Implement tools (function calling) for Claude

ull stop sequence

.env.example

@@ -5,12 +5,18 @@
 # All values have reasonable defaults, so you only need to change the ones you
 # want to override.
 
+# Use production mode unless you are developing locally.
+NODE_ENV=production
+
 # ------------------------------------------------------------------------------
 # General settings:
 
 # The title displayed on the info page.
 # SERVER_TITLE=Coom Tunnel
 
+# The route name used to proxy requests to APIs, relative to the Web site root.
+# PROXY_ENDPOINT_ROUTE=/proxy
+
 # Text model requests allowed per minute per user.
 # TEXT_MODEL_RATE_LIMIT=4
 # Image model requests allowed per minute per user.
@@ -34,11 +40,28 @@
 
 # Which model types users are allowed to access.
 # The following model families are recognized:
-# turbo | gpt4 | gpt4-32k | gpt4-turbo | dall-e | claude | gemini-pro | mistral-tiny | mistral-small | mistral-medium | aws-claude | azure-turbo | azure-gpt4 | azure-gpt4-32k | azure-gpt4-turbo
-# By default, all models are allowed except for 'dall-e'. To allow DALL-E image
-# generation, uncomment the line below and add 'dall-e' to the list.
-# ALLOWED_MODEL_FAMILIES=turbo,gpt4,gpt4-32k,gpt4-turbo,claude,gemini-pro,mistral-tiny,mistral-small,mistral-medium,aws-claude,azure-turbo,azure-gpt4,azure-gpt4-32k,azure-gpt4-turbo
 
+# turbo | gpt4 | gpt4-32k | gpt4-turbo | gpt4o | 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-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,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
+
+# 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
+# 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=
+
+# 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.
@@ -51,14 +74,15 @@
 # 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="This content violates /aicg/'s acceptable use policy."
+# REJECT_MESSAGE="You can't say that here."
 
 # Whether prompts should be logged to Google Sheets.
 # Requires additional setup. See `docs/google-sheets.md` for more information.
 # PROMPT_LOGGING=false
 
-# The port to listen on.
+# 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
@@ -66,6 +90,13 @@
 # Detail level of logging. (trace | debug | info | warn | error)
 # LOG_LEVEL=info
 
+# 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
+
 # ------------------------------------------------------------------------------
 # Optional settings for user management, access control, and quota enforcement:
 # See `docs/user-management.md` for more information and setup instructions.
@@ -85,43 +116,58 @@
 # ALLOW_NICKNAME_CHANGES=true
 
 # Default token quotas for each model family. (0 for unlimited)
-# 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.
+# Specify as TOKEN_QUOTA_MODEL_FAMILY=value, replacing dashes with underscores.
 # 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
+# TOKEN_QUOTA_GCP_CLAUDE=0
+# "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 3 costs around US$0.10 per image (10000 tokens).
+# See `docs/dall-e-configuration.md` for more information.
+# TOKEN_QUOTA_DALL_E=0
 
 # How often to refresh token quotas. (hourly | daily)
 # Leave unset to never automatically refresh quotas.
 # QUOTA_REFRESH_PERIOD=daily
 
+# 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:
-# Do not put any passwords or API keys directly in this file.
-# For Huggingface, set them via the Secrets section in your Space's config UI.
+# For Huggingface, set them via the Secrets section in your Space's config UI. Dp not set them in .env.
 # For Render, create a "secret file" called .env using the Environment tab.
 
 # 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
+# To restrict access to the admin interface to specific IP addresses, set the
+# ADMIN_WHITELIST environment variable to a comma-separated list of CIDR blocks.
+# ADMIN_WHITELIST=0.0.0.0/0
+
 
 # With firebase_rtdb gatekeeper storage, the Firebase project credentials.
 # FIREBASE_KEY=xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx

.gitignore

@@ -1,8 +1,11 @@
-.env
+.aider*
+.env*
+!.env.vault
 .venv
 .vscode
 .idea
 build
 greeting.md
 node_modules
+
 http-client.private.env.json

.prettierrc

@@ -1,11 +1,10 @@
 {
+  "plugins": ["prettier-plugin-ejs"],
   "overrides": [
     {
-      "files": [
-        "*.ejs"
-      ],
+      "files": "*.ejs",
       "options": {
-        "printWidth": 160,
+        "printWidth": 120,
         "bracketSameLine": true
       }
     }

README.md

@@ -1,34 +1,50 @@
 # OAI Reverse Proxy
 
-Reverse proxy server for the OpenAI and Anthropic APIs. Forwards text generation requests while rejecting administrative/billing requests. Includes optional rate limiting and prompt filtering to prevent abuse.
+Reverse proxy server for various LLM APIs.
 
 ### Table of Contents
 - [What is this?](#what-is-this)
-- [Why?](#why)
-- [Usage Instructions](#setup-instructions)
-  - [Deploy to Huggingface (Recommended)](#deploy-to-huggingface-recommended)
-  - [Deploy to Repl.it (WIP)](#deploy-to-replit-wip)
+- [Features](#features)
+- [Usage Instructions](#usage-instructions)
+  - [Self-hosting](#self-hosting)
+  - [Huggingface (outdated, not advised)](#huggingface-outdated-not-advised)
+  - [Render (outdated, not advised)](#render-outdated-not-advised)
 - [Local Development](#local-development)
 
 ## What is this?
-If you would like to provide a friend access to an API via keys you own, you can use this to keep your keys safe while still allowing them to generate text with the API. You can also use this if you'd like to build a client-side application which uses the OpenAI or Anthropic APIs, but don't want to build your own backend. You should never embed your real API keys in a client-side application. Instead, you can have your frontend connect to this reverse proxy and forward requests to the downstream service.
+This project allows you to run a reverse proxy server for various LLM APIs.
 
-This keeps your keys safe and allows you to use the rate limiting and prompt filtering features of the proxy to prevent abuse.
-
-## Why?
-OpenAI keys have full account permissions. They can revoke themselves, generate new keys, modify spend quotas, etc. **You absolutely should not share them, post them publicly, nor embed them in client-side applications as they can be easily stolen.**
-
-This proxy only forwards text generation requests to the downstream service and rejects requests which would otherwise modify your account. 
+## Features
+- [x] Support for multiple APIs
+  - [x] [OpenAI](https://openai.com/)
+  - [x] [Anthropic](https://www.anthropic.com/)
+  - [x] [AWS Bedrock](https://aws.amazon.com/bedrock/)
+  - [x] [Vertex AI (GCP)](https://cloud.google.com/vertex-ai/)
+  - [x] [Google MakerSuite/Gemini API](https://ai.google.dev/)
+  - [x] [Azure OpenAI](https://azure.microsoft.com/en-us/products/ai-services/openai-service)
+- [x] Translation from OpenAI-formatted prompts to any other API, including streaming responses
+- [x] Multiple API keys with rotation and rate limit handling
+- [x] Basic user management
+  - [x] Simple role-based permissions
+  - [x] Per-model token quotas
+  - [x] Temporary user accounts
+- [x] Prompt and completion logging
+- [x] Abuse detection and prevention
 
 ---
 
 ## Usage Instructions
-If you'd like to run your own instance of this proxy, 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'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.
 
-### Deploy to Huggingface (Recommended)
+### Self-hosting
+[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.
+
+### Huggingface (outdated, not advised)
 [See here for instructions on how to deploy to a Huggingface Space.](./docs/deploy-huggingface.md)
 
-### Deploy to Render
+### Render (outdated, not advised)
 [See here for instructions on how to deploy to Render.com.](./docs/deploy-render.md)
 
 ## Local Development
@@ -40,3 +56,12 @@ To run the proxy locally for development or testing, install Node.js >= 18.0.0 a
 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.
+
+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/ci/.gitlab-ci.yml

@@ -0,0 +1,21 @@
+stages:
+  - build
+
+build_image:
+  stage: build
+  image:
+    name: gcr.io/kaniko-project/executor:debug
+    entrypoint: [""]
+  script:
+    - |
+      if [ "$CI_COMMIT_REF_NAME" = "main" ]; then
+        TAG="latest"
+      else
+        TAG=$CI_COMMIT_REF_NAME
+      fi
+    - echo "Building image with tag $TAG"
+    - BASE64_AUTH=$(echo -n "$DOCKER_HUB_USERNAME:$DOCKER_HUB_ACCESS_TOKEN" | base64)
+    - echo "{\"auths\":{\"https://index.docker.io/v1/\":{\"auth\":\"$BASE64_AUTH\"}}}" > /kaniko/.docker/config.json
+    - /kaniko/executor --context $CI_PROJECT_DIR --dockerfile $CI_PROJECT_DIR/docker/ci/Dockerfile --destination docker.io/khanonci/oai-reverse-proxy:$TAG --build-arg CI_COMMIT_REF_NAME=$CI_COMMIT_REF_NAME --build-arg CI_COMMIT_SHA=$CI_COMMIT_SHA --build-arg CI_PROJECT_PATH=$CI_PROJECT_PATH
+  only:
+    - main

docker/ci/Dockerfile

@@ -0,0 +1,22 @@
+FROM node:18-bullseye-slim
+
+WORKDIR /app
+COPY . .
+
+RUN npm ci
+RUN npm run build
+RUN npm prune --production
+
+EXPOSE 7860
+ENV PORT=7860
+ENV NODE_ENV=production
+
+ARG CI_COMMIT_REF_NAME
+ARG CI_COMMIT_SHA
+ARG CI_PROJECT_PATH
+
+ENV GITGUD_BRANCH=$CI_COMMIT_REF_NAME
+ENV GITGUD_COMMIT=$CI_COMMIT_SHA
+ENV GITGUD_PROJECT=$CI_PROJECT_PATH
+
+CMD [ "npm", "start" ]

docker/docker-compose-selfhost.yml

@@ -0,0 +1,17 @@
+# Before running this, create a .env and greeting.md file.
+# Refer to .env.example for the required environment variables.
+# User-generated content is stored in the data directory.
+# When self-hosting, it's recommended to run this behind a reverse proxy like
+# nginx or Caddy to handle SSL/TLS and rate limiting. Refer to
+# docs/self-hosting.md for more information and an example nginx config.
+version: '3.8'
+services:
+  oai-reverse-proxy:
+    image: khanonci/oai-reverse-proxy:latest
+    ports:
+      - "127.0.0.1:7860:7860"
+    env_file:
+      - ./.env
+    volumes:
+      - ./greeting.md:/app/greeting.md
+      - ./data:/app/data

docs/aws-configuration.md

@@ -45,7 +45,7 @@ You can also request Claude Instant, but support for this isn't fully implemente
 ### Supported model IDs
 Users can send these model IDs to the proxy to invoke the corresponding models.
 - **Claude**
-  - `anthropic.claude-v1` (~18k context, claude 1.3)
+  - `anthropic.claude-v1` (~18k context, claude 1.3 -- EOL 2024-02-28)
   - `anthropic.claude-v2` (~100k context, claude 2.0)
   - `anthropic.claude-v2:1` (~200k context, claude 2.1)
 - **Claude Instant**

docs/deploy-huggingface.md

@@ -1,5 +1,7 @@
 # Deploy to Huggingface Space
 
+**⚠️ This method is no longer recommended.  Please use the [self-hosting instructions](./self-hosting.md) instead.**
+
 This repository can be deployed to a [Huggingface Space](https://huggingface.co/spaces).  This is a free service that allows you to run a simple server in the cloud.  You can use it to safely share your OpenAI API key with a friend.
 
 ### 1. Get an API key

docs/deploy-render.md

@@ -1,4 +1,7 @@
 # Deploy to Render.com
+
+**⚠️ 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.
 
 ### 1. Create account
@@ -28,6 +31,8 @@ The service will be created according to the instructions in the `render.yaml` f
   - For example, `OPENAI_KEY=sk-abc123`.
 - Click **Save Changes**.
 
+**IMPORTANT:** Set `TRUSTED_PROXIES=3`, otherwise users' IP addresses will not be recorded correctly (the server will see the IP address of Render's load balancer instead of the user's real IP address).
+
 The service will automatically rebuild and deploy with the new environment variables.  This will take a few minutes.  The link to your deployed proxy will appear at the top of the page.
 
 If you want to change the URL, go to the **Settings** tab of your Web Service and click the **Edit** button next to **Name**.  You can also set a custom domain, though I haven't tried this yet.

docs/gcp-configuration.md

@@ -0,0 +1,35 @@
+# 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

@@ -0,0 +1,135 @@
+# 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/self-hosting.md

