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zack3d/OAI-Proxy:main zack3d/OAI-Proxy:o1-role-reasoning zack3d/OAI-Proxy:o1-200k zack3d/OAI-Proxy:o1-check-family zack3d/OAI-Proxy:penurin-main-patch-71429 zack3d/OAI-Proxy:add-tool-fix-claude zack3d/OAI-Proxy:oai-deprecated-toolcall-fix zack3d/OAI-Proxy:aws-mistral zack3d/OAI-Proxy:cohere zack3d/OAI-Proxy:sqlite-users zack3d/OAI-Proxy:api-support-refactor zack3d/OAI-Proxy:combined-endpoint zack3d/OAI-Proxy:fix-express-trust-proxy zack3d/OAI-Proxy:captcha zack3d/OAI-Proxy:key-persistence zack3d/OAI-Proxy:add-assistant-postamble zack3d/OAI-Proxy:datasets-persistence zack3d/OAI-Proxy:tokenize zack3d/OAI-Proxy:scale-autochurn zack3d/OAI-Proxy:airtable-logging
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pull from: zack3d/OAI-Proxy:api-support-refactor
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zack3d/OAI-Proxy:main zack3d/OAI-Proxy:o1-role-reasoning zack3d/OAI-Proxy:o1-200k zack3d/OAI-Proxy:o1-check-family zack3d/OAI-Proxy:penurin-main-patch-71429 zack3d/OAI-Proxy:add-tool-fix-claude zack3d/OAI-Proxy:oai-deprecated-toolcall-fix zack3d/OAI-Proxy:aws-mistral zack3d/OAI-Proxy:cohere zack3d/OAI-Proxy:sqlite-users zack3d/OAI-Proxy:api-support-refactor zack3d/OAI-Proxy:combined-endpoint zack3d/OAI-Proxy:fix-express-trust-proxy zack3d/OAI-Proxy:captcha zack3d/OAI-Proxy:key-persistence zack3d/OAI-Proxy:add-assistant-postamble zack3d/OAI-Proxy:datasets-persistence zack3d/OAI-Proxy:tokenize zack3d/OAI-Proxy:scale-autochurn zack3d/OAI-Proxy:airtable-logging

1 Commits
main .. api-support-refactor

Author SHA1 Message Date
nai-degen 84acc429d7 wip 2024-03-16 00:04:27 -05:00
215 changed files with 4874 additions and 20783 deletions
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.env.example
+45 -114
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@@ -8,32 +8,12 @@
# Use production mode unless you are developing locally.
NODE_ENV=production
# Detail level of diagnostic logging. (trace | debug | info | warn | error)
# LOG_LEVEL=info
# ------------------------------------------------------------------------------
# General settings:
# 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
@@ -44,90 +24,55 @@ NODE_ENV=production
# Max number of context tokens a user can request at once.
# Increase this if your proxy allow GPT 32k or 128k context
# MAX_CONTEXT_TOKENS_OPENAI=32768
# MAX_CONTEXT_TOKENS_ANTHROPIC=32768
# MAX_CONTEXT_TOKENS_OPENAI=16384
# Max number of output tokens a user can request at once.
# MAX_OUTPUT_TOKENS_OPENAI=1024
# MAX_OUTPUT_TOKENS_ANTHROPIC=1024
# MAX_OUTPUT_TOKENS_OPENAI=400
# MAX_OUTPUT_TOKENS_ANTHROPIC=400
# Whether to show the estimated cost of consumed tokens on the info page.
# SHOW_TOKEN_COSTS=false
# Whether to automatically check API keys for validity.
# Disabled by default in local development mode, but enabled in production.
# Note: CHECK_KEYS is disabled by default in local development mode, but enabled
# by default in production mode.
# CHECK_KEYS=true
# Which model types users are allowed to access.
# The following model families are recognized:
# turbo | gpt4 | gpt4-32k | gpt4-turbo | gpt4o | o1 | dall-e | 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-o1 | azure-dall-e
# | 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
# turbo | gpt4 | gpt4-32k | gpt4-turbo | dall-e | claude | claude-opus | gemini-pro | mistral-tiny | mistral-small | mistral-medium | mistral-large | aws-claude | azure-turbo | azure-gpt4 | azure-gpt4-32k | azure-gpt4-turbo | azure-dall-e
# By default, all models are allowed except for 'dall-e' / 'azure-dall-e'.
# 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,claude,claude-opus,gemini-pro,mistral-tiny,mistral-small,mistral-medium,mistral-large,aws-claude,azure-turbo,azure-gpt4,azure-gpt4-32k,azure-gpt4-turbo
# 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 | 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.
# ALLOWED_VISION_SERVICES=
# Whether prompts should be logged to Google Sheets.
# Requires additional setup. See `docs/google-sheets.md` for more information.
# PROMPT_LOGGING=false
# Specifies the number of proxies or load balancers in front of the server.
# For Cloudflare or Hugging Face deployments, the default of 1 is correct.
# For any other deployments, please see config.ts as the correct configuration
# depends on your setup. Misconfiguring this value can result in problems
# accurately tracking IP addresses and enforcing rate limits.
# TRUSTED_PROXIES=1
# Whether cookies should be set without the Secure flag, for hosts that don't
# support SSL. True by default in development, false in production.
# USE_INSECURE_COOKIES=false
# Reorganizes requests in the queue according to their token count, placing
# larger prompts further back. The penalty is determined by (promptTokens *
# TOKENS_PUNISHMENT_FACTOR). A value of 1.0 adds one second per 1000 tokens.
# When there is no queue or it is very short, the effect is negligible (this
# setting only reorders the queue, it does not artificially delay requests).
# TOKENS_PUNISHMENT_FACTOR=0.0
# Captcha verification settings. Refer to docs/pow-captcha.md for guidance.
# CAPTCHA_MODE=none
# POW_TOKEN_HOURS=24
# POW_TOKEN_MAX_IPS=2
# POW_DIFFICULTY_LEVEL=low
# POW_CHALLENGE_TIMEOUT=30
# -------------------------------------------------------------------------------
# Blocking settings:
# Allows blocking requests depending on content, referers, or IP addresses.
# This is a convenience feature; if you need more robust functionality it is
# highly recommended to put this application behind nginx or Cloudflare, as they
# will have better performance.
# IP addresses or CIDR blocks from which requests will be blocked.
# IP_BLACKLIST=10.0.0.1/24
# URLs from which requests will be blocked.
# BLOCKED_ORIGINS=reddit.com,9gag.com
# Message to show when requests are blocked.
# BLOCK_MESSAGE="You must be over the age of majority in your country to use this service."
# Destination to redirect blocked requests to.
# BLOCK_REDIRECT="https://roblox.com/"
# Comma-separated list of phrases that will be rejected. Surround phrases with
# quotes if they contain commas. You can use regular expression tokens.
# Avoid overly broad phrases as will trigger on any match in the entire prompt.
# Comma-separated list of phrases that will be rejected. Only whole words are matched.
# Surround phrases with quotes if they contain commas.
# Avoid short or common phrases as this tests the entire prompt.
# REJECT_PHRASES="phrase one,phrase two,"phrase three, which has a comma",phrase four"
# Message to show when requests are rejected.
# REJECT_MESSAGE="You can't say that here."
# REJECT_MESSAGE="This content violates /aicg/'s acceptable use policy."
# Whether prompts should be logged to Google Sheets.
# Requires additional setup. See `docs/google-sheets.md` for more information.
# PROMPT_LOGGING=false
# The port and network interface to listen on.
# PORT=7860
# BIND_ADDRESS=0.0.0.0
# Whether cookies should be set without the Secure flag, for hosts that don't support SSL.
# USE_INSECURE_COOKIES=false
# Detail level of logging. (trace | debug | info | warn | error)
# LOG_LEVEL=info
# ------------------------------------------------------------------------------
# Optional settings for user management, access control, and quota enforcement:
@@ -136,11 +81,8 @@ NODE_ENV=production
# Which access control method to use. (none | proxy_key | user_token)
# GATEKEEPER=none
# Which persistence method to use. (memory | firebase_rtdb | sqlite)
# Which persistence method to use. (memory | firebase_rtdb)
# 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
@@ -151,34 +93,29 @@ NODE_ENV=production
# ALLOW_NICKNAME_CHANGES=true
# Default token quotas for each model family. (0 for unlimited)
# Specify as TOKEN_QUOTA_MODEL_FAMILY=value (replacing dashes with underscores).
# eg. TOKEN_QUOTA_TURBO=0, TOKEN_QUOTA_GPT4=1000000, TOKEN_QUOTA_GPT4_32K=100000
# "Tokens" for image-generation models are counted at a rate of 100000 tokens
# per US$1.00 generated, which is similar to the cost of GPT-4 Turbo.
# DALL-E "tokens" are counted at a rate of 100000 tokens per US$1.00 generated,
# which is similar to the cost of GPT-4 Turbo.
# DALL-E 3 costs around US$0.10 per image (10000 tokens).
# See `docs/dall-e-configuration.md` for more information.
# TOKEN_QUOTA_TURBO=0
# TOKEN_QUOTA_GPT4=0
# TOKEN_QUOTA_GPT4_32K=0
# TOKEN_QUOTA_GPT4_TURBO=0
# TOKEN_QUOTA_DALL_E=0
# TOKEN_QUOTA_CLAUDE=0
# TOKEN_QUOTA_GEMINI_PRO=0
# TOKEN_QUOTA_AWS_CLAUDE=0
# How often to refresh token quotas. (hourly | daily)
# Leave unset to never automatically refresh quotas.
# QUOTA_REFRESH_PERIOD=daily
# -------------------------------------------------------------------------------
# HTTP agent settings:
# If you need to change how the proxy makes requests to other servers, such
# as when checking keys or forwarding users' requests to external services,
# you can configure an alternative HTTP agent. Otherwise the default OS settings
# will be used.
# The name of the network interface to use. The first external IPv4 address
# belonging to this interface will be used for outgoing requests.
# HTTP_AGENT_INTERFACE=enp0s3
# The URL of a proxy server to use. Supports SOCKS4, SOCKS5, HTTP, and HTTPS.
# Note that if your proxy server issues a self-signed certificate, you may need
# NODE_EXTRA_CA_CERTS set to the path to your certificate. You will need to set
# that variable in your environment, not in this file.
# HTTP_AGENT_PROXY_URL=http://test:test@127.0.0.1:8000
# Specifies the number of proxies or load balancers in front of the server.
# For Cloudflare or Hugging Face deployments, the default of 1 is correct.
# For any other deployments, please see config.ts as the correct configuration
# depends on your setup. Misconfiguring this value can result in problems
# accurately tracking IP addresses and enforcing rate limits.
# TRUSTED_PROXIES=1
# ------------------------------------------------------------------------------
# Secrets and keys:
@@ -187,24 +124,18 @@ NODE_ENV=production
# You can add multiple API keys by separating them with a comma.
# For AWS credentials, separate the access key ID, secret key, and region with a colon.
# For GCP credentials, separate the project ID, client email, region, and private key with a colon.
OPENAI_KEY=sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
ANTHROPIC_KEY=sk-ant-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
GOOGLE_AI_KEY=AIzaxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
# See `docs/aws-configuration.md` for more information, there may be additional steps required to set up AWS.
AWS_CREDENTIALS=myaccesskeyid:mysecretkey:us-east-1,anotheraccesskeyid:anothersecretkey:us-west-2
# See `docs/azure-configuration.md` for more information, there may be additional steps required to set up Azure.
AZURE_CREDENTIALS=azure-resource-name:deployment-id:api-key,another-azure-resource-name:another-deployment-id:another-api-key
GCP_CREDENTIALS=project-id:client-email:region:private-key
# With proxy_key gatekeeper, the password users must provide to access the API.
# PROXY_KEY=your-secret-key
# With user_token gatekeeper, the admin password used to manage users.
# ADMIN_KEY=your-very-secret-key
# Restrict access to the admin interface to specific IP addresses, specified
# as a comma-separated list of CIDR ranges.
# ADMIN_WHITELIST=0.0.0.0/0
# With firebase_rtdb gatekeeper storage, the Firebase project credentials.
# FIREBASE_KEY=xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
.gitignore
+1 -1
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@@ -7,5 +7,5 @@
build
greeting.md
node_modules
.windsurfrules
http-client.private.env.json
.prettierrc
+4 -3
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@@ -1,10 +1,11 @@
{
"plugins": ["prettier-plugin-ejs"],
"overrides": [
{
"files": "*.ejs",
"files": [
"*.ejs"
],
"options": {
"printWidth": 120,
"printWidth": 160,
"bracketSameLine": true
}
}
.windsurfrules
-33
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@@ -1,33 +0,0 @@
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.
CODEBASE_GUIDE.md
-321
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@@ -1,321 +0,0 @@
# 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.*
README.md
+36 -38
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@@ -1,20 +1,16 @@
# OAI Reverse Proxy - just a shitty fork
# OAI Reverse Proxy
Reverse proxy server for various LLM APIs.
### Table of Contents
<!-- TOC -->
* [OAI Reverse Proxy](#oai-reverse-proxy)
* [Table of Contents](#table-of-contents)
* [What is this?](#what-is-this)
* [Features](#features)
* [Usage Instructions](#usage-instructions)
* [Personal Use (single-user)](#personal-use-single-user)
* [Updating](#updating)
* [Local Development](#local-development)
* [Self-hosting](#self-hosting)
* [Building](#building)
* [Forking](#forking)
<!-- TOC -->
- [What is this?](#what-is-this)
- [Features](#features)
- [Usage Instructions](#usage-instructions)
- [Self-hosting](#self-hosting)
- [Alternatives](#alternatives)
- [Huggingface (outdated, not advised)](#huggingface-outdated-not-advised)
- [Render (outdated, not advised)](#render-outdated-not-advised)
- [Local Development](#local-development)
## What is this?
This project allows you to run a reverse proxy server for various LLM APIs.
@@ -23,8 +19,7 @@ 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/) (Claude4 is fucked, dont care)
- [x] [Vertex AI (GCP)](https://cloud.google.com/vertex-ai/)
- [x] [AWS Bedrock](https://aws.amazon.com/bedrock/)
- [x] [Google MakerSuite/Gemini API](https://ai.google.dev/)
- [x] [Azure OpenAI](https://azure.microsoft.com/en-us/products/ai-services/openai-service)
- [x] Translation from OpenAI-formatted prompts to any other API, including streaming responses
@@ -33,40 +28,43 @@ This project allows you to run a reverse proxy server for various LLM APIs.
- [x] Simple role-based permissions
- [x] Per-model token quotas
- [x] Temporary user accounts
- [x] Event audit logging
- [x] Optional full logging of prompts and completions
- [x] Prompt and completion logging
- [x] Abuse detection and prevention
- [x] IP address and user token model invocation rate limits
- [x] IP blacklists
- [x] Proof-of-work challenge for access by anonymous users
---
## Usage Instructions
If you'd like to run your own instance of this server, you'll need to deploy it somewhere and configure it with your API keys. A few easy options are provided below, though you can also deploy it to any other service you'd like if you know what you're doing and the service supports Node.js.
### Personal Use (single-user)
If you just want to run the proxy server to use yourself without hosting it for others:
1. Install [Node.js](https://nodejs.org/en/download/) >= 18.0.0
2. Clone this repository
3. Create a `.env` file in the root of the project and add your API keys. See the [.env.example](./.env.example) file for an example.
4. Install dependencies with `npm install`
5. Run `npm run build`
6. Run `npm start`
#### Updating
You must re-run `npm install` and `npm run build` whenever you pull new changes from the repository.
#### Local Development
Use `npm run start:dev` to run the proxy in development mode with watch mode enabled. Use `npm run type-check` to run the type checker across the project.
### Self-hosting
[See here for instructions on how to self-host the application on your own VPS or local machine and expose it to the internet for others to use.](./docs/self-hosting.md)
[See here for instructions on how to self-host the application on your own VPS or local machine.](./docs/self-hosting.md)
**Ensure you set the `TRUSTED_PROXIES` environment variable according to your deployment.** Refer to [.env.example](./.env.example) and [config.ts](./src/config.ts) for more information.
### Alternatives
Fiz and Sekrit are working on some alternative ways to deploy this conveniently. While I'm not involved in this effort beyond providing technical advice regarding my code, I'll link to their work here for convenience: [Sekrit's rentry](https://rentry.org/sekrit)
### Huggingface (outdated, not advised)
[See here for instructions on how to deploy to a Huggingface Space.](./docs/deploy-huggingface.md)
### Render (outdated, not advised)
[See here for instructions on how to deploy to Render.com.](./docs/deploy-render.md)
## Local Development
To run the proxy locally for development or testing, install Node.js >= 18.0.0 and follow the steps below.
1. Clone the repo
2. Install dependencies with `npm install`
3. Create a `.env` file in the root of the project and add your API keys. See the [.env.example](./.env.example) file for an example.
4. Start the server in development mode with `npm run start:dev`.
You can also use `npm run start:dev:tsc` to enable project-wide type checking at the cost of slower startup times. `npm run type-check` can be used to run type checking without starting the server.
## Building
To build the project, run `npm run build`. This will compile the TypeScript code to JavaScript and output it to the `build` directory. You should run this whenever you pull new changes from the repository.
To build the project, run `npm run build`. This will compile the TypeScript code to JavaScript and output it to the `build` directory.
Note that if you are trying to build the server on a very memory-constrained (<= 1GB) VPS, you may need to run the build with `NODE_OPTIONS=--max_old_space_size=2048 npm run build` to avoid running out of memory during the build process, assuming you have swap enabled. The application itself should run fine on a 512MB VPS for most reasonable traffic levels.
## Forking
If you are forking the repository on GitGud, you may wish to disable GitLab CI/CD or you will be spammed with emails about failed builds due not having any CI runners. You can do this by going to *Settings > General > Visibility, project features, permissions* and then disabling the "CI/CD" feature.
docker/render/Dockerfile
+2 -1
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@@ -17,8 +17,9 @@ ARG GREETING_URL
RUN if [ -n "$GREETING_URL" ]; then \
curl -sL "$GREETING_URL" > greeting.md; \
fi
COPY . .
COPY package*.json greeting.md* ./
RUN npm install
COPY . .
RUN npm run build
RUN --mount=type=secret,id=_env,dst=/etc/secrets/.env cat /etc/secrets/.env >> .env
EXPOSE 10000
docs/deploy-render.md
+1 -1
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@@ -1,6 +1,6 @@
# Deploy to Render.com
**⚠️ This method is no longer supported or recommended and may not work. Please use the [self-hosting instructions](./self-hosting.md) instead.**
**⚠️ This method is no longer recommended. Please use the [self-hosting instructions](./self-hosting.md) instead.**
Render.com offers a free tier that includes 750 hours of compute time per month. This is enough to run a single proxy instance 24/7. Instances shut down after 15 minutes without traffic but start up again automatically when a request is received. You can use something like https://app.checklyhq.com/ to ping your proxy every 15 minutes to keep it alive.
docs/gcp-configuration.md
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@@ -1,35 +0,0 @@
# Configuring the proxy for Vertex AI (GCP)
The proxy supports GCP models via the `/proxy/gcp/claude` endpoint. There are a few extra steps necessary to use GCP compared to the other supported APIs.
- [Setting keys](#setting-keys)
- [Setup Vertex AI](#setup-vertex-ai)
- [Supported model IDs](#supported-model-ids)
## Setting keys
Use the `GCP_CREDENTIALS` environment variable to set the GCP API keys.
Like other APIs, you can provide multiple keys separated by commas. Each GCP key, however, is a set of credentials including the project id, client email, region and private key. These are separated by a colon (`:`).
For example:
```
GCP_CREDENTIALS=my-first-project:xxx@yyy.com:us-east5:-----BEGIN PRIVATE KEY-----xxx-----END PRIVATE KEY-----,my-first-project2:xxx2@yyy.com:us-east5:-----BEGIN PRIVATE KEY-----xxx-----END PRIVATE KEY-----
```
## Setup Vertex AI
1. Go to [https://cloud.google.com/vertex-ai](https://cloud.google.com/vertex-ai) and sign up for a GCP account. ($150 free credits without credit card or $300 free credits with credit card, credits expire in 90 days)
2. Go to [https://console.cloud.google.com/marketplace/product/google/aiplatform.googleapis.com](https://console.cloud.google.com/marketplace/product/google/aiplatform.googleapis.com) to enable Vertex AI API.
3. Go to [https://console.cloud.google.com/vertex-ai](https://console.cloud.google.com/vertex-ai) and navigate to Model Garden to apply for access to the Claude models.
4. Create a [Service Account](https://console.cloud.google.com/projectselector/iam-admin/serviceaccounts/create?walkthrough_id=iam--create-service-account#step_index=1) , and make sure to grant the role of "Vertex AI User" or "Vertex AI Administrator".
5. On the service account page you just created, create a new key and select "JSON". The JSON file will be downloaded automatically.
6. The required credential is in the JSON file you just downloaded.
## Supported model IDs
Users can send these model IDs to the proxy to invoke the corresponding models.
- **Claude**
- `claude-3-haiku@20240307`
- `claude-3-sonnet@20240229`
- `claude-3-opus@20240229`
- `claude-3-5-sonnet@20240620`
docs/pow-captcha.md
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@@ -1,135 +0,0 @@
# Proof-of-work Verification
You can require users to complete a proof-of-work before they can access the
proxy. This can increase the cost of denial of service attacks and slow down
automated abuse.
When configured, users access the challenge UI and request a token. The server
sends a challenge to the client, which asks the user's browser to find a
solution to the challenge that meets a certain constraint (the difficulty
level). Once the user has found a solution, they can submit it to the server
and get a user token valid for a period you specify.
The proof-of-work challenge uses the argon2id hash function.
## Configuration
To enable proof-of-work verification, set the following environment variables:
```
GATEKEEPER=user_token
CAPTCHA_MODE=proof_of_work
# Validity of the token in hours
POW_TOKEN_HOURS=24
# Max number of IPs that can use a user_token issued via proof-of-work
POW_TOKEN_MAX_IPS=2
# The difficulty level of the proof-of-work challenge. You can use one of the
# predefined levels specified below, or you can specify a custom number of
# expected hash iterations.
POW_DIFFICULTY_LEVEL=low
# The time limit for solving the challenge, in minutes
POW_CHALLENGE_TIMEOUT=30
```
## Difficulty Levels
The difficulty level controls how long, on average, it will take for a user to
solve the proof-of-work challenge. Due to randomness, the actual time can very
significantly; lucky users may solve the challenge in a fraction of the average
time, while unlucky users may take much longer.
The difficulty level doesn't affect the speed of the hash function itself, only
the number of hashes that will need to be computed. Therefore, the time required
to complete the challenge scales linearly with the difficulty level's iteration
count.
You can adjust the difficulty level while the proxy is running from the admin
interface.
Be aware that there is a time limit for solving the challenge, by default set to
30 minutes. Above 'high' difficulty, you will probably need to increase the time
limit or it will be very hard for users with slow devices to find a solution
within the time limit.
### Low
- Average of 200 iterations required
- Default setting.
### Medium
- Average of 900 iterations required
### High
- Average of 1900 iterations required
### Extreme
- Average of 4000 iterations required
- Not recommended unless you are expecting very high levels of abuse
- May require increasing `POW_CHALLENGE_TIMEOUT`
### Custom
Setting `POW_DIFFICULTY_LEVEL` to an integer will use that number of iterations
as the difficulty level.
## Other challenge settings
- `POW_CHALLENGE_TIMEOUT`: The time limit for solving the challenge, in minutes.
Default is 30.
- `POW_TOKEN_HOURS`: The period of time for which a user token issued via proof-
of-work can be used. Default is 24 hours. Starts when the challenge is solved.
- `POW_TOKEN_MAX_IPS`: The maximum number of unique IPs that can use a single
user token issued via proof-of-work. Default is 2.
- `POW_TOKEN_PURGE_HOURS`: The period of time after which an expired user token
issued via proof-of-work will be removed from the database. Until it is
purged, users can refresh expired tokens by completing a half-difficulty
challenge. Default is 48 hours.
- `POW_MAX_TOKENS_PER_IP`: The maximum number of active user tokens that can
be associated with a single IP address. After this limit is reached, the
oldest token will be forcibly expired when a new token is issued. Set to 0
to disable this feature. Default is 0.
## Custom argon2id parameters
You can set custom argon2id parameters for the proof-of-work challenge.
Generally, you should not need to change these unless you have a specific
reason to do so.
The listed values are the defaults.
```
ARGON2_TIME_COST=8
ARGON2_MEMORY_KB=65536
ARGON2_PARALLELISM=1
ARGON2_HASH_LENGTH=32
```
Increasing parallelism will not do much except increase memory consumption for
both the client and server, because browser proof-of-work implementations are
single-threaded. It's better to increase the time cost if you want to increase
the difficulty.
Increasing memory too much may cause memory exhaustion on some mobile devices,
particularly on iOS due to the way Safari handles WebAssembly memory allocation.
## Tested hash rates
These were measured with the default argon2id parameters listed above. These
tests were not at all scientific so take them with a grain of salt.
Safari does not like large WASM memory usage, so concurrency is limited to 4 to
avoid overallocating memory on mobile WebKit browsers. Thermal throttling can
also significantly reduce hash rates on mobile devices.
- Intel Core i9-13900K (Chrome): 33-35 H/s
- Intel Core i9-13900K (Firefox): 29-32 H/s
- Intel Core i9-13900K (Chrome, in VM limited to 4 cores): 12.2 - 13.0 H/s
- iPad Pro (M2) (Safari, 6 workers): 8.0 - 10 H/s
- Thermal throttles early. 8 cores is normal concurrency, but unstable.
- iPhone 15 Pro Max (Safari): 4.0 - 4.6 H/s
- Samsung Galaxy S10e (Chrome): 3.6 - 3.8 H/s
- This is a 2019 phone almost matching an iPhone five years newer because of
bad Safari performance.
docs/user-management.md
-22
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@@ -12,8 +12,6 @@ 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`)
@@ -63,23 +61,3 @@ To use Firebase Realtime Database to persist user data, set the following enviro
8. Set `GATEKEEPER_STORE` to `firebase_rtdb` in your environment if you haven't already.
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.
You can provide a comma-separated list containing individual IPv4 or IPv6 addresses, or CIDR ranges.
To whitelist an entire IP range, use CIDR notation. For example, `192.168.0.1/24` would whitelist all addresses from `192.168.0.0` to `192.168.0.255`.
To disable the whitelist, set `ADMIN_WHITELIST=0.0.0.0/0,::0`, which will allow access from any IPv4 or IPv6 address. This is the default behavior.
package-lock.json
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package.json
+14 -27
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@@ -4,12 +4,10 @@
"description": "Reverse proxy for the OpenAI API",
"scripts": {
"build": "tsc && copyfiles -u 1 src/**/*.ejs build",
"database:migrate": "ts-node scripts/migrate.ts",
"postinstall": "patch-package",
"prepare": "husky install",
"start": "node --trace-deprecation --trace-warnings build/server.js",
"start": "node build/server.js",
"start:dev": "nodemon --watch src --exec ts-node --transpile-only src/server.ts",
"start:debug": "ts-node --inspect --transpile-only src/server.ts",
"start:replit": "tsc && node build/server.js",
"start:watch": "nodemon --require source-map-support/register build/server.js",
"type-check": "tsc --noEmit"
},
@@ -21,52 +19,42 @@
"dependencies": {
"@anthropic-ai/tokenizer": "^0.0.4",
"@aws-crypto/sha256-js": "^5.2.0",
"@huggingface/jinja": "^0.3.0",
"@node-rs/argon2": "^1.8.3",
"@smithy/eventstream-codec": "^2.1.3",
"@smithy/eventstream-serde-node": "^2.1.3",
"@smithy/protocol-http": "^3.2.1",
"@smithy/signature-v4": "^2.1.3",
"@smithy/types": "^2.10.1",
"@smithy/util-utf8": "^2.1.1",
"axios": "^1.7.4",
"better-sqlite3": "^10.0.0",
"axios": "^1.3.5",
"check-disk-space": "^3.4.0",
"cookie-parser": "^1.4.6",
"copyfiles": "^2.4.1",
"cors": "^2.8.5",
"csrf-csrf": "^2.3.0",
"dotenv": "^16.3.1",
"ejs": "^3.1.10",
"express": "^4.19.3",
"ejs": "^3.1.9",
"express": "^4.18.2",
"express-session": "^1.17.3",
"firebase-admin": "^12.5.0",
"glob": "^10.3.12",
"firebase-admin": "^11.10.1",
"googleapis": "^122.0.0",
"http-proxy": "1.18.1",
"http-proxy-middleware": "^3.0.2",
"ipaddr.js": "^2.1.0",
"http-proxy-middleware": "^3.0.0-beta.1",
"memorystore": "^1.6.7",
"multer": "^1.4.5-lts.1",
"node-schedule": "^2.1.1",
"patch-package": "^8.0.0",
"pino": "^8.11.0",
"pino-http": "^8.3.3",
"proxy-agent": "^6.4.0",
"sanitize-html": "^2.13.0",
"sharp": "^0.34.2",
"sanitize-html": "2.12.1",
"sharp": "^0.32.6",
"showdown": "^2.1.0",
"source-map-support": "^0.5.21",
"stream-json": "^1.8.0",
"tiktoken": "^1.0.10",
"tinyws": "^0.1.0",
"uuid": "^9.0.0",
"zlib": "^1.0.5",
"zod": "^3.22.3",
"zod-error": "^1.5.0"
},
"devDependencies": {
"@smithy/types": "^3.3.0",
"@types/better-sqlite3": "^7.6.10",
"@types/cookie-parser": "^1.4.3",
"@types/cors": "^2.8.13",
"@types/express": "^4.17.17",
@@ -78,19 +66,18 @@
"@types/stream-json": "^1.7.7",
"@types/uuid": "^9.0.1",
"concurrently": "^8.0.1",
"esbuild": "^0.25.5",
"esbuild": "^0.17.16",
"esbuild-register": "^3.4.2",
"husky": "^8.0.3",
"nodemon": "^3.0.1",
"pino-pretty": "^10.2.3",
"prettier": "^3.0.3",
"prettier-plugin-ejs": "^1.0.3",
"ts-node": "^10.9.1",
"typescript": "^5.4.2"
},
"overrides": {
"node-fetch@2.x": {
"whatwg-url": "14.x"
}
"google-gax": "^3.6.1",
"postcss": "^8.4.31",
"follow-redirects": "^1.15.4"
}
}
patches/README.md
-23
View File
@@ -1,23 +0,0 @@
# Patches
Contains monkey patches for certain packages, applied using `patch-package`.
## `http-proxy+1.18.1.patch`
Modifies the `http-proxy` package to work around an incompatibility with
body-parser and SOCKS5 proxies due to some esoteric stream handling behavior
when `socks-proxy-agent` is used instead of a generic http.Agent.
Modification involves adjusting the `buffer` property on ProxyServer's `options`
object to be a function that returns a stream instead of a stream itself. This
allows us to give it a function which produces a new Readable from the already-
parsed request body.
With the old implementation we would need to create an entirely new ProxyServer
instance for each request, which is not ideal under heavy load.
`http-proxy` hasn't been updated in six years so it's unlikely that this patch
will be broken by future updates, but it's stil pinned to 1.18.1 for now.
### See also
https://github.com/chimurai/http-proxy-middleware/issues/40
https://github.com/chimurai/http-proxy-middleware/issues/299
https://github.com/http-party/node-http-proxy/pull/1027
patches/http-proxy+1.18.1.patch
-13
View File
@@ -1,13 +0,0 @@
diff --git a/node_modules/http-proxy/lib/http-proxy/passes/web-incoming.js b/node_modules/http-proxy/lib/http-proxy/passes/web-incoming.js
index 7ae7355..c825c27 100644
--- a/node_modules/http-proxy/lib/http-proxy/passes/web-incoming.js
+++ b/node_modules/http-proxy/lib/http-proxy/passes/web-incoming.js
@@ -167,7 +167,7 @@ module.exports = {
}
}
- (options.buffer || req).pipe(proxyReq);
+ (options.buffer(req) || req).pipe(proxyReq);
proxyReq.on('response', function(proxyRes) {
if(server) { server.emit('proxyRes', proxyRes, req, res); }
public/css/reset.css
-349
View File
@@ -1,349 +0,0 @@
/*! normalize.css v8.0.1 | MIT License | github.com/necolas/normalize.css */
/* Document
========================================================================== */
/**
* 1. Correct the line height in all browsers.
* 2. Prevent adjustments of font size after orientation changes in iOS.
*/
html {
line-height: 1.15; /* 1 */
-webkit-text-size-adjust: 100%; /* 2 */
}
/* Sections
========================================================================== */
/**
* Remove the margin in all browsers.
*/
body {
margin: 0;
}
/**
* Render the `main` element consistently in IE.
*/
main {
display: block;
}
/**
* Correct the font size and margin on `h1` elements within `section` and
* `article` contexts in Chrome, Firefox, and Safari.
*/
h1 {
font-size: 2em;
margin: 0.67em 0;
}
/* Grouping content
========================================================================== */
/**
* 1. Add the correct box sizing in Firefox.
* 2. Show the overflow in Edge and IE.
*/
hr {
box-sizing: content-box; /* 1 */
height: 0; /* 1 */
overflow: visible; /* 2 */
}
/**
* 1. Correct the inheritance and scaling of font size in all browsers.
* 2. Correct the odd `em` font sizing in all browsers.
*/
pre {
font-family: monospace, monospace; /* 1 */
font-size: 1em; /* 2 */
}
/* Text-level semantics
========================================================================== */
/**
* Remove the gray background on active links in IE 10.
*/
a {
background-color: transparent;
}
/**
* 1. Remove the bottom border in Chrome 57-
* 2. Add the correct text decoration in Chrome, Edge, IE, Opera, and Safari.
*/
abbr[title] {
border-bottom: none; /* 1 */
text-decoration: underline; /* 2 */
text-decoration: underline dotted; /* 2 */
}
/**
* Add the correct font weight in Chrome, Edge, and Safari.
*/
b,
strong {
font-weight: bolder;
}
/**
* 1. Correct the inheritance and scaling of font size in all browsers.
* 2. Correct the odd `em` font sizing in all browsers.
*/
code,
kbd,
samp {
font-family: monospace, monospace; /* 1 */
font-size: 1em; /* 2 */
}
/**
* Add the correct font size in all browsers.
*/
small {
font-size: 80%;
}
/**
* Prevent `sub` and `sup` elements from affecting the line height in
* all browsers.
*/
sub,
sup {
font-size: 75%;
line-height: 0;
position: relative;
vertical-align: baseline;
}
sub {
bottom: -0.25em;
}
sup {
top: -0.5em;
}
/* Embedded content
========================================================================== */
/**
* Remove the border on images inside links in IE 10.
*/
img {
border-style: none;
}
/* Forms
========================================================================== */
/**
* 1. Change the font styles in all browsers.
* 2. Remove the margin in Firefox and Safari.
*/
button,
input,
optgroup,
select,
textarea {
font-family: inherit; /* 1 */
font-size: 100%; /* 1 */
line-height: 1.15; /* 1 */
margin: 0; /* 2 */
}
/**
* Show the overflow in IE.
* 1. Show the overflow in Edge.
*/
button,
input { /* 1 */
overflow: visible;
}
/**
* Remove the inheritance of text transform in Edge, Firefox, and IE.
* 1. Remove the inheritance of text transform in Firefox.
*/
button,
select { /* 1 */
text-transform: none;
}
/**
* Correct the inability to style clickable types in iOS and Safari.
*/
button,
[type="button"],
[type="reset"],
[type="submit"] {
-webkit-appearance: button;
}
/**
* Remove the inner border and padding in Firefox.
*/
button::-moz-focus-inner,
[type="button"]::-moz-focus-inner,
[type="reset"]::-moz-focus-inner,
[type="submit"]::-moz-focus-inner {
border-style: none;
padding: 0;
}
/**
* Restore the focus styles unset by the previous rule.
*/
button:-moz-focusring,
[type="button"]:-moz-focusring,
[type="reset"]:-moz-focusring,
[type="submit"]:-moz-focusring {
outline: 1px dotted ButtonText;
}
/**
* Correct the padding in Firefox.
*/
fieldset {
padding: 0.35em 0.75em 0.625em;
}
/**
* 1. Correct the text wrapping in Edge and IE.
* 2. Correct the color inheritance from `fieldset` elements in IE.
* 3. Remove the padding so developers are not caught out when they zero out
* `fieldset` elements in all browsers.
*/
legend {
box-sizing: border-box; /* 1 */
color: inherit; /* 2 */
display: table; /* 1 */
max-width: 100%; /* 1 */
padding: 0; /* 3 */
white-space: normal; /* 1 */
}
/**
* Add the correct vertical alignment in Chrome, Firefox, and Opera.
*/
progress {
vertical-align: baseline;
}
/**
* Remove the default vertical scrollbar in IE 10+.
*/
textarea {
overflow: auto;
}
/**
* 1. Add the correct box sizing in IE 10.
* 2. Remove the padding in IE 10.
*/
[type="checkbox"],
[type="radio"] {
box-sizing: border-box; /* 1 */
padding: 0; /* 2 */
}
/**
* Correct the cursor style of increment and decrement buttons in Chrome.
*/
[type="number"]::-webkit-inner-spin-button,
[type="number"]::-webkit-outer-spin-button {
height: auto;
}
/**
* 1. Correct the odd appearance in Chrome and Safari.
* 2. Correct the outline style in Safari.
*/
[type="search"] {
-webkit-appearance: textfield; /* 1 */
outline-offset: -2px; /* 2 */
}
/**
* Remove the inner padding in Chrome and Safari on macOS.
