properly enforce allowedModelFamilies; refactor HPM proxyReq handlers

.env.example

@@ -11,11 +11,17 @@
 # The title displayed on the info page.
 # SERVER_TITLE=Coom Tunnel
 
-# Model requests allowed per minute per user.
+# Text model requests allowed per minute per user.
-# MODEL_RATE_LIMIT=4
+# 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 | bison | 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,bison,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.
+# Comma-separated list of phrases that will be rejected. Only whole words are matched.
-# REJECT_DISALLOWED=false
+# 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_BISON=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

@@ -3,6 +3,8 @@ 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

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-v1` (~18k context, claude 1.3)
-  - `anthropic.claude-v2` (~100k context)
+  - `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,bison,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

@@ -25,6 +25,8 @@ 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

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",
@@ -33,6 +34,7 @@
         "pino": "^8.11.0",
         "pino-http": "^8.3.3",
         "sanitize-html": "^2.11.0",
+        "sharp": "^0.32.6",
         "showdown": "^2.1.0",
         "tiktoken": "^1.0.10",
         "uuid": "^9.0.0",
@@ -1373,15 +1375,20 @@
       }
     },
     "node_modules/axios": {
-      "version": "1.3.5",
+      "version": "1.6.1",
-      "resolved": "https://registry.npmjs.org/axios/-/axios-1.3.5.tgz",
+      "resolved": "https://registry.npmjs.org/axios/-/axios-1.6.1.tgz",
-      "integrity": "sha512-glL/PvG/E+xCWwV8S6nCHcrfg1exGx7vxyUIivIA1iL7BIh6bePylCfVHwp6k13ao7SATxB6imau2kqY+I67kw==",
+      "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 +1430,52 @@
         "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 +1635,14 @@
         "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 +1670,11 @@
         "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 +1689,18 @@
         "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 +1717,15 @@
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       "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 +2087,28 @@
         "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 +2148,14 @@
         "npm": "1.2.8000 || >= 1.4.16"
       }
     },
+    "node_modules/detect-libc": {
+      "version": "2.0.2",
+      "resolved": "https://registry.npmjs.org/detect-libc/-/detect-libc-2.0.2.tgz",
+      "integrity": "sha512-UX6sGumvvqSaXgdKGUsgZWqcUyIXZ/vZTrlRT/iobiKhGL0zL4d3osHj3uqllWJK+i+sixDS/3COVEOFbupFyw==",
+      "engines": {
+        "node": ">=8"
+      }
+    },
     "node_modules/diff": {
       "version": "4.0.2",
       "resolved": "https://registry.npmjs.org/diff/-/diff-4.0.2.tgz",
@@ -2188,7 +2305,6 @@
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-      "devOptional": true,
       "dependencies": {
         "once": "^1.4.0"
       }
@@ -2473,6 +2589,14 @@
         "node": ">=0.8.x"
       }
     },
+    "node_modules/expand-template": {
+      "version": "2.0.3",
+      "resolved": "https://registry.npmjs.org/expand-template/-/expand-template-2.0.3.tgz",
+      "integrity": "sha512-XYfuKMvj4O35f/pOXLObndIRvyQ+/+6AhODh+OKWj9S9498pHHn/IMszH+gt0fBCRWMNfk1ZSp5x3AifmnI2vg==",
+      "engines": {
+        "node": ">=6"
+      }
+    },
     "node_modules/express": {
       "version": "4.18.2",
       "resolved": "https://registry.npmjs.org/express/-/express-4.18.2.tgz",
@@ -2557,6 +2681,11 @@
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       "optional": true
     },
+    "node_modules/fast-fifo": {
+      "version": "1.3.2",
+      "resolved": "https://registry.npmjs.org/fast-fifo/-/fast-fifo-1.3.2.tgz",
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+    },
     "node_modules/fast-levenshtein": {
       "version": "2.0.6",
       "resolved": "https://registry.npmjs.org/fast-levenshtein/-/fast-levenshtein-2.0.6.tgz",
@@ -2718,6 +2847,11 @@
         "node": ">= 0.6"
       }
     },
+    "node_modules/fs-constants": {
+      "version": "1.0.0",
+      "resolved": "https://registry.npmjs.org/fs-constants/-/fs-constants-1.0.0.tgz",
+      "integrity": "sha512-y6OAwoSIf7FyjMIv94u+b5rdheZEjzR63GTyZJm5qh4Bi+2YgwLCcI/fPFZkL5PSixOt6ZNKm+w+Hfp/Bciwow=="
+    },
     "node_modules/fs.realpath": {
       "version": "1.0.0",
       "resolved": "https://registry.npmjs.org/fs.realpath/-/fs.realpath-1.0.0.tgz",
@@ -2795,6 +2929,11 @@
         "url": "https://github.com/sponsors/ljharb"
       }
     },
+    "node_modules/github-from-package": {
+      "version": "0.0.0",
+      "resolved": "https://registry.npmjs.org/github-from-package/-/github-from-package-0.0.0.tgz",
+      "integrity": "sha512-SyHy3T1v2NUXn29OsWdxmK6RwHD+vkj3v8en8AOBZ1wBQ/hCAQ5bAQTD02kW4W9tUp/3Qh6J8r9EvntiyCmOOw=="
+    },
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       "resolved": "https://registry.npmjs.org/glob/-/glob-8.1.0.tgz",
@@ -3246,6 +3385,11 @@
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     },
+    "node_modules/ini": {
+      "version": "1.3.8",
+      "resolved": "https://registry.npmjs.org/ini/-/ini-1.3.8.tgz",
+      "integrity": "sha512-JV/yugV2uzW5iMRSiZAyDtQd+nxtUnjeLt0acNdw98kKLrvuRVyB80tsREOE7yvGVgalhZ6RNXCmEHkUKBKxew=="
+    },
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@@ -3254,6 +3398,11 @@
         "node": ">= 0.10"
       }
     },
+    "node_modules/is-arrayish": {
+      "version": "0.3.2",
+      "resolved": "https://registry.npmjs.org/is-arrayish/-/is-arrayish-0.3.2.tgz",
+      "integrity": "sha512-eVRqCvVlZbuw3GrM63ovNSNAeA1K16kaR/LRY/92w0zxQ5/1YzwblUX652i4Xs9RwAGjW9d9y6X88t8OaAJfWQ=="
+    },
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       "version": "2.1.0",
       "resolved": "https://registry.npmjs.org/is-binary-path/-/is-binary-path-2.1.0.tgz",
@@ -3780,6 +3929,17 @@
         "node": ">= 0.6"
       }
     },
+    "node_modules/mimic-response": {
+      "version": "3.1.0",
+      "resolved": "https://registry.npmjs.org/mimic-response/-/mimic-response-3.1.0.tgz",
+      "integrity": "sha512-z0yWI+4FDrrweS8Zmt4Ej5HdJmky15+L2e6Wgn3+iK5fWzb6T3fhNFq2+MeTRb064c6Wr4N/wv0DzQTjNzHNGQ==",
+      "engines": {
+        "node": ">=10"
+      },
+      "funding": {
+        "url": "https://github.com/sponsors/sindresorhus"
+      }
+    },
     "node_modules/minimatch": {
       "version": "3.1.2",
       "resolved": "https://registry.npmjs.org/minimatch/-/minimatch-3.1.2.tgz",
@@ -3810,6 +3970,11 @@
         "node": ">=10"
       }
     },
+    "node_modules/mkdirp-classic": {
+      "version": "0.5.3",
+      "resolved": "https://registry.npmjs.org/mkdirp-classic/-/mkdirp-classic-0.5.3.tgz",
+      "integrity": "sha512-gKLcREMhtuZRwRAfqP3RFW+TK4JqApVBtOIftVgjuABpAtpxhPGaDcfvbhNvD0B8iD1oUr/txX35NjcaY6Ns/A=="
+    },
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       "resolved": "https://registry.npmjs.org/ms/-/ms-2.0.0.tgz",
@@ -3860,6 +4025,11 @@
         "node": "^10 || ^12 || ^13.7 || ^14 || >=15.0.1"
       }
     },
+    "node_modules/napi-build-utils": {
+      "version": "1.0.2",
+      "resolved": "https://registry.npmjs.org/napi-build-utils/-/napi-build-utils-1.0.2.tgz",
+      "integrity": "sha512-ONmRUqK7zj7DWX0D9ADe03wbwOBZxNAfF20PlGfCWQcD3+/MakShIHrMqx9YwPTfxDdF1zLeL+RGZiR9kGMLdg=="
+    },
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       "resolved": "https://registry.npmjs.org/negotiator/-/negotiator-0.6.3.tgz",
@@ -3868,6 +4038,22 @@
         "node": ">= 0.6"
       }
     },
+    "node_modules/node-abi": {
+      "version": "3.51.0",
+      "resolved": "https://registry.npmjs.org/node-abi/-/node-abi-3.51.0.tgz",
+      "integrity": "sha512-SQkEP4hmNWjlniS5zdnfIXTk1x7Ome85RDzHlTbBtzE97Gfwz/Ipw4v/Ryk20DWIy3yCNVLVlGKApCnmvYoJbA==",
+      "dependencies": {
+        "semver": "^7.3.5"
+      },
+      "engines": {
+        "node": ">=10"
+      }
+    },
+    "node_modules/node-addon-api": {
+      "version": "6.1.0",
+      "resolved": "https://registry.npmjs.org/node-addon-api/-/node-addon-api-6.1.0.tgz",
+      "integrity": "sha512-+eawOlIgy680F0kBzPUNFhMZGtJ1YmqM6l4+Crf4IkImjYrO/mqPwRMh352g23uIaQKFItcQ64I7KMaJxHgAVA=="
+    },
     "node_modules/node-fetch": {
       "version": "2.6.9",
       "resolved": "https://registry.npmjs.org/node-fetch/-/node-fetch-2.6.9.tgz",
@@ -4217,6 +4403,70 @@
         "node": "^10 || ^12 || >=14"
       }
     },
+    "node_modules/prebuild-install": {
+      "version": "7.1.1",
+      "resolved": "https://registry.npmjs.org/prebuild-install/-/prebuild-install-7.1.1.tgz",
+      "integrity": "sha512-jAXscXWMcCK8GgCoHOfIr0ODh5ai8mj63L2nWrjuAgXE6tDyYGnx4/8o/rCgU+B4JSyZBKbeZqzhtwtC3ovxjw==",
+      "dependencies": {
+        "detect-libc": "^2.0.0",
+        "expand-template": "^2.0.3",
+        "github-from-package": "0.0.0",
+        "minimist": "^1.2.3",
+        "mkdirp-classic": "^0.5.3",
+        "napi-build-utils": "^1.0.1",
+        "node-abi": "^3.3.0",
+        "pump": "^3.0.0",
+        "rc": "^1.2.7",
+        "simple-get": "^4.0.0",
+        "tar-fs": "^2.0.0",
+        "tunnel-agent": "^0.6.0"
+      },
+      "bin": {
+        "prebuild-install": "bin.js"
+      },
+      "engines": {
+        "node": ">=10"
+      }
+    },
+    "node_modules/prebuild-install/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/prebuild-install/node_modules/tar-fs": {
+      "version": "2.1.1",
+      "resolved": "https://registry.npmjs.org/tar-fs/-/tar-fs-2.1.1.tgz",
+      "integrity": "sha512-V0r2Y9scmbDRLCNex/+hYzvp/zyYjvFbHPNgVTKfQvVrb6guiE/fxP+XblDNR011utopbkex2nM4dHNV6GDsng==",
+      "dependencies": {
+        "chownr": "^1.1.1",
+        "mkdirp-classic": "^0.5.2",
+        "pump": "^3.0.0",
+        "tar-stream": "^2.1.4"
+      }
+    },
+    "node_modules/prebuild-install/node_modules/tar-stream": {
+      "version": "2.2.0",
+      "resolved": "https://registry.npmjs.org/tar-stream/-/tar-stream-2.2.0.tgz",
+      "integrity": "sha512-ujeqbceABgwMZxEJnk2HDY2DlnUZ+9oEcb1KzTVfYHio0UE6dG71n60d8D2I4qNvleWrrXpmjpt7vZeF1LnMZQ==",
+      "dependencies": {
+        "bl": "^4.0.3",
+        "end-of-stream": "^1.4.1",
+        "fs-constants": "^1.0.0",
+        "inherits": "^2.0.3",
+        "readable-stream": "^3.1.1"
+      },
+      "engines": {
+        "node": ">=6"
+      }
+    },
     "node_modules/prettier": {
       "version": "3.0.3",
       "resolved": "https://registry.npmjs.org/prettier/-/prettier-3.0.3.tgz",
@@ -4352,7 +4602,6 @@
       "version": "3.0.0",
       "resolved": "https://registry.npmjs.org/pump/-/pump-3.0.0.tgz",
       "integrity": "sha512-LwZy+p3SFs1Pytd/jYct4wpv49HiYCqd9Rlc5ZVdk0V+8Yzv6jR5Blk3TRmPL1ft69TxP0IMZGJ+WPFU2BFhww==",
-      "dev": true,
       "dependencies": {
         "end-of-stream": "^1.1.0",
         "once": "^1.3.1"
@@ -4372,6 +4621,11 @@
         "url": "https://github.com/sponsors/ljharb"
       }
     },
+    "node_modules/queue-tick": {
+      "version": "1.0.1",
+      "resolved": "https://registry.npmjs.org/queue-tick/-/queue-tick-1.0.1.tgz",
+      "integrity": "sha512-kJt5qhMxoszgU/62PLP1CJytzd2NKetjSRnyuj31fDd3Rlcz3fzlFdFLD1SItunPwyqEOkca6GbV612BWfaBag=="
+    },
     "node_modules/quick-format-unescaped": {
       "version": "4.0.4",
       "resolved": "https://registry.npmjs.org/quick-format-unescaped/-/quick-format-unescaped-4.0.4.tgz",
@@ -4407,6 +4661,28 @@
         "node": ">= 0.8"
       }
     },
+    "node_modules/rc": {
+      "version": "1.2.8",
+      "resolved": "https://registry.npmjs.org/rc/-/rc-1.2.8.tgz",
+      "integrity": "sha512-y3bGgqKj3QBdxLbLkomlohkvsA8gdAiUQlSBJnBhfn+BPxg4bc62d8TcBW15wavDfgexCgccckhcZvywyQYPOw==",
+      "dependencies": {
+        "deep-extend": "^0.6.0",
+        "ini": "~1.3.0",
+        "minimist": "^1.2.0",
+        "strip-json-comments": "~2.0.1"
+      },
+      "bin": {
+        "rc": "cli.js"
+      }
+    },
+    "node_modules/rc/node_modules/strip-json-comments": {
+      "version": "2.0.1",
+      "resolved": "https://registry.npmjs.org/strip-json-comments/-/strip-json-comments-2.0.1.tgz",
+      "integrity": "sha512-4gB8na07fecVVkOI6Rs4e7T6NOTki5EmL7TUduTs6bu3EdnSycntVJ4re8kgZA+wx9IueI2Y11bfbgwtzuE0KQ==",
+      "engines": {
+        "node": ">=0.10.0"
+      }
+    },
     "node_modules/readable-stream": {
       "version": "4.3.0",
       "resolved": "https://registry.npmjs.org/readable-stream/-/readable-stream-4.3.0.tgz",
@@ -4615,9 +4891,9 @@
       "dev": true
     },
     "node_modules/semver": {
-      "version": "7.5.3",
+      "version": "7.5.4",
-      "resolved": "https://registry.npmjs.org/semver/-/semver-7.5.3.tgz",
+      "resolved": "https://registry.npmjs.org/semver/-/semver-7.5.4.tgz",
-      "integrity": "sha512-QBlUtyVk/5EeHbi7X0fw6liDZc7BBmEaSYn01fMU1OUYbf6GPsbTtd8WmnqbI20SeycoHSeiybkE/q1Q+qlThQ==",
+      "integrity": "sha512-1bCSESV6Pv+i21Hvpxp3Dx+pSD8lIPt8uVjRrxAUt/nbswYc+tK6Y2btiULjd4+fnq15PX+nqQDC7Oft7WkwcA==",
       "dependencies": {
         "lru-cache": "^6.0.0"
       },
@@ -4675,6 +4951,28 @@
       "resolved": "https://registry.npmjs.org/setprototypeof/-/setprototypeof-1.2.0.tgz",
       "integrity": "sha512-E5LDX7Wrp85Kil5bhZv46j8jOeboKq5JMmYM3gVGdGH8xFpPWXUMsNrlODCrkoxMEeNi/XZIwuRvY4XNwYMJpw=="
     },
+    "node_modules/sharp": {
+      "version": "0.32.6",
+      "resolved": "https://registry.npmjs.org/sharp/-/sharp-0.32.6.tgz",
+      "integrity": "sha512-KyLTWwgcR9Oe4d9HwCwNM2l7+J0dUQwn/yf7S0EnTtb0eVS4RxO0eUSvxPtzT4F3SY+C4K6fqdv/DO27sJ/v/w==",
+      "hasInstallScript": true,
+      "dependencies": {
+        "color": "^4.2.3",
+        "detect-libc": "^2.0.2",
+        "node-addon-api": "^6.1.0",
+        "prebuild-install": "^7.1.1",
+        "semver": "^7.5.4",
+        "simple-get": "^4.0.1",
+        "tar-fs": "^3.0.4",
+        "tunnel-agent": "^0.6.0"
+      },
+      "engines": {
+        "node": ">=14.15.0"
+      },
+      "funding": {
+        "url": "https://opencollective.com/libvips"
+      }
+    },
     "node_modules/shell-quote": {
       "version": "1.8.1",
       "resolved": "https://registry.npmjs.org/shell-quote/-/shell-quote-1.8.1.tgz",
@@ -4712,6 +5010,57 @@
         "url": "https://github.com/sponsors/ljharb"
       }
     },
+    "node_modules/simple-concat": {
+      "version": "1.0.1",
+      "resolved": "https://registry.npmjs.org/simple-concat/-/simple-concat-1.0.1.tgz",
+      "integrity": "sha512-cSFtAPtRhljv69IK0hTVZQ+OfE9nePi/rtJmw5UjHeVyVroEqJXP1sFztKUy1qU+xvz3u/sfYJLa947b7nAN2Q==",
+      "funding": [
+        {
+          "type": "github",
+          "url": "https://github.com/sponsors/feross"
+        },
+        {
+          "type": "patreon",
+          "url": "https://www.patreon.com/feross"
+        },
+        {
+          "type": "consulting",
+          "url": "https://feross.org/support"
+        }
+      ]
+    },
+    "node_modules/simple-get": {
+      "version": "4.0.1",
+      "resolved": "https://registry.npmjs.org/simple-get/-/simple-get-4.0.1.tgz",
+      "integrity": "sha512-brv7p5WgH0jmQJr1ZDDfKDOSeWWg+OVypG99A/5vYGPqJ6pxiaHLy8nxtFjBA7oMa01ebA9gfh1uMCFqOuXxvA==",
+      "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": {
+        "decompress-response": "^6.0.0",
+        "once": "^1.3.1",
+        "simple-concat": "^1.0.0"
+      }
+    },
+    "node_modules/simple-swizzle": {
+      "version": "0.2.2",
+      "resolved": "https://registry.npmjs.org/simple-swizzle/-/simple-swizzle-0.2.2.tgz",
+      "integrity": "sha512-JA//kQgZtbuY83m+xT+tXJkmJncGMTFT+C+g2h2R9uxkYIrE2yy9sgmcLhCnw57/WSD+Eh3J97FPEDFnbXnDUg==",
+      "dependencies": {
+        "is-arrayish": "^0.3.1"
+      }
+    },
     "node_modules/simple-update-notifier": {
       "version": "2.0.0",
       "resolved": "https://registry.npmjs.org/simple-update-notifier/-/simple-update-notifier-2.0.0.tgz",
@@ -4809,11 +5158,19 @@
         "node": ">=10.0.0"
       }
     },
+    "node_modules/streamx": {
+      "version": "2.15.4",
+      "resolved": "https://registry.npmjs.org/streamx/-/streamx-2.15.4.tgz",
+      "integrity": "sha512-uSXKl88bibiUCQ1eMpItRljCzDENcDx18rsfDmV79r0e/ThfrAwxG4Y2FarQZ2G4/21xcOKmFFd1Hue+ZIDwHw==",
+      "dependencies": {
+        "fast-fifo": "^1.1.0",
+        "queue-tick": "^1.0.1"
+      }
+    },
     "node_modules/string_decoder": {
       "version": "1.3.0",
       "resolved": "https://registry.npmjs.org/string_decoder/-/string_decoder-1.3.0.tgz",
       "integrity": "sha512-hkRX8U1WjJFd8LsDJ2yQ/wWWxaopEsABU1XfkM8A+j0+85JAGppt16cr1Whg6KIbb4okU6Mql6BOj+uup/wKeA==",
-      "devOptional": true,
       "dependencies": {
         "safe-buffer": "~5.2.0"
       }
@@ -4872,6 +5229,26 @@
         "node": ">=4"
       }
     },
+    "node_modules/tar-fs": {
+      "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 +5424,17 @@
       "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",
@@ -41,6 +42,7 @@
     "pino": "^8.11.0",
     "pino-http": "^8.3.3",
     "sanitize-html": "^2.11.0",
+    "sharp": "^0.32.6",
     "showdown": "^2.1.0",
     "tiktoken": "^1.0.10",
     "uuid": "^9.0.0",

