Compare commits
1 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
 nai-degen
|
5cf158ef73 |
+28
-122
@@ -5,187 +5,93 @@
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# All values have reasonable defaults, so you only need to change the ones you
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# want to override.
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# Use production mode unless you are developing locally.
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NODE_ENV=production
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# Detail level of diagnostic logging. (trace | debug | info | warn | error)
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# LOG_LEVEL=info
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# ------------------------------------------------------------------------------
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# General settings:
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# The title displayed on the info page.
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# SERVER_TITLE=Coom Tunnel
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# The route name used to proxy requests to APIs, relative to the Web site root.
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# PROXY_ENDPOINT_ROUTE=/proxy
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# Text model requests allowed per minute per user.
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# TEXT_MODEL_RATE_LIMIT=4
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# Image model requests allowed per minute per user.
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# IMAGE_MODEL_RATE_LIMIT=2
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# Max number of context tokens a user can request at once.
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# Increase this if your proxy allow GPT 32k or 128k context
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# MAX_CONTEXT_TOKENS_OPENAI=32768
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# MAX_CONTEXT_TOKENS_ANTHROPIC=32768
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# Model requests allowed per minute per user.
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# MODEL_RATE_LIMIT=4
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# Max number of output tokens a user can request at once.
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# MAX_OUTPUT_TOKENS_OPENAI=1024
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# MAX_OUTPUT_TOKENS_ANTHROPIC=1024
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# MAX_OUTPUT_TOKENS_OPENAI=300
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# MAX_OUTPUT_TOKENS_ANTHROPIC=400
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# Whether to show the estimated cost of consumed tokens on the info page.
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# SHOW_TOKEN_COSTS=false
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# Whether to automatically check API keys for validity.
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# Disabled by default in local development mode, but enabled in production.
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# Note: CHECK_KEYS is disabled by default in local development mode, but enabled
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# by default in production mode.
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# CHECK_KEYS=true
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# Which model types users are allowed to access.
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# The following model families are recognized:
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# turbo | gpt4 | gpt4-32k | gpt4-turbo | gpt4o | o1 | dall-e | claude
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# | claude-opus | gemini-flash | gemini-pro | gemini-ultra | mistral-tiny |
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# | mistral-small | mistral-medium | mistral-large | aws-claude |
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# | aws-claude-opus | gcp-claude | gcp-claude-opus | azure-turbo | azure-gpt4
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# | azure-gpt4-32k | azure-gpt4-turbo | azure-gpt4o | azure-o1 | azure-dall-e
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# ALLOWED_MODEL_FAMILIES=claude,turbo,gpt4,gpt4-32k
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# By default, all models are allowed except for dall-e and o1.
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# To allow DALL-E image generation, uncomment the line below and add 'dall-e' or
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# 'azure-dall-e' to the list of allowed model families.
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# ALLOWED_MODEL_FAMILIES=turbo,gpt4,gpt4-32k,gpt4-turbo,gpt4o,claude,claude-opus,gemini-flash,gemini-pro,gemini-ultra,mistral-tiny,mistral-small,mistral-medium,mistral-large,aws-claude,aws-claude-opus,gcp-claude,gcp-claude-opus,azure-turbo,azure-gpt4,azure-gpt4-32k,azure-gpt4-turbo,azure-gpt4o
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# Which services can be used to process prompts containing images via multimodal
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# models. The following services are recognized:
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# openai | anthropic | aws | gcp | azure | google-ai | mistral-ai
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# Do not enable this feature unless all users are trusted, as you will be liable
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# for any user-submitted images containing illegal content.
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# By default, no image services are allowed and image prompts are rejected.
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# ALLOWED_VISION_SERVICES=
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# Whether prompts should be logged to Google Sheets.
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# Requires additional setup. See `docs/google-sheets.md` for more information.
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# PROMPT_LOGGING=false
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# Specifies the number of proxies or load balancers in front of the server.
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# For Cloudflare or Hugging Face deployments, the default of 1 is correct.
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# For any other deployments, please see config.ts as the correct configuration
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# depends on your setup. Misconfiguring this value can result in problems
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# accurately tracking IP addresses and enforcing rate limits.
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# TRUSTED_PROXIES=1
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# Whether cookies should be set without the Secure flag, for hosts that don't
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# support SSL. True by default in development, false in production.
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# USE_INSECURE_COOKIES=false
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# Reorganizes requests in the queue according to their token count, placing
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# larger prompts further back. The penalty is determined by (promptTokens *
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# TOKENS_PUNISHMENT_FACTOR). A value of 1.0 adds one second per 1000 tokens.
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# When there is no queue or it is very short, the effect is negligible (this
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# setting only reorders the queue, it does not artificially delay requests).
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# TOKENS_PUNISHMENT_FACTOR=0.0
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# Captcha verification settings. Refer to docs/pow-captcha.md for guidance.
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# CAPTCHA_MODE=none
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# POW_TOKEN_HOURS=24
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# POW_TOKEN_MAX_IPS=2
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# POW_DIFFICULTY_LEVEL=low
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# POW_CHALLENGE_TIMEOUT=30
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||||
|
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# -------------------------------------------------------------------------------
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# Blocking settings:
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# Allows blocking requests depending on content, referers, or IP addresses.
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# This is a convenience feature; if you need more robust functionality it is
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# highly recommended to put this application behind nginx or Cloudflare, as they
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# will have better performance.
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# IP addresses or CIDR blocks from which requests will be blocked.
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# IP_BLACKLIST=10.0.0.1/24
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# URLs from which requests will be blocked.
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# BLOCKED_ORIGINS=reddit.com,9gag.com
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# Message to show when requests are blocked.
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# BLOCK_MESSAGE="You must be over the age of majority in your country to use this service."
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# Destination to redirect blocked requests to.
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# BLOCK_REDIRECT="https://roblox.com/"
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# Comma-separated list of phrases that will be rejected. Surround phrases with
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# quotes if they contain commas. You can use regular expression tokens.
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# Avoid overly broad phrases as will trigger on any match in the entire prompt.
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# REJECT_PHRASES="phrase one,phrase two,"phrase three, which has a comma",phrase four"
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# Whether to reject requests containing disallowed content.
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# REJECT_DISALLOWED=false
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# Message to show when requests are rejected.
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# REJECT_MESSAGE="You can't say that here."
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# REJECT_MESSAGE="This content violates /aicg/'s acceptable use policy."
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# Whether prompts should be logged to Google Sheets.
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# Requires additional setup. See `docs/google-sheets.md` for more information.
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# PROMPT_LOGGING=false
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||||
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||||
# The port to listen on.
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# PORT=7860
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||||
# Detail level of logging. (trace | debug | info | warn | error)
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||||
# LOG_LEVEL=info
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||||
|
||||
# ------------------------------------------------------------------------------
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||||
# Optional settings for user management, access control, and quota enforcement:
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||||
# See `docs/user-management.md` for more information and setup instructions.
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||||
# See `docs/user-quotas.md` to learn how to set up quotas.
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||||
|
||||
# Which access control method to use. (none | proxy_key | user_token)
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||||
# Which access control method to use. (none | proxy_token | user_token)
|
||||
# GATEKEEPER=none
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||||
# Which persistence method to use. (memory | firebase_rtdb)
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||||
# GATEKEEPER_STORE=memory
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||||
|
||||
# Maximum number of unique IPs a user can connect from. (0 for unlimited)
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||||
# MAX_IPS_PER_USER=0
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||||
# Whether user_tokens should be automatically disabled when reaching the IP limit.
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||||
# MAX_IPS_AUTO_BAN=true
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||||
|
||||
# With user_token gatekeeper, whether to allow users to change their nickname.
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||||
# ALLOW_NICKNAME_CHANGES=true
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||||
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||||
# Default token quotas for each model family. (0 for unlimited)
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||||
# Specify as TOKEN_QUOTA_MODEL_FAMILY=value (replacing dashes with underscores).
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||||
# eg. TOKEN_QUOTA_TURBO=0, TOKEN_QUOTA_GPT4=1000000, TOKEN_QUOTA_GPT4_32K=100000
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||||
# "Tokens" for image-generation models are counted at a rate of 100000 tokens
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# per US$1.00 generated, which is similar to the cost of GPT-4 Turbo.
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||||
# DALL-E 3 costs around US$0.10 per image (10000 tokens).
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||||
# See `docs/dall-e-configuration.md` for more information.
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||||
# TOKEN_QUOTA_DALL_E=0
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# TOKEN_QUOTA_TURBO=0
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# TOKEN_QUOTA_GPT4=0
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||||
# TOKEN_QUOTA_GPT4_32K=0
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||||
# TOKEN_QUOTA_CLAUDE=0
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||||
|
||||
# How often to refresh token quotas. (hourly | daily)
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||||
# Leave unset to never automatically refresh quotas.
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||||
# QUOTA_REFRESH_PERIOD=daily
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||||
|
||||
# -------------------------------------------------------------------------------
|
||||
# HTTP agent settings:
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||||
# If you need to change how the proxy makes requests to other servers, such
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||||
# as when checking keys or forwarding users' requests to external services,
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||||
# you can configure an alternative HTTP agent. Otherwise the default OS settings
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||||
# will be used.
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||||
|
||||
# The name of the network interface to use. The first external IPv4 address
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||||
# belonging to this interface will be used for outgoing requests.
|
||||
# HTTP_AGENT_INTERFACE=enp0s3
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||||
|
||||
# The URL of a proxy server to use. Supports SOCKS4, SOCKS5, HTTP, and HTTPS.
|
||||
# Note that if your proxy server issues a self-signed certificate, you may need
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||||
# NODE_EXTRA_CA_CERTS set to the path to your certificate. You will need to set
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||||
# that variable in your environment, not in this file.
|
||||
# HTTP_AGENT_PROXY_URL=http://test:test@127.0.0.1:8000
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||||
|
||||
# ------------------------------------------------------------------------------
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||||
# Secrets and keys:
|
||||
# For Huggingface, set them via the Secrets section in your Space's config UI. Dp not set them in .env.
|
||||
# Do not put any passwords or API keys directly in this file.
|
||||
# For Huggingface, set them via the Secrets section in your Space's config UI.
|
||||
# For Render, create a "secret file" called .env using the Environment tab.
|
||||
|
||||
# You can add multiple API keys by separating them with a comma.
|
||||
# For AWS credentials, separate the access key ID, secret key, and region with a colon.
|
||||
# For GCP credentials, separate the project ID, client email, region, and private key with a colon.
|
||||
OPENAI_KEY=sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
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||||
ANTHROPIC_KEY=sk-ant-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
|
||||
GOOGLE_AI_KEY=AIzaxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
|
||||
# See `docs/aws-configuration.md` for more information, there may be additional steps required to set up AWS.
|
||||
AWS_CREDENTIALS=myaccesskeyid:mysecretkey:us-east-1,anotheraccesskeyid:anothersecretkey:us-west-2
|
||||
# See `docs/azure-configuration.md` for more information, there may be additional steps required to set up Azure.
|
||||
AZURE_CREDENTIALS=azure-resource-name:deployment-id:api-key,another-azure-resource-name:another-deployment-id:another-api-key
|
||||
GCP_CREDENTIALS=project-id:client-email:region:private-key
|
||||
|
||||
# With proxy_key gatekeeper, the password users must provide to access the API.
|
||||
# PROXY_KEY=your-secret-key
|
||||
|
||||
# With user_token gatekeeper, the admin password used to manage users.
|
||||
# ADMIN_KEY=your-very-secret-key
|
||||
# Restrict access to the admin interface to specific IP addresses, specified
|
||||
# as a comma-separated list of CIDR ranges.
|
||||
# ADMIN_WHITELIST=0.0.0.0/0
|
||||
|
||||
# With firebase_rtdb gatekeeper storage, the Firebase project credentials.
|
||||
# FIREBASE_KEY=xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
|
||||
|
||||
+1
-6
@@ -1,11 +1,6 @@
|
||||
.aider*
|
||||
.env*
|
||||
!.env.vault
|
||||
.env
|
||||
.venv
|
||||
.vscode
|
||||
.idea
|
||||
build
|
||||
greeting.md
|
||||
node_modules
|
||||
|
||||
http-client.private.env.json
|
||||
|
||||
+5
-5
@@ -1,13 +1,13 @@
|
||||
{
|
||||
"plugins": ["prettier-plugin-ejs"],
|
||||
"overrides": [
|
||||
{
|
||||
"files": "*.ejs",
|
||||
"files": [
|
||||
"*.ejs"
|
||||
],
|
||||
"options": {
|
||||
"printWidth": 120,
|
||||
"printWidth": 160,
|
||||
"bracketSameLine": true
|
||||
}
|
||||
}
|
||||
],
|
||||
"trailingComma": "es5"
|
||||
]
|
||||
}
|
||||
|
||||
@@ -1,72 +1,42 @@
|
||||
# OAI Reverse Proxy
|
||||
Reverse proxy server for various LLM APIs.
|
||||
|
||||
Reverse proxy server for the OpenAI and Anthropic APIs. Forwards text generation requests while rejecting administrative/billing requests. Includes optional rate limiting and prompt filtering to prevent abuse.
|
||||
|
||||
### Table of Contents
|
||||
<!-- TOC -->
|
||||
* [OAI Reverse Proxy](#oai-reverse-proxy)
|
||||
* [Table of Contents](#table-of-contents)
|
||||
* [What is this?](#what-is-this)
|
||||
* [Features](#features)
|
||||
* [Usage Instructions](#usage-instructions)
|
||||
* [Personal Use (single-user)](#personal-use-single-user)
|
||||
* [Updating](#updating)
|
||||
* [Local Development](#local-development)
|
||||
* [Self-hosting](#self-hosting)
|
||||
* [Building](#building)
|
||||
* [Forking](#forking)
|
||||
<!-- TOC -->
|
||||
- [What is this?](#what-is-this)
|
||||
- [Why?](#why)
|
||||
- [Usage Instructions](#setup-instructions)
|
||||
- [Deploy to Huggingface (Recommended)](#deploy-to-huggingface-recommended)
|
||||
- [Deploy to Repl.it (WIP)](#deploy-to-replit-wip)
|
||||
- [Local Development](#local-development)
|
||||
|
||||
## What is this?
|
||||
This project allows you to run a reverse proxy server for various LLM APIs.
|
||||
If you would like to provide a friend access to an API via keys you own, you can use this to keep your keys safe while still allowing them to generate text with the API. You can also use this if you'd like to build a client-side application which uses the OpenAI or Anthropic APIs, but don't want to build your own backend. You should never embed your real API keys in a client-side application. Instead, you can have your frontend connect to this reverse proxy and forward requests to the downstream service.
|
||||
|
||||
## Features
|
||||
- [x] Support for multiple APIs
|
||||
- [x] [OpenAI](https://openai.com/)
|
||||
- [x] [Anthropic](https://www.anthropic.com/)
|
||||
- [x] [AWS Bedrock](https://aws.amazon.com/bedrock/)
|
||||
- [x] [Vertex AI (GCP)](https://cloud.google.com/vertex-ai/)
|
||||
- [x] [Google MakerSuite/Gemini API](https://ai.google.dev/)
|
||||
- [x] [Azure OpenAI](https://azure.microsoft.com/en-us/products/ai-services/openai-service)
|
||||
- [x] Translation from OpenAI-formatted prompts to any other API, including streaming responses
|
||||
- [x] Multiple API keys with rotation and rate limit handling
|
||||
- [x] Basic user management
|
||||
- [x] Simple role-based permissions
|
||||
- [x] Per-model token quotas
|
||||
- [x] Temporary user accounts
|
||||
- [x] Event audit logging
|
||||
- [x] Optional full logging of prompts and completions
|
||||
- [x] Abuse detection and prevention
|
||||
- [x] IP address and user token model invocation rate limits
|
||||
- [x] IP blacklists
|
||||
- [x] Proof-of-work challenge for access by anonymous users
|
||||
This keeps your keys safe and allows you to use the rate limiting and prompt filtering features of the proxy to prevent abuse.
|
||||
|
||||
## Why?
|
||||
OpenAI keys have full account permissions. They can revoke themselves, generate new keys, modify spend quotas, etc. **You absolutely should not share them, post them publicly, nor embed them in client-side applications as they can be easily stolen.**
|
||||
|
||||
This proxy only forwards text generation requests to the downstream service and rejects requests which would otherwise modify your account.
|
||||
|
||||
---
|
||||
|
||||
## Usage Instructions
|
||||
If you'd like to run your own instance of this server, you'll need to deploy it somewhere and configure it with your API keys. A few easy options are provided below, though you can also deploy it to any other service you'd like if you know what you're doing and the service supports Node.js.
|
||||
If you'd like to run your own instance of this proxy, you'll need to deploy it somewhere and configure it with your API keys. A few easy options are provided below, though you can also deploy it to any other service you'd like.
|
||||
|
||||
### Personal Use (single-user)
|
||||
If you just want to run the proxy server to use yourself without hosting it for others:
|
||||
1. Install [Node.js](https://nodejs.org/en/download/) >= 18.0.0
|
||||
2. Clone this repository
|
||||
### Deploy to Huggingface (Recommended)
|
||||
[See here for instructions on how to deploy to a Huggingface Space.](./docs/deploy-huggingface.md)
|
||||
|
||||
### Deploy to Render
|
||||
[See here for instructions on how to deploy to Render.com.](./docs/deploy-render.md)
|
||||
|
||||
## Local Development
|
||||
To run the proxy locally for development or testing, install Node.js >= 18.0.0 and follow the steps below.
|
||||
|
||||
1. Clone the repo
|
||||
2. Install dependencies with `npm install`
|
||||
3. Create a `.env` file in the root of the project and add your API keys. See the [.env.example](./.env.example) file for an example.
|
||||
4. Install dependencies with `npm install`
|
||||
5. Run `npm run build`
|
||||
6. Run `npm start`
|
||||
4. Start the server in development mode with `npm run start:dev`.
|
||||
|
||||
#### Updating
|
||||
You must re-run `npm install` and `npm run build` whenever you pull new changes from the repository.
|
||||
|
||||
#### Local Development
|
||||
Use `npm run start:dev` to run the proxy in development mode with watch mode enabled. Use `npm run type-check` to run the type checker across the project.
|
||||
|
||||
### Self-hosting
|
||||
[See here for instructions on how to self-host the application on your own VPS or local machine and expose it to the internet for others to use.](./docs/self-hosting.md)
|
||||
|
||||
**Ensure you set the `TRUSTED_PROXIES` environment variable according to your deployment.** Refer to [.env.example](./.env.example) and [config.ts](./src/config.ts) for more information.
|
||||
|
||||
## Building
|
||||
To build the project, run `npm run build`. This will compile the TypeScript code to JavaScript and output it to the `build` directory. You should run this whenever you pull new changes from the repository.
|
||||
|
||||
Note that if you are trying to build the server on a very memory-constrained (<= 1GB) VPS, you may need to run the build with `NODE_OPTIONS=--max_old_space_size=2048 npm run build` to avoid running out of memory during the build process, assuming you have swap enabled. The application itself should run fine on a 512MB VPS for most reasonable traffic levels.
|
||||
|
||||
## Forking
|
||||
If you are forking the repository on GitGud, you may wish to disable GitLab CI/CD or you will be spammed with emails about failed builds due not having any CI runners. You can do this by going to *Settings > General > Visibility, project features, permissions* and then disabling the "CI/CD" feature.
|
||||
You can also use `npm run start:dev:tsc` to enable project-wide type checking at the cost of slower startup times. `npm run type-check` can be used to run type checking without starting the server.
|
||||
|
||||
@@ -1,2 +0,0 @@
|
||||
*
|
||||
!.gitkeep
|
||||
@@ -1,21 +0,0 @@
|
||||
stages:
|
||||
- build
|
||||
|
||||
build_image:
|
||||
stage: build
|
||||
image:
|
||||
name: gcr.io/kaniko-project/executor:debug
|
||||
entrypoint: [""]
|
||||
script:
|
||||
- |
|
||||
if [ "$CI_COMMIT_REF_NAME" = "main" ]; then
|
||||
TAG="latest"
|
||||
else
|
||||
TAG=$CI_COMMIT_REF_NAME
|
||||
fi
|
||||
- echo "Building image with tag $TAG"
|
||||
- BASE64_AUTH=$(echo -n "$DOCKER_HUB_USERNAME:$DOCKER_HUB_ACCESS_TOKEN" | base64)
|
||||
- echo "{\"auths\":{\"https://index.docker.io/v1/\":{\"auth\":\"$BASE64_AUTH\"}}}" > /kaniko/.docker/config.json
|
||||
- /kaniko/executor --context $CI_PROJECT_DIR --dockerfile $CI_PROJECT_DIR/docker/ci/Dockerfile --destination docker.io/khanonci/oai-reverse-proxy:$TAG --build-arg CI_COMMIT_REF_NAME=$CI_COMMIT_REF_NAME --build-arg CI_COMMIT_SHA=$CI_COMMIT_SHA --build-arg CI_PROJECT_PATH=$CI_PROJECT_PATH
|
||||
only:
|
||||
- main
|
||||
@@ -1,22 +0,0 @@
|
||||
FROM node:18-bullseye-slim
|
||||
|
||||
WORKDIR /app
|
||||
COPY . .
|
||||
|
||||
RUN npm ci
|
||||
RUN npm run build
|
||||
RUN npm prune --production
|
||||
|
||||
EXPOSE 7860
|
||||
ENV PORT=7860
|
||||
ENV NODE_ENV=production
|
||||
|
||||
ARG CI_COMMIT_REF_NAME
|
||||
ARG CI_COMMIT_SHA
|
||||
ARG CI_PROJECT_PATH
|
||||
|
||||
ENV GITGUD_BRANCH=$CI_COMMIT_REF_NAME
|
||||
ENV GITGUD_COMMIT=$CI_COMMIT_SHA
|
||||
ENV GITGUD_PROJECT=$CI_PROJECT_PATH
|
||||
|
||||
CMD [ "npm", "start" ]
|
||||
@@ -1,17 +0,0 @@
|
||||
# Before running this, create a .env and greeting.md file.
|
||||
# Refer to .env.example for the required environment variables.
|
||||
# User-generated content is stored in the data directory.
|
||||
# When self-hosting, it's recommended to run this behind a reverse proxy like
|
||||
# nginx or Caddy to handle SSL/TLS and rate limiting. Refer to
|
||||
# docs/self-hosting.md for more information and an example nginx config.
|
||||
version: '3.8'
|
||||
services:
|
||||
oai-reverse-proxy:
|
||||
image: khanonci/oai-reverse-proxy:latest
|
||||
ports:
|
||||
- "127.0.0.1:7860:7860"
|
||||
env_file:
|
||||
- ./.env
|
||||
volumes:
|
||||
- ./greeting.md:/app/greeting.md
|
||||
- ./data:/app/data
|
||||
@@ -3,13 +3,9 @@ RUN apt-get update && \
|
||||
apt-get install -y git
|
||||
RUN git clone https://gitgud.io/khanon/oai-reverse-proxy.git /app
|
||||
WORKDIR /app
|
||||
RUN chown -R 1000:1000 /app
|
||||
USER 1000
|
||||
RUN npm install
|
||||
COPY Dockerfile greeting.md* .env* ./
|
||||
RUN npm run build
|
||||
EXPOSE 7860
|
||||
ENV NODE_ENV=production
|
||||
# Huggigface free VMs have 16GB of RAM so we can be greedy
|
||||
ENV NODE_OPTIONS="--max-old-space-size=12882"
|
||||
CMD [ "npm", "start" ]
|
||||
|
||||
@@ -17,8 +17,9 @@ ARG GREETING_URL
|
||||
RUN if [ -n "$GREETING_URL" ]; then \
|
||||
curl -sL "$GREETING_URL" > greeting.md; \
|
||||
fi
|
||||
COPY . .
|
||||
COPY package*.json greeting.md* ./
|
||||
RUN npm install
|
||||
COPY . .
|
||||
RUN npm run build
|
||||
RUN --mount=type=secret,id=_env,dst=/etc/secrets/.env cat /etc/secrets/.env >> .env
|
||||
EXPOSE 10000
|
||||
|
||||
Binary file not shown.
|
Before Width: | Height: | Size: 4.2 KiB |
@@ -1,58 +0,0 @@
|
||||
# Configuring the proxy for AWS Bedrock
|
||||
|
||||
The proxy supports AWS Bedrock models via the `/proxy/aws/claude` endpoint. There are a few extra steps necessary to use AWS Bedrock compared to the other supported APIs.
|
||||
|
||||
- [Setting keys](#setting-keys)
|
||||
- [Attaching policies](#attaching-policies)
|
||||
- [Provisioning models](#provisioning-models)
|
||||
- [Note regarding logging](#note-regarding-logging)
|
||||
|
||||
## Setting keys
|
||||
|
||||
Use the `AWS_CREDENTIALS` environment variable to set the AWS API keys.
|
||||
|
||||
Like other APIs, you can provide multiple keys separated by commas. Each AWS key, however, is a set of credentials including the access key, secret key, and region. These are separated by a colon (`:`).
|
||||
|
||||
For example:
|
||||
|
||||
```
|
||||
AWS_CREDENTIALS=AKIA000000000000000:somesecretkey:us-east-1,AKIA111111111111111:anothersecretkey:us-west-2
|
||||
```
|
||||
|
||||
## Attaching policies
|
||||
|
||||
Unless your credentials belong to the root account, the principal will need to be granted the following permissions:
|
||||
|
||||
- `bedrock:InvokeModel`
|
||||
- `bedrock:InvokeModelWithResponseStream`
|
||||
- `bedrock:GetModelInvocationLoggingConfiguration`
|
||||
- The proxy needs this to determine whether prompt/response logging is enabled. By default, the proxy won't use credentials unless it can conclusively determine that logging is disabled, for privacy reasons.
|
||||
|
||||
Use the IAM console or the AWS CLI to attach these policies to the principal associated with the credentials.
|
||||
|
||||
## Provisioning models
|
||||
|
||||
AWS does not automatically provide accounts with access to every model. You will need to provision the models you want to use, in the regions you want to use them in. You can do this from the AWS console.
|
||||
|
||||
⚠️ **Models are region-specific.** Currently AWS only offers Claude in a small number of regions. Switch to the AWS region you want to use, then go to the models page and request access to **Anthropic / Claude**.
|
||||
|
||||
|
||||
|
||||
Access is generally granted more or less instantly. Once your account has access, you can enable the model by checking the box next to it.
|
||||
|
||||
You can also request Claude Instant, but support for this isn't fully implemented yet.
|
||||
|
||||
### Supported model IDs
|
||||
Users can send these model IDs to the proxy to invoke the corresponding models.
|
||||
- **Claude**
|
||||
- `anthropic.claude-v1` (~18k context, claude 1.3 -- EOL 2024-02-28)
|
||||
- `anthropic.claude-v2` (~100k context, claude 2.0)
|
||||
- `anthropic.claude-v2:1` (~200k context, claude 2.1)
|
||||
- **Claude Instant**
|
||||
- `anthropic.claude-instant-v1` (~100k context, claude instant 1.2)
|
||||
|
||||
## Note regarding logging
|
||||
|
||||
By default, the proxy will refuse to use keys if it finds that logging is enabled, or if it doesn't have permission to check logging status.
|
||||
|
||||
If you can't attach the `bedrock:GetModelInvocationLoggingConfiguration` policy to the principal, you can set the `ALLOW_AWS_LOGGING` environment variable to `true` to force the proxy to use the keys anyway. A warning will appear on the info page when this is enabled.
|
||||
@@ -1,30 +0,0 @@
|
||||
# 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.
|
||||
@@ -1,71 +0,0 @@
|
||||
# Configuring the proxy for DALL-E
|
||||
|
||||
The proxy supports DALL-E 2 and DALL-E 3 image generation via the `/proxy/openai-images` endpoint. By default it is disabled as it is somewhat expensive and potentially more open to abuse than text generation.
|
||||
|
||||
- [Updating your Dockerfile](#updating-your-dockerfile)
|
||||
- [Enabling DALL-E](#enabling-dall-e)
|
||||
- [Setting quotas](#setting-quotas)
|
||||
- [Rate limiting](#rate-limiting)
|
||||
|
||||
## Updating your Dockerfile
|
||||
If you are using a previous version of the Dockerfile supplied with the proxy, it doesn't have the necessary permissions to let the proxy save temporary files.
|
||||
|
||||
You can replace the entire thing with the new Dockerfile at [./docker/huggingface/Dockerfile](../docker/huggingface/Dockerfile) (or the equivalent for Render deployments).
|
||||
|
||||
You can also modify your existing Dockerfile; just add the following lines after the `WORKDIR` line:
|
||||
|
||||
```Dockerfile
|
||||
# Existing
|
||||
RUN git clone https://gitgud.io/khanon/oai-reverse-proxy.git /app
|
||||
WORKDIR /app
|
||||
|
||||
# Take ownership of the app directory and switch to the non-root user
|
||||
RUN chown -R 1000:1000 /app
|
||||
USER 1000
|
||||
|
||||
# Existing
|
||||
RUN npm install
|
||||
```
|
||||
|
||||
## Enabling DALL-E
|
||||
Add `dall-e` to the `ALLOWED_MODEL_FAMILIES` environment variable to enable DALL-E. For example:
|
||||
|
||||
```
|
||||
# GPT3.5 Turbo, GPT-4, GPT-4 Turbo, and DALL-E
|
||||
ALLOWED_MODEL_FAMILIES=turbo,gpt-4,gpt-4turbo,dall-e
|
||||
|
||||
# All models as of this writing
|
||||
ALLOWED_MODEL_FAMILIES=turbo,gpt4,gpt4-32k,gpt4-turbo,claude,gemini-pro,aws-claude,dall-e
|
||||
```
|
||||
|
||||
Refer to [.env.example](../.env.example) for a full list of supported model families. You can add `dall-e` to that list to enable all models.