*/
[type="search"]::-webkit-search-decoration {
-webkit-appearance: none;
}
/**
* 1. Correct the inability to style clickable types in iOS and Safari.
* 2. Change font properties to `inherit` in Safari.
*/
::-webkit-file-upload-button {
-webkit-appearance: button; /* 1 */
font: inherit; /* 2 */
}
/* Interactive
========================================================================== */
/*
* Add the correct display in Edge, IE 10+, and Firefox.
*/
details {
display: block;
}
/*
* Add the correct display in all browsers.
*/
summary {
display: list-item;
}
/* Misc
========================================================================== */
/**
* Add the correct display in IE 10+.
*/
template {
display: none;
}
/**
* Add the correct display in IE 10.
*/
[hidden] {
display: none;
}
public/css/sakura-dark.css
-231
View File
@@ -1,231 +0,0 @@
/* modified https://github.com/oxalorg/sakura */
html {
font-size: 62.5%;
font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto,
"Helvetica Neue", Arial, "Noto Sans", sans-serif;
}
body {
font-size: 1.8rem;
line-height: 1.618;
max-width: 38em;
margin: auto;
color: #c9c9c9;
background-color: #222222;
padding: 13px;
}
@media (max-width: 684px) {
body {
font-size: 1.53rem;
}
}
@media (max-width: 382px) {
body {
font-size: 1.35rem;
}
}
h1,
h2,
h3,
h4,
h5,
h6 {
line-height: 1.1;
font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto,
"Helvetica Neue", Arial, "Noto Sans", sans-serif;
font-weight: 700;
margin-top: 3rem;
margin-bottom: 1.5rem;
overflow-wrap: break-word;
word-wrap: break-word;
-ms-word-break: break-all;
word-break: break-word;
}
h1 {
font-size: 2.35em;
}
h2 {
font-size: 2em;
}
h3 {
font-size: 1.75em;
}
h4 {
font-size: 1.5em;
}
h5 {
font-size: 1.25em;
}
h6 {
font-size: 1em;
}
p {
margin-top: 0px;
margin-bottom: 2.5rem;
}
small,
sub,
sup {
font-size: 75%;
}
hr {
border-color: #ffffff;
}
a {
text-decoration: none;
color: #ffffff;
}
a:visited {
color: #e6e6e6;
}
a:hover {
color: #c9c9c9;
text-decoration: underline;
}
ul {
padding-left: 1.4em;
margin-top: 0px;
margin-bottom: 2.5rem;
}
li {
margin-bottom: 0.4em;
}
blockquote {
margin-left: 0px;
margin-right: 0px;
padding-left: 1em;
padding-top: 0.8em;
padding-bottom: 0.8em;
padding-right: 0.8em;
border-left: 5px solid #ffffff;
margin-bottom: 2.5rem;
background-color: #4a4a4a;
}
blockquote p {
margin-bottom: 0;
}
img,
video {
height: auto;
max-width: 100%;
margin-top: 0px;
margin-bottom: 2.5rem;
}
pre {
background-color: #4a4a4a;
display: block;
padding: 1em;
overflow-x: auto;
margin-top: 0px;
margin-bottom: 2.5rem;
font-size: 0.9em;
}
code,
kbd,
samp {
font-size: 0.9em;
padding: 0 0.5em;
background-color: #4a4a4a;
white-space: pre-wrap;
}
pre > code {
padding: 0;
background-color: transparent;
white-space: pre;
font-size: 1em;
}
table {
text-align: justify;
width: 100%;
border-collapse: collapse;
margin-bottom: 2rem;
}
td,
th {
padding: 0.5em;
border-bottom: 1px solid #4a4a4a;
}
input,
textarea {
border: 1px solid #c9c9c9;
}
input:focus,
textarea:focus {
border: 1px solid #ffffff;
}
textarea {
width: 100%;
}
.button,
button,
input[type="submit"],
input[type="reset"],
input[type="button"],
input[type="file"]::file-selector-button {
display: inline-block;
padding: 5px 10px;
text-align: center;
text-decoration: none;
white-space: nowrap;
background-color: #ffffff;
color: #222222;
border-radius: 1px;
border: 1px solid #ffffff;
cursor: pointer;
box-sizing: border-box;
}
.button[disabled],
button[disabled],
input[type="submit"][disabled],
input[type="reset"][disabled],
input[type="button"][disabled],
input[type="file"][disabled] {
cursor: default;
opacity: 0.5;
}
.button:hover,
button:hover,
input[type="submit"]:hover,
input[type="reset"]:hover,
input[type="button"]:hover,
input[type="file"]::file-selector-button:hover {
background-color: #c9c9c9;
color: #222222;
outline: 0;
}
.button:focus-visible,
button:focus-visible,
input[type="submit"]:focus-visible,
input[type="reset"]:focus-visible,
input[type="button"]:focus-visible,
input[type="file"]::file-selector-button:focus-visible {
outline-style: solid;
outline-width: 2px;
}
textarea,
select,
input {
color: #c9c9c9;
padding: 6px 10px;
margin-bottom: 10px;
background-color: #4a4a4a;
border: 1px solid #4a4a4a;
border-radius: 4px;
box-shadow: none;
box-sizing: border-box;
}
textarea:focus,
select:focus,
input:focus {
border: 1px solid #ffffff;
outline: 0;
}
input[type="checkbox"]:focus {
outline: 1px dotted #ffffff;
}
label,
legend,
fieldset {
display: block;
margin-bottom: 0.5rem;
font-weight: 600;
}
public/css/sakura.css
-237
View File
@@ -1,237 +0,0 @@
/* modified https://github.com/oxalorg/sakura */
:root {
--accent-color: #4a4a4a;
--accent-color-hover: #5a5a5a;
--link-color: #58739c;
--link-visted-color: #6f5e6f;
}
html {
font-size: 62.5%;
font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto,
"Helvetica Neue", Arial, "Noto Sans", sans-serif;
}
body {
font-size: 1.8rem;
line-height: 1.618;
max-width: 38em;
margin: auto;
color: #4a4a4a;
background-color: #f9f9f9;
padding: 13px;
}
@media (max-width: 684px) {
body {
font-size: 1.53rem;
}
}
@media (max-width: 382px) {
body {
font-size: 1.35rem;
}
}
h1,
h2,
h3,
h4,
h5,
h6 {
line-height: 1.1;
font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto,
"Helvetica Neue", Arial, "Noto Sans", sans-serif;
font-weight: 700;
margin-top: 3rem;
margin-bottom: 1.5rem;
overflow-wrap: break-word;
word-wrap: break-word;
-ms-word-break: break-all;
word-break: break-word;
}
h1 {
font-size: 2.35em;
}
h2 {
font-size: 2em;
}
h3 {
font-size: 1.75em;
}
h4 {
font-size: 1.5em;
}
h5 {
font-size: 1.25em;
}
h6 {
font-size: 1em;
}
p {
margin-top: 0;
margin-bottom: 2.5rem;
}
small,
sub,
sup {
font-size: 75%;
}
hr {
border-color: var(--accent-color);
}
a {
text-decoration: none;
color: var(--link-color);
}
a:visited {
color: var(--link-visted-color);
}
a:hover {
color: var(--accent-color-hover);
text-decoration: underline;
}
ul {
padding-left: 1.4em;
margin-top: 0;
margin-bottom: 2.5rem;
}
li {
margin-bottom: 0.4em;
}
blockquote {
margin-left: 0;
margin-right: 0;
padding-left: 1em;
padding-top: 0.8em;
padding-bottom: 0.8em;
padding-right: 0.8em;
border-left: 5px solid var(--accent-color);
margin-bottom: 2.5rem;
background-color: #f1f1f1;
}
blockquote p {
margin-bottom: 0;
}
img,
video {
height: auto;
max-width: 100%;
margin-top: 0;
margin-bottom: 2.5rem;
}
pre {
background-color: #f1f1f1;
display: block;
padding: 1em;
overflow-x: auto;
margin-top: 0;
margin-bottom: 2.5rem;
font-size: 0.9em;
}
code,
kbd,
samp {
font-size: 0.9em;
padding: 0 0.5em;
background-color: #f1f1f1;
white-space: pre-wrap;
}
pre > code {
padding: 0;
background-color: transparent;
white-space: pre;
font-size: 1em;
}
table {
text-align: justify;
width: 100%;
border-collapse: collapse;
margin-bottom: 2rem;
}
td,
th {
padding: 0.5em;
border-bottom: 1px solid #f1f1f1;
}
input,
textarea {
border: 1px solid #4a4a4a;
}
input:focus,
textarea:focus {
border: 1px solid var(--accent-color);
}
textarea {
width: 100%;
}
.button,
button,
input[type="submit"],
input[type="reset"],
input[type="button"],
input[type="file"]::file-selector-button {
display: inline-block;
padding: 5px 10px;
text-align: center;
text-decoration: none;
white-space: nowrap;
background-color: var(--accent-color);
color: #f9f9f9;
border-radius: 2px;
border: 1px solid var(--accent-color);
cursor: pointer;
box-sizing: border-box;
}
.button[disabled],
button[disabled],
input[type="submit"][disabled],
input[type="reset"][disabled],
input[type="button"][disabled],
input[type="file"][disabled] {
cursor: default;
opacity: 0.5;
}
.button:hover,
button:hover,
input[type="submit"]:hover,
input[type="reset"]:hover,
input[type="button"]:hover,
input[type="file"]::file-selector-button:hover {
background-color: var(--accent-color-hover);
color: #f9f9f9;
outline: 0;
}
.button:focus-visible,
button:focus-visible,
input[type="submit"]:focus-visible,
input[type="reset"]:focus-visible,
input[type="button"]:focus-visible,
input[type="file"]::file-selector-button:focus-visible {
outline-style: solid;
outline-width: 2px;
}
textarea,
select,
input {
color: #4a4a4a;
padding: 6px 10px;
margin-bottom: 10px;
background-color: #f1f1f1;
border: 1px solid #f1f1f1;
border-radius: 4px;
box-shadow: none;
box-sizing: border-box;
}
textarea:focus,
select:focus,
input:focus {
border: 1px solid var(--accent-color);
outline: 0;
}
input[type="checkbox"]:focus {
outline: 1px dotted var(--accent-color);
}
label,
legend,
fieldset {
display: block;
margin-bottom: 0.5rem;
font-weight: 600;
}
public/js/hash-worker.js
-120
View File
@@ -1,120 +0,0 @@
importScripts(
"https://cdn.jsdelivr.net/npm/hash-wasm@4.11.0/dist/argon2.umd.min.js"
);
let active = false;
let nonce = 0;
let signature = "";
let lastNotify = 0;
let hashesSinceLastNotify = 0;
let params = {
salt: null,
hashLength: 0,
iterations: 0,
memorySize: 0,
parallelism: 0,
targetValue: BigInt(0),
safariFix: false,
};
self.onmessage = async (event) => {
const { data } = event;
switch (data.type) {
case "stop":
active = false;
self.postMessage({ type: "paused", hashes: hashesSinceLastNotify });
return;
case "start":
active = true;
signature = data.signature;
nonce = data.nonce;
const c = data.challenge;
const salt = new Uint8Array(c.s.length / 2);
for (let i = 0; i < c.s.length; i += 2) {
salt[i / 2] = parseInt(c.s.slice(i, i + 2), 16);
}
params = {
salt: salt,
hashLength: c.hl,
iterations: c.t,
memorySize: c.m,
parallelism: c.p,
targetValue: BigInt(c.d.slice(0, -1)),
safariFix: data.isMobileWebkit,
};
console.log("Started", params);
self.postMessage({ type: "started" });
setTimeout(solve, 0);
break;
}
};
const doHash = async (password) => {
const { salt, hashLength, iterations, memorySize, parallelism } = params;
return await self.hashwasm.argon2id({
password,
salt,
hashLength,
iterations,
memorySize,
parallelism,
});
};
const checkHash = (hash) => {
const { targetValue } = params;
const hashValue = BigInt(`0x${hash}`);
return hashValue <= targetValue;
};
const solve = async () => {
if (!active) {
console.log("Stopped solver", nonce);
return;
}
// Safari WASM doesn't like multiple calls in one worker
const batchSize = 1;
const batch = [];
for (let i = 0; i < batchSize; i++) {
batch.push(nonce++);
}
try {
const results = await Promise.all(
batch.map(async (nonce) => {
const hash = await doHash(String(nonce));
return { hash, nonce };
})
);
hashesSinceLastNotify += batchSize;
const solution = results.find(({ hash }) => checkHash(hash));
if (solution) {
console.log("Solution found", solution, params.salt);
self.postMessage({ type: "solved", nonce: solution.nonce });
active = false;
} else {
if (Date.now() - lastNotify >= 500) {
console.log("Last nonce", nonce, "Hashes", hashesSinceLastNotify);
self.postMessage({ type: "progress", hashes: hashesSinceLastNotify });
lastNotify = Date.now();
hashesSinceLastNotify = 0;
}
setTimeout(solve, 10);
}
} catch (error) {
console.error("Error", error);
const stack = error.stack;
const debug = {
stack,
lastNonce: nonce,
targetValue: params.targetValue,
};
self.postMessage({ type: "error", error: error.message, debug });
active = false;
}
};
scripts/migrate.ts
-39
View File
@@ -1,39 +0,0 @@
import Database from "better-sqlite3";
import { DATABASE_VERSION, migrateDatabase } from "../src/shared/database";
import { logger } from "../src/logger";
import { config } from "../src/config";
const log = logger.child({ module: "scripts/migrate" });
async function runMigration() {
let targetVersion = Number(process.argv[2]) || undefined;
if (!targetVersion) {
log.info("Enter target version or leave empty to use the latest version.");
process.stdin.resume();
process.stdin.setEncoding("utf8");
const input = await new Promise<string>((resolve) => {
process.stdin.on("data", (text) => {
resolve((String(text) || "").trim());
});
});
process.stdin.pause();
targetVersion = Number(input);
if (!targetVersion) {
targetVersion = DATABASE_VERSION;
}
}
const db = new Database(config.sqliteDataPath, {
verbose: (msg, ...args) => log.debug({ args }, String(msg)),
});
const currentVersion = db.pragma("user_version", { simple: true });
log.info({ currentVersion, targetVersion }, "Running migrations.");
migrateDatabase(targetVersion, db);
}
runMigration().catch((error) => {
log.error(error, "Migration failed.");
process.exit(1);
});
scripts/oai-reverse-proxy.http
-33
View File
@@ -230,39 +230,6 @@ Content-Type: application/json
]
}
###
# @name Proxy / GCP Claude -- Native Completion
POST {{proxy-host}}/proxy/gcp/claude/v1/complete
Authorization: Bearer {{proxy-key}}
anthropic-version: 2023-01-01
Content-Type: application/json
{
"model": "claude-v2",
"max_tokens_to_sample": 10,
"temperature": 0,
"stream": true,
"prompt": "What is genshin impact\n\n:Assistant:"
}
###
# @name Proxy / GCP Claude -- OpenAI-to-Anthropic API Translation
POST {{proxy-host}}/proxy/gcp/claude/chat/completions
Authorization: Bearer {{proxy-key}}
Content-Type: application/json
{
"model": "gpt-3.5-turbo",
"max_tokens": 50,
"stream": true,
"messages": [
{
"role": "user",
"content": "What is genshin impact?"
}
]
}
###
# @name Proxy / Azure OpenAI -- Native Chat Completions
POST {{proxy-host}}/proxy/azure/openai/chat/completions
scripts/seed-events.ts
-102
View File
@@ -1,102 +0,0 @@
import Database from "better-sqlite3";
import { v4 as uuidv4 } from "uuid";
import { config } from "../src/config";
function generateRandomIP() {
return (
Math.floor(Math.random() * 255) +
"." +
Math.floor(Math.random() * 255) +
"." +
Math.floor(Math.random() * 255) +
"." +
Math.floor(Math.random() * 255)
);
}
function generateRandomDate() {
const end = new Date();
const start = new Date(end);
start.setDate(end.getDate() - 90);
const randomDate = new Date(
start.getTime() + Math.random() * (end.getTime() - start.getTime())
);
return randomDate.toISOString();
}
function generateMockSHA256() {
const characters = 'abcdef0123456789';
let hash = '';
for (let i = 0; i < 64; i++) {
const randomIndex = Math.floor(Math.random() * characters.length);
hash += characters[randomIndex];
}
return hash;
}
function getRandomModelFamily() {
const modelFamilies = [
"turbo",
"gpt4",
"gpt4-32k",
"gpt4-turbo",
"claude",
"claude-opus",
"gemini-pro",
"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",
"dall-e",
"azure-dall-e",
];
return modelFamilies[Math.floor(Math.random() * modelFamilies.length)];
}
(async () => {
const db = new Database(config.sqliteDataPath);
const numRows = 100;
const insertStatement = db.prepare(`
INSERT INTO events (type, ip, date, model, family, hashes, userToken, inputTokens, outputTokens)
VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?)
`);
const users = Array.from({ length: 10 }, () => uuidv4());
function getRandomUser() {
return users[Math.floor(Math.random() * users.length)];
}
const transaction = db.transaction(() => {
for (let i = 0; i < numRows; i++) {
insertStatement.run(
"chat_completion",
generateRandomIP(),
generateRandomDate(),
getRandomModelFamily() + "-" + Math.floor(Math.random() * 100),
getRandomModelFamily(),
Array.from(
{ length: Math.floor(Math.random() * 10) },
generateMockSHA256
).join(","),
getRandomUser(),
Math.floor(Math.random() * 500),
Math.floor(Math.random() * 6000)
);
}
});
transaction();
console.log(`Inserted ${numRows} rows into the events table.`);
db.close();
})();
scripts/test-aws-signing.ts
-118
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@@ -1,118 +0,0 @@
// uses the aws sdk to sign a request, then uses axios to send it to the bedrock REST API manually
import axios from "axios";
import { Sha256 } from "@aws-crypto/sha256-js";
import { SignatureV4 } from "@smithy/signature-v4";
import { HttpRequest } from "@smithy/protocol-http";
const AWS_ACCESS_KEY_ID = process.env.AWS_ACCESS_KEY_ID!;
const AWS_SECRET_ACCESS_KEY = process.env.AWS_SECRET_ACCESS_KEY!;
// Copied from amazon bedrock docs
// List models
// ListFoundationModels
// Service: Amazon Bedrock
// List of Bedrock foundation models that you can use. For more information, see Foundation models in the
// Bedrock User Guide.
// Request Syntax
// GET /foundation-models?
// byCustomizationType=byCustomizationType&byInferenceType=byInferenceType&byOutputModality=byOutputModality&byProvider=byProvider
// HTTP/1.1
// URI Request Parameters
// The request uses the following URI parameters.
// byCustomizationType (p. 38)
// List by customization type.
// Valid Values: FINE_TUNING
// byInferenceType (p. 38)
// List by inference type.
// Valid Values: ON_DEMAND | PROVISIONED
// byOutputModality (p. 38)
// List by output modality type.
// Valid Values: TEXT | IMAGE | EMBEDDING
// byProvider (p. 38)
// A Bedrock model provider.
// Pattern: ^[a-z0-9-]{1,63}$
// Request Body
// The request does not have a request body
// Run inference on a text model
// Send an invoke request to run inference on a Titan Text G1 - Express model. We set the accept
// parameter to accept any content type in the response.
// POST https://bedrock.us-east-1.amazonaws.com/model/amazon.titan-text-express-v1/invoke
// -H accept: */*
// -H content-type: application/json
// Payload
// {"inputText": "Hello world"}
// Example response
// Response for the above request.
// -H content-type: application/json
// Payload
// <the model response>
const AMZ_REGION = "us-east-1";
const AMZ_HOST = "invoke-bedrock.us-east-1.amazonaws.com";
async function listModels() {
const httpRequest = new HttpRequest({
method: "GET",
protocol: "https:",
hostname: AMZ_HOST,
path: "/foundation-models",
headers: { ["Host"]: AMZ_HOST },
});
const signedRequest = await signRequest(httpRequest);
const response = await axios.get(
`https://${signedRequest.hostname}${signedRequest.path}`,
{ headers: signedRequest.headers }
);
console.log(response.data);
}
async function invokeModel() {
const model = "anthropic.claude-v1";
const httpRequest = new HttpRequest({
method: "POST",
protocol: "https:",
hostname: AMZ_HOST,
path: `/model/${model}/invoke`,
headers: {
["Host"]: AMZ_HOST,
["accept"]: "*/*",
["content-type"]: "application/json",
},
body: JSON.stringify({
temperature: 0.5,
prompt: "\n\nHuman:Hello world\n\nAssistant:",
max_tokens_to_sample: 10,
}),
});
console.log("httpRequest", httpRequest);
const signedRequest = await signRequest(httpRequest);
const response = await axios.post(
`https://${signedRequest.hostname}${signedRequest.path}`,
signedRequest.body,
{ headers: signedRequest.headers }
);
console.log(response.status);
console.log(response.headers);
console.log(response.data);
console.log("full url", response.request.res.responseUrl);
}
async function signRequest(request: HttpRequest) {
const signer = new SignatureV4({
sha256: Sha256,
credentials: {
accessKeyId: AWS_ACCESS_KEY_ID,
secretAccessKey: AWS_SECRET_ACCESS_KEY,
},
region: AMZ_REGION,
service: "bedrock",
});
return await signer.sign(request, { signingDate: new Date() });
}
// listModels();
// invokeModel();
scripts/test-queue.js
-53
View File
@@ -1,53 +0,0 @@
const axios = require("axios");
function randomInteger(max) {
return Math.floor(Math.random() * max + 1);
}
async function testQueue() {
const requests = Array(10).fill(undefined).map(async function() {
const maxTokens = randomInteger(2000);
const headers = {
"Authorization": "Bearer test",
"Content-Type": "application/json",
"X-Forwarded-For": `${randomInteger(255)}.${randomInteger(255)}.${randomInteger(255)}.${randomInteger(255)}`,
};
const payload = {
model: "gpt-4o-mini-2024-07-18",
max_tokens: 20 + maxTokens,
stream: false,
messages: [{role: "user", content: "You are being benchmarked regarding your reliability at outputting exact, machine-comprehensible data. Output the sentence \"The quick brown fox jumps over the lazy dog.\" Do not precede it with quotemarks or any form of preamble, and do not output anything after the sentence."}],
temperature: 0,
};
try {
const response = await axios.post(
"http://localhost:7860/proxy/openai/v1/chat/completions",
payload,
{ headers }
);
if (response.status !== 200) {
console.error(`Request {$maxTokens} finished with status code ${response.status} and response`, response.data);
return;
}
const content = response.data.choices[0].message.content;
console.log(
`Request ${maxTokens} `,
content === "The quick brown fox jumps over the lazy dog." ? "OK" : `mangled: ${content}`
);
} catch (error) {
const msg = error.response;
console.error(`Error in req ${maxTokens}:`, error.message, msg || "");
}
});
await Promise.all(requests);
console.log("All requests finished");
}
testQueue();
src/admin/api/events.ts
-49
View File
@@ -1,49 +0,0 @@
import { Router } from "express";
import { z } from "zod";
import { encodeCursor, decodeCursor } from "../../shared/utils";
import { eventsRepo } from "../../shared/database/repos/event";
const router = Router();
/**
* Returns events for the given user token.
* GET /admin/events/:token
* @query first - The number of events to return.
* @query after - The cursor to start returning events from (exclusive).
*/
router.get("/:token", (req, res) => {
const schema = z.object({
token: z.string(),
first: z.coerce.number().int().positive().max(200).default(25),
after: z
.string()
.optional()
.transform((v) => {
try {
return decodeCursor(v);
} catch {
return null;
}
})
.nullable(),
sort: z.string().optional(),
});
const args = schema.safeParse({ ...req.params, ...req.query });
if (!args.success) {
return res.status(400).json({ error: args.error });
}
const data = eventsRepo
.getUserEvents(args.data.token, {
limit: args.data.first,
cursor: args.data.after,
})
.map((e) => ({ node: e, cursor: encodeCursor(e.date) }));
res.json({
data,
endCursor: data[data.length - 1]?.cursor,
});
});
export { router as eventsApiRouter };
src/admin/routes.ts
+4 -57
View File
@@ -1,32 +1,17 @@
import express, { Router } from "express";
import { createWhitelistMiddleware } from "../shared/cidr";
import { authorize } from "./auth";
import { HttpError } from "../shared/errors";
import { injectCsrfToken, checkCsrfToken } from "../shared/inject-csrf";
import { injectLocals } from "../shared/inject-locals";
import { withSession } from "../shared/with-session";
import { config } from "../config";
import { injectCsrfToken, checkCsrfToken } from "../shared/inject-csrf";
import { renderPage } from "../info-page";
import { buildInfo } from "../service-info";
import { authorize } from "./auth";
import { loginRouter } from "./login";
import { eventsApiRouter } from "./api/events";
import { usersApiRouter } from "./api/users";
import { usersApiRouter as apiRouter } from "./api/users";
import { usersWebRouter as webRouter } from "./web/manage";
import { logger } from "../logger";
import { keyPool } from "../shared/key-management";
const adminRouter = Router();
const whitelist = createWhitelistMiddleware(
"ADMIN_WHITELIST",
config.adminWhitelist
);
if (!whitelist.ranges.length && config.adminKey?.length) {
logger.error("ADMIN_WHITELIST is empty. No admin requests will be allowed. Set 0.0.0.0/0 to allow all.");
}
adminRouter.use(whitelist);
adminRouter.use(
express.json({ limit: "20mb" }),
express.urlencoded({ extended: true, limit: "20mb" })
@@ -34,45 +19,7 @@ adminRouter.use(
adminRouter.use(withSession);
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("/users", authorize({ via: "header" }), apiRouter);
adminRouter.use(checkCsrfToken);
adminRouter.use(injectLocals);
src/admin/web/manage.ts
+13 -273
View File
@@ -1,5 +1,4 @@
import { Router } from "express";
import ipaddr from "ipaddr.js";
import multer from "multer";
import { z } from "zod";
import { config } from "../../config";
@@ -16,8 +15,6 @@ import {
UserTokenCounts,
} from "../../shared/users/schema";
import { getLastNImages } from "../../shared/file-storage/image-history";
import { blacklists, parseCidrs, whitelists } from "../../shared/cidr";
import { invalidatePowChallenges } from "../../user/web/pow-captcha";
const router = Router();
@@ -43,74 +40,6 @@ router.get("/create-user", (req, res) => {
});
});
router.get("/anti-abuse", (_req, res) => {
const wl = [...whitelists.entries()];
const bl = [...blacklists.entries()];
res.render("admin_anti-abuse", {
captchaMode: config.captchaMode,
difficulty: config.powDifficultyLevel,
whitelists: wl.map((w) => ({
name: w[0],
mode: "whitelist",
ranges: w[1].ranges,
})),
blacklists: bl.map((b) => ({
name: b[0],
mode: "blacklist",
ranges: b[1].ranges,
})),
});
});
router.post("/cidr", (req, res) => {
const body = req.body;
const valid = z
.object({
action: z.enum(["add", "remove"]),
mode: z.enum(["whitelist", "blacklist"]),
name: z.string().min(1),
mask: z.string().min(1),
})
.safeParse(body);
if (!valid.success) {
throw new HttpError(
400,
valid.error.issues.flatMap((issue) => issue.message).join(", ")
);
}
const { mode, name, mask } = valid.data;
const list = (mode === "whitelist" ? whitelists : blacklists).get(name);
if (!list) {
throw new HttpError(404, "List not found");
}
if (valid.data.action === "remove") {
const newRanges = new Set(list.ranges);
newRanges.delete(mask);
list.updateRanges([...newRanges]);
req.session.flash = {
type: "success",
message: `${mode} ${name} updated`,
};
return res.redirect("/admin/manage/anti-abuse");
} else if (valid.data.action === "add") {
const result = parseCidrs(mask);
if (result.length === 0) {
throw new HttpError(400, "Invalid CIDR mask");
}
const newRanges = new Set([...list.ranges, mask]);
list.updateRanges([...newRanges]);
req.session.flash = {
type: "success",
message: `${mode} ${name} updated`,
};
return res.redirect("/admin/manage/anti-abuse");
}
});
router.post("/create-user", (req, res) => {
const body = req.body;
@@ -132,11 +61,10 @@ router.post("/create-user", (req, res) => {
)
.transform((data: any) => {
const expiresAt = Date.now() + data.temporaryUserDuration * 60 * 1000;
const tokenLimits = MODEL_FAMILIES.reduce((limits, modelFamily) => {
const quotaValue = data[`temporaryUserQuota_${modelFamily}`];
limits[modelFamily] = typeof quotaValue === 'number' ? quotaValue : 0;
const tokenLimits = MODEL_FAMILIES.reduce((limits, model) => {
limits[model] = data[`temporaryUserQuota_${model}`];
return limits;
}, {} as any);
}, {} as UserTokenCounts);
return { ...data, expiresAt, tokenLimits };
});
@@ -190,70 +118,7 @@ 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());
// 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);
const result = z.array(UserPartialSchema).safeParse(data.users);
if (!result.success) throw new HttpError(400, result.error.toString());
const upserts = result.data.map((user) => userStore.upsertUser(user));
@@ -332,14 +197,7 @@ router.post("/maintenance", (req, res) => {
let flash = { type: "", message: "" };
switch (action) {
case "recheck": {
const checkable: LLMService[] = [
"openai",
"anthropic",
"aws",
"gcp",
"azure",
"google-ai"
];
const checkable: LLMService[] = ["openai", "anthropic", "aws", "azure"];
checkable.forEach((s) => keyPool.recheck(s));
const keyCount = keyPool
.list()
@@ -365,14 +223,10 @@ router.post("/maintenance", (req, res) => {
break;
}
case "downloadImageMetadata": {
const data = JSON.stringify(
{
exportedAt: new Date().toISOString(),
generations: getLastNImages(),
},
null,
2
);
const data = JSON.stringify({
exportedAt: new Date().toISOString(),
generations: getLastNImages()
}, null, 2);
res.setHeader(
"Content-Disposition",
`attachment; filename=image-metadata-${new Date().toISOString()}.json`
@@ -380,123 +234,14 @@ router.post("/maintenance", (req, res) => {
res.setHeader("Content-Type", "application/json");
return res.send(data);
}
case "expireTempTokens": {
const users = userStore.getUsers();
const temps = users.filter((u) => u.type === "temporary");
temps.forEach((user) => {
user.expiresAt = Date.now();
user.disabledReason = "Admin forced expiration.";
userStore.upsertUser(user);
});
invalidatePowChallenges();
flash.type = "success";
flash.message = `${temps.length} temporary users marked for expiration.`;
break;
}
case "cleanTempTokens": {
const users = userStore.getUsers();
const disabledTempUsers = users.filter(
(u) => u.type === "temporary" && u.expiresAt && u.expiresAt < Date.now()
);
disabledTempUsers.forEach((user) => {
user.disabledAt = 1; //will be cleaned up by the next cron job
userStore.upsertUser(user);
});
flash.type = "success";
flash.message = `${disabledTempUsers.length} disabled temporary users marked for cleanup.`;
break;
}
case "setDifficulty": {
const selected = req.body["pow-difficulty"];
const valid = ["low", "medium", "high", "extreme"];
const isNumber = Number.isInteger(Number(selected));
if (!selected || !valid.includes(selected) && !isNumber) {
throw new HttpError(400, "Invalid difficulty " + selected);
}
config.powDifficultyLevel = isNumber ? Number(selected) : selected;
invalidatePowChallenges();
break;
}
case "generateTempIpReport": {
const tempUsers = userStore
.getUsers()
.filter((u) => u.type === "temporary");
const ipv4RangeMap = new Map<string, Set<string>>();
const ipv6RangeMap = new Map<string, Set<string>>();
tempUsers.forEach((u) => {
u.ip.forEach((ip) => {
try {
const parsed = ipaddr.parse(ip);
if (parsed.kind() === "ipv4") {
const subnet =
parsed.toNormalizedString().split(".").slice(0, 3).join(".") +
".0/24";
const userSet = ipv4RangeMap.get(subnet) || new Set();
userSet.add(u.token);
ipv4RangeMap.set(subnet, userSet);
} else if (parsed.kind() === "ipv6") {
const subnet =
parsed.toNormalizedString().split(":").slice(0, 4).join(":") +
"::/48";
const userSet = ipv6RangeMap.get(subnet) || new Set();
userSet.add(u.token);
ipv6RangeMap.set(subnet, userSet);
}
} catch (e) {
req.log.warn(
{ ip, error: e.message },
"Invalid IP address; skipping"
);
}
});
});
const ipv4Ranges = Array.from(ipv4RangeMap.entries())
.map(([subnet, userSet]) => ({
subnet,
distinctTokens: userSet.size,
}))
.sort((a, b) => b.distinctTokens - a.distinctTokens);
const ipv6Ranges = Array.from(ipv6RangeMap.entries())
.map(([subnet, userSet]) => ({
subnet,
distinctTokens: userSet.size,
}))
.sort((a, b) => {
if (a.distinctTokens === b.distinctTokens) {
return a.subnet.localeCompare(b.subnet);
}
return b.distinctTokens - a.distinctTokens;
});
const data = JSON.stringify(
{
exportedAt: new Date().toISOString(),
ipv4Ranges,
ipv6Ranges,
},
null,
2
);
res.setHeader(
"Content-Disposition",
`attachment; filename=temp-ip-report-${new Date().toISOString()}.json`
);
res.setHeader("Content-Type", "application/json");
return res.send(data);
}
default: {
throw new HttpError(400, "Invalid action");
}
}
req.session.flash = flash;
const referer = req.get("referer");
return res.redirect(referer || "/admin/manage");
return res.redirect(`/admin/manage`);
});
router.get("/download-stats", (_req, res) => {
@@ -611,14 +356,9 @@ router.post("/generate-stats", (req, res) => {
function getSumsForUser(user: User) {
const sums = MODEL_FAMILIES.reduce(
(s, model) => {
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);
const tokens = user.tokenCounts[model] ?? 0;
s.sumTokens += tokens;
s.sumCost += getTokenCostUsd(model, tokens);
return s;
},
{ sumTokens: 0, sumCost: 0, prettyUsage: "" }
src/admin/web/views/admin_anti-abuse.ejs
-160
View File
@@ -1,160 +0,0 @@
<%- include("partials/shared_header", { title: "Proof of Work Verification Settings - OAI Reverse Proxy Admin" }) %>
<style>
details {
margin-top: 1em;
}
details summary {
font-weight: bold;
cursor: pointer;
}
details p {
margin-left: 1em;
}
#token-manage {
display: flex;
width: 100%;
}
#token-manage button {
flex-grow: 1;
margin: 0 0.5em;
}
</style>
<h1>Abuse Mitigation Settings</h1>
<div>
<h2>Proof-of-Work Verification</h2>
<p>
The Proof-of-Work difficulty level is used to determine how much work a client must perform to earn a temporary user
token. Higher difficulty levels require more work, which can help mitigate abuse by making it more expensive for
attackers to generate tokens. However, higher difficulty levels can also make it more difficult for legitimate users
to generate tokens. Refer to documentation for guidance.
</p>
<%if (captchaMode === "none") { %>
<p>
<strong>PoW verification is not enabled. Set <code>CAPTCHA_MODE=proof_of_work</code> to enable.</strong>
</p>
<% } else { %>
<h3>Difficulty Level</h3>
<div>
<label for="difficulty">Difficulty Level:</label>
<select name="difficulty" id="difficulty" onchange="difficultyChanged(event)">
<option value="low">Low</option>
<option value="medium">Medium</option>
<option value="high">High</option>
<option value="extreme">Extreme</option>
<option value="custom">Custom</option>
</select>
<div id="custom-difficulty-container" style="display: none">
<label for="customDifficulty">Hashes required (average):</label>
<input type="number" id="customDifficulty" value="0" min="1" max="1000000000" />
</div>
<button onclick='doAction("setDifficulty")'>Update Difficulty</button>
</div>
<div><span id="currentDifficulty">Current Difficulty: <%= difficulty %></span></div>
<% } %>
<form id="maintenanceForm" action="/admin/manage/maintenance" method="post">
<input id="_csrf" type="hidden" name="_csrf" value="<%= csrfToken %>" />
<input id="hiddenAction" type="hidden" name="action" value="" />
<input id="hiddenDifficulty" type="hidden" name="pow-difficulty" value="" />
</form>
<h3>Manage Temporary User Tokens</h3>
<div id="token-manage">
<p><button onclick='doAction("expireTempTokens")'>🕒 Expire All Temp Tokens</button></p>
<p><button onclick='doAction("cleanTempTokens")'>🧹 Delete Expired Temp Tokens</button></p>
<p><button onclick='doAction("generateTempIpReport")'>📊 Generate Temp Token IP Report</button></p>
</div>
</div>
<div>
<h2>IP Whitelists and Blacklists</h2>
<p>
You can specify IP ranges to whitelist or blacklist from accessing the proxy. Entries can be specified as single
addresses or
<a href="https://en.wikipedia.org/wiki/Classless_Inter-Domain_Routing#CIDR_notation">CIDR notation</a>. IPv6 is
supported but not recommended for use with the current version of the proxy.
</p>
<p>
<strong>Note:</strong> Changes here are not persisted across server restarts. If you want to make changes permanent,
you can copy the values to your deployment configuration.
</p>
<% for (let i = 0; i < whitelists.length; i++) { %>
<%- include("partials/admin-cidr-widget", { list: whitelists[i] }) %>
<% } %>
<% for (let i = 0; i < blacklists.length; i++) { %>
<%- include("partials/admin-cidr-widget", { list: blacklists[i] }) %>
<% } %>
<form action="/admin/manage/cidr" method="post" id="cidrForm">
<input id="_csrf" type="hidden" name="_csrf" value="<%= csrfToken %>" />
<input type="hidden" name="action" value="add" />
<input type="hidden" name="name" value="" />
<input type="hidden" name="mode" value="" />
<input type="hidden" name="mask" value="" />
</form>
<details>
<summary>Copy environment variables</summary>
<p>
If you have made changes with the UI, you can copy the values below to your deployment configuration to persist
them across server restarts.