scripts/oai-reverse-proxy.http

@@ -0,0 +1,248 @@
+# 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-3.5-turbo",
+  "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 / Google PaLM -- OpenAI-to-PaLM API Translation
+POST {{proxy-host}}/proxy/google-palm/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 +1,44 @@
+const axios = require("axios");
+
+const concurrentRequests = 5;
+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/azure/openai/v1/chat/completions",
+      payload,
+      { headers }
+    );
+    console.log(
+      `Req ${i} finished with status code ${response.status} and response:`,
+      response.data
+    );
+  } catch (error) {
+    console.error(`Error in req ${i}:`, error.message);
+  }
+};
+
+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 +4,7 @@ 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 { buildInfoPageHtml } from "../info-page";
 import { loginRouter } from "./login";
 import { usersApiRouter as apiRouter } from "./api/users";
 import { usersWebRouter as webRouter } from "./web/manage";
@@ -23,6 +24,11 @@ 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(
+    buildInfoPageHtml(req.protocol + "://" + req.get("host"), true)
+  );
+});
 
 adminRouter.use(
   (

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 +1,17 @@
 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;
@@ -28,6 +33,17 @@ 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 +81,20 @@ 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 +113,10 @@ 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. */
+  /** Whether requests containing the following phrases should be rejected. */
-  rejectDisallowed?: boolean;
+  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 +175,20 @@ 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.
@@ -162,22 +199,25 @@ export const config: Config = {
   anthropicKey: getEnvWithDefault("ANTHROPIC_KEY", ""),
   googlePalmKey: getEnvWithDefault("GOOGLE_PALM_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),
+  textModelRateLimit: getEnvWithDefault("TEXT_MODEL_RATE_LIMIT", 4),
-  maxContextTokensOpenAI: getEnvWithDefault("MAX_CONTEXT_TOKENS_OPENAI", 0),
+  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 +227,16 @@ export const config: Config = {
     "turbo",
     "gpt4",
     "gpt4-32k",
+    "gpt4-turbo",
     "claude",
     "bison",
     "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 +258,21 @@ 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: {
+  tokenQuota: MODEL_FAMILIES.reduce(
-    turbo: getEnvWithDefault("TOKEN_QUOTA_TURBO", 0),
+    (acc, family: ModelFamily) => {
-    gpt4: getEnvWithDefault("TOKEN_QUOTA_GPT4", 0),
+      acc[family] = getEnvWithDefault(
-    "gpt4-32k": getEnvWithDefault("TOKEN_QUOTA_GPT4_32K", 0),
+        `TOKEN_QUOTA_${family.toUpperCase().replace(/-/g, "_")}`,
-    claude: getEnvWithDefault("TOKEN_QUOTA_CLAUDE", 0),
+        0
-    bison: getEnvWithDefault("TOKEN_QUOTA_BISON", 0),
+      ) as number;
-    "aws-claude": getEnvWithDefault("TOKEN_QUOTA_AWS_CLAUDE", 0),
+      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 +288,16 @@ 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."
+      { textLimit: limit, imageLimit: config.imageModelRateLimit },
-    );
+      "MODEL_RATE_LIMIT is deprecated. Use TEXT_MODEL_RATE_LIMIT and IMAGE_MODEL_RATE_LIMIT instead."
-    config.allowedModelFamilies = config.allowedModelFamilies.filter(
-      (f) => !f.includes("gpt4")
     );
   }
 
@@ -284,7 +338,8 @@ 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))
@@ -313,9 +368,10 @@ export const OMITTED_KEYS: (keyof Config)[] = [
   "anthropicKey",
   "googlePalmKey",
   "awsCredentials",
+  "azureCredentials",
   "proxyKey",
   "adminKey",
-  "checkKeys",
+  "rejectPhrases",
   "showTokenCosts",
   "googleSheetsKey",
   "firebaseKey",
@@ -326,6 +382,11 @@ export const OMITTED_KEYS: (keyof Config)[] = [
   "blockMessage",
   "blockRedirect",
   "allowNicknameChanges",
+  "showRecentImages",
+  "useInsecureCookies",
+  "staticServiceInfo",
+  "checkKeys",
+  "allowedModelFamilies",
 ];
 
 const getKeys = Object.keys as <T extends object>(obj: T) => Array<keyof T>;
@@ -374,6 +435,7 @@ function getEnvWithDefault<T>(env: string | string[], defaultValue: T): T {
         "ANTHROPIC_KEY",
         "GOOGLE_PALM_KEY",
         "AWS_CREDENTIALS",
+        "AZURE_CREDENTIALS",
       ].includes(String(env))
     ) {
       return value as unknown as T;
@@ -415,3 +477,11 @@ 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

@@ -1,19 +1,26 @@
+/** This whole module really sucks */
 import fs from "fs";
 import { Request, Response } from "express";
 import showdown from "showdown";
 import { config, listConfig } from "./config";
 import {
   AnthropicKey,
-  GooglePalmKey,
-  OpenAIKey,
   AwsBedrockKey,
+  AzureOpenAIKey,
+  GooglePalmKey,
   keyPool,
+  OpenAIKey,
 } from "./shared/key-management";
-import { ModelFamily, OpenAIModelFamily } from "./shared/models";
+import {
+  AzureOpenAIModelFamily,
+  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 { getLastNImages } from "./shared/file-storage/image-history";
 
 const INFO_PAGE_TTL = 2000;
 let infoPageHtml: string | undefined;
@@ -22,6 +29,8 @@ let infoPageLastUpdated = 0;
 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 keyIsGooglePalmKey = (k: KeyPoolKey): k is GooglePalmKey =>
@@ -47,6 +56,7 @@ type ServiceAggregates = {
   anthropicKeys?: number;
   palmKeys?: number;
   awsKeys?: number;
+  azureKeys?: number;
   proompts: number;
   tokens: number;
   tokenCost: number;
@@ -61,17 +71,18 @@ 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 res.send(infoPageHtml);
-    return;
   }
 
-  // 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));
+  infoPageHtml = buildInfoPageHtml(baseUrl + "/proxy");
+  infoPageLastUpdated = Date.now();
+
+  res.send(infoPageHtml);
 };
 
 function getCostString(cost: number) {
@@ -79,8 +90,9 @@ function getCostString(cost: number) {
   return ` ($${cost.toFixed(2)})`;
 }
 
-function cacheInfoPageHtml(baseUrl: string) {
+export function buildInfoPageHtml(baseUrl: string, asAdmin = false) {
   const keys = keyPool.list();
+  const hideFullInfo = config.staticServiceInfo && !asAdmin;
 
   modelStats.clear();
   serviceStats.clear();
@@ -90,32 +102,58 @@ function cacheInfoPageHtml(baseUrl: string) {
   const anthropicKeys = serviceStats.get("anthropicKeys") || 0;
   const palmKeys = serviceStats.get("palmKeys") || 0;
   const awsKeys = serviceStats.get("awsKeys") || 0;
+  const azureKeys = serviceStats.get("azureKeys") || 0;
   const proompts = serviceStats.get("proompts") || 0;
   const tokens = serviceStats.get("tokens") || 0;
   const tokenCost = serviceStats.get("tokenCost") || 0;
 