|
||||
|
||||
## Setting quotas
|
||||
DALL-E doesn't bill by token like text generation models. Instead there is a fixed cost per image generated, depending on the model, image size, and selected quality.
|
||||
|
||||
The proxy still uses tokens to set quotas for users. The cost for each generated image will be converted to "tokens" at a rate of 100000 tokens per US$1.00. This works out to a similar cost-per-token as GPT-4 Turbo, so you can use similar token quotas for both.
|
||||
|
||||
Use `TOKEN_QUOTA_DALL_E` to set the default quota for image generation. Otherwise it works the same as token quotas for other models.
|
||||
|
||||
```
|
||||
# ~50 standard DALL-E images per refresh period, or US$2.00
|
||||
TOKEN_QUOTA_DALL_E=200000
|
||||
```
|
||||
|
||||
Refer to [https://openai.com/pricing](https://openai.com/pricing) for the latest pricing information. As of this writing, the cheapest DALL-E 3 image costs $0.04 per generation, which works out to 4000 tokens. Higher resolution and quality settings can cost up to $0.12 per image, or 12000 tokens.
|
||||
|
||||
## Rate limiting
|
||||
The old `MODEL_RATE_LIMIT` setting has been split into `TEXT_MODEL_RATE_LIMIT` and `IMAGE_MODEL_RATE_LIMIT`. Whatever value you previously set for `MODEL_RATE_LIMIT` will be used for text models.
|
||||
|
||||
If you don't specify a `IMAGE_MODEL_RATE_LIMIT`, it defaults to half of the `TEXT_MODEL_RATE_LIMIT`, to a minimum of 1 image per minute.
|
||||
|
||||
```
|
||||
# 4 text generations per minute, 2 images per minute
|
||||
TEXT_MODEL_RATE_LIMIT=4
|
||||
IMAGE_MODEL_RATE_LIMIT=2
|
||||
```
|
||||
|
||||
If a prompt is filtered by OpenAI's content filter, it won't count towards the rate limit.
|
||||
|
||||
## Hiding recent images
|
||||
By default, the proxy shows the last 12 recently generated images by users. You can hide this section by setting `SHOW_RECENT_IMAGES` to `false`.
|
||||
@@ -1,7 +1,5 @@
|
||||
# Deploy to Huggingface Space
|
||||
|
||||
**⚠️ This method is no longer recommended. Please use the [self-hosting instructions](./self-hosting.md) instead.**
|
||||
|
||||
This repository can be deployed to a [Huggingface Space](https://huggingface.co/spaces). This is a free service that allows you to run a simple server in the cloud. You can use it to safely share your OpenAI API key with a friend.
|
||||
|
||||
### 1. Get an API key
|
||||
@@ -27,14 +25,11 @@ RUN apt-get update && \
|
||||
apt-get install -y git
|
||||
RUN git clone https://gitgud.io/khanon/oai-reverse-proxy.git /app
|
||||
WORKDIR /app
|
||||
RUN chown -R 1000:1000 /app
|
||||
USER 1000
|
||||
RUN npm install
|
||||
COPY Dockerfile greeting.md* .env* ./
|
||||
RUN npm run build
|
||||
EXPOSE 7860
|
||||
ENV NODE_ENV=production
|
||||
ENV NODE_OPTIONS="--max-old-space-size=12882"
|
||||
CMD [ "npm", "start" ]
|
||||
```
|
||||
- Click "Commit new file to `main`" to save the Dockerfile.
|
||||
@@ -93,12 +88,6 @@ See `.env.example` for a full list of available settings, or check `config.ts` f
|
||||
|
||||
## Restricting access to the server
|
||||
|
||||
If you want to restrict access to the server, you can set a `PROXY_KEY` secret. This key will need to be passed in the Authentication header of every request to the server, just like an OpenAI API key. Set the `GATEKEEPER` mode to `proxy_key`, and then set the `PROXY_KEY` variable to whatever password you want.
|
||||
If you want to restrict access to the server, you can set a `PROXY_KEY` secret. This key will need to be passed in the Authentication header of every request to the server, just like an OpenAI API key.
|
||||
|
||||
Add this using the same method as the OPENAI_KEY secret above. Don't add this to your `.env` file because that file is public and anyone can see it.
|
||||
|
||||
Example:
|
||||
```
|
||||
GATEKEEPER=proxy_key
|
||||
PROXY_KEY=your_secret_password
|
||||
```
|
||||
|
||||
@@ -1,7 +1,4 @@
|
||||
# Deploy to Render.com
|
||||
|
||||
**⚠️ This method is no longer supported or recommended and may not work. Please use the [self-hosting instructions](./self-hosting.md) instead.**
|
||||
|
||||
Render.com offers a free tier that includes 750 hours of compute time per month. This is enough to run a single proxy instance 24/7. Instances shut down after 15 minutes without traffic but start up again automatically when a request is received. You can use something like https://app.checklyhq.com/ to ping your proxy every 15 minutes to keep it alive.
|
||||
|
||||
### 1. Create account
|
||||
@@ -31,8 +28,6 @@ The service will be created according to the instructions in the `render.yaml` f
|
||||
- For example, `OPENAI_KEY=sk-abc123`.
|
||||
- Click **Save Changes**.
|
||||
|
||||
**IMPORTANT:** Set `TRUSTED_PROXIES=3`, otherwise users' IP addresses will not be recorded correctly (the server will see the IP address of Render's load balancer instead of the user's real IP address).
|
||||
|
||||
The service will automatically rebuild and deploy with the new environment variables. This will take a few minutes. The link to your deployed proxy will appear at the top of the page.
|
||||
|
||||
If you want to change the URL, go to the **Settings** tab of your Web Service and click the **Edit** button next to **Name**. You can also set a custom domain, though I haven't tried this yet.
|
||||
|
||||
@@ -1,35 +0,0 @@
|
||||
# Configuring the proxy for Vertex AI (GCP)
|
||||
|
||||
The proxy supports GCP models via the `/proxy/gcp/claude` endpoint. There are a few extra steps necessary to use GCP compared to the other supported APIs.
|
||||
|
||||
- [Setting keys](#setting-keys)
|
||||
- [Setup Vertex AI](#setup-vertex-ai)
|
||||
- [Supported model IDs](#supported-model-ids)
|
||||
|
||||
## Setting keys
|
||||
|
||||
Use the `GCP_CREDENTIALS` environment variable to set the GCP API keys.
|
||||
|
||||
Like other APIs, you can provide multiple keys separated by commas. Each GCP key, however, is a set of credentials including the project id, client email, region and private key. These are separated by a colon (`:`).
|
||||
|
||||
For example:
|
||||
|
||||
```
|
||||
GCP_CREDENTIALS=my-first-project:xxx@yyy.com:us-east5:-----BEGIN PRIVATE KEY-----xxx-----END PRIVATE KEY-----,my-first-project2:xxx2@yyy.com:us-east5:-----BEGIN PRIVATE KEY-----xxx-----END PRIVATE KEY-----
|
||||
```
|
||||
|
||||
## Setup Vertex AI
|
||||
1. Go to [https://cloud.google.com/vertex-ai](https://cloud.google.com/vertex-ai) and sign up for a GCP account. ($150 free credits without credit card or $300 free credits with credit card, credits expire in 90 days)
|
||||
2. Go to [https://console.cloud.google.com/marketplace/product/google/aiplatform.googleapis.com](https://console.cloud.google.com/marketplace/product/google/aiplatform.googleapis.com) to enable Vertex AI API.
|
||||
3. Go to [https://console.cloud.google.com/vertex-ai](https://console.cloud.google.com/vertex-ai) and navigate to Model Garden to apply for access to the Claude models.
|
||||
4. Create a [Service Account](https://console.cloud.google.com/projectselector/iam-admin/serviceaccounts/create?walkthrough_id=iam--create-service-account#step_index=1) , and make sure to grant the role of "Vertex AI User" or "Vertex AI Administrator".
|
||||
5. On the service account page you just created, create a new key and select "JSON". The JSON file will be downloaded automatically.
|
||||
6. The required credential is in the JSON file you just downloaded.
|
||||
|
||||
## Supported model IDs
|
||||
Users can send these model IDs to the proxy to invoke the corresponding models.
|
||||
- **Claude**
|
||||
- `claude-3-haiku@20240307`
|
||||
- `claude-3-sonnet@20240229`
|
||||
- `claude-3-opus@20240229`
|
||||
- `claude-3-5-sonnet@20240620`
|
||||
@@ -1,135 +0,0 @@
|
||||
# Proof-of-work Verification
|
||||
|
||||
You can require users to complete a proof-of-work before they can access the
|
||||
proxy. This can increase the cost of denial of service attacks and slow down
|
||||
automated abuse.
|
||||
|
||||
When configured, users access the challenge UI and request a token. The server
|
||||
sends a challenge to the client, which asks the user's browser to find a
|
||||
solution to the challenge that meets a certain constraint (the difficulty
|
||||
level). Once the user has found a solution, they can submit it to the server
|
||||
and get a user token valid for a period you specify.
|
||||
|
||||
The proof-of-work challenge uses the argon2id hash function.
|
||||
|
||||
## Configuration
|
||||
|
||||
To enable proof-of-work verification, set the following environment variables:
|
||||
|
||||
```
|
||||
GATEKEEPER=user_token
|
||||
CAPTCHA_MODE=proof_of_work
|
||||
# Validity of the token in hours
|
||||
POW_TOKEN_HOURS=24
|
||||
# Max number of IPs that can use a user_token issued via proof-of-work
|
||||
POW_TOKEN_MAX_IPS=2
|
||||
# The difficulty level of the proof-of-work challenge. You can use one of the
|
||||
# predefined levels specified below, or you can specify a custom number of
|
||||
# expected hash iterations.
|
||||
POW_DIFFICULTY_LEVEL=low
|
||||
# The time limit for solving the challenge, in minutes
|
||||
POW_CHALLENGE_TIMEOUT=30
|
||||
```
|
||||
|
||||
## Difficulty Levels
|
||||
|
||||
The difficulty level controls how long, on average, it will take for a user to
|
||||
solve the proof-of-work challenge. Due to randomness, the actual time can very
|
||||
significantly; lucky users may solve the challenge in a fraction of the average
|
||||
time, while unlucky users may take much longer.
|
||||
|
||||
The difficulty level doesn't affect the speed of the hash function itself, only
|
||||
the number of hashes that will need to be computed. Therefore, the time required
|
||||
to complete the challenge scales linearly with the difficulty level's iteration
|
||||
count.
|
||||
|
||||
You can adjust the difficulty level while the proxy is running from the admin
|
||||
interface.
|
||||
|
||||
Be aware that there is a time limit for solving the challenge, by default set to
|
||||
30 minutes. Above 'high' difficulty, you will probably need to increase the time
|
||||
limit or it will be very hard for users with slow devices to find a solution
|
||||
within the time limit.
|
||||
|
||||
### Low
|
||||
|
||||
- Average of 200 iterations required
|
||||
- Default setting.
|
||||
|
||||
### Medium
|
||||
|
||||
- Average of 900 iterations required
|
||||
|
||||
### High
|
||||
|
||||
- Average of 1900 iterations required
|
||||
|
||||
### Extreme
|
||||
|
||||
- Average of 4000 iterations required
|
||||
- Not recommended unless you are expecting very high levels of abuse
|
||||
- May require increasing `POW_CHALLENGE_TIMEOUT`
|
||||
|
||||
### Custom
|
||||
|
||||
Setting `POW_DIFFICULTY_LEVEL` to an integer will use that number of iterations
|
||||
as the difficulty level.
|
||||
|
||||
## Other challenge settings
|
||||
|
||||
- `POW_CHALLENGE_TIMEOUT`: The time limit for solving the challenge, in minutes.
|
||||
Default is 30.
|
||||
- `POW_TOKEN_HOURS`: The period of time for which a user token issued via proof-
|
||||
of-work can be used. Default is 24 hours. Starts when the challenge is solved.
|
||||
- `POW_TOKEN_MAX_IPS`: The maximum number of unique IPs that can use a single
|
||||
user token issued via proof-of-work. Default is 2.
|
||||
- `POW_TOKEN_PURGE_HOURS`: The period of time after which an expired user token
|
||||
issued via proof-of-work will be removed from the database. Until it is
|
||||
purged, users can refresh expired tokens by completing a half-difficulty
|
||||
challenge. Default is 48 hours.
|
||||
- `POW_MAX_TOKENS_PER_IP`: The maximum number of active user tokens that can
|
||||
be associated with a single IP address. After this limit is reached, the
|
||||
oldest token will be forcibly expired when a new token is issued. Set to 0
|
||||
to disable this feature. Default is 0.
|
||||
|
||||
## Custom argon2id parameters
|
||||
|
||||
You can set custom argon2id parameters for the proof-of-work challenge.
|
||||
Generally, you should not need to change these unless you have a specific
|
||||
reason to do so.
|
||||
|
||||
The listed values are the defaults.
|
||||
|
||||
```
|
||||
ARGON2_TIME_COST=8
|
||||
ARGON2_MEMORY_KB=65536
|
||||
ARGON2_PARALLELISM=1
|
||||
ARGON2_HASH_LENGTH=32
|
||||
```
|
||||
|
||||
Increasing parallelism will not do much except increase memory consumption for
|
||||
both the client and server, because browser proof-of-work implementations are
|
||||
single-threaded. It's better to increase the time cost if you want to increase
|
||||
the difficulty.
|
||||
|
||||
Increasing memory too much may cause memory exhaustion on some mobile devices,
|
||||
particularly on iOS due to the way Safari handles WebAssembly memory allocation.
|
||||
|
||||
## Tested hash rates
|
||||
|
||||
These were measured with the default argon2id parameters listed above. These
|
||||
tests were not at all scientific so take them with a grain of salt.
|
||||
|
||||
Safari does not like large WASM memory usage, so concurrency is limited to 4 to
|
||||
avoid overallocating memory on mobile WebKit browsers. Thermal throttling can
|
||||
also significantly reduce hash rates on mobile devices.
|
||||
|
||||
- Intel Core i9-13900K (Chrome): 33-35 H/s
|
||||
- Intel Core i9-13900K (Firefox): 29-32 H/s
|
||||
- Intel Core i9-13900K (Chrome, in VM limited to 4 cores): 12.2 - 13.0 H/s
|
||||
- iPad Pro (M2) (Safari, 6 workers): 8.0 - 10 H/s
|
||||
- Thermal throttles early. 8 cores is normal concurrency, but unstable.
|
||||
- iPhone 15 Pro Max (Safari): 4.0 - 4.6 H/s
|
||||
- Samsung Galaxy S10e (Chrome): 3.6 - 3.8 H/s
|
||||
- This is a 2019 phone almost matching an iPhone five years newer because of
|
||||
bad Safari performance.
|
||||
@@ -1,150 +0,0 @@
|
||||
# Quick self-hosting guide
|
||||
|
||||
Temporary guide for self-hosting. This will be improved in the future to provide more robust instructions and options. Provided commands are for Ubuntu.
|
||||
|
||||
This uses prebuilt Docker images for convenience. If you want to make adjustments to the code you can instead clone the repo and follow the Local Development guide in the [README](../README.md).
|
||||
|
||||
## Table of Contents
|
||||
- [Requirements](#requirements)
|
||||
- [Running the application](#running-the-application)
|
||||
- [Setting up a reverse proxy](#setting-up-a-reverse-proxy)
|
||||
- [trycloudflare](#trycloudflare)
|
||||
- [nginx](#nginx)
|
||||
- [Example basic nginx configuration (no SSL)](#example-basic-nginx-configuration-no-ssl)
|
||||
- [Example with Cloudflare SSL](#example-with-cloudflare-ssl)
|
||||
- [Updating/Restarting the application](#updatingrestarting-the-application)
|
||||
|
||||
## Requirements
|
||||
|
||||
- Docker
|
||||
- Docker Compose
|
||||
- A VPS with at least 512MB of RAM (1GB recommended)
|
||||
- A domain name
|
||||
|
||||
If you don't have a VPS and domain name you can use TryCloudflare to set up a temporary URL that you can share with others. See [trycloudflare](#trycloudflare) for more information.
|
||||
|
||||
## Running the application
|
||||
|
||||
- Install Docker and Docker Compose
|
||||
- Create a new directory for the application
|
||||
- This will contain your .env file, greeting file, and any user-generated files
|
||||
- Execute the following commands:
|
||||
- ```
|
||||
touch .env
|
||||
touch greeting.md
|
||||
echo "OPENAI_KEY=your-openai-key" >> .env
|
||||
curl https://gitgud.io/khanon/oai-reverse-proxy/-/raw/main/docker/docker-compose-selfhost.yml -o docker-compose.yml
|
||||
```
|
||||
- You can set further environment variables and keys in the `.env` file. See [.env.example](../.env.example) for a list of available options.
|
||||
- You can set a custom greeting in `greeting.md`. This will be displayed on the homepage.
|
||||
- Run `docker compose up -d`
|
||||
|
||||
You can check logs with `docker compose logs -n 100 -f`.
|
||||
|
||||
The provided docker-compose file listens on port 7860 but binds to localhost only. You should use a reverse proxy to expose the application to the internet as described in the next section.
|
||||
|
||||
## Setting up a reverse proxy
|
||||
|
||||
Rather than exposing the application directly to the internet, it is recommended to set up a reverse proxy. This will allow you to use HTTPS and add additional security measures.
|
||||
|
||||
### trycloudflare
|
||||
|
||||
This will give you a temporary (72 hours) URL that you can use to let others connect to your instance securely, without having to set up a reverse proxy. If you are running the server on your home network, this is probably the best option.
|
||||
- Install `cloudflared` following the instructions at [try.cloudflare.com](https://try.cloudflare.com/).
|
||||
- Run `cloudflared tunnel --url http://localhost:7860`
|
||||
- You will be given a temporary URL that you can share with others.
|
||||
|
||||
If you have a VPS, you should use a proper reverse proxy like nginx instead for a more permanent solution which will allow you to use your own domain name, handle SSL, and add additional security/anti-abuse measures.
|
||||
|
||||
### nginx
|
||||
|
||||
First, install nginx.
|
||||
- `sudo apt update && sudo apt install nginx`
|
||||
|
||||
#### Example basic nginx configuration (no SSL)
|
||||
|
||||
- `sudo nano /etc/nginx/sites-available/oai.conf`
|
||||
- ```
|
||||
server {
|
||||
listen 80;
|
||||
server_name example.com;
|
||||
|
||||
location / {
|
||||
proxy_pass http://localhost:7860;
|
||||
}
|
||||
}
|
||||
```
|
||||
- Replace `example.com` with your domain name.
|
||||
- Ctrl+X to exit, Y to save, Enter to confirm.
|
||||
- `sudo ln -s /etc/nginx/sites-available/oai.conf /etc/nginx/sites-enabled`
|
||||
- `sudo nginx -t`
|
||||
- This will check the configuration file for errors.
|
||||
- `sudo systemctl restart nginx`
|
||||
- This will restart nginx and apply the new configuration.
|
||||
|
||||
#### Example with Cloudflare SSL
|
||||
|
||||
This allows you to use a self-signed certificate on the server, and have Cloudflare handle client SSL. You need to have a Cloudflare account and have your domain set up with Cloudflare already, pointing to your server's IP address.
|
||||
|
||||
- Set Cloudflare to use Full SSL mode. Since we are using a self-signed certificate, don't use Full (strict) mode.
|
||||
- Create a self-signed certificate:
|
||||
- `openssl req -x509 -nodes -days 365 -newkey rsa:2048 -keyout /etc/ssl/private/nginx-selfsigned.key -out /etc/ssl/certs/nginx-selfsigned.crt`
|
||||
- `sudo nano /etc/nginx/sites-available/oai.conf`
|
||||
- ```
|
||||
server {
|
||||
listen 443 ssl;
|
||||
server_name yourdomain.com www.yourdomain.com;
|
||||
|
||||
ssl_certificate /etc/ssl/certs/nginx-selfsigned.crt;
|
||||
ssl_certificate_key /etc/ssl/private/nginx-selfsigned.key;
|
||||
|
||||
# Only allow inbound traffic from Cloudflare
|
||||
allow 173.245.48.0/20;
|
||||
allow 103.21.244.0/22;
|
||||
allow 103.22.200.0/22;
|
||||
allow 103.31.4.0/22;
|
||||
allow 141.101.64.0/18;
|
||||
allow 108.162.192.0/18;
|
||||
allow 190.93.240.0/20;
|
||||
allow 188.114.96.0/20;
|
||||
allow 197.234.240.0/22;
|
||||
allow 198.41.128.0/17;
|
||||
allow 162.158.0.0/15;
|
||||
allow 104.16.0.0/13;
|
||||
allow 104.24.0.0/14;
|
||||
allow 172.64.0.0/13;
|
||||
allow 131.0.72.0/22;
|
||||
deny all;
|
||||
|
||||
location / {
|
||||
proxy_pass http://localhost:7860;
|
||||
proxy_http_version 1.1;
|
||||
proxy_set_header Upgrade $http_upgrade;
|
||||
proxy_set_header Connection 'upgrade';
|
||||
proxy_set_header Host $host;
|
||||
proxy_cache_bypass $http_upgrade;
|
||||
}
|
||||
|
||||
ssl_protocols TLSv1.2 TLSv1.3;
|
||||
ssl_ciphers 'ECDHE-ECDSA-AES128-GCM-SHA256:ECDHE-RSA-AES128-GCM-SHA256';
|
||||
ssl_prefer_server_ciphers on;
|
||||
ssl_session_cache shared:SSL:10m;
|
||||
}
|
||||
```
|
||||
- Replace `yourdomain.com` with your domain name.
|
||||
- Ctrl+X to exit, Y to save, Enter to confirm.
|
||||
- `sudo ln -s /etc/nginx/sites-available/oai.conf /etc/nginx/sites-enabled`
|
||||
|
||||
## Updating/Restarting the application
|
||||
|
||||
After making an .env change, you need to restart the application for it to take effect.
|
||||
|
||||
- `docker compose down`
|
||||
- `docker compose up -d`
|
||||
|
||||
To update the application to the latest version:
|
||||
|
||||
- `docker compose pull`
|
||||
- `docker compose down`
|
||||
- `docker compose up -d`
|
||||
- `docker image prune -f`
|
||||
@@ -12,7 +12,6 @@ Several of these features require you to set secrets in your environment. If usi
|
||||
- [Memory](#memory)
|
||||
- [Firebase Realtime Database](#firebase-realtime-database)
|
||||
- [Firebase setup instructions](#firebase-setup-instructions)
|
||||
- [Whitelisting admin IP addresses](#whitelisting-admin-ip-addresses)
|
||||
|
||||
## No user management (`GATEKEEPER=none`)
|
||||
|
||||
@@ -62,12 +61,3 @@ To use Firebase Realtime Database to persist user data, set the following enviro
|
||||
8. Set `GATEKEEPER_STORE` to `firebase_rtdb` in your environment if you haven't already.
|
||||
|
||||
The proxy server will attempt to connect to your Firebase Realtime Database at startup and will throw an error if it cannot connect. If you see this error, check that your `FIREBASE_RTDB_URL` and `FIREBASE_KEY` secrets are set correctly.
|
||||
|
||||
## Whitelisting admin IP addresses
|
||||
You can add your own IP ranges to the `ADMIN_WHITELIST` environment variable for additional security.
|
||||
|
||||
You can provide a comma-separated list containing individual IPv4 or IPv6 addresses, or CIDR ranges.
|
||||
|
||||
To whitelist an entire IP range, use CIDR notation. For example, `192.168.0.1/24` would whitelist all addresses from `192.168.0.0` to `192.168.0.255`.
|
||||
|
||||
To disable the whitelist, set `ADMIN_WHITELIST=0.0.0.0/0,::0`, which will allow access from any IPv4 or IPv6 address. This is the default behavior.
|
||||
|
||||
@@ -1,9 +0,0 @@
|
||||
{
|
||||
"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"
|
||||
}
|
||||
}
|
||||
Generated
+841
-2953
File diff suppressed because it is too large
Load Diff
+15
-44
@@ -4,14 +4,12 @@
|
||||
"description": "Reverse proxy for the OpenAI API",
|
||||
"scripts": {
|
||||
"build": "tsc && copyfiles -u 1 src/**/*.ejs build",
|
||||
"database:migrate": "ts-node scripts/migrate.ts",
|
||||
"postinstall": "patch-package",
|
||||
"prepare": "husky install",
|
||||
"start": "node --trace-deprecation --trace-warnings build/server.js",
|
||||
"start:dev": "nodemon --watch src --exec ts-node --transpile-only src/server.ts",
|
||||
"start:debug": "ts-node --inspect --transpile-only src/server.ts",
|
||||
"start:watch": "nodemon --require source-map-support/register build/server.js",
|
||||
"type-check": "tsc --noEmit"
|
||||
"start:replit": "tsc && node build/server.js",
|
||||
"start": "node build/server.js",
|
||||
"type-check": "tsc --noEmit",
|
||||
"prepare": "husky install"
|
||||
},
|
||||
"engines": {
|
||||
"node": ">=18.0.0"
|
||||
@@ -20,53 +18,31 @@
|
||||
"license": "MIT",
|
||||
"dependencies": {
|
||||
"@anthropic-ai/tokenizer": "^0.0.4",
|
||||
"@aws-crypto/sha256-js": "^5.2.0",
|
||||
"@huggingface/jinja": "^0.3.0",
|
||||
"@node-rs/argon2": "^1.8.3",
|
||||
"@smithy/eventstream-codec": "^2.1.3",
|
||||
"@smithy/eventstream-serde-node": "^2.1.3",
|
||||
"@smithy/protocol-http": "^3.2.1",
|
||||
"@smithy/signature-v4": "^2.1.3",
|
||||
"@smithy/util-utf8": "^2.1.1",
|
||||
"axios": "^1.7.4",
|
||||
"better-sqlite3": "^10.0.0",
|
||||
"check-disk-space": "^3.4.0",
|
||||
"axios": "^1.3.5",
|
||||
"cookie-parser": "^1.4.6",
|
||||
"copyfiles": "^2.4.1",
|
||||
"cors": "^2.8.5",
|
||||
"csrf-csrf": "^2.3.0",
|
||||
"dotenv": "^16.3.1",
|
||||
"ejs": "^3.1.10",
|
||||
"express": "^4.19.3",
|
||||
"dotenv": "^16.0.3",
|
||||
"ejs": "^3.1.9",
|
||||
"express": "^4.18.2",
|
||||
"express-session": "^1.17.3",
|
||||
"firebase-admin": "^12.5.0",
|
||||
"glob": "^10.3.12",
|
||||
"firebase-admin": "^11.10.1",
|
||||
"googleapis": "^122.0.0",
|
||||
"http-proxy": "1.18.1",
|
||||
"http-proxy-middleware": "^3.0.2",
|
||||
"ipaddr.js": "^2.1.0",
|
||||
"http-proxy-middleware": "^3.0.0-beta.1",
|
||||
"memorystore": "^1.6.7",
|
||||
"multer": "^1.4.5-lts.1",
|
||||
"node-schedule": "^2.1.1",
|
||||
"patch-package": "^8.0.0",
|
||||
"pino": "^8.11.0",
|
||||
"pino-http": "^8.3.3",
|
||||
"proxy-agent": "^6.4.0",
|
||||
"sanitize-html": "^2.13.0",
|
||||
"sharp": "^0.32.6",
|
||||
"sanitize-html": "^2.11.0",
|
||||
"showdown": "^2.1.0",
|
||||
"source-map-support": "^0.5.21",
|
||||
"stream-json": "^1.8.0",
|
||||
"tiktoken": "^1.0.10",
|
||||
"tinyws": "^0.1.0",
|
||||
"uuid": "^9.0.0",
|
||||
"zlib": "^1.0.5",
|
||||
"zod": "^3.22.3",
|
||||
"zod-error": "^1.5.0"
|
||||
"zod": "^3.21.4"
|
||||
},
|
||||
"devDependencies": {
|
||||
"@smithy/types": "^3.3.0",
|
||||
"@types/better-sqlite3": "^7.6.10",
|
||||
"@types/cookie-parser": "^1.4.3",
|
||||
"@types/cors": "^2.8.13",
|
||||
"@types/express": "^4.17.17",
|
||||
@@ -75,22 +51,17 @@
|
||||
"@types/node-schedule": "^2.1.0",
|
||||
"@types/sanitize-html": "^2.9.0",
|
||||
"@types/showdown": "^2.0.0",
|
||||
"@types/stream-json": "^1.7.7",
|
||||
"@types/uuid": "^9.0.1",
|
||||
"concurrently": "^8.0.1",
|
||||
"esbuild": "^0.17.16",
|
||||
"esbuild-register": "^3.4.2",
|
||||
"husky": "^8.0.3",
|
||||
"nodemon": "^3.0.1",
|
||||
"pino-pretty": "^10.2.3",
|
||||
"prettier": "^3.0.3",
|
||||
"prettier-plugin-ejs": "^1.0.3",
|
||||
"source-map-support": "^0.5.21",
|
||||
"ts-node": "^10.9.1",
|
||||
"typescript": "^5.4.2"
|
||||
"typescript": "^5.0.4"
|
||||
},
|
||||
"overrides": {
|
||||
"node-fetch@2.x": {
|
||||
"whatwg-url": "14.x"
|
||||
}
|
||||
"google-gax": "^3.6.1"
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1,23 +0,0 @@
|
||||
# Patches
|
||||
Contains monkey patches for certain packages, applied using `patch-package`.
|
||||
|
||||
## `http-proxy+1.18.1.patch`
|
||||
Modifies the `http-proxy` package to work around an incompatibility with
|
||||
body-parser and SOCKS5 proxies due to some esoteric stream handling behavior
|
||||
when `socks-proxy-agent` is used instead of a generic http.Agent.