</p>
<pre>
<% for (let i = 0; i < whitelists.length; i++) { %><%= whitelists[i].name %>=<%= whitelists[i].ranges.join(",") %><% } %>
<% for (let i = 0; i < blacklists.length; i++) { %><%= blacklists[i].name %>=<%= blacklists[i].ranges.join(",") %><% } %>
</pre>
</details>
</div>
<script>
function difficultyChanged(event) {
const value = event.target.value;
if (value === "custom") {
document.getElementById("custom-difficulty-container").style.display = "block";
} else {
document.getElementById("custom-difficulty-container").style.display = "none";
}
}
function doAction(action) {
document.getElementById("hiddenAction").value = action;
if (action === "setDifficulty") {
const selected = document.getElementById("difficulty").value;
const hiddenDifficulty = document.getElementById("hiddenDifficulty");
if (selected === "custom") {
hiddenDifficulty.value = document.getElementById("customDifficulty").value;
} else {
hiddenDifficulty.value = selected;
}
}
document.getElementById("maintenanceForm").submit();
}
function onAddCidr(event) {
const list = event.target.dataset;
const newMask = prompt("Enter the IP or CIDR range to add to the list:");
if (!newMask) {
return;
}
const form = document.getElementById("cidrForm");
form["action"].value = "add";
form["name"].value = list.name;
form["mode"].value = list.mode;
form["mask"].value = newMask;
form.submit();
}
function onRemoveCidr(event) {
const list = event.target.dataset;
const removeMask = event.target.dataset.mask;
if (!removeMask) {
return;
}
const form = document.getElementById("cidrForm");
form["action"].value = "remove";
form["name"].value = list.name;
form["mode"].value = list.mode;
form["mask"].value = removeMask;
form.submit();
}
</script>
<%- include("partials/admin-footer") %>
src/admin/web/views/admin_create-user.ejs
+3 -2
View File
@@ -51,8 +51,9 @@
<legend>Temporary User Options</legend>
<div class="temporary-user-fieldset">
<p class="full-width">
Temporary users will be disabled after the specified duration, and their records will be permanently deleted after some time.
These options apply only to new temporary users; existing ones use whatever options were in effect when they were created.
Temporary users will be disabled after the specified duration, and their records will be deleted 72 hours after that.
These options apply only to new
temporary users; existing ones use whatever options were in effect when they were created.
</p>
<label for="temporaryUserDuration" class="full-width">Access duration (in minutes)</label>
<input type="number" name="temporaryUserDuration" id="temporaryUserDuration" value="60" class="full-width" />
src/admin/web/views/admin_download-stats.ejs
+36 -27
View File
@@ -5,6 +5,18 @@
flex-direction: column;
}
#statsForm div {
display: flex;
flex-direction: row;
margin-bottom: 0.5em;
}
#statsForm div label {
width: 6em;
text-align: right;
margin-right: 1em;
}
#statsForm ul {
margin: 0;
padding-left: 2em;
@@ -21,17 +33,17 @@
}
</style>
<h1>Download Stats</h1>
<p>Download usage statistics to a Markdown document. You can paste this into a service like Rentry.org to share it.</p>
<p>
Download usage statistics to a Markdown document. You can paste this into a service like Rentry.org to share it.
</p>
<div>
<h3>Options</h3>
<form
id="statsForm"
action="/admin/manage/generate-stats"
method="post"
style="display: flex; flex-direction: column">
<form id="statsForm" action="/admin/manage/generate-stats" method="post"
style="display: flex; flex-direction: column;">
<input id="_csrf" type="hidden" name="_csrf" value="<%= csrfToken %>" />
<div>
<label for="anon"><input id="anon" type="checkbox" name="anon" value="true" /> <span>Anonymize</span></label>
<label for="anon">Anonymize</label>
<input id="anon" type="checkbox" name="anon" value="true" />
</div>
<div>
<label for="sort">Sort</label>
@@ -52,12 +64,11 @@
</select>
</div>
<div>
<label for="format">Custom Format</label>
<ul>
<li><code>{{header}}</code></li>
<li><code>{{stats}}</code></li>
<li><code>{{time}}</code></li>
</ul>
<label for="format">Custom Format <ul>
<li><code>{{header}}</code></li>
<li><code>{{stats}}</code></li>
<li><code>{{time}}</code></li>
</ul></label>
<textarea id="format" name="format" rows="10" cols="50" placeholder="{{stats}}">
# Stats
{{header}}
@@ -104,35 +115,33 @@
loadDefaults();
async function fetchAndCopy() {
const form = document.getElementById("statsForm");
const form = document.getElementById('statsForm');
const formData = new FormData(form);
const response = await fetch(form.action, {
method: "POST",
headers: { "Content-Type": "application/x-www-form-urlencoded" },
credentials: "same-origin",
method: 'POST',
headers: { 'Content-Type': 'application/x-www-form-urlencoded' },
credentials: 'same-origin',
body: new URLSearchParams(formData),
});
if (response.ok) {
const content = await response.text();
copyToClipboard(content);
} else {
throw new Error("Failed to fetch generated stats. Try reloading the page.");
throw new Error('Failed to fetch generated stats. Try reloading the page.');
}
}
function copyToClipboard(text) {
navigator.clipboard
.writeText(text)
.then(() => {
alert("Copied to clipboard");
})
.catch((err) => {
alert("Failed to copy to clipboard. Try downloading the file instead.");
});
navigator.clipboard.writeText(text).then(() => {
alert('Copied to clipboard');
}).catch(err => {
alert('Failed to copy to clipboard. Try downloading the file instead.');
});
}
document.getElementById("copyButton").addEventListener("click", fetchAndCopy);
document.getElementById('copyButton').addEventListener('click', fetchAndCopy);
</script>
<%- include("partials/admin-footer") %>
src/admin/web/views/admin_import-users.ejs
+5 -11
View File
@@ -18,19 +18,13 @@
</li>
<li>
<code>tokenCounts</code> (optional): the number of tokens the user has
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.
consumed. This should be an object with keys <code>turbo</code>,
<code>gpt4</code>, and <code>claude</code>.
</li>
<li>
<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>.
<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>.
</li>
<li>
<code>createdAt</code> (optional): the timestamp when the user was created
src/admin/web/views/admin_index.ejs
+2 -3
View File
@@ -25,14 +25,13 @@
<li><a href="/admin/manage/import-users">Import Users</a></li>
<li><a href="/admin/manage/export-users">Export Users</a></li>
<li><a href="/admin/manage/download-stats">Download Rentry Stats</a>
<li><a href="/admin/manage/anti-abuse">Abuse Mitigation Settings</a></li>
<li><a href="/admin/service-info">Service Info</a></li>
</ul>
<h3>Maintenance</h3>
<form id="maintenanceForm" action="/admin/manage/maintenance" method="post">
<input id="_csrf" type="hidden" name="_csrf" value="<%= csrfToken %>" />
<input id="hiddenAction" type="hidden" name="action" value="" />
<div>
<div display="flex" flex-direction="column">
<fieldset>
<legend>Key Recheck</legend>
<button id="recheck-keys" type="button" onclick="submitForm('recheck')">Force Key Recheck</button>
@@ -43,7 +42,7 @@
<legend>Bulk Quota Management</legend>
<p>
<button id="refresh-quotas" type="button" onclick="submitForm('resetQuotas')">Refresh All Quotas</button>
Immediately refreshes all users' quotas by the configured amounts.
Resets all users' quotas to the values set in the <code>TOKEN_QUOTA_*</code> environment variables.
</p>
<p>
<button id="clear-token-counts" type="button" onclick="submitForm('resetCounts')">Clear All Token Counts</button>
src/admin/web/views/admin_list-users.ejs
+3 -2
View File
@@ -4,8 +4,9 @@
<% if (users.length === 0) { %>
<p>No users found.</p>
<% } else { %>
<label for="toggle-nicknames"><input type="checkbox" id="toggle-nicknames" onchange="toggleNicknames()" /> Show Nicknames</label>
<table class="striped full-width">
<input type="checkbox" id="toggle-nicknames" onchange="toggleNicknames()" />
<label for="toggle-nicknames">Show Nicknames</label>
<table class="striped">
<thead>
<tr>
<th>User</th>
src/admin/web/views/admin_view-user.ejs
+14 -33
View File
@@ -55,9 +55,8 @@
<td><%- user.disabledReason %></td>
<% if (user.disabledAt) { %>
<td class="actions">
<a title="Edit" id="edit-disabledReason" href="#" data-field="disabledReason" data-token="<%= user.token %>"
>✏️</a
>
<a title="Edit" id="edit-disabledReason" href="#" data-field="disabledReason"
data-token="<%= user.token %>">✏️</a>
</td>
<% } %>
</tr>
@@ -73,8 +72,7 @@
<td colspan="2"><%- include("partials/shared_user_ip_list", { user, shouldRedact: false }) %></td>
</tr>
<tr>
<th scope="row">
Admin Note <span title="Unlike nickname, this is not visible to or editable by the user">🔒</span>
<th scope="row">Admin Note <span title="Unlike nickname, this is not visible to or editable by the user">🔒</span>
</th>
<td><%- user.adminNote ?? "none" %></td>
<td class="actions">
@@ -87,24 +85,14 @@
<td colspan="2"><%- user.expiresAt %></td>
</tr>
<% } %>
<% if (user.meta) { %>
<tr>
<th scope="row">Meta</th>
<td colspan="2"><%- JSON.stringify(user.meta) %></td>
</tr>
<% } %>
</tbody>
</table>
<form style="display: none" id="current-values">
<form style="display:none" id="current-values">
<input type="hidden" name="token" value="<%- user.token %>" />
<% ["nickname", "type", "disabledAt", "disabledReason", "maxIps", "adminNote"].forEach(function (key) { %>
<input type="hidden" name="<%- key %>" value="<%- user[key] %>" />
<% }); %>
<!-- tokenRefresh_ keys are dynamically generated -->
<% Object.entries(quota).forEach(([family]) => { %>
<input type="hidden" name="tokenRefresh_<%- family %>" value="<%- user.tokenRefresh[family] || quota[family] %>" />
<% }); %>
</form>
<h3>Quota Information</h3>
@@ -114,8 +102,7 @@
<input type="hidden" name="_csrf" value="<%- csrfToken %>" />
<button type="submit" class="btn btn-primary">Refresh Quotas for User</button>
</form>
<% } %>
<%- include("partials/shared_quota-info", { quota, user, showRefreshEdit: true }) %>
<% } %> <%- include("partials/shared_quota-info", { quota, user }) %>
<p><a href="/admin/manage/list-users">Back to User List</a></p>
@@ -126,25 +113,18 @@
const token = a.dataset.token;
const field = a.dataset.field;
const existingValue = document.querySelector(`#current-values input[name=${field}]`).value;
let value = prompt(`Enter new value for '${field}':`, existingValue);
let value = prompt(`Enter new value for '${field}'':`, existingValue);
if (value !== null) {
if (value === "") {
value = null;
}
const payload = { _csrf: document.querySelector("meta[name=csrf-token]").getAttribute("content") };
if (field.startsWith("tokenRefresh_")) {
const family = field.slice("tokenRefresh_".length);
payload.tokenRefresh = { [family]: Number(value) };
} else {
payload[field] = value;
}
fetch(`/admin/manage/edit-user/${token}`, {
method: "POST",
credentials: "same-origin",
body: JSON.stringify(payload),
body: JSON.stringify({
[field]: value,
_csrf: document.querySelector("meta[name=csrf-token]").getAttribute("content"),
}),
headers: { "Content-Type": "application/json", Accept: "application/json" },
})
.then((res) => Promise.all([res.ok, res.json()]))
@@ -152,7 +132,9 @@
const url = new URL(window.location.href);
const params = new URLSearchParams();
if (!ok) {
alert(`Failed to edit user: ${json.message}`);
params.set("flash", `error: ${json.error.message}`);
} else {
params.set("flash", `success: User's ${field} updated.`);
}
url.search = params.toString();
window.location.assign(url);
@@ -162,5 +144,4 @@
});
</script>
<%- include("partials/admin-ban-xhr-script") %>
<%- include("partials/admin-footer") %>
<%- include("partials/admin-ban-xhr-script") %> <%- include("partials/admin-footer") %>
src/admin/web/views/partials/admin-cidr-widget.ejs
-13
View File
@@ -1,13 +0,0 @@
<h3>
<%= list.name %>
(<%= list.mode %>)
</h3>
<ul>
<% list.ranges.forEach(function(mask) { %>
<li>
<%= mask %>
<button class="remove" data-mode="<%= list.mode %>" data-name="<%= list.name %>" data-mask="<%= mask %>" onclick="onRemoveCidr(event)">Remove</button>
</li>
<% }); %>
</ul>
<button class="add" data-mode="<%= list.mode %>" data-name="<%= list.name %>" onclick="onAddCidr(event)">Add</button>
src/config.ts
+75 -395
View File
@@ -1,9 +1,8 @@
import crypto from "crypto";
import dotenv from "dotenv";
import type firebase from "firebase-admin";
import path from "path";
import pino from "pino";
import type { LLMService, ModelFamily } from "./shared/models";
import type { ModelFamily } from "./shared/models";
import { MODEL_FAMILIES } from "./shared/models";
dotenv.config();
@@ -29,40 +28,10 @@ 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.
@@ -75,13 +44,6 @@ type Config = {
* @example `AWS_CREDENTIALS=access_key_1:secret_key_1:us-east-1,access_key_2:secret_key_2:us-west-2`
*/
awsCredentials?: string;
/**
* Comma-delimited list of GCP credentials. Each credential item should be a
* colon-delimited list of access key, secret key, and GCP region.
*
* @example `GCP_CREDENTIALS=project1:1@1.com:us-east5:-----BEGIN PRIVATE KEY-----xxx-----END PRIVATE KEY-----,project2:2@2.com:us-east5:-----BEGIN PRIVATE KEY-----xxx-----END PRIVATE KEY-----`
*/
gcpCredentials?: string;
/**
* Comma-delimited list of Azure OpenAI credentials. Each credential item
* should be a colon-delimited list of Azure resource name, deployment ID, and
@@ -103,6 +65,11 @@ 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
@@ -119,14 +86,10 @@ 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" | "sqlite";
gatekeeperStore: "memory" | "firebase_rtdb";
/** 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
@@ -144,70 +107,9 @@ type Config = {
* `maxIpsPerUser` limit, or if only connections from new IPs are be rejected.
*/
maxIpsAutoBan: boolean;
/**
* Which captcha verification mode to use. Requires `user_token` gatekeeper.
* Allows users to automatically obtain a token by solving a captcha.
* - `none`: No captcha verification; tokens are issued manually.
* - `proof_of_work`: Users must solve an Argon2 proof of work to obtain a
* temporary usertoken valid for a limited period.
*/
captchaMode: "none" | "proof_of_work";
/**
* Duration (in hours) for which a PoW-issued temporary user token is valid.
*/
powTokenHours: number;
/**
* The maximum number of IPs from which a single temporary user token can be
* used. Upon reaching the limit, the `maxIpsAutoBan` behavior is triggered.
*/
powTokenMaxIps: number;
/**
* Difficulty level for the proof-of-work challenge.
* - `low`: 200 iterations
* - `medium`: 900 iterations
* - `high`: 1900 iterations
* - `extreme`: 4000 iterations
* - `number`: A custom number of iterations to use.
*
* Difficulty level only affects the number of iterations used in the PoW,
* not the complexity of the hash itself. Therefore, the average time-to-solve
* will scale linearly with the number of iterations.
*
* Refer to docs/proof-of-work.md for guidance and hashrate benchmarks.
*/
powDifficultyLevel: "low" | "medium" | "high" | "extreme" | number;
/**
* Duration (in minutes) before a PoW challenge expires. Users' browsers must
* solve the challenge within this time frame or it will be rejected. Should
* be kept somewhat low to prevent abusive clients from working on many
* challenges in parallel, but you may need to increase this value for higher
* difficulty levels or older devices will not be able to solve the challenge
* in time.
*
* Defaults to 30 minutes.
*/
powChallengeTimeout: number;
/**
* Duration (in hours) before expired temporary user tokens are purged from
* the user database. Users can refresh expired tokens by solving a faster PoW
* challenge as long as the original token has not been purged. Once purged,
* the user must solve a full PoW challenge to obtain a new token.
*
* Defaults to 48 hours. At 0, tokens are purged immediately upon expiry.
*/
powTokenPurgeHours: number;
/**
* Maximum number of active temporary user tokens that can be associated with
* a single IP address. Note that this may impact users sending requests from
* hosted AI chat clients such as Agnaistic or RisuAI, as they may share IPs.
*
* When the limit is reached, the oldest token with the same IP will be
* expired. At 0, no limit is enforced. Defaults to 0.
*/
// powMaxTokensPerIp: number;
/** Per-user limit for requests per minute to text and chat models. */
/** Per-IP limit for requests per minute to text and chat models. */
textModelRateLimit: number;
/** Per-user limit for requests per minute to image generation models. */
/** Per-IP limit for requests per minute to image generation models. */
imageModelRateLimit: number;
/**
* For OpenAI, the maximum number of context tokens (prompt + max output) a
@@ -244,38 +146,10 @@ type Config = {
* key and can't attach the policy, you can set this to true.
*/
allowAwsLogging?: boolean;
/**
* Path to the SQLite database file for storing data such as event logs. By
* default, the database will be stored at `data/database.sqlite`.
*
* Ensure target is writable by the server process, and be careful not to
* select a path that is served publicly. The default path is safe.
*/
sqliteDataPath?: string;
/**
* Whether to log events, such as generated completions, to the database.
* Events are associated with IP+user token pairs. If user_token mode is
* disabled, no events will be logged.
*
* Currently there is no pruning mechanism for the events table, so it will
* grow indefinitely. You may want to periodically prune the table manually.
*/
eventLogging?: boolean;
/**
* When hashing prompt histories, how many messages to trim from the end.
* If zero, only the full prompt hash will be stored.
* If greater than zero, for each number N, a hash of the prompt with the
* last N messages removed will be stored.
*
* Experimental function, config may change in future versions.
*/
eventLoggingTrim?: number;
/** Whether prompts and responses should be logged to persistent storage. */
promptLogging?: boolean;
/** Which prompt logging backend to use. */
promptLoggingBackend?: "google_sheets" | "file";
/** Prefix for prompt logging files when using the file backend. */
promptLoggingFilePrefix?: string;
promptLoggingBackend?: "google_sheets";
/** Base64-encoded Google Sheets API key. */
googleSheetsKey?: string;
/** Google Sheets spreadsheet ID. */
@@ -375,83 +249,11 @@ type Config = {
* risk.
*/
allowOpenAIToolUsage?: boolean;
/**
* Which services will accept prompts containing images, for use with
* multimodal models. Users with `special` role are exempt from this
* restriction.
*
* Do not enable this feature for untrusted users, as malicious users could
* send images which violate your provider's terms of service or local laws.
*
* 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,xai
*/
allowedVisionServices: LLMService[];
/**
* Allows overriding the default proxy endpoint route. Defaults to /proxy.
* A leading slash is required.
*/
proxyEndpointRoute: string;
/**
* If set, only requests from these IP addresses will be permitted to use the
* admin API and UI. Provide a comma-separated list of IP addresses or CIDR
* ranges. If not set, the admin API and UI will be open to all requests.
*/
adminWhitelist: string[];
/**
* If set, requests from these IP addresses will be blocked from using the
* application. Provide a comma-separated list of IP addresses or CIDR ranges.
* If not set, no IP addresses will be blocked.
*
* Takes precedence over the adminWhitelist.
*/
ipBlacklist: string[];
/**
* If set, pushes requests further back into the queue according to their
* token costs by factor*tokens*milliseconds (or more intuitively
* factor*thousands_of_tokens*seconds).
* Accepts floats.
*/
tokensPunishmentFactor: number;
/**
* Configuration for HTTP requests made by the proxy to other servers, such
* as when checking keys or forwarding users' requests to external services.
* If not set, all requests will be made using the default agent.
*
* If set, the proxy may make requests to other servers using the specified
* settings. This is useful if you wish to route users' requests through
* another proxy or VPN, or if you have multiple network interfaces and want
* to use a specific one for outgoing requests.
*/
httpAgent?: {
/**
* The name of the network interface to use. The first external IPv4 address
* belonging to this interface will be used for outgoing requests.
*/
interface?: string;
/**
* The URL of a proxy server to use. Supports SOCKS4, SOCKS5, HTTP, and
* HTTPS. If not set, the proxy will be made using the default agent.
* - SOCKS4: `socks4://some-socks-proxy.com:9050`
* - SOCKS5: `socks5://username:password@some-socks-proxy.com:9050`
* - HTTP: `http://proxy-server-over-tcp.com:3128`
* - HTTPS: `https://proxy-server-over-tls.com:3129`
*
* **Note:** If your proxy server issues a certificate, you may need to set
* `NODE_EXTRA_CA_CERTS` to the path to your certificate, otherwise this
* application will reject TLS connections.
*/
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.
@@ -461,60 +263,52 @@ 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", ""),
sqliteDataPath: getEnvWithDefault(
"SQLITE_DATA_PATH",
path.join(DATA_DIR, "database.sqlite")
),
eventLogging: getEnvWithDefault("EVENT_LOGGING", false),
eventLoggingTrim: getEnvWithDefault("EVENT_LOGGING_TRIM", 5),
serviceInfoPassword: getEnvWithDefault("SERVICE_INFO_PASSWORD", ""),
gatekeeper: getEnvWithDefault("GATEKEEPER", "none"),
gatekeeperStore: getEnvWithDefault("GATEKEEPER_STORE", "memory") as Config["gatekeeperStore"],
sqliteUserStorePath: getEnvWithDefault(
"SQLITE_USER_STORE_PATH",
path.join(DATA_DIR, "user-store.sqlite")
),
gatekeeperStore: getEnvWithDefault("GATEKEEPER_STORE", "memory"),
maxIpsPerUser: getEnvWithDefault("MAX_IPS_PER_USER", 0),
maxIpsAutoBan: getEnvWithDefault("MAX_IPS_AUTO_BAN", false),
captchaMode: getEnvWithDefault("CAPTCHA_MODE", "none"),
powTokenHours: getEnvWithDefault("POW_TOKEN_HOURS", 24),
powTokenMaxIps: getEnvWithDefault("POW_TOKEN_MAX_IPS", 2),
powDifficultyLevel: getEnvWithDefault("POW_DIFFICULTY_LEVEL", "low"),
powChallengeTimeout: getEnvWithDefault("POW_CHALLENGE_TIMEOUT", 30),
powTokenPurgeHours: getEnvWithDefault("POW_TOKEN_PURGE_HOURS", 48),
maxIpsAutoBan: getEnvWithDefault("MAX_IPS_AUTO_BAN", true),
firebaseRtdbUrl: getEnvWithDefault("FIREBASE_RTDB_URL", undefined),
firebaseKey: getEnvWithDefault("FIREBASE_KEY", undefined),
textModelRateLimit: getEnvWithDefault("TEXT_MODEL_RATE_LIMIT", 4),
imageModelRateLimit: getEnvWithDefault("IMAGE_MODEL_RATE_LIMIT", 4),
maxContextTokensOpenAI: getEnvWithDefault("MAX_CONTEXT_TOKENS_OPENAI", 32768),
maxContextTokensOpenAI: getEnvWithDefault("MAX_CONTEXT_TOKENS_OPENAI", 16384),
maxContextTokensAnthropic: getEnvWithDefault(
"MAX_CONTEXT_TOKENS_ANTHROPIC",
32768
0
),
maxOutputTokensOpenAI: getEnvWithDefault(
["MAX_OUTPUT_TOKENS_OPENAI", "MAX_OUTPUT_TOKENS"],
1024
400
),
maxOutputTokensAnthropic: getEnvWithDefault(
["MAX_OUTPUT_TOKENS_ANTHROPIC", "MAX_OUTPUT_TOKENS"],
1024
),
allowedModelFamilies: getEnvWithDefault(
"ALLOWED_MODEL_FAMILIES",
getDefaultModelFamilies()
400
),
allowedModelFamilies: getEnvWithDefault("ALLOWED_MODEL_FAMILIES", [
"turbo",
"gpt4",
"gpt4-32k",
"gpt4-turbo",
"claude",
"claude-opus",
"gemini-pro",
"mistral-tiny",
"mistral-small",
"mistral-medium",
"mistral-large",
"aws-claude",
"azure-turbo",
"azure-gpt4",
"azure-gpt4-turbo",
"azure-gpt4-32k",
]),
rejectPhrases: parseCsv(getEnvWithDefault("REJECT_PHRASES", "")),
rejectMessage: getEnvWithDefault(
"REJECT_MESSAGE",
@@ -526,10 +320,6 @@ export const config: Config = {
allowAwsLogging: getEnvWithDefault("ALLOW_AWS_LOGGING", false),
promptLogging: getEnvWithDefault("PROMPT_LOGGING", false),
promptLoggingBackend: getEnvWithDefault("PROMPT_LOGGING_BACKEND", undefined),
promptLoggingFilePrefix: getEnvWithDefault(
"PROMPT_LOGGING_FILE_PREFIX",
"prompt-logs"
),
googleSheetsKey: getEnvWithDefault("GOOGLE_SHEETS_KEY", undefined),
googleSheetsSpreadsheetId: getEnvWithDefault(
"GOOGLE_SHEETS_SPREADSHEET_ID",
@@ -558,62 +348,20 @@ export const config: Config = {
staticServiceInfo: getEnvWithDefault("STATIC_SERVICE_INFO", false),
trustedProxies: getEnvWithDefault("TRUSTED_PROXIES", 1),
allowOpenAIToolUsage: getEnvWithDefault("ALLOW_OPENAI_TOOL_USAGE", false),
allowedVisionServices: parseCsv(
getEnvWithDefault("ALLOWED_VISION_SERVICES", "")
) as LLMService[],
proxyEndpointRoute: getEnvWithDefault("PROXY_ENDPOINT_ROUTE", "/proxy"),
adminWhitelist: parseCsv(
getEnvWithDefault("ADMIN_WHITELIST", "0.0.0.0/0,::/0")
),
ipBlacklist: parseCsv(getEnvWithDefault("IP_BLACKLIST", "")),
tokensPunishmentFactor: getEnvWithDefault("TOKENS_PUNISHMENT_FACTOR", 0.0),
httpAgent: {
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() {
function generateCookieSecret() {
if (process.env.COOKIE_SECRET !== undefined) {
// legacy, replaced by SIGNING_KEY
return process.env.COOKIE_SECRET;
} else if (process.env.SIGNING_KEY !== undefined) {
return process.env.SIGNING_KEY;
}
const secrets = [
config.adminKey,
config.openaiKey,
config.anthropicKey,
config.googleAIKey,
config.mistralAIKey,
config.deepseekKey,
config.xaiKey,
config.awsCredentials,
config.gcpCredentials,
config.azureCredentials,
];
if (secrets.filter((s) => s).length === 0) {
startupLogger.warn(
"No SIGNING_KEY or secrets are set. All sessions, cookies, and proofs of work will be invalidated on restart."
);
return crypto.randomBytes(32).toString("hex");
}
startupLogger.info("No SIGNING_KEY set; one will be generated from secrets.");
startupLogger.info(
"It's recommended to set SIGNING_KEY explicitly to ensure users' sessions and cookies always persist across restarts."
);
const seed = secrets.map((s) => s || "n/a").join("");
const seed = "" + config.adminKey + config.openaiKey + config.anthropicKey;
const crypto = require("crypto");
return crypto.createHash("sha256").update(seed).digest("hex");
}
const signingKey = generateSigningKey();
export const SECRET_SIGNING_KEY = signingKey;
export const COOKIE_SECRET = generateCookieSecret();
export async function assertConfigIsValid() {
if (process.env.MODEL_RATE_LIMIT !== undefined) {
@@ -629,23 +377,6 @@ export async function assertConfigIsValid() {
);
}
if (process.env.ALLOW_IMAGE_PROMPTS === "true") {
const hasAllowedServices = config.allowedVisionServices.length > 0;
if (!hasAllowedServices) {
config.allowedVisionServices = ["openai", "anthropic"];
startupLogger.warn(
{ allowedVisionServices: config.allowedVisionServices },
"ALLOW_IMAGE_PROMPTS is deprecated. Use ALLOWED_VISION_SERVICES instead."
);
}
}
if (config.promptLogging && !config.promptLoggingBackend) {
throw new Error(
"Prompt logging is enabled but no backend is configured. Set PROMPT_LOGGING_BACKEND to 'google_sheets' or 'file'."
);
}
if (!["none", "proxy_key", "user_token"].includes(config.gatekeeper)) {
throw new Error(
`Invalid gatekeeper mode: ${config.gatekeeper}. Must be one of: none, proxy_key, user_token.`
@@ -658,35 +389,18 @@ export async function assertConfigIsValid() {
);
}
if (
config.captchaMode === "proof_of_work" &&
config.gatekeeper !== "user_token"
) {
throw new Error(
"Captcha mode 'proof_of_work' requires gatekeeper mode 'user_token'."
);
}
if (config.captchaMode === "proof_of_work") {
const val = config.powDifficultyLevel;
const isDifficulty =
typeof val === "string" &&
["low", "medium", "high", "extreme"].includes(val);
const isIterations =
typeof val === "number" && Number.isInteger(val) && val > 0;
if (!isDifficulty && !isIterations) {
throw new Error(
"Invalid POW_DIFFICULTY_LEVEL. Must be one of: low, medium, high, extreme, or a positive integer."
);
}
}
if (config.gatekeeper === "proxy_key" && !config.proxyKey) {
throw new Error(
"`proxy_key` gatekeeper mode requires a `PROXY_KEY` to be set."
);
}
if (config.gatekeeper !== "proxy_key" && config.proxyKey) {
throw new Error(
"`PROXY_KEY` is set, but gatekeeper mode is not `proxy_key`. Make sure to set `GATEKEEPER=proxy_key`."
);
}
if (
config.gatekeeperStore === "firebase_rtdb" &&
(!config.firebaseKey || !config.firebaseRtdbUrl)
@@ -696,41 +410,6 @@ 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) {
if (config.httpAgent.interface && config.httpAgent.proxyUrl) {
throw new Error(
"Cannot set both `HTTP_AGENT_INTERFACE` and `HTTP_AGENT_PROXY_URL`."
);
}
}
if (config.enableInfoPageLogin) {
if (!["token", "password"].includes(config.serviceInfoAuthMode)) {
throw new Error(
`Invalid SERVICE_INFO_AUTH_MODE: ${config.serviceInfoAuthMode}. Must be 'token' or 'password'.`
);
}
if (config.serviceInfoAuthMode === "password" && !config.serviceInfoPassword) {
throw new Error(
"SERVICE_INFO_AUTH_MODE is 'password' but SERVICE_INFO_PASSWORD is not set."
);
}
// If service info login is token-based, gatekeeper must be 'user_token' mode for getUser() to be effective.
if (config.serviceInfoAuthMode === "token" && config.gatekeeper !== "user_token") {
throw new Error(
"SERVICE_INFO_AUTH_MODE is 'token' for info page login, but GATEKEEPER is not 'user_token'. User token authentication will not work."
);
}
}
// Ensure forks which add new secret-like config keys don't unwittingly expose
// them to users.
for (const key of getKeys(config)) {
@@ -744,16 +423,15 @@ export async function assertConfigIsValid() {
`Config key "${key}" may be sensitive but is exposed. Add it to SENSITIVE_KEYS or OMITTED_KEYS.`
);
}
await maybeInitializeFirebase();
}
/**
* Config keys that are masked on the info page, but not hidden as their
* presence may be relevant to the user due to privacy implications.
*/
export const SENSITIVE_KEYS: (keyof Config)[] = [
"googleSheetsSpreadsheetId",
"httpAgent",
];
export const SENSITIVE_KEYS: (keyof Config)[] = ["googleSheetsSpreadsheetId"];
/**
* Config keys that are not displayed on the info page at all, generally because
@@ -766,28 +444,18 @@ export const OMITTED_KEYS = [
"openaiKey",
"anthropicKey",
"googleAIKey",
"deepseekKey",
"xaiKey",
"cohereKey",
"qwenKey",
"moonshotKey",
"mistralAIKey",
"awsCredentials",
"gcpCredentials",
"azureCredentials",
"proxyKey",
"adminKey",
"serviceInfoPassword",
"rejectPhrases",
"rejectMessage",
"showTokenCosts",
"promptLoggingFilePrefix",
"googleSheetsKey",
"firebaseKey",
"firebaseRtdbUrl",
"sqliteDataPath",
"sqliteUserStorePath",
"eventLogging",
"eventLoggingTrim",
"gatekeeperStore",
"maxIpsPerUser",
"blockedOrigins",
@@ -801,12 +469,6 @@ export const OMITTED_KEYS = [
"allowedModelFamilies",
"trustedProxies",
"proxyEndpointRoute",
"adminWhitelist",
"ipBlacklist",
"powTokenPurgeHours",
"loginImageUrl",
"enableInfoPageLogin",
"serviceInfoPassword",
] satisfies (keyof Config)[];
type OmitKeys = (typeof OMITTED_KEYS)[number];
@@ -867,9 +529,7 @@ function getEnvWithDefault<T>(env: string | string[], defaultValue: T): T {
"ANTHROPIC_KEY",
"GOOGLE_AI_KEY",
"AWS_CREDENTIALS",
"GCP_CREDENTIALS",
"AZURE_CREDENTIALS",
"QWEN_KEY",
].includes(String(env))
) {
return value as unknown as T;
@@ -886,6 +546,32 @@ function getEnvWithDefault<T>(env: string | string[], defaultValue: T): T {
}
}
let firebaseApp: firebase.app.App | undefined;
async function maybeInitializeFirebase() {
if (!config.gatekeeperStore.startsWith("firebase")) {
return;
}
const firebase = await import("firebase-admin");
const firebaseKey = Buffer.from(config.firebaseKey!, "base64").toString();
const app = firebase.initializeApp({
credential: firebase.credential.cert(JSON.parse(firebaseKey)),
databaseURL: config.firebaseRtdbUrl,
});
await app.database().ref("connection-test").set(Date.now());
firebaseApp = app;
}
export function getFirebaseApp(): firebase.app.App {
if (!firebaseApp) {
throw new Error("Firebase app not initialized.");
}
return firebaseApp;
}
function parseCsv(val: string): string[] {
if (!val) return [];
@@ -893,9 +579,3 @@ function parseCsv(val: string): string[] {
const matches = val.match(regex) || [];
return matches.map((item) => item.replace(/^"|"$/g, "").trim());
}
function getDefaultModelFamilies(): ModelFamily[] {
return MODEL_FAMILIES.filter(
(f) => !f.includes("o1-pro") && !f.includes("o3-pro")
) as ModelFamily[];
}
src/info-page.ts
+123 -266
View File
@@ -1,8 +1,4 @@
/* ──────────────────────────────────────────────────────────────
Login-gated info page
drop-in replacement for src/info-page.ts
──────────────────────────────────────────────────────────── */
/** This whole module kinda sucks */
import fs from "fs";
import express, { Router, Request, Response } from "express";
import showdown from "showdown";
@@ -12,166 +8,38 @@ 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 { 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 = "/";
import { checkCsrfToken, injectCsrfToken } from "./shared/inject-csrf";
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",
turbo: "GPT-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",
"gemini-pro": "Gemini Pro",
"gemini-ultra": "Gemini Ultra",
"mistral-tiny": "Mistral 7B",
"mistral-small": "Mistral Nemo",
"mistral-small": "Mixtral Small", // Originally 8x7B, but that now refers to the older open-weight version. Mixtral Small is a newer closed-weight update to the 8x7B model.
"mistral-medium": "Mistral Medium",
"mistral-large": "Mistral Large",
"aws-claude": "AWS Claude (Sonnet)",
"aws-claude-opus": "AWS Claude (Opus)",
"aws-mistral-tiny": "AWS Mistral 7B",
"aws-mistral-small": "AWS Mistral Nemo",
"aws-mistral-medium": "AWS Mistral Medium",
"aws-mistral-large": "AWS Mistral Large",
"gcp-claude": "GCP Claude (Sonnet)",
"gcp-claude-opus": "GCP Claude (Opus)",
"azure-turbo": "Azure GPT-3.5 Turbo",
"azure-gpt4": "Azure GPT-4",
"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>`
? `\n## Server Greeting\n${fs.readFileSync("greeting.md", "utf8")}`
: "";
/* ──────────────── Login page ──────────────────────── */
function renderLoginPage(csrf: string, error?: string) {
const errBlock = error
? `<div class="error-message">${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 function handleInfoPage(req: Request, res: Response) {
export const handleInfoPage = (req: Request, res: Response) => {
if (infoPageLastUpdated + INFO_PAGE_TTL > Date.now()) {
return res.send(infoPageHtml);
}
@@ -186,46 +54,54 @@ export function 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>
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" />
<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>
<head>
<meta charset="utf-8" />
<meta name="robots" content="noindex" />
<title>${title}</title>
<style>
body {
font-family: sans-serif;
background-color: #f0f0f0;
padding: 1em;
}
@media (prefers-color-scheme: dark) {
body {
background-color: #222;
color: #eee;
}
a:link, a:visited {
color: #bbe;
}
}
</style>
</head>
<body>
${headerHtml}
<hr />
<h2>Service Info</h2>
<pre>${JSON.stringify(info, null, 2)}</pre>
${getSelfServiceLinks()}
</body>
</html>`;
}
/* ──────────────── header & helper functions ──────────────── */
/* (all copied verbatim from original file) */
/**
* If the server operator provides a `greeting.md` file, it will be included in
* the rendered info page.
