47 Commits

Author SHA1 Message Date
nai-degen 94d4efe9bb properly enforce allowedModelFamilies; refactor HPM proxyReq handlers 2023-12-05 22:07:56 -06:00
random-username-423 12276a1f59 Fix AWS Claude Model Reassigning (khanon/oai-reverse-proxy!55) 2023-12-06 03:21:27 +00:00
nai-degen fdd824f0e4 adds azure rate limit auto-retry 2023-12-04 01:24:33 -06:00
khanon fbdea30264 Azure OpenAI suport (khanon/oai-reverse-proxy!48) 2023-12-04 04:21:18 +00:00
nai-degen cd1b9d0e0c don't print google api key to container logs on error 2023-12-01 11:23:56 -06:00
nai-degen 9e61d9029f adds claude-2.1 (untested) 2023-11-21 11:32:43 -06:00
nai-degen f95e24afbb fixes incorrect max model size for gpt4-v 2023-11-19 02:23:41 -06:00
khanon f29049f993 Support for GPT-4-Vision (khanon/oai-reverse-proxy!54) 2023-11-19 05:06:21 +00:00
nai-degen 7f2f324e26 fixes render dockerfile and dalle3 model detection 2023-11-18 12:27:14 -06:00
nai-degen dc61291933 adds temporary keychecker var to treat dall-e-2 the same as dall-e-3 2023-11-17 20:24:36 -06:00
nai-degen 6c02e9b265 don't enqueue requests which fail stream check 2023-11-17 14:36:47 -06:00
nai-degen e018672968 re-adds keychecker info to STATIC_INFO_PAGE 2023-11-16 02:16:24 -06:00
nai-degen bfd7e23124 encodes queue payload 2023-11-16 01:19:01 -06:00
khanon 6aa6bebf08 Scale SSE heartbeat size with traffic (khanon/oai-reverse-proxy!53) 2023-11-16 05:45:35 +00:00
nai-degen 6acdf35914 removes length from stalled request error message 2023-11-15 17:18:51 -06:00
nai-degen 3de79873e9 adds STATIC_SERVICE_INFO config 2023-11-15 17:12:07 -06:00
nai-degen 3aca9e90f0 fixes rate limiter always using IMAGE_MODEL_RATE_LIMIT 2023-11-15 13:07:58 -06:00
nai-degen 5fabe1d1f8 uses exponential moving average for wait time calculation 2023-11-14 01:36:11 -06:00
nai-degen 4a68c14477 further increases OpenAI rate limit backoff 2023-11-14 01:28:28 -06:00
khanon 20c064394a OpenAI DALL-E Image Generation (khanon/oai-reverse-proxy!52) 2023-11-14 05:41:19 +00:00
nai-degen 3ea23760c3 adjusts prompt logging to truncate huge prompts from the end 2023-11-11 20:14:32 -06:00
nai-degen 5db07404f2 fixes infopage crash when check_keys is disabled 2023-11-10 22:41:57 -06:00
nai-degen c453a5f2ad logs usertoken lookup attempts 2023-11-10 22:41:36 -06:00
nai-degen c7a095d345 removes debug log 2023-11-09 16:25:57 -06:00
nai-degen e9110611fa adds REJECT_PHRASES configuration setting 2023-11-09 16:24:49 -06:00
nai-degen 79e1fe09e4 fixes multiple enumeration on infopage 2023-11-08 12:02:23 -06:00
dllt98 08b2196bfb Update .env.example to include MAX_CONTEXT_TOKENS_OPENAI (khanon/oai-reverse-proxy!50) 2023-11-08 02:50:19 +00:00
nai-degen 350d6542cf fixes stats for non-openai models 2023-11-06 22:41:48 -06:00
nai-degen c9c24f86bb improvements to infopage key categorization 2023-11-06 22:13:34 -06:00
nai-degen b6f8f15a1f tries to prevent per-day rate limited keys from bricking the queue 2023-11-06 21:16:36 -06:00
nai-degen 5467136c1a adds gpt4-turbo to userschema; updates docs 2023-11-06 16:35:35 -06:00
nai-degen 0d5dfeccf8 adds gpt4-turbo model family and support for gpt-4-1106-preview model 2023-11-06 15:29:43 -06:00
nai-degen b615ffa433 fixes issue with local development cookies 2023-11-06 10:28:27 -06:00
nai-degen a27163a629 adds option to not disable keys when reaching IP limit 2023-11-06 10:15:57 -06:00
nai-degen 5a8fb3aff6 adds USE_INSECURE_COOKIES for hosts without SSL support 2023-11-03 15:25:06 -05:00
nai-degen 51dd0c71ba removes unused import in openai proxy 2023-10-24 13:17:46 -05:00
nai-degen 89e1ed46d5 re-signs AWS requests on every attempt to fix fucked up queueing 2023-10-24 13:10:50 -05:00
nai-degen 26dc79c8f1 fixes broken AWS rate limit backoff 2023-10-24 09:19:46 -05:00
nai-degen 89e9b67f3f fixes AWS mid-stream rate limits not actually marking key as rate-limited 2023-10-23 22:47:29 -05:00
nai-degen 52ec2ec265 fixes blank AWS responses due to reqs sometimes using wrong handler 2023-10-23 22:23:06 -05:00
nai-degen 8bd2f749c1 reduces logging severity of prompt validation errors 2023-10-23 20:30:27 -05:00
khanon ff27ca3780 Update info-page.ts 2023-10-20 00:33:57 +00:00
nai-degen 41a463d2c8 possibly fix issue with AWS keychecker due to amazon API change 2023-10-16 12:17:02 -05:00
nai-degen 3f7e50f87e follow-up 'fixes empty AWS streaming responses when under heavy load' 2023-10-15 00:06:38 -05:00
nai-degen f6cfc6e882 fixes empty AWS streaming responses when under heavy load 2023-10-15 00:05:36 -05:00
nai-degen af4d8dae40 changes default AMZ_HOST to bedrock-runtime.region.amazonaws.com 2023-10-12 15:39:06 -05:00
nai-degen 725fd6e6f1 deprioritizes queued Agnai.chat requests and limits concurrency to five across all shared IPs 2023-10-09 12:36:54 -05:00
102 changed files with 4290 additions and 1847 deletions
-4
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@@ -1,4 +0,0 @@
root = true
[*]
end_of_line = crlf
+33 -6
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@@ -11,11 +11,17 @@
# The title displayed on the info page.
# SERVER_TITLE=Coom Tunnel
# Model requests allowed per minute per user.
# MODEL_RATE_LIMIT=4
# Text model requests allowed per minute per user.
# TEXT_MODEL_RATE_LIMIT=4
# Image model requests allowed per minute per user.
# IMAGE_MODEL_RATE_LIMIT=2
# Max number of context tokens a user can request at once.
# Increase this if your proxy allow GPT 32k or 128k context
# MAX_CONTEXT_TOKENS_OPENAI=16384
# Max number of output tokens a user can request at once.
# MAX_OUTPUT_TOKENS_OPENAI=300
# MAX_OUTPUT_TOKENS_OPENAI=400
# MAX_OUTPUT_TOKENS_ANTHROPIC=400
# Whether to show the estimated cost of consumed tokens on the info page.
@@ -27,7 +33,11 @@
# CHECK_KEYS=true
# Which model types users are allowed to access.
# ALLOWED_MODEL_FAMILIES=claude,turbo,gpt4,gpt4-32k
# The following model families are recognized:
# turbo | gpt4 | gpt4-32k | gpt4-turbo | dall-e | claude | 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.
# REJECT_DISALLOWED=false
# Comma-separated list of phrases that will be rejected. Only whole words are matched.
# Surround phrases with quotes if they contain commas.
# Avoid short or common phrases as this tests the entire prompt.
# REJECT_PHRASES="phrase one,phrase two,"phrase three, which has a comma",phrase four"
# Message to show when requests are rejected.
# REJECT_MESSAGE="This content violates /aicg/'s acceptable use policy."
@@ -48,6 +60,9 @@
# The port to listen on.
# PORT=7860
# Whether cookies should be set without the Secure flag, for hosts that don't support SSL.
# USE_INSECURE_COOKIES=false
# Detail level of logging. (trace | debug | info | warn | error)
# LOG_LEVEL=info
@@ -63,15 +78,25 @@
# Maximum number of unique IPs a user can connect from. (0 for unlimited)
# MAX_IPS_PER_USER=0
# Whether user_tokens should be automatically disabled when reaching the IP limit.
# MAX_IPS_AUTO_BAN=true
# With user_token gatekeeper, whether to allow users to change their nickname.
# ALLOW_NICKNAME_CHANGES=true
# Default token quotas for each model family. (0 for unlimited)
# DALL-E "tokens" are counted at a rate of 100000 tokens per US$1.00 generated,
# which is similar to the cost of GPT-4 Turbo.
# DALL-E 3 costs around US$0.10 per image (10000 tokens).
# See `docs/dall-e-configuration.md` for more information.
# TOKEN_QUOTA_TURBO=0
# TOKEN_QUOTA_GPT4=0
# TOKEN_QUOTA_GPT4_32K=0
# TOKEN_QUOTA_GPT4_TURBO=0
# TOKEN_QUOTA_DALL_E=0
# TOKEN_QUOTA_CLAUDE=0
# TOKEN_QUOTA_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
+1
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@@ -5,3 +5,4 @@
build
greeting.md
node_modules
http-client.private.env.json
+2
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@@ -0,0 +1,2 @@
*
!.gitkeep
View File
+2
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@@ -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
+4 -3
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@@ -45,10 +45,11 @@ You can also request Claude Instant, but support for this isn't fully implemente
### Supported model IDs
Users can send these model IDs to the proxy to invoke the corresponding models.
- **Claude**
- `anthropic.claude-v1` (~18k context)
- `anthropic.claude-v2` (~100k context)
- `anthropic.claude-v1` (~18k context, claude 1.3)
- `anthropic.claude-v2` (~100k context, claude 2.0)
- `anthropic.claude-v2:1` (~200k context, claude 2.1)
- **Claude Instant**
- `anthropic.claude-instant-v1`
- `anthropic.claude-instant-v1` (~100k context, claude instant 1.2)
## Note regarding logging
+30
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@@ -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.
+71
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@@ -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`.
+2
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@@ -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
+9
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@@ -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"
}
}
+397 -9
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@@ -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",
"resolved": "https://registry.npmjs.org/axios/-/axios-1.3.5.tgz",
"integrity": "sha512-glL/PvG/E+xCWwV8S6nCHcrfg1exGx7vxyUIivIA1iL7BIh6bePylCfVHwp6k13ao7SATxB6imau2kqY+I67kw==",
"version": "1.6.1",
"resolved": "https://registry.npmjs.org/axios/-/axios-1.6.1.tgz",
"integrity": "sha512-vfBmhDpKafglh0EldBEbVuoe7DyAavGSLWhuSm5ZSEKQnHhBf0xAAwybbNH1IkrJNGnS/VG4I5yxig1pCEXE4g==",
"dependencies": {
"follow-redirects": "^1.15.0",
"form-data": "^4.0.0",
"proxy-from-env": "^1.1.0"
}
},
"node_modules/b4a": {
"version": "1.6.4",
"resolved": "https://registry.npmjs.org/b4a/-/b4a-1.6.4.tgz",
"integrity": "sha512-fpWrvyVHEKyeEvbKZTVOeZF3VSKKWtJxFIxX/jaVPf+cLbGUSitjb49pHLqPV2BUNNZ0LcoeEGfE/YCpyDYHIw=="
},
"node_modules/balanced-match": {
"version": "1.0.2",
"resolved": "https://registry.npmjs.org/balanced-match/-/balanced-match-1.0.2.tgz",
@@ -1423,6 +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 @@
"resolved": "https://registry.npmjs.org/color-name/-/color-name-1.1.4.tgz",
"integrity": "sha512-dOy+3AuW3a2wNbZHIuMZpTcgjGuLU/uBL/ubcZF9OXbDo8ff4O8yVp5Bf0efS8uEoYo5q4Fx7dY9OgQGXgAsQA=="
},
"node_modules/color-string": {
"version": "1.9.1",
"resolved": "https://registry.npmjs.org/color-string/-/color-string-1.9.1.tgz",
"integrity": "sha512-shrVawQFojnZv6xM40anx4CkoDP+fZsw/ZerEMsW/pyzsRbElpsL/DBVW7q3ExxwusdNXI3lXpuhEZkzs8p5Eg==",
"dependencies": {
"color-name": "^1.0.0",
"simple-swizzle": "^0.2.2"
}
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"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",
+2
View File
@@ -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",
+248
View File
@@ -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?"
}
]
}
+44
View File
@@ -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();
+6
View File
@@ -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(
(
+7
View File
@@ -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">
+104 -56
View File
@@ -1,13 +1,17 @@
import dotenv from "dotenv";
import type firebase from "firebase-admin";
import { hostname } from "os";
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;
@@ -29,6 +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.
@@ -51,12 +66,12 @@ type Config = {
*/
gatekeeper: "none" | "proxy_key" | "user_token";
/**
* Persistence layer to use for user and key management.
* - `memory`: Data is stored in memory and lost on restart (default)
* - `firebase_rtdb`: Data is stored in Firebase Realtime Database; requires
* `firebaseKey` and `firebaseRtdbUrl` to be set.
* Persistence layer to use for user management.
* - `memory`: Users are stored in memory and are lost on restart (default)
* - `firebase_rtdb`: Users are stored in a Firebase Realtime Database;
* requires `firebaseKey` and `firebaseRtdbUrl` to be set.
*/
persistenceProvider: "memory" | "firebase_rtdb";
gatekeeperStore: "memory" | "firebase_rtdb";
/** URL of the Firebase Realtime Database if using the Firebase RTDB store. */
firebaseRtdbUrl?: string;
/**
@@ -66,26 +81,20 @@ type Config = {
*/
firebaseKey?: string;
/**
* The root key under which data will be stored in the Firebase RTDB. This
* allows multiple instances of the proxy to share the same database while
* keeping their data separate.
*
* If you want multiple proxies to share the same data, set all of their
* `firebaseRtdbRoot` to the same value. Beware that there will likely
* be conflicts because concurrent writes are not yet supported and proxies
* currently assume they have exclusive access to the database.
*
* Defaults to the system hostname so that data is kept separate.
*/
firebaseRtdbRoot: 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.
@@ -104,10 +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. */
rejectDisallowed?: boolean;
/** Whether requests containing the following phrases should be rejected. */
rejectPhrases: string[];
/** Message to return when rejecting requests. */
rejectMessage?: string;
rejectMessage: string;
/** Verbosity level of diagnostic logging. */
logLevel: "trace" | "debug" | "info" | "warn" | "error";
/**
@@ -166,6 +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.
@@ -176,23 +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"),
persistenceProvider: getEnvWithDefault("PERSISTENCE_PROVIDER", "memory"),
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),
firebaseRtdbRoot: getEnvWithDefault("FIREBASE_RTDB_ROOT", hostname()),
modelRateLimit: getEnvWithDefault("MODEL_RATE_LIMIT", 4),
maxContextTokensOpenAI: getEnvWithDefault("MAX_CONTEXT_TOKENS_OPENAI", 0),
textModelRateLimit: getEnvWithDefault("TEXT_MODEL_RATE_LIMIT", 4),
imageModelRateLimit: getEnvWithDefault("IMAGE_MODEL_RATE_LIMIT", 4),
maxContextTokensOpenAI: getEnvWithDefault("MAX_CONTEXT_TOKENS_OPENAI", 16384),
maxContextTokensAnthropic: getEnvWithDefault(
"MAX_CONTEXT_TOKENS_ANTHROPIC",
0
),
maxOutputTokensOpenAI: getEnvWithDefault(
["MAX_OUTPUT_TOKENS_OPENAI", "MAX_OUTPUT_TOKENS"],
300
400
),
maxOutputTokensAnthropic: getEnvWithDefault(
["MAX_OUTPUT_TOKENS_ANTHROPIC", "MAX_OUTPUT_TOKENS"],
@@ -202,11 +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."
@@ -228,16 +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: {
turbo: getEnvWithDefault("TOKEN_QUOTA_TURBO", 0),
gpt4: getEnvWithDefault("TOKEN_QUOTA_GPT4", 0),
"gpt4-32k": getEnvWithDefault("TOKEN_QUOTA_GPT4_32K", 0),
claude: getEnvWithDefault("TOKEN_QUOTA_CLAUDE", 0),
bison: getEnvWithDefault("TOKEN_QUOTA_BISON", 0),
"aws-claude": getEnvWithDefault("TOKEN_QUOTA_AWS_CLAUDE", 0),
},
tokenQuota: MODEL_FAMILIES.reduce(
(acc, family: ModelFamily) => {
acc[family] = getEnvWithDefault(
`TOKEN_QUOTA_${family.toUpperCase().replace(/-/g, "_")}`,
0
) as number;
return acc;
},
{} as { [key in ModelFamily]: number }
),
quotaRefreshPeriod: getEnvWithDefault("QUOTA_REFRESH_PERIOD", undefined),
allowNicknameChanges: getEnvWithDefault("ALLOW_NICKNAME_CHANGES", true),
showRecentImages: getEnvWithDefault("SHOW_RECENT_IMAGES", true),
useInsecureCookies: getEnvWithDefault("USE_INSECURE_COOKIES", isDev),
staticServiceInfo: getEnvWithDefault("STATIC_SERVICE_INFO", false),
} as const;
function generateCookieSecret() {
@@ -253,20 +288,17 @@ function generateCookieSecret() {
export const COOKIE_SECRET = generateCookieSecret();
export async function assertConfigIsValid() {
if (process.env.TURBO_ONLY === "true") {
startupLogger.warn(
"TURBO_ONLY is deprecated. Use ALLOWED_MODEL_FAMILIES=turbo instead."
);
config.allowedModelFamilies = config.allowedModelFamilies.filter(
(f) => !f.includes("gpt4")
);
}
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);
if (!!process.env.GATEKEEPER_STORE) {
startupLogger.warn(
"GATEKEEPER_STORE is deprecated. Use PERSISTENCE_PROVIDER instead. Configuration will be migrated."
{ textLimit: limit, imageLimit: config.imageModelRateLimit },
"MODEL_RATE_LIMIT is deprecated. Use TEXT_MODEL_RATE_LIMIT and IMAGE_MODEL_RATE_LIMIT instead."
);
config.persistenceProvider = process.env.GATEKEEPER_STORE as any;
}
if (!["none", "proxy_key", "user_token"].includes(config.gatekeeper)) {
@@ -294,11 +326,11 @@ export async function assertConfigIsValid() {
}
if (
config.persistenceProvider === "firebase_rtdb" &&
config.gatekeeperStore === "firebase_rtdb" &&
(!config.firebaseKey || !config.firebaseRtdbUrl)
) {
throw new Error(
"Firebase RTDB persistence requires `FIREBASE_KEY` and `FIREBASE_RTDB_URL` to be set."
"Firebase RTDB store requires `FIREBASE_KEY` and `FIREBASE_RTDB_URL` to be set."