|
||||
|
||||
Modification involves adjusting the `buffer` property on ProxyServer's `options`
|
||||
object to be a function that returns a stream instead of a stream itself. This
|
||||
allows us to give it a function which produces a new Readable from the already-
|
||||
parsed request body.
|
||||
|
||||
With the old implementation we would need to create an entirely new ProxyServer
|
||||
instance for each request, which is not ideal under heavy load.
|
||||
|
||||
`http-proxy` hasn't been updated in six years so it's unlikely that this patch
|
||||
will be broken by future updates, but it's stil pinned to 1.18.1 for now.
|
||||
|
||||
### See also
|
||||
https://github.com/chimurai/http-proxy-middleware/issues/40
|
||||
https://github.com/chimurai/http-proxy-middleware/issues/299
|
||||
https://github.com/http-party/node-http-proxy/pull/1027
|
||||
@@ -1,13 +0,0 @@
|
||||
diff --git a/node_modules/http-proxy/lib/http-proxy/passes/web-incoming.js b/node_modules/http-proxy/lib/http-proxy/passes/web-incoming.js
|
||||
index 7ae7355..c825c27 100644
|
||||
--- a/node_modules/http-proxy/lib/http-proxy/passes/web-incoming.js
|
||||
+++ b/node_modules/http-proxy/lib/http-proxy/passes/web-incoming.js
|
||||
@@ -167,7 +167,7 @@ module.exports = {
|
||||
}
|
||||
}
|
||||
|
||||
- (options.buffer || req).pipe(proxyReq);
|
||||
+ (options.buffer(req) || req).pipe(proxyReq);
|
||||
|
||||
proxyReq.on('response', function(proxyRes) {
|
||||
if(server) { server.emit('proxyRes', proxyRes, req, res); }
|
||||
@@ -1,349 +0,0 @@
|
||||
/*! normalize.css v8.0.1 | MIT License | github.com/necolas/normalize.css */
|
||||
|
||||
/* Document
|
||||
========================================================================== */
|
||||
|
||||
/**
|
||||
* 1. Correct the line height in all browsers.
|
||||
* 2. Prevent adjustments of font size after orientation changes in iOS.
|
||||
*/
|
||||
|
||||
html {
|
||||
line-height: 1.15; /* 1 */
|
||||
-webkit-text-size-adjust: 100%; /* 2 */
|
||||
}
|
||||
|
||||
/* Sections
|
||||
========================================================================== */
|
||||
|
||||
/**
|
||||
* Remove the margin in all browsers.
|
||||
*/
|
||||
|
||||
body {
|
||||
margin: 0;
|
||||
}
|
||||
|
||||
/**
|
||||
* Render the `main` element consistently in IE.
|
||||
*/
|
||||
|
||||
main {
|
||||
display: block;
|
||||
}
|
||||
|
||||
/**
|
||||
* Correct the font size and margin on `h1` elements within `section` and
|
||||
* `article` contexts in Chrome, Firefox, and Safari.
|
||||
*/
|
||||
|
||||
h1 {
|
||||
font-size: 2em;
|
||||
margin: 0.67em 0;
|
||||
}
|
||||
|
||||
/* Grouping content
|
||||
========================================================================== */
|
||||
|
||||
/**
|
||||
* 1. Add the correct box sizing in Firefox.
|
||||
* 2. Show the overflow in Edge and IE.
|
||||
*/
|
||||
|
||||
hr {
|
||||
box-sizing: content-box; /* 1 */
|
||||
height: 0; /* 1 */
|
||||
overflow: visible; /* 2 */
|
||||
}
|
||||
|
||||
/**
|
||||
* 1. Correct the inheritance and scaling of font size in all browsers.
|
||||
* 2. Correct the odd `em` font sizing in all browsers.
|
||||
*/
|
||||
|
||||
pre {
|
||||
font-family: monospace, monospace; /* 1 */
|
||||
font-size: 1em; /* 2 */
|
||||
}
|
||||
|
||||
/* Text-level semantics
|
||||
========================================================================== */
|
||||
|
||||
/**
|
||||
* Remove the gray background on active links in IE 10.
|
||||
*/
|
||||
|
||||
a {
|
||||
background-color: transparent;
|
||||
}
|
||||
|
||||
/**
|
||||
* 1. Remove the bottom border in Chrome 57-
|
||||
* 2. Add the correct text decoration in Chrome, Edge, IE, Opera, and Safari.
|
||||
*/
|
||||
|
||||
abbr[title] {
|
||||
border-bottom: none; /* 1 */
|
||||
text-decoration: underline; /* 2 */
|
||||
text-decoration: underline dotted; /* 2 */
|
||||
}
|
||||
|
||||
/**
|
||||
* Add the correct font weight in Chrome, Edge, and Safari.
|
||||
*/
|
||||
|
||||
b,
|
||||
strong {
|
||||
font-weight: bolder;
|
||||
}
|
||||
|
||||
/**
|
||||
* 1. Correct the inheritance and scaling of font size in all browsers.
|
||||
* 2. Correct the odd `em` font sizing in all browsers.
|
||||
*/
|
||||
|
||||
code,
|
||||
kbd,
|
||||
samp {
|
||||
font-family: monospace, monospace; /* 1 */
|
||||
font-size: 1em; /* 2 */
|
||||
}
|
||||
|
||||
/**
|
||||
* Add the correct font size in all browsers.
|
||||
*/
|
||||
|
||||
small {
|
||||
font-size: 80%;
|
||||
}
|
||||
|
||||
/**
|
||||
* Prevent `sub` and `sup` elements from affecting the line height in
|
||||
* all browsers.
|
||||
*/
|
||||
|
||||
sub,
|
||||
sup {
|
||||
font-size: 75%;
|
||||
line-height: 0;
|
||||
position: relative;
|
||||
vertical-align: baseline;
|
||||
}
|
||||
|
||||
sub {
|
||||
bottom: -0.25em;
|
||||
}
|
||||
|
||||
sup {
|
||||
top: -0.5em;
|
||||
}
|
||||
|
||||
/* Embedded content
|
||||
========================================================================== */
|
||||
|
||||
/**
|
||||
* Remove the border on images inside links in IE 10.
|
||||
*/
|
||||
|
||||
img {
|
||||
border-style: none;
|
||||
}
|
||||
|
||||
/* Forms
|
||||
========================================================================== */
|
||||
|
||||
/**
|
||||
* 1. Change the font styles in all browsers.
|
||||
* 2. Remove the margin in Firefox and Safari.
|
||||
*/
|
||||
|
||||
button,
|
||||
input,
|
||||
optgroup,
|
||||
select,
|
||||
textarea {
|
||||
font-family: inherit; /* 1 */
|
||||
font-size: 100%; /* 1 */
|
||||
line-height: 1.15; /* 1 */
|
||||
margin: 0; /* 2 */
|
||||
}
|
||||
|
||||
/**
|
||||
* Show the overflow in IE.
|
||||
* 1. Show the overflow in Edge.
|
||||
*/
|
||||
|
||||
button,
|
||||
input { /* 1 */
|
||||
overflow: visible;
|
||||
}
|
||||
|
||||
/**
|
||||
* Remove the inheritance of text transform in Edge, Firefox, and IE.
|
||||
* 1. Remove the inheritance of text transform in Firefox.
|
||||
*/
|
||||
|
||||
button,
|
||||
select { /* 1 */
|
||||
text-transform: none;
|
||||
}
|
||||
|
||||
/**
|
||||
* Correct the inability to style clickable types in iOS and Safari.
|
||||
*/
|
||||
|
||||
button,
|
||||
[type="button"],
|
||||
[type="reset"],
|
||||
[type="submit"] {
|
||||
-webkit-appearance: button;
|
||||
}
|
||||
|
||||
/**
|
||||
* Remove the inner border and padding in Firefox.
|
||||
*/
|
||||
|
||||
button::-moz-focus-inner,
|
||||
[type="button"]::-moz-focus-inner,
|
||||
[type="reset"]::-moz-focus-inner,
|
||||
[type="submit"]::-moz-focus-inner {
|
||||
border-style: none;
|
||||
padding: 0;
|
||||
}
|
||||
|
||||
/**
|
||||
* Restore the focus styles unset by the previous rule.
|
||||
*/
|
||||
|
||||
button:-moz-focusring,
|
||||
[type="button"]:-moz-focusring,
|
||||
[type="reset"]:-moz-focusring,
|
||||
[type="submit"]:-moz-focusring {
|
||||
outline: 1px dotted ButtonText;
|
||||
}
|
||||
|
||||
/**
|
||||
* Correct the padding in Firefox.
|
||||
*/
|
||||
|
||||
fieldset {
|
||||
padding: 0.35em 0.75em 0.625em;
|
||||
}
|
||||
|
||||
/**
|
||||
* 1. Correct the text wrapping in Edge and IE.
|
||||
* 2. Correct the color inheritance from `fieldset` elements in IE.
|
||||
* 3. Remove the padding so developers are not caught out when they zero out
|
||||
* `fieldset` elements in all browsers.
|
||||
*/
|
||||
|
||||
legend {
|
||||
box-sizing: border-box; /* 1 */
|
||||
color: inherit; /* 2 */
|
||||
display: table; /* 1 */
|
||||
max-width: 100%; /* 1 */
|
||||
padding: 0; /* 3 */
|
||||
white-space: normal; /* 1 */
|
||||
}
|
||||
|
||||
/**
|
||||
* Add the correct vertical alignment in Chrome, Firefox, and Opera.
|
||||
*/
|
||||
|
||||
progress {
|
||||
vertical-align: baseline;
|
||||
}
|
||||
|
||||
/**
|
||||
* Remove the default vertical scrollbar in IE 10+.
|
||||
*/
|
||||
|
||||
textarea {
|
||||
overflow: auto;
|
||||
}
|
||||
|
||||
/**
|
||||
* 1. Add the correct box sizing in IE 10.
|
||||
* 2. Remove the padding in IE 10.
|
||||
*/
|
||||
|
||||
[type="checkbox"],
|
||||
[type="radio"] {
|
||||
box-sizing: border-box; /* 1 */
|
||||
padding: 0; /* 2 */
|
||||
}
|
||||
|
||||
/**
|
||||
* Correct the cursor style of increment and decrement buttons in Chrome.
|
||||
*/
|
||||
|
||||
[type="number"]::-webkit-inner-spin-button,
|
||||
[type="number"]::-webkit-outer-spin-button {
|
||||
height: auto;
|
||||
}
|
||||
|
||||
/**
|
||||
* 1. Correct the odd appearance in Chrome and Safari.
|
||||
* 2. Correct the outline style in Safari.
|
||||
*/
|
||||
|
||||
[type="search"] {
|
||||
-webkit-appearance: textfield; /* 1 */
|
||||
outline-offset: -2px; /* 2 */
|
||||
}
|
||||
|
||||
/**
|
||||
* Remove the inner padding in Chrome and Safari on macOS.
|
||||
*/
|
||||
|
||||
[type="search"]::-webkit-search-decoration {
|
||||
-webkit-appearance: none;
|
||||
}
|
||||
|
||||
/**
|
||||
* 1. Correct the inability to style clickable types in iOS and Safari.
|
||||
* 2. Change font properties to `inherit` in Safari.
|
||||
*/
|
||||
|
||||
::-webkit-file-upload-button {
|
||||
-webkit-appearance: button; /* 1 */
|
||||
font: inherit; /* 2 */
|
||||
}
|
||||
|
||||
/* Interactive
|
||||
========================================================================== */
|
||||
|
||||
/*
|
||||
* Add the correct display in Edge, IE 10+, and Firefox.
|
||||
*/
|
||||
|
||||
details {
|
||||
display: block;
|
||||
}
|
||||
|
||||
/*
|
||||
* Add the correct display in all browsers.
|
||||
*/
|
||||
|
||||
summary {
|
||||
display: list-item;
|
||||
}
|
||||
|
||||
/* Misc
|
||||
========================================================================== */
|
||||
|
||||
/**
|
||||
* Add the correct display in IE 10+.
|
||||
*/
|
||||
|
||||
template {
|
||||
display: none;
|
||||
}
|
||||
|
||||
/**
|
||||
* Add the correct display in IE 10.
|
||||
*/
|
||||
|
||||
[hidden] {
|
||||
display: none;
|
||||
}
|
||||
@@ -1,231 +0,0 @@
|
||||
/* modified https://github.com/oxalorg/sakura */
|
||||
html {
|
||||
font-size: 62.5%;
|
||||
font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto,
|
||||
"Helvetica Neue", Arial, "Noto Sans", sans-serif;
|
||||
}
|
||||
body {
|
||||
font-size: 1.8rem;
|
||||
line-height: 1.618;
|
||||
max-width: 38em;
|
||||
margin: auto;
|
||||
color: #c9c9c9;
|
||||
background-color: #222222;
|
||||
padding: 13px;
|
||||
}
|
||||
@media (max-width: 684px) {
|
||||
body {
|
||||
font-size: 1.53rem;
|
||||
}
|
||||
}
|
||||
@media (max-width: 382px) {
|
||||
body {
|
||||
font-size: 1.35rem;
|
||||
}
|
||||
}
|
||||
h1,
|
||||
h2,
|
||||
h3,
|
||||
h4,
|
||||
h5,
|
||||
h6 {
|
||||
line-height: 1.1;
|
||||
font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto,
|
||||
"Helvetica Neue", Arial, "Noto Sans", sans-serif;
|
||||
font-weight: 700;
|
||||
margin-top: 3rem;
|
||||
margin-bottom: 1.5rem;
|
||||
overflow-wrap: break-word;
|
||||
word-wrap: break-word;
|
||||
-ms-word-break: break-all;
|
||||
word-break: break-word;
|
||||
}
|
||||
h1 {
|
||||
font-size: 2.35em;
|
||||
}
|
||||
h2 {
|
||||
font-size: 2em;
|
||||
}
|
||||
h3 {
|
||||
font-size: 1.75em;
|
||||
}
|
||||
h4 {
|
||||
font-size: 1.5em;
|
||||
}
|
||||
h5 {
|
||||
font-size: 1.25em;
|
||||
}
|
||||
h6 {
|
||||
font-size: 1em;
|
||||
}
|
||||
p {
|
||||
margin-top: 0px;
|
||||
margin-bottom: 2.5rem;
|
||||
}
|
||||
small,
|
||||
sub,
|
||||
sup {
|
||||
font-size: 75%;
|
||||
}
|
||||
hr {
|
||||
border-color: #ffffff;
|
||||
}
|
||||
a {
|
||||
text-decoration: none;
|
||||
color: #ffffff;
|
||||
}
|
||||
a:visited {
|
||||
color: #e6e6e6;
|
||||
}
|
||||
a:hover {
|
||||
color: #c9c9c9;
|
||||
text-decoration: underline;
|
||||
}
|
||||
ul {
|
||||
padding-left: 1.4em;
|
||||
margin-top: 0px;
|
||||
margin-bottom: 2.5rem;
|
||||
}
|
||||
li {
|
||||
margin-bottom: 0.4em;
|
||||
}
|
||||
blockquote {
|
||||
margin-left: 0px;
|
||||
margin-right: 0px;
|
||||
padding-left: 1em;
|
||||
padding-top: 0.8em;
|
||||
padding-bottom: 0.8em;
|
||||
padding-right: 0.8em;
|
||||
border-left: 5px solid #ffffff;
|
||||
margin-bottom: 2.5rem;
|
||||
background-color: #4a4a4a;
|
||||
}
|
||||
blockquote p {
|
||||
margin-bottom: 0;
|
||||
}
|
||||
img,
|
||||
video {
|
||||
height: auto;
|
||||
max-width: 100%;
|
||||
margin-top: 0px;
|
||||
margin-bottom: 2.5rem;
|
||||
}
|
||||
pre {
|
||||
background-color: #4a4a4a;
|
||||
display: block;
|
||||
padding: 1em;
|
||||
overflow-x: auto;
|
||||
margin-top: 0px;
|
||||
margin-bottom: 2.5rem;
|
||||
font-size: 0.9em;
|
||||
}
|
||||
code,
|
||||
kbd,
|
||||
samp {
|
||||
font-size: 0.9em;
|
||||
padding: 0 0.5em;
|
||||
background-color: #4a4a4a;
|
||||
white-space: pre-wrap;
|
||||
}
|
||||
pre > code {
|
||||
padding: 0;
|
||||
background-color: transparent;
|
||||
white-space: pre;
|
||||
font-size: 1em;
|
||||
}
|
||||
table {
|
||||
text-align: justify;
|
||||
width: 100%;
|
||||
border-collapse: collapse;
|
||||
margin-bottom: 2rem;
|
||||
}
|
||||
td,
|
||||
th {
|
||||
padding: 0.5em;
|
||||
border-bottom: 1px solid #4a4a4a;
|
||||
}
|
||||
input,
|
||||
textarea {
|
||||
border: 1px solid #c9c9c9;
|
||||
}
|
||||
input:focus,
|
||||
textarea:focus {
|
||||
border: 1px solid #ffffff;
|
||||
}
|
||||
textarea {
|
||||
width: 100%;
|
||||
}
|
||||
.button,
|
||||
button,
|
||||
input[type="submit"],
|
||||
input[type="reset"],
|
||||
input[type="button"],
|
||||
input[type="file"]::file-selector-button {
|
||||
display: inline-block;
|
||||
padding: 5px 10px;
|
||||
text-align: center;
|
||||
text-decoration: none;
|
||||
white-space: nowrap;
|
||||
background-color: #ffffff;
|
||||
color: #222222;
|
||||
border-radius: 1px;
|
||||
border: 1px solid #ffffff;
|
||||
cursor: pointer;
|
||||
box-sizing: border-box;
|
||||
}
|
||||
.button[disabled],
|
||||
button[disabled],
|
||||
input[type="submit"][disabled],
|
||||
input[type="reset"][disabled],
|
||||
input[type="button"][disabled],
|
||||
input[type="file"][disabled] {
|
||||
cursor: default;
|
||||
opacity: 0.5;
|
||||
}
|
||||
.button:hover,
|
||||
button:hover,
|
||||
input[type="submit"]:hover,
|
||||
input[type="reset"]:hover,
|
||||
input[type="button"]:hover,
|
||||
input[type="file"]::file-selector-button:hover {
|
||||
background-color: #c9c9c9;
|
||||
color: #222222;
|
||||
outline: 0;
|
||||
}
|
||||
.button:focus-visible,
|
||||
button:focus-visible,
|
||||
input[type="submit"]:focus-visible,
|
||||
input[type="reset"]:focus-visible,
|
||||
input[type="button"]:focus-visible,
|
||||
input[type="file"]::file-selector-button:focus-visible {
|
||||
outline-style: solid;
|
||||
outline-width: 2px;
|
||||
}
|
||||
textarea,
|
||||
select,
|
||||
input {
|
||||
color: #c9c9c9;
|
||||
padding: 6px 10px;
|
||||
margin-bottom: 10px;
|
||||
background-color: #4a4a4a;
|
||||
border: 1px solid #4a4a4a;
|
||||
border-radius: 4px;
|
||||
box-shadow: none;
|
||||
box-sizing: border-box;
|
||||
}
|
||||
textarea:focus,
|
||||
select:focus,
|
||||
input:focus {
|
||||
border: 1px solid #ffffff;
|
||||
outline: 0;
|
||||
}
|
||||
input[type="checkbox"]:focus {
|
||||
outline: 1px dotted #ffffff;
|
||||
}
|
||||
label,
|
||||
legend,
|
||||
fieldset {
|
||||
display: block;
|
||||
margin-bottom: 0.5rem;
|
||||
font-weight: 600;
|
||||
}
|
||||
@@ -1,237 +0,0 @@
|
||||
/* modified https://github.com/oxalorg/sakura */
|
||||
:root {
|
||||
--accent-color: #4a4a4a;
|
||||
--accent-color-hover: #5a5a5a;
|
||||
--link-color: #58739c;
|
||||
--link-visted-color: #6f5e6f;
|
||||
}
|
||||
html {
|
||||
font-size: 62.5%;
|
||||
font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto,
|
||||
"Helvetica Neue", Arial, "Noto Sans", sans-serif;
|
||||
}
|
||||
body {
|
||||
font-size: 1.8rem;
|
||||
line-height: 1.618;
|
||||
max-width: 38em;
|
||||
margin: auto;
|
||||
color: #4a4a4a;
|
||||
background-color: #f9f9f9;
|
||||
padding: 13px;
|
||||
}
|
||||
@media (max-width: 684px) {
|
||||
body {
|
||||
font-size: 1.53rem;
|
||||
}
|
||||
}
|
||||
@media (max-width: 382px) {
|
||||
body {
|
||||
font-size: 1.35rem;
|
||||
}
|
||||
}
|
||||
h1,
|
||||
h2,
|
||||
h3,
|
||||
h4,
|
||||
h5,
|
||||
h6 {
|
||||
line-height: 1.1;
|
||||
font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto,
|
||||
"Helvetica Neue", Arial, "Noto Sans", sans-serif;
|
||||
font-weight: 700;
|
||||
margin-top: 3rem;
|
||||
margin-bottom: 1.5rem;
|
||||
overflow-wrap: break-word;
|
||||
word-wrap: break-word;
|
||||
-ms-word-break: break-all;
|
||||
word-break: break-word;
|
||||
}
|
||||
h1 {
|
||||
font-size: 2.35em;
|
||||
}
|
||||
h2 {
|
||||
font-size: 2em;
|
||||
}
|
||||
h3 {
|
||||
font-size: 1.75em;
|
||||
}
|
||||
h4 {
|
||||
font-size: 1.5em;
|
||||
}
|
||||
h5 {
|
||||
font-size: 1.25em;
|
||||
}
|
||||
h6 {
|
||||
font-size: 1em;
|
||||
}
|
||||
p {
|
||||
margin-top: 0;
|
||||
margin-bottom: 2.5rem;
|
||||
}
|
||||
small,
|
||||
sub,
|
||||
sup {
|
||||
font-size: 75%;
|
||||
}
|
||||
hr {
|
||||
border-color: var(--accent-color);
|
||||
}
|
||||
a {
|
||||
text-decoration: none;
|
||||
color: var(--link-color);
|
||||
}
|
||||
a:visited {
|
||||
color: var(--link-visted-color);
|
||||
}
|
||||
a:hover {
|
||||
color: var(--accent-color-hover);
|
||||
text-decoration: underline;
|
||||
}
|
||||
ul {
|
||||
padding-left: 1.4em;
|
||||
margin-top: 0;
|
||||
margin-bottom: 2.5rem;
|
||||
}
|
||||
li {
|
||||
margin-bottom: 0.4em;
|
||||
}
|
||||
blockquote {
|
||||
margin-left: 0;
|
||||
margin-right: 0;
|
||||
padding-left: 1em;
|
||||
padding-top: 0.8em;
|
||||
padding-bottom: 0.8em;
|
||||
padding-right: 0.8em;
|
||||
border-left: 5px solid var(--accent-color);
|
||||
margin-bottom: 2.5rem;
|
||||
background-color: #f1f1f1;
|
||||
}
|
||||
blockquote p {
|
||||
margin-bottom: 0;
|
||||
}
|
||||
img,
|
||||
video {
|
||||
height: auto;
|
||||
max-width: 100%;
|
||||
margin-top: 0;
|
||||
margin-bottom: 2.5rem;
|
||||
}
|
||||
pre {
|
||||
background-color: #f1f1f1;
|
||||
display: block;
|
||||
padding: 1em;
|
||||
overflow-x: auto;
|
||||
margin-top: 0;
|
||||
margin-bottom: 2.5rem;
|
||||
font-size: 0.9em;
|
||||
}
|
||||
code,
|
||||
kbd,
|
||||
samp {
|
||||
font-size: 0.9em;
|
||||
padding: 0 0.5em;
|
||||
background-color: #f1f1f1;
|
||||
white-space: pre-wrap;
|
||||
}
|
||||
pre > code {
|
||||
padding: 0;
|
||||
background-color: transparent;
|
||||
white-space: pre;
|
||||
font-size: 1em;
|
||||
}
|
||||
table {
|
||||
text-align: justify;
|
||||
width: 100%;
|
||||
border-collapse: collapse;
|
||||
margin-bottom: 2rem;
|
||||
}
|
||||
td,
|
||||
th {
|
||||
padding: 0.5em;
|
||||
border-bottom: 1px solid #f1f1f1;
|
||||
}
|
||||
input,
|
||||
textarea {
|
||||
border: 1px solid #4a4a4a;
|
||||
}
|
||||
input:focus,
|
||||
textarea:focus {
|
||||
border: 1px solid var(--accent-color);
|
||||
}
|
||||
textarea {
|
||||
width: 100%;
|
||||
}
|
||||
.button,
|
||||
button,
|
||||
input[type="submit"],
|
||||
input[type="reset"],
|
||||
input[type="button"],
|
||||
input[type="file"]::file-selector-button {
|
||||
display: inline-block;
|
||||
padding: 5px 10px;
|
||||
text-align: center;
|
||||
text-decoration: none;
|
||||
white-space: nowrap;
|
||||
background-color: var(--accent-color);
|
||||
color: #f9f9f9;
|
||||
border-radius: 2px;
|
||||
border: 1px solid var(--accent-color);
|
||||
cursor: pointer;
|
||||
box-sizing: border-box;
|
||||
}
|
||||
.button[disabled],
|
||||
button[disabled],
|
||||
input[type="submit"][disabled],
|
||||
input[type="reset"][disabled],
|
||||
input[type="button"][disabled],
|
||||
input[type="file"][disabled] {
|
||||
cursor: default;
|
||||
opacity: 0.5;
|
||||
}
|
||||
.button:hover,
|
||||
button:hover,
|
||||
input[type="submit"]:hover,
|
||||
input[type="reset"]:hover,
|
||||
input[type="button"]:hover,
|
||||
input[type="file"]::file-selector-button:hover {
|
||||
background-color: var(--accent-color-hover);
|
||||
color: #f9f9f9;
|
||||
outline: 0;
|
||||
}
|
||||
.button:focus-visible,
|
||||
button:focus-visible,
|
||||
input[type="submit"]:focus-visible,
|
||||
input[type="reset"]:focus-visible,
|
||||
input[type="button"]:focus-visible,
|
||||
input[type="file"]::file-selector-button:focus-visible {
|
||||
outline-style: solid;
|
||||
outline-width: 2px;
|
||||
}
|
||||
textarea,
|
||||
select,
|
||||
input {
|
||||
color: #4a4a4a;
|
||||
padding: 6px 10px;
|
||||
margin-bottom: 10px;
|
||||
background-color: #f1f1f1;
|
||||
border: 1px solid #f1f1f1;
|
||||
border-radius: 4px;
|
||||
box-shadow: none;
|
||||
box-sizing: border-box;
|
||||
}
|
||||
textarea:focus,
|
||||
select:focus,
|
||||
input:focus {
|
||||
border: 1px solid var(--accent-color);
|
||||
outline: 0;
|
||||
}
|
||||
input[type="checkbox"]:focus {
|
||||
outline: 1px dotted var(--accent-color);
|
||||
}
|
||||
label,
|
||||
legend,
|
||||
fieldset {
|
||||
display: block;
|
||||
margin-bottom: 0.5rem;
|
||||
font-weight: 600;
|
||||
}
|
||||
@@ -1,120 +0,0 @@
|
||||
importScripts(
|
||||
"https://cdn.jsdelivr.net/npm/hash-wasm@4.11.0/dist/argon2.umd.min.js"
|
||||
);
|
||||
|
||||
let active = false;
|
||||
let nonce = 0;
|
||||
let signature = "";
|
||||
let lastNotify = 0;
|
||||
let hashesSinceLastNotify = 0;
|
||||
let params = {
|
||||
salt: null,
|
||||
hashLength: 0,
|
||||
iterations: 0,
|
||||
memorySize: 0,
|
||||
parallelism: 0,
|
||||
targetValue: BigInt(0),
|
||||
safariFix: false,
|
||||
};
|
||||
|
||||
self.onmessage = async (event) => {
|
||||
const { data } = event;
|
||||
switch (data.type) {
|
||||
case "stop":
|
||||
active = false;
|
||||
self.postMessage({ type: "paused", hashes: hashesSinceLastNotify });
|
||||
return;
|
||||
case "start":
|
||||
active = true;
|
||||
signature = data.signature;
|
||||
nonce = data.nonce;
|
||||
|
||||
const c = data.challenge;
|
||||
const salt = new Uint8Array(c.s.length / 2);
|
||||
for (let i = 0; i < c.s.length; i += 2) {
|
||||
salt[i / 2] = parseInt(c.s.slice(i, i + 2), 16);
|
||||
}
|
||||
|
||||
params = {
|
||||
salt: salt,
|
||||
hashLength: c.hl,
|
||||
iterations: c.t,
|
||||
memorySize: c.m,
|
||||
parallelism: c.p,
|
||||
targetValue: BigInt(c.d.slice(0, -1)),
|
||||
safariFix: data.isMobileWebkit,
|
||||
};
|
||||
|
||||
console.log("Started", params);
|
||||
self.postMessage({ type: "started" });
|
||||
setTimeout(solve, 0);
|
||||
break;
|
||||
}
|
||||
};
|
||||
|
||||
const doHash = async (password) => {
|
||||
const { salt, hashLength, iterations, memorySize, parallelism } = params;
|
||||
return await self.hashwasm.argon2id({
|
||||
password,
|
||||
salt,
|
||||
hashLength,
|
||||
iterations,
|
||||
memorySize,
|
||||
parallelism,
|
||||
});
|
||||
};
|
||||
|
||||
const checkHash = (hash) => {
|
||||
const { targetValue } = params;
|
||||
const hashValue = BigInt(`0x${hash}`);
|
||||
return hashValue <= targetValue;
|
||||
};
|
||||
|
||||
const solve = async () => {
|
||||
if (!active) {
|
||||
console.log("Stopped solver", nonce);
|
||||
return;
|
||||
}
|
||||
|
||||
// Safari WASM doesn't like multiple calls in one worker
|
||||
const batchSize = 1;
|
||||
const batch = [];
|
||||
for (let i = 0; i < batchSize; i++) {
|
||||
batch.push(nonce++);
|
||||
}
|
||||
|
||||
try {
|
||||
const results = await Promise.all(
|
||||
batch.map(async (nonce) => {
|
||||
const hash = await doHash(String(nonce));
|
||||
return { hash, nonce };
|
||||
})
|
||||
);
|
||||
hashesSinceLastNotify += batchSize;
|
||||
|
||||
const solution = results.find(({ hash }) => checkHash(hash));
|
||||
if (solution) {
|
||||
console.log("Solution found", solution, params.salt);
|
||||
self.postMessage({ type: "solved", nonce: solution.nonce });
|
||||
active = false;
|
||||
} else {
|
||||
if (Date.now() - lastNotify >= 500) {
|
||||
console.log("Last nonce", nonce, "Hashes", hashesSinceLastNotify);
|
||||
self.postMessage({ type: "progress", hashes: hashesSinceLastNotify });
|
||||
lastNotify = Date.now();
|
||||
hashesSinceLastNotify = 0;
|
||||
}
|
||||
setTimeout(solve, 10);
|
||||
}
|
||||
} catch (error) {
|
||||
console.error("Error", error);
|
||||
const stack = error.stack;
|
||||
const debug = {
|
||||
stack,
|
||||
lastNonce: nonce,
|
||||
targetValue: params.targetValue,
|
||||
};
|
||||
self.postMessage({ type: "error", error: error.message, debug });
|
||||
active = false;
|
||||
}
|
||||
};
|
||||
@@ -1,39 +0,0 @@
|
||||
import Database from "better-sqlite3";
|
||||
import { DATABASE_VERSION, migrateDatabase } from "../src/shared/database";
|
||||
import { logger } from "../src/logger";
|
||||
import { config } from "../src/config";
|
||||
|
||||
const log = logger.child({ module: "scripts/migrate" });
|
||||
|
||||
async function runMigration() {
|
||||
let targetVersion = Number(process.argv[2]) || undefined;
|
||||
|
||||
if (!targetVersion) {
|
||||
log.info("Enter target version or leave empty to use the latest version.");
|
||||
process.stdin.resume();
|
||||
process.stdin.setEncoding("utf8");
|
||||
const input = await new Promise<string>((resolve) => {
|
||||
process.stdin.on("data", (text) => {
|
||||
resolve((String(text) || "").trim());
|
||||
});
|
||||
});
|
||||
process.stdin.pause();
|
||||
targetVersion = Number(input);
|
||||
if (!targetVersion) {
|
||||
targetVersion = DATABASE_VERSION;
|
||||
}
|
||||
}
|
||||
|
||||
const db = new Database(config.sqliteDataPath, {
|
||||
verbose: (msg, ...args) => log.debug({ args }, String(msg)),
|
||||
});
|
||||
|
||||
const currentVersion = db.pragma("user_version", { simple: true });
|
||||
log.info({ currentVersion, targetVersion }, "Running migrations.");
|
||||
migrateDatabase(targetVersion, db);
|
||||
}
|
||||
|
||||
runMigration().catch((error) => {
|
||||
log.error(error, "Migration failed.");
|
||||
process.exit(1);
|
||||
});
|
||||
@@ -1,309 +0,0 @@
|
||||
# OAI Reverse Proxy
|
||||
|
||||
###
|
||||
# @name OpenAI -- Chat Completions
|
||||
POST https://api.openai.com/v1/chat/completions
|
||||
Authorization: Bearer {{oai-key-1}}
|
||||
Content-Type: application/json
|
||||
|
||||
{
|
||||
"model": "gpt-3.5-turbo",
|
||||
"max_tokens": 30,
|
||||
"stream": false,
|
||||
"messages": [
|
||||
{
|
||||
"role": "user",
|
||||
"content": "This is a test prompt."