**/
function buildInfoPageHeader(info: ServiceInfo) {
const title = getServerTitle();
// TODO: use some templating engine instead of this mess
let infoBody = `# ${title}`;
if (config.promptLogging) {
infoBody += `\n## Prompt Logging Enabled
This proxy keeps full logs of all prompts and AI responses. Prompt logs are anonymous and do not contain IP addresses or timestamps.
@@ -244,9 +120,9 @@ This proxy keeps full logs of all prompts and AI responses. Prompt logs are anon
for (const modelFamily of config.allowedModelFamilies) {
const service = MODEL_FAMILY_SERVICE[modelFamily];
const hasKeys = keyPool.list().some(
(k) => k.service === service && k.modelFamilies.includes(modelFamily)
);
const hasKeys = keyPool.list().some((k) => {
return k.service === service && k.modelFamilies.includes(modelFamily);
});
const wait = info[modelFamily]?.estimatedQueueTime;
if (hasKeys && wait) {
@@ -257,7 +133,9 @@ This proxy keeps full logs of all prompts and AI responses. Prompt logs are anon
}
infoBody += "\n\n" + waits.join(" / ");
infoBody += customGreeting;
infoBody += buildRecentImageSection();
return converter.makeHtml(infoBody);
@@ -265,60 +143,55 @@ This proxy keeps full logs of all prompts and AI responses. Prompt logs are anon
function getSelfServiceLinks() {
if (config.gatekeeper !== "user_token") return "";
const links = [["Check your user token", "/user/lookup"]];
if (config.captchaMode !== "none") {
links.unshift(["Request a user token", "/user/captcha"]);
}
return `<div class="self-service-links">${links
.map(([t, l]) => `<a href="${l}">${t}</a>`)
.join(" | ")}</div>`;
return `<footer style="font-size: 0.8em;"><hr /><a target="_blank" href="/user/lookup">Check your user token info</a></footer>`;
}
function getServerTitle() {
if (process.env.SERVER_TITLE) return process.env.SERVER_TITLE;
if (process.env.SPACE_ID)
// Use manually set title if available
if (process.env.SERVER_TITLE) {
return process.env.SERVER_TITLE;
}
// Huggingface
if (process.env.SPACE_ID) {
return `${process.env.SPACE_AUTHOR_NAME} / ${process.env.SPACE_TITLE}`;
if (process.env.RENDER)
}
// Render
if (process.env.RENDER) {
return `Render / ${process.env.RENDER_SERVICE_NAME}`;
return "Tunnel";
}
return "OAI Reverse Proxy";
}
function buildRecentImageSection() {
const imageModels: ModelFamily[] = [
"azure-dall-e",
"dall-e",
"gpt-image",
"azure-gpt-image",
];
// Condition 1: Is the feature enabled via config?
// Condition 2: Is at least one relevant image model family allowed in config?
const dalleModels: ModelFamily[] = ["azure-dall-e", "dall-e"];
if (
!config.showRecentImages ||
imageModels.every((f) => !config.allowedModelFamilies.includes(f))
dalleModels.every((f) => !config.allowedModelFamilies.includes(f))
) {
return ""; // Exit if feature is disabled or no relevant models are allowed
}
// Condition 3: Are there any actual images to display?
const recentImages = getLastNImages(12).reverse();
if (recentImages.length === 0) {
// If the feature is enabled and models are allowed, but no images exist,
// do not render the section, including its title.
return "";
}
// If all conditions pass (feature enabled, models allowed, images exist), build and return the HTML
let html = `<h2>Recent Image Generations</h2>`;
html += `<div style="display:flex;flex-wrap:wrap;" id="recent-images">`;
let html = `<h2>Recent DALL-E Generations</h2>`;
const recentImages = getLastNImages(12).reverse();
if (recentImages.length === 0) {
html += `<p>No images yet.</p>`;
return html;
}
html += `<div style="display: flex; flex-wrap: wrap;" id="recent-images">`;
for (const { url, prompt } of recentImages) {
const thumbUrl = url.replace(/\.png$/, "_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><p style="clear:both;text-align:center;">
<a href="/user/image-history">View all recent images</a></p>`;
html += `</div>`;
html += `<p style="clear: both; text-align: center;"><a href="/user/image-history">View all recent images</a></p>`
return html;
}
@@ -328,76 +201,60 @@ function escapeHtml(unsafe: string) {
.replace(/</g, "&lt;")
.replace(/>/g, "&gt;")
.replace(/"/g, "&quot;")
.replace(/'/g, "&#39;")
.replace(/\[/g, "&#91;")
.replace(/]/g, "&#93;");
.replace(/'/g, "&#39;");
}
function getExternalUrlForHuggingfaceSpaceId(spaceId: string) {
try {
const [u, s] = spaceId.split("/");
return `https://${u}-${s.replace(/_/g, "-")}.hf.space`;
} catch {
const [username, spacename] = spaceId.split("/");
return `https://${username}-${spacename.replace(/_/g, "-")}.hf.space`;
} catch (e) {
return "";
}
}
/* ──────────────── ROUTER ─────────────────────────────────── */
const infoPageRouter = Router();
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: ${reason}`));
} else {
// User doesn't exist
return res
.status(401)
.send(renderLoginPage(res.locals.csrfToken, "Invalid token. Please try again."));
}
function checkIfUnlocked(
req: Request,
res: Response,
next: express.NextFunction
) {
if (config.serviceInfoPassword?.length && !req.session?.unlocked) {
return res.redirect("/unlock-info");
}
});
/* GET / – either login form or info page */
if (config.enableInfoPageLogin) {
infoPageRouter.get(LOGIN_ROUTE, requireLogin, handleInfoPage);
} else {
infoPageRouter.get(LOGIN_ROUTE, handleInfoPage);
next();
}
/* ─── Removed the public /status route : simply not added ─── */
const infoPageRouter = Router();
if (config.serviceInfoPassword?.length) {
infoPageRouter.use(
express.json({ limit: "1mb" }),
express.urlencoded({ extended: true, limit: "1mb" })
);
infoPageRouter.use(withSession);
infoPageRouter.use(injectCsrfToken, checkCsrfToken);
infoPageRouter.post("/unlock-info", (req, res) => {
if (req.body.password !== config.serviceInfoPassword) {
return res.status(403).send("Incorrect password");
}
req.session!.unlocked = true;
res.redirect("/");
});
infoPageRouter.get("/unlock-info", (_req, res) => {
if (_req.session?.unlocked) return res.redirect("/");
res.send(`
<form method="post" action="/unlock-info">
<h1>Unlock Service Info</h1>
<input type="hidden" name="_csrf" value="${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));
});
export { infoPageRouter };
src/proxy/add-v1.ts
-9
View File
@@ -1,9 +0,0 @@
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.match(/^\/(v1alpha|v1beta)\//)) {
req.url = `/v1${req.url}`;
}
next();
}
src/proxy/anthropic.ts
+171 -200
View File
@@ -1,16 +1,22 @@
import { Request, RequestHandler, Router } from "express";
import { Request, Response, RequestHandler, Router } from "express";
import { createProxyMiddleware } from "http-proxy-middleware";
import { config } from "../config";
import { logger } from "../logger";
import { createQueueMiddleware } from "./queue";
import { ipLimiter } from "./rate-limit";
import { handleProxyError } from "./middleware/common";
import {
addKey,
addAnthropicPreamble,
createPreprocessorMiddleware,
finalizeBody,
createOnProxyReqHandler,
} 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 { claudeModels } from "../shared/claude-models";
import { validateClaude41OpusParameters } from "../shared/claude-4-1-validation";
import {
ProxyResHandlerWithBody,
createOnProxyResHandler,
} from "./middleware/response";
import { sendErrorToClient } from "./middleware/response/error-generator";
let modelsCache: any = null;
let modelsCacheTime = 0;
@@ -20,32 +26,40 @@ const getModelsResponse = () => {
return modelsCache;
}
if (!config.anthropicKey) return { object: "list", data: [], has_more: false, first_id: null, last_id: null };
if (!config.anthropicKey) return { object: "list", data: [] };
const date = new Date()
const models = claudeModels.map(model => ({
// Common
id: model.anthropicId,
owned_by: "anthropic",
// Anthropic
type: "model",
display_name: model.displayName,
created_at: date.toISOString(),
// OpenAI
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-opus-20240229",
"claude-3-sonnet-20240229",
];
const models = claudeVariants.map((id) => ({
id,
object: "model",
created: date.getTime(),
}));
created: new Date().getTime(),
owned_by: "anthropic",
permission: [],
root: "claude",
parent: null,
}));
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();
modelsCache = { object: "list", data: models };
modelsCacheTime = new Date().getTime();
return modelsCache;
};
@@ -54,7 +68,8 @@ const handleModelRequest: RequestHandler = (_req, res) => {
res.status(200).json(getModelsResponse());
};
const anthropicBlockingResponseHandler: ProxyResHandlerWithBody = async (
/** Only used for non-streaming requests. */
const anthropicResponseHandler: ProxyResHandlerWithBody = async (
_proxyRes,
req,
res,
@@ -107,6 +122,12 @@ export function transformAnthropicChatResponseToAnthropicText(
};
}
/**
* Transforms a model response from the Anthropic API to match those from the
* OpenAI API, for users using Claude via the OpenAI-compatible endpoint. This
* is only used for non-streaming requests as streaming requests are handled
* on-the-fly.
*/
function transformAnthropicTextResponseToOpenAI(
anthropicBody: Record<string, any>,
req: Request
@@ -135,7 +156,7 @@ function transformAnthropicTextResponseToOpenAI(
};
}
export function transformAnthropicChatResponseToOpenAI(
function transformAnthropicChatResponseToOpenAI(
anthropicBody: Record<string, any>
): Record<string, any> {
return {
@@ -157,187 +178,75 @@ export function transformAnthropicChatResponseToOpenAI(
};
}
/**
* If a client using the OpenAI compatibility endpoint requests an actual OpenAI
* model, reassigns it to Sonnet.
*/
function maybeReassignModel(req: Request) {
const model = req.body.model;
if (model.includes("claude")) return; // use whatever model the user requested
req.body.model = "claude-3-5-sonnet-latest";
}
/**
* 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) {
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) {
const req = manager.request;
const pathname = req.url.split("?")[0];
req.log.debug({ pathname }, "Anthropic path filter");
const isText = req.outboundApi === "anthropic-text";
const isChat = req.outboundApi === "anthropic-chat";
if (isChat && pathname === "/v1/complete") {
manager.setPath("/v1/messages");
}
if (isText && pathname === "/v1/chat/completions") {
manager.setPath("/v1/complete");
}
if (isChat && pathname === "/v1/chat/completions") {
manager.setPath("/v1/messages");
}
if (isChat && ["sonnet", "opus"].includes(req.params.type)) {
manager.setPath("/v1/messages");
}
}
const anthropicProxy = createQueuedProxyMiddleware({
target: "https://api.anthropic.com",
mutations: [selectUpstreamPath, addKey, finalizeBody],
blockingResponseHandler: anthropicBlockingResponseHandler,
const anthropicProxy = createQueueMiddleware({
proxyMiddleware: createProxyMiddleware({
target: "https://api.anthropic.com",
changeOrigin: true,
selfHandleResponse: true,
logger,
on: {
proxyReq: createOnProxyReqHandler({
pipeline: [addKey, addAnthropicPreamble, finalizeBody],
}),
proxyRes: createOnProxyResHandler([anthropicResponseHandler]),
error: handleProxyError,
},
// Abusing pathFilter to rewrite the paths dynamically.
pathFilter: (pathname, req) => {
const isText = req.outboundApi === "anthropic-text";
const isChat = req.outboundApi === "anthropic-chat";
if (isChat && pathname === "/v1/complete") {
req.url = "/v1/messages";
}
if (isText && pathname === "/v1/chat/completions") {
req.url = "/v1/complete";
}
if (isChat && pathname === "/v1/chat/completions") {
req.url = "/v1/messages";
}
if (isChat && ["sonnet", "opus"].includes(req.params.type)) {
req.url = "/v1/messages";
}
return true;
},
}),
});
const nativeAnthropicChatPreprocessor = createPreprocessorMiddleware(
{ inApi: "anthropic-chat", outApi: "anthropic-chat", service: "anthropic" },
{ 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",
},
{ afterTransform: [setAnthropicBetaHeader, addWebSearchTool] }
);
const textToChatPreprocessor = createPreprocessorMiddleware({
inApi: "anthropic-text",
outApi: "anthropic-chat",
service: "anthropic",
});
/**
* 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) => {
const model = req.body.model;
const isClaude4Model = model?.includes("claude-sonnet-4") || model?.includes("claude-opus-4");
if (model?.startsWith("claude-3") || isClaude4Model) {
if (req.body.model?.startsWith("claude-3")) {
textToChatPreprocessor(req, res, next);
} else {
nativeTextPreprocessor(req, res, next);
}
};
const oaiToTextPreprocessor = createPreprocessorMiddleware(
{
inApi: "openai",
outApi: "anthropic-text",
service: "anthropic",
},
{ afterTransform: [setAnthropicBetaHeader] }
);
const oaiToTextPreprocessor = createPreprocessorMiddleware({
inApi: "openai",
outApi: "anthropic-text",
service: "anthropic",
});
const oaiToChatPreprocessor = createPreprocessorMiddleware(
{
inApi: "openai",
outApi: "anthropic-chat",
service: "anthropic",
},
{ afterTransform: [setAnthropicBetaHeader, addWebSearchTool] }
);
const oaiToChatPreprocessor = createPreprocessorMiddleware({
inApi: "openai",
outApi: "anthropic-chat",
service: "anthropic",
});
/**
* Routes an OpenAI prompt to either the legacy Claude text completion endpoint
@@ -345,9 +254,7 @@ const oaiToChatPreprocessor = createPreprocessorMiddleware(
*/
const preprocessOpenAICompatRequest: RequestHandler = (req, res, next) => {
maybeReassignModel(req);
const model = req.body.model;
const isClaude4 = model?.includes("claude-sonnet-4") || model?.includes("claude-opus-4");
if (model?.includes("claude-3") || isClaude4) {
if (req.body.model?.includes("claude-3")) {
oaiToChatPreprocessor(req, res, next);
} else {
oaiToTextPreprocessor(req, res, next);
@@ -360,7 +267,11 @@ anthropicRouter.get("/v1/models", handleModelRequest);
anthropicRouter.post(
"/v1/messages",
ipLimiter,
nativeAnthropicChatPreprocessor,
createPreprocessorMiddleware({
inApi: "anthropic-chat",
outApi: "anthropic-chat",
service: "anthropic",
}),
anthropicProxy
);
// Anthropic text completion endpoint. Translates to Anthropic chat completion
@@ -380,5 +291,65 @@ anthropicRouter.post(
preprocessOpenAICompatRequest,
anthropicProxy
);
// Temporarily force Anthropic Text to Anthropic Chat for frontends which do not
// yet support the new model. Forces claude-3. Will be removed once common
// frontends have been updated.
anthropicRouter.post(
"/v1/:type(sonnet|opus)/:action(complete|messages)",
ipLimiter,
handleAnthropicTextCompatRequest,
createPreprocessorMiddleware({
inApi: "anthropic-text",
outApi: "anthropic-chat",
service: "anthropic",
}),
anthropicProxy
);
function handleAnthropicTextCompatRequest(
req: Request,
res: Response,
next: any
) {
const type = req.params.type;
const action = req.params.action;
const alreadyInChatFormat = Boolean(req.body.messages);
const compatModel = `claude-3-${type}-20240229`;
req.log.info(
{ type, inputModel: req.body.model, compatModel, alreadyInChatFormat },
"Handling Anthropic compatibility request"
);
if (action === "messages" || alreadyInChatFormat) {
return sendErrorToClient({
req,
res,
options: {
title: "Unnecessary usage of compatibility endpoint",
message: `Your client seems to already support the new Claude API format. This endpoint is intended for clients that do not yet support the new format.\nUse the normal \`/anthropic\` proxy endpoint instead.`,
format: "unknown",
statusCode: 400,
reqId: req.id,
obj: {
requested_endpoint: "/anthropic/" + type,
correct_endpoint: "/anthropic",
},
},
});
}
req.body.model = compatModel;
next();
}
/**
* If a client using the OpenAI compatibility endpoint requests an actual OpenAI
* model, reassigns it to Claude 3 Sonnet.
*/
function maybeReassignModel(req: Request) {
const model = req.body.model;
if (!model.startsWith("gpt-")) return;
req.body.model = "claude-3-sonnet-20240229";
}
export const anthropic = anthropicRouter;
src/proxy/aws-claude.ts
-341
View File
@@ -1,341 +0,0 @@
import { Request, RequestHandler, Router } from "express";
import { v4 } from "uuid";
import {
transformAnthropicChatResponseToAnthropicText,
transformAnthropicChatResponseToOpenAI,
} from "./anthropic";
import { ipLimiter } from "./rate-limit";
import {
createPreprocessorMiddleware,
finalizeSignedRequest,
signAwsRequest,
} 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,
req,
res,
body
) => {
if (typeof body !== "object") {
throw new Error("Expected body to be an object");
}
let newBody = body;
switch (`${req.inboundApi}<-${req.outboundApi}`) {
case "openai<-anthropic-text":
req.log.info("Transforming Anthropic Text back to OpenAI format");
newBody = transformAwsTextResponseToOpenAI(body, req);
break;
case "openai<-anthropic-chat":
req.log.info("Transforming AWS Anthropic Chat back to OpenAI format");
newBody = transformAnthropicChatResponseToOpenAI(body);
break;
case "anthropic-text<-anthropic-chat":
req.log.info("Transforming AWS Anthropic Chat back to Text format");
newBody = transformAnthropicChatResponseToAnthropicText(body);
break;
}
// AWS does not always confirm the model in the response, so we have to add it
if (!newBody.model && req.body.model) {
newBody.model = req.body.model;
}
res.status(200).json({ ...newBody, proxy: body.proxy });
};
function transformAwsTextResponseToOpenAI(
awsBody: Record<string, any>,
req: Request
): Record<string, any> {
const totalTokens = (req.promptTokens ?? 0) + (req.outputTokens ?? 0);
return {
id: "aws-" + v4(),
object: "chat.completion",
created: Date.now(),
model: req.body.model,
usage: {
prompt_tokens: req.promptTokens,
completion_tokens: req.outputTokens,
total_tokens: totalTokens,
},
choices: [
{
message: {
role: "assistant",
content: awsBody.completion?.trim(),
},
finish_reason: awsBody.stop_reason,
index: 0,
},
],
};
}
const awsClaudeProxy = createQueuedProxyMiddleware({
target: ({ signedRequest }) => {
if (!signedRequest) throw new Error("Must sign request before proxying");
return `${signedRequest.protocol}//${signedRequest.hostname}`;
},
mutations: [signAwsRequest, finalizeSignedRequest],
blockingResponseHandler: awsBlockingResponseHandler,
});
const nativeTextPreprocessor = createPreprocessorMiddleware(
{ inApi: "anthropic-text", outApi: "anthropic-text", service: "aws" },
{ afterTransform: [maybeReassignModel] }
);
const textToChatPreprocessor = createPreprocessorMiddleware(
{ inApi: "anthropic-text", outApi: "anthropic-chat", service: "aws" },
{ afterTransform: [maybeReassignModel] }
);
/**
* Routes text completion prompts to aws anthropic-chat if they need translation
* (claude-3 based models do not support the old text completion endpoint).
*/
const preprocessAwsTextRequest: RequestHandler = (req, res, next) => {
if (req.body.model?.includes("claude-3")) {
textToChatPreprocessor(req, res, next);
} else {
nativeTextPreprocessor(req, res, next);
}
};
const oaiToAwsTextPreprocessor = createPreprocessorMiddleware(
{ inApi: "openai", outApi: "anthropic-text", service: "aws" },
{ afterTransform: [maybeReassignModel] }
);
const oaiToAwsChatPreprocessor = createPreprocessorMiddleware(
{ inApi: "openai", outApi: "anthropic-chat", service: "aws" },
{ afterTransform: [maybeReassignModel] }
);
/**
* Routes an OpenAI prompt to either the legacy Claude text completion endpoint
* or the new Claude chat completion endpoint, based on the requested model.
*/
const preprocessOpenAICompatRequest: RequestHandler = (req, res, next) => {
if (req.body.model?.includes("claude-3")) {
oaiToAwsChatPreprocessor(req, res, next);
} else {
oaiToAwsTextPreprocessor(req, res, next);
}
};
const awsClaudeRouter = Router();
// Native(ish) Anthropic text completion endpoint.
awsClaudeRouter.post(
"/v1/complete",
ipLimiter,
preprocessAwsTextRequest,
awsClaudeProxy
);
// Native Anthropic chat completion endpoint.
awsClaudeRouter.post(
"/v1/messages",
ipLimiter,
createPreprocessorMiddleware(
{ inApi: "anthropic-chat", outApi: "anthropic-chat", service: "aws" },
{ afterTransform: [maybeReassignModel] }
),
awsClaudeProxy
);
// OpenAI-to-AWS Anthropic compatibility endpoint.
awsClaudeRouter.post(
"/v1/chat/completions",
ipLimiter,
preprocessOpenAICompatRequest,
awsClaudeProxy
);
/**
* Tries to deal with:
* - frontends sending AWS model names even when they want to use the OpenAI-
* compatible endpoint
* - frontends sending Anthropic model names that AWS doesn't recognize
* - frontends sending OpenAI model names because they expect the proxy to
* translate them
*
* If client sends AWS model ID it will be used verbatim. Otherwise, various
* 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
if (model.includes("anthropic.claude")) {
return;
}
// Anthropic model names can look like:
// - claude-v1
// - claude-2.1
// - 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 =
/^(?: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.`);
}
// 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}.${minor}` : major;
switch (ver) {
case "1":
case "1.0":
req.body.model = "anthropic.claude-v1";
return;
case "2":
case "2.0":
req.body.model = "anthropic.claude-v2";
return;
case "2.1":
req.body.model = "anthropic.claude-v2:1";
return;
case "3":
case "3.0":
// there is only one snapshot for all Claude 3 models so there is no need
// to check the revision
switch (name) {
case "sonnet":
req.body.model = "anthropic.claude-3-sonnet-20240229-v1:0";
return;
case "haiku":
req.body.model = "anthropic.claude-3-haiku-20240307-v1:0";
return;
case "opus":
req.body.model = "anthropic.claude-3-opus-20240229-v1:0";
return;
}
break;
case "3.5":
switch (name) {
case "sonnet":
switch (rev) {
case "20241022":
case "latest":
req.body.model = "anthropic.claude-3-5-sonnet-20241022-v2:0";
return;
case "20240620":
req.body.model = "anthropic.claude-3-5-sonnet-20240620-v1:0";
return;
}
break;
case "haiku":
switch (rev) {
case "20241022":
case "latest":
req.body.model = "anthropic.claude-3-5-haiku-20241022-v1:0";
return;
}
case "opus":
// Add after model id is announced never
break;
}
case "3.7":
switch (name) {
case "sonnet":
req.body.model = "anthropic.claude-3-7-sonnet-20250219-v1:0";
return;
}
break;
case "4":
case "4.0":
// Mapping "claude-4-..." variants to their actual AWS Bedrock IDs
// as defined in src/shared/claude-models.ts.
switch (name) {
case "sonnet":
req.body.model = "anthropic.claude-sonnet-4-20250514-v1:0";
return;
case "opus":
req.body.model = "anthropic.claude-opus-4-20250514-v1:0";
return;
// No case for "haiku" here, as "claude-4-haiku" is not defined
// in claude-models.ts. It will fall through and throw an error.
}
break;
case "4.1":
// Mapping "claude-4.1-..." variants to their actual AWS Bedrock IDs
// as defined in src/shared/claude-models.ts.
switch (name) {
case "opus":
req.body.model = "anthropic.claude-opus-4-1-20250805-v1:0";
return;
// No sonnet or haiku variants for 4.1 yet
}
break;
}
throw new Error(`Provided model name (${model}) could not be mapped to a known AWS Claude model ID.`);
}
export const awsClaude = awsClaudeRouter;
src/proxy/aws-mistral.ts
-95
View File
@@ -1,95 +0,0 @@
import { Request, Router } from "express";
import {
detectMistralInputApi,
transformMistralTextToMistralChat,
} from "./mistral-ai";
import { ipLimiter } from "./rate-limit";
import { ProxyResHandlerWithBody } from "./middleware/response";
import {
createPreprocessorMiddleware,
finalizeSignedRequest,
signAwsRequest,
} from "./middleware/request";
import { createQueuedProxyMiddleware } from "./middleware/request/proxy-middleware-factory";
const awsMistralBlockingResponseHandler: ProxyResHandlerWithBody = async (
_proxyRes,
req,
res,
body
) => {
if (typeof body !== "object") {
throw new Error("Expected body to be an object");
}
let newBody = body;
if (req.inboundApi === "mistral-ai" && req.outboundApi === "mistral-text") {
newBody = transformMistralTextToMistralChat(body);
}
// AWS does not always confirm the model in the response, so we have to add it
if (!newBody.model && req.body.model) {
newBody.model = req.body.model;
}
res.status(200).json({ ...newBody, proxy: body.proxy });
};
const awsMistralProxy = createQueuedProxyMiddleware({
target: ({ signedRequest }) => {
if (!signedRequest) throw new Error("Must sign request before proxying");
return `${signedRequest.protocol}//${signedRequest.hostname}`;
},
mutations: [signAwsRequest,finalizeSignedRequest],
blockingResponseHandler: awsMistralBlockingResponseHandler,
});
function maybeReassignModel(req: Request) {
const model = req.body.model;
// If it looks like an AWS model, use it as-is
if (model.startsWith("mistral.")) {
return;
}
// Mistral 7B Instruct
else if (model.includes("7b")) {
req.body.model = "mistral.mistral-7b-instruct-v0:2";
}
// Mistral 8x7B Instruct
else if (model.includes("8x7b")) {
req.body.model = "mistral.mixtral-8x7b-instruct-v0:1";
}
// Mistral Large (Feb 2024)
else if (model.includes("large-2402")) {
req.body.model = "mistral.mistral-large-2402-v1:0";
}
// Mistral Large 2 (July 2024)
else if (model.includes("large")) {
req.body.model = "mistral.mistral-large-2407-v1:0";
}
// Mistral Small (Feb 2024)
else if (model.includes("small")) {
req.body.model = "mistral.mistral-small-2402-v1:0";
} else {
throw new Error(
`Can't map '${model}' to a supported AWS model ID; make sure you are requesting a Mistral model supported by Amazon Bedrock`
);
}
}
const nativeMistralChatPreprocessor = createPreprocessorMiddleware(
{ inApi: "mistral-ai", outApi: "mistral-ai", service: "aws" },
{
beforeTransform: [detectMistralInputApi],
afterTransform: [maybeReassignModel],
}
);
const awsMistralRouter = Router();
awsMistralRouter.post(
"/v1/chat/completions",
ipLimiter,
nativeMistralChatPreprocessor,
awsMistralProxy
);
export const awsMistral = awsMistralRouter;
src/proxy/aws.ts
+290 -81
View File
@@ -1,98 +1,307 @@
/* Shared code between AWS Claude and AWS Mistral endpoints. */
import { Request, Response, Router } from "express";
import { Request, RequestHandler, Response, Router } from "express";
import { createProxyMiddleware } from "http-proxy-middleware";
import { v4 } from "uuid";
import { config } from "../config";
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";
import { logger } from "../logger";
import { createQueueMiddleware } from "./queue";
import { ipLimiter } from "./rate-limit";
import { handleProxyError } from "./middleware/common";
import {
createPreprocessorMiddleware,
signAwsRequest,
finalizeSignedRequest,
createOnProxyReqHandler,
} from "./middleware/request";
import {
ProxyResHandlerWithBody,
createOnProxyResHandler,
} from "./middleware/response";
import { transformAnthropicChatResponseToAnthropicText } from "./anthropic";
import { sendErrorToClient } from "./middleware/response/error-generator";
const awsRouter = Router();
awsRouter.get(["/:vendor?/v1/models", "/:vendor?/models"], handleModelsRequest);
awsRouter.use("/claude", addV1, awsClaude);
awsRouter.use("/mistral", addV1, awsMistral);
const LATEST_AWS_V2_MINOR_VERSION = "1";
let modelsCache: any = null;
let modelsCacheTime = 0;
const getModelsResponse = () => {
if (new Date().getTime() - modelsCacheTime < 1000 * 60) {
return modelsCache;
}
const MODELS_CACHE_TTL = 10000;
let modelsCache: Record<string, any> = {};
let modelsCacheTime: Record<string, number> = {};
function handleModelsRequest(req: Request, res: Response) {
if (!config.awsCredentials) return { object: "list", data: [] };
const vendor = req.params.vendor?.length
? req.params.vendor === "claude"
? "anthropic"
: req.params.vendor
: "all";
// https://docs.aws.amazon.com/bedrock/latest/userguide/model-ids.html
const variants = [
"anthropic.claude-v2",
"anthropic.claude-v2:1",
"anthropic.claude-3-haiku-20240307-v1:0",
"anthropic.claude-3-sonnet-20240229-v1:0",
];
const cacheTime = modelsCacheTime[vendor] || 0;
if (new Date().getTime() - cacheTime < MODELS_CACHE_TTL) {
return res.json(modelsCache[vendor]);
const models = variants.map((id) => ({
id,
object: "model",
created: new Date().getTime(),
owned_by: "anthropic",
permission: [],
root: "claude",
parent: null,
}));
modelsCache = { object: "list", data: models };
modelsCacheTime = new Date().getTime();
return modelsCache;
};
const handleModelRequest: RequestHandler = (_req, res) => {
res.status(200).json(getModelsResponse());
};
/** Only used for non-streaming requests. */
const awsResponseHandler: ProxyResHandlerWithBody = async (
_proxyRes,
req,
res,
body
) => {
if (typeof body !== "object") {
throw new Error("Expected body to be an object");
}
const availableAwsModelIds = new Set<string>();
for (const key of keyPool.list()) {
if (key.isDisabled || key.service !== "aws") continue;
(key as AwsBedrockKey).modelIds.forEach((id) => availableAwsModelIds.add(id));
let newBody = body;
switch (`${req.inboundApi}<-${req.outboundApi}`) {
case "openai<-anthropic-text":
req.log.info("Transforming Anthropic Text back to OpenAI format");
newBody = transformAwsTextResponseToOpenAI(body, req);
break;
// case "openai<-anthropic-chat":
// todo: implement this
case "anthropic-text<-anthropic-chat":
req.log.info("Transforming AWS Anthropic Chat back to Text format");
newBody = transformAnthropicChatResponseToAnthropicText(body);
break;
}
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"],
]);
// AWS does not always confirm the model in the response, so we have to add it
if (!newBody.model && req.body.model) {
newBody.model = req.body.model;
}
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: date.getTime(),
permission: [],
root: "mistral",
parent: null,
};
});
res.status(200).json({ ...newBody, proxy: body.proxy });
};
const allModels = [...claudeModelsList, ...mistralModelsList];
const filteredModels = vendor === "all"
? allModels
: allModels.filter(m => m.root === vendor);
modelsCache[vendor] = {
object: "list",
data: filteredModels,
has_more: false,
first_id: filteredModels[0]?.id,
last_id: filteredModels[filteredModels.length - 1]?.id,
/**
* Transforms a model response from the Anthropic API to match those from the
* OpenAI API, for users using Claude via the OpenAI-compatible endpoint. This
* is only used for non-streaming requests as streaming requests are handled
* on-the-fly.
*/
function transformAwsTextResponseToOpenAI(
awsBody: Record<string, any>,
req: Request
): Record<string, any> {
const totalTokens = (req.promptTokens ?? 0) + (req.outputTokens ?? 0);
return {
id: "aws-" + v4(),
object: "chat.completion",
created: Date.now(),
model: req.body.model,
usage: {
prompt_tokens: req.promptTokens,
completion_tokens: req.outputTokens,
total_tokens: totalTokens,
},
choices: [
{
message: {
role: "assistant",
content: awsBody.completion?.trim(),
},
finish_reason: awsBody.stop_reason,
index: 0,
},
],
};
modelsCacheTime[vendor] = date.getTime();
}
return res.json(modelsCache[vendor]);
const awsProxy = createQueueMiddleware({
beforeProxy: signAwsRequest,
proxyMiddleware: createProxyMiddleware({
target: "bad-target-will-be-rewritten",
router: ({ signedRequest }) => {
if (!signedRequest) throw new Error("Must sign request before proxying");
return `${signedRequest.protocol}//${signedRequest.hostname}`;
},
changeOrigin: true,
selfHandleResponse: true,
logger,
on: {
proxyReq: createOnProxyReqHandler({ pipeline: [finalizeSignedRequest] }),
proxyRes: createOnProxyResHandler([awsResponseHandler]),
error: handleProxyError,
},
}),
});
const nativeTextPreprocessor = createPreprocessorMiddleware(
{ inApi: "anthropic-text", outApi: "anthropic-text", service: "aws" },
{ afterTransform: [maybeReassignModel] }
);
const textToChatPreprocessor = createPreprocessorMiddleware(
{ inApi: "anthropic-text", outApi: "anthropic-chat", service: "aws" },
{ afterTransform: [maybeReassignModel] }
);
/**
* Routes text completion prompts to aws anthropic-chat if they need translation
* (claude-3 based models do not support the old text completion endpoint).