@@ -0,0 +1,150 @@
+# Quick self-hosting guide
+
+Temporary guide for self-hosting. This will be improved in the future to provide more robust instructions and options. Provided commands are for Ubuntu.
+
+This uses prebuilt Docker images for convenience. If you want to make adjustments to the code you can instead clone the repo and follow the Local Development guide in the [README](../README.md).
+
+## Table of Contents
+- [Requirements](#requirements)
+- [Running the application](#running-the-application)
+- [Setting up a reverse proxy](#setting-up-a-reverse-proxy)
+  - [trycloudflare](#trycloudflare)
+  - [nginx](#nginx)
+    - [Example basic nginx configuration (no SSL)](#example-basic-nginx-configuration-no-ssl)
+    - [Example with Cloudflare SSL](#example-with-cloudflare-ssl)
+- [Updating/Restarting the application](#updatingrestarting-the-application)
+
+## Requirements
+
+- Docker
+- Docker Compose
+- A VPS with at least 512MB of RAM (1GB recommended)
+- A domain name
+
+If you don't have a VPS and domain name you can use TryCloudflare to set up a temporary URL that you can share with others. See [trycloudflare](#trycloudflare) for more information.
+
+## Running the application
+
+- Install Docker and Docker Compose
+- Create a new directory for the application
+  - This will contain your .env file, greeting file, and any user-generated files
+- Execute the following commands:
+  - ```
+    touch .env
+    touch greeting.md
+    echo "OPENAI_KEY=your-openai-key" >> .env
+    curl https://gitgud.io/khanon/oai-reverse-proxy/-/raw/main/docker/docker-compose-selfhost.yml -o docker-compose.yml
+    ```
+  - You can set further environment variables and keys in the `.env` file. See [.env.example](../.env.example) for a list of available options.
+  - You can set a custom greeting in `greeting.md`. This will be displayed on the homepage.
+- Run `docker compose up -d`
+
+You can check logs with `docker compose logs -n 100 -f`.
+
+The provided docker-compose file listens on port 7860 but binds to localhost only. You should use a reverse proxy to expose the application to the internet as described in the next section.
+
+## Setting up a reverse proxy
+
+Rather than exposing the application directly to the internet, it is recommended to set up a reverse proxy. This will allow you to use HTTPS and add additional security measures.
+
+### trycloudflare
+
+This will give you a temporary (72 hours) URL that you can use to let others connect to your instance securely, without having to set up a reverse proxy. If you are running the server on your home network, this is probably the best option.
+- Install `cloudflared` following the instructions at [try.cloudflare.com](https://try.cloudflare.com/).
+- Run `cloudflared tunnel --url http://localhost:7860`
+- You will be given a temporary URL that you can share with others.
+
+If you have a VPS, you should use a proper reverse proxy like nginx instead for a more permanent solution which will allow you to use your own domain name, handle SSL, and add additional security/anti-abuse measures.
+
+### nginx
+
+First, install nginx.
+- `sudo apt update && sudo apt install nginx`
+
+#### Example basic nginx configuration (no SSL)
+
+- `sudo nano /etc/nginx/sites-available/oai.conf`
+  - ```
+    server {
+        listen 80;
+        server_name example.com;
+    
+        location / {
+            proxy_pass http://localhost:7860;
+        }
+    }
+    ```
+  - Replace `example.com` with your domain name.
+  - Ctrl+X to exit, Y to save, Enter to confirm.
+- `sudo ln -s /etc/nginx/sites-available/oai.conf /etc/nginx/sites-enabled`
+- `sudo nginx -t`
+  - This will check the configuration file for errors.
+- `sudo systemctl restart nginx`
+  - This will restart nginx and apply the new configuration.
+
+#### Example with Cloudflare SSL
+
+This allows you to use a self-signed certificate on the server, and have Cloudflare handle client SSL. You need to have a Cloudflare account and have your domain set up with Cloudflare already, pointing to your server's IP address.
+
+- Set Cloudflare to use Full SSL mode. Since we are using a self-signed certificate, don't use Full (strict) mode.
+- Create a self-signed certificate:
+  - `openssl req -x509 -nodes -days 365 -newkey rsa:2048 -keyout /etc/ssl/private/nginx-selfsigned.key -out /etc/ssl/certs/nginx-selfsigned.crt`
+- `sudo nano /etc/nginx/sites-available/oai.conf`
+  - ```
+    server {
+        listen 443 ssl;
+        server_name yourdomain.com www.yourdomain.com;
+    
+        ssl_certificate /etc/ssl/certs/nginx-selfsigned.crt;
+        ssl_certificate_key /etc/ssl/private/nginx-selfsigned.key;
+    
+        # Only allow inbound traffic from Cloudflare
+        allow 173.245.48.0/20;
+        allow 103.21.244.0/22;
+        allow 103.22.200.0/22;
+        allow 103.31.4.0/22;
+        allow 141.101.64.0/18;
+        allow 108.162.192.0/18;
+        allow 190.93.240.0/20;
+        allow 188.114.96.0/20;
+        allow 197.234.240.0/22;
+        allow 198.41.128.0/17;
+        allow 162.158.0.0/15;
+        allow 104.16.0.0/13;
+        allow 104.24.0.0/14;
+        allow 172.64.0.0/13;
+        allow 131.0.72.0/22;
+        deny all;
+    
+        location / {
+            proxy_pass http://localhost:7860;
+            proxy_http_version 1.1;
+            proxy_set_header Upgrade $http_upgrade;
+            proxy_set_header Connection 'upgrade';
+            proxy_set_header Host $host;
+            proxy_cache_bypass $http_upgrade;
+        }
+    
+        ssl_protocols TLSv1.2 TLSv1.3;
+        ssl_ciphers 'ECDHE-ECDSA-AES128-GCM-SHA256:ECDHE-RSA-AES128-GCM-SHA256';
+        ssl_prefer_server_ciphers on;
+        ssl_session_cache shared:SSL:10m;
+    }
+    ```
+  - Replace `yourdomain.com` with your domain name.
+  - Ctrl+X to exit, Y to save, Enter to confirm.
+- `sudo ln -s /etc/nginx/sites-available/oai.conf /etc/nginx/sites-enabled`
+
+## Updating/Restarting the application
+
+After making an .env change, you need to restart the application for it to take effect.
+
+- `docker compose down`
+- `docker compose up -d`
+
+To update the application to the latest version:
+
+- `docker compose pull`
+- `docker compose down`
+- `docker compose up -d`
+- `docker image prune -f`

docs/user-management.md

@@ -12,6 +12,7 @@ Several of these features require you to set secrets in your environment. If usi
   - [Memory](#memory)
   - [Firebase Realtime Database](#firebase-realtime-database)
     - [Firebase setup instructions](#firebase-setup-instructions)
+- [Whitelisting admin IP addresses](#whitelisting-admin-ip-addresses)
 
 ## No user management (`GATEKEEPER=none`)
 
@@ -61,3 +62,12 @@ 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.
+
+## 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.json

@@ -4,6 +4,7 @@
   "description": "Reverse proxy for the OpenAI API",
   "scripts": {
     "build": "tsc && copyfiles -u 1 src/**/*.ejs build",
+    "database:migrate": "ts-node scripts/migrate.ts",
     "prepare": "husky install",
     "start": "node build/server.js",
     "start:dev": "nodemon --watch src --exec ts-node --transpile-only src/server.ts",
@@ -18,32 +19,39 @@
   "license": "MIT",
   "dependencies": {
     "@anthropic-ai/tokenizer": "^0.0.4",
-    "@aws-crypto/sha256-js": "^5.1.0",
-    "@smithy/protocol-http": "^3.0.6",
-    "@smithy/signature-v4": "^2.0.10",
-    "@smithy/types": "^2.3.4",
-    "axios": "^1.3.5",
+    "@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/util-utf8": "^2.1.1",
+    "axios": "^1.7.4",
+    "better-sqlite3": "^10.0.0",
     "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": "^16.0.3",
-    "ejs": "^3.1.9",
+    "dotenv": "^16.3.1",
+    "ejs": "^3.1.10",
     "express": "^4.18.2",
     "express-session": "^1.17.3",
-    "firebase-admin": "^11.10.1",
+    "firebase-admin": "^12.3.1",
+    "glob": "^10.3.12",
     "googleapis": "^122.0.0",
     "http-proxy-middleware": "^3.0.0-beta.1",
-    "lifion-aws-event-stream": "^1.0.7",
+    "ipaddr.js": "^2.1.0",
     "memorystore": "^1.6.7",
     "multer": "^1.4.5-lts.1",
     "node-schedule": "^2.1.1",
     "pino": "^8.11.0",
     "pino-http": "^8.3.3",
-    "sanitize-html": "^2.11.0",
+    "sanitize-html": "^2.13.0",
     "sharp": "^0.32.6",
     "showdown": "^2.1.0",
+    "source-map-support": "^0.5.21",
     "stream-json": "^1.8.0",
     "tiktoken": "^1.0.10",
     "uuid": "^9.0.0",
@@ -52,6 +60,8 @@
     "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",
@@ -69,12 +79,13 @@
     "nodemon": "^3.0.1",
     "pino-pretty": "^10.2.3",
     "prettier": "^3.0.3",
-    "source-map-support": "^0.5.21",
+    "prettier-plugin-ejs": "^1.0.3",
     "ts-node": "^10.9.1",
-    "typescript": "^5.1.3"
+    "typescript": "^5.4.2"
   },
   "overrides": {
-    "google-gax": "^3.6.1",
-    "postcss": "^8.4.31"
+    "braces": "^3.0.3",
+    "fast-xml-parser": "^4.4.1",
+    "follow-redirects": "^1.15.4"
   }
 }

public/css/reset.css

@@ -0,0 +1,349 @@
+/*! 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

@@ -0,0 +1,231 @@
+/* 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

@@ -0,0 +1,237 @@
+/* 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

@@ -0,0 +1,121 @@
+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;
+      // decode salt to Uint8Array
+      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 > 1000) {
+        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

@@ -0,0 +1,39 @@
+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

@@ -230,6 +230,39 @@ 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

@@ -0,0 +1,102 @@
+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

@@ -0,0 +1,118 @@
+// 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();

src/admin/api/events.ts

@@ -0,0 +1,49 @@
+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

@@ -1,17 +1,31 @@
 import express, { Router } from "express";
-import { authorize } from "./auth";
+import { createWhitelistMiddleware } from "../shared/cidr";
 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 { injectCsrfToken, checkCsrfToken } from "../shared/inject-csrf";
+import { config } from "../config";
 import { renderPage } from "../info-page";
 import { buildInfo } from "../service-info";
+import { authorize } from "./auth";
 import { loginRouter } from "./login";
-import { usersApiRouter as apiRouter } from "./api/users";
+import { eventsApiRouter } from "./api/events";
+import { usersApiRouter } from "./api/users";
 import { usersWebRouter as webRouter } from "./web/manage";
+import { logger } from "../logger";
 
 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" })
@@ -19,7 +33,8 @@ adminRouter.use(
 adminRouter.use(withSession);
 adminRouter.use(injectCsrfToken);
 
-adminRouter.use("/users", authorize({ via: "header" }), apiRouter);
+adminRouter.use("/users", authorize({ via: "header" }), usersApiRouter);
+adminRouter.use("/events", authorize({ via: "header" }), eventsApiRouter);
 
 adminRouter.use(checkCsrfToken);
 adminRouter.use(injectLocals);

src/admin/web/manage.ts

@@ -1,4 +1,5 @@
 import { Router } from "express";
+import ipaddr from "ipaddr.js";
 import multer from "multer";
 import { z } from "zod";
 import { config } from "../../config";
@@ -6,7 +7,7 @@ import { HttpError } from "../../shared/errors";
 import * as userStore from "../../shared/users/user-store";
 import { parseSort, sortBy, paginate } from "../../shared/utils";
 import { keyPool } from "../../shared/key-management";
-import { MODEL_FAMILIES } from "../../shared/models";
+import { LLMService, MODEL_FAMILIES } from "../../shared/models";
 import { getTokenCostUsd, prettyTokens } from "../../shared/stats";
 import {
   User,
@@ -14,6 +15,9 @@ import {
   UserSchema,
   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();
 
@@ -39,6 +43,74 @@ 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;
 
@@ -196,13 +268,20 @@ router.post("/maintenance", (req, res) => {
   let flash = { type: "", message: "" };
   switch (action) {
     case "recheck": {
-      keyPool.recheck("openai");
-      keyPool.recheck("anthropic");
-      const size = keyPool
+      const checkable: LLMService[] = [
+        "openai",
+        "anthropic",
+        "aws",
+        "gcp",
+        "azure",
+      ];
+      checkable.forEach((s) => keyPool.recheck(s));
+      const keyCount = keyPool
         .list()
-        .filter((k) => k.service !== "google-ai").length;
+        .filter((k) => checkable.includes(k.service)).length;
+
       flash.type = "success";
-      flash.message = `Scheduled recheck of ${size} keys for OpenAI and Anthropic.`;
+      flash.message = `Scheduled recheck of ${keyCount} keys.`;
       break;
     }
     case "resetQuotas": {
@@ -220,14 +299,138 @@ router.post("/maintenance", (req, res) => {
       flash.message = `All users' token usage records reset.`;
       break;
     }
+    case "downloadImageMetadata": {
+      const data = JSON.stringify(
+        {
+          exportedAt: new Date().toISOString(),
+          generations: getLastNImages(),
+        },
+        null,
+        2
+      );
+      res.setHeader(
+        "Content-Disposition",
+        `attachment; filename=image-metadata-${new Date().toISOString()}.json`
+      );
+      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"];
+      if (!selected || !valid.includes(selected)) {
+        throw new HttpError(400, "Invalid difficulty" + selected);
+      }
+      config.powDifficultyLevel = 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(`/admin/manage`);
+  return res.redirect(referer || "/admin/manage");
 });
 
 router.get("/download-stats", (_req, res) => {

src/admin/web/views/admin_anti-abuse.ejs

@@ -0,0 +1,140 @@
+<%- 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>
+    <span id="currentDifficulty">Current: <%= difficulty %></span>
+    <select name="difficulty" id="difficulty">
+      <option value="low">Low</option>
+      <option value="medium">Medium</option>
+      <option value="high">High</option>
+      <option value="extreme">Extreme</option>
+    </select>
+    <button onclick='doAction("setDifficulty")'>Update Difficulty</button>
+  </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. Note that 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>
+  <p>
+    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>
+  <% 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 doAction(action) {
+    document.getElementById("hiddenAction").value = action;
+    if (action === "setDifficulty") {
+      document.getElementById("hiddenDifficulty").value = document.getElementById("difficulty").value;
+    }
+    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

@@ -51,9 +51,8 @@
     <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 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.
+        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.
       </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

@@ -5,18 +5,6 @@
     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;
@@ -33,17 +21,17 @@
   }
 </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">Anonymize</label>
-      <input id="anon" type="checkbox" name="anon" value="true" />
+      <label for="anon"><input id="anon" type="checkbox" name="anon" value="true" /> <span>Anonymize</span></label>
     </div>
     <div>
       <label for="sort">Sort</label>
@@ -64,11 +52,12 @@
       </select>
     </div>
     <div>
-      <label for="format">Custom Format <ul>
-          <li><code>{{header}}</code></li>
-          <li><code>{{stats}}</code></li>
-          <li><code>{{time}}</code></li>
-        </ul></label>
+      <label for="format">Custom Format</label>
+      <ul>
+        <li><code>{{header}}</code></li>
+        <li><code>{{stats}}</code></li>
+        <li><code>{{time}}</code></li>
+      </ul>
       <textarea id="format" name="format" rows="10" cols="50" placeholder="{{stats}}">
 # Stats
 {{header}}
@@ -115,33 +104,35 @@
   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_index.ejs

@@ -25,13 +25,14 @@
   <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 display="flex" flex-direction="column">
+  <div>
     <fieldset>
       <legend>Key Recheck</legend>
       <button id="recheck-keys" type="button" onclick="submitForm('recheck')">Force Key Recheck</button>
@@ -42,7 +43,7 @@
       <legend>Bulk Quota Management</legend>
       <p>
         <button id="refresh-quotas" type="button" onclick="submitForm('resetQuotas')">Refresh All Quotas</button>
-        Resets all users' quotas to the values set in the <code>TOKEN_QUOTA_*</code> environment variables.
+        Immediately refreshes all users' quotas by the configured amounts.
       </p>
       <p>
         <button id="clear-token-counts" type="button" onclick="submitForm('resetCounts')">Clear All Token Counts</button>
@@ -50,6 +51,13 @@
       </p>
     </fieldset>
     <% } %>
+    <% if (imageGenerationEnabled) { %>
+    <fieldset>
+      <legend>Image Generation</legend>
+      <button id="download-image-metadata" type="button" onclick="submitForm('downloadImageMetadata')">Download Image Metadata</button>
+      <label for="download-image-metadata">Downloads a metadata file containing URL, prompt, and truncated user token for all cached images.</label>
+    </fieldset>
+    <% } %>
   </div>
 </form>
 

src/admin/web/views/admin_list-users.ejs

@@ -4,9 +4,8 @@
     <% if (users.length === 0) { %>
     <p>No users found.</p>
     <% } else { %>
-    <input type="checkbox" id="toggle-nicknames" onchange="toggleNicknames()" />
-    <label for="toggle-nicknames">Show Nicknames</label>
-    <table>
+    <label for="toggle-nicknames"><input type="checkbox" id="toggle-nicknames" onchange="toggleNicknames()" /> Show Nicknames</label>
+    <table class="striped full-width">
       <thead>
         <tr>
           <th>User</th>

src/admin/web/views/admin_view-user.ejs

@@ -55,8 +55,9 @@
       <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>
@@ -72,7 +73,8 @@
       <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">
@@ -85,14 +87,24 @@
       <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>
@@ -102,7 +114,8 @@
   <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 }) %>
+<% } %>
+<%- include("partials/shared_quota-info", { quota, user, showRefreshEdit: true }) %>
 
 <p><a href="/admin/manage/list-users">Back to User List</a></p>
 
@@ -113,18 +126,25 @@
       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({
-            [field]: value,
-            _csrf: document.querySelector("meta[name=csrf-token]").getAttribute("content"),
-          }),
+          body: JSON.stringify(payload),
           headers: { "Content-Type": "application/json", Accept: "application/json" },
         })
           .then((res) => Promise.all([res.ok, res.json()]))
@@ -132,9 +152,7 @@
             const url = new URL(window.location.href);
             const params = new URLSearchParams();
             if (!ok) {
-              params.set("flash", `error: ${json.error.message}`);
-            } else {
-              params.set("flash", `success: User's ${field} updated.`);
+              alert(`Failed to edit user: ${json.message}`);
             }
             url.search = params.toString();
             window.location.assign(url);
@@ -144,4 +162,5 @@
   });
 </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

@@ -0,0 +1,13 @@
+<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

@@ -1,8 +1,9 @@
+import crypto from "crypto";
 import dotenv from "dotenv";
 import type firebase from "firebase-admin";
 import path from "path";
 import pino from "pino";
-import type { ModelFamily } from "./shared/models";
+import type { LLMService, ModelFamily } from "./shared/models";
 import { MODEL_FAMILIES } from "./shared/models";
 
 dotenv.config();
@@ -16,6 +17,8 @@ export const USER_ASSETS_DIR = path.join(DATA_DIR, "user-files");
 type Config = {
   /** The port the proxy server will listen on. */
   port: number;
+  /** The network interface the proxy server will listen on. */
+  bindAddress: string;
   /** Comma-delimited list of OpenAI API keys. */
   openaiKey?: string;
   /** Comma-delimited list of Anthropic API keys. */
@@ -42,6 +45,13 @@ 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
@@ -63,6 +73,11 @@ 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
@@ -100,9 +115,70 @@ type Config = {
    * `maxIpsPerUser` limit, or if only connections from new IPs are be rejected.
    */
   maxIpsAutoBan: boolean;
-  /** Per-IP limit for requests per minute to text and chat models. */
+  /**
+   * 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. */
   textModelRateLimit: number;
-  /** Per-IP limit for requests per minute to image generation models. */
+  /** Per-user limit for requests per minute to image generation models. */
   imageModelRateLimit: number;
   /**
    * For OpenAI, the maximum number of context tokens (prompt + max output) a
@@ -139,10 +215,38 @@ 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";
+  promptLoggingBackend?: "google_sheets" | "file";
+  /** Prefix for prompt logging files when using the file backend. */
+  promptLoggingFilePrefix?: string;
   /** Base64-encoded Google Sheets API key. */
   googleSheetsKey?: string;
   /** Google Sheets spreadsheet ID. */
@@ -198,57 +302,136 @@ type Config = {
    * configured ADMIN_KEY and go to /admin/service-info.
    **/
   staticServiceInfo?: boolean;
+  /**
+   * Trusted proxy hops. If you are deploying the server behind a reverse proxy
+   * (Nginx, Cloudflare Tunnel, AWS WAF, etc.) the IP address of incoming
+   * requests will be the IP address of the proxy, not the actual user.
+   *
+   * Depending on your hosting configuration, there may be multiple proxies/load
+   * balancers between your server and the user. Each one will append the
+   * incoming IP address to the `X-Forwarded-For` header. The user's real IP
+   * address will be the first one in the list, assuming the header has not been
+   * tampered with. Setting this value correctly ensures that the server doesn't
+   * trust values in `X-Forwarded-For` not added by trusted proxies.
+   *
+   * In order for the server to determine the user's real IP address, you need
+   * to tell it how many proxies are between the user and the server so it can
+   * select the correct IP address from the `X-Forwarded-For` header.
+   *
+   * *WARNING:* If you set it incorrectly, the proxy will either record the
+   * wrong IP address, or it will be possible for users to spoof their IP
+   * addresses and bypass rate limiting. Check the request logs to see what
+   * incoming X-Forwarded-For values look like.
+   *
+   * Examples:
+   *  - X-Forwarded-For: "34.1.1.1, 172.1.1.1, 10.1.1.1" => trustedProxies: 3
+   *  - X-Forwarded-For: "34.1.1.1" => trustedProxies: 1
+   *  - no X-Forwarded-For header => trustedProxies: 0 (the actual IP of the incoming request will be used)
+   *
+   * As of 2024/01/08:
+   * For HuggingFace or Cloudflare Tunnel, use 1.
+   * For Render, use 3.
+   * For deployments not behind a load balancer, use 0.
+   *
+   * You should double check against your actual request logs to be sure.
+   *
+   * Defaults to 1, as most deployments are on HuggingFace or Cloudflare Tunnel.
+   */
+  trustedProxies?: number;
+  /**
+   * Whether to allow OpenAI tool usage.  The proxy doesn't impelment any
+   * support for tools/function calling but can pass requests and responses as
+   * is. Note that the proxy also cannot accurately track quota usage for
+   * requests involving tools, so you must opt in to this feature at your own
+   * 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
+   */
+  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[];
 };
 
 // To change configs, create a file called .env in the root directory.
 // See .env.example for an example.
 export const config: Config = {
   port: getEnvWithDefault("PORT", 7860),
+  bindAddress: getEnvWithDefault("BIND_ADDRESS", "0.0.0.0"),
   openaiKey: getEnvWithDefault("OPENAI_KEY", ""),
   anthropicKey: getEnvWithDefault("ANTHROPIC_KEY", ""),
   googleAIKey: getEnvWithDefault("GOOGLE_AI_KEY", ""),
   mistralAIKey: getEnvWithDefault("MISTRAL_AI_KEY", ""),
   awsCredentials: getEnvWithDefault("AWS_CREDENTIALS", ""),
+  gcpCredentials: getEnvWithDefault("GCP_CREDENTIALS", ""),
   azureCredentials: getEnvWithDefault("AZURE_CREDENTIALS", ""),
   proxyKey: getEnvWithDefault("PROXY_KEY", ""),
   adminKey: getEnvWithDefault("ADMIN_KEY", ""),
+  serviceInfoPassword: getEnvWithDefault("SERVICE_INFO_PASSWORD", ""),
+  sqliteDataPath: getEnvWithDefault(
+    "SQLITE_DATA_PATH",
+    path.join(DATA_DIR, "database.sqlite")
+  ),
+  eventLogging: getEnvWithDefault("EVENT_LOGGING", false),
+  eventLoggingTrim: getEnvWithDefault("EVENT_LOGGING_TRIM", 5),
   gatekeeper: getEnvWithDefault("GATEKEEPER", "none"),
   gatekeeperStore: getEnvWithDefault("GATEKEEPER_STORE", "memory"),
   maxIpsPerUser: getEnvWithDefault("MAX_IPS_PER_USER", 0),
-  maxIpsAutoBan: getEnvWithDefault("MAX_IPS_AUTO_BAN", true),
+  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),
   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", 16384),
+  maxContextTokensOpenAI: getEnvWithDefault("MAX_CONTEXT_TOKENS_OPENAI", 32768),
   maxContextTokensAnthropic: getEnvWithDefault(
     "MAX_CONTEXT_TOKENS_ANTHROPIC",
-    0
+    32768
   ),
   maxOutputTokensOpenAI: getEnvWithDefault(
     ["MAX_OUTPUT_TOKENS_OPENAI", "MAX_OUTPUT_TOKENS"],
-    400
+    1024
   ),
   maxOutputTokensAnthropic: getEnvWithDefault(
     ["MAX_OUTPUT_TOKENS_ANTHROPIC", "MAX_OUTPUT_TOKENS"],
-    400
+    1024
+  ),
+  allowedModelFamilies: getEnvWithDefault(
+    "ALLOWED_MODEL_FAMILIES",
+    getDefaultModelFamilies()
   ),
-  allowedModelFamilies: getEnvWithDefault("ALLOWED_MODEL_FAMILIES", [
-    "turbo",
-    "gpt4",
-    "gpt4-32k",
-    "gpt4-turbo",
-    "claude",
-    "gemini-pro",
-    "mistral-tiny",
-    "mistral-small",
-    "mistral-medium",
-    "aws-claude",
-    "azure-turbo",
-    "azure-gpt4",
-    "azure-gpt4-turbo",
-    "azure-gpt4-32k",
-  ]),
   rejectPhrases: parseCsv(getEnvWithDefault("REJECT_PHRASES", "")),
   rejectMessage: getEnvWithDefault(
     "REJECT_MESSAGE",
@@ -260,6 +443,10 @@ 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",
@@ -286,19 +473,53 @@ export const config: Config = {
   showRecentImages: getEnvWithDefault("SHOW_RECENT_IMAGES", true),
   useInsecureCookies: getEnvWithDefault("USE_INSECURE_COOKIES", isDev),
   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", "")),
 } as const;
 
-function generateCookieSecret() {
+function generateSigningKey() {
   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 seed = "" + config.adminKey + config.openaiKey + config.anthropicKey;
-  const crypto = require("crypto");
+  const secrets = [
+    config.adminKey,
+    config.openaiKey,
+    config.anthropicKey,
+    config.googleAIKey,
+    config.mistralAIKey,
+    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("");
   return crypto.createHash("sha256").update(seed).digest("hex");
 }
 
-export const COOKIE_SECRET = generateCookieSecret();
+const signingKey = generateSigningKey();
+export const SECRET_SIGNING_KEY = signingKey;
 
 export async function assertConfigIsValid() {
   if (process.env.MODEL_RATE_LIMIT !== undefined) {
@@ -314,6 +535,23 @@ 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.`
@@ -326,15 +564,32 @@ export async function assertConfigIsValid() {
     );
   }
 
-  if (config.gatekeeper === "proxy_key" && !config.proxyKey) {
+  if (
+    config.captchaMode === "proof_of_work" &&
+    config.gatekeeper !== "user_token"
+  ) {
     throw new Error(
-      "`proxy_key` gatekeeper mode requires a `PROXY_KEY` to be set."
+      "Captcha mode 'proof_of_work' requires gatekeeper mode 'user_token'."
     );
   }
 
-  if (config.gatekeeper !== "proxy_key" && config.proxyKey) {
+  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` is set, but gatekeeper mode is not `proxy_key`. Make sure to set `GATEKEEPER=proxy_key`."
+      "`proxy_key` gatekeeper mode requires a `PROXY_KEY` to be set."
     );
   }
 
@@ -376,20 +631,28 @@ export const SENSITIVE_KEYS: (keyof Config)[] = ["googleSheetsSpreadsheetId"];
  */
 export const OMITTED_KEYS = [
   "port",
+  "bindAddress",
   "logLevel",
   "openaiKey",
   "anthropicKey",
   "googleAIKey",
   "mistralAIKey",
   "awsCredentials",
+  "gcpCredentials",
   "azureCredentials",
   "proxyKey",
   "adminKey",
+  "serviceInfoPassword",
   "rejectPhrases",
+  "rejectMessage",
   "showTokenCosts",
+  "promptLoggingFilePrefix",
   "googleSheetsKey",
   "firebaseKey",
   "firebaseRtdbUrl",
+  "sqliteDataPath",
+  "eventLogging",
+  "eventLoggingTrim",
   "gatekeeperStore",
   "maxIpsPerUser",
   "blockedOrigins",
@@ -401,6 +664,11 @@ export const OMITTED_KEYS = [
   "staticServiceInfo",
   "checkKeys",
   "allowedModelFamilies",
+  "trustedProxies",
+  "proxyEndpointRoute",
+  "adminWhitelist",
+  "ipBlacklist",
+  "powTokenPurgeHours",
 ] satisfies (keyof Config)[];
 type OmitKeys = (typeof OMITTED_KEYS)[number];
 
@@ -461,6 +729,7 @@ function getEnvWithDefault<T>(env: string | string[], defaultValue: T): T {
         "ANTHROPIC_KEY",
         "GOOGLE_AI_KEY",
         "AWS_CREDENTIALS",
+        "GCP_CREDENTIALS",
         "AZURE_CREDENTIALS",
       ].includes(String(env))
     ) {
@@ -511,3 +780,7 @@ 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("dall-e")) as ModelFamily[];
+}

src/info-page.ts

@@ -1,35 +1,51 @@
 /** This whole module kinda sucks */
 import fs from "fs";
-import { Request, Response } from "express";
+import express, { Router, Request, Response } from "express";
 import showdown from "showdown";
 import { config } from "./config";
 import { buildInfo, ServiceInfo } from "./service-info";
 import { getLastNImages } from "./shared/file-storage/image-history";
 import { keyPool } from "./shared/key-management";
 import { MODEL_FAMILY_SERVICE, ModelFamily } from "./shared/models";
+import { withSession } from "./shared/with-session";
+import { checkCsrfToken, injectCsrfToken } from "./shared/inject-csrf";
 
 const INFO_PAGE_TTL = 2000;
 const MODEL_FAMILY_FRIENDLY_NAME: { [f in ModelFamily]: string } = {
-  "turbo": "GPT-3.5 Turbo",
-  "gpt4": "GPT-4",
+  turbo: "GPT-4o Mini / 3.5 Turbo",
+  gpt4: "GPT-4",
   "gpt4-32k": "GPT-4 32k",
   "gpt4-turbo": "GPT-4 Turbo",
+  gpt4o: "GPT-4o",
   "dall-e": "DALL-E",
-  "claude": "Claude",
+  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": "Mixtral 8x7B",
-  "mistral-medium": "Mistral Medium (prototype)",
-  "aws-claude": "AWS Claude",
+  "mistral-small": "Mistral Nemo",
+  "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-dall-e": "Azure DALL-E",
 };
 
 const converter = new showdown.Converter();
 const customGreeting = fs.existsSync("greeting.md")
-  ? `\n## Server Greeting\n${fs.readFileSync("greeting.md", "utf8")}`
+  ? `<div id="servergreeting">${fs.readFileSync("greeting.md", "utf8")}</div>`
   : "";
 let infoPageHtml: string | undefined;
 let infoPageLastUpdated = 0;
@@ -44,7 +60,7 @@ export const handleInfoPage = (req: Request, res: Response) => {
       ? getExternalUrlForHuggingfaceSpaceId(process.env.SPACE_ID)
       : req.protocol + "://" + req.get("host");
 
-  const info = buildInfo(baseUrl + "/proxy");
+  const info = buildInfo(baseUrl + config.proxyEndpointRoute);
   infoPageHtml = renderPage(info);
   infoPageLastUpdated = Date.now();
 
@@ -55,19 +71,42 @@ 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" media="screen" />
+    <link rel="stylesheet" href="/res/css/sakura.css" media="screen" />
+    <link rel="stylesheet" href="/res/css/sakura-dark.css" media="screen and (prefers-color-scheme: dark)" />
+    <style>
+      body {
+        font-family: sans-serif;
+        padding: 1em;
+        max-width: 900px;
+        margin: 0;
+      }
+      
+      .self-service-links {
+        display: flex;
+        justify-content: center;
+        margin-bottom: 1em;
+        padding: 0.5em;
+        font-size: 0.8em;
+      }
+      
+      .self-service-links a {
+        margin: 0 0.5em;
+      }
+    </style>
   </head>
-  <body style="font-family: sans-serif; background-color: #f0f0f0; padding: 1em;">
+  <body>
     ${headerHtml}
     <hr />
+    ${getSelfServiceLinks()}
     <h2>Service Info</h2>
     <pre>${JSON.stringify(info, null, 2)}</pre>
-    ${getSelfServiceLinks()}
   </body>
 </html>`;
 }
@@ -104,7 +143,9 @@ This proxy keeps full logs of all prompts and AI responses. Prompt logs are anon
 
     const wait = info[modelFamily]?.estimatedQueueTime;
     if (hasKeys && wait) {
-      waits.push(`**${MODEL_FAMILY_FRIENDLY_NAME[modelFamily] || modelFamily}**: ${wait}`);
+      waits.push(
+        `**${MODEL_FAMILY_FRIENDLY_NAME[modelFamily] || modelFamily}**: ${wait}`
+      );
     }
   }
 
@@ -119,7 +160,15 @@ This proxy keeps full logs of all prompts and AI responses. Prompt logs are anon
 
 function getSelfServiceLinks() {
   if (config.gatekeeper !== "user_token") return "";
-  return `<footer style="font-size: 0.8em;"><hr /><a target="_blank" href="/user/lookup">Check your user token info</a></footer>`;
+
+  const links = [["Check your user token", "/user/lookup"]];
+  if (config.captchaMode !== "none") {
+    links.unshift(["Request a user token", "/user/captcha"]);
+  }
+
+  return `<div class="self-service-links">${links
+    .map(([text, link]) => `<a target="_blank" href="${link}">${text}</a>`)
+    .join(" | ")}</div>`;
 }
 
 function getServerTitle() {
@@ -142,9 +191,10 @@ function getServerTitle() {
 }
 
 function buildRecentImageSection() {
+  const dalleModels: ModelFamily[] = ["azure-dall-e", "dall-e"];
   if (
-    !config.allowedModelFamilies.includes("dall-e") ||
-    !config.showRecentImages
+    !config.showRecentImages ||
+    dalleModels.every((f) => !config.allowedModelFamilies.includes(f))
   ) {
     return "";
   }
@@ -165,6 +215,7 @@ function buildRecentImageSection() {
 </div>`;
   }
   html += `</div>`;
+  html += `<p style="clear: both; text-align: center;"><a href="/user/image-history">View all recent images</a></p>`;
 
   return html;
 }
@@ -175,7 +226,9 @@ function escapeHtml(unsafe: string) {
     .replace(/</g, "&lt;")
     .replace(/>/g, "&gt;")
     .replace(/"/g, "&quot;")
-    .replace(/'/g, "&#39;");
+    .replace(/'/g, "&#39;")
+    .replace(/\[/g, "&#91;")
+    .replace(/]/g, "&#93;");
 }
 
 function getExternalUrlForHuggingfaceSpaceId(spaceId: string) {
@@ -186,3 +239,49 @@ function getExternalUrlForHuggingfaceSpaceId(spaceId: string) {
     return "";
   }
 }
+
+function checkIfUnlocked(
+  req: Request,
+  res: Response,
+  next: express.NextFunction
+) {
+  if (config.serviceInfoPassword?.length && !req.session?.unlocked) {
+    return res.redirect("/unlock-info");
+  }
+  next();
+}
+
+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

@@ -0,0 +1,9 @@
+import { NextFunction, Request, Response } from "express";
+
+export function addV1(req: Request, res: Response, next: NextFunction) {
+  // Clients don't consistently use the /v1 prefix so we'll add it for them.
+  if (!req.path.startsWith("/v1/") && !req.path.startsWith("/v1beta/")) {
+    req.url = `/v1${req.url}`;
+  }
+  next();
+}

src/proxy/anthropic.ts

@@ -1,4 +1,4 @@
-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";
@@ -16,6 +16,7 @@ import {
   ProxyResHandlerWithBody,
   createOnProxyResHandler,
 } from "./middleware/response";
+import { sendErrorToClient } from "./middleware/response/error-generator";
 
 let modelsCache: any = null;
 let modelsCacheTime = 0;
@@ -42,6 +43,10 @@ const getModelsResponse = () => {
     "claude-2",
     "claude-2.0",
     "claude-2.1",
+    "claude-3-haiku-20240307",
+    "claude-3-opus-20240229",
+    "claude-3-sonnet-20240229",
+    "claude-3-5-sonnet-20240620",
   ];
 
   const models = claudeVariants.map((id) => ({
@@ -65,7 +70,7 @@ const handleModelRequest: RequestHandler = (_req, res) => {
 };
 
 /** Only used for non-streaming requests. */
-const anthropicResponseHandler: ProxyResHandlerWithBody = async (
+const anthropicBlockingResponseHandler: ProxyResHandlerWithBody = async (
   _proxyRes,
   req,
   res,
@@ -75,30 +80,56 @@ const anthropicResponseHandler: ProxyResHandlerWithBody = async (
     throw new Error("Expected body to be an object");
   }
 
-  if (config.promptLogging) {
-    const host = req.get("host");
-    body.proxy_note = `Prompts are logged on this proxy instance. See ${host} for more information.`;
+  let newBody = body;
+  switch (`${req.inboundApi}<-${req.outboundApi}`) {
+    case "openai<-anthropic-text":
+      req.log.info("Transforming Anthropic Text back to OpenAI format");
+      newBody = transformAnthropicTextResponseToOpenAI(body, req);
+      break;
+    case "openai<-anthropic-chat":
+      req.log.info("Transforming Anthropic Chat back to OpenAI format");
+      newBody = transformAnthropicChatResponseToOpenAI(body);
+      break;
+    case "anthropic-text<-anthropic-chat":
+      req.log.info("Transforming Anthropic Chat back to Anthropic chat format");
+      newBody = transformAnthropicChatResponseToAnthropicText(body);
+      break;
   }
 
-  if (req.inboundApi === "openai") {
-    req.log.info("Transforming Anthropic response to OpenAI format");
-    body = transformAnthropicResponse(body, req);
-  }
-
-  if (req.tokenizerInfo) {
-    body.proxy_tokenizer = req.tokenizerInfo;
-  }
-
-  res.status(200).json(body);
+  res.status(200).json({ ...newBody, proxy: body.proxy });
 };
 
+function flattenChatResponse(
+  content: { type: string; text: string }[]
+): string {
+  return content
+    .map((part: { type: string; text: string }) =>
+      part.type === "text" ? part.text : ""
+    )
+    .join("\n");
+}
+
+export function transformAnthropicChatResponseToAnthropicText(
+  anthropicBody: Record<string, any>
+): Record<string, any> {
+  return {
+    type: "completion",
+    id: "ant-" + anthropicBody.id,
+    completion: flattenChatResponse(anthropicBody.content),
+    stop_reason: anthropicBody.stop_reason,
+    stop: anthropicBody.stop_sequence,
+    model: anthropicBody.model,
+    usage: anthropicBody.usage,
+  };
+}
+
 /**
  * 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 transformAnthropicResponse(
+export function transformAnthropicTextResponseToOpenAI(
   anthropicBody: Record<string, any>,
   req: Request
 ): Record<string, any> {
@@ -126,6 +157,50 @@ function transformAnthropicResponse(
   };
 }
 
+export function transformAnthropicChatResponseToOpenAI(
+  anthropicBody: Record<string, any>
+): Record<string, any> {
+  return {
+    id: "ant-" + anthropicBody.id,
+    object: "chat.completion",
+    created: Date.now(),
+    model: anthropicBody.model,
+    usage: anthropicBody.usage,
+    choices: [
+      {
+        message: {
+          role: "assistant",
+          content: flattenChatResponse(anthropicBody.content),
+        },
+        finish_reason: anthropicBody.stop_reason,
+        index: 0,
+      },
+    ],
+  };
+}
+
+/**
+ * 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";
+}
+
+/**
+ * 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
+ */
+function setAnthropicBetaHeader(req: Request) {
+  const { max_tokens_to_sample } = req.body;
+  if (max_tokens_to_sample > 4096) {
+    req.headers["anthropic-beta"] = "max-tokens-3-5-sonnet-2024-07-15";
+  }
+}
+
 const anthropicProxy = createQueueMiddleware({
   proxyMiddleware: createProxyMiddleware({
     target: "https://api.anthropic.com",
@@ -136,53 +211,109 @@ const anthropicProxy = createQueueMiddleware({
       proxyReq: createOnProxyReqHandler({
         pipeline: [addKey, addAnthropicPreamble, finalizeBody],
       }),
-      proxyRes: createOnProxyResHandler([anthropicResponseHandler]),
+      proxyRes: createOnProxyResHandler([anthropicBlockingResponseHandler]),
       error: handleProxyError,
     },
-    pathRewrite: {
-      // Send OpenAI-compat requests to the real Anthropic endpoint.
-      "^/v1/chat/completions": "/v1/complete",
+    // 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] }
+);
+
+const nativeTextPreprocessor = createPreprocessorMiddleware({
+  inApi: "anthropic-text",
+  outApi: "anthropic-text",
+  service: "anthropic",
+});
+
+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) => {
+  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",
+});
+
+const oaiToChatPreprocessor = createPreprocessorMiddleware({
+  inApi: "openai",
+  outApi: "anthropic-chat",
+  service: "anthropic",
+});
+
+/**
+ * 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) => {
+  maybeReassignModel(req);
+  if (req.body.model?.includes("claude-3")) {
+    oaiToChatPreprocessor(req, res, next);
+  } else {
+    oaiToTextPreprocessor(req, res, next);
+  }
+};
+
 const anthropicRouter = Router();
 anthropicRouter.get("/v1/models", handleModelRequest);
 // Native Anthropic chat completion endpoint.
 anthropicRouter.post(
-  "/v1/complete",
+  "/v1/messages",
   ipLimiter,
-  createPreprocessorMiddleware({
-    inApi: "anthropic",
-    outApi: "anthropic",
-    service: "anthropic",
-  }),
+  nativeAnthropicChatPreprocessor,
   anthropicProxy
 );
-// OpenAI-to-Anthropic compatibility endpoint.
+// Anthropic text completion endpoint. Translates to Anthropic chat completion
+// if the requested model is a Claude 3 model.
+anthropicRouter.post(
+  "/v1/complete",
+  ipLimiter,
+  preprocessAnthropicTextRequest,
+  anthropicProxy
+);
+// OpenAI-to-Anthropic compatibility endpoint. Accepts an OpenAI chat completion
+// request and transforms/routes it to the appropriate Anthropic format and
+// endpoint based on the requested model.
 anthropicRouter.post(
   "/v1/chat/completions",
   ipLimiter,
-  createPreprocessorMiddleware(
-    { inApi: "openai", outApi: "anthropic", service: "anthropic" },
-    { afterTransform: [maybeReassignModel] }
-  ),
+  preprocessOpenAICompatRequest,
   anthropicProxy
 );
 
-function maybeReassignModel(req: Request) {
-  const model = req.body.model;
-  if (!model.startsWith("gpt-")) return;
-
-  const bigModel = process.env.CLAUDE_BIG_MODEL || "claude-v1-100k";
-  const contextSize = req.promptTokens! + req.outputTokens!;
-  if (contextSize > 8500) {
-    req.log.debug(
-      { model: bigModel, contextSize },
-      "Using Claude 100k model for OpenAI-to-Anthropic request"
-    );
-    req.body.model = bigModel;
-  }
-}
-
 export const anthropic = anthropicRouter;

src/proxy/aws-claude.ts

@@ -0,0 +1,253 @@
+import { Request, RequestHandler, Router } from "express";
+import { createProxyMiddleware } from "http-proxy-middleware";
+import { v4 } from "uuid";
+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,
+  transformAnthropicChatResponseToOpenAI,
+} from "./anthropic";
+
+/** 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");
+  }
+
+  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 });
+};
+
+/**
+ * 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,
+      },
+    ],
+  };
+}
+
+const awsClaudeProxy = 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 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) {
+  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-v1:0
+  const pattern =
+    /^(claude-)?(instant-)?(v)?(\d+)([.-](\d))?(-\d+k)?(-sonnet-|-opus-|-haiku-)?(\d*)/i;
+  const match = model.match(pattern);
+
+  // If there's no match, fallback to Claude v2 as it is most likely to be
+  // available on AWS.
+  if (!match) {
+    req.body.model = `anthropic.claude-v2:1`;
+    return;
+  }
+
+  const [_, _cl, instant, _v, major, _sep, minor, _ctx, name, _rev] = match;
+
+  if (instant) {
+    req.body.model = "anthropic.claude-instant-v1";
+    return;
+  }
+
+  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 "3":
+    case "3.0":
+      if (name.includes("opus")) {
+        req.body.model = "anthropic.claude-3-opus-20240229-v1:0";
+      } else if (name.includes("haiku")) {
+        req.body.model = "anthropic.claude-3-haiku-20240307-v1:0";
+      } else {
+        req.body.model = "anthropic.claude-3-sonnet-20240229-v1:0";
+      }
+      return;
+    case "3.5":
+      req.body.model = "anthropic.claude-3-5-sonnet-20240620-v1:0";
+      return;
+  }
+
+  // Fallback to Claude 2.1
+  req.body.model = `anthropic.claude-v2:1`;
+  return;
+}
+
+export const awsClaude = awsClaudeRouter;

src/proxy/aws-mistral.ts

@@ -0,0 +1,110 @@
+import { Request } from "express";
+import {
+  createOnProxyResHandler,
+  ProxyResHandlerWithBody,
+} from "./middleware/response";
+import { createQueueMiddleware } from "./queue";
+import {
+  createOnProxyReqHandler,
+  createPreprocessorMiddleware,
+  finalizeSignedRequest,
+  signAwsRequest,
+} from "./middleware/request";
+import { createProxyMiddleware } from "http-proxy-middleware";
+import { logger } from "../logger";
+import { handleProxyError } from "./middleware/common";
+import { Router } from "express";
+import { ipLimiter } from "./rate-limit";
+import { detectMistralInputApi, transformMistralTextToMistralChat } from "./mistral-ai";
+
+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 = 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([awsMistralBlockingResponseHandler]),
+      error: handleProxyError,
+    },
+  }),
+});
+
+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

@@ -1,218 +1,75 @@
-import { Request, RequestHandler, Router } from "express";
-import { createProxyMiddleware } from "http-proxy-middleware";
-import { v4 } from "uuid";
+/* Shared code between AWS Claude and AWS Mistral endpoints. */
+
+import { Request, Response, Router } from "express";
 import { config } from "../config";
-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";
-
-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;
-  }
-
-  if (!config.awsCredentials) return { object: "list", data: [] };
-
-  const variants = [
-    "anthropic.claude-v1",
-    "anthropic.claude-v2",
-    "anthropic.claude-v2:1",
-  ];
-
-  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");
-  }
-
-  if (config.promptLogging) {
-    const host = req.get("host");
-    body.proxy_note = `Prompts are logged on this proxy instance. See ${host} for more information.`;
-  }
-
-  if (req.inboundApi === "openai") {
-    req.log.info("Transforming AWS Claude response to OpenAI format");
-    body = transformAwsResponse(body, req);
-  }
-
-  if (req.tokenizerInfo) {
-    body.proxy_tokenizer = req.tokenizerInfo;
-  }
-
-  // AWS does not confirm the model in the response, so we have to add it
-  body.model = req.body.model;
-
-  res.status(200).json(body);
-};
-
-/**
- * Transforms a model response from the Anthropic API to match those from the
- * OpenAI API, for users using Claude via the OpenAI-compatible endpoint. This
- * is only used for non-streaming requests as streaming requests are handled
- * on-the-fly.
- */
-function transformAwsResponse(
-  awsBody: Record<string, any>,
-  req: Request
-): Record<string, any> {
-  const totalTokens = (req.promptTokens ?? 0) + (req.outputTokens ?? 0);
-  return {
-    id: "aws-" + v4(),
-    object: "chat.completion",
-    created: Date.now(),
-    model: req.body.model,
-    usage: {
-      prompt_tokens: req.promptTokens,
-      completion_tokens: req.outputTokens,
-      total_tokens: totalTokens,
-    },
-    choices: [
-      {
-        message: {
-          role: "assistant",
-          content: awsBody.completion?.trim(),
-        },
-        finish_reason: awsBody.stop_reason,
-        index: 0,
-      },
-    ],
-  };
-}
-
-const awsProxy = createQueueMiddleware({
-  beforeProxy: signAwsRequest,
-  proxyMiddleware: createProxyMiddleware({
-    target: "bad-target-will-be-rewritten",
-    router: ({ signedRequest }) => {
-      if (!signedRequest) throw new Error("Must sign request before proxying");
-      return `${signedRequest.protocol}//${signedRequest.hostname}`;
-    },
-    changeOrigin: true,
-    selfHandleResponse: true,
-    logger,
-    on: {
-      proxyReq: createOnProxyReqHandler({ pipeline: [finalizeSignedRequest] }),
-      proxyRes: createOnProxyResHandler([awsResponseHandler]),
-      error: handleProxyError,
-    },
-  }),
-});
+import { addV1 } from "./add-v1";
+import { awsClaude } from "./aws-claude";
+import { awsMistral } from "./aws-mistral";
+import { AwsBedrockKey, keyPool } from "../shared/key-management";
 
 const awsRouter = Router();
-awsRouter.get("/v1/models", handleModelRequest);
-// Native(ish) Anthropic chat completion endpoint.
-awsRouter.post(
-  "/v1/complete",
-  ipLimiter,
-  createPreprocessorMiddleware(
-    { inApi: "anthropic", outApi: "anthropic", service: "aws" },
-    { afterTransform: [maybeReassignModel] }
-  ),
-  awsProxy
-);
-// OpenAI-to-AWS Anthropic compatibility endpoint.
-awsRouter.post(
-  "/v1/chat/completions",
-  ipLimiter,
-  createPreprocessorMiddleware(
-    { inApi: "openai", outApi: "anthropic", service: "aws" },
-    { afterTransform: [maybeReassignModel] }
-  ),
-  awsProxy
-);
+awsRouter.get(["/:vendor?/v1/models", "/:vendor?/models"], handleModelsRequest);
+awsRouter.use("/claude", addV1, awsClaude);
+awsRouter.use("/mistral", addV1, awsMistral);
 
-/**
- * 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;
+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: [] };
 
-  // If client already specified an AWS Claude model ID, use it
-  if (model.includes("anthropic.claude")) {
-    return;
+  const vendor = req.params.vendor?.length
+    ? req.params.vendor === "claude"
+      ? "anthropic"
+      : req.params.vendor
+    : "all";
+
+  const cacheTime = modelsCacheTime[vendor] || 0;
+  if (new Date().getTime() - cacheTime < MODELS_CACHE_TTL) {
+    return res.json(modelsCache[vendor]);
   }
 
-  const pattern = /^(claude-)?(instant-)?(v)?(\d+)(\.(\d+))?(-\d+k)?$/i;
-  const match = model.match(pattern);
-
-  // If there's no match, return the latest v2 model
-  if (!match) {
-    req.body.model = `anthropic.claude-v2:${LATEST_AWS_V2_MINOR_VERSION}`;
-    return;
+  const availableModelIds = new Set<string>();
+  for (const key of keyPool.list()) {
+    if (key.isDisabled || key.service !== "aws") continue;
+    (key as AwsBedrockKey).modelIds.forEach((id) => availableModelIds.add(id));
   }
 
-  const [, , instant, , major, , minor] = match;
+  // https://docs.aws.amazon.com/bedrock/latest/userguide/model-ids.html
+  const models = [
+    "anthropic.claude-v2",
+    "anthropic.claude-v2:1",
+    "anthropic.claude-3-haiku-20240307-v1:0",
+    "anthropic.claude-3-sonnet-20240229-v1:0",
+    "anthropic.claude-3-5-sonnet-20240620-v1:0",
+    "anthropic.claude-3-opus-20240229-v1:0",
+    "mistral.mistral-7b-instruct-v0:2",
+    "mistral.mixtral-8x7b-instruct-v0:1",
+    "mistral.mistral-large-2402-v1:0",
+    "mistral.mistral-large-2407-v1:0",
+    "mistral.mistral-small-2402-v1:0",
+  ]
+    .filter((id) => availableModelIds.has(id))
+    .map((id) => {
+      const vendor = id.match(/^(.*)\./)?.[1];
+      return {
+        id,
+        object: "model",
+        created: new Date().getTime(),
+        owned_by: vendor,
+        permission: [],
+        root: vendor,
+        parent: null,
+      };
+    });
 
-  if (instant) {
-    req.body.model = "anthropic.claude-instant-v1";
-    return;
-  }
+  modelsCache[vendor] = {
+    object: "list",
+    data: models.filter((m) => vendor === "all" || m.root === vendor),
+  };
+  modelsCacheTime[vendor] = new Date().getTime();
 
-  // 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:${LATEST_AWS_V2_MINOR_VERSION}`;
-    return;
-  }
-
-  // Fallback to latest v2 model
-  req.body.model = `anthropic.claude-v2:${LATEST_AWS_V2_MINOR_VERSION}`;
-  return;
+  return res.json(modelsCache[vendor]);
 }
 
 export const aws = awsRouter;

src/proxy/azure.ts

@@ -3,9 +3,9 @@ import { createProxyMiddleware } from "http-proxy-middleware";
 import { config } from "../config";
 import { keyPool } from "../shared/key-management";
 import {
-  ModelFamily,
   AzureOpenAIModelFamily,
   getAzureOpenAIModelFamily,
+  ModelFamily,
 } from "../shared/models";
 import { logger } from "../logger";
 import { KNOWN_OPENAI_MODELS } from "./openai";
@@ -80,16 +80,7 @@ const azureOpenaiResponseHandler: ProxyResHandlerWithBody = async (
     throw new Error("Expected body to be an object");
   }
 
-  if (config.promptLogging) {
-    const host = req.get("host");
-    body.proxy_note = `Prompts are logged on this proxy instance. See ${host} for more information.`;
-  }
-
-  if (req.tokenizerInfo) {
-    body.proxy_tokenizer = req.tokenizerInfo;
-  }
-
-  res.status(200).json(body);
+  res.status(200).json({ ...body, proxy: body.proxy });
 };
 
 const azureOpenAIProxy = createQueueMiddleware({
@@ -124,5 +115,15 @@ azureOpenAIRouter.post(
   }),
   azureOpenAIProxy
 );
+azureOpenAIRouter.post(
+  "/v1/images/generations",
+  ipLimiter,
+  createPreprocessorMiddleware({
+    inApi: "openai-image",
+    outApi: "openai-image",
+    service: "azure",
+  }),
+  azureOpenAIProxy
+);
 
 export const azure = azureOpenAIRouter;

src/proxy/gatekeeper.ts

@@ -1,6 +1,7 @@
-import type { Request, RequestHandler } from "express";
+import type { Request, Response, 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;
@@ -11,6 +12,7 @@ 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);
@@ -23,6 +25,12 @@ function getProxyAuthorizationFromRequest(req: Request): string | undefined {
     delete req.headers["x-api-key"];
     return token;
   }
+  
+  if (req.query.key) {
+    const token = req.query.key?.toString();
+    delete req.query.key;
+    return token;
+  }
 
   return undefined;
 }
@@ -46,24 +54,65 @@ export const gatekeeper: RequestHandler = (req, res, next) => {
   }
 
   if (GATEKEEPER === "user_token" && token) {
-    const { user, result } = authenticate(token, req.ip);
+    // RisuAI users all come from a handful of aws lambda IPs so we cannot use
+    // 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 { user, result } = authenticate(token, ip);
 
     switch (result) {
       case "success":
         req.user = user;
         return next();
       case "limited":
-        return res.status(403).json({
-          error: `Forbidden: no more IPs can authenticate with this token`,
-        });
+        return sendError(
+          req,
+          res,
+          403,
+          `Forbidden: no more IP addresses allowed for this user token`,
+          { currentIp: ip, maxIps: user?.maxIps }
+        );
       case "disabled":
         const bannedUser = getUser(token);
         if (bannedUser?.disabledAt) {
-          const reason = bannedUser.disabledReason || "Token disabled";
-          return res.status(403).json({ error: `Forbidden: ${reason}` });
+          const reason = bannedUser.disabledReason || "User token disabled";
+          return sendError(req, res, 403, `Forbidden: ${reason}`);
         }
     }
   }
 
-  res.status(401).json({ error: "Unauthorized" });
+  sendError(req, res, 401, "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

@@ -0,0 +1,193 @@
+import { Request, 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 {
+  createPreprocessorMiddleware,
+  signGcpRequest,
+  finalizeSignedRequest,
+  createOnProxyReqHandler,
+} from "./middleware/request";
+import {
+  ProxyResHandlerWithBody,
+  createOnProxyResHandler,
+} from "./middleware/response";
+import { transformAnthropicChatResponseToOpenAI } from "./anthropic";
+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-sonnet@20240229",
+    "claude-3-opus@20240229",
+    "claude-3-5-sonnet@20240620",
+  ];
+
+  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 gcpResponseHandler: 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 = createQueueMiddleware({
+  beforeProxy: signGcpRequest,
+  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([gcpResponseHandler]),
+      error: handleProxyError,
+    },
+  }),
+});
+
+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) {
+  const model = req.body.model;
+
+  // If it looks like an GCP model, use it as-is
+  // if (model.includes("anthropic.claude")) {
+  if (model.startsWith("claude-") && model.includes("@")) {
+    return;
+  }
+
+  // Anthropic model names can look like:
+  // - claude-v1
+  // - claude-2.1
+  // - claude-3-5-sonnet-20240620-v1:0
+  const pattern =
+    /^(claude-)?(instant-)?(v)?(\d+)([.-](\d{1}))?(-\d+k)?(-sonnet-|-opus-|-haiku-)?(\d*)/i;
+  const match = model.match(pattern);
+
+  // If there's no match, fallback to Claude3 Sonnet as it is most likely to be
+  // available on GCP.
+  if (!match) {
+    req.body.model = `claude-3-sonnet@${LATEST_GCP_SONNET_MINOR_VERSION}`;
+    return;
+  }
+
+  const [_, _cl, instant, _v, major, _sep, minor, _ctx, name, _rev] = match;
+  
+  const ver = minor ? `${major}.${minor}` : major;
+  switch (ver) {
+    case "3":
+    case "3.0":
+      if (name.includes("opus")) {
+        req.body.model = "claude-3-opus@20240229";
+      } else if (name.includes("haiku")) {
+        req.body.model = "claude-3-haiku@20240307";
+      } else {
+        req.body.model = "claude-3-sonnet@20240229";
+      }
+      return;
+    case "3.5":
+      req.body.model = "claude-3-5-sonnet@20240620";
+      return;
+  }
+
+  // Fallback to Claude3 Sonnet
+  req.body.model = `claude-3-sonnet@${LATEST_GCP_SONNET_MINOR_VERSION}`;
+  return;
+}
+
+export const gcp = gcpRouter;

src/proxy/google-ai.ts

@@ -10,17 +10,20 @@ import {
   createOnProxyReqHandler,
   createPreprocessorMiddleware,
   finalizeSignedRequest,
-  forceModel,
 } from "./middleware/request";
 import {
   createOnProxyResHandler,
   ProxyResHandlerWithBody,
 } from "./middleware/response";
 import { addGoogleAIKey } from "./middleware/request/preprocessors/add-google-ai-key";
+import { GoogleAIKey, keyPool } from "../shared/key-management";
 
 let modelsCache: any = null;
 let modelsCacheTime = 0;
 
+// https://ai.google.dev/models/gemini
+// TODO: list models https://ai.google.dev/tutorials/rest_quickstart#list_models
+
 const getModelsResponse = () => {
   if (new Date().getTime() - modelsCacheTime < 1000 * 60) {
     return modelsCache;
@@ -28,9 +31,19 @@ const getModelsResponse = () => {
 
   if (!config.googleAIKey) return { object: "list", data: [] };
 
-  const googleAIVariants = ["gemini-pro"];
+  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 models = googleAIVariants.map((id) => ({
+  const modelIds = Array.from(
+    new Set(keys.map((k) => k.modelIds).flat())
+  ).filter((id) => id.startsWith("models/gemini"));
+  const models = modelIds.map((id) => ({
     id,
     object: "model",
     created: new Date().getTime(),
@@ -61,21 +74,13 @@ const googleAIResponseHandler: ProxyResHandlerWithBody = async (
     throw new Error("Expected body to be an object");
   }
 
-  if (config.promptLogging) {
-    const host = req.get("host");
-    body.proxy_note = `Prompts are logged on this proxy instance. See ${host} for more information.`;
-  }
-
+  let newBody = body;
   if (req.inboundApi === "openai") {
     req.log.info("Transforming Google AI response to OpenAI format");
-    body = transformGoogleAIResponse(body, req);
+    newBody = transformGoogleAIResponse(body, req);
   }
 
-  if (req.tokenizerInfo) {
-    body.proxy_tokenizer = req.tokenizerInfo;
-  }
-
-  res.status(200).json(body);
+  res.status(200).json({ ...newBody, proxy: body.proxy });
 };
 
 function transformGoogleAIResponse(
@@ -115,7 +120,17 @@ const googleAIProxy = createQueueMiddleware({
     },
     changeOrigin: true,
     selfHandleResponse: true,
-    logger,
+    // Prevent logging of the API key by HPM
+    logger: logger.child(
+      {},
+      {
+        redact: {
+          paths: ["*"],
+          censor: (v) =>
+            typeof v === "string" ? v.replace(/key=\S+/g, "key=xxxxxxx") : v,
+        },
+      }
+    ),
     on: {
       proxyReq: createOnProxyReqHandler({ pipeline: [finalizeSignedRequest] }),
       proxyRes: createOnProxyResHandler([googleAIResponseHandler]),
@@ -126,15 +141,67 @@ const googleAIProxy = createQueueMiddleware({
 
 const googleAIRouter = Router();
 googleAIRouter.get("/v1/models", handleModelRequest);
+
+// Native Google AI chat completion endpoint
+googleAIRouter.post(
+  "/v1beta/models/:modelId:(generateContent|streamGenerateContent)",
+  ipLimiter,
+  createPreprocessorMiddleware(
+    {
+      inApi: "google-ai",
+      outApi: "google-ai",
+      service: "google-ai",
+    },
+    { beforeTransform: [maybeReassignModel], afterTransform: [setStreamFlag] }
+  ),
+  googleAIProxy
+);
+
 // OpenAI-to-Google AI compatibility endpoint.
 googleAIRouter.post(
   "/v1/chat/completions",
   ipLimiter,
   createPreprocessorMiddleware(
     { inApi: "openai", outApi: "google-ai", service: "google-ai" },
-    { afterTransform: [forceModel("gemini-pro")] }
+    { afterTransform: [maybeReassignModel] }
   ),
   googleAIProxy
 );
 
+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;
+  }
+}
+
+/**
+ * Replaces requests for non-Google AI models with gemini-pro-1.5-latest.
+ * Also strips models/ from the beginning of the model IDs.
+ **/
+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;
+
+  const requested = model;
+  if (requested.startsWith("models/")) {
+    req.body.model = requested.slice("models/".length);
+  }
+
+  if (requested.includes("gemini")) {
+    return;
+  }
+
+  req.log.info({ requested }, "Reassigning model to gemini-pro-1.5-latest");
+  req.body.model = "gemini-pro-1.5-latest";
+}
+
 export const googleAI = googleAIRouter;

