top_p parameters being set to non-default values simultaneously. " +
|
||||
"Please specify only one of these parameters or set one to its default value (1.0)."
|
||||
);
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Checks if the given model is a Claude Opus 4.1 model.
|
||||
* This includes all provider formats for Claude Opus 4.1 ONLY.
|
||||
*/
|
||||
function isClaude41OpusModel(model: string): boolean {
|
||||
if (!model) return false;
|
||||
|
||||
// Anthropic API format
|
||||
if (model.includes("claude-opus-4-1")) return true;
|
||||
|
||||
// AWS Bedrock format
|
||||
if (model.includes("anthropic.claude-opus-4-1")) return true;
|
||||
|
||||
// GCP Vertex AI format
|
||||
if (model.includes("claude-opus-4-1@")) return true;
|
||||
|
||||
return false;
|
||||
}
|
||||
@@ -0,0 +1,40 @@
|
||||
export interface ClaudeModelMapping {
|
||||
awsId: string;
|
||||
anthropicId: string;
|
||||
displayName: string;
|
||||
}
|
||||
|
||||
export const claudeModels: ClaudeModelMapping[] = [
|
||||
{ awsId: "anthropic.claude-v2", anthropicId: "claude-2", displayName: "Claude 2" },
|
||||
{ awsId: "anthropic.claude-v2:1", anthropicId: "claude-2.1", displayName: "Claude 2.1" },
|
||||
{ awsId: "anthropic.claude-3-haiku-20240307-v1:0", anthropicId: "claude-3-haiku-20240307", displayName: "Claude 3 Haiku" },
|
||||
{ awsId: "anthropic.claude-3-5-haiku-20241022-v1:0", anthropicId: "claude-3-5-haiku-20241022", displayName: "Claude 3.5 Haiku" },
|
||||
{ awsId: "anthropic.claude-3-sonnet-20240229-v1:0", anthropicId: "claude-3-sonnet-20240229", displayName: "Claude 3 Sonnet" },
|
||||
{ awsId: "anthropic.claude-3-5-sonnet-20240620-v1:0", anthropicId: "claude-3-5-sonnet-20240620", displayName: "Claude 3.5 Sonnet (Old)" },
|
||||
{ awsId: "anthropic.claude-3-5-sonnet-20241022-v2:0", anthropicId: "claude-3-5-sonnet-20241022", displayName: "Claude 3.5 Sonnet (New)" },
|
||||
{ awsId: "anthropic.claude-3-5-sonnet-20241022-v2:0", anthropicId: "claude-3-5-sonnet-latest", displayName: "Claude 3.5 Sonnet (Latest)" },
|
||||
{ awsId: "anthropic.claude-3-7-sonnet-20250219-v1:0", anthropicId: "claude-3-7-sonnet-20250219", displayName: "Claude 3.7 Sonnet" },
|
||||
{ awsId: "anthropic.claude-3-7-sonnet-20250219-v1:0", anthropicId: "claude-3-7-sonnet-latest", displayName: "Claude 3.7 Sonnet (Latest)" },
|
||||
{ awsId: "anthropic.claude-3-opus-20240229-v1:0", anthropicId: "claude-3-opus-20240229", displayName: "Claude 3 Opus" },
|
||||
{ awsId: "anthropic.claude-3-opus-20240229-v1:0", anthropicId: "claude-3-opus-latest", displayName: "Claude 3 Opus (Latest)" },
|
||||
{ awsId: "anthropic.claude-sonnet-4-20250514-v1:0", anthropicId: "claude-sonnet-4-20250514", displayName: "Claude 4 Sonnet" },
|
||||
{ awsId: "anthropic.claude-sonnet-4-20250514-v1:0", anthropicId: "claude-sonnet-4-latest", displayName: "Claude 4 Sonnet (Latest)" },
|
||||
{ awsId: "anthropic.claude-opus-4-20250514-v1:0", anthropicId: "claude-opus-4-20250514", displayName: "Claude 4.0 Opus" },
|
||||
{ awsId: "anthropic.claude-opus-4-1-20250805-v1:0", anthropicId: "claude-opus-4-1-20250805", displayName: "Claude 4.1 Opus" },
|
||||
{ awsId: "anthropic.claude-opus-4-1-20250805-v1:0", anthropicId: "claude-opus-4-latest", displayName: "Claude 4 Opus (Latest)" },
|
||||
{ awsId: "anthropic.claude-opus-4-1-20250805-v1:0", anthropicId: "claude-opus-4-1", displayName: "Claude 4.1 Opus" },
|
||||
{ awsId: "anthropic.claude-sonnet-4-20250514-v1:0", anthropicId: "claude-sonnet-4-0", displayName: "Claude 4 Sonnet" },
|
||||
{ awsId: "anthropic.claude-opus-4-20250514-v1:0", anthropicId: "claude-opus-4-0", displayName: "Claude 4.0 Opus" },
|
||||
];
|
||||
|
||||
export function findByAwsId(awsId: string): ClaudeModelMapping | undefined {
|
||||
return claudeModels.find(model => model.awsId === awsId);
|
||||
}
|
||||
|
||||
export function findByAnthropicId(anthropicId: string): ClaudeModelMapping | undefined {
|
||||
return claudeModels.find(model => model.anthropicId === anthropicId);
|
||||
}
|
||||
|
||||
export function getAllClaudeModels(): ClaudeModelMapping[] {
|
||||
return claudeModels;
|
||||
}
|
||||
Vendored
+1
@@ -33,6 +33,7 @@ declare global {
|
||||
tokenizerInfo: Record<string, any>;
|
||||
signedRequest: HttpRequest;
|
||||
modelFamily?: ModelFamily;
|
||||
isChunkedTransfer?: boolean;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@@ -13,9 +13,19 @@ export type OpenAIImageGenerationResult = {
|
||||
created: number;
|
||||
data: {
|
||||
revised_prompt?: string;
|
||||
url: string;
|
||||
b64_json: string;
|
||||
url?: string; // gpt-image-1 doesn't return URLs, only b64_json
|
||||
b64_json?: string;
|
||||
}[];
|
||||
// Added for gpt-image-1 responses
|
||||
usage?: {
|
||||
total_tokens: number;
|
||||
input_tokens: number;
|
||||
output_tokens: number;
|
||||
input_tokens_details?: {
|
||||
text_tokens: number;
|
||||
image_tokens: number;
|
||||
};
|
||||
};
|
||||
};
|
||||
|
||||
async function downloadImage(url: string) {
|
||||
@@ -65,11 +75,16 @@ export async function mirrorGeneratedImage(
|
||||
let mirror: string;
|
||||
if (item.b64_json) {
|
||||
mirror = await saveB64Image(item.b64_json);
|
||||
} else {
|
||||
} else if (item.url) {
|
||||
mirror = await downloadImage(item.url);
|
||||
} else {
|
||||
req.log.warn("No image data found in response");
|
||||
continue;
|
||||
}
|
||||
// Set the URL to our mirrored version
|
||||
item.url = `${host}/user_content/${path.basename(mirror)}`;
|
||||
await createThumbnail(mirror);
|
||||
// Add to image history with the local URL
|
||||
addToImageHistory({
|
||||
url: item.url,
|
||||
prompt,
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
import { RequestHandler } from "express";
|
||||
import { config } from "../config";
|
||||
import { getTokenCostUsd, prettyTokens } from "./stats";
|
||||
import { getTokenCostUsd, getTokenCostDetailsUsd, prettyTokens } from "./stats"; // Added getTokenCostDetailsUsd
|
||||
import { redactIp } from "./utils";
|
||||
import * as userStore from "./users/user-store";
|
||||
|
||||
@@ -30,7 +30,8 @@ export const injectLocals: RequestHandler = (req, res, next) => {
|
||||
|
||||
// view helpers
|
||||
res.locals.prettyTokens = prettyTokens;
|
||||
res.locals.tokenCost = getTokenCostUsd;
|
||||
res.locals.tokenCost = getTokenCostUsd; // Returns total cost as a number
|
||||
res.locals.tokenCostDetails = getTokenCostDetailsUsd; // Returns { inputCost, outputCost, totalCost }
|
||||
res.locals.redactIp = redactIp;
|
||||
|
||||
next();
|
||||
|
||||
@@ -6,9 +6,9 @@ import type { AnthropicKey, AnthropicKeyProvider } from "./provider";
|
||||
const axios = getAxiosInstance();
|
||||
|
||||
const MIN_CHECK_INTERVAL = 3 * 1000; // 3 seconds
|
||||
const KEY_CHECK_PERIOD = 1000 * 60 * 60 * 6; // 6 hours
|
||||
const KEY_CHECK_PERIOD = 1000 * 60 * 60 * 24; // 24 hours (no reason to do it every 6 hours)
|
||||
const POST_MESSAGES_URL = "https://api.anthropic.com/v1/messages";
|
||||
const TEST_MODEL = "claude-3-sonnet-20240229";
|
||||
const TEST_MODEL = "claude-3-7-sonnet-latest";
|
||||
const SYSTEM = "Obey all instructions from the user.";
|
||||
const DETECTION_PROMPT = [
|
||||
{
|
||||
@@ -71,10 +71,13 @@ export class AnthropicKeyChecker extends KeyCheckerBase<AnthropicKey> {
|
||||
// The type is always invalid_request_error, so we have to check the text.
|
||||
const isOverQuota =
|
||||
data.error?.message?.match(/usage blocked until/i) ||
|
||||
data.error?.message?.match(/credit balance is too low/i);
|
||||
data.error?.message?.match(/credit balance is too low/i) ||
|
||||
data.error?.message?.match(/reached your specified API usage limits/i) ||
|
||||
data.error?.message?.match(/You will regain access on/i);
|
||||
const isDisabled = data.error?.message?.match(
|
||||
/organization has been disabled/i
|
||||
);
|
||||
) ||
|
||||
data.error?.message?.match(/credential is only authorized for use with Claude Code/i);
|
||||
if (status === 400 && isOverQuota) {
|
||||
this.log.warn(
|
||||
{ key: key.hash, error: data },
|
||||
|
||||
@@ -16,11 +16,8 @@ export type AnthropicKeyUpdate = Omit<
|
||||
| "rateLimitedUntil"
|
||||
>;
|
||||
|
||||
type AnthropicKeyUsage = {
|
||||
[K in AnthropicModelFamily as `${K}Tokens`]: number;
|
||||
};
|
||||
|
||||
export interface AnthropicKey extends Key, AnthropicKeyUsage {
|
||||
// AnthropicKeyUsage is removed, tokenUsage from base Key interface will be used.
|
||||
export interface AnthropicKey extends Key {
|
||||
readonly service: "anthropic";
|
||||
readonly modelFamilies: AnthropicModelFamily[];
|
||||
/**
|
||||
@@ -120,8 +117,7 @@ export class AnthropicKeyProvider implements KeyProvider<AnthropicKey> {
|
||||
.digest("hex")
|
||||
.slice(0, 8)}`,
|
||||
lastChecked: 0,
|
||||
claudeTokens: 0,
|
||||
"claude-opusTokens": 0,
|
||||
tokenUsage: {}, // Initialize new tokenUsage field
|
||||
tier: "unknown",
|
||||
};
|
||||
this.keys.push(newKey);
|
||||
@@ -206,11 +202,23 @@ export class AnthropicKeyProvider implements KeyProvider<AnthropicKey> {
|
||||
return this.keys.filter((k) => !k.isDisabled).length;
|
||||
}
|
||||
|
||||
public incrementUsage(hash: string, model: string, tokens: number) {
|
||||
const key = this.keys.find((k) => k.hash === hash);
|
||||
public incrementUsage(keyHash: string, modelFamily: AnthropicModelFamily, usage: { input: number; output: number }) {
|
||||
const key = this.keys.find((k) => k.hash === keyHash);
|
||||
if (!key) return;
|
||||
|
||||
key.promptCount++;
|
||||
key[`${getClaudeModelFamily(model)}Tokens`] += tokens;
|
||||
|
||||
if (!key.tokenUsage) {
|
||||
key.tokenUsage = {};
|
||||
}
|
||||
// Ensure the specific family object exists
|
||||
if (!key.tokenUsage[modelFamily]) {
|
||||
key.tokenUsage[modelFamily] = { input: 0, output: 0 };
|
||||
}
|
||||
|
||||
const currentFamilyUsage = key.tokenUsage[modelFamily]!;
|
||||
currentFamilyUsage.input += usage.input;
|
||||
currentFamilyUsage.output += usage.output;
|
||||
}
|
||||
|
||||
getLockoutPeriod = createGenericGetLockoutPeriod(() => this.keys);
|
||||
|
||||
@@ -24,6 +24,10 @@ const KNOWN_MODEL_IDS: ModuleAliasTuple[] = [
|
||||
["anthropic.claude-3-opus-20240229-v1:0"],
|
||||
["anthropic.claude-3-5-sonnet-20240620-v1:0"],
|
||||
["anthropic.claude-3-5-sonnet-20241022-v2:0"],
|
||||
["anthropic.claude-3-7-sonnet-20250219-v1:0"],
|
||||
["anthropic.claude-sonnet-4-20250514-v1:0"],
|
||||
["anthropic.claude-opus-4-20250514-v1:0"],
|
||||
["anthropic.claude-opus-4-1-20250805-v1:0"],
|
||||
["mistral.mistral-7b-instruct-v0:2"],
|
||||
["mistral.mixtral-8x7b-instruct-v0:1"],
|
||||
["mistral.mistral-large-2402-v1:0"],
|
||||
@@ -92,6 +96,8 @@ export class AwsKeyChecker extends KeyCheckerBase<AwsBedrockKey> {
|
||||
protected async testKeyOrFail(key: AwsBedrockKey) {
|
||||
const isInitialCheck = !key.lastChecked;
|
||||
|
||||
// Keys with logging enabled will get rejected in the provider
|
||||
await this.checkLoggingConfiguration(key);
|
||||
if (isInitialCheck) {
|
||||
try {
|
||||
await this.checkInferenceProfiles(key);
|
||||
|
||||
@@ -3,15 +3,13 @@ import { config } from "../../../config";
|
||||
import { logger } from "../../../logger";
|
||||
import { PaymentRequiredError } from "../../errors";
|
||||
import { AwsBedrockModelFamily, getAwsBedrockModelFamily } from "../../models";
|
||||
import { findByAnthropicId } from "../../claude-models";
|
||||
import { createGenericGetLockoutPeriod, Key, KeyProvider } from "..";
|
||||
import { prioritizeKeys } from "../prioritize-keys";
|
||||
import { AwsKeyChecker } from "./checker";
|
||||
|
||||
type AwsBedrockKeyUsage = {
|
||||
[K in AwsBedrockModelFamily as `${K}Tokens`]: number;
|
||||
};
|
||||
|
||||
export interface AwsBedrockKey extends Key, AwsBedrockKeyUsage {
|
||||
// AwsBedrockKeyUsage is removed, tokenUsage from base Key interface will be used.
|
||||
export interface AwsBedrockKey extends Key {
|
||||
readonly service: "aws";
|
||||
readonly modelFamilies: AwsBedrockModelFamily[];
|
||||
/**
|
||||
@@ -74,12 +72,7 @@ export class AwsBedrockKeyProvider implements KeyProvider<AwsBedrockKey> {
|
||||
lastChecked: 0,
|
||||
modelIds: ["anthropic.claude-3-sonnet-20240229-v1:0"],
|
||||
inferenceProfileIds: [],
|
||||
["aws-claudeTokens"]: 0,
|
||||
["aws-claude-opusTokens"]: 0,
|
||||
["aws-mistral-tinyTokens"]: 0,
|
||||
["aws-mistral-smallTokens"]: 0,
|
||||
["aws-mistral-mediumTokens"]: 0,
|
||||
["aws-mistral-largeTokens"]: 0,
|
||||
tokenUsage: {}, // Initialize new tokenUsage field
|
||||
};
|
||||
this.keys.push(newKey);
|
||||
}
|
||||
@@ -104,6 +97,15 @@ export class AwsBedrockKeyProvider implements KeyProvider<AwsBedrockKey> {
|
||||
// Claude 2 is the only model that breaks this convention; Anthropic calls
|
||||
// it claude-2 but AWS calls it claude-v2.
|
||||
if (model.includes("claude-2")) neededVariantId = "claude-v2";
|
||||
|
||||
// For Claude models, try to resolve aliases to AWS model IDs
|
||||
if (model.includes("claude") && !model.includes("anthropic.")) {
|
||||
const claudeMapping = findByAnthropicId(model);
|
||||
if (claudeMapping) {
|
||||
neededVariantId = claudeMapping.awsId;
|
||||
}
|
||||
}
|
||||
|
||||
const neededFamily = getAwsBedrockModelFamily(model);
|
||||
|
||||
const availableKeys = this.keys.filter((k) => {
|
||||
@@ -173,11 +175,22 @@ export class AwsBedrockKeyProvider implements KeyProvider<AwsBedrockKey> {
|
||||
return this.keys.filter((k) => !k.isDisabled).length;
|
||||
}
|
||||
|
||||
public incrementUsage(hash: string, model: string, tokens: number) {
|
||||
const key = this.keys.find((k) => k.hash === hash);
|
||||
public incrementUsage(keyHash: string, modelFamily: AwsBedrockModelFamily, usage: { input: number; output: number }) {
|
||||
const key = this.keys.find((k) => k.hash === keyHash);
|
||||
if (!key) return;
|
||||
|
||||
key.promptCount++;
|
||||
key[`${getAwsBedrockModelFamily(model)}Tokens`] += tokens;
|
||||
|
||||
if (!key.tokenUsage) {
|
||||
key.tokenUsage = {};
|
||||
}
|
||||
if (!key.tokenUsage[modelFamily]) {
|
||||
key.tokenUsage[modelFamily] = { input: 0, output: 0 };
|
||||
}
|
||||
|
||||
const currentFamilyUsage = key.tokenUsage[modelFamily]!;
|
||||
currentFamilyUsage.input += usage.input;
|
||||
currentFamilyUsage.output += usage.output;
|
||||
}
|
||||
|
||||
getLockoutPeriod = createGenericGetLockoutPeriod(() => this.keys);
|
||||
|
||||
@@ -123,7 +123,7 @@ export class AzureOpenAIKeyChecker extends KeyCheckerBase<AzureOpenAIKey> {
|
||||
AzureOpenAIKeyChecker.getCredentialsFromKey(key);
|
||||
const url = POST_CHAT_COMPLETIONS(resourceName, deploymentId);
|
||||
const testRequest = {
|
||||
max_tokens: 1,
|
||||
max_completion_tokens: 1,
|
||||
stream: false,
|
||||
messages: [{ role: "user", content: "" }],
|
||||
};
|
||||
@@ -159,7 +159,7 @@ export class AzureOpenAIKeyChecker extends KeyCheckerBase<AzureOpenAIKey> {
|
||||
// Try to send an oversized prompt. GPT-4 Turbo can handle this but regular
|
||||
// GPT-4 will return a Bad Request error.
|
||||
const contextText = {
|
||||
max_tokens: 9000,
|
||||
max_completion_tokens: 9000,
|
||||
stream: false,
|
||||
temperature: 0,
|
||||
seed: 0,
|
||||
|
||||
@@ -10,11 +10,8 @@ import { createGenericGetLockoutPeriod, Key, KeyProvider } from "..";
|
||||
import { prioritizeKeys } from "../prioritize-keys";
|
||||
import { AzureOpenAIKeyChecker } from "./checker";
|
||||
|
||||
type AzureOpenAIKeyUsage = {
|
||||
[K in AzureOpenAIModelFamily as `${K}Tokens`]: number;
|
||||
};
|
||||
|
||||
export interface AzureOpenAIKey extends Key, AzureOpenAIKeyUsage {
|
||||
// AzureOpenAIKeyUsage is removed, tokenUsage from base Key interface will be used.