);
}
@@ -306,7 +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))
@@ -335,19 +368,25 @@ export const OMITTED_KEYS: (keyof Config)[] = [
"anthropicKey",
"googlePalmKey",
"awsCredentials",
"azureCredentials",
"proxyKey",
"adminKey",
"checkKeys",
"rejectPhrases",
"showTokenCosts",
"googleSheetsKey",
"persistenceProvider",
"firebaseKey",
"firebaseRtdbUrl",
"gatekeeperStore",
"maxIpsPerUser",
"blockedOrigins",
"blockMessage",
"blockRedirect",
"allowNicknameChanges",
"showRecentImages",
"useInsecureCookies",
"staticServiceInfo",
"checkKeys",
"allowedModelFamilies",
];
const getKeys = Object.keys as <T extends object>(obj: T) => Array<keyof T>;
@@ -396,6 +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;
@@ -415,7 +455,7 @@ function getEnvWithDefault<T>(env: string | string[], defaultValue: T): T {
let firebaseApp: firebase.app.App | undefined;
async function maybeInitializeFirebase() {
if (!config.persistenceProvider.startsWith("firebase")) {
if (!config.gatekeeperStore.startsWith("firebase")) {
return;
}
@@ -437,3 +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());
}
+235 -92
View File
@@ -1,3 +1,4 @@
/** This whole module really sucks */
import fs from "fs";
import { Request, Response } from "express";
import showdown from "showdown";
@@ -5,15 +6,21 @@ import { config, listConfig } from "./config";
import {
AnthropicKey,
AwsBedrockKey,
AzureOpenAIKey,
GooglePalmKey,
OpenAIKey,
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;
return res.send(infoPageHtml);
}
// Sometimes huggingface doesn't send the host header and makes us guess.
const baseUrl =
process.env.SPACE_ID && !req.get("host")?.includes("hf.space")
? getExternalUrlForHuggingfaceSpaceId(process.env.SPACE_ID)
: req.protocol + "://" + req.get("host");
res.send(cacheInfoPageHtml(baseUrl));
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 = {
uptime: Math.floor(process.uptime()),
endpoints: {
...(openaiKeys ? { openai: baseUrl + "/proxy/openai" } : {}),
...(openaiKeys
? { ["openai2"]: baseUrl + "/proxy/openai/turbo-instruct" }
: {}),
...(anthropicKeys ? { anthropic: baseUrl + "/proxy/anthropic" } : {}),
...(palmKeys ? { "google-palm": baseUrl + "/proxy/google-palm" } : {}),
...(awsKeys ? { aws: baseUrl + "/proxy/aws/claude" } : {}),
},
const allowDalle = config.allowedModelFamilies.includes("dall-e");
const endpoints = {
...(openaiKeys ? { openai: baseUrl + "/openai" } : {}),
...(openaiKeys ? { openai2: baseUrl + "/openai/turbo-instruct" } : {}),
...(openaiKeys && allowDalle
? { ["openai-image"]: baseUrl + "/openai-image" }
: {}),
...(anthropicKeys ? { anthropic: baseUrl + "/anthropic" } : {}),
...(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() } : {}),
openaiKeys,
anthropicKeys,
palmKeys,
awsKeys,
...(config.textModelRateLimit ? { proomptersNow: getUniqueIps() } : {}),
};
const keyInfo = { openaiKeys, anthropicKeys, palmKeys, awsKeys, azureKeys };
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() } : {}),
...(awsKeys ? { "aws-claude": getAwsInfo() } : {}),
...(palmKeys ? getPalmInfo() : {}),
...(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);
let families = new Set<OpenAIModelFamily>();
const keys = keyPool.list().filter((k) => {
const isOpenAI = keyIsOpenAIKey(k);
if (isOpenAI) k.modelFamilies.forEach((f) => families.add(f));
return isOpenAI;
}) as Omit<OpenAIKey, "key">[];
families = new Set([...families].filter((f) => allowedFamilies.has(f)));
const keys = keyPool.list().filter(keyIsOpenAIKey);
const enabledFamilies = new Set(config.allowedModelFamilies);
const accessibleFamilies = keys
.flatMap((k) => k.modelFamilies)
.filter((f) => enabledFamilies.has(f))
.concat("turbo");
const familySet = new Set(accessibleFamilies);
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(`${f}__overQuota`) || 0,
};
// Don't show trial/revoked keys for non-turbo families.
// Generally those stats only make sense for the lowest-tier model.
if (f !== "turbo") {
delete info[f]!.trialKeys;
delete info[f]!.revokedKeys;
}
});
} else {
info.status = "Key checking is disabled.";
@@ -303,11 +344,14 @@ function getOpenAIInfo() {
};
}
families.forEach((f) => {
if (info[f]) {
familySet.forEach((f) => {
if (enabledFamilies.has(f)) {
if (!info[f]) info[f] = { activeKeys: 0 }; // may occur if checkKeys is disabled
const { estimatedQueueTime, proomptersInQueue } = getQueueInformation(f);
info[f]!.proomptersInQueue = proomptersInQueue;
info[f]!.estimatedQueueTime = estimatedQueueTime;
} else {
(info[f]! as any).status = "GPT-3.5-Turbo is disabled on this proxy.";
}
});
@@ -318,6 +362,7 @@ function getAnthropicInfo() {
const claudeInfo: Partial<ModelAggregates> = {
active: modelStats.get("claude__active") || 0,
pozzed: modelStats.get("claude__pozzed") || 0,
revoked: modelStats.get("claude__revoked") || 0,
};
const queue = getQueueInformation("claude");
@@ -335,6 +380,7 @@ function getAnthropicInfo() {
usage: `${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${getCostString(cost)}`,
activeKeys: bisonInfo.active,
proomptersInQueue: bisonInfo.queued,
estimatedQueueTime: bisonInfo.queueTime,
bison: {
usage: `${prettyTokens(tokens)} tokens${getCostString(cost)}`,
activeKeys: bisonInfo.active,
revokedKeys: bisonInfo.revoked,
proomptersInQueue: bisonInfo.queued,
estimatedQueueTime: bisonInfo.queueTime,
},
};
}
function getAwsInfo() {
const awsInfo: Partial<ModelAggregates> = {
active: modelStats.get("aws-claude__active") || 0,
revoked: modelStats.get("aws-claude__revoked") || 0,
};
const queue = getQueueInformation("aws-claude");
@@ -377,20 +428,65 @@ function getAwsInfo() {
const logged = modelStats.get("aws-claude__awsLogged") || 0;
const logMsg = config.allowAwsLogging
? `${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)}`,
activeKeys: awsInfo.active,
proomptersInQueue: awsInfo.queued,
estimatedQueueTime: awsInfo.queueTime,
...(logged > 0 ? { privacy: logMsg } : {}),
"aws-claude": {
usage: `${prettyTokens(tokens)} tokens${getCostString(cost)}`,
activeKeys: awsInfo.active,
revokedKeys: awsInfo.revoked,
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${getCostString(
cost
)}`;
}
return azureInfo;
}
const customGreeting = fs.existsSync("greeting.md")
? fs.readFileSync("greeting.md", "utf8")
: null;
? `\n## Server Greeting\n${fs.readFileSync("greeting.md", "utf8")}`
: "";
/**
* 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!
The server operator has enabled prompt logging. The prompts you send to this proxy and the AI responses you receive may be saved.
infoBody += `\n## Prompt Logging Enabled
This proxy keeps full logs of all prompts and AI responses. Prompt logs are anonymous and do not contain IP addresses or timestamps.
Logs are anonymous and do not contain IP addresses or timestamps. [You can see the type of data logged here, along with the rest of the code.](https://gitgud.io/khanon/oai-reverse-proxy/-/blob/main/src/prompt-logging/index.ts).
[You can see the type of data logged here, along with the rest of the code.](https://gitgud.io/khanon/oai-reverse-proxy/-/blob/main/src/shared/prompt-logging/index.ts).
**If you are uncomfortable with this, don't send prompts to this proxy!**`;
}
if (config.staticServiceInfo) {
return converter.makeHtml(infoBody + customGreeting);
}
const waits: string[] = [];
infoBody += `\n## Estimated Wait Times\nIf the AI is busy, your prompt will processed when a slot frees up.`;
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:** ${dalleWait}`);
}
}
if (config.anthropicKey) {
@@ -446,9 +553,10 @@ Logs are anonymous and do not contain IP addresses or timestamps. [You can see t
infoBody += "\n\n" + waits.join(" / ");
if (customGreeting) {
infoBody += `\n## Server Greeting\n${customGreeting}`;
}
infoBody += 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`;
+10 -21
View File
@@ -7,13 +7,10 @@ import { ipLimiter } from "./rate-limit";
import { handleProxyError } from "./middleware/common";
import {
addKey,
applyQuotaLimits,
addAnthropicPreamble,
blockZoomerOrigins,
createPreprocessorMiddleware,
finalizeBody,
languageFilter,
stripHeaders, createOnProxyReqHandler
createOnProxyReqHandler,
} from "./middleware/request";
import {
ProxyResHandlerWithBody,
@@ -42,8 +39,9 @@ const getModelsResponse = () => {
"claude-instant-v1.1",
"claude-instant-v1.1-100k",
"claude-instant-v1.0",
"claude-2", // claude-2 is 100k by default it seems
"claude-2",
"claude-2.0",
"claude-2.1",
];
const models = claudeVariants.map((id) => ({
@@ -87,9 +85,8 @@ const anthropicResponseHandler: ProxyResHandlerWithBody = async (
body = transformAnthropicResponse(body, req);
}
// TODO: Remove once tokenization is stable
if (req.debug) {
body.proxy_tokenizer_debug_info = req.debug;
if (req.tokenizerInfo) {
body.proxy_tokenizer = req.tokenizerInfo;
}
res.status(200).json(body);
@@ -129,23 +126,15 @@ function transformAnthropicResponse(
};
}
const anthropicProxy = createQueueMiddleware(
createProxyMiddleware({
const anthropicProxy = createQueueMiddleware({
proxyMiddleware: createProxyMiddleware({
target: "https://api.anthropic.com",
changeOrigin: true,
selfHandleResponse: true,
logger,
on: {
proxyReq: createOnProxyReqHandler({
pipeline: [
applyQuotaLimits,
addKey,
addAnthropicPreamble,
languageFilter,
blockZoomerOrigins,
stripHeaders,
finalizeBody,
],
pipeline: [addKey, addAnthropicPreamble, finalizeBody],
}),
proxyRes: createOnProxyResHandler([anthropicResponseHandler]),
error: handleProxyError,
@@ -154,8 +143,8 @@ const anthropicProxy = createQueueMiddleware(
// Send OpenAI-compat requests to the real Anthropic endpoint.
"^/v1/chat/completions": "/v1/complete",
},
})
);
}),
});
const anthropicRouter = Router();
anthropicRouter.get("/v1/models", handleModelRequest);
+59 -37
View File
@@ -7,20 +7,18 @@ import { createQueueMiddleware } from "./queue";
import { ipLimiter } from "./rate-limit";
import { handleProxyError } from "./middleware/common";
import {
applyQuotaLimits,
createPreprocessorMiddleware,
stripHeaders,
signAwsRequest,
finalizeAwsRequest,
finalizeSignedRequest,
createOnProxyReqHandler,
languageFilter,
blockZoomerOrigins,
} from "./middleware/request";
import {
ProxyResHandlerWithBody,
createOnProxyResHandler,
} from "./middleware/response";
const LATEST_AWS_V2_MINOR_VERSION = "1";
let modelsCache: any = null;
let modelsCacheTime = 0;
@@ -31,7 +29,11 @@ const getModelsResponse = () => {
if (!config.awsCredentials) return { object: "list", data: [] };
const variants = ["anthropic.claude-v1", "anthropic.claude-v2"];
const variants = [
"anthropic.claude-v1",
"anthropic.claude-v2",
"anthropic.claude-v2:1",
];
const models = variants.map((id) => ({
id,
@@ -74,9 +76,8 @@ const awsResponseHandler: ProxyResHandlerWithBody = async (
body = transformAwsResponse(body, req);
}
// TODO: Remove once tokenization is stable
if (req.debug) {
body.proxy_tokenizer_debug_info = req.debug;
if (req.tokenizerInfo) {
body.proxy_tokenizer = req.tokenizerInfo;
}
// AWS does not confirm the model in the response, so we have to add it
@@ -119,34 +120,24 @@ function transformAwsResponse(
};
}
const awsProxy = createQueueMiddleware(
createProxyMiddleware({
const awsProxy = createQueueMiddleware({
beforeProxy: signAwsRequest,
proxyMiddleware: createProxyMiddleware({
target: "bad-target-will-be-rewritten",
router: ({ signedRequest }) => {
if (!signedRequest) {
throw new Error("AWS requests must go through signAwsRequest first");
}
if (!signedRequest) throw new Error("Must sign request before proxying");
return `${signedRequest.protocol}//${signedRequest.hostname}`;
},
changeOrigin: true,
selfHandleResponse: true,
logger,
on: {
proxyReq: createOnProxyReqHandler({
pipeline: [
applyQuotaLimits,
// Credentials are added by signAwsRequest preprocessor
languageFilter,
blockZoomerOrigins,
stripHeaders,
finalizeAwsRequest,
],
}),
proxyReq: createOnProxyReqHandler({ pipeline: [finalizeSignedRequest] }),
proxyRes: createOnProxyResHandler([awsResponseHandler]),
error: handleProxyError,
},
})
);
}),
});
const awsRouter = Router();
awsRouter.get("/v1/models", handleModelRequest);
@@ -156,7 +147,7 @@ awsRouter.post(
ipLimiter,
createPreprocessorMiddleware(
{ inApi: "anthropic", outApi: "anthropic", service: "aws" },
{ afterTransform: [maybeReassignModel, signAwsRequest] }
{ afterTransform: [maybeReassignModel] }
),
awsProxy
);
@@ -166,7 +157,7 @@ awsRouter.post(
ipLimiter,
createPreprocessorMiddleware(
{ inApi: "openai", outApi: "anthropic", service: "aws" },
{ afterTransform: [maybeReassignModel, signAwsRequest] }
{ afterTransform: [maybeReassignModel] }
),
awsProxy
);
@@ -181,16 +172,47 @@ awsRouter.post(
*/
function maybeReassignModel(req: Request) {
const model = req.body.model;
// User's client sent an AWS model already
if (model.includes("anthropic.claude")) return;
// User's client is sending Anthropic-style model names, check for v1
if (model.match(/^claude-v?1/)) {
req.body.model = "anthropic.claude-v1";
} else {
// User's client requested v2 or possibly some OpenAI model, default to v2
req.body.model = "anthropic.claude-v2";
// If client already specified an AWS Claude model ID, use it
if (model.includes("anthropic.claude")) {
return;
}
// TODO: Handle claude-instant
const pattern = /^(claude-)?(instant-)?(v)?(\d+)(\.(\d+))?(-\d+k)?$/i;
const match = model.match(pattern);
// If there's no match, return the latest v2 model
if (!match) {
req.body.model = `anthropic.claude-v2:${LATEST_AWS_V2_MINOR_VERSION}`;
return;
}
const [, , instant, , major, , minor] = match;
if (instant) {
req.body.model = "anthropic.claude-instant-v1";
return;
}
// There's only one v1 model
if (major === "1") {
req.body.model = "anthropic.claude-v1";
return;
}
// Try to map Anthropic API v2 models to AWS v2 models
if (major === "2") {
if (minor === "0") {
req.body.model = "anthropic.claude-v2";
return;
}
req.body.model = `anthropic.claude-v2:${LATEST_AWS_V2_MINOR_VERSION}`;
return;
}
// Fallback to latest v2 model
req.body.model = `anthropic.claude-v2:${LATEST_AWS_V2_MINOR_VERSION}`;
return;
}
export const aws = awsRouter;
+128
View File
@@ -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;
+14 -11
View File
@@ -46,19 +46,22 @@ export const gatekeeper: RequestHandler = (req, res, next) => {
}
if (GATEKEEPER === "user_token" && token) {
const user = authenticate(token, req.ip);
if (user) {
req.user = user;
return next();
} else {
const maybeBannedUser = getUser(token);
if (maybeBannedUser?.disabledAt) {
const { user, result } = authenticate(token, req.ip);
switch (result) {
case "success":
req.user = user;
return next();
case "limited":
return res.status(403).json({
error: `Forbidden: ${
maybeBannedUser.disabledReason || "Token disabled"
}`,
error: `Forbidden: no more IPs can authenticate with this token`,
});
}
case "disabled":
const bannedUser = getUser(token);
if (bannedUser?.disabledAt) {
const reason = bannedUser.disabledReason || "Token disabled";
return res.status(403).json({ error: `Forbidden: ${reason}` });
}
}
}
+18 -8
View File
@@ -4,16 +4,15 @@ import { ZodError } from "zod";
import { generateErrorMessage } from "zod-error";
import { buildFakeSse } from "../../shared/streaming";
import { assertNever } from "../../shared/utils";
import { QuotaExceededError } from "./request/apply-quota-limits";
import { QuotaExceededError } from "./request/preprocessors/apply-quota-limits";
const OPENAI_CHAT_COMPLETION_ENDPOINT = "/v1/chat/completions";
const OPENAI_TEXT_COMPLETION_ENDPOINT = "/v1/completions";
const OPENAI_EMBEDDINGS_ENDPOINT = "/v1/embeddings";
const OPENAI_IMAGE_COMPLETION_ENDPOINT = "/v1/images/generations";
const ANTHROPIC_COMPLETION_ENDPOINT = "/v1/complete";
/** Returns true if we're making a request to a completion endpoint. */
export function isCompletionRequest(req: Request) {
// 99% sure this function is not needed anymore
export function isTextGenerationRequest(req: Request) {
return (
req.method === "POST" &&
[
@@ -24,6 +23,13 @@ export function isCompletionRequest(req: Request) {
);
}
export function isImageGenerationRequest(req: Request) {
return (
req.method === "POST" &&
req.path.startsWith(OPENAI_IMAGE_COMPLETION_ENDPOINT)
);
}
export function isEmbeddingsRequest(req: Request) {
return (
req.method === "POST" && req.path.startsWith(OPENAI_EMBEDDINGS_ENDPOINT)
@@ -53,8 +59,8 @@ export function writeErrorResponse(
res.write(`data: [DONE]\n\n`);
res.end();
} else {
if (req.debug && errorPayload.error) {
errorPayload.error.proxy_tokenizer_debug_info = req.debug;
if (req.tokenizerInfo && typeof errorPayload.error === "object") {
errorPayload.error.proxy_tokenizer = req.tokenizerInfo;
}
res.status(statusCode).json(errorPayload);
}
@@ -90,7 +96,7 @@ function classifyError(err: Error): {
} & Record<string, any> {
const defaultError = {
status: 500,
userMessage: `Reverse proxy encountered an unexpected error. (${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;
@@ -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,
}
);
}
};
+20 -19
View File
@@ -2,29 +2,30 @@ import type { Request } from "express";
import type { ClientRequest } from "http";
import type { ProxyReqCallback } from "http-proxy";
export { createOnProxyReqHandler } from "./rewrite";
export { createOnProxyReqHandler } from "./onproxyreq-factory";
export {
createPreprocessorMiddleware,
createEmbeddingsPreprocessorMiddleware,
} from "./preprocess";
} from "./preprocessor-factory";
// Express middleware (runs before http-proxy-middleware, can be async)
export { applyQuotaLimits } from "./apply-quota-limits";
export { validateContextSize } from "./validate-context-size";
export { countPromptTokens } from "./count-prompt-tokens";
export { setApiFormat } from "./set-api-format";
export { signAwsRequest } from "./sign-aws-request";
export { transformOutboundPayload } from "./transform-outbound-payload";
export { addAzureKey } from "./preprocessors/add-azure-key";
export { applyQuotaLimits } from "./preprocessors/apply-quota-limits";
export { validateContextSize } from "./preprocessors/validate-context-size";
export { countPromptTokens } from "./preprocessors/count-prompt-tokens";
export { languageFilter } from "./preprocessors/language-filter";
export { setApiFormat } from "./preprocessors/set-api-format";
export { signAwsRequest } from "./preprocessors/sign-aws-request";
export { transformOutboundPayload } from "./preprocessors/transform-outbound-payload";
// HPM middleware (runs on onProxyReq, cannot be async)
export { addKey, addKeyForEmbeddingsRequest } from "./add-key";
export { addAnthropicPreamble } from "./add-anthropic-preamble";
export { blockZoomerOrigins } from "./block-zoomer-origins";
export { finalizeBody } from "./finalize-body";
export { finalizeAwsRequest } from "./finalize-aws-request";
export { languageFilter } from "./language-filter";
export { limitCompletions } from "./limit-completions";
export { stripHeaders } from "./strip-headers";
// http-proxy-middleware callbacks (runs on onProxyReq, cannot be async)
export { addKey, addKeyForEmbeddingsRequest } from "./onproxyreq/add-key";
export { addAnthropicPreamble } from "./onproxyreq/add-anthropic-preamble";
export { blockZoomerOrigins } from "./onproxyreq/block-zoomer-origins";
export { checkModelFamily } from "./onproxyreq/check-model-family";
export { finalizeBody } from "./onproxyreq/finalize-body";
export { finalizeSignedRequest } from "./onproxyreq/finalize-signed-request";
export { stripHeaders } from "./onproxyreq/strip-headers";
/**
* Middleware that runs prior to the request being handled by http-proxy-
@@ -43,7 +44,7 @@ export { stripHeaders } from "./strip-headers";
export type RequestPreprocessor = (req: Request) => void | Promise<void>;
/**
* Middleware that runs immediately before the request is sent to the API in
* Callbacks that run immediately before the request is sent to the API in
* response to http-proxy-middleware's `proxyReq` event.
