test

.env.example

@@ -11,11 +11,17 @@
 # The title displayed on the info page.
 # SERVER_TITLE=Coom Tunnel
 
-# Model requests allowed per minute per user.
-# MODEL_RATE_LIMIT=4
+# Text model requests allowed per minute per user.
+# TEXT_MODEL_RATE_LIMIT=4
+# Image model requests allowed per minute per user.
+# IMAGE_MODEL_RATE_LIMIT=2
+
+# Max number of context tokens a user can request at once.
+# Increase this if your proxy allow GPT 32k or 128k context
+# MAX_CONTEXT_TOKENS_OPENAI=16384
 
 # Max number of output tokens a user can request at once.
-# MAX_OUTPUT_TOKENS_OPENAI=300
+# MAX_OUTPUT_TOKENS_OPENAI=400
 # MAX_OUTPUT_TOKENS_ANTHROPIC=400
 
 # Whether to show the estimated cost of consumed tokens on the info page.
@@ -27,7 +33,11 @@
 # CHECK_KEYS=true
 
 # Which model types users are allowed to access.
-# ALLOWED_MODEL_FAMILIES=claude,turbo,gpt4,gpt4-32k
+# 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
 
 # URLs from which requests will be blocked.
 # BLOCKED_ORIGINS=reddit.com,9gag.com
@@ -36,8 +46,10 @@
 # Destination to redirect blocked requests to.
 # BLOCK_REDIRECT="https://roblox.com/"
 
-# Whether to reject requests containing disallowed content.
-# REJECT_DISALLOWED=false
+# Comma-separated list of phrases that will be rejected. Only whole words are matched.
+# Surround phrases with quotes if they contain commas.
+# Avoid short or common phrases as this tests the entire prompt.
+# REJECT_PHRASES="phrase one,phrase two,"phrase three, which has a comma",phrase four"
 # Message to show when requests are rejected.
 # REJECT_MESSAGE="This content violates /aicg/'s acceptable use policy."
 
@@ -48,6 +60,9 @@
 # The port to listen on.
 # PORT=7860
 
+# Whether cookies should be set without the Secure flag, for hosts that don't support SSL.
+# USE_INSECURE_COOKIES=false
+
 # Detail level of logging. (trace | debug | info | warn | error)
 # LOG_LEVEL=info
 
@@ -63,15 +78,25 @@
 
 # Maximum number of unique IPs a user can connect from. (0 for unlimited)
 # MAX_IPS_PER_USER=0
+# Whether user_tokens should be automatically disabled when reaching the IP limit.
+# MAX_IPS_AUTO_BAN=true
 
 # With user_token gatekeeper, whether to allow users to change their nickname.
 # 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.
 # TOKEN_QUOTA_TURBO=0
 # TOKEN_QUOTA_GPT4=0
 # TOKEN_QUOTA_GPT4_32K=0
+# TOKEN_QUOTA_GPT4_TURBO=0
+# TOKEN_QUOTA_DALL_E=0
 # TOKEN_QUOTA_CLAUDE=0
+# TOKEN_QUOTA_GEMINI_PRO=0
+# TOKEN_QUOTA_AWS_CLAUDE=0
 
 # How often to refresh token quotas. (hourly | daily)
 # Leave unset to never automatically refresh quotas.
@@ -89,6 +114,8 @@ OPENAI_KEY=sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
 ANTHROPIC_KEY=sk-ant-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
 # 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
 
 # With proxy_key gatekeeper, the password users must provide to access the API.
 # PROXY_KEY=your-secret-key

.gitignore

@@ -5,3 +5,4 @@
 build
 greeting.md
 node_modules
+http-client.private.env.json

data/.gitignore

@@ -0,0 +1,2 @@
+*
+!.gitkeep

docker/huggingface/Dockerfile

@@ -3,9 +3,13 @@ RUN apt-get update && \
     apt-get install -y git
 RUN git clone https://gitgud.io/khanon/oai-reverse-proxy.git /app
 WORKDIR /app
+RUN chown -R 1000:1000 /app
+USER 1000
 RUN npm install
 COPY Dockerfile greeting.md* .env* ./
 RUN npm run build
 EXPOSE 7860
 ENV NODE_ENV=production
+# Huggigface free VMs have 16GB of RAM so we can be greedy
+ENV NODE_OPTIONS="--max-old-space-size=12882"
 CMD [ "npm", "start" ]

docs/aws-configuration.md

@@ -45,10 +45,11 @@ 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)
-  - `anthropic.claude-v2` (~100k context)
+  - `anthropic.claude-v1` (~18k context, claude 1.3)
+  - `anthropic.claude-v2` (~100k context, claude 2.0)
+  - `anthropic.claude-v2:1` (~200k context, claude 2.1)
 - **Claude Instant**
-  - `anthropic.claude-instant-v1`
+  - `anthropic.claude-instant-v1` (~100k context, claude instant 1.2)
 
 ## Note regarding logging
 

docs/azure-configuration.md

@@ -0,0 +1,30 @@
+# Configuring the proxy for Azure
+
+The proxy supports Azure OpenAI Service via the `/proxy/azure/openai` endpoint. The process of setting it up is slightly different from regular OpenAI.
+
+- [Setting keys](#setting-keys)
+- [Model assignment](#model-assignment)
+
+## Setting keys
+
+Use the `AZURE_CREDENTIALS` environment variable to set the Azure API keys.
+
+Like other APIs, you can provide multiple keys separated by commas. Each Azure key, however, is a set of values including the Resource Name, Deployment ID, and API key. These are separated by a colon (`:`).
+
+For example:
+```
+AZURE_CREDENTIALS=contoso-ml:gpt4-8k:0123456789abcdef0123456789abcdef,northwind-corp:testdeployment:0123456789abcdef0123456789abcdef
+```
+
+## Model assignment
+Note that each Azure deployment is assigned a model when you create it in the Azure OpenAI Service portal. If you want to use a different model, you'll need to create a new deployment, and therefore a new key to be added to the AZURE_CREDENTIALS environment variable. Each credential only grants access to one model.
+
+### Supported model IDs
+Users can send normal OpenAI model IDs to the proxy to invoke the corresponding models. For the most part they work the same with Azure. GPT-3.5 Turbo has an ID of "gpt-35-turbo" because Azure doesn't allow periods in model names, but the proxy should automatically convert this to the correct ID.
+
+As noted above, you can only use model IDs for which a deployment has been created and added to the proxy.
+
+## On content filtering
+Be aware that all Azure OpenAI Service deployments have content filtering enabled by default at a Medium level. Prompts or responses which are deemed to be inappropriate will be rejected by the API. This is a feature of the Azure OpenAI Service and not the proxy.
+
+You can disable this from deployment's settings within Azure, but you would need to request an exemption from Microsoft for your organization first. See [this page](https://learn.microsoft.com/en-us/azure/ai-services/openai/how-to/content-filters) for more information.

docs/dall-e-configuration.md

@@ -0,0 +1,71 @@
+# Configuring the proxy for DALL-E
+
+The proxy supports DALL-E 2 and DALL-E 3 image generation via the `/proxy/openai-images` endpoint. By default it is disabled as it is somewhat expensive and potentially more open to abuse than text generation.
+
+- [Updating your Dockerfile](#updating-your-dockerfile)
+- [Enabling DALL-E](#enabling-dall-e)
+- [Setting quotas](#setting-quotas)
+- [Rate limiting](#rate-limiting)
+
+## Updating your Dockerfile
+If you are using a previous version of the Dockerfile supplied with the proxy, it doesn't have the necessary permissions to let the proxy save temporary files.
+
+You can replace the entire thing with the new Dockerfile at [./docker/huggingface/Dockerfile](../docker/huggingface/Dockerfile) (or the equivalent for Render deployments).
+
+You can also modify your existing Dockerfile; just add the following lines after the `WORKDIR` line:
+
+```Dockerfile
+# Existing
+RUN git clone https://gitgud.io/khanon/oai-reverse-proxy.git /app
+WORKDIR /app
+
+# Take ownership of the app directory and switch to the non-root user
+RUN chown -R 1000:1000 /app
+USER 1000
+
+# Existing
+RUN npm install
+```
+
+## Enabling DALL-E
+Add `dall-e` to the `ALLOWED_MODEL_FAMILIES` environment variable to enable DALL-E. For example:
+
+```
+# GPT3.5 Turbo, GPT-4, GPT-4 Turbo, and DALL-E
+ALLOWED_MODEL_FAMILIES=turbo,gpt-4,gpt-4turbo,dall-e
+
+# All models as of this writing
+ALLOWED_MODEL_FAMILIES=turbo,gpt4,gpt4-32k,gpt4-turbo,claude,gemini-pro,aws-claude,dall-e
+```
+
+Refer to [.env.example](../.env.example) for a full list of supported model families. You can add `dall-e` to that list to enable all models.
+
+## Setting quotas
+DALL-E doesn't bill by token like text generation models. Instead there is a fixed cost per image generated, depending on the model, image size, and selected quality.
+
+The proxy still uses tokens to set quotas for users. The cost for each generated image will be converted to "tokens" at a rate of 100000 tokens per US$1.00. This works out to a similar cost-per-token as GPT-4 Turbo, so you can use similar token quotas for both.
+
+Use `TOKEN_QUOTA_DALL_E` to set the default quota for image generation. Otherwise it works the same as token quotas for other models.
+
+```
+# ~50 standard DALL-E images per refresh period, or US$2.00
+TOKEN_QUOTA_DALL_E=200000
+```
+
+Refer to [https://openai.com/pricing](https://openai.com/pricing) for the latest pricing information. As of this writing, the cheapest DALL-E 3 image costs $0.04 per generation, which works out to 4000 tokens. Higher resolution and quality settings can cost up to $0.12 per image, or 12000 tokens. 
+
+## Rate limiting
+The old `MODEL_RATE_LIMIT` setting has been split into `TEXT_MODEL_RATE_LIMIT` and `IMAGE_MODEL_RATE_LIMIT`. Whatever value you previously set for `MODEL_RATE_LIMIT` will be used for text models.
+
+If you don't specify a `IMAGE_MODEL_RATE_LIMIT`, it defaults to half of the `TEXT_MODEL_RATE_LIMIT`, to a minimum of 1 image per minute.
+
+```
+# 4 text generations per minute, 2 images per minute
+TEXT_MODEL_RATE_LIMIT=4
+IMAGE_MODEL_RATE_LIMIT=2
+```
+
+If a prompt is filtered by OpenAI's content filter, it won't count towards the rate limit.
+
+## Hiding recent images
+By default, the proxy shows the last 12 recently generated images by users. You can hide this section by setting `SHOW_RECENT_IMAGES` to `false`.