-  const info = {
+  const allowDalle = config.allowedModelFamilies.includes("dall-e");
-    uptime: Math.floor(process.uptime()),
+
-    endpoints: {
+  const endpoints = {
-      ...(openaiKeys ? { openai: baseUrl + "/proxy/openai" } : {}),
+    ...(openaiKeys ? { openai: baseUrl + "/openai" } : {}),
-      ...(openaiKeys
+    ...(openaiKeys ? { openai2: baseUrl + "/openai/turbo-instruct" } : {}),
-        ? { ["openai2"]: baseUrl + "/proxy/openai/turbo-instruct" }
+    ...(openaiKeys && allowDalle
-        : {}),
+      ? { ["openai-image"]: baseUrl + "/openai-image" }
-      ...(anthropicKeys ? { anthropic: baseUrl + "/proxy/anthropic" } : {}),
+      : {}),
-      ...(palmKeys ? { "google-palm": baseUrl + "/proxy/google-palm" } : {}),
+    ...(anthropicKeys ? { anthropic: baseUrl + "/anthropic" } : {}),
-      ...(awsKeys ? { aws: baseUrl + "/proxy/aws/claude" } : {}),
+    ...(palmKeys ? { "google-palm": baseUrl + "/google-palm" } : {}),
-    },
+    ...(awsKeys ? { aws: baseUrl + "/aws/claude" } : {}),
+    ...(azureKeys ? { azure: baseUrl + "/azure/openai" } : {}),
+  };
+
+  const stats = {
     proompts,
     tookens: `${prettyTokens(tokens)}${getCostString(tokenCost)}`,
-    ...(config.modelRateLimit ? { proomptersNow: getUniqueIps() } : {}),
+    ...(config.textModelRateLimit ? { proomptersNow: getUniqueIps() } : {}),
-    openaiKeys,
+  };
-    anthropicKeys,
+
-    palmKeys,
+  const keyInfo = { openaiKeys, anthropicKeys, palmKeys, awsKeys, azureKeys };
-    awsKeys,
+  for (const key of Object.keys(keyInfo)) {
+    if (!(keyInfo as any)[key]) delete (keyInfo as any)[key];
+  }
+
+  const providerInfo = {
     ...(openaiKeys ? getOpenAIInfo() : {}),
     ...(anthropicKeys ? getAnthropicInfo() : {}),
-    ...(palmKeys ? { "palm-bison": getPalmInfo() } : {}),
+    ...(palmKeys ? getPalmInfo() : {}),
-    ...(awsKeys ? { "aws-claude": getAwsInfo() } : {}),
+    ...(awsKeys ? getAwsInfo() : {}),
+    ...(azureKeys ? getAzureInfo() : {}),
+  };
+
+  if (hideFullInfo) {
+    for (const provider of Object.keys(providerInfo)) {
+      delete (providerInfo as any)[provider].proomptersInQueue;
+      delete (providerInfo as any)[provider].estimatedQueueTime;
+      delete (providerInfo as any)[provider].usage;
+    }
+  }
+
+  const info = {
+    uptime: Math.floor(process.uptime()),
+    endpoints,
+    ...(hideFullInfo ? {} : stats),
+    ...keyInfo,
+    ...providerInfo,
     config: listConfig(),
     build: process.env.BUILD_INFO || "dev",
   };
@@ -123,7 +161,7 @@ function cacheInfoPageHtml(baseUrl: string) {
   const title = getServerTitle();
   const headerHtml = buildInfoPageHeader(new showdown.Converter(), title);
 
-  const pageBody = `<!DOCTYPE html>
+  return `<!DOCTYPE html>
 <html lang="en">
   <head>
     <meta charset="utf-8" />
@@ -138,11 +176,6 @@ function cacheInfoPageHtml(baseUrl: string) {
     ${getSelfServiceLinks()}
   </body>
 </html>`;
-
-  infoPageHtml = pageBody;
-  infoPageLastUpdated = Date.now();
-
-  return pageBody;
 }
 
 function getUniqueOpenAIOrgs(keys: KeyPoolKey[]) {
@@ -166,13 +199,10 @@ function addKeyToAggregates(k: KeyPoolKey) {
   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);
+  increment(serviceStats, "azureKeys", k.service === "azure" ? 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":
@@ -183,30 +213,35 @@ function addKeyToAggregates(k: KeyPoolKey) {
         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);
+        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);
       });
-
-      if (families.includes("gpt4-32k")) {
-        family = "gpt4-32k";
-      } else if (families.includes("gpt4")) {
-        family = "gpt4";
-      } else {
-        family = "turbo";
-      }
-
-      increment(modelStats, `${family}__trial`, k.isTrial ? 1 : 0);
       break;
-    case "anthropic":
+    case "azure":
+      if (!keyIsAzureKey(k)) throw new Error("Invalid key type");
+      k.modelFamilies.forEach((f) => {
+        const tokens = k[`${f}Tokens`];
+        sumTokens += tokens;
+        sumCost += getTokenCostUsd(f, tokens);
+        increment(modelStats, `${f}__tokens`, tokens);
+        increment(modelStats, `${f}__active`, k.isDisabled ? 0 : 1);
+        increment(modelStats, `${f}__revoked`, k.isRevoked ? 1 : 0);
+      });
+      break;
+    case "anthropic": {
       if (!keyIsAnthropicKey(k)) throw new Error("Invalid key type");
-      family = "claude";
+      const family = "claude";
       sumTokens += k.claudeTokens;
       sumCost += getTokenCostUsd(family, k.claudeTokens);
+      increment(modelStats, `${family}__active`, k.isDisabled ? 0 : 1);
+      increment(modelStats, `${family}__revoked`, k.isRevoked ? 1 : 0);
       increment(modelStats, `${family}__tokens`, k.claudeTokens);
       increment(modelStats, `${family}__pozzed`, k.isPozzed ? 1 : 0);
       increment(
@@ -215,18 +250,24 @@ function addKeyToAggregates(k: KeyPoolKey) {
         Boolean(k.lastChecked) ? 0 : 1
       );
       break;
-    case "google-palm":
+    }
+    case "google-palm": {
       if (!keyIsGooglePalmKey(k)) throw new Error("Invalid key type");
-      family = "bison";
+      const family = "bison";
       sumTokens += k.bisonTokens;
       sumCost += getTokenCostUsd(family, k.bisonTokens);
+      increment(modelStats, `${family}__active`, k.isDisabled ? 0 : 1);
+      increment(modelStats, `${family}__revoked`, k.isRevoked ? 1 : 0);
       increment(modelStats, `${family}__tokens`, k.bisonTokens);
       break;
-    case "aws":
+    }
+    case "aws": {
       if (!keyIsAwsKey(k)) throw new Error("Invalid key type");
-      family = "aws-claude";
+      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
@@ -236,19 +277,13 @@ function addKeyToAggregates(k: KeyPoolKey) {
       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() {
@@ -264,14 +299,13 @@ function getOpenAIInfo() {
     };
   } = {};
 
-  const allowedFamilies = new Set(config.allowedModelFamilies);
+  const keys = keyPool.list().filter(keyIsOpenAIKey);
-  let families = new Set<OpenAIModelFamily>();
+  const enabledFamilies = new Set(config.allowedModelFamilies);
-  const keys = keyPool.list().filter((k) => {
+  const accessibleFamilies = keys
-    const isOpenAI = keyIsOpenAIKey(k);
+    .flatMap((k) => k.modelFamilies)
-    if (isOpenAI) k.modelFamilies.forEach((f) => families.add(f));
+    .filter((f) => enabledFamilies.has(f))
-    return isOpenAI;
+    .concat("turbo");
-  }) as Omit<OpenAIKey, "key">[];
+  const familySet = new Set(accessibleFamilies);
-  families = new Set([...families].filter((f) => allowedFamilies.has(f)));
 
   if (config.checkKeys) {
     const unchecked = serviceStats.get("openAiUncheckedKeys") || 0;
@@ -281,7 +315,7 @@ function getOpenAIInfo() {
     info.openaiKeys = keys.length;
     info.openaiOrgs = getUniqueOpenAIOrgs(keys);
 
-    families.forEach((f) => {
+    familySet.forEach((f) => {
       const tokens = modelStats.get(`${f}__tokens`) || 0;
       const cost = getTokenCostUsd(f, tokens);
 
@@ -292,6 +326,13 @@ function getOpenAIInfo() {
         revokedKeys: modelStats.get(`${f}__revoked`) || 0,
         overQuotaKeys: modelStats.get(`${f}__overQuota`) || 0,
       };
+
+      // Don't show trial/revoked keys for non-turbo families.
+      // Generally those stats only make sense for the lowest-tier model.
+      if (f !== "turbo") {
+        delete info[f]!.trialKeys;
+        delete info[f]!.revokedKeys;
+      }
     });
   } else {
     info.status = "Key checking is disabled.";
@@ -303,11 +344,14 @@ function getOpenAIInfo() {
     };
   }
 
-  families.forEach((f) => {
+  familySet.forEach((f) => {
-    if (info[f]) {
+    if (enabledFamilies.has(f)) {
+      if (!info[f]) info[f] = { activeKeys: 0 }; // may occur if checkKeys is disabled
       const { estimatedQueueTime, proomptersInQueue } = getQueueInformation(f);
       info[f]!.proomptersInQueue = proomptersInQueue;
       info[f]!.estimatedQueueTime = estimatedQueueTime;
+    } else {
+      (info[f]! as any).status = "GPT-3.5-Turbo is disabled on this proxy.";
     }
   });
 
@@ -318,6 +362,7 @@ function getAnthropicInfo() {
   const claudeInfo: Partial<ModelAggregates> = {
     active: modelStats.get("claude__active") || 0,
     pozzed: modelStats.get("claude__pozzed") || 0,
+    revoked: modelStats.get("claude__revoked") || 0,
   };
 
   const queue = getQueueInformation("claude");
@@ -335,6 +380,7 @@ function getAnthropicInfo() {
       usage: `${prettyTokens(tokens)} tokens${getCostString(cost)}`,
       ...(unchecked > 0 ? { status: `Checking ${unchecked} keys...` } : {}),
       activeKeys: claudeInfo.active,
+      revokedKeys: claudeInfo.revoked,
       ...(config.checkKeys ? { pozzedKeys: claudeInfo.pozzed } : {}),
       proomptersInQueue: claudeInfo.queued,
       estimatedQueueTime: claudeInfo.queueTime,
@@ -345,6 +391,7 @@ function getAnthropicInfo() {
 function getPalmInfo() {
   const bisonInfo: Partial<ModelAggregates> = {
     active: modelStats.get("bison__active") || 0,
+    revoked: modelStats.get("bison__revoked") || 0,
   };
 
   const queue = getQueueInformation("bison");
@@ -355,16 +402,20 @@ function getPalmInfo() {
   const cost = getTokenCostUsd("bison", tokens);
 
   return {
-    usage: `${prettyTokens(tokens)} tokens${getCostString(cost)}`,
+    bison: {
-    activeKeys: bisonInfo.active,
+      usage: `${prettyTokens(tokens)} tokens${getCostString(cost)}`,
-    proomptersInQueue: bisonInfo.queued,
+      activeKeys: bisonInfo.active,
-    estimatedQueueTime: bisonInfo.queueTime,
+      revokedKeys: bisonInfo.revoked,
+      proomptersInQueue: bisonInfo.queued,
+      estimatedQueueTime: bisonInfo.queueTime,
+    },
   };
 }
 
 function getAwsInfo() {
   const awsInfo: Partial<ModelAggregates> = {
     active: modelStats.get("aws-claude__active") || 0,
+    revoked: modelStats.get("aws-claude__revoked") || 0,
   };
 
   const queue = getQueueInformation("aws-claude");
@@ -377,20 +428,65 @@ function getAwsInfo() {
   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.`;
+    : `${logged} active keys are potentially logged and can't be used. Set ALLOW_AWS_LOGGING=true to override.`;
 
   return {
-    usage: `${prettyTokens(tokens)} tokens${getCostString(cost)}`,
+    "aws-claude": {
-    activeKeys: awsInfo.active,
+      usage: `${prettyTokens(tokens)} tokens${getCostString(cost)}`,
-    proomptersInQueue: awsInfo.queued,
+      activeKeys: awsInfo.active,
-    estimatedQueueTime: awsInfo.queueTime,
+      revokedKeys: awsInfo.revoked,
-    ...(logged > 0 ? { privacy: logMsg } : {}),
+      proomptersInQueue: awsInfo.queued,
+      estimatedQueueTime: awsInfo.queueTime,
+      ...(logged > 0 ? { privacy: logMsg } : {}),
+    },
   };
 }
 
+function getAzureInfo() {
+  const azureFamilies = [
+    "azure-turbo",
+    "azure-gpt4",
+    "azure-gpt4-turbo",
+    "azure-gpt4-32k",
+  ] as const;
+
+  const azureInfo: {
+    [modelFamily in AzureOpenAIModelFamily]?: {
+      usage?: string;
+      activeKeys: number;
+      revokedKeys?: number;
+      proomptersInQueue?: number;
+      estimatedQueueTime?: string;
+    };
+  } = {};
+  for (const family of azureFamilies) {
+    const familyAllowed = config.allowedModelFamilies.includes(family);
+    const activeKeys = modelStats.get(`${family}__active`) || 0;
+
+    if (!familyAllowed || activeKeys === 0) continue;
+
+    azureInfo[family] = {
+      activeKeys,
+      revokedKeys: modelStats.get(`${family}__revoked`) || 0,
+    };
+
+    const queue = getQueueInformation(family);
+    azureInfo[family]!.proomptersInQueue = queue.proomptersInQueue;
+    azureInfo[family]!.estimatedQueueTime = queue.estimatedQueueTime;
+
+    const tokens = modelStats.get(`${family}__tokens`) || 0;
+    const cost = getTokenCostUsd(family, tokens);
+    azureInfo[family]!.usage = `${prettyTokens(tokens)} tokens${getCostString(
+      cost
+    )}`;
+  }
+
+  return azureInfo;
+}
+
 const customGreeting = fs.existsSync("greeting.md")
-  ? fs.readFileSync("greeting.md", "utf8")
+  ? `\n## Server Greeting\n${fs.readFileSync("greeting.md", "utf8")}`
-  : null;
+  : "";
 