*/
const awsTextCompletionRouter: RequestHandler = (req, res, next) => {
if (req.body.model?.includes("claude-3")) {
textToChatPreprocessor(req, res, next);
} else {
nativeTextPreprocessor(req, res, next);
}
};
const awsRouter = Router();
awsRouter.get("/v1/models", handleModelRequest);
// Native(ish) Anthropic text completion endpoint.
awsRouter.post("/v1/complete", ipLimiter, awsTextCompletionRouter, awsProxy);
// Native Anthropic chat completion endpoint.
awsRouter.post(
"/v1/messages",
ipLimiter,
createPreprocessorMiddleware(
{ inApi: "anthropic-chat", outApi: "anthropic-chat", service: "aws" },
{ afterTransform: [maybeReassignModel] }
),
awsProxy
);
// Temporary force-Claude3 endpoint
awsRouter.post(
"/v1/sonnet/:action(complete|messages)",
ipLimiter,
handleCompatibilityRequest,
createPreprocessorMiddleware({
inApi: "anthropic-text",
outApi: "anthropic-chat",
service: "aws",
}),
awsProxy
);
// OpenAI-to-AWS Anthropic compatibility endpoint.
awsRouter.post(
"/v1/chat/completions",
ipLimiter,
createPreprocessorMiddleware(
{ inApi: "openai", outApi: "anthropic-text", service: "aws" },
{ afterTransform: [maybeReassignModel] }
),
awsProxy
);
/**
* Tries to deal with:
* - frontends sending AWS model names even when they want to use the OpenAI-
* compatible endpoint
* - frontends sending Anthropic model names that AWS doesn't recognize
* - frontends sending OpenAI model names because they expect the proxy to
* translate them
*/
function maybeReassignModel(req: Request) {
const model = req.body.model;
// If client already specified an AWS Claude model ID, use it
if (model.includes("anthropic.claude")) {
return;
}
const pattern =
/^(claude-)?(instant-)?(v)?(\d+)(\.(\d+))?(-\d+k)?(-sonnet-?|-opus-?)(\d*)/i;
const match = model.match(pattern);
// If there's no match, return the latest v2 model
if (!match) {
req.body.model = `anthropic.claude-v2:${LATEST_AWS_V2_MINOR_VERSION}`;
return;
}
const instant = match[2];
const major = match[4];
const minor = match[6];
if (instant) {
req.body.model = "anthropic.claude-instant-v1";
return;
}
// There's only one v1 model
if (major === "1") {
req.body.model = "anthropic.claude-v1";
return;
}
// Try to map Anthropic API v2 models to AWS v2 models
if (major === "2") {
if (minor === "0") {
req.body.model = "anthropic.claude-v2";
return;
}
req.body.model = `anthropic.claude-v2:${LATEST_AWS_V2_MINOR_VERSION}`;
return;
}
// AWS currently only supports one v3 model.
const variant = match[8]; // sonnet or opus
const variantVersion = match[9];
if (major === "3") {
req.body.model = "anthropic.claude-3-sonnet-20240229-v1:0";
return;
}
// Fallback to latest v2 model
req.body.model = `anthropic.claude-v2:${LATEST_AWS_V2_MINOR_VERSION}`;
return;
}
export function handleCompatibilityRequest(
req: Request,
res: Response,
next: any
) {
const action = req.params.action;
const alreadyInChatFormat = Boolean(req.body.messages);
const compatModel = "anthropic.claude-3-sonnet-20240229-v1:0";
req.log.info(
{ inputModel: req.body.model, compatModel, alreadyInChatFormat },
"Handling AWS compatibility request"
);
if (action === "messages" || alreadyInChatFormat) {
return sendErrorToClient({
req,
res,
options: {
title: "Unnecessary usage of compatibility endpoint",
message: `Your client seems to already support the new Claude API format. This endpoint is intended for clients that do not yet support the new format.\nUse the normal \`/aws/claude\` proxy endpoint instead.`,
format: "unknown",
statusCode: 400,
reqId: req.id,
obj: {
requested_endpoint: "/aws/claude/sonnet",
correct_endpoint: "/aws/claude",
},
},
});
}
req.body.model = compatModel;
next();
}
export const aws = awsRouter;
src/proxy/azure.ts
+70 -18
View File
@@ -1,30 +1,73 @@
import { RequestHandler, Router } from "express";
import { createProxyMiddleware } from "http-proxy-middleware";
import { config } from "../config";
import { generateModelList } from "./openai";
import { keyPool } from "../shared/key-management";
import {
AzureOpenAIModelFamily,
getAzureOpenAIModelFamily,
ModelFamily,
} from "../shared/models";
import { logger } from "../logger";
import { KNOWN_OPENAI_MODELS } from "./openai";
import { createQueueMiddleware } from "./queue";
import { ipLimiter } from "./rate-limit";
import { handleProxyError } from "./middleware/common";
import {
addAzureKey,
createOnProxyReqHandler,
createPreprocessorMiddleware,
finalizeSignedRequest,
} from "./middleware/request";
import { ProxyResHandlerWithBody } from "./middleware/response";
import { createQueuedProxyMiddleware } from "./middleware/request/proxy-middleware-factory";
import {
createOnProxyResHandler,
ProxyResHandlerWithBody,
} from "./middleware/response";
let modelsCache: any = null;
let modelsCacheTime = 0;
const handleModelRequest: RequestHandler = (_req, res) => {
function getModelsResponse() {
if (new Date().getTime() - modelsCacheTime < 1000 * 60) {
return res.status(200).json(modelsCache);
return modelsCache;
}
if (!config.azureCredentials) return { object: "list", data: [] };
let available = new Set<AzureOpenAIModelFamily>();
for (const key of keyPool.list()) {
if (key.isDisabled || key.service !== "azure") continue;
key.modelFamilies.forEach((family) =>
available.add(family as AzureOpenAIModelFamily)
);
}
const allowed = new Set<ModelFamily>(config.allowedModelFamilies);
available = new Set([...available].filter((x) => allowed.has(x)));
const result = generateModelList("azure");
const models = KNOWN_OPENAI_MODELS.map((id) => ({
id,
object: "model",
created: new Date().getTime(),
owned_by: "azure",
permission: [
{
id: "modelperm-" + id,
object: "model_permission",
created: new Date().getTime(),
organization: "*",
group: null,
is_blocking: false,
},
],
root: id,
parent: null,
})).filter((model) => available.has(getAzureOpenAIModelFamily(model.id)));
modelsCache = { object: "list", data: result };
modelsCache = { object: "list", data: models };
modelsCacheTime = new Date().getTime();
res.status(200).json(modelsCache);
return modelsCache;
}
const handleModelRequest: RequestHandler = (_req, res) => {
res.status(200).json(getModelsResponse());
};
const azureOpenaiResponseHandler: ProxyResHandlerWithBody = async (
@@ -40,17 +83,26 @@ const azureOpenaiResponseHandler: ProxyResHandlerWithBody = async (
res.status(200).json({ ...body, proxy: body.proxy });
};
const azureOpenAIProxy = createQueuedProxyMiddleware({
target: ({ signedRequest }) => {
if (!signedRequest) throw new Error("Must sign request before proxying");
const { hostname, protocol } = signedRequest;
return `${protocol}//${hostname}`;
},
mutations: [addAzureKey, finalizeSignedRequest],
blockingResponseHandler: azureOpenaiResponseHandler,
const azureOpenAIProxy = createQueueMiddleware({
beforeProxy: addAzureKey,
proxyMiddleware: createProxyMiddleware({
target: "will be set by router",
router: (req) => {
if (!req.signedRequest) throw new Error("signedRequest not set");
const { hostname, path } = req.signedRequest;
return `https://${hostname}${path}`;
},
changeOrigin: true,
selfHandleResponse: true,
logger,
on: {
proxyReq: createOnProxyReqHandler({ pipeline: [finalizeSignedRequest] }),
proxyRes: createOnProxyResHandler([azureOpenaiResponseHandler]),
error: handleProxyError,
},
}),
});
const azureOpenAIRouter = Router();
azureOpenAIRouter.get("/v1/models", handleModelRequest);
azureOpenAIRouter.post(
src/proxy/cohere.ts
-222
View File
@@ -1,222 +0,0 @@
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;
src/proxy/deepseek.ts
-135
View File
@@ -1,135 +0,0 @@
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;
src/proxy/gatekeeper.ts
+10 -57
View File
@@ -1,7 +1,6 @@
import type { Request, Response, RequestHandler } from "express";
import type { Request, RequestHandler } from "express";
import { config } from "../config";
import { authenticate, getUser } from "../shared/users/user-store";
import { sendErrorToClient } from "./middleware/response/error-generator";
const GATEKEEPER = config.gatekeeper;
const PROXY_KEY = config.proxyKey;
@@ -12,7 +11,6 @@ function getProxyAuthorizationFromRequest(req: Request): string | undefined {
// pass the _proxy_ key in this header too, instead of providing it as a
// Bearer token in the Authorization header. So we need to check both.
// Prefer the Authorization header if both are present.
// Google AI uses a key querystring parameter.
if (req.headers.authorization) {
const token = req.headers.authorization?.slice("Bearer ".length);
@@ -26,18 +24,6 @@ function getProxyAuthorizationFromRequest(req: Request): string | undefined {
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();
delete req.query.key;
return token;
}
return undefined;
}
@@ -64,9 +50,9 @@ export const gatekeeper: RequestHandler = (req, res, next) => {
// IP alone to distinguish between them and prevent usertoken sharing.
// Risu sends a signed token in the request headers with an anonymous user
// ID that we can instead use to associate requests with an individual.
const ip = req.risuToken?.length
? `risu${req.risuToken}-${req.ip}`
: req.ip;
const ip = req.risuToken?.length ?
`risu${req.risuToken}-${req.ip}` :
req.ip;
const { user, result } = authenticate(token, ip);
@@ -75,50 +61,17 @@ export const gatekeeper: RequestHandler = (req, res, next) => {
req.user = user;
return next();
case "limited":
return sendError(
req,
res,
403,
`Forbidden: no more IP addresses allowed for this user token`,
{ currentIp: ip, maxIps: user?.maxIps }
);
return res.status(403).json({
error: `Forbidden: no more IPs can authenticate with this token`,
});
case "disabled":
const bannedUser = getUser(token);
if (bannedUser?.disabledAt) {
const reason = bannedUser.disabledReason || "User token disabled";
return sendError(req, res, 403, `Forbidden: ${reason}`);
const reason = bannedUser.disabledReason || "Token disabled";
return res.status(403).json({ error: `Forbidden: ${reason}` });
}
}
}
sendError(req, res, 401, "Unauthorized");
res.status(401).json({ error: "Unauthorized" });
};
function sendError(
req: Request,
res: Response,
status: number,
message: string,
data: any = {}
) {
const isPost = req.method === "POST";
const hasBody = isPost && req.body;
const hasModel = hasBody && req.body.model;
if (!hasModel) {
return res.status(status).json({ error: message });
}
sendErrorToClient({
req,
res,
options: {
title: `Proxy gatekeeper error (HTTP ${status})`,
message,
format: "unknown",
statusCode: status,
reqId: req.id,
obj: data,
},
});
}
src/proxy/gcp.ts
-257
View File
@@ -1,257 +0,0 @@
import { Request, RequestHandler, Router } from "express";
import { config } from "../config";
import { transformAnthropicChatResponseToOpenAI } from "./anthropic";
import { ipLimiter } from "./rate-limit";
import {
createPreprocessorMiddleware,
finalizeSignedRequest,
signGcpRequest,
} from "./middleware/request";
import { ProxyResHandlerWithBody } from "./middleware/response";
import { createQueuedProxyMiddleware } from "./middleware/request/proxy-middleware-factory";
import { validateClaude41OpusParameters } from "../shared/claude-4-1-validation";
const LATEST_GCP_SONNET_MINOR_VERSION = "20240229";
let modelsCache: any = null;
let modelsCacheTime = 0;
const getModelsResponse = () => {
if (new Date().getTime() - modelsCacheTime < 1000 * 60) {
return modelsCache;
}
if (!config.gcpCredentials) return { object: "list", data: [] };
// https://docs.anthropic.com/en/docs/about-claude/models
const variants = [
"claude-3-haiku@20240307",
"claude-3-5-haiku@20241022",
"claude-3-5-sonnet@20240620",
"claude-3-5-sonnet-v2@20241022",
"claude-3-7-sonnet@20250219",
"claude-sonnet-4@20250514",
"claude-opus-4@20250514",
"claude-opus-4-1@20250805",
];
const models = variants.map((id) => ({
id,
object: "model",
created: new Date().getTime(),
owned_by: "anthropic",
permission: [],
root: "claude",
parent: null,
}));
modelsCache = { object: "list", data: models };
modelsCacheTime = new Date().getTime();
return modelsCache;
};
const handleModelRequest: RequestHandler = (_req, res) => {
res.status(200).json(getModelsResponse());
};
const gcpBlockingResponseHandler: ProxyResHandlerWithBody = async (
_proxyRes,
req,
res,
body
) => {
if (typeof body !== "object") {
throw new Error("Expected body to be an object");
}
let newBody = body;
switch (`${req.inboundApi}<-${req.outboundApi}`) {
case "openai<-anthropic-chat":
req.log.info("Transforming Anthropic Chat back to OpenAI format");
newBody = transformAnthropicChatResponseToOpenAI(body);
break;
}
res.status(200).json({ ...newBody, proxy: body.proxy });
};
const gcpProxy = createQueuedProxyMiddleware({
target: ({ signedRequest }) => {
if (!signedRequest) throw new Error("Must sign request before proxying");
return `${signedRequest.protocol}//${signedRequest.hostname}`;
},
mutations: [signGcpRequest, finalizeSignedRequest],
blockingResponseHandler: gcpBlockingResponseHandler,
});
const oaiToChatPreprocessor = createPreprocessorMiddleware(
{ inApi: "openai", outApi: "anthropic-chat", service: "gcp" },
{ afterTransform: [maybeReassignModel] }
);
/**
* Routes an OpenAI prompt to either the legacy Claude text completion endpoint
* or the new Claude chat completion endpoint, based on the requested model.
*/
const preprocessOpenAICompatRequest: RequestHandler = (req, res, next) => {
oaiToChatPreprocessor(req, res, next);
};
const gcpRouter = Router();
gcpRouter.get("/v1/models", handleModelRequest);
// Native Anthropic chat completion endpoint.
gcpRouter.post(
"/v1/messages",
ipLimiter,
createPreprocessorMiddleware(
{ inApi: "anthropic-chat", outApi: "anthropic-chat", service: "gcp" },
{ afterTransform: [maybeReassignModel] }
),
gcpProxy
);
// OpenAI-to-GCP Anthropic compatibility endpoint.
gcpRouter.post(
"/v1/chat/completions",
ipLimiter,
preprocessOpenAICompatRequest,
gcpProxy
);
/**
* Tries to deal with:
* - frontends sending GCP model names even when they want to use the OpenAI-
* compatible endpoint
* - frontends sending Anthropic model names that GCP doesn't recognize
* - frontends sending OpenAI model names because they expect the proxy to
* translate them
*
* If client sends GCP model ID it will be used verbatim. Otherwise, various
* 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.startsWith("claude-") && model.includes("@")) {
return;
}
// Anthropic model names can look like:
// - 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 (!match) {
req.body.model = DEFAULT_MODEL;
return;
}
// 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":
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 (flavor) {
case "haiku":
req.body.model = "claude-3-5-haiku@20241022";
return;
case "opus":
// 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;
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;
src/proxy/google-ai.ts
+42 -203
View File
@@ -1,24 +1,25 @@
import { Request, RequestHandler, Router, Response, NextFunction } from "express";
import { Request, RequestHandler, Router } from "express";
import { createProxyMiddleware } from "http-proxy-middleware";
import { v4 } from "uuid";
import { GoogleAIKey, keyPool } from "../shared/key-management";
import { config } from "../config";
import { logger } from "../logger";
import { createQueueMiddleware } from "./queue";
import { ipLimiter } from "./rate-limit";
import { handleProxyError } from "./middleware/common";
import {
createOnProxyReqHandler,
createPreprocessorMiddleware,
finalizeSignedRequest,
} from "./middleware/request";
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";
import {
createOnProxyResHandler,
ProxyResHandlerWithBody,
} from "./middleware/response";
import { addGoogleAIKey } from "./middleware/request/preprocessors/add-google-ai-key";
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
@@ -29,24 +30,10 @@ const getModelsResponse = () => {
if (!config.googleAIKey) return { object: "list", data: [] };
const keys = keyPool
.list()
.filter((k) => k.service === "google-ai") as GoogleAIKey[];
if (keys.length === 0) {
modelsCache = { object: "list", data: [] };
modelsCacheTime = new Date().getTime();
return modelsCache;
}
const googleAIVariants = ["gemini-pro", "gemini-1.0-pro", "gemini-1.5-pro"];
// 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/") && !id.includes("bard"));
// Strip "models/" prefix from IDs before creating model objects
const models = modelIds.map((id) => ({
// Strip "models/" prefix from ID for consistency with request processing
id: id.startsWith("models/") ? id.slice("models/".length) : id,
const models = googleAIVariants.map((id) => ({
id,
object: "model",
created: new Date().getTime(),
owned_by: "google",
@@ -61,51 +48,12 @@ const getModelsResponse = () => {
return modelsCache;
};
// 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) => {
const handleModelRequest: RequestHandler = (_req, res) => {
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 (
/** Only used for non-streaming requests. */
const googleAIResponseHandler: ProxyResHandlerWithBody = async (
_proxyRes,
req,
res,
@@ -129,30 +77,8 @@ function transformGoogleAIResponse(
req: Request
): Record<string, any> {
const totalTokens = (req.promptTokens ?? 0) + (req.outputTokens ?? 0);
// 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}?): /, () => "");
}
const parts = resBody.candidates[0].content?.parts ?? [{ text: "" }];
const content = parts[0].text.replace(/^(.{0,50}?): /, () => "");
return {
id: "goo-" + v4(),
object: "chat.completion",
@@ -166,130 +92,43 @@ function transformGoogleAIResponse(
choices: [
{
message: { role: "assistant", content },
finish_reason: resBody.candidates?.[0]?.finishReason || "STOP",
finish_reason: resBody.candidates[0].finishReason,
index: 0,
},
],
};
}
const googleAIProxy = createQueuedProxyMiddleware({
target: ({ signedRequest }: { signedRequest: any }) => {
if (!signedRequest) throw new Error("Must sign request before proxying");
const { protocol, hostname} = signedRequest;
return `${protocol}//${hostname}`;
},
mutations: [addGoogleAIKey, finalizeSignedRequest],
blockingResponseHandler: googleAIBlockingResponseHandler,
const googleAIProxy = createQueueMiddleware({
beforeProxy: addGoogleAIKey,
proxyMiddleware: createProxyMiddleware({
target: "bad-target-will-be-rewritten",
router: ({ signedRequest }) => {
const { protocol, hostname, path } = signedRequest;
return `${protocol}//${hostname}${path}`;
},
changeOrigin: true,
selfHandleResponse: true,
logger,
on: {
proxyReq: createOnProxyReqHandler({ pipeline: [finalizeSignedRequest] }),
proxyRes: createOnProxyResHandler([googleAIResponseHandler]),
error: handleProxyError,
},
}),
});
const googleAIRouter = Router();
googleAIRouter.get("/v1/models", handleModelRequest);
googleAIRouter.get("/:apiVersion(v1alpha|v1beta)/models", handleNativeModelRequest);
/**
* 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");
if (isStreaming) {
req.body.stream = true;
req.isStreaming = true;
} else {
req.body.stream = false;
req.isStreaming = false;
}
}
/**
* 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.
const model = req.body.model || req.url.split("/").pop()?.split(":").shift();
if (!model) {
throw new Error("You must specify a model with your request.");
}
req.body.model = model;
// 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");
}
// 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]
}
),
createPreprocessorMiddleware({
inApi: "openai",
outApi: "google-ai",
service: "google-ai",
}),
googleAIProxy
);
src/proxy/middleware/common.ts
+20 -61
View File
@@ -1,24 +1,21 @@
import { Request, Response } from "express";
import http from "http";
import { Socket } from "net";
import httpProxy from "http-proxy";
import { ZodError } from "zod";
import { generateErrorMessage } from "zod-error";
import { HttpError } from "../../shared/errors";
import { assertNever } from "../../shared/utils";
import { QuotaExceededError } from "./request/preprocessors/apply-quota-limits";
import { sendErrorToClient } from "./response/error-generator";
import { HttpError } from "../../shared/errors";
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_ALPHA_COMPLETION_ENDPOINT = "/v1alpha/models";
const GOOGLE_AI_BETA_COMPLETION_ENDPOINT = "/v1beta/models";
export function isTextGenerationRequest(req: Request) {
return (
@@ -26,13 +23,10 @@ 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_ALPHA_COMPLETION_ENDPOINT,
GOOGLE_AI_BETA_COMPLETION_ENDPOINT,
].some((endpoint) => req.path.startsWith(endpoint))
);
}
@@ -60,13 +54,13 @@ export function sendProxyError(
const msg =
statusCode === 500
? `The proxy encountered an error while trying to process your prompt.`
: `The proxy encountered an error while trying to send your prompt to the API.`;
: `The proxy encountered an error while trying to send your prompt to the upstream service.`;
sendErrorToClient({
options: {
format: req.inboundApi,
title: `Proxy error (HTTP ${statusCode} ${statusMessage})`,
message: `${msg} Further details are provided below.`,
message: `${msg} Further technical details are provided below.`,
obj: errorPayload,
reqId: req.id,
model: req.body?.model,
@@ -76,23 +70,16 @@ export function sendProxyError(
});
}
/**
* Handles errors thrown during preparation of a proxy request (before it is
* sent to the upstream API), typically due to validation, quota, or other
* pre-flight checks. Depending on the error class, this function will send an
* appropriate error response to the client, streaming it if necessary.
*/
export const handleProxyError: httpProxy.ErrorCallback = (err, req, res) => {
req.log.error(err, `Error during http-proxy-middleware request`);
classifyErrorAndSend(err, req as Request, res as Response);
};
export const classifyErrorAndSend = (
err: Error,
req: Request,
res: Response | Socket
res: Response
) => {
if (res instanceof Socket) {
// We should always have an Express response object here, but http-proxy's
// ErrorCallback type says it could be just a Socket.
req.log.error(err, "Caught error while proxying request to target but cannot send error response to client.");
return res.destroy();
}
try {
const { statusCode, statusMessage, userMessage, ...errorDetails } =
classifyError(err);
@@ -234,28 +221,9 @@ export function getCompletionFromBody(req: Request, body: Record<string, any>) {
switch (format) {
case "openai":
case "mistral-ai":
// Few possible values:
// - 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 || "";
// Can be null if the model wants to invoke tools rather than return a
// completion.
return body.choices[0].message.content || "";
case "openai-text":
return body.choices[0].text;
case "anthropic-chat":
@@ -284,15 +252,7 @@ export function getCompletionFromBody(req: Request, body: Record<string, any>) {
if ("choices" in body) {
return body.choices[0].message.content;
}
const text = body.candidates[0].content?.parts?.[0]?.text;
if (!text) {
req.log.warn(
{ body: JSON.stringify(body) },
"Received empty Google AI text completion"
);
return "";
}
return text;
return body.candidates[0].content.parts[0].text;
case "openai-image":
return body.data?.map((item: any) => item.url).join("\n");
default:
@@ -300,23 +260,22 @@ export function getCompletionFromBody(req: Request, body: Record<string, any>) {
}
}
export function getModelFromBody(req: Request, resBody: Record<string, any>) {
export function getModelFromBody(req: Request, body: Record<string, any>) {
const format = req.outboundApi;
switch (format) {
case "openai":
case "openai-text":
case "openai-responses":
return resBody.model;
case "mistral-ai":
case "mistral-text":
return body.model;
case "openai-image":
case "google-ai":
// These formats don't have a model in the response body.
return req.body.model;
case "anthropic-chat":
case "anthropic-text":
// Anthropic confirms the model in the response, but AWS Claude doesn't.
return resBody.model || req.body.model;
return body.model || req.body.model;
case "google-ai":
// Google doesn't confirm the model in the response.
return req.body.model;
default:
assertNever(format);
}
src/proxy/middleware/request/index.ts
+35 -28
View File
@@ -1,38 +1,42 @@
import type { Request } from "express";
import type { ClientRequest } from "http";
import type { ProxyReqCallback } from "http-proxy";
import { ProxyReqManager } from "./proxy-req-manager";
export { createOnProxyReqHandler } from "./onproxyreq-factory";
export {
createPreprocessorMiddleware,
createEmbeddingsPreprocessorMiddleware,
} from "./preprocessor-factory";
// Preprocessors (runs before request is queued, usually body transformation/validation)
// Express middleware (runs before http-proxy-middleware, can be async)
export { addAzureKey } from "./preprocessors/add-azure-key";
export { applyQuotaLimits } from "./preprocessors/apply-quota-limits";
export { blockZoomerOrigins } from "./preprocessors/block-zoomer-origins";
export { validateContextSize } from "./preprocessors/validate-context-size";
export { countPromptTokens } from "./preprocessors/count-prompt-tokens";
export { languageFilter } from "./preprocessors/language-filter";
export { setApiFormat } from "./preprocessors/set-api-format";
export { signAwsRequest } from "./preprocessors/sign-aws-request";
export { transformOutboundPayload } from "./preprocessors/transform-outbound-payload";
export { validateContextSize } from "./preprocessors/validate-context-size";
export { validateModelFamily } from "./preprocessors/validate-model-family";
export { validateVision } from "./preprocessors/validate-vision";
// Proxy request mutators (runs every time request is dequeued, before proxying, usually for auth/signing)
export { addKey, addKeyForEmbeddingsRequest } from "./mutators/add-key";
export { addAzureKey } from "./mutators/add-azure-key";
export { finalizeBody } from "./mutators/finalize-body";
export { finalizeSignedRequest } from "./mutators/finalize-signed-request";
export { signAwsRequest } from "./mutators/sign-aws-request";
export { signGcpRequest } from "./mutators/sign-vertex-ai-request";
export { stripHeaders } from "./mutators/strip-headers";
// http-proxy-middleware callbacks (runs on onProxyReq, cannot be async)
export { addKey, addKeyForEmbeddingsRequest } from "./onproxyreq/add-key";
export { addAnthropicPreamble } from "./onproxyreq/add-anthropic-preamble";
export { blockZoomerOrigins } from "./onproxyreq/block-zoomer-origins";
export { checkModelFamily } from "./onproxyreq/check-model-family";
export { finalizeBody } from "./onproxyreq/finalize-body";
export { finalizeSignedRequest } from "./onproxyreq/finalize-signed-request";
export { stripHeaders } from "./onproxyreq/strip-headers";
/**
* Middleware that runs prior to the request being queued or handled by
* http-proxy-middleware. You will not have access to the proxied
* request/response objects since they have not yet been sent to the API.
* Middleware that runs prior to the request being handled by http-proxy-
* middleware.
*
* User will have been authenticated by the proxy's gatekeeper, but the request
* won't have been assigned an upstream API key yet.
* Async functions can be used here, but you will not have access to the proxied
* request/response objects, nor the data set by ProxyRequestMiddleware
* functions as they have not yet been run.
*
* User will have been authenticated by the time this middleware runs, but your
* request won't have been assigned an API key yet.
*
* Note that these functions only run once ever per request, even if the request
* is automatically retried by the request queue middleware.
@@ -40,14 +44,17 @@ export { stripHeaders } from "./mutators/strip-headers";
export type RequestPreprocessor = (req: Request) => void | Promise<void>;
/**
* Middleware that runs immediately before the request is proxied to the
* upstream API, after dequeueing the request from the request queue.
* Callbacks that run immediately before the request is sent to the API in
* response to http-proxy-middleware's `proxyReq` event.
*
* Because these middleware may be run multiple times per request if a retryable
* error occurs and the request put back in the queue, they must be idempotent.
* A change manager is provided to allow the middleware to make changes to the
* request which can be automatically reverted.
* Async functions cannot be used here as HPM's event emitter is not async and
* will not wait for the promise to resolve before sending the request.
*
* Note that these functions may be run multiple times per request if the
* first attempt is rate limited and the request is automatically retried by the
* request queue middleware.
*/
export type ProxyReqMutator = (
changeManager: ProxyReqManager
) => void | Promise<void>;
export type HPMRequestCallback = ProxyReqCallback<ClientRequest, Request>;
export const forceModel = (model: string) => (req: Request) =>
void (req.body.model = model);
src/proxy/middleware/request/mutators/add-google-ai-key.ts
-47
View File
@@ -1,47 +0,0 @@
import { keyPool } from "../../../../shared/key-management";
import { ProxyReqMutator } from "../index";
export const addGoogleAIKey: ProxyReqMutator = (manager) => {
const req = manager.request;
const inboundValid =
req.inboundApi === "openai" || req.inboundApi === "google-ai";
const outboundValid = req.outboundApi === "google-ai";
const serviceValid = req.service === "google-ai";
if (!inboundValid || !outboundValid || !serviceValid) {
throw new Error("addGoogleAIKey called on invalid request");
}
const model = req.body.model;
const key = keyPool.get(model, "google-ai");
manager.setKey(key);
req.log.info(
{ key: key.hash, model, stream: req.isStreaming },
"Assigned Google AI API key to request"
);
// https://generativelanguage.googleapis.com/v1beta/models/$MODEL_ID:generateContent?key=$API_KEY
// https://generativelanguage.googleapis.com/v1beta/models/$MODEL_ID:streamGenerateContent?key=${API_KEY}
const payload = { ...req.body, stream: undefined, model: undefined };
// For OpenAI -> Google conversion we don't actually have the API version
const apiVersion = req.params.apiVersion || "v1beta"
// TODO: this isn't actually signed, so the manager api is a little unclear
// with the ProxyReqManager refactor, it's probably no longer necesasry to
// do this because we can modify the path using Manager.setPath.
manager.setSignedRequest({
method: "POST",
protocol: "https:",
hostname: "generativelanguage.googleapis.com",
path: `/${apiVersion}/models/${model}:${
req.isStreaming ? "streamGenerateContent?alt=sse&" : "generateContent?"
}key=${key.key}`,
headers: {
["host"]: `generativelanguage.googleapis.com`,
["content-type"]: "application/json",
},
body: JSON.stringify(payload),
});
};
src/proxy/middleware/request/mutators/finalize-body.ts
-67
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@@ -1,67 +0,0 @@
import type { ProxyReqMutator } from "../index";
/** Finalize the rewritten request body. Must be the last mutator. */
export const finalizeBody: ProxyReqMutator = (manager) => {
const req = manager.request;
if (["POST", "PUT", "PATCH"].includes(req.method ?? "") && req.body) {
// For image generation requests, remove stream flag.
if (req.outboundApi === "openai-image") {
delete req.body.stream;
}
// For anthropic text to chat requests, remove undefined prompt.
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);
manager.setHeader("Content-Length", String(Buffer.byteLength(serialized)));
manager.setBody(serialized);
}
};
src/proxy/middleware/request/mutators/finalize-signed-request.ts
-32
View File
@@ -1,32 +0,0 @@
import { ProxyReqMutator } from "../index";
/**
* For AWS/GCP/Azure/Google requests, the body is signed earlier in the request
* pipeline, before the proxy middleware. This function just assigns the path
* and headers to the proxy request.
*/
export const finalizeSignedRequest: ProxyReqMutator = (manager) => {
const req = manager.request;
if (!req.signedRequest) {
throw new Error("Expected req.signedRequest to be set");
}
// The path depends on the selected model and the assigned key's region.
manager.setPath(req.signedRequest.path);
// Amazon doesn't want extra headers, so we need to remove all of them and
// reassign only the ones specified in the signed request.
const headers = req.signedRequest.headers;
Object.keys(headers).forEach((key) => {
manager.removeHeader(key);
});
Object.entries(req.signedRequest.headers).forEach(([key, value]) => {
manager.setHeader(key, value);
});
const serialized =
typeof req.signedRequest.body === "string"
? req.signedRequest.body
: JSON.stringify(req.signedRequest.body);
manager.setHeader("Content-Length", String(Buffer.byteLength(serialized)));
manager.setBody(serialized);
};
src/proxy/middleware/request/mutators/sign-aws-request.ts
-159
View File
@@ -1,159 +0,0 @@
import express, { Request } from "express";
import { Sha256 } from "@aws-crypto/sha256-js";
import { SignatureV4 } from "@smithy/signature-v4";
import { HttpRequest } from "@smithy/protocol-http";
import {
AnthropicV1TextSchema,
AnthropicV1MessagesSchema,
} from "../../../../shared/api-schemas";
import { AwsBedrockKey, keyPool } from "../../../../shared/key-management";
import {
AWSMistralV1ChatCompletionsSchema,
AWSMistralV1TextCompletionsSchema,
} from "../../../../shared/api-schemas/mistral-ai";
import { ProxyReqMutator } from "../index";
const AMZ_HOST =
process.env.AMZ_HOST || "bedrock-runtime.%REGION%.amazonaws.com";
/**
* Signs an outgoing AWS request with the appropriate headers modifies the
* request object in place to fix the path.
* This happens AFTER request transformation.
*/
export const signAwsRequest: ProxyReqMutator = async (manager) => {
const req = manager.request;
const { model, stream } = req.body;
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);
// AWS only uses 2023-06-01 and does not actually check this header, but we
// set it so that the stream adapter always selects the correct transformer.
manager.setHeader("anthropic-version", "2023-06-01");
// If our key has an inference profile compatible with the requested model,
// we want to use the inference profile instead of the model ID when calling
// InvokeModel as that will give us higher rate limits.
const profile =
key.inferenceProfileIds.find((p) => p.includes(model)) || model;
// Uses the AWS SDK to sign a request, then modifies our HPM proxy request
// with the headers generated by the SDK.
const newRequest = new HttpRequest({
method: "POST",
protocol: "https:",
hostname: host,
path: `/model/${profile}/invoke${stream ? "-with-response-stream" : ""}`,
headers: {
["Host"]: host,
["content-type"]: "application/json",
},
body: JSON.stringify(getStrictlyValidatedBodyForAws(req)),
});
if (stream) {
newRequest.headers["x-amzn-bedrock-accept"] = "application/json";
} else {
newRequest.headers["accept"] = "*/*";
}
const { body, inboundApi, outboundApi } = req;
req.log.info(
{ key: key.hash, model: body.model, profile, inboundApi, outboundApi },
"Assigned AWS credentials to request"
);
manager.setSignedRequest(await sign(newRequest, getCredentialParts(req)));
};
type Credential = {
accessKeyId: string;
secretAccessKey: string;
region: string;
};
function getCredentialParts(req: express.Request): Credential {
const [accessKeyId, secretAccessKey, region] = req.key!.key.split(":");
if (!accessKeyId || !secretAccessKey || !region) {
req.log.error(
{ key: req.key!.hash },
"AWS_CREDENTIALS isn't correctly formatted; refer to the docs"
);
throw new Error("The key assigned to this request is invalid.");
}
return { accessKeyId, secretAccessKey, region };
}
async function sign(request: HttpRequest, credential: Credential) {
const { accessKeyId, secretAccessKey, region } = credential;
const signer = new SignatureV4({
sha256: Sha256,
credentials: { accessKeyId, secretAccessKey },
region,
service: "bedrock",
});
return signer.sign(request);
}
function getStrictlyValidatedBodyForAws(req: Readonly<Request>): unknown {
// AWS uses vendor API formats but imposes additional (more strict) validation
// rules, namely that extraneous parameters are not allowed. We will validate
// using the vendor's zod schema but apply `.strip` to ensure that any
// extraneous parameters are removed.
let strippedParams: Record<string, unknown> = {};
switch (req.outboundApi) {
case "anthropic-text":
strippedParams = AnthropicV1TextSchema.pick({
prompt: true,
max_tokens_to_sample: true,
stop_sequences: true,
temperature: true,
top_k: true,
top_p: true,
})
.strip()
.parse(req.body);
break;
case "anthropic-chat":
strippedParams = AnthropicV1MessagesSchema.pick({
messages: true,
system: true,
max_tokens: true,
stop_sequences: true,
temperature: true,
top_k: true,
top_p: true,
tools: true,
tool_choice: true,
thinking: true
})
.strip()
.parse(req.body);
strippedParams.anthropic_version = "bedrock-2023-05-31";
break;
case "mistral-ai":
strippedParams = AWSMistralV1ChatCompletionsSchema.parse(req.body);
break;
case "mistral-text":
strippedParams = AWSMistralV1TextCompletionsSchema.parse(req.body);
break;
default:
throw new Error("Unexpected outbound API for AWS.");
}
return strippedParams;
}
src/proxy/middleware/request/mutators/sign-vertex-ai-request.ts
-78
View File
@@ -1,78 +0,0 @@
import { AnthropicV1MessagesSchema } from "../../../../shared/api-schemas";
import { GcpKey, keyPool } from "../../../../shared/key-management";
import { ProxyReqMutator } from "../index";
import {
getCredentialsFromGcpKey,
refreshGcpAccessToken,
} from "../../../../shared/key-management/gcp/oauth";
const GCP_HOST = process.env.GCP_HOST || "%REGION%-aiplatform.googleapis.com";
export const signGcpRequest: ProxyReqMutator = async (manager) => {
const req = manager.request;
const serviceValid = req.service === "gcp";
if (!serviceValid) {
throw new Error("addVertexAIKey called on invalid request");
}
if (!req.body?.model) {
throw new Error("You must specify a model with your request.");
}
const { model } = req.body;
const key: GcpKey = keyPool.get(model, "gcp") as GcpKey;
if (!key.accessToken || Date.now() > key.accessTokenExpiresAt) {
const [token, durationSec] = await refreshGcpAccessToken(key);
keyPool.update(key, {
accessToken: token,
accessTokenExpiresAt: Date.now() + durationSec * 1000 * 0.95,
} as GcpKey);
// nb: key received by `get` is a clone and will not have the new access
// token we just set, so it must be manually updated.
key.accessToken = token;
}
manager.setKey(key);
req.log.info({ key: key.hash, model }, "Assigned GCP key to request");
// TODO: This should happen in transform-outbound-payload.ts
// TODO: Support tools
let strippedParams: Record<string, unknown>;
strippedParams = AnthropicV1MessagesSchema.pick({
messages: true,
system: true,
max_tokens: true,
stop_sequences: true,
temperature: true,
top_k: true,
top_p: true,
stream: true,
tools: true,
tool_choice: true,
thinking: true
})
.strip()
.parse(req.body);
strippedParams.anthropic_version = "vertex-2023-10-16";
const credential = await getCredentialsFromGcpKey(key);
const host = GCP_HOST.replace("%REGION%", credential.region);
// GCP doesn't use the anthropic-version header, but we set it to ensure the
// stream adapter selects the correct transformer.
manager.setHeader("anthropic-version", "2023-06-01");
manager.setSignedRequest({
method: "POST",
protocol: "https:",
hostname: host,
path: `/v1/projects/${credential.projectId}/locations/${credential.region}/publishers/anthropic/models/${model}:streamRawPredict`,
headers: {
["host"]: host,
["content-type"]: "application/json",
["authorization"]: `Bearer ${key.accessToken}`,
},
body: JSON.stringify(strippedParams),
});
};
src/proxy/middleware/request/mutators/strip-headers.ts
-33
View File
@@ -1,33 +0,0 @@
import { ProxyReqMutator } from "../index";
/**
* Removes origin and referer headers before sending the request to the API for
* privacy reasons.
*/
export const stripHeaders: ProxyReqMutator = (manager) => {
manager.removeHeader("origin");
manager.removeHeader("referer");
// Some APIs refuse requests coming from browsers to discourage embedding
// API keys in client-side code, so we must remove all CORS/fetch headers.
Object.keys(manager.request.headers).forEach((key) => {
if (key.startsWith("sec-")) {
manager.removeHeader(key);
}
});
manager.removeHeader("tailscale-user-login");
manager.removeHeader("tailscale-user-name");
manager.removeHeader("tailscale-headers-info");
manager.removeHeader("tailscale-user-profile-pic");
manager.removeHeader("cf-connecting-ip");
manager.removeHeader("cf-ray");
manager.removeHeader("cf-visitor");
manager.removeHeader("cf-warp-tag-id");
manager.removeHeader("forwarded");
manager.removeHeader("true-client-ip");
manager.removeHeader("x-forwarded-for");
manager.removeHeader("x-forwarded-host");
manager.removeHeader("x-forwarded-proto");
manager.removeHeader("x-real-ip");
};
src/proxy/middleware/request/onproxyreq-factory.ts
+45
View File
@@ -0,0 +1,45 @@
import {
applyQuotaLimits,
blockZoomerOrigins,
checkModelFamily,
HPMRequestCallback,
stripHeaders,
} from "./index";
type ProxyReqHandlerFactoryOptions = { pipeline: HPMRequestCallback[] };
/**
* Returns an http-proxy-middleware request handler that runs the given set of
* onProxyReq callback functions in sequence.
*
* These will run each time a request is proxied, including on automatic retries
* by the queue after encountering a rate limit.
*/
export const createOnProxyReqHandler = ({
pipeline,
}: ProxyReqHandlerFactoryOptions): HPMRequestCallback => {
const callbackPipeline = [
checkModelFamily,
applyQuotaLimits,
blockZoomerOrigins,
stripHeaders,
...pipeline,
];
return (proxyReq, req, res, options) => {
// The streaming flag must be set before any other onProxyReq handler runs,
// as it may influence the behavior of subsequent handlers.
// Image generation requests can't be streamed.