docs/deploy-huggingface.md

@@ -25,11 +25,14 @@ RUN apt-get update && \
     apt-get install -y git
 RUN git clone https://gitgud.io/khanon/oai-reverse-proxy.git /app
 WORKDIR /app
+RUN chown -R 1000:1000 /app
+USER 1000
 RUN npm install
 COPY Dockerfile greeting.md* .env* ./
 RUN npm run build
 EXPOSE 7860
 ENV NODE_ENV=production
+ENV NODE_OPTIONS="--max-old-space-size=12882"
 CMD [ "npm", "start" ]
 ```
 - Click "Commit new file to `main`" to save the Dockerfile.

http-client.env.json

@@ -0,0 +1,9 @@
+{
+  "dev": {
+    "proxy-host": "http://localhost:7860",
+    "oai-key-1": "override in http-client.private.env.json",
+    "proxy-key": "override in http-client.private.env.json",
+    "azu-resource-name": "override in http-client.private.env.json",
+    "azu-deployment-id": "override in http-client.private.env.json"
+  }
+}

package-lock.json

@@ -15,6 +15,7 @@
         "@smithy/signature-v4": "^2.0.10",
         "@smithy/types": "^2.3.4",
         "axios": "^1.3.5",
+        "check-disk-space": "^3.4.0",
         "cookie-parser": "^1.4.6",
         "copyfiles": "^2.4.1",
         "cors": "^2.8.5",
@@ -33,7 +34,9 @@
         "pino": "^8.11.0",
         "pino-http": "^8.3.3",
         "sanitize-html": "^2.11.0",
+        "sharp": "^0.32.6",
         "showdown": "^2.1.0",
+        "stream-json": "^1.8.0",
         "tiktoken": "^1.0.10",
         "uuid": "^9.0.0",
         "zlib": "^1.0.5",
@@ -49,6 +52,7 @@
         "@types/node-schedule": "^2.1.0",
         "@types/sanitize-html": "^2.9.0",
         "@types/showdown": "^2.0.0",
+        "@types/stream-json": "^1.7.7",
         "@types/uuid": "^9.0.1",
         "concurrently": "^8.0.1",
         "esbuild": "^0.17.16",
@@ -1183,6 +1187,25 @@
       "integrity": "sha512-70xBJoLv+oXjB5PhtA8vo7erjLDp9/qqI63SRHm4REKrwuPOLs8HhXwlZJBJaB4kC18cCZ1UUZ6Fb/PLFW4TCA==",
       "dev": true
     },
+    "node_modules/@types/stream-chain": {
+      "version": "2.0.4",
+      "resolved": "https://registry.npmjs.org/@types/stream-chain/-/stream-chain-2.0.4.tgz",
+      "integrity": "sha512-V7TsWLHrx79KumkHqSD7F8eR6POpEuWb6PuXJ7s/dRHAf3uVst3Jkp1yZ5XqIfECZLQ4a28vBVstTErmsMBvaQ==",
+      "dev": true,
+      "dependencies": {
+        "@types/node": "*"
+      }
+    },
+    "node_modules/@types/stream-json": {
+      "version": "1.7.7",
+      "resolved": "https://registry.npmjs.org/@types/stream-json/-/stream-json-1.7.7.tgz",
+      "integrity": "sha512-hHG7cLQ09H/m9i0jzL6UJAeLLxIWej90ECn0svO4T8J0nGcl89xZDQ2ujT4WKlvg0GWkcxJbjIDzW/v7BYUM6Q==",
+      "dev": true,
+      "dependencies": {
+        "@types/node": "*",
+        "@types/stream-chain": "*"
+      }
+    },
     "node_modules/@types/uuid": {
       "version": "9.0.1",
       "resolved": "https://registry.npmjs.org/@types/uuid/-/uuid-9.0.1.tgz",
@@ -1373,15 +1396,20 @@
       }
     },
     "node_modules/axios": {
-      "version": "1.3.5",
-      "resolved": "https://registry.npmjs.org/axios/-/axios-1.3.5.tgz",
-      "integrity": "sha512-glL/PvG/E+xCWwV8S6nCHcrfg1exGx7vxyUIivIA1iL7BIh6bePylCfVHwp6k13ao7SATxB6imau2kqY+I67kw==",
+      "version": "1.6.1",
+      "resolved": "https://registry.npmjs.org/axios/-/axios-1.6.1.tgz",
+      "integrity": "sha512-vfBmhDpKafglh0EldBEbVuoe7DyAavGSLWhuSm5ZSEKQnHhBf0xAAwybbNH1IkrJNGnS/VG4I5yxig1pCEXE4g==",
       "dependencies": {
         "follow-redirects": "^1.15.0",
         "form-data": "^4.0.0",
         "proxy-from-env": "^1.1.0"
       }
     },
+    "node_modules/b4a": {
+      "version": "1.6.4",
+      "resolved": "https://registry.npmjs.org/b4a/-/b4a-1.6.4.tgz",
+      "integrity": "sha512-fpWrvyVHEKyeEvbKZTVOeZF3VSKKWtJxFIxX/jaVPf+cLbGUSitjb49pHLqPV2BUNNZ0LcoeEGfE/YCpyDYHIw=="
+    },
     "node_modules/balanced-match": {
       "version": "1.0.2",
       "resolved": "https://registry.npmjs.org/balanced-match/-/balanced-match-1.0.2.tgz",
@@ -1423,6 +1451,52 @@
         "node": ">=8"
       }
     },
+    "node_modules/bl": {
+      "version": "4.1.0",
+      "resolved": "https://registry.npmjs.org/bl/-/bl-4.1.0.tgz",
+      "integrity": "sha512-1W07cM9gS6DcLperZfFSj+bWLtaPGSOHWhPiGzXmvVJbRLdG82sH/Kn8EtW1VqWVA54AKf2h5k5BbnIbwF3h6w==",
+      "dependencies": {
+        "buffer": "^5.5.0",
+        "inherits": "^2.0.4",
+        "readable-stream": "^3.4.0"
+      }
+    },
+    "node_modules/bl/node_modules/buffer": {
+      "version": "5.7.1",
+      "resolved": "https://registry.npmjs.org/buffer/-/buffer-5.7.1.tgz",
+      "integrity": "sha512-EHcyIPBQ4BSGlvjB16k5KgAJ27CIsHY/2JBmCRReo48y9rQ3MaUzWX3KVlBa4U7MyX02HdVj0K7C3WaB3ju7FQ==",
+      "funding": [
+        {
+          "type": "github",
+          "url": "https://github.com/sponsors/feross"
+        },
+        {
+          "type": "patreon",
+          "url": "https://www.patreon.com/feross"
+        },
+        {
+          "type": "consulting",
+          "url": "https://feross.org/support"
+        }
+      ],
+      "dependencies": {
+        "base64-js": "^1.3.1",
+        "ieee754": "^1.1.13"
+      }
+    },
+    "node_modules/bl/node_modules/readable-stream": {
+      "version": "3.6.2",
+      "resolved": "https://registry.npmjs.org/readable-stream/-/readable-stream-3.6.2.tgz",
+      "integrity": "sha512-9u/sniCrY3D5WdsERHzHE4G2YCXqoG5FTHUiCC4SIbr6XcLZBY05ya9EKjYek9O5xOAwjGq+1JdGBAS7Q9ScoA==",
+      "dependencies": {
+        "inherits": "^2.0.3",
+        "string_decoder": "^1.1.1",
+        "util-deprecate": "^1.0.1"
+      },
+      "engines": {
+        "node": ">= 6"
+      }
+    },
     "node_modules/bluebird": {
       "version": "3.7.2",
       "resolved": "https://registry.npmjs.org/bluebird/-/bluebird-3.7.2.tgz",
@@ -1582,6 +1656,14 @@
         "node": ">=8"
       }
     },
+    "node_modules/check-disk-space": {
+      "version": "3.4.0",
+      "resolved": "https://registry.npmjs.org/check-disk-space/-/check-disk-space-3.4.0.tgz",
+      "integrity": "sha512-drVkSqfwA+TvuEhFipiR1OC9boEGZL5RrWvVsOthdcvQNXyCCuKkEiTOTXZ7qxSf/GLwq4GvzfrQD/Wz325hgw==",
+      "engines": {
+        "node": ">=16"
+      }
+    },
     "node_modules/chokidar": {
       "version": "3.5.3",
       "resolved": "https://registry.npmjs.org/chokidar/-/chokidar-3.5.3.tgz",
@@ -1609,6 +1691,11 @@
         "fsevents": "~2.3.2"
       }
     },
+    "node_modules/chownr": {
+      "version": "1.1.4",
+      "resolved": "https://registry.npmjs.org/chownr/-/chownr-1.1.4.tgz",
+      "integrity": "sha512-jJ0bqzaylmJtVnNgzTeSOs8DPavpbYgEr/b0YL8/2GO3xJEhInFmhKMUnEJQjZumK7KXGFhUy89PrsJWlakBVg=="
+    },
     "node_modules/cliui": {
       "version": "8.0.1",
       "resolved": "https://registry.npmjs.org/cliui/-/cliui-8.0.1.tgz",
@@ -1623,6 +1710,18 @@
         "node": ">=12"
       }
     },
+    "node_modules/color": {
+      "version": "4.2.3",
+      "resolved": "https://registry.npmjs.org/color/-/color-4.2.3.tgz",
+      "integrity": "sha512-1rXeuUUiGGrykh+CeBdu5Ie7OJwinCgQY0bc7GCRxy5xVHy+moaqkpL/jqQq0MtQOeYcrqEz4abc5f0KtU7W4A==",
+      "dependencies": {
+        "color-convert": "^2.0.1",
+        "color-string": "^1.9.0"
+      },
+      "engines": {
+        "node": ">=12.5.0"
+      }
+    },
     "node_modules/color-convert": {
       "version": "2.0.1",
       "resolved": "https://registry.npmjs.org/color-convert/-/color-convert-2.0.1.tgz",
@@ -1639,6 +1738,15 @@
       "resolved": "https://registry.npmjs.org/color-name/-/color-name-1.1.4.tgz",
       "integrity": "sha512-dOy+3AuW3a2wNbZHIuMZpTcgjGuLU/uBL/ubcZF9OXbDo8ff4O8yVp5Bf0efS8uEoYo5q4Fx7dY9OgQGXgAsQA=="
     },
+    "node_modules/color-string": {
+      "version": "1.9.1",
+      "resolved": "https://registry.npmjs.org/color-string/-/color-string-1.9.1.tgz",
+      "integrity": "sha512-shrVawQFojnZv6xM40anx4CkoDP+fZsw/ZerEMsW/pyzsRbElpsL/DBVW7q3ExxwusdNXI3lXpuhEZkzs8p5Eg==",
+      "dependencies": {
+        "color-name": "^1.0.0",
+        "simple-swizzle": "^0.2.2"
+      }
+    },
     "node_modules/colorette": {
       "version": "2.0.20",
       "resolved": "https://registry.npmjs.org/colorette/-/colorette-2.0.20.tgz",
@@ -2000,6 +2108,28 @@
         "ms": "2.0.0"
       }
     },
+    "node_modules/decompress-response": {
+      "version": "6.0.0",
+      "resolved": "https://registry.npmjs.org/decompress-response/-/decompress-response-6.0.0.tgz",
+      "integrity": "sha512-aW35yZM6Bb/4oJlZncMH2LCoZtJXTRxES17vE3hoRiowU2kWHaJKFkSBDnDR+cm9J+9QhXmREyIfv0pji9ejCQ==",
+      "dependencies": {
+        "mimic-response": "^3.1.0"
+      },
+      "engines": {
+        "node": ">=10"
+      },
+      "funding": {
+        "url": "https://github.com/sponsors/sindresorhus"
+      }
+    },
+    "node_modules/deep-extend": {
+      "version": "0.6.0",
+      "resolved": "https://registry.npmjs.org/deep-extend/-/deep-extend-0.6.0.tgz",
+      "integrity": "sha512-LOHxIOaPYdHlJRtCQfDIVZtfw/ufM8+rVj649RIHzcm/vGwQRXFt6OPqIFWsm2XEMrNIEtWR64sY1LEKD2vAOA==",
+      "engines": {
+        "node": ">=4.0.0"
+      }
+    },
     "node_modules/deep-is": {
       "version": "0.1.4",
       "resolved": "https://registry.npmjs.org/deep-is/-/deep-is-0.1.4.tgz",
@@ -2039,6 +2169,14 @@
         "npm": "1.2.8000 || >= 1.4.16"
       }
     },
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+      "version": "3.0.4",
+      "resolved": "https://registry.npmjs.org/tar-fs/-/tar-fs-3.0.4.tgz",
+      "integrity": "sha512-5AFQU8b9qLfZCX9zp2duONhPmZv0hGYiBPJsyUdqMjzq/mqVpy/rEUSeHk1+YitmxugaptgBh5oDGU3VsAJq4w==",
+      "dependencies": {
+        "mkdirp-classic": "^0.5.2",
+        "pump": "^3.0.0",
+        "tar-stream": "^3.1.5"
+      }
+    },
+    "node_modules/tar-stream": {
+      "version": "3.1.6",
+      "resolved": "https://registry.npmjs.org/tar-stream/-/tar-stream-3.1.6.tgz",
+      "integrity": "sha512-B/UyjYwPpMBv+PaFSWAmtYjwdrlEaZQEhMIBFNC5oEG8lpiW8XjcSdmEaClj28ArfKScKHs2nshz3k2le6crsg==",
+      "dependencies": {
+        "b4a": "^1.6.4",
+        "fast-fifo": "^1.2.0",
+        "streamx": "^2.15.0"
+      }
+    },
     "node_modules/teeny-request": {
       "version": "8.0.3",
       "resolved": "https://registry.npmjs.org/teeny-request/-/teeny-request-8.0.3.tgz",
@@ -5047,6 +5458,17 @@
       "resolved": "https://registry.npmjs.org/tslib/-/tslib-2.6.2.tgz",
       "integrity": "sha512-AEYxH93jGFPn/a2iVAwW87VuUIkR1FVUKB77NwMF7nBTDkDrrT/Hpt/IrCJ0QXhW27jTBDcf5ZY7w6RiqTMw2Q=="
     },
+    "node_modules/tunnel-agent": {
+      "version": "0.6.0",
+      "resolved": "https://registry.npmjs.org/tunnel-agent/-/tunnel-agent-0.6.0.tgz",
+      "integrity": "sha512-McnNiV1l8RYeY8tBgEpuodCC1mLUdbSN+CYBL7kJsJNInOP8UjDDEwdk6Mw60vdLLrr5NHKZhMAOSrR2NZuQ+w==",
+      "dependencies": {
+        "safe-buffer": "^5.0.1"
+      },
+      "engines": {
+        "node": "*"
+      }
+    },
     "node_modules/type-is": {
       "version": "1.6.18",
       "resolved": "https://registry.npmjs.org/type-is/-/type-is-1.6.18.tgz",

package.json

@@ -23,6 +23,7 @@
     "@smithy/signature-v4": "^2.0.10",
     "@smithy/types": "^2.3.4",
     "axios": "^1.3.5",
+    "check-disk-space": "^3.4.0",
     "cookie-parser": "^1.4.6",
     "copyfiles": "^2.4.1",
     "cors": "^2.8.5",
@@ -41,7 +42,9 @@
     "pino": "^8.11.0",
     "pino-http": "^8.3.3",
     "sanitize-html": "^2.11.0",
+    "sharp": "^0.32.6",
     "showdown": "^2.1.0",
+    "stream-json": "^1.8.0",
     "tiktoken": "^1.0.10",
     "uuid": "^9.0.0",
     "zlib": "^1.0.5",
@@ -57,6 +60,7 @@
     "@types/node-schedule": "^2.1.0",
     "@types/sanitize-html": "^2.9.0",
     "@types/showdown": "^2.0.0",
+    "@types/stream-json": "^1.7.7",
     "@types/uuid": "^9.0.1",
     "concurrently": "^8.0.1",
     "esbuild": "^0.17.16",

scripts/oai-reverse-proxy.http

@@ -0,0 +1,276 @@
+# OAI Reverse Proxy
+
+###
+# @name OpenAI -- Chat Completions
+POST https://api.openai.com/v1/chat/completions
+Authorization: Bearer {{oai-key-1}}
+Content-Type: application/json
+
+{
+  "model": "gpt-3.5-turbo",
+  "max_tokens": 30,
+  "stream": false,
+  "messages": [
+    {
+      "role": "user",
+      "content": "This is a test prompt."
+    }
+  ]
+}
+
+###
+# @name OpenAI -- Text Completions
+POST https://api.openai.com/v1/completions
+Authorization: Bearer {{oai-key-1}}
+Content-Type: application/json
+
+{
+  "model": "gpt-3.5-turbo-instruct",
+  "max_tokens": 30,
+  "stream": false,
+  "prompt": "This is a test prompt where"
+}
+
+###
+# @name OpenAI -- Create Embedding
+POST https://api.openai.com/v1/embeddings
+Authorization: Bearer {{oai-key-1}}
+Content-Type: application/json
+
+{
+  "model": "text-embedding-ada-002",
+  "input": "This is a test embedding input."
+}
+
+###
+# @name OpenAI -- Get Organizations
+GET https://api.openai.com/v1/organizations
+Authorization: Bearer {{oai-key-1}}
+
+###
+# @name OpenAI -- Get Models
+GET https://api.openai.com/v1/models
+Authorization: Bearer {{oai-key-1}}
+
+###
+# @name Azure OpenAI -- Chat Completions
+POST https://{{azu-resource-name}}.openai.azure.com/openai/deployments/{{azu-deployment-id}}/chat/completions?api-version=2023-09-01-preview
+api-key: {{azu-key-1}}
+Content-Type: application/json
+
+{
+  "max_tokens": 1,
+  "stream": false,
+  "messages": [
+    {
+      "role": "user",
+      "content": "This is a test prompt."
+    }
+  ]
+}
+
+###
+# @name Proxy / OpenAI -- Get Models
+GET {{proxy-host}}/proxy/openai/v1/models
+Authorization: Bearer {{proxy-key}}
+
+###
+# @name Proxy / OpenAI -- Native Chat Completions
+POST {{proxy-host}}/proxy/openai/chat/completions
+Authorization: Bearer {{proxy-key}}
+Content-Type: application/json
+
+{
+  "model": "gpt-4-1106-preview",
+  "max_tokens": 20,
+  "stream": true,
+  "temperature": 1,
+  "seed": 123,
+  "messages": [
+    {
+      "role": "user",
+      "content": "phrase one"
+    }
+  ]
+}
+
+###
+# @name Proxy / OpenAI -- Native Text Completions
+POST {{proxy-host}}/proxy/openai/v1/turbo-instruct/chat/completions
+Authorization: Bearer {{proxy-key}}
+Content-Type: application/json
+
+{
+  "model": "gpt-3.5-turbo-instruct",
+  "max_tokens": 20,
+  "temperature": 0,
+  "prompt": "Genshin Impact is a game about",
+  "stream": false
+}
+
+###
+# @name Proxy / OpenAI -- Chat-to-Text API Translation
+# Accepts a chat completion request and reformats it to work with the text completion API. `model` is ignored.
+POST {{proxy-host}}/proxy/openai/turbo-instruct/chat/completions
+Authorization: Bearer {{proxy-key}}
+Content-Type: application/json
+
+{
+  "model": "gpt-4",
+  "max_tokens": 20,
+  "stream": true,
+  "messages": [
+    {
+      "role": "user",
+      "content": "What is the name of the fourth president of the united states?"
+    },
+    {
+      "role": "assistant",
+      "content": "That would be George Washington."
+    },
+    {
+      "role": "user",
+      "content": "I don't think that's right..."
+    }
+  ]
+}
+
+###
+# @name Proxy / OpenAI -- Create Embedding
+POST {{proxy-host}}/proxy/openai/embeddings
+Authorization: Bearer {{proxy-key}}
+Content-Type: application/json
+
+{
+  "model": "text-embedding-ada-002",
+  "input": "This is a test embedding input."
+}
+
+
+###
+# @name Proxy / Anthropic -- Native Completion (old API)
+POST {{proxy-host}}/proxy/anthropic/v1/complete
+Authorization: Bearer {{proxy-key}}
+anthropic-version: 2023-01-01
+Content-Type: application/json
+
+{
+  "model": "claude-v1.3",
+  "max_tokens_to_sample": 20,
+  "temperature": 0.2,
+  "stream": true,
+  "prompt": "What is genshin impact\n\n:Assistant:"
+}
+
+###
+# @name Proxy / Anthropic -- Native Completion (2023-06-01 API)
+POST {{proxy-host}}/proxy/anthropic/v1/complete
+Authorization: Bearer {{proxy-key}}
+anthropic-version: 2023-06-01
+Content-Type: application/json
+
+{
+  "model": "claude-v1.3",
+  "max_tokens_to_sample": 20,
+  "temperature": 0.2,
+  "stream": true,
+  "prompt": "What is genshin impact\n\n:Assistant:"
+}
+
+###
+# @name Proxy / Anthropic -- OpenAI-to-Anthropic API Translation
+POST {{proxy-host}}/proxy/anthropic/v1/chat/completions
+Authorization: Bearer {{proxy-key}}
+#anthropic-version: 2023-06-01
+Content-Type: application/json
+
+{
+  "model": "gpt-3.5-turbo",
+  "max_tokens": 20,
+  "stream": false,
+  "temperature": 0,
+  "messages": [
+    {
+      "role": "user",
+      "content": "What is genshin impact"
+    }
+  ]
+}
+
+###
+# @name Proxy / AWS Claude -- Native Completion
+POST {{proxy-host}}/proxy/aws/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 / AWS Claude -- OpenAI-to-Anthropic API Translation
+POST {{proxy-host}}/proxy/aws/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
+Authorization: Bearer {{proxy-key}}
+Content-Type: application/json
+
+{
+  "model": "gpt-4",
+  "max_tokens": 20,
+  "stream": true,
+  "temperature": 1,
+  "seed": 2,
+  "messages": [
+    {
+      "role": "user",
+      "content": "Hi what is the name of the fourth president of the united states?"
+    },
+    {
+      "role": "assistant",
+      "content": "That would be George Washington."
+    },
+    {
+      "role": "user",
+      "content": "That's not right."
+    }
+  ]
+}
+
+###
+# @name Proxy / Google AI -- OpenAI-to-Google AI API Translation
+POST {{proxy-host}}/proxy/google-ai/v1/chat/completions
+Authorization: Bearer {{proxy-key}}
+Content-Type: application/json
+
+{
+  "model": "gpt-4",
+  "max_tokens": 42,
+  "messages": [
+    {
+      "role": "user",
+      "content": "Hi what is the name of the fourth president of the united states?"
+    }
+  ]
+}

scripts/test-concurrency.js

@@ -0,0 +1,45 @@
+const axios = require("axios");
+
+const concurrentRequests = 75;
+const headers = {
+  Authorization: "Bearer test",
+  "Content-Type": "application/json",
+};
+
+const payload = {
+  model: "gpt-4",
+  max_tokens: 1,
+  stream: false,
+  messages: [{ role: "user", content: "Hi" }],
+};
+
+const makeRequest = async (i) => {
+  try {
+    const response = await axios.post(
+      "http://localhost:7860/proxy/google-ai/v1/chat/completions",
+      payload,
+      { headers }
+    );
+    console.log(
+      `Req ${i} finished with status code ${response.status} and response:`,
+      response.data
+    );
+  } catch (error) {
+    const msg = error.response
+    console.error(`Error in req ${i}:`, error.message, msg || "");
+  }
+};
+
+const executeRequestsConcurrently = () => {
+  const promises = [];
+  for (let i = 1; i <= concurrentRequests; i++) {
+    console.log(`Starting request ${i}`);
+    promises.push(makeRequest(i));
+  }
+
+  Promise.all(promises).then(() => {
+    console.log("All requests finished");
+  });
+};
+
+executeRequestsConcurrently();

src/admin/routes.ts

@@ -4,6 +4,8 @@ import { HttpError } from "../shared/errors";
 import { injectLocals } from "../shared/inject-locals";
 import { withSession } from "../shared/with-session";
 import { injectCsrfToken, checkCsrfToken } from "../shared/inject-csrf";
+import { renderPage } from "../info-page";
+import { buildInfo } from "../service-info";
 import { loginRouter } from "./login";
 import { usersApiRouter as apiRouter } from "./api/users";
 import { usersWebRouter as webRouter } from "./web/manage";
@@ -23,6 +25,11 @@ adminRouter.use(checkCsrfToken);
 adminRouter.use(injectLocals);
 adminRouter.use("/", loginRouter);
 adminRouter.use("/manage", authorize({ via: "cookie" }), webRouter);
+adminRouter.use("/service-info", authorize({ via: "cookie" }), (req, res) => {
+  return res.send(
+    renderPage(buildInfo(req.protocol + "://" + req.get("host"), true))
+  );
+});
 
 adminRouter.use(
   (

src/admin/web/manage.ts

@@ -200,7 +200,7 @@ router.post("/maintenance", (req, res) => {
       keyPool.recheck("anthropic");
       const size = keyPool
         .list()
-        .filter((k) => k.service !== "google-palm").length;
+        .filter((k) => k.service !== "google-ai").length;
       flash.type = "success";
       flash.message = `Scheduled recheck of ${size} keys for OpenAI and Anthropic.`;
       break;

src/admin/web/views/admin_index.ejs

@@ -1,5 +1,11 @@
 <%- include("partials/shared_header", { title: "OAI Reverse Proxy Admin" }) %>
 <h1>OAI Reverse Proxy Admin</h1>
+<% if (!usersEnabled) { %>
+<p style="color: red; background-color: #eedddd; padding: 1em">
+  <strong>🚨 <code>user_token</code> gatekeeper is not enabled.</strong><br />
+  <br />None of the user management features will do anything.
+</p>
+<% } %>
 <% if (!persistenceEnabled) { %>
 <p style="color: red; background-color: #eedddd; padding: 1em">
   <strong>⚠️ Users will be lost when the server restarts because persistence is not configured.</strong><br />
@@ -19,6 +25,7 @@
   <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/service-info">Service Info</a></li>
 </ul>
 <h3>Maintenance</h3>
 <form id="maintenanceForm" action="/admin/manage/maintenance" method="post">

src/config.ts

@@ -1,12 +1,18 @@
 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 { MODEL_FAMILIES } from "./shared/models";
+
 dotenv.config();
 
 const startupLogger = pino({ level: "debug" }).child({ module: "startup" });
 const isDev = process.env.NODE_ENV !== "production";
 
+export const DATA_DIR = path.join(__dirname, "..", "data");
+export const USER_ASSETS_DIR = path.join(DATA_DIR, "user-files");
+
 type Config = {
   /** The port the proxy server will listen on. */
   port: number;
@@ -14,8 +20,16 @@ type Config = {
   openaiKey?: string;
   /** Comma-delimited list of Anthropic API keys. */
   anthropicKey?: string;
-  /** Comma-delimited list of Google PaLM API keys. */
-  googlePalmKey?: string;
+  /**
+   * Comma-delimited list of Google AI API keys. Note that these are not the
+   * same as the GCP keys/credentials used for Vertex AI; the models are the
+   * same but the APIs are different. Vertex is the GCP product for enterprise.
+   **/
+  googleAIKey?: string;
+  /**
+   * Comma-delimited list of Mistral AI API keys.
+   */
+  mistralAIKey?: string;
   /**
    * Comma-delimited list of AWS credentials. Each credential item should be a
    * colon-delimited list of access key, secret key, and AWS region.
@@ -28,6 +42,17 @@ 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 Azure OpenAI credentials. Each credential item
+   * should be a colon-delimited list of Azure resource name, deployment ID, and
+   * API key.
+   *
+   * The resource name is the subdomain in your Azure OpenAI deployment's URL,
+   * e.g. `https://resource-name.openai.azure.com
+   *
+   * @example `AZURE_CREDENTIALS=resource_name_1:deployment_id_1:api_key_1,resource_name_2:deployment_id_2:api_key_2`
+   */
+  azureCredentials?: string;
   /**
    * The proxy key to require for requests. Only applicable if the user
    * management mode is set to 'proxy_key', and required if so.
@@ -65,13 +90,20 @@ type Config = {
    */
   firebaseKey?: string;
   /**
-   * Maximum number of IPs per user, after which their token is disabled.
+   * Maximum number of IPs allowed per user token.
    * Users with the manually-assigned `special` role are exempt from this limit.
    * - Defaults to 0, which means that users are not IP-limited.
    */
   maxIpsPerUser: number;
-  /** Per-IP limit for requests per minute to OpenAI's completions endpoint. */
-  modelRateLimit: number;
+  /**
+   * Whether a user token should be automatically disabled if it exceeds the
+   * `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. */
+  textModelRateLimit: number;
+  /** Per-IP limit for requests per minute to image generation models. */
+  imageModelRateLimit: number;
   /**
    * For OpenAI, the maximum number of context tokens (prompt + max output) a
    * user can request before their request is rejected.
@@ -90,10 +122,10 @@ type Config = {
   maxOutputTokensOpenAI: number;
   /** For Anthropic, the maximum number of sampled tokens a user can request. */
   maxOutputTokensAnthropic: number;
-  /** Whether requests containing disallowed characters should be rejected. */
-  rejectDisallowed?: boolean;
+  /** Whether requests containing the following phrases should be rejected. */
+  rejectPhrases: string[];
   /** Message to return when rejecting requests. */
-  rejectMessage?: string;
+  rejectMessage: string;
   /** Verbosity level of diagnostic logging. */
   logLevel: "trace" | "debug" | "info" | "warn" | "error";
   /**
@@ -152,6 +184,20 @@ type Config = {
   quotaRefreshPeriod?: "hourly" | "daily" | string;
   /** Whether to allow users to change their own nicknames via the UI. */
   allowNicknameChanges: boolean;
+  /** Whether to show recent DALL-E image generations on the homepage. */
+  showRecentImages: boolean;
+  /**
+   * If true, cookies will be set without the `Secure` attribute, allowing
+   * the admin UI to used over HTTP.
+   */
+  useInsecureCookies: boolean;
+  /**
+   * Whether to use a more minimal public Service Info page with static content.
+   * Disables all stats pertaining to traffic, prompt/token usage, and queues.
+   * The full info page will appear if you have signed in as an admin using the
+   * configured ADMIN_KEY and go to /admin/service-info.
+   **/
+  staticServiceInfo?: boolean;
 };
 
 // To change configs, create a file called .env in the root directory.
@@ -160,24 +206,28 @@ export const config: Config = {
   port: getEnvWithDefault("PORT", 7860),
   openaiKey: getEnvWithDefault("OPENAI_KEY", ""),
   anthropicKey: getEnvWithDefault("ANTHROPIC_KEY", ""),
-  googlePalmKey: getEnvWithDefault("GOOGLE_PALM_KEY", ""),
+  googleAIKey: getEnvWithDefault("GOOGLE_AI_KEY", ""),
+  mistralAIKey: getEnvWithDefault("MISTRAL_AI_KEY", ""),
   awsCredentials: getEnvWithDefault("AWS_CREDENTIALS", ""),
+  azureCredentials: getEnvWithDefault("AZURE_CREDENTIALS", ""),
   proxyKey: getEnvWithDefault("PROXY_KEY", ""),
   adminKey: getEnvWithDefault("ADMIN_KEY", ""),
   gatekeeper: getEnvWithDefault("GATEKEEPER", "none"),
   gatekeeperStore: getEnvWithDefault("GATEKEEPER_STORE", "memory"),
   maxIpsPerUser: getEnvWithDefault("MAX_IPS_PER_USER", 0),
+  maxIpsAutoBan: getEnvWithDefault("MAX_IPS_AUTO_BAN", true),
   firebaseRtdbUrl: getEnvWithDefault("FIREBASE_RTDB_URL", undefined),
   firebaseKey: getEnvWithDefault("FIREBASE_KEY", undefined),
-  modelRateLimit: getEnvWithDefault("MODEL_RATE_LIMIT", 4),
-  maxContextTokensOpenAI: getEnvWithDefault("MAX_CONTEXT_TOKENS_OPENAI", 0),
+  textModelRateLimit: getEnvWithDefault("TEXT_MODEL_RATE_LIMIT", 4),
+  imageModelRateLimit: getEnvWithDefault("IMAGE_MODEL_RATE_LIMIT", 4),
+  maxContextTokensOpenAI: getEnvWithDefault("MAX_CONTEXT_TOKENS_OPENAI", 16384),
   maxContextTokensAnthropic: getEnvWithDefault(
     "MAX_CONTEXT_TOKENS_ANTHROPIC",
     0
   ),
   maxOutputTokensOpenAI: getEnvWithDefault(
     ["MAX_OUTPUT_TOKENS_OPENAI", "MAX_OUTPUT_TOKENS"],
-    300
+    400
   ),
   maxOutputTokensAnthropic: getEnvWithDefault(
     ["MAX_OUTPUT_TOKENS_ANTHROPIC", "MAX_OUTPUT_TOKENS"],
@@ -187,11 +237,19 @@ export const config: Config = {
     "turbo",
     "gpt4",
     "gpt4-32k",
+    "gpt4-turbo",
     "claude",
-    "bison",
+    "gemini-pro",
+    "mistral-tiny",
+    "mistral-small",
+    "mistral-medium",
     "aws-claude",
+    "azure-turbo",
+    "azure-gpt4",
+    "azure-gpt4-turbo",
+    "azure-gpt4-32k",
   ]),
-  rejectDisallowed: getEnvWithDefault("REJECT_DISALLOWED", false),
+  rejectPhrases: parseCsv(getEnvWithDefault("REJECT_PHRASES", "")),
   rejectMessage: getEnvWithDefault(
     "REJECT_MESSAGE",
     "This content violates /aicg/'s acceptable use policy."
@@ -213,16 +271,21 @@ export const config: Config = {
     "You must be over the age of majority in your country to use this service."
   ),
   blockRedirect: getEnvWithDefault("BLOCK_REDIRECT", "https://www.9gag.com"),
-  tokenQuota: {
-    turbo: getEnvWithDefault("TOKEN_QUOTA_TURBO", 0),
-    gpt4: getEnvWithDefault("TOKEN_QUOTA_GPT4", 0),
-    "gpt4-32k": getEnvWithDefault("TOKEN_QUOTA_GPT4_32K", 0),
-    claude: getEnvWithDefault("TOKEN_QUOTA_CLAUDE", 0),
-    bison: getEnvWithDefault("TOKEN_QUOTA_BISON", 0),
-    "aws-claude": getEnvWithDefault("TOKEN_QUOTA_AWS_CLAUDE", 0),
-  },
+  tokenQuota: MODEL_FAMILIES.reduce(
+    (acc, family: ModelFamily) => {
+      acc[family] = getEnvWithDefault(
+        `TOKEN_QUOTA_${family.toUpperCase().replace(/-/g, "_")}`,
+        0
+      ) as number;
+      return acc;
+    },
+    {} as { [key in ModelFamily]: number }
+  ),
   quotaRefreshPeriod: getEnvWithDefault("QUOTA_REFRESH_PERIOD", undefined),
   allowNicknameChanges: getEnvWithDefault("ALLOW_NICKNAME_CHANGES", true),
+  showRecentImages: getEnvWithDefault("SHOW_RECENT_IMAGES", true),
+  useInsecureCookies: getEnvWithDefault("USE_INSECURE_COOKIES", isDev),
+  staticServiceInfo: getEnvWithDefault("STATIC_SERVICE_INFO", false),
 } as const;
 
 function generateCookieSecret() {
@@ -238,12 +301,16 @@ function generateCookieSecret() {
 export const COOKIE_SECRET = generateCookieSecret();
 
 export async function assertConfigIsValid() {
-  if (process.env.TURBO_ONLY === "true") {
+  if (process.env.MODEL_RATE_LIMIT !== undefined) {
+    const limit =
+      parseInt(process.env.MODEL_RATE_LIMIT, 10) || config.textModelRateLimit;
+
+    config.textModelRateLimit = limit;
+    config.imageModelRateLimit = Math.max(Math.floor(limit / 2), 1);
+
     startupLogger.warn(
-      "TURBO_ONLY is deprecated. Use ALLOWED_MODEL_FAMILIES=turbo instead."
-    );
-    config.allowedModelFamilies = config.allowedModelFamilies.filter(
-      (f) => !f.includes("gpt4")
+      { textLimit: limit, imageLimit: config.imageModelRateLimit },
+      "MODEL_RATE_LIMIT is deprecated. Use TEXT_MODEL_RATE_LIMIT and IMAGE_MODEL_RATE_LIMIT instead."
     );
   }
 
@@ -284,7 +351,8 @@ export async function assertConfigIsValid() {
   // them to users.
   for (const key of getKeys(config)) {
     const maybeSensitive = ["key", "credentials", "secret", "password"].some(
-      (sensitive) => key.toLowerCase().includes(sensitive)
+      (sensitive) =>
+        key.toLowerCase().includes(sensitive) && !["checkKeys"].includes(key)
     );
     const secured = new Set([...SENSITIVE_KEYS, ...OMITTED_KEYS]);
     if (maybeSensitive && !secured.has(key))
@@ -306,16 +374,18 @@ export const SENSITIVE_KEYS: (keyof Config)[] = ["googleSheetsSpreadsheetId"];
  * Config keys that are not displayed on the info page at all, generally because
  * they are not relevant to the user or can be inferred from other config.
  */
-export const OMITTED_KEYS: (keyof Config)[] = [
+export const OMITTED_KEYS = [
   "port",
   "logLevel",
   "openaiKey",
   "anthropicKey",
-  "googlePalmKey",
+  "googleAIKey",
+  "mistralAIKey",
   "awsCredentials",
+  "azureCredentials",
   "proxyKey",
   "adminKey",
-  "checkKeys",
+  "rejectPhrases",
   "showTokenCosts",
   "googleSheetsKey",
   "firebaseKey",
@@ -326,34 +396,51 @@ export const OMITTED_KEYS: (keyof Config)[] = [
   "blockMessage",
   "blockRedirect",
   "allowNicknameChanges",
-];
+  "showRecentImages",
+  "useInsecureCookies",
+  "staticServiceInfo",
+  "checkKeys",
+  "allowedModelFamilies",
+] satisfies (keyof Config)[];
+type OmitKeys = (typeof OMITTED_KEYS)[number];
+
+type Printable<T> = {
+  [P in keyof T as Exclude<P, OmitKeys>]: T[P] extends object
+    ? Printable<T[P]>
+    : string;
+};
+type PublicConfig = Printable<Config>;
 
 const getKeys = Object.keys as <T extends object>(obj: T) => Array<keyof T>;
 
-export function listConfig(obj: Config = config): Record<string, any> {
-  const result: Record<string, any> = {};
+export function listConfig(obj: Config = config) {
+  const result: Record<string, unknown> = {};
   for (const key of getKeys(obj)) {
     const value = obj[key]?.toString() || "";
 
-    const shouldOmit =
-      OMITTED_KEYS.includes(key) || value === "" || value === "undefined";
     const shouldMask = SENSITIVE_KEYS.includes(key);
+    const shouldOmit =
+      OMITTED_KEYS.includes(key as OmitKeys) ||
+      value === "" ||
+      value === "undefined";
 
     if (shouldOmit) {
       continue;
     }
 
+    const validKey = key as keyof Printable<Config>;
+
     if (value && shouldMask) {
-      result[key] = "********";
+      result[validKey] = "********";
     } else {
-      result[key] = value;
+      result[validKey] = value;
     }
 
     if (typeof obj[key] === "object" && !Array.isArray(obj[key])) {
       result[key] = listConfig(obj[key] as unknown as Config);
     }
   }
-  return result;
+  return result as PublicConfig;
 }
 
 /**
@@ -372,8 +459,9 @@ function getEnvWithDefault<T>(env: string | string[], defaultValue: T): T {
       [
         "OPENAI_KEY",
         "ANTHROPIC_KEY",
-        "GOOGLE_PALM_KEY",
+        "GOOGLE_AI_KEY",
         "AWS_CREDENTIALS",
+        "AZURE_CREDENTIALS",
       ].includes(String(env))
     ) {
       return value as unknown as T;
@@ -415,3 +503,11 @@ export function getFirebaseApp(): firebase.app.App {
   }
   return firebaseApp;
 }
+
+function parseCsv(val: string): string[] {
+  if (!val) return [];
+
+  const regex = /(".*?"|[^",]+)(?=\s*,|\s*$)/g;
+  const matches = val.match(regex) || [];
+  return matches.map((item) => item.replace(/^"|"$/g, "").trim());
+}

src/info-page.ts

@@ -1,129 +1,61 @@
+/** This whole module kinda sucks */
 import fs from "fs";
 import { Request, Response } from "express";
 import showdown from "showdown";
-import { config, listConfig } from "./config";
-import {
-  AnthropicKey,
-  GooglePalmKey,
-  OpenAIKey,
-  AwsBedrockKey,
-  keyPool,
-} from "./shared/key-management";
-import { ModelFamily, OpenAIModelFamily } from "./shared/models";
-import { getUniqueIps } from "./proxy/rate-limit";
-import { getEstimatedWaitTime, getQueueLength } from "./proxy/queue";
-import { getTokenCostUsd, prettyTokens } from "./shared/stats";
-import { assertNever } from "./shared/utils";
+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";
 
 const INFO_PAGE_TTL = 2000;
+const MODEL_FAMILY_FRIENDLY_NAME: { [f in ModelFamily]: string } = {
+  "turbo": "GPT-3.5 Turbo",
+  "gpt4": "GPT-4",
+  "gpt4-32k": "GPT-4 32k",
+  "gpt4-turbo": "GPT-4 Turbo",
+  "dall-e": "DALL-E",
+  "claude": "Claude",
+  "gemini-pro": "Gemini Pro",
+  "mistral-tiny": "Mistral 7B",
+  "mistral-small": "Mixtral 8x7B",
+  "mistral-medium": "Mistral Medium (prototype)",
+  "aws-claude": "AWS Claude",
+  "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",
+};
+
+const converter = new showdown.Converter();
+const customGreeting = fs.existsSync("greeting.md")
+  ? `\n## Server Greeting\n${fs.readFileSync("greeting.md", "utf8")}`
+  : "";
 let infoPageHtml: string | undefined;
 let infoPageLastUpdated = 0;
 
-type KeyPoolKey = ReturnType<typeof keyPool.list>[0];
-const keyIsOpenAIKey = (k: KeyPoolKey): k is OpenAIKey =>
-  k.service === "openai";
-const keyIsAnthropicKey = (k: KeyPoolKey): k is AnthropicKey =>
-  k.service === "anthropic";
-const keyIsGooglePalmKey = (k: KeyPoolKey): k is GooglePalmKey =>
-  k.service === "google-palm";
-const keyIsAwsKey = (k: KeyPoolKey): k is AwsBedrockKey => k.service === "aws";
-
-type ModelAggregates = {
-  active: number;
-  trial?: number;
-  revoked?: number;
-  overQuota?: number;
-  pozzed?: number;
-  awsLogged?: number;
-  queued: number;
-  queueTime: string;
-  tokens: number;
-};
-type ModelAggregateKey = `${ModelFamily}__${keyof ModelAggregates}`;
-type ServiceAggregates = {
-  status?: string;
-  openaiKeys?: number;
-  openaiOrgs?: number;
-  anthropicKeys?: number;
-  palmKeys?: number;
-  awsKeys?: number;
-  proompts: number;
-  tokens: number;
-  tokenCost: number;
-  openAiUncheckedKeys?: number;
-  anthropicUncheckedKeys?: number;
-} & {
-  [modelFamily in ModelFamily]?: ModelAggregates;
-};
-
-const modelStats = new Map<ModelAggregateKey, number>();
-const serviceStats = new Map<keyof ServiceAggregates, number>();
-
 export const handleInfoPage = (req: Request, res: Response) => {
   if (infoPageLastUpdated + INFO_PAGE_TTL > Date.now()) {
-    res.send(infoPageHtml);
-    return;
+    return res.send(infoPageHtml);
   }
 
-  // Sometimes huggingface doesn't send the host header and makes us guess.
   const baseUrl =
     process.env.SPACE_ID && !req.get("host")?.includes("hf.space")
       ? getExternalUrlForHuggingfaceSpaceId(process.env.SPACE_ID)
       : req.protocol + "://" + req.get("host");
 
-  res.send(cacheInfoPageHtml(baseUrl));
+  const info = buildInfo(baseUrl + "/proxy");
+  infoPageHtml = renderPage(info);
+  infoPageLastUpdated = Date.now();
+
+  res.send(infoPageHtml);
 };
 
-function getCostString(cost: number) {
-  if (!config.showTokenCosts) return "";
-  return ` ($${cost.toFixed(2)})`;
-}
-
-function cacheInfoPageHtml(baseUrl: string) {
-  const keys = keyPool.list();
-
-  modelStats.clear();
-  serviceStats.clear();
-  keys.forEach(addKeyToAggregates);
-
-  const openaiKeys = serviceStats.get("openaiKeys") || 0;
-  const anthropicKeys = serviceStats.get("anthropicKeys") || 0;
-  const palmKeys = serviceStats.get("palmKeys") || 0;
-  const awsKeys = serviceStats.get("awsKeys") || 0;
-  const proompts = serviceStats.get("proompts") || 0;
-  const tokens = serviceStats.get("tokens") || 0;
-  const tokenCost = serviceStats.get("tokenCost") || 0;
-
-  const info = {
-    uptime: Math.floor(process.uptime()),
-    endpoints: {
-      ...(openaiKeys ? { openai: baseUrl + "/proxy/openai" } : {}),
-      ...(openaiKeys
-        ? { ["openai2"]: baseUrl + "/proxy/openai/turbo-instruct" }
-        : {}),
-      ...(anthropicKeys ? { anthropic: baseUrl + "/proxy/anthropic" } : {}),
-      ...(palmKeys ? { "google-palm": baseUrl + "/proxy/google-palm" } : {}),
-      ...(awsKeys ? { aws: baseUrl + "/proxy/aws/claude" } : {}),
-    },
-    proompts,
-    tookens: `${prettyTokens(tokens)}${getCostString(tokenCost)}`,
-    ...(config.modelRateLimit ? { proomptersNow: getUniqueIps() } : {}),
-    openaiKeys,
-    anthropicKeys,
-    palmKeys,
-    awsKeys,
-    ...(openaiKeys ? getOpenAIInfo() : {}),
-    ...(anthropicKeys ? getAnthropicInfo() : {}),
-    ...(palmKeys ? { "palm-bison": getPalmInfo() } : {}),
-    ...(awsKeys ? { "aws-claude": getAwsInfo() } : {}),
-    config: listConfig(),
-    build: process.env.BUILD_INFO || "dev",
-  };
-
+export function renderPage(info: ServiceInfo) {
   const title = getServerTitle();
-  const headerHtml = buildInfoPageHeader(new showdown.Converter(), title);
+  const headerHtml = buildInfoPageHeader(info);
 
-  const pageBody = `<!DOCTYPE html>
+  return `<!DOCTYPE html>
 <html lang="en">
   <head>
     <meta charset="utf-8" />
@@ -138,317 +70,50 @@ function cacheInfoPageHtml(baseUrl: string) {
     ${getSelfServiceLinks()}
   </body>
 </html>`;
-
-  infoPageHtml = pageBody;
-  infoPageLastUpdated = Date.now();
-
-  return pageBody;
 }
 
-function getUniqueOpenAIOrgs(keys: KeyPoolKey[]) {
-  const orgIds = new Set(
-    keys.filter((k) => k.service === "openai").map((k: any) => k.organizationId)
-  );
-  return orgIds.size;
-}
-
-function increment<T extends keyof ServiceAggregates | ModelAggregateKey>(
-  map: Map<T, number>,
-  key: T,
-  delta = 1
-) {
-  map.set(key, (map.get(key) || 0) + delta);
-}
-
-function addKeyToAggregates(k: KeyPoolKey) {
-  increment(serviceStats, "proompts", k.promptCount);
-  increment(serviceStats, "openaiKeys", k.service === "openai" ? 1 : 0);
-  increment(serviceStats, "anthropicKeys", k.service === "anthropic" ? 1 : 0);
-  increment(serviceStats, "palmKeys", k.service === "google-palm" ? 1 : 0);
-  increment(serviceStats, "awsKeys", k.service === "aws" ? 1 : 0);
-
-  let sumTokens = 0;
-  let sumCost = 0;
-  let family: ModelFamily;
-  const families = k.modelFamilies.filter((f) =>
-    config.allowedModelFamilies.includes(f)
-  );
-
-  switch (k.service) {
-    case "openai":
-      if (!keyIsOpenAIKey(k)) throw new Error("Invalid key type");
-      increment(
-        serviceStats,
-        "openAiUncheckedKeys",
-        Boolean(k.lastChecked) ? 0 : 1
-      );
-
-      // Technically this would not account for keys that have tokens recorded
-      // on models they aren't provisioned for, but that would be strange
-      k.modelFamilies.forEach((f) => {
-        const tokens = k[`${f}Tokens`];
-        sumTokens += tokens;
-        sumCost += getTokenCostUsd(f, tokens);
-        increment(modelStats, `${f}__tokens`, tokens);
-      });
-
-      if (families.includes("gpt4-32k")) {
-        family = "gpt4-32k";
-      } else if (families.includes("gpt4")) {
-        family = "gpt4";
-      } else {
-        family = "turbo";
-      }
-
-      increment(modelStats, `${family}__trial`, k.isTrial ? 1 : 0);
-      break;
-    case "anthropic":
-      if (!keyIsAnthropicKey(k)) throw new Error("Invalid key type");
-      family = "claude";
-      sumTokens += k.claudeTokens;
-      sumCost += getTokenCostUsd(family, k.claudeTokens);
-      increment(modelStats, `${family}__tokens`, k.claudeTokens);
-      increment(modelStats, `${family}__pozzed`, k.isPozzed ? 1 : 0);
-      increment(
-        serviceStats,
-        "anthropicUncheckedKeys",
-        Boolean(k.lastChecked) ? 0 : 1
-      );
-      break;
-    case "google-palm":
-      if (!keyIsGooglePalmKey(k)) throw new Error("Invalid key type");
-      family = "bison";
-      sumTokens += k.bisonTokens;
-      sumCost += getTokenCostUsd(family, k.bisonTokens);
-      increment(modelStats, `${family}__tokens`, k.bisonTokens);
-      break;
-    case "aws":
-      if (!keyIsAwsKey(k)) throw new Error("Invalid key type");
-      family = "aws-claude";
-      sumTokens += k["aws-claudeTokens"];
-      sumCost += getTokenCostUsd(family, k["aws-claudeTokens"]);
-      increment(modelStats, `${family}__tokens`, k["aws-claudeTokens"]);
-
-      // Ignore revoked keys for aws logging stats, but include keys where the
-      // logging status is unknown.
-      const countAsLogged =
-        k.lastChecked && !k.isDisabled && k.awsLoggingStatus !== "disabled";
-      increment(modelStats, `${family}__awsLogged`, countAsLogged ? 1 : 0);
-
-      break;
-    default:
-      assertNever(k.service);
-  }
-
-  increment(serviceStats, "tokens", sumTokens);
-  increment(serviceStats, "tokenCost", sumCost);
-  increment(modelStats, `${family}__active`, k.isDisabled ? 0 : 1);
-  if ("isRevoked" in k) {
-    increment(modelStats, `${family}__revoked`, k.isRevoked ? 1 : 0);
-  }
-  if ("isOverQuota" in k) {
-    increment(modelStats, `${family}__overQuota`, k.isOverQuota ? 1 : 0);
-  }
-}
-
-function getOpenAIInfo() {
-  const info: { status?: string; openaiKeys?: number; openaiOrgs?: number } & {
-    [modelFamily in OpenAIModelFamily]?: {
-      usage?: string;
-      activeKeys: number;
-      trialKeys?: number;
-      revokedKeys?: number;
-      overQuotaKeys?: number;
-      proomptersInQueue?: number;
-      estimatedQueueTime?: string;
-    };
-  } = {};
-
-  const allowedFamilies = new Set(config.allowedModelFamilies);
-  let families = new Set<OpenAIModelFamily>();
-  const keys = keyPool.list().filter((k) => {
-    const isOpenAI = keyIsOpenAIKey(k);
-    if (isOpenAI) k.modelFamilies.forEach((f) => families.add(f));
-    return isOpenAI;
-  }) as Omit<OpenAIKey, "key">[];
-  families = new Set([...families].filter((f) => allowedFamilies.has(f)));
-
-  if (config.checkKeys) {
-    const unchecked = serviceStats.get("openAiUncheckedKeys") || 0;
-    if (unchecked > 0) {
-      info.status = `Checking ${unchecked} keys...`;
-    }
-    info.openaiKeys = keys.length;
-    info.openaiOrgs = getUniqueOpenAIOrgs(keys);
-
-    families.forEach((f) => {
-      const tokens = modelStats.get(`${f}__tokens`) || 0;
-      const cost = getTokenCostUsd(f, tokens);
-
-      info[f] = {
-        usage: `${prettyTokens(tokens)} tokens${getCostString(cost)}`,
-        activeKeys: modelStats.get(`${f}__active`) || 0,
-        trialKeys: modelStats.get(`${f}__trial`) || 0,
-        revokedKeys: modelStats.get(`${f}__revoked`) || 0,
-        overQuotaKeys: modelStats.get(`${f}__overQuota`) || 0,
-      };
-    });
-  } else {
-    info.status = "Key checking is disabled.";
-    info.turbo = { activeKeys: keys.filter((k) => !k.isDisabled).length };
-    info.gpt4 = {
-      activeKeys: keys.filter(
-        (k) => !k.isDisabled && k.modelFamilies.includes("gpt4")
-      ).length,
-    };
-  }
-
-  families.forEach((f) => {
-    if (info[f]) {
-      const { estimatedQueueTime, proomptersInQueue } = getQueueInformation(f);
-      info[f]!.proomptersInQueue = proomptersInQueue;
-      info[f]!.estimatedQueueTime = estimatedQueueTime;
-    }
-  });
-
-  return info;
-}
-
-function getAnthropicInfo() {
-  const claudeInfo: Partial<ModelAggregates> = {
-    active: modelStats.get("claude__active") || 0,
-    pozzed: modelStats.get("claude__pozzed") || 0,
-  };
-
-  const queue = getQueueInformation("claude");
-  claudeInfo.queued = queue.proomptersInQueue;
-  claudeInfo.queueTime = queue.estimatedQueueTime;
-
-  const tokens = modelStats.get("claude__tokens") || 0;
-  const cost = getTokenCostUsd("claude", tokens);
-
-  const unchecked =
-    (config.checkKeys && serviceStats.get("anthropicUncheckedKeys")) || 0;
-
-  return {
-    claude: {
-      usage: `${prettyTokens(tokens)} tokens${getCostString(cost)}`,
-      ...(unchecked > 0 ? { status: `Checking ${unchecked} keys...` } : {}),
-      activeKeys: claudeInfo.active,
-      ...(config.checkKeys ? { pozzedKeys: claudeInfo.pozzed } : {}),
-      proomptersInQueue: claudeInfo.queued,
-      estimatedQueueTime: claudeInfo.queueTime,
-    },
-  };
-}
-
-function getPalmInfo() {
-  const bisonInfo: Partial<ModelAggregates> = {
-    active: modelStats.get("bison__active") || 0,
-  };
-
-  const queue = getQueueInformation("bison");
-  bisonInfo.queued = queue.proomptersInQueue;
-  bisonInfo.queueTime = queue.estimatedQueueTime;
-
-  const tokens = modelStats.get("bison__tokens") || 0;
-  const cost = getTokenCostUsd("bison", tokens);
-
-  return {
-    usage: `${prettyTokens(tokens)} tokens${getCostString(cost)}`,
-    activeKeys: bisonInfo.active,
-    proomptersInQueue: bisonInfo.queued,
-    estimatedQueueTime: bisonInfo.queueTime,
-  };
-}
-
-function getAwsInfo() {
-  const awsInfo: Partial<ModelAggregates> = {
-    active: modelStats.get("aws-claude__active") || 0,
-  };
-
-  const queue = getQueueInformation("aws-claude");
-  awsInfo.queued = queue.proomptersInQueue;
-  awsInfo.queueTime = queue.estimatedQueueTime;
-
-  const tokens = modelStats.get("aws-claude__tokens") || 0;
-  const cost = getTokenCostUsd("aws-claude", tokens);
-
-  const logged = modelStats.get("aws-claude__awsLogged") || 0;
-  const logMsg = config.allowAwsLogging
-    ? `${logged} active keys are potentially logged.`
-    : `${logged} active keys are potentially logged and can't be used.`;
-
-  return {
-    usage: `${prettyTokens(tokens)} tokens${getCostString(cost)}`,
-    activeKeys: awsInfo.active,
-    proomptersInQueue: awsInfo.queued,
-    estimatedQueueTime: awsInfo.queueTime,
-    ...(logged > 0 ? { privacy: logMsg } : {}),
-  };
-}
-
-const customGreeting = fs.existsSync("greeting.md")
-  ? fs.readFileSync("greeting.md", "utf8")
-  : null;
-
 /**
  * If the server operator provides a `greeting.md` file, it will be included in
  * the rendered info page.
  **/
-function buildInfoPageHeader(converter: showdown.Converter, title: string) {
+function buildInfoPageHeader(info: ServiceInfo) {
+  const title = getServerTitle();
   // TODO: use some templating engine instead of this mess
-  let infoBody = `<!-- Header for Showdown's parser, don't remove this line -->
-# ${title}`;
+  let infoBody = `# ${title}`;
   if (config.promptLogging) {
-    infoBody += `\n## Prompt logging is enabled!
-The server operator has enabled prompt logging. The prompts you send to this proxy and the AI responses you receive may be saved.
+    infoBody += `\n## Prompt Logging Enabled
+This proxy keeps full logs of all prompts and AI responses. Prompt logs are anonymous and do not contain IP addresses or timestamps.
 
-Logs are anonymous and do not contain IP addresses or timestamps. [You can see the type of data logged here, along with the rest of the code.](https://gitgud.io/khanon/oai-reverse-proxy/-/blob/main/src/prompt-logging/index.ts).
+[You can see the type of data logged here, along with the rest of the code.](https://gitgud.io/khanon/oai-reverse-proxy/-/blob/main/src/shared/prompt-logging/index.ts).
 
 **If you are uncomfortable with this, don't send prompts to this proxy!**`;
   }
 
+  if (config.staticServiceInfo) {
+    return converter.makeHtml(infoBody + customGreeting);
+  }
+
   const waits: string[] = [];
-  infoBody += `\n## Estimated Wait Times\nIf the AI is busy, your prompt will processed when a slot frees up.`;
 
-  if (config.openaiKey) {
-    // TODO: un-fuck this
-    const keys = keyPool.list().filter((k) => k.service === "openai");
+  for (const modelFamily of config.allowedModelFamilies) {
+    const service = MODEL_FAMILY_SERVICE[modelFamily];
 
-    const turboWait = getQueueInformation("turbo").estimatedQueueTime;
-    waits.push(`**Turbo:** ${turboWait}`);
+    const hasKeys = keyPool.list().some((k) => {
+      return k.service === service && k.modelFamilies.includes(modelFamily);
+    });
 
-    const gpt4Wait = getQueueInformation("gpt4").estimatedQueueTime;
-    const hasGpt4 = keys.some((k) => k.modelFamilies.includes("gpt4"));
-    const allowedGpt4 = config.allowedModelFamilies.includes("gpt4");
-    if (hasGpt4 && allowedGpt4) {
-      waits.push(`**GPT-4:** ${gpt4Wait}`);
+    const wait = info[modelFamily]?.estimatedQueueTime;
+    if (hasKeys && wait) {
+      waits.push(`**${MODEL_FAMILY_FRIENDLY_NAME[modelFamily] || modelFamily}**: ${wait}`);
     }
-
-    const gpt432kWait = getQueueInformation("gpt4-32k").estimatedQueueTime;
-    const hasGpt432k = keys.some((k) => k.modelFamilies.includes("gpt4-32k"));
-    const allowedGpt432k = config.allowedModelFamilies.includes("gpt4-32k");
-    if (hasGpt432k && allowedGpt432k) {
-      waits.push(`**GPT-4-32k:** ${gpt432kWait}`);
-    }
-  }
-
-  if (config.anthropicKey) {
-    const claudeWait = getQueueInformation("claude").estimatedQueueTime;
-    waits.push(`**Claude:** ${claudeWait}`);
-  }
-
-  if (config.awsCredentials) {
-    const awsClaudeWait = getQueueInformation("aws-claude").estimatedQueueTime;
-    waits.push(`**Claude (AWS):** ${awsClaudeWait}`);
   }
 
   infoBody += "\n\n" + waits.join(" / ");
 
-  if (customGreeting) {
-    infoBody += `\n## Server Greeting\n${customGreeting}`;
-  }
+  infoBody += customGreeting;
+
+  infoBody += buildRecentImageSection();
+
   return converter.makeHtml(infoBody);
 }
 
@@ -457,21 +122,6 @@ function getSelfServiceLinks() {
   return `<footer style="font-size: 0.8em;"><hr /><a target="_blank" href="/user/lookup">Check your user token info</a></footer>`;
 }
 
-/** Returns queue time in seconds, or minutes + seconds if over 60 seconds. */
-function getQueueInformation(partition: ModelFamily) {
-  const waitMs = getEstimatedWaitTime(partition);
-  const waitTime =
-    waitMs < 60000
-      ? `${Math.round(waitMs / 1000)}sec`
-      : `${Math.round(waitMs / 60000)}min, ${Math.round(
-          (waitMs % 60000) / 1000
-        )}sec`;
-  return {
-    proomptersInQueue: getQueueLength(partition),
-    estimatedQueueTime: waitMs > 2000 ? waitTime : "no wait",
-  };
-}
-
 function getServerTitle() {
   // Use manually set title if available
   if (process.env.SERVER_TITLE) {
@@ -491,9 +141,44 @@ function getServerTitle() {
   return "OAI Reverse Proxy";
 }
 
+function buildRecentImageSection() {
+  if (
+    !config.allowedModelFamilies.includes("dall-e") ||
+    !config.showRecentImages
+  ) {
+    return "";
+  }
+
+  let html = `<h2>Recent DALL-E Generations</h2>`;
+  const recentImages = getLastNImages(12).reverse();
+  if (recentImages.length === 0) {
+    html += `<p>No images yet.</p>`;
+    return html;
+  }
+
+  html += `<div style="display: flex; flex-wrap: wrap;" id="recent-images">`;
+  for (const { url, prompt } of recentImages) {
+    const thumbUrl = url.replace(/\.png$/, "_t.jpg");
+    const escapedPrompt = escapeHtml(prompt);
+    html += `<div style="margin: 0.5em;" class="recent-image">
+<a href="${url}" target="_blank"><img src="${thumbUrl}" title="${escapedPrompt}" alt="${escapedPrompt}" style="max-width: 150px; max-height: 150px;" /></a>
+</div>`;
+  }
+  html += `</div>`;
+
+  return html;
+}
+
+function escapeHtml(unsafe: string) {
+  return unsafe
+    .replace(/&/g, "&amp;")
+    .replace(/</g, "&lt;")
+    .replace(/>/g, "&gt;")
+    .replace(/"/g, "&quot;")
+    .replace(/'/g, "&#39;");
+}
+
 function getExternalUrlForHuggingfaceSpaceId(spaceId: string) {
-  // Huggingface broke their amazon elb config and no longer sends the
-  // x-forwarded-host header. This is a workaround.
   try {
     const [username, spacename] = spaceId.split("/");
     return `https://${username}-${spacename.replace(/_/g, "-")}.hf.space`;

src/proxy/anthropic.ts

@@ -7,13 +7,10 @@ import { ipLimiter } from "./rate-limit";
 import { handleProxyError } from "./middleware/common";
 import {
   addKey,
-  applyQuotaLimits,
   addAnthropicPreamble,
-  blockZoomerOrigins,
   createPreprocessorMiddleware,
   finalizeBody,
-  languageFilter,
-  stripHeaders, createOnProxyReqHandler
+  createOnProxyReqHandler,
 } from "./middleware/request";
 import {
   ProxyResHandlerWithBody,
@@ -42,8 +39,9 @@ const getModelsResponse = () => {
     "claude-instant-v1.1",
     "claude-instant-v1.1-100k",
     "claude-instant-v1.0",
-    "claude-2", // claude-2 is 100k by default it seems
+    "claude-2",
     "claude-2.0",
+    "claude-2.1",
   ];
 
   const models = claudeVariants.map((id) => ({
@@ -87,9 +85,8 @@ const anthropicResponseHandler: ProxyResHandlerWithBody = async (
     body = transformAnthropicResponse(body, req);
   }
 
-  // TODO: Remove once tokenization is stable
-  if (req.debug) {
-    body.proxy_tokenizer_debug_info = req.debug;
+  if (req.tokenizerInfo) {
+    body.proxy_tokenizer = req.tokenizerInfo;
   }
 
   res.status(200).json(body);
@@ -129,23 +126,15 @@ function transformAnthropicResponse(
   };
 }
 
-const anthropicProxy = createQueueMiddleware(
-  createProxyMiddleware({
+const anthropicProxy = createQueueMiddleware({
+  proxyMiddleware: createProxyMiddleware({
     target: "https://api.anthropic.com",
     changeOrigin: true,
     selfHandleResponse: true,
     logger,
     on: {
       proxyReq: createOnProxyReqHandler({
-        pipeline: [
-          applyQuotaLimits,
-          addKey,
-          addAnthropicPreamble,
-          languageFilter,
-          blockZoomerOrigins,
-          stripHeaders,
-          finalizeBody,
-        ],
+        pipeline: [addKey, addAnthropicPreamble, finalizeBody],
       }),
       proxyRes: createOnProxyResHandler([anthropicResponseHandler]),
       error: handleProxyError,
@@ -154,8 +143,8 @@ const anthropicProxy = createQueueMiddleware(
       // Send OpenAI-compat requests to the real Anthropic endpoint.
       "^/v1/chat/completions": "/v1/complete",
     },
-  })
-);
+  }),
+});
 
 const anthropicRouter = Router();
 anthropicRouter.get("/v1/models", handleModelRequest);

src/proxy/aws.ts

@@ -7,20 +7,18 @@ import { createQueueMiddleware } from "./queue";
 import { ipLimiter } from "./rate-limit";
 import { handleProxyError } from "./middleware/common";
 import {
-  applyQuotaLimits,
   createPreprocessorMiddleware,
-  stripHeaders,
   signAwsRequest,
-  finalizeAwsRequest,
+  finalizeSignedRequest,
   createOnProxyReqHandler,
-  languageFilter,
-  blockZoomerOrigins,
 } from "./middleware/request";
 import {
   ProxyResHandlerWithBody,
   createOnProxyResHandler,
 } from "./middleware/response";
 
+const LATEST_AWS_V2_MINOR_VERSION = "1";
+
 let modelsCache: any = null;
 let modelsCacheTime = 0;
 
@@ -31,7 +29,11 @@ const getModelsResponse = () => {
 
   if (!config.awsCredentials) return { object: "list", data: [] };
 
-  const variants = ["anthropic.claude-v1", "anthropic.claude-v2"];
+  const variants = [
+    "anthropic.claude-v1",
+    "anthropic.claude-v2",
+    "anthropic.claude-v2:1",
+  ];
 
   const models = variants.map((id) => ({
     id,
@@ -74,9 +76,8 @@ const awsResponseHandler: ProxyResHandlerWithBody = async (
     body = transformAwsResponse(body, req);
   }
 
-  // TODO: Remove once tokenization is stable
-  if (req.debug) {
-    body.proxy_tokenizer_debug_info = req.debug;
+  if (req.tokenizerInfo) {
+    body.proxy_tokenizer = req.tokenizerInfo;
   }
 
   // AWS does not confirm the model in the response, so we have to add it
@@ -119,34 +120,24 @@ function transformAwsResponse(
   };
 }
 
-const awsProxy = createQueueMiddleware(
-  createProxyMiddleware({
+const awsProxy = createQueueMiddleware({
+  beforeProxy: signAwsRequest,
+  proxyMiddleware: createProxyMiddleware({
     target: "bad-target-will-be-rewritten",
     router: ({ signedRequest }) => {
-      if (!signedRequest) {
-        throw new Error("AWS requests must go through signAwsRequest first");
-      }
+      if (!signedRequest) throw new Error("Must sign request before proxying");
       return `${signedRequest.protocol}//${signedRequest.hostname}`;
     },
     changeOrigin: true,
     selfHandleResponse: true,
     logger,
     on: {
-      proxyReq: createOnProxyReqHandler({
-        pipeline: [
-          applyQuotaLimits,
-          // Credentials are added by signAwsRequest preprocessor
-          languageFilter,
-          blockZoomerOrigins,
-          stripHeaders,
-          finalizeAwsRequest,
-        ],
-      }),
+      proxyReq: createOnProxyReqHandler({ pipeline: [finalizeSignedRequest] }),
       proxyRes: createOnProxyResHandler([awsResponseHandler]),
       error: handleProxyError,
     },
-  })
-);
+  }),
+});
 
 const awsRouter = Router();
 awsRouter.get("/v1/models", handleModelRequest);
@@ -156,7 +147,7 @@ awsRouter.post(
   ipLimiter,
   createPreprocessorMiddleware(
     { inApi: "anthropic", outApi: "anthropic", service: "aws" },
-    { afterTransform: [maybeReassignModel, signAwsRequest] }
+    { afterTransform: [maybeReassignModel] }
   ),
   awsProxy
 );
@@ -166,7 +157,7 @@ awsRouter.post(
   ipLimiter,
   createPreprocessorMiddleware(
     { inApi: "openai", outApi: "anthropic", service: "aws" },
-    { afterTransform: [maybeReassignModel, signAwsRequest] }
+    { afterTransform: [maybeReassignModel] }
   ),
   awsProxy
 );
@@ -181,16 +172,47 @@ awsRouter.post(
  */
 function maybeReassignModel(req: Request) {
   const model = req.body.model;
-  // User's client sent an AWS model already
-  if (model.includes("anthropic.claude")) return;
-  // User's client is sending Anthropic-style model names, check for v1
-  if (model.match(/^claude-v?1/)) {
-    req.body.model = "anthropic.claude-v1";
-  } else {
-    // User's client requested v2 or possibly some OpenAI model, default to v2
-    req.body.model = "anthropic.claude-v2";
+
+  // If client already specified an AWS Claude model ID, use it
+  if (model.includes("anthropic.claude")) {
+    return;
   }
-  // TODO: Handle claude-instant
+
+  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 [, , instant, , major, , minor] = match;
+
+  if (instant) {
+    req.body.model = "anthropic.claude-instant-v1";
+    return;
+  }
+
+  // There's only one v1 model
+  if (major === "1") {
+    req.body.model = "anthropic.claude-v1";
+    return;
+  }
+
+  // Try to map Anthropic API v2 models to AWS v2 models
+  if (major === "2") {
+    if (minor === "0") {
+      req.body.model = "anthropic.claude-v2";
+      return;
+    }
+    req.body.model = `anthropic.claude-v2:${LATEST_AWS_V2_MINOR_VERSION}`;
+    return;
+  }
+
+  // Fallback to latest v2 model
+  req.body.model = `anthropic.claude-v2:${LATEST_AWS_V2_MINOR_VERSION}`;
+  return;
 }
 
 export const aws = awsRouter;

src/proxy/azure.ts

@@ -0,0 +1,128 @@
+import { RequestHandler, Router } from "express";
+import { createProxyMiddleware } from "http-proxy-middleware";
+import { config } from "../config";
+import { keyPool } from "../shared/key-management";
+import {
+  ModelFamily,
+  AzureOpenAIModelFamily,
+  getAzureOpenAIModelFamily,
+} from "../shared/models";
+import { logger } from "../logger";
+import { KNOWN_OPENAI_MODELS } from "./openai";
+import { createQueueMiddleware } from "./queue";
+import { ipLimiter } from "./rate-limit";
+import { handleProxyError } from "./middleware/common";
+import {
+  addAzureKey,
+  createOnProxyReqHandler,
+  createPreprocessorMiddleware,
+  finalizeSignedRequest,
+} from "./middleware/request";
+import {
+  createOnProxyResHandler,
+  ProxyResHandlerWithBody,
+} from "./middleware/response";
+
+let modelsCache: any = null;
+let modelsCacheTime = 0;
+
+function getModelsResponse() {
+  if (new Date().getTime() - modelsCacheTime < 1000 * 60) {
+    return modelsCache;
+  }
+
+  let available = new Set<AzureOpenAIModelFamily>();
+  for (const key of keyPool.list()) {
+    if (key.isDisabled || key.service !== "azure") continue;
+    key.modelFamilies.forEach((family) =>
+      available.add(family as AzureOpenAIModelFamily)
+    );
+  }
+  const allowed = new Set<ModelFamily>(config.allowedModelFamilies);
+  available = new Set([...available].filter((x) => allowed.has(x)));
+
+  const models = KNOWN_OPENAI_MODELS.map((id) => ({
+    id,
+    object: "model",
+    created: new Date().getTime(),
+    owned_by: "azure",
+    permission: [
+      {
+        id: "modelperm-" + id,
+        object: "model_permission",
+        created: new Date().getTime(),
+        organization: "*",
+        group: null,
+        is_blocking: false,
+      },
+    ],
+    root: id,
+    parent: null,
+  })).filter((model) => available.has(getAzureOpenAIModelFamily(model.id)));
+
+  modelsCache = { object: "list", data: models };
+  modelsCacheTime = new Date().getTime();
+
+  return modelsCache;
+}
+
+const handleModelRequest: RequestHandler = (_req, res) => {
+  res.status(200).json(getModelsResponse());
+};
+
+const azureOpenaiResponseHandler: 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 ${host} for more information.`;
+  }
+
+  if (req.tokenizerInfo) {
+    body.proxy_tokenizer = req.tokenizerInfo;
+  }
+
+  res.status(200).json(body);
+};
+
+const azureOpenAIProxy = createQueueMiddleware({
+  beforeProxy: addAzureKey,
+  proxyMiddleware: createProxyMiddleware({
+    target: "will be set by router",
+    router: (req) => {
+      if (!req.signedRequest) throw new Error("signedRequest not set");
+      const { hostname, path } = req.signedRequest;
+      return `https://${hostname}${path}`;
+    },
+    changeOrigin: true,
+    selfHandleResponse: true,
+    logger,
+    on: {
+      proxyReq: createOnProxyReqHandler({ pipeline: [finalizeSignedRequest] }),
+      proxyRes: createOnProxyResHandler([azureOpenaiResponseHandler]),
+      error: handleProxyError,
+    },
+  }),
+});
+
+const azureOpenAIRouter = Router();
+azureOpenAIRouter.get("/v1/models", handleModelRequest);
+azureOpenAIRouter.post(
+  "/v1/chat/completions",
+  ipLimiter,
+  createPreprocessorMiddleware({
+    inApi: "openai",
+    outApi: "openai",
+    service: "azure",
+  }),
+  azureOpenAIProxy
+);
+
+export const azure = azureOpenAIRouter;

src/proxy/gatekeeper.ts

@@ -46,19 +46,22 @@ export const gatekeeper: RequestHandler = (req, res, next) => {
   }
 
   if (GATEKEEPER === "user_token" && token) {
-    const user = authenticate(token, req.ip);
-    if (user) {
-      req.user = user;
-      return next();
-    } else {
-      const maybeBannedUser = getUser(token);
-      if (maybeBannedUser?.disabledAt) {
+    const { user, result } = authenticate(token, req.ip);
+
+    switch (result) {
+      case "success":
+        req.user = user;
+        return next();
+      case "limited":
         return res.status(403).json({
-          error: `Forbidden: ${
-            maybeBannedUser.disabledReason || "Token disabled"
-          }`,
+          error: `Forbidden: no more IPs can authenticate with this token`,
         });
-      }
+      case "disabled":
+        const bannedUser = getUser(token);
+        if (bannedUser?.disabledAt) {
+          const reason = bannedUser.disabledReason || "Token disabled";
+          return res.status(403).json({ error: `Forbidden: ${reason}` });
+        }
     }
   }
 

src/proxy/google-ai.ts

@@ -0,0 +1,140 @@
+import { Request, RequestHandler, Router } from "express";
+import { createProxyMiddleware } from "http-proxy-middleware";
+import { v4 } from "uuid";
+import { config } from "../config";
+import { logger } from "../logger";