src/proxy/middleware/common.ts

@@ -1,16 +1,22 @@
 import { Request, Response } from "express";
+import http from "http";
 import httpProxy from "http-proxy";
 import { ZodError } from "zod";
 import { generateErrorMessage } from "zod-error";
-import { makeCompletionSSE } from "../../shared/streaming";
+import { HttpError } from "../../shared/errors";
 import { assertNever } from "../../shared/utils";
 import { QuotaExceededError } from "./request/preprocessors/apply-quota-limits";
+import { sendErrorToClient } from "./response/error-generator";
 
 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 ANTHROPIC_COMPLETION_ENDPOINT = "/v1/complete";
+const ANTHROPIC_MESSAGES_ENDPOINT = "/v1/messages";
+const ANTHROPIC_SONNET_COMPAT_ENDPOINT = "/v1/sonnet";
+const ANTHROPIC_OPUS_COMPAT_ENDPOINT = "/v1/opus";
+const GOOGLE_AI_COMPLETION_ENDPOINT = "/v1beta/models";
 
 export function isTextGenerationRequest(req: Request) {
   return (
@@ -19,6 +25,10 @@ export function isTextGenerationRequest(req: Request) {
       OPENAI_CHAT_COMPLETION_ENDPOINT,
       OPENAI_TEXT_COMPLETION_ENDPOINT,
       ANTHROPIC_COMPLETION_ENDPOINT,
+      ANTHROPIC_MESSAGES_ENDPOINT,
+      ANTHROPIC_SONNET_COMPAT_ENDPOINT,
+      ANTHROPIC_OPUS_COMPAT_ENDPOINT,
+      GOOGLE_AI_COMPLETION_ENDPOINT,
     ].some((endpoint) => req.path.startsWith(endpoint))
   );
 }
@@ -36,7 +46,7 @@ export function isEmbeddingsRequest(req: Request) {
   );
 }
 
-export function writeErrorResponse(
+export function sendProxyError(
   req: Request,
   res: Response,
   statusCode: number,
@@ -46,31 +56,20 @@ export function writeErrorResponse(
   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 upstream service.`;
+      : `The proxy encountered an error while trying to send your prompt to the API.`;
 
-  // If we're mid-SSE stream, send a data event with the error payload and end
-  // the stream. Otherwise just send a normal error response.
-  if (
-    res.headersSent ||
-    String(res.getHeader("content-type")).startsWith("text/event-stream")
-  ) {
-    const event = makeCompletionSSE({
+  sendErrorToClient({
+    options: {
       format: req.inboundApi,
       title: `Proxy error (HTTP ${statusCode} ${statusMessage})`,
-      message: `${msg} Further technical details are provided below.`,
+      message: `${msg} Further details are provided below.`,
       obj: errorPayload,
       reqId: req.id,
       model: req.body?.model,
-    });
-    res.write(event);
-    res.write(`data: [DONE]\n\n`);
-    res.end();
-  } else {
-    if (req.tokenizerInfo && typeof errorPayload.error === "object") {
-      errorPayload.error.proxy_tokenizer = req.tokenizerInfo;
-    }
-    res.status(statusCode).json(errorPayload);
-  }
+    },
+    req,
+    res,
+  });
 }
 
 export const handleProxyError: httpProxy.ErrorCallback = (err, req, res) => {
@@ -86,11 +85,12 @@ export const classifyErrorAndSend = (
   try {
     const { statusCode, statusMessage, userMessage, ...errorDetails } =
       classifyError(err);
-    writeErrorResponse(req, res, statusCode, statusMessage, {
+    sendProxyError(req, res, statusCode, statusMessage, {
       error: { message: userMessage, ...errorDetails },
     });
   } catch (error) {
     req.log.error(error, `Error writing error response headers, giving up.`);
+    res.end();
   }
 };
 
@@ -113,6 +113,35 @@ function classifyError(err: Error): {
   };
 
   switch (err.constructor.name) {
+    case "HttpError":
+      const statusCode = (err as HttpError).status;
+      return {
+        statusCode,
+        statusMessage: `HTTP ${statusCode} ${http.STATUS_CODES[statusCode]}`,
+        userMessage: `Reverse proxy error: ${err.message}`,
+        type: "proxy_http_error",
+      };
+    case "BadRequestError":
+      return {
+        statusCode: 400,
+        statusMessage: "Bad Request",
+        userMessage: `Request is not valid. (${err.message})`,
+        type: "proxy_bad_request",
+      };
+    case "NotFoundError":
+      return {
+        statusCode: 404,
+        statusMessage: "Not Found",
+        userMessage: `Requested resource not found. (${err.message})`,
+        type: "proxy_not_found",
+      };
+    case "PaymentRequiredError":
+      return {
+        statusCode: 402,
+        statusMessage: "No Keys Available",
+        userMessage: err.message,
+        type: "proxy_no_keys_available",
+      };
     case "ZodError":
       const userMessage = generateErrorMessage((err as ZodError).issues, {
         prefix: "Request validation failed. ",
@@ -194,14 +223,32 @@ export function getCompletionFromBody(req: Request, body: Record<string, any>) {
   switch (format) {
     case "openai":
     case "mistral-ai":
-      return body.choices[0].message.content;
+      // 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 "mistral-text":
+      return body.outputs?.[0]?.text || "";
     case "openai-text":
       return body.choices[0].text;
-    case "anthropic":
+    case "anthropic-chat":
+      if (!body.content) {
+        req.log.error(
+          { body: JSON.stringify(body) },
+          "Received empty Anthropic chat completion"
+        );
+        return "";
+      }
+      return body.content
+        .map(({ text, type }: { type: string; text: string }) =>
+          type === "text" ? text : `[Unsupported content type: ${type}]`
+        )
+        .join("\n");
+    case "anthropic-text":
       if (!body.completion) {
         req.log.error(
           { body: JSON.stringify(body) },
-          "Received empty Anthropic completion"
+          "Received empty Anthropic text completion"
         );
         return "";
       }
@@ -218,21 +265,22 @@ export function getCompletionFromBody(req: Request, body: Record<string, any>) {
   }
 }
 
-export function getModelFromBody(req: Request, body: Record<string, any>) {
+export function getModelFromBody(req: Request, resBody: Record<string, any>) {
   const format = req.outboundApi;
   switch (format) {
     case "openai":
     case "openai-text":
+      return resBody.model;
     case "mistral-ai":
-      return body.model;
+    case "mistral-text":
     case "openai-image":
-      return req.body.model;
-    case "anthropic":
-      // Anthropic confirms the model in the response, but AWS Claude doesn't.
-      return body.model || req.body.model;
     case "google-ai":
-      // Google doesn't confirm the model in the response.
+      // 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;
     default:
       assertNever(format);
   }

src/proxy/middleware/request/index.ts

@@ -11,16 +11,18 @@ export {
 // 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 { 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 { signGcpRequest } from "./preprocessors/sign-vertex-ai-request";
 export { transformOutboundPayload } from "./preprocessors/transform-outbound-payload";
+export { validateContextSize } from "./preprocessors/validate-context-size";
+export { validateVision } from "./preprocessors/validate-vision";
 
 // 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 { addKey, addKeyForEmbeddingsRequest } from "./onproxyreq/add-key";
 export { blockZoomerOrigins } from "./onproxyreq/block-zoomer-origins";
 export { checkModelFamily } from "./onproxyreq/check-model-family";
 export { finalizeBody } from "./onproxyreq/finalize-body";

src/proxy/middleware/request/onproxyreq/add-anthropic-preamble.ts

@@ -7,18 +7,19 @@ import { HPMRequestCallback } from "../index";
  * 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") {
+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) {
+  if (req.key.requiresPreamble && prompt) {
     preamble = prompt.startsWith("\n\nHuman:") ? "" : "\n\nHuman:";
     req.log.debug({ key: req.key.hash, preamble }, "Adding preamble to prompt");
   }

src/proxy/middleware/request/onproxyreq/add-key.ts

@@ -1,63 +1,66 @@
+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";
 
-/** Add a key that can service this request to the request object. */
 export const addKey: HPMRequestCallback = (proxyReq, req) => {
   let assignedKey: Key;
+  const { service, inboundApi, outboundApi, body } = req;
 
-  if (!req.inboundApi || !req.outboundApi) {
+  if (!inboundApi || !outboundApi) {
     const err = new Error(
       "Request API format missing. Did you forget to add the request preprocessor to your router?"
     );
-    req.log.error(
-      { in: req.inboundApi, out: req.outboundApi, path: req.path },
-      err.message
-    );
+    req.log.error({ inboundApi, outboundApi, path: req.path }, err.message);
     throw err;
   }
 
-  if (!req.body?.model) {
+  if (!body?.model) {
     throw new Error("You must specify a model with your request.");
   }
 
-  if (req.inboundApi === req.outboundApi) {
-    assignedKey = keyPool.get(req.body.model);
+  let needsMultimodal = false;
+  if (outboundApi === "anthropic-chat") {
+    needsMultimodal = containsImageContent(
+      body.messages as AnthropicChatMessage[]
+    );
+  }
+
+  if (inboundApi === outboundApi) {
+    assignedKey = keyPool.get(body.model, service, needsMultimodal);
   } else {
-    switch (req.outboundApi) {
+    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.
-      case "anthropic":
-        assignedKey = keyPool.get("claude-v1");
+      // 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);
         break;
       case "openai-text":
-        assignedKey = keyPool.get("gpt-3.5-turbo-instruct");
+        assignedKey = keyPool.get("gpt-3.5-turbo-instruct", service);
+        break;
+      case "openai-image":
+        assignedKey = keyPool.get("dall-e-3", service);
         break;
       case "openai":
         throw new Error(
-          "OpenAI Chat as an API translation target is not supported"
+          `Outbound API ${outboundApi} is not supported for ${inboundApi}`
         );
-      case "google-ai":
-        throw new Error("add-key should not be used for this model.");
-      case "mistral-ai":
-        throw new Error("Mistral AI should never be translated");
-      case "openai-image":
-        assignedKey = keyPool.get("dall-e-3");
-        break;
       default:
-        assertNever(req.outboundApi);
+        assertNever(outboundApi);
     }
   }
 
   req.key = assignedKey;
   req.log.info(
-    {
-      key: assignedKey.hash,
-      model: req.body?.model,
-      fromApi: req.inboundApi,
-      toApi: req.outboundApi,
-    },
+    { key: assignedKey.hash, model: body.model, inboundApi, outboundApi },
     "Assigned key to request"
   );
 
@@ -71,6 +74,8 @@ export const addKey: HPMRequestCallback = (proxyReq, req) => {
       if (key.organizationId) {
         proxyReq.setHeader("OpenAI-Organization", key.organizationId);
       }
+      proxyReq.setHeader("Authorization", `Bearer ${assignedKey.key}`);
+      break;
     case "mistral-ai":
       proxyReq.setHeader("Authorization", `Bearer ${assignedKey.key}`);
       break;
@@ -79,6 +84,7 @@ export const addKey: HPMRequestCallback = (proxyReq, req) => {
       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:
@@ -106,7 +112,7 @@ export const addKeyForEmbeddingsRequest: HPMRequestCallback = (
 
   req.body = { input: req.body.input, model: "text-embedding-ada-002" };
 
-  const key = keyPool.get("text-embedding-ada-002") as OpenAIKey;
+  const key = keyPool.get("text-embedding-ada-002", "openai") as OpenAIKey;
 
   req.key = key;
   req.log.info(

src/proxy/middleware/request/onproxyreq/check-model-family.ts

@@ -1,14 +1,16 @@
-import { HPMRequestCallback } from "../index";
 import { config } from "../../../../config";
 import { ForbiddenError } from "../../../../shared/errors";
 import { getModelFamilyForRequest } from "../../../../shared/models";
+import { HPMRequestCallback } from "../index";
 
 /**
  * Ensures the selected model family is enabled by the proxy configuration.
- **/
-export const checkModelFamily: HPMRequestCallback = (_proxyReq, req, res) => {
+ */
+export const checkModelFamily: HPMRequestCallback = (_proxyReq, req) => {
   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

@@ -8,6 +8,10 @@ export const finalizeBody: HPMRequestCallback = (proxyReq, req) => {
     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));

src/proxy/middleware/request/onproxyreq/finalize-signed-request.ts

@@ -1,7 +1,7 @@
 import type { HPMRequestCallback } from "../index";
 
 /**
- * For AWS/Azure/Google requests, the body is signed earlier in the request
+ * 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.
  */

src/proxy/middleware/request/onproxyreq/strip-headers.ts

@@ -7,10 +7,15 @@ import { HPMRequestCallback } from "../index";
 export const stripHeaders: HPMRequestCallback = (proxyReq) => {
   proxyReq.setHeader("origin", "");
   proxyReq.setHeader("referer", "");
-
+  proxyReq.removeHeader("tailscale-user-login");
+  proxyReq.removeHeader("tailscale-user-name");
+  proxyReq.removeHeader("tailscale-headers-info");
+  proxyReq.removeHeader("tailscale-user-profile-pic")
   proxyReq.removeHeader("cf-connecting-ip");
   proxyReq.removeHeader("forwarded");
   proxyReq.removeHeader("true-client-ip");
   proxyReq.removeHeader("x-forwarded-for");
+  proxyReq.removeHeader("x-forwarded-host");
+  proxyReq.removeHeader("x-forwarded-proto");
   proxyReq.removeHeader("x-real-ip");
 };

src/proxy/middleware/request/preprocessor-factory.ts

@@ -1,15 +1,16 @@
 import { RequestHandler } from "express";
+import { ZodIssue } from "zod";
 import { initializeSseStream } from "../../../shared/streaming";
 import { classifyErrorAndSend } from "../common";
 import {
   RequestPreprocessor,
-  validateContextSize,
   countPromptTokens,
+  languageFilter,
   setApiFormat,
   transformOutboundPayload,
-  languageFilter,
+  validateContextSize,
+  validateVision,
 } from ".";
-import { ZodIssue } from "zod";
 
 type RequestPreprocessorOptions = {
   /**
@@ -50,6 +51,7 @@ export const createPreprocessorMiddleware = (
     languageFilter,
     ...(afterTransform ?? []),
     validateContextSize,
+    validateVision,
   ];
   return async (...args) => executePreprocessors(preprocessors, args);
 };
@@ -71,6 +73,9 @@ async function executePreprocessors(
   preprocessors: RequestPreprocessor[],
   [req, res, next]: Parameters<RequestHandler>
 ) {
+  handleTestMessage(req, res, next);
+  if (res.headersSent) return;
+
   try {
     for (const preprocessor of preprocessors) {
       await preprocessor(req);
@@ -79,9 +84,9 @@ async function executePreprocessors(
   } catch (error) {
     if (error.constructor.name === "ZodError") {
       const msg = error?.issues
-        ?.map((issue: ZodIssue) => issue.message)
+        ?.map((issue: ZodIssue) => `${issue.path.join(".")}: ${issue.message}`)
         .join("; ");
-      req.log.info(msg, "Prompt validation failed.");
+      req.log.warn({ issues: msg }, "Prompt validation failed.");
     } else {
       req.log.error(error, "Error while executing request preprocessor");
     }
@@ -99,3 +104,62 @@ async function executePreprocessors(
     classifyErrorAndSend(error as Error, req, res);
   }
 }
+
+/**
+ * Bypasses the API call and returns a test message response if the request body
+ * is a known test message from SillyTavern. Otherwise these messages just waste
+ * API request quota and confuse users when the proxy is busy, because ST always
+ * makes them with `stream: false` (which is not allowed when the proxy is busy)
+ */
+const handleTestMessage: RequestHandler = (req, res) => {
+  const { method, body } = req;
+  if (method !== "POST") {
+    return;
+  }
+
+  if (isTestMessage(body)) {
+    req.log.info({ body }, "Received test message. Skipping API call.");
+    res.json({
+      id: "test-message",
+      object: "chat.completion",
+      created: Date.now(),
+      model: body.model,
+      // openai chat
+      choices: [
+        {
+          message: { role: "assistant", content: "Hello!" },
+          finish_reason: "stop",
+          index: 0,
+        },
+      ],
+      // anthropic text
+      completion: "Hello!",
+      // anthropic chat
+      content: [{ type: "text", text: "Hello!" }],
+      proxy_note:
+        "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;
+
+  if (messages) {
+    return (
+      messages.length === 1 &&
+      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:" ||
+      prompt?.startsWith("Hi\n\n")
+    );
+  }
+}

src/proxy/middleware/request/preprocessors/add-azure-key.ts

@@ -1,8 +1,15 @@
-import { AzureOpenAIKey, keyPool } from "../../../../shared/key-management";
+import {
+  APIFormat,
+  AzureOpenAIKey,
+  keyPool,
+} from "../../../../shared/key-management";
 import { RequestPreprocessor } from "../index";
 
 export const addAzureKey: RequestPreprocessor = (req) => {
-  const apisValid = req.inboundApi === "openai" && req.outboundApi === "openai";
+  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");
@@ -16,9 +23,25 @@ export const addAzureKey: RequestPreprocessor = (req) => {
     ? req.body.model
     : `azure-${req.body.model}`;
 
-  req.key = keyPool.get(model);
+  req.key = keyPool.get(model, "azure");
   req.body.model = model;
 
+  // Handles the sole Azure API deviation from the OpenAI spec (that I know of)
+  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
+    // Azure seems to just want to combine them into logprobs: number
+    // if (typeof req.body.logprobs === "boolean") {
+    //   req.body.logprobs = req.body.top_logprobs || undefined;
+    //   delete req.body.top_logprobs
+    // }
+
+    // Temporarily just disabling logprobs for Azure because their model support
+    // is random: `This model does not support the 'logprobs' parameter.`
+    delete req.body.logprobs;
+    delete req.body.top_logprobs;
+  }
+
   req.log.info(
     { key: req.key.hash, model },
     "Assigned Azure OpenAI key to request"
@@ -27,11 +50,16 @@ export const addAzureKey: RequestPreprocessor = (req) => {
   const cred = req.key as AzureOpenAIKey;
   const { resourceName, deploymentId, apiKey } = getCredentialsFromKey(cred);
 
+  const operation =
+    req.outboundApi === "openai" ? "/chat/completions" : "/images/generations";
+  const apiVersion =
+    req.outboundApi === "openai" ? "2023-09-01-preview" : "2024-02-15-preview";
+
   req.signedRequest = {
     method: "POST",
     protocol: "https:",
     hostname: `${resourceName}.openai.azure.com`,
-    path: `/openai/deployments/${deploymentId}/chat/completions?api-version=2023-09-01-preview`,
+    path: `/openai/deployments/${deploymentId}${operation}?api-version=${apiVersion}`,
     headers: {
       ["host"]: `${resourceName}.openai.azure.com`,
       ["content-type"]: "application/json",

src/proxy/middleware/request/preprocessors/add-google-ai-key.ts

@@ -2,39 +2,38 @@ 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 inboundValid =
+    req.inboundApi === "openai" || req.inboundApi === "google-ai";
+  const outboundValid = req.outboundApi === "google-ai";
+  
   const serviceValid = req.service === "google-ai";
-  if (!apisValid || !serviceValid) {
+  if (!inboundValid || !outboundValid || !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);
-
+  req.isStreaming = req.isStreaming || req.body.stream;
+  req.key = keyPool.get(model, "google-ai");
   req.log.info(
-    { key: req.key.hash, model },
+    { key: req.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}
-
-  req.isStreaming = req.isStreaming || req.body.stream;
-  delete req.body.stream;
+  const payload = { ...req.body, stream: undefined, model: undefined };
 
   req.signedRequest = {
     method: "POST",
     protocol: "https:",
     hostname: "generativelanguage.googleapis.com",
-    path: `/v1beta/models/${model}:${req.isStreaming ? "streamGenerateContent" : "generateContent"}?key=${req.key.key}`,
+    path: `/v1beta/models/${model}:${
+      req.isStreaming ? "streamGenerateContent" : "generateContent"
+    }?key=${req.key.key}`,
     headers: {
       ["host"]: `generativelanguage.googleapis.com`,
       ["content-type"]: "application/json",
     },
-    body: JSON.stringify(req.body),
+    body: JSON.stringify(payload),
   };
 };

src/proxy/middleware/request/preprocessors/count-prompt-tokens.ts

@@ -1,11 +1,11 @@
 import { RequestPreprocessor } from "../index";
 import { countTokens } from "../../../../shared/tokenization";
 import { assertNever } from "../../../../shared/utils";
-import type {
+import {
   GoogleAIChatMessage,
   MistralAIChatMessage,
   OpenAIChatMessage,
-} from "./transform-outbound-payload";
+} from "../../../../shared/api-schemas";
 
 /**
  * Given a request with an already-transformed body, counts the number of
@@ -28,7 +28,19 @@ export const countPromptTokens: RequestPreprocessor = async (req) => {
       result = await countTokens({ req, prompt, service });
       break;
     }
-    case "anthropic": {
+    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 };
+      result = await countTokens({ req, prompt, service });
+      break;
+    }
+    case "anthropic-text": {
       req.outputTokens = req.body.max_tokens_to_sample;
       const prompt: string = req.body.prompt;
       result = await countTokens({ req, prompt, service });
@@ -40,9 +52,11 @@ export const countPromptTokens: RequestPreprocessor = async (req) => {
       result = await countTokens({ req, prompt, service });
       break;
     }
-    case "mistral-ai": {
+    case "mistral-ai":
+    case "mistral-text": {
       req.outputTokens = req.body.max_tokens;
-      const prompt: MistralAIChatMessage[] = req.body.messages;
+      const prompt: string | MistralAIChatMessage[] =
+        req.body.messages ?? req.body.prompt;
       result = await countTokens({ req, prompt, service });
       break;
     }

src/proxy/middleware/request/preprocessors/language-filter.ts

@@ -2,11 +2,12 @@ import { Request } from "express";
 import { config } from "../../../../config";
 import { assertNever } from "../../../../shared/utils";
 import { RequestPreprocessor } from "../index";
-import { UserInputError } from "../../../../shared/errors";
+import { BadRequestError } from "../../../../shared/errors";
 import {
   MistralAIChatMessage,
   OpenAIChatMessage,
-} from "./transform-outbound-payload";
+  flattenAnthropicMessages,
+} from "../../../../shared/api-schemas";
 
 const rejectedClients = new Map<string, number>();
 
@@ -45,7 +46,7 @@ export const languageFilter: RequestPreprocessor = async (req) => {
       req.res!.once("close", resolve);
       setTimeout(resolve, delay);
     });
-    throw new UserInputError(config.rejectMessage);
+    throw new BadRequestError(config.rejectMessage);
   }
 };
 
@@ -53,8 +54,8 @@ function getPromptFromRequest(req: Request) {
   const service = req.outboundApi;
   const body = req.body;
   switch (service) {
-    case "anthropic":
-      return body.prompt;
+    case "anthropic-chat":
+      return flattenAnthropicMessages(body.messages);
     case "openai":
     case "mistral-ai":
       return body.messages
@@ -69,8 +70,10 @@ function getPromptFromRequest(req: Request) {
           return `${msg.role}: ${text}`;
         })
         .join("\n\n");
+    case "anthropic-text":
     case "openai-text":
     case "openai-image":
+    case "mistral-text":
       return body.prompt;
     case "google-ai":
       return body.prompt.text;

src/proxy/middleware/request/preprocessors/sign-aws-request.ts

@@ -1,10 +1,17 @@
-import express from "express";
+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 { keyPool } from "../../../../shared/key-management";
+import {
+  AnthropicV1TextSchema,
+  AnthropicV1MessagesSchema,
+} from "../../../../shared/api-schemas";
+import { AwsBedrockKey, keyPool } from "../../../../shared/key-management";
 import { RequestPreprocessor } from "../index";
-import { AnthropicV1CompleteSchema } from "./transform-outbound-payload";
+import {
+  AWSMistralV1ChatCompletionsSchema,
+  AWSMistralV1TextCompletionsSchema,
+} from "../../../../shared/api-schemas/mistral-ai";
 
 const AMZ_HOST =
   process.env.AMZ_HOST || "bedrock-runtime.%REGION%.amazonaws.com";
@@ -12,46 +19,47 @@ const AMZ_HOST =
 /**
  * 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) => {
-  req.key = keyPool.get("anthropic.claude-v2");
-
   const { model, stream } = req.body;
+  req.key = keyPool.get(model, "aws");
+
   req.isStreaming = stream === true || stream === "true";
 
-  let preamble = req.body.prompt.startsWith("\n\nHuman:") ? "" : "\n\nHuman:";
-  req.body.prompt = preamble + req.body.prompt;
-
-  // AWS supports only a subset of Anthropic's parameters and is more strict
-  // about unknown parameters.
-  // TODO: This should happen in transform-outbound-payload.ts
-  const strippedParams = AnthropicV1CompleteSchema.pick({
-    prompt: true,
-    max_tokens_to_sample: true,
-    stop_sequences: true,
-    temperature: true,
-    top_k: true,
-    top_p: true,
-  }).strip().parse(req.body);
+  // 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;
+  }
 
   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";
 
+  // 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 =
+    (req.key as AwsBedrockKey).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/${model}/invoke${stream ? "-with-response-stream" : ""}`,
+    path: `/model/${profile}/invoke${stream ? "-with-response-stream" : ""}`,
     headers: {
       ["Host"]: host,
       ["content-type"]: "application/json",
     },
-    body: JSON.stringify(strippedParams),
+    body: JSON.stringify(applyAwsStrictValidation(req)),
   });
 
   if (stream) {
@@ -60,6 +68,18 @@ export const signAwsRequest: RequestPreprocessor = async (req) => {
     newRequest.headers["accept"] = "*/*";
   }
 
+  const { key, body, inboundApi, outboundApi } = req;
+  req.log.info(
+    {
+      key: key.hash,
+      model: body.model,
+      inferenceProfile: profile,
+      inboundApi,
+      outboundApi,
+    },
+    "Assigned AWS credentials to request"
+  );
+
   req.signedRequest = await sign(newRequest, getCredentialParts(req));
 };
 
@@ -68,6 +88,7 @@ type Credential = {
   secretAccessKey: string;
   region: string;
 };
+
 function getCredentialParts(req: express.Request): Credential {
   const [accessKeyId, secretAccessKey, region] = req.key!.key.split(":");
 
@@ -94,3 +115,50 @@ async function sign(request: HttpRequest, credential: Credential) {
 
   return signer.sign(request);
 }
+
+function applyAwsStrictValidation(req: 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,
+      })
+        .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/preprocessors/sign-vertex-ai-request.ts

@@ -0,0 +1,202 @@
+import express from "express";
+import crypto from "crypto";
+import { keyPool } from "../../../../shared/key-management";
+import { RequestPreprocessor } from "../index";
+import { AnthropicV1MessagesSchema } from "../../../../shared/api-schemas";
+
+const GCP_HOST = process.env.GCP_HOST || "%REGION%-aiplatform.googleapis.com";
+
+export const signGcpRequest: RequestPreprocessor = async (req) => {
+  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, stream } = req.body;
+  req.key = keyPool.get(model, "gcp");
+
+  req.log.info({ key: req.key.hash, model }, "Assigned GCP key to request");
+
+  req.isStreaming = String(stream) === "true";
+
+  // TODO: This should happen in transform-outbound-payload.ts
+  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,
+    tools: true,
+    tool_choice: true,
+    stream: true,
+  })
+    .strip()
+    .parse(req.body);
+  strippedParams.anthropic_version = "vertex-2023-10-16";
+  
+  const [accessToken, credential] = await getAccessToken(req);
+
+  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.
+  req.headers["anthropic-version"] = "2023-06-01";
+
+  req.signedRequest = {
+    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 ${accessToken}`,
+    },
+    body: JSON.stringify(strippedParams),
+  };
+};
+
+async function getAccessToken(
+  req: express.Request
+): Promise<[string, Credential]> {
+  // TODO: access token caching to reduce latency
+  const credential = getCredentialParts(req);
+  const signedJWT = await createSignedJWT(
+    credential.clientEmail,
+    credential.privateKey
+  );
+  const [accessToken, jwtError] = await exchangeJwtForAccessToken(signedJWT);
+  if (accessToken === null) {
+    req.log.warn(
+      { key: req.key!.hash, jwtError },
+      "Unable to get the access token"
+    );
+    throw new Error("The access token is invalid.");
+  }
+  return [accessToken, credential];
+}
+
+async function createSignedJWT(email: string, pkey: string): Promise<string> {
+  let cryptoKey = await crypto.subtle.importKey(
+    "pkcs8",
+    str2ab(atob(pkey)),
+    {
+      name: "RSASSA-PKCS1-v1_5",
+      hash: { name: "SHA-256" },
+    },
+    false,
+    ["sign"]
+  );
+
+  const authUrl = "https://www.googleapis.com/oauth2/v4/token";
+  const issued = Math.floor(Date.now() / 1000);
+  const expires = issued + 600;
+
+  const header = {
+    alg: "RS256",
+    typ: "JWT",
+  };
+
+  const payload = {
+    iss: email,
+    aud: authUrl,
+    iat: issued,
+    exp: expires,
+    scope: "https://www.googleapis.com/auth/cloud-platform",
+  };
+
+  const encodedHeader = urlSafeBase64Encode(JSON.stringify(header));
+  const encodedPayload = urlSafeBase64Encode(JSON.stringify(payload));
+
+  const unsignedToken = `${encodedHeader}.${encodedPayload}`;
+
+  const signature = await crypto.subtle.sign(
+    "RSASSA-PKCS1-v1_5",
+    cryptoKey,
+    str2ab(unsignedToken)
+  );
+
+  const encodedSignature = urlSafeBase64Encode(signature);
+  return `${unsignedToken}.${encodedSignature}`;
+}
+
+async function exchangeJwtForAccessToken(
+  signedJwt: string
+): Promise<[string | null, string]> {
+  const authUrl = "https://www.googleapis.com/oauth2/v4/token";
+  const params = {
+    grant_type: "urn:ietf:params:oauth:grant-type:jwt-bearer",
+    assertion: signedJwt,
+  };
+
+  const r = await fetch(authUrl, {
+    method: "POST",
+    headers: { "Content-Type": "application/x-www-form-urlencoded" },
+    body: Object.entries(params)
+      .map(([k, v]) => `${k}=${v}`)
+      .join("&"),
+  }).then((res) => res.json());
+
+  if (r.access_token) {
+    return [r.access_token, ""];
+  }
+
+  return [null, JSON.stringify(r)];
+}
+
+function str2ab(str: string): ArrayBuffer {
+  const buffer = new ArrayBuffer(str.length);
+  const bufferView = new Uint8Array(buffer);
+  for (let i = 0; i < str.length; i++) {
+    bufferView[i] = str.charCodeAt(i);
+  }
+  return buffer;
+}
+
+function urlSafeBase64Encode(data: string | ArrayBuffer): string {
+  let base64: string;
+  if (typeof data === "string") {
+    base64 = btoa(
+      encodeURIComponent(data).replace(/%([0-9A-F]{2})/g, (match, p1) =>
+        String.fromCharCode(parseInt("0x" + p1, 16))
+      )
+    );
+  } else {
+    base64 = btoa(String.fromCharCode(...new Uint8Array(data)));
+  }
+  return base64.replace(/\+/g, "-").replace(/\//g, "_").replace(/=+$/, "");
+}
+
+type Credential = {
+  projectId: string;
+  clientEmail: string;
+  region: string;
+  privateKey: string;
+};
+
+function getCredentialParts(req: express.Request): Credential {
+  const [projectId, clientEmail, region, rawPrivateKey] =
+    req.key!.key.split(":");
+  if (!projectId || !clientEmail || !region || !rawPrivateKey) {
+    req.log.error(
+      { key: req.key!.hash },
+      "GCP_CREDENTIALS isn't correctly formatted; refer to the docs"
+    );
+    throw new Error("The key assigned to this request is invalid.");
+  }
+
+  const privateKey = rawPrivateKey
+    .replace(
+      /-----BEGIN PRIVATE KEY-----|-----END PRIVATE KEY-----|\r|\n|\\n/g,
+      ""
+    )
+    .trim();
+
+  return { projectId, clientEmail, region, privateKey };
+}

src/proxy/middleware/request/preprocessors/transform-outbound-payload.ts

@@ -1,222 +1,45 @@
 import { Request } from "express";
-import { z } from "zod";
-import { config } from "../../../../config";
 import {
-  isTextGenerationRequest,
+  API_REQUEST_VALIDATORS,
+  API_REQUEST_TRANSFORMERS,
+} from "../../../../shared/api-schemas";
+import { BadRequestError } from "../../../../shared/errors";
+import { fixMistralPrompt } from "../../../../shared/api-schemas/mistral-ai";
+import {
   isImageGenerationRequest,
+  isTextGenerationRequest,
 } from "../../common";
 import { RequestPreprocessor } from "../index";
-import { APIFormat } from "../../../../shared/key-management";
-
-const CLAUDE_OUTPUT_MAX = config.maxOutputTokensAnthropic;
-const OPENAI_OUTPUT_MAX = config.maxOutputTokensOpenAI;
-
-// TODO: move schemas to shared
-
-// https://console.anthropic.com/docs/api/reference#-v1-complete
-export const AnthropicV1CompleteSchema = z
-  .object({
-    model: z.string().max(100),
-    prompt: z.string({
-      required_error:
-        "No prompt found. Are you sending an OpenAI-formatted request to the Claude endpoint?",
-    }),
-    max_tokens_to_sample: z.coerce
-      .number()
-      .int()
-      .transform((v) => Math.min(v, CLAUDE_OUTPUT_MAX)),
-    stop_sequences: z.array(z.string().max(500)).optional(),
-    stream: z.boolean().optional().default(false),
-    temperature: z.coerce.number().optional().default(1),
-    top_k: z.coerce.number().optional(),
-    top_p: z.coerce.number().optional(),
-  })
-  .strip();
-
-// https://platform.openai.com/docs/api-reference/chat/create
-const OpenAIV1ChatContentArraySchema = z.array(
-  z.union([
-    z.object({ type: z.literal("text"), text: z.string() }),
-    z.object({
-      type: z.literal("image_url"),
-      image_url: z.object({
-        url: z.string().url(),
-        detail: z.enum(["low", "auto", "high"]).optional().default("auto"),
-      }),
-    }),
-  ])
-);
-
-export const OpenAIV1ChatCompletionSchema = z
-  .object({
-    model: z.string().max(100),
-    messages: z.array(
-      z.object({
-        role: z.enum(["system", "user", "assistant"]),
-        content: z.union([z.string(), OpenAIV1ChatContentArraySchema]),
-        name: z.string().optional(),
-      }),
-      {
-        required_error:
-          "No `messages` found. Ensure you've set the correct completion endpoint.",
-        invalid_type_error:
-          "Messages were not formatted correctly. Refer to the OpenAI Chat API documentation for more information.",
-      }
-    ),
-    temperature: z.number().optional().default(1),
-    top_p: z.number().optional().default(1),
-    n: z
-      .literal(1, {
-        errorMap: () => ({
-          message: "You may only request a single completion at a time.",
-        }),
-      })
-      .optional(),
-    stream: z.boolean().optional().default(false),
-    stop: z
-      .union([z.string().max(500), z.array(z.string().max(500))])
-      .optional(),
-    max_tokens: z.coerce
-      .number()
-      .int()
-      .nullish()
-      .default(16)
-      .transform((v) => Math.min(v ?? OPENAI_OUTPUT_MAX, OPENAI_OUTPUT_MAX)),
-    frequency_penalty: z.number().optional().default(0),
-    presence_penalty: z.number().optional().default(0),
-    logit_bias: z.any().optional(),
-    user: z.string().max(500).optional(),
-    seed: z.number().int().optional(),
-  })
-  .strip();
-
-export type OpenAIChatMessage = z.infer<
-  typeof OpenAIV1ChatCompletionSchema
->["messages"][0];
-
-const OpenAIV1TextCompletionSchema = z
-  .object({
-    model: z
-      .string()
-      .max(100)
-      .regex(
-        /^gpt-3.5-turbo-instruct/,
-        "Model must start with 'gpt-3.5-turbo-instruct'"
-      ),
-    prompt: z.string({
-      required_error:
-        "No `prompt` found. Ensure you've set the correct completion endpoint.",
-    }),
-    logprobs: z.number().int().nullish().default(null),
-    echo: z.boolean().optional().default(false),
-    best_of: z.literal(1).optional(),
-    stop: z
-      .union([z.string().max(500), z.array(z.string().max(500)).max(4)])
-      .optional(),
-    suffix: z.string().max(1000).optional(),
-  })
-  .strip()
-  .merge(OpenAIV1ChatCompletionSchema.omit({ messages: true }));
-
-// https://platform.openai.com/docs/api-reference/images/create
-const OpenAIV1ImagesGenerationSchema = z
-  .object({
-    prompt: z.string().max(4000),
-    model: z.string().max(100).optional(),
-    quality: z.enum(["standard", "hd"]).optional().default("standard"),
-    n: z.number().int().min(1).max(4).optional().default(1),
-    response_format: z.enum(["url", "b64_json"]).optional(),
-    size: z
-      .enum(["256x256", "512x512", "1024x1024", "1792x1024", "1024x1792"])
-      .optional()
-      .default("1024x1024"),
-    style: z.enum(["vivid", "natural"]).optional().default("vivid"),
-    user: z.string().max(500).optional(),
-  })
-  .strip();
-
-// https://developers.generativeai.google/api/rest/generativelanguage/models/generateContent
-const GoogleAIV1GenerateContentSchema = z
-  .object({
-    model: z.string().max(100), //actually specified in path but we need it for the router
-    stream: z.boolean().optional().default(false), // also used for router
-    contents: z.array(
-      z.object({
-        parts: z.array(z.object({ text: z.string() })),
-        role: z.enum(["user", "model"]),
-      })
-    ),
-    tools: z.array(z.object({})).max(0).optional(),
-    safetySettings: z.array(z.object({})).max(0).optional(),
-    generationConfig: z.object({
-      temperature: z.number().optional(),
-      maxOutputTokens: z.coerce
-        .number()
-        .int()
-        .optional()
-        .default(16)
-        .transform((v) => Math.min(v, 1024)), // TODO: Add config
-      candidateCount: z.literal(1).optional(),
-      topP: z.number().optional(),
-      topK: z.number().optional(),
-      stopSequences: z.array(z.string().max(500)).max(5).optional(),
-    }),
-  })
-  .strip();
-
-export type GoogleAIChatMessage = z.infer<
-  typeof GoogleAIV1GenerateContentSchema
->["contents"][0];
-
-// https://docs.mistral.ai/api#operation/createChatCompletion
-const MistralAIV1ChatCompletionsSchema = z.object({
-  model: z.string(),
-  messages: z.array(
-    z.object({
-      role: z.enum(["system", "user", "assistant"]),
-      content: z.string(),
-    })
-  ),
-  temperature: z.number().optional().default(0.7),
-  top_p: z.number().optional().default(1),
-  max_tokens: z.coerce
-    .number()
-    .int()
-    .nullish()
-    .transform((v) => Math.min(v ?? OPENAI_OUTPUT_MAX, OPENAI_OUTPUT_MAX)),
-  stream: z.boolean().optional().default(false),
-  safe_mode: z.boolean().optional().default(false),
-  random_seed: z.number().int().optional(),
-});
-
-export type MistralAIChatMessage = z.infer<
-  typeof MistralAIV1ChatCompletionsSchema
->["messages"][0];
-
-const VALIDATORS: Record<APIFormat, z.ZodSchema<any>> = {
-  anthropic: AnthropicV1CompleteSchema,
-  openai: OpenAIV1ChatCompletionSchema,
-  "openai-text": OpenAIV1TextCompletionSchema,
-  "openai-image": OpenAIV1ImagesGenerationSchema,
-  "google-ai": GoogleAIV1GenerateContentSchema,
-  "mistral-ai": MistralAIV1ChatCompletionsSchema,
-};
 
 /** 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 || notTransformable) return;
+  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."
+    );
+    return;
+  }
 
-  if (sameService) {
-    const result = VALIDATORS[req.inboundApi].safeParse(req.body);
+  applyMistralPromptFixes(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].safeParse(req.body);
     if (!result.success) {
-      req.log.error(
+      req.log.warn(
         { issues: result.error.issues, body: req.body },
-        "Request validation failed"
+        "Native prompt request validation failed."
       );
       throw result.error;
     }
@@ -224,301 +47,50 @@ export const transformOutboundPayload: RequestPreprocessor = async (req) => {
     return;
   }
 
-  if (req.inboundApi === "openai" && req.outboundApi === "anthropic") {
-    req.body = openaiToAnthropic(req);
+  // 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.body = await transFn(req);
     return;
   }
 
-  if (req.inboundApi === "openai" && req.outboundApi === "google-ai") {
-    req.body = openaiToGoogleAI(req);
-    return;
-  }
-
-  if (req.inboundApi === "openai" && req.outboundApi === "openai-text") {
-    req.body = openaiToOpenaiText(req);
-    return;
-  }
-
-  if (req.inboundApi === "openai" && req.outboundApi === "openai-image") {
-    req.body = openaiToOpenaiImage(req);
-    return;
-  }
-
-  throw new Error(
-    `'${req.inboundApi}' -> '${req.outboundApi}' request proxying is not supported. Make sure your client is configured to use the correct API.`
+  throw new BadRequestError(
+    `${transformation} proxying is not supported. Make sure your client is configured to send requests in the correct format and to the correct endpoint.`
   );
 };
 
-function openaiToAnthropic(req: Request) {
-  const { body } = req;
-  const result = OpenAIV1ChatCompletionSchema.safeParse(body);
-  if (!result.success) {
-    req.log.warn(
-      { issues: result.error.issues, body },
-      "Invalid OpenAI-to-Anthropic request"
+// 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);
+    req.body.messages = fixMistralPrompt(result.messages);
+    req.log.info(
+      { n: req.body.messages.length, prev: result.messages.length },
+      "Applied Mistral chat prompt fixes."
     );
-    throw result.error;
-  }
 
-  req.headers["anthropic-version"] = "2023-06-01";
-
-  const { messages, ...rest } = result.data;
-  const prompt = openAIMessagesToClaudePrompt(messages);
-
-  let stops = rest.stop
-    ? Array.isArray(rest.stop)
-      ? rest.stop
-      : [rest.stop]
-    : [];
-  // Recommended by Anthropic
-  stops.push("\n\nHuman:");
-  // Helps with jailbreak prompts that send fake system messages and multi-bot
-  // chats that prefix bot messages with "System: Respond as <bot name>".
-  stops.push("\n\nSystem:");
-  // Remove duplicates
-  stops = [...new Set(stops)];
-
-  return {
-    // Model may be overridden in `calculate-context-size.ts` to avoid having
-    // a circular dependency (`calculate-context-size.ts` needs an already-
-    // transformed request body to count tokens, but this function would like
-    // to know the count to select a model).
-    model: process.env.CLAUDE_SMALL_MODEL || "claude-v1",
-    prompt: prompt,
-    max_tokens_to_sample: rest.max_tokens,
-    stop_sequences: stops,
-    stream: rest.stream,
-    temperature: rest.temperature,
-    top_p: rest.top_p,
-  };
-}
-
-function openaiToOpenaiText(req: Request) {
-  const { body } = req;
-  const result = OpenAIV1ChatCompletionSchema.safeParse(body);
-  if (!result.success) {
-    req.log.warn(
-      { issues: result.error.issues, body },
-      "Invalid OpenAI-to-OpenAI-text request"
-    );
-    throw result.error;
-  }
-
-  const { messages, ...rest } = result.data;
-  const prompt = flattenOpenAIChatMessages(messages);
-
-  let stops = rest.stop
-    ? Array.isArray(rest.stop)
-      ? rest.stop
-      : [rest.stop]
-    : [];
-  stops.push("\n\nUser:");
-  stops = [...new Set(stops)];
-
-  const transformed = { ...rest, prompt: prompt, stop: stops };
-  return OpenAIV1TextCompletionSchema.parse(transformed);
-}
-
-// Takes the last chat message and uses it verbatim as the image prompt.
-function openaiToOpenaiImage(req: Request) {
-  const { body } = req;
-  const result = OpenAIV1ChatCompletionSchema.safeParse(body);
-  if (!result.success) {
-    req.log.warn(
-      { issues: result.error.issues, body },
-      "Invalid OpenAI-to-OpenAI-image request"
-    );
-    throw result.error;
-  }
-
-  const { messages } = result.data;
-  const prompt = messages.filter((m) => m.role === "user").pop()?.content;
-  if (Array.isArray(prompt)) {
-    throw new Error("Image generation prompt must be a text message.");
-  }
-
-  if (body.stream) {
-    throw new Error(
-      "Streaming is not supported for image generation requests."
-    );
-  }
-
-  // Some frontends do weird things with the prompt, like prefixing it with a
-  // character name or wrapping the entire thing in quotes. We will look for
-  // the index of "Image:" and use everything after that as the prompt.
-
-  const index = prompt?.toLowerCase().indexOf("image:");
-  if (index === -1 || !prompt) {
-    throw new Error(
-      `Start your prompt with 'Image:' followed by a description of the image you want to generate (received: ${prompt}).`
-    );
-  }
-
-  // TODO: Add some way to specify parameters via chat message
-  const transformed = {
-    model: body.model.includes("dall-e") ? body.model : "dall-e-3",
-    quality: "standard",
-    size: "1024x1024",
-    response_format: "url",
-    prompt: prompt.slice(index! + 6).trim(),
-  };
-  return OpenAIV1ImagesGenerationSchema.parse(transformed);
-}
-
-function openaiToGoogleAI(
-  req: Request
-): z.infer<typeof GoogleAIV1GenerateContentSchema> {
-  const { body } = req;
-  const result = OpenAIV1ChatCompletionSchema.safeParse({
-    ...body,
-    model: "gpt-3.5-turbo",
-  });
-  if (!result.success) {
-    req.log.warn(
-      { issues: result.error.issues, body },
-      "Invalid OpenAI-to-Google AI request"
-    );
-    throw result.error;
-  }
-
-  const { messages, ...rest } = result.data;
-  const foundNames = new Set<string>();
-  const contents = messages
-    .map((m) => {
-      const role = m.role === "assistant" ? "model" : "user";
-      // Detects character names so we can set stop sequences for them as Gemini
-      // is prone to continuing as the next character.
-      // If names are not available, we'll still try to prefix the message
-      // with generic names so we can set stops for them but they don't work
-      // as well as real names.
-      const text = flattenOpenAIMessageContent(m.content);
-      const propName = m.name?.trim();
-      const textName =
-        m.role === "system" ? "" : text.match(/^(.{0,50}?): /)?.[1]?.trim();
-      const name =
-        propName || textName || (role === "model" ? "Character" : "User");
-
-      foundNames.add(name);
-
-      // Prefixing messages with their character name seems to help avoid
-      // Gemini trying to continue as the next character, or at the very least
-      // ensures it will hit the stop sequence.  Otherwise it will start a new
-      // paragraph and switch perspectives.
-      // The response will be very likely to include this prefix so frontends
-      // will need to strip it out.
-      const textPrefix = textName ? "" : `${name}: `;
-      return {
-        parts: [{ text: textPrefix + text }],
-        role: m.role === "assistant" ? ("model" as const) : ("user" as const),
-      };
-    })
-    .reduce<GoogleAIChatMessage[]>((acc, msg) => {
-      const last = acc[acc.length - 1];
-      if (last?.role === msg.role) {
-        last.parts[0].text += "\n\n" + msg.parts[0].text;
-      } else {
-        acc.push(msg);
-      }
-      return acc;
-    }, []);
-
-  let stops = rest.stop
-    ? Array.isArray(rest.stop)
-      ? rest.stop
-      : [rest.stop]
-    : [];
-  stops.push(...Array.from(foundNames).map((name) => `\n${name}:`));
-  stops = [...new Set(stops)].slice(0, 5);
-
-  return {
-    model: "gemini-pro",
-    stream: rest.stream,
-    contents,
-    tools: [],
-    generationConfig: {
-      maxOutputTokens: rest.max_tokens,
-      stopSequences: stops,
-      topP: rest.top_p,
-      topK: 40, // openai schema doesn't have this, google ai defaults to 40
-      temperature: rest.temperature,
-    },
-    safetySettings: [
-      { category: "HARM_CATEGORY_HARASSMENT", threshold: "BLOCK_NONE" },
-      { category: "HARM_CATEGORY_HATE_SPEECH", threshold: "BLOCK_NONE" },
-      { category: "HARM_CATEGORY_SEXUALLY_EXPLICIT", threshold: "BLOCK_NONE" },
-      { category: "HARM_CATEGORY_DANGEROUS_CONTENT", threshold: "BLOCK_NONE" },
-    ],
-  };
-}
-
-export function openAIMessagesToClaudePrompt(messages: OpenAIChatMessage[]) {
-  return (
-    messages
-      .map((m) => {
-        let role: string = m.role;
-        if (role === "assistant") {
-          role = "Assistant";
-        } else if (role === "system") {
-          role = "System";
-        } else if (role === "user") {
-          role = "Human";
-        }
-        const name = m.name?.trim();
-        const content = flattenOpenAIMessageContent(m.content);
-        // https://console.anthropic.com/docs/prompt-design
-        // `name` isn't supported by Anthropic but we can still try to use it.
-        return `\n\n${role}: ${name ? `(as ${name}) ` : ""}${content}`;
-      })
-      .join("") + "\n\nAssistant:"
-  );
-}
-
-function flattenOpenAIChatMessages(messages: OpenAIChatMessage[]) {
-  // Temporary to allow experimenting with prompt strategies
-  const PROMPT_VERSION: number = 1;
-  switch (PROMPT_VERSION) {
-    case 1:
-      return (
-        messages
-          .map((m) => {
-            // Claude-style human/assistant turns
-            let role: string = m.role;
-            if (role === "assistant") {
-              role = "Assistant";
-            } else if (role === "system") {
-              role = "System";
-            } else if (role === "user") {
-              role = "User";
-            }
-            return `\n\n${role}: ${flattenOpenAIMessageContent(m.content)}`;
-          })
-          .join("") + "\n\nAssistant:"
+    // If the prompt relies on `prefix: true` for the last message, we need to
+    // convert it to a text completions request because AWS Mistral support for
+    // this feature is broken.
+    // On Mistral La Plateforme, we can't do this because they don't expose
+    // a text completions endpoint.
+    const { messages } = req.body;
+    const lastMessage = messages && messages[messages.length - 1];
+    if (lastMessage?.role === "assistant" && req.service === "aws") {
+      // enable prefix if client forgot, otherwise the template will insert an
+      // eos token which is very unlikely to be what the client wants.
+      lastMessage.prefix = true;
+      req.outboundApi = "mistral-text";
+      req.log.info(
+        "Native Mistral chat prompt relies on assistant message prefix. Converting to text completions request."
       );
-    case 2:
-      return messages
-        .map((m) => {
-          // Claude without prefixes (except system) and no Assistant priming
-          let role: string = "";
-          if (role === "system") {
-            role = "System: ";
-          }
-          return `\n\n${role}${flattenOpenAIMessageContent(m.content)}`;
-        })
-        .join("");
-    default:
-      throw new Error(`Unknown prompt version: ${PROMPT_VERSION}`);
+    }
   }
 }
-
-function flattenOpenAIMessageContent(
-  content: OpenAIChatMessage["content"]
-): string {
-  return Array.isArray(content)
-    ? content
-        .map((contentItem) => {
-          if ("text" in contentItem) return contentItem.text;
-          if ("image_url" in contentItem) return "[ Uploaded Image Omitted ]";
-        })
-        .join("\n")
-    : content;
-}

src/proxy/middleware/request/preprocessors/validate-context-size.ts

@@ -6,8 +6,9 @@ import { RequestPreprocessor } from "../index";
 
 const CLAUDE_MAX_CONTEXT = config.maxContextTokensAnthropic;
 const OPENAI_MAX_CONTEXT = config.maxContextTokensOpenAI;
-const GOOGLE_AI_MAX_CONTEXT = 32000;
-const MISTRAL_AI_MAX_CONTENT = 32768;
+// todo: make configurable
+const GOOGLE_AI_MAX_CONTEXT = 1024000;
+const MISTRAL_AI_MAX_CONTENT = 131072;
 
 /**
  * Assigns `req.promptTokens` and `req.outputTokens` based on the request body
@@ -29,14 +30,17 @@ export const validateContextSize: RequestPreprocessor = async (req) => {
     case "openai-text":
       proxyMax = OPENAI_MAX_CONTEXT;
       break;
-    case "anthropic":
+    case "anthropic-chat":
+    case "anthropic-text":
       proxyMax = CLAUDE_MAX_CONTEXT;
       break;
     case "google-ai":
       proxyMax = GOOGLE_AI_MAX_CONTEXT;
       break;
     case "mistral-ai":
+    case "mistral-text":
       proxyMax = MISTRAL_AI_MAX_CONTENT;
+      break;
     case "openai-image":
       return;
     default:
@@ -44,15 +48,28 @@ 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-4-1106(-preview)?/)) {
+  } else if (model.match(/^gpt-4o/)) {
+    modelMax = 128000;
+  } 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(/gpt-3.5-turbo/)) {
-    modelMax = 4096;
+    modelMax = 16384;
   } else if (model.match(/gpt-4-32k/)) {
     modelMax = 32768;
   } else if (model.match(/gpt-4/)) {
@@ -65,13 +82,21 @@ export const validateContextSize: RequestPreprocessor = async (req) => {
     modelMax = 100000;
   } else if (model.match(/^claude-2/)) {
     modelMax = 200000;
-  } 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(/^claude-3/)) {
+    modelMax = 200000;
+  } else if (model.match(/^gemini-/)) {
+    modelMax = 1024000;
+  } else if (model.match(/^anthropic\.claude-3/)) {
+    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(/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;

src/proxy/middleware/request/preprocessors/validate-vision.ts

@@ -0,0 +1,44 @@
+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 { 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 "anthropic-chat":
+      hasImage = containsImageContentAnthropic(req.body.messages);
+      break;
+    case "anthropic-text":
+    case "google-ai":
+    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/response/error-generator.ts

@@ -0,0 +1,385 @@
+import express from "express";
+import { APIFormat } from "../../../shared/key-management";
+import { assertNever } from "../../../shared/utils";
+import { initializeSseStream } from "../../../shared/streaming";
+
+function getMessageContent({
+  title,
+  message,
+  obj,
+}: {
+  title: string;
+  message: string;
+  obj?: Record<string, any>;
+}) {
+  /*
+  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."
+  }
+  ```
+   */
+
+  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;
+  }
+
+  return [
+    header,
+    friendlyMessage,
+    serializedObj,
+    prettyTrace,
+    "<!-- oai-proxy-error -->",
+  ].join("\n\n");
+}
+
+type ErrorGeneratorOptions = {
+  format: APIFormat | "unknown";
+  title: string;
+  message: string;
+  obj?: Record<string, any>;
+  reqId: string | number | object;
+  model?: string;
+  statusCode?: number;
+};
+
+export function tryInferFormat(body: any): APIFormat | "unknown" {
+  if (typeof body !== "object" || !body.model) {
+    return "unknown";
+  }
+
+  if (body.model.includes("gpt")) {
+    return "openai";
+  }
+
+  if (body.model.includes("mistral")) {
+    return "mistral-ai";
+  }
+
+  if (body.model.includes("claude")) {
+    return body.messages?.length ? "anthropic-chat" : "anthropic-text";
+  }
+
+  if (body.model.includes("gemini")) {
+    return "google-ai";
+  }
+
+  return "unknown";
+}
+
+// avoid leaking upstream hostname on dns resolution error
+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;
+}
+
+export function sendErrorToClient({
+  options,
+  req,
+  res,
+}: {
+  options: ErrorGeneratorOptions;
+  req: express.Request;
+  res: express.Response;
+}) {
+  const redactedOpts = redactHostname(options);
+  const { format: inputFormat } = redactedOpts;
+
+  const format =
+    inputFormat === "unknown" ? tryInferFormat(req.body) : inputFormat;
+  if (format === "unknown") {
+    return res.status(redactedOpts.statusCode || 400).json({
+      error: redactedOpts.message,
+      details: redactedOpts.obj,
+    });
+  }
+
+  const completion = buildSpoofedCompletion({ ...redactedOpts, format });
+  const event = buildSpoofedSSE({ ...redactedOpts, format });
+  const isStreaming =
+    req.isStreaming || req.body.stream === true || req.body.stream === "true";
+
+  if (!res.headersSent) {
+    res.setHeader("x-oai-proxy-error", redactedOpts.title);
+    res.setHeader("x-oai-proxy-error-status", redactedOpts.statusCode || 500);
+  }
+
+  if (isStreaming) {
+    if (!res.headersSent) {
+      initializeSseStream(res);
+    }
+    res.write(event);
+    res.write(`data: [DONE]\n\n`);
+    res.end();
+  } else {
+    res.status(200).json(completion);
+  }
+}
+
+/**
+ * Returns a non-streaming completion object that looks like it came from the
+ * service that the request is being proxied to. Used to send error messages to
+ * the client and have them look like normal responses, for clients with poor
+ * error handling.
+ */
+export function buildSpoofedCompletion({
+  format,
+  title,
+  message,
+  obj,
+  reqId,
+  model = "unknown",
+}: ErrorGeneratorOptions & { format: Exclude<APIFormat, "unknown"> }) {
+  const id = String(reqId);
+  const content = getMessageContent({ title, message, obj });
+
+  switch (format) {
+    case "openai":
+    case "mistral-ai":
+      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-text":
+      return {
+        outputs: [{ text: content, stop_reason: title }],
+        model,
+      }
+    case "openai-text":
+      return {
+        id: "error-" + id,
+        object: "text_completion",
+        created: Date.now(),
+        model,
+        usage: { prompt_tokens: 0, completion_tokens: 0, total_tokens: 0 },
+        choices: [
+          { text: content, index: 0, logprobs: null, finish_reason: title },
+        ],
+      };
+    case "anthropic-text":
+      return {
+        id: "error-" + id,
+        type: "completion",
+        completion: content,
+        stop_reason: title,
+        stop: null,
+        model,
+      };
+    case "anthropic-chat":
+      return {
+        id: "error-" + id,
+        type: "message",
+        role: "assistant",
+        content: [{ type: "text", text: content }],
+        model,
+        stop_reason: title,
+        stop_sequence: null,
+      };
+    case "google-ai":
+      return {
+        candidates: [
+          {
+            content: { parts: [{ text: content }], role: "model" },
+            finishReason: title,
+            index: 0,
+            tokenCount: null,
+            safetyRatings: [],
+          },
+        ],
+      };
+    case "openai-image":
+      return obj;
+    default:
+      assertNever(format);
+  }
+}
+
+/**
+ * Returns an SSE message that looks like a completion event for the service
+ * that the request is being proxied to. Used to send error messages to the
+ * client in the middle of a streaming request.
+ */
+export function buildSpoofedSSE({
+  format,
+  title,
+  message,
+  obj,
+  reqId,
+  model = "unknown",
+}: ErrorGeneratorOptions & { format: Exclude<APIFormat, "unknown"> }) {
+  const id = String(reqId);
+  const content = getMessageContent({ title, message, obj });
+
+  let event;
+
+  switch (format) {
+    case "openai":
+    case "mistral-ai":
+      event = {
+        id: "chatcmpl-" + id,
+        object: "chat.completion.chunk",
+        created: Date.now(),
+        model,
+        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,
+        object: "text_completion",
+        created: Date.now(),
+        choices: [
+          { text: content, index: 0, logprobs: null, finish_reason: title },
+        ],
+        model,
+      };
+      break;
+    case "anthropic-text":
+      event = {
+        completion: content,
+        stop_reason: title,
+        truncated: false,
+        stop: null,
+        model,
+        log_id: "proxy-req-" + id,
+      };
+      break;
+    case "anthropic-chat":
+      event = {
+        type: "content_block_delta",
+        index: 0,
+        delta: { type: "text_delta", text: content },
+      };
+      break;
+    case "google-ai":
+      // TODO: google ai supports two streaming transports, SSE and JSON.
+      // we currently only support SSE.
+      // return JSON.stringify({
+      event = {
+        candidates: [
+          {
+            content: { parts: [{ text: content }], role: "model" },
+            finishReason: title,
+            index: 0,
+            tokenCount: null,
+            safetyRatings: [],
+          },
+        ],
+      };
+      break;
+    case "openai-image":
+      return JSON.stringify(obj);
+    default:
+      assertNever(format);
+  }
+
+  if (format === "anthropic-text") {
+    return (
+      ["event: completion", `data: ${JSON.stringify(event)}`].join("\n") +
+      "\n\n"
+    );
+  }
+
+  // ugh.
+  if (format === "anthropic-chat") {
+    return (
+      [
+        [
+          "event: message_start",
+          `data: ${JSON.stringify({
+            type: "message_start",
+            message: {
+              id: "error-" + id,
+              type: "message",
+              role: "assistant",
+              content: [],
+              model,
+            },
+          })}`,
+        ].join("\n"),
+        [
+          "event: content_block_start",
+          `data: ${JSON.stringify({
+            type: "content_block_start",
+            index: 0,
+            content_block: { type: "text", text: "" },
+          })}`,
+        ].join("\n"),
+        ["event: content_block_delta", `data: ${JSON.stringify(event)}`].join(
+          "\n"
+        ),
+        [
+          "event: content_block_stop",
+          `data: ${JSON.stringify({ type: "content_block_stop", index: 0 })}`,
+        ].join("\n"),
+        [
+          "event: message_delta",
+          `data: ${JSON.stringify({
+            type: "message_delta",
+            delta: { stop_reason: title, stop_sequence: null, usage: null },
+          })}`,
+        ],
+        [
+          "event: message_stop",
+          `data: ${JSON.stringify({ type: "message_stop" })}`,
+        ].join("\n"),
+      ].join("\n\n") + "\n\n"
+    );
+  }
+
+  return `data: ${JSON.stringify(event)}\n\n`;
+}