|
||||
}
|
||||
]
|
||||
}
|
||||
|
||||
###
|
||||
# @name OpenAI -- Text Completions
|
||||
POST https://api.openai.com/v1/completions
|
||||
Authorization: Bearer {{oai-key-1}}
|
||||
Content-Type: application/json
|
||||
|
||||
{
|
||||
"model": "gpt-3.5-turbo-instruct",
|
||||
"max_tokens": 30,
|
||||
"stream": false,
|
||||
"prompt": "This is a test prompt where"
|
||||
}
|
||||
|
||||
###
|
||||
# @name OpenAI -- Create Embedding
|
||||
POST https://api.openai.com/v1/embeddings
|
||||
Authorization: Bearer {{oai-key-1}}
|
||||
Content-Type: application/json
|
||||
|
||||
{
|
||||
"model": "text-embedding-ada-002",
|
||||
"input": "This is a test embedding input."
|
||||
}
|
||||
|
||||
###
|
||||
# @name OpenAI -- Get Organizations
|
||||
GET https://api.openai.com/v1/organizations
|
||||
Authorization: Bearer {{oai-key-1}}
|
||||
|
||||
###
|
||||
# @name OpenAI -- Get Models
|
||||
GET https://api.openai.com/v1/models
|
||||
Authorization: Bearer {{oai-key-1}}
|
||||
|
||||
###
|
||||
# @name Azure OpenAI -- Chat Completions
|
||||
POST https://{{azu-resource-name}}.openai.azure.com/openai/deployments/{{azu-deployment-id}}/chat/completions?api-version=2023-09-01-preview
|
||||
api-key: {{azu-key-1}}
|
||||
Content-Type: application/json
|
||||
|
||||
{
|
||||
"max_tokens": 1,
|
||||
"stream": false,
|
||||
"messages": [
|
||||
{
|
||||
"role": "user",
|
||||
"content": "This is a test prompt."
|
||||
}
|
||||
]
|
||||
}
|
||||
|
||||
###
|
||||
# @name Proxy / OpenAI -- Get Models
|
||||
GET {{proxy-host}}/proxy/openai/v1/models
|
||||
Authorization: Bearer {{proxy-key}}
|
||||
|
||||
###
|
||||
# @name Proxy / OpenAI -- Native Chat Completions
|
||||
POST {{proxy-host}}/proxy/openai/chat/completions
|
||||
Authorization: Bearer {{proxy-key}}
|
||||
Content-Type: application/json
|
||||
|
||||
{
|
||||
"model": "gpt-4-1106-preview",
|
||||
"max_tokens": 20,
|
||||
"stream": true,
|
||||
"temperature": 1,
|
||||
"seed": 123,
|
||||
"messages": [
|
||||
{
|
||||
"role": "user",
|
||||
"content": "phrase one"
|
||||
}
|
||||
]
|
||||
}
|
||||
|
||||
###
|
||||
# @name Proxy / OpenAI -- Native Text Completions
|
||||
POST {{proxy-host}}/proxy/openai/v1/turbo-instruct/chat/completions
|
||||
Authorization: Bearer {{proxy-key}}
|
||||
Content-Type: application/json
|
||||
|
||||
{
|
||||
"model": "gpt-3.5-turbo-instruct",
|
||||
"max_tokens": 20,
|
||||
"temperature": 0,
|
||||
"prompt": "Genshin Impact is a game about",
|
||||
"stream": false
|
||||
}
|
||||
|
||||
###
|
||||
# @name Proxy / OpenAI -- Chat-to-Text API Translation
|
||||
# Accepts a chat completion request and reformats it to work with the text completion API. `model` is ignored.
|
||||
POST {{proxy-host}}/proxy/openai/turbo-instruct/chat/completions
|
||||
Authorization: Bearer {{proxy-key}}
|
||||
Content-Type: application/json
|
||||
|
||||
{
|
||||
"model": "gpt-4",
|
||||
"max_tokens": 20,
|
||||
"stream": true,
|
||||
"messages": [
|
||||
{
|
||||
"role": "user",
|
||||
"content": "What is the name of the fourth president of the united states?"
|
||||
},
|
||||
{
|
||||
"role": "assistant",
|
||||
"content": "That would be George Washington."
|
||||
},
|
||||
{
|
||||
"role": "user",
|
||||
"content": "I don't think that's right..."
|
||||
}
|
||||
]
|
||||
}
|
||||
|
||||
###
|
||||
# @name Proxy / OpenAI -- Create Embedding
|
||||
POST {{proxy-host}}/proxy/openai/embeddings
|
||||
Authorization: Bearer {{proxy-key}}
|
||||
Content-Type: application/json
|
||||
|
||||
{
|
||||
"model": "text-embedding-ada-002",
|
||||
"input": "This is a test embedding input."
|
||||
}
|
||||
|
||||
|
||||
###
|
||||
# @name Proxy / Anthropic -- Native Completion (old API)
|
||||
POST {{proxy-host}}/proxy/anthropic/v1/complete
|
||||
Authorization: Bearer {{proxy-key}}
|
||||
anthropic-version: 2023-01-01
|
||||
Content-Type: application/json
|
||||
|
||||
{
|
||||
"model": "claude-v1.3",
|
||||
"max_tokens_to_sample": 20,
|
||||
"temperature": 0.2,
|
||||
"stream": true,
|
||||
"prompt": "What is genshin impact\n\n:Assistant:"
|
||||
}
|
||||
|
||||
###
|
||||
# @name Proxy / Anthropic -- Native Completion (2023-06-01 API)
|
||||
POST {{proxy-host}}/proxy/anthropic/v1/complete
|
||||
Authorization: Bearer {{proxy-key}}
|
||||
anthropic-version: 2023-06-01
|
||||
Content-Type: application/json
|
||||
|
||||
{
|
||||
"model": "claude-v1.3",
|
||||
"max_tokens_to_sample": 20,
|
||||
"temperature": 0.2,
|
||||
"stream": true,
|
||||
"prompt": "What is genshin impact\n\n:Assistant:"
|
||||
}
|
||||
|
||||
###
|
||||
# @name Proxy / Anthropic -- OpenAI-to-Anthropic API Translation
|
||||
POST {{proxy-host}}/proxy/anthropic/v1/chat/completions
|
||||
Authorization: Bearer {{proxy-key}}
|
||||
#anthropic-version: 2023-06-01
|
||||
Content-Type: application/json
|
||||
|
||||
{
|
||||
"model": "gpt-3.5-turbo",
|
||||
"max_tokens": 20,
|
||||
"stream": false,
|
||||
"temperature": 0,
|
||||
"messages": [
|
||||
{
|
||||
"role": "user",
|
||||
"content": "What is genshin impact"
|
||||
}
|
||||
]
|
||||
}
|
||||
|
||||
###
|
||||
# @name Proxy / AWS Claude -- Native Completion
|
||||
POST {{proxy-host}}/proxy/aws/claude/v1/complete
|
||||
Authorization: Bearer {{proxy-key}}
|
||||
anthropic-version: 2023-01-01
|
||||
Content-Type: application/json
|
||||
|
||||
{
|
||||
"model": "claude-v2",
|
||||
"max_tokens_to_sample": 10,
|
||||
"temperature": 0,
|
||||
"stream": true,
|
||||
"prompt": "What is genshin impact\n\n:Assistant:"
|
||||
}
|
||||
|
||||
###
|
||||
# @name Proxy / AWS Claude -- OpenAI-to-Anthropic API Translation
|
||||
POST {{proxy-host}}/proxy/aws/claude/chat/completions
|
||||
Authorization: Bearer {{proxy-key}}
|
||||
Content-Type: application/json
|
||||
|
||||
{
|
||||
"model": "gpt-3.5-turbo",
|
||||
"max_tokens": 50,
|
||||
"stream": true,
|
||||
"messages": [
|
||||
{
|
||||
"role": "user",
|
||||
"content": "What is genshin impact?"
|
||||
}
|
||||
]
|
||||
}
|
||||
|
||||
###
|
||||
# @name Proxy / GCP Claude -- Native Completion
|
||||
POST {{proxy-host}}/proxy/gcp/claude/v1/complete
|
||||
Authorization: Bearer {{proxy-key}}
|
||||
anthropic-version: 2023-01-01
|
||||
Content-Type: application/json
|
||||
|
||||
{
|
||||
"model": "claude-v2",
|
||||
"max_tokens_to_sample": 10,
|
||||
"temperature": 0,
|
||||
"stream": true,
|
||||
"prompt": "What is genshin impact\n\n:Assistant:"
|
||||
}
|
||||
|
||||
###
|
||||
# @name Proxy / GCP Claude -- OpenAI-to-Anthropic API Translation
|
||||
POST {{proxy-host}}/proxy/gcp/claude/chat/completions
|
||||
Authorization: Bearer {{proxy-key}}
|
||||
Content-Type: application/json
|
||||
|
||||
{
|
||||
"model": "gpt-3.5-turbo",
|
||||
"max_tokens": 50,
|
||||
"stream": true,
|
||||
"messages": [
|
||||
{
|
||||
"role": "user",
|
||||
"content": "What is genshin impact?"
|
||||
}
|
||||
]
|
||||
}
|
||||
|
||||
###
|
||||
# @name Proxy / Azure OpenAI -- Native Chat Completions
|
||||
POST {{proxy-host}}/proxy/azure/openai/chat/completions
|
||||
Authorization: Bearer {{proxy-key}}
|
||||
Content-Type: application/json
|
||||
|
||||
{
|
||||
"model": "gpt-4",
|
||||
"max_tokens": 20,
|
||||
"stream": true,
|
||||
"temperature": 1,
|
||||
"seed": 2,
|
||||
"messages": [
|
||||
{
|
||||
"role": "user",
|
||||
"content": "Hi what is the name of the fourth president of the united states?"
|
||||
},
|
||||
{
|
||||
"role": "assistant",
|
||||
"content": "That would be George Washington."
|
||||
},
|
||||
{
|
||||
"role": "user",
|
||||
"content": "That's not right."
|
||||
}
|
||||
]
|
||||
}
|
||||
|
||||
###
|
||||
# @name Proxy / Google AI -- OpenAI-to-Google AI API Translation
|
||||
POST {{proxy-host}}/proxy/google-ai/v1/chat/completions
|
||||
Authorization: Bearer {{proxy-key}}
|
||||
Content-Type: application/json
|
||||
|
||||
{
|
||||
"model": "gpt-4",
|
||||
"max_tokens": 42,
|
||||
"messages": [
|
||||
{
|
||||
"role": "user",
|
||||
"content": "Hi what is the name of the fourth president of the united states?"
|
||||
}
|
||||
]
|
||||
}
|
||||
@@ -1,102 +0,0 @@
|
||||
import Database from "better-sqlite3";
|
||||
import { v4 as uuidv4 } from "uuid";
|
||||
import { config } from "../src/config";
|
||||
|
||||
function generateRandomIP() {
|
||||
return (
|
||||
Math.floor(Math.random() * 255) +
|
||||
"." +
|
||||
Math.floor(Math.random() * 255) +
|
||||
"." +
|
||||
Math.floor(Math.random() * 255) +
|
||||
"." +
|
||||
Math.floor(Math.random() * 255)
|
||||
);
|
||||
}
|
||||
|
||||
function generateRandomDate() {
|
||||
const end = new Date();
|
||||
const start = new Date(end);
|
||||
start.setDate(end.getDate() - 90);
|
||||
const randomDate = new Date(
|
||||
start.getTime() + Math.random() * (end.getTime() - start.getTime())
|
||||
);
|
||||
return randomDate.toISOString();
|
||||
}
|
||||
|
||||
function generateMockSHA256() {
|
||||
const characters = 'abcdef0123456789';
|
||||
let hash = '';
|
||||
|
||||
for (let i = 0; i < 64; i++) {
|
||||
const randomIndex = Math.floor(Math.random() * characters.length);
|
||||
hash += characters[randomIndex];
|
||||
}
|
||||
|
||||
return hash;
|
||||
}
|
||||
|
||||
function getRandomModelFamily() {
|
||||
const modelFamilies = [
|
||||
"turbo",
|
||||
"gpt4",
|
||||
"gpt4-32k",
|
||||
"gpt4-turbo",
|
||||
"claude",
|
||||
"claude-opus",
|
||||
"gemini-pro",
|
||||
"mistral-tiny",
|
||||
"mistral-small",
|
||||
"mistral-medium",
|
||||
"mistral-large",
|
||||
"aws-claude",
|
||||
"aws-claude-opus",
|
||||
"gcp-claude",
|
||||
"gcp-claude-opus",
|
||||
"azure-turbo",
|
||||
"azure-gpt4",
|
||||
"azure-gpt4-32k",
|
||||
"azure-gpt4-turbo",
|
||||
"dall-e",
|
||||
"azure-dall-e",
|
||||
];
|
||||
return modelFamilies[Math.floor(Math.random() * modelFamilies.length)];
|
||||
}
|
||||
|
||||
(async () => {
|
||||
const db = new Database(config.sqliteDataPath);
|
||||
const numRows = 100;
|
||||
const insertStatement = db.prepare(`
|
||||
INSERT INTO events (type, ip, date, model, family, hashes, userToken, inputTokens, outputTokens)
|
||||
VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?)
|
||||
`);
|
||||
|
||||
const users = Array.from({ length: 10 }, () => uuidv4());
|
||||
function getRandomUser() {
|
||||
return users[Math.floor(Math.random() * users.length)];
|
||||
}
|
||||
|
||||
const transaction = db.transaction(() => {
|
||||
for (let i = 0; i < numRows; i++) {
|
||||
insertStatement.run(
|
||||
"chat_completion",
|
||||
generateRandomIP(),
|
||||
generateRandomDate(),
|
||||
getRandomModelFamily() + "-" + Math.floor(Math.random() * 100),
|
||||
getRandomModelFamily(),
|
||||
Array.from(
|
||||
{ length: Math.floor(Math.random() * 10) },
|
||||
generateMockSHA256
|
||||
).join(","),
|
||||
getRandomUser(),
|
||||
Math.floor(Math.random() * 500),
|
||||
Math.floor(Math.random() * 6000)
|
||||
);
|
||||
}
|
||||
});
|
||||
|
||||
transaction();
|
||||
|
||||
console.log(`Inserted ${numRows} rows into the events table.`);
|
||||
db.close();
|
||||
})();
|
||||
@@ -1,118 +0,0 @@
|
||||
// uses the aws sdk to sign a request, then uses axios to send it to the bedrock REST API manually
|
||||
import axios from "axios";
|
||||
import { Sha256 } from "@aws-crypto/sha256-js";
|
||||
import { SignatureV4 } from "@smithy/signature-v4";
|
||||
import { HttpRequest } from "@smithy/protocol-http";
|
||||
|
||||
const AWS_ACCESS_KEY_ID = process.env.AWS_ACCESS_KEY_ID!;
|
||||
const AWS_SECRET_ACCESS_KEY = process.env.AWS_SECRET_ACCESS_KEY!;
|
||||
|
||||
// Copied from amazon bedrock docs
|
||||
|
||||
// List models
|
||||
// ListFoundationModels
|
||||
// Service: Amazon Bedrock
|
||||
// List of Bedrock foundation models that you can use. For more information, see Foundation models in the
|
||||
// Bedrock User Guide.
|
||||
// Request Syntax
|
||||
// GET /foundation-models?
|
||||
// byCustomizationType=byCustomizationType&byInferenceType=byInferenceType&byOutputModality=byOutputModality&byProvider=byProvider
|
||||
// HTTP/1.1
|
||||
// URI Request Parameters
|
||||
// The request uses the following URI parameters.
|
||||
// byCustomizationType (p. 38)
|
||||
// List by customization type.
|
||||
// Valid Values: FINE_TUNING
|
||||
// byInferenceType (p. 38)
|
||||
// List by inference type.
|
||||
// Valid Values: ON_DEMAND | PROVISIONED
|
||||
// byOutputModality (p. 38)
|
||||
// List by output modality type.
|
||||
// Valid Values: TEXT | IMAGE | EMBEDDING
|
||||
// byProvider (p. 38)
|
||||
// A Bedrock model provider.
|
||||
// Pattern: ^[a-z0-9-]{1,63}$
|
||||
// Request Body
|
||||
// The request does not have a request body
|
||||
|
||||
// Run inference on a text model
|
||||
// Send an invoke request to run inference on a Titan Text G1 - Express model. We set the accept
|
||||
// parameter to accept any content type in the response.
|
||||
// POST https://bedrock.us-east-1.amazonaws.com/model/amazon.titan-text-express-v1/invoke
|
||||
// -H accept: */*
|
||||
// -H content-type: application/json
|
||||
// Payload
|
||||
// {"inputText": "Hello world"}
|
||||
// Example response
|
||||
// Response for the above request.
|
||||
// -H content-type: application/json
|
||||
// Payload
|
||||
// <the model response>
|
||||
|
||||
const AMZ_REGION = "us-east-1";
|
||||
const AMZ_HOST = "invoke-bedrock.us-east-1.amazonaws.com";
|
||||
|
||||
async function listModels() {
|
||||
const httpRequest = new HttpRequest({
|
||||
method: "GET",
|
||||
protocol: "https:",
|
||||
hostname: AMZ_HOST,
|
||||
path: "/foundation-models",
|
||||
headers: { ["Host"]: AMZ_HOST },
|
||||
});
|
||||
|
||||
const signedRequest = await signRequest(httpRequest);
|
||||
const response = await axios.get(
|
||||
`https://${signedRequest.hostname}${signedRequest.path}`,
|
||||
{ headers: signedRequest.headers }
|
||||
);
|
||||
console.log(response.data);
|
||||
}
|
||||
|
||||
async function invokeModel() {
|
||||
const model = "anthropic.claude-v1";
|
||||
const httpRequest = new HttpRequest({
|
||||
method: "POST",
|
||||
protocol: "https:",
|
||||
hostname: AMZ_HOST,
|
||||
path: `/model/${model}/invoke`,
|
||||
headers: {
|
||||
["Host"]: AMZ_HOST,
|
||||
["accept"]: "*/*",
|
||||
["content-type"]: "application/json",
|
||||
},
|
||||
body: JSON.stringify({
|
||||
temperature: 0.5,
|
||||
prompt: "\n\nHuman:Hello world\n\nAssistant:",
|
||||
max_tokens_to_sample: 10,
|
||||
}),
|
||||
});
|
||||
console.log("httpRequest", httpRequest);
|
||||
|
||||
const signedRequest = await signRequest(httpRequest);
|
||||
const response = await axios.post(
|
||||
`https://${signedRequest.hostname}${signedRequest.path}`,
|
||||
signedRequest.body,
|
||||
{ headers: signedRequest.headers }
|
||||
);
|
||||
console.log(response.status);
|
||||
console.log(response.headers);
|
||||
console.log(response.data);
|
||||
console.log("full url", response.request.res.responseUrl);
|
||||
}
|
||||
|
||||
async function signRequest(request: HttpRequest) {
|
||||
const signer = new SignatureV4({
|
||||
sha256: Sha256,
|
||||
credentials: {
|
||||
accessKeyId: AWS_ACCESS_KEY_ID,
|
||||
secretAccessKey: AWS_SECRET_ACCESS_KEY,
|
||||
},
|
||||
region: AMZ_REGION,
|
||||
service: "bedrock",
|
||||
});
|
||||
return await signer.sign(request, { signingDate: new Date() });
|
||||
}
|
||||
|
||||
// listModels();
|
||||
// invokeModel();
|
||||
@@ -1,45 +0,0 @@
|
||||
const axios = require("axios");
|
||||
|
||||
const concurrentRequests = 75;
|
||||
const headers = {
|
||||
Authorization: "Bearer test",
|
||||
"Content-Type": "application/json",
|
||||
};
|
||||
|
||||
const payload = {
|
||||
model: "gpt-4",
|
||||
max_tokens: 1,
|
||||
stream: false,
|
||||
messages: [{ role: "user", content: "Hi" }],
|
||||
};
|
||||
|
||||
const makeRequest = async (i) => {
|
||||
try {
|
||||
const response = await axios.post(
|
||||
"http://localhost:7860/proxy/google-ai/v1/chat/completions",
|
||||
payload,
|
||||
{ headers }
|
||||
);
|
||||
console.log(
|
||||
`Req ${i} finished with status code ${response.status} and response:`,
|
||||
response.data
|
||||
);
|
||||
} catch (error) {
|
||||
const msg = error.response
|
||||
console.error(`Error in req ${i}:`, error.message, msg || "");
|
||||
}
|
||||
};
|
||||
|
||||
const executeRequestsConcurrently = () => {
|
||||
const promises = [];
|
||||
for (let i = 1; i <= concurrentRequests; i++) {
|
||||
console.log(`Starting request ${i}`);
|
||||
promises.push(makeRequest(i));
|
||||
}
|
||||
|
||||
Promise.all(promises).then(() => {
|
||||
console.log("All requests finished");
|
||||
});
|
||||
};
|
||||
|
||||
executeRequestsConcurrently();
|
||||
@@ -1,53 +0,0 @@
|
||||
const axios = require("axios");
|
||||
|
||||
function randomInteger(max) {
|
||||
return Math.floor(Math.random() * max + 1);
|
||||
}
|
||||
|
||||
async function testQueue() {
|
||||
const requests = Array(10).fill(undefined).map(async function() {
|
||||
const maxTokens = randomInteger(2000);
|
||||
|
||||
const headers = {
|
||||
"Authorization": "Bearer test",
|
||||
"Content-Type": "application/json",
|
||||
"X-Forwarded-For": `${randomInteger(255)}.${randomInteger(255)}.${randomInteger(255)}.${randomInteger(255)}`,
|
||||
};
|
||||
|
||||
const payload = {
|
||||
model: "gpt-4o-mini-2024-07-18",
|
||||
max_tokens: 20 + maxTokens,
|
||||
stream: false,
|
||||
messages: [{role: "user", content: "You are being benchmarked regarding your reliability at outputting exact, machine-comprehensible data. Output the sentence \"The quick brown fox jumps over the lazy dog.\" Do not precede it with quotemarks or any form of preamble, and do not output anything after the sentence."}],
|
||||
temperature: 0,
|
||||
};
|
||||
|
||||
try {
|
||||
const response = await axios.post(
|
||||
"http://localhost:7860/proxy/openai/v1/chat/completions",
|
||||
payload,
|
||||
{ headers }
|
||||
);
|
||||
|
||||
if (response.status !== 200) {
|
||||
console.error(`Request {$maxTokens} finished with status code ${response.status} and response`, response.data);
|
||||
return;
|
||||
}
|
||||
|
||||
const content = response.data.choices[0].message.content;
|
||||
|
||||
console.log(
|
||||
`Request ${maxTokens} `,
|
||||
content === "The quick brown fox jumps over the lazy dog." ? "OK" : `mangled: ${content}`
|
||||
);
|
||||
} catch (error) {
|
||||
const msg = error.response;
|
||||
console.error(`Error in req ${maxTokens}:`, error.message, msg || "");
|
||||
}
|
||||
});
|
||||
|
||||
await Promise.all(requests);
|
||||
console.log("All requests finished");
|
||||
}
|
||||
|
||||
testQueue();
|
||||
@@ -1,49 +0,0 @@
|
||||
import { Router } from "express";
|
||||
import { z } from "zod";
|
||||
import { encodeCursor, decodeCursor } from "../../shared/utils";
|
||||
import { eventsRepo } from "../../shared/database/repos/event";
|
||||
|
||||
const router = Router();
|
||||
|
||||
/**
|
||||
* Returns events for the given user token.
|
||||
* GET /admin/events/:token
|
||||
* @query first - The number of events to return.
|
||||
* @query after - The cursor to start returning events from (exclusive).