+import { createQueueMiddleware } from "./queue";
+import { ipLimiter } from "./rate-limit";
+import { handleProxyError } from "./middleware/common";
+import {
+  createOnProxyReqHandler,
+  createPreprocessorMiddleware,
+  finalizeSignedRequest,
+  forceModel,
+} from "./middleware/request";
+import {
+  createOnProxyResHandler,
+  ProxyResHandlerWithBody,
+} from "./middleware/response";
+import { addGoogleAIKey } from "./middleware/request/preprocessors/add-google-ai-key";
+
+let modelsCache: any = null;
+let modelsCacheTime = 0;
+
+const getModelsResponse = () => {
+  if (new Date().getTime() - modelsCacheTime < 1000 * 60) {
+    return modelsCache;
+  }
+
+  if (!config.googleAIKey) return { object: "list", data: [] };
+
+  const googleAIVariants = ["gemini-pro"];
+
+  const models = googleAIVariants.map((id) => ({
+    id,
+    object: "model",
+    created: new Date().getTime(),
+    owned_by: "google",
+    permission: [],
+    root: "google",
+    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 googleAIResponseHandler: 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 ${host} for more information.`;
+  }
+
+  if (req.inboundApi === "openai") {
+    req.log.info("Transforming Google AI response to OpenAI format");
+    body = transformGoogleAIResponse(body, req);
+  }
+
+  if (req.tokenizerInfo) {
+    body.proxy_tokenizer = req.tokenizerInfo;
+  }
+
+  res.status(200).json(body);
+};
+
+function transformGoogleAIResponse(
+  resBody: Record<string, any>,
+  req: Request
+): Record<string, any> {
+  const totalTokens = (req.promptTokens ?? 0) + (req.outputTokens ?? 0);
+  const parts = resBody.candidates[0].content?.parts ?? [{ text: "" }];
+  const content = parts[0].text.replace(/^(.{0,50}?): /, () => "");
+  return {
+    id: "goo-" + v4(),
+    object: "chat.completion",
+    created: Date.now(),
+    model: req.body.model,
+    usage: {
+      prompt_tokens: req.promptTokens,
+      completion_tokens: req.outputTokens,
+      total_tokens: totalTokens,
+    },
+    choices: [
+      {
+        message: { role: "assistant", content },
+        finish_reason: resBody.candidates[0].finishReason,
+        index: 0,
+      },
+    ],
+  };
+}
+
+const googleAIProxy = createQueueMiddleware({
+  beforeProxy: addGoogleAIKey,
+  proxyMiddleware: createProxyMiddleware({
+    target: "bad-target-will-be-rewritten",
+    router: ({ signedRequest }) => {
+      const { protocol, hostname, path } = signedRequest;
+      return `${protocol}//${hostname}${path}`;
+    },
+    changeOrigin: true,
+    selfHandleResponse: true,
+    logger,
+    on: {
+      proxyReq: createOnProxyReqHandler({ pipeline: [finalizeSignedRequest] }),
+      proxyRes: createOnProxyResHandler([googleAIResponseHandler]),
+      error: handleProxyError,
+    },
+  }),
+});
+
+const googleAIRouter = Router();
+googleAIRouter.get("/v1/models", handleModelRequest);
+// 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")] }
+  ),
+  googleAIProxy
+);
+
+export const googleAI = googleAIRouter;

src/proxy/middleware/common.ts

@@ -2,18 +2,17 @@ import { Request, Response } from "express";
 import httpProxy from "http-proxy";
 import { ZodError } from "zod";
 import { generateErrorMessage } from "zod-error";
-import { buildFakeSse } from "../../shared/streaming";
+import { makeCompletionSSE } from "../../shared/streaming";
 import { assertNever } from "../../shared/utils";
-import { QuotaExceededError } from "./request/apply-quota-limits";
+import { QuotaExceededError } from "./request/preprocessors/apply-quota-limits";
 
 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";
 
-/** Returns true if we're making a request to a completion endpoint. */
-export function isCompletionRequest(req: Request) {
-  // 99% sure this function is not needed anymore
+export function isTextGenerationRequest(req: Request) {
   return (
     req.method === "POST" &&
     [
@@ -24,6 +23,13 @@ export function isCompletionRequest(req: Request) {
   );
 }
 
+export function isImageGenerationRequest(req: Request) {
+  return (
+    req.method === "POST" &&
+    req.path.startsWith(OPENAI_IMAGE_COMPLETION_ENDPOINT)
+  );
+}
+
 export function isEmbeddingsRequest(req: Request) {
   return (
     req.method === "POST" && req.path.startsWith(OPENAI_EMBEDDINGS_ENDPOINT)
@@ -34,11 +40,13 @@ export function writeErrorResponse(
   req: Request,
   res: Response,
   statusCode: number,
+  statusMessage: string,
   errorPayload: Record<string, any>
 ) {
-  const errorSource = errorPayload.error?.type?.startsWith("proxy")
-    ? "proxy"
-    : "upstream";
+  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.`;
 
   // 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.
@@ -46,15 +54,20 @@ export function writeErrorResponse(
     res.headersSent ||
     String(res.getHeader("content-type")).startsWith("text/event-stream")
   ) {
-    const errorTitle = `${errorSource} error (${statusCode})`;
-    const errorContent = JSON.stringify(errorPayload, null, 2);
-    const msg = buildFakeSse(errorTitle, errorContent, req);
-    res.write(msg);
+    const event = makeCompletionSSE({
+      format: req.inboundApi,
+      title: `Proxy error (HTTP ${statusCode} ${statusMessage})`,
+      message: `${msg} Further technical 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.debug && errorPayload.error) {
-      errorPayload.error.proxy_tokenizer_debug_info = req.debug;
+    if (req.tokenizerInfo && typeof errorPayload.error === "object") {
+      errorPayload.error.proxy_tokenizer = req.tokenizerInfo;
     }
     res.status(statusCode).json(errorPayload);
   }
@@ -71,8 +84,9 @@ export const classifyErrorAndSend = (
   res: Response
 ) => {
   try {
-    const { status, userMessage, ...errorDetails } = classifyError(err);
-    writeErrorResponse(req, res, status, {
+    const { statusCode, statusMessage, userMessage, ...errorDetails } =
+      classifyError(err);
+    writeErrorResponse(req, res, statusCode, statusMessage, {
       error: { message: userMessage, ...errorDetails },
     });
   } catch (error) {
@@ -82,15 +96,18 @@ export const classifyErrorAndSend = (
 
 function classifyError(err: Error): {
   /** HTTP status code returned to the client. */
-  status: number;
+  statusCode: number;
+  /** HTTP status message returned to the client. */
+  statusMessage: string;
   /** Message displayed to the user. */
   userMessage: string;
   /** Short error type, e.g. "proxy_validation_error". */
   type: string;
 } & Record<string, any> {
   const defaultError = {
-    status: 500,
-    userMessage: `Reverse proxy encountered an unexpected error. (${err.message})`,
+    statusCode: 500,
+    statusMessage: "Internal Server Error",
+    userMessage: `Reverse proxy error: ${err.message}`,
     type: "proxy_internal_error",
     stack: err.stack,
   };
@@ -103,22 +120,36 @@ function classifyError(err: Error): {
         code: { enabled: false },
         maxErrors: 3,
         transform: ({ issue, ...rest }) => {
-          return `At '${rest.pathComponent}', ${issue.message}`;
+          return `At '${rest.pathComponent}': ${issue.message}`;
         },
       });
-      return { status: 400, userMessage, type: "proxy_validation_error" };
-    case "ForbiddenError":
+      return {
+        statusCode: 400,
+        statusMessage: "Bad Request",
+        userMessage,
+        type: "proxy_validation_error",
+      };
+    case "ZoomerForbiddenError":
       // Mimics a ban notice from OpenAI, thrown when blockZoomerOrigins blocks
       // a request.
       return {
-        status: 403,
+        statusCode: 403,
+        statusMessage: "Forbidden",
         userMessage: `Your account has been disabled for violating our terms of service.`,
         type: "organization_account_disabled",
         code: "policy_violation",
       };
+    case "ForbiddenError":
+      return {
+        statusCode: 403,
+        statusMessage: "Forbidden",
+        userMessage: `Request is not allowed. (${err.message})`,
+        type: "proxy_forbidden",
+      };
     case "QuotaExceededError":
       return {
-        status: 429,
+        statusCode: 429,
+        statusMessage: "Too Many Requests",
         userMessage: `You've exceeded your token quota for this model type.`,
         type: "proxy_quota_exceeded",
         info: (err as QuotaExceededError).quotaInfo,
@@ -128,21 +159,24 @@ function classifyError(err: Error): {
         switch (err.code) {
           case "ENOTFOUND":
             return {
-              status: 502,
+              statusCode: 502,
+              statusMessage: "Bad Gateway",
               userMessage: `Reverse proxy encountered a DNS error while trying to connect to the upstream service.`,
               type: "proxy_network_error",
               code: err.code,
             };
           case "ECONNREFUSED":
             return {
-              status: 502,
+              statusCode: 502,
+              statusMessage: "Bad Gateway",
               userMessage: `Reverse proxy couldn't connect to the upstream service.`,
               type: "proxy_network_error",
               code: err.code,
             };
           case "ECONNRESET":
             return {
-              status: 504,
+              statusCode: 504,
+              statusMessage: "Gateway Timeout",
               userMessage: `Reverse proxy timed out while waiting for the upstream service to respond.`,
               type: "proxy_network_error",
               code: err.code,
@@ -159,6 +193,7 @@ export function getCompletionFromBody(req: Request, body: Record<string, any>) {
   const format = req.outboundApi;
   switch (format) {
     case "openai":
+    case "mistral-ai":
       return body.choices[0].message.content;
     case "openai-text":
       return body.choices[0].text;
@@ -171,8 +206,13 @@ export function getCompletionFromBody(req: Request, body: Record<string, any>) {
         return "";
       }
       return body.completion.trim();
-    case "google-palm":
-      return body.candidates[0].output;
+    case "google-ai":
+      if ("choices" in body) {
+        return body.choices[0].message.content;
+      }
+      return body.candidates[0].content.parts[0].text;
+    case "openai-image":
+      return body.data?.map((item: any) => item.url).join("\n");
     default:
       assertNever(format);
   }
@@ -183,11 +223,14 @@ export function getModelFromBody(req: Request, body: Record<string, any>) {
   switch (format) {
     case "openai":
     case "openai-text":
+    case "mistral-ai":
       return body.model;
+    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-palm":
+    case "google-ai":
       // Google doesn't confirm the model in the response.
       return req.body.model;
     default:

src/proxy/middleware/request/apply-quota-limits.ts

@@ -1,30 +0,0 @@
-import { hasAvailableQuota } from "../../../shared/users/user-store";
-import { isCompletionRequest } from "../common";
-import { ProxyRequestMiddleware } from ".";
-
-export class QuotaExceededError extends Error {
-  public quotaInfo: any;
-  constructor(message: string, quotaInfo: any) {
-    super(message);
-    this.name = "QuotaExceededError";
-    this.quotaInfo = quotaInfo;
-  }
-}
-
-export const applyQuotaLimits: ProxyRequestMiddleware = (_proxyReq, req) => {
-  if (!isCompletionRequest(req) || !req.user) {
-    return;
-  }
-
-  const requestedTokens = (req.promptTokens ?? 0) + (req.outputTokens ?? 0);
-  if (!hasAvailableQuota(req.user.token, req.body.model, requestedTokens)) {
-    throw new QuotaExceededError(
-      "You have exceeded your proxy token quota for this model.",
-      {
-        quota: req.user.tokenLimits,
-        used: req.user.tokenCounts,
-        requested: requestedTokens,
-      }
-    );
-  }
-};

src/proxy/middleware/request/index.ts

@@ -2,29 +2,30 @@ import type { Request } from "express";
 import type { ClientRequest } from "http";
 import type { ProxyReqCallback } from "http-proxy";
 
-export { createOnProxyReqHandler } from "./rewrite";
+export { createOnProxyReqHandler } from "./onproxyreq-factory";
 export {
   createPreprocessorMiddleware,
   createEmbeddingsPreprocessorMiddleware,
-} from "./preprocess";
+} from "./preprocessor-factory";
 
 // Express middleware (runs before http-proxy-middleware, can be async)
-export { applyQuotaLimits } from "./apply-quota-limits";
-export { validateContextSize } from "./validate-context-size";
-export { countPromptTokens } from "./count-prompt-tokens";
-export { setApiFormat } from "./set-api-format";
-export { signAwsRequest } from "./sign-aws-request";
-export { transformOutboundPayload } from "./transform-outbound-payload";
+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 { transformOutboundPayload } from "./preprocessors/transform-outbound-payload";
 
-// HPM middleware (runs on onProxyReq, cannot be async)
-export { addKey, addKeyForEmbeddingsRequest } from "./add-key";
-export { addAnthropicPreamble } from "./add-anthropic-preamble";
-export { blockZoomerOrigins } from "./block-zoomer-origins";
-export { finalizeBody } from "./finalize-body";
-export { finalizeAwsRequest } from "./finalize-aws-request";
-export { languageFilter } from "./language-filter";
-export { limitCompletions } from "./limit-completions";
-export { stripHeaders } from "./strip-headers";
+// http-proxy-middleware callbacks (runs on onProxyReq, cannot be async)
+export { addKey, addKeyForEmbeddingsRequest } from "./onproxyreq/add-key";
+export { addAnthropicPreamble } from "./onproxyreq/add-anthropic-preamble";
+export { blockZoomerOrigins } from "./onproxyreq/block-zoomer-origins";
+export { checkModelFamily } from "./onproxyreq/check-model-family";
+export { finalizeBody } from "./onproxyreq/finalize-body";
+export { finalizeSignedRequest } from "./onproxyreq/finalize-signed-request";
+export { stripHeaders } from "./onproxyreq/strip-headers";
 
 /**
  * Middleware that runs prior to the request being handled by http-proxy-
@@ -43,7 +44,7 @@ export { stripHeaders } from "./strip-headers";
 export type RequestPreprocessor = (req: Request) => void | Promise<void>;
 
 /**
- * Middleware that runs immediately before the request is sent to the API in
+ * Callbacks that run immediately before the request is sent to the API in
  * response to http-proxy-middleware's `proxyReq` event.
  *
  * Async functions cannot be used here as HPM's event emitter is not async and
@@ -53,7 +54,7 @@ export type RequestPreprocessor = (req: Request) => void | Promise<void>;
  * first attempt is rate limited and the request is automatically retried by the
  * request queue middleware.
  */
-export type ProxyRequestMiddleware = ProxyReqCallback<ClientRequest, Request>;
+export type HPMRequestCallback = ProxyReqCallback<ClientRequest, Request>;
 
 export const forceModel = (model: string) => (req: Request) =>
   void (req.body.model = model);

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

@@ -1,56 +0,0 @@
-import { Request } from "express";
-import { config } from "../../../config";
-import { logger } from "../../../logger";
-import { assertNever } from "../../../shared/utils";
-import { isCompletionRequest } from "../common";
-import { ProxyRequestMiddleware } from ".";
-
-const DISALLOWED_REGEX =
-  /[\u2E80-\u2E99\u2E9B-\u2EF3\u2F00-\u2FD5\u3005\u3007\u3021-\u3029\u3038-\u303B\u3400-\u4DB5\u4E00-\u9FD5\uF900-\uFA6D\uFA70-\uFAD9]/;
-
-// Our shitty free-tier VMs will fall over if we test every single character in
-// each 15k character request ten times a second. So we'll just sample 20% of
-// the characters and hope that's enough.
-const containsDisallowedCharacters = (text: string) => {
-  const sampleSize = Math.ceil(text.length * 0.2);
-  const sample = text
-    .split("")
-    .sort(() => 0.5 - Math.random())
-    .slice(0, sampleSize)
-    .join("");
-  return DISALLOWED_REGEX.test(sample);
-};
-
-/** Block requests containing too many disallowed characters. */
-export const languageFilter: ProxyRequestMiddleware = (_proxyReq, req) => {
-  if (!config.rejectDisallowed) {
-    return;
-  }
-
-  if (isCompletionRequest(req)) {
-    const combinedText = getPromptFromRequest(req);
-    if (containsDisallowedCharacters(combinedText)) {
-      logger.warn(`Blocked request containing bad characters`);
-      _proxyReq.destroy(new Error(config.rejectMessage));
-    }
-  }
-};
-
-function getPromptFromRequest(req: Request) {
-  const service = req.outboundApi;
-  const body = req.body;
-  switch (service) {
-    case "anthropic":
-      return body.prompt;
-    case "openai":
-      return body.messages
-        .map((m: { content: string }) => m.content)
-        .join("\n");
-    case "openai-text":
-      return body.prompt;
-    case "google-palm":
-      return body.prompt.text;
-    default:
-      assertNever(service);
-  }
-}

src/proxy/middleware/request/limit-completions.ts

@@ -1,16 +0,0 @@
-import { isCompletionRequest } from "../common";
-import { ProxyRequestMiddleware } from ".";
-
-/**
- * Don't allow multiple completions to be requested to prevent abuse.
- * OpenAI-only, Anthropic provides no such parameter.
- **/
-export const limitCompletions: ProxyRequestMiddleware = (_proxyReq, req) => {
-  if (isCompletionRequest(req) && req.outboundApi === "openai") {
-    const originalN = req.body?.n || 1;
-    req.body.n = 1;
-    if (originalN !== req.body.n) {
-      req.log.warn(`Limiting completion choices from ${originalN} to 1`);
-    }
-  }
-};

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

@@ -0,0 +1,45 @@
+import {
+  applyQuotaLimits,
+  blockZoomerOrigins,
+  checkModelFamily,
+  HPMRequestCallback,
+  stripHeaders,
+} from "./index";
+
+type ProxyReqHandlerFactoryOptions = { pipeline: HPMRequestCallback[] };
+
+/**
+ * Returns an http-proxy-middleware request handler that runs the given set of
+ * onProxyReq callback functions in sequence.
+ *
+ * These will run each time a request is proxied, including on automatic retries
+ * by the queue after encountering a rate limit.
+ */
+export const createOnProxyReqHandler = ({
+  pipeline,
+}: ProxyReqHandlerFactoryOptions): HPMRequestCallback => {
+  const callbackPipeline = [
+    checkModelFamily,
+    applyQuotaLimits,
+    blockZoomerOrigins,
+    stripHeaders,
+    ...pipeline,
+  ];
+  return (proxyReq, req, res, options) => {
+    // The streaming flag must be set before any other onProxyReq handler runs,
+    // as it may influence the behavior of subsequent handlers.
+    // Image generation requests can't be streamed.
+    // TODO: this flag is set in too many places
+    req.isStreaming =
+      req.isStreaming || req.body.stream === true || req.body.stream === "true";
+    req.body.stream = req.isStreaming;
+
+    try {
+      for (const fn of callbackPipeline) {
+        fn(proxyReq, req, res, options);
+      }
+    } catch (error) {
+      proxyReq.destroy(error);
+    }
+  };
+};

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

@@ -1,17 +1,17 @@
-import { AnthropicKey, Key } from "../../../shared/key-management";
-import { isCompletionRequest } from "../common";
-import { ProxyRequestMiddleware } from ".";
+import { AnthropicKey, Key } from "../../../../shared/key-management";
+import { isTextGenerationRequest } from "../../common";
+import { HPMRequestCallback } from "../index";
 
 /**
  * Some keys require the prompt to start with `\n\nHuman:`. There is no way to
  * know this without trying to send the request and seeing if it fails. If a
  * key is marked as requiring a preamble, it will be added here.
  */
-export const addAnthropicPreamble: ProxyRequestMiddleware = (
+export const addAnthropicPreamble: HPMRequestCallback = (
   _proxyReq,
   req
 ) => {
-  if (!isCompletionRequest(req) || req.key?.service !== "anthropic") {
+  if (!isTextGenerationRequest(req) || req.key?.service !== "anthropic") {
     return;
   }
 

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

@@ -1,24 +1,12 @@
-import { Key, OpenAIKey, keyPool } from "../../../shared/key-management";
-import { isCompletionRequest, isEmbeddingsRequest } from "../common";
-import { ProxyRequestMiddleware } from ".";
-import { assertNever } from "../../../shared/utils";
+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: ProxyRequestMiddleware = (proxyReq, req) => {
+export const addKey: HPMRequestCallback = (proxyReq, req) => {
   let assignedKey: Key;
 
-  if (!isCompletionRequest(req)) {
-    // Horrible, horrible hack to stop the proxy from complaining about clients
-    // not sending a model when they are requesting the list of models (which
-    // requires a key, but obviously not a model).
-
-    // I don't think this is needed anymore since models requests are no longer
-    // proxied to the upstream API. Everything going through this is either a
-    // completion request or a special case like OpenAI embeddings.
-    req.log.warn({ path: req.path }, "addKey called on non-completion request");
-    req.body.model = "gpt-3.5-turbo";
-  }
-
   if (!req.inboundApi || !req.outboundApi) {
     const err = new Error(
       "Request API format missing. Did you forget to add the request preprocessor to your router?"
@@ -34,10 +22,6 @@ export const addKey: ProxyRequestMiddleware = (proxyReq, req) => {
     throw new Error("You must specify a model with your request.");
   }
 
-  // TODO: use separate middleware to deal with stream flags
-  req.isStreaming = req.body.stream === true || req.body.stream === "true";
-  req.body.stream = req.isStreaming;
-
   if (req.inboundApi === req.outboundApi) {
     assignedKey = keyPool.get(req.body.model);
   } else {
@@ -47,10 +31,6 @@ export const addKey: ProxyRequestMiddleware = (proxyReq, req) => {
       case "anthropic":
         assignedKey = keyPool.get("claude-v1");
         break;
-      case "google-palm":
-        assignedKey = keyPool.get("text-bison-001");
-        delete req.body.stream;
-        break;
       case "openai-text":
         assignedKey = keyPool.get("gpt-3.5-turbo-instruct");
         break;
@@ -58,6 +38,13 @@ export const addKey: ProxyRequestMiddleware = (proxyReq, req) => {
         throw new Error(
           "OpenAI Chat as an API translation target is not supported"
         );
+      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);
     }
@@ -84,19 +71,16 @@ export const addKey: ProxyRequestMiddleware = (proxyReq, req) => {
       if (key.organizationId) {
         proxyReq.setHeader("OpenAI-Organization", key.organizationId);
       }
+    case "mistral-ai":
       proxyReq.setHeader("Authorization", `Bearer ${assignedKey.key}`);
       break;
-    case "google-palm":
-      const originalPath = proxyReq.path;
-      proxyReq.path = originalPath.replace(
-        /(\?.*)?$/,
-        `?key=${assignedKey.key}`
-      );
+    case "azure":
+      const azureKey = assignedKey.key;
+      proxyReq.setHeader("api-key", azureKey);
       break;
     case "aws":
-      throw new Error(
-        "add-key should not be used for AWS security credentials. Use sign-aws-request instead."
-      );
+    case "google-ai":
+      throw new Error("add-key should not be used for this service.");
     default:
       assertNever(assignedKey.service);
   }
@@ -106,7 +90,7 @@ export const addKey: ProxyRequestMiddleware = (proxyReq, req) => {
  * Special case for embeddings requests which don't go through the normal
  * request pipeline.
  */
-export const addKeyForEmbeddingsRequest: ProxyRequestMiddleware = (
+export const addKeyForEmbeddingsRequest: HPMRequestCallback = (
   proxyReq,
   req
 ) => {
@@ -120,7 +104,7 @@ export const addKeyForEmbeddingsRequest: ProxyRequestMiddleware = (
     throw new Error("Embeddings requests must be from OpenAI");
   }
 
-  req.body = { input: req.body.input, model: "text-embedding-ada-002" }
+  req.body = { input: req.body.input, model: "text-embedding-ada-002" };
 
   const key = keyPool.get("text-embedding-ada-002") as OpenAIKey;
 

src/proxy/middleware/request/onproxyreq/block-zoomer-origins.ts

@@ -1,12 +1,11 @@
-import { isCompletionRequest } from "../common";
-import { ProxyRequestMiddleware } from ".";
+import { HPMRequestCallback } from "../index";
 
 const DISALLOWED_ORIGIN_SUBSTRINGS = "janitorai.com,janitor.ai".split(",");
 
-class ForbiddenError extends Error {
+class ZoomerForbiddenError extends Error {
   constructor(message: string) {
     super(message);
-    this.name = "ForbiddenError";
+    this.name = "ZoomerForbiddenError";
   }
 }
 
@@ -14,11 +13,7 @@ class ForbiddenError extends Error {
  * Blocks requests from Janitor AI users with a fake, scary error message so I
  * stop getting emails asking for tech support.
  */
-export const blockZoomerOrigins: ProxyRequestMiddleware = (_proxyReq, req) => {
-  if (!isCompletionRequest(req)) {
-    return;
-  }
-
+export const blockZoomerOrigins: HPMRequestCallback = (_proxyReq, req) => {
   const origin = req.headers.origin || req.headers.referer;
   if (origin && DISALLOWED_ORIGIN_SUBSTRINGS.some((s) => origin.includes(s))) {
     // Venus-derivatives send a test prompt to check if the proxy is working.
@@ -27,7 +22,7 @@ export const blockZoomerOrigins: ProxyRequestMiddleware = (_proxyReq, req) => {
       return;
     }
 
-    throw new ForbiddenError(
+    throw new ZoomerForbiddenError(
       `Your access was terminated due to violation of our policies, please check your email for more information. If you believe this is in error and would like to appeal, please contact us through our help center at help.openai.com.`
     );
   }

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

@@ -0,0 +1,14 @@
+import { HPMRequestCallback } from "../index";
+import { config } from "../../../../config";
+import { ForbiddenError } from "../../../../shared/errors";
+import { getModelFamilyForRequest } from "../../../../shared/models";
+
+/**
+ * Ensures the selected model family is enabled by the proxy configuration.
+ **/
+export const checkModelFamily: HPMRequestCallback = (_proxyReq, req, res) => {
+  const family = getModelFamilyForRequest(req);
+  if (!config.allowedModelFamilies.includes(family)) {
+    throw new ForbiddenError(`Model family '${family}' is not enabled on this proxy`);
+  }
+};

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

@@ -1,9 +1,14 @@
 import { fixRequestBody } from "http-proxy-middleware";
-import type { ProxyRequestMiddleware } from ".";
+import type { HPMRequestCallback } from "../index";
 
 /** Finalize the rewritten request body. Must be the last rewriter. */
-export const finalizeBody: ProxyRequestMiddleware = (proxyReq, req) => {
+export const finalizeBody: HPMRequestCallback = (proxyReq, req) => {
   if (["POST", "PUT", "PATCH"].includes(req.method ?? "") && req.body) {
+    // For image generation requests, remove stream flag.
+    if (req.outboundApi === "openai-image") {
+      delete req.body.stream;
+    }
+
     const updatedBody = JSON.stringify(req.body);
     proxyReq.setHeader("Content-Length", Buffer.byteLength(updatedBody));
     (req as any).rawBody = Buffer.from(updatedBody);

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

@@ -1,11 +1,11 @@
-import type { ProxyRequestMiddleware } from ".";
+import type { HPMRequestCallback } from "../index";
 
 /**
- * For AWS 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.
+ * For AWS/Azure/Google requests, the body is signed earlier in the request
+ * pipeline, before the proxy middleware. This function just assigns the path
+ * and headers to the proxy request.
  */
-export const finalizeAwsRequest: ProxyRequestMiddleware = (proxyReq, req) => {
+export const finalizeSignedRequest: HPMRequestCallback = (proxyReq, req) => {
   if (!req.signedRequest) {
     throw new Error("Expected req.signedRequest to be set");
   }

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

@@ -1,10 +1,10 @@
-import { ProxyRequestMiddleware } from ".";
+import { HPMRequestCallback } from "../index";
 
 /**
  * Removes origin and referer headers before sending the request to the API for
  * privacy reasons.
  **/
-export const stripHeaders: ProxyRequestMiddleware = (proxyReq) => {
+export const stripHeaders: HPMRequestCallback = (proxyReq) => {
   proxyReq.setHeader("origin", "");
   proxyReq.setHeader("referer", "");
 

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

@@ -7,7 +7,9 @@ import {
   countPromptTokens,
   setApiFormat,
   transformOutboundPayload,
+  languageFilter,
 } from ".";
+import { ZodIssue } from "zod";
 
 type RequestPreprocessorOptions = {
   /**
@@ -27,6 +29,14 @@ type RequestPreprocessorOptions = {
 /**
  * Returns a middleware function that processes the request body into the given
  * API format, and then sequentially runs the given additional preprocessors.
+ *
+ * These run first in the request lifecycle, a single time per request before it
+ * is added to the request queue. They aren't run again if the request is
+ * re-attempted after a rate limit.
+ *
+ * To run a preprocessor on every re-attempt, pass it to createQueueMiddleware.
+ * It will run after these preprocessors, but before the request is sent to
+ * http-proxy-middleware.
  */
 export const createPreprocessorMiddleware = (
   apiFormat: Parameters<typeof setApiFormat>[0],
@@ -37,6 +47,7 @@ export const createPreprocessorMiddleware = (
     ...(beforeTransform ?? []),
     transformOutboundPayload,
     countPromptTokens,
+    languageFilter,
     ...(afterTransform ?? []),
     validateContextSize,
   ];
@@ -66,14 +77,25 @@ async function executePreprocessors(
     }
     next();
   } catch (error) {
-    req.log.error(error, "Error while executing request preprocessor");
+    if (error.constructor.name === "ZodError") {
+      const msg = error?.issues
+        ?.map((issue: ZodIssue) => issue.message)
+        .join("; ");
+      req.log.info(msg, "Prompt validation failed.");
+    } else {
+      req.log.error(error, "Error while executing request preprocessor");
+    }
 
     // If the requested has opted into streaming, the client probably won't
     // handle a non-eventstream response, but we haven't initialized the SSE
     // stream yet as that is typically done later by the request queue. We'll
     // do that here and then call classifyErrorAndSend to use the streaming
     // error handler.
-    initializeSseStream(res)
+    const { stream } = req.body;
+    const isStreaming = stream === "true" || stream === true;
+    if (isStreaming && !res.headersSent) {
+      initializeSseStream(res);
+    }
     classifyErrorAndSend(error as Error, req, res);
   }
 }

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

@@ -0,0 +1,50 @@
+import { AzureOpenAIKey, keyPool } from "../../../../shared/key-management";
+import { RequestPreprocessor } from "../index";
+
+export const addAzureKey: RequestPreprocessor = (req) => {
+  const apisValid = req.inboundApi === "openai" && req.outboundApi === "openai";
+  const serviceValid = req.service === "azure";
+  if (!apisValid || !serviceValid) {
+    throw new Error("addAzureKey called on invalid request");
+  }
+
+  if (!req.body?.model) {
+    throw new Error("You must specify a model with your request.");
+  }
+
+  const model = req.body.model.startsWith("azure-")
+    ? req.body.model
+    : `azure-${req.body.model}`;
+
+  req.key = keyPool.get(model);
+  req.body.model = model;
+
+  req.log.info(
+    { key: req.key.hash, model },
+    "Assigned Azure OpenAI key to request"
+  );
+
+  const cred = req.key as AzureOpenAIKey;
+  const { resourceName, deploymentId, apiKey } = getCredentialsFromKey(cred);
+
+  req.signedRequest = {
+    method: "POST",
+    protocol: "https:",
+    hostname: `${resourceName}.openai.azure.com`,
+    path: `/openai/deployments/${deploymentId}/chat/completions?api-version=2023-09-01-preview`,
+    headers: {
+      ["host"]: `${resourceName}.openai.azure.com`,
+      ["content-type"]: "application/json",
+      ["api-key"]: apiKey,
+    },
+    body: JSON.stringify(req.body),
+  };
+};
+
+function getCredentialsFromKey(key: AzureOpenAIKey) {
+  const [resourceName, deploymentId, apiKey] = key.key.split(":");
+  if (!resourceName || !deploymentId || !apiKey) {
+    throw new Error("Assigned Azure OpenAI key is not in the correct format.");
+  }
+  return { resourceName, deploymentId, apiKey };
+}

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

@@ -0,0 +1,40 @@
+import { keyPool } from "../../../../shared/key-management";
+import { RequestPreprocessor } from "../index";
+
+export const addGoogleAIKey: RequestPreprocessor = (req) => {
+  const apisValid = req.inboundApi === "openai" && req.outboundApi === "google-ai";
+  const serviceValid = req.service === "google-ai";
+  if (!apisValid || !serviceValid) {
+    throw new Error("addGoogleAIKey called on invalid request");
+  }
+
+  if (!req.body?.model) {
+    throw new Error("You must specify a model with your request.");
+  }
+
+  const model = req.body.model;
+  req.key = keyPool.get(model);
+
+  req.log.info(
+    { key: req.key.hash, model },
+    "Assigned Google AI API key to request"
+  );
+
+  // https://generativelanguage.googleapis.com/v1beta/models/$MODEL_ID:generateContent?key=$API_KEY
+  // https://generativelanguage.googleapis.com/v1beta/models/$MODEL_ID:streamGenerateContent?key=${API_KEY}
+
+  req.isStreaming = req.isStreaming || req.body.stream;
+  delete req.body.stream;
+
+  req.signedRequest = {
+    method: "POST",
+    protocol: "https:",
+    hostname: "generativelanguage.googleapis.com",
+    path: `/v1beta/models/${model}:${req.isStreaming ? "streamGenerateContent" : "generateContent"}?key=${req.key.key}`,
+    headers: {
+      ["host"]: `generativelanguage.googleapis.com`,
+      ["content-type"]: "application/json",
+    },
+    body: JSON.stringify(req.body),
+  };
+};

src/proxy/middleware/request/preprocessors/apply-quota-limits.ts

@@ -0,0 +1,37 @@
+import { hasAvailableQuota } from "../../../../shared/users/user-store";
+import { isImageGenerationRequest, isTextGenerationRequest } from "../../common";
+import { HPMRequestCallback } from "../index";
+
+export class QuotaExceededError extends Error {
+  public quotaInfo: any;
+  constructor(message: string, quotaInfo: any) {
+    super(message);
+    this.name = "QuotaExceededError";
+    this.quotaInfo = quotaInfo;
+  }
+}
+
+export const applyQuotaLimits: HPMRequestCallback = (_proxyReq, req) => {
+  const subjectToQuota =
+    isTextGenerationRequest(req) || isImageGenerationRequest(req);
+  if (!subjectToQuota || !req.user) return;
+
+  const requestedTokens = (req.promptTokens ?? 0) + (req.outputTokens ?? 0);
+  if (
+    !hasAvailableQuota({
+      userToken: req.user.token,
+      model: req.body.model,
+      api: req.outboundApi,
+      requested: requestedTokens,
+    })
+  ) {
+    throw new QuotaExceededError(
+      "You have exceeded your proxy token quota for this model.",
+      {
+        quota: req.user.tokenLimits,
+        used: req.user.tokenCounts,
+        requested: requestedTokens,
+      }
+    );
+  }
+};

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

@@ -1,6 +1,11 @@
-import { RequestPreprocessor } from "./index";
-import { countTokens, OpenAIPromptMessage } from "../../../shared/tokenization";
-import { assertNever } from "../../../shared/utils";
+import { RequestPreprocessor } from "../index";
+import { countTokens } from "../../../../shared/tokenization";
+import { assertNever } from "../../../../shared/utils";
+import type {
+  GoogleAIChatMessage,
+  MistralAIChatMessage,
+  OpenAIChatMessage,
+} from "./transform-outbound-payload";
 
 /**
  * Given a request with an already-transformed body, counts the number of
@@ -13,7 +18,7 @@ export const countPromptTokens: RequestPreprocessor = async (req) => {
   switch (service) {
     case "openai": {
       req.outputTokens = req.body.max_tokens;
-      const prompt: OpenAIPromptMessage[] = req.body.messages;
+      const prompt: OpenAIChatMessage[] = req.body.messages;
       result = await countTokens({ req, prompt, service });
       break;
     }
@@ -29,20 +34,30 @@ export const countPromptTokens: RequestPreprocessor = async (req) => {
       result = await countTokens({ req, prompt, service });
       break;
     }
-    case "google-palm": {
-      req.outputTokens = req.body.maxOutputTokens;
-      const prompt: string = req.body.prompt.text;
+    case "google-ai": {
+      req.outputTokens = req.body.generationConfig.maxOutputTokens;
+      const prompt: GoogleAIChatMessage[] = req.body.contents;
       result = await countTokens({ req, prompt, service });
       break;
     }
+    case "mistral-ai": {
+      req.outputTokens = req.body.max_tokens;
+      const prompt: MistralAIChatMessage[] = req.body.messages;
+      result = await countTokens({ req, prompt, service });
+      break;
+    }
+    case "openai-image": {
+      req.outputTokens = 1;
+      result = await countTokens({ req, service });
+      break;
+    }
     default:
       assertNever(service);
   }
 
   req.promptTokens = result.token_count;
 
-  // TODO: Remove once token counting is stable
   req.log.debug({ result: result }, "Counted prompt tokens.");
-  req.debug = req.debug ?? {};
-  req.debug = { ...req.debug, ...result };
-};
+  req.tokenizerInfo = req.tokenizerInfo ?? {};
+  req.tokenizerInfo = { ...req.tokenizerInfo, ...result };
+};

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

@@ -0,0 +1,80 @@
+import { Request } from "express";
+import { config } from "../../../../config";
+import { assertNever } from "../../../../shared/utils";
+import { RequestPreprocessor } from "../index";
+import { UserInputError } from "../../../../shared/errors";
+import {
+  MistralAIChatMessage,
+  OpenAIChatMessage,
+} from "./transform-outbound-payload";
+
+const rejectedClients = new Map<string, number>();
+
+setInterval(() => {
+  rejectedClients.forEach((count, ip) => {
+    if (count > 0) {
+      rejectedClients.set(ip, Math.floor(count / 2));
+    } else {
+      rejectedClients.delete(ip);
+    }
+  });
+}, 30000);
+
+/**
+ * Block requests containing blacklisted phrases. Repeated rejections from the
+ * same IP address will be throttled.
+ */
+export const languageFilter: RequestPreprocessor = async (req) => {
+  if (!config.rejectPhrases.length) return;
+
+  const prompt = getPromptFromRequest(req);
+  const match = config.rejectPhrases.find((phrase) =>
+    prompt.match(new RegExp(phrase, "i"))
+  );
+
+  if (match) {
+    const ip = req.ip;
+    const rejections = (rejectedClients.get(req.ip) || 0) + 1;
+    const delay = Math.min(60000, Math.pow(2, rejections - 1) * 1000);
+    rejectedClients.set(ip, rejections);
+    req.log.warn(
+      { match, ip, rejections, delay },
+      "Prompt contains rejected phrase"
+    );
+    await new Promise((resolve) => {
+      req.res!.once("close", resolve);
+      setTimeout(resolve, delay);
+    });
+    throw new UserInputError(config.rejectMessage);
+  }
+};
+
+function getPromptFromRequest(req: Request) {
+  const service = req.outboundApi;
+  const body = req.body;
+  switch (service) {
+    case "anthropic":
+      return body.prompt;
+    case "openai":
+    case "mistral-ai":
+      return body.messages
+        .map((msg: OpenAIChatMessage | MistralAIChatMessage) => {
+          const text = Array.isArray(msg.content)
+            ? msg.content
+                .map((c) => {
+                  if ("text" in c) return c.text;
+                })
+                .join()
+            : msg.content;
+          return `${msg.role}: ${text}`;
+        })
+        .join("\n\n");
+    case "openai-text":
+    case "openai-image":
+      return body.prompt;
+    case "google-ai":
+      return body.prompt.text;
+    default:
+      assertNever(service);
+  }
+}

src/proxy/middleware/request/preprocessors/set-api-format.ts

@@ -1,13 +1,14 @@
 import { Request } from "express";
-import { APIFormat, LLMService } from "../../../shared/key-management";
-import { RequestPreprocessor } from ".";
+import { APIFormat } from "../../../../shared/key-management";
+import { LLMService } from "../../../../shared/models";
+import { RequestPreprocessor } from "../index";
 
 export const setApiFormat = (api: {
   inApi: Request["inboundApi"];
   outApi: APIFormat;
-  service: LLMService,
+  service: LLMService;
 }): RequestPreprocessor => {
-  return function configureRequestApiFormat (req) {
+  return function configureRequestApiFormat(req) {
     req.inboundApi = api.inApi;
     req.outboundApi = api.outApi;
     req.service = api.service;

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

@@ -2,12 +2,12 @@ import express 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 { RequestPreprocessor } from ".";
+import { keyPool } from "../../../../shared/key-management";
+import { RequestPreprocessor } from "../index";
 import { AnthropicV1CompleteSchema } from "./transform-outbound-payload";
 
 const AMZ_HOST =
-  process.env.AMZ_HOST || "invoke-bedrock.%REGION%.amazonaws.com";
+  process.env.AMZ_HOST || "bedrock-runtime.%REGION%.amazonaws.com";
 
 /**
  * Signs an outgoing AWS request with the appropriate headers modifies the
@@ -32,7 +32,7 @@ export const signAwsRequest: RequestPreprocessor = async (req) => {
     temperature: true,
     top_k: true,
     top_p: true,
-  }).parse(req.body);
+  }).strip().parse(req.body);
 
   const credential = getCredentialParts(req);
   const host = AMZ_HOST.replace("%REGION%", credential.region);

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

@@ -0,0 +1,524 @@
+import { Request } from "express";
+import { z } from "zod";
+import { config } from "../../../../config";
+import {
+  isTextGenerationRequest,
+  isImageGenerationRequest,
+} 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 (sameService) {
+    const result = VALIDATORS[req.inboundApi].safeParse(req.body);
+    if (!result.success) {
+      req.log.error(
+        { issues: result.error.issues, body: req.body },
+        "Request validation failed"
+      );
+      throw result.error;
+    }
+    req.body = result.data;
+    return;
+  }
+
+  if (req.inboundApi === "openai" && req.outboundApi === "anthropic") {
+    req.body = openaiToAnthropic(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.`
+  );
+};
+
+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"
+    );
+    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}: ${flattenOpenAIMessageContent(m.content)}`;
+          })
+          .join("") + "\n\nAssistant:"
+      );
+    case 2:
+      return messages
+        .map((m) => {
+          // Claude without prefixes (except system) and no Assistant priming
+          let role: string = "";
+          if (role === "system") {
+            role = "System: ";
+          }
+          return `\n\n${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

@@ -1,12 +1,13 @@
 import { Request } from "express";
 import { z } from "zod";
-import { config } from "../../../config";
-import { assertNever } from "../../../shared/utils";
-import { RequestPreprocessor } from ".";
+import { config } from "../../../../config";
+import { assertNever } from "../../../../shared/utils";
+import { RequestPreprocessor } from "../index";
 
 const CLAUDE_MAX_CONTEXT = config.maxContextTokensAnthropic;
 const OPENAI_MAX_CONTEXT = config.maxContextTokensOpenAI;
-const BISON_MAX_CONTEXT = 8100;
+const GOOGLE_AI_MAX_CONTEXT = 32000;
+const MISTRAL_AI_MAX_CONTENT = 32768;
 
 /**
  * Assigns `req.promptTokens` and `req.outputTokens` based on the request body
@@ -31,9 +32,13 @@ export const validateContextSize: RequestPreprocessor = async (req) => {
     case "anthropic":
       proxyMax = CLAUDE_MAX_CONTEXT;
       break;
-    case "google-palm":
-      proxyMax = BISON_MAX_CONTEXT;
+    case "google-ai":
+      proxyMax = GOOGLE_AI_MAX_CONTEXT;
       break;
+    case "mistral-ai":
+      proxyMax = MISTRAL_AI_MAX_CONTENT;
+    case "openai-image":
+      return;
     default:
       assertNever(req.outboundApi);
   }
@@ -42,6 +47,10 @@ export const validateContextSize: RequestPreprocessor = async (req) => {
   let modelMax: number;
   if (model.match(/gpt-3.5-turbo-16k/)) {
     modelMax = 16384;
+  } else if (model.match(/gpt-4-1106(-preview)?/)) {
+    modelMax = 131072;
+  } else if (model.match(/^gpt-4(-\d{4})?-vision(-preview)?$/)) {
+    modelMax = 131072;
   } else if (model.match(/gpt-3.5-turbo/)) {
     modelMax = 4096;
   } else if (model.match(/gpt-4-32k/)) {
@@ -52,18 +61,20 @@ export const validateContextSize: RequestPreprocessor = async (req) => {
     modelMax = 100000;
   } else if (model.match(/^claude-(?:instant-)?v1(?:\.\d)?$/)) {
     modelMax = 9000;
-  } else if (model.match(/^claude-2/)) {
+  } else if (model.match(/^claude-2\.0/)) {
     modelMax = 100000;
-  } else if (model.match(/^text-bison-\d{3}$/)) {
-    modelMax = BISON_MAX_CONTEXT;
+  } else if (model.match(/^claude-2/)) {
+    modelMax = 200000;
+  } else if (model.match(/^gemini-\d{3}$/)) {
+    modelMax = GOOGLE_AI_MAX_CONTEXT;
+  } else if (model.match(/^mistral-(tiny|small|medium)$/)) {
+    modelMax = MISTRAL_AI_MAX_CONTENT;
   } else if (model.match(/^anthropic\.claude/)) {
     // Not sure if AWS Claude has the same context limit as Anthropic Claude.
     modelMax = 100000;
   } else {
-    // Don't really want to throw here because I don't want to have to update
-    // this ASAP every time a new model is released.
-    req.log.warn({ model }, "Unknown model, using 100k token limit.");
-    modelMax = 100000;
+    req.log.warn({ model }, "Unknown model, using 200k token limit.");
+    modelMax = 200000;
   }
 
   const finalMax = Math.min(proxyMax, modelMax);
@@ -81,10 +92,10 @@ export const validateContextSize: RequestPreprocessor = async (req) => {
     "Prompt size validated"
   );
 
-  req.debug.prompt_tokens = promptTokens;
-  req.debug.completion_tokens = outputTokens;
-  req.debug.max_model_tokens = modelMax;
-  req.debug.max_proxy_tokens = proxyMax;
+  req.tokenizerInfo.prompt_tokens = promptTokens;
+  req.tokenizerInfo.completion_tokens = outputTokens;
+  req.tokenizerInfo.max_model_tokens = modelMax;
+  req.tokenizerInfo.max_proxy_tokens = proxyMax;
 };
 
 function assertRequestHasTokenCounts(

src/proxy/middleware/request/rewrite.ts

@@ -1,35 +0,0 @@
-import { Request } from "express";
-import { ClientRequest } from "http";
-import httpProxy from "http-proxy";
-import { ProxyRequestMiddleware } from "./index";
-
-type ProxyReqCallback = httpProxy.ProxyReqCallback<ClientRequest, Request>;
-type RewriterOptions = {
-  beforeRewrite?: ProxyReqCallback[];
-  pipeline: ProxyRequestMiddleware[];
-};
-
-export const createOnProxyReqHandler = ({
-  beforeRewrite = [],
-  pipeline,
-}: RewriterOptions): ProxyReqCallback => {
-  return (proxyReq, req, res, options) => {
-    try {
-      for (const validator of beforeRewrite) {
-        validator(proxyReq, req, res, options);
-      }
-    } catch (error) {
-      req.log.error(error, "Error while executing proxy request validator");
-      proxyReq.destroy(error);
-    }
-
-    try {
-      for (const rewriter of pipeline) {
-        rewriter(proxyReq, req, res, options);
-      }
-    } catch (error) {
-      req.log.error(error, "Error while executing proxy request rewriter");
-      proxyReq.destroy(error);
-    }
-  };
-};

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

@@ -1,332 +0,0 @@
-import { Request } from "express";
-import { z } from "zod";
-import { config } from "../../../config";
-import { OpenAIPromptMessage } from "../../../shared/tokenization";
-import { isCompletionRequest } from "../common";
-import { RequestPreprocessor } from ".";
-import { APIFormat } from "../../../shared/key-management";
-
-const CLAUDE_OUTPUT_MAX = config.maxOutputTokensAnthropic;
-const OPENAI_OUTPUT_MAX = config.maxOutputTokensOpenAI;
-
-// https://console.anthropic.com/docs/api/reference#-v1-complete
-export const AnthropicV1CompleteSchema = z.object({
-  model: z.string(),
-  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()).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.any().optional(),
-});
-
-// https://platform.openai.com/docs/api-reference/chat/create
-const OpenAIV1ChatCompletionSchema = z.object({
-  model: z.string(),
-  messages: z.array(
-    z.object({
-      role: z.enum(["system", "user", "assistant"]),
-      content: z.string(),
-      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(), z.array(z.string())]).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().optional(),
-});
-
-const OpenAIV1TextCompletionSchema = z
-  .object({
-    model: z
-      .string()
-      .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(), z.array(z.string()).max(4)]).optional(),
-    suffix: z.string().optional(),
-  })
-  .merge(OpenAIV1ChatCompletionSchema.omit({ messages: true }));
-
-// https://developers.generativeai.google/api/rest/generativelanguage/models/generateText
-const PalmV1GenerateTextSchema = z.object({
-  model: z.string(),
-  prompt: z.object({ text: z.string() }),
-  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(),
-  safetySettings: z.array(z.object({})).max(0).optional(),
-  stopSequences: z.array(z.string()).max(5).optional(),
-});
-
-const VALIDATORS: Record<APIFormat, z.ZodSchema<any>> = {
-  anthropic: AnthropicV1CompleteSchema,
-  openai: OpenAIV1ChatCompletionSchema,
-  "openai-text": OpenAIV1TextCompletionSchema,
-  "google-palm": PalmV1GenerateTextSchema,
-};
-
-/** 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 = !isCompletionRequest(req);
-
-  if (alreadyTransformed || notTransformable) {
-    return;
-  }
-
-  if (sameService) {
-    const result = VALIDATORS[req.inboundApi].safeParse(req.body);
-    if (!result.success) {
-      req.log.error(
-        { issues: result.error.issues, body: req.body },
-        "Request validation failed"
-      );
-      throw result.error;
-    }
-    req.body = result.data;
-    return;
-  }
-
-  if (req.inboundApi === "openai" && req.outboundApi === "anthropic") {
-    req.body = openaiToAnthropic(req);
-    return;
-  }
-
-  if (req.inboundApi === "openai" && req.outboundApi === "google-palm") {
-    req.body = openaiToPalm(req);
-    return;
-  }
-
-  if (req.inboundApi === "openai" && req.outboundApi === "openai-text") {
-    req.body = openaiToOpenaiText(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.`
-  );
-};
-
-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"
-    );
-    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);
-}
-
-function openaiToPalm(req: Request): z.infer<typeof PalmV1GenerateTextSchema> {
-  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-Palm 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)];
-
-  z.array(z.string()).max(5).parse(stops);
-
-  return {
-    prompt: { text: prompt },
-    maxOutputTokens: rest.max_tokens,
-    stopSequences: stops,
-    model: "text-bison-001",
-    topP: rest.top_p,
-    temperature: rest.temperature,
-    safetySettings: [
-      { category: "HARM_CATEGORY_UNSPECIFIED", threshold: "BLOCK_NONE" },
-      { category: "HARM_CATEGORY_DEROGATORY", threshold: "BLOCK_NONE" },
-      { category: "HARM_CATEGORY_TOXICITY", threshold: "BLOCK_NONE" },
-      { category: "HARM_CATEGORY_VIOLENCE", threshold: "BLOCK_NONE" },
-      { category: "HARM_CATEGORY_SEXUAL", threshold: "BLOCK_NONE" },
-      { category: "HARM_CATEGORY_MEDICAL", threshold: "BLOCK_NONE" },
-      { category: "HARM_CATEGORY_DANGEROUS", threshold: "BLOCK_NONE" },
-    ],
-  };
-}
-
-export function openAIMessagesToClaudePrompt(messages: OpenAIPromptMessage[]) {
-  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";
-        }
-        // 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}: ${m.name?.trim() ? `(as ${m.name}) ` : ""}${
-          m.content
-        }`;
-      })
-      .join("") + "\n\nAssistant:"
-  );
-}
-
-function flattenOpenAiChatMessages(messages: OpenAIPromptMessage[]) {
-  // 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}: ${m.content}`;
-          })
-          .join("") + "\n\nAssistant:"
-      );
-    case 2:
-      return messages
-        .map((m) => {
-          // Claude without prefixes (except system) and no Assistant priming
-          let role: string = "";
-          if (role === "system") {
-            role = "System: ";
-          }
-          return `\n\n${role}${m.content}`;
-        })
-        .join("");
-    default:
-      throw new Error(`Unknown prompt version: ${PROMPT_VERSION}`);
-  }
-}

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

@@ -1,14 +1,16 @@
 import { pipeline } from "stream";
 import { promisify } from "util";
 import {
-  buildFakeSse,
+  makeCompletionSSE,
   copySseResponseHeaders,
-  initializeSseStream
+  initializeSseStream,
 } from "../../../shared/streaming";
-import { decodeResponseBody, RawResponseBodyHandler } from ".";
+import { enqueue } from "../../queue";
+import { decodeResponseBody, RawResponseBodyHandler, RetryableError } from ".";
 import { SSEStreamAdapter } from "./streaming/sse-stream-adapter";
 import { SSEMessageTransformer } from "./streaming/sse-message-transformer";
 import { EventAggregator } from "./streaming/event-aggregator";
+import { keyPool } from "../../../shared/key-management";
 
 const pipelineAsync = promisify(pipeline);
 
@@ -33,7 +35,7 @@ export const handleStreamedResponse: RawResponseBodyHandler = async (
   }
 
   if (proxyRes.statusCode! > 201) {
-    req.isStreaming = false; // Forces non-streaming response handler to execute
+    req.isStreaming = false;
     req.log.warn(
       { statusCode: proxyRes.statusCode, key: hash },
       `Streaming request returned error status code. Falling back to non-streaming response handler.`
@@ -56,10 +58,10 @@ export const handleStreamedResponse: RawResponseBodyHandler = async (
   const prefersNativeEvents = req.inboundApi === req.outboundApi;
   const contentType = proxyRes.headers["content-type"];
 
-  const adapter = new SSEStreamAdapter({ contentType });
+  const adapter = new SSEStreamAdapter({ contentType, api: req.outboundApi });
   const aggregator = new EventAggregator({ format: req.outboundApi });
   const transformer = new SSEMessageTransformer({
-    inputFormat: req.outboundApi, // outbound from the request's perspective
+    inputFormat: req.outboundApi,
     inputApiVersion: String(req.headers["anthropic-version"]),
     logger: req.log,
     requestId: String(req.id),
@@ -79,9 +81,29 @@ export const handleStreamedResponse: RawResponseBodyHandler = async (
     res.end();
     return aggregator.getFinalResponse();
   } catch (err) {
-    const errorEvent = buildFakeSse("stream-error", err.message, req);
-    res.write(`${errorEvent}data: [DONE]\n\n`);
-    res.end();
+    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);
+    } else {
+      const { message, stack, lastEvent } = err;
+      const eventText = JSON.stringify(lastEvent, null, 2) ?? "undefined"
+      const errorEvent = makeCompletionSSE({
+        format: req.inboundApi,
+        title: "Proxy stream error",
+        message: "An unexpected error occurred while streaming the response.",
+        obj: { message, stack, lastEvent: eventText },
+        reqId: req.id,
+        model: req.body?.model,
+      });
+      res.write(errorEvent);
+      res.write(`data: [DONE]\n\n`);
+      res.end();
+    }
     throw err;
   }
 };

src/proxy/middleware/response/index.ts

@@ -3,7 +3,6 @@ import { Request, Response } from "express";
 import * as http from "http";
 import util from "util";
 import zlib from "zlib";
-import { logger } from "../../../logger";
 import { enqueue, trackWaitTime } from "../../queue";
 import { HttpError } from "../../../shared/errors";
 import { keyPool } from "../../../shared/key-management";
@@ -14,13 +13,16 @@ import {
   incrementTokenCount,
 } from "../../../shared/users/user-store";
 import { assertNever } from "../../../shared/utils";
+import { refundLastAttempt } from "../../rate-limit";
 import {
   getCompletionFromBody,
-  isCompletionRequest,
+  isImageGenerationRequest,
+  isTextGenerationRequest,
   writeErrorResponse,
 } from "../common";
 import { handleStreamedResponse } from "./handle-streamed-response";
 import { logPrompt } from "./log-prompt";
+import { saveImage } from "./save-image";
 
 const DECODER_MAP = {
   gzip: util.promisify(zlib.gunzip),
@@ -34,7 +36,7 @@ const isSupportedContentEncoding = (
   return contentEncoding in DECODER_MAP;
 };
 
-class RetryableError extends Error {
+export class RetryableError extends Error {
   constructor(message: string) {
     super(message);
     this.name = "RetryableError";
@@ -107,6 +109,7 @@ export const createOnProxyResHandler = (apiMiddleware: ProxyResMiddleware) => {
           countResponseTokens,
           incrementUsage,
           copyHttpHeaders,
+          saveImage,
           logPrompt,
           ...apiMiddleware
         );
@@ -149,13 +152,13 @@ export const createOnProxyResHandler = (apiMiddleware: ProxyResMiddleware) => {
   };
 };
 
-function reenqueueRequest(req: Request) {
+async function reenqueueRequest(req: Request) {
   req.log.info(
     { key: req.key?.hash, retryCount: req.retryCount },
     `Re-enqueueing request due to retryable error`
   );
   req.retryCount++;
-  enqueue(req);
+  await enqueue(req);
 }
 
 /**
@@ -188,8 +191,8 @@ export const decodeResponseBody: RawResponseBodyHandler = async (
           body = await decoder(body);
         } else {
           const errorMessage = `Proxy received response with unsupported content-encoding: ${contentEncoding}`;
-          logger.warn({ contentEncoding, key: req.key?.hash }, errorMessage);
-          writeErrorResponse(req, res, 500, {
+          req.log.warn({ contentEncoding, key: req.key?.hash }, errorMessage);
+          writeErrorResponse(req, res, 500, "Internal Server Error", {
             error: errorMessage,
             contentEncoding,
           });
@@ -205,8 +208,10 @@ export const decodeResponseBody: RawResponseBodyHandler = async (
         return resolve(body.toString());
       } catch (error: any) {
         const errorMessage = `Proxy received response with invalid JSON: ${error.message}`;
-        logger.warn({ error: error.stack, key: req.key?.hash }, errorMessage);
-        writeErrorResponse(req, res, 500, { error: errorMessage });
+        req.log.warn({ error: error.stack, key: req.key?.hash }, errorMessage);
+        writeErrorResponse(req, res, 500, "Internal Server Error", {
+          error: errorMessage,
+        });
         return reject(errorMessage);
       }
     });
@@ -234,6 +239,7 @@ const handleUpstreamErrors: ProxyResHandlerWithBody = async (
   body
 ) => {
   const statusCode = proxyRes.statusCode || 500;
+  const statusMessage = proxyRes.statusMessage || "Internal Server Error";
 
   if (statusCode < 400) {
     return;
@@ -250,16 +256,16 @@ const handleUpstreamErrors: ProxyResHandlerWithBody = async (
   } catch (parseError) {
     // Likely Bad Gateway or Gateway Timeout from upstream's reverse proxy
     const hash = req.key?.hash;
-    const statusMessage = proxyRes.statusMessage || "Unknown error";
-    logger.warn({ statusCode, statusMessage, key: hash }, parseError.message);
+    req.log.warn({ statusCode, statusMessage, key: hash }, parseError.message);
 
     const errorObject = {
-      statusCode,
-      statusMessage: proxyRes.statusMessage,
       error: parseError.message,
-      proxy_note: `This is likely a temporary error with the upstream service.`,
+      status: statusCode,
+      statusMessage,
+      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, errorObject);
+
+    writeErrorResponse(req, res, statusCode, statusMessage, errorObject);
     throw new HttpError(statusCode, parseError.message);
   }
 
@@ -268,7 +274,7 @@ const handleUpstreamErrors: ProxyResHandlerWithBody = async (
     errorPayload.error?.type ||
     getAwsErrorType(proxyRes.headers["x-amzn-errortype"]);
 
-  logger.warn(
+  req.log.warn(
     { statusCode, type: errorType, errorPayload, key: req.key?.hash },
     `Received error response from upstream. (${proxyRes.statusMessage})`
   );
@@ -285,12 +291,24 @@ const handleUpstreamErrors: ProxyResHandlerWithBody = async (
     // For Anthropic, this is usually due to missing preamble.
     switch (service) {
       case "openai":
-      case "google-palm":
-        errorPayload.proxy_note = `Upstream service rejected the request as invalid. Your prompt may be too long for ${req.body?.model}.`;
+      case "google-ai":
+      case "mistral-ai":
+      case "azure":
+        const filteredCodes = ["content_policy_violation", "content_filter"];
+        if (filteredCodes.includes(errorPayload.error?.code)) {
+          errorPayload.proxy_note = `Request was filtered by the upstream API's content moderation system. Modify your prompt and try again.`;
+          refundLastAttempt(req);
+        } 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);
+        } 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":
-        maybeHandleMissingPreambleError(req, errorPayload);
+        await maybeHandleMissingPreambleError(req, errorPayload);
         break;
       default:
         assertNever(service);
@@ -300,7 +318,11 @@ const handleUpstreamErrors: ProxyResHandlerWithBody = async (
     keyPool.disable(req.key!, "revoked");
     errorPayload.proxy_note = `API key is invalid or revoked. ${tryAgainMessage}`;
   } else if (statusCode === 403) {
-    // Amazon is the only service that returns 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.
@@ -321,16 +343,21 @@ const handleUpstreamErrors: ProxyResHandlerWithBody = async (
   } else if (statusCode === 429) {
     switch (service) {
       case "openai":
-        handleOpenAIRateLimitError(req, tryAgainMessage, errorPayload);
+        await handleOpenAIRateLimitError(req, tryAgainMessage, errorPayload);
         break;
       case "anthropic":
-        handleAnthropicRateLimitError(req, errorPayload);
+        await handleAnthropicRateLimitError(req, errorPayload);
         break;
       case "aws":
-        handleAwsRateLimitError(req, errorPayload);
+        await handleAwsRateLimitError(req, errorPayload);
+        break;
+      case "azure":
+      case "mistral-ai":
+        await handleAzureRateLimitError(req, errorPayload);
+        break;
+      case "google-ai":
+        await handleGoogleAIRateLimitError(req, errorPayload);
         break;
-      case "google-palm":
-        throw new Error("Rate limit handling not implemented for PaLM");
       default:
         assertNever(service);
     }
@@ -351,12 +378,18 @@ const handleUpstreamErrors: ProxyResHandlerWithBody = async (
       case "anthropic":
         errorPayload.proxy_note = `The requested Claude model might not exist, or the key might not be provisioned for it.`;
         break;
-      case "google-palm":
-        errorPayload.proxy_note = `The requested Google PaLM model might not exist, or the key might not be provisioned for it.`;
+      case "google-ai":
+        errorPayload.proxy_note = `The requested Google AI model might not exist, or the key might not be provisioned for it.`;
+        break;
+      case "mistral-ai":
+        errorPayload.proxy_note = `The requested Mistral AI model might not exist, or the key might not be provisioned for it.`;
         break;
       case "aws":
         errorPayload.proxy_note = `The requested AWS 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;
       default:
         assertNever(service);
     }
@@ -372,7 +405,7 @@ const handleUpstreamErrors: ProxyResHandlerWithBody = async (
     );
   }
 
-  writeErrorResponse(req, res, statusCode, errorPayload);
+  writeErrorResponse(req, res, statusCode, statusMessage, errorPayload);
   throw new HttpError(statusCode, errorPayload.error?.message);
 };
 
@@ -395,7 +428,7 @@ const handleUpstreamErrors: ProxyResHandlerWithBody = async (
  * }
  * ```
  */
-function maybeHandleMissingPreambleError(
+async function maybeHandleMissingPreambleError(
   req: Request,
   errorPayload: ProxiedErrorPayload
 ) {
@@ -408,27 +441,27 @@ function maybeHandleMissingPreambleError(
       "Request failed due to missing preamble. Key will be marked as such for subsequent requests."
     );
     keyPool.update(req.key!, { requiresPreamble: true });
-    reenqueueRequest(req);
+    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.`;
   }
 }
 