*
* Async functions cannot be used here as HPM's event emitter is not async and
@@ -53,7 +54,7 @@ export type RequestPreprocessor = (req: Request) => void | Promise<void>;
* first attempt is rate limited and the request is automatically retried by the
* request queue middleware.
*/
export type ProxyRequestMiddleware = ProxyReqCallback<ClientRequest, Request>;
export type HPMRequestCallback = ProxyReqCallback<ClientRequest, Request>;
export const forceModel = (model: string) => (req: Request) =>
void (req.body.model = model);
@@ -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);
}
}
@@ -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`);
}
}
};
@@ -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);
}
};
};
@@ -1,17 +1,17 @@
import { AnthropicKey, Key } from "../../../shared/key-management";
import { isCompletionRequest } from "../common";
import { ProxyRequestMiddleware } from ".";
import { AnthropicKey, Key } from "../../../../shared/key-management";
import { isTextGenerationRequest } from "../../common";
import { HPMRequestCallback } from "../index";
/**
* Some keys require the prompt to start with `\n\nHuman:`. There is no way to
* know this without trying to send the request and seeing if it fails. If a
* key is marked as requiring a preamble, it will be added here.
*/
export const addAnthropicPreamble: ProxyRequestMiddleware = (
export const addAnthropicPreamble: HPMRequestCallback = (
_proxyReq,
req
) => {
if (!isCompletionRequest(req) || req.key?.service !== "anthropic") {
if (!isTextGenerationRequest(req) || req.key?.service !== "anthropic") {
return;
}
@@ -1,24 +1,12 @@
import { Key, OpenAIKey, keyPool } from "../../../shared/key-management";
import { isCompletionRequest, isEmbeddingsRequest } from "../common";
import { ProxyRequestMiddleware } from ".";
import { assertNever } from "../../../shared/utils";
import { Key, OpenAIKey, keyPool } from "../../../../shared/key-management";
import { isEmbeddingsRequest } from "../../common";
import { HPMRequestCallback } from "../index";
import { assertNever } from "../../../../shared/utils";
/** Add a key that can service this request to the request object. */
export const addKey: ProxyRequestMiddleware = (proxyReq, req) => {
export const addKey: HPMRequestCallback = (proxyReq, req) => {
let assignedKey: Key;
if (!isCompletionRequest(req)) {
// Horrible, horrible hack to stop the proxy from complaining about clients
// not sending a model when they are requesting the list of models (which
// requires a key, but obviously not a model).
// I don't think this is needed anymore since models requests are no longer
// proxied to the upstream API. Everything going through this is either a
// completion request or a special case like OpenAI embeddings.
req.log.warn({ path: req.path }, "addKey called on non-completion request");
req.body.model = "gpt-3.5-turbo";
}
if (!req.inboundApi || !req.outboundApi) {
const err = new Error(
"Request API format missing. Did you forget to add the request preprocessor to your router?"
@@ -34,10 +22,6 @@ export const addKey: ProxyRequestMiddleware = (proxyReq, req) => {
throw new Error("You must specify a model with your request.");
}
// TODO: use separate middleware to deal with stream flags
req.isStreaming = req.body.stream === true || req.body.stream === "true";
req.body.stream = req.isStreaming;
if (req.inboundApi === req.outboundApi) {
assignedKey = keyPool.get(req.body.model);
} else {
@@ -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;
@@ -1,5 +1,4 @@
import { isCompletionRequest } from "../common";
import { ProxyRequestMiddleware } from ".";
import { HPMRequestCallback } from "../index";
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) => {
if (!isCompletionRequest(req)) {
return;
}
export const blockZoomerOrigins: HPMRequestCallback = (_proxyReq, req) => {
const origin = req.headers.origin || req.headers.referer;
if (origin && DISALLOWED_ORIGIN_SUBSTRINGS.some((s) => origin.includes(s))) {
// Venus-derivatives send a test prompt to check if the proxy is working.
@@ -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`);
}
};
@@ -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);
@@ -1,11 +1,11 @@
import type { ProxyRequestMiddleware } from ".";
import type { HPMRequestCallback } from "../index";
/**
* For AWS requests, the body is signed earlier in the request pipeline, before
* the proxy middleware. This function just assigns the path and headers to the
* proxy request.
* For AWS/Azure requests, the body is signed earlier in the request pipeline,
* before the proxy middleware. This function just assigns the path and headers
* to the proxy request.
*/
export const finalizeAwsRequest: ProxyRequestMiddleware = (proxyReq, req) => {
export const finalizeSignedRequest: HPMRequestCallback = (proxyReq, req) => {
if (!req.signedRequest) {
throw new Error("Expected req.signedRequest to be set");
}
@@ -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", "");
@@ -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);
}
}
@@ -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 };
}
@@ -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,
}
);
}
};
@@ -1,6 +1,7 @@
import { RequestPreprocessor } from "./index";
import { countTokens, OpenAIPromptMessage } from "../../../shared/tokenization";
import { assertNever } from "../../../shared/utils";
import { RequestPreprocessor } from "../index";
import { countTokens } from "../../../../shared/tokenization";
import { assertNever } from "../../../../shared/utils";
import type { 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.debug = { ...req.debug, ...result };
};
req.tokenizerInfo = req.tokenizerInfo ?? {};
req.tokenizerInfo = { ...req.tokenizerInfo, ...result };
};
@@ -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);
}
}
@@ -1,13 +1,13 @@
import { Request } from "express";
import { APIFormat, LLMService } from "../../../shared/key-management";
import { RequestPreprocessor } from ".";
import { APIFormat, LLMService } from "../../../../shared/key-management";
import { RequestPreprocessor } from "../index";
export const setApiFormat = (api: {
inApi: Request["inboundApi"];
outApi: APIFormat;
service: LLMService;
service: LLMService,
}): RequestPreprocessor => {
return function configureRequestApiFormat(req) {
return function configureRequestApiFormat (req) {
req.inboundApi = api.inApi;
req.outboundApi = api.outApi;
req.service = api.service;
@@ -2,12 +2,12 @@ import express from "express";
import { Sha256 } from "@aws-crypto/sha256-js";
import { SignatureV4 } from "@smithy/signature-v4";
import { HttpRequest } from "@smithy/protocol-http";
import { keyPool } from "../../../shared/key-management";
import { RequestPreprocessor } from ".";
import { keyPool } from "../../../../shared/key-management";
import { RequestPreprocessor } from "../index";
import { AnthropicV1CompleteSchema } from "./transform-outbound-payload";
const AMZ_HOST =
process.env.AMZ_HOST || "invoke-bedrock.%REGION%.amazonaws.com";
process.env.AMZ_HOST || "bedrock-runtime.%REGION%.amazonaws.com";
/**
* Signs an outgoing AWS request with the appropriate headers modifies the
@@ -1,14 +1,15 @@
import { Request } from "express";
import { z } from "zod";
import { config } from "../../../config";
import { OpenAIPromptMessage } from "../../../shared/tokenization";
import { isCompletionRequest } from "../common";
import { RequestPreprocessor } from ".";
import { APIFormat } from "../../../shared/key-management";
import { config } from "../../../../config";
import { isTextGenerationRequest, isImageGenerationRequest } from "../../common";
import { RequestPreprocessor } from "../index";
import { APIFormat } from "../../../../shared/key-management";
const CLAUDE_OUTPUT_MAX = config.maxOutputTokensAnthropic;
const OPENAI_OUTPUT_MAX = config.maxOutputTokensOpenAI;
// TODO: move schemas to shared
// https://console.anthropic.com/docs/api/reference#-v1-complete
export const AnthropicV1CompleteSchema = z.object({
model: z.string(),
@@ -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) {
return;
}
if (alreadyTransformed || notTransformable) 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 ${m.name}) ` : ""}${
m.content
}`;
return `\n\n${role}: ${name ? `(as ${name}) ` : ""}${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: ${PROMPT_VERSION}`);
}
}
function flattenOpenAIMessageContent(
content: OpenAIChatMessage["content"]
): string {
return Array.isArray(content)
? content
.map((contentItem) => {
if ("text" in contentItem) return contentItem.text;
if ("image_url" in contentItem) return "[ Uploaded Image Omitted ]";
})
.join("\n")
: content;
}
@@ -1,8 +1,8 @@
import { Request } from "express";
import { z } from "zod";
import { config } from "../../../config";
import { assertNever } from "../../../shared/utils";
import { RequestPreprocessor } from ".";
import { config } from "../../../../config";
import { assertNever } from "../../../../shared/utils";
import { RequestPreprocessor } from "../index";
const CLAUDE_MAX_CONTEXT = config.maxContextTokensAnthropic;
const OPENAI_MAX_CONTEXT = config.maxContextTokensOpenAI;
@@ -34,6 +34,8 @@ export const validateContextSize: RequestPreprocessor = async (req) => {
case "google-palm":
proxyMax = BISON_MAX_CONTEXT;
break;
case "openai-image":
return;
default:
assertNever(req.outboundApi);
}
@@ -42,6 +44,10 @@ export const validateContextSize: RequestPreprocessor = async (req) => {
let modelMax: number;
if (model.match(/gpt-3.5-turbo-16k/)) {
modelMax = 16384;
} else if (model.match(/gpt-4-1106(-preview)?/)) {
modelMax = 131072;
} else if (model.match(/^gpt-4(-\d{4})?-vision(-preview)?$/)) {
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
// this ASAP every time a new model is released.
req.log.warn({ model }, "Unknown model, using 100k token limit.");
modelMax = 100000;
req.log.warn({ model }, "Unknown model, using 200k token limit.");
modelMax = 200000;
}
const finalMax = Math.min(proxyMax, modelMax);
@@ -81,10 +87,10 @@ export const validateContextSize: RequestPreprocessor = async (req) => {
"Prompt size validated"
);
req.debug.prompt_tokens = promptTokens;
req.debug.completion_tokens = outputTokens;
req.debug.max_model_tokens = modelMax;
req.debug.max_proxy_tokens = proxyMax;
req.tokenizerInfo.prompt_tokens = promptTokens;
req.tokenizerInfo.completion_tokens = outputTokens;
req.tokenizerInfo.max_model_tokens = modelMax;
req.tokenizerInfo.max_proxy_tokens = proxyMax;
};
function assertRequestHasTokenCounts(
-35
View File
@@ -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);
}
};
};
@@ -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);
res.write(`${errorEvent}data: [DONE]\n\n`);
res.end();
if (err instanceof RetryableError) {
keyPool.markRateLimited(req.key!);
req.log.warn(
{ key: req.key!.hash, retryCount: req.retryCount },
`Re-enqueueing request due to retryable error during streaming response.`
);
req.retryCount++;
enqueue(req);
} else {
const errorEvent = buildFakeSse("stream-error", err.message, req);
res.write(`${errorEvent}data: [DONE]\n\n`);
res.end();
}
throw err;
}
};
+75 -16
View File
@@ -3,10 +3,9 @@ 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 { AnthropicKey, keyPool } from "../../../shared/key-management";
import { keyPool } from "../../../shared/key-management";
import { getOpenAIModelFamily } from "../../../shared/models";
import { countTokens } from "../../../shared/tokenization";
import {
@@ -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);
}
@@ -407,7 +428,7 @@ function maybeHandleMissingPreambleError(
{ key: req.key?.hash },
"Request failed due to missing preamble. Key will be marked as such for subsequent requests."
);
keyPool.update(req.key as AnthropicKey, { requiresPreamble: true });
keyPool.update(req.key!, { requiresPreamble: true });
reenqueueRequest(req);
throw new RetryableError("Claude request re-enqueued to add preamble.");
} else {
@@ -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) {
req.debug.completion_tokens = tokens;
if (req.tokenizerInfo) {
req.tokenizerInfo.completion_tokens = tokens;
}
req.outputTokens = tokens.token_count;
+46 -13
View File
@@ -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)) {
return;
}
const loggable =
isTextGenerationRequest(req) || isImageGenerationRequest(req);
if (!loggable) return;
const promptPayload = getPromptForRequest(req);
const promptPayload = getPromptForRequest(req, responseBody);
const promptFlattened = flattenMessages(promptPayload);
const response = getCompletionFromBody(req, responseBody);
const model = getModelFromBody(req, responseBody);
@@ -41,12 +43,18 @@ export const logPrompt: ProxyResHandlerWithBody = async (
});
};
type OaiMessage = {
role: "user" | "assistant" | "system";
content: string;
type OaiImageResult = {
prompt: string;
size: string;
style: string;
quality: string;
revisedPrompt?: string;
};
const getPromptForRequest = (req: Request): string | OaiMessage[] => {
const getPromptForRequest = (
req: Request,
responseBody: Record<string, any>
): string | OpenAIChatMessage[] | 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 => {
if (typeof messages === "string") {
return messages.trim();
const flattenMessages = (
val: string | OpenAIChatMessage[] | OaiImageResult
): string => {
if (typeof val === "string") {
return val.trim();
}
return messages.map((m) => `${m.role}: ${m.content}`).join("\n");
if (Array.isArray(val)) {
return val
.map(({ content, role }) => {
const text = Array.isArray(content)
? content
.map((c) => {
if ("text" in c) return c.text;
if ("image_url" in c) return "(( Attached Image ))";
})
.join("\n")
: content;
return `${role}: ${text}`;
})
.join("\n");
}
return val.prompt.trim();
};
@@ -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
);
}
};
@@ -4,7 +4,7 @@ import {
mergeEventsForAnthropic,
mergeEventsForOpenAIChat,
mergeEventsForOpenAIText,
OpenAIChatCompletionStreamEvent,
OpenAIChatCompletionStreamEvent
} from "./index";
/**
@@ -33,9 +33,10 @@ 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);
}
}
}
}
@@ -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);
}
@@ -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(
{ event: JSON.stringify(event) },
"Received bad streaming event from AWS"
);
const message = JSON.stringify(event);
return getFakeErrorCompletion("proxy AWS error", message);
const eventStr = JSON.stringify(event);
// Under high load, AWS can rugpull us by returning a 200 and starting the
// stream but then immediately sending a rate limit error as the first
// event. My guess is some race condition in their rate limiting check
// that occurs if two requests arrive at the same time when only one
// concurrency slot is available.