// TODO: this flag is set in too many places
req.isStreaming =
req.isStreaming || req.body.stream === true || req.body.stream === "true";
req.body.stream = req.isStreaming;
try {
for (const fn of callbackPipeline) {
fn(proxyReq, req, res, options);
}
} catch (error) {
proxyReq.destroy(error);
}
};
};
src/proxy/middleware/request/onproxyreq/add-anthropic-preamble.ts
+33
View File
@@ -0,0 +1,33 @@
import { AnthropicKey, Key } from "../../../../shared/key-management";
import { isTextGenerationRequest } from "../../common";
import { HPMRequestCallback } from "../index";
/**
* Some keys require the prompt to start with `\n\nHuman:`. There is no way to
* know this without trying to send the request and seeing if it fails. If a
* key is marked as requiring a preamble, it will be added here.
*/
export const addAnthropicPreamble: HPMRequestCallback = (_proxyReq, req) => {
if (
!isTextGenerationRequest(req) ||
req.key?.service !== "anthropic" ||
req.outboundApi !== "anthropic-text"
) {
return;
}
let preamble = "";
let prompt = req.body.prompt;
assertAnthropicKey(req.key);
if (req.key.requiresPreamble && prompt) {
preamble = prompt.startsWith("\n\nHuman:") ? "" : "\n\nHuman:";
req.log.debug({ key: req.key.hash, preamble }, "Adding preamble to prompt");
}
req.body.prompt = preamble + prompt;
};
function assertAnthropicKey(key: Key): asserts key is AnthropicKey {
if (key.service !== "anthropic") {
throw new Error(`Expected an Anthropic key, got '${key.service}'`);
}
}
src/proxy/middleware/request/mutators/add-key.ts → src/proxy/middleware/request/onproxyreq/add-key.ts
+24 -60
View File
@@ -1,13 +1,9 @@
import { AnthropicChatMessage } from "../../../../shared/api-schemas";
import { containsImageContent } from "../../../../shared/api-schemas/anthropic";
import { Key, OpenAIKey, keyPool } from "../../../../shared/key-management";
import { isEmbeddingsRequest } from "../../common";
import { HPMRequestCallback } from "../index";
import { assertNever } from "../../../../shared/utils";
import { ProxyReqMutator } from "../index";
export const addKey: ProxyReqMutator = (manager) => {
const req = manager.request;
export const addKey: HPMRequestCallback = (proxyReq, req) => {
let assignedKey: Key;
const { service, inboundApi, outboundApi, body } = req;
@@ -23,51 +19,36 @@ export const addKey: ProxyReqMutator = (manager) => {
throw new Error("You must specify a model with your request.");
}
let needsMultimodal = false;
if (outboundApi === "anthropic-chat") {
needsMultimodal = containsImageContent(
body.messages as AnthropicChatMessage[]
);
}
if (inboundApi === outboundApi) {
// 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);
assignedKey = keyPool.get(body.model, service);
} else {
switch (outboundApi) {
// If we are translating between API formats we may need to select a model
// for the user, because the provided model is for the inbound API.
// TODO: This whole else condition is probably no longer needed since API
// translation now reassigns the model earlier in the request pipeline.
case "anthropic-text":
case "anthropic-chat":
case "mistral-ai":
case "mistral-text":
case "google-ai":
assignedKey = keyPool.get(body.model, service);
case "anthropic-text":
assignedKey = keyPool.get("claude-v1", service);
break;
case "openai-text":
assignedKey = keyPool.get("gpt-3.5-turbo-instruct", service);
break;
case "openai-image":
// 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);
assignedKey = keyPool.get("dall-e-3", service);
break;
case "openai":
case "google-ai":
case "mistral-ai":
throw new Error(
`Outbound API ${outboundApi} is not supported for ${inboundApi}`
`add-key should not be called for outbound API ${outboundApi}`
);
default:
assertNever(outboundApi);
}
}
manager.setKey(assignedKey);
req.key = assignedKey;
req.log.info(
{ key: assignedKey.hash, model: body.model, inboundApi, outboundApi },
"Assigned key to request"
@@ -76,42 +57,23 @@ export const addKey: ProxyReqMutator = (manager) => {
// TODO: KeyProvider should assemble all necessary headers
switch (assignedKey.service) {
case "anthropic":
manager.setHeader("X-API-Key", assignedKey.key);
if (!manager.request.headers["anthropic-version"]) {
manager.setHeader("anthropic-version", "2023-06-01");
}
proxyReq.setHeader("X-API-Key", assignedKey.key);
break;
case "openai":
const key: OpenAIKey = assignedKey as OpenAIKey;
if (key.organizationId && !key.key.includes("svcacct")) {
manager.setHeader("OpenAI-Organization", key.organizationId);
if (key.organizationId) {
proxyReq.setHeader("OpenAI-Organization", key.organizationId);
}
manager.setHeader("Authorization", `Bearer ${assignedKey.key}`);
proxyReq.setHeader("Authorization", `Bearer ${assignedKey.key}`);
break;
case "mistral-ai":
manager.setHeader("Authorization", `Bearer ${assignedKey.key}`);
proxyReq.setHeader("Authorization", `Bearer ${assignedKey.key}`);
break;
case "azure":
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}`);
proxyReq.setHeader("api-key", azureKey);
break;
case "aws":
case "gcp":
case "google-ai":
throw new Error("add-key should not be used for this service.");
default:
@@ -123,8 +85,10 @@ export const addKey: ProxyReqMutator = (manager) => {
* Special case for embeddings requests which don't go through the normal
* request pipeline.
*/
export const addKeyForEmbeddingsRequest: ProxyReqMutator = (manager) => {
const req = manager.request;
export const addKeyForEmbeddingsRequest: HPMRequestCallback = (
proxyReq,
req
) => {
if (!isEmbeddingsRequest(req)) {
throw new Error(
"addKeyForEmbeddingsRequest called on non-embeddings request"
@@ -135,18 +99,18 @@ export const addKeyForEmbeddingsRequest: ProxyReqMutator = (manager) => {
throw new Error("Embeddings requests must be from OpenAI");
}
manager.setBody({ input: req.body.input, model: "text-embedding-ada-002" });
req.body = { input: req.body.input, model: "text-embedding-ada-002" };
const key = keyPool.get("text-embedding-ada-002", "openai") as OpenAIKey;
manager.setKey(key);
req.key = key;
req.log.info(
{ key: key.hash, toApi: req.outboundApi },
"Assigned Turbo key to embeddings request"
);
manager.setHeader("Authorization", `Bearer ${key.key}`);
proxyReq.setHeader("Authorization", `Bearer ${key.key}`);
if (key.organizationId) {
manager.setHeader("OpenAI-Organization", key.organizationId);
proxyReq.setHeader("OpenAI-Organization", key.organizationId);
}
};
src/proxy/middleware/request/preprocessors/block-zoomer-origins.ts → src/proxy/middleware/request/onproxyreq/block-zoomer-origins.ts
+4 -4
View File
@@ -1,6 +1,6 @@
import { RequestPreprocessor } from "../index";
import { HPMRequestCallback } from "../index";
const DISALLOWED_ORIGIN_SUBSTRINGS = "janitorai.com,janitor.ai,vip.jewproxy.tech,jewproxy.tech".split(",");
const DISALLOWED_ORIGIN_SUBSTRINGS = "janitorai.com,janitor.ai".split(",");
class ZoomerForbiddenError extends Error {
constructor(message: string) {
@@ -13,8 +13,8 @@ class ZoomerForbiddenError extends Error {
* Blocks requests from Janitor AI users with a fake, scary error message so I
* stop getting emails asking for tech support.
*/
export const blockZoomerOrigins: RequestPreprocessor = (req) => {
const origin = req.headers.origin || req.headers.referer || req.headers.host;
export const blockZoomerOrigins: HPMRequestCallback = (_proxyReq, req) => {
const origin = req.headers.origin || req.headers.referer;
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.
src/proxy/middleware/request/preprocessors/validate-model-family.ts → src/proxy/middleware/request/onproxyreq/check-model-family.ts
+4 -6
View File
@@ -1,16 +1,14 @@
import { HPMRequestCallback } from "../index";
import { config } from "../../../../config";
import { ForbiddenError } from "../../../../shared/errors";
import { getModelFamilyForRequest } from "../../../../shared/models";
import { RequestPreprocessor } from "../index";
/**
* Ensures the selected model family is enabled by the proxy configuration.
*/
export const validateModelFamily: RequestPreprocessor = (req) => {
**/
export const checkModelFamily: HPMRequestCallback = (_proxyReq, req, res) => {
const family = getModelFamilyForRequest(req);
if (!config.allowedModelFamilies.includes(family)) {
throw new ForbiddenError(
`Model family '${family}' is not enabled on this proxy`
);
throw new ForbiddenError(`Model family '${family}' is not enabled on this proxy`);
}
};
src/proxy/middleware/request/onproxyreq/finalize-body.ts
+23
View File
@@ -0,0 +1,23 @@
import { fixRequestBody } from "http-proxy-middleware";
import type { HPMRequestCallback } from "../index";
/** Finalize the rewritten request body. Must be the last rewriter. */
export const finalizeBody: HPMRequestCallback = (proxyReq, req) => {
if (["POST", "PUT", "PATCH"].includes(req.method ?? "") && req.body) {
// For image generation requests, remove stream flag.
if (req.outboundApi === "openai-image") {
delete req.body.stream;
}
// For anthropic text to chat requests, remove undefined prompt.
if (req.outboundApi === "anthropic-chat") {
delete req.body.prompt;
}
const updatedBody = JSON.stringify(req.body);
proxyReq.setHeader("Content-Length", Buffer.byteLength(updatedBody));
(req as any).rawBody = Buffer.from(updatedBody);
// body-parser and http-proxy-middleware don't play nice together
fixRequestBody(proxyReq, req);
}
};
src/proxy/middleware/request/onproxyreq/finalize-signed-request.ts
+26
View File
@@ -0,0 +1,26 @@
import type { HPMRequestCallback } from "../index";
/**
* For AWS/Azure/Google requests, the body is signed earlier in the request
* pipeline, before the proxy middleware. This function just assigns the path
* and headers to the proxy request.
*/
export const finalizeSignedRequest: HPMRequestCallback = (proxyReq, req) => {
if (!req.signedRequest) {
throw new Error("Expected req.signedRequest to be set");
}
// The path depends on the selected model and the assigned key's region.
proxyReq.path = req.signedRequest.path;
// Amazon doesn't want extra headers, so we need to remove all of them and
// reassign only the ones specified in the signed request.
proxyReq.getRawHeaderNames().forEach(proxyReq.removeHeader.bind(proxyReq));
Object.entries(req.signedRequest.headers).forEach(([key, value]) => {
proxyReq.setHeader(key, value);
});
// Don't use fixRequestBody here because it adds a content-length header.
// Amazon doesn't want that and it breaks the signature.
proxyReq.write(req.signedRequest.body);
};
src/proxy/middleware/request/onproxyreq/strip-headers.ts
+16
View File
@@ -0,0 +1,16 @@
import { HPMRequestCallback } from "../index";
/**
* Removes origin and referer headers before sending the request to the API for
* privacy reasons.
**/
export const stripHeaders: HPMRequestCallback = (proxyReq) => {
proxyReq.setHeader("origin", "");
proxyReq.setHeader("referer", "");
proxyReq.removeHeader("cf-connecting-ip");
proxyReq.removeHeader("forwarded");
proxyReq.removeHeader("true-client-ip");
proxyReq.removeHeader("x-forwarded-for");
proxyReq.removeHeader("x-real-ip");
};
src/proxy/middleware/request/preprocessor-factory.ts
+10 -28
View File
@@ -4,15 +4,11 @@ import { initializeSseStream } from "../../../shared/streaming";
import { classifyErrorAndSend } from "../common";
import {
RequestPreprocessor,
blockZoomerOrigins,
validateContextSize,
countPromptTokens,
languageFilter,
setApiFormat,
transformOutboundPayload,
validateContextSize,
validateModelFamily,
validateVision,
applyQuotaLimits,
languageFilter,
} from ".";
type RequestPreprocessorOptions = {
@@ -33,15 +29,14 @@ type RequestPreprocessorOptions = {
/**
* Returns a middleware function that processes the request body into the given
* API format, and then sequentially runs the given additional preprocessors.
* These should be used for validation and transformations that only need to
* happen once per request.
*
* These run first in the request lifecycle, a single time per request before it
* is added to the request queue. They aren't run again if the request is
* re-attempted after a rate limit.
*
* To run functions against requests every time they are re-attempted, write a
* ProxyReqMutator and pass it to createQueuedProxyMiddleware instead.
* To run a preprocessor on every re-attempt, pass it to createQueueMiddleware.
* It will run after these preprocessors, but before the request is sent to
* http-proxy-middleware.
*/
export const createPreprocessorMiddleware = (
apiFormat: Parameters<typeof setApiFormat>[0],
@@ -49,16 +44,12 @@ export const createPreprocessorMiddleware = (
): RequestHandler => {
const preprocessors: RequestPreprocessor[] = [
setApiFormat(apiFormat),
blockZoomerOrigins,
...(beforeTransform ?? []),
transformOutboundPayload,
countPromptTokens,
languageFilter,
...(afterTransform ?? []),
validateContextSize,
validateVision,
validateModelFamily,
applyQuotaLimits,
];
return async (...args) => executePreprocessors(preprocessors, args);
};
@@ -90,10 +81,10 @@ async function executePreprocessors(
next();
} catch (error) {
if (error.constructor.name === "ZodError") {
const issues = error?.issues
?.map((issue: ZodIssue) => `${issue.path.join(".")}: ${issue.message}`)
const msg = error?.issues
?.map((issue: ZodIssue) => issue.message)
.join("; ");
req.log.warn({ issues }, "Prompt failed preprocessor validation.");
req.log.info(msg, "Prompt validation failed.");
} else {
req.log.error(error, "Error while executing request preprocessor");
}
@@ -143,21 +134,14 @@ const handleTestMessage: RequestHandler = (req, res) => {
completion: "Hello!",
// anthropic chat
content: [{ type: "text", text: "Hello!" }],
// gemini
candidates: [
{
content: { parts: [{ text: "Hello!" }] },
finishReason: "stop",
},
],
proxy_note:
"SillyTavern connection test detected. Your prompt was not sent to the actual model and this response was generated by the proxy.",
"This response was generated by the proxy's test message handler and did not go to the API.",
});
}
};
function isTestMessage(body: any) {
const { messages, prompt, contents } = body;
const { messages, prompt } = body;
if (messages) {
return (
@@ -165,8 +149,6 @@ function isTestMessage(body: any) {
messages[0].role === "user" &&
messages[0].content === "Hi"
);
} else if (contents) {
return contents.length === 1 && contents[0].parts[0]?.text === "Hi";
} else {
return (
prompt?.trim() === "Human: Hi\n\nAssistant:" ||
src/proxy/middleware/request/mutators/add-azure-key.ts → src/proxy/middleware/request/preprocessors/add-azure-key.ts
+7 -13
View File
@@ -3,16 +3,14 @@ import {
AzureOpenAIKey,
keyPool,
} from "../../../../shared/key-management";
import { ProxyReqMutator } from "../index";
import { RequestPreprocessor } from "../index";
export const addAzureKey: ProxyReqMutator = async (manager) => {
const req = manager.request;
export const addAzureKey: RequestPreprocessor = (req) => {
const validAPIs: APIFormat[] = ["openai", "openai-image"];
const apisValid = [req.outboundApi, req.inboundApi].every((api) =>
validAPIs.includes(api)
);
const serviceValid = req.service === "azure";
if (!apisValid || !serviceValid) {
throw new Error("addAzureKey called on invalid request");
}
@@ -24,15 +22,11 @@ export const addAzureKey: ProxyReqMutator = async (manager) => {
const model = req.body.model.startsWith("azure-")
? req.body.model
: `azure-${req.body.model}`;
// TODO: untracked mutation to body, I think this should just be a
// RequestPreprocessor because we don't need to do it every dequeue.
req.key = keyPool.get(model, "azure");
req.body.model = model;
const key = keyPool.get(model, "azure");
manager.setKey(key);
// Handles the sole Azure API deviation from the OpenAI spec (that I know of)
// TODO: this should also probably be a RequestPreprocessor
const notNullOrUndefined = (x: any) => x !== null && x !== undefined;
if ([req.body.logprobs, req.body.top_logprobs].some(notNullOrUndefined)) {
// OpenAI wants logprobs: true/false and top_logprobs: number
@@ -49,7 +43,7 @@ export const addAzureKey: ProxyReqMutator = async (manager) => {
}
req.log.info(
{ key: key.hash, model },
{ key: req.key.hash, model },
"Assigned Azure OpenAI key to request"
);
@@ -61,7 +55,7 @@ export const addAzureKey: ProxyReqMutator = async (manager) => {
const apiVersion =
req.outboundApi === "openai" ? "2023-09-01-preview" : "2024-02-15-preview";
manager.setSignedRequest({
req.signedRequest = {
method: "POST",
protocol: "https:",
hostname: `${resourceName}.openai.azure.com`,
@@ -72,7 +66,7 @@ export const addAzureKey: ProxyReqMutator = async (manager) => {
["api-key"]: apiKey,
},
body: JSON.stringify(req.body),
});
};
};
function getCredentialsFromKey(key: AzureOpenAIKey) {
src/proxy/middleware/request/preprocessors/add-google-ai-key.ts
+40
View File
@@ -0,0 +1,40 @@
import { keyPool } from "../../../../shared/key-management";
import { RequestPreprocessor } from "../index";
export const addGoogleAIKey: RequestPreprocessor = (req) => {
const apisValid = req.inboundApi === "openai" && req.outboundApi === "google-ai";
const serviceValid = req.service === "google-ai";
if (!apisValid || !serviceValid) {
throw new Error("addGoogleAIKey called on invalid request");
}
if (!req.body?.model) {
throw new Error("You must specify a model with your request.");
}
const model = req.body.model;
req.key = keyPool.get(model, "google-ai");
req.log.info(
{ key: req.key.hash, model },
"Assigned Google AI API key to request"
);
// https://generativelanguage.googleapis.com/v1beta/models/$MODEL_ID:generateContent?key=$API_KEY
// https://generativelanguage.googleapis.com/v1beta/models/$MODEL_ID:streamGenerateContent?key=${API_KEY}
req.isStreaming = req.isStreaming || req.body.stream;
delete req.body.stream;
req.signedRequest = {
method: "POST",
protocol: "https:",
hostname: "generativelanguage.googleapis.com",
path: `/v1beta/models/${model}:${req.isStreaming ? "streamGenerateContent" : "generateContent"}?key=${req.key.key}`,
headers: {
["host"]: `generativelanguage.googleapis.com`,
["content-type"]: "application/json",
},
body: JSON.stringify(req.body),
};
};
src/proxy/middleware/request/preprocessors/apply-quota-limits.ts
+3 -3
View File
@@ -1,6 +1,6 @@
import { hasAvailableQuota } from "../../../../shared/users/user-store";
import { isImageGenerationRequest, isTextGenerationRequest } from "../../common";
import { RequestPreprocessor } from "../index";
import { HPMRequestCallback } from "../index";
export class QuotaExceededError extends Error {
public quotaInfo: any;
@@ -11,7 +11,7 @@ export class QuotaExceededError extends Error {
}
}
export const applyQuotaLimits: RequestPreprocessor = (req) => {
export const applyQuotaLimits: HPMRequestCallback = (_proxyReq, req) => {
const subjectToQuota =
isTextGenerationRequest(req) || isImageGenerationRequest(req);
if (!subjectToQuota || !req.user) return;
@@ -34,4 +34,4 @@ export const applyQuotaLimits: RequestPreprocessor = (req) => {
}
);
}
};
};
src/proxy/middleware/request/preprocessors/count-prompt-tokens.ts
+8 -70
View File
@@ -1,18 +1,12 @@
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 {
AnthropicChatMessage,
flattenAnthropicMessages,
} from "../../../../shared/api-schemas/anthropic";
import {
MistralAIChatMessage,
ContentItem,
isMistralVisionModel
} from "../../../../shared/api-schemas/mistral-ai";
import { isGrokVisionModel } from "../../../../shared/api-schemas/xai";
GoogleAIChatMessage,
MistralAIChatMessage,
OpenAIChatMessage,
} from "../../../../shared/api-support";
/**
* Given a request with an already-transformed body, counts the number of
@@ -24,13 +18,7 @@ export const countPromptTokens: RequestPreprocessor = async (req) => {
switch (service) {
case "openai": {
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-responses": {
req.outputTokens = req.body.max_completion_tokens || req.body.max_tokens;
req.outputTokens = req.body.max_tokens;
const prompt: OpenAIChatMessage[] = req.body.messages;
result = await countTokens({ req, prompt, service });
break;
@@ -43,13 +31,7 @@ export const countPromptTokens: RequestPreprocessor = async (req) => {
}
case "anthropic-chat": {
req.outputTokens = req.body.max_tokens;
let system = req.body.system ?? "";
if (Array.isArray(system)) {
system = system
.map((m: { type: string; text: string }) => m.text)
.join("\n");
}
const prompt = { system, messages: req.body.messages };
const prompt: AnthropicChatMessage[] = req.body.messages;
result = await countTokens({ req, prompt, service });
break;
}
@@ -65,50 +47,10 @@ export const countPromptTokens: RequestPreprocessor = async (req) => {
result = await countTokens({ req, prompt, service });
break;
}
case "mistral-ai":
case "mistral-text": {
case "mistral-ai": {
req.outputTokens = req.body.max_tokens;
// 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;
const prompt: MistralAIChatMessage[] = req.body.messages;
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": {
@@ -116,10 +58,6 @@ 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);
}
src/proxy/middleware/request/preprocessors/language-filter.ts
+5 -17
View File
@@ -1,5 +1,4 @@
import { Request } from "express";
import { z } from "zod";
import { config } from "../../../../config";
import { assertNever } from "../../../../shared/utils";
import { RequestPreprocessor } from "../index";
@@ -8,8 +7,7 @@ import {
MistralAIChatMessage,
OpenAIChatMessage,
flattenAnthropicMessages,
} from "../../../../shared/api-schemas";
import { GoogleAIV1GenerateContentSchema } from "../../../../shared/api-schemas/google-ai";
} from "../../../../shared/api-support";
const rejectedClients = new Map<string, number>();
@@ -52,16 +50,14 @@ export const languageFilter: RequestPreprocessor = async (req) => {
}
};
/*
TODO: this is not type safe and does not raise errors if request body zod schema
is changed.
*/
function getPromptFromRequest(req: Request) {
const service = req.outboundApi;
const body = req.body;
switch (service) {
case "anthropic-chat":
return flattenAnthropicMessages(body.messages);
case "anthropic-text":
return body.prompt;
case "openai":
case "mistral-ai":
return body.messages
@@ -76,19 +72,11 @@ function getPromptFromRequest(req: Request) {
return `${msg.role}: ${text}`;
})
.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.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");
}
case "google-ai":
return body.prompt.text;
default:
assertNever(service);
}
src/proxy/middleware/request/preprocessors/set-api-format.ts
-14
View File
@@ -4,22 +4,8 @@ import { LLMService } from "../../../../shared/models";
import { RequestPreprocessor } from "../index";
export const setApiFormat = (api: {
/**
* The API format the user made the request in and expects the response to be
* in.
*/
inApi: Request["inboundApi"];
/**
* The API format the proxy will make the request in and expects the response
* to be in. If different from `inApi`, the proxy will transform the user's
* request body to this format, and will transform the response body or stream
* events from this format.
*/
outApi: APIFormat;
/**
* The service the request will be sent to, which determines authentication
* and possibly the streaming transport.
*/
service: LLMService;
}): RequestPreprocessor => {
return function configureRequestApiFormat(req) {
src/proxy/middleware/request/preprocessors/sign-aws-request.ts
+129
View File
@@ -0,0 +1,129 @@
import express from "express";
import { Sha256 } from "@aws-crypto/sha256-js";
import { SignatureV4 } from "@smithy/signature-v4";
import { HttpRequest } from "@smithy/protocol-http";
import {
AnthropicV1TextSchema,
AnthropicV1MessagesSchema,
} from "../../../../shared/api-support";
import { keyPool } from "../../../../shared/key-management";
import { RequestPreprocessor } from "../index";
const AMZ_HOST =
process.env.AMZ_HOST || "bedrock-runtime.%REGION%.amazonaws.com";
/**
* Signs an outgoing AWS request with the appropriate headers modifies the
* request object in place to fix the path.
* This happens AFTER request transformation.
*/
export const signAwsRequest: RequestPreprocessor = async (req) => {
const { model, stream } = req.body;
req.key = keyPool.get(model, "aws");
req.isStreaming = stream === true || stream === "true";
// same as addAnthropicPreamble for non-AWS requests, but has to happen here
if (req.outboundApi === "anthropic-text") {
let preamble = req.body.prompt.startsWith("\n\nHuman:") ? "" : "\n\nHuman:";
req.body.prompt = preamble + req.body.prompt;
}
// AWS uses mostly the same parameters as Anthropic, with a few removed params
// and much stricter validation on unused parameters. Rather than treating it
// as a separate schema we will use the anthropic ones and strip the unused
// parameters.
// TODO: This should happen in transform-outbound-payload.ts
let strippedParams: Record<string, unknown>;
if (req.outboundApi === "anthropic-chat") {
strippedParams = AnthropicV1MessagesSchema.pick({
messages: true,
max_tokens: true,
stop_sequences: true,
temperature: true,
top_k: true,
top_p: true,
})
.strip()
.parse(req.body);
strippedParams.anthropic_version = "bedrock-2023-05-31";
} else {
strippedParams = AnthropicV1TextSchema.pick({
prompt: true,
max_tokens_to_sample: true,
stop_sequences: true,
temperature: true,
top_k: true,
top_p: true,
})
.strip()
.parse(req.body);
}
const credential = getCredentialParts(req);
const host = AMZ_HOST.replace("%REGION%", credential.region);
// AWS only uses 2023-06-01 and does not actually check this header, but we
// set it so that the stream adapter always selects the correct transformer.
req.headers["anthropic-version"] = "2023-06-01";
// Uses the AWS SDK to sign a request, then modifies our HPM proxy request
// with the headers generated by the SDK.
const newRequest = new HttpRequest({
method: "POST",
protocol: "https:",
hostname: host,
path: `/model/${model}/invoke${stream ? "-with-response-stream" : ""}`,
headers: {
["Host"]: host,
["content-type"]: "application/json",
},
body: JSON.stringify(strippedParams),
});
if (stream) {
newRequest.headers["x-amzn-bedrock-accept"] = "application/json";
} else {
newRequest.headers["accept"] = "*/*";
}
const { key, body, inboundApi, outboundApi } = req;
req.log.info(
{ key: key.hash, model: body.model, inboundApi, outboundApi },
"Assigned AWS credentials to request"
);
req.signedRequest = await sign(newRequest, getCredentialParts(req));
};
type Credential = {
accessKeyId: string;
secretAccessKey: string;
region: string;
};
function getCredentialParts(req: express.Request): Credential {
const [accessKeyId, secretAccessKey, region] = req.key!.key.split(":");
if (!accessKeyId || !secretAccessKey || !region) {
req.log.error(
{ key: req.key!.hash },
"AWS_CREDENTIALS isn't correctly formatted; refer to the docs"
);
throw new Error("The key assigned to this request is invalid.");
}
return { accessKeyId, secretAccessKey, region };
}
async function sign(request: HttpRequest, credential: Credential) {
const { accessKeyId, secretAccessKey, region } = credential;
const signer = new SignatureV4({
sha256: Sha256,
credentials: { accessKeyId, secretAccessKey },
region,
service: "bedrock",
});
return signer.sign(request);
}
src/proxy/middleware/request/preprocessors/transform-outbound-payload.ts
+25 -205
View File
@@ -1,53 +1,52 @@
import { Request } from "express";
import {
API_REQUEST_VALIDATORS,
API_REQUEST_TRANSFORMERS,
} from "../../../../shared/api-schemas";
} from "../../../../shared/api-support";
import { BadRequestError } from "../../../../shared/errors";
import { fixMistralPrompt, isMistralVisionModel } from "../../../../shared/api-schemas/mistral-ai";
import {
isImageGenerationRequest,
isTextGenerationRequest,
} from "../../common";
import { RequestPreprocessor } from "../index";
import { fixMistralPrompt } from "../../../../shared/api-support/kits/mistral-ai/request-transformers";
/** Transforms an incoming request body to one that matches the target API. */
export const transformOutboundPayload: RequestPreprocessor = async (req) => {
const sameService = req.inboundApi === req.outboundApi;
const alreadyTransformed = req.retryCount > 0;
const notTransformable =
!isTextGenerationRequest(req) && !isImageGenerationRequest(req);
if (alreadyTransformed) {
return;
} else if (notTransformable) {
// This is probably an indication of a bug in the proxy.
const { inboundApi, outboundApi, method, path } = req;
req.log.warn(
{ inboundApi, outboundApi, method, path },
"`transformOutboundPayload` called on a non-transformable request."
if (alreadyTransformed || notTransformable) return;
// TODO: this should be an APIFormatTransformer
if (req.inboundApi === "mistral-ai") {
const messages = req.body.messages;
req.body.messages = fixMistralPrompt(messages);
req.log.info(
{ old: messages.length, new: req.body.messages.length },
"Fixed Mistral prompt"
);
}
if (sameService) {
const result = API_REQUEST_VALIDATORS[req.inboundApi].safeParse(req.body);
if (!result.success) {
req.log.warn(
{ issues: result.error.issues, body: req.body },
"Request validation failed"
);
throw result.error;
}
req.body = result.data;
return;
}
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.
const isNativePrompt = req.inboundApi === req.outboundApi;
if (isNativePrompt) {
const result = API_REQUEST_VALIDATORS[req.inboundApi].parse(req.body);
req.body = result;
return;
}
// Prompt requires translation from one API format to another.
const transformation = `${req.inboundApi}->${req.outboundApi}` as const;
const transFn = API_REQUEST_TRANSFORMERS[transformation];
if (transFn) {
req.log.info({ transformation }, "Transforming request...");
req.log.info({ transformation }, "Transforming request");
req.body = await transFn(req);
return;
}
@@ -56,182 +55,3 @@ export const transformOutboundPayload: RequestPreprocessor = async (req) => {
`${transformation} proxying is not supported. Make sure your client is configured to send requests in the correct format and to the correct endpoint.`
);
};
// 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") {
// Mistral Chat is very similar to OpenAI but not identical and many clients
// don't properly handle the differences. We will try to validate the
// 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,
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.
// On Mistral La Plateforme, we can't do this because they don't expose
// a text completions endpoint.
const { messages } = req.body;
const lastMessage = messages && messages[messages.length - 1];
if (lastMessage?.role === "assistant" && req.service === "aws") {
// enable prefix if client forgot, otherwise the template will insert an
// eos token which is very unlikely to be what the client wants.
lastMessage.prefix = true;
req.outboundApi = "mistral-text";
req.log.info(
"Native Mistral chat prompt relies on assistant message prefix. Converting to text completions request."
);
}
}
}
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");
}
}
}
src/proxy/middleware/request/preprocessors/validate-context-size.ts
+10 -84
View File
@@ -6,9 +6,8 @@ import { RequestPreprocessor } from "../index";
const CLAUDE_MAX_CONTEXT = config.maxContextTokensAnthropic;
const OPENAI_MAX_CONTEXT = config.maxContextTokensOpenAI;
// todo: make configurable
const GOOGLE_AI_MAX_CONTEXT = 2048000;
const MISTRAL_AI_MAX_CONTENT = 131072;
const GOOGLE_AI_MAX_CONTEXT = 32000;
const MISTRAL_AI_MAX_CONTENT = 32768;
/**
* Assigns `req.promptTokens` and `req.outputTokens` based on the request body
@@ -28,7 +27,6 @@ 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":
@@ -39,7 +37,6 @@ export const validateContextSize: RequestPreprocessor = async (req) => {
proxyMax = GOOGLE_AI_MAX_CONTEXT;
break;
case "mistral-ai":
case "mistral-text":
proxyMax = MISTRAL_AI_MAX_CONTENT;
break;
case "openai-image":
@@ -49,62 +46,17 @@ export const validateContextSize: RequestPreprocessor = async (req) => {
}
proxyMax ||= Number.MAX_SAFE_INTEGER;
if (req.user?.type === "special") {
req.log.debug("Special user, not enforcing proxy context limit.");
proxyMax = Number.MAX_SAFE_INTEGER;
}
let modelMax: number;
if (model.match(/gpt-3.5-turbo-16k/)) {
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$/)) {
modelMax = 400000;
} else if (model.match(/^chatgpt-4o/)) {
modelMax = 128000;
} else if (model.match(/gpt-4-turbo(-\d{4}-\d{2}-\d{2})?$/)) {
modelMax = 131072;
} else if (model.match(/gpt-4-turbo(-preview)?$/)) {
modelMax = 131072;
} else if (model.match(/gpt-4-(0125|1106)(-preview)?$/)) {
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})?$/)) {
modelMax = 128000;
} else if (model.match(/^o1-pro(-\d{4}-\d{2}-\d{2})?$/)) {
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;
modelMax = 4096;
} else if (model.match(/gpt-4-32k/)) {
modelMax = 32768;
} else if (model.match(/gpt-4/)) {
@@ -119,43 +71,17 @@ 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/)) {
} else if (model.match(/^gemini-\d{3}$/)) {
modelMax = GOOGLE_AI_MAX_CONTEXT;
} else if (model.match(/^mistral-(tiny|small|medium)$/)) {
modelMax = MISTRAL_AI_MAX_CONTENT;
} else if (model.match(/^anthropic\.claude-3-sonnet/)) {
modelMax = 200000;
} else if (model.match(/^anthropic\.claude-v2:\d/)) {
modelMax = 200000;
} else if (model.match(/^anthropic\.claude/)) {
// Not sure if AWS Claude has the same context limit as 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
// catch-all
modelMax = MISTRAL_AI_MAX_CONTENT;
} else {
req.log.warn({ model }, "Unknown model, using 200k token limit.");
modelMax = 200000;
@@ -191,4 +117,4 @@ function assertRequestHasTokenCounts(
})
.nonstrict()
.parse({ promptTokens: req.promptTokens, outputTokens: req.outputTokens });
}
}
src/proxy/middleware/request/preprocessors/validate-vision.ts
-50
View File
@@ -1,50 +0,0 @@
import { config } from "../../../../config";
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";
/**
* Rejects prompts containing images if multimodal prompts are disabled.
*/
export const validateVision: RequestPreprocessor = async (req) => {
if (req.service === undefined) {
throw new Error("Request service must be set before validateVision");
}
if (req.user?.type === "special") return;
if (config.allowedVisionServices.includes(req.service)) return;
// vision not allowed for req's service, block prompts with images
let hasImage = false;
switch (req.outboundApi) {
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 "google-ai":
hasImage = containsImageContentGoogleAI(req.body.contents);
break;
case "anthropic-text":
case "mistral-ai":
case "mistral-text":
case "openai-image":
case "openai-text":
return;
default:
assertNever(req.outboundApi);
}
if (hasImage) {
throw new ForbiddenError(
"Prompts containing images are not permitted. Disable 'Send Inline Images' in your client and try again."
);
}
};
src/proxy/middleware/request/proxy-middleware-factory.ts
-135
View File
@@ -1,135 +0,0 @@
import { Request, Response } from "express";
import http from "http";
import ProxyServer from "http-proxy";
import { Readable } from "stream";
import {
createProxyMiddleware,
Options,
debugProxyErrorsPlugin,
proxyEventsPlugin,
} from "http-proxy-middleware";
import { ProxyReqMutator, stripHeaders } from "./index";
import { createOnProxyResHandler, ProxyResHandlerWithBody } from "../response";
import { createQueueMiddleware } from "../../queue";
import { getHttpAgents } from "../../../shared/network";
import { classifyErrorAndSend } from "../common";
/**
* Options for the `createQueuedProxyMiddleware` factory function.
*/
type ProxyMiddlewareFactoryOptions = {
/**
* Functions which receive a ProxyReqManager and can modify the request before
* it is proxied. The modifications will be automatically reverted if the
* request needs to be returned to the queue.
*/
mutations?: ProxyReqMutator[];
/**
* The target URL to proxy requests to. This can be a string or a function
* which accepts the request and returns a string.
*/
target: string | Options<Request>["router"];
/**
* A function which receives the proxy response and the JSON-decoded request
* body. Only fired for non-streaming responses; streaming responses are
* handled in `handle-streaming-response.ts`.
*/
blockingResponseHandler?: ProxyResHandlerWithBody;
};
/**
* Returns a middleware function that accepts incoming requests and places them
* into the request queue. When the request is dequeued, it is proxied to the
* target URL using the given options and middleware. Non-streaming responses
* are handled by the given `blockingResponseHandler`.
*/
export function createQueuedProxyMiddleware({
target,
mutations,
blockingResponseHandler,
}: ProxyMiddlewareFactoryOptions) {
const hpmTarget = typeof target === "string" ? target : "https://setbyrouter";
const hpmRouter = typeof target === "function" ? target : undefined;
const [httpAgent, httpsAgent] = getHttpAgents();
const agent = hpmTarget.startsWith("http:") ? httpAgent : httpsAgent;
const proxyMiddleware = createProxyMiddleware<Request, Response>({
target: hpmTarget,
router: hpmRouter,
agent,
changeOrigin: true,
toProxy: true,
selfHandleResponse: typeof blockingResponseHandler === "function",
// Disable HPM logger plugin (requires re-adding the other default plugins).