 /**
  * If the server operator provides a `greeting.md` file, it will be included in
@@ -401,16 +497,20 @@ function buildInfoPageHeader(converter: showdown.Converter, title: string) {
   let infoBody = `<!-- Header for Showdown's parser, don't remove this line -->
 # ${title}`;
   if (config.promptLogging) {
-    infoBody += `\n## Prompt logging is enabled!
+    infoBody += `\n## Prompt Logging Enabled
-The server operator has enabled prompt logging. The prompts you send to this proxy and the AI responses you receive may be saved.
+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.`;
+  infoBody += `\n## Estimated Wait Times`;
 
   if (config.openaiKey) {
     // TODO: un-fuck this
@@ -432,6 +532,13 @@ Logs are anonymous and do not contain IP addresses or timestamps. [You can see t
     if (hasGpt432k && allowedGpt432k) {
       waits.push(`**GPT-4-32k:** ${gpt432kWait}`);
     }
+
+    const dalleWait = getQueueInformation("dall-e").estimatedQueueTime;
+    const hasDalle = keys.some((k) => k.modelFamilies.includes("dall-e"));
+    const allowedDalle = config.allowedModelFamilies.includes("dall-e");
+    if (hasDalle && allowedDalle) {
+      waits.push(`**DALL-E:** ${dalleWait}`);
+    }
   }
 
   if (config.anthropicKey) {
@@ -446,9 +553,10 @@ Logs are anonymous and do not contain IP addresses or timestamps. [You can see t
 
   infoBody += "\n\n" + waits.join(" / ");
 
-  if (customGreeting) {
+  infoBody += customGreeting;
-    infoBody += `\n## Server Greeting\n${customGreeting}`;
+
-  }
+  infoBody += buildRecentImageSection();
+
   return converter.makeHtml(infoBody);
 }
 
@@ -491,9 +599,44 @@ 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,
+  createOnProxyReqHandler,
-  stripHeaders, 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.tokenizerInfo) {
-  if (req.debug) {
+    body.proxy_tokenizer = req.tokenizerInfo;
-    body.proxy_tokenizer_debug_info = req.debug;
   }
 
   res.status(200).json(body);
@@ -129,23 +126,15 @@ function transformAnthropicResponse(
   };
 }
 
-const anthropicProxy = createQueueMiddleware(
+const anthropicProxy = createQueueMiddleware({
-  createProxyMiddleware({
+  proxyMiddleware: createProxyMiddleware({
     target: "https://api.anthropic.com",
     changeOrigin: true,
     selfHandleResponse: true,
     logger,
     on: {
       proxyReq: createOnProxyReqHandler({
-        pipeline: [
+        pipeline: [addKey, addAnthropicPreamble, finalizeBody],
-          applyQuotaLimits,
-          addKey,
-          addAnthropicPreamble,
-          languageFilter,
-          blockZoomerOrigins,
-          stripHeaders,
-          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.tokenizerInfo) {
-  if (req.debug) {
+    body.proxy_tokenizer = req.tokenizerInfo;
-    body.proxy_tokenizer_debug_info = req.debug;
   }
 
   // AWS does not confirm the model in the response, so we have to add it
@@ -119,34 +120,24 @@ function transformAwsResponse(
   };
 }
 
-const awsProxy = createQueueMiddleware(
+const awsProxy = createQueueMiddleware({
-  createProxyMiddleware({
+  beforeProxy: signAwsRequest,
+  proxyMiddleware: createProxyMiddleware({
     target: "bad-target-will-be-rewritten",
     router: ({ signedRequest }) => {
-      if (!signedRequest) {
+      if (!signedRequest) throw new Error("Must sign request before proxying");
-        throw new Error("AWS requests must go through signAwsRequest first");
-      }
       return `${signedRequest.protocol}//${signedRequest.hostname}`;
     },
     changeOrigin: true,
     selfHandleResponse: true,
     logger,
     on: {
-      proxyReq: createOnProxyReqHandler({
+      proxyReq: createOnProxyReqHandler({ pipeline: [finalizeSignedRequest] }),
-        pipeline: [
-          applyQuotaLimits,
-          // Credentials are added by signAwsRequest preprocessor
-          languageFilter,
-          blockZoomerOrigins,
-          stripHeaders,
-          finalizeAwsRequest,
-        ],
-      }),
       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;
+  // If client already specified an AWS Claude model ID, use it
-  // User's client is sending Anthropic-style model names, check for v1
+  if (model.includes("anthropic.claude")) {
-  if (model.match(/^claude-v?1/)) {
+    return;
-    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";
   }
-  // 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);
+    const { user, result } = authenticate(token, req.ip);
-    if (user) {
+
-      req.user = user;
+    switch (result) {
-      return next();
+      case "success":
-    } else {
+        req.user = user;
-      const maybeBannedUser = getUser(token);
+        return next();
-      if (maybeBannedUser?.disabledAt) {
+      case "limited":
         return res.status(403).json({
-          error: `Forbidden: ${
+          error: `Forbidden: no more IPs can authenticate with this token`,
-            maybeBannedUser.disabledReason || "Token disabled"
-          }`,
         });
-      }
+      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/middleware/common.ts

@@ -4,16 +4,15 @@ import { ZodError } from "zod";
 import { generateErrorMessage } from "zod-error";
 import { buildFakeSse } 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 isTextGenerationRequest(req: Request) {
-export function isCompletionRequest(req: Request) {
-  // 99% sure this function is not needed anymore
   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)
@@ -53,8 +59,8 @@ export function writeErrorResponse(
     res.write(`data: [DONE]\n\n`);
     res.end();
   } else {
-    if (req.debug && errorPayload.error) {
+    if (req.tokenizerInfo && typeof errorPayload.error === "object") {
-      errorPayload.error.proxy_tokenizer_debug_info = req.debug;
+      errorPayload.error.proxy_tokenizer = req.tokenizerInfo;
     }
     res.status(statusCode).json(errorPayload);
   }
@@ -90,7 +96,7 @@ function classifyError(err: Error): {
 } & Record<string, any> {
   const defaultError = {
     status: 500,
-    userMessage: `Reverse proxy encountered an unexpected error. (${err.message})`,
+    userMessage: `Reverse proxy error: ${err.message}`,
     type: "proxy_internal_error",
     stack: err.stack,
   };
@@ -103,7 +109,7 @@ function classifyError(err: Error): {
         code: { enabled: false },
         maxErrors: 3,
         transform: ({ issue, ...rest }) => {
-          return `At '${rest.pathComponent}', ${issue.message}`;
+          return `At '${rest.pathComponent}': ${issue.message}`;
         },
       });
       return { status: 400, userMessage, type: "proxy_validation_error" };
@@ -173,6 +179,8 @@ export function getCompletionFromBody(req: Request, body: Record<string, any>) {
       return body.completion.trim();
     case "google-palm":
       return body.candidates[0].output;
+    case "openai-image":
+      return body.data?.map((item: any) => item.url).join("\n");
     default:
       assertNever(format);
   }
@@ -184,6 +192,8 @@ export function getModelFromBody(req: Request, body: Record<string, any>) {
     case "openai":
     case "openai-text":
       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;

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 { addAzureKey } from "./preprocessors/add-azure-key";
-export { validateContextSize } from "./validate-context-size";
+export { applyQuotaLimits } from "./preprocessors/apply-quota-limits";
-export { countPromptTokens } from "./count-prompt-tokens";
+export { validateContextSize } from "./preprocessors/validate-context-size";
-export { setApiFormat } from "./set-api-format";
+export { countPromptTokens } from "./preprocessors/count-prompt-tokens";
-export { signAwsRequest } from "./sign-aws-request";
+export { languageFilter } from "./preprocessors/language-filter";
-export { transformOutboundPayload } from "./transform-outbound-payload";
+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)
+// http-proxy-middleware callbacks (runs on onProxyReq, cannot be async)
-export { addKey, addKeyForEmbeddingsRequest } from "./add-key";
+export { addKey, addKeyForEmbeddingsRequest } from "./onproxyreq/add-key";
-export { addAnthropicPreamble } from "./add-anthropic-preamble";
+export { addAnthropicPreamble } from "./onproxyreq/add-anthropic-preamble";
-export { blockZoomerOrigins } from "./block-zoomer-origins";
+export { blockZoomerOrigins } from "./onproxyreq/block-zoomer-origins";
-export { finalizeBody } from "./finalize-body";
+export { checkModelFamily } from "./onproxyreq/check-model-family";
-export { finalizeAwsRequest } from "./finalize-aws-request";
+export { finalizeBody } from "./onproxyreq/finalize-body";
-export { languageFilter } from "./language-filter";
+export { finalizeSignedRequest } from "./onproxyreq/finalize-signed-request";
-export { limitCompletions } from "./limit-completions";
+export { stripHeaders } from "./onproxyreq/strip-headers";
-export { stripHeaders } from "./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 +1,43 @@
+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.
+    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 { AnthropicKey, Key } from "../../../../shared/key-management";
-import { isCompletionRequest } from "../common";
+import { isTextGenerationRequest } from "../../common";
-import { ProxyRequestMiddleware } from ".";
+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 { Key, OpenAIKey, keyPool } from "../../../../shared/key-management";
-import { isCompletionRequest, isEmbeddingsRequest } from "../common";
+import { isEmbeddingsRequest } from "../../common";
-import { ProxyRequestMiddleware } from ".";
+import { HPMRequestCallback } from "../index";
-import { assertNever } from "../../../shared/utils";
+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 {
@@ -58,6 +42,9 @@ export const addKey: ProxyRequestMiddleware = (proxyReq, req) => {
         throw new Error(
           "OpenAI Chat as an API translation target is not supported"
         );
+      case "openai-image":
+        assignedKey = keyPool.get("dall-e-3");
+        break;
       default:
         assertNever(req.outboundApi);
     }
@@ -93,6 +80,10 @@ export const addKey: ProxyRequestMiddleware = (proxyReq, req) => {
         `?key=${assignedKey.key}`
       );
       break;
+    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."
@@ -106,7 +97,7 @@ 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 +111,7 @@ 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

@@ -1,5 +1,4 @@
-import { isCompletionRequest } from "../common";
+import { HPMRequestCallback } from "../index";
-import { ProxyRequestMiddleware } from ".";
 
 const DISALLOWED_ORIGIN_SUBSTRINGS = "janitorai.com,janitor.ai".split(",");
 
@@ -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) => {
+export const blockZoomerOrigins: HPMRequestCallback = (_proxyReq, req) => {
-  if (!isCompletionRequest(req)) {
-    return;
-  }
-
   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.

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

@@ -0,0 +1,13 @@
+import { HPMRequestCallback } from "../index";
+import { config } from "../../../../config";
+import { getModelFamilyForRequest } from "../../../../shared/models";
+
+/**
+ * Ensures the selected model family is enabled by the proxy configuration.
+ **/
+export const checkModelFamily: HPMRequestCallback = (proxyReq, req) => {
+  const family = getModelFamilyForRequest(req);
+  if (!config.allowedModelFamilies.includes(family)) {
+    throw new Error(`Model family ${family} is not permitted 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
+ * For AWS/Azure requests, the body is signed earlier in the request pipeline,
- * the proxy middleware. This function just assigns the path and headers to the
+ * before the proxy middleware. This function just assigns the path and headers
- * proxy request.
+ * 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/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 +1,7 @@
-import { RequestPreprocessor } from "./index";
+import { RequestPreprocessor } from "../index";
-import { countTokens, OpenAIPromptMessage } from "../../../shared/tokenization";
+import { countTokens } from "../../../../shared/tokenization";
-import { assertNever } from "../../../shared/utils";
+import { assertNever } from "../../../../shared/utils";
+import type { OpenAIChatMessage } from "./transform-outbound-payload";
 
 /**
  * Given a request with an already-transformed body, counts the number of
@@ -13,7 +14,7 @@ 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;
     }
@@ -35,14 +36,18 @@ export const countPromptTokens: RequestPreprocessor = async (req) => {
       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.tokenizerInfo = req.tokenizerInfo ?? {};
-  req.debug = { ...req.debug, ...result };
+  req.tokenizerInfo = { ...req.tokenizerInfo, ...result };
 };

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

@@ -0,0 +1,76 @@
+import { Request } from "express";
+import { config } from "../../../../config";
+import { assertNever } from "../../../../shared/utils";
+import { RequestPreprocessor } from "../index";
+import { UserInputError } from "../../../../shared/errors";
+import { 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":
+      return body.messages
+        .map((msg: OpenAIChatMessage) => {
+          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-palm":
+      return body.prompt.text;
+    default:
+      assertNever(service);
+  }
+}

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

@@ -1,6 +1,6 @@
 import { Request } from "express";
-import { APIFormat, LLMService } from "../../../shared/key-management";
+import { APIFormat, LLMService } from "../../../../shared/key-management";
-import { RequestPreprocessor } from ".";
+import { RequestPreprocessor } from "../index";
 
 export const setApiFormat = (api: {
   inApi: Request["inboundApi"];

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 { keyPool } from "../../../../shared/key-management";
-import { RequestPreprocessor } from ".";
+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

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

@@ -1,14 +1,15 @@
 import { Request } from "express";
 import { z } from "zod";
-import { config } from "../../../config";
+import { config } from "../../../../config";
-import { OpenAIPromptMessage } from "../../../shared/tokenization";
+import { isTextGenerationRequest, isImageGenerationRequest } from "../../common";
-import { isCompletionRequest } from "../common";
+import { RequestPreprocessor } from "../index";
-import { RequestPreprocessor } from ".";
+import { APIFormat } from "../../../../shared/key-management";
-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(),
@@ -29,12 +30,25 @@ export const AnthropicV1CompleteSchema = z.object({
 });
 