if (headers[":exception-type"] === "throttlingException") {
log.warn(
{ event: eventStr },
"AWS request throttled after streaming has already started; retrying"
);
throw new RetryableError("AWS request throttled mid-stream");
} else {
log.error(
{ event: eventStr },
"Received 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
+142
View File
@@ -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;
+38 -55
View File
@@ -3,60 +3,53 @@ import { createProxyMiddleware } from "http-proxy-middleware";
import { config } from "../config";
import { keyPool } from "../shared/key-management";
import {
getOpenAIModelFamily,
ModelFamily,
OpenAIModelFamily,
getOpenAIModelFamily,
} from "../shared/models";
import { logger } from "../logger";
import { createQueueMiddleware } from "./queue";
import { ipLimiter } from "./rate-limit";
import { handleProxyError } from "./middleware/common";
import {
RequestPreprocessor,
addKey,
addKeyForEmbeddingsRequest,
applyQuotaLimits,
blockZoomerOrigins,
createEmbeddingsPreprocessorMiddleware,
createOnProxyReqHandler,
createPreprocessorMiddleware,
finalizeBody,
forceModel,
languageFilter,
limitCompletions,
stripHeaders,
createOnProxyReqHandler,
RequestPreprocessor,
} from "./middleware/request";
import {
createOnProxyResHandler,
ProxyResHandlerWithBody,
} from "./middleware/response";
// https://platform.openai.com/docs/models/overview
export const KNOWN_OPENAI_MODELS = [
"gpt-4-1106-preview",
"gpt-4-vision-preview",
"gpt-4",
"gpt-4-0613",
"gpt-4-0314", // EOL 2024-06-13
"gpt-4-32k",
"gpt-4-32k-0613",
"gpt-4-32k-0314", // EOL 2024-06-13
"gpt-3.5-turbo",
"gpt-3.5-turbo-0301", // EOL 2024-06-13
"gpt-3.5-turbo-0613",
"gpt-3.5-turbo-16k",
"gpt-3.5-turbo-16k-0613",
"gpt-3.5-turbo-instruct",
"gpt-3.5-turbo-instruct-0914",
"text-embedding-ada-002",
];
let modelsCache: any = null;
let modelsCacheTime = 0;
function getModelsResponse() {
if (new Date().getTime() - modelsCacheTime < 1000 * 60) {
return modelsCache;
}
// https://platform.openai.com/docs/models/overview
const knownModels = [
"gpt-4",
"gpt-4-0613",
"gpt-4-0314", // EOL 2024-06-13
"gpt-4-32k",
"gpt-4-32k-0613",
"gpt-4-32k-0314", // EOL 2024-06-13
"gpt-3.5-turbo",
"gpt-3.5-turbo-0301", // EOL 2024-06-13
"gpt-3.5-turbo-0613",
"gpt-3.5-turbo-16k",
"gpt-3.5-turbo-16k-0613",
"gpt-3.5-turbo-instruct",
"gpt-3.5-turbo-instruct-0914",
"text-embedding-ada-002",
];
export function generateModelList(models = KNOWN_OPENAI_MODELS) {
let available = new Set<OpenAIModelFamily>();
for (const key of keyPool.list()) {
if (key.isDisabled || key.service !== "openai") continue;
@@ -67,7 +60,7 @@ function getModelsResponse() {
const allowed = new Set<ModelFamily>(config.allowedModelFamilies);
available = new Set([...available].filter((x) => allowed.has(x)));
const models = knownModels
return models
.map((id) => ({
id,
object: "model",
@@ -87,15 +80,14 @@ function getModelsResponse() {
parent: null,
}))
.filter((model) => available.has(getOpenAIModelFamily(model.id)));
modelsCache = { object: "list", data: models };
modelsCacheTime = new Date().getTime();
return modelsCache;
}
const handleModelRequest: RequestHandler = (_req, res) => {
res.status(200).json(getModelsResponse());
if (new Date().getTime() - modelsCacheTime < 1000 * 60) return modelsCache;
const result = generateModelList();
modelsCache = { object: "list", data: result };
modelsCacheTime = new Date().getTime();
res.status(200).json(modelsCache);
};
/** Handles some turbo-instruct special cases. */
@@ -137,9 +129,8 @@ const openaiResponseHandler: ProxyResHandlerWithBody = async (
body = transformTurboInstructResponse(body);
}
// TODO: Remove once tokenization is stable
if (req.debug) {
body.proxy_tokenizer_debug_info = req.debug;
if (req.tokenizerInfo) {
body.proxy_tokenizer = req.tokenizerInfo;
}
res.status(200).json(body);
@@ -163,29 +154,21 @@ function transformTurboInstructResponse(
return transformed;
}
const openaiProxy = createQueueMiddleware(
createProxyMiddleware({
const openaiProxy = createQueueMiddleware({
proxyMiddleware: createProxyMiddleware({
target: "https://api.openai.com",
changeOrigin: true,
selfHandleResponse: true,
logger,
on: {
proxyReq: createOnProxyReqHandler({
pipeline: [
applyQuotaLimits,
addKey,
languageFilter,
limitCompletions,
blockZoomerOrigins,
stripHeaders,
finalizeBody,
],
pipeline: [addKey, finalizeBody],
}),
proxyRes: createOnProxyResHandler([openaiResponseHandler]),
error: handleProxyError,
},
})
);
}),
});
const openaiEmbeddingsProxy = createProxyMiddleware({
target: "https://api.openai.com",
@@ -194,7 +177,7 @@ const openaiEmbeddingsProxy = createProxyMiddleware({
logger,
on: {
proxyReq: createOnProxyReqHandler({
pipeline: [addKeyForEmbeddingsRequest, stripHeaders, finalizeBody],
pipeline: [addKeyForEmbeddingsRequest, finalizeBody],
}),
error: handleProxyError,
},
+7 -20
View File
@@ -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.debug) {
body.proxy_tokenizer_debug_info = req.debug;
if (req.tokenizerInfo) {
body.proxy_tokenizer = req.tokenizerInfo;
}
// 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(
createProxyMiddleware({
const googlePalmProxy = createQueueMiddleware({
proxyMiddleware: createProxyMiddleware({
target: "https://generativelanguage.googleapis.com",
changeOrigin: true,
selfHandleResponse: true,
logger,
on: {
proxyReq: createOnProxyReqHandler({
beforeRewrite: [reassignPathForPalmModel],
pipeline: [
applyQuotaLimits,
addKey,
languageFilter,
blockZoomerOrigins,
stripHeaders,
finalizeBody,
],
pipeline: [reassignPathForPalmModel, addKey, finalizeBody],
}),
proxyRes: createOnProxyResHandler([palmResponseHandler]),
error: handleProxyError,
},
})
);
}),
});
const palmRouter = Router();
palmRouter.get("/v1/models", handleModelRequest);
+252 -128
View File
@@ -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 } from "../shared/key-management";
import {
getClaudeModelFamily,
getGooglePalmModelFamily,
getOpenAIModelFamily,
ModelFamily,
} from "../shared/models";
import { getModelFamilyForRequest, MODEL_FAMILIES, 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) {
return req.user.token;
}
if (req.risuToken) {
return req.risuToken;
}
if (req.user) return req.user.token;
if (req.risuToken) return req.risuToken;
if (isFromSharedIp(req)) return "shared-ip";
return req.ip;
}
const sameUserPredicate = (incoming: Request) => (queued: Request) => {
const queuedId = getIdentifier(queued);
const incomingId = getIdentifier(incoming);
return queuedId === incomingId;
};
const sharesIdentifierWith = (incoming: Request) => (queued: Request) =>
getIdentifier(queued) === getIdentifier(incoming);
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
// more spots in the queue. Can't make it unlimited because people will
// intentionally abuse it.
// Authenticated users always get a single spot in the queue.
const isAgnai = AGNAI_DOT_CHAT_IP.includes(req.ip);
// Requests from shared IP addresses such as Agnai.chat are exempt from IP-
// based rate limiting but can only occupy a certain number of slots in the
// queue. Authenticated users always get a single spot in the queue.
const isSharedIp = isFromSharedIp(req);
const maxConcurrentQueuedRequests =
isGuest && isAgnai ? AGNAI_CONCURRENCY_LIMIT : USER_CONCURRENCY_LIMIT;
isGuest && isSharedIp ? AGNAI_CONCURRENCY_LIMIT : USER_CONCURRENCY_LIMIT;
if (enqueuedRequestCount >= maxConcurrentQueuedRequests) {
if (isAgnai) {
if (isSharedIp) {
// Re-enqueued requests are not counted towards the limit since they
// already made it through the queue once.
if (req.retryCount === 0) {
@@ -83,9 +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(() => {
if (process.env.NODE_ENV === "production") {
if (!req.query.badSseParser) req.res!.write(": queue heartbeat\n\n");
} else {
req.log.info(`Sending heartbeat to request in queue.`);
const partition = getPartitionForRequest(req);
const avgWait = Math.round(getEstimatedWaitTime(partition) / 1000);
const currentDuration = Math.round((Date.now() - req.startTime) / 1000);
const debugMsg = `queue length: ${queue.length}; elapsed time: ${currentDuration}s; avg wait: ${avgWait}s`;
req.res!.write(buildFakeSse("heartbeat", debugMsg, req));
}
}, 10000);
registerHeartbeat(req);
} else if (getProxyLoad() > LOAD_THRESHOLD) {
throw new Error(
"Due to heavy traffic on this proxy, you must enable streaming for your request."
);
}
// Register a handler to remove the request from the queue if the connection
// is aborted or closed before it is dequeued.
queue.push(req);
req.queueOutTime = 0;
const removeFromQueue = () => {
req.log.info(`Removing aborted request from queue.`);
const index = queue.indexOf(req);
if (index !== -1) {
queue.splice(index, 1);
}
if (req.heartbeatInterval) {
clearInterval(req.heartbeatInterval);
}
if (req.heartbeatInterval) clearInterval(req.heartbeatInterval);
if (req.monitorInterval) clearInterval(req.monitorInterval);
};
req.onAborted = removeFromQueue;
req.res!.once("close", removeFromQueue);
@@ -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 ?? "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) {
clearInterval(req.heartbeatInterval);
}
if (req.heartbeatInterval) clearInterval(req.heartbeatInterval);
if (req.monitorInterval) clearInterval(req.monitorInterval);
// Track the time leaving the queue now, but don't add it to the wait times
// yet because we don't know if the request will succeed or fail. We track
@@ -201,40 +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.
// TODO: `getLockoutPeriod` uses model names instead of model families
// TODO: genericize this it's really ugly
const gpt432kLockout = keyPool.getLockoutPeriod("gpt-4-32k");
const gpt4Lockout = keyPool.getLockoutPeriod("gpt-4");
const turboLockout = keyPool.getLockoutPeriod("gpt-3.5-turbo");
const claudeLockout = keyPool.getLockoutPeriod("claude-v1");
const palmLockout = keyPool.getLockoutPeriod("text-bison-001");
const awsClaudeLockout = keyPool.getLockoutPeriod("anthropic.claude-v2");
// the others, because we only track rate limits for the key as a whole.
const reqs: (Request | undefined)[] = [];
if (gpt432kLockout === 0) {
reqs.push(dequeue("gpt4-32k"));
}
if (gpt4Lockout === 0) {
reqs.push(dequeue("gpt4"));
}
if (turboLockout === 0) {
reqs.push(dequeue("turbo"));
}
if (claudeLockout === 0) {
reqs.push(dequeue("claude"));
}
if (palmLockout === 0) {
reqs.push(dequeue("bison"));
}
if (awsClaudeLockout === 0) {
reqs.push(dequeue("aws-claude"));
}
MODEL_FAMILIES.forEach((modelFamily) => {
const lockout = keyPool.getLockoutPeriod(modelFamily);
if (lockout === 0) {
reqs.push(dequeue(modelFamily));
}
});
reqs.filter(Boolean).forEach((req) => {
if (req?.proceed) {
req.log.info({ retries: req.retryCount }, `Dequeuing request.`);
const modelFamily = getModelFamilyForRequest(req!);
req.log.info({
retries: req.retryCount,
partition: modelFamily,
}, `Dequeuing request.`);
req.proceed();
}
});
@@ -267,38 +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. */
export function getEstimatedWaitTime(partition: ModelFamily) {
const now = Date.now();
const recentWaits = waitTimes.filter(
(wt) => wt.partition === partition && now - wt.end < 300 * 1000
);
if (recentWaits.length === 0) {
return 0;
}
const WAIT_TIME_INTERVAL = 3000;
const ALPHA_HISTORICAL = 0.2;
const ALPHA_CURRENT = 0.3;
const historicalEmas: Map<ModelFamily, number> = new Map();
const currentEmas: Map<ModelFamily, number> = new Map();
const estimates: Map<ModelFamily, number> = new Map();
return (
recentWaits.reduce((sum, wt) => sum + wt.end - wt.start, 0) /
recentWaits.length
);
export function getEstimatedWaitTime(partition: ModelFamily) {
return estimates.get(partition) ?? 0;
}
/**
* Returns estimated wait time for the given queue partition in milliseconds.
* Requests which are deprioritized are not included in the calculation as they
* would skew the results due to their longer wait times.
*/
function calculateWaitTime(partition: ModelFamily) {
const now = Date.now();
const recentWaits = waitTimes
.filter((wait) => {
const isSamePartition = wait.partition === partition;
const isRecent = now - wait.end < 300 * 1000;
const isNormalPriority = !wait.isDeprioritized;
return isSamePartition && isRecent && isNormalPriority;
})
.map((wait) => wait.end - wait.start);
const recentAverage = recentWaits.length
? recentWaits.reduce((sum, wait) => sum + wait, 0) / recentWaits.length
: 0;
const historicalEma = historicalEmas.get(partition) ?? 0;
historicalEmas.set(
partition,
ALPHA_HISTORICAL * recentAverage + (1 - ALPHA_HISTORICAL) * historicalEma
);
const currentWaits = queue
.filter((req) => {
const isSamePartition = getModelFamilyForRequest(req) === partition;
const isNormalPriority = !isFromSharedIp(req);
return isSamePartition && isNormalPriority;
})
.map((req) => now - req.startTime!);
const longestCurrentWait = Math.max(...currentWaits, 0);
const currentEma = currentEmas.get(partition) ?? 0;
currentEmas.set(
partition,
ALPHA_CURRENT * longestCurrentWait + (1 - ALPHA_CURRENT) * currentEma
);
return (historicalEma + currentEma) / 2;
}
setInterval(() => {
MODEL_FAMILIES.forEach((modelFamily) => {
estimates.set(modelFamily, calculateWaitTime(modelFamily));
});
}, WAIT_TIME_INTERVAL);
export function getQueueLength(partition: ModelFamily | "all" = "all") {
if (partition === "all") {
return queue.length;
@@ -307,9 +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);
}
+67 -30
View File
@@ -1,28 +1,34 @@
import { Request, Response, NextFunction } from "express";
import { config } from "../config";
export const AGNAI_DOT_CHAT_IP = [
export const SHARED_IP_ADDRESSES = new Set([
// Agnai.chat
"157.230.249.32", // old
"157.245.148.56",
"174.138.29.50",
"209.97.162.44",
];
]);
const RATE_LIMIT_ENABLED = Boolean(config.modelRateLimit);
const RATE_LIMIT = Math.max(1, config.modelRateLimit);
const ONE_MINUTE_MS = 60 * 1000;
const lastAttempts = new Map<string, number[]>();
type Timestamp = number;
/** Tracks time of last attempts from each IP address or token. */
const lastAttempts = new Map<string, Timestamp[]>();
/** Tracks time of exempted attempts from shared IPs like Agnai.chat. */
const exemptedRequests: Timestamp[] = [];
const expireOldAttempts = (now: number) => (attempt: number) =>
const isRecentAttempt = (now: Timestamp) => (attempt: Timestamp) =>
attempt > now - ONE_MINUTE_MS;
const getTryAgainInMs = (ip: string) => {
const getTryAgainInMs = (ip: string, type: "text" | "image") => {
const now = Date.now();
const attempts = lastAttempts.get(ip) || [];
const validAttempts = attempts.filter(expireOldAttempts(now));
const validAttempts = attempts.filter(isRecentAttempt(now));
if (validAttempts.length >= RATE_LIMIT) {
const limit =
type === "text" ? config.textModelRateLimit : config.imageModelRateLimit;
if (validAttempts.length >= limit) {
return validAttempts[0] - now + ONE_MINUTE_MS;
} else {
lastAttempts.set(ip, [...validAttempts, now]);
@@ -30,21 +36,25 @@ const getTryAgainInMs = (ip: string) => {
}
};
const getStatus = (ip: string) => {
const getStatus = (ip: string, type: "text" | "image") => {
const now = Date.now();
const attempts = lastAttempts.get(ip) || [];
const validAttempts = attempts.filter(expireOldAttempts(now));
const validAttempts = attempts.filter(isRecentAttempt(now));
const limit =
type === "text" ? config.textModelRateLimit : config.imageModelRateLimit;
return {
remaining: Math.max(0, RATE_LIMIT - validAttempts.length),
remaining: Math.max(0, limit - validAttempts.length),
reset: validAttempts.length > 0 ? validAttempts[0] + ONE_MINUTE_MS : now,
};
};
/** Prunes attempts and IPs that are no longer relevant after one minutes. */
/** Prunes attempts and IPs that are no longer relevant after one minute. */
const clearOldAttempts = () => {
const now = Date.now();
for (const [ip, attempts] of lastAttempts.entries()) {
const validAttempts = attempts.filter(expireOldAttempts(now));
const validAttempts = attempts.filter(isRecentAttempt(now));
if (validAttempts.length === 0) {
lastAttempts.delete(ip);
} else {
@@ -54,8 +64,25 @@ const clearOldAttempts = () => {
};
setInterval(clearOldAttempts, 10 * 1000);
export const getUniqueIps = () => {
return lastAttempts.size;
/** Prunes exempted requests which are older than one minute. */
const clearOldExemptions = () => {
const now = Date.now();
const validExemptions = exemptedRequests.filter(isRecentAttempt(now));
exemptedRequests.splice(0, exemptedRequests.length, ...validExemptions);
};
setInterval(clearOldExemptions, 10 * 1000);
export const getUniqueIps = () => lastAttempts.size;
/**
* Can be used to manually remove the most recent attempt from an IP address,
* ie. in case a prompt triggered OpenAI's content filter and therefore did not
* result in a generation.
*/
export const refundLastAttempt = (req: Request) => {
const key = req.user?.token || req.risuToken || req.ip;
const attempts = lastAttempts.get(key) || [];
attempts.pop();
};
export const ipLimiter = async (
@@ -63,36 +90,46 @@ export const ipLimiter = async (
res: Response,
next: NextFunction
) => {
if (!RATE_LIMIT_ENABLED) return next();
const imageLimit = config.imageModelRateLimit;
const textLimit = config.textModelRateLimit;
if (!textLimit && !imageLimit) return next();
if (req.user?.type === "special") return next();
// Exempt Agnai.chat from rate limiting since it's shared between a lot of
// users. Dunno how to prevent this from being abused without some sort of
// identifier sent from Agnaistic to identify specific users.
if (AGNAI_DOT_CHAT_IP.includes(req.ip)) {
req.log.info("Exempting Agnai request from rate limiting.");
next();
return;
// Exempts Agnai.chat from IP-based rate limiting because its IPs are shared
// by many users. Instead, the request queue will limit the number of such
// requests that may wait in the queue at a time, and sorts them to the end to
// let individual users go first.
if (SHARED_IP_ADDRESSES.has(req.ip)) {
exemptedRequests.push(Date.now());
req.log.info(
{ ip: req.ip, recentExemptions: exemptedRequests.length },
"Exempting Agnai request from rate limiting."
);
return next();
}
const type = (req.baseUrl + req.path).includes("openai-image")
? "image"
: "text";
const limit = type === "image" ? imageLimit : textLimit;
// If user is authenticated, key rate limiting by their token. Otherwise, key
// rate limiting by their IP address. Mitigates key sharing.
const rateLimitKey = req.user?.token || req.risuToken || req.ip;
const { remaining, reset } = getStatus(rateLimitKey);
res.set("X-RateLimit-Limit", config.modelRateLimit.toString());
const { remaining, reset } = getStatus(rateLimitKey, type);
res.set("X-RateLimit-Limit", limit.toString());
res.set("X-RateLimit-Remaining", remaining.toString());
res.set("X-RateLimit-Reset", reset.toString());
const tryAgainInMs = getTryAgainInMs(rateLimitKey);
const tryAgainInMs = getTryAgainInMs(rateLimitKey, type);
if (tryAgainInMs > 0) {
res.set("Retry-After", tryAgainInMs.toString());
res.status(429).json({
error: {
type: "proxy_rate_limited",
message: `This proxy is rate limited to ${
config.modelRateLimit
} prompts per minute. Please try again in ${Math.ceil(
message: `This model type is rate limited to ${limit} prompts per minute. Please try again in ${Math.ceil(
tryAgainInMs / 1000
)} seconds.`,
},
+6 -2
View File
@@ -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.urlencoded({ extended: true, limit: "1536kb" })
express.json({ limit: "10mb" }),
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");
+28 -13
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@@ -1,20 +1,23 @@
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 { handleInfoPage } from "./info-page";
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 { checkOrigin } from "./proxy/check-origin";
import { start as startRequestQueue } from "./proxy/queue";
import { proxyRouter } from "./proxy/routes";
import { init as initKeyPool } from "./shared/key-management/key-pool";
import { handleInfoPage } from "./info-page";
import { logQueue } from "./shared/prompt-logging";
import { init as initTokenizers } from "./shared/tokenization";
import { start as startRequestQueue } from "./proxy/queue";
import { init as initUserStore } from "./shared/users/user-store";
import { init as initTokenizers } from "./shared/tokenization";
import { checkOrigin } from "./proxy/check-origin";
import { userRouter } from "./user/routes";
const PORT = config.port;
@@ -25,9 +28,7 @@ app.use(
pinoHttp({
quietReqLogger: true,
logger,
autoLogging: {
ignore: ({ url }) => ["/health"].includes(url as string),
},
autoLogging: { ignore: ({ url }) => ["/health"].includes(url as string) },
redact: {
paths: [
"req.headers.cookie",
@@ -40,6 +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);
@@ -92,18 +100,21 @@ async function start() {
logger.info("Checking configs and external dependencies...");
await assertConfigIsValid();
logger.info("Starting key pool...");
await initKeyPool();
keyPool.init();
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...");
@@ -114,8 +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."