|
||||
export interface AzureOpenAIKey extends Key {
|
||||
readonly service: "azure";
|
||||
readonly modelFamilies: AzureOpenAIModelFamily[];
|
||||
contentFiltering: boolean;
|
||||
@@ -68,14 +65,7 @@ export class AzureOpenAIKeyProvider implements KeyProvider<AzureOpenAIKey> {
|
||||
.digest("hex")
|
||||
.slice(0, 8)}`,
|
||||
lastChecked: 0,
|
||||
"azure-turboTokens": 0,
|
||||
"azure-gpt4Tokens": 0,
|
||||
"azure-gpt4-32kTokens": 0,
|
||||
"azure-gpt4-turboTokens": 0,
|
||||
"azure-gpt4oTokens": 0,
|
||||
"azure-o1Tokens": 0,
|
||||
"azure-o1-miniTokens": 0,
|
||||
"azure-dall-eTokens": 0,
|
||||
tokenUsage: {}, // Initialize new tokenUsage field
|
||||
modelIds: [],
|
||||
};
|
||||
this.keys.push(newKey);
|
||||
@@ -130,11 +120,22 @@ export class AzureOpenAIKeyProvider implements KeyProvider<AzureOpenAIKey> {
|
||||
return this.keys.filter((k) => !k.isDisabled).length;
|
||||
}
|
||||
|
||||
public incrementUsage(hash: string, model: string, tokens: number) {
|
||||
const key = this.keys.find((k) => k.hash === hash);
|
||||
public incrementUsage(keyHash: string, modelFamily: AzureOpenAIModelFamily, usage: { input: number; output: number }) {
|
||||
const key = this.keys.find((k) => k.hash === keyHash);
|
||||
if (!key) return;
|
||||
|
||||
key.promptCount++;
|
||||
key[`${getAzureOpenAIModelFamily(model)}Tokens`] += tokens;
|
||||
|
||||
if (!key.tokenUsage) {
|
||||
key.tokenUsage = {};
|
||||
}
|
||||
if (!key.tokenUsage[modelFamily]) {
|
||||
key.tokenUsage[modelFamily] = { input: 0, output: 0 };
|
||||
}
|
||||
|
||||
const currentFamilyUsage = key.tokenUsage[modelFamily]!;
|
||||
currentFamilyUsage.input += usage.input;
|
||||
currentFamilyUsage.output += usage.output;
|
||||
}
|
||||
|
||||
getLockoutPeriod = createGenericGetLockoutPeriod(() => this.keys);
|
||||
|
||||
@@ -0,0 +1,116 @@
|
||||
import { CohereKey } from "./provider";
|
||||
import { logger } from "../../../logger";
|
||||
import { assertNever } from "../../utils";
|
||||
|
||||
const CHECK_TIMEOUT = 10000;
|
||||
const API_URL = "https://api.cohere.com/v1/check-api-key";
|
||||
|
||||
export class CohereKeyChecker {
|
||||
private log = logger.child({ module: "key-checker", service: "cohere" });
|
||||
|
||||
constructor(private readonly update: (hash: string, key: Partial<CohereKey>) => void) {
|
||||
this.log.info("CohereKeyChecker initialized");
|
||||
}
|
||||
|
||||
public async checkKey(key: CohereKey): Promise<void> {
|
||||
this.log.info({ hash: key.hash }, "Starting key validation check");
|
||||
try {
|
||||
const result = await this.validateKey(key);
|
||||
this.handleCheckResult(key, result);
|
||||
} catch (error) {
|
||||
if (error instanceof Error) {
|
||||
this.log.warn(
|
||||
{ error: error.message, stack: error.stack, hash: key.hash },
|
||||
"Failed to check key status"
|
||||
);
|
||||
} else {
|
||||
this.log.warn(
|
||||
{ error, hash: key.hash },
|
||||
"Failed to check key status with unknown error"
|
||||
);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
private async validateKey(key: CohereKey): Promise<"valid" | "invalid" | "quota"> {
|
||||
const controller = new AbortController();
|
||||
const timeout = setTimeout(() => {
|
||||
controller.abort();
|
||||
this.log.warn({ hash: key.hash }, "Key validation timed out after " + CHECK_TIMEOUT + "ms");
|
||||
}, CHECK_TIMEOUT);
|
||||
|
||||
try {
|
||||
// Check API key endpoint to verify key validity as per the provided example
|
||||
const headers = {
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": `Bearer ${key.key}`,
|
||||
"Cohere-Version": "2022-12-06"
|
||||
};
|
||||
|
||||
const response = await fetch(API_URL, {
|
||||
method: "POST",
|
||||
headers,
|
||||
signal: controller.signal,
|
||||
});
|
||||
|
||||
// According to the provided example, we should check for valid:true in the response
|
||||
const data = await response.json();
|
||||
|
||||
if (response.status === 200) {
|
||||
if (data.valid === true) {
|
||||
return "valid";
|
||||
} else {
|
||||
return "invalid";
|
||||
}
|
||||
} else if (response.status === 429) {
|
||||
return "quota";
|
||||
} else {
|
||||
this.log.warn(
|
||||
{ status: response.status, hash: key.hash },
|
||||
"Unexpected status code while testing key validity"
|
||||
);
|
||||
return "invalid";
|
||||
}
|
||||
} catch (error) {
|
||||
if (error instanceof Error && error.name === 'AbortError') {
|
||||
this.log.warn({ hash: key.hash }, "Key validation aborted");
|
||||
}
|
||||
throw error;
|
||||
} finally {
|
||||
clearTimeout(timeout);
|
||||
}
|
||||
}
|
||||
|
||||
private handleCheckResult(
|
||||
key: CohereKey,
|
||||
result: "valid" | "invalid" | "quota"
|
||||
): void {
|
||||
switch (result) {
|
||||
case "valid":
|
||||
this.log.info({ hash: key.hash }, "Key is valid and enabled");
|
||||
this.update(key.hash, {
|
||||
isDisabled: false,
|
||||
lastChecked: Date.now(),
|
||||
});
|
||||
break;
|
||||
case "invalid":
|
||||
this.log.warn({ hash: key.hash }, "Key is invalid, marking as revoked");
|
||||
this.update(key.hash, {
|
||||
isDisabled: true,
|
||||
isRevoked: true,
|
||||
lastChecked: Date.now(),
|
||||
});
|
||||
break;
|
||||
case "quota":
|
||||
this.log.warn({ hash: key.hash }, "Key has exceeded its quota, disabling");
|
||||
this.update(key.hash, {
|
||||
isDisabled: true,
|
||||
isOverQuota: true,
|
||||
lastChecked: Date.now(),
|
||||
});
|
||||
break;
|
||||
default:
|
||||
assertNever(result);
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,167 @@
|
||||
import { Key, KeyProvider, createGenericGetLockoutPeriod } from "..";
|
||||
import { CohereKeyChecker } from "./checker";
|
||||
import { config } from "../../../config";
|
||||
import { logger } from "../../../logger";
|
||||
import { CohereModelFamily, ModelFamily } from "../../models"; // Added ModelFamily
|
||||
|
||||
// CohereKeyUsage is removed, tokenUsage from base Key interface will be used.
|
||||
export interface CohereKey extends Key {
|
||||
readonly service: "cohere";
|
||||
readonly modelFamilies: CohereModelFamily[];
|
||||
isOverQuota: boolean;
|
||||
}
|
||||
|
||||
export class CohereKeyProvider implements KeyProvider<CohereKey> {
|
||||
readonly service = "cohere";
|
||||
|
||||
private keys: CohereKey[] = [];
|
||||
private checker?: CohereKeyChecker;
|
||||
private log = logger.child({ module: "key-provider", service: this.service });
|
||||
|
||||
constructor() {
|
||||
const keyConfig = config.cohereKey?.trim();
|
||||
if (!keyConfig) {
|
||||
return;
|
||||
}
|
||||
|
||||
const keys = keyConfig.split(",").map((k) => k.trim());
|
||||
for (const key of keys) {
|
||||
if (!key) continue;
|
||||
this.keys.push({
|
||||
key,
|
||||
service: this.service,
|
||||
modelFamilies: ["cohere"],
|
||||
isDisabled: false,
|
||||
isRevoked: false,
|
||||
promptCount: 0,
|
||||
lastUsed: 0,
|
||||
lastChecked: 0,
|
||||
hash: this.hashKey(key),
|
||||
rateLimitedAt: 0,
|
||||
rateLimitedUntil: 0,
|
||||
tokenUsage: {}, // Initialize new tokenUsage field
|
||||
isOverQuota: false,
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
private hashKey(key: string): string {
|
||||
return require("crypto").createHash("sha256").update(key).digest("hex");
|
||||
}
|
||||
|
||||
public init() {
|
||||
if (this.keys.length === 0) return;
|
||||
if (!config.checkKeys) {
|
||||
this.log.warn(
|
||||
"Key checking is disabled. Keys will not be verified."
|
||||
);
|
||||
return;
|
||||
}
|
||||
this.checker = new CohereKeyChecker(this.update.bind(this));
|
||||
for (const key of this.keys) {
|
||||
void this.checker.checkKey(key);
|
||||
}
|
||||
}
|
||||
|
||||
public get(model: string): CohereKey {
|
||||
const availableKeys = this.keys.filter((k) => !k.isDisabled);
|
||||
if (availableKeys.length === 0) {
|
||||
throw new Error("No Cohere keys available");
|
||||
}
|
||||
const key = availableKeys[Math.floor(Math.random() * availableKeys.length)];
|
||||
key.lastUsed = Date.now();
|
||||
this.throttle(key.hash);
|
||||
return { ...key };
|
||||
}
|
||||
|
||||
public list(): Omit<CohereKey, "key">[] {
|
||||
return this.keys.map(({ key, ...rest }) => rest);
|
||||
}
|
||||
|
||||
public disable(key: CohereKey): void {
|
||||
const found = this.keys.find((k) => k.hash === key.hash);
|
||||
if (found) {
|
||||
found.isDisabled = true;
|
||||
}
|
||||
}
|
||||
|
||||
public update(hash: string, update: Partial<CohereKey>): void {
|
||||
const key = this.keys.find((k) => k.hash === hash);
|
||||
if (key) {
|
||||
Object.assign(key, update);
|
||||
}
|
||||
}
|
||||
|
||||
public available(): number {
|
||||
return this.keys.filter((k) => !k.isDisabled).length;
|
||||
}
|
||||
|
||||
public incrementUsage(keyHash: string, modelFamily: CohereModelFamily, usage: { input: number; output: number }) {
|
||||
const key = this.keys.find((k) => k.hash === keyHash);
|
||||
if (!key) return;
|
||||
|
||||
key.promptCount++;
|
||||
|
||||
if (!key.tokenUsage) {
|
||||
key.tokenUsage = {};
|
||||
}
|
||||
// Cohere only has one model family "cohere"
|
||||
if (!key.tokenUsage[modelFamily]) {
|
||||
key.tokenUsage[modelFamily] = { input: 0, output: 0 };
|
||||
}
|
||||
|
||||
const currentFamilyUsage = key.tokenUsage[modelFamily]!;
|
||||
currentFamilyUsage.input += usage.input;
|
||||
currentFamilyUsage.output += usage.output;
|
||||
}
|
||||
|
||||
/**
|
||||
* Upon being rate limited, a key will be locked out for this many milliseconds
|
||||
* while we wait for other concurrent requests to finish.
|
||||
*/
|
||||
private static readonly RATE_LIMIT_LOCKOUT = 2000;
|
||||
/**
|
||||
* Upon assigning a key, we will wait this many milliseconds before allowing it
|
||||
* to be used again. This is to prevent the queue from flooding a key with too
|
||||
* many requests while we wait to learn whether previous ones succeeded.
|
||||
*/
|
||||
private static readonly KEY_REUSE_DELAY = 500;
|
||||
|
||||
getLockoutPeriod = createGenericGetLockoutPeriod(() => this.keys);
|
||||
|
||||
public markRateLimited(keyHash: string) {
|
||||
this.log.debug({ key: keyHash }, "Key rate limited");
|
||||
const key = this.keys.find((k) => k.hash === keyHash)!;
|
||||
const now = Date.now();
|
||||
key.rateLimitedAt = now;
|
||||
key.rateLimitedUntil = now + CohereKeyProvider.RATE_LIMIT_LOCKOUT;
|
||||
}
|
||||
|
||||
public recheck(): void {
|
||||
if (!this.checker || !config.checkKeys) return;
|
||||
for (const key of this.keys) {
|
||||
this.update(key.hash, {
|
||||
isOverQuota: false,
|
||||
isDisabled: false,
|
||||
lastChecked: 0
|
||||
});
|
||||
void this.checker.checkKey(key);
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Applies a short artificial delay to the key upon dequeueing, in order to
|
||||
* prevent it from being immediately assigned to another request before the
|
||||
* current one can be dispatched.
|
||||
**/
|
||||
private throttle(hash: string) {
|
||||
const now = Date.now();
|
||||
const key = this.keys.find((k) => k.hash === hash)!;
|
||||
|
||||
const currentRateLimit = key.rateLimitedUntil;
|
||||
const nextRateLimit = now + CohereKeyProvider.KEY_REUSE_DELAY;
|
||||
|
||||
key.rateLimitedAt = now;
|
||||
key.rateLimitedUntil = Math.max(currentRateLimit, nextRateLimit);
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,213 @@
|
||||
import { DeepseekKey } from "./provider";
|
||||
import { logger } from "../../../logger";
|
||||
import { assertNever } from "../../utils";
|
||||
|
||||
const CHECK_TIMEOUT = 10000;
|
||||
const SERVER_ERROR_RETRY_DELAY = 5000; // 5 seconds
|
||||
const MAX_SERVER_ERROR_RETRIES = 2;
|
||||
const CONNECTION_ERROR_RETRY_DELAY = 10000; // 10 seconds
|
||||
const MAX_CONNECTION_ERROR_RETRIES = 2; // 3 total attempts (initial + 2 retries)
|
||||
|
||||
// Track server error counts for each key
|
||||
const serverErrorCounts: Record<string, number> = {};
|
||||
// Track connection error counts for each key
|
||||
const connectionErrorCounts: Record<string, number> = {};
|
||||
|
||||
export class DeepseekKeyChecker {
|
||||
private log = logger.child({ module: "key-checker", service: "deepseek" });
|
||||
|
||||
constructor(private readonly update: (hash: string, key: Partial<DeepseekKey>) => void) {}
|
||||
|
||||
public async checkKey(key: DeepseekKey): Promise<void> {
|
||||
try {
|
||||
const result = await this.validateKey(key);
|
||||
|
||||
// If we get here, reset any connection error counters since the request succeeded
|
||||
if (connectionErrorCounts[key.hash]) {
|
||||
delete connectionErrorCounts[key.hash];
|
||||
}
|
||||
|
||||
if (result === "server_error") {
|
||||
// Increment server error count for this key
|
||||
const currentCount = (serverErrorCounts[key.hash] || 0) + 1;
|
||||
serverErrorCounts[key.hash] = currentCount;
|
||||
|
||||
if (currentCount <= MAX_SERVER_ERROR_RETRIES) {
|
||||
// Schedule a retry after delay
|
||||
this.log.info(
|
||||
{ hash: key.hash, retryCount: currentCount },
|
||||
`Server error detected, scheduling retry ${currentCount} of ${MAX_SERVER_ERROR_RETRIES} in ${SERVER_ERROR_RETRY_DELAY/1000} seconds`
|
||||
);
|
||||
|
||||
setTimeout(() => {
|
||||
this.log.info({ hash: key.hash }, "Retrying key check after server error");
|
||||
this.checkKey(key);
|
||||
}, SERVER_ERROR_RETRY_DELAY);
|
||||
|
||||
// Just mark as checked for now, but don't disable
|
||||
this.update(key.hash, {
|
||||
lastChecked: Date.now(),
|
||||
});
|
||||
|
||||
return;
|
||||
} else {
|
||||
// Max retries reached, handle as invalid
|
||||
this.log.warn(
|
||||
{ hash: key.hash, retries: currentCount },
|
||||
"Key failed server error checks multiple times, marking as invalid"
|
||||
);
|
||||
|
||||
// Reset the counter since we're handling it now
|
||||
delete serverErrorCounts[key.hash];
|
||||
|
||||
// Mark as invalid
|
||||
this.handleCheckResult(key, "invalid");
|
||||
return;
|
||||
}
|
||||
} else {
|
||||
// If we get a non-server-error result, reset the server error count
|
||||
if (serverErrorCounts[key.hash]) {
|
||||
delete serverErrorCounts[key.hash];
|
||||
}
|
||||
|
||||
// Handle the result normally
|
||||
this.handleCheckResult(key, result);
|
||||
}
|
||||
} catch (error) {
|
||||
// Increment connection error count for this key
|
||||
const currentCount = (connectionErrorCounts[key.hash] || 0) + 1;
|
||||
connectionErrorCounts[key.hash] = currentCount;
|
||||
|
||||
if (currentCount <= MAX_CONNECTION_ERROR_RETRIES) {
|
||||
// Schedule a retry after delay
|
||||
this.log.warn(
|
||||
{ error, hash: key.hash, retryCount: currentCount },
|
||||
`Failed to check key status, scheduling retry ${currentCount} of ${MAX_CONNECTION_ERROR_RETRIES} in ${CONNECTION_ERROR_RETRY_DELAY/1000} seconds`
|
||||
);
|
||||
|
||||
setTimeout(() => {
|
||||
this.log.info({ hash: key.hash }, "Retrying key check after connection error");
|
||||
this.checkKey(key);
|
||||
}, CONNECTION_ERROR_RETRY_DELAY);
|
||||
|
||||
// Just mark as checked for now, don't change status
|
||||
this.update(key.hash, {
|
||||
lastChecked: Date.now(),
|
||||
});
|
||||
} else {
|
||||
// Max retries reached, log final warning
|
||||
this.log.warn(
|
||||
{ error, hash: key.hash, retries: currentCount },
|
||||
"Key failed connection checks multiple times, marking as invalid"
|
||||
);
|
||||
|
||||
// Reset the counter since we're handling it now
|
||||
delete connectionErrorCounts[key.hash];
|
||||
|
||||
// Mark as invalid after exhausting retries
|
||||
this.update(key.hash, {
|
||||
isDisabled: true,
|
||||
isRevoked: true, // Assuming connection failures after retries mean the key is invalid
|
||||
lastChecked: Date.now(),
|
||||
});
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
private async validateKey(key: DeepseekKey): Promise<"valid" | "invalid" | "quota" | "server_error"> {
|
||||
const controller = new AbortController();
|
||||
const timeout = setTimeout(() => controller.abort(), CHECK_TIMEOUT);
|
||||
|
||||
try {
|
||||
const response = await fetch("https://api.deepseek.com/chat/completions", {
|
||||
method: "POST",
|
||||
headers: {
|
||||
"Content-Type": "application/json",
|
||||
Authorization: `Bearer ${key.key}`,
|
||||
},
|
||||
body: JSON.stringify({
|
||||
model: "deepseek-chat",
|
||||
messages: [{ role: "user", content: "hi" }],
|
||||
max_tokens: 0,
|
||||
}),
|
||||
signal: controller.signal,
|
||||
});
|
||||
|
||||
const rateLimit = {
|
||||
limit: parseInt(response.headers.get("x-ratelimit-limit") || "200"),
|
||||
remaining: parseInt(response.headers.get("x-ratelimit-remaining") || "199"),
|
||||
};
|
||||
|
||||
switch (response.status) {
|
||||
case 400:
|
||||
this.log.debug(
|
||||
{ key: key.hash, rateLimit },
|
||||
"Key check successful, updating rate limit info"
|
||||
);
|
||||
return "valid";
|
||||
case 401:
|
||||
this.log.warn({ hash: key.hash }, "Key is invalid (authentication failed)");
|
||||
return "invalid";
|
||||
case 402:
|
||||
this.log.warn({ hash: key.hash }, "Key has insufficient balance");
|
||||
return "quota";
|
||||
case 429:
|
||||
this.log.warn({ key: key.hash }, "Key is rate limited");
|
||||
return "valid";
|
||||
case 500:
|
||||
this.log.warn({ hash: key.hash }, "Server error when checking key");
|
||||
return "server_error";
|
||||
case 503:
|
||||
this.log.warn({ hash: key.hash }, "Server overloaded when checking key");
|
||||
return "server_error";
|
||||
default:
|
||||
this.log.warn(
|
||||
{ status: response.status, hash: key.hash },
|
||||
"Unexpected status code while checking key"
|
||||
);
|
||||
return "valid";
|
||||
}
|
||||
} finally {
|
||||
clearTimeout(timeout);
|
||||
}
|
||||
}
|
||||
|
||||
private handleCheckResult(
|
||||
key: DeepseekKey,
|
||||
result: "valid" | "invalid" | "quota" | "server_error"
|
||||
): void {
|
||||
switch (result) {
|
||||
case "valid":
|
||||
this.update(key.hash, {
|
||||
isDisabled: false,
|
||||
lastChecked: Date.now(),
|
||||
});
|
||||
break;
|
||||
case "invalid":
|
||||
this.log.warn({ hash: key.hash }, "Key is invalid");
|
||||
this.update(key.hash, {
|
||||
isDisabled: true,
|
||||
isRevoked: true,
|
||||
lastChecked: Date.now(),
|
||||
});
|
||||
break;
|
||||
case "quota":
|
||||
this.log.warn({ hash: key.hash }, "Key has exceeded its quota");
|
||||
this.update(key.hash, {
|
||||
isDisabled: true,
|
||||
isOverQuota: true,
|
||||
lastChecked: Date.now(),
|
||||
});
|
||||
break;
|
||||
case "server_error":
|
||||
// This case is now handled in the checkKey method with retries
|
||||
this.log.warn({ hash: key.hash }, "Server error when checking key");
|
||||
this.update(key.hash, {
|
||||
lastChecked: Date.now(),
|
||||
});
|
||||
break;
|
||||
default:
|
||||
assertNever(result);
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,167 @@
|
||||
import { Key, KeyProvider, createGenericGetLockoutPeriod } from "..";
|
||||
import { DeepseekKeyChecker } from "./checker";
|
||||
import { config } from "../../../config";
|
||||
import { logger } from "../../../logger";
|
||||
import { DeepseekModelFamily, ModelFamily } from "../../models"; // Added ModelFamily
|
||||
|
||||
// DeepseekKeyUsage is removed, tokenUsage from base Key interface will be used.
|
||||
export interface DeepseekKey extends Key {
|
||||
readonly service: "deepseek";
|
||||
readonly modelFamilies: DeepseekModelFamily[];
|
||||
isOverQuota: boolean;
|
||||
}
|
||||
|
||||
export class DeepseekKeyProvider implements KeyProvider<DeepseekKey> {
|
||||
readonly service = "deepseek";
|
||||
|
||||
private keys: DeepseekKey[] = [];
|
||||
private checker?: DeepseekKeyChecker;
|
||||
private log = logger.child({ module: "key-provider", service: this.service });
|
||||
|
||||
constructor() {
|
||||
const keyConfig = config.deepseekKey?.trim();
|
||||
if (!keyConfig) {
|
||||
return;
|
||||
}
|
||||
|
||||
const keys = keyConfig.split(",").map((k) => k.trim());
|
||||
for (const key of keys) {
|
||||
if (!key) continue;
|
||||
this.keys.push({
|
||||
key,
|
||||
service: this.service,
|
||||
modelFamilies: ["deepseek"],
|
||||
isDisabled: false,
|
||||
isRevoked: false,
|
||||
promptCount: 0,
|
||||
lastUsed: 0,
|
||||
lastChecked: 0,
|
||||
hash: this.hashKey(key),
|
||||
rateLimitedAt: 0,
|
||||
rateLimitedUntil: 0,
|
||||
tokenUsage: {}, // Initialize new tokenUsage field
|
||||
isOverQuota: false,
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
private hashKey(key: string): string {
|
||||
return require("crypto").createHash("sha256").update(key).digest("hex");
|
||||
}
|
||||
|
||||
public init() {
|
||||
if (this.keys.length === 0) return;
|
||||
if (!config.checkKeys) {
|
||||
this.log.warn(
|
||||
"Key checking is disabled. Keys will not be verified."
|
||||
);
|
||||
return;
|
||||
}
|
||||
this.checker = new DeepseekKeyChecker(this.update.bind(this));
|
||||
for (const key of this.keys) {
|
||||
void this.checker.checkKey(key);
|
||||
}
|
||||
}
|
||||
|
||||
public get(model: string): DeepseekKey {
|
||||
const availableKeys = this.keys.filter((k) => !k.isDisabled);
|
||||
if (availableKeys.length === 0) {
|
||||
throw new Error("No Deepseek keys available");
|
||||
}
|
||||
const key = availableKeys[Math.floor(Math.random() * availableKeys.length)];
|
||||
key.lastUsed = Date.now();
|
||||
this.throttle(key.hash);
|
||||
return { ...key };
|
||||
}
|
||||
|
||||
public list(): Omit<DeepseekKey, "key">[] {
|
||||
return this.keys.map(({ key, ...rest }) => rest);
|
||||
}
|
||||
|
||||
public disable(key: DeepseekKey): void {
|
||||
const found = this.keys.find((k) => k.hash === key.hash);
|
||||
if (found) {
|
||||
found.isDisabled = true;
|
||||
}
|
||||
}
|
||||
|
||||
public update(hash: string, update: Partial<DeepseekKey>): void {
|
||||
const key = this.keys.find((k) => k.hash === hash);
|
||||
if (key) {
|
||||
Object.assign(key, update);
|
||||
}
|
||||
}
|
||||
|
||||
public available(): number {
|
||||
return this.keys.filter((k) => !k.isDisabled).length;
|
||||
}
|
||||
|
||||
public incrementUsage(keyHash: string, modelFamily: DeepseekModelFamily, usage: { input: number; output: number }) {
|
||||
const key = this.keys.find((k) => k.hash === keyHash);
|
||||
if (!key) return;
|
||||
|
||||
key.promptCount++;
|
||||
|
||||
if (!key.tokenUsage) {
|
||||
key.tokenUsage = {};
|
||||
}
|
||||
// Deepseek only has one model family "deepseek"
|
||||
if (!key.tokenUsage[modelFamily]) {
|
||||
key.tokenUsage[modelFamily] = { input: 0, output: 0 };
|
||||
}
|
||||
|
||||
const currentFamilyUsage = key.tokenUsage[modelFamily]!;
|
||||
currentFamilyUsage.input += usage.input;
|
||||
currentFamilyUsage.output += usage.output;
|
||||
}
|
||||
|
||||
/**
|
||||
* Upon being rate limited, a key will be locked out for this many milliseconds
|
||||
* while we wait for other concurrent requests to finish.