|
||||
*/
|
||||
router.get("/:token", (req, res) => {
|
||||
const schema = z.object({
|
||||
token: z.string(),
|
||||
first: z.coerce.number().int().positive().max(200).default(25),
|
||||
after: z
|
||||
.string()
|
||||
.optional()
|
||||
.transform((v) => {
|
||||
try {
|
||||
return decodeCursor(v);
|
||||
} catch {
|
||||
return null;
|
||||
}
|
||||
})
|
||||
.nullable(),
|
||||
sort: z.string().optional(),
|
||||
});
|
||||
const args = schema.safeParse({ ...req.params, ...req.query });
|
||||
if (!args.success) {
|
||||
return res.status(400).json({ error: args.error });
|
||||
}
|
||||
|
||||
const data = eventsRepo
|
||||
.getUserEvents(args.data.token, {
|
||||
limit: args.data.first,
|
||||
cursor: args.data.after,
|
||||
})
|
||||
.map((e) => ({ node: e, cursor: encodeCursor(e.date) }));
|
||||
|
||||
res.json({
|
||||
data,
|
||||
endCursor: data[data.length - 1]?.cursor,
|
||||
});
|
||||
});
|
||||
|
||||
export { router as eventsApiRouter };
|
||||
+4
-26
@@ -1,31 +1,15 @@
|
||||
import express, { Router } from "express";
|
||||
import { createWhitelistMiddleware } from "../shared/cidr";
|
||||
import { authorize } from "./auth";
|
||||
import { HttpError } from "../shared/errors";
|
||||
import { injectCsrfToken, checkCsrfToken } from "../shared/inject-csrf";
|
||||
import { injectLocals } from "../shared/inject-locals";
|
||||
import { withSession } from "../shared/with-session";
|
||||
import { config } from "../config";
|
||||
import { renderPage } from "../info-page";
|
||||
import { buildInfo } from "../service-info";
|
||||
import { authorize } from "./auth";
|
||||
import { injectCsrfToken, checkCsrfToken } from "../shared/inject-csrf";
|
||||
import { loginRouter } from "./login";
|
||||
import { eventsApiRouter } from "./api/events";
|
||||
import { usersApiRouter } from "./api/users";
|
||||
import { usersApiRouter as apiRouter } from "./api/users";
|
||||
import { usersWebRouter as webRouter } from "./web/manage";
|
||||
import { logger } from "../logger";
|
||||
|
||||
const adminRouter = Router();
|
||||
|
||||
const whitelist = createWhitelistMiddleware(
|
||||
"ADMIN_WHITELIST",
|
||||
config.adminWhitelist
|
||||
);
|
||||
|
||||
if (!whitelist.ranges.length && config.adminKey?.length) {
|
||||
logger.error("ADMIN_WHITELIST is empty. No admin requests will be allowed. Set 0.0.0.0/0 to allow all.");
|
||||
}
|
||||
|
||||
adminRouter.use(whitelist);
|
||||
adminRouter.use(
|
||||
express.json({ limit: "20mb" }),
|
||||
express.urlencoded({ extended: true, limit: "20mb" })
|
||||
@@ -33,18 +17,12 @@ adminRouter.use(
|
||||
adminRouter.use(withSession);
|
||||
adminRouter.use(injectCsrfToken);
|
||||
|
||||
adminRouter.use("/users", authorize({ via: "header" }), usersApiRouter);
|
||||
adminRouter.use("/events", authorize({ via: "header" }), eventsApiRouter);
|
||||
adminRouter.use("/users", authorize({ via: "header" }), apiRouter);
|
||||
|
||||
adminRouter.use(checkCsrfToken);
|
||||
adminRouter.use(injectLocals);
|
||||
adminRouter.use("/", loginRouter);
|
||||
adminRouter.use("/manage", authorize({ via: "cookie" }), webRouter);
|
||||
adminRouter.use("/service-info", authorize({ via: "cookie" }), (req, res) => {
|
||||
return res.send(
|
||||
renderPage(buildInfo(req.protocol + "://" + req.get("host"), true))
|
||||
);
|
||||
});
|
||||
|
||||
adminRouter.use(
|
||||
(
|
||||
|
||||
+7
-212
@@ -1,5 +1,4 @@
|
||||
import { Router } from "express";
|
||||
import ipaddr from "ipaddr.js";
|
||||
import multer from "multer";
|
||||
import { z } from "zod";
|
||||
import { config } from "../../config";
|
||||
@@ -7,7 +6,7 @@ import { HttpError } from "../../shared/errors";
|
||||
import * as userStore from "../../shared/users/user-store";
|
||||
import { parseSort, sortBy, paginate } from "../../shared/utils";
|
||||
import { keyPool } from "../../shared/key-management";
|
||||
import { LLMService, MODEL_FAMILIES } from "../../shared/models";
|
||||
import { MODEL_FAMILIES } from "../../shared/models";
|
||||
import { getTokenCostUsd, prettyTokens } from "../../shared/stats";
|
||||
import {
|
||||
User,
|
||||
@@ -15,9 +14,6 @@ import {
|
||||
UserSchema,
|
||||
UserTokenCounts,
|
||||
} from "../../shared/users/schema";
|
||||
import { getLastNImages } from "../../shared/file-storage/image-history";
|
||||
import { blacklists, parseCidrs, whitelists } from "../../shared/cidr";
|
||||
import { invalidatePowChallenges } from "../../user/web/pow-captcha";
|
||||
|
||||
const router = Router();
|
||||
|
||||
@@ -43,74 +39,6 @@ router.get("/create-user", (req, res) => {
|
||||
});
|
||||
});
|
||||
|
||||
router.get("/anti-abuse", (_req, res) => {
|
||||
const wl = [...whitelists.entries()];
|
||||
const bl = [...blacklists.entries()];
|
||||
|
||||
res.render("admin_anti-abuse", {
|
||||
captchaMode: config.captchaMode,
|
||||
difficulty: config.powDifficultyLevel,
|
||||
whitelists: wl.map((w) => ({
|
||||
name: w[0],
|
||||
mode: "whitelist",
|
||||
ranges: w[1].ranges,
|
||||
})),
|
||||
blacklists: bl.map((b) => ({
|
||||
name: b[0],
|
||||
mode: "blacklist",
|
||||
ranges: b[1].ranges,
|
||||
})),
|
||||
});
|
||||
});
|
||||
|
||||
router.post("/cidr", (req, res) => {
|
||||
const body = req.body;
|
||||
const valid = z
|
||||
.object({
|
||||
action: z.enum(["add", "remove"]),
|
||||
mode: z.enum(["whitelist", "blacklist"]),
|
||||
name: z.string().min(1),
|
||||
mask: z.string().min(1),
|
||||
})
|
||||
.safeParse(body);
|
||||
|
||||
if (!valid.success) {
|
||||
throw new HttpError(
|
||||
400,
|
||||
valid.error.issues.flatMap((issue) => issue.message).join(", ")
|
||||
);
|
||||
}
|
||||
|
||||
const { mode, name, mask } = valid.data;
|
||||
const list = (mode === "whitelist" ? whitelists : blacklists).get(name);
|
||||
if (!list) {
|
||||
throw new HttpError(404, "List not found");
|
||||
}
|
||||
if (valid.data.action === "remove") {
|
||||
const newRanges = new Set(list.ranges);
|
||||
newRanges.delete(mask);
|
||||
list.updateRanges([...newRanges]);
|
||||
req.session.flash = {
|
||||
type: "success",
|
||||
message: `${mode} ${name} updated`,
|
||||
};
|
||||
return res.redirect("/admin/manage/anti-abuse");
|
||||
} else if (valid.data.action === "add") {
|
||||
const result = parseCidrs(mask);
|
||||
if (result.length === 0) {
|
||||
throw new HttpError(400, "Invalid CIDR mask");
|
||||
}
|
||||
|
||||
const newRanges = new Set([...list.ranges, mask]);
|
||||
list.updateRanges([...newRanges]);
|
||||
req.session.flash = {
|
||||
type: "success",
|
||||
message: `${mode} ${name} updated`,
|
||||
};
|
||||
return res.redirect("/admin/manage/anti-abuse");
|
||||
}
|
||||
});
|
||||
|
||||
router.post("/create-user", (req, res) => {
|
||||
const body = req.body;
|
||||
|
||||
@@ -268,21 +196,13 @@ router.post("/maintenance", (req, res) => {
|
||||
let flash = { type: "", message: "" };
|
||||
switch (action) {
|
||||
case "recheck": {
|
||||
const checkable: LLMService[] = [
|
||||
"openai",
|
||||
"anthropic",
|
||||
"aws",
|
||||
"gcp",
|
||||
"azure",
|
||||
"google-ai"
|
||||
];
|
||||
checkable.forEach((s) => keyPool.recheck(s));
|
||||
const keyCount = keyPool
|
||||
keyPool.recheck("openai");
|
||||
keyPool.recheck("anthropic");
|
||||
const size = keyPool
|
||||
.list()
|
||||
.filter((k) => checkable.includes(k.service)).length;
|
||||
|
||||
.filter((k) => k.service !== "google-palm").length;
|
||||
flash.type = "success";
|
||||
flash.message = `Scheduled recheck of ${keyCount} keys.`;
|
||||
flash.message = `Scheduled recheck of ${size} keys for OpenAI and Anthropic.`;
|
||||
break;
|
||||
}
|
||||
case "resetQuotas": {
|
||||
@@ -300,139 +220,14 @@ router.post("/maintenance", (req, res) => {
|
||||
flash.message = `All users' token usage records reset.`;
|
||||
break;
|
||||
}
|
||||
case "downloadImageMetadata": {
|
||||
const data = JSON.stringify(
|
||||
{
|
||||
exportedAt: new Date().toISOString(),
|
||||
generations: getLastNImages(),
|
||||
},
|
||||
null,
|
||||
2
|
||||
);
|
||||
res.setHeader(
|
||||
"Content-Disposition",
|
||||
`attachment; filename=image-metadata-${new Date().toISOString()}.json`
|
||||
);
|
||||
res.setHeader("Content-Type", "application/json");
|
||||
return res.send(data);
|
||||
}
|
||||
case "expireTempTokens": {
|
||||
const users = userStore.getUsers();
|
||||
const temps = users.filter((u) => u.type === "temporary");
|
||||
temps.forEach((user) => {
|
||||
user.expiresAt = Date.now();
|
||||
user.disabledReason = "Admin forced expiration.";
|
||||
userStore.upsertUser(user);
|
||||
});
|
||||
invalidatePowChallenges();
|
||||
flash.type = "success";
|
||||
flash.message = `${temps.length} temporary users marked for expiration.`;
|
||||
break;
|
||||
}
|
||||
case "cleanTempTokens": {
|
||||
const users = userStore.getUsers();
|
||||
const disabledTempUsers = users.filter(
|
||||
(u) => u.type === "temporary" && u.expiresAt && u.expiresAt < Date.now()
|
||||
);
|
||||
disabledTempUsers.forEach((user) => {
|
||||
user.disabledAt = 1; //will be cleaned up by the next cron job
|
||||
userStore.upsertUser(user);
|
||||
});
|
||||
flash.type = "success";
|
||||
flash.message = `${disabledTempUsers.length} disabled temporary users marked for cleanup.`;
|
||||
break;
|
||||
}
|
||||
case "setDifficulty": {
|
||||
const selected = req.body["pow-difficulty"];
|
||||
const valid = ["low", "medium", "high", "extreme"];
|
||||
const isNumber = Number.isInteger(Number(selected));
|
||||
if (!selected || !valid.includes(selected) && !isNumber) {
|
||||
throw new HttpError(400, "Invalid difficulty " + selected);
|
||||
}
|
||||
config.powDifficultyLevel = isNumber ? Number(selected) : selected;
|
||||
invalidatePowChallenges();
|
||||
break;
|
||||
}
|
||||
case "generateTempIpReport": {
|
||||
const tempUsers = userStore
|
||||
.getUsers()
|
||||
.filter((u) => u.type === "temporary");
|
||||
const ipv4RangeMap = new Map<string, Set<string>>();
|
||||
const ipv6RangeMap = new Map<string, Set<string>>();
|
||||
|
||||
tempUsers.forEach((u) => {
|
||||
u.ip.forEach((ip) => {
|
||||
try {
|
||||
const parsed = ipaddr.parse(ip);
|
||||
if (parsed.kind() === "ipv4") {
|
||||
const subnet =
|
||||
parsed.toNormalizedString().split(".").slice(0, 3).join(".") +
|
||||
".0/24";
|
||||
const userSet = ipv4RangeMap.get(subnet) || new Set();
|
||||
userSet.add(u.token);
|
||||
ipv4RangeMap.set(subnet, userSet);
|
||||
} else if (parsed.kind() === "ipv6") {
|
||||
const subnet =
|
||||
parsed.toNormalizedString().split(":").slice(0, 4).join(":") +
|
||||
"::/48";
|
||||
const userSet = ipv6RangeMap.get(subnet) || new Set();
|
||||
userSet.add(u.token);
|
||||
ipv6RangeMap.set(subnet, userSet);
|
||||
}
|
||||
} catch (e) {
|
||||
req.log.warn(
|
||||
{ ip, error: e.message },
|
||||
"Invalid IP address; skipping"
|
||||
);
|
||||
}
|
||||
});
|
||||
});
|
||||
|
||||
const ipv4Ranges = Array.from(ipv4RangeMap.entries())
|
||||
.map(([subnet, userSet]) => ({
|
||||
subnet,
|
||||
distinctTokens: userSet.size,
|
||||
}))
|
||||
.sort((a, b) => b.distinctTokens - a.distinctTokens);
|
||||
|
||||
const ipv6Ranges = Array.from(ipv6RangeMap.entries())
|
||||
.map(([subnet, userSet]) => ({
|
||||
subnet,
|
||||
distinctTokens: userSet.size,
|
||||
}))
|
||||
.sort((a, b) => {
|
||||
if (a.distinctTokens === b.distinctTokens) {
|
||||
return a.subnet.localeCompare(b.subnet);
|
||||
}
|
||||
return b.distinctTokens - a.distinctTokens;
|
||||
});
|
||||
|
||||
const data = JSON.stringify(
|
||||
{
|
||||
exportedAt: new Date().toISOString(),
|
||||
ipv4Ranges,
|
||||
ipv6Ranges,
|
||||
},
|
||||
null,
|
||||
2
|
||||
);
|
||||
|
||||
res.setHeader(
|
||||
"Content-Disposition",
|
||||
`attachment; filename=temp-ip-report-${new Date().toISOString()}.json`
|
||||
);
|
||||
res.setHeader("Content-Type", "application/json");
|
||||
return res.send(data);
|
||||
}
|
||||
default: {
|
||||
throw new HttpError(400, "Invalid action");
|
||||
}
|
||||
}
|
||||
|
||||
req.session.flash = flash;
|
||||
const referer = req.get("referer");
|
||||
|
||||
return res.redirect(referer || "/admin/manage");
|
||||
return res.redirect(`/admin/manage`);
|
||||
});
|
||||
|
||||
router.get("/download-stats", (_req, res) => {
|
||||
|
||||
@@ -1,160 +0,0 @@
|
||||
<%- include("partials/shared_header", { title: "Proof of Work Verification Settings - OAI Reverse Proxy Admin" }) %>
|
||||
<style>
|
||||
details {
|
||||
margin-top: 1em;
|
||||
}
|
||||
details summary {
|
||||
font-weight: bold;
|
||||
cursor: pointer;
|
||||
}
|
||||
details p {
|
||||
margin-left: 1em;
|
||||
}
|
||||
|
||||
#token-manage {
|
||||
display: flex;
|
||||
width: 100%;
|
||||
}
|
||||
#token-manage button {
|
||||
flex-grow: 1;
|
||||
margin: 0 0.5em;
|
||||
}
|
||||
</style>
|
||||
|
||||
<h1>Abuse Mitigation Settings</h1>
|
||||
<div>
|
||||
<h2>Proof-of-Work Verification</h2>
|
||||
<p>
|
||||
The Proof-of-Work difficulty level is used to determine how much work a client must perform to earn a temporary user
|
||||
token. Higher difficulty levels require more work, which can help mitigate abuse by making it more expensive for
|
||||
attackers to generate tokens. However, higher difficulty levels can also make it more difficult for legitimate users
|
||||
to generate tokens. Refer to documentation for guidance.
|
||||
</p>
|
||||
<%if (captchaMode === "none") { %>
|
||||
<p>
|
||||
<strong>PoW verification is not enabled. Set <code>CAPTCHA_MODE=proof_of_work</code> to enable.</strong>
|
||||
</p>
|
||||
<% } else { %>
|
||||
<h3>Difficulty Level</h3>
|
||||
<div>
|
||||
<label for="difficulty">Difficulty Level:</label>
|
||||
<select name="difficulty" id="difficulty" onchange="difficultyChanged(event)">
|
||||
<option value="low">Low</option>
|
||||
<option value="medium">Medium</option>
|
||||
<option value="high">High</option>
|
||||
<option value="extreme">Extreme</option>
|
||||
<option value="custom">Custom</option>
|
||||
</select>
|
||||
<div id="custom-difficulty-container" style="display: none">
|
||||
<label for="customDifficulty">Hashes required (average):</label>
|
||||
<input type="number" id="customDifficulty" value="0" min="1" max="1000000000" />
|
||||
</div>
|
||||
<button onclick='doAction("setDifficulty")'>Update Difficulty</button>
|
||||
</div>
|
||||
<div><span id="currentDifficulty">Current Difficulty: <%= difficulty %></span></div>
|
||||
<% } %>
|
||||
<form id="maintenanceForm" action="/admin/manage/maintenance" method="post">
|
||||
<input id="_csrf" type="hidden" name="_csrf" value="<%= csrfToken %>" />
|
||||
<input id="hiddenAction" type="hidden" name="action" value="" />
|
||||
<input id="hiddenDifficulty" type="hidden" name="pow-difficulty" value="" />
|
||||
</form>
|
||||
<h3>Manage Temporary User Tokens</h3>
|
||||
<div id="token-manage">
|
||||
<p><button onclick='doAction("expireTempTokens")'>🕒 Expire All Temp Tokens</button></p>
|
||||
<p><button onclick='doAction("cleanTempTokens")'>🧹 Delete Expired Temp Tokens</button></p>
|
||||
<p><button onclick='doAction("generateTempIpReport")'>📊 Generate Temp Token IP Report</button></p>
|
||||
</div>
|
||||
</div>
|
||||
<div>
|
||||
<h2>IP Whitelists and Blacklists</h2>
|
||||
<p>
|
||||
You can specify IP ranges to whitelist or blacklist from accessing the proxy. Entries can be specified as single
|
||||
addresses or
|
||||
<a href="https://en.wikipedia.org/wiki/Classless_Inter-Domain_Routing#CIDR_notation">CIDR notation</a>. IPv6 is
|
||||
supported but not recommended for use with the current version of the proxy.
|
||||
</p>
|
||||
<p>
|
||||
<strong>Note:</strong> Changes here are not persisted across server restarts. If you want to make changes permanent,
|
||||
you can copy the values to your deployment configuration.
|
||||
</p>
|
||||
<% for (let i = 0; i < whitelists.length; i++) { %>
|
||||
<%- include("partials/admin-cidr-widget", { list: whitelists[i] }) %>
|
||||
<% } %>
|
||||
<% for (let i = 0; i < blacklists.length; i++) { %>
|
||||
<%- include("partials/admin-cidr-widget", { list: blacklists[i] }) %>
|
||||
<% } %>
|
||||
<form action="/admin/manage/cidr" method="post" id="cidrForm">
|
||||
<input id="_csrf" type="hidden" name="_csrf" value="<%= csrfToken %>" />
|
||||
<input type="hidden" name="action" value="add" />
|
||||
<input type="hidden" name="name" value="" />
|
||||
<input type="hidden" name="mode" value="" />
|
||||
<input type="hidden" name="mask" value="" />
|
||||
</form>
|
||||
<details>
|
||||
<summary>Copy environment variables</summary>
|
||||
<p>
|
||||
If you have made changes with the UI, you can copy the values below to your deployment configuration to persist
|
||||
them across server restarts.
|
||||
</p>
|
||||
<pre>
|
||||
<% for (let i = 0; i < whitelists.length; i++) { %><%= whitelists[i].name %>=<%= whitelists[i].ranges.join(",") %><% } %>
|
||||
<% for (let i = 0; i < blacklists.length; i++) { %><%= blacklists[i].name %>=<%= blacklists[i].ranges.join(",") %><% } %>
|
||||
</pre>
|
||||
</details>
|
||||
</div>
|
||||
|
||||
<script>
|
||||
function difficultyChanged(event) {
|
||||
const value = event.target.value;
|
||||
if (value === "custom") {
|
||||
document.getElementById("custom-difficulty-container").style.display = "block";
|
||||
} else {
|
||||
document.getElementById("custom-difficulty-container").style.display = "none";
|
||||
}
|
||||
}
|
||||
|
||||
function doAction(action) {
|
||||
document.getElementById("hiddenAction").value = action;
|
||||
if (action === "setDifficulty") {
|
||||
const selected = document.getElementById("difficulty").value;
|
||||
const hiddenDifficulty = document.getElementById("hiddenDifficulty");
|
||||
if (selected === "custom") {
|
||||
hiddenDifficulty.value = document.getElementById("customDifficulty").value;
|
||||
} else {
|
||||
hiddenDifficulty.value = selected;
|
||||
}
|
||||
}
|
||||
document.getElementById("maintenanceForm").submit();
|
||||
}
|
||||
|
||||
function onAddCidr(event) {
|
||||
const list = event.target.dataset;
|
||||
const newMask = prompt("Enter the IP or CIDR range to add to the list:");
|
||||
if (!newMask) {
|
||||
return;
|
||||
}
|
||||
|
||||
const form = document.getElementById("cidrForm");
|
||||
form["action"].value = "add";
|
||||
form["name"].value = list.name;
|
||||
form["mode"].value = list.mode;
|
||||
form["mask"].value = newMask;
|
||||
form.submit();
|
||||
}
|
||||
|
||||
function onRemoveCidr(event) {
|
||||
const list = event.target.dataset;
|
||||
const removeMask = event.target.dataset.mask;
|
||||
if (!removeMask) {
|
||||
return;
|
||||
}
|
||||
|
||||
const form = document.getElementById("cidrForm");
|
||||
form["action"].value = "remove";
|
||||
form["name"].value = list.name;
|
||||
form["mode"].value = list.mode;
|
||||
form["mask"].value = removeMask;
|
||||
form.submit();
|
||||
}
|
||||
</script>
|
||||
<%- include("partials/admin-footer") %>
|
||||
@@ -51,8 +51,9 @@
|
||||
<legend>Temporary User Options</legend>
|
||||
<div class="temporary-user-fieldset">
|
||||
<p class="full-width">
|
||||
Temporary users will be disabled after the specified duration, and their records will be permanently deleted after some time.
|
||||
These options apply only to new temporary users; existing ones use whatever options were in effect when they were created.
|
||||
Temporary users will be disabled after the specified duration, and their records will be deleted 72 hours after that.
|
||||
These options apply only to new
|
||||
temporary users; existing ones use whatever options were in effect when they were created.
|
||||
</p>
|
||||
<label for="temporaryUserDuration" class="full-width">Access duration (in minutes)</label>
|
||||
<input type="number" name="temporaryUserDuration" id="temporaryUserDuration" value="60" class="full-width" />
|
||||
|
||||
@@ -5,6 +5,18 @@
|
||||
flex-direction: column;
|
||||
}
|
||||
|
||||
#statsForm div {
|
||||
display: flex;
|
||||
flex-direction: row;
|
||||
margin-bottom: 0.5em;
|
||||
}
|
||||
|
||||
#statsForm div label {
|
||||
width: 6em;
|
||||
text-align: right;
|
||||
margin-right: 1em;
|
||||
}
|
||||
|
||||
#statsForm ul {
|
||||
margin: 0;
|
||||
padding-left: 2em;
|
||||
@@ -21,17 +33,17 @@
|
||||
}
|
||||
</style>
|
||||
<h1>Download Stats</h1>
|
||||
<p>Download usage statistics to a Markdown document. You can paste this into a service like Rentry.org to share it.</p>
|
||||
<p>
|
||||
Download usage statistics to a Markdown document. You can paste this into a service like Rentry.org to share it.
|
||||
</p>
|
||||
<div>
|
||||
<h3>Options</h3>
|
||||
<form
|
||||
id="statsForm"
|
||||
action="/admin/manage/generate-stats"
|
||||
method="post"
|
||||
style="display: flex; flex-direction: column">
|
||||
<form id="statsForm" action="/admin/manage/generate-stats" method="post"
|
||||
style="display: flex; flex-direction: column;">
|
||||
<input id="_csrf" type="hidden" name="_csrf" value="<%= csrfToken %>" />
|
||||
<div>
|
||||
<label for="anon"><input id="anon" type="checkbox" name="anon" value="true" /> <span>Anonymize</span></label>
|
||||
<label for="anon">Anonymize</label>
|
||||
<input id="anon" type="checkbox" name="anon" value="true" />
|
||||
</div>
|
||||
<div>
|
||||
<label for="sort">Sort</label>
|
||||
@@ -52,12 +64,11 @@
|
||||
</select>
|
||||
</div>
|
||||
<div>
|
||||
<label for="format">Custom Format</label>
|
||||
<ul>
|
||||
<li><code>{{header}}</code></li>
|
||||
<li><code>{{stats}}</code></li>
|
||||
<li><code>{{time}}</code></li>
|
||||
</ul>
|
||||
<label for="format">Custom Format <ul>
|
||||
<li><code>{{header}}</code></li>
|
||||
<li><code>{{stats}}</code></li>
|
||||
<li><code>{{time}}</code></li>
|
||||
</ul></label>
|
||||
<textarea id="format" name="format" rows="10" cols="50" placeholder="{{stats}}">
|
||||
# Stats
|
||||
{{header}}
|
||||
@@ -104,35 +115,33 @@
|
||||
loadDefaults();
|
||||
|
||||
async function fetchAndCopy() {
|
||||
const form = document.getElementById("statsForm");
|
||||
const form = document.getElementById('statsForm');
|
||||
const formData = new FormData(form);
|
||||
|
||||
const response = await fetch(form.action, {
|
||||
method: "POST",
|
||||
headers: { "Content-Type": "application/x-www-form-urlencoded" },
|
||||
credentials: "same-origin",
|
||||
method: 'POST',
|
||||
headers: { 'Content-Type': 'application/x-www-form-urlencoded' },
|
||||
credentials: 'same-origin',
|
||||
body: new URLSearchParams(formData),
|
||||
});
|
||||
|
||||
|
||||
if (response.ok) {
|
||||
const content = await response.text();
|
||||
copyToClipboard(content);
|
||||
} else {
|
||||
throw new Error("Failed to fetch generated stats. Try reloading the page.");
|
||||
throw new Error('Failed to fetch generated stats. Try reloading the page.');
|
||||
}
|
||||
}
|
||||
|
||||
function copyToClipboard(text) {
|
||||
navigator.clipboard
|
||||
.writeText(text)
|
||||
.then(() => {
|
||||
alert("Copied to clipboard");
|
||||
})
|
||||
.catch((err) => {
|
||||
alert("Failed to copy to clipboard. Try downloading the file instead.");
|
||||
});
|
||||
navigator.clipboard.writeText(text).then(() => {
|
||||
alert('Copied to clipboard');
|
||||
}).catch(err => {
|
||||
alert('Failed to copy to clipboard. Try downloading the file instead.');
|
||||
});
|
||||
}
|
||||
|
||||
document.getElementById("copyButton").addEventListener("click", fetchAndCopy);
|
||||
document.getElementById('copyButton').addEventListener('click', fetchAndCopy);
|
||||
</script>
|
||||
<%- include("partials/admin-footer") %>
|
||||
|
||||
@@ -1,11 +1,5 @@
|
||||
<%- 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 />
|
||||
@@ -25,14 +19,12 @@
|
||||
<li><a href="/admin/manage/import-users">Import Users</a></li>
|
||||
<li><a href="/admin/manage/export-users">Export Users</a></li>
|
||||
<li><a href="/admin/manage/download-stats">Download Rentry Stats</a>
|
||||
<li><a href="/admin/manage/anti-abuse">Abuse Mitigation Settings</a></li>
|
||||
<li><a href="/admin/service-info">Service Info</a></li>
|
||||
</ul>
|
||||
<h3>Maintenance</h3>
|
||||
<form id="maintenanceForm" action="/admin/manage/maintenance" method="post">
|
||||
<input id="_csrf" type="hidden" name="_csrf" value="<%= csrfToken %>" />
|
||||
<input id="hiddenAction" type="hidden" name="action" value="" />
|
||||
<div>
|
||||
<div display="flex" flex-direction="column">
|
||||
<fieldset>
|
||||
<legend>Key Recheck</legend>
|
||||
<button id="recheck-keys" type="button" onclick="submitForm('recheck')">Force Key Recheck</button>
|
||||
@@ -43,7 +35,7 @@
|
||||
<legend>Bulk Quota Management</legend>
|
||||
<p>
|
||||
<button id="refresh-quotas" type="button" onclick="submitForm('resetQuotas')">Refresh All Quotas</button>
|
||||
Immediately refreshes all users' quotas by the configured amounts.
|
||||
Resets all users' quotas to the values set in the <code>TOKEN_QUOTA_*</code> environment variables.