);
}
+22
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@@ -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;
}
+6
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@@ -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 };
@@ -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;
}
@@ -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.");
}
}
+6 -2
View File
@@ -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"];
+2 -1
View File
@@ -11,7 +11,8 @@ export const injectLocals: RequestHandler = (req, res, next) => {
quota.turbo > 0 || quota.gpt4 > 0 || quota.claude > 0;
res.locals.quota = quota;
res.locals.nextQuotaRefresh = userStore.getNextQuotaRefresh();
res.locals.persistenceEnabled = config.persistenceProvider !== "memory";
res.locals.persistenceEnabled = config.gatekeeperStore !== "memory";
res.locals.usersEnabled = config.gatekeeper === "user_token";
res.locals.showTokenCosts = config.showTokenCosts;
res.locals.maxIps = config.maxIpsPerUser;
+10 -32
View File
@@ -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) {
if (key.isDisabled) {
this.log.warn({ key: key.hash }, "Skipping check for disabled key.");
this.scheduleNextCheck();
return;
}
this.log.debug({ key: key.hash }, "Checking key...");
let isInitialCheck = !key.lastChecked;
try {
const [{ pozzed }] = await Promise.all([this.testLiveness(key)]);
const updates = { isPozzed: pozzed };
this.updateKey(key.hash, updates);
this.log.info(
{ key: key.hash, models: key.modelFamilies },
"Key check complete."
);
} catch (error) {
// touch the key so we don't check it again for a while
this.updateKey(key.hash, {});
this.handleAxiosError(key, error as AxiosError);
}
this.lastCheck = Date.now();
// Only enqueue the next check if this wasn't a startup check, since those
// are batched together elsewhere.
if (!isInitialCheck) {
this.scheduleNextCheck();
}
protected async testKeyOrFail(key: AnthropicKey) {
const [{ pozzed }] = await Promise.all([this.testLiveness(key)]);
const updates = { isPozzed: pozzed };
this.updateKey(key.hash, updates);
this.log.info(
{ key: key.hash, models: key.modelFamilies },
"Checked key."
);
}
protected handleAxiosError(key: AnthropicKey, error: AxiosError) {
@@ -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;
+108 -35
View File
@@ -1,22 +1,28 @@
import crypto from "crypto";
import { Key, KeyProvider } from "..";
import { config } from "../../../config";
import { logger } from "../../../logger";
import type { AnthropicModelFamily } from "../../models";
import { KeyProviderBase } from "../key-provider-base";
import { Key } from "../types";
import { AnthropicKeyChecker } from "./checker";
const RATE_LIMIT_LOCKOUT = 2000;
const KEY_REUSE_DELAY = 500;
// https://docs.anthropic.com/claude/reference/selecting-a-model
export const ANTHROPIC_SUPPORTED_MODELS = [
"claude-instant-v1",
"claude-instant-v1-100k",
"claude-v1",
"claude-v1-100k",
"claude-2",
] as const;
export type AnthropicModel = (typeof ANTHROPIC_SUPPORTED_MODELS)[number];
export type AnthropicModel =
| "claude-instant-v1"
| "claude-instant-v1-100k"
| "claude-v1"
| "claude-v1-100k"
| "claude-2"
| "claude-2.1";
export type AnthropicKeyUpdate = Omit<
Partial<AnthropicKey>,
| "key"
| "hash"
| "lastUsed"
| "promptCount"
| "rateLimitedAt"
| "rateLimitedUntil"
>;
type AnthropicKeyUsage = {
[K in AnthropicModelFamily as `${K}Tokens`]: number;
@@ -44,33 +50,72 @@ export interface AnthropicKey extends Key, AnthropicKeyUsage {
isPozzed: boolean;
}
export class AnthropicKeyProvider extends KeyProviderBase<AnthropicKey> {
readonly service = "anthropic" as const;
/**
* Upon being rate limited, a key will be locked out for this many milliseconds
* while we wait for other concurrent requests to finish.
*/
const RATE_LIMIT_LOCKOUT = 2000;
/**
* Upon assigning a key, we will wait this many milliseconds before allowing it
* to be used again. This is to prevent the queue from flooding a key with too
* many requests while we wait to learn whether previous ones succeeded.
*/
const KEY_REUSE_DELAY = 500;
protected readonly keys: AnthropicKey[] = [];
export class AnthropicKeyProvider implements KeyProvider<AnthropicKey> {
readonly service = "anthropic";
private keys: AnthropicKey[] = [];
private checker?: AnthropicKeyChecker;
protected log = logger.child({ module: "key-provider", service: this.service });
private log = logger.child({ module: "key-provider", service: this.service });
public async init() {
const storeName = this.store.constructor.name;
const loadedKeys = await this.store.load();
if (loadedKeys.length === 0) {
return this.log.warn({ via: storeName }, "No Anthropic keys found.");
constructor() {
const keyConfig = config.anthropicKey?.trim();
if (!keyConfig) {
this.log.warn(
"ANTHROPIC_KEY is not set. Anthropic 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: AnthropicKey = {
key,
service: this.service,
modelFamilies: ["claude"],
isDisabled: false,
isRevoked: false,
isPozzed: false,
promptCount: 0,
lastUsed: 0,
rateLimitedAt: 0,
rateLimitedUntil: 0,
requiresPreamble: false,
hash: `ant-${crypto
.createHash("sha256")
.update(key)
.digest("hex")
.slice(0, 8)}`,
lastChecked: 0,
claudeTokens: 0,
};
this.keys.push(newKey);
}
this.log.info({ keyCount: this.keys.length }, "Loaded Anthropic keys.");
}
this.keys.push(...loadedKeys);
this.log.info(
{ count: this.keys.length, via: storeName },
"Loaded Anthropic keys."
);
public init() {
if (config.checkKeys) {
this.checker = new AnthropicKeyChecker(this.keys, this.update.bind(this));
this.checker.start();
}
}
public list() {
return this.keys.map((k) => Object.freeze({ ...k, key: undefined }));
}
public get(_model: AnthropicModel) {
// Currently, all Anthropic keys have access to all models. This will almost
// certainly change when they move out of beta later this year.
@@ -107,14 +152,26 @@ export class AnthropicKeyProvider extends KeyProviderBase<AnthropicKey> {
const selectedKey = keysByPriority[0];
selectedKey.lastUsed = now;
selectedKey.rateLimitedAt = now;
// Intended to throttle the queue processor as otherwise it will just
// flood the API with requests and we want to wait a sec to see if we're
// going to get a rate limit error on this key.
selectedKey.rateLimitedUntil = now + KEY_REUSE_DELAY;
this.throttle(selectedKey.hash);
return { ...selectedKey };
}
public disable(key: AnthropicKey) {
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<AnthropicKey>) {
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;
@@ -122,7 +179,7 @@ export class AnthropicKeyProvider extends KeyProviderBase<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.
@@ -164,4 +221,20 @@ export class AnthropicKeyProvider extends KeyProviderBase<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);
}
}
@@ -1,43 +0,0 @@
import crypto from "crypto";
import type { AnthropicKey, SerializedKey } from "../index";
import { KeySerializerBase } from "../key-serializer-base";
const SERIALIZABLE_FIELDS: (keyof AnthropicKey)[] = [
"key",
"service",
"hash",
"promptCount",
"claudeTokens",
];
export type SerializedAnthropicKey = SerializedKey &
Partial<Pick<AnthropicKey, (typeof SERIALIZABLE_FIELDS)[number]>>;
export class AnthropicKeySerializer extends KeySerializerBase<AnthropicKey> {
constructor() {
super(SERIALIZABLE_FIELDS);
}
deserialize({ key, ...rest }: SerializedAnthropicKey): AnthropicKey {
return {
key,
service: "anthropic" as const,
modelFamilies: ["claude" as const],
isDisabled: false,
isRevoked: false,
isPozzed: false,
promptCount: 0,
lastUsed: 0,
rateLimitedAt: 0,
rateLimitedUntil: 0,
requiresPreamble: false,
hash: `ant-${crypto
.createHash("sha256")
.update(key)
.digest("hex")
.slice(0, 8)}`,
lastChecked: 0,
claudeTokens: 0,
...rest,
};
}
}
+25 -47
View File
@@ -8,11 +8,13 @@ import type { AwsBedrockKey, AwsBedrockKeyProvider } from "./provider";
const MIN_CHECK_INTERVAL = 3 * 1000; // 3 seconds
const KEY_CHECK_PERIOD = 3 * 60 * 1000; // 3 minutes
const AMZ_HOST =
process.env.AMZ_HOST || "bedrock-runtime.%REGION%.amazonaws.com";
const GET_CALLER_IDENTITY_URL = `https://sts.amazonaws.com/?Action=GetCallerIdentity&Version=2011-06-15`;
const GET_INVOCATION_LOGGING_CONFIG_URL = (region: string) =>
`https://bedrock.${region}.amazonaws.com/logging/modelinvocations`;
const POST_INVOKE_MODEL_URL = (region: string, model: string) =>
`https://invoke-bedrock.${region}.amazonaws.com/model/${model}/invoke`;
`https://${AMZ_HOST.replace("%REGION%", region)}/model/${model}/invoke`;
const TEST_PROMPT = "\n\nHuman:\n\nAssistant:";
type AwsError = { error: {} };
@@ -30,58 +32,36 @@ type GetLoggingConfigResponse = {
type UpdateFn = typeof AwsBedrockKeyProvider.prototype.update;
export class AwsKeyChecker extends KeyCheckerBase<AwsBedrockKey> {
private readonly updateKey: UpdateFn;
constructor(keys: AwsBedrockKey[], updateKey: UpdateFn) {
super(keys, {
service: "aws",
keyCheckPeriod: KEY_CHECK_PERIOD,
minCheckInterval: MIN_CHECK_INTERVAL,
updateKey,
});
this.updateKey = updateKey;
}
protected async checkKey(key: AwsBedrockKey) {
if (key.isDisabled) {
this.log.warn({ key: key.hash }, "Skipping check for disabled key.");
this.scheduleNextCheck();
return;
protected async testKeyOrFail(key: AwsBedrockKey) {
// Only check models on startup. For now all models must be available to
// the proxy because we don't route requests to different keys.
const modelChecks: Promise<unknown>[] = [];
const isInitialCheck = !key.lastChecked;
if (isInitialCheck) {
modelChecks.push(this.invokeModel("anthropic.claude-v1", key));
modelChecks.push(this.invokeModel("anthropic.claude-v2", key));
}
this.log.debug({ key: key.hash }, "Checking key...");
let isInitialCheck = !key.lastChecked;
try {
// Only check models on startup. For now all models must be available to
// the proxy because we don't route requests to different keys.
const modelChecks: Promise<unknown>[] = [];
if (isInitialCheck) {
modelChecks.push(this.invokeModel("anthropic.claude-v1", key));
modelChecks.push(this.invokeModel("anthropic.claude-v2", key));
}
await Promise.all(modelChecks);
await this.checkLoggingConfiguration(key);
await Promise.all(modelChecks);
await this.checkLoggingConfiguration(key);
this.log.info(
{
key: key.hash,
models: key.modelFamilies,
logged: key.awsLoggingStatus,
},
"Key check complete."
);
} catch (error) {
this.handleAxiosError(key, error as AxiosError);
}
this.updateKey(key.hash, {});
this.lastCheck = Date.now();
// Only enqueue the next check if this wasn't a startup check, since those
// are batched together elsewhere.
if (!isInitialCheck) {
this.scheduleNextCheck();
}
this.log.info(
{
key: key.hash,
models: key.modelFamilies,
logged: key.awsLoggingStatus,
},
"Checked key."
);
}
protected handleAxiosError(key: AwsBedrockKey, error: AxiosError) {
@@ -165,12 +145,10 @@ export class AwsKeyChecker extends KeyCheckerBase<AwsBedrockKey> {
const errorType = (headers["x-amzn-errortype"] as string).split(":")[0];
const errorMessage = data?.message;
// We're looking for a specific error type and message here:
// We're looking for a specific error type and message here
// "ValidationException"
// "Malformed input request: -1 is not greater or equal to 0, please reformat your input and try again."
// "Malformed input request: 2 schema violations found, please reformat your input and try again." (if there are multiple issues)
const correctErrorType = errorType === "ValidationException";
const correctErrorMessage = errorMessage?.match(/malformed input request/i);
const correctErrorMessage = errorMessage?.match(/max_tokens_to_sample/);
if (!correctErrorType || !correctErrorMessage) {
throw new AxiosError(
`Unexpected error when invoking model ${model}: ${errorMessage}`,
@@ -182,7 +160,7 @@ export class AwsKeyChecker extends KeyCheckerBase<AwsBedrockKey> {
}
this.log.debug(
{ key: key.hash, errorType, data, status },
{ key: key.hash, errorType, data, status, model },
"Liveness test complete."
);
}
+94 -33
View File
@@ -1,20 +1,15 @@
import crypto from "crypto";
import { Key, KeyProvider } from "..";
import { config } from "../../../config";
import { logger } from "../../../logger";
import type { AwsBedrockModelFamily } from "../../models";
import { KeyProviderBase } from "../key-provider-base";
import { Key } from "../types";
import { AwsKeyChecker } from "./checker";
const RATE_LIMIT_LOCKOUT = 2000;
const KEY_REUSE_DELAY = 500;
// https://docs.aws.amazon.com/bedrock/latest/userguide/model-ids-arns.html
export const AWS_BEDROCK_SUPPORTED_MODELS = [
"anthropic.claude-v1",
"anthropic.claude-v2",
"anthropic.claude-instant-v1",
] as const;
export type AwsBedrockModel = (typeof AWS_BEDROCK_SUPPORTED_MODELS)[number];
export type AwsBedrockModel =
| "anthropic.claude-v1"
| "anthropic.claude-v2"
| "anthropic.claude-instant-v1";
type AwsBedrockKeyUsage = {
[K in AwsBedrockModelFamily as `${K}Tokens`]: number;
@@ -36,33 +31,71 @@ export interface AwsBedrockKey extends Key, AwsBedrockKeyUsage {
awsLoggingStatus: "unknown" | "disabled" | "enabled";
}
export class AwsBedrockKeyProvider extends KeyProviderBase<AwsBedrockKey> {
readonly service = "aws" as const;
/**
* 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;
protected readonly keys: AwsBedrockKey[] = [];
export class AwsBedrockKeyProvider implements KeyProvider<AwsBedrockKey> {
readonly service = "aws";
private keys: AwsBedrockKey[] = [];
private checker?: AwsKeyChecker;
protected log = logger.child({ module: "key-provider", service: this.service });
private log = logger.child({ module: "key-provider", service: this.service });
public async init() {
const storeName = this.store.constructor.name;
const loadedKeys = await this.store.load();
if (loadedKeys.length === 0) {
return this.log.warn({ via: storeName }, "No AWS credentials found.");
constructor() {
const keyConfig = config.awsCredentials?.trim();
if (!keyConfig) {
this.log.warn(
"AWS_CREDENTIALS is not set. AWS Bedrock 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: AwsBedrockKey = {
key,
service: this.service,
modelFamilies: ["aws-claude"],
isDisabled: false,
isRevoked: false,
promptCount: 0,
lastUsed: 0,
rateLimitedAt: 0,
rateLimitedUntil: 0,
awsLoggingStatus: "unknown",
hash: `aws-${crypto
.createHash("sha256")
.update(key)
.digest("hex")
.slice(0, 8)}`,
lastChecked: 0,
["aws-claudeTokens"]: 0,
};
this.keys.push(newKey);
}
this.log.info({ keyCount: this.keys.length }, "Loaded AWS Bedrock keys.");
}
this.keys.push(...loadedKeys);
this.log.info(
{ count: this.keys.length, via: storeName },
"Loaded AWS Bedrock keys."
);
public init() {
if (config.checkKeys) {
this.checker = new AwsKeyChecker(this.keys, this.update.bind(this));
this.checker.start();
}
}
public list() {
return this.keys.map((k) => Object.freeze({ ...k, key: undefined }));
}
public get(_model: AwsBedrockModel) {
const availableKeys = this.keys.filter((k) => {
const isNotLogged = k.awsLoggingStatus === "disabled";
@@ -96,14 +129,26 @@ export class AwsBedrockKeyProvider extends KeyProviderBase<AwsBedrockKey> {
const selectedKey = keysByPriority[0];
selectedKey.lastUsed = now;
selectedKey.rateLimitedAt = now;
// Intended to throttle the queue processor as otherwise it will just
// flood the API with requests and we want to wait a sec to see if we're
// going to get a rate limit error on this key.
selectedKey.rateLimitedUntil = now + KEY_REUSE_DELAY;
this.throttle(selectedKey.hash);
return { ...selectedKey };
}
public disable(key: AwsBedrockKey) {
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<AwsBedrockKey>) {
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;
@@ -111,7 +156,7 @@ export class AwsBedrockKeyProvider extends KeyProviderBase<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.
@@ -148,4 +193,20 @@ export class AwsBedrockKeyProvider extends KeyProviderBase<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);
}
}
@@ -1,43 +0,0 @@
import crypto from "crypto";
import type { AwsBedrockKey, SerializedKey } from "../index";
import { KeySerializerBase } from "../key-serializer-base";
const SERIALIZABLE_FIELDS: (keyof AwsBedrockKey)[] = [
"key",
"service",
"hash",
"promptCount",
"aws-claudeTokens",
];
export type SerializedAwsBedrockKey = SerializedKey &
Partial<Pick<AwsBedrockKey, (typeof SERIALIZABLE_FIELDS)[number]>>;
export class AwsBedrockKeySerializer extends KeySerializerBase<AwsBedrockKey> {
constructor() {
super(SERIALIZABLE_FIELDS);
}
deserialize(serializedKey: SerializedAwsBedrockKey): AwsBedrockKey {
const { key, ...rest } = serializedKey;
return {
key,
service: "aws",
modelFamilies: ["aws-claude"],
isDisabled: false,
isRevoked: false,
promptCount: 0,
lastUsed: 0,
rateLimitedAt: 0,
rateLimitedUntil: 0,
awsLoggingStatus: "unknown",
hash: `aws-${crypto
.createHash("sha256")
.update(key)
.digest("hex")
.slice(0, 8)}`,
lastChecked: 0,
["aws-claudeTokens"]: 0,
...rest,
};
}
}
+149
View File
@@ -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 };
}
}
+215
View File
@@ -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);
}
}
+82 -10
View File
@@ -1,10 +1,82 @@
export { keyPool } from "./key-pool";
export { OPENAI_SUPPORTED_MODELS } from "./openai/provider";
export { ANTHROPIC_SUPPORTED_MODELS } from "./anthropic/provider";
export { GOOGLE_PALM_SUPPORTED_MODELS } from "./palm/provider";
export { AWS_BEDROCK_SUPPORTED_MODELS } from "./aws/provider";
export type { AnthropicKey } from "./anthropic/provider";
export type { OpenAIKey } from "./openai/provider";
export type { GooglePalmKey } from "./palm/provider";
export type { AwsBedrockKey } from "./aws/provider";
export * from "./types";
import { OpenAIModel } from "./openai/provider";
import { AnthropicModel } from "./anthropic/provider";
import { GooglePalmModel } from "./palm/provider";
import { AwsBedrockModel } from "./aws/provider";
import { AzureOpenAIModel } from "./azure/provider";
import { KeyPool } from "./key-pool";
import type { ModelFamily } from "../models";
/** The request and response format used by a model's API. */
export type APIFormat =
| "openai"
| "anthropic"
| "google-palm"
| "openai-text"
| "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"
| "azure";
export type Model =
| OpenAIModel
| AnthropicModel
| GooglePalmModel
| AwsBedrockModel
| AzureOpenAIModel;
export interface Key {
/** The API key itself. Never log this, use `hash` instead. */
readonly key: string;
/** The service that this key is for. */
service: LLMService;
/** The model families that this key has access to. */
modelFamilies: ModelFamily[];
/** Whether this key is currently disabled, meaning its quota has been exceeded or it has been revoked. */
isDisabled: boolean;
/** Whether this key specifically has been revoked. */
isRevoked: boolean;
/** The number of prompts that have been sent with this key. */
promptCount: number;
/** The time at which this key was last used. */
lastUsed: number;
/** The time at which this key was last checked. */
lastChecked: number;
/** Hash of the key, for logging and to find the key in the pool. */
hash: string;
}
/*
KeyPool and KeyProvider's similarities are a relic of the old design where
there was only a single KeyPool for OpenAI keys. Now that there are multiple
supported services, the service-specific functionality has been moved to
KeyProvider and KeyPool is just a wrapper around multiple KeyProviders,
delegating to the appropriate one based on the model requested.