-function handleAnthropicRateLimitError(
+async function handleAnthropicRateLimitError(
   req: Request,
   errorPayload: ProxiedErrorPayload
 ) {
   if (errorPayload.error?.type === "rate_limit_error") {
     keyPool.markRateLimited(req.key!);
-    reenqueueRequest(req);
+    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.`;
   }
 }
 
-function handleAwsRateLimitError(
+async function handleAwsRateLimitError(
   req: Request,
   errorPayload: ProxiedErrorPayload
 ) {
@@ -436,7 +469,7 @@ function handleAwsRateLimitError(
   switch (errorType) {
     case "ThrottlingException":
       keyPool.markRateLimited(req.key!);
-      reenqueueRequest(req);
+      await reenqueueRequest(req);
       throw new RetryableError("AWS rate-limited request re-enqueued.");
     case "ModelNotReadyException":
       errorPayload.proxy_note = `The requested model is overloaded. Try again in a few seconds.`;
@@ -446,14 +479,15 @@ function handleAwsRateLimitError(
   }
 }
 
-function handleOpenAIRateLimitError(
+async function handleOpenAIRateLimitError(
   req: Request,
   tryAgainMessage: string,
   errorPayload: ProxiedErrorPayload
-): Record<string, any> {
+): Promise<Record<string, any>> {
   const type = errorPayload.error?.type;
   switch (type) {
     case "insufficient_quota":
+    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}`;
@@ -470,10 +504,66 @@ function handleOpenAIRateLimitError(
       break;
     case "requests":
     case "tokens":
-      // Per-minute request or token rate limit is exceeded, which we can retry
       keyPool.markRateLimited(req.key!);
-      reenqueueRequest(req);
+      if (errorPayload.error?.message?.match(/on requests per day/)) {
+        // This key has a very low rate limit, so we can't re-enqueue it.
+        errorPayload.proxy_note = `Assigned key has reached its per-day request limit for this model. Try another model.`;
+        break;
+      }
+
+      // Per-minute request or token rate limit is exceeded, which we can retry
+      await reenqueueRequest(req);
       throw new RetryableError("Rate-limited request re-enqueued.");
+    // WIP/nonfunctional
+    // case "tokens_usage_based":
+    //   // Weird new rate limit type that seems limited to preview models.
+    //   // Distinct from `tokens` type. Can be per-minute or per-day.
+    //
+    //   // I've seen reports of this error for 500k tokens/day and 10k tokens/min.
+    //   // 10k tokens per minute is problematic, because this is much less than
+    //   // GPT4-Turbo's max context size for a single prompt and is effectively a
+    //   // cap on the max context size for just that key+model, which the app is
+    //   // not able to deal with.
+    //
+    //   // Similarly if there is a 500k tokens per day limit and 450k tokens have
+    //   // been used today, the max context for that key becomes 50k tokens until
+    //   // the next day and becomes progressively smaller as more tokens are used.
+    //
+    //   // To work around these keys we will first retry the request a few times.
+    //   // After that we will reject the request, and if it's a per-day limit we
+    //   // will also disable the key.
+    //
+    //   // "Rate limit reached for gpt-4-1106-preview in organization org-xxxxxxxxxxxxxxxxxxx on tokens_usage_based per day: Limit 500000, Used 460000, Requested 50000"
+    //   // "Rate limit reached for gpt-4-1106-preview in organization org-xxxxxxxxxxxxxxxxxxx on tokens_usage_based per min: Limit 10000, Requested 40000"
+    //
+    //   const regex =
+    //     /Rate limit reached for .+ in organization .+ on \w+ per (day|min): Limit (\d+)(?:, Used (\d+))?, Requested (\d+)/;
+    //   const [, period, limit, used, requested] =
+    //     errorPayload.error?.message?.match(regex) || [];
+    //
+    //   req.log.warn(
+    //     { key: req.key?.hash, period, limit, used, requested },
+    //     "Received `tokens_usage_based` rate limit error from OpenAI."
+    //   );
+    //
+    //   if (!period || !limit || !requested) {
+    //     errorPayload.proxy_note = `Unrecognized rate limit error from OpenAI. (${errorPayload.error?.message})`;
+    //     break;
+    //   }
+    //
+    //   if (req.retryCount < 2) {
+    //     await reenqueueRequest(req);
+    //     throw new RetryableError("Rate-limited request re-enqueued.");
+    //   }
+    //
+    //   if (period === "min") {
+    //     errorPayload.proxy_note = `Assigned key can't be used for prompts longer than ${limit} tokens, and no other keys are available right now. Reduce the length of your prompt or try again in a few minutes.`;
+    //   } else {
+    //     errorPayload.proxy_note = `Assigned key  has reached its per-day request limit for this model. Try another model.`;
+    //   }
+    //
+    //   keyPool.markRateLimited(req.key!);
+    //   break;
     default:
       errorPayload.proxy_note = `This is likely a temporary error with OpenAI. Try again in a few seconds.`;
       break;
@@ -481,14 +571,56 @@ function handleOpenAIRateLimitError(
   return errorPayload;
 }
 
+async function handleAzureRateLimitError(
+  req: Request,
+  errorPayload: ProxiedErrorPayload
+) {
+  const code = errorPayload.error?.code;
+  switch (code) {
+    case "429":
+      keyPool.markRateLimited(req.key!);
+      await reenqueueRequest(req);
+      throw new RetryableError("Rate-limited request re-enqueued.");
+    default:
+      errorPayload.proxy_note = `Unrecognized rate limit error from Azure (${code}). Please report this.`;
+      break;
+  }
+}
+
+//{"error":{"code":429,"message":"Resource has been exhausted (e.g. check quota).","status":"RESOURCE_EXHAUSTED"}
+async function handleGoogleAIRateLimitError(
+  req: Request,
+  errorPayload: ProxiedErrorPayload
+) {
+  const status = errorPayload.error?.status;
+  switch (status) {
+    case "RESOURCE_EXHAUSTED":
+      keyPool.markRateLimited(req.key!);
+      await reenqueueRequest(req);
+      throw new RetryableError("Rate-limited request re-enqueued.");
+    default:
+      errorPayload.proxy_note = `Unrecognized rate limit error from Google AI (${status}). Please report this.`;
+      break;
+  }
+}
+
 const incrementUsage: ProxyResHandlerWithBody = async (_proxyRes, req) => {
-  if (isCompletionRequest(req)) {
+  if (isTextGenerationRequest(req) || isImageGenerationRequest(req)) {
     const model = req.body.model;
     const tokensUsed = req.promptTokens! + req.outputTokens!;
+    req.log.debug(
+      {
+        model,
+        tokensUsed,
+        promptTokens: req.promptTokens,
+        outputTokens: req.outputTokens,
+      },
+      `Incrementing usage for model`
+    );
     keyPool.incrementUsage(req.key!, model, tokensUsed);
     if (req.user) {
       incrementPromptCount(req.user.token);
-      incrementTokenCount(req.user.token, model, tokensUsed);
+      incrementTokenCount(req.user.token, model, req.outboundApi, tokensUsed);
     }
   }
 };
@@ -499,6 +631,12 @@ const countResponseTokens: ProxyResHandlerWithBody = async (
   _res,
   body
 ) => {
+  if (req.outboundApi === "openai-image") {
+    req.outputTokens = req.promptTokens;
+    req.promptTokens = 0;
+    return;
+  }
+
   // This function is prone to breaking if the upstream API makes even minor
   // changes to the response format, especially for SSE responses. If you're
   // seeing errors in this function, check the reassembled response body from
@@ -513,8 +651,8 @@ const countResponseTokens: ProxyResHandlerWithBody = async (
       { service, tokens, prevOutputTokens: req.outputTokens },
       `Counted tokens for completion`
     );
-    if (req.debug) {
-      req.debug.completion_tokens = tokens;
+    if (req.tokenizerInfo) {
+      req.tokenizerInfo.completion_tokens = tokens;
     }
 
     req.outputTokens = tokens.token_count;

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

@@ -4,10 +4,15 @@ import { logQueue } from "../../../shared/prompt-logging";
 import {
   getCompletionFromBody,
   getModelFromBody,
-  isCompletionRequest,
+  isImageGenerationRequest,
+  isTextGenerationRequest,
 } from "../common";
 import { ProxyResHandlerWithBody } from ".";
 import { assertNever } from "../../../shared/utils";
+import {
+  MistralAIChatMessage,
+  OpenAIChatMessage,
+} from "../request/preprocessors/transform-outbound-payload";
 
 /** If prompt logging is enabled, enqueues the prompt for logging. */
 export const logPrompt: ProxyResHandlerWithBody = async (
@@ -23,11 +28,11 @@ export const logPrompt: ProxyResHandlerWithBody = async (
     throw new Error("Expected body to be an object");
   }
 
-  if (!isCompletionRequest(req)) {
-    return;
-  }
+  const loggable =
+    isTextGenerationRequest(req) || isImageGenerationRequest(req);
+  if (!loggable) return;
 
-  const promptPayload = getPromptForRequest(req);
+  const promptPayload = getPromptForRequest(req, responseBody);
   const promptFlattened = flattenMessages(promptPayload);
   const response = getCompletionFromBody(req, responseBody);
   const model = getModelFromBody(req, responseBody);
@@ -41,32 +46,64 @@ export const logPrompt: ProxyResHandlerWithBody = async (
   });
 };
 
-type OaiMessage = {
-  role: "user" | "assistant" | "system";
-  content: string;
+type OaiImageResult = {
+  prompt: string;
+  size: string;
+  style: string;
+  quality: string;
+  revisedPrompt?: string;
 };
 
-const getPromptForRequest = (req: Request): string | OaiMessage[] => {
+const getPromptForRequest = (
+  req: Request,
+  responseBody: Record<string, any>
+): string | OpenAIChatMessage[] | 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.
   switch (req.outboundApi) {
     case "openai":
+    case "mistral-ai":
       return req.body.messages;
     case "openai-text":
       return req.body.prompt;
+    case "openai-image":
+      return {
+        prompt: req.body.prompt,
+        size: req.body.size,
+        style: req.body.style,
+        quality: req.body.quality,
+        revisedPrompt: responseBody.data[0].revised_prompt,
+      };
     case "anthropic":
       return req.body.prompt;
-    case "google-palm":
+    case "google-ai":
       return req.body.prompt.text;
     default:
       assertNever(req.outboundApi);
   }
 };
 
-const flattenMessages = (messages: string | OaiMessage[]): string => {
-  if (typeof messages === "string") {
-    return messages.trim();
+const flattenMessages = (
+  val: string | OpenAIChatMessage[] | MistralAIChatMessage[] | OaiImageResult
+): string => {
+  if (typeof val === "string") {
+    return val.trim();
   }
-  return messages.map((m) => `${m.role}: ${m.content}`).join("\n");
+  if (Array.isArray(val)) {
+    return val
+      .map(({ content, role }) => {
+        const text = Array.isArray(content)
+          ? content
+              .map((c) => {
+                if ("text" in c) return c.text;
+                if ("image_url" in c) return "(( Attached Image ))";
+              })
+              .join("\n")
+          : content;
+        return `${role}: ${text}`;
+      })
+      .join("\n");
+  }
+  return val.prompt.trim();
 };

src/proxy/middleware/response/save-image.ts

@@ -0,0 +1,27 @@
+import { ProxyResHandlerWithBody } from "./index";
+import { mirrorGeneratedImage, OpenAIImageGenerationResult } from "../../../shared/file-storage/mirror-generated-image";
+
+export const saveImage: ProxyResHandlerWithBody = async (
+  _proxyRes,
+  req,
+  _res,
+  body,
+) => {
+  if (req.outboundApi !== "openai-image") {
+    return;
+  }
+
+  if (typeof body !== "object") {
+    throw new Error("Expected body to be an object");
+  }
+
+  if (body.data) {
+    const baseUrl = req.protocol + "://" + req.get("host");
+    const prompt = body.data[0].revised_prompt ?? req.body.prompt;
+    await mirrorGeneratedImage(
+      baseUrl,
+      prompt,
+      body as OpenAIImageGenerationResult
+    );
+  }
+};

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

@@ -4,7 +4,7 @@ import {
   mergeEventsForAnthropic,
   mergeEventsForOpenAIChat,
   mergeEventsForOpenAIText,
-  OpenAIChatCompletionStreamEvent
+  OpenAIChatCompletionStreamEvent,
 } from "./index";
 
 /**
@@ -27,15 +27,17 @@ export class EventAggregator {
   getFinalResponse() {
     switch (this.format) {
       case "openai":
+      case "google-ai":
+      case "mistral-ai":
         return mergeEventsForOpenAIChat(this.events);
       case "openai-text":
         return mergeEventsForOpenAIText(this.events);
       case "anthropic":
         return mergeEventsForAnthropic(this.events);
-      case "google-palm":
-        throw new Error("Google PaLM API does not support streaming responses");
+      case "openai-image":
+        throw new Error(`SSE aggregation not supported for ${this.format}`);
       default:
         assertNever(this.format);
     }
   }
-}
+}

src/proxy/middleware/response/streaming/index.ts

@@ -25,6 +25,8 @@ export type StreamingCompletionTransformer = (
 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 { googleAIToOpenAI } from "./transformers/google-ai-to-openai";
+export { passthroughToOpenAI } from "./transformers/passthrough-to-openai";
 export { mergeEventsForOpenAIChat } from "./aggregators/openai-chat";
 export { mergeEventsForOpenAIText } from "./aggregators/openai-text";
 export { mergeEventsForAnthropic } from "./aggregators/anthropic";

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

@@ -7,9 +7,10 @@ import {
   anthropicV2ToOpenAI,
   OpenAIChatCompletionStreamEvent,
   openAITextToOpenAIChat,
+  googleAIToOpenAI,
+  passthroughToOpenAI,
   StreamingCompletionTransformer,
 } from "./index";
-import { passthroughToOpenAI } from "./transformers/passthrough-to-openai";
 
 const genlog = logger.child({ module: "sse-transformer" });
 
@@ -28,6 +29,7 @@ type SSEMessageTransformerOptions = TransformOptions & {
 export class SSEMessageTransformer extends Transform {
   private lastPosition: number;
   private msgCount: number;
+  private readonly inputFormat: APIFormat;
   private readonly transformFn: StreamingCompletionTransformer;
   private readonly log;
   private readonly fallbackId: string;
@@ -42,6 +44,7 @@ export class SSEMessageTransformer extends Transform {
       options.inputFormat,
       options.inputApiVersion
     );
+    this.inputFormat = options.inputFormat;
     this.fallbackId = options.requestId;
     this.fallbackModel = options.requestedModel;
     this.log.debug(
@@ -67,17 +70,30 @@ export class SSEMessageTransformer extends Transform {
         });
       this.lastPosition = newPosition;
 
+      // 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
+      // content moderation system's response to the prompt. A lot of frontends
+      // don't expect this and neither does our event aggregator so we drop it.
+      if (this.inputFormat === "openai" && this.msgCount <= 1) {
+        if (originalMessage.includes("prompt_filter_results")) {
+          this.log.debug("Dropping Azure OpenAI content moderation SSE event");
+          return callback();
+        }
+      }
+
       this.emit("originalMessage", originalMessage);
 
       // Some events may not be transformed, e.g. ping events
       if (!transformedMessage) return callback();
 
       if (this.msgCount === 1) {
+        // TODO: does this need to be skipped for passthroughToOpenAI?
         this.push(createInitialMessage(transformedMessage));
       }
       this.push(transformedMessage);
       callback();
     } catch (err) {
+      err.lastEvent = chunk?.toString();
       this.log.error(err, "Error transforming SSE message");
       callback(err);
     }
@@ -90,6 +106,7 @@ function getTransformer(
 ): StreamingCompletionTransformer {
   switch (responseApi) {
     case "openai":
+    case "mistral-ai":
       return passthroughToOpenAI;
     case "openai-text":
       return openAITextToOpenAIChat;
@@ -97,8 +114,10 @@ function getTransformer(
       return version === "2023-01-01"
         ? anthropicV1ToOpenAI
         : anthropicV2ToOpenAI;
-    case "google-palm":
-      throw new Error("Google PaLM does not support streaming responses");
+    case "google-ai":
+      return googleAIToOpenAI;
+    case "openai-image":
+      throw new Error(`SSE transformation not supported for ${responseApi}`);
     default:
       assertNever(responseApi);
   }

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

@@ -1,13 +1,25 @@
 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 { 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" });
 
-type SSEStreamAdapterOptions = TransformOptions & { contentType?: string };
+type SSEStreamAdapterOptions = TransformOptions & {
+  contentType?: string;
+  api: APIFormat;
+};
 type AwsEventStreamMessage = {
-  headers: { ":message-type": "event" | "exception" };
+  headers: {
+    ":message-type": "event" | "exception";
+    ":exception-type"?: string;
+  };
   payload: { message?: string /** base64 encoded */; bytes?: string };
 };
 
@@ -17,31 +29,60 @@ type AwsEventStreamMessage = {
  */
 export class SSEStreamAdapter extends Transform {
   private readonly isAwsStream;
-  private parser = new Parser();
+  private readonly isGoogleStream;
+  private awsParser = new Parser();
+  private jsonParser = StreamArray.withParser();
   private partialMessage = "";
+  private decoder = new StringDecoder("utf8");
 
   constructor(options?: SSEStreamAdapterOptions) {
     super(options);
     this.isAwsStream =
       options?.contentType === "application/vnd.amazon.eventstream";
+    this.isGoogleStream = options?.api === "google-ai";
 
-    this.parser.on("data", (data: AwsEventStreamMessage) => {
+    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");
+      }
+    });
   }
 
   protected processAwsEvent(event: AwsEventStreamMessage): string | null {
     const { payload, headers } = event;
     if (headers[":message-type"] === "exception" || !payload.bytes) {
-      log.error(
-        { event: JSON.stringify(event) },
-        "Received bad streaming event from AWS"
-      );
-      const message = JSON.stringify(event);
-      return getFakeErrorCompletion("proxy AWS error", message);
+      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
@@ -54,44 +95,62 @@ export class SSEStreamAdapter extends Transform {
     }
   }
 
+  // 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 {
+    try {
+      const candidates = value.candidates ?? [{}];
+      const hasParts = candidates[0].content?.parts?.length > 0;
+      if (hasParts) {
+        return `data: ${JSON.stringify(value)}`;
+      } else {
+        log.error({ event: value }, "Received bad Google AI event");
+        return `data: ${makeCompletionSSE({
+          format: "google-ai",
+          title: "Proxy stream error",
+          message:
+            "The proxy received malformed or unexpected data from Google AI while streaming.",
+          obj: value,
+          reqId: "proxy-sse-adapter-message",
+          model: "",
+        })}`;
+      }
+    } catch (error) {
+      error.lastEvent = value;
+      this.emit("error", error);
+      return null;
+    }
+  }
+
   _transform(chunk: Buffer, _encoding: BufferEncoding, callback: Function) {
     try {
       if (this.isAwsStream) {
-        this.parser.write(chunk);
+        this.awsParser.write(chunk);
+      } else if (this.isGoogleStream) {
+        this.jsonParser.write(chunk);
       } 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 = chunk.toString("utf8");
+        const str = this.decoder.write(chunk);
 
-        const fullMessages = (this.partialMessage + str).split(/\r?\n\r?\n/);
+        const fullMessages = (this.partialMessage + str).split(
+          /\r\r|\n\n|\r\n\r\n/
+        );
         this.partialMessage = fullMessages.pop() || "";
 
         for (const message of fullMessages) {
           // Mixing line endings will break some clients and our request queue
           // will have already sent \n for heartbeats, so we need to normalize
           // to \n.
-          this.push(message.replace(/\r\n/g, "\n") + "\n\n");
+          this.push(message.replace(/\r\n?/g, "\n") + "\n\n");
         }
       }
       callback();
     } catch (error) {
+      error.lastEvent = chunk?.toString();
       this.emit("error", error);
       callback(error);
     }
   }
 }
-
-function getFakeErrorCompletion(type: string, message: string) {
-  const content = `\`\`\`\n[${type}: ${message}]\n\`\`\`\n`;
-  const fakeEvent = JSON.stringify({
-    log_id: "aws-proxy-sse-message",
-    stop_reason: type,
-    completion:
-      "\nProxy encountered an error during streaming response.\n" + content,
-    truncated: false,
-    stop: null,
-    model: "",
-  });
-  return ["event: completion", `data: ${fakeEvent}\n\n`].join("\n");
-}

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

@@ -0,0 +1,76 @@
+import { StreamingCompletionTransformer } from "../index";
+import { parseEvent, ServerSentEvent } from "../parse-sse";
+import { logger } from "../../../../../logger";
+
+const log = logger.child({
+  module: "sse-transformer",
+  transformer: "google-ai-to-openai",
+});
+
+type GoogleAIStreamEvent = {
+  candidates: {
+    content: { parts: { text: string }[]; role: string };
+    finishReason?: "STOP" | "MAX_TOKENS" | "SAFETY" | "RECITATION" | "OTHER";
+    index: number;
+    tokenCount?: number;
+    safetyRatings: { category: string; probability: string }[];
+  }[];
+};
+
+/**
+ * Transforms an incoming Google AI SSE to an equivalent OpenAI
+ * chat.completion.chunk SSE.
+ */
+export const googleAIToOpenAI: StreamingCompletionTransformer = (params) => {
+  const { data, index } = params;
+
+  const rawEvent = parseEvent(data);
+  if (!rawEvent.data || rawEvent.data === "[DONE]") {
+    return { position: -1 };
+  }
+
+  const completionEvent = asCompletion(rawEvent);
+  if (!completionEvent) {
+    return { position: -1 };
+  }
+
+  const parts = completionEvent.candidates[0].content.parts;
+  let content = parts[0]?.text ?? "";
+
+  // If this is the first chunk, try stripping speaker names from the response
+  // e.g. "John: Hello" -> "Hello"
+  if (index === 0) {
+    content = content.replace(/^(.*?): /, "").trim();
+  }
+
+  const newEvent = {
+    id: "goo-" + params.fallbackId,
+    object: "chat.completion.chunk" as const,
+    created: Date.now(),
+    model: params.fallbackModel,
+    choices: [
+      {
+        index: 0,
+        delta: { content },
+        finish_reason: completionEvent.candidates[0].finishReason ?? null,
+      },
+    ],
+  };
+
+  return { position: -1, event: newEvent };
+};
+
+function asCompletion(event: ServerSentEvent): GoogleAIStreamEvent | null {
+  try {
+    const parsed = JSON.parse(event.data) as GoogleAIStreamEvent;
+    if (parsed.candidates?.length > 0) {
+      return parsed;
+    } else {
+      // noinspection ExceptionCaughtLocallyJS
+      throw new Error("Missing required fields");
+    }
+  } catch (error) {
+    log.warn({ error: error.stack, event }, "Received invalid event");
+  }
+  return null;
+}

src/proxy/mistral-ai.ts

@@ -0,0 +1,116 @@
+import { RequestHandler, Router } from "express";
+import { createProxyMiddleware } from "http-proxy-middleware";
+import { config } from "../config";
+import { keyPool } from "../shared/key-management";
+import {
+  getMistralAIModelFamily,
+  MistralAIModelFamily,
+  ModelFamily,
+} from "../shared/models";
+import { logger } from "../logger";
+import { createQueueMiddleware } from "./queue";
+import { ipLimiter } from "./rate-limit";
+import { handleProxyError } from "./middleware/common";
+import {
+  addKey,
+  createOnProxyReqHandler,
+  createPreprocessorMiddleware,
+  finalizeBody,
+} from "./middleware/request";
+import {
+  createOnProxyResHandler,
+  ProxyResHandlerWithBody,
+} from "./middleware/response";
+
+// https://docs.mistral.ai/platform/endpoints
+export const KNOWN_MISTRAL_AI_MODELS = [
+  "mistral-tiny",
+  "mistral-small",
+  "mistral-medium",
+];
+
+let modelsCache: any = null;
+let modelsCacheTime = 0;
+
+export function generateModelList(models = KNOWN_MISTRAL_AI_MODELS) {
+  let available = new Set<MistralAIModelFamily>();
+  for (const key of keyPool.list()) {
+    if (key.isDisabled || key.service !== "mistral-ai") continue;
+    key.modelFamilies.forEach((family) =>
+      available.add(family as MistralAIModelFamily)
+    );
+  }
+  const allowed = new Set<ModelFamily>(config.allowedModelFamilies);
+  available = new Set([...available].filter((x) => allowed.has(x)));
+
+  return models
+    .map((id) => ({
+      id,
+      object: "model",
+      created: new Date().getTime(),
+      owned_by: "mistral-ai",
+    }))
+    .filter((model) => available.has(getMistralAIModelFamily(model.id)));
+}
+
+const handleModelRequest: RequestHandler = (_req, res) => {
+  if (new Date().getTime() - modelsCacheTime < 1000 * 60) return modelsCache;
+  const result = generateModelList();
+  modelsCache = { object: "list", data: result };
+  modelsCacheTime = new Date().getTime();
+  res.status(200).json(modelsCache);
+};
+
+const mistralAIResponseHandler: 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.tokenizerInfo) {
+    body.proxy_tokenizer = req.tokenizerInfo;
+  }
+
+  res.status(200).json(body);
+};
+
+const mistralAIProxy = createQueueMiddleware({
+  proxyMiddleware: createProxyMiddleware({
+    target: "https://api.mistral.ai",
+    changeOrigin: true,
+    selfHandleResponse: true,
+    logger,
+    on: {
+      proxyReq: createOnProxyReqHandler({
+        pipeline: [addKey, finalizeBody],
+      }),
+      proxyRes: createOnProxyResHandler([mistralAIResponseHandler]),
+      error: handleProxyError,
+    },
+  }),
+});
+
+const mistralAIRouter = Router();
+mistralAIRouter.get("/v1/models", handleModelRequest);
+// General chat completion endpoint.
+mistralAIRouter.post(
+  "/v1/chat/completions",
+  ipLimiter,
+  createPreprocessorMiddleware({
+    inApi: "mistral-ai",
+    outApi: "mistral-ai",
+    service: "mistral-ai",
+  }),
+  mistralAIProxy
+);
+
+export const mistralAI = mistralAIRouter;

src/proxy/openai-image.ts

@@ -0,0 +1,141 @@
+import { RequestHandler, Router, Request } from "express";
+import { createProxyMiddleware } from "http-proxy-middleware";
+import { config } from "../config";
+import { logger } from "../logger";
+import { createQueueMiddleware } from "./queue";
+import { ipLimiter } from "./rate-limit";
+import { handleProxyError } from "./middleware/common";
+import {
+  addKey,
+  createPreprocessorMiddleware,
+  finalizeBody,
+  createOnProxyReqHandler,
+} from "./middleware/request";
+import {
+  createOnProxyResHandler,
+  ProxyResHandlerWithBody,
+} from "./middleware/response";
+import { generateModelList } from "./openai";
+import {
+  OpenAIImageGenerationResult,
+} from "../shared/file-storage/mirror-generated-image";
+
+const KNOWN_MODELS = ["dall-e-2", "dall-e-3"];
+
+let modelListCache: any = null;
+let modelListValid = 0;
+const handleModelRequest: RequestHandler = (_req, res) => {
+  if (new Date().getTime() - modelListValid < 1000 * 60) return modelListCache;
+  const result = generateModelList(KNOWN_MODELS);
+  modelListCache = { object: "list", data: result };
+  modelListValid = new Date().getTime();
+  res.status(200).json(modelListCache);
+};
+
+const openaiImagesResponseHandler: 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 ${host} for more information.`;
+  }
+
+  if (req.inboundApi === "openai") {
+    req.log.info("Transforming OpenAI image response to OpenAI chat format");
+    body = transformResponseForChat(body as OpenAIImageGenerationResult, req);
+  }
+
+  if (req.tokenizerInfo) {
+    body.proxy_tokenizer = req.tokenizerInfo;
+  }
+
+  res.status(200).json(body);
+};
+
+/**
+ * Transforms a DALL-E image generation response into a chat response, simply
+ * embedding the image URL into the chat message as a Markdown image.
+ */
+function transformResponseForChat(
+  imageBody: OpenAIImageGenerationResult,
+  req: Request
+): Record<string, any> {
+  const prompt = imageBody.data[0].revised_prompt ?? req.body.prompt;
+  const content = imageBody.data
+    .map((item) => {
+      const { url, b64_json } = item;
+      if (b64_json) {
+        return `![${prompt}](data:image/png;base64,${b64_json})`;
+      } else {
+        return `![${prompt}](${url})`;
+      }
+    })
+    .join("\n\n");
+
+  return {
+    id: "dalle-" + req.id,
+    object: "chat.completion",
+    created: Date.now(),
+    model: req.body.model,
+    usage: {
+      prompt_tokens: 0,
+      completion_tokens: req.outputTokens,
+      total_tokens: req.outputTokens,
+    },
+    choices: [
+      {
+        message: { role: "assistant", content },
+        finish_reason: "stop",
+        index: 0,
+      },
+    ],
+  };
+}
+
+const openaiImagesProxy = createQueueMiddleware({
+  proxyMiddleware: createProxyMiddleware({
+    target: "https://api.openai.com",
+    changeOrigin: true,
+    selfHandleResponse: true,
+    logger,
+    pathRewrite: {
+      "^/v1/chat/completions": "/v1/images/generations",
+    },
+    on: {
+      proxyReq: createOnProxyReqHandler({ pipeline: [addKey, finalizeBody] }),
+      proxyRes: createOnProxyResHandler([openaiImagesResponseHandler]),
+      error: handleProxyError,
+    },
+  }),
+});
+
+const openaiImagesRouter = Router();
+openaiImagesRouter.get("/v1/models", handleModelRequest);
+openaiImagesRouter.post(
+  "/v1/images/generations",
+  ipLimiter,
+  createPreprocessorMiddleware({
+    inApi: "openai-image",
+    outApi: "openai-image",
+    service: "openai",
+  }),
+  openaiImagesProxy
+);
+openaiImagesRouter.post(
+  "/v1/chat/completions",
+  ipLimiter,
+  createPreprocessorMiddleware({
+    inApi: "openai",
+    outApi: "openai-image",
+    service: "openai",
+  }),
+  openaiImagesProxy
+);
+export const openaiImage = openaiImagesRouter;

src/proxy/openai.ts

@@ -3,60 +3,53 @@ import { createProxyMiddleware } from "http-proxy-middleware";
 import { config } from "../config";
 import { keyPool } from "../shared/key-management";
 import {
+  getOpenAIModelFamily,
   ModelFamily,
   OpenAIModelFamily,
-  getOpenAIModelFamily,
 } from "../shared/models";
 import { logger } from "../logger";
 import { createQueueMiddleware } from "./queue";
 import { ipLimiter } from "./rate-limit";
 import { handleProxyError } from "./middleware/common";
 import {
-  RequestPreprocessor,
   addKey,
   addKeyForEmbeddingsRequest,
-  applyQuotaLimits,
-  blockZoomerOrigins,
   createEmbeddingsPreprocessorMiddleware,
+  createOnProxyReqHandler,
   createPreprocessorMiddleware,
   finalizeBody,
   forceModel,
-  languageFilter,
-  limitCompletions,
-  stripHeaders,
-  createOnProxyReqHandler,
+  RequestPreprocessor,
 } from "./middleware/request";
 import {
   createOnProxyResHandler,
   ProxyResHandlerWithBody,
 } from "./middleware/response";
 