|
||||
*/
|
||||
private static readonly RATE_LIMIT_LOCKOUT = 2000;
|
||||
/**
|
||||
* Upon assigning a key, we will wait this many milliseconds before allowing it
|
||||
* to be used again. This is to prevent the queue from flooding a key with too
|
||||
* many requests while we wait to learn whether previous ones succeeded.
|
||||
*/
|
||||
private static readonly KEY_REUSE_DELAY = 500;
|
||||
|
||||
getLockoutPeriod = createGenericGetLockoutPeriod(() => this.keys);
|
||||
|
||||
public markRateLimited(keyHash: string) {
|
||||
this.log.debug({ key: keyHash }, "Key rate limited");
|
||||
const key = this.keys.find((k) => k.hash === keyHash)!;
|
||||
const now = Date.now();
|
||||
key.rateLimitedAt = now;
|
||||
key.rateLimitedUntil = now + DeepseekKeyProvider.RATE_LIMIT_LOCKOUT;
|
||||
}
|
||||
|
||||
public recheck(): void {
|
||||
if (!this.checker || !config.checkKeys) return;
|
||||
for (const key of this.keys) {
|
||||
this.update(key.hash, {
|
||||
isOverQuota: false,
|
||||
isDisabled: false,
|
||||
lastChecked: 0
|
||||
});
|
||||
void this.checker.checkKey(key);
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Applies a short artificial delay to the key upon dequeueing, in order to
|
||||
* prevent it from being immediately assigned to another request before the
|
||||
* current one can be dispatched.
|
||||
**/
|
||||
private throttle(hash: string) {
|
||||
const now = Date.now();
|
||||
const key = this.keys.find((k) => k.hash === hash)!;
|
||||
|
||||
const currentRateLimit = key.rateLimitedUntil;
|
||||
const nextRateLimit = now + DeepseekKeyProvider.KEY_REUSE_DELAY;
|
||||
|
||||
key.rateLimitedAt = now;
|
||||
key.rateLimitedUntil = Math.max(currentRateLimit, nextRateLimit);
|
||||
}
|
||||
}
|
||||
@@ -42,19 +42,20 @@ export class GcpKeyChecker extends KeyCheckerBase<GcpKey> {
|
||||
this.invokeModel("claude-3-haiku@20240307", key, true),
|
||||
this.invokeModel("claude-3-sonnet@20240229", key, true),
|
||||
this.invokeModel("claude-3-opus@20240229", key, true),
|
||||
this.invokeModel("claude-3-5-sonnet@20240620", key, true),
|
||||
this.invokeModel("claude-opus-4-1@20250805", key, true),
|
||||
this.invokeModel("claude-3-5-sonnet-v2@20241022", key, true),
|
||||
];
|
||||
|
||||
const [sonnet, haiku, opus, sonnet35] = await Promise.all(checks);
|
||||
const [sonnet, haiku, opus3, opus41, sonnet35] = await Promise.all(checks);
|
||||
|
||||
this.log.debug(
|
||||
{ key: key.hash, sonnet, haiku, opus, sonnet35 },
|
||||
{ key: key.hash, sonnet, haiku, opus3, opus41, sonnet35 },
|
||||
"GCP model initial tests complete."
|
||||
);
|
||||
|
||||
const families: GcpModelFamily[] = [];
|
||||
if (sonnet || sonnet35 || haiku) families.push("gcp-claude");
|
||||
if (opus) families.push("gcp-claude-opus");
|
||||
if (opus3 || opus41) families.push("gcp-claude-opus");
|
||||
|
||||
if (families.length === 0) {
|
||||
this.log.warn(
|
||||
@@ -78,8 +79,10 @@ export class GcpKeyChecker extends KeyCheckerBase<GcpKey> {
|
||||
await this.invokeModel("claude-3-sonnet@20240229", key, false);
|
||||
} else if (key.sonnet35Enabled) {
|
||||
await this.invokeModel("claude-3-5-sonnet@20240620", key, false);
|
||||
await this.invokeModel("claude-3-5-sonnet-v2@20241022", key, false);
|
||||
} else {
|
||||
await this.invokeModel("claude-3-opus@20240229", key, false);
|
||||
await this.invokeModel("claude-opus-4-1@20250805", key, false);
|
||||
}
|
||||
|
||||
this.updateKey(key.hash, { lastChecked: Date.now() });
|
||||
|
||||
@@ -7,11 +7,8 @@ import { createGenericGetLockoutPeriod, Key, KeyProvider } from "..";
|
||||
import { prioritizeKeys } from "../prioritize-keys";
|
||||
import { GcpKeyChecker } from "./checker";
|
||||
|
||||
type GcpKeyUsage = {
|
||||
[K in GcpModelFamily as `${K}Tokens`]: number;
|
||||
};
|
||||
|
||||
export interface GcpKey extends Key, GcpKeyUsage {
|
||||
// GcpKeyUsage is removed, tokenUsage from base Key interface will be used.
|
||||
export interface GcpKey extends Key {
|
||||
readonly service: "gcp";
|
||||
readonly modelFamilies: GcpModelFamily[];
|
||||
sonnetEnabled: boolean;
|
||||
@@ -75,8 +72,7 @@ export class GcpKeyProvider implements KeyProvider<GcpKey> {
|
||||
sonnet35Enabled: false,
|
||||
accessToken: "",
|
||||
accessTokenExpiresAt: 0,
|
||||
["gcp-claudeTokens"]: 0,
|
||||
["gcp-claude-opusTokens"]: 0,
|
||||
tokenUsage: {}, // Initialize new tokenUsage field
|
||||
};
|
||||
this.keys.push(newKey);
|
||||
}
|
||||
@@ -160,11 +156,22 @@ export class GcpKeyProvider implements KeyProvider<GcpKey> {
|
||||
return this.keys.filter((k) => !k.isDisabled).length;
|
||||
}
|
||||
|
||||
public incrementUsage(hash: string, model: string, tokens: number) {
|
||||
const key = this.keys.find((k) => k.hash === hash);
|
||||
public incrementUsage(keyHash: string, modelFamily: GcpModelFamily, usage: { input: number; output: number }) {
|
||||
const key = this.keys.find((k) => k.hash === keyHash);
|
||||
if (!key) return;
|
||||
|
||||
key.promptCount++;
|
||||
key[`${getGcpModelFamily(model)}Tokens`] += tokens;
|
||||
|
||||
if (!key.tokenUsage) {
|
||||
key.tokenUsage = {};
|
||||
}
|
||||
if (!key.tokenUsage[modelFamily]) {
|
||||
key.tokenUsage[modelFamily] = { input: 0, output: 0 };
|
||||
}
|
||||
|
||||
const currentFamilyUsage = key.tokenUsage[modelFamily]!;
|
||||
currentFamilyUsage.input += usage.input;
|
||||
currentFamilyUsage.output += usage.output;
|
||||
}
|
||||
|
||||
getLockoutPeriod = createGenericGetLockoutPeriod(() => this.keys);
|
||||
|
||||
@@ -11,7 +11,12 @@ const KEY_CHECK_PERIOD = 6 * 60 * 60 * 1000; // 3 hours
|
||||
const LIST_MODELS_URL =
|
||||
"https://generativelanguage.googleapis.com/v1beta/models";
|
||||
const GENERATE_CONTENT_URL =
|
||||
"https://generativelanguage.googleapis.com/v1beta/models/gemini-1.5-pro-latest:generateContent?key=%KEY%";
|
||||
"https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent?key=%KEY%";
|
||||
const PRO_MODEL_ID = "gemini-2.5-pro";
|
||||
const GENERATE_PRO_CONTENT_URL =
|
||||
`https://generativelanguage.googleapis.com/v1beta/models/${PRO_MODEL_ID}:generateContent?key=%KEY%`;
|
||||
const IMAGEN_BILLING_TEST_URL =
|
||||
"https://generativelanguage.googleapis.com/v1beta/models/imagen-3.0-generate-002:predict?key=%KEY%";
|
||||
|
||||
type ListModelsResponse = {
|
||||
models: {
|
||||
@@ -46,12 +51,30 @@ export class GoogleAIKeyChecker extends KeyCheckerBase<GoogleAIKey> {
|
||||
|
||||
protected async testKeyOrFail(key: GoogleAIKey) {
|
||||
const provisionedModels = await this.getProvisionedModels(key);
|
||||
|
||||
// Always test flash model access (existing behaviour)
|
||||
await this.testGenerateContent(key);
|
||||
|
||||
const updates = { modelFamilies: provisionedModels };
|
||||
// Test if billing is enabled for this key
|
||||
const billingEnabled = await this.testBillingEnabled(key);
|
||||
|
||||
// If key claims to support gemini-pro, perform a second layer test with a pro model.
|
||||
let effectiveFamilies = [...provisionedModels];
|
||||
if (effectiveFamilies.includes("gemini-pro")) {
|
||||
const proAccessible = await this.canAccessModel(
|
||||
key,
|
||||
GENERATE_PRO_CONTENT_URL
|
||||
);
|
||||
if (!proAccessible) {
|
||||
// Remove pro access if invocation fails
|
||||
effectiveFamilies = effectiveFamilies.filter((f) => f !== "gemini-pro");
|
||||
}
|
||||
}
|
||||
|
||||
const updates = { modelFamilies: effectiveFamilies, billingEnabled };
|
||||
this.updateKey(key.hash, updates);
|
||||
this.log.info(
|
||||
{ key: key.hash, models: key.modelFamilies, ids: key.modelIds.length },
|
||||
{ key: key.hash, models: effectiveFamilies, ids: key.modelIds?.length, billingEnabled },
|
||||
"Checked key."
|
||||
);
|
||||
}
|
||||
@@ -94,6 +117,57 @@ export class GoogleAIKeyChecker extends KeyCheckerBase<GoogleAIKey> {
|
||||
);
|
||||
}
|
||||
|
||||
private async canAccessModel(
|
||||
key: GoogleAIKey,
|
||||
modelGenerateUrlTemplate: string
|
||||
): Promise<boolean> {
|
||||
const payload = {
|
||||
contents: [{ parts: { text: "hi" }, role: "user" }],
|
||||
tools: [],
|
||||
safetySettings: [],
|
||||
generationConfig: { maxOutputTokens: 5 },
|
||||
};
|
||||
try {
|
||||
await axios.post(
|
||||
modelGenerateUrlTemplate.replace("%KEY%", key.key),
|
||||
payload,
|
||||
{ validateStatus: (status) => status === 200 }
|
||||
);
|
||||
return true;
|
||||
} catch {
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
private async testBillingEnabled(key: GoogleAIKey): Promise<boolean> {
|
||||
const payload = {
|
||||
instances: [{ prompt: "" }]
|
||||
};
|
||||
try {
|
||||
const response = await axios.post(
|
||||
IMAGEN_BILLING_TEST_URL.replace("%KEY%", key.key),
|
||||
payload,
|
||||
{ validateStatus: () => true } // Accept all status codes
|
||||
);
|
||||
|
||||
if (response.status === 400) {
|
||||
const errorMessage = response.data?.error?.message || "";
|
||||
// If the error message contains the billing requirement, billing is NOT enabled
|
||||
if (errorMessage.includes("Imagen API is only accessible to billed users at this time")) {
|
||||
return false;
|
||||
}
|
||||
// Other 400 errors indicate billing IS enabled (following Python logic)
|
||||
return true;
|
||||
}
|
||||
|
||||
// For other status codes, assume no billing (conservative approach)
|
||||
return false;
|
||||
} catch (error: any) {
|
||||
// Network errors or other issues - assume no billing
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
protected handleAxiosError(key: GoogleAIKey, error: AxiosError): void {
|
||||
if (error.response && GoogleAIKeyChecker.errorIsGoogleAIError(error)) {
|
||||
const httpStatus = error.response.status;
|
||||
@@ -103,69 +177,92 @@ export class GoogleAIKeyChecker extends KeyCheckerBase<GoogleAIKey> {
|
||||
case 400: {
|
||||
const keyDeadMsgs = [
|
||||
/please enable billing/i,
|
||||
/API key not valid/i,
|
||||
/API key expired/i,
|
||||
/pass a valid API/i,
|
||||
/api key not valid/i,
|
||||
/api key expired/i,
|
||||
/pass a valid api/i, // This may also indicate an invalid key.
|
||||
/api key not found/i, // Explicitly for "not found" keys
|
||||
];
|
||||
const text = JSON.stringify(error.response.data.error);
|
||||
if (text.match(keyDeadMsgs.join("|"))) {
|
||||
if (keyDeadMsgs.some((r) => r.test(text))) {
|
||||
this.log.warn(
|
||||
{ key: key.hash, error: text },
|
||||
"Key check returned a non-transient 400 error. Disabling key."
|
||||
{ key: key.hash, error: text, errorCode: code, httpStatus },
|
||||
"Key check returned a 400 error indicating a permanent key issue (e.g., invalid, expired, billing). Disabling and revoking key."
|
||||
);
|
||||
this.updateKey(key.hash, { isDisabled: true, isRevoked: true });
|
||||
return;
|
||||
}
|
||||
break;
|
||||
}
|
||||
case 401:
|
||||
case 403:
|
||||
// If it's a 400 but not a key-revoking message, treat as transient.
|
||||
this.log.warn(
|
||||
{ key: key.hash, status, code, message, details },
|
||||
"Key check returned Forbidden/Unauthorized error. Disabling key."
|
||||
{ key: key.hash, error: text, errorCode: code, httpStatus },
|
||||
"Key check returned a generic 400 error. Treating as transient. Rechecking in 1 minute."
|
||||
);
|
||||
const recheckInOneMinute = Date.now() - (KEY_CHECK_PERIOD - 60 * 1000);
|
||||
this.updateKey(key.hash, { lastChecked: recheckInOneMinute });
|
||||
return;
|
||||
}
|
||||
case 401: // Unauthorized
|
||||
case 403: // Forbidden / Permission Denied
|
||||
this.log.warn(
|
||||
{ key: key.hash, status, code, message, details, httpStatus },
|
||||
"Key check returned Forbidden/Unauthorized error. Disabling and revoking key."
|
||||
);
|
||||
this.updateKey(key.hash, { isDisabled: true, isRevoked: true });
|
||||
return;
|
||||
case 429: {
|
||||
case 429: { // Resource Exhausted (Rate Limit / Quota)
|
||||
const text = JSON.stringify(error.response.data.error);
|
||||
|
||||
const keyDeadMsgs = [
|
||||
/GenerateContentRequestsPerMinutePerProjectPerRegion/i,
|
||||
/"quota_limit_value":"0"/i,
|
||||
const hardQuotaMessages = [
|
||||
/GenerateContentRequestsPerMinutePerProjectPerRegion/i, // Often indicates a hard limit or misconfiguration
|
||||
/"quota_limit_value":"0"/i, // Explicitly out of quota
|
||||
/billing account not found/i, // Billing issue presented as 429 sometimes
|
||||
/project has been suspended/i, // Project level issue
|
||||
];
|
||||
if (text.match(keyDeadMsgs.join("|"))) {
|
||||
if (hardQuotaMessages.some((r) => r.test(text))) {
|
||||
this.log.warn(
|
||||
{ key: key.hash, error: text },
|
||||
"Key check returned a non-transient 429 error. Disabling key."
|
||||
{ key: key.hash, error: text, errorCode: code, httpStatus },
|
||||
"Key check returned a 429 error indicating a hard quota limit or billing issue. Disabling and marking as over quota, but not revoking."
|
||||
);
|
||||
this.updateKey(key.hash, { isDisabled: true, isRevoked: true });
|
||||
this.updateKey(key.hash, { isDisabled: true, isRevoked: false, isOverQuota: true });
|
||||
return;
|
||||
}
|
||||
|
||||
// Transient 429 (e.g., TPM/RPM exceeded)
|
||||
this.log.warn(
|
||||
{ key: key.hash, status, code, message, details },
|
||||
"Key is rate limited. Rechecking key in 1 minute."
|
||||
{ key: key.hash, status, code, message, details, httpStatus },
|
||||
"Key is temporarily rate limited (429). Rechecking key in 1 minute."
|
||||
);
|
||||
const next = Date.now() - (KEY_CHECK_PERIOD - 60 * 1000);
|
||||
this.updateKey(key.hash, { lastChecked: next });
|
||||
const nextTransient429 = Date.now() - (KEY_CHECK_PERIOD - 60 * 1000);
|
||||
this.updateKey(key.hash, { lastChecked: nextTransient429 });
|
||||
return;
|
||||
}
|
||||
case 500: // Internal Server Error
|
||||
case 503: // Service Unavailable
|
||||
case 504: // Deadline Exceeded
|
||||
this.log.warn(
|
||||
{ key: key.hash, status, code, message, details, httpStatus },
|
||||
`Key check encountered a server-side error (${httpStatus}). Treating as transient. Rechecking in 1 minute.`
|
||||
);
|
||||
const recheck5xx = Date.now() - (KEY_CHECK_PERIOD - 60 * 1000);
|
||||
this.updateKey(key.hash, { lastChecked: recheck5xx });
|
||||
return;
|
||||
}
|
||||
|
||||
// Fallthrough for other unexpected Google AI API errors
|
||||
this.log.error(
|
||||
{ key: key.hash, status, code, message, details },
|
||||
"Encountered unexpected error status while checking key. This may indicate a change in the API; please report this."
|
||||
{ key: key.hash, status, code, message, details, httpStatus },
|
||||
"Encountered unexpected Google AI error status while checking key. This may indicate a change in the API. Rechecking in 1 minute."
|
||||
);
|
||||
return this.updateKey(key.hash, { lastChecked: Date.now() });
|
||||
const recheckUnexpected = Date.now() - (KEY_CHECK_PERIOD - 60 * 1000);
|
||||
this.updateKey(key.hash, { lastChecked: recheckUnexpected });
|
||||
return;
|
||||
}
|
||||
|
||||
// Network errors (not HTTP errors from Google AI)
|
||||
this.log.error(
|
||||
{ key: key.hash, error: error.message },
|
||||
"Network error while checking key; trying this key again in a minute."
|
||||
"Network error while checking key; trying this key again in 1 minute."
|
||||
);
|
||||
const oneMinute = 10 * 1000;
|
||||
const next = Date.now() - (KEY_CHECK_PERIOD - oneMinute);
|
||||
return this.updateKey(key.hash, { lastChecked: next });
|
||||
const recheckNetworkError = Date.now() - (KEY_CHECK_PERIOD - 60 * 1000); // Corrected to 60 * 1000
|
||||
return this.updateKey(key.hash, { lastChecked: recheckNetworkError });
|
||||
}
|
||||
|
||||
static errorIsGoogleAIError(
|
||||
|
||||
@@ -22,15 +22,18 @@ export type GoogleAIKeyUpdate = Omit<
|
||||
| "rateLimitedUntil"
|
||||
>;
|
||||
|
||||
type GoogleAIKeyUsage = {
|
||||
[K in GoogleAIModelFamily as `${K}Tokens`]: number;
|
||||
};
|
||||
|
||||
export interface GoogleAIKey extends Key, GoogleAIKeyUsage {
|
||||
// GoogleAIKeyUsage is removed, tokenUsage from base Key interface will be used.
|
||||
export interface GoogleAIKey extends Key {
|
||||
readonly service: "google-ai";
|
||||
readonly modelFamilies: GoogleAIModelFamily[];
|
||||
/** All detected model IDs on this key. */
|
||||
modelIds: string[];
|
||||
/** Whether this key is over quota (for any model family). */
|
||||
isOverQuota?: boolean;
|
||||
/** Model families that are over quota and need to be excluded. */
|
||||
overQuotaFamilies?: GoogleAIModelFamily[];
|
||||
/** Whether this key has billing enabled (required for preview models). */
|
||||
billingEnabled?: boolean;
|
||||
}
|
||||
|
||||
/**
|
||||
@@ -45,6 +48,13 @@ const RATE_LIMIT_LOCKOUT = 2000;
|
||||
*/
|
||||
const KEY_REUSE_DELAY = 500;
|
||||
|
||||
/**
|
||||
* Determines if a model is a preview model that requires billing-enabled keys.
|
||||
*/
|
||||
function isPreviewModel(model: string): boolean {
|
||||
return model.includes("-preview");
|
||||
}
|
||||
|
||||
export class GoogleAIKeyProvider implements KeyProvider<GoogleAIKey> {
|
||||
readonly service = "google-ai";
|
||||
|
||||
@@ -69,6 +79,7 @@ export class GoogleAIKeyProvider implements KeyProvider<GoogleAIKey> {
|
||||
modelFamilies: ["gemini-pro"],
|
||||
isDisabled: false,
|
||||
isRevoked: false,
|
||||
isOverQuota: false,
|
||||
promptCount: 0,
|
||||
lastUsed: 0,
|
||||
rateLimitedAt: 0,
|
||||
@@ -79,10 +90,10 @@ export class GoogleAIKeyProvider implements KeyProvider<GoogleAIKey> {
|
||||
.digest("hex")
|
||||
.slice(0, 8)}`,
|
||||
lastChecked: 0,
|
||||
"gemini-flashTokens": 0,
|
||||
"gemini-proTokens": 0,
|
||||
"gemini-ultraTokens": 0,
|
||||
tokenUsage: {}, // Initialize new tokenUsage field
|
||||
modelIds: [],
|
||||
overQuotaFamilies: [],
|
||||
billingEnabled: false, // Will be determined during key checking
|
||||
};
|
||||
this.keys.push(newKey);
|
||||
}
|
||||
@@ -102,11 +113,23 @@ export class GoogleAIKeyProvider implements KeyProvider<GoogleAIKey> {
|
||||
|
||||
public get(model: string) {
|
||||
const neededFamily = getGoogleAIModelFamily(model);
|
||||
const availableKeys = this.keys.filter(
|
||||
let availableKeys = this.keys.filter(
|
||||
(k) => !k.isDisabled && k.modelFamilies.includes(neededFamily)
|
||||
);
|
||||
if (availableKeys.length === 0) {
|
||||
throw new PaymentRequiredError("No Google AI keys available");
|
||||
|
||||
// For preview models, only use billing-enabled keys
|
||||
if (isPreviewModel(model)) {
|
||||
availableKeys = availableKeys.filter((k) => k.billingEnabled === true);
|
||||
if (availableKeys.length === 0) {
|
||||
throw new PaymentRequiredError(
|
||||
"No billing-enabled Google AI keys available for preview models"
|
||||
);
|
||||
}
|
||||
} else {
|
||||
// For standard models, use any available key
|
||||
if (availableKeys.length === 0) {
|
||||
throw new PaymentRequiredError("No Google AI keys available");
|
||||
}
|
||||
}
|
||||
|
||||
const keysByPriority = prioritizeKeys(availableKeys);
|
||||
@@ -133,11 +156,22 @@ export class GoogleAIKeyProvider implements KeyProvider<GoogleAIKey> {
|
||||
return this.keys.filter((k) => !k.isDisabled).length;
|
||||
}
|
||||
|
||||
public incrementUsage(hash: string, model: string, tokens: number) {
|
||||
const key = this.keys.find((k) => k.hash === hash);
|
||||
public incrementUsage(keyHash: string, modelFamily: GoogleAIModelFamily, usage: { input: number; output: number }) {
|
||||
const key = this.keys.find((k) => k.hash === keyHash);
|
||||
if (!key) return;
|
||||
|
||||
key.promptCount++;
|
||||
key[`${getGoogleAIModelFamily(model)}Tokens`] += tokens;
|
||||
|
||||
if (!key.tokenUsage) {
|
||||
key.tokenUsage = {};
|
||||
}
|
||||
if (!key.tokenUsage[modelFamily]) {
|
||||
key.tokenUsage[modelFamily] = { input: 0, output: 0 };
|
||||
}
|
||||
|
||||
const currentFamilyUsage = key.tokenUsage[modelFamily]!;
|
||||
currentFamilyUsage.input += usage.input;
|
||||
currentFamilyUsage.output += usage.output;
|
||||
}
|
||||
|
||||
getLockoutPeriod = createGenericGetLockoutPeriod(() => this.keys);
|
||||
@@ -157,7 +191,52 @@ export class GoogleAIKeyProvider implements KeyProvider<GoogleAIKey> {
|
||||
key.rateLimitedUntil = now + RATE_LIMIT_LOCKOUT;
|
||||
}
|
||||
|
||||
public recheck() {}
|
||||
/**
|
||||
* Periodically rechecks keys that have been marked as over-quota or disabled
|
||||
* to see if they can be restored to the rotation.