Existing code will continue to call methods on KeyPool, which routes them to
the appropriate KeyProvider or returns data aggregated across all KeyProviders
for service-agnostic functionality.
*/
export interface KeyProvider<T extends Key = Key> {
readonly service: LLMService;
init(): void;
get(model: Model): T;
list(): Omit<T, "key">[];
disable(key: T): void;
update(hash: string, update: Partial<T>): void;
available(): number;
incrementUsage(hash: string, model: string, tokens: number): void;
getLockoutPeriod(model: ModelFamily): number;
markRateLimited(hash: string): void;
recheck(): void;
}
export const keyPool = new KeyPool();
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";
+57 -20
View File
@@ -1,16 +1,19 @@
import { AxiosError } from "axios";
import pino from "pino";
import { logger } from "../../logger";
import { Key } from "./types";
import { Key } from "./index";
import { AxiosError } from "axios";
type KeyCheckerOptions = {
type KeyCheckerOptions<TKey extends Key = Key> = {
service: string;
keyCheckPeriod: number;
minCheckInterval: number;
recurringChecksEnabled?: boolean;
updateKey: (hash: string, props: Partial<TKey>) => void;
};
export abstract class KeyCheckerBase<TKey extends Key> {
protected readonly service: string;
protected readonly RECURRING_CHECKS_ENABLED: boolean;
/** Minimum time in between any two key checks. */
protected readonly MIN_CHECK_INTERVAL: number;
/**
@@ -19,16 +22,19 @@ export abstract class KeyCheckerBase<TKey extends Key> {
* than this.
*/
protected readonly KEY_CHECK_PERIOD: number;
protected readonly updateKey: (hash: string, props: Partial<TKey>) => void;
protected readonly keys: TKey[] = [];
protected log: pino.Logger;
protected timeout?: NodeJS.Timeout;
protected lastCheck = 0;
protected constructor(keys: TKey[], opts: KeyCheckerOptions) {
protected constructor(keys: TKey[], opts: KeyCheckerOptions<TKey>) {
const { service, keyCheckPeriod, minCheckInterval } = opts;
this.keys = keys;
this.KEY_CHECK_PERIOD = keyCheckPeriod;
this.MIN_CHECK_INTERVAL = minCheckInterval;
this.RECURRING_CHECKS_ENABLED = opts.recurringChecksEnabled ?? true;
this.updateKey = opts.updateKey;
this.service = service;
this.log = logger.child({ module: "key-checker", service });
}
@@ -52,31 +58,34 @@ export abstract class KeyCheckerBase<TKey extends Key> {
* the minimum check interval.
*/
public scheduleNextCheck() {
// Gives each concurrent check a correlation ID to make logs less confusing.
const callId = Math.random().toString(36).slice(2, 8);
const timeoutId = this.timeout?.[Symbol.toPrimitive]?.();
const checkLog = this.log.child({ callId, timeoutId });
const enabledKeys = this.keys.filter((key) => !key.isDisabled);
checkLog.debug({ enabled: enabledKeys.length }, "Scheduling next check...");
const uncheckedKeys = enabledKeys.filter((key) => !key.lastChecked);
const numEnabled = enabledKeys.length;
const numUnchecked = uncheckedKeys.length;
clearTimeout(this.timeout);
this.timeout = undefined;
if (enabledKeys.length === 0) {
checkLog.warn("All keys are disabled. Key checker stopping.");
if (!numEnabled) {
checkLog.warn("All keys are disabled. Stopping.");
return;
}
// Perform startup checks for any keys that haven't been checked yet.
const uncheckedKeys = enabledKeys.filter((key) => !key.lastChecked);
checkLog.debug({ unchecked: uncheckedKeys.length }, "# of unchecked keys");
if (uncheckedKeys.length > 0) {
const keysToCheck = uncheckedKeys.slice(0, 12);
checkLog.debug({ numEnabled, numUnchecked }, "Scheduling next check...");
if (numUnchecked > 0) {
const keycheckBatch = uncheckedKeys.slice(0, 12);
this.timeout = setTimeout(async () => {
try {
await Promise.all(keysToCheck.map((key) => this.checkKey(key)));
await Promise.all(keycheckBatch.map((key) => this.checkKey(key)));
} catch (error) {
this.log.error({ error }, "Error checking one or more keys.");
checkLog.error({ error }, "Error checking one or more keys.");
}
checkLog.info("Batch complete.");
this.scheduleNextCheck();
@@ -84,11 +93,18 @@ export abstract class KeyCheckerBase<TKey extends Key> {
checkLog.info(
{
batch: keysToCheck.map((k) => k.hash),
remaining: uncheckedKeys.length - keysToCheck.length,
batch: keycheckBatch.map((k) => k.hash),
remaining: uncheckedKeys.length - keycheckBatch.length,
newTimeoutId: this.timeout?.[Symbol.toPrimitive]?.(),
},
"Scheduled batch check."
"Scheduled batch of initial checks."
);
return;
}
if (!this.RECURRING_CHECKS_ENABLED) {
checkLog.info(
"Initial checks complete and recurring checks are disabled for this service. Stopping."
);
return;
}
@@ -106,14 +122,35 @@ export abstract class KeyCheckerBase<TKey extends Key> {
);
const delay = nextCheck - Date.now();
this.timeout = setTimeout(() => this.checkKey(oldestKey), delay);
this.timeout = setTimeout(
() => this.checkKey(oldestKey).then(() => this.scheduleNextCheck()),
delay
);
checkLog.debug(
{ key: oldestKey.hash, nextCheck: new Date(nextCheck), delay },
"Scheduled single key check."
"Scheduled next recurring check."
);
}
protected abstract checkKey(key: TKey): Promise<void>;
public async checkKey(key: TKey): Promise<void> {
if (key.isDisabled) {
this.log.warn({ key: key.hash }, "Skipping check for disabled key.");
this.scheduleNextCheck();
return;
}
this.log.debug({ key: key.hash }, "Checking key...");
try {
await this.testKeyOrFail(key);
} catch (error) {
this.updateKey(key.hash, {});
this.handleAxiosError(key, error as AxiosError);
}
this.lastCheck = Date.now();
}
protected abstract testKeyOrFail(key: TKey): Promise<void>;
protected abstract handleAxiosError(key: TKey, error: AxiosError): void;
}
+58 -48
View File
@@ -4,42 +4,44 @@ import os from "os";
import schedule from "node-schedule";
import { config } from "../../config";
import { logger } from "../../logger";
import { KeyProviderBase } from "./key-provider-base";
import { getSerializer } from "./serializers";
import { FirebaseKeyStore, MemoryKeyStore } from "./stores";
import { AnthropicKeyProvider } from "./anthropic/provider";
import { OpenAIKeyProvider } from "./openai/provider";
import { Key, Model, KeyProvider, LLMService } from "./index";
import { AnthropicKeyProvider, AnthropicKeyUpdate } from "./anthropic/provider";
import { OpenAIKeyProvider, OpenAIKeyUpdate } from "./openai/provider";
import { GooglePalmKeyProvider } from "./palm/provider";
import { AwsBedrockKeyProvider } from "./aws/provider";
import { Key, KeyStore, LLMService, Model, ServiceToKey } from "./types";
import { ModelFamily } from "../models";
import { assertNever } from "../utils";
import { AzureOpenAIKeyProvider } from "./azure/provider";
type AllowedPartial = OpenAIKeyUpdate | AnthropicKeyUpdate;
export class KeyPool {
private keyProviders: KeyProviderBase[] = [];
private keyProviders: KeyProvider[] = [];
private recheckJobs: Partial<Record<LLMService, schedule.Job | null>> = {
openai: null,
};
constructor() {
this.keyProviders.push(
new OpenAIKeyProvider(createKeyStore("openai")),
new AnthropicKeyProvider(createKeyStore("anthropic")),
new GooglePalmKeyProvider(createKeyStore("google-palm")),
new AwsBedrockKeyProvider(createKeyStore("aws"))
);
this.keyProviders.push(new OpenAIKeyProvider());
this.keyProviders.push(new AnthropicKeyProvider());
this.keyProviders.push(new GooglePalmKeyProvider());
this.keyProviders.push(new AwsBedrockKeyProvider());
this.keyProviders.push(new AzureOpenAIKeyProvider());
}
public async init() {
await Promise.all(this.keyProviders.map((p) => p.init()));
public init() {
this.keyProviders.forEach((provider) => provider.init());
const availableKeys = this.available("all");
if (availableKeys === 0) {
throw new Error("No keys loaded, the application cannot start.");
throw new Error(
"No keys loaded. Ensure that at least one key is configured."
);
}
this.scheduleRecheck();
}
public get(model: Model): Key {
const service = this.getService(model);
const service = this.getServiceForModel(model);
return this.getKeyProvider(service).get(model);
}
@@ -61,7 +63,7 @@ export class KeyPool {
}
}
public update<T extends Key>(key: T, props: Partial<T>): void {
public update(key: Key, props: AllowedPartial): void {
const service = this.getKeyProvider(key.service);
service.update(key.hash, props);
}
@@ -69,7 +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);
}
@@ -79,9 +81,9 @@ export class KeyPool {
provider.incrementUsage(key.hash, model, tokens);
}
public getLockoutPeriod(model: Model): number {
const service = this.getService(model);
return this.getKeyProvider(service).getLockoutPeriod(model);
public getLockoutPeriod(family: ModelFamily): number {
const service = this.getServiceForModelFamily(family);
return this.getKeyProvider(service).getLockoutPeriod(family);
}
public markRateLimited(key: Key): void {
@@ -106,8 +108,12 @@ export class KeyPool {
provider.recheck();
}
private getService(model: Model): LLMService {
if (model.startsWith("gpt") || model.startsWith("text-embedding-ada")) {
private getServiceForModel(model: Model): LLMService {
if (
model.startsWith("gpt") ||
model.startsWith("text-embedding-ada") ||
model.startsWith("dall-e")
) {
// https://platform.openai.com/docs/models/model-endpoint-compatibility
return "openai";
} else if (model.startsWith("claude-")) {
@@ -120,11 +126,37 @@ 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 getKeyProvider(service: LLMService): KeyProviderBase {
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)!;
}
@@ -153,25 +185,3 @@ export class KeyPool {
this.recheckJobs.openai = job;
}
}
function createKeyStore<S extends LLMService>(
service: S
): KeyStore<ServiceToKey[S]> {
const serializer = getSerializer(service);
switch (config.persistenceProvider) {
case "memory":
return new MemoryKeyStore(service, serializer);
case "firebase_rtdb":
return new FirebaseKeyStore(service, serializer);
default:
throw new Error(`Unknown store type: ${config.persistenceProvider}`);
}
}
export let keyPool: KeyPool;
export async function init() {
keyPool = new KeyPool();
await keyPool.init();
}
@@ -1,65 +0,0 @@
import { logger } from "../../logger";
import { Key, KeyStore, LLMService, Model } from "./types";
export abstract class KeyProviderBase<K extends Key = Key> {
public abstract readonly service: LLMService;
protected abstract readonly keys: K[];
protected abstract log: typeof logger;
protected readonly store: KeyStore<K>;
public constructor(keyStore: KeyStore<K>) {
this.store = keyStore;
}
public abstract init(): Promise<void>;
public addKey(key: K): void {
this.keys.push(key);
this.store.add(key);
}
public abstract get(model: Model): K;
/**
* Returns a list of all keys, with the actual key value removed. Don't
* mutate the returned objects; use `update` instead to ensure the changes
* are synced to the key store.
*/
public list(): Omit<K, "key">[] {
return this.keys.map((k) => Object.freeze({ ...k, key: undefined }));
}
public disable(key: K): void {
const keyFromPool = this.keys.find((k) => k.hash === key.hash);
if (!keyFromPool || keyFromPool.isDisabled) return;
this.update(key.hash, { isDisabled: true } as Partial<K>, true);
this.log.warn({ key: key.hash }, "Key disabled");
}
public update(hash: string, update: Partial<K>, force = false): void {
const key = this.keys.find((k) => k.hash === hash);
if (!key) {
throw new Error(`No key with hash ${hash}`);
}
Object.assign(key, { lastChecked: Date.now(), ...update });
this.store.update(hash, update, force);
}
public available(): number {
return this.keys.filter((k) => !k.isDisabled).length;
}
public abstract incrementUsage(
hash: string,
model: string,
tokens: number
): void;
public abstract getLockoutPeriod(model: Model): number;
public abstract markRateLimited(hash: string): void;
public abstract recheck(): void;
}
@@ -1,31 +0,0 @@
import { Key, KeySerializer, SerializedKey } from "./types";
export abstract class KeySerializerBase<K extends Key>
implements KeySerializer<K>
{
protected constructor(protected serializableFields: (keyof K)[]) {}
serialize(keyObj: K): SerializedKey {
return {
...Object.fromEntries(
this.serializableFields
.map((f) => [f, keyObj[f]])
.filter(([, v]) => v !== undefined)
),
key: keyObj.key,
};
}
partialSerialize(key: string, update: Partial<K>): Partial<SerializedKey> {
return {
...Object.fromEntries(
this.serializableFields
.map((f) => [f, update[f]])
.filter(([, v]) => v !== undefined)
),
key,
};
}
abstract deserialize(serializedKey: SerializedKey): K;
}
+45 -60
View File
@@ -2,6 +2,7 @@ import axios, { AxiosError } from "axios";
import type { OpenAIModelFamily } from "../../models";
import { KeyCheckerBase } from "../key-checker-base";
import type { OpenAIKey, OpenAIKeyProvider } from "./provider";
import { getOpenAIModelFamily } from "../../models";
const MIN_CHECK_INTERVAL = 3 * 1000; // 3 seconds
const KEY_CHECK_PERIOD = 60 * 60 * 1000; // 1 hour
@@ -26,65 +27,41 @@ type UpdateFn = typeof OpenAIKeyProvider.prototype.update;
export class OpenAIKeyChecker extends KeyCheckerBase<OpenAIKey> {
private readonly cloneKey: CloneFn;
private readonly updateKey: UpdateFn;
constructor(keys: OpenAIKey[], cloneFn: CloneFn, updateKey: UpdateFn) {
super(keys, {
service: "openai",
keyCheckPeriod: KEY_CHECK_PERIOD,
minCheckInterval: MIN_CHECK_INTERVAL,
recurringChecksEnabled: false,
updateKey,
});
this.cloneKey = cloneFn;
this.updateKey = updateKey;
}
protected async checkKey(key: OpenAIKey) {
if (key.isDisabled) {
this.log.warn({ key: key.hash }, "Skipping check for disabled key.");
this.scheduleNextCheck();
return;
}
this.log.debug({ key: key.hash }, "Checking key...");
let isInitialCheck = !key.lastChecked;
try {
// We only need to check for provisioned models on the initial check.
if (isInitialCheck) {
const [provisionedModels, livenessTest] = await Promise.all([
this.getProvisionedModels(key),
this.testLiveness(key),
this.maybeCreateOrganizationClones(key),
]);
const updates = {
modelFamilies: provisionedModels,
isTrial: livenessTest.rateLimit <= 250,
};
this.updateKey(key.hash, updates);
} else {
// No updates needed as models and trial status generally don't change.
const [_livenessTest] = await Promise.all([this.testLiveness(key)]);
this.updateKey(key.hash, {});
}
this.log.info(
{ key: key.hash, models: key.modelFamilies, trial: key.isTrial },
"Key check complete."
);
} catch (error) {
// touch the key so we don't check it again for a while
protected async testKeyOrFail(key: OpenAIKey) {
// We only need to check for provisioned models on the initial check.
const isInitialCheck = !key.lastChecked;
if (isInitialCheck) {
const [provisionedModels, livenessTest] = await Promise.all([
this.getProvisionedModels(key),
this.testLiveness(key),
this.maybeCreateOrganizationClones(key),
]);
const updates = {
modelFamilies: provisionedModels,
isTrial: livenessTest.rateLimit <= 250,
};
this.updateKey(key.hash, updates);
} else {
// No updates needed as models and trial status generally don't change.
const [_livenessTest] = await Promise.all([this.testLiveness(key)]);
this.updateKey(key.hash, {});
this.handleAxiosError(key, error as AxiosError);
}
this.lastCheck = Date.now();
// Only enqueue the next check if this wasn't a startup check, since those
// are batched together elsewhere.
if (!isInitialCheck) {
this.log.info(
{ key: key.hash },
"Recurring keychecks are disabled, no-op."
);
// this.scheduleNextCheck();
}
this.log.info(
{ key: key.hash, models: key.modelFamilies, trial: key.isTrial },
"Checked key."
);
}
private async getProvisionedModels(
@@ -94,29 +71,26 @@ export class OpenAIKeyChecker extends KeyCheckerBase<OpenAIKey> {
const { data } = await axios.get<GetModelsResponse>(GET_MODELS_URL, opts);
const models = data.data;
const families: OpenAIModelFamily[] = [];
if (models.some(({ id }) => id.startsWith("gpt-3.5-turbo"))) {
families.push("turbo");
}
const families = new Set<OpenAIModelFamily>();
models.forEach(({ id }) => families.add(getOpenAIModelFamily(id, "turbo")));
if (models.some(({ id }) => id.startsWith("gpt-4"))) {
families.push("gpt4");
}
if (models.some(({ id }) => id.startsWith("gpt-4-32k"))) {
families.push("gpt4-32k");
}
// as of 2023-11-18, many keys no longer return the dalle3 model but still
// have access to it via the api for whatever reason.