src/proxy/middleware/response/handle-blocking-response.ts

@@ -0,0 +1,76 @@
+import util from "util";
+import zlib from "zlib";
+import { sendProxyError } from "../common";
+import type { RawResponseBodyHandler } from "./index";
+
+const DECODER_MAP = {
+  gzip: util.promisify(zlib.gunzip),
+  deflate: util.promisify(zlib.inflate),
+  br: util.promisify(zlib.brotliDecompress),
+};
+
+const isSupportedContentEncoding = (
+  contentEncoding: string
+): contentEncoding is keyof typeof DECODER_MAP => {
+  return contentEncoding in DECODER_MAP;
+};
+
+/**
+ * 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<string>((resolve, reject) => {
+    let chunks: Buffer[] = [];
+    proxyRes.on("data", (chunk) => chunks.push(chunk));
+    proxyRes.on("end", async () => {
+      let body = Buffer.concat(chunks);
+
+      const contentEncoding = proxyRes.headers["content-encoding"];
+      if (contentEncoding) {
+        if (isSupportedContentEncoding(contentEncoding)) {
+          const decoder = DECODER_MAP[contentEncoding];
+          // @ts-ignore - started failing after upgrading TypeScript, don't care
+          // as it was never a problem.
+          body = await decoder(body);
+        } else {
+          const error = `Proxy received response with unsupported content-encoding: ${contentEncoding}`;
+          req.log.warn({ contentEncoding, key: req.key?.hash }, error);
+          sendProxyError(req, res, 500, "Internal Server Error", {
+            error,
+            contentEncoding,
+          });
+          return reject(error);
+        }
+      }
+
+      try {
+        if (proxyRes.headers["content-type"]?.includes("application/json")) {
+          const json = JSON.parse(body.toString());
+          return resolve(json);
+        }
+        return resolve(body.toString());
+      } catch (e) {
+        const msg = `Proxy received response with invalid JSON: ${e.message}`;
+        req.log.warn({ error: e.stack, key: req.key?.hash }, msg);
+        sendProxyError(req, res, 500, "Internal Server Error", { error: msg });
+        return reject(msg);
+      }
+    });
+  });
+};

src/proxy/middleware/response/handle-streamed-response.ts

@@ -1,28 +1,40 @@
-import { pipeline } from "stream";
+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 {
-  makeCompletionSSE,
   copySseResponseHeaders,
   initializeSseStream,
 } from "../../../shared/streaming";
-import { enqueue } from "../../queue";
-import { decodeResponseBody, RawResponseBodyHandler, RetryableError } from ".";
-import { SSEStreamAdapter } from "./streaming/sse-stream-adapter";
-import { SSEMessageTransformer } from "./streaming/sse-message-transformer";
+import { reenqueueRequest } from "../../queue";
+import type { RawResponseBodyHandler } from ".";
+import { handleBlockingResponse } from "./handle-blocking-response";
+import { buildSpoofedSSE, sendErrorToClient } from "./error-generator";
+import { getAwsEventStreamDecoder } from "./streaming/aws-event-stream-decoder";
 import { EventAggregator } from "./streaming/event-aggregator";
-import { keyPool } from "../../../shared/key-management";
+import { SSEMessageTransformer } from "./streaming/sse-message-transformer";
+import { SSEStreamAdapter } from "./streaming/sse-stream-adapter";
 
 const pipelineAsync = promisify(pipeline);
 
 /**
- * Consume the SSE stream and forward events to the client. Once the stream is
- * stream is closed, resolve with the full response body so that subsequent
- * middleware can work with it.
+ * `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.
  *
- * Typically we would only need of the raw response handlers to execute, but
- * in the event a streamed request results in a non-200 response, we need to
- * fall back to the non-streaming response handler so that the error handler
- * can inspect the error response.
+ * 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).
+ *
+ * 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.
  */
 export const handleStreamedResponse: RawResponseBodyHandler = async (
   proxyRes,
@@ -40,28 +52,45 @@ export const handleStreamedResponse: RawResponseBodyHandler = async (
       { statusCode: proxyRes.statusCode, key: hash },
       `Streaming request returned error status code. Falling back to non-streaming response handler.`
     );
-    return decodeResponseBody(proxyRes, req, res);
+    return handleBlockingResponse(proxyRes, req, res);
   }
 
-  req.log.debug(
-    { headers: proxyRes.headers, key: hash },
-    `Starting to proxy SSE stream.`
-  );
+  req.log.debug({ headers: proxyRes.headers }, `Starting to proxy SSE stream.`);
 
-  // Users waiting in the queue already have a SSE connection open for the
-  // heartbeat, so we can't always send the stream headers.
+  // Typically, streaming will have already been initialized by the request
+  // queue to send heartbeat pings.
   if (!res.headersSent) {
     copySseResponseHeaders(proxyRes, res);
     initializeSseStream(res);
   }
 
   const prefersNativeEvents = req.inboundApi === req.outboundApi;
-  const contentType = proxyRes.headers["content-type"];
+  const streamOptions = {
+    contentType: proxyRes.headers["content-type"],
+    api: req.outboundApi,
+    logger: req.log,
+  };
 
-  const adapter = new SSEStreamAdapter({ contentType, api: req.outboundApi });
-  const aggregator = new EventAggregator({ format: req.outboundApi });
+  // 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);
+
+  // Decoder reads from the raw response buffer and produces a stream of
+  // discrete events in some format (text/event-stream, vnd.amazon.event-stream,
+  // streaming JSON, etc).
+  const decoder = getDecoder({ ...streamOptions, input: proxyRes });
+  // Adapter consumes the decoded events and produces server-sent events so we
+  // have a standard event format for the client and to translate between API
+  // message formats.
+  const adapter = new SSEStreamAdapter(streamOptions);
+  // Transformer converts server-sent events from one vendor's API message
+  // format to another.
   const transformer = new SSEMessageTransformer({
-    inputFormat: req.outboundApi,
+    inputFormat: req.outboundApi, // The format of the upstream service's events
+    outputFormat: req.inboundApi, // The format the client requested
     inputApiVersion: String(req.headers["anthropic-version"]),
     logger: req.log,
     requestId: String(req.id),
@@ -76,23 +105,33 @@ export const handleStreamedResponse: RawResponseBodyHandler = async (
     });
 
   try {
-    await pipelineAsync(proxyRes, adapter, transformer);
-    req.log.debug({ key: hash }, `Finished proxying SSE stream.`);
+    await Promise.race([
+      handleAbortedStream(req, res),
+      pipelineAsync(proxyRes, decoder, adapter, transformer),
+    ]);
+    req.log.debug(`Finished proxying SSE stream.`);
     res.end();
     return aggregator.getFinalResponse();
   } catch (err) {
     if (err instanceof RetryableError) {
       keyPool.markRateLimited(req.key!);
-      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);
+      await reenqueueRequest(req);
+    } else if (err instanceof BadRequestError) {
+      sendErrorToClient({
+        req,
+        res,
+        options: {
+          format: req.inboundApi,
+          title: "Proxy streaming error (Bad Request)",
+          message: `The API returned an error while streaming your request. Your prompt might not be formatted correctly.\n\n*${err.message}*`,
+          reqId: req.id,
+          model: req.body?.model,
+        },
+      });
     } else {
       const { message, stack, lastEvent } = err;
-      const eventText = JSON.stringify(lastEvent, null, 2) ?? "undefined"
-      const errorEvent = makeCompletionSSE({
+      const eventText = JSON.stringify(lastEvent, null, 2) ?? "undefined";
+      const errorEvent = buildSpoofedSSE({
         format: req.inboundApi,
         title: "Proxy stream error",
         message: "An unexpected error occurred while streaming the response.",
@@ -104,6 +143,54 @@ export const handleStreamedResponse: RawResponseBodyHandler = async (
       res.write(`data: [DONE]\n\n`);
       res.end();
     }
-    throw err;
+
+    // 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;
+    }
   }
 };
+
+function handleAbortedStream(req: express.Request, res: express.Response) {
+  return new Promise<void>((resolve) =>
+    res.on("close", () => {
+      if (!res.writableEnded) {
+        req.log.info("Client prematurely closed connection during stream.");
+      }
+      resolve();
+    })
+  );
+}
+
+function getDecoder(options: {
+  input: Readable;
+  api: APIFormat;
+  logger: typeof logger;
+  contentType?: string;
+}) {
+  const { api, contentType, input, logger } = options;
+  if (contentType?.includes("application/vnd.amazon.eventstream")) {
+    return getAwsEventStreamDecoder({ input, logger });
+  } else if (api === "google-ai") {
+    return StreamArray.withParser();
+  } else {
+    // Passthrough stream, but ensures split chunks across multi-byte characters
+    // are handled correctly.
+    const stringDecoder = new StringDecoder("utf8");
+    return new Transform({
+      readableObjectMode: true,
+      writableObjectMode: false,
+      transform(chunk, _encoding, callback) {
+        const text = stringDecoder.write(chunk);
+        if (text) this.push(text);
+        callback();
+      },
+    });
+  }
+}

src/proxy/middleware/response/index.ts

@@ -1,10 +1,9 @@
 /* This file is fucking horrendous, sorry */
+// TODO: extract all per-service error response handling into its own modules
 import { Request, Response } from "express";
 import * as http from "http";
-import util from "util";
-import zlib from "zlib";
-import { enqueue, trackWaitTime } from "../../queue";
-import { HttpError } from "../../../shared/errors";
+import { config } from "../../../config";
+import { HttpError, RetryableError } from "../../../shared/errors";
 import { keyPool } from "../../../shared/key-management";
 import { getOpenAIModelFamily } from "../../../shared/models";
 import { countTokens } from "../../../shared/tokenization";
@@ -13,45 +12,31 @@ import {
   incrementTokenCount,
 } from "../../../shared/users/user-store";
 import { assertNever } from "../../../shared/utils";
+import { reenqueueRequest, trackWaitTime } from "../../queue";
 import { refundLastAttempt } from "../../rate-limit";
 import {
   getCompletionFromBody,
   isImageGenerationRequest,
   isTextGenerationRequest,
-  writeErrorResponse,
+  sendProxyError,
 } from "../common";
+import { handleBlockingResponse } from "./handle-blocking-response";
 import { handleStreamedResponse } from "./handle-streamed-response";
 import { logPrompt } from "./log-prompt";
+import { logEvent } from "./log-event";
 import { saveImage } from "./save-image";
 