+// https://platform.openai.com/docs/models/overview
+export const KNOWN_OPENAI_MODELS = [
+  "gpt-4-1106-preview",
+  "gpt-4-vision-preview",
+  "gpt-4",
+  "gpt-4-0613",
+  "gpt-4-0314", // EOL 2024-06-13
+  "gpt-4-32k",
+  "gpt-4-32k-0613",
+  "gpt-4-32k-0314", // EOL 2024-06-13
+  "gpt-3.5-turbo",
+  "gpt-3.5-turbo-0301", // EOL 2024-06-13
+  "gpt-3.5-turbo-0613",
+  "gpt-3.5-turbo-16k",
+  "gpt-3.5-turbo-16k-0613",
+  "gpt-3.5-turbo-instruct",
+  "gpt-3.5-turbo-instruct-0914",
+  "text-embedding-ada-002",
+];
+
 let modelsCache: any = null;
 let modelsCacheTime = 0;
 
-function getModelsResponse() {
-  if (new Date().getTime() - modelsCacheTime < 1000 * 60) {
-    return modelsCache;
-  }
-
-  // https://platform.openai.com/docs/models/overview
-  const knownModels = [
-    "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-3.5-turbo",
-    "gpt-3.5-turbo-0301", // EOL 2024-06-13
-    "gpt-3.5-turbo-0613",
-    "gpt-3.5-turbo-16k",
-    "gpt-3.5-turbo-16k-0613",
-    "gpt-3.5-turbo-instruct",
-    "gpt-3.5-turbo-instruct-0914",
-    "text-embedding-ada-002",
-  ];
-
+export function generateModelList(models = KNOWN_OPENAI_MODELS) {
   let available = new Set<OpenAIModelFamily>();
   for (const key of keyPool.list()) {
     if (key.isDisabled || key.service !== "openai") continue;
@@ -67,7 +60,7 @@ function getModelsResponse() {
   const allowed = new Set<ModelFamily>(config.allowedModelFamilies);
   available = new Set([...available].filter((x) => allowed.has(x)));
 
-  const models = knownModels
+  return models
     .map((id) => ({
       id,
       object: "model",
@@ -87,15 +80,14 @@ function getModelsResponse() {
       parent: null,
     }))
     .filter((model) => available.has(getOpenAIModelFamily(model.id)));
-
-  modelsCache = { object: "list", data: models };
-  modelsCacheTime = new Date().getTime();
-
-  return modelsCache;
 }
 
 const handleModelRequest: RequestHandler = (_req, res) => {
-  res.status(200).json(getModelsResponse());
+  if (new Date().getTime() - modelsCacheTime < 1000 * 60) return modelsCache;
+  const result = generateModelList();
+  modelsCache = { object: "list", data: result };
+  modelsCacheTime = new Date().getTime();
+  res.status(200).json(modelsCache);
 };
 
 /** Handles some turbo-instruct special cases. */
@@ -137,9 +129,8 @@ const openaiResponseHandler: ProxyResHandlerWithBody = async (
     body = transformTurboInstructResponse(body);
   }
 
-  // TODO: Remove once tokenization is stable
-  if (req.debug) {
-    body.proxy_tokenizer_debug_info = req.debug;
+  if (req.tokenizerInfo) {
+    body.proxy_tokenizer = req.tokenizerInfo;
   }
 
   res.status(200).json(body);
@@ -163,29 +154,21 @@ function transformTurboInstructResponse(
   return transformed;
 }
 
-const openaiProxy = createQueueMiddleware(
-  createProxyMiddleware({
+const openaiProxy = createQueueMiddleware({
+  proxyMiddleware: createProxyMiddleware({
     target: "https://api.openai.com",
     changeOrigin: true,
     selfHandleResponse: true,
     logger,
     on: {
       proxyReq: createOnProxyReqHandler({
-        pipeline: [
-          applyQuotaLimits,
-          addKey,
-          languageFilter,
-          limitCompletions,
-          blockZoomerOrigins,
-          stripHeaders,
-          finalizeBody,
-        ],
+        pipeline: [addKey, finalizeBody],
       }),
       proxyRes: createOnProxyResHandler([openaiResponseHandler]),
       error: handleProxyError,
     },
-  })
-);
+  }),
+});
 
 const openaiEmbeddingsProxy = createProxyMiddleware({
   target: "https://api.openai.com",
@@ -194,7 +177,7 @@ const openaiEmbeddingsProxy = createProxyMiddleware({
   logger,
   on: {
     proxyReq: createOnProxyReqHandler({
-      pipeline: [addKeyForEmbeddingsRequest, stripHeaders, finalizeBody],
+      pipeline: [addKeyForEmbeddingsRequest, finalizeBody],
     }),
     error: handleProxyError,
   },

src/proxy/palm.ts

@@ -1,183 +0,0 @@
-import { Request, RequestHandler, Router } from "express";
-import * as http from "http";
-import { createProxyMiddleware } from "http-proxy-middleware";
-import { v4 } from "uuid";
-import { config } from "../config";
-import { logger } from "../logger";
-import { createQueueMiddleware } from "./queue";
-import { ipLimiter } from "./rate-limit";
-import { handleProxyError } from "./middleware/common";
-import {
-  addKey,
-  applyQuotaLimits,
-  blockZoomerOrigins,
-  createOnProxyReqHandler,
-  createPreprocessorMiddleware,
-  finalizeBody,
-  forceModel,
-  languageFilter,
-  stripHeaders,
-} from "./middleware/request";
-import {
-  createOnProxyResHandler,
-  ProxyResHandlerWithBody,
-} from "./middleware/response";
-
-let modelsCache: any = null;
-let modelsCacheTime = 0;
-
-const getModelsResponse = () => {
-  if (new Date().getTime() - modelsCacheTime < 1000 * 60) {
-    return modelsCache;
-  }
-
-  if (!config.googlePalmKey) return { object: "list", data: [] };
-
-  const bisonVariants = ["text-bison-001"];
-
-  const models = bisonVariants.map((id) => ({
-    id,
-    object: "model",
-    created: new Date().getTime(),
-    owned_by: "google",
-    permission: [],
-    root: "palm",
-    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 palmResponseHandler: 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 Google PaLM response to OpenAI format");
-    body = transformPalmResponse(body, req);
-  }
-
-  // TODO: Remove once tokenization is stable
-  if (req.debug) {
-    body.proxy_tokenizer_debug_info = req.debug;
-  }
-
-  // TODO: PaLM has no streaming capability which will pose a problem here if
-  // requests wait in the queue for too long.  Probably need to fake streaming
-  // and return the entire completion in one stream event using the other
-  // response handler.
-  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 transformPalmResponse(
-  palmRespBody: Record<string, any>,
-  req: Request
-): Record<string, any> {
-  const totalTokens = (req.promptTokens ?? 0) + (req.outputTokens ?? 0);
-  return {
-    id: "plm-" + 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: palmRespBody.candidates[0].output,
-        },
-        finish_reason: null, // palm doesn't return this
-        index: 0,
-      },
-    ],
-  };
-}
-
-function reassignPathForPalmModel(proxyReq: http.ClientRequest, req: Request) {
-  if (req.body.stream) {
-    throw new Error("Google PaLM API doesn't support streaming requests");
-  }
-
-  // PaLM API specifies the model in the URL path, not the request body. This
-  // doesn't work well with our rewriter architecture, so we need to manually
-  // fix it here.
-
-  // POST https://generativelanguage.googleapis.com/v1beta2/{model=models/*}:generateText
-  // POST https://generativelanguage.googleapis.com/v1beta2/{model=models/*}:generateMessage
-
-  // The chat api (generateMessage) is not very useful at this time as it has
-  // few params and no adjustable safety settings.
-
-  proxyReq.path = proxyReq.path.replace(
-    /^\/v1\/chat\/completions/,
-    `/v1beta2/models/${req.body.model}:generateText`
-  );
-}
-
-const googlePalmProxy = createQueueMiddleware(
-  createProxyMiddleware({
-    target: "https://generativelanguage.googleapis.com",
-    changeOrigin: true,
-    selfHandleResponse: true,
-    logger,
-    on: {
-      proxyReq: createOnProxyReqHandler({
-        beforeRewrite: [reassignPathForPalmModel],
-        pipeline: [
-          applyQuotaLimits,
-          addKey,
-          languageFilter,
-          blockZoomerOrigins,
-          stripHeaders,
-          finalizeBody,
-        ],
-      }),
-      proxyRes: createOnProxyResHandler([palmResponseHandler]),
-      error: handleProxyError,
-    },
-  })
-);
-
-const palmRouter = Router();
-palmRouter.get("/v1/models", handleModelRequest);
-// OpenAI-to-Google PaLM compatibility endpoint.
-palmRouter.post(
-  "/v1/chat/completions",
-  ipLimiter,
-  createPreprocessorMiddleware(
-    { inApi: "openai", outApi: "google-palm", service: "google-palm" },
-    { afterTransform: [forceModel("text-bison-001")] }
-  ),
-  googlePalmProxy
-);
-
-export const googlePalm = palmRouter;

src/proxy/queue.ts

@@ -4,10 +4,6 @@
  * a given key has generated, so our queue will simply retry requests that fail
  * with a non-billing related 429 over and over again until they succeed.
  *
- * Dequeueing can operate in one of two modes:
- * - 'fair': requests are dequeued in the order they were enqueued.
- * - 'random': requests are dequeued randomly, not really a queue at all.
- *
  * When a request to a proxied endpoint is received, we create a closure around
  * the call to http-proxy-middleware and attach it to the request. This allows
  * us to pause the request until we have a key available. Further, if the
@@ -15,18 +11,19 @@
  * back in the queue and it will be retried later using the same closure.
  */
 
+import crypto from "crypto";
 import type { Handler, Request } from "express";
-import { keyPool, SupportedModel } from "../shared/key-management";
+import { keyPool } from "../shared/key-management";
 import {
-  getClaudeModelFamily,
-  getGooglePalmModelFamily,
-  getOpenAIModelFamily,
+  getModelFamilyForRequest,
+  MODEL_FAMILIES,
   ModelFamily,
 } from "../shared/models";
-import { buildFakeSse, initializeSseStream } from "../shared/streaming";
-import { assertNever } from "../shared/utils";
+import { makeCompletionSSE, initializeSseStream } from "../shared/streaming";
 import { logger } from "../logger";
-import { AGNAI_DOT_CHAT_IP } from "./rate-limit";
+import { getUniqueIps, SHARED_IP_ADDRESSES } from "./rate-limit";
+import { RequestPreprocessor } from "./middleware/request";
+import { handleProxyError } from "./middleware/common";
 
 const queue: Request[] = [];
 const log = logger.child({ module: "request-queue" });
@@ -35,44 +32,51 @@ const log = logger.child({ module: "request-queue" });
 const AGNAI_CONCURRENCY_LIMIT = 5;
 /** Maximum number of queue slots for individual users. */
 const USER_CONCURRENCY_LIMIT = 1;
+const MIN_HEARTBEAT_SIZE = parseInt(process.env.MIN_HEARTBEAT_SIZE_B ?? "512");
+const MAX_HEARTBEAT_SIZE =
+  1024 * parseInt(process.env.MAX_HEARTBEAT_SIZE_KB ?? "1024");
+const HEARTBEAT_INTERVAL =
+  1000 * parseInt(process.env.HEARTBEAT_INTERVAL_SEC ?? "5");
+const LOAD_THRESHOLD = parseFloat(process.env.LOAD_THRESHOLD ?? "50");
+const PAYLOAD_SCALE_FACTOR = parseFloat(
+  process.env.PAYLOAD_SCALE_FACTOR ?? "6"
+);
+const QUEUE_JOIN_TIMEOUT = 5000;
 
 /**
- * Returns a unique identifier for a request. This is used to determine if a
+ * Returns an identifier for a request. This is used to determine if a
  * request is already in the queue.
+ *
  * This can be (in order of preference):
  * - user token assigned by the proxy operator
  * - x-risu-tk header, if the request is from RisuAI.xyz
+ * - 'shared-ip' if the request is from a shared IP address like Agnai.chat
  * - IP address
  */
 function getIdentifier(req: Request) {
-  if (req.user) {
-    return req.user.token;
-  }
-  if (req.risuToken) {
-    return req.risuToken;
-  }
+  if (req.user) return req.user.token;
+  if (req.risuToken) return req.risuToken;
+  if (isFromSharedIp(req)) return "shared-ip";
   return req.ip;
 }
 
-const sameUserPredicate = (incoming: Request) => (queued: Request) => {
-  const queuedId = getIdentifier(queued);
-  const incomingId = getIdentifier(incoming);
-  return queuedId === incomingId;
-};
+const sharesIdentifierWith = (incoming: Request) => (queued: Request) =>
+  getIdentifier(queued) === getIdentifier(incoming);
 
-export function enqueue(req: Request) {
-  const enqueuedRequestCount = queue.filter(sameUserPredicate(req)).length;
+const isFromSharedIp = (req: Request) => SHARED_IP_ADDRESSES.has(req.ip);
+
+export async function enqueue(req: Request) {
+  const enqueuedRequestCount = queue.filter(sharesIdentifierWith(req)).length;
   let isGuest = req.user?.token === undefined;
 
-  // All Agnai.chat requests come from the same IP, so we allow them to have
-  // more spots in the queue. Can't make it unlimited because people will
-  // intentionally abuse it.
-  // Authenticated users always get a single spot in the queue.
-  const isAgnai = AGNAI_DOT_CHAT_IP.includes(req.ip);
+  // 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 && isAgnai ? AGNAI_CONCURRENCY_LIMIT : USER_CONCURRENCY_LIMIT;
+    isGuest && isSharedIp ? AGNAI_CONCURRENCY_LIMIT : USER_CONCURRENCY_LIMIT;
   if (enqueuedRequestCount >= maxConcurrentQueuedRequests) {
-    if (isAgnai) {
+    if (isSharedIp) {
       // Re-enqueued requests are not counted towards the limit since they
       // already made it through the queue once.
       if (req.retryCount === 0) {
@@ -83,9 +87,6 @@ export function enqueue(req: Request) {
     }
   }
 
-  queue.push(req);
-  req.queueOutTime = 0;
-
   // shitty hack to remove hpm's event listeners on retried requests
   removeProxyMiddlewareEventListeners(req);
 
@@ -96,33 +97,26 @@ export function enqueue(req: Request) {
   if (stream === "true" || stream === true || req.isStreaming) {
     const res = req.res!;
     if (!res.headersSent) {
-      initStreaming(req);
+      await initStreaming(req);
     }
-    req.heartbeatInterval = setInterval(() => {
-      if (process.env.NODE_ENV === "production") {
-        if (!req.query.badSseParser) req.res!.write(": queue heartbeat\n\n");
-      } else {
-        req.log.info(`Sending heartbeat to request in queue.`);
-        const partition = getPartitionForRequest(req);
-        const avgWait = Math.round(getEstimatedWaitTime(partition) / 1000);
-        const currentDuration = Math.round((Date.now() - req.startTime) / 1000);
-        const debugMsg = `queue length: ${queue.length}; elapsed time: ${currentDuration}s; avg wait: ${avgWait}s`;
-        req.res!.write(buildFakeSse("heartbeat", debugMsg, req));
-      }
-    }, 10000);
+    registerHeartbeat(req);
+  } else if (getProxyLoad() > LOAD_THRESHOLD) {
+    throw new Error(
+      "Due to heavy traffic on this proxy, you must enable streaming for your request."
+    );
   }
 
-  // Register a handler to remove the request from the queue if the connection
-  // is aborted or closed before it is dequeued.
+  queue.push(req);
+  req.queueOutTime = 0;
+
   const removeFromQueue = () => {
     req.log.info(`Removing aborted request from queue.`);
     const index = queue.indexOf(req);
     if (index !== -1) {
       queue.splice(index, 1);
     }
-    if (req.heartbeatInterval) {
-      clearInterval(req.heartbeatInterval);
-    }
+    if (req.heartbeatInterval) clearInterval(req.heartbeatInterval);
+    if (req.monitorInterval) clearInterval(req.monitorInterval);
   };
   req.onAborted = removeFromQueue;
   req.res!.once("close", removeFromQueue);
@@ -130,37 +124,26 @@ export function enqueue(req: Request) {
   if (req.retryCount ?? 0 > 0) {
     req.log.info({ retries: req.retryCount }, `Enqueued request for retry.`);
   } else {
-    req.log.info(`Enqueued new request.`);
-  }
-}
-
-function getPartitionForRequest(req: Request): ModelFamily {
-  // There is a single request queue, but it is partitioned by model family.
-  // Model families are typically separated on cost/rate limit boundaries so
-  // they should be treated as separate queues.
-  const model = (req.body.model as SupportedModel) ?? "gpt-3.5-turbo";
-
-  // Weird special case for AWS because they serve multiple models from
-  // different vendors, even if currently only one is supported.
-  if (req.service === "aws") {
-    return "aws-claude";
-  }
-
-  switch (req.outboundApi) {
-    case "anthropic":
-      return getClaudeModelFamily(model);
-    case "openai":
-    case "openai-text":
-      return getOpenAIModelFamily(model);
-    case "google-palm":
-      return getGooglePalmModelFamily(model);
-    default:
-      assertNever(req.outboundApi);
+    const size = req.socket.bytesRead;
+    const endpoint = req.url?.split("?")[0];
+    req.log.info({ size, endpoint }, `Enqueued new request.`);
   }
 }
 
 function getQueueForPartition(partition: ModelFamily): Request[] {
-  return queue.filter((req) => getPartitionForRequest(req) === partition);
+  return queue
+    .filter((req) => getModelFamilyForRequest(req) === partition)
+    .sort((a, b) => {
+      // Certain requests are exempted from IP-based rate limiting because they
+      // come from a shared IP address. To prevent these requests from starving
+      // out other requests during periods of high traffic, we sort them to the
+      // end of the queue.
+      const aIsExempted = isFromSharedIp(a);
+      const bIsExempted = isFromSharedIp(b);
+      if (aIsExempted && !bIsExempted) return 1;
+      if (!aIsExempted && bIsExempted) return -1;
+      return 0;
+    });
 }
 
 export function dequeue(partition: ModelFamily): Request | undefined {
@@ -180,9 +163,8 @@ export function dequeue(partition: ModelFamily): Request | undefined {
     req.onAborted = undefined;
   }
 
-  if (req.heartbeatInterval) {
-    clearInterval(req.heartbeatInterval);
-  }
+  if (req.heartbeatInterval) clearInterval(req.heartbeatInterval);
+  if (req.monitorInterval) clearInterval(req.monitorInterval);
 
   // Track the time leaving the queue now, but don't add it to the wait times
   // yet because we don't know if the request will succeed or fail. We track
@@ -201,40 +183,23 @@ export function dequeue(partition: ModelFamily): Request | undefined {
 function processQueue() {
   // This isn't completely correct, because a key can service multiple models.
   // Currently if a key is locked out on one model it will also stop servicing
-  // the others, because we only track one rate limit per key.
-
-  // TODO: `getLockoutPeriod` uses model names instead of model families
-  // TODO: genericize this it's really ugly
-  const gpt432kLockout = keyPool.getLockoutPeriod("gpt-4-32k");
-  const gpt4Lockout = keyPool.getLockoutPeriod("gpt-4");
-  const turboLockout = keyPool.getLockoutPeriod("gpt-3.5-turbo");
-  const claudeLockout = keyPool.getLockoutPeriod("claude-v1");
-  const palmLockout = keyPool.getLockoutPeriod("text-bison-001");
-  const awsClaudeLockout = keyPool.getLockoutPeriod("anthropic.claude-v2");
+  // the others, because we only track rate limits for the key as a whole.
 
   const reqs: (Request | undefined)[] = [];
-  if (gpt432kLockout === 0) {
-    reqs.push(dequeue("gpt4-32k"));
-  }
-  if (gpt4Lockout === 0) {
-    reqs.push(dequeue("gpt4"));
-  }
-  if (turboLockout === 0) {
-    reqs.push(dequeue("turbo"));
-  }
-  if (claudeLockout === 0) {
-    reqs.push(dequeue("claude"));
-  }
-  if (palmLockout === 0) {
-    reqs.push(dequeue("bison"));
-  }
-  if (awsClaudeLockout === 0) {
-    reqs.push(dequeue("aws-claude"));
-  }
+  MODEL_FAMILIES.forEach((modelFamily) => {
+    const lockout = keyPool.getLockoutPeriod(modelFamily);
+    if (lockout === 0) {
+      reqs.push(dequeue(modelFamily));
+    }
+  });
 
   reqs.filter(Boolean).forEach((req) => {
     if (req?.proceed) {
-      req.log.info({ retries: req.retryCount }, `Dequeuing request.`);
+      const modelFamily = getModelFamilyForRequest(req!);
+      req.log.info(
+        { retries: req.retryCount, partition: modelFamily },
+        `Dequeuing request.`
+      );
       req.proceed();
     }
   });
@@ -267,38 +232,93 @@ function cleanQueue() {
 }
 
 export function start() {
+  MODEL_FAMILIES.forEach((modelFamily) => {
+    historicalEmas.set(modelFamily, 0);
+    currentEmas.set(modelFamily, 0);
+    estimates.set(modelFamily, 0);
+  });
   processQueue();
   cleanQueue();
   log.info(`Started request queue.`);
 }
 
-let waitTimes: { partition: ModelFamily; start: number; end: number }[] = [];
+let waitTimes: {
+  partition: ModelFamily;
+  start: number;
+  end: number;
+  isDeprioritized: boolean;
+}[] = [];
 
 /** Adds a successful request to the list of wait times. */
 export function trackWaitTime(req: Request) {
   waitTimes.push({
-    partition: getPartitionForRequest(req),
+    partition: getModelFamilyForRequest(req),
     start: req.startTime!,
     end: req.queueOutTime ?? Date.now(),
+    isDeprioritized: isFromSharedIp(req),
   });
 }
 
-/** Returns average wait time in milliseconds. */
-export function getEstimatedWaitTime(partition: ModelFamily) {
-  const now = Date.now();
-  const recentWaits = waitTimes.filter(
-    (wt) => wt.partition === partition && now - wt.end < 300 * 1000
-  );
-  if (recentWaits.length === 0) {
-    return 0;
-  }
+const WAIT_TIME_INTERVAL = 3000;
+const ALPHA_HISTORICAL = 0.2;
+const ALPHA_CURRENT = 0.3;
+const historicalEmas: Map<ModelFamily, number> = new Map();
+const currentEmas: Map<ModelFamily, number> = new Map();
+const estimates: Map<ModelFamily, number> = new Map();
 
-  return (
-    recentWaits.reduce((sum, wt) => sum + wt.end - wt.start, 0) /
-    recentWaits.length
-  );
+export function getEstimatedWaitTime(partition: ModelFamily) {
+  return estimates.get(partition) ?? 0;
 }
 
+/**
+ * Returns estimated wait time for the given queue partition in milliseconds.
+ * Requests which are deprioritized are not included in the calculation as they
+ * would skew the results due to their longer wait times.
+ */
+function calculateWaitTime(partition: ModelFamily) {
+  const now = Date.now();
+  const recentWaits = waitTimes
+    .filter((wait) => {
+      const isSamePartition = wait.partition === partition;
+      const isRecent = now - wait.end < 300 * 1000;
+      const isNormalPriority = !wait.isDeprioritized;
+      return isSamePartition && isRecent && isNormalPriority;
+    })
+    .map((wait) => wait.end - wait.start);
+  const recentAverage = recentWaits.length
+    ? recentWaits.reduce((sum, wait) => sum + wait, 0) / recentWaits.length
+    : 0;
+
+  const historicalEma = historicalEmas.get(partition) ?? 0;
+  historicalEmas.set(
+    partition,
+    ALPHA_HISTORICAL * recentAverage + (1 - ALPHA_HISTORICAL) * historicalEma
+  );
+
+  const currentWaits = queue
+    .filter((req) => {
+      const isSamePartition = getModelFamilyForRequest(req) === partition;
+      const isNormalPriority = !isFromSharedIp(req);
+      return isSamePartition && isNormalPriority;
+    })
+    .map((req) => now - req.startTime!);
+  const longestCurrentWait = Math.max(...currentWaits, 0);
+
+  const currentEma = currentEmas.get(partition) ?? 0;
+  currentEmas.set(
+    partition,
+    ALPHA_CURRENT * longestCurrentWait + (1 - ALPHA_CURRENT) * currentEma
+  );
+
+  return (historicalEma + currentEma) / 2;
+}
+
+setInterval(() => {
+  MODEL_FAMILIES.forEach((modelFamily) => {
+    estimates.set(modelFamily, calculateWaitTime(modelFamily));
+  });
+}, WAIT_TIME_INTERVAL);
+
 export function getQueueLength(partition: ModelFamily | "all" = "all") {
   if (partition === "all") {
     return queue.length;
@@ -307,14 +327,32 @@ export function getQueueLength(partition: ModelFamily | "all" = "all") {
   return modelQueue.length;
 }
 
-export function createQueueMiddleware(proxyMiddleware: Handler): Handler {
-  return (req, res, next) => {
-    req.proceed = () => {
+export function createQueueMiddleware({
+  beforeProxy,
+  proxyMiddleware,
+}: {
+  beforeProxy?: RequestPreprocessor;
+  proxyMiddleware: Handler;
+}): Handler {
+  return async (req, res, next) => {
+    req.proceed = async () => {
+      if (beforeProxy) {
+        try {
+          // Hack to let us run asynchronous middleware before the
+          // http-proxy-middleware handler. This is used to sign AWS requests
+          // before they are proxied, as the signing is asynchronous.
+          // Unlike RequestPreprocessors, this runs every time the request is
+          // dequeued, not just the first time.
+          await beforeProxy(req);
+        } catch (err) {
+          return handleProxyError(err, req, res);
+        }
+      }
       proxyMiddleware(req, res, next);
     };
 
     try {
-      enqueue(req);
+      await enqueue(req);
     } catch (err: any) {
       req.res!.status(429).json({
         type: "proxy_error",
@@ -329,14 +367,22 @@ export function createQueueMiddleware(proxyMiddleware: Handler): Handler {
 function killQueuedRequest(req: Request) {
   if (!req.res || req.res.writableEnded) {
     req.log.warn(`Attempted to terminate request that has already ended.`);
+    queue.splice(queue.indexOf(req), 1);
     return;
   }
   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. The queue is currently ${queue.length} requests long.`;
+    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 fakeErrorEvent = buildFakeSse("proxy queue error", message, req);
-      res.write(fakeErrorEvent);
+      const event = makeCompletionSSE({
+        format: req.inboundApi,
+        title: "Proxy queue error",
+        message,
+        reqId: String(req.id),
+        model: req.body?.model,
+      });
+      res.write(event);
+      res.write(`data: [DONE]\n\n`);
       res.end();
     } else {
       res.status(500).json({ error: message });
@@ -346,18 +392,39 @@ function killQueuedRequest(req: Request) {
   }
 }
 
-function initStreaming(req: Request) {
+async function initStreaming(req: Request) {
   const res = req.res!;
   initializeSseStream(res);
 
-  if (req.query.badSseParser) {
-    // Some clients have a broken SSE parser that doesn't handle comments
-    // correctly. These clients can pass ?badSseParser=true to
-    // disable comments in the SSE stream.
-    return;
-  }
+  const joinMsg = `: joining queue at position ${
+    queue.length
+  }\n\n${getHeartbeatPayload()}`;
 
-  res.write(`: joining queue at position ${queue.length}\n\n`);
+  let drainTimeout: NodeJS.Timeout;
+  const welcome = new Promise<void>((resolve, reject) => {
+    const onDrain = () => {
+      clearTimeout(drainTimeout);
+      req.log.debug(`Client finished consuming join message.`);
+      res.off("drain", onDrain);
+      resolve();
+    };
+
+    drainTimeout = setTimeout(() => {
+      res.off("drain", onDrain);
+      res.destroy();
+      reject(new Error("Unreponsive streaming client; killing connection"));
+    }, QUEUE_JOIN_TIMEOUT);
+
+    if (!res.write(joinMsg)) {
+      req.log.warn("Kernel buffer is full; holding client request.");
+      res.once("drain", onDrain);
+    } else {
+      clearTimeout(drainTimeout);
+      resolve();
+    }
+  });
+
+  await welcome;
 }
 
 /**
@@ -413,3 +480,85 @@ function removeProxyMiddlewareEventListeners(req: Request) {
     req.removeListener("error", reqOnError as any);
   }
 }
+
+export function registerHeartbeat(req: Request) {
+  const res = req.res!;
+
+  let isBufferFull = false;
+  let bufferFullCount = 0;
+  req.heartbeatInterval = setInterval(() => {
+    if (isBufferFull) {
+      bufferFullCount++;
+      if (bufferFullCount >= 3) {
+        req.log.error("Heartbeat skipped too many times; killing connection.");
+        res.destroy();
+      } else {
+        req.log.warn({ bufferFullCount }, "Heartbeat skipped; buffer is full.");
+      }
+      return;
+    }
+
+    const data = getHeartbeatPayload();
+    if (!res.write(data)) {
+      isBufferFull = true;
+      res.once("drain", () => (isBufferFull = false));
+    }
+  }, HEARTBEAT_INTERVAL);
+  monitorHeartbeat(req);
+}
+
+function monitorHeartbeat(req: Request) {
+  const res = req.res!;
+
+  let lastBytesSent = 0;
+  req.monitorInterval = setInterval(() => {
+    const bytesSent = res.socket?.bytesWritten ?? 0;
+    const bytesSinceLast = bytesSent - lastBytesSent;
+    req.log.debug(
+      {
+        previousBytesSent: lastBytesSent,
+        currentBytesSent: bytesSent,
+      },
+      "Heartbeat monitor check."
+    );
+    lastBytesSent = bytesSent;
+
+    const minBytes = Math.floor(getHeartbeatSize() / 2);
+    if (bytesSinceLast < minBytes) {
+      req.log.warn(
+        { minBytes, bytesSinceLast },
+        "Queued request is processing heartbeats enough data or server is overloaded; killing connection."
+      );
+      res.destroy();
+    }
+  }, HEARTBEAT_INTERVAL * 2);
+}
+
+/** Sends larger heartbeats when the queue is overloaded */
+function getHeartbeatSize() {
+  const load = getProxyLoad();
+
+  if (load <= LOAD_THRESHOLD) {
+    return MIN_HEARTBEAT_SIZE;
+  } else {
+    const excessLoad = load - LOAD_THRESHOLD;
+    const size =
+      MIN_HEARTBEAT_SIZE + Math.pow(excessLoad * PAYLOAD_SCALE_FACTOR, 2);
+    if (size > MAX_HEARTBEAT_SIZE) return MAX_HEARTBEAT_SIZE;
+    return size;
+  }
+}
+
+function getHeartbeatPayload() {
+  const size = getHeartbeatSize();
+  const data =
+    process.env.NODE_ENV === "production"
+      ? crypto.randomBytes(size).toString("base64")
+      : `payload size: ${size}`;
+
+  return `: queue heartbeat ${data}\n\n`;
+}
+
+function getProxyLoad() {
+  return Math.max(getUniqueIps(), queue.length);
+}

src/proxy/rate-limit.ts

@@ -1,28 +1,34 @@
 import { Request, Response, NextFunction } from "express";
 import { config } from "../config";
 
-export const AGNAI_DOT_CHAT_IP = [
+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 RATE_LIMIT_ENABLED = Boolean(config.modelRateLimit);
-const RATE_LIMIT = Math.max(1, config.modelRateLimit);
 const ONE_MINUTE_MS = 60 * 1000;
 
-const lastAttempts = new Map<string, number[]>();
+type Timestamp = number;
+/** Tracks time of last attempts from each IP address or token. */
+const lastAttempts = new Map<string, Timestamp[]>();
+/** Tracks time of exempted attempts from shared IPs like Agnai.chat. */
+const exemptedRequests: Timestamp[] = [];
 
-const expireOldAttempts = (now: number) => (attempt: number) =>
+const isRecentAttempt = (now: Timestamp) => (attempt: Timestamp) =>
   attempt > now - ONE_MINUTE_MS;
 
-const getTryAgainInMs = (ip: string) => {
+const getTryAgainInMs = (ip: string, type: "text" | "image") => {
   const now = Date.now();
   const attempts = lastAttempts.get(ip) || [];
-  const validAttempts = attempts.filter(expireOldAttempts(now));
+  const validAttempts = attempts.filter(isRecentAttempt(now));
 
-  if (validAttempts.length >= RATE_LIMIT) {
+  const limit =
+    type === "text" ? config.textModelRateLimit : config.imageModelRateLimit;
+
+  if (validAttempts.length >= limit) {
     return validAttempts[0] - now + ONE_MINUTE_MS;
   } else {
     lastAttempts.set(ip, [...validAttempts, now]);
@@ -30,21 +36,25 @@ const getTryAgainInMs = (ip: string) => {
   }
 };
 
-const getStatus = (ip: string) => {
+const getStatus = (ip: string, type: "text" | "image") => {
   const now = Date.now();
   const attempts = lastAttempts.get(ip) || [];
-  const validAttempts = attempts.filter(expireOldAttempts(now));
+  const validAttempts = attempts.filter(isRecentAttempt(now));
+
+  const limit =
+    type === "text" ? config.textModelRateLimit : config.imageModelRateLimit;
+
   return {
-    remaining: Math.max(0, RATE_LIMIT - validAttempts.length),
+    remaining: Math.max(0, limit - validAttempts.length),
     reset: validAttempts.length > 0 ? validAttempts[0] + ONE_MINUTE_MS : now,
   };
 };
 
-/** Prunes attempts and IPs that are no longer relevant after one minutes. */
+/** Prunes attempts and IPs that are no longer relevant after one minute. */
 const clearOldAttempts = () => {
   const now = Date.now();
   for (const [ip, attempts] of lastAttempts.entries()) {
-    const validAttempts = attempts.filter(expireOldAttempts(now));
+    const validAttempts = attempts.filter(isRecentAttempt(now));
     if (validAttempts.length === 0) {
       lastAttempts.delete(ip);
     } else {
@@ -54,8 +64,25 @@ const clearOldAttempts = () => {
 };
 setInterval(clearOldAttempts, 10 * 1000);
 
-export const getUniqueIps = () => {
-  return lastAttempts.size;
+/** Prunes exempted requests which are older than one minute. */
+const clearOldExemptions = () => {
+  const now = Date.now();
+  const validExemptions = exemptedRequests.filter(isRecentAttempt(now));
+  exemptedRequests.splice(0, exemptedRequests.length, ...validExemptions);
+};
+setInterval(clearOldExemptions, 10 * 1000);
+
+export const getUniqueIps = () => lastAttempts.size;
+
+/**
+ * Can be used to manually remove the most recent attempt from an IP address,
+ * ie. in case a prompt triggered OpenAI's content filter and therefore did not
+ * result in a generation.
+ */
+export const refundLastAttempt = (req: Request) => {
+  const key = req.user?.token || req.risuToken || req.ip;
+  const attempts = lastAttempts.get(key) || [];
+  attempts.pop();
 };
 
 export const ipLimiter = async (
@@ -63,36 +90,46 @@ export const ipLimiter = async (
   res: Response,
   next: NextFunction
 ) => {
-  if (!RATE_LIMIT_ENABLED) return next();
+  const imageLimit = config.imageModelRateLimit;
+  const textLimit = config.textModelRateLimit;
+
+  if (!textLimit && !imageLimit) return next();
   if (req.user?.type === "special") return next();
 
-  // Exempt Agnai.chat from rate limiting since it's shared between a lot of
-  // users. Dunno how to prevent this from being abused without some sort of
-  // identifier sent from Agnaistic to identify specific users.
-  if (AGNAI_DOT_CHAT_IP.includes(req.ip)) {
-    req.log.info("Exempting Agnai request from rate limiting.");
-    next();
-    return;
+  // 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 limit = type === "image" ? imageLimit : textLimit;
+
   // If user is authenticated, key rate limiting by their token. Otherwise, key
   // rate limiting by their IP address. Mitigates key sharing.
   const rateLimitKey = req.user?.token || req.risuToken || req.ip;
 
-  const { remaining, reset } = getStatus(rateLimitKey);
-  res.set("X-RateLimit-Limit", config.modelRateLimit.toString());
+  const { remaining, reset } = getStatus(rateLimitKey, type);
+  res.set("X-RateLimit-Limit", limit.toString());
   res.set("X-RateLimit-Remaining", remaining.toString());
   res.set("X-RateLimit-Reset", reset.toString());
 
-  const tryAgainInMs = getTryAgainInMs(rateLimitKey);
+  const tryAgainInMs = getTryAgainInMs(rateLimitKey, type);
   if (tryAgainInMs > 0) {
     res.set("Retry-After", tryAgainInMs.toString());
     res.status(429).json({
       error: {
         type: "proxy_rate_limited",
-        message: `This proxy is rate limited to ${
-          config.modelRateLimit
-        } prompts per minute. Please try again in ${Math.ceil(
+        message: `This model type is rate limited to ${limit} prompts per minute. Please try again in ${Math.ceil(
           tryAgainInMs / 1000
         )} seconds.`,
       },

src/proxy/routes.ts

@@ -2,9 +2,12 @@ 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 { anthropic } from "./anthropic";
-import { googlePalm } from "./palm";
+import { googleAI } from "./google-ai";
+import { mistralAI } from "./mistral-ai";
 import { aws } from "./aws";
+import { azure } from "./azure";
 
 const proxyRouter = express.Router();
 proxyRouter.use((req, _res, next) => {
@@ -16,8 +19,8 @@ proxyRouter.use((req, _res, next) => {
   next();
 });
 proxyRouter.use(
-  express.json({ limit: "1536kb" }),
-  express.urlencoded({ extended: true, limit: "1536kb" })
+  express.json({ limit: "1mb" }),
+  express.urlencoded({ extended: true, limit: "1mb" })
 );
 proxyRouter.use(gatekeeper);
 proxyRouter.use(checkRisuToken);
@@ -27,9 +30,12 @@ proxyRouter.use((req, _res, next) => {
   next();
 });
 proxyRouter.use("/openai", addV1, openai);
+proxyRouter.use("/openai-image", addV1, openaiImage);
 proxyRouter.use("/anthropic", addV1, anthropic);
-proxyRouter.use("/google-palm", addV1, googlePalm);
+proxyRouter.use("/google-ai", addV1, googleAI);
+proxyRouter.use("/mistral-ai", addV1, mistralAI);
 proxyRouter.use("/aws/claude", addV1, aws);
+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");

src/server.ts

@@ -1,15 +1,19 @@
-import { assertConfigIsValid, config } from "./config";
+import { assertConfigIsValid, config, USER_ASSETS_DIR } from "./config";
 import "source-map-support/register";
+import checkDiskSpace from "check-disk-space";
 import express from "express";
 import cors from "cors";
 import path from "path";
 import pinoHttp from "pino-http";
+import os from "os";
 import childProcess from "child_process";
 import { logger } from "./logger";
+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 } from "./info-page";
+import { handleInfoPage, renderPage } from "./info-page";
+import { buildInfo } from "./service-info";
 import { logQueue } from "./shared/prompt-logging";
 import { start as startRequestQueue } from "./proxy/queue";
 import { init as initUserStore } from "./shared/users/user-store";
@@ -25,9 +29,7 @@ app.use(
   pinoHttp({
     quietReqLogger: true,
     logger,
-    autoLogging: {
-      ignore: ({ url }) => ["/health"].includes(url as string),
-    },
+    autoLogging: { ignore: ({ url }) => ["/health"].includes(url as string) },
     redact: {
       paths: [
         "req.headers.cookie",
@@ -40,6 +42,11 @@ app.use(
       ],
       censor: "********",
     },
+    customProps: (req) => {
+      const user = (req as express.Request).user;
+      if (user) return { userToken: `...${user.token.slice(-5)}` };
+      return {};
+    },
   })
 );
 
@@ -47,6 +54,10 @@ app.use(
 // 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("view engine", "ejs");
 app.set("views", [
@@ -55,17 +66,20 @@ app.set("views", [
   path.join(__dirname, "shared/views"),
 ]);
 