// if (families.has("dall-e") && !models.find(({ id }) => id === "dall-e-3")) {
// families.delete("dall-e");
// }
// We want to update the key's model families here, but we don't want to
// update its `lastChecked` timestamp because we need to let the liveness
// check run before we can consider the key checked.
const familiesArray = [...families];
const keyFromPool = this.keys.find((k) => k.hash === key.hash)!;
this.updateKey(key.hash, {
modelFamilies: families,
modelFamilies: familiesArray,
lastChecked: keyFromPool.lastChecked,
});
return families;
return familiesArray;
}
private async maybeCreateOrganizationClones(key: OpenAIKey) {
@@ -140,6 +114,17 @@ export class OpenAIKeyChecker extends KeyCheckerBase<OpenAIKey> {
.filter(({ is_default }) => !is_default)
.map(({ id }) => id);
this.cloneKey(key.hash, ids);
// It's possible that the keychecker may be stopped if all non-cloned keys
// happened to be unusable, in which case this clnoe will never be checked
// unless we restart the keychecker.
if (!this.timeout) {
this.log.warn(
{ parent: key.hash },
"Restarting key checker to check cloned keys."
);
this.scheduleNextCheck();
}
}
protected handleAxiosError(key: OpenAIKey, error: AxiosError) {
+193 -103
View File
@@ -1,23 +1,26 @@
/* Manages OpenAI API keys. Tracks usage, disables expired keys, and provides
round-robin access to keys. Keys are stored in the OPENAI_KEY environment
variable as a comma-separated list of keys. */
import crypto from "crypto";
import { IncomingHttpHeaders } from "http";
import http from "http";
import { Key, KeyProvider, Model } from "../index";
import { config } from "../../../config";
import { logger } from "../../../logger";
import { getOpenAIModelFamily, OpenAIModelFamily } from "../../models";
import { Key, Model } from "../types";
import { OpenAIKeyChecker } from "./checker";
import { KeyProviderBase } from "../key-provider-base";
import { getOpenAIModelFamily, OpenAIModelFamily } from "../../models";
const KEY_REUSE_DELAY = 1000;
export const OPENAI_SUPPORTED_MODELS = [
"gpt-3.5-turbo",
"gpt-3.5-turbo-instruct",
"gpt-4",
"gpt-4-32k",
"text-embedding-ada-002",
] as const;
export type OpenAIModel = (typeof OPENAI_SUPPORTED_MODELS)[number];
export type OpenAIModel =
| "gpt-3.5-turbo"
| "gpt-3.5-turbo-instruct"
| "gpt-4"
| "gpt-4-32k"
| "gpt-4-1106"
| "text-embedding-ada-002"
| "dall-e-2"
| "dall-e-3"
// Flattening model families instead of using a nested object for easier
// cloning.
type OpenAIKeyUsage = {
[K in OpenAIModelFamily as `${K}Tokens`]: number;
};
@@ -59,32 +62,77 @@ export interface OpenAIKey extends Key, OpenAIKeyUsage {
* tokens.
*/
rateLimitTokensReset: number;
/**
* This key's maximum request rate for GPT-4, per minute.
*/
gpt4Rpm: number;
}
export class OpenAIKeyProvider extends KeyProviderBase<OpenAIKey> {
export type OpenAIKeyUpdate = Omit<
Partial<OpenAIKey>,
"key" | "hash" | "promptCount"
>;
/**
* 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 = 1000;
export class OpenAIKeyProvider implements KeyProvider<OpenAIKey> {
readonly service = "openai" as const;
protected readonly keys: OpenAIKey[] = [];
private keys: OpenAIKey[] = [];
private checker?: OpenAIKeyChecker;
protected log = logger.child({ module: "key-provider", service: this.service });
private log = logger.child({ module: "key-provider", service: this.service });
public async init() {
const storeName = this.store.constructor.name;
const loadedKeys = await this.store.load();
// TODO: after key management UI, keychecker should always be enabled
// because keys may be added after initialization.
if (loadedKeys.length === 0) {
return this.log.warn({ via: storeName }, "No OpenAI keys found.");
constructor() {
const keyString = config.openaiKey?.trim();
if (!keyString) {
this.log.warn("OPENAI_KEY is not set. OpenAI API will not be available.");
return;
}
let bareKeys: string[];
bareKeys = keyString.split(",").map((k) => k.trim());
bareKeys = [...new Set(bareKeys)];
for (const k of bareKeys) {
const newKey: OpenAIKey = {
key: k,
service: "openai" as const,
modelFamilies: [
"turbo" as const,
"gpt4" as const,
"gpt4-turbo" as const,
],
isTrial: false,
isDisabled: false,
isRevoked: false,
isOverQuota: false,
lastUsed: 0,
lastChecked: 0,
promptCount: 0,
hash: `oai-${crypto
.createHash("sha256")
.update(k)
.digest("hex")
.slice(0, 8)}`,
rateLimitedAt: 0,
rateLimitRequestsReset: 0,
rateLimitTokensReset: 0,
turboTokens: 0,
gpt4Tokens: 0,
"gpt4-32kTokens": 0,
"gpt4-turboTokens": 0,
"dall-eTokens": 0,
gpt4Rpm: 0,
};
this.keys.push(newKey);
}
this.log.info({ keyCount: this.keys.length }, "Loaded OpenAI keys.");
}
this.keys.push(...loadedKeys);
this.log.info(
{ count: this.keys.length, via: storeName },
"Loaded OpenAI keys."
);
public init() {
if (config.checkKeys) {
const cloneFn = this.clone.bind(this);
const updateFn = this.update.bind(this);
@@ -93,26 +141,33 @@ export class OpenAIKeyProvider extends KeyProviderBase<OpenAIKey> {
}
}
/**
* Returns a list of all keys, with the key field removed.
* Don't mutate returned keys, use a KeyPool method instead.
**/
public list() {
return this.keys.map((key) => {
return Object.freeze({
...key,
key: undefined,
});
});
}
public get(model: Model) {
const neededFamily = getOpenAIModelFamily(model);
const excludeTrials = model === "text-embedding-ada-002";
const availableKeys = this.keys.filter(
// Allow keys which...
// Allow keys which
(key) =>
!key.isDisabled && // ...are not disabled
key.modelFamilies.includes(neededFamily) && // ...have access to the model
(!excludeTrials || !key.isTrial) // ...and are not trials (if applicable)
!key.isDisabled && // are not disabled
key.modelFamilies.includes(neededFamily) && // have access to the model
(!excludeTrials || !key.isTrial) // and are not trials (if applicable)
);
if (availableKeys.length === 0) {
throw new Error(`No active keys available for ${neededFamily} models.`);
}
if (!config.allowedModelFamilies.includes(neededFamily)) {
throw new Error(
`Proxy operator has disabled access to ${neededFamily} models.`
);
throw new Error(`No keys available for model family '${neededFamily}'.`);
}
// Select a key, from highest priority to lowest priority:
@@ -156,31 +211,18 @@ export class OpenAIKeyProvider extends KeyProviderBase<OpenAIKey> {
return a.lastUsed - b.lastUsed;
});
// logger.debug(
// {
// byPriority: keysByPriority.map((k) => ({
// hash: k.hash,
// isRateLimited: now - k.rateLimitedAt < rateLimitThreshold,
// modelFamilies: k.modelFamilies,
// })),
// },
// "Keys sorted by priority"
// );
const selectedKey = keysByPriority[0];
selectedKey.lastUsed = now;
// When a key is selected, we rate-limit it for a brief period of time to
// prevent the queue processor from immediately flooding it with requests
// while the initial request is still being processed (which is when we will
// get new rate limit headers).
// Instead, we will let a request through every second until the key
// becomes fully saturated and locked out again.
selectedKey.rateLimitedAt = now;
selectedKey.rateLimitRequestsReset = KEY_REUSE_DELAY;
this.throttle(selectedKey.hash);
return { ...selectedKey };
}
/** Called by the key checker to update key information. */
public update(keyHash: string, update: OpenAIKeyUpdate) {
const keyFromPool = this.keys.find((k) => k.hash === keyHash)!;
Object.assign(keyFromPool, { lastChecked: Date.now(), ...update });
}
/** Called by the key checker to create clones of keys for the given orgs. */
public clone(keyHash: string, newOrgIds: string[]) {
const keyFromPool = this.keys.find((k) => k.hash === keyHash)!;
@@ -189,6 +231,8 @@ export class OpenAIKeyProvider extends KeyProviderBase<OpenAIKey> {
...keyFromPool,
organizationId: orgId,
isDisabled: false,
isRevoked: false,
isOverQuota: false,
hash: `oai-${crypto
.createHash("sha256")
.update(keyFromPool.key + orgId)
@@ -202,25 +246,33 @@ export class OpenAIKeyProvider extends KeyProviderBase<OpenAIKey> {
);
return clone;
});
clones.forEach((clone) => this.addKey(clone));
this.keys.push(...clones);
}
/** Disables a key, or does nothing if the key isn't in this pool. */
public disable(key: Key) {
const keyFromPool = this.keys.find((k) => k.hash === key.hash);
if (!keyFromPool || keyFromPool.isDisabled) return;
this.update(key.hash, { isDisabled: true });
this.log.warn({ key: key.hash }, "Key disabled");
}
public available() {
return this.keys.filter((k) => !k.isDisabled).length;
}
/**
* Given a model, returns the period until a key will be available to service
* the request, or returns 0 if a key is ready immediately.
*/
public getLockoutPeriod(model: Model = "gpt-4"): number {
const neededFamily = getOpenAIModelFamily(model);
public getLockoutPeriod(family: OpenAIModelFamily): number {
const activeKeys = this.keys.filter(
(key) => !key.isDisabled && key.modelFamilies.includes(neededFamily)
(key) => !key.isDisabled && key.modelFamilies.includes(family)
);
if (activeKeys.length === 0) {
// If there are no active keys for this model we can't fulfill requests.
// We'll return 0 to let the request through and return an error,
// otherwise the request will be stuck in the queue forever.
return 0;
}
// Don't lock out if there are no keys available or the queue will stall.
// Just let it through so the add-key middleware can throw an error.
if (activeKeys.length === 0) return 0;
// A key is rate-limited if its `rateLimitedAt` plus the greater of its
// `rateLimitRequestsReset` and `rateLimitTokensReset` is after the
@@ -233,7 +285,7 @@ export class OpenAIKeyProvider extends KeyProviderBase<OpenAIKey> {
key.rateLimitRequestsReset,
key.rateLimitTokensReset
);
return now < key.rateLimitedAt + resetTime;
return now < key.rateLimitedAt + Math.min(20000, resetTime);
}).length;
const anyNotRateLimited = rateLimitedKeys < activeKeys.length;
@@ -242,14 +294,16 @@ export class OpenAIKeyProvider extends KeyProviderBase<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;
})
);
}
@@ -258,6 +312,10 @@ export class OpenAIKeyProvider extends KeyProviderBase<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) {
@@ -267,35 +325,21 @@ export class OpenAIKeyProvider extends KeyProviderBase<OpenAIKey> {
key[`${getOpenAIModelFamily(model)}Tokens`] += tokens;
}
public updateRateLimits(keyHash: string, headers: IncomingHttpHeaders) {
public updateRateLimits(keyHash: string, headers: http.IncomingHttpHeaders) {
const key = this.keys.find((k) => k.hash === keyHash)!;
const requestsReset = headers["x-ratelimit-reset-requests"];
const tokensReset = headers["x-ratelimit-reset-tokens"];
// Sometimes OpenAI only sends one of the two rate limit headers, it's
// unclear why.
if (requestsReset && typeof requestsReset === "string") {
this.log.debug(
{ key: key.hash, requestsReset },
`Updating rate limit requests reset time`
);
if (typeof requestsReset === "string") {
key.rateLimitRequestsReset = getResetDurationMillis(requestsReset);
}
if (tokensReset && typeof tokensReset === "string") {
this.log.debug(
{ key: key.hash, tokensReset },
`Updating rate limit tokens reset time`
);
if (typeof tokensReset === "string") {
key.rateLimitTokensReset = getResetDurationMillis(tokensReset);
}
if (!requestsReset && !tokensReset) {
this.log.warn(
{ key: key.hash },
`No rate limit headers in OpenAI response; skipping update`
);
this.log.warn({ key: key.hash }, `No ratelimit headers; skipping update`);
return;
}
}
@@ -311,21 +355,67 @@ export class OpenAIKeyProvider extends KeyProviderBase<OpenAIKey> {
});
this.checker?.scheduleNextCheck();
}
/**
* Called when a key is selected for a request, briefly disabling it to
* avoid spamming the API with requests while we wait to learn whether this
* key is already rate limited.
*/
private throttle(hash: string) {
const now = Date.now();
const key = this.keys.find((k) => k.hash === hash)!;
const currentRateLimit =
Math.max(key.rateLimitRequestsReset, key.rateLimitTokensReset) +
key.rateLimitedAt;
const nextRateLimit = now + KEY_REUSE_DELAY;
// Don't throttle if the key is already naturally rate limited.
if (currentRateLimit > nextRateLimit) return;
key.rateLimitedAt = Date.now();
key.rateLimitRequestsReset = KEY_REUSE_DELAY;
}
}
// wip
function calculateRequestsPerMinute(headers: http.IncomingHttpHeaders) {
const requestsLimit = headers["x-ratelimit-limit-requests"];
const requestsReset = headers["x-ratelimit-reset-requests"];
if (typeof requestsLimit !== "string" || typeof requestsReset !== "string") {
return 0;
}
const limit = parseInt(requestsLimit, 10);
const reset = getResetDurationMillis(requestsReset);
// If `reset` is less than one minute, OpenAI specifies the `limit` as an
// integer representing requests per minute. Otherwise it actually means the
// requests per day.
const isPerMinute = reset < 60000;
if (isPerMinute) return limit;
return limit / 1440;
}
/**
* Converts reset string ("21.0032s" or "21ms") to a number of milliseconds.
* Result is clamped to 10s even though the API returns up to 60s, because the
* API returns the time until the entire quota is reset, even if a key may be
* able to fulfill requests before then due to partial resets.
* Converts reset string ("14m25s", "21.0032s", "14ms" or "21ms") to a number of
* milliseconds.
**/
function getResetDurationMillis(resetDuration?: string): number {
const match = resetDuration?.match(/(\d+(\.\d+)?)(s|ms)/);
const match = resetDuration?.match(
/(?:(\d+)m(?!s))?(?:(\d+(?:\.\d+)?)s)?(?:(\d+)ms)?/
);
if (match) {
const [, time, , unit] = match;
const value = parseFloat(time);
const result = unit === "s" ? value * 1000 : value;
return Math.min(result, 10000);
const [, minutes, seconds, milliseconds] = match.map(Number);
const minutesToMillis = (minutes || 0) * 60 * 1000;
const secondsToMillis = (seconds || 0) * 1000;
const millisecondsValue = milliseconds || 0;
return minutesToMillis + secondsToMillis + millisecondsValue;
}
return 0;
}
@@ -1,49 +0,0 @@
import crypto from "crypto";
import type { OpenAIKey, SerializedKey } from "../index";
import { KeySerializerBase } from "../key-serializer-base";
const SERIALIZABLE_FIELDS: (keyof OpenAIKey)[] = [
"key",
"service",
"hash",
"organizationId",
"promptCount",
"gpt4Tokens",
"gpt4-32kTokens",
"turboTokens",
];
export type SerializedOpenAIKey = SerializedKey &
Partial<Pick<OpenAIKey, (typeof SERIALIZABLE_FIELDS)[number]>>;
export class OpenAIKeySerializer extends KeySerializerBase<OpenAIKey> {
constructor() {
super(SERIALIZABLE_FIELDS);
}
deserialize({ key, ...rest }: SerializedOpenAIKey): OpenAIKey {
return {
key,
service: "openai",
modelFamilies: ["turbo" as const, "gpt4" as const],
isTrial: false,
isDisabled: false,
isRevoked: false,
isOverQuota: false,
lastUsed: 0,
lastChecked: 0,
promptCount: 0,
hash: `oai-${crypto
.createHash("sha256")
.update(key)
.digest("hex")
.slice(0, 8)}`,
rateLimitedAt: 0,
rateLimitRequestsReset: 0,
rateLimitTokensReset: 0,
turboTokens: 0,
gpt4Tokens: 0,
"gpt4-32kTokens": 0,
...rest,
};
}
}
+99 -27
View File
@@ -1,14 +1,21 @@
import crypto from "crypto";
import { Key, KeyProvider } from "..";
import { config } from "../../../config";
import { logger } from "../../../logger";
import type { GooglePalmModelFamily } from "../../models";
import { KeyProviderBase } from "../key-provider-base";
import { Key } from "../types";
const RATE_LIMIT_LOCKOUT = 2000;
const KEY_REUSE_DELAY = 500;
// https://developers.generativeai.google.com/models/language
export const GOOGLE_PALM_SUPPORTED_MODELS = ["text-bison-001"] as const;
export type GooglePalmModel = (typeof GOOGLE_PALM_SUPPORTED_MODELS)[number];
export type GooglePalmModel = "text-bison-001";
export type GooglePalmKeyUpdate = Omit<
Partial<GooglePalmKey>,
| "key"
| "hash"
| "lastUsed"
| "promptCount"
| "rateLimitedAt"
| "rateLimitedUntil"
>;
type GooglePalmKeyUsage = {
[K in GooglePalmModelFamily as `${K}Tokens`]: number;
@@ -23,25 +30,62 @@ export interface GooglePalmKey extends Key, GooglePalmKeyUsage {
rateLimitedUntil: number;
}
export class GooglePalmKeyProvider extends KeyProviderBase<GooglePalmKey> {
/**
* Upon being rate limited, a key will be locked out for this many milliseconds
* while we wait for other concurrent requests to finish.
*/
const RATE_LIMIT_LOCKOUT = 2000;
/**
* Upon assigning a key, we will wait this many milliseconds before allowing it
* to be used again. This is to prevent the queue from flooding a key with too
* many requests while we wait to learn whether previous ones succeeded.
*/
const KEY_REUSE_DELAY = 500;
export class GooglePalmKeyProvider implements KeyProvider<GooglePalmKey> {
readonly service = "google-palm";
protected keys: GooglePalmKey[] = [];
protected log = logger.child({ module: "key-provider", service: this.service });
private keys: GooglePalmKey[] = [];
private log = logger.child({ module: "key-provider", service: this.service });
public async init() {
const storeName = this.store.constructor.name;
const loadedKeys = await this.store.load();
if (loadedKeys.length === 0) {
return this.log.warn({ via: storeName }, "No Google PaLM keys found.");
constructor() {
const keyConfig = config.googlePalmKey?.trim();
if (!keyConfig) {
this.log.warn(
"GOOGLE_PALM_KEY is not set. PaLM API will not be available."
);
return;
}
let bareKeys: string[];
bareKeys = [...new Set(keyConfig.split(",").map((k) => k.trim()))];
for (const key of bareKeys) {
const newKey: GooglePalmKey = {
key,
service: this.service,
modelFamilies: ["bison"],
isDisabled: false,
isRevoked: false,
promptCount: 0,
lastUsed: 0,
rateLimitedAt: 0,
rateLimitedUntil: 0,
hash: `plm-${crypto
.createHash("sha256")
.update(key)
.digest("hex")
.slice(0, 8)}`,
lastChecked: 0,
bisonTokens: 0,
};
this.keys.push(newKey);
}
this.log.info({ keyCount: this.keys.length }, "Loaded PaLM keys.");
}
this.keys.push(...loadedKeys);
this.log.info(
{ count: this.keys.length, via: storeName },
"Loaded PaLM keys."