-const DECODER_MAP = {
-  gzip: util.promisify(zlib.gunzip),
-  deflate: util.promisify(zlib.inflate),
-  br: util.promisify(zlib.brotliDecompress),
-};
-
-const isSupportedContentEncoding = (
-  contentEncoding: string
-): contentEncoding is keyof typeof DECODER_MAP => {
-  return contentEncoding in DECODER_MAP;
-};
-
-export class RetryableError extends Error {
-  constructor(message: string) {
-    super(message);
-    this.name = "RetryableError";
-  }
-}
-
 /**
- * Either decodes or streams the entire response body and then passes it as the
- * last argument to the rest of the middleware stack.
+ * Either decodes or streams the entire response body and then resolves with it.
+ * @returns The response body as a string or parsed JSON object depending on the
+ * response's content-type.
  */
 export type RawResponseBodyHandler = (
   proxyRes: http.IncomingMessage,
   req: Request,
   res: Response
 ) => Promise<string | Record<string, any>>;
+
 export type ProxyResHandlerWithBody = (
   proxyRes: http.IncomingMessage,
   req: Request,
@@ -75,6 +60,10 @@ export type ProxyResMiddleware = ProxyResHandlerWithBody[];
  * middleware from executing as it consumes the stream and forwards events to
  * the client. Once the stream is closed, the finalized body will be attached
  * to res.body and the remaining middleware will execute.
+ *
+ * @param apiMiddleware - Custom middleware to execute after the common response
+ * handlers. These *only* execute for non-streaming responses, so should be used
+ * to transform non-streaming responses into the desired format.
  */
 export const createOnProxyResHandler = (apiMiddleware: ProxyResMiddleware) => {
   return async (
@@ -82,35 +71,35 @@ export const createOnProxyResHandler = (apiMiddleware: ProxyResMiddleware) => {
     req: Request,
     res: Response
   ) => {
-    const initialHandler = req.isStreaming
+    const initialHandler: RawResponseBodyHandler = req.isStreaming
       ? handleStreamedResponse
-      : decodeResponseBody;
-
+      : handleBlockingResponse;
     let lastMiddleware = initialHandler.name;
 
     try {
       const body = await initialHandler(proxyRes, req, res);
-
       const middlewareStack: ProxyResMiddleware = [];
 
       if (req.isStreaming) {
-        // `handleStreamedResponse` writes to the response and ends it, so
-        // we can only execute middleware that doesn't write to the response.
+        // Handlers for streaming requests must never write to the response.
         middlewareStack.push(
-          trackRateLimit,
+          trackKeyRateLimit,
           countResponseTokens,
           incrementUsage,
-          logPrompt
+          logPrompt,
+          logEvent
         );
       } else {
         middlewareStack.push(
-          trackRateLimit,
+          trackKeyRateLimit,
+          injectProxyInfo,
           handleUpstreamErrors,
           countResponseTokens,
           incrementUsage,
           copyHttpHeaders,
           saveImage,
           logPrompt,
+          logEvent,
           ...apiMiddleware
         );
       }
@@ -152,72 +141,6 @@ export const createOnProxyResHandler = (apiMiddleware: ProxyResMiddleware) => {
   };
 };
 
-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);
-}
-
-/**
- * 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.
- * @throws {Error} Unsupported content-encoding or invalid application/json body
- */
-export const decodeResponseBody: RawResponseBodyHandler = async (
-  proxyRes,
-  req,
-  res
-) => {
-  if (req.isStreaming) {
-    const err = new Error("decodeResponseBody called for a streaming request.");
-    req.log.error({ stack: err.stack, api: req.inboundApi }, err.message);
-    throw err;
-  }
-
-  return new Promise<string>((resolve, reject) => {
-    let chunks: Buffer[] = [];
-    proxyRes.on("data", (chunk) => chunks.push(chunk));
-    proxyRes.on("end", async () => {
-      let body = Buffer.concat(chunks);
-
-      const contentEncoding = proxyRes.headers["content-encoding"];
-      if (contentEncoding) {
-        if (isSupportedContentEncoding(contentEncoding)) {
-          const decoder = DECODER_MAP[contentEncoding];
-          body = await decoder(body);
-        } else {
-          const errorMessage = `Proxy received response with unsupported content-encoding: ${contentEncoding}`;
-          req.log.warn({ contentEncoding, key: req.key?.hash }, errorMessage);
-          writeErrorResponse(req, res, 500, "Internal Server Error", {
-            error: errorMessage,
-            contentEncoding,
-          });
-          return reject(errorMessage);
-        }
-      }
-
-      try {
-        if (proxyRes.headers["content-type"]?.includes("application/json")) {
-          const json = JSON.parse(body.toString());
-          return resolve(json);
-        }
-        return resolve(body.toString());
-      } catch (error: any) {
-        const errorMessage = `Proxy received response with invalid JSON: ${error.message}`;
-        req.log.warn({ error: error.stack, key: req.key?.hash }, errorMessage);
-        writeErrorResponse(req, res, 500, "Internal Server Error", {
-          error: errorMessage,
-        });
-        return reject(errorMessage);
-      }
-    });
-  });
-};
-
 type ProxiedErrorPayload = {
   error?: Record<string, any>;
   message?: string;
@@ -240,15 +163,9 @@ const handleUpstreamErrors: ProxyResHandlerWithBody = async (
 ) => {
   const statusCode = proxyRes.statusCode || 500;
   const statusMessage = proxyRes.statusMessage || "Internal Server Error";
-
-  if (statusCode < 400) {
-    return;
-  }
-
   let errorPayload: ProxiedErrorPayload;
-  const tryAgainMessage = keyPool.available(req.body?.model)
-    ? `There may be more keys available for this model; try again in a few seconds.`
-    : "There are no more keys available for this model.";
+
+  if (statusCode < 400) return;
 
   try {
     assertJsonResponse(body);
@@ -265,10 +182,17 @@ const handleUpstreamErrors: ProxyResHandlerWithBody = async (
       proxy_note: `Proxy got back an error, but it was not in JSON format. This is likely a temporary problem with the upstream service.`,
     };
 
-    writeErrorResponse(req, res, statusCode, statusMessage, errorObject);
+    sendProxyError(req, res, statusCode, statusMessage, errorObject);
     throw new HttpError(statusCode, parseError.message);
   }
 
+  const service = req.key!.service;
+  if (service === "gcp") {
+    if (Array.isArray(errorPayload)) {
+      errorPayload = errorPayload[0];
+    }
+  }
+
   const errorType =
     errorPayload.error?.code ||
     errorPayload.error?.type ||
@@ -279,19 +203,23 @@ const handleUpstreamErrors: ProxyResHandlerWithBody = async (
     `Received error response from upstream. (${proxyRes.statusMessage})`
   );
 
-  const service = req.key!.service;
+  // TODO: split upstream error handling into separate modules for each service,
+  // this is out of control.
+
   if (service === "aws") {
     // Try to standardize the error format for AWS
     errorPayload.error = { message: errorPayload.message, type: errorType };
     delete errorPayload.message;
+  } else if (service === "gcp") {
+    // Try to standardize the error format for GCP
+    if (errorPayload.error?.code) { // GCP Error
+      errorPayload.error = { message: errorPayload.error.message, type: errorPayload.error.status || errorPayload.error.code };
+    }
   }
 
   if (statusCode === 400) {
-    // Bad request. For OpenAI, this is usually due to prompt length.
-    // For Anthropic, this is usually due to missing preamble.
     switch (service) {
       case "openai":
-      case "google-ai":
       case "mistral-ai":
       case "azure":
         const filteredCodes = ["content_policy_violation", "content_filter"];
@@ -301,14 +229,18 @@ const handleUpstreamErrors: ProxyResHandlerWithBody = async (
         } else if (errorPayload.error?.code === "billing_hard_limit_reached") {
           // For some reason, some models return this 400 error instead of the
           // same 429 billing error that other models return.
-          await handleOpenAIRateLimitError(req, tryAgainMessage, errorPayload);
+          await handleOpenAIRateLimitError(req, errorPayload);
         } else {
           errorPayload.proxy_note = `The upstream API rejected the request. Your prompt may be too long for ${req.body?.model}.`;
         }
         break;
       case "anthropic":
       case "aws":
-        await maybeHandleMissingPreambleError(req, errorPayload);
+      case "gcp":
+        await handleAnthropicAwsBadRequestError(req, errorPayload);
+        break;
+      case "google-ai":
+        await handleGoogleAIBadRequestError(req, errorPayload);
         break;
       default:
         assertNever(service);
@@ -316,34 +248,61 @@ const handleUpstreamErrors: ProxyResHandlerWithBody = async (
   } else if (statusCode === 401) {
     // Key is invalid or was revoked
     keyPool.disable(req.key!, "revoked");
-    errorPayload.proxy_note = `API key is invalid or revoked. ${tryAgainMessage}`;
+    errorPayload.proxy_note = `Assigned API key is invalid or revoked, please try again.`;
   } else if (statusCode === 403) {
-    if (service === "anthropic") {
-      keyPool.disable(req.key!, "revoked");
-      errorPayload.proxy_note = `API key is invalid or revoked. ${tryAgainMessage}`;
-      return;
-    }
-    switch (errorType) {
-      case "UnrecognizedClientException":
-        // Key is invalid.
+    switch (service) {
+      case "anthropic":
+        if (
+          errorType === "permission_error" &&
+          errorPayload.error?.message?.toLowerCase().includes("multimodal")
+        ) {
+          req.log.warn(
+            { key: req.key?.hash },
+            "This Anthropic key does not support multimodal prompts."
+          );
+          keyPool.update(req.key!, { allowsMultimodality: false });
+          await reenqueueRequest(req);
+          throw new RetryableError(
+            "Claude request re-enqueued because key does not support multimodality."
+          );
+        } else {
+          keyPool.disable(req.key!, "revoked");
+          errorPayload.proxy_note = `Assigned API key is invalid or revoked, please try again.`;
+        }
+        return;
+      case "aws":
+        switch (errorType) {
+          case "UnrecognizedClientException":
+            // Key is invalid.
+            keyPool.disable(req.key!, "revoked");
+            errorPayload.proxy_note = `Assigned API key is invalid or revoked, please try again.`;
+            break;
+          case "AccessDeniedException":
+            const isModelAccessError =
+              errorPayload.error?.message?.includes(`specified model ID`);
+            if (!isModelAccessError) {
+              req.log.error(
+                { key: req.key?.hash, model: req.body?.model },
+                "Disabling key due to AccessDeniedException when invoking model. If credentials are valid, check IAM permissions."
+              );
+              keyPool.disable(req.key!, "revoked");
+            }
+            errorPayload.proxy_note = `API key doesn't have access to the requested resource. Model ID: ${req.body?.model}`;
+            break;
+          default:
+            errorPayload.proxy_note = `Received 403 error. Key may be invalid.`;
+        }
+        return;
+        case "mistral-ai":
+        case "gcp":
         keyPool.disable(req.key!, "revoked");
-        errorPayload.proxy_note = `API key is invalid or revoked. ${tryAgainMessage}`;
-        break;
-      case "AccessDeniedException":
-        req.log.error(
-          { key: req.key?.hash, model: req.body?.model },
-          "Disabling key due to AccessDeniedException when invoking model. If credentials are valid, check IAM permissions."
-        );
-        keyPool.disable(req.key!, "revoked");
-        errorPayload.proxy_note = `API key doesn't have access to the requested resource.`;
-        break;
-      default:
-        errorPayload.proxy_note = `Received 403 error. Key may be invalid.`;
+        errorPayload.proxy_note = `Assigned API key is invalid or revoked, please try again.`;
+        return;
     }
   } else if (statusCode === 429) {
     switch (service) {
       case "openai":
-        await handleOpenAIRateLimitError(req, tryAgainMessage, errorPayload);
+        await handleOpenAIRateLimitError(req, errorPayload);
         break;
       case "anthropic":
         await handleAnthropicRateLimitError(req, errorPayload);
@@ -351,6 +310,9 @@ const handleUpstreamErrors: ProxyResHandlerWithBody = async (
       case "aws":
         await handleAwsRateLimitError(req, errorPayload);
         break;
+      case "gcp":
+        await handleGcpRateLimitError(req, errorPayload);
+        break;
       case "azure":
       case "mistral-ai":
         await handleAzureRateLimitError(req, errorPayload);
@@ -387,6 +349,9 @@ const handleUpstreamErrors: ProxyResHandlerWithBody = async (
       case "aws":
         errorPayload.proxy_note = `The requested AWS resource might not exist, or the key might not have access to it.`;
         break;
+      case "gcp":
+        errorPayload.proxy_note = `The requested GCP resource might not exist, or the key might not have access to it.`;
+        break;
       case "azure":
         errorPayload.proxy_note = `The assigned Azure deployment does not support the requested model.`;
         break;
@@ -405,37 +370,23 @@ const handleUpstreamErrors: ProxyResHandlerWithBody = async (
     );
   }
 
-  writeErrorResponse(req, res, statusCode, statusMessage, errorPayload);
+  sendProxyError(req, res, statusCode, statusMessage, errorPayload);
+  // This is bubbled up to onProxyRes's handler for logging but will not trigger
+  // a write to the response as `sendProxyError` has just done that.
   throw new HttpError(statusCode, errorPayload.error?.message);
 };
 
-/**
- * This is a workaround for a very strange issue where certain API keys seem to
- * enforce more strict input validation than others -- specifically, they will
- * require a `\n\nHuman:` prefix on the prompt, perhaps to prevent the key from
- * being used as a generic text completion service and to enforce the use of
- * the chat RLHF.  This is not documented anywhere, and it's not clear why some
- * keys enforce this and others don't.
- * This middleware checks for that specific error and marks the key as being
- * one that requires the prefix, and then re-enqueues the request.
- * The exact error is:
- * ```
- * {
- *   "error": {
- *     "type": "invalid_request_error",
- *     "message": "prompt must start with \"\n\nHuman:\" turn"
- *   }
- * }
- * ```
- */
-async function maybeHandleMissingPreambleError(
+async function handleAnthropicAwsBadRequestError(
   req: Request,
   errorPayload: ProxiedErrorPayload
 ) {
-  if (
-    errorPayload.error?.type === "invalid_request_error" &&
-    errorPayload.error?.message === 'prompt must start with "\n\nHuman:" turn'
-  ) {
+  const { error } = errorPayload;
+  const isMissingPreamble = error?.message.startsWith(
+    `prompt must start with "\n\nHuman:" turn`
+  );
+
+  // Some keys mandate a \n\nHuman: preamble, which we can add and retry
+  if (isMissingPreamble) {
     req.log.warn(
       { key: req.key?.hash },
       "Request failed due to missing preamble. Key will be marked as such for subsequent requests."
@@ -443,9 +394,37 @@ async function maybeHandleMissingPreambleError(
     keyPool.update(req.key!, { requiresPreamble: true });
     await reenqueueRequest(req);
     throw new RetryableError("Claude request re-enqueued to add preamble.");
-  } else {
-    errorPayload.proxy_note = `Proxy received unrecognized error from Anthropic. Check the specific error for more information.`;
   }
+
+  // {"type":"error","error":{"type":"invalid_request_error","message":"Usage blocked until 2024-03-01T00:00:00+00:00 due to user specified spend limits."}}
+  // {"type":"error","error":{"type":"invalid_request_error","message":"Your credit balance is too low to access the Claude API. Please go to Plans & Billing to upgrade or purchase credits."}}
+  const isOverQuota =
+    error?.message?.match(/usage blocked until/i) ||
+    error?.message?.match(/credit balance is too low/i);
+  if (isOverQuota) {
+    req.log.warn(
+      { key: req.key?.hash, message: error?.message },
+      "Anthropic key has hit spending limit and will be disabled."
+    );
+    keyPool.disable(req.key!, "quota");
+    errorPayload.proxy_note = `Assigned key has hit its spending limit. ${error?.message}`;
+    return;
+  }
+
+  const isDisabled =
+    error?.message?.match(/organization has been disabled/i) ||
+    error?.message?.match(/^operation not allowed/i);
+  if (isDisabled) {
+    req.log.warn(
+      { key: req.key?.hash, message: error?.message },
+      "Anthropic/AWS key has been disabled."
+    );
+    keyPool.disable(req.key!, "revoked");
+    errorPayload.proxy_note = `Assigned key has been disabled. (${error?.message})`;
+    return;
+  }
+
+  errorPayload.proxy_note = `Unrecognized error from the API. (${error?.message})`;
 }
 
 async function handleAnthropicRateLimitError(
@@ -457,7 +436,7 @@ async function handleAnthropicRateLimitError(
     await reenqueueRequest(req);
     throw new RetryableError("Claude rate-limited request re-enqueued.");
   } else {
-    errorPayload.proxy_note = `Unrecognized rate limit error from Anthropic. Key may be over quota.`;
+    errorPayload.proxy_note = `Unrecognized 429 Too Many Requests error from the API.`;
   }
 }
 
@@ -479,9 +458,21 @@ async function handleAwsRateLimitError(
   }
 }
 
+async function handleGcpRateLimitError(
+  req: Request,
+  errorPayload: ProxiedErrorPayload
+) {
+  if (errorPayload.error?.type === "RESOURCE_EXHAUSTED") {
+    keyPool.markRateLimited(req.key!);
+    await reenqueueRequest(req);
+    throw new RetryableError("GCP rate-limited request re-enqueued.");
+  } else {
+    errorPayload.proxy_note = `Unrecognized 429 Too Many Requests error from GCP.`;
+  }
+}
+
 async function handleOpenAIRateLimitError(
   req: Request,
-  tryAgainMessage: string,
   errorPayload: ProxiedErrorPayload
 ): Promise<Record<string, any>> {
   const type = errorPayload.error?.type;
@@ -490,17 +481,17 @@ async function handleOpenAIRateLimitError(
     case "invalid_request_error": // this is the billing_hard_limit_reached error seen in some cases
       // Billing quota exceeded (key is dead, disable it)
       keyPool.disable(req.key!, "quota");
-      errorPayload.proxy_note = `Assigned key's quota has been exceeded. ${tryAgainMessage}`;
+      errorPayload.proxy_note = `Assigned key's quota has been exceeded. Please try again.`;
       break;
     case "access_terminated":
       // Account banned (key is dead, disable it)
       keyPool.disable(req.key!, "revoked");
-      errorPayload.proxy_note = `Assigned key has been banned by OpenAI for policy violations. ${tryAgainMessage}`;
+      errorPayload.proxy_note = `Assigned key has been banned by OpenAI for policy violations. Please try again.`;
       break;
     case "billing_not_active":
       // Key valid but account billing is delinquent
       keyPool.disable(req.key!, "quota");
-      errorPayload.proxy_note = `Assigned key has been disabled due to delinquent billing. ${tryAgainMessage}`;
+      errorPayload.proxy_note = `Assigned key has been disabled due to delinquent billing. Please try again.`;
       break;
     case "requests":
     case "tokens":
@@ -565,7 +556,7 @@ async function handleOpenAIRateLimitError(
     //   keyPool.markRateLimited(req.key!);
     //   break;
     default:
-      errorPayload.proxy_note = `This is likely a temporary error with OpenAI. Try again in a few seconds.`;
+      errorPayload.proxy_note = `This is likely a temporary error with the API. Try again in a few seconds.`;
       break;
   }
   return errorPayload;
@@ -587,6 +578,42 @@ async function handleAzureRateLimitError(
   }
 }
 
+//{"error":{"code":400,"message":"API Key not found. Please pass a valid API key.","status":"INVALID_ARGUMENT","details":[{"@type":"type.googleapis.com/google.rpc.ErrorInfo","reason":"API_KEY_INVALID","domain":"googleapis.com","metadata":{"service":"generativelanguage.googleapis.com"}}]}}
+//{"error":{"code":400,"message":"Gemini API free tier is not available in your country. Please enable billing on your project in Google AI Studio.","status":"FAILED_PRECONDITION"}}
+async function handleGoogleAIBadRequestError(
+  req: Request,
+  errorPayload: ProxiedErrorPayload
+) {
+  const error = errorPayload.error || {};
+  const { message, status, details } = error;
+
+  if (status === "INVALID_ARGUMENT") {
+    const reason = details?.[0]?.reason;
+    if (reason === "API_KEY_INVALID") {
+      req.log.warn(
+        { key: req.key?.hash, status, reason, msg: error.message },
+        "Received `API_KEY_INVALID` error from Google AI. Check the configured API key."
+      );
+      keyPool.disable(req.key!, "revoked");
+      errorPayload.proxy_note = `Assigned API key is invalid.`;
+    }
+  } else if (status === "FAILED_PRECONDITION") {
+    if (message.match(/please enable billing/i)) {
+      req.log.warn(
+        { key: req.key?.hash, status, msg: error.message },
+        "Cannot use key due to billing restrictions."
+      );
+      keyPool.disable(req.key!, "revoked");
+      errorPayload.proxy_note = `Assigned API key cannot be used.`;
+    }
+  } else {
+    req.log.warn(
+      { key: req.key?.hash, status, msg: error.message },
+      "Received unexpected 400 error from Google AI."
+    );
+  }
+}
+
 //{"error":{"code":429,"message":"Resource has been exhausted (e.g. check quota).","status":"RESOURCE_EXHAUSTED"}
 async function handleGoogleAIRateLimitError(
   req: Request,
@@ -666,7 +693,7 @@ const countResponseTokens: ProxyResHandlerWithBody = async (
   }
 };
 
-const trackRateLimit: ProxyResHandlerWithBody = async (proxyRes, req) => {
+const trackKeyRateLimit: ProxyResHandlerWithBody = async (proxyRes, req) => {
   keyPool.updateRateLimits(req.key!, proxyRes.headers);
 };
 
@@ -690,6 +717,38 @@ const copyHttpHeaders: ProxyResHandlerWithBody = async (
   });
 };
 
+/**
+ * Injects metadata into the response, such as the tokenizer used, logging
+ * status, upstream API endpoint used, and whether the input prompt was modified
+ * or transformed.
+ * Only used for non-streaming requests.
+ */
+const injectProxyInfo: ProxyResHandlerWithBody = async (
+  _proxyRes,
+  req,
+  res,
+  body
+) => {
+  const { service, inboundApi, outboundApi, tokenizerInfo } = req;
+  const native = inboundApi === outboundApi;
+  const info: any = {
+    logged: config.promptLogging,
+    tokens: tokenizerInfo,
+    service,
+    in_api: inboundApi,
+    out_api: outboundApi,
+    prompt_transformed: !native,
+  };
+
+  if (req.query?.debug?.length) {
+    info.final_request_body = req.signedRequest?.body || req.body;
+  }
+
+  if (typeof body === "object") {
+    body.proxy = info;
+  }
+};
+
 function getAwsErrorType(header: string | string[] | undefined) {
   const val = String(header).match(/^(\w+):?/)?.[1];
   return val || String(header);

src/proxy/middleware/response/log-event.ts

@@ -0,0 +1,81 @@
+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

@@ -10,9 +10,12 @@ import {
 import { ProxyResHandlerWithBody } from ".";
 import { assertNever } from "../../../shared/utils";
 import {
+  AnthropicChatMessage,
+  flattenAnthropicMessages,
+  GoogleAIChatMessage,
   MistralAIChatMessage,
   OpenAIChatMessage,
-} from "../request/preprocessors/transform-outbound-payload";
+} from "../../../shared/api-schemas";
 
 /** If prompt logging is enabled, enqueues the prompt for logging. */
 export const logPrompt: ProxyResHandlerWithBody = async (
@@ -57,7 +60,13 @@ type OaiImageResult = {
 const getPromptForRequest = (
   req: Request,
   responseBody: Record<string, any>
-): string | OpenAIChatMessage[] | MistralAIChatMessage[] | OaiImageResult => {
+):
+  | string
+  | OpenAIChatMessage[]
+  | { contents: GoogleAIChatMessage[] }
+  | { system: string; messages: AnthropicChatMessage[] }
+  | MistralAIChatMessage[]
+  | OaiImageResult => {
   // Since the prompt logger only runs after the request has been proxied, we
   // can assume the body has already been transformed to the target API's
   // format.
@@ -65,7 +74,17 @@ const getPromptForRequest = (
     case "openai":
     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 };
     case "openai-text":
+    case "anthropic-text":
+    case "mistral-text":
       return req.body.prompt;
     case "openai-image":
       return {
@@ -75,21 +94,37 @@ const getPromptForRequest = (
         quality: req.body.quality,
         revisedPrompt: responseBody.data[0].revised_prompt,
       };
-    case "anthropic":
-      return req.body.prompt;
     case "google-ai":
-      return req.body.prompt.text;
+      return { contents: req.body.contents };
     default:
       assertNever(req.outboundApi);
   }
 };
 
 const flattenMessages = (
-  val: string | OpenAIChatMessage[] | MistralAIChatMessage[] | OaiImageResult
+  val:
+    | string
+    | OaiImageResult
+    | OpenAIChatMessage[]
+    | { contents: GoogleAIChatMessage[] }
+    | { system: string; messages: AnthropicChatMessage[] }
+    | MistralAIChatMessage[]
 ): 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.map((p) => p.text).join("\n");
+        return `${role}: ${text}`;
+      })
+      .join("\n");
+  }
   if (Array.isArray(val)) {
     return val
       .map(({ content, role }) => {
@@ -98,6 +133,8 @@ const flattenMessages = (
               .map((c) => {
                 if ("text" in c) return c.text;
                 if ("image_url" in c) return "(( Attached Image ))";
+                if ("source" in c) return "(( Attached Image ))";
+                return "(( Unsupported Content ))";
               })
               .join("\n")
           : content;
@@ -107,3 +144,20 @@ 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/save-image.ts

@@ -1,11 +1,14 @@
 import { ProxyResHandlerWithBody } from "./index";
-import { mirrorGeneratedImage, OpenAIImageGenerationResult } from "../../../shared/file-storage/mirror-generated-image";
+import {
+  mirrorGeneratedImage,
+  OpenAIImageGenerationResult,
+} from "../../../shared/file-storage/mirror-generated-image";
 
 export const saveImage: ProxyResHandlerWithBody = async (
   _proxyRes,
   req,
   _res,
-  body,
+  body
 ) => {
   if (req.outboundApi !== "openai-image") {
     return;
@@ -16,12 +19,15 @@ export const saveImage: ProxyResHandlerWithBody = async (
   }
 
   if (body.data) {
-    const baseUrl = req.protocol + "://" + req.get("host");
     const prompt = body.data[0].revised_prompt ?? req.body.prompt;
-    await mirrorGeneratedImage(
-      baseUrl,
+    const res = await mirrorGeneratedImage(
+      req,
       prompt,
       body as OpenAIImageGenerationResult
     );
+    req.log.info(
+      { urls: res.data.map((item) => item.url) },
+      "Saved generated image to user_content"
+    );
   }
 };

src/proxy/middleware/response/streaming/aggregators/anthropic-chat.ts

@@ -0,0 +1,49 @@
+import { OpenAIChatCompletionStreamEvent } from "../index";
+
+export type AnthropicChatCompletionResponse = {
+  id: string;
+  type: "message";
+  role: "assistant";
+  content: { type: "text"; text: string }[];
+  model: string;
+  stop_reason: string | null;
+  stop_sequence: string | null;
+  usage: { input_tokens: number; output_tokens: number };
+};
+
+/**
+ * Given a list of OpenAI chat completion events, compiles them into a single
+ * finalized Anthropic chat completion response so that non-streaming middleware
+ * can operate on it as if it were a blocking response.
+ */
+export function mergeEventsForAnthropicChat(
+  events: OpenAIChatCompletionStreamEvent[]
+): AnthropicChatCompletionResponse {
+  let merged: AnthropicChatCompletionResponse = {
+    id: "",
+    type: "message",
+    role: "assistant",
+    content: [],
+    model: "",
+    stop_reason: null,
+    stop_sequence: null,
+    usage: { input_tokens: 0, output_tokens: 0 },
+  };
+  merged = events.reduce((acc, event, i) => {
+    // The first event will only contain role assignment and response metadata
+    if (i === 0) {
+      acc.id = event.id;
+      acc.model = event.model;
+      acc.content = [{ type: "text", text: "" }];
+      return acc;
+    }
+
+    acc.stop_reason = event.choices[0].finish_reason ?? "";
+    if (event.choices[0].delta.content) {
+      acc.content[0].text += event.choices[0].delta.content;
+    }
+
+    return acc;
+  }, merged);
+  return merged;
+}

src/proxy/middleware/response/streaming/aggregators/anthropic-text.ts

@@ -1,6 +1,6 @@
 import { OpenAIChatCompletionStreamEvent } from "../index";
 
-export type AnthropicCompletionResponse = {
+export type AnthropicTextCompletionResponse = {
   completion: string;
   stop_reason: string;
   truncated: boolean;
@@ -15,10 +15,10 @@ export type AnthropicCompletionResponse = {
  * finalized Anthropic completion response so that non-streaming middleware
  * can operate on it as if it were a blocking response.
  */
-export function mergeEventsForAnthropic(
+export function mergeEventsForAnthropicText(
   events: OpenAIChatCompletionStreamEvent[]
-): AnthropicCompletionResponse {
-  let merged: AnthropicCompletionResponse = {
+): AnthropicTextCompletionResponse {
+  let merged: AnthropicTextCompletionResponse = {
     log_id: "",
     exception: null,
     model: "",

src/proxy/middleware/response/streaming/aggregators/mistral-chat.ts

@@ -0,0 +1,39 @@
+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

@@ -0,0 +1,33 @@
+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

@@ -0,0 +1,93 @@
+import pino from "pino";
+import { Duplex, Readable } from "stream";
+import { EventStreamMarshaller } from "@smithy/eventstream-serde-node";
+import { fromUtf8, toUtf8 } from "@smithy/util-utf8";
+import { Message } from "@smithy/eventstream-codec";
+
+/**
+ * Decodes a Readable stream, such as a proxied HTTP response, into a stream of
+ * Message objects using the AWS SDK's EventStreamMarshaller. Error events in
+ * the amazon eventstream protocol are decoded as Message objects and will not
+ * emit an error event on the decoder stream.
+ */
+export function getAwsEventStreamDecoder(params: {
+  input: Readable;
+  logger: pino.Logger;
+}): Duplex {
+  const { input, logger } = params;
+  const config = { utf8Encoder: toUtf8, utf8Decoder: fromUtf8 };
+  const eventStream = new EventStreamMarshaller(config).deserialize(
+    input,
+    async (input: Record<string, Message>) => {
+      const eventType = Object.keys(input)[0];
+      let result;
+      if (eventType === "chunk") {
+        result = input[eventType];
+      } else {
+        // AWS unmarshaller treats non-chunk events (errors and exceptions) oddly.
+        result = { [eventType]: input[eventType] } as any;
+      }
+      return result;
+    }
+  );
+  return new AWSEventStreamDecoder(eventStream, { logger });
+}
+
+class AWSEventStreamDecoder extends Duplex {
+  private readonly asyncIterable: AsyncIterable<Message>;
+  private iterator: AsyncIterator<Message>;
+  private reading: boolean;
+  private logger: pino.Logger;
+
+  constructor(
+    asyncIterable: AsyncIterable<Message>,
+    options: { logger: pino.Logger }
+  ) {
+    super({ ...options, objectMode: true });
+    this.asyncIterable = asyncIterable;
+    this.iterator = this.asyncIterable[Symbol.asyncIterator]();
+    this.reading = false;
+    this.logger = options.logger.child({ module: "aws-eventstream-decoder" });
+  }
+
+  async _read(_size: number) {
+    if (this.reading) return;
+    this.reading = true;
+
+    try {
+      while (true) {
+        const { value, done } = await this.iterator.next();
+        if (done) {
+          this.push(null);
+          break;
+        }
+        if (!this.push(value)) break;
+      }
+    } catch (err) {
+      // AWS SDK's EventStreamMarshaller emits errors in the stream itself as
+      // whatever our deserializer returns, which will not be Error objects
+      // because we want to pass the Message to the next stream for processing.
+      // Any actual Error thrown here is some failure during deserialization.
+      const isAwsError = !(err instanceof Error);
+
+      if (isAwsError) {
+        this.logger.warn({ err: err.headers }, "Received AWS error event");
+        this.push(err);
+        this.push(null);
+      } else {
+        this.logger.error(err, "Error during AWS stream deserialization");
+        this.destroy(err);
+      }
+    } finally {
+      this.reading = false;
+    }
+  }
+
+  _write(_chunk: any, _encoding: string, callback: () => void) {
+    callback();
+  }
+
+  _final(callback: () => void) {
+    callback();
+  }
+}

src/proxy/middleware/response/streaming/event-aggregator.ts

@@ -1,10 +1,19 @@
+import express from "express";
 import { APIFormat } from "../../../../shared/key-management";
 import { assertNever } from "../../../../shared/utils";
 import {
-  mergeEventsForAnthropic,
+  anthropicV2ToOpenAI,
+  mergeEventsForAnthropicChat,
+  mergeEventsForAnthropicText,
   mergeEventsForOpenAIChat,
   mergeEventsForOpenAIText,
+  mergeEventsForMistralChat,
+  mergeEventsForMistralText,
+  AnthropicV2StreamEvent,
   OpenAIChatCompletionStreamEvent,
+  mistralAIToOpenAI,
+  MistralAIStreamEvent,
+  MistralChatCompletionEvent,
 } from "./index";
 
 /**
@@ -12,32 +21,111 @@ import {
  * compiles them into a single finalized response for downstream middleware.
  */
 export class EventAggregator {
-  private readonly format: APIFormat;
+  private readonly model: string;
+  private readonly requestFormat: APIFormat;
+  private readonly responseFormat: APIFormat;
   private readonly events: OpenAIChatCompletionStreamEvent[];
 
-  constructor({ format }: { format: APIFormat }) {
+  constructor({ body, inboundApi, outboundApi }: express.Request) {
     this.events = [];
-    this.format = format;
+    this.requestFormat = inboundApi;
+    this.responseFormat = outboundApi;
+    this.model = body.model;
   }
 
-  addEvent(event: OpenAIChatCompletionStreamEvent) {
-    this.events.push(event);
+  addEvent(
+    event:
+      | OpenAIChatCompletionStreamEvent
+      | AnthropicV2StreamEvent
+      | MistralAIStreamEvent
+  ) {
+    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);
+      }
+    }
   }
 
   getFinalResponse() {
-    switch (this.format) {
+    switch (this.responseFormat) {
       case "openai":
-      case "google-ai":
-      case "mistral-ai":
+      case "google-ai": // TODO: this is probably wrong now that we support native Google Makersuite prompts
         return mergeEventsForOpenAIChat(this.events);
       case "openai-text":
         return mergeEventsForOpenAIText(this.events);
-      case "anthropic":
-        return mergeEventsForAnthropic(this.events);
+      case "anthropic-text":
+        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.format}`);
+        throw new Error(
+          `SSE aggregation not supported for ${this.responseFormat}`
+        );
       default:
-        assertNever(this.format);
+        assertNever(this.responseFormat);
     }
   }
+
+  hasEvents() {
+    return this.events.length > 0;
+  }
+}
+
+function eventIsOpenAIEvent(
+  event: any
+): 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

@@ -1,9 +1,36 @@
-export type SSEResponseTransformArgs = {
+export type SSEResponseTransformArgs<S = Record<string, any>> = {
   data: string;
   lastPosition: number;
   index: number;
   fallbackId: string;
   fallbackModel: string;
+  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;
+  completion: string;
+  stop_reason: string | null;
 };
 
 export type OpenAIChatCompletionStreamEvent = {
@@ -16,17 +43,29 @@ export type OpenAIChatCompletionStreamEvent = {
     delta: { role?: string; content?: string };
     finish_reason: string | null;
   }[];
-}
+};
 
-export type StreamingCompletionTransformer = (
-  params: SSEResponseTransformArgs
-) => { position: number; event?: OpenAIChatCompletionStreamEvent };
+export type StreamingCompletionTransformer<
+  T = OpenAIChatCompletionStreamEvent,
+  S = any,
+> = (params: SSEResponseTransformArgs<S>) => {
+  position: number;
+  event?: T;
+  state?: S;
+};
 
 export { openAITextToOpenAIChat } from "./transformers/openai-text-to-openai";
 export { anthropicV1ToOpenAI } from "./transformers/anthropic-v1-to-openai";
 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 { mergeEventsForAnthropic } from "./aggregators/anthropic";
+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/parse-sse.ts

@@ -3,27 +3,27 @@ export type ServerSentEvent = { id?: string; type?: string; data: string };
 /** Given a string of SSE data, parse it into a `ServerSentEvent` object. */
 export function parseEvent(event: string) {
   const buffer: ServerSentEvent = { data: "" };
-  return event.split(/\r?\n/).reduce(parseLine, buffer)
+  return event.split(/\r?\n/).reduce(parseLine, buffer);
 }
 
 function parseLine(event: ServerSentEvent, line: string) {
   const separator = line.indexOf(":");
-  const field = separator === -1 ? line : line.slice(0,separator);
+  const field = separator === -1 ? line : line.slice(0, separator);
   const value = separator === -1 ? "" : line.slice(separator + 1);
 
   switch (field) {
-    case 'id':
-      event.id = value.trim()
-      break
-    case 'event':
-      event.type = value.trim()
-      break
-    case 'data':
-      event.data += value.trimStart()
-      break
+    case "id":
+      event.id = value.trim();
+      break;
+    case "event":
+      event.type = value.trim();
+      break;
+    case "data":
+      event.data += value.trimStart();
+      break;
     default:
-      break
+      break;
   }
 