 // https://platform.openai.com/docs/api-reference/chat/create
-const OpenAIV1ChatCompletionSchema = z.object({
+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(),
   messages: z.array(
     z.object({
       role: z.enum(["system", "user", "assistant"]),
-      content: z.string(),
+      content: z.union([z.string(), OpenAIV1ChatContentArraySchema]),
       name: z.string().optional(),
     }),
     {
@@ -65,8 +79,13 @@ const OpenAIV1ChatCompletionSchema = z.object({
   presence_penalty: z.number().optional().default(0),
   logit_bias: z.any().optional(),
   user: z.string().optional(),
+  seed: z.number().int().optional(),
 });
 
+export type OpenAIChatMessage = z.infer<
+  typeof OpenAIV1ChatCompletionSchema
+>["messages"][0];
+
 const OpenAIV1TextCompletionSchema = z
   .object({
     model: z
@@ -87,6 +106,21 @@ const OpenAIV1TextCompletionSchema = z
   })
   .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().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().optional(),
+});
+
 // https://developers.generativeai.google/api/rest/generativelanguage/models/generateText
 const PalmV1GenerateTextSchema = z.object({
   model: z.string(),
@@ -109,6 +143,7 @@ const VALIDATORS: Record<APIFormat, z.ZodSchema<any>> = {
   anthropic: AnthropicV1CompleteSchema,
   openai: OpenAIV1ChatCompletionSchema,
   "openai-text": OpenAIV1TextCompletionSchema,
+  "openai-image": OpenAIV1ImagesGenerationSchema,
   "google-palm": PalmV1GenerateTextSchema,
 };
 
@@ -116,11 +151,10 @@ const VALIDATORS: Record<APIFormat, z.ZodSchema<any>> = {
 export const transformOutboundPayload: RequestPreprocessor = async (req) => {
   const sameService = req.inboundApi === req.outboundApi;
   const alreadyTransformed = req.retryCount > 0;
-  const notTransformable = !isCompletionRequest(req);
+  const notTransformable =
+    !isTextGenerationRequest(req) && !isImageGenerationRequest(req);
 
-  if (alreadyTransformed || notTransformable) {
+  if (alreadyTransformed || notTransformable) return;
-    return;
-  }
 
   if (sameService) {
     const result = VALIDATORS[req.inboundApi].safeParse(req.body);
@@ -150,6 +184,11 @@ export const transformOutboundPayload: RequestPreprocessor = async (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.`
   );
@@ -211,7 +250,7 @@ function openaiToOpenaiText(req: Request) {
   }
 
   const { messages, ...rest } = result.data;
-  const prompt = flattenOpenAiChatMessages(messages);
+  const prompt = flattenOpenAIChatMessages(messages);
 
   let stops = rest.stop
     ? Array.isArray(rest.stop)
@@ -225,6 +264,52 @@ function openaiToOpenaiText(req: Request) {
   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 openaiToPalm(req: Request): z.infer<typeof PalmV1GenerateTextSchema> {
   const { body } = req;
   const result = OpenAIV1ChatCompletionSchema.safeParse({
@@ -240,7 +325,7 @@ function openaiToPalm(req: Request): z.infer<typeof PalmV1GenerateTextSchema> {
   }
 
   const { messages, ...rest } = result.data;
-  const prompt = flattenOpenAiChatMessages(messages);
+  const prompt = flattenOpenAIChatMessages(messages);
 
   let stops = rest.stop
     ? Array.isArray(rest.stop)
@@ -272,7 +357,7 @@ function openaiToPalm(req: Request): z.infer<typeof PalmV1GenerateTextSchema> {
   };
 }
 
-export function openAIMessagesToClaudePrompt(messages: OpenAIPromptMessage[]) {
+export function openAIMessagesToClaudePrompt(messages: OpenAIChatMessage[]) {
   return (
     messages
       .map((m) => {
@@ -284,17 +369,17 @@ export function openAIMessagesToClaudePrompt(messages: OpenAIPromptMessage[]) {
         } 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}: ${m.name?.trim() ? `(as ${m.name}) ` : ""}${
+        return `\n\n${role}: ${name ? `(as ${name}) ` : ""}${content}`;
-          m.content
-        }`;
       })
       .join("") + "\n\nAssistant:"
   );
 }
 
-function flattenOpenAiChatMessages(messages: OpenAIPromptMessage[]) {
+function flattenOpenAIChatMessages(messages: OpenAIChatMessage[]) {
   // Temporary to allow experimenting with prompt strategies
   const PROMPT_VERSION: number = 1;
   switch (PROMPT_VERSION) {
@@ -311,7 +396,7 @@ function flattenOpenAiChatMessages(messages: OpenAIPromptMessage[]) {
             } else if (role === "user") {
               role = "User";
             }
-            return `\n\n${role}: ${m.content}`;
+            return `\n\n${role}: ${flattenOpenAIMessageContent(m.content)}`;
           })
           .join("") + "\n\nAssistant:"
       );
@@ -323,10 +408,23 @@ function flattenOpenAiChatMessages(messages: OpenAIPromptMessage[]) {
           if (role === "system") {
             role = "System: ";
           }
-          return `\n\n${role}${m.content}`;
+          return `\n\n${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

@@ -1,8 +1,8 @@
 import { Request } from "express";
 import { z } from "zod";
-import { config } from "../../../config";
+import { config } from "../../../../config";
-import { assertNever } from "../../../shared/utils";
+import { assertNever } from "../../../../shared/utils";
-import { RequestPreprocessor } from ".";
+import { RequestPreprocessor } from "../index";
 
 const CLAUDE_MAX_CONTEXT = config.maxContextTokensAnthropic;
 const OPENAI_MAX_CONTEXT = config.maxContextTokensOpenAI;
@@ -34,6 +34,8 @@ export const validateContextSize: RequestPreprocessor = async (req) => {
     case "google-palm":
       proxyMax = BISON_MAX_CONTEXT;
       break;
+    case "openai-image":
+      return;
     default:
       assertNever(req.outboundApi);
   }
@@ -42,6 +44,10 @@ 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)?$/)) {
+    modelMax = 131072;
   } else if (model.match(/gpt-3.5-turbo/)) {
     modelMax = 4096;
   } else if (model.match(/gpt-4-32k/)) {
@@ -52,18 +58,18 @@ export const validateContextSize: RequestPreprocessor = async (req) => {
     modelMax = 100000;
   } else if (model.match(/^claude-(?:instant-)?v1(?:\.\d)?$/)) {
     modelMax = 9000;
-  } else if (model.match(/^claude-2/)) {
+  } else if (model.match(/^claude-2\.0/)) {
     modelMax = 100000;
+  } else if (model.match(/^claude-2/)) {
+    modelMax = 200000;
   } else if (model.match(/^text-bison-\d{3}$/)) {
     modelMax = BISON_MAX_CONTEXT;
   } 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
+    req.log.warn({ model }, "Unknown model, using 200k token limit.");
-    // this ASAP every time a new model is released.
+    modelMax = 200000;
-    req.log.warn({ model }, "Unknown model, using 100k token limit.");
-    modelMax = 100000;
   }
 
   const finalMax = Math.min(proxyMax, modelMax);
@@ -81,10 +87,10 @@ export const validateContextSize: RequestPreprocessor = async (req) => {
     "Prompt size validated"
   );
 
-  req.debug.prompt_tokens = promptTokens;
+  req.tokenizerInfo.prompt_tokens = promptTokens;
-  req.debug.completion_tokens = outputTokens;
+  req.tokenizerInfo.completion_tokens = outputTokens;
-  req.debug.max_model_tokens = modelMax;
+  req.tokenizerInfo.max_model_tokens = modelMax;
-  req.debug.max_proxy_tokens = proxyMax;
+  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/response/handle-streamed-response.ts

@@ -1,14 +1,17 @@
+import express from "express";
 import { pipeline } from "stream";
 import { promisify } from "util";
 import {
   buildFakeSse,
   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 +36,7 @@ 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.`
@@ -59,7 +62,7 @@ export const handleStreamedResponse: RawResponseBodyHandler = async (
   const adapter = new SSEStreamAdapter({ contentType });
   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 +82,19 @@ export const handleStreamedResponse: RawResponseBodyHandler = async (
     res.end();
     return aggregator.getFinalResponse();
   } catch (err) {
-    const errorEvent = buildFakeSse("stream-error", err.message, req);
+    if (err instanceof RetryableError) {
-    res.write(`${errorEvent}data: [DONE]\n\n`);
+      keyPool.markRateLimited(req.key!);
-    res.end();
+      req.log.warn(
+        { key: req.key!.hash, retryCount: req.retryCount },
+        `Re-enqueueing request due to retryable error during streaming response.`
+      );
+      req.retryCount++;
+      enqueue(req);
+    } else {
+      const errorEvent = buildFakeSse("stream-error", err.message, req);
+      res.write(`${errorEvent}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
         );
@@ -188,7 +191,7 @@ 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);
+          req.log.warn({ contentEncoding, key: req.key?.hash }, errorMessage);
           writeErrorResponse(req, res, 500, {
             error: errorMessage,
             contentEncoding,
@@ -205,7 +208,7 @@ 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);
+        req.log.warn({ error: error.stack, key: req.key?.hash }, errorMessage);
         writeErrorResponse(req, res, 500, { error: errorMessage });
         return reject(errorMessage);
       }
@@ -251,7 +254,7 @@ const handleUpstreamErrors: ProxyResHandlerWithBody = async (
     // 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,
@@ -268,7 +271,7 @@ 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})`
   );
@@ -286,7 +289,18 @@ const handleUpstreamErrors: ProxyResHandlerWithBody = async (
     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 "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.
+          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":
@@ -329,8 +343,12 @@ const handleUpstreamErrors: ProxyResHandlerWithBody = async (
       case "aws":
         handleAwsRateLimitError(req, errorPayload);
         break;
+      case "azure":
+        handleAzureRateLimitError(req, errorPayload);
+        break;
       case "google-palm":
-        throw new Error("Rate limit handling not implemented for PaLM");
+        errorPayload.proxy_note = `Automatic rate limit retries are not supported for this service. Try again in a few seconds.`;
+        break;
       default:
         assertNever(service);
     }
@@ -357,6 +375,9 @@ const handleUpstreamErrors: ProxyResHandlerWithBody = async (
       case "aws":
         errorPayload.proxy_note = `The requested AWS resource might not exist, or the key might not have access to it.`;
         break;
+      case "azure":
+        errorPayload.proxy_note = `The assigned Azure deployment does not support the requested model.`;
+        break;
       default:
         assertNever(service);
     }
@@ -454,6 +475,7 @@ function handleOpenAIRateLimitError(
   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}`;
@@ -470,8 +492,14 @@ function handleOpenAIRateLimitError(
       break;
     case "requests":
     case "tokens":
-      // Per-minute request or token rate limit is exceeded, which we can retry
       keyPool.markRateLimited(req.key!);
+      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
       reenqueueRequest(req);
       throw new RetryableError("Rate-limited request re-enqueued.");
     default:
@@ -481,14 +509,39 @@ function handleOpenAIRateLimitError(
   return errorPayload;
 }
 
+function handleAzureRateLimitError(
+  req: Request,
+  errorPayload: ProxiedErrorPayload
+) {
+  const code = errorPayload.error?.code;
+  switch (code) {
+    case "429":
+      keyPool.markRateLimited(req.key!);
+      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;
+  }
+}
+
 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 +552,12 @@ 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 +572,8 @@ const countResponseTokens: ProxyResHandlerWithBody = async (
       { service, tokens, prevOutputTokens: req.outputTokens },
       `Counted tokens for completion`
     );
-    if (req.debug) {
+    if (req.tokenizerInfo) {
-      req.debug.completion_tokens = tokens;
+      req.tokenizerInfo.completion_tokens = tokens;
     }
 
     req.outputTokens = tokens.token_count;

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

@@ -4,10 +4,12 @@ import { logQueue } from "../../../shared/prompt-logging";
 import {
   getCompletionFromBody,
   getModelFromBody,
-  isCompletionRequest,
+  isImageGenerationRequest,
+  isTextGenerationRequest,
 } from "../common";
 import { ProxyResHandlerWithBody } from ".";
 import { assertNever } from "../../../shared/utils";
+import { OpenAIChatMessage } from "../request/preprocessors/transform-outbound-payload";
 
 /** If prompt logging is enabled, enqueues the prompt for logging. */
 export const logPrompt: ProxyResHandlerWithBody = async (
@@ -23,11 +25,11 @@ export const logPrompt: ProxyResHandlerWithBody = async (
     throw new Error("Expected body to be an object");
   }
 
-  if (!isCompletionRequest(req)) {
+  const loggable =
-    return;
+    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);
@@ -41,12 +43,18 @@ export const logPrompt: ProxyResHandlerWithBody = async (
   });
 };
 
-type OaiMessage = {
+type OaiImageResult = {
-  role: "user" | "assistant" | "system";
+  prompt: string;
-  content: 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[] | 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.
@@ -55,6 +63,14 @@ const getPromptForRequest = (req: Request): string | OaiMessage[] => {
       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":
@@ -64,9 +80,26 @@ const getPromptForRequest = (req: Request): string | OaiMessage[] => {
   }
 };
 
-const flattenMessages = (messages: string | OaiMessage[]): string => {
+const flattenMessages = (
-  if (typeof messages === "string") {
+  val: string | OpenAIChatMessage[] | OaiImageResult
-    return messages.trim();
+): 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

@@ -33,7 +33,8 @@ export class EventAggregator {
       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/sse-message-transformer.ts

@@ -28,6 +28,7 @@ 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 +43,7 @@ export class SSEMessageTransformer extends Transform {
       options.inputFormat,
       options.inputApiVersion
     );
+    this.inputFormat = options.inputFormat;
     this.fallbackId = options.requestId;
     this.fallbackModel = options.requestedModel;
     this.log.debug(
@@ -67,12 +69,24 @@ 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);
@@ -98,7 +112,8 @@ function getTransformer(
         ? anthropicV1ToOpenAI
         : anthropicV2ToOpenAI;
     case "google-palm":
-      throw new Error("Google PaLM does not support streaming responses");
+    case "openai-image":
+      throw new Error(`SSE transformation not supported for ${responseApi}`);
     default:
       assertNever(responseApi);
   }