// Contrary to name, debugProxyErrorsPlugin is not just for debugging and
// fixes several error handling/connection close issues in http-proxy core.
ejectPlugins: true,
// Inferred (via Options<express.Request>) as Plugin<express.Request>, but
// the default plugins only allow http.IncomingMessage for TReq. They are
// compatible with express.Request, so we can use them. `Plugin` type is not
// exported for some reason.
plugins: [
debugProxyErrorsPlugin,
pinoLoggerPlugin,
proxyEventsPlugin,
] as any,
on: {
proxyRes: createOnProxyResHandler(
blockingResponseHandler ? [blockingResponseHandler] : []
),
error: classifyErrorAndSend,
},
buffer: ((req: Request) => {
// This is a hack/monkey patch and is not part of the official
// http-proxy-middleware package. See patches/http-proxy+1.18.1.patch.
let payload = req.body;
if (typeof payload === "string") {
payload = Buffer.from(payload);
}
const stream = new Readable();
stream.push(payload);
stream.push(null);
return stream;
}) as any,
});
return createQueueMiddleware({
mutations: [stripHeaders, ...(mutations ?? [])],
proxyMiddleware,
});
}
type ProxiedResponse = http.IncomingMessage & Response & any;
function pinoLoggerPlugin(proxyServer: ProxyServer<Request>) {
proxyServer.on("error", (err, req, res, target) => {
req.log.error(
{ originalUrl: req.originalUrl, targetUrl: String(target), err },
"Error occurred while proxying request to target"
);
});
proxyServer.on("proxyReq", (proxyReq, req) => {
const { protocol, host, path } = proxyReq;
req.log.info(
{
from: req.originalUrl,
to: `${protocol}//${host}${path}`,
},
"Sending request to upstream API..."
);
});
proxyServer.on("proxyRes", (proxyRes: ProxiedResponse, req, _res) => {
const { protocol, host, path } = proxyRes.req;
req.log.info(
{
target: `${protocol}//${host}${path}`,
status: proxyRes.statusCode,
contentType: proxyRes.headers["content-type"],
contentEncoding: proxyRes.headers["content-encoding"],
contentLength: proxyRes.headers["content-length"],
transferEncoding: proxyRes.headers["transfer-encoding"],
},
"Got response from upstream API."
);
});
}
src/proxy/middleware/request/proxy-req-manager.ts
-112
View File
@@ -1,112 +0,0 @@
import { Request } from "express";
import { Key } from "../../../shared/key-management";
import { assertNever } from "../../../shared/utils";
/**
* Represents a change to the request that will be reverted if the request
* fails.
*/
interface ProxyReqMutation {
target: "header" | "path" | "body" | "api-key" | "signed-request";
key?: string;
originalValue: any | undefined;
}
/**
* Manages a request's headers, body, and path, allowing them to be modified
* before the request is proxied and automatically reverted if the request
* needs to be retried.
*/
export class ProxyReqManager {
private req: Request;
private mutations: ProxyReqMutation[] = [];
/**
* A read-only proxy of the request object. Avoid changing any properties
* here as they will persist across retries.
*/
public readonly request: Readonly<Request>;
constructor(req: Request) {
this.req = req;
this.request = new Proxy(req, {
get: (target, prop) => {
if (typeof prop === "string") return target[prop as keyof Request];
return undefined;
},
});
}
setHeader(name: string, newValue: string): void {
const originalValue = this.req.get(name);
this.mutations.push({ target: "header", key: name, originalValue });
this.req.headers[name.toLowerCase()] = newValue;
}
removeHeader(name: string): void {
const originalValue = this.req.get(name);
this.mutations.push({ target: "header", key: name, originalValue });
delete this.req.headers[name.toLowerCase()];
}
setBody(newBody: any): void {
const originalValue = this.req.body;
this.mutations.push({ target: "body", key: "body", originalValue });
this.req.body = newBody;
}
setKey(newKey: Key): void {
const originalValue = this.req.key;
this.mutations.push({ target: "api-key", key: "key", originalValue });
this.req.key = newKey;
}
setPath(newPath: string): void {
const originalValue = this.req.path;
this.mutations.push({ target: "path", key: "path", originalValue });
this.req.url = newPath;
}
setSignedRequest(newSignedRequest: typeof this.req.signedRequest): void {
const originalValue = this.req.signedRequest;
this.mutations.push({ target: "signed-request", key: "signedRequest", originalValue });
this.req.signedRequest = newSignedRequest;
}
hasChanged(): boolean {
return this.mutations.length > 0;
}
revert(): void {
for (const mutation of this.mutations.reverse()) {
switch (mutation.target) {
case "header":
if (mutation.originalValue === undefined) {
delete this.req.headers[mutation.key!.toLowerCase()];
continue;
} else {
this.req.headers[mutation.key!.toLowerCase()] =
mutation.originalValue;
}
break;
case "path":
this.req.url = mutation.originalValue;
break;
case "body":
this.req.body = mutation.originalValue;
break;
case "api-key":
// We don't reset the key here because it's not a property of the
// inbound request, so we'd only ever be reverting it to null.
break;
case "signed-request":
this.req.signedRequest = mutation.originalValue;
break;
default:
assertNever(mutation.target);
}
}
this.mutations = [];
}
}
src/proxy/middleware/response/compression.ts
-36
View File
@@ -1,36 +0,0 @@
import util from "util";
import zlib from "zlib";
import { PassThrough } from "stream";
const BUFFER_DECODER_MAP = {
gzip: util.promisify(zlib.gunzip),
deflate: util.promisify(zlib.inflate),
br: util.promisify(zlib.brotliDecompress),
text: (data: Buffer) => data,
};
const STREAM_DECODER_MAP = {
gzip: zlib.createGunzip,
deflate: zlib.createInflate,
br: zlib.createBrotliDecompress,
text: () => new PassThrough(),
};
type SupportedContentEncoding = keyof typeof BUFFER_DECODER_MAP;
const isSupportedContentEncoding = (
encoding: string
): encoding is SupportedContentEncoding => encoding in BUFFER_DECODER_MAP;
export async function decompressBuffer(buf: Buffer, encoding: string = "text") {
if (isSupportedContentEncoding(encoding)) {
return (await BUFFER_DECODER_MAP[encoding](buf)).toString();
}
throw new Error(`Unsupported content-encoding: ${encoding}`);
}
export function getStreamDecompressor(encoding: string = "text") {
if (isSupportedContentEncoding(encoding)) {
return STREAM_DECODER_MAP[encoding]();
}
throw new Error(`Unsupported content-encoding: ${encoding}`);
}
src/proxy/middleware/response/error-generator.ts
+62 -152
View File
@@ -2,77 +2,59 @@ import express from "express";
import { APIFormat } from "../../../shared/key-management";
import { assertNever } from "../../../shared/utils";
import { initializeSseStream } from "../../../shared/streaming";
import http from "http";
/**
* Returns a Markdown-formatted message that renders semi-nicely in most chat
* frontends. For example:
*
* **Proxy error (HTTP 404 Not Found)**
* The proxy encountered an error while trying to send your prompt to the upstream service. Further technical details are provided below.
* ***
* *The requested Claude model might not exist, or the key might not be provisioned for it.*
* ```
* {
* "type": "error",
* "error": {
* "type": "not_found_error",
* "message": "model: some-invalid-model-id",
* },
* "proxy_note": "The requested Claude model might not exist, or the key might not be provisioned for it."
* }
* ```
*/
function getMessageContent(params: {
function getMessageContent({
title,
message,
obj,
}: {
title: string;
message: string;
obj?: Record<string, any>;
}) {
const { title, message, obj } = params;
const note = obj?.proxy_note || obj?.error?.message || "";
const header = `### **${title}**`;
const friendlyMessage = note ? `${message}\n\n----\n\n*${note}*` : message;
const serializedObj = obj
? ["```", JSON.stringify(obj, null, 2), "```"].join("\n")
: "";
const { stack } = JSON.parse(JSON.stringify(obj ?? {}));
let prettyTrace = "";
if (stack && obj) {
prettyTrace = [
"Include this trace when reporting an issue.",
"```",
stack,
"```",
].join("\n");
delete obj.stack;
/*
Constructs a Markdown-formatted message that renders semi-nicely in most chat
frontends. For example:
**Proxy error (HTTP 404 Not Found)**
The proxy encountered an error while trying to send your prompt to the upstream service. Further technical details are provided below.
***
*The requested Claude model might not exist, or the key might not be provisioned for it.*
```
{
"type": "error",
"error": {
"type": "not_found_error",
"message": "model: some-invalid-model-id",
},
"proxy_note": "The requested Claude model might not exist, or the key might not be provisioned for it."
}
return [
header,
friendlyMessage,
serializedObj,
prettyTrace,
"<!-- oai-proxy-error -->",
].join("\n\n");
```
*/
const note = obj?.proxy_note || obj?.error?.message || "";
const friendlyMessage = note ? `${message}\n\n***\n\n*${note}*` : message;
const details = JSON.parse(JSON.stringify(obj ?? {}));
let stack = "";
if (details.stack) {
stack = `\n\nInclude this trace when reporting an issue.\n\`\`\`\n${details.stack}\n\`\`\``;
delete details.stack;
}
return `\n\n**${title}**\n${friendlyMessage}${
obj ? `\n\`\`\`\n${JSON.stringify(obj, null, 2)}\n\`\`\`\n${stack}` : ""
}`;
}
type ErrorGeneratorOptions = {
format: APIFormat | "unknown";
title: string;
message: string;
obj?: Record<string, any>;
obj?: object;
reqId: string | number | object;
model?: string;
statusCode?: number;
};
/**
* Very crude inference of the request format based on the request body. Don't
* rely on this to be very accurate.
*/
function tryInferFormat(body: any): APIFormat | "unknown" {
export function tryInferFormat(body: any): APIFormat | "unknown" {
if (typeof body !== "object" || !body.model) {
return "unknown";
}
@@ -96,82 +78,42 @@ function tryInferFormat(body: any): APIFormat | "unknown" {
return "unknown";
}
/**
* Redacts the hostname from the error message if it contains a DNS resolution
* error. This is to avoid leaking upstream hostnames on DNS resolution errors,
* as those may contain sensitive information about the proxy's configuration.
*/
function redactHostname(options: ErrorGeneratorOptions): ErrorGeneratorOptions {
if (!options.message.includes("getaddrinfo")) return options;
const redacted = { ...options };
redacted.message = "Could not resolve hostname";
if (typeof redacted.obj?.error === "object") {
redacted.obj = {
...redacted.obj,
error: { message: "Could not resolve hostname" },
};
}
return redacted;
}
/**
* Generates an appropriately-formatted error response and sends it to the
* client over their requested transport (blocking or SSE stream).
*/
export function sendErrorToClient(params: {
export function sendErrorToClient({
options,
req,
res,
}: {
options: ErrorGeneratorOptions;
req: express.Request;
res: express.Response;
}) {
const { req, res } = params;
const options = redactHostname(params.options);
const { statusCode, message, title, obj: details } = options;
const { format: inputFormat } = options;
// Since we want to send the error in a format the client understands, we
// need to know the request format. `setApiFormat` might not have been called
// yet, so we'll try to infer it from the request body.
// This is an error thrown before we know the format of the request, so we
// can't send a response in the format the client expects.
const format =
options.format === "unknown" ? tryInferFormat(req.body) : options.format;
inputFormat === "unknown" ? tryInferFormat(req.body) : inputFormat;
if (format === "unknown") {
// Early middleware error (auth, rate limit) so we can only send something
// generic.
const code = statusCode || 400;
const hasDetails = details && Object.keys(details).length > 0;
return res.status(code).json({
error: {
message,
type: http.STATUS_CODES[code]!.replace(/\s+/g, "_").toLowerCase(),
},
...(hasDetails ? { details } : {}),
return res.status(options.statusCode || 400).json({
error: options.message,
details: options.obj,
});
}
// Cannot modify headers if client opted into streaming and made it into the
// proxy request queue, because that immediately starts an SSE stream.
if (!res.headersSent) {
res.setHeader("x-oai-proxy-error", title);
res.setHeader("x-oai-proxy-error-status", statusCode || 500);
}
const completion = buildSpoofedCompletion({ ...options, format });
const event = buildSpoofedSSE({ ...options, format });
const isStreaming =
req.isStreaming || req.body.stream === true || req.body.stream === "true";
// By this point, we know the request format. To get the error to display in
// chat clients' UIs, we'll send it as a 200 response as a spoofed completion
// from the language model. Depending on whether the client is streaming, we
// will either send an SSE event or a JSON response.
const isStreaming = req.isStreaming || String(req.body.stream) === "true";
if (isStreaming) {
// User can have opted into streaming but not made it into the queue yet,
// in which case the stream must be started first.
if (!res.headersSent) {
initializeSseStream(res);
}
res.write(buildSpoofedSSE({ ...options, format }));
res.write(event);
res.write(`data: [DONE]\n\n`);
res.end();
} else {
res.status(200).json(buildSpoofedCompletion({ ...options, format }));
res.status(200).json(completion);
}
}
@@ -194,21 +136,6 @@ 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,
@@ -224,11 +151,6 @@ export function buildSpoofedCompletion({
},
],
};
case "mistral-text":
return {
outputs: [{ text: content, stop_reason: title }],
model,
};
case "openai-text":
return {
id: "error-" + id,
@@ -260,7 +182,13 @@ export function buildSpoofedCompletion({
stop_sequence: null,
};
case "google-ai":
// TODO: Native Google AI non-streaming responses are not supported, this
// is an untested guess at what the response should look like.
return {
id: "error-" + id,
object: "chat.completion",
created: Date.now(),
model,
candidates: [
{
content: { parts: [{ text: content }], role: "model" },
@@ -298,15 +226,6 @@ 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,
@@ -316,11 +235,6 @@ export function buildSpoofedSSE({
choices: [{ delta: { content }, index: 0, finish_reason: title }],
};
break;
case "mistral-text":
event = {
outputs: [{ text: content, stop_reason: title }],
};
break;
case "openai-text":
event = {
id: "cmpl-" + id,
@@ -350,10 +264,7 @@ export function buildSpoofedSSE({
};
break;
case "google-ai":
// TODO: google ai supports two streaming transports, SSE and JSON.
// we currently only support SSE.
// return JSON.stringify({
event = {
return JSON.stringify({
candidates: [
{
content: { parts: [{ text: content }], role: "model" },
@@ -363,8 +274,7 @@ export function buildSpoofedSSE({
safetyRatings: [],
},
],
};
break;
});
case "openai-image":
return JSON.stringify(obj);
default:
src/proxy/middleware/response/handle-blocking-response.ts
-70
View File
@@ -1,70 +0,0 @@
import { sendProxyError } from "../common";
import type { RawResponseBodyHandler } from "./index";
import { decompressBuffer } from "./compression";
/**
* Handles the response from the upstream service and decodes the body if
* necessary. If the response is JSON, it will be parsed and returned as an
* object. Otherwise, it will be returned as a string. Does not handle streaming
* responses.
* @throws {Error} Unsupported content-encoding or invalid application/json body
*/
export const handleBlockingResponse: RawResponseBodyHandler = async (
proxyRes,
req,
res
) => {
if (req.isStreaming) {
const err = new Error(
"handleBlockingResponse called for a streaming request."
);
req.log.error({ stack: err.stack, api: req.inboundApi }, err.message);
throw err;
}
return new Promise((resolve, reject) => {
let chunks: Buffer[] = [];
proxyRes.on("data", (chunk) => chunks.push(chunk));
proxyRes.on("end", async () => {
const contentEncoding = proxyRes.headers["content-encoding"];
const contentType = proxyRes.headers["content-type"];
let body: string | Buffer = Buffer.concat(chunks);
const rejectWithMessage = function (msg: string, err: Error) {
const error = `${msg} (${err.message})`;
req.log.warn(
{ msg: error, stack: err.stack },
"Error in blocking response handler"
);
sendProxyError(req, res, 500, "Internal Server Error", { error });
return reject(error);
};
try {
body = await decompressBuffer(body, contentEncoding);
} catch (e) {
return rejectWithMessage(`Could not decode response body`, e);
}
try {
return resolve(tryParseAsJson(body, contentType));
} catch (e) {
return rejectWithMessage("API responded with invalid JSON", e);
}
});
});
};
function tryParseAsJson(body: string, contentType?: string) {
// If the response is declared as JSON, it must parse or we will throw
if (contentType?.includes("application/json")) {
return JSON.parse(body);
}
// If it's not declared as JSON, some APIs we'll try to parse it as JSON
// anyway since some APIs return the wrong content-type header in some cases.
// If it fails to parse, we'll just return the raw body without throwing.
try {
return JSON.parse(body);
} catch (e) {
return body;
}
}
src/proxy/middleware/response/handle-streamed-response.ts
+39 -52
View File
@@ -1,61 +1,59 @@
import express from "express";
import { pipeline, Readable, Transform } from "stream";
import StreamArray from "stream-json/streamers/StreamArray";
import { StringDecoder } from "string_decoder";
import { promisify } from "util";
import type { logger } from "../../../logger";
import { BadRequestError, RetryableError } from "../../../shared/errors";
import { APIFormat, keyPool } from "../../../shared/key-management";
import {
copySseResponseHeaders,
initializeSseStream,
} from "../../../shared/streaming";
import { reenqueueRequest } from "../../queue";
import type { RawResponseBodyHandler } from ".";
import { handleBlockingResponse } from "./handle-blocking-response";
import { buildSpoofedSSE, sendErrorToClient } from "./error-generator";
import type { logger } from "../../../logger";
import { enqueue } from "../../queue";
import { decodeResponseBody, RawResponseBodyHandler, RetryableError } from ".";
import { getAwsEventStreamDecoder } from "./streaming/aws-event-stream-decoder";
import { EventAggregator } from "./streaming/event-aggregator";
import { SSEMessageTransformer } from "./streaming/sse-message-transformer";
import { SSEStreamAdapter } from "./streaming/sse-stream-adapter";
import { getStreamDecompressor } from "./compression";
import { buildSpoofedSSE, sendErrorToClient } from "./error-generator";
import { BadRequestError } from "../../../shared/errors";
const pipelineAsync = promisify(pipeline);
/**
* `handleStreamedResponse` consumes a streamed response from the upstream API,
* decodes chunk-by-chunk into a stream of events, transforms those events into
* the client's requested format, and forwards the result to the client.
*
* `handleStreamedResponse` consumes and transforms a streamed response from the
* upstream service, forwarding events to the client in their requested format.
* After the entire stream has been consumed, it resolves with the full response
* body so that subsequent middleware in the chain can process it as if it were
* a non-streaming response (to count output tokens, track usage, etc).
* a non-streaming response.
*
* In the event of an error, the request's streaming flag is unset and the
* request is bounced back to the non-streaming response handler. If the error
* is retryable, that handler will re-enqueue the request and also reset the
* streaming flag. Unfortunately the streaming flag is set and unset in multiple
* places, so it's hard to keep track of.
* In the event of an error, the request's streaming flag is unset and the non-
* streaming response handler is called instead.
*
* If the error is retryable, that handler will re-enqueue the request and also
* reset the streaming flag. Unfortunately the streaming flag is set and unset
* in multiple places, so it's hard to keep track of.
*/
export const handleStreamedResponse: RawResponseBodyHandler = async (
proxyRes,
req,
res
) => {
const { headers, statusCode } = proxyRes;
const { hash } = req.key!;
if (!req.isStreaming) {
throw new Error("handleStreamedResponse called for non-streaming request.");
}
if (statusCode! > 201) {
if (proxyRes.statusCode! > 201) {
req.isStreaming = false;
req.log.warn(
{ statusCode },
{ statusCode: proxyRes.statusCode, key: hash },
`Streaming request returned error status code. Falling back to non-streaming response handler.`
);
return handleBlockingResponse(proxyRes, req, res);
return decodeResponseBody(proxyRes, req, res);
}
req.log.debug({ headers }, `Starting to proxy SSE stream.`);
req.log.debug({ headers: proxyRes.headers }, `Starting to proxy SSE stream.`);
// Typically, streaming will have already been initialized by the request
// queue to send heartbeat pings.
@@ -66,25 +64,18 @@ export const handleStreamedResponse: RawResponseBodyHandler = async (
const prefersNativeEvents = req.inboundApi === req.outboundApi;
const streamOptions = {
contentType: headers["content-type"],
contentType: proxyRes.headers["content-type"],
api: req.outboundApi,
logger: req.log,
};
// While the request is streaming, aggregator collects all events so that we
// can compile them into a single response object and publish that to the
// remaining middleware. Because we have an OpenAI transformer for every
// supported format, EventAggregator always consumes OpenAI events so that we
// only have to write one aggregator (OpenAI input) for each output format.
const aggregator = new EventAggregator(req);
const decompressor = getStreamDecompressor(headers["content-encoding"]);
// Decoder reads from the response bytes to produce a stream of plaintext.
// Decoder turns the raw response stream into a stream of events in some
// format (text/event-stream, vnd.amazon.event-stream, streaming JSON, etc).
const decoder = getDecoder({ ...streamOptions, input: proxyRes });
// Adapter consumes the decoded text and produces server-sent events so we
// have a standard event format for the client and to translate between API
// message formats.
// Adapter transforms the decoded events into server-sent events.
const adapter = new SSEStreamAdapter(streamOptions);
// Aggregator compiles all events into a single response object.
const aggregator = new EventAggregator({ format: req.outboundApi });
// Transformer converts server-sent events from one vendor's API message
// format to another.
const transformer = new SSEMessageTransformer({
@@ -106,7 +97,7 @@ export const handleStreamedResponse: RawResponseBodyHandler = async (
try {
await Promise.race([
handleAbortedStream(req, res),
pipelineAsync(proxyRes, decompressor, decoder, adapter, transformer),
pipelineAsync(proxyRes, decoder, adapter, transformer),
]);
req.log.debug(`Finished proxying SSE stream.`);
res.end();
@@ -114,7 +105,12 @@ export const handleStreamedResponse: RawResponseBodyHandler = async (
} catch (err) {
if (err instanceof RetryableError) {
keyPool.markRateLimited(req.key!);
await reenqueueRequest(req);
req.log.warn(
{ key: req.key!.hash, retryCount: req.retryCount },
`Re-enqueueing request due to retryable error during streaming response.`
);
req.retryCount++;
await enqueue(req);
} else if (err instanceof BadRequestError) {
sendErrorToClient({
req,
@@ -142,17 +138,7 @@ export const handleStreamedResponse: RawResponseBodyHandler = async (
res.write(`data: [DONE]\n\n`);
res.end();
}
// At this point the response is closed. If the request resulted in any
// tokens being consumed (suggesting a mid-stream error), we will resolve
// and continue the middleware chain so tokens can be counted.
if (aggregator.hasEvents()) {
return aggregator.getFinalResponse();
} else {
// If there is nothing, then this was a completely failed prompt that
// will not have billed any tokens. Throw to stop the middleware chain.
throw err;
}
throw err;
}
};
@@ -173,13 +159,14 @@ function getDecoder(options: {
logger: typeof logger;
contentType?: string;
}) {
const { contentType, input, logger } = options;
const { api, contentType, input, logger } = options;
if (contentType?.includes("application/vnd.amazon.eventstream")) {
return getAwsEventStreamDecoder({ input, logger });
} else if (contentType?.includes("application/json")) {
throw new Error("JSON streaming not supported, request SSE instead");
} else if (api === "google-ai") {
return StreamArray.withParser();
} else {
// Ensures split chunks across multi-byte characters are handled correctly.
// Passthrough stream, but ensures split chunks across multi-byte characters
// are handled correctly.
const stringDecoder = new StringDecoder("utf8");
return new Transform({
readableObjectMode: true,
src/proxy/middleware/response/index.ts
+252 -548
View File
File diff suppressed because it is too large Load Diff
src/proxy/middleware/response/log-event.ts
-81
View File
@@ -1,81 +0,0 @@
import { createHash } from "crypto";
import { config } from "../../../config";
import { eventLogger } from "../../../shared/prompt-logging";
import { getModelFromBody, isTextGenerationRequest } from "../common";
import { ProxyResHandlerWithBody } from ".";
import {
OpenAIChatMessage,
AnthropicChatMessage,
} from "../../../shared/api-schemas";
/** If event logging is enabled, logs a chat completion event. */
export const logEvent: ProxyResHandlerWithBody = async (
_proxyRes,
req,
_res,
responseBody
) => {
if (!config.eventLogging) {
return;
}
if (typeof responseBody !== "object") {
throw new Error("Expected body to be an object");
}
if (!["openai", "anthropic-chat"].includes(req.outboundApi)) {
// only chat apis are supported
return;
}
if (!req.user) {
return;
}
const loggable = isTextGenerationRequest(req);
if (!loggable) return;
const messages = req.body.messages as
| OpenAIChatMessage[]
| AnthropicChatMessage[];
let hashes = [];
hashes.push(hashMessages(messages));
for (
let i = 1;
i <= Math.min(config.eventLoggingTrim!, messages.length);
i++
) {
hashes.push(hashMessages(messages.slice(0, -i)));
}
const model = getModelFromBody(req, responseBody);
const userToken = req.user!.token;
const family = req.modelFamily!;
eventLogger.logEvent({
ip: req.ip,
type: "chat_completion",
model,
family,
hashes,
userToken,
inputTokens: req.promptTokens ?? 0,
outputTokens: req.outputTokens ?? 0,
});
};
const hashMessages = (
messages: OpenAIChatMessage[] | AnthropicChatMessage[]
): string => {
let hasher = createHash("sha256");
let messageTexts = [];
for (const msg of messages) {
if (!["system", "user", "assistant"].includes(msg.role)) continue;
if (typeof msg.content === "string") {
messageTexts.push(msg.content);
} else if (Array.isArray(msg.content)) {
if (msg.content[0].type === "text") {
messageTexts.push(msg.content[0].text);
}
}
}
hasher.update(messageTexts.join("<|im_sep|>"));
return hasher.digest("hex");
};
src/proxy/middleware/response/log-prompt.ts
+13 -49
View File
@@ -12,10 +12,10 @@ import { assertNever } from "../../../shared/utils";
import {
AnthropicChatMessage,
flattenAnthropicMessages,
GoogleAIChatMessage,
MistralAIChatMessage,
OpenAIChatMessage,
} from "../../../shared/api-schemas";
} from "../../../shared/api-support";
import { APIFormat } from "../../../shared/key-management";
/** If prompt logging is enabled, enqueues the prompt for logging. */
export const logPrompt: ProxyResHandlerWithBody = async (
@@ -36,7 +36,7 @@ export const logPrompt: ProxyResHandlerWithBody = async (
if (!loggable) return;
const promptPayload = getPromptForRequest(req, responseBody);
const promptFlattened = flattenMessages(promptPayload);
const promptFlattened = flattenMessages(promptPayload, req.outboundApi);
const response = getCompletionFromBody(req, responseBody);
const model = getModelFromBody(req, responseBody);
@@ -63,8 +63,7 @@ const getPromptForRequest = (
):
| string
| OpenAIChatMessage[]
| { contents: GoogleAIChatMessage[] }
| { system: string; messages: AnthropicChatMessage[] }
| AnthropicChatMessage[]
| MistralAIChatMessage[]
| OaiImageResult => {
// Since the prompt logger only runs after the request has been proxied, we
@@ -72,21 +71,10 @@ 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":
let system = req.body.system;
if (Array.isArray(system)) {
system = system
.map((m: { type: string; text: string }) => m.text)
.join("\n");
}
return { system, messages: req.body.messages };
return req.body.messages;
case "openai-text":
case "anthropic-text":
case "mistral-text":
return req.body.prompt;
case "openai-image":
return {
@@ -96,8 +84,10 @@ const getPromptForRequest = (
quality: req.body.quality,
revisedPrompt: responseBody.data[0].revised_prompt,
};
case "anthropic-text":
return req.body.prompt;
case "google-ai":
return { contents: req.body.contents };
return req.body.prompt.text;
default:
assertNever(req.outboundApi);
}
@@ -108,24 +98,15 @@ const flattenMessages = (
| string
| OaiImageResult
| OpenAIChatMessage[]
| { contents: GoogleAIChatMessage[] }
| { system: string; messages: AnthropicChatMessage[] }
| MistralAIChatMessage[]
| AnthropicChatMessage[]
| MistralAIChatMessage[],
format: APIFormat
): string => {
if (typeof val === "string") {
return val.trim();
}
if (isAnthropicChatPrompt(val)) {
const { system, messages } = val;
return `System: ${system}\n\n${flattenAnthropicMessages(messages)}`;
}
if (isGoogleAIChatPrompt(val)) {
return val.contents
.map(({ parts, role }) => {
const text = parts.filter(p => 'text' in p).map((p) => (p as { text: string }).text).join("\n");
return `${role}: ${text}`;
})
.join("\n");
if (format === "anthropic-chat") {
return flattenAnthropicMessages(val as AnthropicChatMessage[]);
}
if (Array.isArray(val)) {
return val
@@ -146,20 +127,3 @@ const flattenMessages = (
}
return val.prompt.trim();
};
function isGoogleAIChatPrompt(
val: unknown
): val is { contents: GoogleAIChatMessage[] } {
return typeof val === "object" && val !== null && "contents" in val;
}
function isAnthropicChatPrompt(
val: unknown
): val is { system: string; messages: AnthropicChatMessage[] } {
return (
typeof val === "object" &&
val !== null &&
"system" in val &&
"messages" in val
);
}
src/proxy/middleware/response/streaming/aggregators/mistral-chat.ts
-39
View File
@@ -1,39 +0,0 @@
import { OpenAIChatCompletionStreamEvent } from "../index";
export type MistralChatCompletionResponse = {
choices: {
index: number;
message: { role: string; content: string };
finish_reason: string | null;
}[];
};
/**
* Given a list of OpenAI chat completion events, compiles them into a single
* finalized Mistral chat completion response so that non-streaming middleware
* can operate on it as if it were a blocking response.
*/
export function mergeEventsForMistralChat(
events: OpenAIChatCompletionStreamEvent[]
): MistralChatCompletionResponse {
let merged: MistralChatCompletionResponse = {
choices: [
{ index: 0, message: { role: "", content: "" }, finish_reason: "" },
],
};
merged = events.reduce((acc, event, i) => {
// The first event will only contain role assignment and response metadata
if (i === 0) {
acc.choices[0].message.role = event.choices[0].delta.role ?? "assistant";
return acc;
}
acc.choices[0].finish_reason = event.choices[0].finish_reason ?? "";
if (event.choices[0].delta.content) {
acc.choices[0].message.content += event.choices[0].delta.content;
}
return acc;
}, merged);
return merged;
}
src/proxy/middleware/response/streaming/aggregators/mistral-text.ts
-33
View File
@@ -1,33 +0,0 @@
import { OpenAIChatCompletionStreamEvent } from "../index";
export type MistralTextCompletionResponse = {
outputs: {
text: string;
stop_reason: string | null;
}[];
};
/**
* Given a list of OpenAI chat completion events, compiles them into a single
* finalized Mistral text completion response so that non-streaming middleware
* can operate on it as if it were a blocking response.
*/
export function mergeEventsForMistralText(
events: OpenAIChatCompletionStreamEvent[]
): MistralTextCompletionResponse {
let merged: MistralTextCompletionResponse = {
outputs: [{ text: "", stop_reason: "" }],
};
merged = events.reduce((acc, event, i) => {
// The first event will only contain role assignment and response metadata
if (i === 0) {
return acc;
}
acc.outputs[0].text += event.choices[0].delta.content ?? "";
acc.outputs[0].stop_reason = event.choices[0].finish_reason ?? "";
return acc;
}, merged);
return merged;
}
src/proxy/middleware/response/streaming/aws-event-stream-decoder.ts
+1 -1
View File
@@ -24,7 +24,7 @@ export function getAwsEventStreamDecoder(params: {
if (eventType === "chunk") {
result = input[eventType];
} else {
// AWS unmarshaller treats non-chunk events (errors and exceptions) oddly.
// AWS unmarshaller treats non-chunk (errors and exceptions) oddly.
result = { [eventType]: input[eventType] } as any;
}
return result;
src/proxy/middleware/response/streaming/event-aggregator.ts
+23 -79
View File
@@ -1,4 +1,3 @@
import express from "express";
import { APIFormat } from "../../../../shared/key-management";
import { assertNever } from "../../../../shared/utils";
import {
@@ -7,13 +6,8 @@ import {
mergeEventsForAnthropicText,
mergeEventsForOpenAIChat,
mergeEventsForOpenAIText,
mergeEventsForMistralChat,
mergeEventsForMistralText,
AnthropicV2StreamEvent,
OpenAIChatCompletionStreamEvent,
mistralAIToOpenAI,
MistralAIStreamEvent,
MistralChatCompletionEvent,
} from "./index";
/**
@@ -21,71 +15,45 @@ import {
* compiles them into a single finalized response for downstream middleware.
*/
export class EventAggregator {
private readonly model: string;
private readonly requestFormat: APIFormat;
private readonly responseFormat: APIFormat;
private readonly format: APIFormat;
private readonly events: OpenAIChatCompletionStreamEvent[];
constructor({ body, inboundApi, outboundApi }: express.Request) {
constructor({ format }: { format: APIFormat }) {
this.events = [];
this.requestFormat = inboundApi;
this.responseFormat = outboundApi;
this.model = body.model;
this.format = format;
}
addEvent(
event:
| OpenAIChatCompletionStreamEvent
| AnthropicV2StreamEvent
| MistralAIStreamEvent
) {
addEvent(event: OpenAIChatCompletionStreamEvent | AnthropicV2StreamEvent) {
if (eventIsOpenAIEvent(event)) {
this.events.push(event);
} else {
// horrible special case. previously all transformers' target format was
// openai, so the event aggregator could conveniently assume all incoming
// events were in openai format.
// now we have added some transformers that convert between non-openai
// formats, so aggregator needs to know how to collapse for more than
// just openai.
// because writing aggregation logic for every possible output format is
// annoying, we will just transform any non-openai output events to openai
// format (even if the client did not request openai at all) so that we
// still only need to write aggregators for openai SSEs.
let openAIEvent: OpenAIChatCompletionStreamEvent | undefined;
switch (this.requestFormat) {
case "anthropic-text":
assertIsAnthropicV2Event(event);
openAIEvent = anthropicV2ToOpenAI({
data: `event: completion\ndata: ${JSON.stringify(event)}\n\n`,
lastPosition: -1,
index: 0,
fallbackId: event.log_id || "fallback-" + Date.now(),
fallbackModel: event.model || this.model || "fallback-claude-3",
})?.event;
break;
case "mistral-ai":
assertIsMistralChatEvent(event);
openAIEvent = mistralAIToOpenAI({
data: `data: ${JSON.stringify(event)}\n\n`,
lastPosition: -1,
index: 0,
fallbackId: "fallback-" + Date.now(),
fallbackModel: this.model || "fallback-mistral",
})?.event;
break;
}
if (openAIEvent) {
this.events.push(openAIEvent);
// now we have added anthropic-chat-to-text, so aggregator needs to know
// how to collapse events from two formats.
// because that is annoying, we will simply transform anthropic events to
// openai (even if the client didn't ask for openai) so we don't have to
// write aggregation logic for anthropic chat (which is also a troublesome
// stateful format).
const openAIEvent = anthropicV2ToOpenAI({
data: `event: completion\ndata: ${JSON.stringify(event)}\n\n`,
lastPosition: -1,
index: 0,
fallbackId: event.log_id || "event-aggregator-fallback",
fallbackModel: event.model || "claude-3-fallback",
});
if (openAIEvent.event) {
this.events.push(openAIEvent.event);
}
}
}
getFinalResponse() {
switch (this.responseFormat) {
switch (this.format) {
case "openai":
case "openai-responses":
case "google-ai":
case "mistral-ai":
return mergeEventsForOpenAIChat(this.events);
case "openai-text":
return mergeEventsForOpenAIText(this.events);
@@ -93,22 +61,12 @@ export class EventAggregator {
return mergeEventsForAnthropicText(this.events);
case "anthropic-chat":
return mergeEventsForAnthropicChat(this.events);
case "mistral-ai":
return mergeEventsForMistralChat(this.events);
case "mistral-text":
return mergeEventsForMistralText(this.events);
case "openai-image":
throw new Error(
`SSE aggregation not supported for ${this.responseFormat}`
);
throw new Error(`SSE aggregation not supported for ${this.format}`);
default:
assertNever(this.responseFormat);
assertNever(this.format);
}
}
hasEvents() {
return this.events.length > 0;
}
}
function eventIsOpenAIEvent(
@@ -116,17 +74,3 @@ function eventIsOpenAIEvent(
): event is OpenAIChatCompletionStreamEvent {
return event?.object === "chat.completion.chunk";
}
function assertIsAnthropicV2Event(event: any): asserts event is AnthropicV2StreamEvent {
if (!event?.completion) {
throw new Error(`Bad event for Anthropic V2 SSE aggregation`);
}
}
function assertIsMistralChatEvent(
event: any
): asserts event is MistralChatCompletionEvent {
if (!event?.choices) {
throw new Error(`Bad event for Mistral SSE aggregation`);
}
}
src/proxy/middleware/response/streaming/index.ts
-23
View File
@@ -7,25 +7,6 @@ export type SSEResponseTransformArgs<S = Record<string, any>> = {
state?: S;
};
export type MistralChatCompletionEvent = {
choices: {
index: number;
message: { role: string; content: string };
stop_reason: string | null;
}[];
};
export type MistralTextCompletionEvent = {
outputs: { text: string; stop_reason: string | null }[];
};
export type MistralAIStreamEvent = {
"amazon-bedrock-invocationMetrics"?: {
inputTokenCount: number;
outputTokenCount: number;
invocationLatency: number;
firstByteLatency: number;
};
} & (MistralChatCompletionEvent | MistralTextCompletionEvent);
export type AnthropicV2StreamEvent = {
log_id?: string;
model?: string;
@@ -60,12 +41,8 @@ export { anthropicV2ToOpenAI } from "./transformers/anthropic-v2-to-openai";
export { anthropicChatToAnthropicV2 } from "./transformers/anthropic-chat-to-anthropic-v2";
export { anthropicChatToOpenAI } from "./transformers/anthropic-chat-to-openai";
export { googleAIToOpenAI } from "./transformers/google-ai-to-openai";
export { mistralAIToOpenAI } from "./transformers/mistral-ai-to-openai";
export { mistralTextToMistralChat } from "./transformers/mistral-text-to-mistral-chat";
export { passthroughToOpenAI } from "./transformers/passthrough-to-openai";
export { mergeEventsForOpenAIChat } from "./aggregators/openai-chat";
export { mergeEventsForOpenAIText } from "./aggregators/openai-text";
export { mergeEventsForAnthropicText } from "./aggregators/anthropic-text";
export { mergeEventsForAnthropicChat } from "./aggregators/anthropic-chat";
export { mergeEventsForMistralChat } from "./aggregators/mistral-chat";
export { mergeEventsForMistralText } from "./aggregators/mistral-text";
src/proxy/middleware/response/streaming/sse-message-transformer.ts
+7 -21
View File
@@ -11,11 +11,8 @@ import {
googleAIToOpenAI,
OpenAIChatCompletionStreamEvent,
openAITextToOpenAIChat,
mistralAIToOpenAI,
mistralTextToMistralChat,
passthroughToOpenAI,
StreamingCompletionTransformer,
MistralChatCompletionEvent,
} from "./index";
type SSEMessageTransformerOptions = TransformOptions & {
@@ -38,9 +35,7 @@ export class SSEMessageTransformer extends Transform {
private readonly inputFormat: APIFormat;
private readonly transformFn: StreamingCompletionTransformer<
// TODO: Refactor transformers to not assume only OpenAI events as output
| OpenAIChatCompletionStreamEvent
| AnthropicV2StreamEvent
| MistralChatCompletionEvent
OpenAIChatCompletionStreamEvent | AnthropicV2StreamEvent
>;
private readonly log;
private readonly fallbackId: string;
@@ -126,17 +121,16 @@ function eventIsOpenAIEvent(
function getTransformer(
responseApi: APIFormat,
version?: string,
// In most cases, we are transforming back to OpenAI. Some responses can be
// translated between two non-OpenAI formats, eg Anthropic Chat -> Anthropic
// Text, or Mistral Text -> Mistral Chat.