-  return event
-}
+  return event;
+}

src/proxy/middleware/response/streaming/sse-message-transformer.ts

@@ -3,23 +3,28 @@ import { logger } from "../../../../logger";
 import { APIFormat } from "../../../../shared/key-management";
 import { assertNever } from "../../../../shared/utils";
 import {
+  anthropicChatToOpenAI,
+  anthropicChatToAnthropicV2,
   anthropicV1ToOpenAI,
+  AnthropicV2StreamEvent,
   anthropicV2ToOpenAI,
+  googleAIToOpenAI,
   OpenAIChatCompletionStreamEvent,
   openAITextToOpenAIChat,
-  googleAIToOpenAI,
+  mistralAIToOpenAI,
+  mistralTextToMistralChat,
   passthroughToOpenAI,
   StreamingCompletionTransformer,
+  MistralChatCompletionEvent,
 } from "./index";
 
-const genlog = logger.child({ module: "sse-transformer" });
-
 type SSEMessageTransformerOptions = TransformOptions & {
   requestedModel: string;
   requestId: string;
   inputFormat: APIFormat;
   inputApiVersion?: string;
-  logger?: typeof logger;
+  outputFormat?: APIFormat;
+  logger: typeof logger;
 };
 
 /**
@@ -28,21 +33,28 @@ type SSEMessageTransformerOptions = TransformOptions & {
  */
 export class SSEMessageTransformer extends Transform {
   private lastPosition: number;
+  private transformState: any;
   private msgCount: number;
   private readonly inputFormat: APIFormat;
-  private readonly transformFn: StreamingCompletionTransformer;
+  private readonly transformFn: StreamingCompletionTransformer<
+    // TODO: Refactor transformers to not assume only OpenAI events as output
+    | OpenAIChatCompletionStreamEvent
+    | AnthropicV2StreamEvent
+    | MistralChatCompletionEvent
+  >;
   private readonly log;
   private readonly fallbackId: string;
   private readonly fallbackModel: string;
 
   constructor(options: SSEMessageTransformerOptions) {
     super({ ...options, readableObjectMode: true });
-    this.log = options.logger?.child({ module: "sse-transformer" }) ?? genlog;
+    this.log = options.logger?.child({ module: "sse-transformer" });
     this.lastPosition = 0;
     this.msgCount = 0;
     this.transformFn = getTransformer(
       options.inputFormat,
-      options.inputApiVersion
+      options.inputApiVersion,
+      options.outputFormat
     );
     this.inputFormat = options.inputFormat;
     this.fallbackId = options.requestId;
@@ -60,15 +72,20 @@ export class SSEMessageTransformer extends Transform {
   _transform(chunk: Buffer, _encoding: BufferEncoding, callback: Function) {
     try {
       const originalMessage = chunk.toString();
-      const { event: transformedMessage, position: newPosition } =
-        this.transformFn({
-          data: originalMessage,
-          lastPosition: this.lastPosition,
-          index: this.msgCount++,
-          fallbackId: this.fallbackId,
-          fallbackModel: this.fallbackModel,
-        });
+      const {
+        event: transformedMessage,
+        position: newPosition,
+        state,
+      } = this.transformFn({
+        data: originalMessage,
+        lastPosition: this.lastPosition,
+        index: this.msgCount++,
+        fallbackId: this.fallbackId,
+        fallbackModel: this.fallbackModel,
+        state: this.transformState,
+      });
       this.lastPosition = newPosition;
+      this.transformState = state;
 
       // Special case for Azure OpenAI, which is 99% the same as OpenAI but
       // sometimes emits an extra event at the beginning of the stream with the
@@ -86,7 +103,7 @@ export class SSEMessageTransformer extends Transform {
       // Some events may not be transformed, e.g. ping events
       if (!transformedMessage) return callback();
 
-      if (this.msgCount === 1) {
+      if (this.msgCount === 1 && eventIsOpenAIEvent(transformedMessage)) {
         // TODO: does this need to be skipped for passthroughToOpenAI?
         this.push(createInitialMessage(transformedMessage));
       }
@@ -100,22 +117,45 @@ export class SSEMessageTransformer extends Transform {
   }
 }
 
+function eventIsOpenAIEvent(
+  event: any
+): event is OpenAIChatCompletionStreamEvent {
+  return event?.object === "chat.completion.chunk";
+}
+
 function getTransformer(
   responseApi: APIFormat,
-  version?: string
-): StreamingCompletionTransformer {
+  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.
+  requestApi: APIFormat = "openai"
+): StreamingCompletionTransformer<
+  | OpenAIChatCompletionStreamEvent
+  | AnthropicV2StreamEvent
+  | MistralChatCompletionEvent
+> {
   switch (responseApi) {
     case "openai":
-    case "mistral-ai":
       return passthroughToOpenAI;
     case "openai-text":
       return openAITextToOpenAIChat;
-    case "anthropic":
+    case "anthropic-text":
       return version === "2023-01-01"
         ? anthropicV1ToOpenAI
         : 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
+        : 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}`);
     default:

src/proxy/middleware/response/streaming/sse-stream-adapter.ts

@@ -1,140 +1,156 @@
+import pino from "pino";
 import { Transform, TransformOptions } from "stream";
-
-import { StringDecoder } from "string_decoder";
-// @ts-ignore
-import { Parser } from "lifion-aws-event-stream";
-import { logger } from "../../../../logger";
-import { RetryableError } from "../index";
+import { Message } from "@smithy/eventstream-codec";
 import { APIFormat } from "../../../../shared/key-management";
-import StreamArray from "stream-json/streamers/StreamArray";
-import { makeCompletionSSE } from "../../../../shared/streaming";
-
-const log = logger.child({ module: "sse-stream-adapter" });
+import { buildSpoofedSSE } from "../error-generator";
+import { BadRequestError, RetryableError } from "../../../../shared/errors";
 
 type SSEStreamAdapterOptions = TransformOptions & {
   contentType?: string;
   api: APIFormat;
-};
-type AwsEventStreamMessage = {
-  headers: {
-    ":message-type": "event" | "exception";
-    ":exception-type"?: string;
-  };
-  payload: { message?: string /** base64 encoded */; bytes?: string };
+  logger: pino.Logger;
 };
 
 /**
- * Receives either text chunks or AWS binary event stream chunks and emits
- * full SSE events.
+ * Receives a stream of events in a variety of formats and transforms them into
+ * Server-Sent Events.
+ *
+ * This is an object-mode stream, so it expects to receive objects and will emit
+ * strings.
  */
 export class SSEStreamAdapter extends Transform {
   private readonly isAwsStream;
   private readonly isGoogleStream;
-  private awsParser = new Parser();
-  private jsonParser = StreamArray.withParser();
+  private api: APIFormat;
   private partialMessage = "";
-  private decoder = new StringDecoder("utf8");
+  private textDecoder = new TextDecoder("utf8");
+  private log: pino.Logger;
 
-  constructor(options?: SSEStreamAdapterOptions) {
-    super(options);
+  constructor(options: SSEStreamAdapterOptions) {
+    super({ ...options, objectMode: true });
     this.isAwsStream =
       options?.contentType === "application/vnd.amazon.eventstream";
     this.isGoogleStream = options?.api === "google-ai";
-
-    this.awsParser.on("data", (data: AwsEventStreamMessage) => {
-      const message = this.processAwsEvent(data);
-      if (message) {
-        this.push(Buffer.from(message + "\n\n"), "utf8");
-      }
-    });
-
-    this.jsonParser.on("data", (data: { value: any }) => {
-      const message = this.processGoogleValue(data.value);
-      if (message) {
-        this.push(Buffer.from(message + "\n\n"), "utf8");
-      }
-    });
+    this.api = options.api;
+    this.log = options.logger.child({ module: "sse-stream-adapter" });
   }
 
-  protected processAwsEvent(event: AwsEventStreamMessage): string | null {
-    const { payload, headers } = event;
-    if (headers[":message-type"] === "exception" || !payload.bytes) {
-      const eventStr = JSON.stringify(event);
-      // Under high load, AWS can rugpull us by returning a 200 and starting the
-      // stream but then immediately sending a rate limit error as the first
-      // event. My guess is some race condition in their rate limiting check
-      // that occurs if two requests arrive at the same time when only one
-      // concurrency slot is available.
-      if (headers[":exception-type"] === "throttlingException") {
-        log.warn(
-          { event: eventStr },
-          "AWS request throttled after streaming has already started; retrying"
-        );
-        throw new RetryableError("AWS request throttled mid-stream");
-      } else {
-        log.error({ event: eventStr }, "Received bad AWS stream event");
-        return makeCompletionSSE({
-          format: "anthropic",
-          title: "Proxy stream error",
-          message:
-            "The proxy received malformed or unexpected data from AWS while streaming.",
-          obj: event,
-          reqId: "proxy-sse-adapter-message",
-          model: "",
-        });
-      }
-    } else {
-      const { bytes } = payload;
-      // technically this is a transformation but we don't really distinguish
-      // between aws claude and anthropic claude at the APIFormat level, so
-      // these will short circuit the message transformer
-      return [
-        "event: completion",
-        `data: ${Buffer.from(bytes, "base64").toString("utf8")}`,
-      ].join("\n");
+  protected processAwsMessage(message: Message): string | null {
+    // Per amazon, headers and body are always present. headers is an object,
+    // body is a Uint8Array, potentially zero-length.
+    const { headers, body } = message;
+    const eventType = headers[":event-type"]?.value;
+    const messageType = headers[":message-type"]?.value;
+    const contentType = headers[":content-type"]?.value;
+    const exceptionType = headers[":exception-type"]?.value;
+    const errorCode = headers[":error-code"]?.value;
+    const bodyStr = this.textDecoder.decode(body);
+
+    switch (messageType) {
+      case "event":
+        if (contentType === "application/json" && eventType === "chunk") {
+          const { bytes } = JSON.parse(bodyStr);
+          const event = Buffer.from(bytes, "base64").toString("utf8");
+          const eventObj = JSON.parse(event);
+
+          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}`;
+          }
+        }
+      // noinspection FallThroughInSwitchStatementJS -- non-JSON data is unexpected
+      case "exception":
+      case "error":
+        const type = String(
+          exceptionType || errorCode || "UnknownError"
+        ).toLowerCase();
+        switch (type) {
+          case "throttlingexception":
+            this.log.warn(
+              "AWS request throttled after streaming has already started; retrying"
+            );
+            throw new RetryableError("AWS request throttled mid-stream");
+          case "validationexception":
+            try {
+              const { message } = JSON.parse(bodyStr);
+              this.log.error({ message }, "Received AWS validation error");
+              this.emit(
+                "error",
+                new BadRequestError(`AWS validation error: ${message}`)
+              );
+              return null;
+            } catch (error) {
+              this.log.error(
+                { body: bodyStr, error },
+                "Could not parse AWS validation error"
+              );
+            }
+          // noinspection FallThroughInSwitchStatementJS -- who knows what this is
+          default:
+            let text;
+            try {
+              text = JSON.parse(bodyStr).message;
+            } catch (error) {
+              text = bodyStr;
+            }
+            const error: any = new Error(
+              `Got mysterious error chunk: [${type}] ${text}`
+            );
+            error.lastEvent = text;
+            this.emit("error", error);
+            return null;
+        }
+      default:
+        // Amazon says this can't ever happen...
+        this.log.error({ message }, "Received very bad AWS stream event");
+        return null;
     }
   }
 
-  // Google doesn't use event streams and just sends elements in an array over
-  // a long-lived HTTP connection. Needs stream-json to parse the array.
-  protected processGoogleValue(value: any): string | null {
+  /** 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 candidates = value.candidates ?? [{}];
       const hasParts = candidates[0].content?.parts?.length > 0;
       if (hasParts) {
-        return `data: ${JSON.stringify(value)}`;
+        return `data: ${JSON.stringify(data.value ?? data)}`;
       } else {
-        log.error({ event: value }, "Received bad Google AI event");
-        return `data: ${makeCompletionSSE({
+        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: value,
+          obj: data,
           reqId: "proxy-sse-adapter-message",
           model: "",
         })}`;
       }
     } catch (error) {
-      error.lastEvent = value;
+      error.lastEvent = data;
       this.emit("error", error);
-      return null;
     }
+    return null;
   }
 
-  _transform(chunk: Buffer, _encoding: BufferEncoding, callback: Function) {
+  _transform(data: any, _enc: string, callback: (err?: Error | null) => void) {
     try {
       if (this.isAwsStream) {
-        this.awsParser.write(chunk);
+        // `data` is a Message object
+        const message = this.processAwsMessage(data);
+        if (message) this.push(message + "\n\n");
       } else if (this.isGoogleStream) {
-        this.jsonParser.write(chunk);
+        // `data` is an element from the Google AI JSON stream
+        const message = this.processGoogleObject(data);
+        if (message) this.push(message + "\n\n");
       } else {
-        // We may receive multiple (or partial) SSE messages in a single chunk,
-        // so we need to buffer and emit separate stream events for full
-        // messages so we can parse/transform them properly.
-        const str = this.decoder.write(chunk);
-
-        const fullMessages = (this.partialMessage + str).split(
+        // `data` is a string, but possibly only a partial message
+        const fullMessages = (this.partialMessage + data).split(
           /\r\r|\n\n|\r\n\r\n/
         );
         this.partialMessage = fullMessages.pop() || "";
@@ -148,9 +164,12 @@ export class SSEStreamAdapter extends Transform {
       }
       callback();
     } catch (error) {
-      error.lastEvent = chunk?.toString();
-      this.emit("error", error);
+      error.lastEvent = data?.toString() ?? "[SSEStreamAdapter] no data";
       callback(error);
     }
   }
+
+  _flush(callback: (err?: Error | null) => void) {
+    callback();
+  }
 }

src/proxy/middleware/response/streaming/transformers/anthropic-chat-to-anthropic-v2.ts

@@ -0,0 +1,129 @@
+import {
+  AnthropicV2StreamEvent,
+  StreamingCompletionTransformer,
+} from "../index";
+import { parseEvent, ServerSentEvent } from "../parse-sse";
+import { logger } from "../../../../../logger";
+
+const log = logger.child({
+  module: "sse-transformer",
+  transformer: "anthropic-chat-to-anthropic-v2",
+});
+
+export type AnthropicChatEventType =
+  | "message_start"
+  | "content_block_start"
+  | "content_block_delta"
+  | "content_block_stop"
+  | "message_delta"
+  | "message_stop";
+
+type AnthropicChatStartEvent = {
+  type: "message_start";
+  message: {
+    id: string;
+    type: "message";
+    role: "assistant";
+    content: [];
+    model: string;
+    stop_reason: null;
+    stop_sequence: null;
+    usage: { input_tokens: number; output_tokens: number };
+  };
+};
+
+type AnthropicChatContentBlockStartEvent = {
+  type: "content_block_start";
+  index: number;
+  content_block: { type: "text"; text: string };
+};
+
+export type AnthropicChatContentBlockDeltaEvent = {
+  type: "content_block_delta";
+  index: number;
+  delta: { type: "text_delta"; text: string };
+};
+
+type AnthropicChatContentBlockStopEvent = {
+  type: "content_block_stop";
+  index: number;
+};
+
+type AnthropicChatMessageDeltaEvent = {
+  type: "message_delta";
+  delta: {
+    stop_reason: string;
+    stop_sequence: null;
+    usage: { output_tokens: number };
+  };
+};
+
+type AnthropicChatMessageStopEvent = {
+  type: "message_stop";
+};
+
+type AnthropicChatTransformerState = { content: string };
+
+/**
+ * Transforms an incoming Anthropic Chat SSE to an equivalent Anthropic V2
+ * Text SSE.
+ * For now we assume there is only one content block and message delta. In the
+ * future Anthropic may add multi-turn responses or multiple content blocks
+ * (probably for multimodal responses, image generation, etc) but as far as I
+ * can tell this is not yet implemented.
+ */
+export const anthropicChatToAnthropicV2: StreamingCompletionTransformer<
+  AnthropicV2StreamEvent,
+  AnthropicChatTransformerState
+> = (params) => {
+  const { data } = params;
+
+  const rawEvent = parseEvent(data);
+  if (!rawEvent.data || !rawEvent.type) {
+    return { position: -1 };
+  }
+
+  const deltaEvent = asAnthropicChatDelta(rawEvent);
+  if (!deltaEvent) {
+    return { position: -1 };
+  }
+
+  const newEvent = {
+    log_id: params.fallbackId,
+    model: params.fallbackModel,
+    completion: deltaEvent.delta.text,
+    stop_reason: null,
+  };
+
+  return { position: -1, event: newEvent };
+};
+
+export function asAnthropicChatDelta(
+  event: ServerSentEvent
+): AnthropicChatContentBlockDeltaEvent | null {
+  if (
+    !event.type ||
+    !["content_block_start", "content_block_delta"].includes(event.type)
+  ) {
+    return null;
+  }
+
+  try {
+    const parsed = JSON.parse(event.data);
+    if (parsed.type === "content_block_delta") {
+      return parsed;
+    } else if (parsed.type === "content_block_start") {
+      return {
+        type: "content_block_delta",
+        index: parsed.index,
+        delta: { type: "text_delta", text: parsed.content_block?.text ?? "" },
+      };
+    } else {
+      // noinspection ExceptionCaughtLocallyJS
+      throw new Error("Invalid event type");
+    }
+  } catch (error) {
+    log.warn({ error: error.stack, event }, "Received invalid event");
+  }
+  return null;
+}

src/proxy/middleware/response/streaming/transformers/anthropic-chat-to-openai.ts

@@ -0,0 +1,45 @@
+import { StreamingCompletionTransformer } from "../index";
+import { parseEvent } from "../parse-sse";
+import { logger } from "../../../../../logger";
+import { asAnthropicChatDelta } from "./anthropic-chat-to-anthropic-v2";
+
+const log = logger.child({
+  module: "sse-transformer",
+  transformer: "anthropic-chat-to-openai",
+});
+
+/**
+ * Transforms an incoming Anthropic Chat SSE to an equivalent OpenAI
+ * chat.completion.chunks SSE.
+ */
+export const anthropicChatToOpenAI: StreamingCompletionTransformer = (
+  params
+) => {
+  const { data } = params;
+
+  const rawEvent = parseEvent(data);
+  if (!rawEvent.data || !rawEvent.type) {
+    return { position: -1 };
+  }
+
+  const deltaEvent = asAnthropicChatDelta(rawEvent);
+  if (!deltaEvent) {
+    return { position: -1 };
+  }
+
+  const newEvent = {
+    id: params.fallbackId,
+    object: "chat.completion.chunk" as const,
+    created: Date.now(),
+    model: params.fallbackModel,
+    choices: [
+      {
+        index: 0,
+        delta: { content: deltaEvent.delta.text },
+        finish_reason: null,
+      },
+    ],
+  };
+
+  return { position: -1, event: newEvent };
+};

src/proxy/middleware/response/streaming/transformers/anthropic-v2-to-openai.ts

@@ -1,4 +1,7 @@
-import { StreamingCompletionTransformer } from "../index";
+import {
+  AnthropicV2StreamEvent,
+  StreamingCompletionTransformer,
+} from "../index";
 import { parseEvent, ServerSentEvent } from "../parse-sse";
 import { logger } from "../../../../../logger";
 
@@ -7,13 +10,6 @@ const log = logger.child({
   transformer: "anthropic-v2-to-openai",
 });
 
-type AnthropicV2StreamEvent = {
-  log_id?: string;
-  model?: string;
-  completion: string;
-  stop_reason: string;
-};
-
 /**
  * Transforms an incoming Anthropic SSE (2023-06-01 API) to an equivalent
  * OpenAI chat.completion.chunk SSE.

src/proxy/middleware/response/streaming/transformers/mistral-ai-to-openai.ts

@@ -0,0 +1,76 @@
+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

@@ -0,0 +1,63 @@
+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

@@ -1,4 +1,4 @@
-import { RequestHandler, Router } from "express";
+import express, { Request, RequestHandler, Router } from "express";
 import { createProxyMiddleware } from "http-proxy-middleware";
 import { config } from "../config";
 import { keyPool } from "../shared/key-management";
@@ -21,12 +21,48 @@ import {
   createOnProxyResHandler,
   ProxyResHandlerWithBody,
 } from "./middleware/response";
+import { BadRequestError } from "../shared/errors";
 
+// 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 = [
+  /*
+  Mistral Nemo
+  "A 12B model built with the partnership with Nvidia.  It is easy to use and a
+  drop-in replacement in any system using Mistral 7B that it supersedes."
+  */
+  "open-mistral-nemo",
+  "open-mistral-nemo-2407",
+  /*
+  Mistral Large
+  "Our flagship model with state-of-the-art reasoning, knowledge, and coding
+  capabilities."
+  */
+  "mistral-large-latest",
+  "mistral-large-2407",
+  "mistral-large-2402", // deprecated
+  /*
+  Codestral
+  "A cutting-edge generative model that has been specifically designed and
+  optimized for code generation tasks, including fill-in-the-middle and code
+  completion."
+  note: this uses a separate bidi completion endpoint that is not implemented
+  */
+  "codestral-latest",
+  "codestral-2405",
+  /* So-called "Research Models" */
+  "open-mistral-7b",
+  "open-mixtral-8x7b",
+  "open-mistral-8x22b",
+  "open-codestral-mamba",
+  /* Deprecated production models */
+  "mistral-small-latest",
+  "mistral-small-2402",
+  "mistral-medium-latest",
+  "mistral-medium-2312",
   "mistral-tiny",
-  "mistral-small",
-  "mistral-medium",
+  "mistral-tiny-2312",
 ];
 
 let modelsCache: any = null;
@@ -54,7 +90,9 @@ export function generateModelList(models = KNOWN_MISTRAL_AI_MODELS) {
 }
 
 const handleModelRequest: RequestHandler = (_req, res) => {
-  if (new Date().getTime() - modelsCacheTime < 1000 * 60) return modelsCache;
+  if (new Date().getTime() - modelsCacheTime < 1000 * 60) {
+    return res.status(200).json(modelsCache);
+  }
   const result = generateModelList();
   modelsCache = { object: "list", data: result };
   modelsCacheTime = new Date().getTime();
@@ -71,18 +109,24 @@ const mistralAIResponseHandler: ProxyResHandlerWithBody = async (
     throw new Error("Expected body to be an object");
   }
 
-  if (config.promptLogging) {
-    const host = req.get("host");
-    body.proxy_note = `Prompts are logged on this proxy instance. See ${host} for more information.`;
+  let newBody = body;
+  if (req.inboundApi === "mistral-text" && req.outboundApi === "mistral-ai") {
+    newBody = transformMistralTextToMistralChat(body);
   }
 
-  if (req.tokenizerInfo) {
-    body.proxy_tokenizer = req.tokenizerInfo;
-  }
-
-  res.status(200).json(body);
+  res.status(200).json({ ...newBody, proxy: body.proxy });
 };
 
+export function transformMistralTextToMistralChat(textBody: any) {
+  return {
+    ...textBody,
+    choices: [
+      { message: { content: textBody.outputs[0].text, role: "assistant" } },
+    ],
+    outputs: undefined,
+  };
+}
+
 const mistralAIProxy = createQueueMiddleware({
   proxyMiddleware: createProxyMiddleware({
     target: "https://api.mistral.ai",
@@ -105,12 +149,37 @@ mistralAIRouter.get("/v1/models", handleModelRequest);
 mistralAIRouter.post(
   "/v1/chat/completions",
   ipLimiter,
-  createPreprocessorMiddleware({
-    inApi: "mistral-ai",
-    outApi: "mistral-ai",
-    service: "mistral-ai",
-  }),
+  createPreprocessorMiddleware(
+    {
+      inApi: "mistral-ai",
+      outApi: "mistral-ai",
+      service: "mistral-ai",
+    },
+    { beforeTransform: [detectMistralInputApi] }
+  ),
   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/openai-image.ts

@@ -16,16 +16,16 @@ import {
   ProxyResHandlerWithBody,
 } from "./middleware/response";
 import { generateModelList } from "./openai";
-import {
-  OpenAIImageGenerationResult,
-} from "../shared/file-storage/mirror-generated-image";
+import { OpenAIImageGenerationResult } from "../shared/file-storage/mirror-generated-image";
 
 const KNOWN_MODELS = ["dall-e-2", "dall-e-3"];
 
 let modelListCache: any = null;
 let modelListValid = 0;
 const handleModelRequest: RequestHandler = (_req, res) => {
-  if (new Date().getTime() - modelListValid < 1000 * 60) return modelListCache;
+  if (new Date().getTime() - modelListValid < 1000 * 60) {
+    return res.status(200).json(modelListCache);
+  }
   const result = generateModelList(KNOWN_MODELS);
   modelListCache = { object: "list", data: result };
   modelListValid = new Date().getTime();
@@ -42,21 +42,16 @@ const openaiImagesResponseHandler: ProxyResHandlerWithBody = async (
     throw new Error("Expected body to be an object");
   }
 
-  if (config.promptLogging) {
-    const host = req.get("host");
-    body.proxy_note = `Prompts are logged on this proxy instance. See ${host} for more information.`;
-  }
-
+  let newBody = body;
   if (req.inboundApi === "openai") {
     req.log.info("Transforming OpenAI image response to OpenAI chat format");
-    body = transformResponseForChat(body as OpenAIImageGenerationResult, req);
+    newBody = transformResponseForChat(
+      body as OpenAIImageGenerationResult,
+      req
+    );
   }
 
-  if (req.tokenizerInfo) {
-    body.proxy_tokenizer = req.tokenizerInfo;
-  }
-
-  res.status(200).json(body);
+  res.status(200).json({ ...newBody, proxy: body.proxy });
 };
 
 /**

src/proxy/openai.ts

@@ -1,7 +1,7 @@
 import { RequestHandler, Router } from "express";
 import { createProxyMiddleware } from "http-proxy-middleware";
 import { config } from "../config";
-import { keyPool } from "../shared/key-management";
+import { keyPool, OpenAIKey } from "../shared/key-management";
 import {
   getOpenAIModelFamily,
   ModelFamily,
@@ -28,37 +28,65 @@ import {
 
 // https://platform.openai.com/docs/models/overview
 export const KNOWN_OPENAI_MODELS = [
-  "gpt-4-1106-preview",
-  "gpt-4-vision-preview",
+  // GPT4o
+  "gpt-4o",
+  "gpt-4o-2024-05-13",
+  "gpt-4o-2024-08-06",
+  // GPT4o Mini
+  "gpt-4o-mini",
+  "gpt-4o-mini-2024-07-18",
+  // GPT4o (ChatGPT)
+  "chatgpt-4o-latest",
+  // GPT4 Turbo (superceded by GPT4o)
+  "gpt-4-turbo",
+  "gpt-4-turbo-2024-04-09", // gpt4-turbo stable, with vision
+  "gpt-4-turbo-preview", // alias for latest turbo preview
+  "gpt-4-0125-preview", // gpt4-turbo preview 2
+  "gpt-4-1106-preview", // gpt4-turbo preview 1
+  // Launch GPT4
   "gpt-4",
   "gpt-4-0613",
-  "gpt-4-0314", // EOL 2024-06-13
-  "gpt-4-32k",
-  "gpt-4-32k-0613",
-  "gpt-4-32k-0314", // EOL 2024-06-13
+  "gpt-4-0314", // legacy
+  // GPT3.5 Turbo (superceded by GPT4o Mini)
   "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-0125", // latest turbo
+  "gpt-3.5-turbo-1106", // older turbo
+  // Text Completion
   "gpt-3.5-turbo-instruct",
   "gpt-3.5-turbo-instruct-0914",
+  // Embeddings
   "text-embedding-ada-002",
+  // Known deprecated models
+  "gpt-4-32k", // alias for 0613
+  "gpt-4-32k-0314", // EOL 2025-06-06
+  "gpt-4-32k-0613", // EOL 2025-06-06
+  "gpt-4-vision-preview", // EOL 2024-12-06
+  "gpt-4-1106-vision-preview", // EOL 2024-12-06
+  "gpt-3.5-turbo-0613", // EOL 2024-09-13
+  "gpt-3.5-turbo-0301", // not on the website anymore, maybe unavailable
+  "gpt-3.5-turbo-16k", // alias for 0613
+  "gpt-3.5-turbo-16k-0613", // EOL 2024-09-13
 ];
 
 let modelsCache: any = null;
 let modelsCacheTime = 0;
 
 export function generateModelList(models = KNOWN_OPENAI_MODELS) {
-  let available = new Set<OpenAIModelFamily>();
+  // 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;
-    key.modelFamilies.forEach((family) =>
-      available.add(family as OpenAIModelFamily)
-    );
+    const asOpenAIKey = key as OpenAIKey;
+    asOpenAIKey.modelFamilies.forEach((f) => availableFamilies.add(f));
+    asOpenAIKey.modelSnapshots.forEach((s) => availableSnapshots.add(s));
   }
+
+  // Remove disabled families
   const allowed = new Set<ModelFamily>(config.allowedModelFamilies);
-  available = new Set([...available].filter((x) => allowed.has(x)));
+  availableFamilies = new Set(
+    [...availableFamilies].filter((x) => allowed.has(x))
+  );
 
   return models
     .map((id) => ({
@@ -79,11 +107,22 @@ export function generateModelList(models = KNOWN_OPENAI_MODELS) {
       root: id,
       parent: null,
     }))
-    .filter((model) => available.has(getOpenAIModelFamily(model.id)));
+    .filter((model) => {
+      // First check if the family is available
+      const hasFamily = availableFamilies.has(getOpenAIModelFamily(model.id));
+      if (!hasFamily) return false;
+
+      // 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 modelsCache;
+  if (new Date().getTime() - modelsCacheTime < 1000 * 60) {
+    return res.status(200).json(modelsCache);
+  }
   const result = generateModelList();
   modelsCache = { object: "list", data: result };
   modelsCacheTime = new Date().getTime();
@@ -119,21 +158,13 @@ const openaiResponseHandler: ProxyResHandlerWithBody = async (
     throw new Error("Expected body to be an object");
   }
 
-  if (config.promptLogging) {
-    const host = req.get("host");
-    body.proxy_note = `Prompts are logged on this proxy instance. See ${host} for more information.`;
-  }
-
+  let newBody = body;
   if (req.outboundApi === "openai-text" && req.inboundApi === "openai") {
     req.log.info("Transforming Turbo-Instruct response to Chat format");
-    body = transformTurboInstructResponse(body);
+    newBody = transformTurboInstructResponse(body);
   }
 
-  if (req.tokenizerInfo) {
-    body.proxy_tokenizer = req.tokenizerInfo;
-  }
-
-  res.status(200).json(body);
+  res.status(200).json({ ...newBody, proxy: body.proxy });
 };
 
 /** Only used for non-streaming responses. */
@@ -161,9 +192,7 @@ const openaiProxy = createQueueMiddleware({
     selfHandleResponse: true,
     logger,
     on: {
-      proxyReq: createOnProxyReqHandler({
-        pipeline: [addKey, finalizeBody],
-      }),
+      proxyReq: createOnProxyReqHandler({ pipeline: [addKey, finalizeBody] }),
       proxyRes: createOnProxyResHandler([openaiResponseHandler]),
       error: handleProxyError,
     },

src/proxy/queue.ts

@@ -12,26 +12,30 @@
  */
 
 import crypto from "crypto";
-import type { Handler, Request } from "express";
+import { Handler, Request } from "express";
+import { BadRequestError, TooManyRequestsError } from "../shared/errors";
 import { keyPool } from "../shared/key-management";
 import {
   getModelFamilyForRequest,
   MODEL_FAMILIES,
   ModelFamily,
 } from "../shared/models";
-import { makeCompletionSSE, initializeSseStream } from "../shared/streaming";
+import { initializeSseStream } from "../shared/streaming";
 import { logger } from "../logger";
-import { getUniqueIps, SHARED_IP_ADDRESSES } from "./rate-limit";
+import { getUniqueIps } from "./rate-limit";
 import { RequestPreprocessor } from "./middleware/request";
 import { handleProxyError } from "./middleware/common";
+import { sendErrorToClient } from "./middleware/response/error-generator";
 
 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 = 1;
+const USER_CONCURRENCY_LIMIT = parseInt(
+  process.env.USER_CONCURRENCY_LIMIT ?? "1"
+);
+/** Maximum number of queue slots for Agnai.chat requests. */
+const AGNAI_CONCURRENCY_LIMIT = USER_CONCURRENCY_LIMIT * 5;
 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");
@@ -56,35 +60,20 @@ 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);
 
-const isFromSharedIp = (req: Request) => SHARED_IP_ADDRESSES.has(req.ip);
-
-export async function enqueue(req: Request) {
+async function enqueue(req: Request) {
   const enqueuedRequestCount = queue.filter(sharesIdentifierWith(req)).length;
-  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 Error("Too many agnai.chat requests are already queued");
-      }
-    } else {
-      throw new Error("Your IP or token already has a request in the queue");
-    }
+  if (enqueuedRequestCount >= USER_CONCURRENCY_LIMIT) {
+    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
@@ -101,8 +90,8 @@ export async function enqueue(req: Request) {
     }
     registerHeartbeat(req);
   } else if (getProxyLoad() > LOAD_THRESHOLD) {
-    throw new Error(
-      "Due to heavy traffic on this proxy, you must enable streaming for your request."
+    throw new BadRequestError(
+      "Due to heavy traffic on this proxy, you must enable streaming in your chat client to use this endpoint."
     );
   }
 
@@ -130,20 +119,17 @@ export 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)
-    .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;
-    });
+  return queue.filter((req) => getModelFamilyForRequest(req) === partition);
 }
 
 export function dequeue(partition: ModelFamily): Request | undefined {
@@ -246,7 +232,6 @@ let waitTimes: {
   partition: ModelFamily;
   start: number;
   end: number;
-  isDeprioritized: boolean;
 }[] = [];
 
 /** Adds a successful request to the list of wait times. */
@@ -255,7 +240,6 @@ export function trackWaitTime(req: Request) {
     partition: getModelFamilyForRequest(req),
     start: req.startTime!,
     end: req.queueOutTime ?? Date.now(),
-    isDeprioritized: isFromSharedIp(req),
   });
 }
 
@@ -281,8 +265,7 @@ function calculateWaitTime(partition: ModelFamily) {
     .filter((wait) => {
       const isSamePartition = wait.partition === partition;
       const isRecent = now - wait.end < 300 * 1000;
-      const isNormalPriority = !wait.isDeprioritized;
-      return isSamePartition && isRecent && isNormalPriority;
+      return isSamePartition && isRecent;
     })
     .map((wait) => wait.end - wait.start);
   const recentAverage = recentWaits.length
@@ -296,11 +279,7 @@ function calculateWaitTime(partition: ModelFamily) {
   );
 
   const currentWaits = queue
-    .filter((req) => {
-      const isSamePartition = getModelFamilyForRequest(req) === partition;
-      const isNormalPriority = !isFromSharedIp(req);
-      return isSamePartition && isNormalPriority;
-    })
+    .filter((req) => getModelFamilyForRequest(req) === partition)
     .map((req) => now - req.startTime!);
   const longestCurrentWait = Math.max(...currentWaits, 0);
 
@@ -354,11 +333,20 @@ export function createQueueMiddleware({
     try {
       await enqueue(req);
     } catch (err: any) {
-      req.res!.status(429).json({
-        type: "proxy_error",
-        message: err.message,
-        stack: err.stack,
-        proxy_note: `Only one request can be queued at a time. If you don't have another request queued, your IP or user token might be in use by another request.`,
+      const title =
+        err.status === 429
+          ? "Proxy queue error (too many concurrent requests)"
+          : "Proxy queue error (streaming required)";
+      sendErrorToClient({
+        options: {
+          title,
+          message: err.message,
+          format: req.inboundApi,
+          reqId: req.id,
+          model: req.body?.model,
+        },
+        req,
+        res,
       });
     }
   };
@@ -373,20 +361,17 @@ function killQueuedRequest(req: Request) {
   const res = req.res;
   try {
     const message = `Your request has been terminated by the proxy because it has been in the queue for more than 5 minutes.`;
-    if (res.headersSent) {
-      const event = makeCompletionSSE({
-        format: req.inboundApi,
-        title: "Proxy queue error",
+    sendErrorToClient({
+      options: {
+        title: "Proxy queue error (request killed)",
         message,
-        reqId: String(req.id),
+        format: req.inboundApi,
+        reqId: req.id,
         model: req.body?.model,
-      });
-      res.write(event);
-      res.write(`data: [DONE]\n\n`);
-      res.end();
-    } else {
-      res.status(500).json({ error: message });
-    }
+      },
+      req,
+      res,
+    });
   } catch (e) {
     req.log.error(e, `Error killing stalled request.`);
   }
@@ -527,7 +512,7 @@ function monitorHeartbeat(req: Request) {
     if (bytesSinceLast < minBytes) {
       req.log.warn(
         { minBytes, bytesSinceLast },
-        "Queued request is processing heartbeats enough data or server is overloaded; killing connection."
+        "Queued request is not processing heartbeats enough data or server is overloaded; killing connection."
       );
       res.destroy();
     }

src/proxy/rate-limit.ts

@@ -1,14 +1,6 @@
 import { Request, Response, NextFunction } from "express";
 import { config } from "../config";
 