|
||||
</p>
|
||||
<p>
|
||||
<button id="clear-token-counts" type="button" onclick="submitForm('resetCounts')">Clear All Token Counts</button>
|
||||
@@ -51,13 +43,6 @@
|
||||
</p>
|
||||
</fieldset>
|
||||
<% } %>
|
||||
<% if (imageGenerationEnabled) { %>
|
||||
<fieldset>
|
||||
<legend>Image Generation</legend>
|
||||
<button id="download-image-metadata" type="button" onclick="submitForm('downloadImageMetadata')">Download Image Metadata</button>
|
||||
<label for="download-image-metadata">Downloads a metadata file containing URL, prompt, and truncated user token for all cached images.</label>
|
||||
</fieldset>
|
||||
<% } %>
|
||||
</div>
|
||||
</form>
|
||||
|
||||
|
||||
@@ -4,8 +4,9 @@
|
||||
<% if (users.length === 0) { %>
|
||||
<p>No users found.</p>
|
||||
<% } else { %>
|
||||
<label for="toggle-nicknames"><input type="checkbox" id="toggle-nicknames" onchange="toggleNicknames()" /> Show Nicknames</label>
|
||||
<table class="striped full-width">
|
||||
<input type="checkbox" id="toggle-nicknames" onchange="toggleNicknames()" />
|
||||
<label for="toggle-nicknames">Show Nicknames</label>
|
||||
<table>
|
||||
<thead>
|
||||
<tr>
|
||||
<th>User</th>
|
||||
|
||||
@@ -55,9 +55,8 @@
|
||||
<td><%- user.disabledReason %></td>
|
||||
<% if (user.disabledAt) { %>
|
||||
<td class="actions">
|
||||
<a title="Edit" id="edit-disabledReason" href="#" data-field="disabledReason" data-token="<%= user.token %>"
|
||||
>✏️</a
|
||||
>
|
||||
<a title="Edit" id="edit-disabledReason" href="#" data-field="disabledReason"
|
||||
data-token="<%= user.token %>">✏️</a>
|
||||
</td>
|
||||
<% } %>
|
||||
</tr>
|
||||
@@ -73,8 +72,7 @@
|
||||
<td colspan="2"><%- include("partials/shared_user_ip_list", { user, shouldRedact: false }) %></td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th scope="row">
|
||||
Admin Note <span title="Unlike nickname, this is not visible to or editable by the user">🔒</span>
|
||||
<th scope="row">Admin Note <span title="Unlike nickname, this is not visible to or editable by the user">🔒</span>
|
||||
</th>
|
||||
<td><%- user.adminNote ?? "none" %></td>
|
||||
<td class="actions">
|
||||
@@ -87,24 +85,14 @@
|
||||
<td colspan="2"><%- user.expiresAt %></td>
|
||||
</tr>
|
||||
<% } %>
|
||||
<% if (user.meta) { %>
|
||||
<tr>
|
||||
<th scope="row">Meta</th>
|
||||
<td colspan="2"><%- JSON.stringify(user.meta) %></td>
|
||||
</tr>
|
||||
<% } %>
|
||||
</tbody>
|
||||
</table>
|
||||
|
||||
<form style="display: none" id="current-values">
|
||||
<form style="display:none" id="current-values">
|
||||
<input type="hidden" name="token" value="<%- user.token %>" />
|
||||
<% ["nickname", "type", "disabledAt", "disabledReason", "maxIps", "adminNote"].forEach(function (key) { %>
|
||||
<input type="hidden" name="<%- key %>" value="<%- user[key] %>" />
|
||||
<% }); %>
|
||||
<!-- tokenRefresh_ keys are dynamically generated -->
|
||||
<% Object.entries(quota).forEach(([family]) => { %>
|
||||
<input type="hidden" name="tokenRefresh_<%- family %>" value="<%- user.tokenRefresh[family] || quota[family] %>" />
|
||||
<% }); %>
|
||||
</form>
|
||||
|
||||
<h3>Quota Information</h3>
|
||||
@@ -114,8 +102,7 @@
|
||||
<input type="hidden" name="_csrf" value="<%- csrfToken %>" />
|
||||
<button type="submit" class="btn btn-primary">Refresh Quotas for User</button>
|
||||
</form>
|
||||
<% } %>
|
||||
<%- include("partials/shared_quota-info", { quota, user, showRefreshEdit: true }) %>
|
||||
<% } %> <%- include("partials/shared_quota-info", { quota, user }) %>
|
||||
|
||||
<p><a href="/admin/manage/list-users">Back to User List</a></p>
|
||||
|
||||
@@ -126,25 +113,18 @@
|
||||
const token = a.dataset.token;
|
||||
const field = a.dataset.field;
|
||||
const existingValue = document.querySelector(`#current-values input[name=${field}]`).value;
|
||||
|
||||
let value = prompt(`Enter new value for '${field}':`, existingValue);
|
||||
let value = prompt(`Enter new value for '${field}'':`, existingValue);
|
||||
if (value !== null) {
|
||||
if (value === "") {
|
||||
value = null;
|
||||
}
|
||||
|
||||
const payload = { _csrf: document.querySelector("meta[name=csrf-token]").getAttribute("content") };
|
||||
if (field.startsWith("tokenRefresh_")) {
|
||||
const family = field.slice("tokenRefresh_".length);
|
||||
payload.tokenRefresh = { [family]: Number(value) };
|
||||
} else {
|
||||
payload[field] = value;
|
||||
}
|
||||
|
||||
fetch(`/admin/manage/edit-user/${token}`, {
|
||||
method: "POST",
|
||||
credentials: "same-origin",
|
||||
body: JSON.stringify(payload),
|
||||
body: JSON.stringify({
|
||||
[field]: value,
|
||||
_csrf: document.querySelector("meta[name=csrf-token]").getAttribute("content"),
|
||||
}),
|
||||
headers: { "Content-Type": "application/json", Accept: "application/json" },
|
||||
})
|
||||
.then((res) => Promise.all([res.ok, res.json()]))
|
||||
@@ -152,7 +132,9 @@
|
||||
const url = new URL(window.location.href);
|
||||
const params = new URLSearchParams();
|
||||
if (!ok) {
|
||||
alert(`Failed to edit user: ${json.message}`);
|
||||
params.set("flash", `error: ${json.error.message}`);
|
||||
} else {
|
||||
params.set("flash", `success: User's ${field} updated.`);
|
||||
}
|
||||
url.search = params.toString();
|
||||
window.location.assign(url);
|
||||
@@ -162,5 +144,4 @@
|
||||
});
|
||||
</script>
|
||||
|
||||
<%- include("partials/admin-ban-xhr-script") %>
|
||||
<%- include("partials/admin-footer") %>
|
||||
<%- include("partials/admin-ban-xhr-script") %> <%- include("partials/admin-footer") %>
|
||||
|
||||
@@ -1,13 +0,0 @@
|
||||
<h3>
|
||||
<%= list.name %>
|
||||
(<%= list.mode %>)
|
||||
</h3>
|
||||
<ul>
|
||||
<% list.ranges.forEach(function(mask) { %>
|
||||
<li>
|
||||
<%= mask %>
|
||||
<button class="remove" data-mode="<%= list.mode %>" data-name="<%= list.name %>" data-mask="<%= mask %>" onclick="onRemoveCidr(event)">Remove</button>
|
||||
</li>
|
||||
<% }); %>
|
||||
</ul>
|
||||
<button class="add" data-mode="<%= list.mode %>" data-name="<%= list.name %>" onclick="onAddCidr(event)">Add</button>
|
||||
+85
-513
@@ -1,68 +1,25 @@
|
||||
import crypto from "crypto";
|
||||
import dotenv from "dotenv";
|
||||
import type firebase from "firebase-admin";
|
||||
import path from "path";
|
||||
import pino from "pino";
|
||||
import type { LLMService, ModelFamily } from "./shared/models";
|
||||
import { MODEL_FAMILIES } from "./shared/models";
|
||||
|
||||
import type { ModelFamily } from "./shared/models";
|
||||
dotenv.config();
|
||||
|
||||
// Can't import the usual logger here because it itself needs the 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 PromptLoggingBackend = "google_sheets";
|
||||
|
||||
type Config = {
|
||||
/** The port the proxy server will listen on. */
|
||||
port: number;
|
||||
/** The network interface the proxy server will listen on. */
|
||||
bindAddress: string;
|
||||
/** Comma-delimited list of OpenAI API keys. */
|
||||
openaiKey?: string;
|
||||
/** Comma-delimited list of Anthropic API keys. */
|
||||
anthropicKey?: string;
|
||||
/**
|
||||
* Comma-delimited list of Google AI API keys. Note that these are not the
|
||||
* same as the GCP keys/credentials used for Vertex AI; the models are the
|
||||
* same but the APIs are different. Vertex is the GCP product for enterprise.
|
||||
**/
|
||||
googleAIKey?: string;
|
||||
/**
|
||||
* Comma-delimited list of Mistral AI API keys.
|
||||
*/
|
||||
mistralAIKey?: string;
|
||||
/**
|
||||
* Comma-delimited list of AWS credentials. Each credential item should be a
|
||||
* colon-delimited list of access key, secret key, and AWS region.
|
||||
*
|
||||
* The credentials must have access to the actions `bedrock:InvokeModel` and
|
||||
* `bedrock:InvokeModelWithResponseStream`. You must also have already
|
||||
* provisioned the necessary models in your AWS account, on the specific
|
||||
* regions specified for each credential. Models are region-specific.
|
||||
*
|
||||
* @example `AWS_CREDENTIALS=access_key_1:secret_key_1:us-east-1,access_key_2:secret_key_2:us-west-2`
|
||||
*/
|
||||
awsCredentials?: string;
|
||||
/**
|
||||
* Comma-delimited list of GCP credentials. Each credential item should be a
|
||||
* colon-delimited list of access key, secret key, and GCP region.
|
||||
*
|
||||
* @example `GCP_CREDENTIALS=project1:1@1.com:us-east5:-----BEGIN PRIVATE KEY-----xxx-----END PRIVATE KEY-----,project2:2@2.com:us-east5:-----BEGIN PRIVATE KEY-----xxx-----END PRIVATE KEY-----`
|
||||
*/
|
||||
gcpCredentials?: string;
|
||||
/**
|
||||
* Comma-delimited list of Azure OpenAI credentials. Each credential item
|
||||
* should be a colon-delimited list of Azure resource name, deployment ID, and
|
||||
* 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;
|
||||
/** Comma-delimited list of Google PaLM API keys. */
|
||||
googlePalmKey?: string;
|
||||
/**
|
||||
* The proxy key to require for requests. Only applicable if the user
|
||||
* management mode is set to 'proxy_key', and required if so.
|
||||
@@ -73,11 +30,6 @@ type Config = {
|
||||
* management mode is set to 'user_token'.
|
||||
*/
|
||||
adminKey?: string;
|
||||
/**
|
||||
* The password required to view the service info/status page. If not set, the
|
||||
* info page will be publicly accessible.
|
||||
*/
|
||||
serviceInfoPassword?: string;
|
||||
/**
|
||||
* Which user management mode to use.
|
||||
* - `none`: No user management. Proxy is open to all requests with basic
|
||||
@@ -105,81 +57,13 @@ type Config = {
|
||||
*/
|
||||
firebaseKey?: string;
|
||||
/**
|
||||
* Maximum number of IPs allowed per user token.
|
||||
* Maximum number of IPs per user, after which their token is disabled.
|
||||
* 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;
|
||||
/**
|
||||
* 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;
|
||||
/**
|
||||
* Which captcha verification mode to use. Requires `user_token` gatekeeper.
|
||||
* Allows users to automatically obtain a token by solving a captcha.
|
||||
* - `none`: No captcha verification; tokens are issued manually.
|
||||
* - `proof_of_work`: Users must solve an Argon2 proof of work to obtain a
|
||||
* temporary usertoken valid for a limited period.
|
||||
*/
|
||||
captchaMode: "none" | "proof_of_work";
|
||||
/**
|
||||
* Duration (in hours) for which a PoW-issued temporary user token is valid.
|
||||
*/
|
||||
powTokenHours: number;
|
||||
/**
|
||||
* The maximum number of IPs from which a single temporary user token can be
|
||||
* used. Upon reaching the limit, the `maxIpsAutoBan` behavior is triggered.
|
||||
*/
|
||||
powTokenMaxIps: number;
|
||||
/**
|
||||
* Difficulty level for the proof-of-work challenge.
|
||||
* - `low`: 200 iterations
|
||||
* - `medium`: 900 iterations
|
||||
* - `high`: 1900 iterations
|
||||
* - `extreme`: 4000 iterations
|
||||
* - `number`: A custom number of iterations to use.
|
||||
*
|
||||
* Difficulty level only affects the number of iterations used in the PoW,
|
||||
* not the complexity of the hash itself. Therefore, the average time-to-solve
|
||||
* will scale linearly with the number of iterations.
|
||||
*
|
||||
* Refer to docs/proof-of-work.md for guidance and hashrate benchmarks.
|
||||
*/
|
||||
powDifficultyLevel: "low" | "medium" | "high" | "extreme" | number;
|
||||
/**
|
||||
* Duration (in minutes) before a PoW challenge expires. Users' browsers must
|
||||
* solve the challenge within this time frame or it will be rejected. Should
|
||||
* be kept somewhat low to prevent abusive clients from working on many
|
||||
* challenges in parallel, but you may need to increase this value for higher
|
||||
* difficulty levels or older devices will not be able to solve the challenge
|
||||
* in time.
|
||||
*
|
||||
* Defaults to 30 minutes.
|
||||
*/
|
||||
powChallengeTimeout: number;
|
||||
/**
|
||||
* Duration (in hours) before expired temporary user tokens are purged from
|
||||
* the user database. Users can refresh expired tokens by solving a faster PoW
|
||||
* challenge as long as the original token has not been purged. Once purged,
|
||||
* the user must solve a full PoW challenge to obtain a new token.
|
||||
*
|
||||
* Defaults to 48 hours. At 0, tokens are purged immediately upon expiry.
|
||||
*/
|
||||
powTokenPurgeHours: number;
|
||||
/**
|
||||
* Maximum number of active temporary user tokens that can be associated with
|
||||
* a single IP address. Note that this may impact users sending requests from
|
||||
* hosted AI chat clients such as Agnaistic or RisuAI, as they may share IPs.
|
||||
*
|
||||
* When the limit is reached, the oldest token with the same IP will be
|
||||
* expired. At 0, no limit is enforced. Defaults to 0.
|
||||
*/
|
||||
// powMaxTokensPerIp: number;
|
||||
/** Per-user limit for requests per minute to text and chat models. */
|
||||
textModelRateLimit: number;
|
||||
/** Per-user limit for requests per minute to image generation models. */
|
||||
imageModelRateLimit: number;
|
||||
/** Per-IP limit for requests per minute to OpenAI's completions endpoint. */
|
||||
modelRateLimit: number;
|
||||
/**
|
||||
* For OpenAI, the maximum number of context tokens (prompt + max output) a
|
||||
* user can request before their request is rejected.
|
||||
@@ -198,55 +82,16 @@ type Config = {
|
||||
maxOutputTokensOpenAI: number;
|
||||
/** For Anthropic, the maximum number of sampled tokens a user can request. */
|
||||
maxOutputTokensAnthropic: number;
|
||||
/** Whether requests containing the following phrases should be rejected. */
|
||||
rejectPhrases: string[];
|
||||
/** Whether requests containing disallowed characters should be rejected. */
|
||||
rejectDisallowed?: boolean;
|
||||
/** Message to return when rejecting requests. */
|
||||
rejectMessage: string;
|
||||
rejectMessage?: string;
|
||||
/** Verbosity level of diagnostic logging. */
|
||||
logLevel: "trace" | "debug" | "info" | "warn" | "error";
|
||||
/**
|
||||
* Whether to allow the usage of AWS credentials which could be logging users'
|
||||
* model invocations. By default, such keys are treated as if they were
|
||||
* disabled because users may not be aware that their usage is being logged.
|
||||
*
|
||||
* Some credentials do not have the policy attached that allows the proxy to
|
||||
* confirm logging status, in which case the proxy assumes that logging could
|
||||
* be enabled and will refuse to use the key. If you still want to use such a
|
||||
* key and can't attach the policy, you can set this to true.
|
||||
*/
|
||||
allowAwsLogging?: boolean;
|
||||
/**
|
||||
* Path to the SQLite database file for storing data such as event logs. By
|
||||
* default, the database will be stored at `data/database.sqlite`.
|
||||
*
|
||||
* Ensure target is writable by the server process, and be careful not to
|
||||
* select a path that is served publicly. The default path is safe.
|
||||
*/
|
||||
sqliteDataPath?: string;
|
||||
/**
|
||||
* Whether to log events, such as generated completions, to the database.
|
||||
* Events are associated with IP+user token pairs. If user_token mode is
|
||||
* disabled, no events will be logged.
|
||||
*
|
||||
* Currently there is no pruning mechanism for the events table, so it will
|
||||
* grow indefinitely. You may want to periodically prune the table manually.
|
||||
*/
|
||||
eventLogging?: boolean;
|
||||
/**
|
||||
* When hashing prompt histories, how many messages to trim from the end.
|
||||
* If zero, only the full prompt hash will be stored.
|
||||
* If greater than zero, for each number N, a hash of the prompt with the
|
||||
* last N messages removed will be stored.
|
||||
*
|
||||
* Experimental function, config may change in future versions.
|
||||
*/
|
||||
eventLoggingTrim?: number;
|
||||
/** Whether prompts and responses should be logged to persistent storage. */
|
||||
promptLogging?: boolean;
|
||||
/** Which prompt logging backend to use. */
|
||||
promptLoggingBackend?: "google_sheets" | "file";
|
||||
/** Prefix for prompt logging files when using the file backend. */
|
||||
promptLoggingFilePrefix?: string;
|
||||
promptLoggingBackend?: PromptLoggingBackend;
|
||||
/** Base64-encoded Google Sheets API key. */
|
||||
googleSheetsKey?: string;
|
||||
/** Google Sheets spreadsheet ID. */
|
||||
@@ -265,7 +110,7 @@ type Config = {
|
||||
blockedOrigins?: string;
|
||||
/** Message to return when rejecting requests from blocked origins. */
|
||||
blockMessage?: string;
|
||||
/** Destination URL to redirect blocked requests to, for non-JSON requests. */
|
||||
/** Desination URL to redirect blocked requests to, for non-JSON requests. */
|
||||
blockRedirect?: string;
|
||||
/** Which model families to allow requests for. Applies only to OpenAI. */
|
||||
allowedModelFamilies: ModelFamily[];
|
||||
@@ -288,188 +133,43 @@ 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;
|
||||
/**
|
||||
* Trusted proxy hops. If you are deploying the server behind a reverse proxy
|
||||
* (Nginx, Cloudflare Tunnel, AWS WAF, etc.) the IP address of incoming
|
||||
* requests will be the IP address of the proxy, not the actual user.
|
||||
*
|
||||
* Depending on your hosting configuration, there may be multiple proxies/load
|
||||
* balancers between your server and the user. Each one will append the
|
||||
* incoming IP address to the `X-Forwarded-For` header. The user's real IP
|
||||
* address will be the first one in the list, assuming the header has not been
|
||||
* tampered with. Setting this value correctly ensures that the server doesn't
|
||||
* trust values in `X-Forwarded-For` not added by trusted proxies.
|
||||
*
|
||||
* In order for the server to determine the user's real IP address, you need
|
||||
* to tell it how many proxies are between the user and the server so it can
|
||||
* select the correct IP address from the `X-Forwarded-For` header.
|
||||
*
|
||||
* *WARNING:* If you set it incorrectly, the proxy will either record the
|
||||
* wrong IP address, or it will be possible for users to spoof their IP
|
||||
* addresses and bypass rate limiting. Check the request logs to see what
|
||||
* incoming X-Forwarded-For values look like.
|
||||
*
|
||||
* Examples:
|
||||
* - X-Forwarded-For: "34.1.1.1, 172.1.1.1, 10.1.1.1" => trustedProxies: 3
|
||||
* - X-Forwarded-For: "34.1.1.1" => trustedProxies: 1
|
||||
* - no X-Forwarded-For header => trustedProxies: 0 (the actual IP of the incoming request will be used)
|
||||
*
|
||||
* As of 2024/01/08:
|
||||
* For HuggingFace or Cloudflare Tunnel, use 1.
|
||||
* For Render, use 3.
|
||||
* For deployments not behind a load balancer, use 0.
|
||||
*
|
||||
* You should double check against your actual request logs to be sure.
|
||||
*
|
||||
* Defaults to 1, as most deployments are on HuggingFace or Cloudflare Tunnel.
|
||||
*/
|
||||
trustedProxies?: number;
|
||||
/**
|
||||
* Whether to allow OpenAI tool usage. The proxy doesn't impelment any
|
||||
* support for tools/function calling but can pass requests and responses as
|
||||
* is. Note that the proxy also cannot accurately track quota usage for
|
||||
* requests involving tools, so you must opt in to this feature at your own
|
||||
* risk.
|
||||
*/
|
||||
allowOpenAIToolUsage?: boolean;
|
||||
/**
|
||||
* Which services will accept prompts containing images, for use with
|
||||
* multimodal models. Users with `special` role are exempt from this
|
||||
* restriction.
|
||||
*
|
||||
* Do not enable this feature for untrusted users, as malicious users could
|
||||
* send images which violate your provider's terms of service or local laws.
|
||||
*
|
||||
* Defaults to no services, meaning image prompts are disabled. Use a comma-
|
||||
* separated list. Available services are:
|
||||
* openai,anthropic,google-ai,mistral-ai,aws,gcp,azure
|
||||
*/
|
||||
allowedVisionServices: LLMService[];
|
||||
/**
|
||||
* Allows overriding the default proxy endpoint route. Defaults to /proxy.
|
||||
* A leading slash is required.
|
||||
*/
|
||||
proxyEndpointRoute: string;
|
||||
/**
|
||||
* If set, only requests from these IP addresses will be permitted to use the
|
||||
* admin API and UI. Provide a comma-separated list of IP addresses or CIDR
|
||||
* ranges. If not set, the admin API and UI will be open to all requests.
|
||||
*/
|
||||
adminWhitelist: string[];
|
||||
/**
|
||||
* If set, requests from these IP addresses will be blocked from using the
|
||||
* application. Provide a comma-separated list of IP addresses or CIDR ranges.
|
||||
* If not set, no IP addresses will be blocked.
|
||||
*
|
||||
* Takes precedence over the adminWhitelist.
|
||||
*/
|
||||
ipBlacklist: string[];
|
||||
/**
|
||||
* If set, pushes requests further back into the queue according to their
|
||||
* token costs by factor*tokens*milliseconds (or more intuitively
|
||||
* factor*thousands_of_tokens*seconds).
|
||||
* Accepts floats.
|
||||
*/
|
||||
tokensPunishmentFactor: number;
|
||||
/**
|
||||
* Configuration for HTTP requests made by the proxy to other servers, such
|
||||
* as when checking keys or forwarding users' requests to external services.
|
||||
* If not set, all requests will be made using the default agent.
|
||||
*
|
||||
* If set, the proxy may make requests to other servers using the specified
|
||||
* settings. This is useful if you wish to route users' requests through
|
||||
* another proxy or VPN, or if you have multiple network interfaces and want
|
||||
* to use a specific one for outgoing requests.
|
||||
*/
|
||||
httpAgent?: {
|
||||
/**
|
||||
* The name of the network interface to use. The first external IPv4 address
|
||||
* belonging to this interface will be used for outgoing requests.
|
||||
*/
|
||||
interface?: string;
|
||||
/**
|
||||
* The URL of a proxy server to use. Supports SOCKS4, SOCKS5, HTTP, and
|
||||
* HTTPS. If not set, the proxy will be made using the default agent.
|
||||
* - SOCKS4: `socks4://some-socks-proxy.com:9050`
|
||||
* - SOCKS5: `socks5://username:password@some-socks-proxy.com:9050`
|
||||
* - HTTP: `http://proxy-server-over-tcp.com:3128`
|
||||
* - HTTPS: `https://proxy-server-over-tls.com:3129`
|
||||
*
|
||||
* **Note:** If your proxy server issues a certificate, you may need to set
|
||||
* `NODE_EXTRA_CA_CERTS` to the path to your certificate, otherwise this
|
||||
* application will reject TLS connections.
|
||||
*/
|
||||
proxyUrl?: string;
|
||||
};
|
||||
};
|
||||
|
||||
// To change configs, create a file called .env in the root directory.
|
||||
// See .env.example for an example.
|
||||
export const config: Config = {
|
||||
port: getEnvWithDefault("PORT", 7860),
|
||||
bindAddress: getEnvWithDefault("BIND_ADDRESS", "0.0.0.0"),
|
||||
openaiKey: getEnvWithDefault("OPENAI_KEY", ""),
|
||||
anthropicKey: getEnvWithDefault("ANTHROPIC_KEY", ""),
|
||||
googleAIKey: getEnvWithDefault("GOOGLE_AI_KEY", ""),
|
||||
mistralAIKey: getEnvWithDefault("MISTRAL_AI_KEY", ""),
|
||||
awsCredentials: getEnvWithDefault("AWS_CREDENTIALS", ""),
|
||||
gcpCredentials: getEnvWithDefault("GCP_CREDENTIALS", ""),
|
||||
azureCredentials: getEnvWithDefault("AZURE_CREDENTIALS", ""),
|
||||
googlePalmKey: getEnvWithDefault("GOOGLE_PALM_KEY", ""),
|
||||
proxyKey: getEnvWithDefault("PROXY_KEY", ""),
|
||||
adminKey: getEnvWithDefault("ADMIN_KEY", ""),
|
||||
serviceInfoPassword: getEnvWithDefault("SERVICE_INFO_PASSWORD", ""),
|
||||
sqliteDataPath: getEnvWithDefault(
|
||||
"SQLITE_DATA_PATH",
|
||||
path.join(DATA_DIR, "database.sqlite")
|
||||
),
|
||||
eventLogging: getEnvWithDefault("EVENT_LOGGING", false),
|
||||
eventLoggingTrim: getEnvWithDefault("EVENT_LOGGING_TRIM", 5),
|
||||
gatekeeper: getEnvWithDefault("GATEKEEPER", "none"),
|
||||
gatekeeperStore: getEnvWithDefault("GATEKEEPER_STORE", "memory"),
|
||||
maxIpsPerUser: getEnvWithDefault("MAX_IPS_PER_USER", 0),
|
||||
maxIpsAutoBan: getEnvWithDefault("MAX_IPS_AUTO_BAN", false),
|
||||
captchaMode: getEnvWithDefault("CAPTCHA_MODE", "none"),
|
||||
powTokenHours: getEnvWithDefault("POW_TOKEN_HOURS", 24),
|
||||
powTokenMaxIps: getEnvWithDefault("POW_TOKEN_MAX_IPS", 2),
|
||||
powDifficultyLevel: getEnvWithDefault("POW_DIFFICULTY_LEVEL", "low"),
|
||||
powChallengeTimeout: getEnvWithDefault("POW_CHALLENGE_TIMEOUT", 30),
|
||||
powTokenPurgeHours: getEnvWithDefault("POW_TOKEN_PURGE_HOURS", 48),
|
||||
firebaseRtdbUrl: getEnvWithDefault("FIREBASE_RTDB_URL", undefined),
|
||||
firebaseKey: getEnvWithDefault("FIREBASE_KEY", undefined),
|
||||
textModelRateLimit: getEnvWithDefault("TEXT_MODEL_RATE_LIMIT", 4),
|
||||
imageModelRateLimit: getEnvWithDefault("IMAGE_MODEL_RATE_LIMIT", 4),
|
||||
maxContextTokensOpenAI: getEnvWithDefault("MAX_CONTEXT_TOKENS_OPENAI", 32768),
|
||||
modelRateLimit: getEnvWithDefault("MODEL_RATE_LIMIT", 4),
|
||||
maxContextTokensOpenAI: getEnvWithDefault("MAX_CONTEXT_TOKENS_OPENAI", 0),
|
||||
maxContextTokensAnthropic: getEnvWithDefault(
|
||||
"MAX_CONTEXT_TOKENS_ANTHROPIC",
|
||||
32768
|
||||
0
|
||||
),
|
||||
maxOutputTokensOpenAI: getEnvWithDefault(
|
||||
["MAX_OUTPUT_TOKENS_OPENAI", "MAX_OUTPUT_TOKENS"],
|
||||
1024
|
||||
300
|
||||
),
|
||||
maxOutputTokensAnthropic: getEnvWithDefault(
|
||||
["MAX_OUTPUT_TOKENS_ANTHROPIC", "MAX_OUTPUT_TOKENS"],
|
||||
1024
|
||||
400
|
||||
),
|
||||
allowedModelFamilies: getEnvWithDefault(
|
||||
"ALLOWED_MODEL_FAMILIES",
|
||||
getDefaultModelFamilies()
|
||||
),
|
||||
rejectPhrases: parseCsv(getEnvWithDefault("REJECT_PHRASES", "")),
|
||||
allowedModelFamilies: getEnvWithDefault("ALLOWED_MODEL_FAMILIES", [
|
||||
"turbo",
|
||||
"gpt4",
|
||||
"gpt4-32k",
|
||||
"claude",
|
||||
]),
|
||||
rejectDisallowed: getEnvWithDefault("REJECT_DISALLOWED", false),
|
||||
rejectMessage: getEnvWithDefault(
|
||||
"REJECT_MESSAGE",
|
||||
"This content violates /aicg/'s acceptable use policy."
|
||||
@@ -477,13 +177,8 @@ export const config: Config = {
|
||||
logLevel: getEnvWithDefault("LOG_LEVEL", "info"),
|
||||
checkKeys: getEnvWithDefault("CHECK_KEYS", !isDev),
|
||||
showTokenCosts: getEnvWithDefault("SHOW_TOKEN_COSTS", false),
|
||||
allowAwsLogging: getEnvWithDefault("ALLOW_AWS_LOGGING", false),
|
||||
promptLogging: getEnvWithDefault("PROMPT_LOGGING", false),
|
||||
promptLoggingBackend: getEnvWithDefault("PROMPT_LOGGING_BACKEND", undefined),
|
||||
promptLoggingFilePrefix: getEnvWithDefault(
|
||||
"PROMPT_LOGGING_FILE_PREFIX",
|
||||
"prompt-logs"
|
||||
),
|
||||
googleSheetsKey: getEnvWithDefault("GOOGLE_SHEETS_KEY", undefined),
|
||||
googleSheetsSpreadsheetId: getEnvWithDefault(
|
||||
"GOOGLE_SHEETS_SPREADSHEET_ID",
|
||||
@@ -495,102 +190,36 @@ 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: 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 }
|
||||
),
|
||||
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),
|
||||
},
|
||||
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),
|
||||
trustedProxies: getEnvWithDefault("TRUSTED_PROXIES", 1),
|
||||
allowOpenAIToolUsage: getEnvWithDefault("ALLOW_OPENAI_TOOL_USAGE", false),
|
||||
allowedVisionServices: parseCsv(
|
||||
getEnvWithDefault("ALLOWED_VISION_SERVICES", "")
|
||||
) as LLMService[],
|
||||
proxyEndpointRoute: getEnvWithDefault("PROXY_ENDPOINT_ROUTE", "/proxy"),
|
||||
adminWhitelist: parseCsv(
|
||||
getEnvWithDefault("ADMIN_WHITELIST", "0.0.0.0/0,::/0")
|
||||
),
|
||||
ipBlacklist: parseCsv(getEnvWithDefault("IP_BLACKLIST", "")),
|
||||
tokensPunishmentFactor: getEnvWithDefault("TOKENS_PUNISHMENT_FACTOR", 0.0),
|
||||
httpAgent: {
|
||||
interface: getEnvWithDefault("HTTP_AGENT_INTERFACE", undefined),
|
||||
proxyUrl: getEnvWithDefault("HTTP_AGENT_PROXY_URL", undefined),
|
||||
},
|
||||
} as const;
|
||||
|
||||
function generateSigningKey() {
|
||||
function generateCookieSecret() {
|
||||
if (process.env.COOKIE_SECRET !== undefined) {
|
||||
// legacy, replaced by SIGNING_KEY
|
||||
return process.env.COOKIE_SECRET;
|
||||
} else if (process.env.SIGNING_KEY !== undefined) {
|
||||
return process.env.SIGNING_KEY;
|
||||
}
|
||||
|
||||
const secrets = [
|
||||
config.adminKey,
|
||||
config.openaiKey,
|
||||
config.anthropicKey,
|
||||
config.googleAIKey,
|
||||
config.mistralAIKey,
|
||||
config.awsCredentials,
|
||||
config.gcpCredentials,
|
||||
config.azureCredentials,
|
||||
];
|
||||
if (secrets.filter((s) => s).length === 0) {
|
||||
startupLogger.warn(
|
||||
"No SIGNING_KEY or secrets are set. All sessions, cookies, and proofs of work will be invalidated on restart."