+app.use("/user_content", express.static(USER_ASSETS_DIR));
+
 app.get("/health", (_req, res) => res.sendStatus(200));
 app.use(cors());
 app.use(checkOrigin);
 
-// routes
 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("/user", userRouter);
 
-// 500 and 404
 app.use((err: any, _req: unknown, res: express.Response, _next: unknown) => {
   if (err.status) {
     res.status(err.status).json({ error: err.message });
@@ -96,13 +110,17 @@ async function start() {
 
   await initTokenizers();
 
+  if (config.allowedModelFamilies.includes("dall-e")) {
+    await setupAssetsDir();
+  }
+
   if (config.gatekeeper === "user_token") {
     await initUserStore();
   }
 
   if (config.promptLogging) {
     logger.info("Starting prompt logging...");
-    logQueue.start();
+    await logQueue.start();
   }
 
   logger.info("Starting request queue...");
@@ -113,8 +131,12 @@ async function start() {
     registerUncaughtExceptionHandler();
   });
 
+  const diskSpace = await checkDiskSpace(
+    __dirname.startsWith("/app") ? "/app" : os.homedir()
+  );
+
   logger.info(
-    { build: process.env.BUILD_INFO, nodeEnv: process.env.NODE_ENV },
+    { build: process.env.BUILD_INFO, nodeEnv: process.env.NODE_ENV, diskSpace },
     "Startup complete."
   );
 }

src/service-info.ts

@@ -0,0 +1,441 @@
+/** Calculates and returns stats about the service. */
+import { config, listConfig } from "./config";
+import {
+  AnthropicKey,
+  AwsBedrockKey,
+  AzureOpenAIKey,
+  GoogleAIKey,
+  keyPool,
+  OpenAIKey,
+} from "./shared/key-management";
+import {
+  AnthropicModelFamily,
+  assertIsKnownModelFamily,
+  AwsBedrockModelFamily,
+  AzureOpenAIModelFamily,
+  GoogleAIModelFamily,
+  LLM_SERVICES,
+  LLMService,
+  MistralAIModelFamily,
+  MODEL_FAMILY_SERVICE,
+  ModelFamily,
+  OpenAIModelFamily,
+} from "./shared/models";
+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";
+
+/** Stats aggregated across all keys for a given service. */
+type ServiceAggregate = "keys" | "uncheckedKeys" | "orgs";
+/** Stats aggregated across all keys for a given model family. */
+type ModelAggregates = {
+  active: number;
+  trial?: number;
+  revoked?: number;
+  overQuota?: number;
+  pozzed?: number;
+  awsLogged?: number;
+  queued: number;
+  queueTime: string;
+  tokens: number;
+};
+/** All possible combinations of model family and aggregate type. */
+type ModelAggregateKey = `${ModelFamily}__${keyof ModelAggregates}`;
+
+type AllStats = {
+  proompts: number;
+  tokens: number;
+  tokenCost: number;
+} & { [modelFamily in ModelFamily]?: ModelAggregates } & {
+  [service in LLMService as `${service}__${ServiceAggregate}`]?: number;
+};
+
+type BaseFamilyInfo = {
+  usage?: string;
+  activeKeys: number;
+  revokedKeys?: number;
+  proomptersInQueue?: number;
+  estimatedQueueTime?: string;
+};
+type OpenAIInfo = BaseFamilyInfo & {
+  trialKeys?: number;
+  overQuotaKeys?: number;
+};
+type AnthropicInfo = BaseFamilyInfo & { pozzedKeys?: number };
+type AwsInfo = BaseFamilyInfo & { privacy?: 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;
+    azure?: string;
+  };
+  proompts?: number;
+  tookens?: string;
+  proomptersNow?: number;
+  status?: string;
+  config: ReturnType<typeof listConfig>;
+  build: string;
+} & { [f in OpenAIModelFamily]?: OpenAIInfo }
+  & { [f in AnthropicModelFamily]?: AnthropicInfo; }
+  & { [f in AwsBedrockModelFamily]?: AwsInfo }
+  & { [f in AzureOpenAIModelFamily]?: BaseFamilyInfo; }
+  & { [f in GoogleAIModelFamily]?: BaseFamilyInfo }
+  & { [f in MistralAIModelFamily]?: BaseFamilyInfo };
+
+// https://stackoverflow.com/a/66661477
+// type DeepKeyOf<T> = (
+//   [T] extends [never]
+//     ? ""
+//     : T extends object
+//     ? {
+//         [K in Exclude<keyof T, symbol>]: `${K}${DotPrefix<DeepKeyOf<T[K]>>}`;
+//       }[Exclude<keyof T, symbol>]
+//     : ""
+// ) extends infer D
+//   ? Extract<D, string>
+//   : never;
+// type DotPrefix<T extends string> = T extends "" ? "" : `.${T}`;
+// type ServiceInfoPath = `{${DeepKeyOf<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: {
+    anthropic: `%BASE%/anthropic`,
+  },
+  "google-ai": {
+    "google-ai": `%BASE%/google-ai`,
+  },
+  "mistral-ai": {
+    "mistral-ai": `%BASE%/mistral-ai`,
+  },
+  aws: {
+    aws: `%BASE%/aws/claude`,
+  },
+  azure: {
+    azure: `%BASE%/azure/openai`,
+  },
+};
+
+const modelStats = new Map<ModelAggregateKey, number>();
+const serviceStats = new Map<keyof AllStats, number>();
+
+let cachedInfo: ServiceInfo | undefined;
+let cacheTime = 0;
+
+export function buildInfo(baseUrl: string, forAdmin = false): ServiceInfo {
+  if (cacheTime + CACHE_TTL > Date.now()) return cachedInfo!;
+
+  const keys = keyPool.list();
+  const accessibleFamilies = new Set(
+    keys
+      .flatMap((k) => k.modelFamilies)
+      .filter((f) => config.allowedModelFamilies.includes(f))
+      .concat("turbo")
+  );
+
+  modelStats.clear();
+  serviceStats.clear();
+  keys.forEach(addKeyToAggregates);
+
+  const endpoints = getEndpoints(baseUrl, accessibleFamilies);
+  const trafficStats = getTrafficStats();
+  const { serviceInfo, modelFamilyInfo } =
+    getServiceModelStats(accessibleFamilies);
+  const status = getStatus();
+
+  if (config.staticServiceInfo && !forAdmin) {
+    delete trafficStats.proompts;
+    delete trafficStats.tookens;
+    delete trafficStats.proomptersNow;
+    for (const family of Object.keys(modelFamilyInfo)) {
+      assertIsKnownModelFamily(family);
+      delete modelFamilyInfo[family]?.proomptersInQueue;
+      delete modelFamilyInfo[family]?.estimatedQueueTime;
+      delete modelFamilyInfo[family]?.usage;
+    }
+  }
+
+  return (cachedInfo = {
+    uptime: Math.floor(process.uptime()),
+    endpoints,
+    ...trafficStats,
+    ...serviceInfo,
+    status,
+    ...modelFamilyInfo,
+    config: listConfig(),
+    build: process.env.BUILD_INFO || "dev",
+  });
+}
+
+function getStatus() {
+  if (!config.checkKeys) return "Key checking is disabled.";
+
+  let unchecked = 0;
+  for (const service of LLM_SERVICES) {
+    unchecked += serviceStats.get(`${service}__uncheckedKeys`) || 0;
+  }
+
+  return unchecked ? `Checking ${unchecked} keys...` : undefined;
+}
+
+function getEndpoints(baseUrl: string, accessibleFamilies: Set<ModelFamily>) {
+  const endpoints: Record<string, string> = {};
+  for (const service of LLM_SERVICES) {
+    for (const [name, url] of Object.entries(SERVICE_ENDPOINTS[service])) {
+      endpoints[name] = url.replace("%BASE%", baseUrl);
+    }
+
+    if (service === "openai" && !accessibleFamilies.has("dall-e")) {
+      delete endpoints["openai-image"];
+    }
+  }
+  return endpoints;
+}
+
+type TrafficStats = Pick<ServiceInfo, "proompts" | "tookens" | "proomptersNow">;
+
+function getTrafficStats(): TrafficStats {
+  const tokens = serviceStats.get("tokens") || 0;
+  const tokenCost = serviceStats.get("tokenCost") || 0;
+  return {
+    proompts: serviceStats.get("proompts") || 0,
+    tookens: `${prettyTokens(tokens)}${getCostSuffix(tokenCost)}`,
+    ...(config.textModelRateLimit ? { proomptersNow: getUniqueIps() } : {}),
+  };
+}
+
+function getServiceModelStats(accessibleFamilies: Set<ModelFamily>) {
+  const serviceInfo: {
+    [s in LLMService as `${s}${"Keys" | "Orgs"}`]?: number;
+  } = {};
+  const modelFamilyInfo: { [f in ModelFamily]?: BaseFamilyInfo } = {};
+
+  for (const service of LLM_SERVICES) {
+    const hasKeys = serviceStats.get(`${service}__keys`) || 0;
+    if (!hasKeys) continue;
+
+    serviceInfo[`${service}Keys`] = hasKeys;
+    accessibleFamilies.forEach((f) => {
+      if (MODEL_FAMILY_SERVICE[f] === service) {
+        modelFamilyInfo[f] = getInfoForFamily(f);
+      }
+    });
+
+    if (service === "openai" && config.checkKeys) {
+      serviceInfo.openaiOrgs = getUniqueOpenAIOrgs(keyPool.list());
+    }
+  }
+  return { serviceInfo, modelFamilyInfo };
+}
+
+function getUniqueOpenAIOrgs(keys: KeyPoolKey[]) {
+  const orgIds = new Set(
+    keys.filter((k) => k.service === "openai").map((k: any) => k.organizationId)
+  );
+  return orgIds.size;
+}
+
+function increment<T extends keyof AllStats | ModelAggregateKey>(
+  map: Map<T, number>,
+  key: T,
+  delta = 1
+) {
+  map.set(key, (map.get(key) || 0) + delta);
+}
+
+function addKeyToAggregates(k: KeyPoolKey) {
+  increment(serviceStats, "proompts", k.promptCount);
+  increment(serviceStats, "openai__keys", k.service === "openai" ? 1 : 0);
+  increment(serviceStats, "anthropic__keys", k.service === "anthropic" ? 1 : 0);
+  increment(serviceStats, "google-ai__keys", k.service === "google-ai" ? 1 : 0);
+  increment(serviceStats, "mistral-ai__keys", k.service === "mistral-ai" ? 1 : 0);
+  increment(serviceStats, "aws__keys", k.service === "aws" ? 1 : 0);
+  increment(serviceStats, "azure__keys", k.service === "azure" ? 1 : 0);
+
+  let sumTokens = 0;
+  let sumCost = 0;
+
+  switch (k.service) {
+    case "openai":
+      if (!keyIsOpenAIKey(k)) throw new Error("Invalid key type");
+      increment(
+        serviceStats,
+        "openai__uncheckedKeys",
+        Boolean(k.lastChecked) ? 0 : 1
+      );
+
+      k.modelFamilies.forEach((f) => {
+        const tokens = k[`${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, `${f}__overQuota`, k.isOverQuota ? 1 : 0);
+      });
+      break;
+    case "azure":
+      if (!keyIsAzureKey(k)) throw new Error("Invalid key type");
+      k.modelFamilies.forEach((f) => {
+        const tokens = k[`${f}Tokens`];
+        sumTokens += tokens;
+        sumCost += getTokenCostUsd(f, tokens);
+        increment(modelStats, `${f}__tokens`, tokens);
+        increment(modelStats, `${f}__active`, k.isDisabled ? 0 : 1);
+        increment(modelStats, `${f}__revoked`, k.isRevoked ? 1 : 0);
+      });
+      break;
+    case "anthropic": {
+      if (!keyIsAnthropicKey(k)) throw new Error("Invalid key type");
+      const family = "claude";
+      sumTokens += k.claudeTokens;
+      sumCost += getTokenCostUsd(family, k.claudeTokens);
+      increment(modelStats, `${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");
+      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);
+      });
+      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, `${family}__tokens`, k["aws-claudeTokens"]);
+
+      // Ignore revoked keys for aws logging stats, but include keys where the
+      // logging status is unknown.
+      const countAsLogged =
+        k.lastChecked && !k.isDisabled && k.awsLoggingStatus !== "disabled";
+      increment(modelStats, `${family}__awsLogged`, countAsLogged ? 1 : 0);
+
+      break;
+    }
+    default:
+      assertNever(k.service);
+  }
+
+  increment(serviceStats, "tokens", sumTokens);
+  increment(serviceStats, "tokenCost", sumCost);
+}
+
+function getInfoForFamily(family: ModelFamily): BaseFamilyInfo {
+  const tokens = modelStats.get(`${family}__tokens`) || 0;
+  const cost = getTokenCostUsd(family, tokens);
+  let info: BaseFamilyInfo & OpenAIInfo & AnthropicInfo & AwsInfo = {
+    usage: `${prettyTokens(tokens)} tokens${getCostSuffix(cost)}`,
+    activeKeys: modelStats.get(`${family}__active`) || 0,
+    revokedKeys: modelStats.get(`${family}__revoked`) || 0,
+  };
+
+  // Add service-specific stats to the info object.
+  if (config.checkKeys) {
+    const service = MODEL_FAMILY_SERVICE[family];
+    switch (service) {
+      case "openai":
+        info.overQuotaKeys = modelStats.get(`${family}__overQuota`) || 0;
+        info.trialKeys = modelStats.get(`${family}__trial`) || 0;
+
+        // Delete trial/revoked keys for non-turbo families.
+        // Trials are turbo 99% of the time, and if a key is invalid we don't
+        // know what models it might have had assigned to it.
+        if (family !== "turbo") {
+          delete info.trialKeys;
+          delete info.revokedKeys;
+        }
+        break;
+      case "anthropic":
+        info.pozzedKeys = modelStats.get(`${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.`
+            : `${logged} active keys are potentially logged and can't be used. Set ALLOW_AWS_LOGGING=true to override.`;
+        }
+        break;
+    }
+  }
+
+  // Add queue stats to the info object.
+  const queue = getQueueInformation(family);
+  info.proomptersInQueue = queue.proomptersInQueue;
+  info.estimatedQueueTime = queue.estimatedQueueTime;
+
+  return info;
+}
+
+/** Returns queue time in seconds, or minutes + seconds if over 60 seconds. */
+function getQueueInformation(partition: ModelFamily) {
+  const waitMs = getEstimatedWaitTime(partition);
+  const waitTime =
+    waitMs < 60000
+      ? `${Math.round(waitMs / 1000)}sec`
+      : `${Math.round(waitMs / 60000)}min, ${Math.round(
+          (waitMs % 60000) / 1000
+        )}sec`;
+  return {
+    proomptersInQueue: getQueueLength(partition),
+    estimatedQueueTime: waitMs > 2000 ? waitTime : "no wait",
+  };
+}

src/shared/custom.d.ts

@@ -1,7 +1,10 @@
+// noinspection JSUnusedGlobalSymbols,ES6UnusedImports
+
 import type { HttpRequest } from "@smithy/types";
 import { Express } from "express-serve-static-core";
-import { APIFormat, Key, LLMService } from "../shared/key-management";
-import { User } from "../shared/users/schema";
+import { APIFormat, Key } from "./key-management";
+import { User } from "./users/schema";
+import { LLMService, ModelFamily } from "./models";
 
 declare global {
   namespace Express {
@@ -22,11 +25,12 @@ declare global {
       onAborted?: () => void;
       proceed: () => void;
       heartbeatInterval?: NodeJS.Timeout;
+      monitorInterval?: NodeJS.Timeout;
       promptTokens?: number;
       outputTokens?: number;
-      // TODO: remove later
-      debug: Record<string, any>;
+      tokenizerInfo: Record<string, any>;
       signedRequest: HttpRequest;
+      modelFamily?: ModelFamily;
     }
   }
 }

src/shared/file-storage/image-history.ts

@@ -0,0 +1,22 @@
+const IMAGE_HISTORY_SIZE = 30;
+const imageHistory = new Array<ImageHistory>(IMAGE_HISTORY_SIZE);
+let index = 0;
+
+type ImageHistory = { url: string; prompt: string };
+
+export function addToImageHistory(image: ImageHistory) {
+  imageHistory[index] = image;
+  index = (index + 1) % IMAGE_HISTORY_SIZE;
+}
+
+export function getLastNImages(n: number) {
+  const result: ImageHistory[] = [];
+  let currentIndex = (index - 1 + IMAGE_HISTORY_SIZE) % IMAGE_HISTORY_SIZE;
+
+  for (let i = 0; i < n; i++) {
+    if (imageHistory[currentIndex]) result.unshift(imageHistory[currentIndex]);
+    currentIndex = (currentIndex - 1 + IMAGE_HISTORY_SIZE) % IMAGE_HISTORY_SIZE;
+  }
+
+  return result;
+}

src/shared/file-storage/index.ts

@@ -0,0 +1,6 @@
+// We need to control the timing of when sharp is imported because it has a
+// native dependency that causes conflicts with node-canvas if they are not
+// imported in a specific order.
+import sharp from "sharp";
+
+export { sharp as libSharp };

src/shared/file-storage/mirror-generated-image.ts

@@ -0,0 +1,73 @@
+import axios from "axios";
+import { promises as fs } from "fs";
+import path from "path";
+import { v4 } from "uuid";
+import { USER_ASSETS_DIR } from "../../config";
+import { addToImageHistory } from "./image-history";
+import { libSharp } from "./index";
+
+
+export type OpenAIImageGenerationResult = {
+  created: number;
+  data: {
+    revised_prompt?: string;
+    url: string;
+    b64_json: string;
+  }[];
+};
+
+async function downloadImage(url: string) {
+  const { data } = await axios.get(url, { responseType: "arraybuffer" });
+  const buffer = Buffer.from(data, "binary");
+  const newFilename = `${v4()}.png`;
+
+  const filepath = path.join(USER_ASSETS_DIR, newFilename);
+  await fs.writeFile(filepath, buffer);
+  return filepath;
+}
+
+async function saveB64Image(b64: string) {
+  const buffer = Buffer.from(b64, "base64");
+  const newFilename = `${v4()}.png`;
+
+  const filepath = path.join(USER_ASSETS_DIR, newFilename);
+  await fs.writeFile(filepath, buffer);
+  return filepath;
+}
+
+async function createThumbnail(filepath: string) {
+  const thumbnailPath = filepath.replace(/(\.[\wd_-]+)$/i, "_t.jpg");
+
+  await libSharp(filepath)
+    .resize(150, 150, {
+      fit: "inside",
+      withoutEnlargement: true,
+    })
+    .toFormat("jpeg")
+    .toFile(thumbnailPath);
+
+  return thumbnailPath;
+}
+
+/**
+ * Downloads generated images and mirrors them to the user_content directory.
+ * Mutates the result object.
+ */
+export async function mirrorGeneratedImage(
+  host: string,
+  prompt: string,
+  result: OpenAIImageGenerationResult
+): Promise<OpenAIImageGenerationResult> {
+  for (const item of result.data) {
+    let mirror: string;
+    if (item.b64_json) {
+      mirror = await saveB64Image(item.b64_json);
+    } else {
+      mirror = await downloadImage(item.url);
+    }
+    item.url = `${host}/user_content/${path.basename(mirror)}`;
+    await createThumbnail(mirror);
+    addToImageHistory({ url: item.url, prompt });
+  }
+  return result;
+}

src/shared/file-storage/setup-assets-dir.ts

@@ -0,0 +1,20 @@
+import { promises as fs } from "fs";
+import { logger } from "../../logger";
+import { USER_ASSETS_DIR } from "../../config";
+
+const log = logger.child({ module: "file-storage" });
+
+export async function setupAssetsDir() {
+  try {
+    log.info({ dir: USER_ASSETS_DIR }, "Setting up user assets directory");
+    await fs.mkdir(USER_ASSETS_DIR, { recursive: true });
+    const stats = await fs.stat(USER_ASSETS_DIR);
+    const mode = stats.mode | 0o666;
+    if (stats.mode !== mode) {
+      await fs.chmod(USER_ASSETS_DIR, mode);
+    }
+  } catch (e) {
+    log.error(e);
+    throw new Error("Could not create user assets directory for DALL-E image generation. You may need to update your Dockerfile to `chown` the working directory to user 1000. See the proxy docs for more information.");
+  }
+}

src/shared/inject-csrf.ts

@@ -1,11 +1,15 @@
 import { doubleCsrf } from "csrf-csrf";
 import express from "express";
-import { COOKIE_SECRET } from "../config";
+import { config, COOKIE_SECRET } from "../config";
 
 const { generateToken, doubleCsrfProtection } = doubleCsrf({
   getSecret: () => COOKIE_SECRET,
   cookieName: "csrf",
-  cookieOptions: { sameSite: "strict", path: "/" },
+  cookieOptions: {
+    sameSite: "strict",
+    path: "/",
+    secure: !config.useInsecureCookies,
+  },
   getTokenFromRequest: (req) => {
     const val = req.body["_csrf"] || req.query["_csrf"];
     delete req.body["_csrf"];

src/shared/inject-locals.ts

@@ -12,6 +12,7 @@ export const injectLocals: RequestHandler = (req, res, next) => {
   res.locals.quota = quota;
   res.locals.nextQuotaRefresh = userStore.getNextQuotaRefresh();
   res.locals.persistenceEnabled = config.gatekeeperStore !== "memory";
+  res.locals.usersEnabled = config.gatekeeper === "user_token";
   res.locals.showTokenCosts = config.showTokenCosts;
   res.locals.maxIps = config.maxIpsPerUser;
 

src/shared/key-management/anthropic/checker.ts

@@ -26,58 +26,36 @@ type AnthropicAPIError = {
 type UpdateFn = typeof AnthropicKeyProvider.prototype.update;
 
 export class AnthropicKeyChecker extends KeyCheckerBase<AnthropicKey> {
-  private readonly updateKey: UpdateFn;
-
   constructor(keys: AnthropicKey[], updateKey: UpdateFn) {
     super(keys, {
       service: "anthropic",
       keyCheckPeriod: KEY_CHECK_PERIOD,
       minCheckInterval: MIN_CHECK_INTERVAL,
+      updateKey,
     });
-    this.updateKey = updateKey;
   }
 
-  protected async checkKey(key: AnthropicKey) {
-    if (key.isDisabled) {
-      this.log.warn({ key: key.hash }, "Skipping check for disabled key.");
-      this.scheduleNextCheck();
-      return;
-    }
-
-    this.log.debug({ key: key.hash }, "Checking key...");
-    let isInitialCheck = !key.lastChecked;
-    try {
-      const [{ pozzed }] = await Promise.all([this.testLiveness(key)]);
-      const updates = { isPozzed: pozzed };
-      this.updateKey(key.hash, updates);
-      this.log.info(
-        { key: key.hash, models: key.modelFamilies },
-        "Key check complete."
-      );
-    } catch (error) {
-      // touch the key so we don't check it again for a while
-      this.updateKey(key.hash, {});
-      this.handleAxiosError(key, error as AxiosError);
-    }
-
-    this.lastCheck = Date.now();
-    // Only enqueue the next check if this wasn't a startup check, since those
-    // are batched together elsewhere.
-    if (!isInitialCheck) {
-      this.scheduleNextCheck();
-    }
+  protected async testKeyOrFail(key: AnthropicKey) {
+    const [{ pozzed }] = await Promise.all([this.testLiveness(key)]);
+    const updates = { isPozzed: pozzed };
+    this.updateKey(key.hash, updates);
+    this.log.info(
+      { key: key.hash, models: key.modelFamilies },
+      "Checked key."
+    );
   }
 
   protected handleAxiosError(key: AnthropicKey, error: AxiosError) {
     if (error.response && AnthropicKeyChecker.errorIsAnthropicAPIError(error)) {
       const { status, data } = error.response;
-      if (status === 401) {
+      if (status === 401 || status === 403) {
         this.log.warn(
           { key: key.hash, error: data },
           "Key is invalid or revoked. Disabling key."
         );
         this.updateKey(key.hash, { isDisabled: true, isRevoked: true });
-      } else if (status === 429) {
+      }
+      else if (status === 429) {
         switch (data.error.type) {
           case "rate_limit_error":
             this.log.warn(

src/shared/key-management/anthropic/provider.ts

@@ -6,14 +6,13 @@ import type { AnthropicModelFamily } from "../../models";
 import { AnthropicKeyChecker } from "./checker";
 
 // https://docs.anthropic.com/claude/reference/selecting-a-model
-export const ANTHROPIC_SUPPORTED_MODELS = [
-  "claude-instant-v1",
-  "claude-instant-v1-100k",
-  "claude-v1",
-  "claude-v1-100k",
-  "claude-2",
-] as const;
-export type AnthropicModel = (typeof ANTHROPIC_SUPPORTED_MODELS)[number];
+export type AnthropicModel =
+  | "claude-instant-v1"
+  | "claude-instant-v1-100k"
+  | "claude-v1"
+  | "claude-v1-100k"
+  | "claude-2"
+  | "claude-2.1";
 
 export type AnthropicKeyUpdate = Omit<
   Partial<AnthropicKey>,
@@ -153,11 +152,7 @@ export class AnthropicKeyProvider implements KeyProvider<AnthropicKey> {
 
     const selectedKey = keysByPriority[0];
     selectedKey.lastUsed = now;
-    selectedKey.rateLimitedAt = now;
-    // Intended to throttle the queue processor as otherwise it will just
-    // flood the API with requests and we want to wait a sec to see if we're
-    // going to get a rate limit error on this key.
-    selectedKey.rateLimitedUntil = now + KEY_REUSE_DELAY;
+    this.throttle(selectedKey.hash);
     return { ...selectedKey };
   }
 
@@ -184,7 +179,7 @@ export class AnthropicKeyProvider implements KeyProvider<AnthropicKey> {
     key.claudeTokens += tokens;
   }
 
-  public getLockoutPeriod(_model: AnthropicModel) {
+  public getLockoutPeriod() {
     const activeKeys = this.keys.filter((k) => !k.isDisabled);
     // Don't lock out if there are no keys available or the queue will stall.
     // Just let it through so the add-key middleware can throw an error.
@@ -226,4 +221,20 @@ export class AnthropicKeyProvider implements KeyProvider<AnthropicKey> {
     });
     this.checker?.scheduleNextCheck();
   }
+
+  /**
+   * Applies a short artificial delay to the key upon dequeueing, in order to
+   * prevent it from being immediately assigned to another request before the
+   * current one can be dispatched.
+   **/
+  private throttle(hash: string) {
+    const now = Date.now();
+    const key = this.keys.find((k) => k.hash === hash)!;
+
+    const currentRateLimit = key.rateLimitedUntil;
+    const nextRateLimit = now + KEY_REUSE_DELAY;
+
+    key.rateLimitedAt = now;
+    key.rateLimitedUntil = Math.max(currentRateLimit, nextRateLimit);
+  }
 }

src/shared/key-management/aws/checker.ts

@@ -8,11 +8,13 @@ import type { AwsBedrockKey, AwsBedrockKeyProvider } from "./provider";
 
 const MIN_CHECK_INTERVAL = 3 * 1000; // 3 seconds
 const KEY_CHECK_PERIOD = 3 * 60 * 1000; // 3 minutes
+const AMZ_HOST =
+  process.env.AMZ_HOST || "bedrock-runtime.%REGION%.amazonaws.com";
 const GET_CALLER_IDENTITY_URL = `https://sts.amazonaws.com/?Action=GetCallerIdentity&Version=2011-06-15`;
 const GET_INVOCATION_LOGGING_CONFIG_URL = (region: string) =>
   `https://bedrock.${region}.amazonaws.com/logging/modelinvocations`;
 const POST_INVOKE_MODEL_URL = (region: string, model: string) =>
-  `https://invoke-bedrock.${region}.amazonaws.com/model/${model}/invoke`;
+  `https://${AMZ_HOST.replace("%REGION%", region)}/model/${model}/invoke`;
 const TEST_PROMPT = "\n\nHuman:\n\nAssistant:";
 
 type AwsError = { error: {} };
@@ -30,58 +32,36 @@ type GetLoggingConfigResponse = {
 type UpdateFn = typeof AwsBedrockKeyProvider.prototype.update;
 
 export class AwsKeyChecker extends KeyCheckerBase<AwsBedrockKey> {
-  private readonly updateKey: UpdateFn;
-
   constructor(keys: AwsBedrockKey[], updateKey: UpdateFn) {
     super(keys, {
       service: "aws",
       keyCheckPeriod: KEY_CHECK_PERIOD,
       minCheckInterval: MIN_CHECK_INTERVAL,
+      updateKey,
     });
-    this.updateKey = updateKey;
   }
 
-  protected async checkKey(key: AwsBedrockKey) {
-    if (key.isDisabled) {
-      this.log.warn({ key: key.hash }, "Skipping check for disabled key.");
-      this.scheduleNextCheck();
-      return;
+  protected async testKeyOrFail(key: AwsBedrockKey) {
+    // Only check models on startup.  For now all models must be available to
+    // the proxy because we don't route requests to different keys.
+    const modelChecks: Promise<unknown>[] = [];
+    const isInitialCheck = !key.lastChecked;
+    if (isInitialCheck) {
+      modelChecks.push(this.invokeModel("anthropic.claude-v1", key));
+      modelChecks.push(this.invokeModel("anthropic.claude-v2", key));
     }
 
-    this.log.debug({ key: key.hash }, "Checking key...");
-    let isInitialCheck = !key.lastChecked;
-    try {
-      // Only check models on startup.  For now all models must be available to
-      // the proxy because we don't route requests to different keys.
-      const modelChecks: Promise<unknown>[] = [];
-      if (isInitialCheck) {
-        modelChecks.push(this.invokeModel("anthropic.claude-v1", key));
-        modelChecks.push(this.invokeModel("anthropic.claude-v2", key));
-      }
+    await Promise.all(modelChecks);
+    await this.checkLoggingConfiguration(key);
 
-      await Promise.all(modelChecks);
-      await this.checkLoggingConfiguration(key);
-
-      this.log.info(
-        {
-          key: key.hash,
-          models: key.modelFamilies,
-          logged: key.awsLoggingStatus,
-        },
-        "Key check complete."
-      );
-    } catch (error) {
-      this.handleAxiosError(key, error as AxiosError);
-    }
-
-    this.updateKey(key.hash, {});
-
-    this.lastCheck = Date.now();
-    // Only enqueue the next check if this wasn't a startup check, since those
-    // are batched together elsewhere.
-    if (!isInitialCheck) {
-      this.scheduleNextCheck();
-    }
+    this.log.info(
+      {
+        key: key.hash,
+        models: key.modelFamilies,
+        logged: key.awsLoggingStatus,
+      },
+      "Checked key."
+    );
   }
 
   protected handleAxiosError(key: AwsBedrockKey, error: AxiosError) {
@@ -165,12 +145,10 @@ export class AwsKeyChecker extends KeyCheckerBase<AwsBedrockKey> {
     const errorType = (headers["x-amzn-errortype"] as string).split(":")[0];
     const errorMessage = data?.message;
 
-    // We're looking for a specific error type and message here:
+    // We're looking for a specific error type and message here
     // "ValidationException"
-    // "Malformed input request: -1 is not greater or equal to 0, please reformat your input and try again."
-    // "Malformed input request: 2 schema violations found, please reformat your input and try again." (if there are multiple issues)
     const correctErrorType = errorType === "ValidationException";
-    const correctErrorMessage = errorMessage?.match(/malformed input request/i);
+    const correctErrorMessage = errorMessage?.match(/max_tokens_to_sample/);
     if (!correctErrorType || !correctErrorMessage) {
       throw new AxiosError(
         `Unexpected error when invoking model ${model}: ${errorMessage}`,
@@ -182,7 +160,7 @@ export class AwsKeyChecker extends KeyCheckerBase<AwsBedrockKey> {
     }
 
     this.log.debug(
-      { key: key.hash, errorType, data, status },
+      { key: key.hash, errorType, data, status, model },
       "Liveness test complete."
     );
   }

src/shared/key-management/aws/provider.ts

@@ -6,12 +6,10 @@ import type { AwsBedrockModelFamily } from "../../models";
 import { AwsKeyChecker } from "./checker";
 
 // https://docs.aws.amazon.com/bedrock/latest/userguide/model-ids-arns.html
-export const AWS_BEDROCK_SUPPORTED_MODELS = [
-  "anthropic.claude-v1",
-  "anthropic.claude-v2",
-  "anthropic.claude-instant-v1",
-] as const;
-export type AwsBedrockModel = (typeof AWS_BEDROCK_SUPPORTED_MODELS)[number];
+export type AwsBedrockModel =
+  | "anthropic.claude-v1"
+  | "anthropic.claude-v2"
+  | "anthropic.claude-instant-v1";
 
 type AwsBedrockKeyUsage = {
   [K in AwsBedrockModelFamily as `${K}Tokens`]: number;
@@ -37,13 +35,13 @@ export interface AwsBedrockKey extends Key, AwsBedrockKeyUsage {
  * Upon being rate limited, a key will be locked out for this many milliseconds
  * while we wait for other concurrent requests to finish.
  */
-const RATE_LIMIT_LOCKOUT = 300;
+const RATE_LIMIT_LOCKOUT = 4000;
 /**
  * Upon assigning a key, we will wait this many milliseconds before allowing it
  * to be used again. This is to prevent the queue from flooding a key with too
  * many requests while we wait to learn whether previous ones succeeded.
  */
-const KEY_REUSE_DELAY = 500;
+const KEY_REUSE_DELAY = 250;
 
 export class AwsBedrockKeyProvider implements KeyProvider<AwsBedrockKey> {
   readonly service = "aws";
@@ -131,11 +129,7 @@ export class AwsBedrockKeyProvider implements KeyProvider<AwsBedrockKey> {
 
     const selectedKey = keysByPriority[0];
     selectedKey.lastUsed = now;
-    selectedKey.rateLimitedAt = now;
-    // Intended to throttle the queue processor as otherwise it will just
-    // flood the API with requests and we want to wait a sec to see if we're
-    // going to get a rate limit error on this key.
-    selectedKey.rateLimitedUntil = now + KEY_REUSE_DELAY;
+    this.throttle(selectedKey.hash);
     return { ...selectedKey };
   }
 
@@ -162,7 +156,7 @@ export class AwsBedrockKeyProvider implements KeyProvider<AwsBedrockKey> {
     key["aws-claudeTokens"] += tokens;
   }
 
-  public getLockoutPeriod(_model: AwsBedrockModel) {
+  public getLockoutPeriod() {
     // TODO: same exact behavior for three providers, should be refactored
     const activeKeys = this.keys.filter((k) => !k.isDisabled);
     // Don't lock out if there are no keys available or the queue will stall.
@@ -199,4 +193,20 @@ export class AwsBedrockKeyProvider implements KeyProvider<AwsBedrockKey> {
       this.update(hash, { lastChecked: 0, isDisabled: false })
     );
   }
+
+  /**
+   * Applies a short artificial delay to the key upon dequeueing, in order to
+   * prevent it from being immediately assigned to another request before the
+   * current one can be dispatched.
+   **/
+  private throttle(hash: string) {
+    const now = Date.now();
+    const key = this.keys.find((k) => k.hash === hash)!;
+
+    const currentRateLimit = key.rateLimitedUntil;
+    const nextRateLimit = now + KEY_REUSE_DELAY;
+
+    key.rateLimitedAt = now;
+    key.rateLimitedUntil = Math.max(currentRateLimit, nextRateLimit);
+  }
 }

src/shared/key-management/azure/checker.ts

@@ -0,0 +1,164 @@
+import axios, { AxiosError } from "axios";
+import { KeyCheckerBase } from "../key-checker-base";
+import type { AzureOpenAIKey, AzureOpenAIKeyProvider } from "./provider";
+import { getAzureOpenAIModelFamily } from "../../models";
+
+const MIN_CHECK_INTERVAL = 3 * 1000; // 3 seconds
+const KEY_CHECK_PERIOD = 3 * 60 * 1000; // 3 minutes
+const AZURE_HOST = process.env.AZURE_HOST || "%RESOURCE_NAME%.openai.azure.com";
+const POST_CHAT_COMPLETIONS = (resourceName: string, deploymentId: string) =>
+  `https://${AZURE_HOST.replace(
+    "%RESOURCE_NAME%",
+    resourceName
+  )}/openai/deployments/${deploymentId}/chat/completions?api-version=2023-09-01-preview`;
+
+type AzureError = {
+  error: {
+    message: string;
+    type: string | null;
+    param: string;
+    code: string;
+    status: number;
+  };
+};
+type UpdateFn = typeof AzureOpenAIKeyProvider.prototype.update;
+
+export class AzureOpenAIKeyChecker extends KeyCheckerBase<AzureOpenAIKey> {
+  constructor(keys: AzureOpenAIKey[], updateKey: UpdateFn) {
+    super(keys, {
+      service: "azure",
+      keyCheckPeriod: KEY_CHECK_PERIOD,
+      minCheckInterval: MIN_CHECK_INTERVAL,
+      recurringChecksEnabled: false,
+      updateKey,
+    });
+  }
+
+  protected async testKeyOrFail(key: AzureOpenAIKey) {
+    const model = await this.testModel(key);
+    this.log.info({ key: key.hash, deploymentModel: model }, "Checked key.");
+    this.updateKey(key.hash, { modelFamilies: [model] });
+  }
+
+  protected handleAxiosError(key: AzureOpenAIKey, error: AxiosError) {
+    if (error.response && AzureOpenAIKeyChecker.errorIsAzureError(error)) {
+      const data = error.response.data;
+      const status = data.error.status;
+      const errorType = data.error.code || data.error.type;
+      switch (errorType) {
+        case "DeploymentNotFound":
+          this.log.warn(
+            { key: key.hash, errorType, error: error.response.data },
+            "Key is revoked or deployment ID is incorrect. Disabling key."
+          );
+          return this.updateKey(key.hash, {
+            isDisabled: true,
+            isRevoked: true,
+          });
+        case "401":
+          this.log.warn(
+            { key: key.hash, errorType, error: error.response.data },
+            "Key is disabled or incorrect. Disabling key."
+          );
+          return this.updateKey(key.hash, {
+            isDisabled: true,
+            isRevoked: true,
+          });
+        case "429":
+          this.log.warn(
+            { key: key.hash, errorType, error: error.response.data },
+            "Key is rate limited. Rechecking key in 1 minute."
+          );
+          this.updateKey(key.hash, { lastChecked: Date.now() });
+          setTimeout(async () => {
+            this.log.info(
+              { key: key.hash },
+              "Rechecking Azure key after rate limit."
+            );
+            await this.checkKey(key);
+          }, 1000 * 60);
+          return;
+        default:
+          this.log.error(
+            { key: key.hash, errorType, error: error.response.data, status },
+            "Unknown Azure API error while checking key. Please report this."
+          );
+          return this.updateKey(key.hash, { lastChecked: Date.now() });
+      }
+    }
+
+    const { response, code } = error;
+    if (code === "ENOTFOUND") {
+      this.log.warn(
+        { key: key.hash, error: error.message },
+        "Resource name is probably incorrect. Disabling key."
+      );
+      return this.updateKey(key.hash, { isDisabled: true, isRevoked: true });
+    }
+
+    const { headers, status, data } = response ?? {};
+    this.log.error(
+      { key: key.hash, status, headers, data, error: error.message },
+      "Network error while checking key; trying this key again in a minute."
+    );
+    const oneMinute = 60 * 1000;
+    const next = Date.now() - (KEY_CHECK_PERIOD - oneMinute);
+    this.updateKey(key.hash, { lastChecked: next });
+  }
+
+  private async testModel(key: AzureOpenAIKey) {
+    const { apiKey, deploymentId, resourceName } =
+      AzureOpenAIKeyChecker.getCredentialsFromKey(key);
+    const url = POST_CHAT_COMPLETIONS(resourceName, deploymentId);
+    const testRequest = {
+      max_tokens: 1,
+      stream: false,
+      messages: [{ role: "user", content: "" }],
+    };
+    const { data } = await axios.post(url, testRequest, {
+      headers: { "Content-Type": "application/json", "api-key": apiKey },
+    });
+
+    const family = getAzureOpenAIModelFamily(data.model);
+
+    // Azure returns "gpt-4" even for GPT-4 Turbo, so we need further checks.
+    // Otherwise we can use the model family Azure returned.
+    if (family !== "azure-gpt4") {
+      return family;
+    }
+
+    // Try to send an oversized prompt. GPT-4 Turbo can handle this but regular
+    // GPT-4 will return a Bad Request error.
+    const contextText = {
+      max_tokens: 9000,
+      stream: false,
+      temperature: 0,
+      seed: 0,
+      messages: [{ role: "user", content: "" }],
+    };
+    const { data: contextTest, status } = await axios.post(url, contextText, {
+      headers: { "Content-Type": "application/json", "api-key": apiKey },
+      validateStatus: (status) => status === 400 || status === 200,
+    });
+    const code = contextTest.error?.code;
+    this.log.debug({ code, status }, "Performed Azure GPT4 context size test.");
+
+    if (code === "context_length_exceeded") return "azure-gpt4";
+    return "azure-gpt4-turbo";
+  }
+
+  static errorIsAzureError(error: AxiosError): error is AxiosError<AzureError> {
+    const data = error.response?.data as any;
+    return data?.error?.code || data?.error?.type;
+  }
+
+  static getCredentialsFromKey(key: AzureOpenAIKey) {
+    const [resourceName, deploymentId, apiKey] = key.key.split(":");
+    if (!resourceName || !deploymentId || !apiKey) {
+      throw new Error(
+        "Invalid Azure credential format. Refer to .env.example and ensure your credentials are in the format RESOURCE_NAME:DEPLOYMENT_ID:API_KEY with commas between each credential set."
+      );
+    }
+    return { resourceName, deploymentId, apiKey };
+  }
+}

src/shared/key-management/azure/provider.ts

@@ -0,0 +1,214 @@
+import crypto from "crypto";
+import { Key, KeyProvider } from "..";
+import { config } from "../../../config";
+import { logger } from "../../../logger";
+import type { AzureOpenAIModelFamily } from "../../models";
+import { getAzureOpenAIModelFamily } from "../../models";
+import { OpenAIModel } from "../openai/provider";
+import { AzureOpenAIKeyChecker } from "./checker";
+
+export type AzureOpenAIModel = Exclude<OpenAIModel, "dall-e">;
+
+type AzureOpenAIKeyUsage = {
+  [K in AzureOpenAIModelFamily as `${K}Tokens`]: number;
+};
+
+export interface AzureOpenAIKey extends Key, AzureOpenAIKeyUsage {
+  readonly service: "azure";
+  readonly modelFamilies: AzureOpenAIModelFamily[];
+  /** The time at which this key was last rate limited. */
+  rateLimitedAt: number;
+  /** The time until which this key is rate limited. */
+  rateLimitedUntil: number;
+  contentFiltering: boolean;
+}
+
+/**
+ * Upon being rate limited, a key will be locked out for this many milliseconds
+ * while we wait for other concurrent requests to finish.
+ */
+const RATE_LIMIT_LOCKOUT = 4000;
+/**
+ * Upon assigning a key, we will wait this many milliseconds before allowing it
+ * to be used again. This is to prevent the queue from flooding a key with too
+ * many requests while we wait to learn whether previous ones succeeded.
+ */
+const KEY_REUSE_DELAY = 250;
+
+export class AzureOpenAIKeyProvider implements KeyProvider<AzureOpenAIKey> {
+  readonly service = "azure";
+
+  private keys: AzureOpenAIKey[] = [];
+  private checker?: AzureOpenAIKeyChecker;
+  private log = logger.child({ module: "key-provider", service: this.service });
+
+  constructor() {
+    const keyConfig = config.azureCredentials;
+    if (!keyConfig) {
+      this.log.warn(
+        "AZURE_CREDENTIALS is not set. Azure OpenAI API will not be available."
+      );
+      return;
+    }
+    let bareKeys: string[];
+    bareKeys = [...new Set(keyConfig.split(",").map((k) => k.trim()))];
+    for (const key of bareKeys) {
+      const newKey: AzureOpenAIKey = {
+        key,
+        service: this.service,
+        modelFamilies: ["azure-gpt4"],
+        isDisabled: false,
+        isRevoked: false,
+        promptCount: 0,
+        lastUsed: 0,
+        rateLimitedAt: 0,
+        rateLimitedUntil: 0,
+        contentFiltering: false,
+        hash: `azu-${crypto
+          .createHash("sha256")
+          .update(key)
+          .digest("hex")
+          .slice(0, 8)}`,
+        lastChecked: 0,
+        "azure-turboTokens": 0,
+        "azure-gpt4Tokens": 0,
+        "azure-gpt4-32kTokens": 0,
+        "azure-gpt4-turboTokens": 0,
+      };
+      this.keys.push(newKey);
+    }
+    this.log.info({ keyCount: this.keys.length }, "Loaded Azure OpenAI keys.");
+  }
+
+  public init() {
+    if (config.checkKeys) {
+      this.checker = new AzureOpenAIKeyChecker(
+        this.keys,
+        this.update.bind(this)
+      );
+      this.checker.start();
+    }
+  }
+
+  public list() {
+    return this.keys.map((k) => Object.freeze({ ...k, key: undefined }));
+  }
+
+  public get(model: AzureOpenAIModel) {
+    const neededFamily = getAzureOpenAIModelFamily(model);
+    const availableKeys = this.keys.filter(
+      (k) => !k.isDisabled && k.modelFamilies.includes(neededFamily)
+    );
+    if (availableKeys.length === 0) {
+      throw new Error(`No keys available for model family '${neededFamily}'.`);
+    }
+
+    // (largely copied from the OpenAI provider, without trial key support)
+    // Select a key, from highest priority to lowest priority:
+    // 1. Keys which are not rate limited
+    //    a. If all keys were rate limited recently, select the least-recently
+    //       rate limited key.
+    // 3. Keys which have not been used in the longest time
+
+    const now = Date.now();
+
+    const keysByPriority = availableKeys.sort((a, b) => {
+      const aRateLimited = now - a.rateLimitedAt < RATE_LIMIT_LOCKOUT;
+      const bRateLimited = now - b.rateLimitedAt < RATE_LIMIT_LOCKOUT;
+
+      if (aRateLimited && !bRateLimited) return 1;
+      if (!aRateLimited && bRateLimited) return -1;
+      if (aRateLimited && bRateLimited) {
+        return a.rateLimitedAt - b.rateLimitedAt;
+      }
+
+      return a.lastUsed - b.lastUsed;
+    });
+
+    const selectedKey = keysByPriority[0];
+    selectedKey.lastUsed = now;
+    this.throttle(selectedKey.hash);
+    return { ...selectedKey };
+  }
+
+  public disable(key: AzureOpenAIKey) {
+    const keyFromPool = this.keys.find((k) => k.hash === key.hash);
+    if (!keyFromPool || keyFromPool.isDisabled) return;
+    keyFromPool.isDisabled = true;
+    this.log.warn({ key: key.hash }, "Key disabled");
+  }
+
+  public update(hash: string, update: Partial<AzureOpenAIKey>) {
+    const keyFromPool = this.keys.find((k) => k.hash === hash)!;
+    Object.assign(keyFromPool, { lastChecked: Date.now(), ...update });
+  }
+
+  public available() {
+    return this.keys.filter((k) => !k.isDisabled).length;
+  }
+
+  public incrementUsage(hash: string, model: string, tokens: number) {
+    const key = this.keys.find((k) => k.hash === hash);
+    if (!key) return;
+    key.promptCount++;
+    key[`${getAzureOpenAIModelFamily(model)}Tokens`] += tokens;
+  }
+
+  // TODO: all of this shit is duplicate code
+
+  public getLockoutPeriod(family: AzureOpenAIModelFamily) {
+    const activeKeys = this.keys.filter(
+      (key) => !key.isDisabled && key.modelFamilies.includes(family)
+    );
+
+    // Don't lock out if there are no keys available or the queue will stall.
+    // Just let it through so the add-key middleware can throw an error.
+    if (activeKeys.length === 0) return 0;
+
+    const now = Date.now();
+    const rateLimitedKeys = activeKeys.filter((k) => now < k.rateLimitedUntil);
+    const anyNotRateLimited = rateLimitedKeys.length < activeKeys.length;
+
+    if (anyNotRateLimited) return 0;
+
+    // If all keys are rate-limited, return time until the first key is ready.
+    return Math.min(...activeKeys.map((k) => k.rateLimitedUntil - now));
+  }
+
+  /**
+   * This is called when we receive a 429, which means there are already five
+   * concurrent requests running on this key. We don't have any information on
+   * when these requests will resolve, so all we can do is wait a bit and try
+   * again. We will lock the key for 2 seconds after getting a 429 before
+   * retrying in order to give the other requests a chance to finish.
+   */
+  public markRateLimited(keyHash: string) {
+    this.log.debug({ key: keyHash }, "Key rate limited");
+    const key = this.keys.find((k) => k.hash === keyHash)!;
+    const now = Date.now();
+    key.rateLimitedAt = now;
+    key.rateLimitedUntil = now + RATE_LIMIT_LOCKOUT;
+  }
+
+  public recheck() {
+    this.keys.forEach(({ hash }) =>
+      this.update(hash, { lastChecked: 0, isDisabled: false })
+    );
+  }
+
+  /**
+   * Applies a short artificial delay to the key upon dequeueing, in order to
+   * prevent it from being immediately assigned to another request before the
+   * current one can be dispatched.
+   **/
+  private throttle(hash: string) {
+    const now = Date.now();
+    const key = this.keys.find((k) => k.hash === hash)!;
+
+    const currentRateLimit = key.rateLimitedUntil;
+    const nextRateLimit = now + KEY_REUSE_DELAY;
+
+    key.rateLimitedAt = now;
+    key.rateLimitedUntil = Math.max(currentRateLimit, nextRateLimit);
+  }
+}

src/shared/key-management/google-ai/provider.ts

@@ -2,17 +2,17 @@ import crypto from "crypto";
 import { Key, KeyProvider } from "..";
 import { config } from "../../../config";
 import { logger } from "../../../logger";
-import type { GooglePalmModelFamily } from "../../models";
+import type { GoogleAIModelFamily } from "../../models";
 