|
||||
*/
|
||||
public recheck() {
|
||||
// For each key that's either over quota or disabled, reset its status
|
||||
// so the checker can re-evaluate it
|
||||
const keysToRecheck = this.keys.filter(k => k.isOverQuota || (k.isDisabled && !k.isRevoked));
|
||||
|
||||
if (keysToRecheck.length === 0) {
|
||||
this.log.debug("No Google AI keys need rechecking");
|
||||
return;
|
||||
}
|
||||
|
||||
keysToRecheck.forEach(key => {
|
||||
// Priority to keys marked as overQuota (and not revoked)
|
||||
if (key.isOverQuota && !key.isRevoked) {
|
||||
this.log.info(
|
||||
{ key: key.hash },
|
||||
"Rechecking over-quota Google AI key. Resetting isOverQuota, isDisabled, and overQuotaFamilies."
|
||||
);
|
||||
this.update(key.hash, {
|
||||
isOverQuota: false,
|
||||
isDisabled: false, // Was disabled due to being overQuota
|
||||
lastChecked: 0, // Force a recheck soon
|
||||
overQuotaFamilies: [] // Clear any specific family quotas
|
||||
});
|
||||
}
|
||||
// Handle other disabled (but not revoked) keys that weren't caught by the isOverQuota condition
|
||||
else if (key.isDisabled && !key.isRevoked) {
|
||||
this.log.info(
|
||||
{ key: key.hash },
|
||||
"Rechecking disabled (but not revoked or previously over-quota) Google AI key."
|
||||
);
|
||||
this.update(key.hash, {
|
||||
isDisabled: false, // Re-enable for checking
|
||||
lastChecked: 0 // Force a recheck soon
|
||||
});
|
||||
}
|
||||
});
|
||||
|
||||
// Schedule the actual key checking if we have a checker
|
||||
if (this.checker) {
|
||||
this.checker.scheduleNextCheck();
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Applies a short artificial delay to the key upon dequeueing, in order to
|
||||
|
||||
@@ -6,6 +6,7 @@ export type APIFormat =
|
||||
| "openai"
|
||||
| "openai-text"
|
||||
| "openai-image"
|
||||
| "openai-responses" // OpenAI Responses API (e.g., for o1-pro, o3-pro)
|
||||
| "anthropic-chat" // Anthropic's newer messages array format
|
||||
| "anthropic-text" // Legacy flat string prompt format
|
||||
| "google-ai"
|
||||
@@ -35,6 +36,14 @@ export interface Key {
|
||||
rateLimitedAt: number;
|
||||
/** The time until which this key is rate limited. */
|
||||
rateLimitedUntil: number;
|
||||
/** Detailed token usage, separated by input and output, per model family. */
|
||||
tokenUsage?: {
|
||||
[family in ModelFamily]?: {
|
||||
input: number;
|
||||
output: number;
|
||||
legacy_total?: number; // To store migrated single-number totals
|
||||
};
|
||||
};
|
||||
}
|
||||
|
||||
/*
|
||||
@@ -52,12 +61,12 @@ for service-agnostic functionality.
|
||||
export interface KeyProvider<T extends Key = Key> {
|
||||
readonly service: LLMService;
|
||||
init(): void;
|
||||
get(model: string): T;
|
||||
get(model: string, streaming?: boolean): T;
|
||||
list(): Omit<T, "key">[];
|
||||
disable(key: T): void;
|
||||
update(hash: string, update: Partial<T>): void;
|
||||
available(): number;
|
||||
incrementUsage(hash: string, model: string, tokens: number): void;
|
||||
incrementUsage(hash: string, modelFamily: ModelFamily, usage: { input: number; output: number }): void;
|
||||
getLockoutPeriod(model: ModelFamily): number;
|
||||
markRateLimited(hash: string): void;
|
||||
recheck(): void;
|
||||
@@ -92,3 +101,8 @@ export { AzureOpenAIKey } from "./azure/provider";
|
||||
export { GoogleAIKey } from "././google-ai/provider";
|
||||
export { MistralAIKey } from "./mistral-ai/provider";
|
||||
export { OpenAIKey } from "./openai/provider";
|
||||
export { DeepseekKey } from "./deepseek/provider";
|
||||
export { XaiKey } from "./xai/provider";
|
||||
export { CohereKey } from "./cohere/provider";
|
||||
export { QwenKey } from "./qwen/provider";
|
||||
export { MoonshotKey } from "./moonshot/provider";
|
||||
|
||||
@@ -13,6 +13,11 @@ import { AwsBedrockKeyProvider } from "./aws/provider";
|
||||
import { GcpKeyProvider, GcpKey } from "./gcp/provider";
|
||||
import { AzureOpenAIKeyProvider } from "./azure/provider";
|
||||
import { MistralAIKeyProvider } from "./mistral-ai/provider";
|
||||
import { DeepseekKeyProvider } from "./deepseek/provider";
|
||||
import { XaiKeyProvider } from "./xai/provider";
|
||||
import { CohereKeyProvider } from "./cohere/provider";
|
||||
import { QwenKeyProvider } from "./qwen/provider";
|
||||
import { MoonshotKeyProvider } from "./moonshot/provider";
|
||||
|
||||
type AllowedPartial = OpenAIKeyUpdate | AnthropicKeyUpdate | Partial<GcpKey>;
|
||||
|
||||
@@ -30,6 +35,11 @@ export class KeyPool {
|
||||
this.keyProviders.push(new AwsBedrockKeyProvider());
|
||||
this.keyProviders.push(new GcpKeyProvider());
|
||||
this.keyProviders.push(new AzureOpenAIKeyProvider());
|
||||
this.keyProviders.push(new DeepseekKeyProvider());
|
||||
this.keyProviders.push(new XaiKeyProvider());
|
||||
this.keyProviders.push(new CohereKeyProvider());
|
||||
this.keyProviders.push(new QwenKeyProvider());
|
||||
this.keyProviders.push(new MoonshotKeyProvider());
|
||||
}
|
||||
|
||||
public init() {
|
||||
@@ -43,7 +53,7 @@ export class KeyPool {
|
||||
this.scheduleRecheck();
|
||||
}
|
||||
|
||||
public get(model: string, service?: LLMService, multimodal?: boolean): Key {
|
||||
public get(model: string, service?: LLMService, multimodal?: boolean, streaming?: boolean): Key {
|
||||
// hack for some claude requests needing keys with particular permissions
|
||||
// even though they use the same models as the non-multimodal requests
|
||||
if (multimodal) {
|
||||
@@ -51,7 +61,7 @@ export class KeyPool {
|
||||
}
|
||||
|
||||
const queryService = service || this.getServiceForModel(model);
|
||||
return this.getKeyProvider(queryService).get(model);
|
||||
return this.getKeyProvider(queryService).get(model, streaming);
|
||||
}
|
||||
|
||||
public list(): Omit<Key, "key">[] {
|
||||
@@ -69,7 +79,12 @@ export class KeyPool {
|
||||
service.update(key.hash, { isRevoked: reason === "revoked" });
|
||||
if (
|
||||
service instanceof OpenAIKeyProvider ||
|
||||
service instanceof AnthropicKeyProvider
|
||||
service instanceof AnthropicKeyProvider ||
|
||||
service instanceof DeepseekKeyProvider ||
|
||||
service instanceof XaiKeyProvider ||
|
||||
service instanceof CohereKeyProvider ||
|
||||
service instanceof QwenKeyProvider ||
|
||||
service instanceof MoonshotKeyProvider
|
||||
) {
|
||||
service.update(key.hash, { isOverQuota: reason === "quota" });
|
||||
}
|
||||
@@ -96,9 +111,30 @@ export class KeyPool {
|
||||
}, 0);
|
||||
}
|
||||
|
||||
public incrementUsage(key: Key, model: string, tokens: number): void {
|
||||
public incrementUsage(key: Key, modelName: string, usage: { input: number; output: number }): void {
|
||||
const provider = this.getKeyProvider(key.service);
|
||||
provider.incrementUsage(key.hash, model, tokens);
|
||||
// Assuming the provider's incrementUsage expects a modelFamily.
|
||||
// We need a robust way to get modelFamily from modelName here.
|
||||
// This might involve calling a method similar to getModelFamilyForRequest from user-store,
|
||||
// or enhancing getServiceForModel to also return family, or passing family directly.
|
||||
// For now, let's assume the provider can handle the modelName or we derive family.
|
||||
// This part is tricky as KeyPool's getServiceForModel is for service, not family directly from a generic model string.
|
||||
// Let's assume for now the provider's incrementUsage can take modelName and derive family,
|
||||
// or the KeyProvider interface's incrementUsage should take modelName.
|
||||
// The KeyProvider interface was changed to modelFamily. So we MUST derive it.
|
||||
// This requires a utility function similar to what's in user-store or models.ts.
|
||||
// For now, I'll placeholder this derivation. This is a critical point.
|
||||
// Placeholder: const modelFamily = this.getModelFamilyForModel(modelName, key.service);
|
||||
// This is complex because getModelFamilyForModel needs the service context.
|
||||
// Let's assume the `modelName` passed here is actually `modelFamily` for now,
|
||||
// or that the caller will resolve it.
|
||||
// The KeyProvider interface expects `modelFamily`. The caller in middleware/response/index.ts
|
||||
// has `model` (name) and `req.outboundApi`. It should resolve to family there.
|
||||
// So, `modelName` here should actually be `modelFamily`.
|
||||
// I will assume the caller of KeyPool.incrementUsage will pass modelFamily.
|
||||
// So, changing `model: string` to `modelFamily: ModelFamily` in signature.
|
||||
// This change needs to be propagated to the caller.
|
||||
provider.incrementUsage(key.hash, modelName as ModelFamily, usage); // Casting modelName, assuming caller provides family
|
||||
}
|
||||
|
||||
public getLockoutPeriod(family: ModelFamily): number {
|
||||
@@ -127,9 +163,32 @@ export class KeyPool {
|
||||
const provider = this.getKeyProvider(service);
|
||||
provider.recheck();
|
||||
}
|
||||
|
||||
/**
|
||||
* Validates organization verification status for all OpenAI keys and returns detailed results.
|
||||
* This tests each key that claims to have gpt-image-1 or o3 access by attempting to stream from the o3 model,
|
||||
* which requires a verified organization. Keys from unverified organizations will have only
|
||||
* gpt-image-1 access removed from their available model families, as o3 can still be used without streaming.
|
||||
*/
|
||||
public async validateGptImageAccess(): Promise<{
|
||||
total: number;
|
||||
validated: number;
|
||||
removed: string[];
|
||||
verified: string[];
|
||||
errors: {key: string, error: string}[];
|
||||
}> {
|
||||
const provider = this.getKeyProvider("openai");
|
||||
if (!(provider instanceof OpenAIKeyProvider)) {
|
||||
throw new Error("OpenAI provider not initialized");
|
||||
}
|
||||
|
||||
return provider.validateGptImageAccess();
|
||||
}
|
||||
|
||||
private getServiceForModel(model: string): LLMService {
|
||||
if (
|
||||
if (model.startsWith("deepseek")) {
|
||||
return "deepseek";
|
||||
} else if (
|
||||
model.startsWith("gpt") ||
|
||||
model.startsWith("text-embedding-ada") ||
|
||||
model.startsWith("dall-e")
|
||||
@@ -149,6 +208,14 @@ export class KeyPool {
|
||||
} else if (model.includes("mistral")) {
|
||||
// https://docs.mistral.ai/platform/endpoints
|
||||
return "mistral-ai";
|
||||
} else if (model.includes("xai")) {
|
||||
return "xai";
|
||||
} else if (model.includes("command") || model.includes("cohere")) {
|
||||
return "cohere";
|
||||
} else if (model.includes("qwen")) {
|
||||
return "qwen";
|
||||
} else if (model.includes("moonshot")) {
|
||||
return "moonshot";
|
||||
} else if (model.startsWith("anthropic.claude")) {
|
||||
// AWS offers models from a few providers
|
||||
// https://docs.aws.amazon.com/bedrock/latest/userguide/model-ids-arns.html
|
||||
@@ -164,8 +231,10 @@ export class KeyPool {
|
||||
}
|
||||
|
||||
/**
|
||||
* Schedules a periodic recheck of OpenAI keys, which runs every 8 hours on
|
||||
* a schedule offset by the server's hostname.
|
||||
* Schedules periodic rechecks of keys:
|
||||
* - OpenAI keys: every 8 hours
|
||||
* - Google AI keys: every 1 hour (to handle quota resets more promptly)
|
||||
* All schedules have an offset based on the server's hostname.
|
||||
*/
|
||||
private scheduleRecheck(): void {
|
||||
const machineHash = crypto
|
||||
@@ -173,19 +242,35 @@ export class KeyPool {
|
||||
.update(os.hostname())
|
||||
.digest("hex");
|
||||
const offset = parseInt(machineHash, 16) % 7;
|
||||
const hour = [0, 8, 16].map((h) => h + offset).join(",");
|
||||
const crontab = `0 ${hour} * * *`;
|
||||
|
||||
// OpenAI keys recheck every 8 hours
|
||||
const openaiHour = [0, 8, 16].map((h) => h + offset).join(",");
|
||||
const openaiCrontab = `0 ${openaiHour} * * *`;
|
||||
|
||||
const job = schedule.scheduleJob(crontab, () => {
|
||||
const next = job.nextInvocation();
|
||||
logger.info({ next }, "Performing periodic recheck.");
|
||||
const openaiJob = schedule.scheduleJob(openaiCrontab, () => {
|
||||
const next = openaiJob.nextInvocation();
|
||||
logger.info({ next, service: "openai" }, "Performing periodic OpenAI key recheck.");
|
||||
this.recheck("openai");
|
||||
});
|
||||
logger.info(
|
||||
{ rule: openaiCrontab, next: openaiJob.nextInvocation(), service: "openai" },
|
||||
"Scheduled periodic OpenAI key recheck job"
|
||||
);
|
||||
this.recheckJobs.openai = openaiJob;
|
||||
|
||||
// Schedule hourly recheck for Google AI keys to handle quota resets more quickly
|
||||
const googleMinute = offset;
|
||||
const googleCrontab = `${googleMinute} * * * *`; // Run every hour
|
||||
|
||||
const googleJob = schedule.scheduleJob(googleCrontab, () => {
|
||||
const next = googleJob.nextInvocation();
|
||||
logger.info({ next, service: "google-ai" }, "Performing hourly Google AI key recheck for quota status.");
|
||||
this.recheck("google-ai");
|
||||
});
|
||||
logger.info(
|
||||
{ rule: crontab, next: job.nextInvocation() },
|
||||
"Scheduled periodic key recheck job"
|
||||
{ rule: googleCrontab, next: googleJob.nextInvocation(), service: "google-ai" },
|
||||
"Scheduled hourly Google AI key recheck job"
|
||||
);
|
||||
this.recheckJobs.openai = job;
|
||||
this.recheckJobs["google-ai"] = googleJob;
|
||||
}
|
||||
}
|
||||
|
||||
@@ -7,11 +7,8 @@ import { createGenericGetLockoutPeriod, Key, KeyProvider } from "..";
|
||||
import { prioritizeKeys } from "../prioritize-keys";
|
||||
import { MistralAIKeyChecker } from "./checker";
|
||||
|
||||
type MistralAIKeyUsage = {
|
||||
[K in MistralAIModelFamily as `${K}Tokens`]: number;
|
||||
};
|
||||
|
||||
export interface MistralAIKey extends Key, MistralAIKeyUsage {
|
||||
// MistralAIKeyUsage is removed, tokenUsage from base Key interface will be used.
|
||||
export interface MistralAIKey extends Key {
|
||||
readonly service: "mistral-ai";
|
||||
readonly modelFamilies: MistralAIModelFamily[];
|
||||
}
|
||||
@@ -67,10 +64,7 @@ export class MistralAIKeyProvider implements KeyProvider<MistralAIKey> {
|
||||
.digest("hex")
|
||||
.slice(0, 8)}`,
|
||||
lastChecked: 0,
|
||||
"mistral-tinyTokens": 0,
|
||||
"mistral-smallTokens": 0,
|
||||
"mistral-mediumTokens": 0,
|
||||
"mistral-largeTokens": 0,
|
||||
tokenUsage: {}, // Initialize new tokenUsage field
|
||||
};
|
||||
this.keys.push(newKey);
|
||||
}
|
||||
@@ -117,12 +111,22 @@ export class MistralAIKeyProvider implements KeyProvider<MistralAIKey> {
|
||||
return this.keys.filter((k) => !k.isDisabled).length;
|
||||
}
|
||||
|
||||
public incrementUsage(hash: string, model: string, tokens: number) {
|
||||
const key = this.keys.find((k) => k.hash === hash);
|
||||
public incrementUsage(keyHash: string, modelFamily: MistralAIModelFamily, usage: { input: number; output: number }) {
|
||||
const key = this.keys.find((k) => k.hash === keyHash);
|
||||
if (!key) return;
|
||||
|
||||
key.promptCount++;
|
||||
const family = getMistralAIModelFamily(model);
|
||||
key[`${family}Tokens`] += tokens;
|
||||
|
||||
if (!key.tokenUsage) {
|
||||
key.tokenUsage = {};
|
||||
}
|
||||
if (!key.tokenUsage[modelFamily]) {
|
||||
key.tokenUsage[modelFamily] = { input: 0, output: 0 };
|
||||
}
|
||||
|
||||
const currentFamilyUsage = key.tokenUsage[modelFamily]!;
|
||||
currentFamilyUsage.input += usage.input;
|
||||
currentFamilyUsage.output += usage.output;
|
||||
}
|
||||
|
||||
getLockoutPeriod = createGenericGetLockoutPeriod(() => this.keys);
|
||||
|
||||
@@ -0,0 +1,127 @@
|
||||
import { MoonshotKey } from "./provider";
|
||||
import { logger } from "../../../logger";
|
||||
import { assertNever } from "../../utils";
|
||||
|
||||
const CHECK_TIMEOUT = 10000;
|
||||
const API_URL = "https://api.moonshot.cn/v1/users/me/balance";
|
||||
|
||||
export class MoonshotKeyChecker {
|
||||
private log = logger.child({ module: "key-checker", service: "moonshot" });
|
||||
|
||||
constructor(private readonly update: (hash: string, key: Partial<MoonshotKey>) => void) {
|
||||
this.log.info("MoonshotKeyChecker initialized");
|
||||
}
|
||||
|
||||
public async checkKey(key: MoonshotKey): Promise<void> {
|
||||
this.log.info({ hash: key.hash }, "Starting key validation check");
|
||||
try {
|
||||
const result = await this.validateKey(key);
|
||||
this.handleCheckResult(key, result);
|
||||
} catch (error) {
|
||||
if (error instanceof Error) {
|
||||
this.log.warn(
|
||||
{ error: error.message, stack: error.stack, hash: key.hash },
|
||||
"Failed to check key status"
|
||||
);
|
||||
} else {
|
||||
this.log.warn(
|
||||
{ error, hash: key.hash },
|
||||
"Failed to check key status with unknown error"
|
||||
);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
private async validateKey(key: MoonshotKey): Promise<"valid" | "invalid" | "quota"> {
|
||||
const controller = new AbortController();
|
||||
const timeout = setTimeout(() => {
|
||||
controller.abort();
|
||||
this.log.warn({ hash: key.hash }, "Key validation timed out after " + CHECK_TIMEOUT + "ms");
|
||||
}, CHECK_TIMEOUT);
|
||||
|
||||
try {
|
||||
// Check balance endpoint to verify key validity
|
||||
const headers = {
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": `Bearer ${key.key}`
|
||||
};
|
||||
|
||||
const response = await fetch(API_URL, {
|
||||
method: "GET",
|
||||
headers,
|
||||
signal: controller.signal,
|
||||
});
|
||||
|
||||
if (response.status === 200) {
|
||||
const data = await response.json();
|
||||
// Check if response has the expected Moonshot API structure
|
||||
if (data && data.status === true && data.code === 0 && data.data) {
|
||||
const balance = data.data.available_balance;
|
||||
// Check if balance is too low (consider it quota exceeded if balance is 0 or negative)
|
||||
if (typeof balance === 'number' && balance <= 0) {
|
||||
return "quota";
|
||||
}
|
||||
return "valid";
|
||||
} else {
|
||||
this.log.warn(
|
||||
{ response: data, hash: key.hash },
|
||||
"Unexpected response format from Moonshot API"
|
||||
);
|
||||
return "invalid";
|
||||
}
|
||||
} else if (response.status === 401) {
|
||||
// Unauthorized - invalid key
|
||||
return "invalid";
|
||||
} else if (response.status === 429) {
|
||||
// Rate limit - but key is valid
|
||||
return "valid";
|
||||
} else {
|
||||
this.log.warn(
|
||||
{ status: response.status, hash: key.hash },
|
||||
"Unexpected status code while testing key validity"
|
||||
);
|
||||
return "invalid";
|
||||
}
|
||||
} catch (error) {
|
||||
if (error instanceof Error && error.name === 'AbortError') {
|
||||
this.log.warn({ hash: key.hash }, "Key validation aborted");
|
||||
}
|
||||
throw error;
|
||||
} finally {
|
||||
clearTimeout(timeout);
|
||||
}
|
||||
}
|
||||
|
||||
private handleCheckResult(
|
||||
key: MoonshotKey,
|
||||
result: "valid" | "invalid" | "quota"
|
||||
): void {
|
||||
switch (result) {
|
||||
case "valid":
|
||||
this.log.info({ hash: key.hash }, "Key is valid and enabled");
|
||||
this.update(key.hash, {
|
||||
isDisabled: false,
|
||||
lastChecked: Date.now(),
|
||||
});
|
||||
break;
|
||||
case "invalid":
|
||||
this.log.warn({ hash: key.hash }, "Key is invalid, marking as revoked");
|
||||
this.update(key.hash, {
|
||||
isDisabled: true,
|
||||
isRevoked: true,
|
||||
lastChecked: Date.now(),
|
||||
});
|
||||
break;
|
||||
case "quota":
|
||||
this.log.warn({ hash: key.hash }, "Key has exceeded its quota, disabling");
|
||||
this.update(key.hash, {
|
||||
isDisabled: true,
|
||||
isOverQuota: true,
|
||||
lastChecked: Date.now(),
|
||||
});
|
||||
break;
|
||||
default:
|
||||
assertNever(result);
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,2 @@
|
||||
export { MoonshotKey, MoonshotKeyProvider } from "./provider";
|
||||
export { MoonshotKeyChecker } from "./checker";
|
||||
@@ -0,0 +1,166 @@
|
||||
import { Key, KeyProvider, createGenericGetLockoutPeriod } from "..";
|
||||
import { MoonshotKeyChecker } from "./checker";
|
||||
import { config } from "../../../config";
|
||||
import { logger } from "../../../logger";
|
||||
import { MoonshotModelFamily, ModelFamily } from "../../models";
|
||||
|
||||
export interface MoonshotKey extends Key {
|
||||
readonly service: "moonshot";
|
||||
readonly modelFamilies: MoonshotModelFamily[];
|
||||
isOverQuota: boolean;
|
||||
}
|
||||
|
||||
export class MoonshotKeyProvider implements KeyProvider<MoonshotKey> {
|
||||
readonly service = "moonshot";
|
||||
|
||||
private keys: MoonshotKey[] = [];
|
||||
private checker?: MoonshotKeyChecker;
|
||||
private log = logger.child({ module: "key-provider", service: this.service });
|
||||
|
||||
constructor() {
|
||||
const keyConfig = config.moonshotKey?.trim();
|
||||
if (!keyConfig) {
|
||||
return;
|
||||
}
|
||||
|
||||
const keys = keyConfig.split(",").map((k) => k.trim());
|
||||
for (const key of keys) {
|
||||
if (!key) continue;
|
||||
this.keys.push({
|
||||
key,
|
||||
service: this.service,
|
||||
modelFamilies: ["moonshot"],
|
||||
isDisabled: false,
|
||||
isRevoked: false,
|
||||
promptCount: 0,
|
||||
lastUsed: 0,
|
||||
lastChecked: 0,
|
||||
hash: this.hashKey(key),
|
||||
rateLimitedAt: 0,
|
||||
rateLimitedUntil: 0,
|
||||
tokenUsage: {},
|
||||
isOverQuota: false,
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
private hashKey(key: string): string {
|
||||
return require("crypto").createHash("sha256").update(key).digest("hex");
|
||||
}
|
||||
|
||||
public init() {
|
||||
if (this.keys.length === 0) return;
|
||||
if (!config.checkKeys) {
|
||||
this.log.warn(
|
||||
"Key checking is disabled. Keys will not be verified."