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

@@ -2,12 +2,16 @@ import { Transform, TransformOptions } from "stream";
 // @ts-ignore
 import { Parser } from "lifion-aws-event-stream";
 import { logger } from "../../../../logger";
+import { RetryableError } from "../index";
 
 const log = logger.child({ module: "sse-stream-adapter" });
 
 type SSEStreamAdapterOptions = TransformOptions & { contentType?: string };
 type AwsEventStreamMessage = {
-  headers: { ":message-type": "event" | "exception" };
+  headers: {
+    ":message-type": "event" | "exception";
+    ":exception-type"?: string;
+  };
   payload: { message?: string /** base64 encoded */; bytes?: string };
 };
 
@@ -36,12 +40,25 @@ export class SSEStreamAdapter extends Transform {
   protected processAwsEvent(event: AwsEventStreamMessage): string | null {
     const { payload, headers } = event;
     if (headers[":message-type"] === "exception" || !payload.bytes) {
-      log.error(
+      const eventStr = JSON.stringify(event);
-        { event: JSON.stringify(event) },
+      // Under high load, AWS can rugpull us by returning a 200 and starting the
-        "Received bad streaming event from AWS"
+      // stream but then immediately sending a rate limit error as the first
-      );
+      // event. My guess is some race condition in their rate limiting check
-      const message = JSON.stringify(event);
+      // that occurs if two requests arrive at the same time when only one
-      return getFakeErrorCompletion("proxy AWS error", message);
+      // 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 unexpected AWS event stream message"
+        );
+        return getFakeErrorCompletion("proxy AWS error", eventStr);
+      }
     } else {
       const { bytes } = payload;
       // technically this is a transformation but we don't really distinguish

src/proxy/openai-image.ts

@@ -0,0 +1,142 @@
+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 {
+  mirrorGeneratedImage,
+  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,
+  RequestPreprocessor,
-  limitCompletions,
-  stripHeaders,
-  createOnProxyReqHandler,
 } 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() {
+export function generateModelList(models = KNOWN_OPENAI_MODELS) {
-  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",
-  ];
-
   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.tokenizerInfo) {
-  if (req.debug) {
+    body.proxy_tokenizer = req.tokenizerInfo;
-    body.proxy_tokenizer_debug_info = req.debug;
   }
 
   res.status(200).json(body);
@@ -163,29 +154,21 @@ function transformTurboInstructResponse(
   return transformed;
 }
 
-const openaiProxy = createQueueMiddleware(
+const openaiProxy = createQueueMiddleware({
-  createProxyMiddleware({
+  proxyMiddleware: createProxyMiddleware({
     target: "https://api.openai.com",
     changeOrigin: true,
     selfHandleResponse: true,
     logger,
     on: {
       proxyReq: createOnProxyReqHandler({
-        pipeline: [
+        pipeline: [addKey, finalizeBody],
-          applyQuotaLimits,
-          addKey,
-          languageFilter,
-          limitCompletions,
-          blockZoomerOrigins,
-          stripHeaders,
-          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

@@ -9,14 +9,10 @@ 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,
@@ -76,9 +72,8 @@ const palmResponseHandler: ProxyResHandlerWithBody = async (
     body = transformPalmResponse(body, req);
   }
 
-  // TODO: Remove once tokenization is stable
+  if (req.tokenizerInfo) {
-  if (req.debug) {
+    body.proxy_tokenizer = req.tokenizerInfo;
-    body.proxy_tokenizer_debug_info = req.debug;
   }
 
   // TODO: PaLM has no streaming capability which will pose a problem here if
@@ -143,29 +138,21 @@ function reassignPathForPalmModel(proxyReq: http.ClientRequest, req: Request) {
   );
 }
 
-const googlePalmProxy = createQueueMiddleware(
+const googlePalmProxy = createQueueMiddleware({
-  createProxyMiddleware({
+  proxyMiddleware: createProxyMiddleware({
     target: "https://generativelanguage.googleapis.com",
     changeOrigin: true,
     selfHandleResponse: true,
     logger,
     on: {
       proxyReq: createOnProxyReqHandler({
-        beforeRewrite: [reassignPathForPalmModel],
+        pipeline: [reassignPathForPalmModel, addKey, finalizeBody],
-        pipeline: [
-          applyQuotaLimits,
-          addKey,
-          languageFilter,
-          blockZoomerOrigins,
-          stripHeaders,
-          finalizeBody,
-        ],
       }),
       proxyRes: createOnProxyResHandler([palmResponseHandler]),
       error: handleProxyError,
     },
-  })
+  }),
-);
+});
 
 const palmRouter = Router();
 palmRouter.get("/v1/models", handleModelRequest);

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 +11,15 @@
  * 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 {
+import { getModelFamilyForRequest, MODEL_FAMILIES, ModelFamily } from "../shared/models";
-  getClaudeModelFamily,
-  getGooglePalmModelFamily,
-  getOpenAIModelFamily,
-  ModelFamily,
-} from "../shared/models";
 import { buildFakeSse, initializeSseStream } from "../shared/streaming";
-import { assertNever } from "../shared/utils";
 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 +28,50 @@ 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"
+);
 
 /**
- * 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) {
+  if (req.user) return req.user.token;
-    return req.user.token;
+  if (req.risuToken) return req.risuToken;
-  }
+  if (isFromSharedIp(req)) return "shared-ip";
-  if (req.risuToken) {
-    return req.risuToken;
-  }
   return req.ip;
 }
 
-const sameUserPredicate = (incoming: Request) => (queued: Request) => {
+const sharesIdentifierWith = (incoming: Request) => (queued: Request) =>
-  const queuedId = getIdentifier(queued);
+  getIdentifier(queued) === getIdentifier(incoming);
-  const incomingId = getIdentifier(incoming);
+
-  return queuedId === incomingId;
+const isFromSharedIp = (req: Request) => SHARED_IP_ADDRESSES.has(req.ip);
-};
 
 export function enqueue(req: Request) {
-  const enqueuedRequestCount = queue.filter(sameUserPredicate(req)).length;
+  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
+  // Requests from shared IP addresses such as Agnai.chat are exempt from IP-
-  // more spots in the queue. Can't make it unlimited because people will
+  // based rate limiting but can only occupy a certain number of slots in the
-  // intentionally abuse it.
+  // queue. Authenticated users always get a single spot in the queue.
-  // Authenticated users always get a single spot in the queue.
+  const isSharedIp = isFromSharedIp(req);
-  const isAgnai = AGNAI_DOT_CHAT_IP.includes(req.ip);
   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 +82,6 @@ export function enqueue(req: Request) {
     }
   }
 
-  queue.push(req);
-  req.queueOutTime = 0;
-
   // shitty hack to remove hpm's event listeners on retried requests
   removeProxyMiddlewareEventListeners(req);
 
@@ -98,31 +94,24 @@ export function enqueue(req: Request) {
     if (!res.headersSent) {
       initStreaming(req);
     }
-    req.heartbeatInterval = setInterval(() => {
+    registerHeartbeat(req);
-      if (process.env.NODE_ENV === "production") {
+  } else if (getProxyLoad() > LOAD_THRESHOLD) {
-        if (!req.query.badSseParser) req.res!.write(": queue heartbeat\n\n");
+    throw new Error(
-      } else {
+      "Due to heavy traffic on this proxy, you must enable streaming for your request."
-        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);
   }
 
-  // Register a handler to remove the request from the queue if the connection
+  queue.push(req);
-  // is aborted or closed before it is dequeued.
+  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) {
+    if (req.heartbeatInterval) clearInterval(req.heartbeatInterval);
-      clearInterval(req.heartbeatInterval);
+    if (req.monitorInterval) clearInterval(req.monitorInterval);
-    }
   };
   req.onAborted = removeFromQueue;
   req.res!.once("close", removeFromQueue);
@@ -134,33 +123,20 @@ export function enqueue(req: 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);
-  }
-}
-
 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 +156,8 @@ export function dequeue(partition: ModelFamily): Request | undefined {
     req.onAborted = undefined;
   }
 
-  if (req.heartbeatInterval) {
+  if (req.heartbeatInterval) clearInterval(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 +176,23 @@ 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.
+  // the others, because we only track rate limits for the key as a whole.
-
-  // 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");
 
   const reqs: (Request | undefined)[] = [];
-  if (gpt432kLockout === 0) {
+  MODEL_FAMILIES.forEach((modelFamily) => {
-    reqs.push(dequeue("gpt4-32k"));
+    const lockout = keyPool.getLockoutPeriod(modelFamily);
-  }
+    if (lockout === 0) {
-  if (gpt4Lockout === 0) {
+      reqs.push(dequeue(modelFamily));
-    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"));
-  }
 
   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 +225,93 @@ 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. */
+const WAIT_TIME_INTERVAL = 3000;
-export function getEstimatedWaitTime(partition: ModelFamily) {
+const ALPHA_HISTORICAL = 0.2;
-  const now = Date.now();
+const ALPHA_CURRENT = 0.3;
-  const recentWaits = waitTimes.filter(
+const historicalEmas: Map<ModelFamily, number> = new Map();
-    (wt) => wt.partition === partition && now - wt.end < 300 * 1000
+const currentEmas: Map<ModelFamily, number> = new Map();
-  );
+const estimates: Map<ModelFamily, number> = new Map();
-  if (recentWaits.length === 0) {
-    return 0;
-  }
 
-  return (
+export function getEstimatedWaitTime(partition: ModelFamily) {
-    recentWaits.reduce((sum, wt) => sum + wt.end - wt.start, 0) /
+  return estimates.get(partition) ?? 0;
-    recentWaits.length
-  );
 }
 
+/**
+ * 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;
@@ -307,9 +320,27 @@ export function getQueueLength(partition: ModelFamily | "all" = "all") {
   return modelQueue.length;
 }
 
-export function createQueueMiddleware(proxyMiddleware: Handler): Handler {
+export function createQueueMiddleware({
+  beforeProxy,
+  proxyMiddleware,
+}: {
+  beforeProxy?: RequestPreprocessor;
+  proxyMiddleware: Handler;
+}): Handler {
   return (req, res, next) => {
-    req.proceed = () => {
+    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);
     };
 
@@ -329,11 +360,12 @@ 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);
@@ -354,10 +386,12 @@ function initStreaming(req: Request) {
     // 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.
+    res.write(getHeartbeatPayload());
     return;
   }
 
   res.write(`: joining queue at position ${queue.length}\n\n`);
+  res.write(getHeartbeatPayload());
 }
 
 /**
@@ -413,3 +447,93 @@ function removeProxyMiddlewareEventListeners(req: Request) {
     req.removeListener("error", reqOnError as any);
   }
 }
+
+export function registerHeartbeat(req: Request) {
+  const res = req.res!;
+
+  const currentSize = getHeartbeatSize();
+  req.log.debug({
+    currentSize,
+    HEARTBEAT_INTERVAL,
+    PAYLOAD_SCALE_FACTOR,
+    MAX_HEARTBEAT_SIZE,
+  }, "Joining queue with heartbeat.");
+
+  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 = () => {
+/** Prunes exempted requests which are older than one minute. */
-  return lastAttempts.size;
+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
+  // Exempts Agnai.chat from IP-based rate limiting because its IPs are shared
-  // users. Dunno how to prevent this from being abused without some sort of
+  // by many users. Instead, the request queue will limit the number of such
-  // identifier sent from Agnaistic to identify specific users.
+  // requests that may wait in the queue at a time, and sorts them to the end to
-  if (AGNAI_DOT_CHAT_IP.includes(req.ip)) {
+  // let individual users go first.
-    req.log.info("Exempting Agnai request from rate limiting.");
+  if (SHARED_IP_ADDRESSES.has(req.ip)) {
-    next();
+    exemptedRequests.push(Date.now());
-    return;
+    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);
+  const { remaining, reset } = getStatus(rateLimitKey, type);
-  res.set("X-RateLimit-Limit", config.modelRateLimit.toString());
+  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 ${
+        message: `This model type is rate limited to ${limit} prompts per minute. Please try again in ${Math.ceil(
-          config.modelRateLimit
-        } prompts per minute. Please try again in ${Math.ceil(
           tryAgainInMs / 1000
         )} seconds.`,
       },

src/proxy/routes.ts

@@ -2,9 +2,11 @@ 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 { aws } from "./aws";
+import { azure } from "./azure";
 
 const proxyRouter = express.Router();
 proxyRouter.use((req, _res, next) => {
@@ -16,8 +18,8 @@ proxyRouter.use((req, _res, next) => {
   next();
 });
 proxyRouter.use(
-  express.json({ limit: "1536kb" }),
+  express.json({ limit: "10mb" }),
-  express.urlencoded({ extended: true, limit: "1536kb" })
+  express.urlencoded({ extended: true, limit: "10mb" })
 );
 proxyRouter.use(gatekeeper);
 proxyRouter.use(checkRisuToken);
@@ -27,9 +29,11 @@ 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("/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

@@ -1,11 +1,14 @@
-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";
@@ -25,9 +28,7 @@ app.use(
   pinoHttp({
     quietReqLogger: true,
     logger,
-    autoLogging: {
+    autoLogging: { ignore: ({ url }) => ["/health"].includes(url as string) },
-      ignore: ({ url }) => ["/health"].includes(url as string),
-    },
     redact: {
       paths: [
         "req.headers.cookie",
@@ -40,6 +41,11 @@ app.use(
       ],
       censor: "********",
     },
+    customProps: (req) => {
+      const user = (req as express.Request).user;
+      if (user) return { userToken: `...${user.token.slice(-5)}` };
+      return {};
+    },
   })
 );
 
@@ -55,6 +61,8 @@ 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);
@@ -96,13 +104,17 @@ 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 +125,12 @@ 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/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