-// https://developers.generativeai.google.com/models/language
-export const GOOGLE_PALM_SUPPORTED_MODELS = [
-  "text-bison-001",
-  // "chat-bison-001", no adjustable safety settings, so it's useless
-] as const;
-export type GooglePalmModel = (typeof GOOGLE_PALM_SUPPORTED_MODELS)[number];
+// Note that Google AI is not the same as Vertex AI, both are provided by Google
+// but Vertex is the GCP product for enterprise. while Google AI is the
+// consumer-ish product. The API is different, and keys are not compatible.
+// https://ai.google.dev/docs/migrate_to_cloud
 
-export type GooglePalmKeyUpdate = Omit<
-  Partial<GooglePalmKey>,
+export type GoogleAIModel = "gemini-pro";
+
+export type GoogleAIKeyUpdate = Omit<
+  Partial<GoogleAIKey>,
   | "key"
   | "hash"
   | "lastUsed"
@@ -21,13 +21,13 @@ export type GooglePalmKeyUpdate = Omit<
   | "rateLimitedUntil"
 >;
 
-type GooglePalmKeyUsage = {
-  [K in GooglePalmModelFamily as `${K}Tokens`]: number;
+type GoogleAIKeyUsage = {
+  [K in GoogleAIModelFamily as `${K}Tokens`]: number;
 };
 
-export interface GooglePalmKey extends Key, GooglePalmKeyUsage {
-  readonly service: "google-palm";
-  readonly modelFamilies: GooglePalmModelFamily[];
+export interface GoogleAIKey extends Key, GoogleAIKeyUsage {
+  readonly service: "google-ai";
+  readonly modelFamilies: GoogleAIModelFamily[];
   /** The time at which this key was last rate limited. */
   rateLimitedAt: number;
   /** The time until which this key is rate limited. */
@@ -46,27 +46,27 @@ const RATE_LIMIT_LOCKOUT = 2000;
  */
 const KEY_REUSE_DELAY = 500;
 
-export class GooglePalmKeyProvider implements KeyProvider<GooglePalmKey> {
-  readonly service = "google-palm";
+export class GoogleAIKeyProvider implements KeyProvider<GoogleAIKey> {
+  readonly service = "google-ai";
 
-  private keys: GooglePalmKey[] = [];
+  private keys: GoogleAIKey[] = [];
   private log = logger.child({ module: "key-provider", service: this.service });
 
   constructor() {
-    const keyConfig = config.googlePalmKey?.trim();
+    const keyConfig = config.googleAIKey?.trim();
     if (!keyConfig) {
       this.log.warn(
-        "GOOGLE_PALM_KEY is not set. PaLM API will not be available."
+        "GOOGLE_AI_KEY is not set. Google AI API will not be available."
       );
       return;
     }
     let bareKeys: string[];
     bareKeys = [...new Set(keyConfig.split(",").map((k) => k.trim()))];
     for (const key of bareKeys) {
-      const newKey: GooglePalmKey = {
+      const newKey: GoogleAIKey = {
         key,
         service: this.service,
-        modelFamilies: ["bison"],
+        modelFamilies: ["gemini-pro"],
         isDisabled: false,
         isRevoked: false,
         promptCount: 0,
@@ -79,11 +79,11 @@ export class GooglePalmKeyProvider implements KeyProvider<GooglePalmKey> {
           .digest("hex")
           .slice(0, 8)}`,
         lastChecked: 0,
-        bisonTokens: 0,
+        "gemini-proTokens": 0,
       };
       this.keys.push(newKey);
     }
-    this.log.info({ keyCount: this.keys.length }, "Loaded PaLM keys.");
+    this.log.info({ keyCount: this.keys.length }, "Loaded Google AI keys.");
   }
 
   public init() {}
@@ -92,10 +92,10 @@ export class GooglePalmKeyProvider implements KeyProvider<GooglePalmKey> {
     return this.keys.map((k) => Object.freeze({ ...k, key: undefined }));
   }
 
-  public get(_model: GooglePalmModel) {
+  public get(_model: GoogleAIModel) {
     const availableKeys = this.keys.filter((k) => !k.isDisabled);
     if (availableKeys.length === 0) {
-      throw new Error("No Google PaLM keys available");
+      throw new Error("No Google AI keys available");
     }
 
     // (largely copied from the OpenAI provider, without trial key support)
@@ -122,22 +122,18 @@ export class GooglePalmKeyProvider implements KeyProvider<GooglePalmKey> {
 
     const selectedKey = keysByPriority[0];
     selectedKey.lastUsed = now;
-    selectedKey.rateLimitedAt = now;
-    // Intended to throttle the queue processor as otherwise it will just
-    // flood the API with requests and we want to wait a sec to see if we're
-    // going to get a rate limit error on this key.
-    selectedKey.rateLimitedUntil = now + KEY_REUSE_DELAY;
+    this.throttle(selectedKey.hash);
     return { ...selectedKey };
   }
 
-  public disable(key: GooglePalmKey) {
+  public disable(key: GoogleAIKey) {
     const keyFromPool = this.keys.find((k) => k.hash === key.hash);
     if (!keyFromPool || keyFromPool.isDisabled) return;
     keyFromPool.isDisabled = true;
     this.log.warn({ key: key.hash }, "Key disabled");
   }
 
-  public update(hash: string, update: Partial<GooglePalmKey>) {
+  public update(hash: string, update: Partial<GoogleAIKey>) {
     const keyFromPool = this.keys.find((k) => k.hash === hash)!;
     Object.assign(keyFromPool, { lastChecked: Date.now(), ...update });
   }
@@ -150,10 +146,10 @@ export class GooglePalmKeyProvider implements KeyProvider<GooglePalmKey> {
     const key = this.keys.find((k) => k.hash === hash);
     if (!key) return;
     key.promptCount++;
-    key.bisonTokens += tokens;
+    key["gemini-proTokens"] += tokens;
   }
 
-  public getLockoutPeriod(_model: GooglePalmModel) {
+  public getLockoutPeriod() {
     const activeKeys = this.keys.filter((k) => !k.isDisabled);
     // Don't lock out if there are no keys available or the queue will stall.
     // Just let it through so the add-key middleware can throw an error.
@@ -186,4 +182,20 @@ export class GooglePalmKeyProvider implements KeyProvider<GooglePalmKey> {
   }
 
   public recheck() {}
+
+  /**
+   * Applies a short artificial delay to the key upon dequeueing, in order to
+   * prevent it from being immediately assigned to another request before the
+   * current one can be dispatched.
+   **/
+  private throttle(hash: string) {
+    const now = Date.now();
+    const key = this.keys.find((k) => k.hash === hash)!;
+
+    const currentRateLimit = key.rateLimitedUntil;
+    const nextRateLimit = now + KEY_REUSE_DELAY;
+
+    key.rateLimitedAt = now;
+    key.rateLimitedUntil = Math.max(currentRateLimit, nextRateLimit);
+  }
 }

src/shared/key-management/index.ts

@@ -1,22 +1,25 @@
-import { OPENAI_SUPPORTED_MODELS, OpenAIModel } from "./openai/provider";
-import {
-  ANTHROPIC_SUPPORTED_MODELS,
-  AnthropicModel,
-} from "./anthropic/provider";
-import { GOOGLE_PALM_SUPPORTED_MODELS, GooglePalmModel } from "./palm/provider";
-import { AWS_BEDROCK_SUPPORTED_MODELS, AwsBedrockModel } from "./aws/provider";
+import type { LLMService, ModelFamily } from "../models";
+import { OpenAIModel } from "./openai/provider";
+import { AnthropicModel } from "./anthropic/provider";
+import { GoogleAIModel } from "./google-ai/provider";
+import { AwsBedrockModel } from "./aws/provider";
+import { AzureOpenAIModel } from "./azure/provider";
 import { KeyPool } from "./key-pool";
-import type { ModelFamily } from "../models";
 
 /** The request and response format used by a model's API. */
-export type APIFormat = "openai" | "anthropic" | "google-palm" | "openai-text";
-/** The service that a model is hosted on; distinct because services like AWS provide multiple APIs, but have their own endpoints and authentication. */
-export type LLMService = "openai" | "anthropic" | "google-palm" | "aws";
+export type APIFormat =
+  | "openai"
+  | "anthropic"
+  | "google-ai"
+  | "mistral-ai"
+  | "openai-text"
+  | "openai-image";
 export type Model =
   | OpenAIModel
   | AnthropicModel
-  | GooglePalmModel
-  | AwsBedrockModel;
+  | GoogleAIModel
+  | AwsBedrockModel
+  | AzureOpenAIModel;
 
 export interface Key {
   /** The API key itself. Never log this, use `hash` instead. */
@@ -60,24 +63,14 @@ export interface KeyProvider<T extends Key = Key> {
   update(hash: string, update: Partial<T>): void;
   available(): number;
   incrementUsage(hash: string, model: string, tokens: number): void;
-  getLockoutPeriod(model: Model): number;
+  getLockoutPeriod(model: ModelFamily): number;
   markRateLimited(hash: string): void;
   recheck(): void;
 }
 
 export const keyPool = new KeyPool();
-export const SUPPORTED_MODELS = [
-  ...OPENAI_SUPPORTED_MODELS,
-  ...ANTHROPIC_SUPPORTED_MODELS,
-] as const;
-export type SupportedModel = (typeof SUPPORTED_MODELS)[number];
-export {
-  OPENAI_SUPPORTED_MODELS,
-  ANTHROPIC_SUPPORTED_MODELS,
-  GOOGLE_PALM_SUPPORTED_MODELS,
-  AWS_BEDROCK_SUPPORTED_MODELS,
-};
 export { AnthropicKey } from "./anthropic/provider";
 export { OpenAIKey } from "./openai/provider";
-export { GooglePalmKey } from "./palm/provider";
-export { AwsBedrockKey } from "./aws/provider";
+export { GoogleAIKey } from "././google-ai/provider";
+export { AwsBedrockKey } from "./aws/provider";
+export { AzureOpenAIKey } from "./azure/provider";

src/shared/key-management/key-checker-base.ts

@@ -3,14 +3,17 @@ import { logger } from "../../logger";
 import { Key } from "./index";
 import { AxiosError } from "axios";
 
-type KeyCheckerOptions = {
+type KeyCheckerOptions<TKey extends Key = Key> = {
   service: string;
   keyCheckPeriod: number;
   minCheckInterval: number;
-}
+  recurringChecksEnabled?: boolean;
+  updateKey: (hash: string, props: Partial<TKey>) => void;
+};
 
 export abstract class KeyCheckerBase<TKey extends Key> {
   protected readonly service: string;
+  protected readonly RECURRING_CHECKS_ENABLED: boolean;
   /** Minimum time in between any two key checks. */
   protected readonly MIN_CHECK_INTERVAL: number;
   /**
@@ -19,16 +22,19 @@ export abstract class KeyCheckerBase<TKey extends Key> {
    * than this.
    */
   protected readonly KEY_CHECK_PERIOD: number;
+  protected readonly updateKey: (hash: string, props: Partial<TKey>) => void;
   protected readonly keys: TKey[] = [];
   protected log: pino.Logger;
   protected timeout?: NodeJS.Timeout;
   protected lastCheck = 0;
 
-  protected constructor(keys: TKey[], opts: KeyCheckerOptions) {
+  protected constructor(keys: TKey[], opts: KeyCheckerOptions<TKey>) {
     const { service, keyCheckPeriod, minCheckInterval } = opts;
     this.keys = keys;
     this.KEY_CHECK_PERIOD = keyCheckPeriod;
     this.MIN_CHECK_INTERVAL = minCheckInterval;
+    this.RECURRING_CHECKS_ENABLED = opts.recurringChecksEnabled ?? true;
+    this.updateKey = opts.updateKey;
     this.service = service;
     this.log = logger.child({ module: "key-checker", service });
   }
@@ -52,31 +58,34 @@ export abstract class KeyCheckerBase<TKey extends Key> {
    * the minimum check interval.
    */
   public scheduleNextCheck() {
+    // Gives each concurrent check a correlation ID to make logs less confusing.
     const callId = Math.random().toString(36).slice(2, 8);
     const timeoutId = this.timeout?.[Symbol.toPrimitive]?.();
     const checkLog = this.log.child({ callId, timeoutId });
 
     const enabledKeys = this.keys.filter((key) => !key.isDisabled);
-    checkLog.debug({ enabled: enabledKeys.length }, "Scheduling next check...");
+    const uncheckedKeys = enabledKeys.filter((key) => !key.lastChecked);
+    const numEnabled = enabledKeys.length;
+    const numUnchecked = uncheckedKeys.length;
 
     clearTimeout(this.timeout);
+    this.timeout = undefined;
 
-    if (enabledKeys.length === 0) {
-      checkLog.warn("All keys are disabled. Key checker stopping.");
+    if (!numEnabled) {
+      checkLog.warn("All keys are disabled. Stopping.");
       return;
     }
 
-    // Perform startup checks for any keys that haven't been checked yet.
-    const uncheckedKeys = enabledKeys.filter((key) => !key.lastChecked);
-    checkLog.debug({ unchecked: uncheckedKeys.length }, "# of unchecked keys");
-    if (uncheckedKeys.length > 0) {
-      const keysToCheck = uncheckedKeys.slice(0, 12);
+    checkLog.debug({ numEnabled, numUnchecked }, "Scheduling next check...");
+
+    if (numUnchecked > 0) {
+      const keycheckBatch = uncheckedKeys.slice(0, 12);
 
       this.timeout = setTimeout(async () => {
         try {
-          await Promise.all(keysToCheck.map((key) => this.checkKey(key)));
+          await Promise.all(keycheckBatch.map((key) => this.checkKey(key)));
         } catch (error) {
-          this.log.error({ error }, "Error checking one or more keys.");
+          checkLog.error({ error }, "Error checking one or more keys.");
         }
         checkLog.info("Batch complete.");
         this.scheduleNextCheck();
@@ -84,11 +93,18 @@ export abstract class KeyCheckerBase<TKey extends Key> {
 
       checkLog.info(
         {
-          batch: keysToCheck.map((k) => k.hash),
-          remaining: uncheckedKeys.length - keysToCheck.length,
+          batch: keycheckBatch.map((k) => k.hash),
+          remaining: uncheckedKeys.length - keycheckBatch.length,
           newTimeoutId: this.timeout?.[Symbol.toPrimitive]?.(),
         },
-        "Scheduled batch check."
+        "Scheduled batch of initial checks."
+      );
+      return;
+    }
+
+    if (!this.RECURRING_CHECKS_ENABLED) {
+      checkLog.info(
+        "Initial checks complete and recurring checks are disabled for this service. Stopping."
       );
       return;
     }
@@ -106,14 +122,35 @@ export abstract class KeyCheckerBase<TKey extends Key> {
     );
 
     const delay = nextCheck - Date.now();
-    this.timeout = setTimeout(() => this.checkKey(oldestKey), delay);
+    this.timeout = setTimeout(
+      () => this.checkKey(oldestKey).then(() => this.scheduleNextCheck()),
+      delay
+    );
     checkLog.debug(
       { key: oldestKey.hash, nextCheck: new Date(nextCheck), delay },
-      "Scheduled single key check."
+      "Scheduled next recurring check."
     );
   }
 
-  protected abstract checkKey(key: TKey): Promise<void>;
+  public async checkKey(key: TKey): Promise<void> {
+    if (key.isDisabled) {
+      this.log.warn({ key: key.hash }, "Skipping check for disabled key.");
+      this.scheduleNextCheck();
+      return;
+    }
+    this.log.debug({ key: key.hash }, "Checking key...");
+
+    try {
+      await this.testKeyOrFail(key);
+    } catch (error) {
+      this.updateKey(key.hash, {});
+      this.handleAxiosError(key, error as AxiosError);
+    }
+
+    this.lastCheck = Date.now();
+  }
+
+  protected abstract testKeyOrFail(key: TKey): Promise<void>;
 
   protected abstract handleAxiosError(key: TKey, error: AxiosError): void;
-}
+}

src/shared/key-management/key-pool.ts

@@ -4,11 +4,14 @@ import os from "os";
 import schedule from "node-schedule";
 import { config } from "../../config";
 import { logger } from "../../logger";
-import { Key, Model, KeyProvider, LLMService } from "./index";
+import { LLMService, MODEL_FAMILY_SERVICE, ModelFamily } from "../models";
+import { Key, Model, KeyProvider } from "./index";
 import { AnthropicKeyProvider, AnthropicKeyUpdate } from "./anthropic/provider";
 import { OpenAIKeyProvider, OpenAIKeyUpdate } from "./openai/provider";
-import { GooglePalmKeyProvider } from "./palm/provider";
+import { GoogleAIKeyProvider } from "./google-ai/provider";
 import { AwsBedrockKeyProvider } from "./aws/provider";
+import { AzureOpenAIKeyProvider } from "./azure/provider";
+import { MistralAIKeyProvider } from "./mistral-ai/provider";
 
 type AllowedPartial = OpenAIKeyUpdate | AnthropicKeyUpdate;
 
@@ -21,8 +24,10 @@ export class KeyPool {
   constructor() {
     this.keyProviders.push(new OpenAIKeyProvider());
     this.keyProviders.push(new AnthropicKeyProvider());
-    this.keyProviders.push(new GooglePalmKeyProvider());
+    this.keyProviders.push(new GoogleAIKeyProvider());
+    this.keyProviders.push(new MistralAIKeyProvider());
     this.keyProviders.push(new AwsBedrockKeyProvider());
+    this.keyProviders.push(new AzureOpenAIKeyProvider());
   }
 
   public init() {
@@ -37,7 +42,7 @@ export class KeyPool {
   }
 
   public get(model: Model): Key {
-    const service = this.getService(model);
+    const service = this.getServiceForModel(model);
     return this.getKeyProvider(service).get(model);
   }
 
@@ -67,7 +72,7 @@ export class KeyPool {
   public available(model: Model | "all" = "all"): number {
     return this.keyProviders.reduce((sum, provider) => {
       const includeProvider =
-        model === "all" || this.getService(model) === provider.service;
+        model === "all" || this.getServiceForModel(model) === provider.service;
       return sum + (includeProvider ? provider.available() : 0);
     }, 0);
   }
@@ -77,9 +82,9 @@ export class KeyPool {
     provider.incrementUsage(key.hash, model, tokens);
   }
 
-  public getLockoutPeriod(model: Model): number {
-    const service = this.getService(model);
-    return this.getKeyProvider(service).getLockoutPeriod(model);
+  public getLockoutPeriod(family: ModelFamily): number {
+    const service = MODEL_FAMILY_SERVICE[family];
+    return this.getKeyProvider(service).getLockoutPeriod(family);
   }
 
   public markRateLimited(key: Key): void {
@@ -104,20 +109,29 @@ export class KeyPool {
     provider.recheck();
   }
 
-  private getService(model: Model): LLMService {
-    if (model.startsWith("gpt") || model.startsWith("text-embedding-ada")) {
+  private getServiceForModel(model: Model): LLMService {
+    if (
+      model.startsWith("gpt") ||
+      model.startsWith("text-embedding-ada") ||
+      model.startsWith("dall-e")
+    ) {
       // https://platform.openai.com/docs/models/model-endpoint-compatibility
       return "openai";
     } else if (model.startsWith("claude-")) {
       // https://console.anthropic.com/docs/api/reference#parameters
       return "anthropic";
-    } else if (model.includes("bison")) {
+    } else if (model.includes("gemini")) {
       // https://developers.generativeai.google.com/models/language
-      return "google-palm";
+      return "google-ai";
+    } else if (model.includes("mistral")) {
+      // https://docs.mistral.ai/platform/endpoints
+      return "mistral-ai";
     } else if (model.startsWith("anthropic.claude")) {
       // AWS offers models from a few providers
       // https://docs.aws.amazon.com/bedrock/latest/userguide/model-ids-arns.html
       return "aws";
+    } else if (model.startsWith("azure")) {
+      return "azure";
     }
     throw new Error(`Unknown service for model '${model}'`);
   }

src/shared/key-management/mistral-ai/checker.ts

@@ -0,0 +1,112 @@
+import axios, { AxiosError } from "axios";
+import type { MistralAIModelFamily, OpenAIModelFamily } from "../../models";
+import { KeyCheckerBase } from "../key-checker-base";
+import type { MistralAIKey, MistralAIKeyProvider } from "./provider";
+import { getMistralAIModelFamily, getOpenAIModelFamily } from "../../models";
+
+const MIN_CHECK_INTERVAL = 3 * 1000; // 3 seconds
+const KEY_CHECK_PERIOD = 60 * 60 * 1000; // 1 hour
+const GET_MODELS_URL = "https://api.mistral.ai/v1/models";
+
+type GetModelsResponse = {
+  data: [{ id: string }];
+};
+
+type MistralAIError = {
+  message: string;
+  request_id: string;
+};
+
+type UpdateFn = typeof MistralAIKeyProvider.prototype.update;
+
+export class MistralAIKeyChecker extends KeyCheckerBase<MistralAIKey> {
+  constructor(keys: MistralAIKey[], updateKey: UpdateFn) {
+    super(keys, {
+      service: "mistral-ai",
+      keyCheckPeriod: KEY_CHECK_PERIOD,
+      minCheckInterval: MIN_CHECK_INTERVAL,
+      recurringChecksEnabled: false,
+      updateKey,
+    });
+  }
+
+  protected async testKeyOrFail(key: MistralAIKey) {
+    // We only need to check for provisioned models on the initial check.
+    const isInitialCheck = !key.lastChecked;
+    if (isInitialCheck) {
+      const provisionedModels = await this.getProvisionedModels(key);
+      const updates = {
+        modelFamilies: provisionedModels,
+      };
+      this.updateKey(key.hash, updates);
+    }
+    this.log.info({ key: key.hash, models: key.modelFamilies }, "Checked key.");
+  }
+
+  private async getProvisionedModels(
+    key: MistralAIKey
+  ): Promise<MistralAIModelFamily[]> {
+    const opts = { headers: MistralAIKeyChecker.getHeaders(key) };
+    const { data } = await axios.get<GetModelsResponse>(GET_MODELS_URL, opts);
+    const models = data.data;
+
+    const families = new Set<MistralAIModelFamily>();
+    models.forEach(({ id }) => families.add(getMistralAIModelFamily(id)));
+
+    // We want to update the key's model families here, but we don't want to
+    // update its `lastChecked` timestamp because we need to let the liveness
+    // check run before we can consider the key checked.
+
+    const familiesArray = [...families];
+    const keyFromPool = this.keys.find((k) => k.hash === key.hash)!;
+    this.updateKey(key.hash, {
+      modelFamilies: familiesArray,
+      lastChecked: keyFromPool.lastChecked,
+    });
+    return familiesArray;
+  }
+
+  protected handleAxiosError(key: MistralAIKey, error: AxiosError) {
+    if (error.response && MistralAIKeyChecker.errorIsMistralAIError(error)) {
+      const { status, data } = error.response;
+      if (status === 401) {
+        this.log.warn(
+          { key: key.hash, error: data },
+          "Key is invalid or revoked. Disabling key."
+        );
+        this.updateKey(key.hash, {
+          isDisabled: true,
+          isRevoked: true,
+          modelFamilies: ["mistral-tiny"],
+        });
+      } else {
+        this.log.error(
+          { key: key.hash, status, error: data },
+          "Encountered unexpected error status while checking key. This may indicate a change in the API; please report this."
+        );
+        this.updateKey(key.hash, { lastChecked: Date.now() });
+      }
+      return;
+    }
+    this.log.error(
+      { key: key.hash, error: error.message },
+      "Network error while checking key; trying this key again in a minute."
+    );
+    const oneMinute = 60 * 1000;
+    const next = Date.now() - (KEY_CHECK_PERIOD - oneMinute);
+    this.updateKey(key.hash, { lastChecked: next });
+  }
+
+  static errorIsMistralAIError(
+    error: AxiosError
+  ): error is AxiosError<MistralAIError> {
+    const data = error.response?.data as any;
+    return data?.message && data?.request_id;
+  }
+
+  static getHeaders(key: MistralAIKey) {
+    return {
+      Authorization: `Bearer ${key.key}`,
+    };
+  }
+}

src/shared/key-management/mistral-ai/provider.ts

@@ -0,0 +1,210 @@
+import crypto from "crypto";
+import { Key, KeyProvider, Model } from "..";
+import { config } from "../../../config";
+import { logger } from "../../../logger";
+import { MistralAIModelFamily, getMistralAIModelFamily } from "../../models";
+import { MistralAIKeyChecker } from "./checker";
+
+export type MistralAIModel =
+  | "mistral-tiny"
+  | "mistral-small"
+  | "mistral-medium";
+
+export type MistralAIKeyUpdate = Omit<
+  Partial<MistralAIKey>,
+  | "key"
+  | "hash"
+  | "lastUsed"
+  | "promptCount"
+  | "rateLimitedAt"
+  | "rateLimitedUntil"
+>;
+
+type MistralAIKeyUsage = {
+  [K in MistralAIModelFamily as `${K}Tokens`]: number;
+};
+
+export interface MistralAIKey extends Key, MistralAIKeyUsage {
+  readonly service: "mistral-ai";
+  readonly modelFamilies: MistralAIModelFamily[];
+  /** The time at which this key was last rate limited. */
+  rateLimitedAt: number;
+  /** The time until which this key is rate limited. */
+  rateLimitedUntil: number;
+}
+
+/**
+ * Upon being rate limited, a key will be locked out for this many milliseconds
+ * while we wait for other concurrent requests to finish.
+ */
+const RATE_LIMIT_LOCKOUT = 2000;
+/**
+ * Upon assigning a key, we will wait this many milliseconds before allowing it
+ * to be used again. This is to prevent the queue from flooding a key with too
+ * many requests while we wait to learn whether previous ones succeeded.
+ */
+const KEY_REUSE_DELAY = 500;
+
+export class MistralAIKeyProvider implements KeyProvider<MistralAIKey> {
+  readonly service = "mistral-ai";
+
+  private keys: MistralAIKey[] = [];
+  private checker?: MistralAIKeyChecker;
+  private log = logger.child({ module: "key-provider", service: this.service });
+
+  constructor() {
+    const keyConfig = config.mistralAIKey?.trim();
+    if (!keyConfig) {
+      this.log.warn(
+        "MISTRAL_AI_KEY is not set. Mistral AI API will not be available."
+      );
+      return;
+    }
+    let bareKeys: string[];
+    bareKeys = [...new Set(keyConfig.split(",").map((k) => k.trim()))];
+    for (const key of bareKeys) {
+      const newKey: MistralAIKey = {
+        key,
+        service: this.service,
+        modelFamilies: ["mistral-tiny", "mistral-small", "mistral-medium"],
+        isDisabled: false,
+        isRevoked: false,
+        promptCount: 0,
+        lastUsed: 0,
+        rateLimitedAt: 0,
+        rateLimitedUntil: 0,
+        hash: `mst-${crypto
+          .createHash("sha256")
+          .update(key)
+          .digest("hex")
+          .slice(0, 8)}`,
+        lastChecked: 0,
+        "mistral-tinyTokens": 0,
+        "mistral-smallTokens": 0,
+        "mistral-mediumTokens": 0,
+      };
+      this.keys.push(newKey);
+    }
+    this.log.info({ keyCount: this.keys.length }, "Loaded Mistral AI keys.");
+  }
+
+  public init() {
+    if (config.checkKeys) {
+      const updateFn = this.update.bind(this);
+      this.checker = new MistralAIKeyChecker(this.keys, updateFn);
+      this.checker.start();
+    }
+  }
+
+  public list() {
+    return this.keys.map((k) => Object.freeze({ ...k, key: undefined }));
+  }
+
+  public get(_model: Model) {
+    const availableKeys = this.keys.filter((k) => !k.isDisabled);
+    if (availableKeys.length === 0) {
+      throw new Error("No Mistral AI keys available");
+    }
+
+    // (largely copied from the OpenAI provider, without trial key support)
+    // Select a key, from highest priority to lowest priority:
+    // 1. Keys which are not rate limited
+    //    a. If all keys were rate limited recently, select the least-recently
+    //       rate limited key.
+    // 3. Keys which have not been used in the longest time
+
+    const now = Date.now();
+
+    const keysByPriority = availableKeys.sort((a, b) => {
+      const aRateLimited = now - a.rateLimitedAt < RATE_LIMIT_LOCKOUT;
+      const bRateLimited = now - b.rateLimitedAt < RATE_LIMIT_LOCKOUT;
+
+      if (aRateLimited && !bRateLimited) return 1;
+      if (!aRateLimited && bRateLimited) return -1;
+      if (aRateLimited && bRateLimited) {
+        return a.rateLimitedAt - b.rateLimitedAt;
+      }
+
+      return a.lastUsed - b.lastUsed;
+    });
+
+    const selectedKey = keysByPriority[0];
+    selectedKey.lastUsed = now;
+    this.throttle(selectedKey.hash);
+    return { ...selectedKey };
+  }
+
+  public disable(key: MistralAIKey) {
+    const keyFromPool = this.keys.find((k) => k.hash === key.hash);
+    if (!keyFromPool || keyFromPool.isDisabled) return;
+    keyFromPool.isDisabled = true;
+    this.log.warn({ key: key.hash }, "Key disabled");
+  }
+
+  public update(hash: string, update: Partial<MistralAIKey>) {
+    const keyFromPool = this.keys.find((k) => k.hash === hash)!;
+    Object.assign(keyFromPool, { lastChecked: Date.now(), ...update });
+  }
+
+  public available() {
+    return this.keys.filter((k) => !k.isDisabled).length;
+  }
+
+  public incrementUsage(hash: string, model: string, tokens: number) {
+    const key = this.keys.find((k) => k.hash === hash);
+    if (!key) return;
+    key.promptCount++;
+    const family = getMistralAIModelFamily(model);
+    key[`${family}Tokens`] += tokens;
+  }
+
+  public getLockoutPeriod() {
+    const activeKeys = this.keys.filter((k) => !k.isDisabled);
+    // Don't lock out if there are no keys available or the queue will stall.
+    // Just let it through so the add-key middleware can throw an error.
+    if (activeKeys.length === 0) return 0;
+
+    const now = Date.now();
+    const rateLimitedKeys = activeKeys.filter((k) => now < k.rateLimitedUntil);
+    const anyNotRateLimited = rateLimitedKeys.length < activeKeys.length;
+
+    if (anyNotRateLimited) return 0;
+
+    // If all keys are rate-limited, return the time until the first key is
+    // ready.
+    return Math.min(...activeKeys.map((k) => k.rateLimitedUntil - now));
+  }
+
+  /**
+   * This is called when we receive a 429, which means there are already five
+   * concurrent requests running on this key. We don't have any information on
+   * when these requests will resolve, so all we can do is wait a bit and try
+   * again. We will lock the key for 2 seconds after getting a 429 before
+   * retrying in order to give the other requests a chance to finish.
+   */
+  public markRateLimited(keyHash: string) {
+    this.log.debug({ key: keyHash }, "Key rate limited");
+    const key = this.keys.find((k) => k.hash === keyHash)!;
+    const now = Date.now();
+    key.rateLimitedAt = now;
+    key.rateLimitedUntil = now + RATE_LIMIT_LOCKOUT;
+  }
+
+  public recheck() {}
+
+  /**
+   * Applies a short artificial delay to the key upon dequeueing, in order to
+   * prevent it from being immediately assigned to another request before the
+   * current one can be dispatched.
+   **/
+  private throttle(hash: string) {
+    const now = Date.now();
+    const key = this.keys.find((k) => k.hash === hash)!;
+
+    const currentRateLimit = key.rateLimitedUntil;
+    const nextRateLimit = now + KEY_REUSE_DELAY;
+
+    key.rateLimitedAt = now;
+    key.rateLimitedUntil = Math.max(currentRateLimit, nextRateLimit);
+  }
+}

src/shared/key-management/openai/checker.ts

@@ -2,6 +2,7 @@ import axios, { AxiosError } from "axios";
 import type { OpenAIModelFamily } from "../../models";
 import { KeyCheckerBase } from "../key-checker-base";
 import type { OpenAIKey, OpenAIKeyProvider } from "./provider";
+import { getOpenAIModelFamily } from "../../models";
 
 const MIN_CHECK_INTERVAL = 3 * 1000; // 3 seconds
 const KEY_CHECK_PERIOD = 60 * 60 * 1000; // 1 hour
@@ -26,65 +27,41 @@ type UpdateFn = typeof OpenAIKeyProvider.prototype.update;
 
 export class OpenAIKeyChecker extends KeyCheckerBase<OpenAIKey> {
   private readonly cloneKey: CloneFn;
-  private readonly updateKey: UpdateFn;
 
   constructor(keys: OpenAIKey[], cloneFn: CloneFn, updateKey: UpdateFn) {
     super(keys, {
       service: "openai",
       keyCheckPeriod: KEY_CHECK_PERIOD,
       minCheckInterval: MIN_CHECK_INTERVAL,
+      recurringChecksEnabled: false,
+      updateKey,
     });
     this.cloneKey = cloneFn;
-    this.updateKey = updateKey;
   }
 
-  protected async checkKey(key: OpenAIKey) {
-    if (key.isDisabled) {
-      this.log.warn({ key: key.hash }, "Skipping check for disabled key.");
-      this.scheduleNextCheck();
-      return;
-    }
-
-    this.log.debug({ key: key.hash }, "Checking key...");
-    let isInitialCheck = !key.lastChecked;
-    try {
-      // We only need to check for provisioned models on the initial check.
-      if (isInitialCheck) {
-        const [provisionedModels, livenessTest] = await Promise.all([
-          this.getProvisionedModels(key),
-          this.testLiveness(key),
-          this.maybeCreateOrganizationClones(key),
-        ]);
-        const updates = {
-          modelFamilies: provisionedModels,
-          isTrial: livenessTest.rateLimit <= 250,
-        };
-        this.updateKey(key.hash, updates);
-      } else {
-        // No updates needed as models and trial status generally don't change.
-        const [_livenessTest] = await Promise.all([this.testLiveness(key)]);
-        this.updateKey(key.hash, {});
-      }
-      this.log.info(
-        { key: key.hash, models: key.modelFamilies, trial: key.isTrial },
-        "Key check complete."
-      );
-    } catch (error) {
-      // touch the key so we don't check it again for a while
+  protected async testKeyOrFail(key: OpenAIKey) {
+    // We only need to check for provisioned models on the initial check.
+    const isInitialCheck = !key.lastChecked;
+    if (isInitialCheck) {
+      const [provisionedModels, livenessTest] = await Promise.all([
+        this.getProvisionedModels(key),
+        this.testLiveness(key),
+        this.maybeCreateOrganizationClones(key),
+      ]);
+      const updates = {
+        modelFamilies: provisionedModels,
+        isTrial: livenessTest.rateLimit <= 250,
+      };
+      this.updateKey(key.hash, updates);
+    } else {
+      // No updates needed as models and trial status generally don't change.
+      const [_livenessTest] = await Promise.all([this.testLiveness(key)]);
       this.updateKey(key.hash, {});
-      this.handleAxiosError(key, error as AxiosError);
-    }
-
-    this.lastCheck = Date.now();
-    // Only enqueue the next check if this wasn't a startup check, since those
-    // are batched together elsewhere.
-    if (!isInitialCheck) {
-      this.log.info(
-        { key: key.hash },
-        "Recurring keychecks are disabled, no-op."
-      );
-      // this.scheduleNextCheck();
     }
+    this.log.info(
+      { key: key.hash, models: key.modelFamilies, trial: key.isTrial },
+      "Checked key."
+    );
   }
 
   private async getProvisionedModels(
@@ -94,29 +71,26 @@ export class OpenAIKeyChecker extends KeyCheckerBase<OpenAIKey> {
     const { data } = await axios.get<GetModelsResponse>(GET_MODELS_URL, opts);
     const models = data.data;
 
-    const families: OpenAIModelFamily[] = [];
-    if (models.some(({ id }) => id.startsWith("gpt-3.5-turbo"))) {
-      families.push("turbo");
-    }
+    const families = new Set<OpenAIModelFamily>();
+    models.forEach(({ id }) => families.add(getOpenAIModelFamily(id, "turbo")));
 
-    if (models.some(({ id }) => id.startsWith("gpt-4"))) {
-      families.push("gpt4");
-    }
-
-    if (models.some(({ id }) => id.startsWith("gpt-4-32k"))) {
-      families.push("gpt4-32k");
-    }
+    // as of 2023-11-18, many keys no longer return the dalle3 model but still
+    // have access to it via the api for whatever reason.
+    // if (families.has("dall-e") && !models.find(({ id }) => id === "dall-e-3")) {
+    //   families.delete("dall-e");
+    // }
 
     // We want to update the key's model families here, but we don't want to
     // update its `lastChecked` timestamp because we need to let the liveness
     // check run before we can consider the key checked.
 