|
||||
);
|
||||
return;
|
||||
}
|
||||
this.checker = new MoonshotKeyChecker(this.update.bind(this));
|
||||
for (const key of this.keys) {
|
||||
void this.checker.checkKey(key);
|
||||
}
|
||||
}
|
||||
|
||||
public get(model: string): MoonshotKey {
|
||||
const availableKeys = this.keys.filter((k) => !k.isDisabled);
|
||||
if (availableKeys.length === 0) {
|
||||
throw new Error("No Moonshot keys available");
|
||||
}
|
||||
const key = availableKeys[Math.floor(Math.random() * availableKeys.length)];
|
||||
key.lastUsed = Date.now();
|
||||
this.throttle(key.hash);
|
||||
return { ...key };
|
||||
}
|
||||
|
||||
public list(): Omit<MoonshotKey, "key">[] {
|
||||
return this.keys.map(({ key, ...rest }) => rest);
|
||||
}
|
||||
|
||||
public disable(key: MoonshotKey): void {
|
||||
const found = this.keys.find((k) => k.hash === key.hash);
|
||||
if (found) {
|
||||
found.isDisabled = true;
|
||||
}
|
||||
}
|
||||
|
||||
public update(hash: string, update: Partial<MoonshotKey>): void {
|
||||
const key = this.keys.find((k) => k.hash === hash);
|
||||
if (key) {
|
||||
Object.assign(key, update);
|
||||
}
|
||||
}
|
||||
|
||||
public available(): number {
|
||||
return this.keys.filter((k) => !k.isDisabled).length;
|
||||
}
|
||||
|
||||
public incrementUsage(keyHash: string, modelFamily: MoonshotModelFamily, usage: { input: number; output: number }) {
|
||||
const key = this.keys.find((k) => k.hash === keyHash);
|
||||
if (!key) return;
|
||||
|
||||
key.promptCount++;
|
||||
|
||||
if (!key.tokenUsage) {
|
||||
key.tokenUsage = {};
|
||||
}
|
||||
// Moonshot only has one model family "moonshot"
|
||||
if (!key.tokenUsage[modelFamily]) {
|
||||
key.tokenUsage[modelFamily] = { input: 0, output: 0 };
|
||||
}
|
||||
|
||||
const currentFamilyUsage = key.tokenUsage[modelFamily]!;
|
||||
currentFamilyUsage.input += usage.input;
|
||||
currentFamilyUsage.output += usage.output;
|
||||
}
|
||||
|
||||
/**
|
||||
* Upon being rate limited, a key will be locked out for this many milliseconds
|
||||
* while we wait for other concurrent requests to finish.
|
||||
*/
|
||||
private static readonly RATE_LIMIT_LOCKOUT = 2000;
|
||||
/**
|
||||
* Upon assigning a key, we will wait this many milliseconds before allowing it
|
||||
* to be used again. This is to prevent the queue from flooding a key with too
|
||||
* many requests while we wait to learn whether previous ones succeeded.
|
||||
*/
|
||||
private static readonly KEY_REUSE_DELAY = 500;
|
||||
|
||||
getLockoutPeriod = createGenericGetLockoutPeriod(() => this.keys);
|
||||
|
||||
public markRateLimited(keyHash: string) {
|
||||
this.log.debug({ key: keyHash }, "Key rate limited");
|
||||
const key = this.keys.find((k) => k.hash === keyHash)!;
|
||||
const now = Date.now();
|
||||
key.rateLimitedAt = now;
|
||||
key.rateLimitedUntil = now + MoonshotKeyProvider.RATE_LIMIT_LOCKOUT;
|
||||
}
|
||||
|
||||
public recheck(): void {
|
||||
if (!this.checker || !config.checkKeys) return;
|
||||
for (const key of this.keys) {
|
||||
this.update(key.hash, {
|
||||
isOverQuota: false,
|
||||
isDisabled: false,
|
||||
lastChecked: 0
|
||||
});
|
||||
void this.checker.checkKey(key);
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Applies a short artificial delay to the key upon dequeueing, in order to
|
||||
* prevent it from being immediately assigned to another request before the
|
||||
* current one can be dispatched.
|
||||
**/
|
||||
private throttle(hash: string) {
|
||||
const now = Date.now();
|
||||
const key = this.keys.find((k) => k.hash === hash)!;
|
||||
|
||||
const currentRateLimit = key.rateLimitedUntil;
|
||||
const nextRateLimit = now + MoonshotKeyProvider.KEY_REUSE_DELAY;
|
||||
|
||||
key.rateLimitedAt = now;
|
||||
key.rateLimitedUntil = Math.max(currentRateLimit, nextRateLimit);
|
||||
}
|
||||
}
|
||||
@@ -1,23 +1,24 @@
|
||||
import { AxiosError } from "axios";
|
||||
import { KeyCheckerBase } from "../key-checker-base";
|
||||
import type { OpenAIKey, OpenAIKeyProvider } from "./provider";
|
||||
import type { OpenAIKey, OpenAIKeyProvider, OpenAIKeyUpdate } from "./provider";
|
||||
import { OpenAIModelFamily, getOpenAIModelFamily } from "../../models";
|
||||
import { getAxiosInstance } from "../../network";
|
||||
|
||||
const axios = getAxiosInstance();
|
||||
|
||||
const MIN_CHECK_INTERVAL = 3 * 1000; // 3 seconds
|
||||
const KEY_CHECK_PERIOD = 60 * 60 * 1000; // 1 hour
|
||||
const KEY_CHECK_PERIOD = 5 * 60 * 60 * 1000; // 5 hours
|
||||
const POST_CHAT_COMPLETIONS_URL = "https://api.openai.com/v1/chat/completions";
|
||||
const POST_IMAGE_GENERATIONS_URL = "https://api.openai.com/v1/images/generations";
|
||||
const GET_MODELS_URL = "https://api.openai.com/v1/models";
|
||||
const GET_ORGANIZATIONS_URL = "https://api.openai.com/v1/organizations";
|
||||
const GET_ORGANIZATIONS_URL = "https://api.openai.com/v1/me";
|
||||
|
||||
type GetModelsResponse = {
|
||||
data: [{ id: string }];
|
||||
};
|
||||
|
||||
type GetOrganizationsResponse = {
|
||||
data: [{ id: string; is_default: boolean }];
|
||||
orgs: {data: [{ id: string; is_default: boolean }]};
|
||||
};
|
||||
|
||||
type OpenAIError = {
|
||||
@@ -50,10 +51,40 @@ export class OpenAIKeyChecker extends KeyCheckerBase<OpenAIKey> {
|
||||
this.testLiveness(key),
|
||||
this.maybeCreateOrganizationClones(key),
|
||||
]);
|
||||
const updates = {
|
||||
const updates: OpenAIKeyUpdate = {
|
||||
modelFamilies: provisionedModels,
|
||||
isTrial: livenessTest.rateLimit <= 250,
|
||||
};
|
||||
|
||||
// Test organization verification status for all keys
|
||||
// This is needed for GPT-5, o1, o3, and gpt-image-1 streaming restrictions
|
||||
try {
|
||||
const isVerifiedOrg = await this.testVerifiedOrg(key);
|
||||
// Always set the organizationVerified field for all keys
|
||||
updates.organizationVerified = isVerifiedOrg;
|
||||
|
||||
// Only remove gpt-image from unverified orgs if they have it
|
||||
if (!isVerifiedOrg && provisionedModels.includes("gpt-image")) {
|
||||
const updatedFamilies = provisionedModels.filter(family => family !== "gpt-image");
|
||||
updates.modelFamilies = updatedFamilies;
|
||||
this.log.warn({ key: key.hash }, "Key's organization is not verified. Removing gpt-image-1 from available models.");
|
||||
}
|
||||
|
||||
if (isVerifiedOrg) {
|
||||
this.log.info({ key: key.hash }, "Verified organization status for key. Can use streaming for GPT-5, o1, o3, and gpt-image-1.");
|
||||
} else {
|
||||
this.log.warn({ key: key.hash }, "Key's organization is not verified. Streaming restricted for GPT-5, o1, o3, and gpt-image-1.");
|
||||
}
|
||||
} catch (error) {
|
||||
// If test fails, assume no access to be safe
|
||||
updates.organizationVerified = false;
|
||||
if (provisionedModels.includes("gpt-image")) {
|
||||
const updatedFamilies = provisionedModels.filter(family => family !== "gpt-image");
|
||||
updates.modelFamilies = updatedFamilies;
|
||||
}
|
||||
this.log.error({ key: key.hash, error }, "Error testing organization verification status. Assuming not verified for safety.");
|
||||
}
|
||||
|
||||
this.updateKey(key.hash, updates);
|
||||
} else {
|
||||
// No updates needed as models and trial status generally don't change.
|
||||
@@ -105,7 +136,7 @@ export class OpenAIKeyChecker extends KeyCheckerBase<OpenAIKey> {
|
||||
GET_ORGANIZATIONS_URL,
|
||||
opts
|
||||
);
|
||||
const organizations = data.data;
|
||||
const organizations = data.orgs.data;
|
||||
const defaultOrg = organizations.find(({ is_default }) => is_default);
|
||||
this.updateKey(key.hash, { organizationId: defaultOrg?.id });
|
||||
if (organizations.length <= 1) return;
|
||||
@@ -288,7 +319,7 @@ export class OpenAIKeyChecker extends KeyCheckerBase<OpenAIKey> {
|
||||
payload,
|
||||
{
|
||||
headers: OpenAIKeyChecker.getHeaders(key),
|
||||
validateStatus: (status) => status === 400,
|
||||
validateStatus: (status) => status === 404,
|
||||
}
|
||||
);
|
||||
const rateLimitHeader = headers["x-ratelimit-limit-requests"];
|
||||
@@ -298,7 +329,7 @@ export class OpenAIKeyChecker extends KeyCheckerBase<OpenAIKey> {
|
||||
if (data.error.type !== "invalid_request_error") {
|
||||
this.log.warn(
|
||||
{ key: key.hash, error: data },
|
||||
"Unexpected 400 error class while checking key; assuming key is valid, but this may indicate a change in the API."
|
||||
"Unexpected 404 error class while checking key; assuming key is valid, but this may indicate a change in the API."
|
||||
);
|
||||
}
|
||||
return { rateLimit };
|
||||
@@ -311,6 +342,129 @@ export class OpenAIKeyChecker extends KeyCheckerBase<OpenAIKey> {
|
||||
return data?.error?.type;
|
||||
}
|
||||
|
||||
/**
|
||||
* Tests whether the key's organization is verified by attempting to stream from the gpt-5-mini model.
|
||||
* Only verified organizations can stream from GPT-5 models, so this is a reliable test for both
|
||||
* GPT-5 streaming and gpt-image-1 access (which also requires verified organization status).
|
||||
* Returns true if the organization is verified.
|
||||
*/
|
||||
public async testVerifiedOrg(key: OpenAIKey): Promise<boolean> {
|
||||
this.log.info({ key: key.hash }, "Testing organization verification status via gpt-5-mini streaming");
|
||||
|
||||
try {
|
||||
const payload = {
|
||||
model: "gpt-5",
|
||||
messages: [{ role: "user", content: "Hi" }],
|
||||
max_completion_tokens: 1,
|
||||
stream: true
|
||||
};
|
||||
|
||||
// Make a minimal streaming request to check organization verification
|
||||
const response = await axios.post(
|
||||
POST_CHAT_COMPLETIONS_URL,
|
||||
payload,
|
||||
{
|
||||
headers: OpenAIKeyChecker.getHeaders(key),
|
||||
validateStatus: (status) => true, // Accept any status code to inspect errors
|
||||
timeout: 30000, // 30 second timeout
|
||||
signal: AbortSignal.timeout(30000)
|
||||
}
|
||||
);
|
||||
|
||||
// If we get a 200 response, the organization is verified
|
||||
if (response.status === 200) {
|
||||
this.log.info(
|
||||
{ key: key.hash, status: response.status },
|
||||
`Organization is verified. Streaming gpt-5-mini request succeeded with status code ${response.status}`
|
||||
);
|
||||
return true;
|
||||
}
|
||||
|
||||
// Check for specific error responses that indicate unverified organization
|
||||
const data = response.data as any;
|
||||
const errorMessage = data?.error?.message || '';
|
||||
|
||||
// Explicitly check for organization verification errors
|
||||
if (errorMessage.includes("organization must be verified")) {
|
||||
this.log.warn(
|
||||
{ key: key.hash, status: response.status, error: errorMessage },
|
||||
"Organization is not verified: verification required for streaming gpt-5-mini"
|
||||
);
|
||||
return false;
|
||||
}
|
||||
|
||||
// If we get a 400 error but it's not about verification, the organization might be verified
|
||||
// but there's another issue with the request
|
||||
if (response.status === 400 && !errorMessage.includes("organization must be verified")) {
|
||||
// Check if the error is specifically about the 'stream' parameter
|
||||
if (errorMessage.includes("stream") && errorMessage.includes("unsupported_value")) {
|
||||
this.log.warn(
|
||||
{ key: key.hash, status: response.status, error: errorMessage },
|
||||
"Organization is not verified: cannot stream with gpt-5-mini"
|
||||
);
|
||||
return false;
|
||||
}
|
||||
|
||||
// If it's some other validation error, the organization might be verified
|
||||
this.log.info(
|
||||
{ key: key.hash, status: response.status, error: errorMessage },
|
||||
"Got 400 error but not related to organization verification. Assuming organization is verified."
|
||||
);
|
||||
return true;
|
||||
}
|
||||
|
||||
// For other status codes, log the issue but assume unverified
|
||||
this.log.warn(
|
||||
{ key: key.hash, status: response.status, error: errorMessage },
|
||||
"Unexpected response when testing organization verification, assuming not verified"
|
||||
);
|
||||
return false;
|
||||
|
||||
} catch (error) {
|
||||
// Handle network errors or request failures
|
||||
if (error instanceof AxiosError && error.response) {
|
||||
const status = error.response.status;
|
||||
const data = error.response.data as any;
|
||||
const errorMessage = data?.error?.message || 'Unknown error';
|
||||
|
||||
// Check for specific error messages related to organization verification
|
||||
if (errorMessage.includes("organization must be verified")) {
|
||||
this.log.warn(
|
||||
{ key: key.hash, status, error: errorMessage },
|
||||
"Organization is not verified based on error message"
|
||||
);
|
||||
return false;
|
||||
}
|
||||
|
||||
// If we get a 400 error but it's not about verification, the organization might be verified
|
||||
if (status === 400 && !errorMessage.includes("organization must be verified")) {
|
||||
// Check if the error is specifically about the 'stream' parameter
|
||||
if (errorMessage.includes("stream") && errorMessage.includes("unsupported_value")) {
|
||||
this.log.warn(
|
||||
{ key: key.hash, status, error: errorMessage },
|
||||
"Organization is not verified: cannot stream with gpt-5-mini"
|
||||
);
|
||||
return false;
|
||||
}
|
||||
|
||||
// If it's some other validation error, the organization might be verified
|
||||
this.log.info(
|
||||
{ key: key.hash, status, error: errorMessage },
|
||||
"Got 400 error but not related to organization verification. Assuming organization is verified."
|
||||
);
|
||||
return true;
|
||||
}
|
||||
}
|
||||
|
||||
// For all other errors, assume unverified for safety
|
||||
this.log.error(
|
||||
{ key: key.hash, error: error instanceof Error ? error.message : String(error) },
|
||||
"Error testing organization verification status. Assuming not verified for safety."
|
||||
);
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
static getHeaders(key: OpenAIKey) {
|
||||
const useOrg = !key.key.includes("svcacct");
|
||||
return {
|
||||
|
||||
@@ -3,16 +3,13 @@ import http from "http";
|
||||
import { Key, KeyProvider } from "../index";
|
||||
import { config } from "../../../config";
|
||||
import { logger } from "../../../logger";
|
||||
import { getOpenAIModelFamily, OpenAIModelFamily } from "../../models";
|
||||
import { getOpenAIModelFamily, OpenAIModelFamily, ModelFamily } from "../../models"; // Added ModelFamily
|
||||
import { PaymentRequiredError } from "../../errors";
|
||||
import { OpenAIKeyChecker } from "./checker";
|
||||
import { prioritizeKeys } from "../prioritize-keys";
|
||||
|
||||
type OpenAIKeyUsage = {
|
||||
[K in OpenAIModelFamily as `${K}Tokens`]: number;
|
||||
};
|
||||
|
||||
export interface OpenAIKey extends Key, OpenAIKeyUsage {
|
||||
// OpenAIKeyUsage is removed, tokenUsage from base Key interface will be used.
|
||||
export interface OpenAIKey extends Key {
|
||||
readonly service: "openai";
|
||||
modelFamilies: OpenAIModelFamily[];
|
||||
/**
|
||||
@@ -23,6 +20,8 @@ export interface OpenAIKey extends Key, OpenAIKeyUsage {
|
||||
organizationId?: string;
|
||||
/** Whether this is a free trial key. These are prioritized over paid keys if they can fulfill the request. */
|
||||
isTrial: boolean;
|
||||
/** Whether the organization associated with this key is verified. Verified organizations can use streaming for GPT-5 models and gpt-image-1. */
|
||||
organizationVerified?: boolean;
|
||||
/** Set when key check returns a non-transient 429. */
|
||||
isOverQuota: boolean;
|
||||
/**
|
||||
@@ -90,6 +89,14 @@ export class OpenAIKeyProvider implements KeyProvider<OpenAIKey> {
|
||||
"gpt4" as const,
|
||||
"gpt4-turbo" as const,
|
||||
"gpt4o" as const,
|
||||
"gpt45" as const,
|
||||
"gpt41" as const,
|
||||
"gpt41-mini" as const,
|
||||
"gpt41-nano" as const,
|
||||
"gpt5" as const,
|
||||
"gpt5-mini" as const,
|
||||
"gpt5-nano" as const,
|
||||
"gpt5-chat-latest" as const,
|
||||
],
|
||||
isTrial: false,
|
||||
isDisabled: false,
|
||||
@@ -107,14 +114,7 @@ export class OpenAIKeyProvider implements KeyProvider<OpenAIKey> {
|
||||
rateLimitedUntil: 0,
|
||||
rateLimitRequestsReset: 0,
|
||||
rateLimitTokensReset: 0,
|
||||
turboTokens: 0,
|
||||
gpt4Tokens: 0,
|
||||
"gpt4-32kTokens": 0,
|
||||
"gpt4-turboTokens": 0,
|
||||
gpt4oTokens: 0,
|
||||
"o1Tokens": 0,
|
||||
"o1-miniTokens": 0,
|
||||
"dall-eTokens": 0,
|
||||
tokenUsage: {}, // Initialize new tokenUsage field
|
||||
modelIds: [],
|
||||
};
|
||||
this.keys.push(newKey);
|
||||
@@ -139,22 +139,97 @@ export class OpenAIKeyProvider implements KeyProvider<OpenAIKey> {
|
||||
return this.keys.map((key) => Object.freeze({ ...key, key: undefined }));
|
||||
}
|
||||
|
||||
public get(requestModel: string) {
|
||||
public get(requestModel: string, streaming?: boolean) {
|
||||
let model = requestModel;
|
||||
|
||||
const neededFamily = getOpenAIModelFamily(model);
|
||||
const excludeTrials = model === "text-embedding-ada-002";
|
||||
const isGptImageRequest = neededFamily === "gpt-image";
|
||||
|
||||
// GPT-5 models (gpt-5, gpt-5-mini, gpt-5-nano) require verified keys for streaming
|
||||
const isGpt5Model = /^gpt-5(-mini|-nano)?(-\d{4}-\d{2}-\d{2})?$/.test(model);
|
||||
const isO1Model = /^o1(-mini|-preview)?(-\d{4}-\d{2}-\d{2})?$/.test(model);
|
||||
const isO3Model = /^o3(-mini)?(-\d{4}-\d{2}-\d{2})?$/.test(model);
|
||||
const isO4MiniModel = /^o4-mini(-\d{4}-\d{2}-\d{2})?$/.test(model);
|
||||
const requiresVerifiedStreaming = (isGpt5Model || isO1Model || isO3Model || isO4MiniModel) && streaming;
|
||||
|
||||
const availableKeys = this.keys.filter(
|
||||
// Allow keys which
|
||||
(key) =>
|
||||
!key.isDisabled && // are not disabled
|
||||
key.modelFamilies.includes(neededFamily) && // have access to the model family we need
|
||||
(!excludeTrials || !key.isTrial) && // and are not trials if we don't want them
|
||||
(!config.checkKeys || key.modelIds.includes(model)) // and have the specific snapshot we need
|
||||
// First, filter keys based on basic criteria
|
||||
let availableKeys = this.keys.filter(
|
||||
(key) =>
|
||||
!key.isDisabled && // not disabled
|
||||
key.modelFamilies.includes(neededFamily) && // has access to the model family we need
|
||||
(!excludeTrials || !key.isTrial) && // not a trial if we don't want trials
|
||||
(!config.checkKeys || key.modelIds.includes(model)) // has the specific snapshot if needed
|
||||
);
|
||||
|
||||
// For gpt-image requests, we need an additional verification step
|
||||
// Only keys from verified organizations can use gpt-image-1
|
||||
if (isGptImageRequest) {
|
||||
this.log.debug(
|
||||
{ model, keyCount: availableKeys.length },
|
||||
"Filtering keys for gpt-image request to ensure verified organization status"
|
||||
);
|
||||
|
||||
// Log the keys that claim to have gpt-image access for debugging
|
||||
availableKeys.forEach(key => {
|
||||
this.log.debug(
|
||||
{ keyHash: key.hash, modelFamilies: key.modelFamilies, orgId: key.organizationId },
|
||||
"Key with gpt-image access"
|
||||
);
|
||||
});
|
||||
|
||||
// Filter to only include keys from verified organizations
|
||||
// Use the organizationVerified field which is set by the key checker
|
||||
const verifiedKeys = availableKeys.filter(key => key.organizationVerified === true);
|
||||
|
||||
if (verifiedKeys.length > 0) {
|
||||
this.log.info(
|
||||
{ model, totalKeys: availableKeys.length, verifiedKeys: verifiedKeys.length },
|
||||
"Using only verified organization keys for gpt-image request"
|
||||
);
|
||||
availableKeys = verifiedKeys;
|
||||
} else {
|
||||
this.log.warn(
|
||||
{ model, totalKeys: availableKeys.length },
|
||||
"No verified organization keys available for gpt-image request"
|
||||
);
|
||||
}
|
||||
}
|
||||
|
||||
// For streaming requests with models that require verified organizations
|
||||
// GPT-5, o1, o3, and o4-mini models require verified organizations for streaming
|
||||
if (requiresVerifiedStreaming) {
|
||||
this.log.debug(
|
||||
{ model, keyCount: availableKeys.length, streaming },
|
||||
"Filtering keys for streaming request to ensure verified organization status"
|
||||
);
|
||||
|
||||
// Filter to only include keys from verified organizations
|
||||
// Use the organizationVerified field which is set by the key checker
|
||||
const verifiedKeys = availableKeys.filter(key => key.organizationVerified === true);
|
||||
|
||||
if (verifiedKeys.length > 0) {
|
||||
this.log.info(
|
||||
{ model, totalKeys: availableKeys.length, verifiedKeys: verifiedKeys.length, streaming },
|
||||
"Using only verified organization keys for streaming request"
|
||||
);
|
||||
availableKeys = verifiedKeys;
|
||||
} else {
|
||||
this.log.warn(
|
||||
{ model, totalKeys: availableKeys.length, streaming },
|
||||
"No verified organization keys available for streaming request"
|
||||
);
|
||||
// Set availableKeys to empty array to trigger the error below
|
||||
availableKeys = [];
|
||||
}
|
||||
}
|
||||
|
||||
if (availableKeys.length === 0) {
|
||||
if (requiresVerifiedStreaming) {
|
||||
throw new PaymentRequiredError(
|
||||
"No verified OpenAI keys available for streaming GPT-5, o1, o3, or o4-mini models. Only verified organizations can stream these models. Please disable streaming or contact support to verify your organization."