-export const SHARED_IP_ADDRESSES = new Set([
-  // Agnai.chat
-  "157.230.249.32", // old
-  "157.245.148.56",
-  "174.138.29.50",
-  "209.97.162.44",
-]);
-
 const ONE_MINUTE_MS = 60 * 1000;
 
 type Timestamp = number;
@@ -20,7 +12,10 @@ const exemptedRequests: Timestamp[] = [];
 const isRecentAttempt = (now: Timestamp) => (attempt: Timestamp) =>
   attempt > now - ONE_MINUTE_MS;
 
-const getTryAgainInMs = (ip: string, type: "text" | "image") => {
+/**
+ * Returns duration in seconds to wait before retrying for Retry-After header.
+ */
+const getRetryAfter = (ip: string, type: "text" | "image") => {
   const now = Date.now();
   const attempts = lastAttempts.get(ip) || [];
   const validAttempts = attempts.filter(isRecentAttempt(now));
@@ -29,7 +24,7 @@ const getTryAgainInMs = (ip: string, type: "text" | "image") => {
     type === "text" ? config.textModelRateLimit : config.imageModelRateLimit;
 
   if (validAttempts.length >= limit) {
-    return validAttempts[0] - now + ONE_MINUTE_MS;
+    return (validAttempts[0] - now + ONE_MINUTE_MS) / 1000;
   } else {
     lastAttempts.set(ip, [...validAttempts, now]);
     return 0;
@@ -96,22 +91,11 @@ export const ipLimiter = async (
   if (!textLimit && !imageLimit) return next();
   if (req.user?.type === "special") return next();
 
-  // Exempts Agnai.chat from IP-based rate limiting because its IPs are shared
-  // by many users. Instead, the request queue will limit the number of such
-  // requests that may wait in the queue at a time, and sorts them to the end to
-  // let individual users go first.
-  if (SHARED_IP_ADDRESSES.has(req.ip)) {
-    exemptedRequests.push(Date.now());
-    req.log.info(
-      { ip: req.ip, recentExemptions: exemptedRequests.length },
-      "Exempting Agnai request from rate limiting."
-    );
-    return next();
-  }
-
-  const type = (req.baseUrl + req.path).includes("openai-image")
-    ? "image"
-    : "text";
+  const path = req.baseUrl + req.path;
+  const type =
+    path.includes("openai-image") || path.includes("images/generations")
+      ? "image"
+      : "text";
   const limit = type === "image" ? imageLimit : textLimit;
 
   // If user is authenticated, key rate limiting by their token. Otherwise, key
@@ -123,15 +107,14 @@ export const ipLimiter = async (
   res.set("X-RateLimit-Remaining", remaining.toString());
   res.set("X-RateLimit-Reset", reset.toString());
 
-  const tryAgainInMs = getTryAgainInMs(rateLimitKey, type);
-  if (tryAgainInMs > 0) {
-    res.set("Retry-After", tryAgainInMs.toString());
+  const retryAfterTime = getRetryAfter(rateLimitKey, type);
+  if (retryAfterTime > 0) {
+    const waitSec = Math.ceil(retryAfterTime).toString();
+    res.set("Retry-After", waitSec);
     res.status(429).json({
       error: {
         type: "proxy_rate_limited",
-        message: `This model type is rate limited to ${limit} prompts per minute. Please try again in ${Math.ceil(
-          tryAgainInMs / 1000
-        )} seconds.`,
+        message: `This model type is rate limited to ${limit} prompts per minute. Please try again in ${waitSec} seconds.`,
       },
     });
   } else {

src/proxy/routes.ts

@@ -1,41 +1,55 @@
-import express, { Request, Response, NextFunction } from "express";
-import { gatekeeper } from "./gatekeeper";
-import { checkRisuToken } from "./check-risu-token";
-import { openai } from "./openai";
-import { openaiImage } from "./openai-image";
+import express from "express";
+import { addV1 } from "./add-v1";
 import { anthropic } from "./anthropic";
-import { googleAI } from "./google-ai";
-import { mistralAI } from "./mistral-ai";
 import { aws } from "./aws";
 import { azure } from "./azure";
+import { checkRisuToken } from "./check-risu-token";
+import { gatekeeper } from "./gatekeeper";
+import { gcp } from "./gcp";
+import { googleAI } from "./google-ai";
+import { mistralAI } from "./mistral-ai";
+import { openai } from "./openai";
+import { openaiImage } from "./openai-image";
+import { sendErrorToClient } from "./middleware/response/error-generator";
 
 const proxyRouter = express.Router();
+
+// Remove `expect: 100-continue` header from requests due to incompatibility
+// with node-http-proxy.
 proxyRouter.use((req, _res, next) => {
   if (req.headers.expect) {
-    // node-http-proxy does not like it when clients send `expect: 100-continue`
-    // and will stall. none of the upstream APIs use this header anyway.
     delete req.headers.expect;
   }
   next();
 });
+
+// Apply body parsers.
 proxyRouter.use(
-  express.json({ limit: "1mb" }),
-  express.urlencoded({ extended: true, limit: "1mb" })
+  express.json({ limit: "100mb" }),
+  express.urlencoded({ extended: true, limit: "100mb" })
 );
+
+// Apply auth/rate limits.
 proxyRouter.use(gatekeeper);
 proxyRouter.use(checkRisuToken);
+
+// Initialize request queue metadata.
 proxyRouter.use((req, _res, next) => {
   req.startTime = Date.now();
   req.retryCount = 0;
   next();
 });
+
+// Proxy endpoints.
 proxyRouter.use("/openai", addV1, openai);
 proxyRouter.use("/openai-image", addV1, openaiImage);
 proxyRouter.use("/anthropic", addV1, anthropic);
 proxyRouter.use("/google-ai", addV1, googleAI);
 proxyRouter.use("/mistral-ai", addV1, mistralAI);
-proxyRouter.use("/aws/claude", addV1, aws);
+proxyRouter.use("/aws", aws);
+proxyRouter.use("/gcp/claude", addV1, gcp);
 proxyRouter.use("/azure/openai", addV1, azure);
+
 // Redirect browser requests to the homepage.
 proxyRouter.get("*", (req, res, next) => {
   const isBrowser = req.headers["user-agent"]?.includes("Mozilla");
@@ -45,12 +59,25 @@ proxyRouter.get("*", (req, res, next) => {
     next();
   }
 });
-export { proxyRouter as proxyRouter };
 
-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.url = `/v1${req.url}`;
-  }
-  next();
-}
+// Send a fake client error if user specifies an invalid proxy endpoint.
+proxyRouter.use((req, res) => {
+  sendErrorToClient({
+    req,
+    res,
+    options: {
+      title: "Proxy error (HTTP 404 Not Found)",
+      message: "The requested proxy endpoint does not exist.",
+      model: req.body?.model,
+      reqId: req.id,
+      format: "unknown",
+      obj: {
+        proxy_note:
+          "Your chat client is using the wrong endpoint. Check the Service Info page for the list of available endpoints.",
+        requested_url: req.originalUrl,
+      },
+    },
+  });
+});
+
+export { proxyRouter as proxyRouter };

src/server.ts

@@ -8,20 +8,24 @@ import pinoHttp from "pino-http";
 import os from "os";
 import childProcess from "child_process";
 import { logger } from "./logger";
+import { createBlacklistMiddleware } from "./shared/cidr";
 import { setupAssetsDir } from "./shared/file-storage/setup-assets-dir";
 import { keyPool } from "./shared/key-management";
 import { adminRouter } from "./admin/routes";
 import { proxyRouter } from "./proxy/routes";
-import { handleInfoPage, renderPage } from "./info-page";
-import { buildInfo } from "./service-info";
+import { infoPageRouter } from "./info-page";
+import { IMAGE_GEN_MODELS } from "./shared/models";
+import { userRouter } from "./user/routes";
 import { logQueue } from "./shared/prompt-logging";
 import { start as startRequestQueue } from "./proxy/queue";
 import { init as initUserStore } from "./shared/users/user-store";
 import { init as initTokenizers } from "./shared/tokenization";
 import { checkOrigin } from "./proxy/check-origin";
-import { userRouter } from "./user/routes";
+import { sendErrorToClient } from "./proxy/middleware/response/error-generator";
+import { initializeDatabase, getDatabase } from "./shared/database";
 
 const PORT = config.port;
+const BIND_ADDRESS = config.bindAddress;
 
 const app = express();
 // middleware
@@ -29,16 +33,23 @@ app.use(
   pinoHttp({
     quietReqLogger: true,
     logger,
-    autoLogging: { ignore: ({ url }) => ["/health"].includes(url as string) },
+    autoLogging: {
+      ignore: ({ url }) => {
+        const ignoreList = ["/health", "/res", "/user_content"];
+        return ignoreList.some((path) => (url as string).startsWith(path));
+      },
+    },
     redact: {
       paths: [
         "req.headers.cookie",
         'res.headers["set-cookie"]',
         "req.headers.authorization",
         'req.headers["x-api-key"]',
+        'req.headers["api-key"]',
         // Don't log the prompt text on transform errors
         "body.messages",
         "body.prompt",
+        "body.contents",
       ],
       censor: "********",
     },
@@ -50,14 +61,7 @@ app.use(
   })
 );
 
-// TODO: Detect (or support manual configuration of) whether the app is behind
-// a load balancer/reverse proxy, which is necessary to determine request IP
-// addresses correctly.
-app.set("trust proxy", true);
-app.use((req, _res, next) => {
-  req.log.info({ ip: req.ip, forwardedFor: req.get("x-forwarded-for") });
-  next();
-});
+app.set("trust proxy", Number(config.trustedProxies));
 
 app.set("view engine", "ejs");
 app.set("views", [
@@ -66,35 +70,62 @@ app.set("views", [
   path.join(__dirname, "shared/views"),
 ]);
 
-app.use("/user_content", express.static(USER_ASSETS_DIR));
+app.use("/user_content", express.static(USER_ASSETS_DIR, { maxAge: "2h" }));
+app.use(
+  "/res",
+  express.static(path.join(__dirname, "..", "public"), {
+    maxAge: "2h",
+    etag: false,
+  })
+);
 
 app.get("/health", (_req, res) => res.sendStatus(200));
 app.use(cors());
+
+const blacklist = createBlacklistMiddleware("IP_BLACKLIST", config.ipBlacklist);
+app.use(blacklist);
+
 app.use(checkOrigin);
 
-app.get("/", handleInfoPage);
-app.get("/status", (req, res) => {
-  res.json(buildInfo(req.protocol + "://" + req.get("host"), false));
-});
 app.use("/admin", adminRouter);
-app.use("/proxy", proxyRouter);
+app.use((req, _, next) => {
+  // For whatever reason SillyTavern just ignores the path a user provides
+  // when using Google AI with reverse proxy.  We'll fix it here.
+  if (req.path.startsWith("/v1beta/models/")) {
+    req.url = `${config.proxyEndpointRoute}/google-ai${req.url}`;
+    return next();
+  }
+  next();
+});
+app.use(config.proxyEndpointRoute, proxyRouter);
 app.use("/user", userRouter);
+if (config.staticServiceInfo) {
+  app.get("/", (_req, res) => res.sendStatus(200));
+} else {
+  app.use("/", infoPageRouter);
+}
 
-app.use((err: any, _req: unknown, res: express.Response, _next: unknown) => {
-  if (err.status) {
-    res.status(err.status).json({ error: err.message });
-  } else {
-    logger.error(err);
-    res.status(500).json({
-      error: {
-        type: "proxy_error",
-        message: err.message,
-        stack: err.stack,
-        proxy_note: `Reverse proxy encountered an internal server error.`,
+app.use(
+  (err: any, req: express.Request, res: express.Response, _next: unknown) => {
+    if (!err.status) {
+      logger.error(err, "Unhandled error in request");
+    }
+
+    sendErrorToClient({
+      req,
+      res,
+      options: {
+        title: `Proxy error (HTTP ${err.status})`,
+        message:
+          "Reverse proxy encountered an unexpected error while processing your request.",
+        reqId: req.id,
+        statusCode: err.status,
+        obj: { error: err.message, stack: err.stack },
+        format: "unknown",
       },
     });
   }
-});
+);
 app.use((_req: unknown, res: express.Response) => {
   res.status(404).json({ error: "Not found" });
 });
@@ -110,7 +141,7 @@ async function start() {
 
   await initTokenizers();
 
-  if (config.allowedModelFamilies.includes("dall-e")) {
+  if (config.allowedModelFamilies.some((f) => IMAGE_GEN_MODELS.includes(f))) {
     await setupAssetsDir();
   }
 
@@ -123,24 +154,43 @@ async function start() {
     await logQueue.start();
   }
 
+  await initializeDatabase();
+
   logger.info("Starting request queue...");
   startRequestQueue();
 
-  app.listen(PORT, async () => {
-    logger.info({ port: PORT }, "Now listening for connections.");
-    registerUncaughtExceptionHandler();
-  });
-
   const diskSpace = await checkDiskSpace(
     __dirname.startsWith("/app") ? "/app" : os.homedir()
   );
 
+  app.listen(PORT, BIND_ADDRESS, () => {
+    logger.info(
+      { port: PORT, interface: BIND_ADDRESS },
+      "Now listening for connections."
+    );
+    registerUncaughtExceptionHandler();
+  });
+
   logger.info(
     { build: process.env.BUILD_INFO, nodeEnv: process.env.NODE_ENV, diskSpace },
     "Startup complete."
   );
 }
 
+function cleanup() {
+  console.log("Shutting down...");
+  if (config.eventLogging) {
+    try {
+      const db = getDatabase();
+      db.close();
+      console.log("Closed sqlite database.");
+    } catch (error) {}
+  }
+  process.exit(0);
+}
+
+process.on("SIGINT", cleanup);
+
 function registerUncaughtExceptionHandler() {
   process.on("uncaughtException", (err: any) => {
     logger.error(
@@ -164,7 +214,18 @@ function registerUncaughtExceptionHandler() {
  * didn't set it to something misleading.
  */
 async function setBuildInfo() {
-  // Render .dockerignore's the .git directory but provides info in the env
+  // For CI builds, use the env vars set during the build process
+  if (process.env.GITGUD_BRANCH) {
+    const sha = process.env.GITGUD_COMMIT?.slice(0, 7) || "unknown SHA";
+    const branch = process.env.GITGUD_BRANCH;
+    const repo = process.env.GITGUD_PROJECT;
+    const buildInfo = `[ci] ${sha} (${branch}@${repo})`;
+    process.env.BUILD_INFO = buildInfo;
+    logger.info({ build: buildInfo }, "Using build info from CI image.");
+    return;
+  }
+
+  // For render, the git directory is dockerignore'd so we use env vars
   if (process.env.RENDER) {
     const sha = process.env.RENDER_GIT_COMMIT?.slice(0, 7) || "unknown SHA";
     const branch = process.env.RENDER_GIT_BRANCH || "unknown branch";
@@ -175,10 +236,10 @@ async function setBuildInfo() {
     return;
   }
 
+  // For huggingface and bare metal deployments, we can get the info from git
   try {
-    // Ignore git's complaints about dubious directory ownership on Huggingface
-    // (which evidently runs dockerized Spaces on Windows with weird NTFS perms)
     if (process.env.SPACE_ID) {
+      // TODO: may not be necessary anymore with adjusted Huggingface dockerfile
       childProcess.execSync("git config --global --add safe.directory /app");
     }
 
@@ -198,7 +259,7 @@ async function setBuildInfo() {
 
     let [sha, branch, remote, status] = await Promise.all(promises);
 
-    remote = remote.match(/.*[\/:]([\w-]+)\/([\w\-\.]+?)(?:\.git)?$/) || [];
+    remote = remote.match(/.*[\/:]([\w-]+)\/([\w\-.]+?)(?:\.git)?$/) || [];
     const repo = remote.slice(-2).join("/");
     status = status
       // ignore Dockerfile changes since that's how the user deploys the app

src/service-info.ts

@@ -1,10 +1,8 @@
-/** Calculates and returns stats about the service. */
 import { config, listConfig } from "./config";
 import {
   AnthropicKey,
   AwsBedrockKey,
-  AzureOpenAIKey,
-  GoogleAIKey,
+  GcpKey,
   keyPool,
   OpenAIKey,
 } from "./shared/key-management";
@@ -12,6 +10,7 @@ import {
   AnthropicModelFamily,
   assertIsKnownModelFamily,
   AwsBedrockModelFamily,
+  GcpModelFamily,
   AzureOpenAIModelFamily,
   GoogleAIModelFamily,
   LLM_SERVICES,
@@ -25,22 +24,16 @@ import { getCostSuffix, getTokenCostUsd, prettyTokens } from "./shared/stats";
 import { getUniqueIps } from "./proxy/rate-limit";
 import { assertNever } from "./shared/utils";
 import { getEstimatedWaitTime, getQueueLength } from "./proxy/queue";
-import { MistralAIKey } from "./shared/key-management/mistral-ai/provider";
 
 const CACHE_TTL = 2000;
 
 type KeyPoolKey = ReturnType<typeof keyPool.list>[0];
 const keyIsOpenAIKey = (k: KeyPoolKey): k is OpenAIKey =>
   k.service === "openai";
-const keyIsAzureKey = (k: KeyPoolKey): k is AzureOpenAIKey =>
-  k.service === "azure";
 const keyIsAnthropicKey = (k: KeyPoolKey): k is AnthropicKey =>
   k.service === "anthropic";
-const keyIsGoogleAIKey = (k: KeyPoolKey): k is GoogleAIKey =>
-  k.service === "google-ai";
-const keyIsMistralAIKey = (k: KeyPoolKey): k is MistralAIKey =>
-  k.service === "mistral-ai";
 const keyIsAwsKey = (k: KeyPoolKey): k is AwsBedrockKey => k.service === "aws";
+const keyIsGcpKey = (k: KeyPoolKey): k is GcpKey => k.service === "gcp";
 
 /** Stats aggregated across all keys for a given service. */
 type ServiceAggregate = "keys" | "uncheckedKeys" | "orgs";
@@ -52,8 +45,15 @@ type ModelAggregates = {
   overQuota?: number;
   pozzed?: number;
   awsLogged?: number;
+  // needed to disambugiate aws-claude family's variants
+  awsClaude2?: number;
+  awsSonnet3?: number;
+  awsSonnet3_5?: number;
+  awsHaiku: number;
+  gcpSonnet?: number;
+  gcpSonnet35?: number;
+  gcpHaiku?: number;
   queued: number;
-  queueTime: string;
   tokens: number;
 };
 /** All possible combinations of model family and aggregate type. */
@@ -78,21 +78,32 @@ type OpenAIInfo = BaseFamilyInfo & {
   trialKeys?: number;
   overQuotaKeys?: number;
 };
-type AnthropicInfo = BaseFamilyInfo & { pozzedKeys?: number };
-type AwsInfo = BaseFamilyInfo & { privacy?: string };
+type AnthropicInfo = BaseFamilyInfo & {
+  trialKeys?: number;
+  prefilledKeys?: number;
+  overQuotaKeys?: number;
+};
+type AwsInfo = BaseFamilyInfo & {
+  privacy?: string;
+  enabledVariants?: string;
+};
+type GcpInfo = BaseFamilyInfo & {
+  enabledVariants?: string;
+};
 
 // prettier-ignore
 export type ServiceInfo = {
   uptime: number;
   endpoints: {
     openai?: string;
-    openai2?: string;
-    "openai-image"?: string;
     anthropic?: string;
     "google-ai"?: string;
     "mistral-ai"?: string;
-    aws?: string;
+    "aws"?: string;
+    gcp?: string;
     azure?: string;
+    "openai-image"?: string;
+    "azure-image"?: string;
   };
   proompts?: number;
   tookens?: string;
@@ -103,6 +114,7 @@ export type ServiceInfo = {
 } & { [f in OpenAIModelFamily]?: OpenAIInfo }
   & { [f in AnthropicModelFamily]?: AnthropicInfo; }
   & { [f in AwsBedrockModelFamily]?: AwsInfo }
+  & { [f in GcpModelFamily]?: GcpInfo }
   & { [f in AzureOpenAIModelFamily]?: BaseFamilyInfo; }
   & { [f in GoogleAIModelFamily]?: BaseFamilyInfo }
   & { [f in MistralAIModelFamily]?: BaseFamilyInfo };
@@ -125,7 +137,6 @@ export type ServiceInfo = {
 const SERVICE_ENDPOINTS: { [s in LLMService]: Record<string, string> } = {
   openai: {
     openai: `%BASE%/openai`,
-    openai2: `%BASE%/openai/turbo-instruct`,
     "openai-image": `%BASE%/openai-image`,
   },
   anthropic: {
@@ -138,14 +149,19 @@ const SERVICE_ENDPOINTS: { [s in LLMService]: Record<string, string> } = {
     "mistral-ai": `%BASE%/mistral-ai`,
   },
   aws: {
-    aws: `%BASE%/aws/claude`,
+    "aws-claude": `%BASE%/aws/claude`,
+    "aws-mistral": `%BASE%/aws/mistral`,
+  },
+  gcp: {
+    gcp: `%BASE%/gcp/claude`,
   },
   azure: {
     azure: `%BASE%/azure/openai`,
+    "azure-image": `%BASE%/azure/openai`,
   },
 };
 
-const modelStats = new Map<ModelAggregateKey, number>();
+const familyStats = new Map<ModelAggregateKey, number>();
 const serviceStats = new Map<keyof AllStats, number>();
 
 let cachedInfo: ServiceInfo | undefined;
@@ -162,7 +178,7 @@ export function buildInfo(baseUrl: string, forAdmin = false): ServiceInfo {
       .concat("turbo")
   );
 
-  modelStats.clear();
+  familyStats.clear();
   serviceStats.clear();
   keys.forEach(addKeyToAggregates);
 
@@ -197,7 +213,8 @@ export function buildInfo(baseUrl: string, forAdmin = false): ServiceInfo {
 }
 
 function getStatus() {
-  if (!config.checkKeys) return "Key checking is disabled.";
+  if (!config.checkKeys)
+    return "Key checking is disabled. The data displayed are not reliable.";
 
   let unchecked = 0;
   for (const service of LLM_SERVICES) {
@@ -209,7 +226,12 @@ function getStatus() {
 
 function getEndpoints(baseUrl: string, accessibleFamilies: Set<ModelFamily>) {
   const endpoints: Record<string, string> = {};
+  const keys = keyPool.list();
   for (const service of LLM_SERVICES) {
+    if (!keys.some((k) => k.service === service)) {
+      continue;
+    }
+
     for (const [name, url] of Object.entries(SERVICE_ENDPOINTS[service])) {
       endpoints[name] = url.replace("%BASE%", baseUrl);
     }
@@ -217,6 +239,10 @@ function getEndpoints(baseUrl: string, accessibleFamilies: Set<ModelFamily>) {
     if (service === "openai" && !accessibleFamilies.has("dall-e")) {
       delete endpoints["openai-image"];
     }
+
+    if (service === "azure" && !accessibleFamilies.has("azure-dall-e")) {
+      delete endpoints["azure-image"];
+    }
   }
   return endpoints;
 }
@@ -271,120 +297,102 @@ function increment<T extends keyof AllStats | ModelAggregateKey>(
 ) {
   map.set(key, (map.get(key) || 0) + delta);
 }
+const addToService = increment.bind(null, serviceStats);
+const addToFamily = increment.bind(null, familyStats);
 
 function addKeyToAggregates(k: KeyPoolKey) {
-  increment(serviceStats, "proompts", k.promptCount);
-  increment(serviceStats, "openai__keys", k.service === "openai" ? 1 : 0);
-  increment(serviceStats, "anthropic__keys", k.service === "anthropic" ? 1 : 0);
-  increment(serviceStats, "google-ai__keys", k.service === "google-ai" ? 1 : 0);
-  increment(serviceStats, "mistral-ai__keys", k.service === "mistral-ai" ? 1 : 0);
-  increment(serviceStats, "aws__keys", k.service === "aws" ? 1 : 0);
-  increment(serviceStats, "azure__keys", k.service === "azure" ? 1 : 0);
+  addToService("proompts", k.promptCount);
+  addToService("openai__keys", k.service === "openai" ? 1 : 0);
+  addToService("anthropic__keys", k.service === "anthropic" ? 1 : 0);
+  addToService("google-ai__keys", k.service === "google-ai" ? 1 : 0);
+  addToService("mistral-ai__keys", k.service === "mistral-ai" ? 1 : 0);
+  addToService("aws__keys", k.service === "aws" ? 1 : 0);
+  addToService("gcp__keys", k.service === "gcp" ? 1 : 0);
+  addToService("azure__keys", k.service === "azure" ? 1 : 0);
 
   let sumTokens = 0;
   let sumCost = 0;
 
+  const incrementGenericFamilyStats = (f: ModelFamily) => {
+    const tokens = (k as any)[`${f}Tokens`];
+    sumTokens += tokens;
+    sumCost += getTokenCostUsd(f, tokens);
+    addToFamily(`${f}__tokens`, tokens);
+    addToFamily(`${f}__revoked`, k.isRevoked ? 1 : 0);
+    addToFamily(`${f}__active`, k.isDisabled ? 0 : 1);
+  };
+
   switch (k.service) {
     case "openai":
       if (!keyIsOpenAIKey(k)) throw new Error("Invalid key type");
-      increment(
-        serviceStats,
-        "openai__uncheckedKeys",
-        Boolean(k.lastChecked) ? 0 : 1
-      );
-
+      addToService("openai__uncheckedKeys", Boolean(k.lastChecked) ? 0 : 1);
       k.modelFamilies.forEach((f) => {
-        const tokens = k[`${f}Tokens`];
-        sumTokens += tokens;
-        sumCost += getTokenCostUsd(f, tokens);
-        increment(modelStats, `${f}__tokens`, tokens);
-        increment(modelStats, `${f}__revoked`, k.isRevoked ? 1 : 0);
-        increment(modelStats, `${f}__active`, k.isDisabled ? 0 : 1);
-        increment(modelStats, `${f}__trial`, k.isTrial ? 1 : 0);
-        increment(modelStats, `${f}__overQuota`, k.isOverQuota ? 1 : 0);
+        incrementGenericFamilyStats(f);
+        addToFamily(`${f}__trial`, k.isTrial ? 1 : 0);
+        addToFamily(`${f}__overQuota`, k.isOverQuota ? 1 : 0);
       });
       break;
-    case "azure":
-      if (!keyIsAzureKey(k)) throw new Error("Invalid key type");
-      k.modelFamilies.forEach((f) => {
-        const tokens = k[`${f}Tokens`];
-        sumTokens += tokens;
-        sumCost += getTokenCostUsd(f, tokens);
-        increment(modelStats, `${f}__tokens`, tokens);
-        increment(modelStats, `${f}__active`, k.isDisabled ? 0 : 1);
-        increment(modelStats, `${f}__revoked`, k.isRevoked ? 1 : 0);
-      });
-      break;
-    case "anthropic": {
+    case "anthropic":
       if (!keyIsAnthropicKey(k)) throw new Error("Invalid key type");
-      const family = "claude";
-      sumTokens += k.claudeTokens;
-      sumCost += getTokenCostUsd(family, k.claudeTokens);
-      increment(modelStats, `${family}__active`, k.isDisabled ? 0 : 1);
-      increment(modelStats, `${family}__revoked`, k.isRevoked ? 1 : 0);
-      increment(modelStats, `${family}__tokens`, k.claudeTokens);
-      increment(modelStats, `${family}__pozzed`, k.isPozzed ? 1 : 0);
-      increment(
-        serviceStats,
-        "anthropic__uncheckedKeys",
-        Boolean(k.lastChecked) ? 0 : 1
-      );
-      break;
-    }
-    case "google-ai": {
-      if (!keyIsGoogleAIKey(k)) throw new Error("Invalid key type");
-      const family = "gemini-pro";
-      sumTokens += k["gemini-proTokens"];
-      sumCost += getTokenCostUsd(family, k["gemini-proTokens"]);
-      increment(modelStats, `${family}__active`, k.isDisabled ? 0 : 1);
-      increment(modelStats, `${family}__revoked`, k.isRevoked ? 1 : 0);
-      increment(modelStats, `${family}__tokens`, k["gemini-proTokens"]);
-      break;
-    }
-    case "mistral-ai": {
-      if (!keyIsMistralAIKey(k)) throw new Error("Invalid key type");
+      addToService("anthropic__uncheckedKeys", Boolean(k.lastChecked) ? 0 : 1);
       k.modelFamilies.forEach((f) => {
-        const tokens = k[`${f}Tokens`];
-        sumTokens += tokens;
-        sumCost += getTokenCostUsd(f, tokens);
-        increment(modelStats, `${f}__tokens`, tokens);
-        increment(modelStats, `${f}__revoked`, k.isRevoked ? 1 : 0);
-        increment(modelStats, `${f}__active`, k.isDisabled ? 0 : 1);
+        incrementGenericFamilyStats(f);
+        addToFamily(`${f}__trial`, k.tier === "free" ? 1 : 0);
+        addToFamily(`${f}__overQuota`, k.isOverQuota ? 1 : 0);
+        addToFamily(`${f}__pozzed`, k.isPozzed ? 1 : 0);
       });
       break;
-    }
+
     case "aws": {
       if (!keyIsAwsKey(k)) throw new Error("Invalid key type");
-      const family = "aws-claude";
-      sumTokens += k["aws-claudeTokens"];
-      sumCost += getTokenCostUsd(family, k["aws-claudeTokens"]);
-      increment(modelStats, `${family}__active`, k.isDisabled ? 0 : 1);
-      increment(modelStats, `${family}__revoked`, k.isRevoked ? 1 : 0);
-      increment(modelStats, `${family}__tokens`, k["aws-claudeTokens"]);
-
+      k.modelFamilies.forEach(incrementGenericFamilyStats);
+      if (!k.isDisabled) {
+        // Don't add revoked keys to available AWS variants
+        k.modelIds.forEach((id) => {
+          if (id.includes("claude-3-sonnet")) {
+            addToFamily(`aws-claude__awsSonnet3`, 1);
+          } else if (id.includes("claude-3-5-sonnet")) {
+            addToFamily(`aws-claude__awsSonnet3_5`, 1);
+          } else if (id.includes("claude-3-haiku")) {
+            addToFamily(`aws-claude__awsHaiku`, 1);
+          } else if (id.includes("claude-v2")) {
+            addToFamily(`aws-claude__awsClaude2`, 1);
+          }
+        });
+      }
       // Ignore revoked keys for aws logging stats, but include keys where the
       // logging status is unknown.
       const countAsLogged =
-        k.lastChecked && !k.isDisabled && k.awsLoggingStatus !== "disabled";
-      increment(modelStats, `${family}__awsLogged`, countAsLogged ? 1 : 0);
-
+        k.lastChecked && !k.isDisabled && k.awsLoggingStatus === "enabled";
+      addToFamily(`aws-claude__awsLogged`, countAsLogged ? 1 : 0);
       break;
     }
+    case "gcp":
+      if (!keyIsGcpKey(k)) throw new Error("Invalid key type");
+      k.modelFamilies.forEach(incrementGenericFamilyStats);
+      // TODO: add modelIds to GcpKey
+      break;
+    // These services don't have any additional stats to track.
+    case "azure":
+    case "google-ai":
+    case "mistral-ai":
+      k.modelFamilies.forEach(incrementGenericFamilyStats);
+      break;
     default:
       assertNever(k.service);
   }
 
-  increment(serviceStats, "tokens", sumTokens);
-  increment(serviceStats, "tokenCost", sumCost);
+  addToService("tokens", sumTokens);
+  addToService("tokenCost", sumCost);
 }
 
 function getInfoForFamily(family: ModelFamily): BaseFamilyInfo {
-  const tokens = modelStats.get(`${family}__tokens`) || 0;
+  const tokens = familyStats.get(`${family}__tokens`) || 0;
   const cost = getTokenCostUsd(family, tokens);
-  let info: BaseFamilyInfo & OpenAIInfo & AnthropicInfo & AwsInfo = {
+  let info: BaseFamilyInfo & OpenAIInfo & AnthropicInfo & AwsInfo & GcpInfo = {
     usage: `${prettyTokens(tokens)} tokens${getCostSuffix(cost)}`,
-    activeKeys: modelStats.get(`${family}__active`) || 0,
-    revokedKeys: modelStats.get(`${family}__revoked`) || 0,
+    activeKeys: familyStats.get(`${family}__active`) || 0,
+    revokedKeys: familyStats.get(`${family}__revoked`) || 0,
   };
 
   // Add service-specific stats to the info object.
@@ -392,8 +400,8 @@ function getInfoForFamily(family: ModelFamily): BaseFamilyInfo {
     const service = MODEL_FAMILY_SERVICE[family];
     switch (service) {
       case "openai":
-        info.overQuotaKeys = modelStats.get(`${family}__overQuota`) || 0;
-        info.trialKeys = modelStats.get(`${family}__trial`) || 0;
+        info.overQuotaKeys = familyStats.get(`${family}__overQuota`) || 0;
+        info.trialKeys = familyStats.get(`${family}__trial`) || 0;
 