@@ -26,46 +26,23 @@ 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) {
+  protected async testKeyOrFail(key: AnthropicKey) {
-    if (key.isDisabled) {
+    const [{ pozzed }] = await Promise.all([this.testLiveness(key)]);
-      this.log.warn({ key: key.hash }, "Skipping check for disabled key.");
+    const updates = { isPozzed: pozzed };
-      this.scheduleNextCheck();
+    this.updateKey(key.hash, updates);
-      return;
+    this.log.info(
-    }
+      { key: key.hash, models: key.modelFamilies },
-
+      "Checked key."
-    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 handleAxiosError(key: AnthropicKey, error: AxiosError) {
@@ -84,6 +61,7 @@ export class AnthropicKeyChecker extends KeyCheckerBase<AnthropicKey> {
               { key: key.hash, error: error.message },
               "Key is rate limited. Rechecking in 10 seconds."
             );
+            0;
             const next = Date.now() - (KEY_CHECK_PERIOD - 10 * 1000);
             this.updateKey(key.hash, { lastChecked: next });
             break;

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 = [
+export type AnthropicModel =
-  "claude-instant-v1",
+  | "claude-instant-v1"
-  "claude-instant-v1-100k",
+  | "claude-instant-v1-100k"
-  "claude-v1",
+  | "claude-v1"
-  "claude-v1-100k",
+  | "claude-v1-100k"
-  "claude-2",
+  | "claude-2"
-] as const;
+  | "claude-2.1";
-export type AnthropicModel = (typeof ANTHROPIC_SUPPORTED_MODELS)[number];
 
 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;
+    this.throttle(selectedKey.hash);
-    // 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;
     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) {
+  protected async testKeyOrFail(key: AwsBedrockKey) {
-    if (key.isDisabled) {
+    // Only check models on startup.  For now all models must be available to
-      this.log.warn({ key: key.hash }, "Skipping check for disabled key.");
+    // the proxy because we don't route requests to different keys.
-      this.scheduleNextCheck();
+    const modelChecks: Promise<unknown>[] = [];
-      return;
+    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...");
+    await Promise.all(modelChecks);
-    let isInitialCheck = !key.lastChecked;
+    await this.checkLoggingConfiguration(key);
-    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);
+    this.log.info(
-      await this.checkLoggingConfiguration(key);
+      {
-
+        key: key.hash,
-      this.log.info(
+        models: key.modelFamilies,
-        {
+        logged: key.awsLoggingStatus,
-          key: key.hash,
+      },
-          models: key.modelFamilies,
+      "Checked key."
-          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();
-    }
   }
 
   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 = [
+export type AwsBedrockModel =
-  "anthropic.claude-v1",
+  | "anthropic.claude-v1"
-  "anthropic.claude-v2",
+  | "anthropic.claude-v2"
-  "anthropic.claude-instant-v1",
+  | "anthropic.claude-instant-v1";
-] as const;
-export type AwsBedrockModel = (typeof AWS_BEDROCK_SUPPORTED_MODELS)[number];
 
 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;
+    this.throttle(selectedKey.hash);
-    // 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;
     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 +1,149 @@
+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] });
+  }
+
+  // provided api-key header isn't valid (401)
+  // {
+  //   "error": {
+  //     "code": "401",
+  //     "message": "Access denied due to invalid subscription key or wrong API endpoint. Make sure to provide a valid key for an active subscription and use a correct regional API endpoint for your resource."
+  //   }
+  // }
+
+  // api key correct but deployment id is wrong (404)
+  // {
+  //   "error": {
+  //     "code": "DeploymentNotFound",
+  //     "message": "The API deployment for this resource does not exist. If you created the deployment within the last 5 minutes, please wait a moment and try again."
+  //   }
+  // }
+
+  // resource name is wrong (node will throw ENOTFOUND)
+
+  // rate limited (429)
+  // TODO: try to reproduce this
+
+  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,
+          });
+        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 },
+    });
+
+    return getAzureOpenAIModelFamily(data.model);
+  }
+
+  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 +1,215 @@
+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";
+import { AwsKeyChecker } from "../aws/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/index.ts

@@ -1,22 +1,31 @@
-import { OPENAI_SUPPORTED_MODELS, OpenAIModel } from "./openai/provider";
+import { OpenAIModel } from "./openai/provider";
-import {
+import { AnthropicModel } from "./anthropic/provider";
-  ANTHROPIC_SUPPORTED_MODELS,
+import { GooglePalmModel } from "./palm/provider";
-  AnthropicModel,
+import { AwsBedrockModel } from "./aws/provider";
-} from "./anthropic/provider";
+import { AzureOpenAIModel } from "./azure/provider";
-import { GOOGLE_PALM_SUPPORTED_MODELS, GooglePalmModel } from "./palm/provider";
-import { AWS_BEDROCK_SUPPORTED_MODELS, AwsBedrockModel } from "./aws/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";
+export type APIFormat =
+  | "openai"
+  | "anthropic"
+  | "google-palm"
+  | "openai-text"
+  | "openai-image";
 /** 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 LLMService =
+  | "openai"
+  | "anthropic"
+  | "google-palm"
+  | "aws"
+  | "azure";
 export type Model =
   | OpenAIModel
   | AnthropicModel
   | GooglePalmModel
-  | AwsBedrockModel;
+  | AwsBedrockModel
+  | AzureOpenAIModel;
 
 export interface Key {
   /** The API key itself. Never log this, use `hash` instead. */
@@ -60,24 +69,14 @@ 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 { 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) {
+    if (!numEnabled) {
-      checkLog.warn("All keys are disabled. Key checker stopping.");
+      checkLog.warn("All keys are disabled. Stopping.");
       return;
     }
 
-    // Perform startup checks for any keys that haven't been checked yet.
+    checkLog.debug({ numEnabled, numUnchecked }, "Scheduling next check...");
-    const uncheckedKeys = enabledKeys.filter((key) => !key.lastChecked);
+
-    checkLog.debug({ unchecked: uncheckedKeys.length }, "# of unchecked keys");
+    if (numUnchecked > 0) {
-    if (uncheckedKeys.length > 0) {
+      const keycheckBatch = uncheckedKeys.slice(0, 12);
-      const keysToCheck = 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),
+          batch: keycheckBatch.map((k) => k.hash),
-          remaining: uncheckedKeys.length - keysToCheck.length,
+          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

@@ -9,6 +9,9 @@ import { AnthropicKeyProvider, AnthropicKeyUpdate } from "./anthropic/provider";
 import { OpenAIKeyProvider, OpenAIKeyUpdate } from "./openai/provider";
 import { GooglePalmKeyProvider } from "./palm/provider";
 import { AwsBedrockKeyProvider } from "./aws/provider";
+import { ModelFamily } from "../models";
+import { assertNever } from "../utils";
+import { AzureOpenAIKeyProvider } from "./azure/provider";
 
 type AllowedPartial = OpenAIKeyUpdate | AnthropicKeyUpdate;
 
@@ -23,6 +26,7 @@ export class KeyPool {
     this.keyProviders.push(new AnthropicKeyProvider());
     this.keyProviders.push(new GooglePalmKeyProvider());
     this.keyProviders.push(new AwsBedrockKeyProvider());
+    this.keyProviders.push(new AzureOpenAIKeyProvider());
   }
 
   public init() {
@@ -37,7 +41,7 @@ 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 +71,7 @@ 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 +81,9 @@ export class KeyPool {
     provider.incrementUsage(key.hash, model, tokens);
   }
 
-  public getLockoutPeriod(model: Model): number {
+  public getLockoutPeriod(family: ModelFamily): number {
-    const service = this.getService(model);
+    const service = this.getServiceForModelFamily(family);
-    return this.getKeyProvider(service).getLockoutPeriod(model);
+    return this.getKeyProvider(service).getLockoutPeriod(family);
   }
 
   public markRateLimited(key: Key): void {
@@ -104,8 +108,12 @@ export class KeyPool {
     provider.recheck();
   }
 
-  private getService(model: Model): LLMService {
+  private getServiceForModel(model: Model): LLMService {
-    if (model.startsWith("gpt") || model.startsWith("text-embedding-ada")) {
+    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-")) {
@@ -118,10 +126,36 @@ export class KeyPool {
       // 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}'`);
   }
 
+  private getServiceForModelFamily(modelFamily: ModelFamily): LLMService {
+    switch (modelFamily) {
+      case "gpt4":
+      case "gpt4-32k":
+      case "gpt4-turbo":
+      case "turbo":
+      case "dall-e":
+        return "openai";
+      case "claude":
+        return "anthropic";
+      case "bison":
+        return "google-palm";
+      case "aws-claude":
+        return "aws";
+      case "azure-turbo":
+      case "azure-gpt4":
+      case "azure-gpt4-32k":
+      case "azure-gpt4-turbo":
+        return "azure";
+      default:
+        assertNever(modelFamily);
+    }
+  }
+
   private getKeyProvider(service: LLMService): KeyProvider {
     return this.keyProviders.find((provider) => provider.service === service)!;
   }

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) {
+  protected async testKeyOrFail(key: OpenAIKey) {
-    if (key.isDisabled) {
+    // We only need to check for provisioned models on the initial check.
-      this.log.warn({ key: key.hash }, "Skipping check for disabled key.");
+    const isInitialCheck = !key.lastChecked;
-      this.scheduleNextCheck();
+    if (isInitialCheck) {
-      return;
+      const [provisionedModels, livenessTest] = await Promise.all([
-    }
+        this.getProvisionedModels(key),
-
+        this.testLiveness(key),
-    this.log.debug({ key: key.hash }, "Checking key...");
+        this.maybeCreateOrganizationClones(key),
-    let isInitialCheck = !key.lastChecked;
+      ]);
-    try {
+      const updates = {
-      // We only need to check for provisioned models on the initial check.
+        modelFamilies: provisionedModels,
-      if (isInitialCheck) {
+        isTrial: livenessTest.rateLimit <= 250,
-        const [provisionedModels, livenessTest] = await Promise.all([
+      };
-          this.getProvisionedModels(key),
+      this.updateKey(key.hash, updates);
-          this.testLiveness(key),
+    } else {
-          this.maybeCreateOrganizationClones(key),
+      // No updates needed as models and trial status generally don't change.
-        ]);
+      const [_livenessTest] = await Promise.all([this.testLiveness(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
       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[] = [];
+    const families = new Set<OpenAIModelFamily>();
-    if (models.some(({ id }) => id.startsWith("gpt-3.5-turbo"))) {
+    models.forEach(({ id }) => families.add(getOpenAIModelFamily(id, "turbo")));
-      families.push("turbo");
-    }
 
-    if (models.some(({ id }) => id.startsWith("gpt-4"))) {
+    // as of 2023-11-18, many keys no longer return the dalle3 model but still
-      families.push("gpt4");
+    // 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");
-    if (models.some(({ id }) => id.startsWith("gpt-4-32k"))) {
+    // }
-      families.push("gpt4-32k");
-    }
 
     // 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";
+  | "gpt-4-1106"
-export const OPENAI_SUPPORTED_MODELS: readonly OpenAIModel[] = [
+  | "text-embedding-ada-002"
-  "gpt-3.5-turbo",
+  | "dall-e-2"
-  "gpt-3.5-turbo-instruct",
+  | "dall-e-3"
-  "gpt-4",
-] as const;
 
 // 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 ${neededFamily} models.`);
+      throw new Error(`No keys available for model family '${neededFamily}'.`);
-    }
-
-    if (!config.allowedModelFamilies.includes(neededFamily)) {
-      throw new Error(
-        `Proxy operator has disabled access to ${neededFamily} models.`
-      );
     }
 
     // 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;
-
+    this.throttle(selectedKey.hash);
-    // 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;
     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 {
+  public getLockoutPeriod(family: OpenAIModelFamily): number {
-    const neededFamily = getOpenAIModelFamily(model);
     const activeKeys = this.keys.filter(
-      (key) => !key.isDisabled && key.modelFamilies.includes(neededFamily)
+      (key) => !key.isDisabled && key.modelFamilies.includes(family)
     );
 
-    if (activeKeys.length === 0) {
+    // Don't lock out if there are no keys available or the queue will stall.
-      // If there are no active keys for this model we can't fulfill requests.
+    // Just let it through so the add-key middleware can throw an error.
-      // We'll return 0 to let the request through and return an error,
+    if (activeKeys.length === 0) return 0;
-      // otherwise the request will be stuck in the queue forever.
-      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
+    if (typeof requestsReset === "string") {
-    // unclear why.
-
-    if (requestsReset && typeof requestsReset === "string") {
-      this.log.debug(
-        { key: key.hash, requestsReset },
-        `Updating rate limit requests reset time`
-      );
       key.rateLimitRequestsReset = getResetDurationMillis(requestsReset);
     }
 
-    if (tokensReset && typeof tokensReset === "string") {
+    if (typeof tokensReset === "string") {
-      this.log.debug(
-        { key: key.hash, tokensReset },
-        `Updating rate limit tokens reset time`
-      );
       key.rateLimitTokensReset = getResetDurationMillis(tokensReset);
     }
 
     if (!requestsReset && !tokensReset) {
-      this.log.warn(
+      this.log.warn({ key: key.hash }, `No ratelimit headers; skipping update`);
-        { key: key.hash },
-        `No rate limit headers in OpenAI response; skipping update`
-      );
       return;
     }
   }
@@ -383,35 +356,66 @@ export class OpenAIKeyProvider implements KeyProvider<OpenAIKey> {
     this.checker?.scheduleNextCheck();
   }
 