|
||||
);
|
||||
}
|
||||
throw new PaymentRequiredError(
|
||||
`No OpenAI keys available for model ${model}`
|
||||
);
|
||||
@@ -200,7 +275,18 @@ export class OpenAIKeyProvider implements KeyProvider<OpenAIKey> {
|
||||
);
|
||||
return clone;
|
||||
});
|
||||
|
||||
// Add the clones to the key pool
|
||||
this.keys.push(...clones);
|
||||
|
||||
// Log the total number of keys after cloning
|
||||
this.log.info(
|
||||
{ totalKeys: this.keys.length, newClones: clones.length },
|
||||
"Added cloned keys to the key pool"
|
||||
);
|
||||
|
||||
// Return the clones so they can be checked immediately if needed
|
||||
return clones;
|
||||
}
|
||||
|
||||
/** Disables a key, or does nothing if the key isn't in this pool. */
|
||||
@@ -279,11 +365,22 @@ export class OpenAIKeyProvider implements KeyProvider<OpenAIKey> {
|
||||
key.rateLimitedUntil = now + key.rateLimitRequestsReset;
|
||||
}
|
||||
|
||||
public incrementUsage(keyHash: string, model: string, tokens: number) {
|
||||
public incrementUsage(keyHash: string, modelFamily: OpenAIModelFamily, usage: { input: number; output: number }) {
|
||||
const key = this.keys.find((k) => k.hash === keyHash);
|
||||
if (!key) return;
|
||||
|
||||
key.promptCount++;
|
||||
key[`${getOpenAIModelFamily(model)}Tokens`] += tokens;
|
||||
|
||||
if (!key.tokenUsage) {
|
||||
key.tokenUsage = {};
|
||||
}
|
||||
if (!key.tokenUsage[modelFamily]) {
|
||||
key.tokenUsage[modelFamily] = { input: 0, output: 0 };
|
||||
}
|
||||
|
||||
const currentFamilyUsage = key.tokenUsage[modelFamily]!;
|
||||
currentFamilyUsage.input += usage.input;
|
||||
currentFamilyUsage.output += usage.output;
|
||||
}
|
||||
|
||||
public updateRateLimits(keyHash: string, headers: http.IncomingHttpHeaders) {
|
||||
@@ -323,6 +420,90 @@ export class OpenAIKeyProvider implements KeyProvider<OpenAIKey> {
|
||||
});
|
||||
this.checker?.scheduleNextCheck();
|
||||
}
|
||||
|
||||
/**
|
||||
* Explicitly tests all keys for organization verification status and returns detailed results.
|
||||
* This checks if the organization is verified, which is required for both gpt-image-1 access
|
||||
* and o3 streaming capabilities.
|
||||
*/
|
||||
public async validateGptImageAccess(): Promise<{
|
||||
total: number;
|
||||
validated: number;
|
||||
removed: string[];
|
||||
verified: string[];
|
||||
errors: {key: string, error: string}[];
|
||||
}> {
|
||||
if (!this.checker) {
|
||||
throw new Error("Key checker not initialized");
|
||||
}
|
||||
|
||||
const results = {
|
||||
total: this.keys.length,
|
||||
validated: 0,
|
||||
removed: [] as string[],
|
||||
verified: [] as string[],
|
||||
errors: [] as {key: string, error: string}[]
|
||||
};
|
||||
|
||||
this.log.info({ keyCount: this.keys.length }, "Starting organization verification check for all OpenAI keys");
|
||||
|
||||
// Process keys sequentially to avoid hitting rate limits
|
||||
for (const key of this.keys) {
|
||||
try {
|
||||
// Skip keys that are already disabled
|
||||
if (key.isDisabled || key.isRevoked) {
|
||||
this.log.debug({ key: key.hash }, "Skipping disabled/revoked key");
|
||||
continue;
|
||||
}
|
||||
|
||||
// Check if the key claims to have gpt-image-1 or o3 access
|
||||
const hasGptImageFamily = key.modelFamilies.includes("gpt-image");
|
||||
const hasO3Family = key.modelFamilies.includes("o3");
|
||||
|
||||
if (hasGptImageFamily || hasO3Family) {
|
||||
// Test the key's organization verification status using o3 streaming
|
||||
const isVerifiedOrg = await this.checker.testVerifiedOrg(key);
|
||||
results.validated++;
|
||||
|
||||
if (!isVerifiedOrg) {
|
||||
// Only remove gpt-image from unverified orgs - they can still use o3, just not stream it
|
||||
const updatedFamilies = key.modelFamilies.filter(family => family !== "gpt-image");
|
||||
this.update(key.hash, { modelFamilies: updatedFamilies });
|
||||
results.removed.push(key.hash);
|
||||
this.log.warn({ key: key.hash }, "Key's organization is not verified. Removing gpt-image-1 from available models.");
|
||||
} else {
|
||||
results.verified.push(key.hash);
|
||||
this.log.info({ key: key.hash }, "Verified organization status for key. Can use gpt-image-1 and o3 streaming.");
|
||||
}
|
||||
} else {
|
||||
this.log.debug({ key: key.hash }, "Key does not claim gpt-image-1 or o3 access. Skipping verification.");
|
||||
}
|
||||
} catch (error) {
|
||||
results.errors.push({ key: key.hash, error: error.message });
|
||||
this.log.error({ key: key.hash, error }, "Error validating organization verification status");
|
||||
|
||||
// If a key errors during validation, only remove gpt-image access to be safe
|
||||
if (key.modelFamilies.includes("gpt-image")) {
|
||||
const updatedFamilies = key.modelFamilies.filter(family => family !== "gpt-image");
|
||||
this.update(key.hash, { modelFamilies: updatedFamilies });
|
||||
results.removed.push(key.hash);
|
||||
}
|
||||
}
|
||||
|
||||
// Delay between checks to avoid hitting rate limits
|
||||
await new Promise(resolve => setTimeout(resolve, 500));
|
||||
}
|
||||
|
||||
this.log.info({
|
||||
total: results.total,
|
||||
validated: results.validated,
|
||||
verified: results.verified.length,
|
||||
removed: results.removed.length,
|
||||
errors: results.errors.length
|
||||
}, "Completed organization verification check");
|
||||
|
||||
return results;
|
||||
}
|
||||
|
||||
/**
|
||||
* Called when a key is selected for a request, briefly disabling it to
|
||||
|
||||
@@ -0,0 +1,144 @@
|
||||
import { Key } from "..";
|
||||
import { QwenModelFamily } from "../../models";
|
||||
|
||||
// Define the QwenKey interface here to avoid circular dependency
|
||||
export interface QwenKey extends Key {
|
||||
readonly service: "qwen";
|
||||
readonly modelFamilies: QwenModelFamily[];
|
||||
isOverQuota: boolean;
|
||||
// "qwenTokens" is removed, tokenUsage from base Key interface will be used.
|
||||
}
|
||||
import { logger } from "../../../logger";
|
||||
import { assertNever } from "../../utils";
|
||||
|
||||
const CHECK_TIMEOUT = 10000;
|
||||
const API_URL = "https://dashscope-intl.aliyuncs.com/compatible-mode/v1/chat/completions";
|
||||
|
||||
export class QwenKeyChecker {
|
||||
private log = logger.child({ module: "key-checker", service: "qwen" });
|
||||
|
||||
constructor(private readonly update: (hash: string, key: Partial<QwenKey>) => void) {
|
||||
this.log.info("QwenKeyChecker initialized");
|
||||
}
|
||||
|
||||
public async checkKey(key: QwenKey): Promise<void> {
|
||||
this.log.info({ hash: key.hash }, "Starting key validation check");
|
||||
try {
|
||||
const result = await this.validateKey(key);
|
||||
this.handleCheckResult(key, result);
|
||||
} catch (error) {
|
||||
if (error instanceof Error) {
|
||||
this.log.warn(
|
||||
{ error: error.message, stack: error.stack, hash: key.hash },
|
||||
"Failed to check key status"
|
||||
);
|
||||
} else {
|
||||
this.log.warn(
|
||||
{ error, hash: key.hash },
|
||||
"Failed to check key status with unknown error"
|
||||
);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
private async validateKey(key: QwenKey): Promise<"valid" | "invalid" | "quota"> {
|
||||
const controller = new AbortController();
|
||||
const timeout = setTimeout(() => {
|
||||
controller.abort();
|
||||
this.log.warn({ hash: key.hash }, "Key validation timed out after " + CHECK_TIMEOUT + "ms");
|
||||
}, CHECK_TIMEOUT);
|
||||
|
||||
try {
|
||||
// Simple test request to check if the key is valid
|
||||
const headers = {
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": `Bearer ${key.key}`
|
||||
};
|
||||
|
||||
const body = {
|
||||
model: "qwen-turbo",
|
||||
max_tokens: 5,
|
||||
temperature: 0.2,
|
||||
messages: [
|
||||
{
|
||||
role: "user",
|
||||
content: "Hello"
|
||||
}
|
||||
]
|
||||
};
|
||||
|
||||
const response = await fetch(API_URL, {
|
||||
method: "POST",
|
||||
headers,
|
||||
body: JSON.stringify(body),
|
||||
signal: controller.signal,
|
||||
});
|
||||
|
||||
// Check response status
|
||||
if (response.status === 200) {
|
||||
return "valid";
|
||||
} else if (response.status === 401) {
|
||||
// Invalid API key
|
||||
return "invalid";
|
||||
} else if (response.status === 429) {
|
||||
// Rate limit or quota exceeded
|
||||
const responseBody = await response.json();
|
||||
const errorMsg = responseBody?.error?.message || "";
|
||||
|
||||
// Check if it's a quota issue or just rate limiting
|
||||
if (errorMsg.includes("quota") || errorMsg.includes("billing")) {
|
||||
return "quota";
|
||||
}
|
||||
|
||||
// Otherwise it's just rate limited, still valid
|
||||
return "valid";
|
||||
} else {
|
||||
this.log.warn(
|
||||
{ status: response.status, hash: key.hash },
|
||||
"Unexpected status code while testing key validity"
|
||||
);
|
||||
return "invalid";
|
||||
}
|
||||
} catch (error) {
|
||||
if (error instanceof Error && error.name === 'AbortError') {
|
||||
this.log.warn({ hash: key.hash }, "Key validation aborted");
|
||||
}
|
||||
throw error;
|
||||
} finally {
|
||||
clearTimeout(timeout);
|
||||
}
|
||||
}
|
||||
|
||||
private handleCheckResult(
|
||||
key: QwenKey,
|
||||
result: "valid" | "invalid" | "quota"
|
||||
): void {
|
||||
switch (result) {
|
||||
case "valid":
|
||||
this.log.info({ hash: key.hash }, "Key is valid and enabled");
|
||||
this.update(key.hash, {
|
||||
isDisabled: false,
|
||||
lastChecked: Date.now(),
|
||||
});
|
||||
break;
|
||||
case "invalid":
|
||||
this.log.warn({ hash: key.hash }, "Key is invalid, marking as revoked");
|
||||
this.update(key.hash, {
|
||||
isDisabled: true,
|
||||
isRevoked: true,
|
||||
lastChecked: Date.now(),
|
||||
});
|
||||
break;
|
||||
case "quota":
|
||||
this.log.warn({ hash: key.hash }, "Key has exceeded its quota, disabling");
|
||||
this.update(key.hash, {
|
||||
isDisabled: true,
|
||||
isOverQuota: true,
|
||||
lastChecked: Date.now(),
|
||||
});
|
||||
break;
|
||||
default:
|
||||
assertNever(result);
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,9 @@
|
||||
import { QwenKeyProvider } from "./provider";
|
||||
|
||||
// Export only the provider and the checker, not the QwenKey interface directly
|
||||
export { QwenKeyProvider } from "./provider";
|
||||
export { QwenKeyChecker } from "./checker";
|
||||
// Re-export the QwenKey interface from provider to maintain compatibility
|
||||
export type { QwenKey } from "./provider";
|
||||
|
||||
export const qwenKeyProvider = new QwenKeyProvider();
|
||||
@@ -0,0 +1,165 @@
|
||||
import { KeyProvider, createGenericGetLockoutPeriod } from "..";
|
||||
import { QwenKeyChecker, QwenKey } from "./checker";
|
||||
import { config } from "../../../config";
|
||||
import { logger } from "../../../logger";
|
||||
import { QwenModelFamily, ModelFamily } from "../../models"; // Added ModelFamily
|
||||
|
||||
// Re-export the QwenKey interface
|
||||
export type { QwenKey } from "./checker";
|
||||
|
||||
export class QwenKeyProvider implements KeyProvider<QwenKey> {
|
||||
readonly service = "qwen";
|
||||
|
||||
private keys: QwenKey[] = [];
|
||||
private checker?: QwenKeyChecker;
|
||||
private log = logger.child({ module: "key-provider", service: this.service });
|
||||
|
||||
constructor() {
|
||||
// Access the qwenKey property from config using indexing to avoid TypeScript error
|
||||
// since the property was added dynamically
|
||||
const keyConfig = (config as any)["qwenKey"]?.trim();
|
||||
if (!keyConfig) {
|
||||
return;
|
||||
}
|
||||
|
||||
const keys = keyConfig.split(",").map((k: string) => k.trim());
|
||||
for (const key of keys) {
|
||||
if (!key) continue;
|
||||
this.keys.push({
|
||||
key,
|
||||
service: this.service,
|
||||
modelFamilies: ["qwen"],
|
||||
isDisabled: false,
|
||||
isRevoked: false,
|
||||
promptCount: 0,
|
||||
lastUsed: 0,
|
||||
lastChecked: 0,
|
||||
hash: this.hashKey(key),
|
||||
rateLimitedAt: 0,
|
||||
rateLimitedUntil: 0,
|
||||
tokenUsage: {}, // Initialize new tokenUsage field
|
||||
isOverQuota: false,
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
private hashKey(key: string): string {
|
||||
return require("crypto").createHash("sha256").update(key).digest("hex");
|
||||
}
|
||||
|
||||
public init() {
|
||||
if (this.keys.length === 0) return;
|
||||
if (!config.checkKeys) {
|
||||
this.log.warn(
|
||||
"Key checking is disabled. Keys will not be verified."
|
||||
);
|
||||
return;
|
||||
}
|
||||
this.checker = new QwenKeyChecker(this.update.bind(this));
|
||||
for (const key of this.keys) {
|
||||
void this.checker.checkKey(key);
|
||||
}
|
||||
}
|
||||
|
||||
public get(model: string): QwenKey {
|
||||
const availableKeys = this.keys.filter((k) => !k.isDisabled);
|
||||
if (availableKeys.length === 0) {
|
||||
throw new Error("No Qwen keys available");
|
||||
}
|
||||
const key = availableKeys[Math.floor(Math.random() * availableKeys.length)];
|
||||
key.lastUsed = Date.now();
|
||||
this.throttle(key.hash);
|
||||
return { ...key };
|
||||
}
|
||||
|
||||
public list(): Omit<QwenKey, "key">[] {
|
||||
return this.keys.map(({ key, ...rest }) => rest);
|
||||
}
|
||||
|
||||
public disable(key: QwenKey): void {
|
||||
const found = this.keys.find((k) => k.hash === key.hash);
|
||||
if (found) {
|
||||
found.isDisabled = true;
|
||||
}
|
||||
}
|
||||
|
||||
public update(hash: string, update: Partial<QwenKey>): void {
|
||||
const key = this.keys.find((k) => k.hash === hash);
|
||||
if (key) {
|
||||
Object.assign(key, update);
|
||||
}
|
||||
}
|
||||
|
||||
public available(): number {
|
||||
return this.keys.filter((k) => !k.isDisabled).length;
|
||||
}
|
||||
|
||||
public incrementUsage(keyHash: string, modelFamily: QwenModelFamily, usage: { input: number; output: number }) {
|
||||
const key = this.keys.find((k) => k.hash === keyHash);
|
||||
if (!key) return;
|
||||
|
||||
key.promptCount++;
|
||||
|
||||
if (!key.tokenUsage) {
|
||||
key.tokenUsage = {};
|
||||
}
|
||||
// Qwen only has one model family "qwen"
|
||||
if (!key.tokenUsage[modelFamily]) {
|
||||
key.tokenUsage[modelFamily] = { input: 0, output: 0 };
|
||||
}
|
||||
|
||||
const currentFamilyUsage = key.tokenUsage[modelFamily]!;
|
||||
currentFamilyUsage.input += usage.input;
|
||||
currentFamilyUsage.output += usage.output;
|
||||
}
|
||||
|
||||
/**
|
||||
* Upon being rate limited, a key will be locked out for this many milliseconds
|
||||
* while we wait for other concurrent requests to finish.
|
||||
*/
|
||||
private static readonly RATE_LIMIT_LOCKOUT = 2000;
|
||||
/**
|
||||
* Upon assigning a key, we will wait this many milliseconds before allowing it
|
||||
* to be used again. This is to prevent the queue from flooding a key with too
|
||||
* many requests while we wait to learn whether previous ones succeeded.
|
||||
*/
|
||||
private static readonly KEY_REUSE_DELAY = 500;
|
||||
|
||||
getLockoutPeriod = createGenericGetLockoutPeriod(() => this.keys);
|
||||
|
||||
public markRateLimited(keyHash: string) {
|
||||
this.log.debug({ key: keyHash }, "Key rate limited");
|
||||
const key = this.keys.find((k) => k.hash === keyHash)!;
|
||||
const now = Date.now();
|
||||
key.rateLimitedAt = now;
|
||||
key.rateLimitedUntil = now + QwenKeyProvider.RATE_LIMIT_LOCKOUT;
|
||||
}
|
||||
|
||||
public recheck(): void {
|
||||
if (!this.checker || !config.checkKeys) return;
|
||||
for (const key of this.keys) {
|
||||
this.update(key.hash, {
|
||||
isOverQuota: false,
|
||||
isDisabled: false,
|
||||
lastChecked: 0
|
||||
});
|
||||
void this.checker.checkKey(key);
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Applies a short artificial delay to the key upon dequeueing, in order to
|
||||
* prevent it from being immediately assigned to another request before the
|
||||
* current one can be dispatched.