);
public init() {}
public list() {
return this.keys.map((k) => Object.freeze({ ...k, key: undefined }));
}
public get(_model: GooglePalmModel) {
@@ -74,14 +118,26 @@ export class GooglePalmKeyProvider extends KeyProviderBase<GooglePalmKey> {
const selectedKey = keysByPriority[0];
selectedKey.lastUsed = now;
selectedKey.rateLimitedAt = now;
// Intended to throttle the queue processor as otherwise it will just
// flood the API with requests and we want to wait a sec to see if we're
// going to get a rate limit error on this key.
selectedKey.rateLimitedUntil = now + KEY_REUSE_DELAY;
this.throttle(selectedKey.hash);
return { ...selectedKey };
}
public disable(key: GooglePalmKey) {
const keyFromPool = this.keys.find((k) => k.hash === key.hash);
if (!keyFromPool || keyFromPool.isDisabled) return;
keyFromPool.isDisabled = true;
this.log.warn({ key: key.hash }, "Key disabled");
}
public update(hash: string, update: Partial<GooglePalmKey>) {
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;
@@ -89,7 +145,7 @@ export class GooglePalmKeyProvider extends KeyProviderBase<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.
@@ -122,4 +178,20 @@ export class GooglePalmKeyProvider extends KeyProviderBase<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);
}
}
@@ -1,42 +0,0 @@
import crypto from "crypto";
import type { GooglePalmKey, SerializedKey } from "../index";
import { KeySerializerBase } from "../key-serializer-base";
const SERIALIZABLE_FIELDS: (keyof GooglePalmKey)[] = [
"key",
"service",
"hash",
"promptCount",
"bisonTokens",
];
export type SerializedGooglePalmKey = SerializedKey &
Partial<Pick<GooglePalmKey, (typeof SERIALIZABLE_FIELDS)[number]>>;
export class GooglePalmKeySerializer extends KeySerializerBase<GooglePalmKey> {
constructor() {
super(SERIALIZABLE_FIELDS);
}
deserialize(serializedKey: SerializedGooglePalmKey): GooglePalmKey {
const { key, ...rest } = serializedKey;
return {
key,
service: "google-palm" as const,
modelFamilies: ["bison"],
isDisabled: false,
isRevoked: false,
promptCount: 0,
lastUsed: 0,
rateLimitedAt: 0,
rateLimitedUntil: 0,
hash: `plm-${crypto
.createHash("sha256")
.update(key)
.digest("hex")
.slice(0, 8)}`,
lastChecked: 0,
bisonTokens: 0,
...rest,
};
}
}
-36
View File
@@ -1,36 +0,0 @@
import { assertNever } from "../utils";
import {
Key,
KeySerializer,
LLMService,
SerializedKey,
ServiceToKey,
} from "./types";
import { OpenAIKeySerializer } from "./openai/serializer";
import { AnthropicKeySerializer } from "./anthropic/serializer";
import { GooglePalmKeySerializer } from "./palm/serializer";
import { AwsBedrockKeySerializer } from "./aws/serializer";
export function assertSerializedKey(k: any): asserts k is SerializedKey {
if (typeof k !== "object" || !k || typeof (k as any).key !== "string") {
throw new Error("Invalid serialized key data");
}
}
export function getSerializer<S extends LLMService>(
service: S
): KeySerializer<ServiceToKey[S]>;
export function getSerializer(service: LLMService): KeySerializer<Key> {
switch (service) {
case "openai":
return new OpenAIKeySerializer();
case "anthropic":
return new AnthropicKeySerializer();
case "google-palm":
return new GooglePalmKeySerializer();
case "aws":
return new AwsBedrockKeySerializer();
default:
assertNever(service);
}
}
@@ -1,125 +0,0 @@
import firebase from "firebase-admin";
import { config, getFirebaseApp } from "../../../config";
import { logger } from "../../../logger";
import { assertSerializedKey } from "../serializers";
import type {
Key,
KeySerializer,
KeyStore,
LLMService,
SerializedKey,
} from "../types";
import { MemoryKeyStore } from "./index";
export class FirebaseKeyStore<K extends Key> implements KeyStore<K> {
private readonly db: firebase.database.Database;
private readonly log: typeof logger;
private readonly pendingUpdates: Map<string, Partial<SerializedKey>>;
private readonly root: string;
private readonly serializer: KeySerializer<K>;
private readonly service: LLMService;
private flushInterval: NodeJS.Timeout | null = null;
private keysRef: firebase.database.Reference | null = null;
constructor(
service: LLMService,
serializer: KeySerializer<K>,
app = getFirebaseApp()
) {
this.db = firebase.database(app);
this.log = logger.child({ module: "firebase-key-store", service });
this.root = `keys/${config.firebaseRtdbRoot.toLowerCase()}/${service}`;
this.serializer = serializer;
this.service = service;
this.pendingUpdates = new Map();
this.scheduleFlush();
}
public async load(isMigrating = false): Promise<K[]> {
const keysRef = this.db.ref(this.root);
const snapshot = await keysRef.once("value");
const keys = snapshot.val();
this.keysRef = keysRef;
if (!keys) {
if (isMigrating) return [];
this.log.warn("No keys found in Firebase. Migrating from environment.");
await this.migrate();
return this.load(true);
}
return Object.values(keys).map((k) => {
assertSerializedKey(k);
return this.serializer.deserialize(k);
});
}
public add(key: K) {
const serialized = this.serializer.serialize(key);
this.pendingUpdates.set(key.hash, serialized);
this.forceFlush();
}
public update(id: string, update: Partial<K>, force = false) {
const existing = this.pendingUpdates.get(id) ?? {};
Object.assign(existing, this.serializer.partialSerialize(id, update));
this.pendingUpdates.set(id, existing);
if (force) this.forceFlush();
}
private forceFlush() {
if (this.flushInterval) clearInterval(this.flushInterval);
this.flushInterval = setTimeout(() => this.flush(), 0);
}
private scheduleFlush() {
if (this.flushInterval) clearInterval(this.flushInterval);
this.flushInterval = setInterval(() => this.flush(), 1000 * 60 * 5);
}
private async flush() {
if (!this.keysRef) {
this.log.warn(
{ pendingUpdates: this.pendingUpdates.size },
"Database not loaded yet. Skipping flush."
);
return this.scheduleFlush();
}
if (this.pendingUpdates.size === 0) {
this.log.debug("No pending key updates to flush.");
return this.scheduleFlush();
}
const updates: Record<string, Partial<SerializedKey>> = {};
this.pendingUpdates.forEach((v, k) => (updates[k] = v));
this.pendingUpdates.clear();
console.log(updates);
await this.keysRef.update(updates);
this.log.debug(
{ count: Object.keys(updates).length },
"Flushed pending key updates."
);
this.scheduleFlush();
}
private async migrate(): Promise<SerializedKey[]> {
const keysRef = this.db.ref(this.root);
const envStore = new MemoryKeyStore<K>(this.service, this.serializer);
const keys = await envStore.load();
if (keys.length === 0) {
this.log.warn("No keys found in environment or Firebase.");
return [];
}
const updates: Record<string, SerializedKey> = {};
keys.forEach((k) => (updates[k.hash] = this.serializer.serialize(k)));
await keysRef.update(updates);
this.log.info({ count: keys.length }, "Migrated keys from environment.");
return Object.values(updates);
}
}
@@ -1,2 +0,0 @@
export { FirebaseKeyStore } from "./firebase";
export { MemoryKeyStore } from "./memory";
@@ -1,41 +0,0 @@
import { assertNever } from "../../utils";
import { Key, KeySerializer, KeyStore, LLMService } from "../types";
export class MemoryKeyStore<K extends Key> implements KeyStore<K> {
private readonly env: string;
private readonly serializer: KeySerializer<K>;
constructor(service: LLMService, serializer: KeySerializer<K>) {
switch (service) {
case "anthropic":
this.env = "ANTHROPIC_KEY";
break;
case "openai":
this.env = "OPENAI_KEY";
break;
case "google-palm":
this.env = "GOOGLE_PALM_KEY";
break;
case "aws":
this.env = "AWS_CREDENTIALS";
break;
default:
assertNever(service);
}
this.serializer = serializer;
}
public async load() {
let envKeys: string[];
envKeys = [
...new Set(process.env[this.env]?.split(",").map((k) => k.trim())),
];
return envKeys
.filter((k) => k)
.map((k) => this.serializer.deserialize({ key: k }));
}
public add() {}
public update() {}
}
-64
View File
@@ -1,64 +0,0 @@
import type { OpenAIKey, OpenAIModel } from "./openai/provider";
import type { AnthropicKey, AnthropicModel } from "./anthropic/provider";
import type { GooglePalmKey, GooglePalmModel } from "./palm/provider";
import type { AwsBedrockKey, AwsBedrockModel } from "./aws/provider";
import type { ModelFamily } from "../models";
/** The request and response format used by a model's API. */
export type APIFormat = "openai" | "anthropic" | "google-palm" | "openai-text";
/**
* The service that a model is hosted on; distinct because services like AWS
* provide APIs from other service providers, but have their own authentication
* and key management.
*/
export type LLMService = "openai" | "anthropic" | "google-palm" | "aws";
export type Model =
| OpenAIModel
| AnthropicModel
| GooglePalmModel
| AwsBedrockModel;
type AllKeys = OpenAIKey | AnthropicKey | GooglePalmKey | AwsBedrockKey;
export type ServiceToKey = {
[K in AllKeys["service"]]: Extract<AllKeys, { service: K }>;
};
export type SerializedKey = { key: string };
export interface Key {
/** The API key itself. Never log this, use `hash` instead. */
readonly key: string;
/** The service that this key is for. */
service: LLMService;
/** The model families that this key has access to. */
modelFamilies: ModelFamily[];
/** Whether this key is currently disabled for some reason. */
isDisabled: boolean;
/**
* Whether this key specifically has been revoked. This is different from
* `isDisabled` because a key can be disabled for other reasons, such as
* exceeding its quota. A revoked key is assumed to be permanently disabled,
* and KeyStore implementations should not return it when loading keys.
*/
isRevoked: boolean;
/** The number of prompts that have been sent with this key. */
promptCount: number;
/** The time at which this key was last used. */
lastUsed: number;
/** The time at which this key was last checked. */
lastChecked: number;
/** Hash of the key, for logging and to find the key in the pool. */
hash: string;
}
export interface KeySerializer<K> {
serialize(keyObj: K): SerializedKey;
deserialize(serializedKey: SerializedKey): K;
partialSerialize(key: string, update: Partial<K>): Partial<SerializedKey>;
}
export interface KeyStore<K extends Key> {
load(): Promise<K[]>;
add(key: K): void;
update(id: string, update: Partial<K>, force?: boolean): void;
}
+89 -10
View File
@@ -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}$": "dall-e",
};
export function getOpenAIModelFamily(model: string): OpenAIModelFamily {
const modelLogger = pino({ level: "debug" }).child({ module: "startup" });
export function getOpenAIModelFamily(
model: string,
defaultFamily: OpenAIModelFamily = "gpt4"
): OpenAIModelFamily {
for (const [regex, family] of Object.entries(OPENAI_MODEL_FAMILY_MAP)) {
if (model.match(regex)) return family;
}
const stack = new Error().stack;
logger.warn({ model, stack }, "Unmapped model family");
return "gpt4";
return defaultFamily;
}
export function getClaudeModelFamily(_model: string): ModelFamily {
export function getClaudeModelFamily(model: string): ModelFamily {
if (model.startsWith("anthropic.")) return getAwsBedrockModelFamily(model);
return "claude";
}
export function getGooglePalmModelFamily(model: string): ModelFamily {
if (model.match(/^\w+-bison-\d{3}$/)) return "bison";
const stack = new Error().stack;
logger.warn({ model, stack }, "Unmapped PaLM model family");
modelLogger.warn({ model }, "Could not determine Google 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);
}
+3 -3
View File
@@ -256,8 +256,8 @@ export const appendBatch = async (batch: PromptLogEntry[]) => {
return [
entry.model,
entry.endpoint,
entry.promptRaw.slice(0, 50000),
entry.promptFlattened.slice(0, 50000),
entry.promptRaw.slice(-50000),
entry.promptFlattened.slice(-50000),
entry.response.slice(0, 50000),
];
});
@@ -396,7 +396,7 @@ export const init = async (onStop: () => void) => {
await loadIndexSheet(false);
await writeIndexSheet();
} catch (e) {
log.info("Creating new index sheet.");
log.warn({ error: e.message }, "Could not load index sheet. Creating a new one.");
await createIndexSheet();
}
};
+1 -1
View File
@@ -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();
+8 -2
View File
@@ -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";
}
}
+12 -15
View File
@@ -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(
type: string,
string: string,
req: Request
) {
export function buildFakeSse(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":
@@ -75,21 +71,22 @@ 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 [
"event: completion",
`data: ${JSON.stringify(fakeEvent)}`,
].join("\n") + "\n\n";
return (
["event: completion", `data: ${JSON.stringify(fakeEvent)}`].join("\n") +
"\n\n"
);
}
return `data: ${JSON.stringify(fakeEvent)}\n\n`;
}
}
-1
View File
@@ -1,2 +1 @@
export { OpenAIPromptMessage } from "./openai";
export { init, countTokens } from "./tokenizer";
+164 -14
View File
@@ -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(
prompt: string | OpenAIPromptMessage[],
export async function getTokenCount(
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];
if (!value || typeof value !== "string") continue;
let textContent: string = "";
const value = message[key as keyof OpenAIChatMessage];
if (!value) continue;
if (Array.isArray(value)) {
for (const item of value) {
if (item.type === "text") {
textContent += item.text;
} else if (item.type === "image_url") {
const { url, detail } = item.image_url;
const cost = await getGpt4VisionTokenCost(url, detail);
numTokens += cost ?? 0;
}
}
} else {
textContent = value;
}
// Break if we get a huge message or exceed the token limit to prevent
// DoS.
// 100k tokens allows for future 100k GPT-4 models and 500k characters
// 200k tokens allows for future 200k GPT-4 models and 500k characters
// is just a sanity check
if (value.length > 500000 || numTokens > 100000) {
numTokens = 100000;
if (textContent.length > 500000 || numTokens > 200000) {
numTokens = 200000;
return {
tokenizer: "tiktoken (prompt length limit exceeded)",
token_count: numTokens,
};
}
numTokens += encoder.encode(value).length;
numTokens += encoder.encode(textContent).length;
if (key === "name") {
numTokens += tokensPerName;
}
@@ -59,6 +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 = {
name?: string;
content: string;
role: string;
};
// Model Resolution Price
// DALL·E 3 1024×1024 $0.040 / image
// 1024×1792, 1792×1024 $0.080 / image
// DALL·E 3 HD 1024×1024 $0.080 / image
// 1024×1792, 1792×1024 $0.120 / image
// DALL·E 2 1024×1024 $0.020 / image
// 512×512 $0.018 / image
// 256×256 $0.016 / image
export const DALLE_TOKENS_PER_DOLLAR = 100000;
/**
* OpenAI image generation with DALL-E doesn't use tokens but everything else
* in the application does. There is a fixed cost for each image generation
* request depending on the model and selected quality/resolution parameters,
* which we convert to tokens at a rate of 100000 tokens per dollar.
*/
export function getOpenAIImageCost(params: {
model: "dall-e-2" | "dall-e-3";
quality: "standard" | "hd";
resolution: "512x512" | "256x256" | "1024x1024" | "1024x1792" | "1792x1024";
n: number | null;
}) {
const { model, quality, resolution, n } = params;
const usd = (() => {
switch (model) {
case "dall-e-2":
switch (resolution) {
case "512x512":
return 0.018;
case "256x256":
return 0.016;
case "1024x1024":
return 0.02;
default:
throw new Error("Invalid resolution");
}
case "dall-e-3":
switch (resolution) {
case "1024x1024":
return quality === "standard" ? 0.04 : 0.08;
case "1024x1792":
case "1792x1024":
return quality === "standard" ? 0.08 : 0.12;
default:
throw new Error("Invalid resolution");
}
default:
throw new Error("Invalid image generation model");
}
})();
const tokens = (n ?? 1) * (usd * DALLE_TOKENS_PER_DOLLAR);
return {
tokenizer: `openai-image cost`,
token_count: Math.ceil(tokens),
};
}
+16 -4
View File
@@ -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:
+2
View File
@@ -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),
+75 -43
View File
@@ -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();
@@ -32,8 +47,8 @@ let quotaRefreshJob: schedule.Job | null = null;
let userCleanupJob: schedule.Job | null = null;
export async function init() {
log.info({ store: config.persistenceProvider }, "Initializing user store...");
if (config.persistenceProvider === "firebase_rtdb") {
log.info({ store: config.gatekeeperStore }, "Initializing user store...");
if (config.gatekeeperStore === "firebase_rtdb") {
await initFirebase();
}
if (config.quotaRefreshPeriod) {
@@ -146,7 +161,7 @@ export function upsertUser(user: UserUpdate) {
usersToFlush.add(user.token);
// Immediately schedule a flush to the database if we're using Firebase.
if (config.persistenceProvider === "firebase_rtdb") {
if (config.gatekeeperStore === "firebase_rtdb") {
setImmediate(flushUsers);
}
@@ -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.ip.includes(ip)) user.ip.push(ip);
const configIpLimit = user.maxIps ?? config.maxIpsPerUser;
const ipLimit =
user.type === "special" || !configIpLimit ? Infinity : configIpLimit;
if (user.ip.length > ipLimit) {
disableUser(token, "IP address limit exceeded.");
return;
if (!user) return { result: "not_found" };
if (user.disabledAt) return { result: "disabled" };
const newIp = !user.ip.includes(ip);
const userLimit = user.maxIps ?? config.maxIpsPerUser;
const enforcedLimit =
user.type === "special" || !userLimit ? Infinity : userLimit;
if (newIp && user.ip.length >= enforcedLimit) {
if (config.maxIpsAutoBan) {
user.ip.push(ip);
disableUser(token, "IP address limit exceeded.");
return { result: "disabled" };
}
return { result: "limited" };
} else if (newIp) {
user.ip.push(ip);
}
user.lastUsedAt = Date.now();
usersToFlush.add(token);
return user;
return { user, result: "success" };
}
export function hasAvailableQuota(
token: string,
model: string,
requested: number
) {
const user = users.get(token);
export function hasAvailableQuota({
userToken,
model,
api,
requested,
}: {
userToken: string;
model: string;
api: APIFormat;
requested: number;
}) {
const user = users.get(userToken);
if (!user) return false;
if (user.type === "special") return true;
const modelFamily = getModelFamilyForQuotaUsage(model);
const modelFamily = getModelFamilyForQuotaUsage(model, api);
const { tokenCounts, tokenLimits } = user;
const tokenLimit = tokenLimits[modelFamily];
@@ -349,27 +383,25 @@ async function flushUsers() {
);
}
// TODO: use key-management/models.ts for family mapping
function getModelFamilyForQuotaUsage(model: string): ModelFamily {
if (model.includes("32k")) {
return "gpt4-32k";
function getModelFamilyForQuotaUsage(
model: string,
api: APIFormat
): ModelFamily {
// TODO: this seems incorrect
if (model.includes("azure")) return getAzureOpenAIModelFamily(model);
switch (api) {
case "openai":
case "openai-text":
case "openai-image":
return getOpenAIModelFamily(model);
case "anthropic":
return getClaudeModelFamily(model);
case "google-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() {
+7 -2
View File
@@ -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];

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