|
||||
);
|
||||
return crypto.randomBytes(32).toString("hex");
|
||||
}
|
||||
|
||||
startupLogger.info("No SIGNING_KEY set; one will be generated from secrets.");
|
||||
startupLogger.info(
|
||||
"It's recommended to set SIGNING_KEY explicitly to ensure users' sessions and cookies always persist across restarts."
|
||||
);
|
||||
const seed = secrets.map((s) => s || "n/a").join("");
|
||||
const seed = "" + config.adminKey + config.openaiKey + config.anthropicKey;
|
||||
const crypto = require("crypto");
|
||||
return crypto.createHash("sha256").update(seed).digest("hex");
|
||||
}
|
||||
|
||||
const signingKey = generateSigningKey();
|
||||
export const SECRET_SIGNING_KEY = signingKey;
|
||||
export const COOKIE_SECRET = generateCookieSecret();
|
||||
|
||||
export async function assertConfigIsValid() {
|
||||
if (process.env.MODEL_RATE_LIMIT !== undefined) {
|
||||
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.TURBO_ONLY === "true") {
|
||||
startupLogger.warn(
|
||||
{ textLimit: limit, imageLimit: config.imageModelRateLimit },
|
||||
"MODEL_RATE_LIMIT is deprecated. Use TEXT_MODEL_RATE_LIMIT and IMAGE_MODEL_RATE_LIMIT instead."
|
||||
"TURBO_ONLY is deprecated. Use ALLOWED_MODEL_FAMILIES=turbo instead."
|
||||
);
|
||||
}
|
||||
|
||||
if (process.env.ALLOW_IMAGE_PROMPTS === "true") {
|
||||
const hasAllowedServices = config.allowedVisionServices.length > 0;
|
||||
if (!hasAllowedServices) {
|
||||
config.allowedVisionServices = ["openai", "anthropic"];
|
||||
startupLogger.warn(
|
||||
{ allowedVisionServices: config.allowedVisionServices },
|
||||
"ALLOW_IMAGE_PROMPTS is deprecated. Use ALLOWED_VISION_SERVICES instead."
|
||||
);
|
||||
}
|
||||
}
|
||||
|
||||
if (config.promptLogging && !config.promptLoggingBackend) {
|
||||
throw new Error(
|
||||
"Prompt logging is enabled but no backend is configured. Set PROMPT_LOGGING_BACKEND to 'google_sheets' or 'file'."
|
||||
config.allowedModelFamilies = config.allowedModelFamilies.filter(
|
||||
(f) => !f.includes("gpt4")
|
||||
);
|
||||
}
|
||||
|
||||
@@ -606,35 +235,18 @@ export async function assertConfigIsValid() {
|
||||
);
|
||||
}
|
||||
|
||||
if (
|
||||
config.captchaMode === "proof_of_work" &&
|
||||
config.gatekeeper !== "user_token"
|
||||
) {
|
||||
throw new Error(
|
||||
"Captcha mode 'proof_of_work' requires gatekeeper mode 'user_token'."
|
||||
);
|
||||
}
|
||||
|
||||
if (config.captchaMode === "proof_of_work") {
|
||||
const val = config.powDifficultyLevel;
|
||||
const isDifficulty =
|
||||
typeof val === "string" &&
|
||||
["low", "medium", "high", "extreme"].includes(val);
|
||||
const isIterations =
|
||||
typeof val === "number" && Number.isInteger(val) && val > 0;
|
||||
if (!isDifficulty && !isIterations) {
|
||||
throw new Error(
|
||||
"Invalid POW_DIFFICULTY_LEVEL. Must be one of: low, medium, high, extreme, or a positive integer."
|
||||
);
|
||||
}
|
||||
}
|
||||
|
||||
if (config.gatekeeper === "proxy_key" && !config.proxyKey) {
|
||||
throw new Error(
|
||||
"`proxy_key` gatekeeper mode requires a `PROXY_KEY` to be set."
|
||||
);
|
||||
}
|
||||
|
||||
if (config.gatekeeper !== "proxy_key" && config.proxyKey) {
|
||||
throw new Error(
|
||||
"`PROXY_KEY` is set, but gatekeeper mode is not `proxy_key`. Make sure to set `GATEKEEPER=proxy_key`."
|
||||
);
|
||||
}
|
||||
|
||||
if (
|
||||
config.gatekeeperStore === "firebase_rtdb" &&
|
||||
(!config.firebaseKey || !config.firebaseRtdbUrl)
|
||||
@@ -644,22 +256,11 @@ export async function assertConfigIsValid() {
|
||||
);
|
||||
}
|
||||
|
||||
if (Object.values(config.httpAgent || {}).filter(Boolean).length === 0) {
|
||||
delete config.httpAgent;
|
||||
} else if (config.httpAgent) {
|
||||
if (config.httpAgent.interface && config.httpAgent.proxyUrl) {
|
||||
throw new Error(
|
||||
"Cannot set both `HTTP_AGENT_INTERFACE` and `HTTP_AGENT_PROXY_URL`."
|
||||
);
|
||||
}
|
||||
}
|
||||
|
||||
// Ensure forks which add new secret-like config keys don't unwittingly expose
|
||||
// them to users.
|
||||
for (const key of getKeys(config)) {
|
||||
const maybeSensitive = ["key", "credentials", "secret", "password"].some(
|
||||
(sensitive) =>
|
||||
key.toLowerCase().includes(sensitive) && !["checkKeys"].includes(key)
|
||||
(sensitive) => key.toLowerCase().includes(sensitive)
|
||||
);
|
||||
const secured = new Set([...SENSITIVE_KEYS, ...OMITTED_KEYS]);
|
||||
if (maybeSensitive && !secured.has(key))
|
||||
@@ -667,101 +268,67 @@ export async function assertConfigIsValid() {
|
||||
`Config key "${key}" may be sensitive but is exposed. Add it to SENSITIVE_KEYS or OMITTED_KEYS.`
|
||||
);
|
||||
}
|
||||
|
||||
await maybeInitializeFirebase();
|
||||
}
|
||||
|
||||
/**
|
||||
* Config keys that are masked on the info page, but not hidden as their
|
||||
* presence may be relevant to the user due to privacy implications.
|
||||
*/
|
||||
export const SENSITIVE_KEYS: (keyof Config)[] = [
|
||||
"googleSheetsSpreadsheetId",
|
||||
"httpAgent",
|
||||
];
|
||||
export const SENSITIVE_KEYS: (keyof Config)[] = ["googleSheetsSpreadsheetId"];
|
||||
|
||||
/**
|
||||
* Config keys that are not displayed on the info page at all, generally because
|
||||
* they are not relevant to the user or can be inferred from other config.
|
||||
*/
|
||||
export const OMITTED_KEYS = [
|
||||
export const OMITTED_KEYS: (keyof Config)[] = [
|
||||
"port",
|
||||
"bindAddress",
|
||||
"logLevel",
|
||||
"openaiKey",
|
||||
"anthropicKey",
|
||||
"googleAIKey",
|
||||
"mistralAIKey",
|
||||
"awsCredentials",
|
||||
"gcpCredentials",
|
||||
"azureCredentials",
|
||||
"googlePalmKey",
|
||||
"proxyKey",
|
||||
"adminKey",
|
||||
"serviceInfoPassword",
|
||||
"rejectPhrases",
|
||||
"rejectMessage",
|
||||
"checkKeys",
|
||||
"showTokenCosts",
|
||||
"promptLoggingFilePrefix",
|
||||
"googleSheetsKey",
|
||||
"firebaseKey",
|
||||
"firebaseRtdbUrl",
|
||||
"sqliteDataPath",
|
||||
"eventLogging",
|
||||
"eventLoggingTrim",
|
||||
"gatekeeperStore",
|
||||
"maxIpsPerUser",
|
||||
"blockedOrigins",
|
||||
"blockMessage",
|
||||
"blockRedirect",
|
||||
"allowNicknameChanges",
|
||||
"showRecentImages",
|
||||
"useInsecureCookies",
|
||||
"staticServiceInfo",
|
||||
"checkKeys",
|
||||
"allowedModelFamilies",
|
||||
"trustedProxies",
|
||||
"proxyEndpointRoute",
|
||||
"adminWhitelist",
|
||||
"ipBlacklist",
|
||||
"powTokenPurgeHours",
|
||||
] satisfies (keyof Config)[];
|
||||
type OmitKeys = (typeof OMITTED_KEYS)[number];
|
||||
|
||||
type Printable<T> = {
|
||||
[P in keyof T as Exclude<P, OmitKeys>]: T[P] extends object
|
||||
? Printable<T[P]>
|
||||
: string;
|
||||
};
|
||||
type PublicConfig = Printable<Config>;
|
||||
];
|
||||
|
||||
const getKeys = Object.keys as <T extends object>(obj: T) => Array<keyof T>;
|
||||
|
||||
export function listConfig(obj: Config = config) {
|
||||
const result: Record<string, unknown> = {};
|
||||
export function listConfig(obj: Config = config): Record<string, any> {
|
||||
const result: Record<string, any> = {};
|
||||
for (const key of getKeys(obj)) {
|
||||
const value = obj[key]?.toString() || "";
|
||||
|
||||
const shouldMask = SENSITIVE_KEYS.includes(key);
|
||||
const shouldOmit =
|
||||
OMITTED_KEYS.includes(key as OmitKeys) ||
|
||||
value === "" ||
|
||||
value === "undefined";
|
||||
OMITTED_KEYS.includes(key) || value === "" || value === "undefined";
|
||||
const shouldMask = SENSITIVE_KEYS.includes(key);
|
||||
|
||||
if (shouldOmit) {
|
||||
continue;
|
||||
}
|
||||
|
||||
const validKey = key as keyof Printable<Config>;
|
||||
|
||||
if (value && shouldMask) {
|
||||
result[validKey] = "********";
|
||||
result[key] = "********";
|
||||
} else {
|
||||
result[validKey] = value;
|
||||
result[key] = value;
|
||||
}
|
||||
|
||||
if (typeof obj[key] === "object" && !Array.isArray(obj[key])) {
|
||||
result[key] = listConfig(obj[key] as unknown as Config);
|
||||
}
|
||||
}
|
||||
return result as PublicConfig;
|
||||
return result;
|
||||
}
|
||||
|
||||
/**
|
||||
@@ -777,14 +344,7 @@ function getEnvWithDefault<T>(env: string | string[], defaultValue: T): T {
|
||||
}
|
||||
try {
|
||||
if (
|
||||
[
|
||||
"OPENAI_KEY",
|
||||
"ANTHROPIC_KEY",
|
||||
"GOOGLE_AI_KEY",
|
||||
"AWS_CREDENTIALS",
|
||||
"GCP_CREDENTIALS",
|
||||
"AZURE_CREDENTIALS",
|
||||
].includes(String(env))
|
||||
["OPENAI_KEY", "ANTHROPIC_KEY", "GOOGLE_PALM_KEY"].includes(String(env))
|
||||
) {
|
||||
return value as unknown as T;
|
||||
}
|
||||
@@ -800,16 +360,28 @@ function getEnvWithDefault<T>(env: string | string[], defaultValue: T): T {
|
||||
}
|
||||
}
|
||||
|
||||
function parseCsv(val: string): string[] {
|
||||
if (!val) return [];
|
||||
let firebaseApp: firebase.app.App | undefined;
|
||||
|
||||
const regex = /(".*?"|[^",]+)(?=\s*,|\s*$)/g;
|
||||
const matches = val.match(regex) || [];
|
||||
return matches.map((item) => item.replace(/^"|"$/g, "").trim());
|
||||
async function maybeInitializeFirebase() {
|
||||
if (!config.gatekeeperStore.startsWith("firebase")) {
|
||||
return;
|
||||
}
|
||||
|
||||
const firebase = await import("firebase-admin");
|
||||
const firebaseKey = Buffer.from(config.firebaseKey!, "base64").toString();
|
||||
const app = firebase.initializeApp({
|
||||
credential: firebase.credential.cert(JSON.parse(firebaseKey)),
|
||||
databaseURL: config.firebaseRtdbUrl,
|
||||
});
|
||||
|
||||
await app.database().ref("connection-test").set(Date.now());
|
||||
|
||||
firebaseApp = app;
|
||||
}
|
||||
|
||||
function getDefaultModelFamilies(): ModelFamily[] {
|
||||
return MODEL_FAMILIES.filter(
|
||||
(f) => !f.includes("dall-e") && !f.includes("o1")
|
||||
) as ModelFamily[];
|
||||
export function getFirebaseApp(): firebase.app.App {
|
||||
if (!firebaseApp) {
|
||||
throw new Error("Firebase app not initialized.");
|
||||
}
|
||||
return firebaseApp;
|
||||
}
|
||||
|
||||
+360
-203
@@ -1,178 +1,420 @@
|
||||
/** This whole module kinda sucks */
|
||||
import fs from "fs";
|
||||
import express, { Router, Request, Response } from "express";
|
||||
import { Request, Response } from "express";
|
||||
import showdown from "showdown";
|
||||
import { config } from "./config";
|
||||
import { buildInfo, ServiceInfo } from "./service-info";
|
||||
import { getLastNImages } from "./shared/file-storage/image-history";
|
||||
import { keyPool } from "./shared/key-management";
|
||||
import { MODEL_FAMILY_SERVICE, ModelFamily } from "./shared/models";
|
||||
import { withSession } from "./shared/with-session";
|
||||
import { checkCsrfToken, injectCsrfToken } from "./shared/inject-csrf";
|
||||
import { config, listConfig } from "./config";
|
||||
import {
|
||||
AnthropicKey,
|
||||
GooglePalmKey,
|
||||
OpenAIKey,
|
||||
keyPool,
|
||||
} from "./shared/key-management";
|
||||
import { ModelFamily, OpenAIModelFamily } from "./shared/models";
|
||||
import { getUniqueIps } from "./proxy/rate-limit";
|
||||
import { getEstimatedWaitTime, getQueueLength } from "./proxy/queue";
|
||||
import { getTokenCostUsd, prettyTokens } from "./shared/stats";
|
||||
import { assertNever } from "./shared/utils";
|
||||
|
||||
const INFO_PAGE_TTL = 2000;
|
||||
const MODEL_FAMILY_FRIENDLY_NAME: { [f in ModelFamily]: string } = {
|
||||
turbo: "GPT-4o Mini / 3.5 Turbo",
|
||||
gpt4: "GPT-4",
|
||||
"gpt4-32k": "GPT-4 32k",
|
||||
"gpt4-turbo": "GPT-4 Turbo",
|
||||
gpt4o: "GPT-4o",
|
||||
o1: "OpenAI o1",
|
||||
"o1-mini": "OpenAI o1 mini",
|
||||
"dall-e": "DALL-E",
|
||||
claude: "Claude (Sonnet)",
|
||||
"claude-opus": "Claude (Opus)",
|
||||
"gemini-flash": "Gemini Flash",
|
||||
"gemini-pro": "Gemini Pro",
|
||||
"gemini-ultra": "Gemini Ultra",
|
||||
"mistral-tiny": "Mistral 7B",
|
||||
"mistral-small": "Mistral Nemo",
|
||||
"mistral-medium": "Mistral Medium",
|
||||
"mistral-large": "Mistral Large",
|
||||
"aws-claude": "AWS Claude (Sonnet)",
|
||||
"aws-claude-opus": "AWS Claude (Opus)",
|
||||
"aws-mistral-tiny": "AWS Mistral 7B",
|
||||
"aws-mistral-small": "AWS Mistral Nemo",
|
||||
"aws-mistral-medium": "AWS Mistral Medium",
|
||||
"aws-mistral-large": "AWS Mistral Large",
|
||||
"gcp-claude": "GCP Claude (Sonnet)",
|
||||
"gcp-claude-opus": "GCP Claude (Opus)",
|
||||
"azure-turbo": "Azure GPT-3.5 Turbo",
|
||||
"azure-gpt4": "Azure GPT-4",
|
||||
"azure-gpt4-32k": "Azure GPT-4 32k",
|
||||
"azure-gpt4-turbo": "Azure GPT-4 Turbo",
|
||||
"azure-gpt4o": "Azure GPT-4o",
|
||||
"azure-o1": "Azure o1",
|
||||
"azure-o1-mini": "Azure o1 mini",
|
||||
"azure-dall-e": "Azure DALL-E",
|
||||
};
|
||||
|
||||
const converter = new showdown.Converter();
|
||||
const customGreeting = fs.existsSync("greeting.md")
|
||||
? `<div id="servergreeting">${fs.readFileSync("greeting.md", "utf8")}</div>`
|
||||
: "";
|
||||
let infoPageHtml: string | undefined;
|
||||
let infoPageLastUpdated = 0;
|
||||
|
||||
type KeyPoolKey = ReturnType<typeof keyPool.list>[0];
|
||||
const keyIsOpenAIKey = (k: KeyPoolKey): k is OpenAIKey =>
|
||||
k.service === "openai";
|
||||
const keyIsAnthropicKey = (k: KeyPoolKey): k is AnthropicKey =>
|
||||
k.service === "anthropic";
|
||||
const keyIsGooglePalmKey = (k: KeyPoolKey): k is GooglePalmKey =>
|
||||
k.service === "google-palm";
|
||||
|
||||
type ModelAggregates = {
|
||||
active: number;
|
||||
trial?: number;
|
||||
revoked?: number;
|
||||
overQuota?: number;
|
||||
pozzed?: number;
|
||||
queued: number;
|
||||
queueTime: string;
|
||||
tokens: number;
|
||||
};
|
||||
type ModelAggregateKey = `${ModelFamily}__${keyof ModelAggregates}`;
|
||||
type ServiceAggregates = {
|
||||
status?: string;
|
||||
openaiKeys?: number;
|
||||
openaiOrgs?: number;
|
||||
anthropicKeys?: number;
|
||||
palmKeys?: number;
|
||||
proompts: number;
|
||||
tokens: number;
|
||||
tokenCost: number;
|
||||
openAiUncheckedKeys?: number;
|
||||
anthropicUncheckedKeys?: number;
|
||||
} & {
|
||||
[modelFamily in ModelFamily]?: ModelAggregates;
|
||||
};
|
||||
|
||||
const modelStats = new Map<ModelAggregateKey, number>();
|
||||
const serviceStats = new Map<keyof ServiceAggregates, number>();
|
||||
|
||||
export const handleInfoPage = (req: Request, res: Response) => {
|
||||
if (infoPageLastUpdated + INFO_PAGE_TTL > Date.now()) {
|
||||
return res.send(infoPageHtml);
|
||||
res.send(infoPageHtml);
|
||||
return;
|
||||
}
|
||||
|
||||
// Sometimes huggingface doesn't send the host header and makes us guess.
|
||||
const baseUrl =
|
||||
process.env.SPACE_ID && !req.get("host")?.includes("hf.space")
|
||||
? getExternalUrlForHuggingfaceSpaceId(process.env.SPACE_ID)
|
||||
: req.protocol + "://" + req.get("host");
|
||||
|
||||
const info = buildInfo(baseUrl + config.proxyEndpointRoute);
|
||||
infoPageHtml = renderPage(info);
|
||||
infoPageLastUpdated = Date.now();
|
||||
|
||||
res.send(infoPageHtml);
|
||||
res.send(cacheInfoPageHtml(baseUrl));
|
||||
};
|
||||
|
||||
export function renderPage(info: ServiceInfo) {
|
||||
const title = getServerTitle();
|
||||
const headerHtml = buildInfoPageHeader(info);
|
||||
function getCostString(cost: number) {
|
||||
if (!config.showTokenCosts) return "";
|
||||
return ` ($${cost.toFixed(2)})`;
|
||||
}
|
||||
|
||||
return `<!doctype html>
|
||||
function cacheInfoPageHtml(baseUrl: string) {
|
||||
const keys = keyPool.list();
|
||||
|
||||
modelStats.clear();
|
||||
serviceStats.clear();
|
||||
keys.forEach(addKeyToAggregates);
|
||||
|
||||
const openaiKeys = serviceStats.get("openaiKeys") || 0;
|
||||
const anthropicKeys = serviceStats.get("anthropicKeys") || 0;
|
||||
const palmKeys = serviceStats.get("palmKeys") || 0;
|
||||
const 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" } : {}),
|
||||
},
|
||||
proompts,
|
||||
tookens: `${prettyTokens(tokens)}${getCostString(tokenCost)}`,
|
||||
...(config.modelRateLimit ? { proomptersNow: getUniqueIps() } : {}),
|
||||
openaiKeys,
|
||||
anthropicKeys,
|
||||
palmKeys,
|
||||
...(openaiKeys ? getOpenAIInfo() : {}),
|
||||
...(anthropicKeys ? getAnthropicInfo() : {}),
|
||||
...(palmKeys ? { "palm-bison": getPalmInfo() } : {}),
|
||||
config: listConfig(),
|
||||
build: process.env.BUILD_INFO || "dev",
|
||||
};
|
||||
|
||||
const title = getServerTitle();
|
||||
const headerHtml = buildInfoPageHeader(new showdown.Converter(), title);
|
||||
|
||||
const pageBody = `<!DOCTYPE html>
|
||||
<html lang="en">
|
||||
<head>
|
||||
<meta charset="utf-8" />
|
||||
<meta name="robots" content="noindex" />
|
||||
<title>${title}</title>
|
||||
<link rel="stylesheet" href="/res/css/reset.css" media="screen" />
|
||||
<link rel="stylesheet" href="/res/css/sakura.css" media="screen" />
|
||||
<link rel="stylesheet" href="/res/css/sakura-dark.css" media="screen and (prefers-color-scheme: dark)" />
|
||||
<style>
|
||||
body {
|
||||
font-family: sans-serif;
|
||||
padding: 1em;
|
||||
max-width: 900px;
|
||||
margin: 0;
|
||||
}
|
||||
|
||||
.self-service-links {
|
||||
display: flex;
|
||||
justify-content: center;
|
||||
margin-bottom: 1em;
|
||||
padding: 0.5em;
|
||||
font-size: 0.8em;
|
||||
}
|
||||
|
||||
.self-service-links a {
|
||||
margin: 0 0.5em;
|
||||
}
|
||||
</style>
|
||||
</head>
|
||||
<body>
|
||||
<body style="font-family: sans-serif; background-color: #f0f0f0; padding: 1em;">
|
||||
${headerHtml}
|
||||
<hr />
|
||||
${getSelfServiceLinks()}
|
||||
<h2>Service Info</h2>
|
||||
<pre>${JSON.stringify(info, null, 2)}</pre>
|
||||
${getSelfServiceLinks()}
|
||||
</body>
|
||||
</html>`;
|
||||
|
||||
infoPageHtml = pageBody;
|
||||
infoPageLastUpdated = Date.now();
|
||||
|
||||
return pageBody;
|
||||
}
|
||||
|
||||
function getUniqueOpenAIOrgs(keys: KeyPoolKey[]) {
|
||||
const orgIds = new Set(
|
||||
keys.filter((k) => k.service === "openai").map((k: any) => k.organizationId)
|
||||
);
|
||||
return orgIds.size;
|
||||
}
|
||||
|
||||
function increment<T extends keyof ServiceAggregates | ModelAggregateKey>(
|
||||
map: Map<T, number>,
|
||||
key: T,
|
||||
delta = 1
|
||||
) {
|
||||
map.set(key, (map.get(key) || 0) + delta);
|
||||
}
|
||||
|
||||
function addKeyToAggregates(k: KeyPoolKey) {
|
||||
increment(serviceStats, "proompts", k.promptCount);
|
||||
increment(serviceStats, "openaiKeys", k.service === "openai" ? 1 : 0);
|
||||
increment(serviceStats, "anthropicKeys", k.service === "anthropic" ? 1 : 0);
|
||||
increment(serviceStats, "palmKeys", k.service === "google-palm" ? 1 : 0);
|
||||
|
||||
let sumTokens = 0;
|
||||
let sumCost = 0;
|
||||
let family: ModelFamily;
|
||||
const families = k.modelFamilies.filter((f) =>
|
||||
config.allowedModelFamilies.includes(f)
|
||||
);
|
||||
|
||||
switch (k.service) {
|
||||
case "openai":
|
||||
case "openai-text":
|
||||
if (!keyIsOpenAIKey(k)) throw new Error("Invalid key type");
|
||||
increment(
|
||||
serviceStats,
|
||||
"openAiUncheckedKeys",
|
||||
Boolean(k.lastChecked) ? 0 : 1
|
||||
);
|
||||
|
||||
// Technically this would not account for keys that have tokens recorded
|
||||
// on models they aren't provisioned for, but that would be strange
|
||||
k.modelFamilies.forEach((f) => {
|
||||
const tokens = k[`${f}Tokens`];
|
||||
sumTokens += tokens;
|
||||
sumCost += getTokenCostUsd(f, tokens);
|
||||
increment(modelStats, `${f}__tokens`, tokens);
|
||||
});
|
||||
|
||||
if (families.includes("gpt4-32k")) {
|
||||
family = "gpt4-32k";
|
||||
} else if (families.includes("gpt4")) {
|
||||
family = "gpt4";
|
||||
} else {
|
||||
family = "turbo";
|
||||
}
|
||||
break;
|
||||
case "anthropic":
|
||||
if (!keyIsAnthropicKey(k)) throw new Error("Invalid key type");
|
||||
family = "claude";
|
||||
sumTokens += k.claudeTokens;
|
||||
sumCost += getTokenCostUsd(family, k.claudeTokens);
|
||||
increment(modelStats, `${family}__tokens`, k.claudeTokens);
|
||||
increment(modelStats, `${family}__pozzed`, k.isPozzed ? 1 : 0);
|
||||
increment(
|
||||
serviceStats,
|
||||
"anthropicUncheckedKeys",
|
||||
Boolean(k.lastChecked) ? 0 : 1
|
||||
);
|
||||
break;
|
||||
case "google-palm":
|
||||
if (!keyIsGooglePalmKey(k)) throw new Error("Invalid key type");
|
||||
family = "bison";
|
||||
sumTokens += k.bisonTokens;
|
||||
sumCost += getTokenCostUsd(family, k.bisonTokens);
|
||||
increment(modelStats, `${family}__tokens`, k.bisonTokens);
|
||||
break;
|
||||
default:
|
||||
assertNever(k.service);
|
||||
}
|
||||
|
||||
increment(serviceStats, "tokens", sumTokens);
|
||||
increment(serviceStats, "tokenCost", sumCost);
|
||||
increment(modelStats, `${family}__active`, k.isDisabled ? 0 : 1);
|
||||
increment(modelStats, `${family}__trial`, k.isTrial ? 1 : 0);
|
||||
if ("isRevoked" in k) {
|
||||
increment(modelStats, `${family}__revoked`, k.isRevoked ? 1 : 0);
|
||||
}
|
||||
if ("isOverQuota" in k) {
|
||||
increment(modelStats, `${family}__overQuota`, k.isOverQuota ? 1 : 0);
|
||||
}
|
||||
}
|
||||
|
||||
function getOpenAIInfo() {
|
||||
const info: { status?: string; openaiKeys?: number; openaiOrgs?: number } & {
|
||||
[modelFamily in OpenAIModelFamily]?: {
|
||||
usage?: string;
|
||||
activeKeys: number;
|
||||
trialKeys?: number;
|
||||
revokedKeys?: number;
|
||||
overQuotaKeys?: number;
|
||||
proomptersInQueue?: number;
|
||||
estimatedQueueTime?: string;
|
||||
};
|
||||
} = {};
|
||||
|
||||
const allowedFamilies = new Set(config.allowedModelFamilies);
|
||||
let families = new Set<OpenAIModelFamily>();
|
||||
const keys = keyPool.list().filter((k) => {
|
||||
const isOpenAI = keyIsOpenAIKey(k);
|
||||
if (isOpenAI) k.modelFamilies.forEach((f) => families.add(f));
|
||||
return isOpenAI;
|
||||
}) as Omit<OpenAIKey, "key">[];
|
||||
families = new Set([...families].filter((f) => allowedFamilies.has(f)));
|
||||
|
||||
if (config.checkKeys) {
|
||||
const unchecked = serviceStats.get("openAiUncheckedKeys") || 0;
|
||||
if (unchecked > 0) {
|
||||
info.status = `Checking ${unchecked} keys...`;
|
||||
}
|
||||
info.openaiKeys = keys.length;
|
||||
info.openaiOrgs = getUniqueOpenAIOrgs(keys);
|
||||
|
||||
families.forEach((f) => {
|
||||
const tokens = modelStats.get(`${f}__tokens`) || 0;
|
||||
const cost = getTokenCostUsd(f, tokens);
|
||||
|
||||
info[f] = {
|
||||
usage: `${prettyTokens(tokens)} tokens${getCostString(cost)}`,
|
||||
activeKeys: modelStats.get(`${f}__active`) || 0,
|
||||
trialKeys: modelStats.get(`${f}__trial`) || 0,
|
||||
revokedKeys: modelStats.get(`${f}__revoked`) || 0,
|
||||
overQuotaKeys: modelStats.get(`${f}__overQuota`) || 0,
|
||||
};
|
||||
});
|
||||
} else {
|
||||
info.status = "Key checking is disabled.";
|
||||
info.turbo = { activeKeys: keys.filter((k) => !k.isDisabled).length };
|
||||
info.gpt4 = {
|
||||
activeKeys: keys.filter(
|
||||
(k) => !k.isDisabled && k.modelFamilies.includes("gpt4")
|
||||
).length,
|
||||
};
|
||||
}
|
||||
|
||||
families.forEach((f) => {
|
||||
if (info[f]) {
|
||||
const { estimatedQueueTime, proomptersInQueue } = getQueueInformation(f);
|
||||
info[f]!.proomptersInQueue = proomptersInQueue;
|
||||
info[f]!.estimatedQueueTime = estimatedQueueTime;
|
||||
}
|
||||
});
|
||||
|
||||
return info;
|
||||
}
|
||||
|
||||
function getAnthropicInfo() {
|
||||
const claudeInfo: Partial<ModelAggregates> = {
|
||||
active: modelStats.get("claude__active") || 0,
|
||||
pozzed: modelStats.get("claude__pozzed") || 0,
|
||||
};
|
||||
|
||||
const queue = getQueueInformation("claude");
|
||||
claudeInfo.queued = queue.proomptersInQueue;
|
||||
claudeInfo.queueTime = queue.estimatedQueueTime;
|
||||
|
||||
const tokens = modelStats.get("claude__tokens") || 0;
|
||||
const cost = getTokenCostUsd("claude", tokens);
|
||||
|
||||
const unchecked =
|
||||
(config.checkKeys && serviceStats.get("anthropicUncheckedKeys")) || 0;
|
||||
|
||||
return {
|
||||
claude: {
|
||||
usage: `${prettyTokens(tokens)} tokens${getCostString(cost)}`,
|
||||
...(unchecked > 0 ? { status: `Checking ${unchecked} keys...` } : {}),
|
||||
activeKeys: claudeInfo.active,
|
||||
...(config.checkKeys ? { pozzedKeys: claudeInfo.pozzed } : {}),
|
||||
proomptersInQueue: claudeInfo.queued,
|
||||
estimatedQueueTime: claudeInfo.queueTime,
|
||||
},
|
||||
};
|
||||
}
|
||||
|
||||
function getPalmInfo() {
|
||||
const bisonInfo: Partial<ModelAggregates> = {
|
||||
active: modelStats.get("bison__active") || 0,
|
||||
};
|
||||
|
||||
const queue = getQueueInformation("bison");
|
||||
bisonInfo.queued = queue.proomptersInQueue;
|
||||
bisonInfo.queueTime = queue.estimatedQueueTime;
|
||||
|
||||
const tokens = modelStats.get("bison__tokens") || 0;
|
||||
const cost = getTokenCostUsd("bison", tokens);
|
||||
|
||||
return {
|
||||
usage: `${prettyTokens(tokens)} tokens${getCostString(cost)}`,
|
||||
activeKeys: bisonInfo.active,
|
||||
proomptersInQueue: bisonInfo.queued,
|
||||
estimatedQueueTime: bisonInfo.queueTime,
|
||||
};
|
||||
}
|
||||
|
||||
const customGreeting = fs.existsSync("greeting.md")
|
||||
? fs.readFileSync("greeting.md", "utf8")
|
||||
: null;
|
||||
|
||||
/**
|
||||
* If the server operator provides a `greeting.md` file, it will be included in
|
||||
* the rendered info page.