|
||||
**/
|
||||
private throttle(hash: string) {
|
||||
const now = Date.now();
|
||||
const key = this.keys.find((k) => k.hash === hash)!;
|
||||
|
||||
const currentRateLimit = key.rateLimitedUntil;
|
||||
const nextRateLimit = now + QwenKeyProvider.KEY_REUSE_DELAY;
|
||||
|
||||
key.rateLimitedAt = now;
|
||||
key.rateLimitedUntil = Math.max(currentRateLimit, nextRateLimit);
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,138 @@
|
||||
import { XaiKey } from "./provider";
|
||||
import { logger } from "../../../logger";
|
||||
import { assertNever } from "../../utils";
|
||||
|
||||
const CHECK_TIMEOUT = 10000;
|
||||
|
||||
export class XaiKeyChecker {
|
||||
private log = logger.child({ module: "key-checker", service: "xai" });
|
||||
|
||||
constructor(private readonly update: (hash: string, key: Partial<XaiKey>) => void) {
|
||||
this.log.info("XaiKeyChecker initialized");
|
||||
}
|
||||
|
||||
public async checkKey(key: XaiKey): Promise<void> {
|
||||
this.log.info({ hash: key.hash }, "Starting key validation check");
|
||||
try {
|
||||
const result = await this.validateKey(key);
|
||||
this.handleCheckResult(key, result);
|
||||
} catch (error) {
|
||||
if (error instanceof Error) {
|
||||
this.log.warn(
|
||||
{ error: error.message, stack: error.stack, hash: key.hash },
|
||||
"Failed to check key status"
|
||||
);
|
||||
} else {
|
||||
this.log.warn(
|
||||
{ error, hash: key.hash },
|
||||
"Failed to check key status with unknown error"
|
||||
);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
private async validateKey(key: XaiKey): Promise<"valid" | "invalid" | "quota"> {
|
||||
const controller = new AbortController();
|
||||
const timeout = setTimeout(() => {
|
||||
controller.abort();
|
||||
this.log.warn({ hash: key.hash }, "Key validation timed out after " + CHECK_TIMEOUT + "ms");
|
||||
}, CHECK_TIMEOUT);
|
||||
|
||||
try {
|
||||
// First check API key endpoint to verify key validity
|
||||
const apiResponse = await fetch("https://api.x.ai/v1/api-key", {
|
||||
method: "GET",
|
||||
headers: {
|
||||
Authorization: `Bearer ${key.key}`,
|
||||
},
|
||||
signal: controller.signal,
|
||||
});
|
||||
|
||||
if (apiResponse.status !== 200) {
|
||||
// Key is invalid or has some other issue
|
||||
return "invalid";
|
||||
}
|
||||
|
||||
const apiData = await apiResponse.json();
|
||||
const isBlocked = apiData.team_blocked || apiData.api_key_blocked || apiData.api_key_disabled;
|
||||
|
||||
if (isBlocked) {
|
||||
return "invalid";
|
||||
}
|
||||
|
||||
// If the key passed the first check, test a minimal API call to verify quota
|
||||
const testResponse = await fetch("https://api.x.ai/v1/chat/completions", {
|
||||
method: "POST",
|
||||
headers: {
|
||||
"Content-Type": "application/json",
|
||||
Authorization: `Bearer ${key.key}`,
|
||||
},
|
||||
body: JSON.stringify({
|
||||
messages: [],
|
||||
model: "grok-3-mini-latest",
|
||||
frequency_penalty: -3.0,
|
||||
}),
|
||||
signal: controller.signal,
|
||||
});
|
||||
|
||||
// If we get 400 or 200, the key is valid (400 might be parameter error but key is valid)
|
||||
if (testResponse.status === 400 || testResponse.status === 200) {
|
||||
return "valid";
|
||||
} else if (testResponse.status === 429) {
|
||||
return "quota";
|
||||
} else if (testResponse.status === 403) {
|
||||
this.log.warn(
|
||||
{ status: testResponse.status, hash: key.hash },
|
||||
"Forbidden (403) response, key is invalid"
|
||||
);
|
||||
return "invalid";
|
||||
} else {
|
||||
this.log.warn(
|
||||
{ status: testResponse.status, hash: key.hash },
|
||||
"Unexpected status code while testing key usage"
|
||||
);
|
||||
return "invalid";
|
||||
}
|
||||
} catch (error) {
|
||||
if (error instanceof Error && error.name === 'AbortError') {
|
||||
this.log.warn({ hash: key.hash }, "Key validation aborted");
|
||||
}
|
||||
throw error;
|
||||
} finally {
|
||||
clearTimeout(timeout);
|
||||
}
|
||||
}
|
||||
|
||||
private handleCheckResult(
|
||||
key: XaiKey,
|
||||
result: "valid" | "invalid" | "quota"
|
||||
): void {
|
||||
switch (result) {
|
||||
case "valid":
|
||||
this.log.info({ hash: key.hash }, "Key is valid and enabled");
|
||||
this.update(key.hash, {
|
||||
isDisabled: false,
|
||||
lastChecked: Date.now(),
|
||||
});
|
||||
break;
|
||||
case "invalid":
|
||||
this.log.warn({ hash: key.hash }, "Key is invalid, marking as revoked");
|
||||
this.update(key.hash, {
|
||||
isDisabled: true,
|
||||
isRevoked: true,
|
||||
lastChecked: Date.now(),
|
||||
});
|
||||
break;
|
||||
case "quota":
|
||||
this.log.warn({ hash: key.hash }, "Key has exceeded its quota, disabling");
|
||||
this.update(key.hash, {
|
||||
isDisabled: true,
|
||||
isOverQuota: true,
|
||||
lastChecked: Date.now(),
|
||||
});
|
||||
break;
|
||||
default:
|
||||
assertNever(result);
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,167 @@
|
||||
import { Key, KeyProvider, createGenericGetLockoutPeriod } from "..";
|
||||
import { XaiKeyChecker } from "./checker";
|
||||
import { config } from "../../../config";
|
||||
import { logger } from "../../../logger";
|
||||
import { XaiModelFamily, ModelFamily } from "../../models"; // Added ModelFamily
|
||||
|
||||
// XaiKeyUsage is removed, tokenUsage from base Key interface will be used.
|
||||
export interface XaiKey extends Key {
|
||||
readonly service: "xai";
|
||||
readonly modelFamilies: XaiModelFamily[];
|
||||
isOverQuota: boolean;
|
||||
}
|
||||
|
||||
export class XaiKeyProvider implements KeyProvider<XaiKey> {
|
||||
readonly service = "xai";
|
||||
|
||||
private keys: XaiKey[] = [];
|
||||
private checker?: XaiKeyChecker;
|
||||
private log = logger.child({ module: "key-provider", service: this.service });
|
||||
|
||||
constructor() {
|
||||
const keyConfig = config.xaiKey?.trim();
|
||||
if (!keyConfig) {
|
||||
return;
|
||||
}
|
||||
|
||||
const keys = keyConfig.split(",").map((k) => k.trim());
|
||||
for (const key of keys) {
|
||||
if (!key) continue;
|
||||
this.keys.push({
|
||||
key,
|
||||
service: this.service,
|
||||
modelFamilies: ["xai"],
|
||||
isDisabled: false,
|
||||
isRevoked: false,
|
||||
promptCount: 0,
|
||||
lastUsed: 0,
|
||||
lastChecked: 0,
|
||||
hash: this.hashKey(key),
|
||||
rateLimitedAt: 0,
|
||||
rateLimitedUntil: 0,
|
||||
tokenUsage: {}, // Initialize new tokenUsage field
|
||||
isOverQuota: false,
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
private hashKey(key: string): string {
|
||||
return require("crypto").createHash("sha256").update(key).digest("hex");
|
||||
}
|
||||
|
||||
public init() {
|
||||
if (this.keys.length === 0) return;
|
||||
if (!config.checkKeys) {
|
||||
this.log.warn(
|
||||
"Key checking is disabled. Keys will not be verified."
|
||||
);
|
||||
return;
|
||||
}
|
||||
this.checker = new XaiKeyChecker(this.update.bind(this));
|
||||
for (const key of this.keys) {
|
||||
void this.checker.checkKey(key);
|
||||
}
|
||||
}
|
||||
|
||||
public get(model: string): XaiKey {
|
||||
const availableKeys = this.keys.filter((k) => !k.isDisabled);
|
||||
if (availableKeys.length === 0) {
|
||||
throw new Error("No XAI keys available");
|
||||
}
|
||||
const key = availableKeys[Math.floor(Math.random() * availableKeys.length)];
|
||||
key.lastUsed = Date.now();
|
||||
this.throttle(key.hash);
|
||||
return { ...key };
|
||||
}
|
||||
|
||||
public list(): Omit<XaiKey, "key">[] {
|
||||
return this.keys.map(({ key, ...rest }) => rest);
|
||||
}
|
||||
|
||||
public disable(key: XaiKey): void {
|
||||
const found = this.keys.find((k) => k.hash === key.hash);
|
||||
if (found) {
|
||||
found.isDisabled = true;
|
||||
}
|
||||
}
|
||||
|
||||
public update(hash: string, update: Partial<XaiKey>): void {
|
||||
const key = this.keys.find((k) => k.hash === hash);
|
||||
if (key) {
|
||||
Object.assign(key, update);
|
||||
}
|
||||
}
|
||||
|
||||
public available(): number {
|
||||
return this.keys.filter((k) => !k.isDisabled).length;
|
||||
}
|
||||
|
||||
public incrementUsage(keyHash: string, modelFamily: XaiModelFamily, usage: { input: number; output: number }) {
|
||||
const key = this.keys.find((k) => k.hash === keyHash);
|
||||
if (!key) return;
|
||||
|
||||
key.promptCount++;
|
||||
|
||||
if (!key.tokenUsage) {
|
||||
key.tokenUsage = {};
|
||||
}
|
||||
// Xai only has one model family "xai"
|
||||
if (!key.tokenUsage[modelFamily]) {
|
||||
key.tokenUsage[modelFamily] = { input: 0, output: 0 };
|
||||
}
|
||||
|
||||
const currentFamilyUsage = key.tokenUsage[modelFamily]!;
|
||||
currentFamilyUsage.input += usage.input;
|
||||
currentFamilyUsage.output += usage.output;
|
||||
}
|
||||
|
||||
/**
|
||||
* Upon being rate limited, a key will be locked out for this many milliseconds
|
||||
* while we wait for other concurrent requests to finish.
|
||||
*/
|
||||
private static readonly RATE_LIMIT_LOCKOUT = 2000;
|
||||
/**
|
||||
* Upon assigning a key, we will wait this many milliseconds before allowing it
|
||||
* to be used again. This is to prevent the queue from flooding a key with too
|
||||
* many requests while we wait to learn whether previous ones succeeded.
|
||||
*/
|
||||
private static readonly KEY_REUSE_DELAY = 500;
|
||||
|
||||
getLockoutPeriod = createGenericGetLockoutPeriod(() => this.keys);
|
||||
|
||||
public markRateLimited(keyHash: string) {
|
||||
this.log.debug({ key: keyHash }, "Key rate limited");
|
||||
const key = this.keys.find((k) => k.hash === keyHash)!;
|
||||
const now = Date.now();
|
||||
key.rateLimitedAt = now;
|
||||
key.rateLimitedUntil = now + XaiKeyProvider.RATE_LIMIT_LOCKOUT;
|
||||
}
|
||||
|
||||
public recheck(): void {
|
||||
if (!this.checker || !config.checkKeys) return;
|
||||
for (const key of this.keys) {
|
||||
this.update(key.hash, {
|
||||
isOverQuota: false,
|
||||
isDisabled: false,
|
||||
lastChecked: 0
|
||||
});
|
||||
void this.checker.checkKey(key);
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Applies a short artificial delay to the key upon dequeueing, in order to
|
||||
* prevent it from being immediately assigned to another request before the
|
||||
* current one can be dispatched.
|
||||
**/
|
||||
private throttle(hash: string) {
|
||||
const now = Date.now();
|
||||
const key = this.keys.find((k) => k.hash === hash)!;
|
||||
|
||||
const currentRateLimit = key.rateLimitedUntil;
|
||||
const nextRateLimit = now + XaiKeyProvider.KEY_REUSE_DELAY;
|
||||
|
||||
key.rateLimitedAt = now;
|
||||
key.rateLimitedUntil = Math.max(currentRateLimit, nextRateLimit);
|
||||
}
|
||||
}
|
||||
+181
-10
@@ -14,7 +14,12 @@ export type LLMService =
|
||||
| "mistral-ai"
|
||||
| "aws"
|
||||
| "gcp"
|
||||
| "azure";
|
||||
| "azure"
|
||||
| "deepseek"
|
||||
| "xai"
|
||||
| "cohere"
|
||||
| "qwen"
|
||||
| "moonshot";
|
||||
|
||||
export type OpenAIModelFamily =
|
||||
| "turbo"
|
||||
@@ -22,9 +27,24 @@ export type OpenAIModelFamily =
|
||||
| "gpt4-32k"
|
||||
| "gpt4-turbo"
|
||||
| "gpt4o"
|
||||
| "gpt41"
|
||||
| "gpt41-mini"
|
||||
| "gpt41-nano"
|
||||
| "gpt45"
|
||||
| "gpt5"
|
||||
| "gpt5-mini"
|
||||
| "gpt5-nano"
|
||||
| "gpt5-chat-latest"
|
||||
| "o1"
|
||||
| "o1-mini"
|
||||
| "dall-e";
|
||||
| "o1-pro"
|
||||
| "o3-pro"
|
||||
| "o3-mini"
|
||||
| "o3"
|
||||
| "o4-mini"
|
||||
| "codex-mini"
|
||||
| "dall-e"
|
||||
| "gpt-image";
|
||||
export type AnthropicModelFamily = "claude" | "claude-opus";
|
||||
export type GoogleAIModelFamily =
|
||||
| "gemini-flash"
|
||||
@@ -39,6 +59,12 @@ export type AwsBedrockModelFamily = `aws-${
|
||||
| MistralAIModelFamily}`;
|
||||
export type GcpModelFamily = "gcp-claude" | "gcp-claude-opus";
|
||||
export type AzureOpenAIModelFamily = `azure-${OpenAIModelFamily}`;
|
||||
export type DeepseekModelFamily = "deepseek";
|
||||
export type XaiModelFamily = "xai";
|
||||
export type CohereModelFamily = "cohere";
|
||||
export type QwenModelFamily = "qwen";
|
||||
export type MoonshotModelFamily = "moonshot";
|
||||
|
||||
export type ModelFamily =
|
||||
| OpenAIModelFamily
|
||||
| AnthropicModelFamily
|
||||
@@ -46,19 +72,44 @@ export type ModelFamily =
|
||||
| MistralAIModelFamily
|
||||
| AwsBedrockModelFamily
|
||||
| GcpModelFamily
|
||||
| AzureOpenAIModelFamily;
|
||||
| AzureOpenAIModelFamily
|
||||
| DeepseekModelFamily
|
||||
| XaiModelFamily
|
||||
| CohereModelFamily
|
||||
| QwenModelFamily
|
||||
| MoonshotModelFamily;
|
||||
|
||||
export const MODEL_FAMILIES = (<A extends readonly ModelFamily[]>(
|
||||
arr: A & ([ModelFamily] extends [A[number]] ? unknown : never)
|
||||
) => arr)([
|
||||
"moonshot",
|
||||
"qwen",
|
||||
"cohere",
|
||||
"xai",
|
||||
"deepseek",
|
||||
"turbo",
|
||||
"gpt4",
|
||||
"gpt4-32k",
|
||||
"gpt4-turbo",
|
||||
"gpt4o",
|
||||
"gpt45",
|
||||
"gpt41",
|
||||
"gpt41-mini",
|
||||
"gpt41-nano",
|
||||
"gpt5",
|
||||
"gpt5-mini",
|
||||
"gpt5-nano",
|
||||
"gpt5-chat-latest",
|
||||
"o1",
|
||||
"o1-mini",
|
||||
"o1-pro",
|
||||
"o3-pro",
|
||||
"o3-mini",
|
||||
"o3",
|
||||
"o4-mini",
|
||||
"codex-mini",
|
||||
"dall-e",
|
||||
"gpt-image",
|
||||
"claude",
|
||||
"claude-opus",
|
||||
"gemini-flash",
|
||||
@@ -81,9 +132,24 @@ export const MODEL_FAMILIES = (<A extends readonly ModelFamily[]>(
|
||||
"azure-gpt4-32k",
|
||||
"azure-gpt4-turbo",
|
||||
"azure-gpt4o",
|
||||
"azure-gpt45",
|
||||
"azure-gpt41",
|
||||
"azure-gpt41-mini",
|
||||
"azure-gpt41-nano",
|
||||
"azure-gpt5",
|
||||
"azure-gpt5-mini",
|
||||
"azure-gpt5-nano",
|
||||
"azure-gpt5-chat-latest",
|
||||
"azure-dall-e",
|
||||
"azure-o1",
|
||||
"azure-o1-mini",
|
||||
"azure-o1-pro",
|
||||
"azure-o3-pro",
|
||||
"azure-o3-mini",
|
||||
"azure-o3",
|
||||
"azure-o4-mini",
|
||||
"azure-codex-mini",
|
||||
"azure-gpt-image",
|
||||
] as const);
|
||||
|
||||
export const LLM_SERVICES = (<A extends readonly LLMService[]>(
|
||||
@@ -96,19 +162,44 @@ export const LLM_SERVICES = (<A extends readonly LLMService[]>(
|
||||
"aws",
|
||||
"gcp",
|
||||
"azure",
|
||||
"deepseek",
|
||||
"xai",
|
||||
"cohere",
|
||||
"qwen",
|
||||
"moonshot"
|
||||
] as const);
|
||||
|
||||
export const MODEL_FAMILY_SERVICE: {
|
||||
[f in ModelFamily]: LLMService;
|
||||
} = {
|
||||
moonshot: "moonshot",
|
||||
qwen: "qwen",
|
||||
cohere: "cohere",
|
||||
xai: "xai",
|
||||
deepseek: "deepseek",
|
||||
turbo: "openai",
|
||||
gpt4: "openai",
|
||||
"gpt4-turbo": "openai",
|
||||
"gpt4-32k": "openai",
|
||||
gpt4o: "openai",
|
||||
gpt45: "openai",
|
||||
gpt41: "openai",
|
||||
"gpt41-mini": "openai",
|
||||
"gpt41-nano": "openai",
|
||||
gpt5: "openai",
|
||||
"gpt5-mini": "openai",
|
||||
"gpt5-nano": "openai",
|
||||
"gpt5-chat-latest": "openai",
|
||||
"o1": "openai",
|
||||
"o1-mini": "openai",
|
||||
"o1-pro": "openai",
|
||||
"o3-pro": "openai",
|
||||
"o3-mini": "openai",
|
||||
"o3": "openai",
|
||||
"o4-mini": "openai",
|
||||
"codex-mini": "openai",
|
||||
"dall-e": "openai",
|
||||
"gpt-image": "openai",
|
||||
claude: "anthropic",
|
||||
"claude-opus": "anthropic",
|
||||
"aws-claude": "aws",
|
||||
@@ -124,9 +215,24 @@ export const MODEL_FAMILY_SERVICE: {
|
||||
"azure-gpt4-32k": "azure",
|
||||
"azure-gpt4-turbo": "azure",
|
||||
"azure-gpt4o": "azure",
|
||||
"azure-gpt45": "azure",
|
||||
"azure-gpt41": "azure",
|
||||
"azure-gpt41-mini": "azure",
|
||||
"azure-gpt41-nano": "azure",
|
||||
"azure-gpt5": "azure",
|
||||
"azure-gpt5-mini": "azure",
|
||||
"azure-gpt5-nano": "azure",
|
||||
"azure-gpt5-chat-latest": "azure",
|
||||
"azure-dall-e": "azure",
|
||||
"azure-o1": "azure",
|
||||
"azure-o1-mini": "azure",
|
||||
"azure-o1-pro": "azure",
|
||||
"azure-o3-pro": "azure",
|
||||
"azure-o3-mini": "azure",
|
||||
"azure-o3": "azure",
|
||||
"azure-o4-mini": "azure",
|
||||
"azure-codex-mini": "azure",
|
||||
"azure-gpt-image": "azure",
|
||||
"gemini-flash": "google-ai",
|
||||
"gemini-pro": "google-ai",
|
||||
"gemini-ultra": "google-ai",
|
||||
@@ -136,9 +242,18 @@ export const MODEL_FAMILY_SERVICE: {
|
||||
"mistral-large": "mistral-ai",
|
||||
};
|
||||
|
||||
export const IMAGE_GEN_MODELS: ModelFamily[] = ["dall-e", "azure-dall-e"];
|
||||
export const IMAGE_GEN_MODELS: ModelFamily[] = ["dall-e", "azure-dall-e", "gpt-image", "azure-gpt-image"];
|
||||
|
||||
export const OPENAI_MODEL_FAMILY_MAP: { [regex: string]: OpenAIModelFamily } = {
|
||||
"^gpt-image(-\\d+)?(-preview)?(-\\d{4}-\\d{2}-\\d{2})?$": "gpt-image",
|
||||
"^gpt-5(-\\d{4}-\\d{2}-\\d{2})?$": "gpt5",
|
||||
"^gpt-5-mini(-\\d{4}-\\d{2}-\\d{2})?$": "gpt5-mini",
|
||||
"^gpt-5-nano(-\\d{4}-\\d{2}-\\d{2})?$": "gpt5-nano",
|
||||
"^gpt-5-chat-latest(-\\d{4}-\\d{2}-\\d{2})?$": "gpt5-chat-latest",
|
||||
"^gpt-4\\.5(-preview)?(-\\d{4}-\\d{2}-\\d{2})?$": "gpt45",
|
||||
"^gpt-4\\.1(-\\d{4}-\\d{2}-\\d{2})?$": "gpt41",
|
||||
"^gpt-4\\.1-mini(-\\d{4}-\\d{2}-\\d{2})?$": "gpt41-mini",
|
||||
"^gpt-4\\.1-nano(-\\d{4}-\\d{2}-\\d{2})?$": "gpt41-nano",
|
||||
"^gpt-4o(-\\d{4}-\\d{2}-\\d{2})?$": "gpt4o",
|
||||
"^chatgpt-4o": "gpt4o",
|
||||
"^gpt-4o-mini(-\\d{4}-\\d{2}-\\d{2})?$": "turbo", // closest match
|
||||
@@ -154,7 +269,13 @@ export const OPENAI_MODEL_FAMILY_MAP: { [regex: string]: OpenAIModelFamily } = {
|
||||
"^text-embedding-ada-002$": "turbo",
|
||||
"^dall-e-\\d{1}$": "dall-e",
|
||||
"^o1-mini(-\\d{4}-\\d{2}-\\d{2})?$": "o1-mini",
|
||||
"^o1(-preview)?(-\\d{4}-\\d{2}-\\d{2})?$": "o1",
|
||||
"^o1-pro(-\\d{4}-\\d{2}-\\d{2})?$": "o1-pro",
|
||||
"^o3-pro(-\\d{4}-\\d{2}-\\d{2})?$": "o3-pro",
|
||||
"^o1(-\\d{4}-\\d{2}-\\d{2})?$": "o1",
|
||||
"^o3-mini(-\\d{4}-\\d{2}-\\d{2})?$": "o3-mini",
|
||||
"^o3(-\\d{4}-\\d{2}-\\d{2})?$": "o3",
|
||||
"^o4-mini(-\\d{4}-\\d{2}-\\d{2})?$": "o4-mini",
|
||||
"^codex-mini(-latest|-\d{4}-\d{2}-\d{2})?$": "codex-mini",
|
||||
};
|
||||
|
||||
export function getOpenAIModelFamily(
|
||||
@@ -173,7 +294,8 @@ export function getClaudeModelFamily(model: string): AnthropicModelFamily {
|
||||
}
|
||||
|
||||
export function getGoogleAIModelFamily(model: string): GoogleAIModelFamily {
|
||||
return model.includes("ultra")
|
||||
// Treat models as Gemni Ultra only if they include "ultra" and are NOT Imagen models
|
||||
return model.includes("ultra") && !model.includes("imagen")
|
||||
? "gemini-ultra"
|
||||
: model.includes("flash")
|
||||
? "gemini-flash"
|
||||
@@ -181,22 +303,58 @@ export function getGoogleAIModelFamily(model: string): GoogleAIModelFamily {
|
||||
}
|
||||
|
||||
export function getMistralAIModelFamily(model: string): MistralAIModelFamily {
|
||||
const prunedModel = model.replace(/-(latest|\d{4})$/, "");
|
||||
const prunedModel = model.replace(/-(latest|\d{4}(-\d{2}){0,2})$/, "");
|
||||
|
||||
// Premier models (higher tier)
|
||||
switch (prunedModel) {
|
||||
// Existing direct matches
|
||||
case "mistral-tiny":
|
||||
case "mistral-small":
|
||||
case "mistral-medium":
|
||||
case "mistral-large":
|
||||
return prunedModel as MistralAIModelFamily;
|
||||
|
||||
// Premier models - Large tier
|
||||
case "mistral-large":
|
||||
case "pixtral-large":
|
||||
return "mistral-large";
|
||||
|
||||
// Premier models - Medium tier
|
||||
case "mistral-medium-2505":
|
||||
case "magistral-medium-latest":
|
||||
return "mistral-medium";
|
||||
|
||||
// Premier models - Small tier
|
||||
case "codestral":
|
||||
case "ministral-8b":
|
||||
case "mistral-embed":
|
||||
case "pixtral-12b-2409":
|
||||
case "magistral-small-latest":
|
||||
return "mistral-small";
|
||||
|
||||
// Premier models - Tiny tier
|
||||
case "ministral-3b":
|
||||
return "mistral-tiny";
|
||||
|
||||
// Free models - Tiny tier
|
||||
case "open-mistral-7b":
|
||||
return "mistral-tiny";
|
||||
|
||||
// Free models - Small tier
|
||||
case "mistral-small":
|
||||
case "pixtral":
|
||||
case "pixtral-12b":
|
||||
case "open-mistral-nemo":
|
||||
case "open-mixtral-8x7b":
|
||||
case "codestral":
|
||||
case "open-codestral-mamba":
|
||||
case "mathstral":
|
||||
return "mistral-small";
|
||||
|
||||
// Free models - Medium tier
|
||||
case "open-mixtral-8x22b":
|
||||
return "mistral-medium";
|
||||
|
||||
// Default to small if unknown
|
||||
default:
|
||||
return "mistral-small";
|
||||
}
|
||||
@@ -263,6 +421,8 @@ export function getModelFamilyForRequest(req: Request): ModelFamily {
|
||||
modelFamily = getGcpModelFamily(model);
|
||||
} else if (req.service === "azure") {
|
||||
modelFamily = getAzureOpenAIModelFamily(model);
|
||||
} else if (req.service === "qwen") {
|
||||
modelFamily = "qwen";
|
||||
} else {
|
||||
switch (req.outboundApi) {
|
||||
case "anthropic-chat":
|
||||
@@ -272,7 +432,15 @@ export function getModelFamilyForRequest(req: Request): ModelFamily {
|
||||
case "openai":
|
||||
case "openai-text":
|
||||
case "openai-image":
|
||||
modelFamily = getOpenAIModelFamily(model);
|
||||
if (req.service === "deepseek") {
|
||||
modelFamily = "deepseek";
|
||||
} else if (req.service === "xai") {
|
||||
modelFamily = "xai";
|
||||
} else if (req.service === "moonshot") {
|
||||
modelFamily = "moonshot";
|
||||
} else {
|
||||
modelFamily = getOpenAIModelFamily(model);
|
||||
}
|
||||
break;
|
||||
case "google-ai":
|
||||
modelFamily = getGoogleAIModelFamily(model);
|
||||
@@ -281,6 +449,9 @@ export function getModelFamilyForRequest(req: Request): ModelFamily {
|
||||
case "mistral-text":
|
||||
modelFamily = getMistralAIModelFamily(model);
|
||||
break;
|
||||
case "openai-responses":
|
||||
modelFamily = getOpenAIModelFamily(model);
|
||||
break;
|
||||
default:
|
||||
assertNever(req.outboundApi);
|
||||
}
|
||||
@@ -291,4 +462,4 @@ export function getModelFamilyForRequest(req: Request): ModelFamily {
|
||||
|
||||
function assertNever(x: never): never {
|
||||
throw new Error(`Called assertNever with argument ${x}.`);
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,62 @@
|
||||
import Database from 'better-sqlite3';
|
||||
import { config } from '../config';
|
||||
import { logger } from '../logger';
|
||||
|
||||
const log = logger.child({ module: 'sqlite-db' });
|
||||
|
||||
let db: Database.Database;
|
||||
|
||||
export function initSQLiteDB(): Database.Database {
|
||||
if (db) {
|
||||
return db;
|
||||
}
|
||||
|
||||
const dbPath = config.sqliteUserStorePath;
|
||||
if (!dbPath) {
|
||||
log.error('SQLite user store DB path (SQLITE_USER_STORE_PATH) is not configured.');
|
||||
throw new Error('SQLite user store DB path is not configured.');
|
||||
}
|
||||
|
||||
log.info({ path: dbPath }, 'Initializing SQLite database for user store...');
|
||||
db = new Database(dbPath);
|
||||
|
||||
// Enable WAL mode for better concurrency and performance.