         // Delete trial/revoked keys for non-turbo families.
         // Trials are turbo 99% of the time, and if a key is invalid we don't
@@ -404,14 +412,36 @@ function getInfoForFamily(family: ModelFamily): BaseFamilyInfo {
         }
         break;
       case "anthropic":
-        info.pozzedKeys = modelStats.get(`${family}__pozzed`) || 0;
+        info.overQuotaKeys = familyStats.get(`${family}__overQuota`) || 0;
+        info.trialKeys = familyStats.get(`${family}__trial`) || 0;
+        info.prefilledKeys = familyStats.get(`${family}__pozzed`) || 0;
         break;
       case "aws":
-        const logged = modelStats.get(`${family}__awsLogged`) || 0;
-        if (logged > 0) {
-          info.privacy = config.allowAwsLogging
-            ? `${logged} active keys are potentially logged.`
-            : `${logged} active keys are potentially logged and can't be used. Set ALLOW_AWS_LOGGING=true to override.`;
+        if (family === "aws-claude") {
+          const logged = familyStats.get(`${family}__awsLogged`) || 0;
+          const variants = new Set<string>();
+          if (familyStats.get(`${family}__awsClaude2`) || 0)
+            variants.add("claude2");
+          if (familyStats.get(`${family}__awsSonnet3`) || 0)
+            variants.add("sonnet3");
+          if (familyStats.get(`${family}__awsSonnet3_5`) || 0)
+            variants.add("sonnet3.5");
+          if (familyStats.get(`${family}__awsHaiku`) || 0)
+            variants.add("haiku");
+          info.enabledVariants = variants.size
+            ? `${Array.from(variants).join(",")}`
+            : undefined;
+          if (logged > 0) {
+            info.privacy = config.allowAwsLogging
+              ? `AWS logging verification inactive. Prompts could be logged.`
+              : `${logged} active keys are potentially logged and can't be used. Set ALLOW_AWS_LOGGING=true to override.`;
+          }
+        }
+        break;
+      case "gcp":
+        if (family === "gcp-claude") {
+          // TODO: implement
+          info.enabledVariants = "not implemented";
         }
         break;
     }

src/shared/api-schemas/anthropic.ts

@@ -0,0 +1,470 @@
+import { z } from "zod";
+import { config } from "../../config";
+import { BadRequestError } from "../errors";
+import {
+  flattenOpenAIMessageContent,
+  OpenAIChatMessage,
+  OpenAIV1ChatCompletionSchema,
+} from "./openai";
+import { APIFormatTransformer } from "./index";
+
+const CLAUDE_OUTPUT_MAX = config.maxOutputTokensAnthropic;
+
+const AnthropicV1BaseSchema = z
+  .object({
+    model: z.string().max(100),
+    stop_sequences: z.array(z.string().max(500)).optional(),
+    stream: z.boolean().optional().default(false),
+    temperature: z.coerce.number().optional().default(1),
+    top_k: z.coerce.number().optional(),
+    top_p: z.coerce.number().optional(),
+    metadata: z.object({ user_id: z.string().optional() }).optional(),
+    tools: z.array(z.any()).optional(),
+    tool_choice: z.any().optional(),
+  })
+  .omit(
+    Boolean(config.allowOpenAIToolUsage) ? {} : { tools: true, tool_choice: true }
+  )
+  .strip();
+
+// https://docs.anthropic.com/claude/reference/complete_post [deprecated]
+export const AnthropicV1TextSchema = AnthropicV1BaseSchema.merge(
+  z.object({
+    prompt: z.string(),
+    max_tokens_to_sample: z.coerce
+      .number()
+      .int()
+      .transform((v) => Math.min(v, CLAUDE_OUTPUT_MAX)),
+  })
+);
+
+const AnthropicV1MessageMultimodalContentSchema = z.array(
+  z.union([
+    z.object({ type: z.literal("text"), text: z.string() }),
+    z.object({
+      type: z.literal("image"),
+      source: z.object({
+        type: z.literal("base64"),
+        media_type: z.string().max(100),
+        data: z.string(),
+      }),
+    }),
+    z.object({
+      type: z.literal("tool_use"),
+      id: z.string(),
+      name: z.string(),
+      input: z.object({}).passthrough(),
+    }),
+    z.object({
+      type: z.literal("tool_result"),
+      tool_use_id: z.string(),
+      is_error: z.boolean().optional(),
+      content: z.union([z.string(), z.object({}).passthrough()]).optional(),
+    }),
+  ])
+);
+
+// https://docs.anthropic.com/claude/reference/messages_post
+export const AnthropicV1MessagesSchema = AnthropicV1BaseSchema.merge(
+  z.object({
+    messages: z.array(
+      z.object({
+        role: z.enum(["user", "assistant"]),
+        content: z.union([
+          z.string(),
+          AnthropicV1MessageMultimodalContentSchema,
+        ]),
+      })
+    ),
+    max_tokens: z
+      .number()
+      .int()
+      .transform((v) => Math.min(v, CLAUDE_OUTPUT_MAX)),
+    system: z
+      .union([
+        z.string(),
+        z.array(z.object({ type: z.literal("text"), text: z.string() })),
+      ])
+      .optional(),
+  })
+);
+export type AnthropicChatMessage = z.infer<
+  typeof AnthropicV1MessagesSchema
+>["messages"][0];
+
+function openAIMessagesToClaudeTextPrompt(messages: OpenAIChatMessage[]) {
+  return (
+    messages
+      .map((m) => {
+        let role: string = m.role;
+        if (role === "assistant") {
+          role = "Assistant";
+        } else if (role === "system") {
+          role = "System";
+        } else if (role === "user") {
+          role = "Human";
+        }
+        const name = m.name?.trim();
+        const content = flattenOpenAIMessageContent(m.content);
+        // https://console.anthropic.com/docs/prompt-design
+        // `name` isn't supported by Anthropic but we can still try to use it.
+        return `\n\n${role}: ${name ? `(as ${name}) ` : ""}${content}`;
+      })
+      .join("") + "\n\nAssistant:"
+  );
+}
+
+export const transformOpenAIToAnthropicChat: APIFormatTransformer<
+  typeof AnthropicV1MessagesSchema
+> = async (req) => {
+  const { body } = req;
+  const result = OpenAIV1ChatCompletionSchema.safeParse(body);
+  if (!result.success) {
+    req.log.warn(
+      { issues: result.error.issues, body },
+      "Invalid OpenAI-to-Anthropic Chat request"
+    );
+    throw result.error;
+  }
+
+  req.headers["anthropic-version"] = "2023-06-01";
+
+  const { messages, ...rest } = result.data;
+  const { messages: newMessages, system } =
+    openAIMessagesToClaudeChatPrompt(messages);
+
+  return {
+    system,
+    messages: newMessages,
+    model: rest.model,
+    max_tokens: rest.max_tokens,
+    stream: rest.stream,
+    temperature: rest.temperature,
+    top_p: rest.top_p,
+    stop_sequences:
+      typeof rest.stop === "string" ? [rest.stop] : rest.stop || undefined,
+    ...(rest.user ? { metadata: { user_id: rest.user } } : {}),
+    // Anthropic supports top_k, but OpenAI does not
+    // OpenAI supports frequency_penalty, presence_penalty, logit_bias, n, seed,
+    // and function calls, but Anthropic does not.
+  };
+};
+
+export const transformOpenAIToAnthropicText: APIFormatTransformer<
+  typeof AnthropicV1TextSchema
+> = async (req) => {
+  const { body } = req;
+  const result = OpenAIV1ChatCompletionSchema.safeParse(body);
+  if (!result.success) {
+    req.log.warn(
+      { issues: result.error.issues, body },
+      "Invalid OpenAI-to-Anthropic Text request"
+    );
+    throw result.error;
+  }
+
+  req.headers["anthropic-version"] = "2023-06-01";
+
+  const { messages, ...rest } = result.data;
+  const prompt = openAIMessagesToClaudeTextPrompt(messages);
+
+  let stops = rest.stop
+    ? Array.isArray(rest.stop)
+      ? rest.stop
+      : [rest.stop]
+    : [];
+  // Recommended by Anthropic
+  stops.push("\n\nHuman:");
+  // Helps with jailbreak prompts that send fake system messages and multi-bot
+  // chats that prefix bot messages with "System: Respond as <bot name>".
+  stops.push("\n\nSystem:");
+  // Remove duplicates
+  stops = [...new Set(stops)];
+
+  return {
+    model: rest.model,
+    prompt: prompt,
+    max_tokens_to_sample: rest.max_tokens,
+    stop_sequences: stops,
+    stream: rest.stream,
+    temperature: rest.temperature,
+    top_p: rest.top_p,
+  };
+};
+
+/**
+ * Converts an older Anthropic Text Completion prompt to the newer Messages API
+ * by splitting the flat text into messages.
+ */
+export const transformAnthropicTextToAnthropicChat: APIFormatTransformer<
+  typeof AnthropicV1MessagesSchema
+> = async (req) => {
+  const { body } = req;
+  const result = AnthropicV1TextSchema.safeParse(body);
+  if (!result.success) {
+    req.log.warn(
+      { issues: result.error.issues, body },
+      "Invalid Anthropic Text-to-Anthropic Chat request"
+    );
+    throw result.error;
+  }
+
+  req.headers["anthropic-version"] = "2023-06-01";
+
+  const { model, max_tokens_to_sample, prompt, ...rest } = result.data;
+  validateAnthropicTextPrompt(prompt);
+
+  // Iteratively slice the prompt into messages. Start from the beginning and
+  // look for the next `\n\nHuman:` or `\n\nAssistant:`. Anything before the
+  // first human message is a system message.
+  let index = prompt.indexOf("\n\nHuman:");
+  let remaining = prompt.slice(index);
+  const system = prompt.slice(0, index);
+  const messages: AnthropicChatMessage[] = [];
+  while (remaining) {
+    const isHuman = remaining.startsWith("\n\nHuman:");
+
+    // Multiple messages from the same role are not permitted in Messages API.
+    // We collect all messages until the next message from the opposite role.
+    const thisRole = isHuman ? "\n\nHuman:" : "\n\nAssistant:";
+    const nextRole = isHuman ? "\n\nAssistant:" : "\n\nHuman:";
+    const nextIndex = remaining.indexOf(nextRole);
+
+    // Collect text up to the next message, or the end of the prompt for the
+    // Assistant prefill if present.
+    const msg = remaining
+      .slice(0, nextIndex === -1 ? undefined : nextIndex)
+      .replace(thisRole, "")
+      .trimStart();
+
+    const role = isHuman ? "user" : "assistant";
+    messages.push({ role, content: msg });
+    remaining = remaining.slice(nextIndex);
+
+    if (nextIndex === -1) break;
+  }
+
+  // fix "messages: final assistant content cannot end with trailing whitespace"
+  const lastMessage = messages[messages.length - 1];
+  if (
+    lastMessage.role === "assistant" &&
+    typeof lastMessage.content === "string"
+  ) {
+    messages[messages.length - 1].content = lastMessage.content.trimEnd();
+  }
+
+  return {
+    model,
+    system,
+    messages,
+    max_tokens: max_tokens_to_sample,
+    ...rest,
+  };
+};
+
+function validateAnthropicTextPrompt(prompt: string) {
+  if (!prompt.includes("\n\nHuman:") || !prompt.includes("\n\nAssistant:")) {
+    throw new BadRequestError(
+      "Prompt must contain at least one human and one assistant message."
+    );
+  }
+  // First human message must be before first assistant message
+  const firstHuman = prompt.indexOf("\n\nHuman:");
+  const firstAssistant = prompt.indexOf("\n\nAssistant:");
+  if (firstAssistant < firstHuman) {
+    throw new BadRequestError(
+      "First Assistant message must come after the first Human message."
+    );
+  }
+}
+
+export function flattenAnthropicMessages(
+  messages: AnthropicChatMessage[]
+): string {
+  return messages
+    .map((msg) => {
+      const name = msg.role === "user" ? "Human" : "Assistant";
+      const parts = Array.isArray(msg.content)
+        ? msg.content
+        : [{ type: "text", text: msg.content }];
+      return `${name}: ${parts
+        .map((part) =>
+          part.type === "text"
+            ? part.text
+            : `[Omitted multimodal content of type ${part.type}]`
+        )
+        .join("\n")}`;
+    })
+    .join("\n\n");
+}
+
+/**
+ * Represents the union of all content types without the `string` shorthand
+ * for `text` content.
+ */
+type AnthropicChatMessageContentWithoutString = Exclude<
+  AnthropicChatMessage["content"],
+  string
+>;
+/** Represents a message with all shorthand `string` content expanded. */
+type ConvertedAnthropicChatMessage = AnthropicChatMessage & {
+  content: AnthropicChatMessageContentWithoutString;
+};
+
+function openAIMessagesToClaudeChatPrompt(messages: OpenAIChatMessage[]): {
+  messages: AnthropicChatMessage[];
+  system: string;
+} {
+  // Similar formats, but Claude doesn't use `name` property and doesn't have
+  // a `system` role.  Also, Claude does not allow consecutive messages from
+  // the same role, so we need to merge them.
+  // 1. Collect all system messages up to the first non-system message and set
+  // that as the `system` prompt.
+  // 2. Iterate through messages and:
+  //   - If the message is from system, reassign it to assistant with System:
+  //     prefix.
+  //   - If message is from same role as previous, append it to the previous
+  //     message rather than creating a new one.
+  //   - Otherwise, create a new message and prefix with `name` if present.
+
+  // TODO: When a Claude message has multiple `text` contents, does the internal
+  // message flattening insert newlines between them?  If not, we may need to
+  // do that here...
+
+  let firstNonSystem = -1;
+  const result: { messages: ConvertedAnthropicChatMessage[]; system: string } =
+    { messages: [], system: "" };
+  for (let i = 0; i < messages.length; i++) {
+    const msg = messages[i];
+    const isSystem = isSystemOpenAIRole(msg.role);
+
+    if (firstNonSystem === -1 && isSystem) {
+      // Still merging initial system messages into the system prompt
+      result.system += getFirstTextContent(msg.content) + "\n";
+      continue;
+    }
+
+    if (firstNonSystem === -1 && !isSystem) {
+      // Encountered the first non-system message
+      firstNonSystem = i;
+
+      if (msg.role === "assistant") {
+        // There is an annoying rule that the first message must be from the user.
+        // This is commonly not the case with roleplay prompts that start with a
+        // block of system messages followed by an assistant message. We will try
+        // to reconcile this by splicing the last line of the system prompt into
+        // a beginning user message -- this is *commonly* ST's [Start a new chat]
+        // nudge, which works okay as a user message.
+
+        // Find the last non-empty line in the system prompt
+        const execResult = /(?:[^\r\n]*\r?\n)*([^\r\n]+)(?:\r?\n)*/d.exec(
+          result.system
+        );
+
+        let text = "";
+        if (execResult) {
+          text = execResult[1];
+          // Remove last line from system so it doesn't get duplicated
+          const [_, [lastLineStart]] = execResult.indices || [];
+          result.system = result.system.slice(0, lastLineStart);
+        } else {
+          // This is a bad prompt; there's no system content to move to user and
+          // it starts with assistant. We don't have any good options.
+          text = "[ Joining chat... ]";
+        }
+
+        result.messages.push({
+          role: "user",
+          content: [{ type: "text", text }],
+        });
+      }
+    }
+
+    const last = result.messages[result.messages.length - 1];
+    // I have to handle tools as system messages to be exhaustive here but the
+    // experience will be bad.
+    const role = isSystemOpenAIRole(msg.role) ? "assistant" : msg.role;
+
+    // Here we will lose the original name if it was a system message, but that
+    // is generally okay because the system message is usually a prompt and not
+    // a character in the chat.
+    const name = msg.role === "system" ? "System" : msg.name?.trim();
+    const content = convertOpenAIContent(msg.content);
+
+    // Prepend the display name to the first text content in the current message
+    // if it exists. We don't need to add the name to every content block.
+    if (name?.length) {
+      const firstTextContent = content.find((c) => c.type === "text");
+      if (firstTextContent && "text" in firstTextContent) {
+        // This mutates the element in `content`.
+        firstTextContent.text = `${name}: ${firstTextContent.text}`;
+      }
+    }
+
+    // Merge messages if necessary. If two assistant roles are consecutive but
+    // had different names, the final converted assistant message will have
+    // multiple characters in it, but the name prefixes should assist the model
+    // in differentiating between speakers.
+    if (last && last.role === role) {
+      last.content.push(...content);
+    } else {
+      result.messages.push({ role, content });
+    }
+  }
+
+  result.system = result.system.trimEnd();
+  return result;
+}
+
+function isSystemOpenAIRole(
+  role: OpenAIChatMessage["role"]
+): role is "system" | "function" | "tool" {
+  return ["system", "function", "tool"].includes(role);
+}
+
+function getFirstTextContent(content: OpenAIChatMessage["content"]) {
+  if (typeof content === "string") return content;
+  for (const c of content) {
+    if ("text" in c) return c.text;
+  }
+  return "[ No text content in this message ]";
+}
+
+function convertOpenAIContent(
+  content: OpenAIChatMessage["content"]
+): AnthropicChatMessageContentWithoutString {
+  if (typeof content === "string") {
+    return [{ type: "text", text: content.trimEnd() }];
+  }
+
+  return content.map((c) => {
+    if ("text" in c) {
+      return { type: "text", text: c.text.trimEnd() };
+    } else if ("image_url" in c) {
+      const url = c.image_url.url;
+      try {
+        const mimeType = url.split(";")[0].split(":")[1];
+        const data = url.split(",")[1];
+        return {
+          type: "image",
+          source: { type: "base64", media_type: mimeType, data },
+        };
+      } catch (e) {
+        return {
+          type: "text",
+          text: `[ Unsupported image URL: ${url.slice(0, 200)} ]`,
+        };
+      }
+    } else {
+      const type = String((c as any)?.type);
+      return { type: "text", text: `[ Unsupported content type: ${type} ]` };
+    }
+  });
+}
+
+export function containsImageContent(messages: AnthropicChatMessage[]) {
+  return messages.some(
+    ({ content }) =>
+      typeof content !== "string" && content.some((c) => c.type === "image")
+  );
+}

src/shared/api-schemas/google-ai.ts

@@ -0,0 +1,125 @@
+import { z } from "zod";
+import {
+  flattenOpenAIMessageContent,
+  OpenAIV1ChatCompletionSchema,
+} from "./openai";
+import { APIFormatTransformer } from "./index";
+
+const GoogleAIV1ContentSchema = z.object({
+  parts: z.array(z.object({ text: z.string() })), // TODO: add other media types
+  role: z.enum(["user", "model"]).optional(),
+});
+
+// https://developers.generativeai.google/api/rest/generativelanguage/models/generateContent
+export const GoogleAIV1GenerateContentSchema = z
+  .object({
+    model: z.string().max(100), //actually specified in path but we need it for the router
+    stream: z.boolean().optional().default(false), // also used for router
+    contents: z.array(GoogleAIV1ContentSchema),
+    tools: z.array(z.object({})).max(0).optional(),
+    safetySettings: z.array(z.object({})).optional(),
+    systemInstruction: GoogleAIV1ContentSchema.optional(),
+    generationConfig: z.object({
+      temperature: z.number().optional(),
+      maxOutputTokens: z.coerce
+        .number()
+        .int()
+        .optional()
+        .default(16)
+        .transform((v) => Math.min(v, 4096)), // TODO: Add config
+      candidateCount: z.literal(1).optional(),
+      topP: z.number().optional(),
+      topK: z.number().optional(),
+      stopSequences: z.array(z.string().max(500)).max(5).optional(),
+    }).default({}),
+  })
+  .strip();
+export type GoogleAIChatMessage = z.infer<
+  typeof GoogleAIV1GenerateContentSchema
+>["contents"][0];
+
+export const transformOpenAIToGoogleAI: APIFormatTransformer<
+  typeof GoogleAIV1GenerateContentSchema
+> = async (req) => {
+  const { body } = req;
+  const result = OpenAIV1ChatCompletionSchema.safeParse({
+    ...body,
+    model: "gpt-3.5-turbo",
+  });
+  if (!result.success) {
+    req.log.warn(
+      { issues: result.error.issues, body },
+      "Invalid OpenAI-to-Google AI request"
+    );
+    throw result.error;
+  }
+
+  const { messages, ...rest } = result.data;
+  const foundNames = new Set<string>();
+  const contents = messages
+    .map((m) => {
+      const role = m.role === "assistant" ? "model" : "user";
+      // Detects character names so we can set stop sequences for them as Gemini
+      // is prone to continuing as the next character.
+      // If names are not available, we'll still try to prefix the message
+      // with generic names so we can set stops for them but they don't work
+      // as well as real names.
+      const text = flattenOpenAIMessageContent(m.content);
+      const propName = m.name?.trim();
+      const textName =
+        m.role === "system" ? "" : text.match(/^(.{0,50}?): /)?.[1]?.trim();
+      const name =
+        propName || textName || (role === "model" ? "Character" : "User");
+
+      foundNames.add(name);
+
+      // Prefixing messages with their character name seems to help avoid
+      // Gemini trying to continue as the next character, or at the very least
+      // ensures it will hit the stop sequence.  Otherwise it will start a new
+      // paragraph and switch perspectives.
+      // The response will be very likely to include this prefix so frontends
+      // will need to strip it out.
+      const textPrefix = textName ? "" : `${name}: `;
+      return {
+        parts: [{ text: textPrefix + text }],
+        role: m.role === "assistant" ? ("model" as const) : ("user" as const),
+      };
+    })
+    .reduce<GoogleAIChatMessage[]>((acc, msg) => {
+      const last = acc[acc.length - 1];
+      if (last?.role === msg.role) {
+        last.parts[0].text += "\n\n" + msg.parts[0].text;
+      } else {
+        acc.push(msg);
+      }
+      return acc;
+    }, []);
+
+  let stops = rest.stop
+    ? Array.isArray(rest.stop)
+      ? rest.stop
+      : [rest.stop]
+    : [];
+  stops.push(...Array.from(foundNames).map((name) => `\n${name}:`));
+  stops = [...new Set(stops)].slice(0, 5);
+
+  return {
+    model: req.body.model,
+    stream: rest.stream,
+    contents,
+    tools: [],
+    generationConfig: {
+      maxOutputTokens: rest.max_tokens,
+      stopSequences: stops,
+      topP: rest.top_p,
+      topK: 40, // openai schema doesn't have this, google ai defaults to 40
+      temperature: rest.temperature,
+    },
+    safetySettings: [
+      { category: "HARM_CATEGORY_HARASSMENT", threshold: "BLOCK_NONE" },
+      { category: "HARM_CATEGORY_HATE_SPEECH", threshold: "BLOCK_NONE" },
+      { category: "HARM_CATEGORY_SEXUALLY_EXPLICIT", threshold: "BLOCK_NONE" },
+      { category: "HARM_CATEGORY_DANGEROUS_CONTENT", threshold: "BLOCK_NONE" },
+    ],
+  };
+};

src/shared/api-schemas/index.ts

@@ -0,0 +1,68 @@
+import type { Request } from "express";
+import { z } from "zod";
+import { APIFormat } from "../key-management";
+import {
+  AnthropicV1TextSchema,
+  AnthropicV1MessagesSchema,
+  transformAnthropicTextToAnthropicChat,
+  transformOpenAIToAnthropicText,
+  transformOpenAIToAnthropicChat,
+} from "./anthropic";
+import { OpenAIV1ChatCompletionSchema } from "./openai";
+import {
+  OpenAIV1TextCompletionSchema,
+  transformOpenAIToOpenAIText,
+} from "./openai-text";
+import {
+  OpenAIV1ImagesGenerationSchema,
+  transformOpenAIToOpenAIImage,
+} from "./openai-image";
+import {
+  GoogleAIV1GenerateContentSchema,
+  transformOpenAIToGoogleAI,
+} from "./google-ai";
+import {
+  MistralAIV1ChatCompletionsSchema,
+  MistralAIV1TextCompletionsSchema,
+  transformMistralChatToText,
+} from "./mistral-ai";
+
+export { OpenAIChatMessage } from "./openai";
+export {
+  AnthropicChatMessage,
+  AnthropicV1TextSchema,
+  AnthropicV1MessagesSchema,
+  flattenAnthropicMessages,
+} from "./anthropic";
+export { GoogleAIChatMessage } from "./google-ai";
+export { MistralAIChatMessage } from "./mistral-ai";
+
+type APIPair = `${APIFormat}->${APIFormat}`;
+type TransformerMap = {
+  [key in APIPair]?: APIFormatTransformer<any>;
+};
+
+export type APIFormatTransformer<Z extends z.ZodType<any, any>> = (
+  req: Request
+) => Promise<z.infer<Z>>;
+
+export const API_REQUEST_TRANSFORMERS: TransformerMap = {
+  "anthropic-text->anthropic-chat": transformAnthropicTextToAnthropicChat,
+  "openai->anthropic-chat": transformOpenAIToAnthropicChat,
+  "openai->anthropic-text": transformOpenAIToAnthropicText,
+  "openai->openai-text": transformOpenAIToOpenAIText,
+  "openai->openai-image": transformOpenAIToOpenAIImage,
+  "openai->google-ai": transformOpenAIToGoogleAI,
+  "mistral-ai->mistral-text": transformMistralChatToText,
+};
+
+export const API_REQUEST_VALIDATORS: Record<APIFormat, z.ZodSchema<any>> = {
+  "anthropic-chat": AnthropicV1MessagesSchema,
+  "anthropic-text": AnthropicV1TextSchema,
+  openai: OpenAIV1ChatCompletionSchema,
+  "openai-text": OpenAIV1TextCompletionSchema,
+  "openai-image": OpenAIV1ImagesGenerationSchema,
+  "google-ai": GoogleAIV1GenerateContentSchema,
+  "mistral-ai": MistralAIV1ChatCompletionsSchema,
+  "mistral-text": MistralAIV1TextCompletionsSchema,
+};

src/shared/api-schemas/mistral-ai.ts

@@ -0,0 +1,166 @@
+import { z } from "zod";
+import { OPENAI_OUTPUT_MAX } from "./openai";
+import { Template } from "@huggingface/jinja";
+import { APIFormatTransformer } from "./index";
+import { logger } from "../../logger";
+
+const MistralChatMessageSchema = z.object({
+  role: z.enum(["system", "user", "assistant", "tool"]), // TODO: implement tools
+  content: z.string(),
+  prefix: z.boolean().optional(),
+});
+
+const MistralMessagesSchema = z.array(MistralChatMessageSchema).refine(
+  (input) => {
+    const prefixIdx = input.findIndex((msg) => Boolean(msg.prefix));
+    if (prefixIdx === -1) return true; // no prefix messages
+    const lastIdx = input.length - 1;
+    const lastMsg = input[lastIdx];
+    return prefixIdx === lastIdx && lastMsg.role === "assistant";
+  },
+  {
+    message:
+      "`prefix` can only be set to `true` on the last message, and only for an assistant message.",
+  }
+);
+
+// https://docs.mistral.ai/api#operation/createChatCompletion
+const BaseMistralAIV1CompletionsSchema = z.object({
+  model: z.string(),
+  messages: MistralMessagesSchema.optional(),
+  prompt: z.string().optional(),
+  temperature: z.number().optional().default(0.7),
+  top_p: z.number().optional().default(1),
+  max_tokens: z.coerce
+    .number()
+    .int()
+    .nullish()
+    .transform((v) => Math.min(v ?? OPENAI_OUTPUT_MAX, OPENAI_OUTPUT_MAX)),
+  stream: z.boolean().optional().default(false),
+  // Mistral docs say that `stop` can be a string or array but AWS Mistral
+  // blows up if a string is passed. We must convert it to an array.
+  stop: z
+    .union([z.string(), z.array(z.string())])
+    .optional()
+    .default([])
+    .transform((v) => (Array.isArray(v) ? v : [v])),
+  random_seed: z.number().int().min(0).optional(),
+  response_format: z
+    .object({ type: z.enum(["text", "json_object"]) })
+    .optional(),
+  safe_prompt: z.boolean().optional().default(false),
+});
+
+export const MistralAIV1ChatCompletionsSchema =
+  BaseMistralAIV1CompletionsSchema.and(
+    z.object({ messages: MistralMessagesSchema })
+  );
+export const MistralAIV1TextCompletionsSchema =
+  BaseMistralAIV1CompletionsSchema.and(z.object({ prompt: z.string() }));
+
+/*
+  Slightly more strict version that only allows a subset of the parameters. AWS
+  Mistral helpfully returns no details if unsupported parameters are passed so
+  this list comes from trial and error as of 2024-08-12.
+*/
+const BaseAWSMistralAIV1CompletionsSchema =
+  BaseMistralAIV1CompletionsSchema.pick({
+    temperature: true,
+    top_p: true,
+    max_tokens: true,
+    stop: true,
+    random_seed: true,
+    // response_format: true,
+    // safe_prompt: true,
+  }).strip();
+export const AWSMistralV1ChatCompletionsSchema =
+  BaseAWSMistralAIV1CompletionsSchema.and(
+    z.object({ messages: MistralMessagesSchema })
+  );
+export const AWSMistralV1TextCompletionsSchema =
+  BaseAWSMistralAIV1CompletionsSchema.and(z.object({ prompt: z.string() }));
+
+export type MistralAIChatMessage = z.infer<typeof MistralChatMessageSchema>;
+
+export function fixMistralPrompt(
+  messages: MistralAIChatMessage[]
+): MistralAIChatMessage[] {
+  // Mistral uses OpenAI format but has some additional requirements:
+  // - Only one system message per request, and it must be the first message if
+  //   present.
+  // - Final message must be a user message, unless it has `prefix: true`.
+  // - Cannot have multiple messages from the same role in a row.
+  // While frontends should be able to handle this, we can fix it here in the
+  // meantime.
+  const fixed = messages.reduce<MistralAIChatMessage[]>((acc, msg) => {
+    if (acc.length === 0) {
+      acc.push(msg);
+      return acc;
+    }
+
+    const copy = { ...msg };
+    // Reattribute subsequent system messages to the user
+    if (msg.role === "system") {
+      copy.role = "user";
+    }
+
+    // Consolidate multiple messages from the same role
+    const last = acc[acc.length - 1];
+    if (last.role === copy.role) {
+      last.content += "\n\n" + copy.content;
+    } else {
+      acc.push(copy);
+    }
+    return acc;
+  }, []);
+
+  // If the last message is an assistant message, mark it as a prefix. An
+  // assistant message at the end of the conversation without `prefix: true`
+  // results in an error.
+  if (fixed[fixed.length - 1].role === "assistant") {
+    fixed[fixed.length - 1].prefix = true;
+  }
+  return fixed;
+}
+
+let jinjaTemplate: Template;
+let renderTemplate: (messages: MistralAIChatMessage[]) => string;
+function renderMistralPrompt(messages: MistralAIChatMessage[]) {
+  if (!jinjaTemplate) {
+    logger.warn("Lazy loading mistral chat template...");
+    const { chatTemplate, bosToken, eosToken } =
+      require("./templates/mistral-template").MISTRAL_TEMPLATE;
+    jinjaTemplate = new Template(chatTemplate);
+    renderTemplate = (messages) =>
+      jinjaTemplate.render({
+        messages,
+        bos_token: bosToken,
+        eos_token: eosToken,
+      });
+  }
+
+  return renderTemplate(messages);
+}
+
+/**
+ * Attempts to convert a Mistral chat completions request to a text completions,
+ * using the official prompt template published by Mistral.
+ */
+export const transformMistralChatToText: APIFormatTransformer<
+  typeof MistralAIV1TextCompletionsSchema
+> = async (req) => {
+  const { body } = req;
+  const result = MistralAIV1ChatCompletionsSchema.safeParse(body);
+  if (!result.success) {
+    req.log.warn(
+      { issues: result.error.issues, body },
+      "Invalid Mistral chat completions request"
+    );
+    throw result.error;
+  }
+
+  const { messages, ...rest } = result.data;
+  const prompt = renderMistralPrompt(messages);
+
+  return { ...rest, prompt, messages: undefined };
+};

src/shared/api-schemas/openai-image.ts

@@ -0,0 +1,68 @@
+import { z } from "zod";
+import { OpenAIV1ChatCompletionSchema } from "./openai";
+import { APIFormatTransformer } from "./index";
+
+// https://platform.openai.com/docs/api-reference/images/create
+export const OpenAIV1ImagesGenerationSchema = z
+  .object({
+    prompt: z.string().max(4000),
+    model: z.string().max(100).optional(),
+    quality: z.enum(["standard", "hd"]).optional().default("standard"),
+    n: z.number().int().min(1).max(4).optional().default(1),
+    response_format: z.enum(["url", "b64_json"]).optional(),
+    size: z
+      .enum(["256x256", "512x512", "1024x1024", "1792x1024", "1024x1792"])
+      .optional()
+      .default("1024x1024"),
+    style: z.enum(["vivid", "natural"]).optional().default("vivid"),
+    user: z.string().max(500).optional(),
+  })
+  .strip();
+
+// Takes the last chat message and uses it verbatim as the image prompt.
+export const transformOpenAIToOpenAIImage: APIFormatTransformer<
+  typeof OpenAIV1ImagesGenerationSchema
+> = async (req) => {
+  const { body } = req;
+  const result = OpenAIV1ChatCompletionSchema.safeParse(body);
+  if (!result.success) {
+    req.log.warn(
+      { issues: result.error.issues, body },
+      "Invalid OpenAI-to-OpenAI-image request"
+    );
+    throw result.error;
+  }
+
+  const { messages } = result.data;
+  const prompt = messages.filter((m) => m.role === "user").pop()?.content;
+  if (Array.isArray(prompt)) {
+    throw new Error("Image generation prompt must be a text message.");
+  }
+
+  if (body.stream) {
+    throw new Error(
+      "Streaming is not supported for image generation requests."
+    );
+  }
+
+  // Some frontends do weird things with the prompt, like prefixing it with a
+  // character name or wrapping the entire thing in quotes. We will look for
+  // the index of "Image:" and use everything after that as the prompt.
+
+  const index = prompt?.toLowerCase().indexOf("image:");
+  if (index === -1 || !prompt) {
+    throw new Error(
+      `Start your prompt with 'Image:' followed by a description of the image you want to generate (received: ${prompt}).`
+    );
+  }
+
+  // TODO: Add some way to specify parameters via chat message
+  const transformed = {
+    model: body.model.includes("dall-e") ? body.model : "dall-e-3",
+    quality: "standard",
+    size: "1024x1024",
+    response_format: "url",
+    prompt: prompt.slice(index! + 6).trim(),
+  };
+  return OpenAIV1ImagesGenerationSchema.parse(transformed);
+};

src/shared/api-schemas/openai-text.ts

@@ -0,0 +1,58 @@
+import { z } from "zod";
+import {
+  flattenOpenAIChatMessages,
+  OpenAIV1ChatCompletionSchema,
+} from "./openai";
+import { APIFormatTransformer } from "./index";
+
+export const OpenAIV1TextCompletionSchema = z
+  .object({
+    model: z
+      .string()
+      .max(100)
+      .regex(
+        /^gpt-3.5-turbo-instruct/,
+        "Model must start with 'gpt-3.5-turbo-instruct'"
+      ),
+    prompt: z.string({
+      required_error:
+        "No `prompt` found. Ensure you've set the correct completion endpoint.",
+    }),
+    logprobs: z.number().int().nullish().default(null),
+    echo: z.boolean().optional().default(false),
+    best_of: z.literal(1).optional(),
+    stop: z
+      .union([z.string().max(500), z.array(z.string().max(500)).max(4)])
+      .optional(),
+    suffix: z.string().max(1000).optional(),
+  })
+  .strip()
+  .merge(OpenAIV1ChatCompletionSchema.omit({ messages: true, logprobs: true }));
+
+export const transformOpenAIToOpenAIText: APIFormatTransformer<
+  typeof OpenAIV1TextCompletionSchema
+> = async (req) => {
+  const { body } = req;
+  const result = OpenAIV1ChatCompletionSchema.safeParse(body);
+  if (!result.success) {
+    req.log.warn(
+      { issues: result.error.issues, body },
+      "Invalid OpenAI-to-OpenAI-text request"
+    );
+    throw result.error;
+  }
+
+  const { messages, ...rest } = result.data;
+  const prompt = flattenOpenAIChatMessages(messages);
+
+  let stops = rest.stop
+    ? Array.isArray(rest.stop)
+      ? rest.stop
+      : [rest.stop]
+    : [];
+  stops.push("\n\nUser:");
+  stops = [...new Set(stops)];
+
+  const transformed = { ...rest, prompt: prompt, stop: stops };
+  return OpenAIV1TextCompletionSchema.parse(transformed);
+};

src/shared/api-schemas/openai.ts

@@ -0,0 +1,143 @@
+import { z } from "zod";
+import { config } from "../../config";
+
+export const OPENAI_OUTPUT_MAX = config.maxOutputTokensOpenAI;
+
+// https://platform.openai.com/docs/api-reference/chat/create
+const OpenAIV1ChatContentArraySchema = z.array(
+  z.union([
+    z.object({ type: z.literal("text"), text: z.string() }),
+    z.object({
+      type: z.union([z.literal("image"), z.literal("image_url")]),
+      image_url: z.object({
+        url: z.string().url(),
+        detail: z.enum(["low", "auto", "high"]).optional().default("auto"),
+      }),
+    }),
+  ])
+);
+export const OpenAIV1ChatCompletionSchema = z
+  .object({
+    model: z.string().max(100),
+    messages: z.array(
+      z.object({
+        role: z.enum(["system", "user", "assistant", "tool", "function"]),
+        content: z.union([z.string(), OpenAIV1ChatContentArraySchema]),
+        name: z.string().optional(),
+        tool_calls: z.array(z.any()).optional(),
+        function_call: z.array(z.any()).optional(),
+        tool_call_id: z.string().optional(),
+      }),
+      {
+        required_error:
+          "No `messages` found. Ensure you've set the correct completion endpoint.",
+        invalid_type_error:
+          "Messages were not formatted correctly. Refer to the OpenAI Chat API documentation for more information.",
+      }
+    ),
+    temperature: z.number().optional().default(1),
+    top_p: z.number().optional().default(1),
+    n: z
+      .literal(1, {
+        errorMap: () => ({
+          message: "You may only request a single completion at a time.",
+        }),
+      })
+      .optional(),
+    stream: z.boolean().optional().default(false),
+    stop: z
+      .union([z.string().max(500), z.array(z.string().max(500))])
+      .nullish(),
+    max_tokens: z.coerce
+      .number()
+      .int()
+      .nullish()
+      .default(Math.min(OPENAI_OUTPUT_MAX, 16384))
+      .transform((v) => Math.min(v ?? OPENAI_OUTPUT_MAX, OPENAI_OUTPUT_MAX)),
+    frequency_penalty: z.number().optional().default(0),
+    presence_penalty: z.number().optional().default(0),
+    logit_bias: z.any().optional(),
+    user: z.string().max(500).optional(),
+    seed: z.number().int().optional(),
+    // Be warned that Azure OpenAI combines these two into a single field.
+    // It's the only deviation from the OpenAI API that I'm aware of so I have
+    // special cased it in `addAzureKey` rather than expecting clients to do it.
+    logprobs: z.boolean().optional(),
+    top_logprobs: z.number().int().optional(),
+    // Quickly adding some newer tool usage params, not tested. They will be
+    // passed through to the API as-is.
+    tools: z.array(z.any()).optional(),
+    functions: z.array(z.any()).optional(),
+    tool_choice: z.any().optional(),
+    function_choice: z.any().optional(),
+    response_format: z.any(),
+  })
+  // Tool usage must be enabled via config because we currently have no way to
+  // track quota usage for them or enforce limits.
+  .omit(
+    Boolean(config.allowOpenAIToolUsage) ? {} : { tools: true, functions: true }
+  )
+  .strip();
+export type OpenAIChatMessage = z.infer<
+  typeof OpenAIV1ChatCompletionSchema
+>["messages"][0];
+
+export function flattenOpenAIMessageContent(
+  content: OpenAIChatMessage["content"]
+): string {
+  return Array.isArray(content)
+    ? content
+        .map((contentItem) => {
+          if ("text" in contentItem) return contentItem.text;
+          if ("image_url" in contentItem) return "[ Uploaded Image Omitted ]";
+        })
+        .join("\n")
+    : content;
+}
+
+export function flattenOpenAIChatMessages(messages: OpenAIChatMessage[]) {
+  // Temporary to allow experimenting with prompt strategies
+  const PROMPT_VERSION: number = 1;
+  switch (PROMPT_VERSION) {
+    case 1:
+      return (
+        messages
+          .map((m) => {
+            // Claude-style human/assistant turns
+            let role: string = m.role;
+            if (role === "assistant") {
+              role = "Assistant";
+            } else if (role === "system") {
+              role = "System";
+            } else if (role === "user") {
+              role = "User";
+            }
+            return `\n\n${role}: ${flattenOpenAIMessageContent(m.content)}`;
+          })
+          .join("") + "\n\nAssistant:"
+      );
+    case 2:
+      return messages
+        .map((m) => {
+          // Claude without prefixes (except system) and no Assistant priming
+          let role: string = "";
+          if (role === "system") {
+            role = "System: ";
+          }
+          return `\n\n${role}${flattenOpenAIMessageContent(m.content)}`;
+        })
+        .join("");
+    default:
+      throw new Error(`Unknown prompt version: ${PROMPT_VERSION}`);
+  }
+}
+
+export function containsImageContent(
+  messages: OpenAIChatMessage[]
+): boolean {
+  return messages.some((m) =>
+    Array.isArray(m.content)
+      ? m.content.some((contentItem) => "image_url" in contentItem)
+      : false
+  );
+}