+    const familiesArray = [...families];
     const keyFromPool = this.keys.find((k) => k.hash === key.hash)!;
     this.updateKey(key.hash, {
-      modelFamilies: families,
+      modelFamilies: familiesArray,
       lastChecked: keyFromPool.lastChecked,
     });
-    return families;
+    return familiesArray;
   }
 
   private async maybeCreateOrganizationClones(key: OpenAIKey) {
@@ -140,6 +114,17 @@ export class OpenAIKeyChecker extends KeyCheckerBase<OpenAIKey> {
       .filter(({ is_default }) => !is_default)
       .map(({ id }) => id);
     this.cloneKey(key.hash, ids);
+
+    // It's possible that the keychecker may be stopped if all non-cloned keys
+    // happened to be unusable, in which case this clnoe will never be checked
+    // unless we restart the keychecker.
+    if (!this.timeout) {
+      this.log.warn(
+        { parent: key.hash },
+        "Restarting key checker to check cloned keys."
+      );
+      this.scheduleNextCheck();
+    }
   }
 
   protected handleAxiosError(key: OpenAIKey, error: AxiosError) {

src/shared/key-management/openai/provider.ts

@@ -14,12 +14,10 @@ export type OpenAIModel =
   | "gpt-3.5-turbo-instruct"
   | "gpt-4"
   | "gpt-4-32k"
-  | "text-embedding-ada-002";
-export const OPENAI_SUPPORTED_MODELS: readonly OpenAIModel[] = [
-  "gpt-3.5-turbo",
-  "gpt-3.5-turbo-instruct",
-  "gpt-4",
-] as const;
+  | "gpt-4-1106"
+  | "text-embedding-ada-002"
+  | "dall-e-2"
+  | "dall-e-3"
 
 // Flattening model families instead of using a nested object for easier
 // cloning.
@@ -64,6 +62,10 @@ export interface OpenAIKey extends Key, OpenAIKeyUsage {
    * tokens.
    */
   rateLimitTokensReset: number;
+  /**
+   * This key's maximum request rate for GPT-4, per minute.
+   */
+  gpt4Rpm: number;
 }
 
 export type OpenAIKeyUpdate = Omit<
@@ -98,7 +100,11 @@ export class OpenAIKeyProvider implements KeyProvider<OpenAIKey> {
       const newKey: OpenAIKey = {
         key: k,
         service: "openai" as const,
-        modelFamilies: ["turbo" as const, "gpt4" as const],
+        modelFamilies: [
+          "turbo" as const,
+          "gpt4" as const,
+          "gpt4-turbo" as const,
+        ],
         isTrial: false,
         isDisabled: false,
         isRevoked: false,
@@ -117,6 +123,9 @@ export class OpenAIKeyProvider implements KeyProvider<OpenAIKey> {
         turboTokens: 0,
         gpt4Tokens: 0,
         "gpt4-32kTokens": 0,
+        "gpt4-turboTokens": 0,
+        "dall-eTokens": 0,
+        gpt4Rpm: 0,
       };
       this.keys.push(newKey);
     }
@@ -158,13 +167,7 @@ export class OpenAIKeyProvider implements KeyProvider<OpenAIKey> {
     );
 
     if (availableKeys.length === 0) {
-      throw new Error(`No active keys available for ${neededFamily} models.`);
-    }
-
-    if (!config.allowedModelFamilies.includes(neededFamily)) {
-      throw new Error(
-        `Proxy operator has disabled access to ${neededFamily} models.`
-      );
+      throw new Error(`No keys available for model family '${neededFamily}'.`);
     }
 
     // Select a key, from highest priority to lowest priority:
@@ -208,28 +211,9 @@ export class OpenAIKeyProvider implements KeyProvider<OpenAIKey> {
       return a.lastUsed - b.lastUsed;
     });
 
-    // logger.debug(
-    //   {
-    //     byPriority: keysByPriority.map((k) => ({
-    //       hash: k.hash,
-    //       isRateLimited: now - k.rateLimitedAt < rateLimitThreshold,
-    //       modelFamilies: k.modelFamilies,
-    //     })),
-    //   },
-    //   "Keys sorted by priority"
-    // );
-
     const selectedKey = keysByPriority[0];
     selectedKey.lastUsed = now;
-
-    // When a key is selected, we rate-limit it for a brief period of time to
-    // prevent the queue processor from immediately flooding it with requests
-    // while the initial request is still being processed (which is when we will
-    // get new rate limit headers).
-    // Instead, we will let a request through every second until the key
-    // becomes fully saturated and locked out again.
-    selectedKey.rateLimitedAt = now;
-    selectedKey.rateLimitRequestsReset = KEY_REUSE_DELAY;
+    this.throttle(selectedKey.hash);
     return { ...selectedKey };
   }
 
@@ -237,7 +221,6 @@ export class OpenAIKeyProvider implements KeyProvider<OpenAIKey> {
   public update(keyHash: string, update: OpenAIKeyUpdate) {
     const keyFromPool = this.keys.find((k) => k.hash === keyHash)!;
     Object.assign(keyFromPool, { lastChecked: Date.now(), ...update });
-    // this.writeKeyStatus();
   }
 
   /** Called by the key checker to create clones of keys for the given orgs. */
@@ -248,6 +231,8 @@ export class OpenAIKeyProvider implements KeyProvider<OpenAIKey> {
         ...keyFromPool,
         organizationId: orgId,
         isDisabled: false,
+        isRevoked: false,
+        isOverQuota: false,
         hash: `oai-${crypto
           .createHash("sha256")
           .update(keyFromPool.key + orgId)
@@ -280,18 +265,14 @@ export class OpenAIKeyProvider implements KeyProvider<OpenAIKey> {
    * Given a model, returns the period until a key will be available to service
    * the request, or returns 0 if a key is ready immediately.
    */
-  public getLockoutPeriod(model: Model = "gpt-4"): number {
-    const neededFamily = getOpenAIModelFamily(model);
+  public getLockoutPeriod(family: OpenAIModelFamily): number {
     const activeKeys = this.keys.filter(
-      (key) => !key.isDisabled && key.modelFamilies.includes(neededFamily)
+      (key) => !key.isDisabled && key.modelFamilies.includes(family)
     );
 
-    if (activeKeys.length === 0) {
-      // If there are no active keys for this model we can't fulfill requests.
-      // We'll return 0 to let the request through and return an error,
-      // otherwise the request will be stuck in the queue forever.
-      return 0;
-    }
+    // Don't lock out if there are no keys available or the queue will stall.
+    // Just let it through so the add-key middleware can throw an error.
+    if (activeKeys.length === 0) return 0;
 
     // A key is rate-limited if its `rateLimitedAt` plus the greater of its
     // `rateLimitRequestsReset` and `rateLimitTokensReset` is after the
@@ -304,7 +285,7 @@ export class OpenAIKeyProvider implements KeyProvider<OpenAIKey> {
         key.rateLimitRequestsReset,
         key.rateLimitTokensReset
       );
-      return now < key.rateLimitedAt + resetTime;
+      return now < key.rateLimitedAt + Math.min(20000, resetTime);
     }).length;
     const anyNotRateLimited = rateLimitedKeys < activeKeys.length;
 
@@ -313,14 +294,16 @@ export class OpenAIKeyProvider implements KeyProvider<OpenAIKey> {
     }
 
     // If all keys are rate-limited, return the time until the first key is
-    // ready.
+    // ready. We don't want to wait longer than 10 seconds because rate limits
+    // are a rolling window and keys may become available sooner than the stated
+    // reset time.
     return Math.min(
       ...activeKeys.map((key) => {
         const resetTime = Math.max(
           key.rateLimitRequestsReset,
           key.rateLimitTokensReset
         );
-        return key.rateLimitedAt + resetTime - now;
+        return key.rateLimitedAt + Math.min(20000, resetTime) - now;
       })
     );
   }
@@ -329,6 +312,10 @@ export class OpenAIKeyProvider implements KeyProvider<OpenAIKey> {
     this.log.debug({ key: keyHash }, "Key rate limited");
     const key = this.keys.find((k) => k.hash === keyHash)!;
     key.rateLimitedAt = Date.now();
+    // DALL-E requests do not send headers telling us when the rate limit will
+    // be reset so we need to set a fallback value here.  Other models will have
+    // this overwritten by the `updateRateLimits` method.
+    key.rateLimitRequestsReset = 20000;
   }
 
   public incrementUsage(keyHash: string, model: string, tokens: number) {
@@ -343,30 +330,16 @@ export class OpenAIKeyProvider implements KeyProvider<OpenAIKey> {
     const requestsReset = headers["x-ratelimit-reset-requests"];
     const tokensReset = headers["x-ratelimit-reset-tokens"];
 
-    // Sometimes OpenAI only sends one of the two rate limit headers, it's
-    // unclear why.
-
-    if (requestsReset && typeof requestsReset === "string") {
-      this.log.debug(
-        { key: key.hash, requestsReset },
-        `Updating rate limit requests reset time`
-      );
+    if (typeof requestsReset === "string") {
       key.rateLimitRequestsReset = getResetDurationMillis(requestsReset);
     }
 
-    if (tokensReset && typeof tokensReset === "string") {
-      this.log.debug(
-        { key: key.hash, tokensReset },
-        `Updating rate limit tokens reset time`
-      );
+    if (typeof tokensReset === "string") {
       key.rateLimitTokensReset = getResetDurationMillis(tokensReset);
     }
 
     if (!requestsReset && !tokensReset) {
-      this.log.warn(
-        { key: key.hash },
-        `No rate limit headers in OpenAI response; skipping update`
-      );
+      this.log.warn({ key: key.hash }, `No ratelimit headers; skipping update`);
       return;
     }
   }
@@ -383,35 +356,66 @@ export class OpenAIKeyProvider implements KeyProvider<OpenAIKey> {
     this.checker?.scheduleNextCheck();
   }
 
-  /** Writes key status to disk. */
-  // public writeKeyStatus() {
-  //   const keys = this.keys.map((key) => ({
-  //     key: key.key,
-  //     isGpt4: key.isGpt4,
-  //     usage: key.usage,
-  //     hardLimit: key.hardLimit,
-  //     isDisabled: key.isDisabled,
-  //   }));
-  //   fs.writeFileSync(
-  //     path.join(__dirname, "..", "keys.json"),
-  //     JSON.stringify(keys, null, 2)
-  //   );
-  // }
+  /**
+   * Called when a key is selected for a request, briefly disabling it to
+   * avoid spamming the API with requests while we wait to learn whether this
+   * key is already rate limited.
+   */
+  private throttle(hash: string) {
+    const now = Date.now();
+    const key = this.keys.find((k) => k.hash === hash)!;
+
+    const currentRateLimit =
+      Math.max(key.rateLimitRequestsReset, key.rateLimitTokensReset) +
+      key.rateLimitedAt;
+    const nextRateLimit = now + KEY_REUSE_DELAY;
+
+    // Don't throttle if the key is already naturally rate limited.
+    if (currentRateLimit > nextRateLimit) return;
+
+    key.rateLimitedAt = Date.now();
+    key.rateLimitRequestsReset = KEY_REUSE_DELAY;
+  }
+}
+
+// wip
+function calculateRequestsPerMinute(headers: http.IncomingHttpHeaders) {
+  const requestsLimit = headers["x-ratelimit-limit-requests"];
+  const requestsReset = headers["x-ratelimit-reset-requests"];
+
+  if (typeof requestsLimit !== "string" || typeof requestsReset !== "string") {
+    return 0;
+  }
+
+  const limit = parseInt(requestsLimit, 10);
+  const reset = getResetDurationMillis(requestsReset);
+
+  // If `reset` is less than one minute, OpenAI specifies the `limit` as an
+  // integer representing requests per minute.  Otherwise it actually means the
+  // requests per day.
+  const isPerMinute = reset < 60000;
+  if (isPerMinute) return limit;
+  return limit / 1440;
 }
 
 /**
- * Converts reset string ("21.0032s" or "21ms") to a number of milliseconds.
- * Result is clamped to 10s even though the API returns up to 60s, because the
- * API returns the time until the entire quota is reset, even if a key may be
- * able to fulfill requests before then due to partial resets.
+ * Converts reset string ("14m25s", "21.0032s", "14ms" or "21ms") to a number of
+ * milliseconds.
  **/
 function getResetDurationMillis(resetDuration?: string): number {
-  const match = resetDuration?.match(/(\d+(\.\d+)?)(s|ms)/);
+  const match = resetDuration?.match(
+    /(?:(\d+)m(?!s))?(?:(\d+(?:\.\d+)?)s)?(?:(\d+)ms)?/
+  );
+
   if (match) {
-    const [, time, , unit] = match;
-    const value = parseFloat(time);
-    const result = unit === "s" ? value * 1000 : value;
-    return Math.min(result, 10000);
+    const [, minutes, seconds, milliseconds] = match.map(Number);
+
+    const minutesToMillis = (minutes || 0) * 60 * 1000;
+    const secondsToMillis = (seconds || 0) * 1000;
+    const millisecondsValue = milliseconds || 0;
+
+    return minutesToMillis + secondsToMillis + millisecondsValue;
   }
+
   return 0;
 }

src/shared/models.ts

@@ -1,14 +1,45 @@
-import { logger } from "../logger";
+// Don't import any other project files here as this is one of the first modules
+// loaded and it will cause circular imports.
 
-export type OpenAIModelFamily = "turbo" | "gpt4" | "gpt4-32k";
+import pino from "pino";
+import type { Request } from "express";
+
+/**
+ * The service that a model is hosted on. Distinct from `APIFormat` because some
+ * services have interoperable APIs (eg Anthropic/AWS, OpenAI/Azure).
+ */
+export type LLMService =
+  | "openai"
+  | "anthropic"
+  | "google-ai"
+  | "mistral-ai"
+  | "aws"
+  | "azure";
+
+export type OpenAIModelFamily =
+  | "turbo"
+  | "gpt4"
+  | "gpt4-32k"
+  | "gpt4-turbo"
+  | "dall-e";
 export type AnthropicModelFamily = "claude";
-export type GooglePalmModelFamily = "bison";
+export type GoogleAIModelFamily = "gemini-pro";
+export type MistralAIModelFamily =
+  | "mistral-tiny"
+  | "mistral-small"
+  | "mistral-medium";
 export type AwsBedrockModelFamily = "aws-claude";
+export type AzureOpenAIModelFamily = `azure-${Exclude<
+  OpenAIModelFamily,
+  "dall-e"
+>}`;
 export type ModelFamily =
   | OpenAIModelFamily
   | AnthropicModelFamily
-  | GooglePalmModelFamily
-  | AwsBedrockModelFamily;
+  | GoogleAIModelFamily
+  | MistralAIModelFamily
+  | AwsBedrockModelFamily
+  | AzureOpenAIModelFamily;
 
 export const MODEL_FAMILIES = (<A extends readonly ModelFamily[]>(
   arr: A & ([ModelFamily] extends [A[number]] ? unknown : never)
@@ -16,44 +47,117 @@ export const MODEL_FAMILIES = (<A extends readonly ModelFamily[]>(
   "turbo",
   "gpt4",
   "gpt4-32k",
+  "gpt4-turbo",
+  "dall-e",
   "claude",
-  "bison",
+  "gemini-pro",
+  "mistral-tiny",
+  "mistral-small",
+  "mistral-medium",
   "aws-claude",
+  "azure-turbo",
+  "azure-gpt4",
+  "azure-gpt4-32k",
+  "azure-gpt4-turbo",
+] as const);
+
+export const LLM_SERVICES = (<A extends readonly LLMService[]>(
+  arr: A & ([LLMService] extends [A[number]] ? unknown : never)
+) => arr)([
+  "openai",
+  "anthropic",
+  "google-ai",
+  "mistral-ai",
+  "aws",
+  "azure",
 ] as const);
 
 export const OPENAI_MODEL_FAMILY_MAP: { [regex: string]: OpenAIModelFamily } = {
+  "^gpt-4-1106(-preview)?$": "gpt4-turbo",
+  "^gpt-4(-\\d{4})?-vision(-preview)?$": "gpt4-turbo",
   "^gpt-4-32k-\\d{4}$": "gpt4-32k",
   "^gpt-4-32k$": "gpt4-32k",
   "^gpt-4-\\d{4}$": "gpt4",
   "^gpt-4$": "gpt4",
   "^gpt-3.5-turbo": "turbo",
   "^text-embedding-ada-002$": "turbo",
+  "^dall-e-\\d{1}$": "dall-e",
 };
 
-export function getOpenAIModelFamily(model: string): OpenAIModelFamily {
+export const MODEL_FAMILY_SERVICE: {
+  [f in ModelFamily]: LLMService;
+} = {
+  turbo: "openai",
+  gpt4: "openai",
+  "gpt4-turbo": "openai",
+  "gpt4-32k": "openai",
+  "dall-e": "openai",
+  claude: "anthropic",
+  "aws-claude": "aws",
+  "azure-turbo": "azure",
+  "azure-gpt4": "azure",
+  "azure-gpt4-32k": "azure",
+  "azure-gpt4-turbo": "azure",
+  "gemini-pro": "google-ai",
+  "mistral-tiny": "mistral-ai",
+  "mistral-small": "mistral-ai",
+  "mistral-medium": "mistral-ai",
+};
+
+pino({ level: "debug" }).child({ module: "startup" });
+
+export function getOpenAIModelFamily(
+  model: string,
+  defaultFamily: OpenAIModelFamily = "gpt4"
+): OpenAIModelFamily {
   for (const [regex, family] of Object.entries(OPENAI_MODEL_FAMILY_MAP)) {
     if (model.match(regex)) return family;
   }
-  const stack = new Error().stack;
-  logger.warn({ model, stack }, "Unmapped model family");
-  return "gpt4";
+  return defaultFamily;
 }
 
-export function getClaudeModelFamily(_model: string): ModelFamily {
+export function getClaudeModelFamily(model: string): ModelFamily {
+  if (model.startsWith("anthropic.")) return getAwsBedrockModelFamily(model);
   return "claude";
 }
 
-export function getGooglePalmModelFamily(model: string): ModelFamily {
-  if (model.match(/^\w+-bison-\d{3}$/)) return "bison";
-  const stack = new Error().stack;
-  logger.warn({ model, stack }, "Unmapped PaLM model family");
-  return "bison";
+export function getGoogleAIModelFamily(_model: string): ModelFamily {
+  return "gemini-pro";
+}
+
+export function getMistralAIModelFamily(model: string): MistralAIModelFamily {
+  switch (model) {
+    case "mistral-tiny":
+    case "mistral-small":
+    case "mistral-medium":
+      return model;
+    default:
+      return "mistral-tiny";
+  }
 }
 
 export function getAwsBedrockModelFamily(_model: string): ModelFamily {
   return "aws-claude";
 }
 
+export function getAzureOpenAIModelFamily(
+  model: string,
+  defaultFamily: AzureOpenAIModelFamily = "azure-gpt4"
+): AzureOpenAIModelFamily {
+  // Azure model names omit periods.  addAzureKey also prepends "azure-" to the
+  // model name to route the request the correct keyprovider, so we need to
+  // remove that as well.
+  const modified = model
+    .replace("gpt-35-turbo", "gpt-3.5-turbo")
+    .replace("azure-", "");
+  for (const [regex, family] of Object.entries(OPENAI_MODEL_FAMILY_MAP)) {
+    if (modified.match(regex)) {
+      return `azure-${family}` as AzureOpenAIModelFamily;
+    }
+  }
+  return defaultFamily;
+}
+
 export function assertIsKnownModelFamily(
   modelFamily: string
 ): asserts modelFamily is ModelFamily {
@@ -61,3 +165,45 @@ export function assertIsKnownModelFamily(
     throw new Error(`Unknown model family: ${modelFamily}`);
   }
 }
+
+export function getModelFamilyForRequest(req: Request): ModelFamily {
+  if (req.modelFamily) return req.modelFamily;
+  // There is a single request queue, but it is partitioned by model family.
+  // Model families are typically separated on cost/rate limit boundaries so
+  // they should be treated as separate queues.
+  const model = req.body.model ?? "gpt-3.5-turbo";
+  let modelFamily: ModelFamily;
+
+  // Weird special case for AWS/Azure because they serve multiple models from
+  // different vendors, even if currently only one is supported.
+  if (req.service === "aws") {
+    modelFamily = getAwsBedrockModelFamily(model);
+  } else if (req.service === "azure") {
+    modelFamily = getAzureOpenAIModelFamily(model);
+  } else {
+    switch (req.outboundApi) {
+      case "anthropic":
+        modelFamily = getClaudeModelFamily(model);
+        break;
+      case "openai":
+      case "openai-text":
+      case "openai-image":
+        modelFamily = getOpenAIModelFamily(model);
+        break;
+      case "google-ai":
+        modelFamily = getGoogleAIModelFamily(model);
+        break;
+      case "mistral-ai":
+        modelFamily = getMistralAIModelFamily(model);
+        break;
+      default:
+        assertNever(req.outboundApi);
+    }
+  }
+
+  return (req.modelFamily = modelFamily);
+}
+
+function assertNever(x: never): never {
+  throw new Error(`Called assertNever with argument ${x}.`);
+}

src/shared/prompt-logging/backends/sheets.ts

@@ -256,8 +256,8 @@ export const appendBatch = async (batch: PromptLogEntry[]) => {
     return [
       entry.model,
       entry.endpoint,
-      entry.promptRaw.slice(0, 50000),
-      entry.promptFlattened.slice(0, 50000),
+      entry.promptRaw.slice(-50000),
+      entry.promptFlattened.slice(-50000),
       entry.response.slice(0, 50000),
     ];
   });
@@ -396,7 +396,7 @@ export const init = async (onStop: () => void) => {
     await loadIndexSheet(false);
     await writeIndexSheet();
   } catch (e) {
-    log.info("Creating new index sheet.");
+    log.warn({ error: e.message }, "Could not load index sheet. Creating a new one.");
     await createIndexSheet();
   }
 };

src/shared/prompt-logging/log-queue.ts

@@ -69,7 +69,7 @@ export const start = async () => {
     log.info("Logging backend initialized.");
     started = true;
   } catch (e) {
-    log.error(e, "Could not initialize logging backend.");
+    log.error({ error: e.message }, "Could not initialize logging backend.");
     return;
   }
   scheduleFlush();

src/shared/stats.ts

@@ -1,3 +1,4 @@
+import { config } from "../config";
 import { ModelFamily } from "./models";
 
 // technically slightly underestimates, because completion tokens cost more
@@ -5,6 +6,9 @@ import { ModelFamily } from "./models";
 export function getTokenCostUsd(model: ModelFamily, tokens: number) {
   let cost = 0;
   switch (model) {
+    case "gpt4-turbo":
+      cost = 0.00001;
+      break;
     case "gpt4-32k":
       cost = 0.00006;
       break;
@@ -12,12 +16,24 @@ export function getTokenCostUsd(model: ModelFamily, tokens: number) {
       cost = 0.00003;
       break;
     case "turbo":
-      cost = 0.0000015;
+      cost = 0.000001;
+      break;
+    case "dall-e":
+      cost = 0.00001;
       break;
     case "aws-claude":
     case "claude":
       cost = 0.00001102;
       break;
+    case "mistral-tiny":
+      cost = 0.00000031;
+      break;
+    case "mistral-small":
+      cost = 0.00000132;
+      break;
+    case "mistral-medium":
+      cost = 0.0000055;
+      break;
   }
   return cost * Math.max(0, tokens);
 }
@@ -31,6 +47,11 @@ export function prettyTokens(tokens: number): string {
   } else if (absTokens < 1000000000) {
     return (tokens / 1000000).toFixed(2) + "m";
   } else {
-    return (tokens / 1000000000).toFixed(2) + "b";
+    return (tokens / 1000000000).toFixed(3) + "b";
   }
 }
+
+export function getCostSuffix(cost: number) {
+  if (!config.showTokenCosts) return "";
+  return ` ($${cost.toFixed(2)})`;
+}

src/shared/streaming.ts

@@ -1,6 +1,7 @@
-import { Request, Response } from "express";
+import { Response } from "express";
 import { IncomingMessage } from "http";
 import { assertNever } from "./utils";
+import { APIFormat } from "./key-management";
 
 export function initializeSseStream(res: Response) {
   res.statusCode = 200;
@@ -39,57 +40,84 @@ export function copySseResponseHeaders(
  * that the request is being proxied to. Used to send error messages to the
  * client in the middle of a streaming request.
  */
-export function buildFakeSse(
-  type: string,
-  string: string,
-  req: Request
-) {
-  let fakeEvent;
-  const content = `\`\`\`\n[${type}: ${string}]\n\`\`\`\n`;
+export function makeCompletionSSE({
+  format,
+  title,
+  message,
+  obj,
+  reqId,
+  model = "unknown",
+}: {
+  format: APIFormat;
+  title: string;
+  message: string;
+  obj?: object;
+  reqId: string | number | object;
+  model?: string;
+}) {
+  const id = String(reqId);
+  const content = `\n\n**${title}**\n${message}${
+    obj ? `\n\`\`\`\n${JSON.stringify(obj, null, 2)}\n\`\`\`\n` : ""
+  }`;
 
-  switch (req.inboundApi) {
+  let event;
+
+  switch (format) {
     case "openai":
-      fakeEvent = {
-        id: "chatcmpl-" + req.id,
+    case "mistral-ai":
+      event = {
+        id: "chatcmpl-" + id,
         object: "chat.completion.chunk",
         created: Date.now(),
-        model: req.body?.model,
-        choices: [{ delta: { content }, index: 0, finish_reason: type }]
+        model,
+        choices: [{ delta: { content }, index: 0, finish_reason: title }],
       };
       break;
     case "openai-text":
-      fakeEvent = {
-        id: "cmpl-" + req.id,
+      event = {
+        id: "cmpl-" + id,
         object: "text_completion",
         created: Date.now(),
         choices: [
-          { text: content, index: 0, logprobs: null, finish_reason: type }
+          { text: content, index: 0, logprobs: null, finish_reason: title },
         ],
-        model: req.body?.model
+        model,
       };
       break;
     case "anthropic":
-      fakeEvent = {
+      event = {
         completion: content,
-        stop_reason: type,
-        truncated: false, // I've never seen this be true
+        stop_reason: title,
+        truncated: false,
         stop: null,
-        model: req.body?.model,
-        log_id: "proxy-req-" + req.id
+        model,
+        log_id: "proxy-req-" + id,
       };
       break;
-    case "google-palm":
-      throw new Error("PaLM not supported as an inbound API format");
+    case "google-ai":
+      return JSON.stringify({
+        candidates: [
+          {
+            content: { parts: [{ text: content }], role: "model" },
+            finishReason: title,
+            index: 0,
+            tokenCount: null,
+            safetyRatings: [],
+          },
+        ],
+      });
+    case "openai-image":
+      throw new Error(`SSE not supported for ${format} requests`);
     default:
-      assertNever(req.inboundApi);
+      assertNever(format);
   }
 
-  if (req.inboundApi === "anthropic") {
-    return [
-      "event: completion",
-      `data: ${JSON.stringify(fakeEvent)}`,
-    ].join("\n") + "\n\n";
+  if (format === "anthropic") {
+    return (
+      ["event: completion", `data: ${JSON.stringify(event)}`].join("\n") +
+      "\n\n"
+    );
   }
 
-  return `data: ${JSON.stringify(fakeEvent)}\n\n`;
-}
+  return `data: ${JSON.stringify(event)}\n\n`;
+}

src/shared/tokenization/index.ts

@@ -1,2 +1 @@
-export { OpenAIPromptMessage } from "./openai";
 export { init, countTokens } from "./tokenizer";

src/shared/tokenization/mistral.ts

@@ -0,0 +1,45 @@
+import { MistralAIChatMessage } from "../../proxy/middleware/request/preprocessors/transform-outbound-payload.js";
+import * as tokenizer from "./mistral-tokenizer-js";
+
+export function init() {
+  tokenizer.initializemistralTokenizer();
+  return true;
+}
+
+export function getTokenCount(prompt: MistralAIChatMessage[] | string) {
+  if (typeof prompt === "string") {
+    return getTextTokenCount(prompt);
+  }
+
+  let chunks = [];
+  for (const message of prompt) {
+    switch (message.role) {
+      case "system":
+        chunks.push(message.content);
+        break;
+      case "assistant":
+        chunks.push(message.content + "</s>");
+        break;
+      case "user":
+        chunks.push("[INST] " + message.content + " [/INST]");
+        break;
+    }
+  }
+  return getTextTokenCount(chunks.join(" "));
+}
+
+function getTextTokenCount(prompt: string) {
+  // Don't try tokenizing if the prompt is massive to prevent DoS.
+  // 500k characters should be sufficient for all supported models.
+  if (prompt.length > 500000) {
+    return {
+      tokenizer: "length fallback",
+      token_count: 100000,
+    };
+  }
+
+  return {
+    tokenizer: "mistral-tokenizer-js",
+    token_count: tokenizer.encode(prompt.normalize("NFKC"))!.length,
+  };
+}

src/shared/tokenization/openai.ts

@@ -1,5 +1,15 @@
 import { Tiktoken } from "tiktoken/lite";
 import cl100k_base from "tiktoken/encoders/cl100k_base.json";
+import { logger } from "../../logger";
+import { libSharp } from "../file-storage";
+import type {
+  GoogleAIChatMessage,
+  OpenAIChatMessage,
+} from "../../proxy/middleware/request/preprocessors/transform-outbound-payload";
+import { z } from "zod";
+
+const log = logger.child({ module: "tokenizer", service: "openai" });
+const GPT4_VISION_SYSTEM_PROMPT_SIZE = 170;
 
 let encoder: Tiktoken;
 
@@ -15,40 +25,58 @@ export function init() {
 // Tested against:
 // https://github.com/openai/openai-cookbook/blob/main/examples/How_to_count_tokens_with_tiktoken.ipynb
 
-export function getTokenCount(
-  prompt: string | OpenAIPromptMessage[],
+export async function getTokenCount(
+  prompt: string | OpenAIChatMessage[],
   model: string
 ) {
   if (typeof prompt === "string") {
     return getTextTokenCount(prompt);
   }
 
-  const gpt4 = model.startsWith("gpt-4");
+  const oldFormatting = model.startsWith("turbo-0301");
+  const vision = model.includes("vision");
 
-  const tokensPerMessage = gpt4 ? 3 : 4;
-  const tokensPerName = gpt4 ? 1 : -1; // turbo omits role if name is present
+  const tokensPerMessage = oldFormatting ? 4 : 3;
+  const tokensPerName = oldFormatting ? -1 : 1; // older formatting replaces role with name if name is present
 
-  let numTokens = 0;
+  let numTokens = vision ? GPT4_VISION_SYSTEM_PROMPT_SIZE : 0;
 
   for (const message of prompt) {
     numTokens += tokensPerMessage;
     for (const key of Object.keys(message)) {
       {
-        const value = message[key as keyof OpenAIPromptMessage];
-        if (!value || typeof value !== "string") continue;
+        let textContent: string = "";
+        const value = message[key as keyof OpenAIChatMessage];
+
+        if (!value) continue;
+
+        if (Array.isArray(value)) {
+          for (const item of value) {
+            if (item.type === "text") {
+              textContent += item.text;
+            } else if (item.type === "image_url") {
+              const { url, detail } = item.image_url;
+              const cost = await getGpt4VisionTokenCost(url, detail);
+              numTokens += cost ?? 0;
+            }
+          }
+        } else {
+          textContent = value;
+        }
+
         // Break if we get a huge message or exceed the token limit to prevent
         // DoS.
-        // 100k tokens allows for future 100k GPT-4 models and 500k characters
+        // 200k tokens allows for future 200k GPT-4 models and 500k characters
         // is just a sanity check
-        if (value.length > 500000 || numTokens > 100000) {
-          numTokens = 100000;
+        if (textContent.length > 500000 || numTokens > 200000) {
+          numTokens = 200000;
           return {
             tokenizer: "tiktoken (prompt length limit exceeded)",
             token_count: numTokens,
           };
         }
 
-        numTokens += encoder.encode(value).length;
+        numTokens += encoder.encode(textContent).length;
         if (key === "name") {
           numTokens += tokensPerName;
         }
@@ -59,6 +87,78 @@ export function getTokenCount(
   return { tokenizer: "tiktoken", token_count: numTokens };
 }
 
+async function getGpt4VisionTokenCost(
+  url: string,
+  detail: "auto" | "low" | "high" = "auto"
+) {
+  // For now we do not allow remote images as the proxy would have to download
+  // them, which is a potential DoS vector.
+  if (!url.startsWith("data:image/")) {
+    throw new Error(
+      "Remote images are not supported. Add the image to your prompt as a base64 data URL."
+    );
+  }
+
+  const base64Data = url.split(",")[1];
+  const buffer = Buffer.from(base64Data, "base64");
+  const image = libSharp(buffer);
+  const metadata = await image.metadata();
+
+  if (!metadata || !metadata.width || !metadata.height) {
+    throw new Error("Prompt includes an image that could not be parsed");
+  }
+
+  const { width, height } = metadata;
+
+  let selectedDetail: "low" | "high";
+  if (detail === "auto") {
+    const threshold = 512 * 512;
+    const imageSize = width * height;
+    selectedDetail = imageSize > threshold ? "high" : "low";
+  } else {
+    selectedDetail = detail;
+  }
+
+  // https://platform.openai.com/docs/guides/vision/calculating-costs
+  if (selectedDetail === "low") {
+    log.info(
+      { width, height, tokens: 85 },
+      "Using fixed GPT-4-Vision token cost for low detail image"
+    );
+    return 85;
+  }
+
+  let newWidth = width;
+  let newHeight = height;
+  if (width > 2048 || height > 2048) {
+    const aspectRatio = width / height;
+    if (width > height) {
+      newWidth = 2048;
+      newHeight = Math.round(2048 / aspectRatio);
+    } else {
+      newHeight = 2048;
+      newWidth = Math.round(2048 * aspectRatio);
+    }
+  }
+
+  if (newWidth < newHeight) {
+    newHeight = Math.round((newHeight / newWidth) * 768);
+    newWidth = 768;
+  } else {
+    newWidth = Math.round((newWidth / newHeight) * 768);
+    newHeight = 768;
+  }
+
+  const tiles = Math.ceil(newWidth / 512) * Math.ceil(newHeight / 512);
+  const tokens = 170 * tiles + 85;
+
+  log.info(
+    { width, height, newWidth, newHeight, tiles, tokens },
+    "Calculated GPT-4-Vision token cost for high detail image"
+  );
+  return tokens;
+}
+
 function getTextTokenCount(prompt: string) {
   if (prompt.length > 500000) {
     return {
@@ -73,8 +173,83 @@ function getTextTokenCount(prompt: string) {
   };
 }
 
-export type OpenAIPromptMessage = {
-  name?: string;
-  content: string;
-  role: string;
-};
+// Model	Resolution	Price
+// DALL·E 3	1024×1024	$0.040 / image
+// 1024×1792, 1792×1024	$0.080 / image
+// DALL·E 3 HD	1024×1024	$0.080 / image
+// 1024×1792, 1792×1024	$0.120 / image
+// DALL·E 2	1024×1024	$0.020 / image
+// 512×512	$0.018 / image
+// 256×256	$0.016 / image
+
+export const DALLE_TOKENS_PER_DOLLAR = 100000;
+
+/**
+ * OpenAI image generation with DALL-E doesn't use tokens but everything else
+ * in the application does. There is a fixed cost for each image generation
+ * request depending on the model and selected quality/resolution parameters,
+ * which we convert to tokens at a rate of 100000 tokens per dollar.
+ */
+export function getOpenAIImageCost(params: {
+  model: "dall-e-2" | "dall-e-3";
+  quality: "standard" | "hd";
+  resolution: "512x512" | "256x256" | "1024x1024" | "1024x1792" | "1792x1024";
+  n: number | null;
+}) {
+  const { model, quality, resolution, n } = params;
+  const usd = (() => {
+    switch (model) {
+      case "dall-e-2":
+        switch (resolution) {
+          case "512x512":
+            return 0.018;
+          case "256x256":
+            return 0.016;
+          case "1024x1024":
+            return 0.02;
+          default:
+            throw new Error("Invalid resolution");
+        }
+      case "dall-e-3":
+        switch (resolution) {
+          case "1024x1024":
+            return quality === "standard" ? 0.04 : 0.08;
+          case "1024x1792":
+          case "1792x1024":
+            return quality === "standard" ? 0.08 : 0.12;
+          default:
+            throw new Error("Invalid resolution");
+        }
+      default:
+        throw new Error("Invalid image generation model");
+    }
+  })();
+
+  const tokens = (n ?? 1) * (usd * DALLE_TOKENS_PER_DOLLAR);
+
+  return {
+    tokenizer: `openai-image cost`,
+    token_count: Math.ceil(tokens),
+  };
+}
+
+export function estimateGoogleAITokenCount(prompt: string | GoogleAIChatMessage[]) {
+  if (typeof prompt === "string") {
+    return getTextTokenCount(prompt);
+  }
+
+  const tokensPerMessage = 3;
+
+  let numTokens = 0;
+  for (const message of prompt) {
+    numTokens += tokensPerMessage;
+    numTokens += encoder.encode(message.parts[0].text).length;
+  }
+
+  numTokens += 3;
+
+  return {
+    tokenizer: "tiktoken (google-ai estimate)",
+    token_count: numTokens,
+  };
+}

src/shared/tokenization/tokenizer.ts

@@ -1,4 +1,9 @@
 import { Request } from "express";
+import type {
+  GoogleAIChatMessage,
+  MistralAIChatMessage,
+  OpenAIChatMessage,
+} from "../../proxy/middleware/request/preprocessors/transform-outbound-payload";
 import { assertNever } from "../utils";
 import {
   init as initClaude,
@@ -7,25 +12,34 @@ import {
 import {
   init as initOpenAi,
   getTokenCount as getOpenAITokenCount,
-  OpenAIPromptMessage,
+  getOpenAIImageCost,
+  estimateGoogleAITokenCount,
 } from "./openai";
+import {
+  init as initMistralAI,
+  getTokenCount as getMistralAITokenCount,
+} from "./mistral";
 import { APIFormat } from "../key-management";
 
 export async function init() {
   initClaude();
   initOpenAi();
+  initMistralAI();
 }
 
 /** Tagged union via `service` field of the different types of requests that can
  * be made to the tokenization service, for both prompts and completions */
 type TokenCountRequest = { req: Request } & (
-  | { prompt: OpenAIPromptMessage[]; completion?: never; service: "openai" }
+  | { prompt: OpenAIChatMessage[]; completion?: never; service: "openai" }
   | {
       prompt: string;
       completion?: never;
-      service: "openai-text" | "anthropic" | "google-palm";
+      service: "openai-text" | "anthropic" | "google-ai";
     }
+  | { prompt?: GoogleAIChatMessage[]; completion?: never; service: "google-ai" }
+  | { prompt: MistralAIChatMessage[]; completion?: never; service: "mistral-ai" }
   | { prompt?: never; completion: string; service: APIFormat }
+  | { prompt?: never; completion?: never; service: "openai-image" }
 );
 
 type TokenCountResult = {
@@ -50,14 +64,29 @@ export async function countTokens({
     case "openai":
     case "openai-text":
       return {
-        ...getOpenAITokenCount(prompt ?? completion, req.body.model),
+        ...(await getOpenAITokenCount(prompt ?? completion, req.body.model)),
         tokenization_duration_ms: getElapsedMs(time),
       };
-    case "google-palm":
-      // TODO: Can't find a tokenization library for PaLM. There is an API
+    case "openai-image":
+      return {
+        ...getOpenAIImageCost({
+          model: req.body.model,
+          quality: req.body.quality,
+          resolution: req.body.size,
+          n: parseInt(req.body.n, 10) || null,
+        }),
+        tokenization_duration_ms: getElapsedMs(time),
+      };
+    case "google-ai":
+      // TODO: Can't find a tokenization library for Gemini. There is an API
       // endpoint for it but it adds significant latency to the request.
       return {
-        ...getOpenAITokenCount(prompt ?? completion, req.body.model),
+        ...estimateGoogleAITokenCount(prompt ?? (completion || [])),
+        tokenization_duration_ms: getElapsedMs(time),
+      };
+    case "mistral-ai":
+      return {
+        ...getMistralAITokenCount(prompt ?? completion),
         tokenization_duration_ms: getElapsedMs(time),
       };
     default:

src/shared/users/schema.ts

@@ -6,8 +6,10 @@ export const tokenCountsSchema: ZodType<UserTokenCounts> = z.object({
   turbo: z.number().optional().default(0),
   gpt4: z.number().optional().default(0),
   "gpt4-32k": z.number().optional().default(0),
+  "gpt4-turbo": z.number().optional().default(0),
+  "dall-e": z.number().optional().default(0),
   claude: z.number().optional().default(0),
-  bison: z.number().optional().default(0),
+  "gemini-pro": z.number().optional().default(0),
   "aws-claude": z.number().optional().default(0),
 });
 

src/shared/users/user-store.ts

@@ -11,9 +11,19 @@ import admin from "firebase-admin";
 import schedule from "node-schedule";
 import { v4 as uuid } from "uuid";
 import { config, getFirebaseApp } from "../../config";
-import { MODEL_FAMILIES, ModelFamily } from "../models";
+import {
+  getAzureOpenAIModelFamily,
+  getClaudeModelFamily,
+  getGoogleAIModelFamily,
+  getMistralAIModelFamily,
+  getOpenAIModelFamily,
+  MODEL_FAMILIES,
+  ModelFamily,
+} from "../models";
 import { logger } from "../../logger";
 import { User, UserTokenCounts, UserUpdate } from "./schema";
+import { APIFormat } from "../key-management";
+import { assertNever } from "../utils";
 
 const log = logger.child({ module: "users" });
 
@@ -21,9 +31,18 @@ const INITIAL_TOKENS: Required<UserTokenCounts> = {
   turbo: 0,
   gpt4: 0,
   "gpt4-32k": 0,
+  "gpt4-turbo": 0,
+  "dall-e": 0,
   claude: 0,
-  bison: 0,
+  "gemini-pro": 0,
+  "mistral-tiny": 0,
+  "mistral-small": 0,
+  "mistral-medium": 0,
   "aws-claude": 0,
+  "azure-turbo": 0,
+  "azure-gpt4": 0,
+  "azure-gpt4-turbo": 0,
+  "azure-gpt4-32k": 0,
 };
 
 const users: Map<string, User> = new Map();
@@ -165,11 +184,12 @@ export function incrementPromptCount(token: string) {
 export function incrementTokenCount(
   token: string,
   model: string,
+  api: APIFormat,
   consumption: number
 ) {
   const user = users.get(token);
   if (!user) return;
-  const modelFamily = getModelFamilyForQuotaUsage(model);
+  const modelFamily = getModelFamilyForQuotaUsage(model, api);
   const existing = user.tokenCounts[modelFamily] ?? 0;
   user.tokenCounts[modelFamily] = existing + consumption;
   usersToFlush.add(token);
@@ -180,34 +200,52 @@ export function incrementTokenCount(
  * to the user's list of IPs. Returns the user if they exist and are not
  * disabled, otherwise returns undefined.
  */
-export function authenticate(token: string, ip: string) {
+export function authenticate(
+  token: string,
+  ip: string
+): { user?: User; result: "success" | "disabled" | "not_found" | "limited" } {
   const user = users.get(token);
-  if (!user || user.disabledAt) return;
-  if (!user.ip.includes(ip)) user.ip.push(ip);
-  
-  const configIpLimit = user.maxIps ?? config.maxIpsPerUser;
-  const ipLimit =
-    user.type === "special" || !configIpLimit ? Infinity : configIpLimit;
-  if (user.ip.length > ipLimit) {
-    disableUser(token, "IP address limit exceeded.");
-    return;
+  if (!user) return { result: "not_found" };
+  if (user.disabledAt) return { result: "disabled" };
+
+  const newIp = !user.ip.includes(ip);
+
+  const userLimit = user.maxIps ?? config.maxIpsPerUser;
+  const enforcedLimit =
+    user.type === "special" || !userLimit ? Infinity : userLimit;
+
+  if (newIp && user.ip.length >= enforcedLimit) {
+    if (config.maxIpsAutoBan) {
+      user.ip.push(ip);
+      disableUser(token, "IP address limit exceeded.");
+      return { result: "disabled" };
+    }
+    return { result: "limited" };
+  } else if (newIp) {
+    user.ip.push(ip);
   }
 
   user.lastUsedAt = Date.now();
   usersToFlush.add(token);
-  return user;
+  return { user, result: "success" };
 }
 
-export function hasAvailableQuota(
-  token: string,
-  model: string,
-  requested: number
-) {
-  const user = users.get(token);
+export function hasAvailableQuota({
+  userToken,
+  model,
+  api,
+  requested,
+}: {
+  userToken: string;
+  model: string;
+  api: APIFormat;
+  requested: number;
+}) {
+  const user = users.get(userToken);
   if (!user) return false;
   if (user.type === "special") return true;
 
-  const modelFamily = getModelFamilyForQuotaUsage(model);
+  const modelFamily = getModelFamilyForQuotaUsage(model, api);
   const { tokenCounts, tokenLimits } = user;
   const tokenLimit = tokenLimits[modelFamily];
 
@@ -349,27 +387,27 @@ async function flushUsers() {
   );
 }
 
-// TODO: use key-management/models.ts for family mapping
-function getModelFamilyForQuotaUsage(model: string): ModelFamily {
-  if (model.includes("32k")) {
-    return "gpt4-32k";
+function getModelFamilyForQuotaUsage(
+  model: string,
+  api: APIFormat
+): ModelFamily {
+  // TODO: this seems incorrect
+  if (model.includes("azure")) return getAzureOpenAIModelFamily(model);
+
+  switch (api) {
+    case "openai":
+    case "openai-text":
+    case "openai-image":
+      return getOpenAIModelFamily(model);
+    case "anthropic":
+      return getClaudeModelFamily(model);
+    case "google-ai":
+      return getGoogleAIModelFamily(model);
+    case "mistral-ai":
+      return getMistralAIModelFamily(model);
+    default:
+      assertNever(api);
   }
-  if (model.startsWith("gpt-4")) {
-    return "gpt4";
-  }
-  if (model.startsWith("gpt-3.5")) {
-    return "turbo";
-  }
-  if (model.includes("bison")) {
-    return "bison";
-  }
-  if (model.startsWith("claude")) {
-    return "claude";
-  }
-  if(model.startsWith("anthropic.claude")) {
-    return "aws-claude";
-  }
-  throw new Error(`Unknown quota model family for model ${model}`);
 }
 
 function getRefreshCrontab() {