-  /** Writes key status to disk. */
+  /**
-  // public writeKeyStatus() {
+   * Called when a key is selected for a request, briefly disabling it to
-  //   const keys = this.keys.map((key) => ({
+   * avoid spamming the API with requests while we wait to learn whether this
-  //     key: key.key,
+   * key is already rate limited.
-  //     isGpt4: key.isGpt4,
+   */
-  //     usage: key.usage,
+  private throttle(hash: string) {
-  //     hardLimit: key.hardLimit,
+    const now = Date.now();
-  //     isDisabled: key.isDisabled,
+    const key = this.keys.find((k) => k.hash === hash)!;
-  //   }));
+
-  //   fs.writeFileSync(
+    const currentRateLimit =
-  //     path.join(__dirname, "..", "keys.json"),
+      Math.max(key.rateLimitRequestsReset, key.rateLimitTokensReset) +
-  //     JSON.stringify(keys, null, 2)
+      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.
+ * Converts reset string ("14m25s", "21.0032s", "14ms" or "21ms") to a number of
- * Result is clamped to 10s even though the API returns up to 60s, because the
+ * milliseconds.
- * 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.
  **/
 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 [, minutes, seconds, milliseconds] = match.map(Number);
-    const value = parseFloat(time);
+
-    const result = unit === "s" ? value * 1000 : value;
+    const minutesToMillis = (minutes || 0) * 60 * 1000;
-    return Math.min(result, 10000);
+    const secondsToMillis = (seconds || 0) * 1000;
+    const millisecondsValue = milliseconds || 0;
+
+    return minutesToMillis + secondsToMillis + millisecondsValue;
   }
+
   return 0;
 }

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

@@ -5,11 +5,7 @@ import { logger } from "../../../logger";
 import type { GooglePalmModelFamily } from "../../models";
 
 // https://developers.generativeai.google.com/models/language
-export const GOOGLE_PALM_SUPPORTED_MODELS = [
+export type GooglePalmModel = "text-bison-001";
-  "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];
 
 export type GooglePalmKeyUpdate = Omit<
   Partial<GooglePalmKey>,
@@ -122,11 +118,7 @@ export class GooglePalmKeyProvider implements KeyProvider<GooglePalmKey> {
 
     const selectedKey = keysByPriority[0];
     selectedKey.lastUsed = now;
-    selectedKey.rateLimitedAt = now;
+    this.throttle(selectedKey.hash);
-    // 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;
     return { ...selectedKey };
   }
 
@@ -153,7 +145,7 @@ export class GooglePalmKeyProvider implements KeyProvider<GooglePalmKey> {
     key.bisonTokens += 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 +178,20 @@ 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/models.ts

@@ -1,14 +1,28 @@
-import { logger } from "../logger";
+// Don't import anything here, this is imported by config.ts
 
-export type OpenAIModelFamily = "turbo" | "gpt4" | "gpt4-32k";
+import pino from "pino";
+import type { Request } from "express";
+import { assertNever } from "./utils";
+
+export type OpenAIModelFamily =
+  | "turbo"
+  | "gpt4"
+  | "gpt4-32k"
+  | "gpt4-turbo"
+  | "dall-e";
 export type AnthropicModelFamily = "claude";
 export type GooglePalmModelFamily = "bison";
 export type AwsBedrockModelFamily = "aws-claude";
+export type AzureOpenAIModelFamily = `azure-${Exclude<
+  OpenAIModelFamily,
+  "dall-e"
+>}`;
 export type ModelFamily =
   | OpenAIModelFamily
   | AnthropicModelFamily
   | GooglePalmModelFamily
-  | AwsBedrockModelFamily;
+  | AwsBedrockModelFamily
+  | AzureOpenAIModelFamily;
 
 export const MODEL_FAMILIES = (<A extends readonly ModelFamily[]>(
   arr: A & ([ModelFamily] extends [A[number]] ? unknown : never)
@@ -16,37 +30,49 @@ export const MODEL_FAMILIES = (<A extends readonly ModelFamily[]>(
   "turbo",
   "gpt4",
   "gpt4-32k",
+  "gpt4-turbo",
+  "dall-e",
   "claude",
   "bison",
   "aws-claude",
+  "azure-turbo",
+  "azure-gpt4",
+  "azure-gpt4-32k",
+  "azure-gpt4-turbo",
 ] 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 {
+const modelLogger = 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;
+  return defaultFamily;
-  logger.warn({ model, stack }, "Unmapped model family");
-  return "gpt4";
 }
 
-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;
+  modelLogger.warn({ model }, "Could not determine Google PaLM model family");
-  logger.warn({ model, stack }, "Unmapped PaLM model family");
   return "bison";
 }
 
@@ -54,6 +80,24 @@ 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 +105,38 @@ 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-palm":
+        modelFamily = getGooglePalmModelFamily(model);
+        break;
+      default:
+        assertNever(req.outboundApi);
+    }
+  }
+
+  return (req.modelFamily = modelFamily);
+}

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.promptRaw.slice(-50000),
-      entry.promptFlattened.slice(0, 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

@@ -5,6 +5,9 @@ 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;
@@ -12,7 +15,10 @@ 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":
@@ -31,6 +37,6 @@ 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";
   }
 }

src/shared/streaming.ts

@@ -39,11 +39,7 @@ 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(
+export function buildFakeSse(type: string, string: string, req: Request) {
-  type: string,
-  string: string,
-  req: Request
-) {
   let fakeEvent;
   const content = `\`\`\`\n[${type}: ${string}]\n\`\`\`\n`;
 
@@ -54,7 +50,7 @@ export function buildFakeSse(
         object: "chat.completion.chunk",
         created: Date.now(),
         model: req.body?.model,
-        choices: [{ delta: { content }, index: 0, finish_reason: type }]
+        choices: [{ delta: { content }, index: 0, finish_reason: type }],
       };
       break;
     case "openai-text":
@@ -63,9 +59,9 @@ export function buildFakeSse(
         object: "text_completion",
         created: Date.now(),
         choices: [
-          { text: content, index: 0, logprobs: null, finish_reason: type }
+          { text: content, index: 0, logprobs: null, finish_reason: type },
         ],
-        model: req.body?.model
+        model: req.body?.model,
       };
       break;
     case "anthropic":
@@ -75,20 +71,21 @@ export function buildFakeSse(
         truncated: false, // I've never seen this be true
         stop: null,
         model: req.body?.model,
-        log_id: "proxy-req-" + req.id
+        log_id: "proxy-req-" + req.id,
       };
       break;
     case "google-palm":
-      throw new Error("PaLM not supported as an inbound API format");
+    case "openai-image":
+      throw new Error(`SSE not supported for ${req.inboundApi} requests`);
     default:
       assertNever(req.inboundApi);
   }
 
   if (req.inboundApi === "anthropic") {
-    return [
+    return (
-      "event: completion",
+      ["event: completion", `data: ${JSON.stringify(fakeEvent)}`].join("\n") +
-      `data: ${JSON.stringify(fakeEvent)}`,
+      "\n\n"
-    ].join("\n") + "\n\n";
+    );
   }
 
   return `data: ${JSON.stringify(fakeEvent)}\n\n`;

src/shared/tokenization/index.ts

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

src/shared/tokenization/openai.ts

@@ -1,5 +1,11 @@
 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 { OpenAIChatMessage } from "../../proxy/middleware/request/preprocessors/transform-outbound-payload";
+
+const log = logger.child({ module: "tokenizer", service: "openai" });
+const GPT4_VISION_SYSTEM_PROMPT_SIZE = 170;
 
 let encoder: Tiktoken;
 
@@ -15,8 +21,8 @@ export function init() {
 // Tested against:
 // https://github.com/openai/openai-cookbook/blob/main/examples/How_to_count_tokens_with_tiktoken.ipynb
 
-export function getTokenCount(
+export async function getTokenCount(
-  prompt: string | OpenAIPromptMessage[],
+  prompt: string | OpenAIChatMessage[],
   model: string
 ) {
   if (typeof prompt === "string") {
@@ -24,31 +30,49 @@ export function getTokenCount(
   }
 
   const gpt4 = model.startsWith("gpt-4");
+  const vision = model.includes("vision");
 
   const tokensPerMessage = gpt4 ? 3 : 4;
   const tokensPerName = gpt4 ? 1 : -1; // turbo omits role 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];
+        let textContent: string = "";
-        if (!value || typeof value !== "string") continue;
+        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) {
+        if (textContent.length > 500000 || numTokens > 200000) {
-          numTokens = 100000;
+          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 +83,78 @@ 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 +169,62 @@ function getTextTokenCount(prompt: string) {
   };
 }
 
-export type OpenAIPromptMessage = {
+// Model	Resolution	Price
-  name?: string;
+// DALL·E 3	1024×1024	$0.040 / image
-  content: string;
+// 1024×1792, 1792×1024	$0.080 / image
-  role: string;
+// 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),
+  };
+}

src/shared/tokenization/tokenizer.ts

@@ -1,4 +1,5 @@
 import { Request } from "express";
+import type { OpenAIChatMessage } from "../../proxy/middleware/request/preprocessors/transform-outbound-payload";
 import { assertNever } from "../utils";
 import {
   init as initClaude,
@@ -7,7 +8,7 @@ import {
 import {
   init as initOpenAi,
   getTokenCount as getOpenAITokenCount,
-  OpenAIPromptMessage,
+  getOpenAIImageCost,
 } from "./openai";
 import { APIFormat } from "../key-management";
 
@@ -19,13 +20,14 @@ export async function init() {
 /** 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";
     }
   | { prompt?: never; completion: string; service: APIFormat }
+  | { prompt?: never; completion?: never; service: "openai-image" }
 );
 
 type TokenCountResult = {
@@ -50,14 +52,24 @@ 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 "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-palm":
       // TODO: Can't find a tokenization library for PaLM. There is an API
       // endpoint for it but it adds significant latency to the request.
       return {
-        ...getOpenAITokenCount(prompt ?? completion, req.body.model),
+        ...(await getOpenAITokenCount(prompt ?? completion, req.body.model)),
         tokenization_duration_ms: getElapsedMs(time),
       };
     default:

src/shared/users/schema.ts

@@ -6,6 +6,8 @@ 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),
   "aws-claude": z.number().optional().default(0),

src/shared/users/user-store.ts

@@ -11,9 +11,18 @@ 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,
+  getGooglePalmModelFamily,
+  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 +30,15 @@ const INITIAL_TOKENS: Required<UserTokenCounts> = {
   turbo: 0,
   gpt4: 0,
   "gpt4-32k": 0,
+  "gpt4-turbo": 0,
+  "dall-e": 0,
   claude: 0,
   bison: 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 +180,12 @@ 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 +196,52 @@ 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) return { result: "not_found" };
-  if (!user.ip.includes(ip)) user.ip.push(ip);
+  if (user.disabledAt) return { result: "disabled" };
 
-  const configIpLimit = user.maxIps ?? config.maxIpsPerUser;
+  const newIp = !user.ip.includes(ip);
-  const ipLimit =
+
-    user.type === "special" || !configIpLimit ? Infinity : configIpLimit;
+  const userLimit = user.maxIps ?? config.maxIpsPerUser;
-  if (user.ip.length > ipLimit) {
+  const enforcedLimit =
-    disableUser(token, "IP address limit exceeded.");
+    user.type === "special" || !userLimit ? Infinity : userLimit;
-    return;
+
+  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(
+export function hasAvailableQuota({
-  token: string,
+  userToken,
-  model: string,
+  model,
-  requested: number
+  api,
-) {
+  requested,
-  const user = users.get(token);
+}: {
+  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 +383,25 @@ async function flushUsers() {
   );
 }
 
-// TODO: use key-management/models.ts for family mapping
+function getModelFamilyForQuotaUsage(
-function getModelFamilyForQuotaUsage(model: string): ModelFamily {
+  model: string,
-  if (model.includes("32k")) {
+  api: APIFormat
-    return "gpt4-32k";
+): 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-palm":
+      return getGooglePalmModelFamily(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() {

src/shared/with-session.ts

@@ -1,7 +1,7 @@
 import cookieParser from "cookie-parser";
 import expressSession from "express-session";
 import MemoryStore from "memorystore";
-import { COOKIE_SECRET } from "../config";
+import { config, COOKIE_SECRET } from "../config";
 
 const ONE_WEEK = 1000 * 60 * 60 * 24 * 7;
 
@@ -12,7 +12,12 @@ const sessionMiddleware = expressSession({
   resave: false,
   saveUninitialized: false,
   store: new (MemoryStore(expressSession))({ checkPeriod: ONE_WEEK }),
-  cookie: { sameSite: "strict", maxAge: ONE_WEEK, signed: true },
+  cookie: {
+    sameSite: "strict",
+    maxAge: ONE_WEEK,
+    signed: true,
+    secure: !config.useInsecureCookies,
+  },
 });
 
 const withSession = [cookieParserMiddleware, sessionMiddleware];

src/types/custom.d.ts

@@ -2,6 +2,7 @@ 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 { ModelFamily } from "../shared/models";
 
 declare global {
   namespace Express {
@@ -22,11 +23,12 @@ declare global {
       onAborted?: () => void;
       proceed: () => void;
       heartbeatInterval?: NodeJS.Timeout;
+      monitorInterval?: NodeJS.Timeout;
       promptTokens?: number;
       outputTokens?: number;
-      // TODO: remove later
+      tokenizerInfo: Record<string, any>;
-      debug: Record<string, any>;
       signedRequest: HttpRequest;
+      modelFamily?: ModelFamily;
     }
   }
 }

src/user/web/self-service.ts

@@ -31,6 +31,10 @@ router.get("/lookup", (_req, res) => {
 router.post("/lookup", (req, res) => {
   const token = req.body.token;
   const user = userStore.getUser(token);
+  req.log.info(
+    { token: truncateToken(token), success: !!user },
+    "User self-service lookup"
+  );
   if (!user) {
     req.session.flash = { type: "error", message: "Invalid user token." };
     return res.redirect("/user/lookup");
@@ -46,6 +50,10 @@ router.post("/edit-nickname", (req, res) => {
     throw new ForbiddenError("Not logged in.");
   } else if (!config.allowNicknameChanges || existing.disabledAt) {
     throw new ForbiddenError("Nickname changes are not allowed.");
+  } else if (!config.maxIpsAutoBan && !existing.ip.includes(req.ip)) {
+    throw new ForbiddenError(
+      "Nickname changes are only allowed from registered IPs."
+    );
   }
 
   const schema = UserPartialSchema.pick({ nickname: true })
@@ -63,4 +71,9 @@ router.post("/edit-nickname", (req, res) => {
   return res.redirect("/user/lookup");
 });
 
+function truncateToken(token: string) {
+  const sliceLength = Math.max(Math.floor(token.length / 8), 1);
+  return `${token.slice(0, sliceLength)}...${token.slice(-sliceLength)}`;
+}
+
 export { router as selfServiceRouter };