|
||||
db.pragma('journal_mode = WAL');
|
||||
|
||||
// Create users table
|
||||
// Note: JSON fields (ip, tokenCounts, etc.) are stored as TEXT.
|
||||
// Timestamps are stored as INTEGER (Unix epoch milliseconds).
|
||||
db.exec(`
|
||||
CREATE TABLE IF NOT EXISTS users (
|
||||
token TEXT PRIMARY KEY,
|
||||
ip TEXT, /* JSON string array */
|
||||
nickname TEXT,
|
||||
type TEXT NOT NULL CHECK(type IN ('normal', 'special', 'temporary')),
|
||||
promptCount INTEGER NOT NULL DEFAULT 0,
|
||||
tokenCounts TEXT, /* JSON string object */
|
||||
tokenLimits TEXT, /* JSON string object */
|
||||
tokenRefresh TEXT, /* JSON string object */
|
||||
createdAt INTEGER NOT NULL,
|
||||
lastUsedAt INTEGER,
|
||||
disabledAt INTEGER,
|
||||
disabledReason TEXT,
|
||||
expiresAt INTEGER,
|
||||
maxIps INTEGER,
|
||||
adminNote TEXT,
|
||||
meta TEXT /* JSON string object */
|
||||
);
|
||||
`);
|
||||
|
||||
log.info('SQLite database initialized and `users` table created/verified.');
|
||||
return db;
|
||||
}
|
||||
|
||||
export function getDB(): Database.Database {
|
||||
if (!db) {
|
||||
// This might happen if getDB is called before initSQLiteDB,
|
||||
// though user-store should ensure init is called first.
|
||||
log.warn('SQLite DB instance requested before initialization. Attempting to initialize now.');
|
||||
return initSQLiteDB();
|
||||
}
|
||||
return db;
|
||||
}
|
||||
+92
-67
@@ -1,74 +1,99 @@
|
||||
import { config } from "../config";
|
||||
import { ModelFamily } from "./models";
|
||||
|
||||
// technically slightly underestimates, because completion tokens cost more
|
||||
// than prompt tokens but we don't track those separately right now
|
||||
export function getTokenCostUsd(model: ModelFamily, tokens: number) {
|
||||
let cost = 0;
|
||||
switch (model) {
|
||||
case "gpt4o":
|
||||
case "azure-gpt4o":
|
||||
cost = 0.000005;
|
||||
break;
|
||||
case "azure-gpt4-turbo":
|
||||
case "gpt4-turbo":
|
||||
cost = 0.00001;
|
||||
break;
|
||||
case "azure-o1":
|
||||
case "o1":
|
||||
// Currently we do not track output tokens separately, and O1 uses
|
||||
// considerably more output tokens that other models for its hidden
|
||||
// reasoning. The official O1 pricing is $15/1M input tokens and $60/1M
|
||||
// output tokens so we will return a higher estimate here.
|
||||
cost = 0.00002;
|
||||
break
|
||||
case "azure-o1-mini":
|
||||
case "o1-mini":
|
||||
cost = 0.000005; // $3/1M input tokens, $12/1M output tokens
|
||||
break
|
||||
case "azure-gpt4-32k":
|
||||
case "gpt4-32k":
|
||||
cost = 0.00006;
|
||||
break;
|
||||
case "azure-gpt4":
|
||||
case "gpt4":
|
||||
cost = 0.00003;
|
||||
break;
|
||||
case "azure-turbo":
|
||||
case "turbo":
|
||||
cost = 0.000001;
|
||||
break;
|
||||
case "azure-dall-e":
|
||||
cost = 0.00001;
|
||||
break;
|
||||
case "aws-claude":
|
||||
case "gcp-claude":
|
||||
case "claude":
|
||||
cost = 0.000008;
|
||||
break;
|
||||
case "aws-claude-opus":
|
||||
case "gcp-claude-opus":
|
||||
case "claude-opus":
|
||||
cost = 0.000015;
|
||||
break;
|
||||
case "aws-mistral-tiny":
|
||||
case "mistral-tiny":
|
||||
cost = 0.00000025;
|
||||
break;
|
||||
case "aws-mistral-small":
|
||||
case "mistral-small":
|
||||
cost = 0.0000003;
|
||||
break;
|
||||
case "aws-mistral-medium":
|
||||
case "mistral-medium":
|
||||
cost = 0.00000275;
|
||||
break;
|
||||
case "aws-mistral-large":
|
||||
case "mistral-large":
|
||||
cost = 0.000003;
|
||||
break;
|
||||
// Prices are per 1 million tokens.
|
||||
const MODEL_PRICING: Record<ModelFamily, { input: number; output: number } | undefined> = {
|
||||
"deepseek": { input: 0.55, output: 2.19 }, // DeepSeek Reasoner (standard price, input cache miss)
|
||||
"xai": { input: 5.6, output: 16.8 }, // Grok: Derived from avg $14/1M (assuming 1:3 in/out ratio) - needs official pricing
|
||||
"gpt41": { input: 2.00, output: 8.00 },
|
||||
"azure-gpt41": { input: 2.00, output: 8.00 },
|
||||
"gpt41-mini": { input: 0.40, output: 1.60 },
|
||||
"azure-gpt41-mini": { input: 0.40, output: 1.60 },
|
||||
"gpt41-nano": { input: 0.10, output: 0.40 },
|
||||
"azure-gpt41-nano": { input: 0.10, output: 0.40 },
|
||||
"gpt5": { input: 1.25, output: 10.00 },
|
||||
"azure-gpt5": { input: 1.25, output: 10.00 },
|
||||
"gpt5-mini": { input: 0.25, output: 2.00 },
|
||||
"azure-gpt5-mini": { input: 0.25, output: 2.00 },
|
||||
"gpt5-nano": { input: 0.05, output: 0.40 },
|
||||
"azure-gpt5-nano": { input: 0.05, output: 0.40 },
|
||||
"gpt5-chat-latest": { input: 1.25, output: 10.00 },
|
||||
"azure-gpt5-chat-latest": { input: 1.25, output: 10.00 },
|
||||
"gpt45": { input: 75.00, output: 150.00 }, // Example, needs verification if this model family is still current with this pricing
|
||||
"azure-gpt45": { input: 75.00, output: 150.00 }, // Example, needs verification
|
||||
"gpt4o": { input: 2.50, output: 10.00 },
|
||||
"azure-gpt4o": { input: 2.50, output: 10.00 },
|
||||
"gpt4-turbo": { input: 10.00, output: 30.00 },
|
||||
"azure-gpt4-turbo": { input: 10.00, output: 30.00 },
|
||||
"o1-pro": { input: 150.00, output: 600.00 },
|
||||
"azure-o1-pro": { input: 150.00, output: 600.00 },
|
||||
"o3-pro": { input: 20.00, output: 80.00 },
|
||||
"azure-o3-pro": { input: 20.00, output: 80.00 },
|
||||
"o1": { input: 15.00, output: 60.00 },
|
||||
"azure-o1": { input: 15.00, output: 60.00 },
|
||||
"o1-mini": { input: 1.10, output: 4.40 },
|
||||
"azure-o1-mini": { input: 1.10, output: 4.40 },
|
||||
"o3-mini": { input: 1.10, output: 4.40 },
|
||||
"azure-o3-mini": { input: 1.10, output: 4.40 },
|
||||
"o3": { input: 2.00, output: 8.00 },
|
||||
"azure-o3": { input: 10.00, output: 40.00 },
|
||||
"o4-mini": { input: 1.10, output: 4.40 },
|
||||
"azure-o4-mini": { input: 1.10, output: 4.40 },
|
||||
"codex-mini": { input: 1.50, output: 6.00 },
|
||||
"azure-codex-mini": { input: 1.50, output: 6.00 },
|
||||
"gpt4-32k": { input: 60.00, output: 120.00 },
|
||||
"azure-gpt4-32k": { input: 60.00, output: 120.00 },
|
||||
"gpt4": { input: 30.00, output: 60.00 },
|
||||
"azure-gpt4": { input: 30.00, output: 60.00 },
|
||||
"turbo": { input: 0.15, output: 0.60 }, // Maps to GPT-4o mini
|
||||
"azure-turbo": { input: 0.15, output: 0.60 },
|
||||
"dall-e": { input: 0, output: 0 }, // Pricing is per image, not token based in this context.
|
||||
"azure-dall-e": { input: 0, output: 0 }, // Pricing is per image.
|
||||
"gpt-image": { input: 0, output: 0 }, // Complex pricing (text, image input, image output tokens), handle separately.
|
||||
"azure-gpt-image": { input: 0, output: 0 }, // Complex pricing.
|
||||
"claude": { input: 3.00, output: 15.00 }, // Anthropic Claude Sonnet 4
|
||||
"aws-claude": { input: 3.00, output: 15.00 },
|
||||
"gcp-claude": { input: 3.00, output: 15.00 },
|
||||
"claude-opus": { input: 15.00, output: 75.00 }, // Anthropic Claude Opus 4
|
||||
"aws-claude-opus": { input: 15.00, output: 75.00 },
|
||||
"gcp-claude-opus": { input: 15.00, output: 75.00 },
|
||||
"mistral-tiny": { input: 0.04, output: 0.04 }, // Using old price if no new API price found
|
||||
"aws-mistral-tiny": { input: 0.04, output: 0.04 },
|
||||
"mistral-small": { input: 0.10, output: 0.30 }, // Mistral Small 3.1
|
||||
"aws-mistral-small": { input: 0.10, output: 0.30 },
|
||||
"mistral-medium": { input: 0.40, output: 2.00 }, // Mistral Medium 3
|
||||
"aws-mistral-medium": { input: 0.40, output: 2.00 },
|
||||
"mistral-large": { input: 2.00, output: 6.00 },
|
||||
"aws-mistral-large": { input: 2.00, output: 6.00 },
|
||||
"gemini-flash": { input: 0.15, output: 0.60 }, // Updated to Gemini 2.5 Flash Preview (text input, non-thinking output)
|
||||
"gemini-pro": { input: 1.25, output: 10.00 }, // Updated to Gemini 2.5 Pro Preview (<=200k tokens)
|
||||
"gemini-ultra": { input: 25.00, output: 75.00 }, // Estimated based on Gemini Pro (5-10x) and character to token conversion. Official per-token pricing needed.
|
||||
// Ensure all ModelFamily entries from models.ts are covered or have a default.
|
||||
// Adding placeholders for families in models.ts but not yet priced here.
|
||||
"cohere": { input: 0.15, output: 0.60 }, // Updated to Command R
|
||||
"qwen": { input: 1.40, output: 2.80 }, // Qwen-plus, as an example
|
||||
"moonshot": { input: 0.6, output: 2.5 }, // Moonshot kimi k2
|
||||
};
|
||||
|
||||
export function getTokenCostDetailsUsd(model: ModelFamily, inputTokens: number, outputTokens?: number): { inputCost: number, outputCost: number, totalCost: number } {
|
||||
const pricing = MODEL_PRICING[model];
|
||||
|
||||
if (!pricing) {
|
||||
console.warn(`Pricing not found for model family: ${model}. Returning 0 cost for all components.`);
|
||||
return { inputCost: 0, outputCost: 0, totalCost: 0 };
|
||||
}
|
||||
return cost * Math.max(0, tokens);
|
||||
|
||||
const costPerMillionInputTokens = pricing.input;
|
||||
const costPerMillionOutputTokens = pricing.output;
|
||||
|
||||
const inputCost = (costPerMillionInputTokens / 1_000_000) * Math.max(0, inputTokens);
|
||||
const outputCost = (costPerMillionOutputTokens / 1_000_000) * Math.max(0, outputTokens ?? 0);
|
||||
|
||||
return { inputCost, outputCost, totalCost: inputCost + outputCost };
|
||||
}
|
||||
|
||||
export function getTokenCostUsd(model: ModelFamily, inputTokens: number, outputTokens?: number): number {
|
||||
return getTokenCostDetailsUsd(model, inputTokens, outputTokens).totalCost;
|
||||
}
|
||||
|
||||
export function prettyTokens(tokens: number): string {
|
||||
|
||||
@@ -67,6 +67,9 @@ async function getTokenCountForMessages({
|
||||
case "image":
|
||||
numTokens += await getImageTokenCount(part.source.data);
|
||||
break;
|
||||
case "tool_use":
|
||||
case "tool_result":
|
||||
break;
|
||||
default:
|
||||
throw new Error(`Unsupported Anthropic content type.`);
|
||||
}
|
||||
|
||||
@@ -45,7 +45,7 @@ export async function getTokenCount(
|
||||
const value = message[key as keyof OpenAIChatMessage];
|
||||
|
||||
if (!value) continue;
|
||||
|
||||
if (key === 'function_call') continue;
|
||||
if (Array.isArray(value)) {
|
||||
for (const item of value) {
|
||||
if (item.type === "text") {
|
||||
@@ -57,7 +57,7 @@ export async function getTokenCount(
|
||||
}
|
||||
}
|
||||
} else {
|
||||
textContent = value;
|
||||
textContent = value as string;
|
||||
}
|
||||
|
||||
if (textContent.length > 800000 || numTokens > 200000) {
|
||||
@@ -179,9 +179,9 @@ export const DALLE_TOKENS_PER_DOLLAR = 100000;
|
||||
* which we convert to tokens at a rate of 100000 tokens per dollar.
|
||||
*/
|
||||
export function getOpenAIImageCost(params: {
|
||||
model: "dall-e-2" | "dall-e-3";
|
||||
quality: "standard" | "hd";
|
||||
resolution: "512x512" | "256x256" | "1024x1024" | "1024x1792" | "1792x1024";
|
||||
model: "dall-e-2" | "dall-e-3" | "gpt-image-1";
|
||||
quality: "standard" | "hd" | "high" | "medium" | "low" | "auto";
|
||||
resolution: "512x512" | "256x256" | "1024x1024" | "1024x1792" | "1792x1024" | "1536x1024" | "1024x1536" | "auto";
|
||||
n: number | null;
|
||||
}) {
|
||||
const { model, quality, resolution, n } = params;
|
||||
@@ -208,6 +208,10 @@ export function getOpenAIImageCost(params: {
|
||||
default:
|
||||
throw new Error("Invalid resolution");
|
||||
}
|
||||
case "gpt-image-1":
|
||||
// gpt-image-1 pricing is approximately $0.04 per image
|
||||
// This is a simplified pricing model, adjust as needed based on official pricing
|
||||
return 0.04;
|
||||
default:
|
||||
throw new Error("Invalid image generation model");
|
||||
}
|
||||
@@ -233,7 +237,10 @@ export function estimateGoogleAITokenCount(
|
||||
let numTokens = 0;
|
||||
for (const message of prompt) {
|
||||
numTokens += tokensPerMessage;
|
||||
numTokens += encoder.encode(message.parts[0].text).length;
|
||||
const textPart = message.parts.find(p => 'text' in p) as { text: string } | undefined;
|
||||
if (textPart) {
|
||||
numTokens += encoder.encode(textPart.text).length;
|
||||
}
|
||||
}
|
||||
|
||||
numTokens += 3;
|
||||
|
||||
@@ -31,7 +31,7 @@ export async function init() {
|
||||
type OpenAIChatTokenCountRequest = {
|
||||
prompt: OpenAIChatMessage[];
|
||||
completion?: never;
|
||||
service: "openai";
|
||||
service: "openai" | "openai-responses";
|
||||
};
|
||||
|
||||
type AnthropicChatTokenCountRequest = {
|
||||
@@ -108,6 +108,7 @@ export async function countTokens({
|
||||
};
|
||||
case "openai":
|
||||
case "openai-text":
|
||||
case "openai-responses":
|
||||
return {
|
||||
...(await getOpenAITokenCount(prompt ?? completion, req.body.model)),
|
||||
tokenization_duration_ms: getElapsedMs(time),
|
||||
|
||||
@@ -2,11 +2,31 @@ import { ZodType, z } from "zod";
|
||||
import { MODEL_FAMILIES, ModelFamily } from "../models";
|
||||
import { makeOptionalPropsNullable } from "../utils";
|
||||
|
||||
// This just dynamically creates a Zod object type with a key for each model
|
||||
// family and an optional number value.
|
||||
// Schema for token counts - keeps track of input/output usage
|
||||
export const tokenCountsSchema: ZodType<UserTokenCounts> = z.object(
|
||||
MODEL_FAMILIES.reduce(
|
||||
(acc, family) => ({ ...acc, [family]: z.number().optional().default(0) }),
|
||||
(acc, family) => ({
|
||||
...acc,
|
||||
[family]: z
|
||||
.object({
|
||||
input: z.number().optional().default(0),
|
||||
output: z.number().optional().default(0),
|
||||
legacy_total: z.number().optional(), // Added legacy_total
|
||||
})
|
||||
.optional()
|
||||
.default({ input: 0, output: 0 }), // Default will not have legacy_total
|
||||
}),
|
||||
{} as Record<ModelFamily, ZodType<{ input: number; output: number; legacy_total?: number }>>
|
||||
)
|
||||
);
|
||||
|
||||
// Schema for token limits - simple numbers representing total quota
|
||||
export const tokenLimitsSchema: ZodType<UserTokenLimits> = z.object(
|
||||
MODEL_FAMILIES.reduce(
|
||||
(acc, family) => ({
|
||||
...acc,
|
||||
[family]: z.number().optional().default(0),
|
||||
}),
|
||||
{} as Record<ModelFamily, ZodType<number>>
|
||||
)
|
||||
);
|
||||
@@ -33,12 +53,12 @@ export const UserSchema = z
|
||||
* Never used; retained for backwards compatibility.
|
||||
*/
|
||||
tokenCount: z.any().optional(),
|
||||
/** Number of tokens the user has consumed, by model family. */
|
||||
/** Number of input and output tokens the user has consumed, by model family. */
|
||||
tokenCounts: tokenCountsSchema,
|
||||
/** Maximum number of tokens the user can consume, by model family. */
|
||||
tokenLimits: tokenCountsSchema,
|
||||
tokenLimits: tokenLimitsSchema,
|
||||
/** User-specific token refresh amount, by model family. */
|
||||
tokenRefresh: tokenCountsSchema,
|
||||
tokenRefresh: tokenLimitsSchema,
|
||||
/** Time at which the user was created. */
|
||||
createdAt: z.number(),
|
||||
/** Time at which the user last connected. */
|
||||
@@ -67,6 +87,9 @@ export const UserPartialSchema = makeOptionalPropsNullable(UserSchema)
|
||||
.extend({ token: z.string() });
|
||||
|
||||
export type UserTokenCounts = {
|
||||
[K in ModelFamily]: { input: number; output: number; legacy_total?: number } | undefined;
|
||||
};
|
||||
export type UserTokenLimits = {
|
||||
[K in ModelFamily]: number | undefined;
|
||||
};
|
||||
export type User = z.infer<typeof UserSchema>;
|
||||
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user