// There's only one case where we're not transforming back to OpenAI, which is
// Anthropic Chat response -> Anthropic Text request. This parameter is only
// used for that case.
requestApi: APIFormat = "openai"
): StreamingCompletionTransformer<
| OpenAIChatCompletionStreamEvent
| AnthropicV2StreamEvent
| MistralChatCompletionEvent
OpenAIChatCompletionStreamEvent | AnthropicV2StreamEvent
> {
switch (responseApi) {
case "openai":
case "mistral-ai":
return passthroughToOpenAI;
case "openai-text":
return openAITextToOpenAIChat;
@@ -146,20 +140,12 @@ function getTransformer(
: anthropicV2ToOpenAI;
case "anthropic-chat":
return requestApi === "anthropic-text"
? anthropicChatToAnthropicV2 // User's legacy text prompt was converted to chat, and response must be converted back to text
? anthropicChatToAnthropicV2
: anthropicChatToOpenAI;
case "google-ai":
return googleAIToOpenAI;
case "mistral-ai":
return mistralAIToOpenAI;
case "mistral-text":
return requestApi === "mistral-ai"
? mistralTextToMistralChat // User's chat request was converted to text, and response must be converted back to chat
: mistralAIToOpenAI;
case "openai-image":
throw new Error(`SSE transformation not supported for ${responseApi}`);
case "openai-responses":
return passthroughToOpenAI;
default:
assertNever(responseApi);
}
src/proxy/middleware/response/streaming/sse-stream-adapter.ts
+38 -4
View File
@@ -2,7 +2,9 @@ import pino from "pino";
import { Transform, TransformOptions } from "stream";
import { Message } from "@smithy/eventstream-codec";
import { APIFormat } from "../../../../shared/key-management";
import { BadRequestError, RetryableError } from "../../../../shared/errors";
import { RetryableError } from "../index";
import { buildSpoofedSSE } from "../error-generator";
import { BadRequestError } from "../../../../shared/errors";
type SSEStreamAdapterOptions = TransformOptions & {
contentType?: string;
@@ -19,6 +21,7 @@ type SSEStreamAdapterOptions = TransformOptions & {
*/
export class SSEStreamAdapter extends Transform {
private readonly isAwsStream;
private readonly isGoogleStream;
private api: APIFormat;
private partialMessage = "";
private textDecoder = new TextDecoder("utf8");
@@ -28,6 +31,7 @@ export class SSEStreamAdapter extends Transform {
super({ ...options, objectMode: true });
this.isAwsStream =
options?.contentType === "application/vnd.amazon.eventstream";
this.isGoogleStream = options?.api === "google-ai";
this.api = options.api;
this.log = options.logger.child({ module: "sse-stream-adapter" });
}
@@ -52,10 +56,8 @@ export class SSEStreamAdapter extends Transform {
if ("completion" in eventObj) {
return ["event: completion", `data: ${event}`].join(`\n`);
} else if (eventObj.type) {
return [`event: ${eventObj.type}`, `data: ${event}`].join(`\n`);
} else {
return `data: ${event}`;
return [`event: ${eventObj.type}`, `data: ${event}`].join(`\n`);
}
}
// noinspection FallThroughInSwitchStatementJS -- non-JSON data is unexpected
@@ -107,12 +109,44 @@ export class SSEStreamAdapter extends Transform {
}
}
/** Processes an incoming array element from the Google AI JSON stream. */
protected processGoogleObject(data: any): string | null {
// Sometimes data has fields key and value, sometimes it's just the
// candidates array.
const candidates = data.value?.candidates ?? data.candidates ?? [{}];
try {
const hasParts = candidates[0].content?.parts?.length > 0;
if (hasParts) {
return `data: ${JSON.stringify(data)}`;
} else {
this.log.error({ event: data }, "Received bad Google AI event");
return `data: ${buildSpoofedSSE({
format: "google-ai",
title: "Proxy stream error",
message:
"The proxy received malformed or unexpected data from Google AI while streaming.",
obj: data,
reqId: "proxy-sse-adapter-message",
model: "",
})}`;
}
} catch (error) {
error.lastEvent = data;
this.emit("error", error);
}
return null;
}
_transform(data: any, _enc: string, callback: (err?: Error | null) => void) {
try {
if (this.isAwsStream) {
// `data` is a Message object
const message = this.processAwsMessage(data);
if (message) this.push(message + "\n\n");
} else if (this.isGoogleStream) {
// `data` is an element from the Google AI JSON stream
const message = this.processGoogleObject(data);
if (message) this.push(message + "\n\n");
} else {
// `data` is a string, but possibly only a partial message
const fullMessages = (this.partialMessage + data).split(
src/proxy/middleware/response/streaming/transformers/anthropic-chat-to-openai.ts
+1 -1
View File
@@ -34,7 +34,7 @@ export const anthropicChatToOpenAI: StreamingCompletionTransformer = (
model: params.fallbackModel,
choices: [
{
index: 0,
index: params.index,
delta: { content: deltaEvent.delta.text },
finish_reason: null,
},
src/proxy/middleware/response/streaming/transformers/google-ai-to-openai.ts
+2 -16
View File
@@ -9,7 +9,7 @@ const log = logger.child({
type GoogleAIStreamEvent = {
candidates: {
content?: { parts?: { text: string }[]; role: string };
content: { parts: { text: string }[]; role: string };
finishReason?: "STOP" | "MAX_TOKENS" | "SAFETY" | "RECITATION" | "OTHER";
index: number;
tokenCount?: number;
@@ -34,15 +34,9 @@ export const googleAIToOpenAI: StreamingCompletionTransformer = (params) => {
return { position: -1 };
}
const parts = completionEvent.candidates[0].content?.parts || [];
const parts = completionEvent.candidates[0].content.parts;
let content = parts[0]?.text ?? "";
if (isSafetyStop(completionEvent)) {
content = `[Proxy Warning] Gemini safety filter triggered: ${JSON.stringify(
completionEvent.candidates[0].safetyRatings
)}`;
}
// If this is the first chunk, try stripping speaker names from the response
// e.g. "John: Hello" -> "Hello"
if (index === 0) {
@@ -66,14 +60,6 @@ export const googleAIToOpenAI: StreamingCompletionTransformer = (params) => {
return { position: -1, event: newEvent };
};
function isSafetyStop(completion: GoogleAIStreamEvent) {
const isSafetyStop = ["SAFETY", "OTHER"].includes(
completion.candidates[0].finishReason ?? ""
);
const hasNoContent = completion.candidates[0].content?.parts?.length === 0;
return isSafetyStop && hasNoContent;
}
function asCompletion(event: ServerSentEvent): GoogleAIStreamEvent | null {
try {
const parsed = JSON.parse(event.data) as GoogleAIStreamEvent;
src/proxy/middleware/response/streaming/transformers/mistral-ai-to-openai.ts
-76
View File
@@ -1,76 +0,0 @@
import { logger } from "../../../../../logger";
import { MistralAIStreamEvent, SSEResponseTransformArgs } from "../index";
import { parseEvent, ServerSentEvent } from "../parse-sse";
const log = logger.child({
module: "sse-transformer",
transformer: "mistral-ai-to-openai",
});
export const mistralAIToOpenAI = (params: SSEResponseTransformArgs) => {
const { data } = params;
const rawEvent = parseEvent(data);
if (!rawEvent.data || rawEvent.data === "[DONE]") {
return { position: -1 };
}
const completionEvent = asCompletion(rawEvent);
if (!completionEvent) {
return { position: -1 };
}
if ("choices" in completionEvent) {
const newChatEvent = {
id: params.fallbackId,
object: "chat.completion.chunk" as const,
created: Date.now(),
model: params.fallbackModel,
choices: [
{
index: completionEvent.choices[0].index,
delta: { content: completionEvent.choices[0].message.content },
finish_reason: completionEvent.choices[0].stop_reason,
},
],
};
return { position: -1, event: newChatEvent };
} else if ("outputs" in completionEvent) {
const newTextEvent = {
id: params.fallbackId,
object: "chat.completion.chunk" as const,
created: Date.now(),
model: params.fallbackModel,
choices: [
{
index: 0,
delta: { content: completionEvent.outputs[0].text },
finish_reason: completionEvent.outputs[0].stop_reason,
},
],
};
return { position: -1, event: newTextEvent };
}
// should never happen
return { position: -1 };
};
function asCompletion(event: ServerSentEvent): MistralAIStreamEvent | null {
try {
const parsed = JSON.parse(event.data);
if (
(Array.isArray(parsed.choices) &&
parsed.choices[0].message !== undefined) ||
(Array.isArray(parsed.outputs) && parsed.outputs[0].text !== undefined)
) {
return parsed;
} else {
// noinspection ExceptionCaughtLocallyJS
throw new Error("Missing required fields");
}
} catch (error) {
log.warn({ error: error.stack, event }, "Received invalid data event");
}
return null;
}
src/proxy/middleware/response/streaming/transformers/mistral-text-to-mistral-chat.ts
-63
View File
@@ -1,63 +0,0 @@
import {
MistralChatCompletionEvent,
MistralTextCompletionEvent,
StreamingCompletionTransformer,
} from "../index";
import { parseEvent, ServerSentEvent } from "../parse-sse";
import { logger } from "../../../../../logger";
const log = logger.child({
module: "sse-transformer",
transformer: "mistral-text-to-mistral-chat",
});
/**
* Transforms an incoming Mistral Text SSE to an equivalent Mistral Chat SSE.
* This is generally used when a client sends a Mistral Chat prompt, but we
* convert it to Mistral Text before sending it to the API to work around
* some bugs in Mistral/AWS prompt templating. In these cases we need to convert
* the response back to Mistral Chat.
*/
export const mistralTextToMistralChat: StreamingCompletionTransformer<
MistralChatCompletionEvent
> = (params) => {
const { data } = params;
const rawEvent = parseEvent(data);
if (!rawEvent.data) {
return { position: -1 };
}
const textCompletion = asTextCompletion(rawEvent);
if (!textCompletion) {
return { position: -1 };
}
const chatEvent: MistralChatCompletionEvent = {
choices: [
{
index: 0,
message: { role: "assistant", content: textCompletion.outputs[0].text },
stop_reason: textCompletion.outputs[0].stop_reason,
},
],
};
return { position: -1, event: chatEvent };
};
function asTextCompletion(
event: ServerSentEvent
): MistralTextCompletionEvent | null {
try {
const parsed = JSON.parse(event.data);
if (Array.isArray(parsed.outputs) && parsed.outputs[0].text !== undefined) {
return parsed;
} else {
// noinspection ExceptionCaughtLocallyJS
throw new Error("Missing required fields");
}
} catch (error: any) {
log.warn({ error: error.stack, event }, "Received invalid data event");
}
return null;
}
src/proxy/mistral-ai.ts
+46 -115
View File
@@ -1,87 +1,48 @@
import { Request, RequestHandler, Router } from "express";
import { BadRequestError } from "../shared/errors";
import { RequestHandler, Router } from "express";
import { createProxyMiddleware } from "http-proxy-middleware";
import { config } from "../config";
import { keyPool } from "../shared/key-management";
import {
getMistralAIModelFamily,
MistralAIModelFamily,
ModelFamily,
} from "../shared/models";
import { config } from "../config";
import { logger } from "../logger";
import { createQueueMiddleware } from "./queue";
import { ipLimiter } from "./rate-limit";
import { handleProxyError } from "./middleware/common";
import {
addKey,
createOnProxyReqHandler,
createPreprocessorMiddleware,
finalizeBody,
} from "./middleware/request";
import { ProxyResHandlerWithBody } from "./middleware/response";
import { createQueuedProxyMiddleware } from "./middleware/request/proxy-middleware-factory";
import {
createOnProxyResHandler,
ProxyResHandlerWithBody,
} from "./middleware/response";
// Mistral can't settle on a single naming scheme and deprecates models within
// 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 = [
/* 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",
// Earlier Mixtral & Mistral models
// Mistral 7b (open weight, legacy)
"open-mistral-7b",
"mistral-tiny-2312",
// Mixtral 8x7b (open weight, legacy)
"open-mixtral-8x7b",
"open-mixtral-8x22b",
"open-codestral-mamba",
"mathstral",
/* Other, too lazy to do it properly now */
"mistral-small-2312",
// Mixtral Small (newer 8x7b, closed weight)
"mistral-small-latest",
"mistral-small-2402",
// Mistral Medium
"mistral-medium-latest",
"mistral-medium-2312",
"mistral-medium-2505",
"magistral-medium-latest",
// Mistral Large
"mistral-large-latest",
"mistral-large-2402",
// Deprecated identifiers (2024-05-01)
"mistral-tiny",
"mistral-tiny-2312",
"mistral-small",
"mistral-medium",
];
let modelsCache: any = null;
@@ -109,7 +70,7 @@ export function generateModelList(models = KNOWN_MISTRAL_AI_MODELS) {
}
const handleModelRequest: RequestHandler = (_req, res) => {
if (new Date().getTime() - modelsCacheTime < 1000 * 60) {
if (new Date().getTime() - modelsCacheTime < 1000 * 60){
return res.status(200).json(modelsCache);
}
const result = generateModelList();
@@ -128,28 +89,23 @@ const mistralAIResponseHandler: ProxyResHandlerWithBody = async (
throw new Error("Expected body to be an object");
}
let newBody = body;
if (req.inboundApi === "mistral-text" && req.outboundApi === "mistral-ai") {
newBody = transformMistralTextToMistralChat(body);
}
res.status(200).json({ ...newBody, proxy: body.proxy });
res.status(200).json({ ...body, proxy: body.proxy });
};
export function transformMistralTextToMistralChat(textBody: any) {
return {
...textBody,
choices: [
{ message: { content: textBody.outputs[0].text, role: "assistant" } },
],
outputs: undefined,
};
}
const mistralAIProxy = createQueuedProxyMiddleware({
target: "https://api.mistral.ai",
mutations: [addKey, finalizeBody],
blockingResponseHandler: mistralAIResponseHandler,
const mistralAIProxy = createQueueMiddleware({
proxyMiddleware: createProxyMiddleware({
target: "https://api.mistral.ai",
changeOrigin: true,
selfHandleResponse: true,
logger,
on: {
proxyReq: createOnProxyReqHandler({
pipeline: [addKey, finalizeBody],
}),
proxyRes: createOnProxyResHandler([mistralAIResponseHandler]),
error: handleProxyError,
},
}),
});
const mistralAIRouter = Router();
@@ -158,37 +114,12 @@ mistralAIRouter.get("/v1/models", handleModelRequest);
mistralAIRouter.post(
"/v1/chat/completions",
ipLimiter,
createPreprocessorMiddleware(
{
inApi: "mistral-ai",
outApi: "mistral-ai",
service: "mistral-ai",
},
{ beforeTransform: [detectMistralInputApi] }
),
createPreprocessorMiddleware({
inApi: "mistral-ai",
outApi: "mistral-ai",
service: "mistral-ai",
}),
mistralAIProxy
);
/**
* We can't determine if a request is Mistral text or chat just from the path
* because they both use the same endpoint. We need to check the request body
* for either `messages` or `prompt`.
* @param req
*/
export function detectMistralInputApi(req: Request) {
const { messages, prompt } = req.body;
if (messages) {
req.inboundApi = "mistral-ai";
req.outboundApi = "mistral-ai";
} else if (prompt && req.service === "mistral-ai") {
// Mistral La Plateforme doesn't expose a text completions endpoint.
throw new BadRequestError(
"Mistral (via La Plateforme API) does not support text completions. This format is only supported on Mistral via the AWS API."
);
} else if (prompt && req.service === "aws") {
req.inboundApi = "mistral-text";
req.outboundApi = "mistral-text";
}
}
export const mistralAI = mistralAIRouter;
src/proxy/moonshot.ts
-219
View File
@@ -1,219 +0,0 @@
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;
src/proxy/openai-image.ts
+37 -123
View File
@@ -1,17 +1,24 @@
import { Request, RequestHandler, Router } from "express";
import { OpenAIImageGenerationResult } from "../shared/file-storage/mirror-generated-image";
import { generateModelList } from "./openai";
import { RequestHandler, Router, Request } from "express";
import { createProxyMiddleware } from "http-proxy-middleware";
import { config } from "../config";
import { logger } from "../logger";
import { createQueueMiddleware } from "./queue";
import { ipLimiter } from "./rate-limit";
import { handleProxyError } from "./middleware/common";
import {
addKey,
createPreprocessorMiddleware,
finalizeBody,
createOnProxyReqHandler,
} from "./middleware/request";
import { ProxyResHandlerWithBody } from "./middleware/response";
import { ProxyReqManager } from "./middleware/request/proxy-req-manager";
import { createQueuedProxyMiddleware } from "./middleware/request/proxy-middleware-factory";
import {
createOnProxyResHandler,
ProxyResHandlerWithBody,
} from "./middleware/response";
import { generateModelList } from "./openai";
import { OpenAIImageGenerationResult } from "../shared/file-storage/mirror-generated-image";
const KNOWN_MODELS = ["dall-e-2", "dall-e-3", "gpt-image-1"];
const KNOWN_MODELS = ["dall-e-2", "dall-e-3"];
let modelListCache: any = null;
let modelListValid = 0;
@@ -19,9 +26,7 @@ const handleModelRequest: RequestHandler = (_req, res) => {
if (new Date().getTime() - modelListValid < 1000 * 60) {
return res.status(200).json(modelListCache);
}
const result = generateModelList("openai").filter((m: { id: string }) =>
KNOWN_MODELS.includes(m.id)
);
const result = generateModelList(KNOWN_MODELS);
modelListCache = { object: "list", data: result };
modelListValid = new Date().getTime();
res.status(200).json(modelListCache);
@@ -58,46 +63,27 @@ 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 `![${prompt}](data:image/${format};base64,${b64_json})`;
return `![${prompt}](data:image/png;base64,${b64_json})`;
} else {
return `![${prompt}](${url})`;
}
})
.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: req.body.model?.includes("gpt-image") ? "gptimage-" + req.id : "dalle-" + req.id,
id: "dalle-" + req.id,
object: "chat.completion",
created: Date.now(),
model: req.body.model,
usage,
usage: {
prompt_tokens: 0,
completion_tokens: req.outputTokens,
total_tokens: req.outputTokens,
},
choices: [
{
message: { role: "assistant", content },
@@ -108,82 +94,21 @@ 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];
req.log.debug({ pathname }, "OpenAI image path filter");
if (req.path.startsWith("/v1/chat/completions")) {
manager.setPath("/v1/images/generations");
}
}
const openaiImagesProxy = createQueuedProxyMiddleware({
target: "https://api.openai.com",
mutations: [replacePath, filterModelParameters, addKey, finalizeBody],
blockingResponseHandler: openaiImagesResponseHandler,
const openaiImagesProxy = createQueueMiddleware({
proxyMiddleware: createProxyMiddleware({
target: "https://api.openai.com",
changeOrigin: true,
selfHandleResponse: true,
logger,
pathRewrite: {
"^/v1/chat/completions": "/v1/images/generations",
},
on: {
proxyReq: createOnProxyReqHandler({ pipeline: [addKey, finalizeBody] }),
proxyRes: createOnProxyResHandler([openaiImagesResponseHandler]),
error: handleProxyError,
},
}),
});
const openaiImagesRouter = Router();
@@ -198,17 +123,6 @@ 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,
src/proxy/openai.ts
+109 -367
View File
@@ -1,81 +1,109 @@
import { Request, RequestHandler, Router } from "express";
import { RequestHandler, Router } from "express";
import { createProxyMiddleware } from "http-proxy-middleware";
import { config } from "../config";
import { BadRequestError } from "../shared/errors";
import { AzureOpenAIKey, keyPool, OpenAIKey } from "../shared/key-management";
import { getOpenAIModelFamily } from "../shared/models";
import { keyPool, OpenAIKey } from "../shared/key-management";
import {
getOpenAIModelFamily,
ModelFamily,
OpenAIModelFamily,
} from "../shared/models";
import { logger } from "../logger";
import { createQueueMiddleware } from "./queue";
import { ipLimiter } from "./rate-limit";
import { handleProxyError } from "./middleware/common";
import {
addKey,
addKeyForEmbeddingsRequest,
createEmbeddingsPreprocessorMiddleware,
createOnProxyReqHandler,
createPreprocessorMiddleware,
finalizeBody,
forceModel,
RequestPreprocessor,
} from "./middleware/request";
import { ProxyResHandlerWithBody } from "./middleware/response";
import { createQueuedProxyMiddleware } from "./middleware/request/proxy-middleware-factory";
import {
createOnProxyResHandler,
ProxyResHandlerWithBody,
} from "./middleware/response";
// https://platform.openai.com/docs/models/overview
export const KNOWN_OPENAI_MODELS = [
"gpt-4-turbo-preview",
"gpt-4-0125-preview",
"gpt-4-1106-preview",
"gpt-4-vision-preview",
"gpt-4",
"gpt-4-0613",
"gpt-4-0314", // EOL 2024-06-13
"gpt-4-32k",
"gpt-4-32k-0314", // EOL 2024-06-13
"gpt-4-32k-0613",
"gpt-3.5-turbo",
"gpt-3.5-turbo-0301", // EOL 2024-06-13
"gpt-3.5-turbo-0613",
"gpt-3.5-turbo-16k",
"gpt-3.5-turbo-16k-0613",
"gpt-3.5-turbo-instruct",
"gpt-3.5-turbo-instruct-0914",
"text-embedding-ada-002",
];
let modelsCache: any = null;
let modelsCacheTime = 0;
export function generateModelList(service: "openai" | "azure") {
const keys = keyPool
.list()
.filter((k) => k.service === service && !k.isDisabled) as
| OpenAIKey[]
| AzureOpenAIKey[];
if (keys.length === 0) return [];
export function generateModelList(models = KNOWN_OPENAI_MODELS) {
// Get available families and snapshots
let availableFamilies = new Set<OpenAIModelFamily>();
const availableSnapshots = new Set<string>();
for (const key of keyPool.list()) {
if (key.isDisabled || key.service !== "openai") continue;
const asOpenAIKey = key as OpenAIKey;
asOpenAIKey.modelFamilies.forEach((f) => availableFamilies.add(f));
asOpenAIKey.modelSnapshots.forEach((s) => availableSnapshots.add(s));
}
const allowedModelFamilies = new Set(config.allowedModelFamilies);
const modelFamilies = new Set(
keys
.flatMap((k) => k.modelFamilies)
.filter((f) => allowedModelFamilies.has(f))
// Remove disabled families
const allowed = new Set<ModelFamily>(config.allowedModelFamilies);
availableFamilies = new Set(
[...availableFamilies].filter((x) => allowed.has(x))
);
const modelIds = new Set(
keys
.flatMap((k) => k.modelIds)
.filter((id) => {
const allowed = modelFamilies.has(getOpenAIModelFamily(id));
const known = ["gpt", "o", "dall-e", "chatgpt", "text-embedding", "codex"].some(
(prefix) => id.startsWith(prefix)
);
const isFinetune = id.includes("ft");
return allowed && known && !isFinetune;
})
);
return models
.map((id) => ({
id,
object: "model",
created: new Date().getTime(),
owned_by: "openai",
permission: [
{
id: "modelperm-" + id,
object: "model_permission",
created: new Date().getTime(),
organization: "*",
group: null,
is_blocking: false,
},
],
root: id,
parent: null,
}))
.filter((model) => {
// First check if the family is available
const hasFamily = availableFamilies.has(getOpenAIModelFamily(model.id));
if (!hasFamily) return false;
return Array.from(modelIds).map((id) => ({
id,
object: "model",
created: new Date().getTime(),
owned_by: service,
permission: [
{
id: "modelperm-" + id,
object: "model_permission",
created: new Date().getTime(),
organization: "*",
group: null,
is_blocking: false,
},
],
root: id,
parent: null,
}));
// Then for snapshots, ensure the specific snapshot is available
const isSnapshot = model.id.match(/-\d{4}(-preview)?$/);
if (!isSnapshot) return true;
return availableSnapshots.has(model.id);
});
}
const handleModelRequest: RequestHandler = (_req, res) => {
if (new Date().getTime() - modelsCacheTime < 1000 * 60) {
return res.status(200).json(modelsCache);
}
if (!config.openaiKey) return { object: "list", data: [] };
const result = generateModelList("openai");
const result = generateModelList();
modelsCache = { object: "list", data: result };
modelsCacheTime = new Date().getTime();
res.status(200).json(modelsCache);
@@ -110,26 +138,16 @@ const openaiResponseHandler: ProxyResHandlerWithBody = async (
throw new Error("Expected body to be an object");
}
const interval = (req as any)._keepAliveInterval
if (interval) {
clearInterval(interval);
res.write(JSON.stringify(body));
res.end();
return;
}
let newBody = body;
if (req.outboundApi === "openai-text" && req.inboundApi === "openai") {
req.log.info("Transforming Turbo-Instruct response to Chat format");
newBody = transformTurboInstructResponse(body);
} else if (req.outboundApi === "openai-responses" && req.inboundApi === "openai") {
req.log.info("Transforming Responses API response to Chat format");
newBody = transformResponsesApiResponse(body);
}
res.status(200).json({ ...newBody, proxy: body.proxy });
};
/** Only used for non-streaming responses. */
function transformTurboInstructResponse(
turboInstructBody: Record<string, any>
): Record<string, any> {
@@ -147,151 +165,31 @@ function transformTurboInstructResponse(
return transformed;
}
function transformResponsesApiResponse(
responsesBody: Record<string, any>
): Record<string, any> {
// If the response is already in chat completion format, return it as is
if (responsesBody.choices && responsesBody.choices[0]?.message) {
return responsesBody;
}
// Create a compatible format for clients expecting chat completions format
const transformed: Record<string, any> = {
id: responsesBody.id || `chatcmpl-${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",
blockingResponseHandler: openaiResponseHandler,
const openaiProxy = createQueueMiddleware({
proxyMiddleware: createProxyMiddleware({
target: "https://api.openai.com",
changeOrigin: true,
selfHandleResponse: true,
logger,
on: {
proxyReq: createOnProxyReqHandler({ pipeline: [addKey, finalizeBody] }),
proxyRes: createOnProxyResHandler([openaiResponseHandler]),
error: handleProxyError,
},
}),
});
const openaiEmbeddingsProxy = createQueuedProxyMiddleware({
mutations: [addKeyForEmbeddingsRequest, finalizeBody],
const openaiEmbeddingsProxy = createProxyMiddleware({
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,
changeOrigin: true,
selfHandleResponse: false,
logger,
on: {
proxyReq: createOnProxyReqHandler({
pipeline: [addKeyForEmbeddingsRequest, finalizeBody],
}),
error: handleProxyError,
},
});
const openaiRouter = Router();
@@ -320,120 +218,17 @@ 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,
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();
},
createPreprocessorMiddleware({
inApi: "openai",
outApi: "openai",
service: "openai",
}),
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",
@@ -442,57 +237,4 @@ openaiRouter.post(
openaiEmbeddingsProxy
);
function forceModel(model: string): RequestPreprocessor {
return (req: Request) => void (req.body.model = model);
}
function fixupMaxTokens(req: Request) {
// 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];
}
}
}
export const openai = openaiRouter;
src/proxy/queue.ts
+68 -65
View File
@@ -12,8 +12,7 @@
*/
import crypto from "crypto";
import { Handler, Request } from "express";
import { config } from "../config";
import type { Handler, Request } from "express";
import { BadRequestError, TooManyRequestsError } from "../shared/errors";
import { keyPool } from "../shared/key-management";
import {
@@ -23,25 +22,24 @@ import {
} from "../shared/models";
import { initializeSseStream } from "../shared/streaming";
import { logger } from "../logger";
import { getUniqueIps } from "./rate-limit";
import { ProxyReqMutator, RequestPreprocessor } from "./middleware/request";
import { getUniqueIps, SHARED_IP_ADDRESSES } from "./rate-limit";
import { RequestPreprocessor } from "./middleware/request";
import { handleProxyError } from "./middleware/common";
import { sendErrorToClient } from "./middleware/response/error-generator";
import { ProxyReqManager } from "./middleware/request/proxy-req-manager";
import { classifyErrorAndSend } from "./middleware/common";
const queue: Request[] = [];
const log = logger.child({ module: "request-queue" });
/** Maximum number of queue slots for Agnai.chat requests. */
const AGNAI_CONCURRENCY_LIMIT = 5;
/** Maximum number of queue slots for individual users. */
const USER_CONCURRENCY_LIMIT = parseInt(
process.env.USER_CONCURRENCY_LIMIT ?? "1"
);
const USER_CONCURRENCY_LIMIT = 1;
const MIN_HEARTBEAT_SIZE = parseInt(process.env.MIN_HEARTBEAT_SIZE_B ?? "512");
const MAX_HEARTBEAT_SIZE =
1024 * parseInt(process.env.MAX_HEARTBEAT_SIZE_KB ?? "1024");
const HEARTBEAT_INTERVAL =
1000 * parseInt(process.env.HEARTBEAT_INTERVAL_SEC ?? "5");
const LOAD_THRESHOLD = parseFloat(process.env.LOAD_THRESHOLD ?? "150");
const LOAD_THRESHOLD = parseFloat(process.env.LOAD_THRESHOLD ?? "50");
const PAYLOAD_SCALE_FACTOR = parseFloat(
process.env.PAYLOAD_SCALE_FACTOR ?? "6"
);
@@ -60,28 +58,39 @@ const QUEUE_JOIN_TIMEOUT = 5000;
function getIdentifier(req: Request) {
if (req.user) return req.user.token;
if (req.risuToken) return req.risuToken;
// if (isFromSharedIp(req)) return "shared-ip";
if (isFromSharedIp(req)) return "shared-ip";
return req.ip;
}
const sharesIdentifierWith = (incoming: Request) => (queued: Request) =>
getIdentifier(queued) === getIdentifier(incoming);
async function enqueue(req: Request) {
if (req.socket.destroyed || req.res?.writableEnded) {
// In rare cases, a request can be disconnected after it is dequeued for a
// retry, but before it is re-enqueued. In this case we may miss the abort
// and the request will loop in the queue forever.
req.log.warn("Attempt to enqueue aborted request.");
throw new Error("Attempt to enqueue aborted request.");
}
const isFromSharedIp = (req: Request) => SHARED_IP_ADDRESSES.has(req.ip);
export async function enqueue(req: Request) {
const enqueuedRequestCount = queue.filter(sharesIdentifierWith(req)).length;
// 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."
);
let isGuest = req.user?.token === undefined;
// Requests from shared IP addresses such as Agnai.chat are exempt from IP-
// based rate limiting but can only occupy a certain number of slots in the
// queue. Authenticated users always get a single spot in the queue.
const isSharedIp = isFromSharedIp(req);
const maxConcurrentQueuedRequests =
isGuest && isSharedIp ? AGNAI_CONCURRENCY_LIMIT : USER_CONCURRENCY_LIMIT;
if (enqueuedRequestCount >= maxConcurrentQueuedRequests) {
if (isSharedIp) {
// Re-enqueued requests are not counted towards the limit since they
// already made it through the queue once.
if (req.retryCount === 0) {
throw new TooManyRequestsError(
"Too many agnai.chat requests are already queued"
);
}
} else {
throw new TooManyRequestsError(
"Your IP or user token already has another request in the queue."
);
}
}
// shitty hack to remove hpm's event listeners on retried requests
@@ -127,17 +136,20 @@ async function enqueue(req: Request) {
}
}
export async function reenqueueRequest(req: Request) {
req.log.info(
{ key: req.key?.hash, retryCount: req.retryCount },
`Re-enqueueing request due to retryable error`
);
req.retryCount++;
await enqueue(req);
}
function getQueueForPartition(partition: ModelFamily): Request[] {
return queue.filter((req) => getModelFamilyForRequest(req) === partition);
return queue
.filter((req) => getModelFamilyForRequest(req) === partition)
.sort((a, b) => {
// Certain requests are exempted from IP-based rate limiting because they
// come from a shared IP address. To prevent these requests from starving
// out other requests during periods of high traffic, we sort them to the
// end of the queue.
const aIsExempted = isFromSharedIp(a);
const bIsExempted = isFromSharedIp(b);
if (aIsExempted && !bIsExempted) return 1;
if (!aIsExempted && bIsExempted) return -1;
return 0;
});
}
export function dequeue(partition: ModelFamily): Request | undefined {
@@ -148,14 +160,7 @@ export function dequeue(partition: ModelFamily): Request | undefined {
}
const req = modelQueue.reduce((prev, curr) =>
prev.startTime +
config.tokensPunishmentFactor *
((prev.promptTokens ?? 0) + (prev.outputTokens ?? 0)) <
curr.startTime +
config.tokensPunishmentFactor *
((curr.promptTokens ?? 0) + (curr.outputTokens ?? 0))
? prev
: curr
prev.startTime < curr.startTime ? prev : curr
);
queue.splice(queue.indexOf(req), 1);
@@ -247,6 +252,7 @@ let waitTimes: {
partition: ModelFamily;
start: number;
end: number;
isDeprioritized: boolean;
}[] = [];
/** Adds a successful request to the list of wait times. */
@@ -255,6 +261,7 @@ export function trackWaitTime(req: Request) {
partition: getModelFamilyForRequest(req),
start: req.startTime!,
end: req.queueOutTime ?? Date.now(),
isDeprioritized: isFromSharedIp(req),
});
}
@@ -280,7 +287,8 @@ function calculateWaitTime(partition: ModelFamily) {
.filter((wait) => {
const isSamePartition = wait.partition === partition;
const isRecent = now - wait.end < 300 * 1000;
return isSamePartition && isRecent;
const isNormalPriority = !wait.isDeprioritized;
return isSamePartition && isRecent && isNormalPriority;
})
.map((wait) => wait.end - wait.start);
const recentAverage = recentWaits.length
@@ -294,7 +302,11 @@ function calculateWaitTime(partition: ModelFamily) {
);
const currentWaits = queue
.filter((req) => getModelFamilyForRequest(req) === partition)
.filter((req) => {
const isSamePartition = getModelFamilyForRequest(req) === partition;
const isNormalPriority = !isFromSharedIp(req);
return isSamePartition && isNormalPriority;
})
.map((req) => now - req.startTime!);
const longestCurrentWait = Math.max(...currentWaits, 0);
@@ -322,35 +334,26 @@ export function getQueueLength(partition: ModelFamily | "all" = "all") {
}
export function createQueueMiddleware({
mutations = [],
beforeProxy,
proxyMiddleware,
}: {
mutations?: ProxyReqMutator[];
beforeProxy?: RequestPreprocessor;
proxyMiddleware: Handler;
}): Handler {
return async (req, res, next) => {
req.proceed = async () => {
// canonicalize the stream field which is set in a few places not always
// consistently
req.isStreaming = req.isStreaming || String(req.body.stream) === "true";
req.body.stream = req.isStreaming;
try {
// Just before executing the proxyMiddleware, we will create a
// ProxyReqManager to track modifications to the request. This allows
// us to revert those changes if the proxied request fails with a
// retryable error. That happens in proxyMiddleware's onProxyRes
// handler.
const changeManager = new ProxyReqManager(req);
req.changeManager = changeManager;
for (const mutator of mutations) {
await mutator(changeManager);
if (beforeProxy) {
try {
// Hack to let us run asynchronous middleware before the
// http-proxy-middleware handler. This is used to sign AWS requests
// before they are proxied, as the signing is asynchronous.
// Unlike RequestPreprocessors, this runs every time the request is
// dequeued, not just the first time.
await beforeProxy(req);
} catch (err) {
return handleProxyError(err, req, res);
}
} catch (err) {
// Failure during request preparation is a fatal error.
return classifyErrorAndSend(err, req, res);
}
proxyMiddleware(req, res, next);
};

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