|
||||
**/
|
||||
function buildInfoPageHeader(info: ServiceInfo) {
|
||||
const title = getServerTitle();
|
||||
function buildInfoPageHeader(converter: showdown.Converter, title: string) {
|
||||
// TODO: use some templating engine instead of this mess
|
||||
let infoBody = `# ${title}`;
|
||||
let infoBody = `<!-- Header for Showdown's parser, don't remove this line -->
|
||||
# ${title}`;
|
||||
if (config.promptLogging) {
|
||||
infoBody += `\n## Prompt Logging Enabled
|
||||
This proxy keeps full logs of all prompts and AI responses. Prompt logs are anonymous and do not contain IP addresses or timestamps.
|
||||
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.
|
||||
|
||||
[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).
|
||||
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).
|
||||
|
||||
**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.`;
|
||||
|
||||
for (const modelFamily of config.allowedModelFamilies) {
|
||||
const service = MODEL_FAMILY_SERVICE[modelFamily];
|
||||
if (config.openaiKey) {
|
||||
// TODO: un-fuck this
|
||||
const keys = keyPool.list().filter((k) => k.service === "openai");
|
||||
|
||||
const hasKeys = keyPool.list().some((k) => {
|
||||
return k.service === service && k.modelFamilies.includes(modelFamily);
|
||||
});
|
||||
const turboWait = getQueueInformation("turbo").estimatedQueueTime;
|
||||
waits.push(`**Turbo:** ${turboWait}`);
|
||||
|
||||
const wait = info[modelFamily]?.estimatedQueueTime;
|
||||
if (hasKeys && wait) {
|
||||
waits.push(
|
||||
`**${MODEL_FAMILY_FRIENDLY_NAME[modelFamily] || modelFamily}**: ${wait}`
|
||||
);
|
||||
const gpt4Wait = getQueueInformation("gpt4").estimatedQueueTime;
|
||||
const hasGpt4 = keys.some((k) => k.modelFamilies.includes("gpt4"));
|
||||
const allowedGpt4 = config.allowedModelFamilies.includes("gpt4");
|
||||
if (hasGpt4 && allowedGpt4) {
|
||||
waits.push(`**GPT-4:** ${gpt4Wait}`);
|
||||
}
|
||||
|
||||
const gpt432kWait = getQueueInformation("gpt4-32k").estimatedQueueTime;
|
||||
const hasGpt432k = keys.some((k) => k.modelFamilies.includes("gpt4-32k"));
|
||||
const allowedGpt432k = config.allowedModelFamilies.includes("gpt4-32k");
|
||||
if (hasGpt432k && allowedGpt432k) {
|
||||
waits.push(`**GPT-4-32k:** ${gpt432kWait}`);
|
||||
}
|
||||
}
|
||||
|
||||
if (config.anthropicKey) {
|
||||
const claudeWait = getQueueInformation("claude").estimatedQueueTime;
|
||||
waits.push(`**Claude:** ${claudeWait}`);
|
||||
}
|
||||
infoBody += "\n\n" + waits.join(" / ");
|
||||
|
||||
infoBody += customGreeting;
|
||||
|
||||
infoBody += buildRecentImageSection();
|
||||
|
||||
if (customGreeting) {
|
||||
infoBody += `\n## Server Greeting\n${customGreeting}`;
|
||||
}
|
||||
return converter.makeHtml(infoBody);
|
||||
}
|
||||
|
||||
function getSelfServiceLinks() {
|
||||
if (config.gatekeeper !== "user_token") return "";
|
||||
return `<footer style="font-size: 0.8em;"><hr /><a target="_blank" href="/user/lookup">Check your user token info</a></footer>`;
|
||||
}
|
||||
|
||||
const links = [["Check your user token", "/user/lookup"]];
|
||||
if (config.captchaMode !== "none") {
|
||||
links.unshift(["Request a user token", "/user/captcha"]);
|
||||
}
|
||||
|
||||
return `<div class="self-service-links">${links
|
||||
.map(([text, link]) => `<a href="${link}">${text}</a>`)
|
||||
.join(" | ")}</div>`;
|
||||
/** Returns queue time in seconds, or minutes + seconds if over 60 seconds. */
|
||||
function getQueueInformation(partition: ModelFamily) {
|
||||
const waitMs = getEstimatedWaitTime(partition);
|
||||
const waitTime =
|
||||
waitMs < 60000
|
||||
? `${Math.round(waitMs / 1000)}sec`
|
||||
: `${Math.round(waitMs / 60000)}min, ${Math.round(
|
||||
(waitMs % 60000) / 1000
|
||||
)}sec`;
|
||||
return {
|
||||
proomptersInQueue: getQueueLength(partition),
|
||||
estimatedQueueTime: waitMs > 2000 ? waitTime : "no wait",
|
||||
};
|
||||
}
|
||||
|
||||
function getServerTitle() {
|
||||
@@ -194,48 +436,9 @@ function getServerTitle() {
|
||||
return "OAI Reverse Proxy";
|
||||
}
|
||||
|
||||
function buildRecentImageSection() {
|
||||
const dalleModels: ModelFamily[] = ["azure-dall-e", "dall-e"];
|
||||
if (
|
||||
!config.showRecentImages ||
|
||||
dalleModels.every((f) => !config.allowedModelFamilies.includes(f))
|
||||
) {
|
||||
return "";
|
||||
}
|
||||
|
||||
let html = `<h2>Recent DALL-E Generations</h2>`;
|
||||
const recentImages = getLastNImages(12).reverse();
|
||||
if (recentImages.length === 0) {
|
||||
html += `<p>No images yet.</p>`;
|
||||
return html;
|
||||
}
|
||||
|
||||
html += `<div style="display: flex; flex-wrap: wrap;" id="recent-images">`;
|
||||
for (const { url, prompt } of recentImages) {
|
||||
const thumbUrl = url.replace(/\.png$/, "_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>`;
|
||||
html += `<p style="clear: both; text-align: center;"><a href="/user/image-history">View all recent images</a></p>`;
|
||||
|
||||
return html;
|
||||
}
|
||||
|
||||
function escapeHtml(unsafe: string) {
|
||||
return unsafe
|
||||
.replace(/&/g, "&")
|
||||
.replace(/</g, "<")
|
||||
.replace(/>/g, ">")
|
||||
.replace(/"/g, """)
|
||||
.replace(/'/g, "'")
|
||||
.replace(/\[/g, "[")
|
||||
.replace(/]/g, "]");
|
||||
}
|
||||
|
||||
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`;
|
||||
@@ -243,49 +446,3 @@ function getExternalUrlForHuggingfaceSpaceId(spaceId: string) {
|
||||
return "";
|
||||
}
|
||||
}
|
||||
|
||||
function checkIfUnlocked(
|
||||
req: Request,
|
||||
res: Response,
|
||||
next: express.NextFunction
|
||||
) {
|
||||
if (config.serviceInfoPassword?.length && !req.session?.unlocked) {
|
||||
return res.redirect("/unlock-info");
|
||||
}
|
||||
next();
|
||||
}
|
||||
|
||||
const infoPageRouter = Router();
|
||||
if (config.serviceInfoPassword?.length) {
|
||||
infoPageRouter.use(
|
||||
express.json({ limit: "1mb" }),
|
||||
express.urlencoded({ extended: true, limit: "1mb" })
|
||||
);
|
||||
infoPageRouter.use(withSession);
|
||||
infoPageRouter.use(injectCsrfToken, checkCsrfToken);
|
||||
infoPageRouter.post("/unlock-info", (req, res) => {
|
||||
if (req.body.password !== config.serviceInfoPassword) {
|
||||
return res.status(403).send("Incorrect password");
|
||||
}
|
||||
req.session!.unlocked = true;
|
||||
res.redirect("/");
|
||||
});
|
||||
infoPageRouter.get("/unlock-info", (_req, res) => {
|
||||
if (_req.session?.unlocked) return res.redirect("/");
|
||||
|
||||
res.send(`
|
||||
<form method="post" action="/unlock-info">
|
||||
<h1>Unlock Service Info</h1>
|
||||
<input type="hidden" name="_csrf" value="${res.locals.csrfToken}" />
|
||||
<input type="password" name="password" placeholder="Password" />
|
||||
<button type="submit">Unlock</button>
|
||||
</form>
|
||||
`);
|
||||
});
|
||||
infoPageRouter.use(checkIfUnlocked);
|
||||
}
|
||||
infoPageRouter.get("/", handleInfoPage);
|
||||
infoPageRouter.get("/status", (req, res) => {
|
||||
res.json(buildInfo(req.protocol + "://" + req.get("host"), false));
|
||||
});
|
||||
export { infoPageRouter };
|
||||
|
||||
@@ -1,20 +1,6 @@
|
||||
import pino from "pino";
|
||||
import { config } from "./config";
|
||||
|
||||
const transport =
|
||||
process.env.NODE_ENV === "production"
|
||||
? undefined
|
||||
: {
|
||||
target: "pino-pretty",
|
||||
options: {
|
||||
singleLine: true,
|
||||
messageFormat: "{if module}\x1b[90m[{module}] \x1b[39m{end}{msg}",
|
||||
ignore: "module",
|
||||
},
|
||||
};
|
||||
|
||||
export const logger = pino({
|
||||
level: config.logLevel,
|
||||
base: { pid: process.pid, module: "server" },
|
||||
transport,
|
||||
});
|
||||
|
||||
@@ -1,9 +0,0 @@
|
||||
import { NextFunction, Request, Response } from "express";
|
||||
|
||||
export function addV1(req: Request, res: Response, next: NextFunction) {
|
||||
// Clients don't consistently use the /v1 prefix so we'll add it for them.
|
||||
if (!req.path.startsWith("/v1/") && !req.path.startsWith("/v1beta/")) {
|
||||
req.url = `/v1${req.url}`;
|
||||
}
|
||||
next();
|
||||
}
|
||||
+98
-190
@@ -1,14 +1,25 @@
|
||||
import { Request, RequestHandler, Router } from "express";
|
||||
import * as http from "http";
|
||||
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,
|
||||
applyQuotaLimits,
|
||||
addAnthropicPreamble,
|
||||
blockZoomerOrigins,
|
||||
createPreprocessorMiddleware,
|
||||
finalizeBody,
|
||||
languageFilter,
|
||||
removeOriginHeaders,
|
||||
} from "./middleware/request";
|
||||
import { ProxyResHandlerWithBody } from "./middleware/response";
|
||||
import { createQueuedProxyMiddleware } from "./middleware/request/proxy-middleware-factory";
|
||||
import { ProxyReqManager } from "./middleware/request/proxy-req-manager";
|
||||
import {
|
||||
ProxyResHandlerWithBody,
|
||||
createOnProxyResHandler,
|
||||
} from "./middleware/response";
|
||||
|
||||
let modelsCache: any = null;
|
||||
let modelsCacheTime = 0;
|
||||
@@ -32,17 +43,8 @@ const getModelsResponse = () => {
|
||||
"claude-instant-v1.1",
|
||||
"claude-instant-v1.1-100k",
|
||||
"claude-instant-v1.0",
|
||||
"claude-2",
|
||||
"claude-2", // claude-2 is 100k by default it seems
|
||||
"claude-2.0",
|
||||
"claude-2.1",
|
||||
"claude-3-haiku-20240307",
|
||||
"claude-3-5-haiku-20241022",
|
||||
"claude-3-opus-20240229",
|
||||
"claude-3-opus-latest",
|
||||
"claude-3-sonnet-20240229",
|
||||
"claude-3-5-sonnet-20240620",
|
||||
"claude-3-5-sonnet-20241022",
|
||||
"claude-3-5-sonnet-latest",
|
||||
];
|
||||
|
||||
const models = claudeVariants.map((id) => ({
|
||||
@@ -65,7 +67,33 @@ const handleModelRequest: RequestHandler = (_req, res) => {
|
||||
res.status(200).json(getModelsResponse());
|
||||
};
|
||||
|
||||
const anthropicBlockingResponseHandler: ProxyResHandlerWithBody = async (
|
||||
const rewriteAnthropicRequest = (
|
||||
proxyReq: http.ClientRequest,
|
||||
req: Request,
|
||||
res: http.ServerResponse
|
||||
) => {
|
||||
const rewriterPipeline = [
|
||||
applyQuotaLimits,
|
||||
addKey,
|
||||
addAnthropicPreamble,
|
||||
languageFilter,
|
||||
blockZoomerOrigins,
|
||||
removeOriginHeaders,
|
||||
finalizeBody,
|
||||
];
|
||||
|
||||
try {
|
||||
for (const rewriter of rewriterPipeline) {
|
||||
rewriter(proxyReq, req, res, {});
|
||||
}
|
||||
} catch (error) {
|
||||
req.log.error(error, "Error while executing proxy rewriter");
|
||||
proxyReq.destroy(error as Error);
|
||||
}
|
||||
};
|
||||
|
||||
/** Only used for non-streaming requests. */
|
||||
const anthropicResponseHandler: ProxyResHandlerWithBody = async (
|
||||
_proxyRes,
|
||||
req,
|
||||
res,
|
||||
@@ -75,50 +103,31 @@ const anthropicBlockingResponseHandler: ProxyResHandlerWithBody = async (
|
||||
throw new Error("Expected body to be an object");
|
||||
}
|
||||
|
||||
let newBody = body;
|
||||
switch (`${req.inboundApi}<-${req.outboundApi}`) {
|
||||
case "openai<-anthropic-text":
|
||||
req.log.info("Transforming Anthropic Text back to OpenAI format");
|
||||
newBody = transformAnthropicTextResponseToOpenAI(body, req);
|
||||
break;
|
||||
case "openai<-anthropic-chat":
|
||||
req.log.info("Transforming Anthropic Chat back to OpenAI format");
|
||||
newBody = transformAnthropicChatResponseToOpenAI(body);
|
||||
break;
|
||||
case "anthropic-text<-anthropic-chat":
|
||||
req.log.info("Transforming Anthropic Chat back to Anthropic chat format");
|
||||
newBody = transformAnthropicChatResponseToAnthropicText(body);
|
||||
break;
|
||||
if (config.promptLogging) {
|
||||
const host = req.get("host");
|
||||
body.proxy_note = `Prompts are logged on this proxy instance. See ${host} for more information.`;
|
||||
}
|
||||
|
||||
res.status(200).json({ ...newBody, proxy: body.proxy });
|
||||
if (req.inboundApi === "openai") {
|
||||
req.log.info("Transforming Anthropic response to OpenAI format");
|
||||
body = transformAnthropicResponse(body, req);
|
||||
}
|
||||
|
||||
// TODO: Remove once tokenization is stable
|
||||
if (req.debug) {
|
||||
body.proxy_tokenizer_debug_info = req.debug;
|
||||
}
|
||||
|
||||
res.status(200).json(body);
|
||||
};
|
||||
|
||||
function flattenChatResponse(
|
||||
content: { type: string; text: string }[]
|
||||
): string {
|
||||
return content
|
||||
.map((part: { type: string; text: string }) =>
|
||||
part.type === "text" ? part.text : ""
|
||||
)
|
||||
.join("\n");
|
||||
}
|
||||
|
||||
export function transformAnthropicChatResponseToAnthropicText(
|
||||
anthropicBody: Record<string, any>
|
||||
): Record<string, any> {
|
||||
return {
|
||||
type: "completion",
|
||||
id: "ant-" + anthropicBody.id,
|
||||
completion: flattenChatResponse(anthropicBody.content),
|
||||
stop_reason: anthropicBody.stop_reason,
|
||||
stop: anthropicBody.stop_sequence,
|
||||
model: anthropicBody.model,
|
||||
usage: anthropicBody.usage,
|
||||
};
|
||||
}
|
||||
|
||||
function transformAnthropicTextResponseToOpenAI(
|
||||
/**
|
||||
* Transforms a model response from the Anthropic API to match those from the
|
||||
* OpenAI API, for users using Claude via the OpenAI-compatible endpoint. This
|
||||
* is only used for non-streaming requests as streaming requests are handled
|
||||
* on-the-fly.
|
||||
*/
|
||||
function transformAnthropicResponse(
|
||||
anthropicBody: Record<string, any>,
|
||||
req: Request
|
||||
): Record<string, any> {
|
||||
@@ -146,155 +155,54 @@ function transformAnthropicTextResponseToOpenAI(
|
||||
};
|
||||
}
|
||||
|
||||
export function transformAnthropicChatResponseToOpenAI(
|
||||
anthropicBody: Record<string, any>
|
||||
): Record<string, any> {
|
||||
return {
|
||||
id: "ant-" + anthropicBody.id,
|
||||
object: "chat.completion",
|
||||
created: Date.now(),
|
||||
model: anthropicBody.model,
|
||||
usage: anthropicBody.usage,
|
||||
choices: [
|
||||
{
|
||||
message: {
|
||||
role: "assistant",
|
||||
content: flattenChatResponse(anthropicBody.content),
|
||||
},
|
||||
finish_reason: anthropicBody.stop_reason,
|
||||
index: 0,
|
||||
},
|
||||
],
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
* If a client using the OpenAI compatibility endpoint requests an actual OpenAI
|
||||
* model, reassigns it to Sonnet.
|
||||
*/
|
||||
function maybeReassignModel(req: Request) {
|
||||
const model = req.body.model;
|
||||
if (model.includes("claude")) return; // use whatever model the user requested
|
||||
req.body.model = "claude-3-5-sonnet-latest";
|
||||
}
|
||||
|
||||
/**
|
||||
* If client requests more than 4096 output tokens the request must have a
|
||||
* particular version header.
|
||||
* https://docs.anthropic.com/en/release-notes/api#july-15th-2024
|
||||
*/
|
||||
function setAnthropicBetaHeader(req: Request) {
|
||||
const { max_tokens_to_sample } = req.body;
|
||||
if (max_tokens_to_sample > 4096) {
|
||||
req.headers["anthropic-beta"] = "max-tokens-3-5-sonnet-2024-07-15";
|
||||
}
|
||||
}
|
||||
|
||||
function selectUpstreamPath(manager: ProxyReqManager) {
|
||||
const req = manager.request;
|
||||
const pathname = req.url.split("?")[0];
|
||||
req.log.debug({ pathname }, "Anthropic path filter");
|
||||
const isText = req.outboundApi === "anthropic-text";
|
||||
const isChat = req.outboundApi === "anthropic-chat";
|
||||
if (isChat && pathname === "/v1/complete") {
|
||||
manager.setPath("/v1/messages");
|
||||
}
|
||||
if (isText && pathname === "/v1/chat/completions") {
|
||||
manager.setPath("/v1/complete");
|
||||
}
|
||||
if (isChat && pathname === "/v1/chat/completions") {
|
||||
manager.setPath("/v1/messages");
|
||||
}
|
||||
if (isChat && ["sonnet", "opus"].includes(req.params.type)) {
|
||||
manager.setPath("/v1/messages");
|
||||
}
|
||||
}
|
||||
|
||||
const anthropicProxy = createQueuedProxyMiddleware({
|
||||
target: "https://api.anthropic.com",
|
||||
mutations: [selectUpstreamPath, addKey, finalizeBody],
|
||||
blockingResponseHandler: anthropicBlockingResponseHandler,
|
||||
});
|
||||
|
||||
const nativeAnthropicChatPreprocessor = createPreprocessorMiddleware(
|
||||
{ inApi: "anthropic-chat", outApi: "anthropic-chat", service: "anthropic" },
|
||||
{ afterTransform: [setAnthropicBetaHeader] }
|
||||
const anthropicProxy = createQueueMiddleware(
|
||||
createProxyMiddleware({
|
||||
target: "https://api.anthropic.com",
|
||||
changeOrigin: true,
|
||||
on: {
|
||||
proxyReq: rewriteAnthropicRequest,
|
||||
proxyRes: createOnProxyResHandler([anthropicResponseHandler]),
|
||||
error: handleProxyError,
|
||||
},
|
||||
selfHandleResponse: true,
|
||||
logger,
|
||||
pathRewrite: {
|
||||
// Send OpenAI-compat requests to the real Anthropic endpoint.
|
||||
"^/v1/chat/completions": "/v1/complete",
|
||||
},
|
||||
})
|
||||
);
|
||||
|
||||
const nativeTextPreprocessor = createPreprocessorMiddleware({
|
||||
inApi: "anthropic-text",
|
||||
outApi: "anthropic-text",
|
||||
service: "anthropic",
|
||||
});
|
||||
|
||||
const textToChatPreprocessor = createPreprocessorMiddleware({
|
||||
inApi: "anthropic-text",
|
||||
outApi: "anthropic-chat",
|
||||
service: "anthropic",
|
||||
});
|
||||
|
||||
/**
|
||||
* Routes text completion prompts to anthropic-chat if they need translation
|
||||
* (claude-3 based models do not support the old text completion endpoint).
|
||||
*/
|
||||
const preprocessAnthropicTextRequest: RequestHandler = (req, res, next) => {
|
||||
if (req.body.model?.startsWith("claude-3")) {
|
||||
textToChatPreprocessor(req, res, next);
|
||||
} else {
|
||||
nativeTextPreprocessor(req, res, next);
|
||||
}
|
||||
};
|
||||
|
||||
const oaiToTextPreprocessor = createPreprocessorMiddleware({
|
||||
inApi: "openai",
|
||||
outApi: "anthropic-text",
|
||||
service: "anthropic",
|
||||
});
|
||||
|
||||
const oaiToChatPreprocessor = createPreprocessorMiddleware({
|
||||
inApi: "openai",
|
||||
outApi: "anthropic-chat",
|
||||
service: "anthropic",
|
||||
});
|
||||
|
||||
/**
|
||||
* Routes an OpenAI prompt to either the legacy Claude text completion endpoint
|
||||
* or the new Claude chat completion endpoint, based on the requested model.
|
||||
*/
|
||||
const preprocessOpenAICompatRequest: RequestHandler = (req, res, next) => {
|
||||
maybeReassignModel(req);
|
||||
if (req.body.model?.includes("claude-3")) {
|
||||
oaiToChatPreprocessor(req, res, next);
|
||||
} else {
|
||||
oaiToTextPreprocessor(req, res, next);
|
||||
}
|
||||
};
|
||||
|
||||
const anthropicRouter = Router();
|
||||
// Fix paths because clients don't consistently use the /v1 prefix.
|
||||
anthropicRouter.use((req, _res, next) => {
|
||||
if (!req.path.startsWith("/v1/")) {
|
||||
req.url = `/v1${req.url}`;
|
||||
}
|
||||
next();
|
||||
});
|
||||
anthropicRouter.get("/v1/models", handleModelRequest);
|
||||
// Native Anthropic chat completion endpoint.
|
||||
anthropicRouter.post(
|
||||
"/v1/messages",
|
||||
ipLimiter,
|
||||
nativeAnthropicChatPreprocessor,
|
||||
anthropicProxy
|
||||
);
|
||||
// Anthropic text completion endpoint. Translates to Anthropic chat completion
|
||||
// if the requested model is a Claude 3 model.
|
||||
anthropicRouter.post(
|
||||
"/v1/complete",
|
||||
ipLimiter,
|
||||
preprocessAnthropicTextRequest,
|
||||
createPreprocessorMiddleware({ inApi: "anthropic", outApi: "anthropic" }),
|
||||
anthropicProxy
|
||||
);
|
||||
// OpenAI-to-Anthropic compatibility endpoint. Accepts an OpenAI chat completion
|
||||
// request and transforms/routes it to the appropriate Anthropic format and
|
||||
// endpoint based on the requested model.
|
||||
// OpenAI-to-Anthropic compatibility endpoint.
|
||||
anthropicRouter.post(
|
||||
"/v1/chat/completions",
|
||||
ipLimiter,
|
||||
preprocessOpenAICompatRequest,
|
||||
createPreprocessorMiddleware({ inApi: "openai", outApi: "anthropic" }),
|
||||
anthropicProxy
|
||||
);
|
||||
// Redirect browser requests to the homepage.
|
||||
anthropicRouter.get("*", (req, res, next) => {
|
||||
const isBrowser = req.headers["user-agent"]?.includes("Mozilla");
|
||||
if (isBrowser) {
|
||||
res.redirect("/");
|
||||
} else {
|
||||
next();
|
||||
}
|
||||
});
|
||||
|
||||
export const anthropic = anthropicRouter;
|
||||
|
||||
@@ -1,257 +0,0 @@
|
||||
import { Request, RequestHandler, Router } from "express";
|
||||
import { v4 } from "uuid";
|
||||
import {
|
||||
transformAnthropicChatResponseToAnthropicText,
|
||||
transformAnthropicChatResponseToOpenAI,
|
||||
} from "./anthropic";
|
||||
import { ipLimiter } from "./rate-limit";
|
||||
import {
|
||||
createPreprocessorMiddleware,
|
||||
finalizeSignedRequest,
|
||||
signAwsRequest,
|
||||
} from "./middleware/request";
|
||||
import { ProxyResHandlerWithBody } from "./middleware/response";
|
||||
import { createQueuedProxyMiddleware } from "./middleware/request/proxy-middleware-factory";
|
||||
|
||||
const awsBlockingResponseHandler: ProxyResHandlerWithBody = async (
|
||||
_proxyRes,
|
||||
req,
|
||||
res,
|
||||
body
|
||||
) => {
|
||||
if (typeof body !== "object") {
|
||||
throw new Error("Expected body to be an object");
|
||||
}
|
||||
|
||||
let newBody = body;
|
||||
switch (`${req.inboundApi}<-${req.outboundApi}`) {
|
||||
case "openai<-anthropic-text":
|
||||
req.log.info("Transforming Anthropic Text back to OpenAI format");
|
||||
newBody = transformAwsTextResponseToOpenAI(body, req);
|
||||
break;
|
||||
case "openai<-anthropic-chat":
|
||||
req.log.info("Transforming AWS Anthropic Chat back to OpenAI format");
|
||||
newBody = transformAnthropicChatResponseToOpenAI(body);
|
||||
break;
|
||||
case "anthropic-text<-anthropic-chat":
|
||||
req.log.info("Transforming AWS Anthropic Chat back to Text format");
|
||||
newBody = transformAnthropicChatResponseToAnthropicText(body);
|
||||
break;
|
||||
}
|
||||
|
||||
// AWS does not always confirm the model in the response, so we have to add it
|
||||
if (!newBody.model && req.body.model) {
|
||||
newBody.model = req.body.model;
|
||||
}
|
||||
|
||||
res.status(200).json({ ...newBody, proxy: body.proxy });
|
||||
};
|
||||
|
||||
function transformAwsTextResponseToOpenAI(
|
||||
awsBody: Record<string, any>,
|
||||
req: Request
|
||||
): Record<string, any> {
|
||||
const totalTokens = (req.promptTokens ?? 0) + (req.outputTokens ?? 0);
|
||||
return {
|
||||
id: "aws-" + v4(),
|
||||
object: "chat.completion",
|
||||
created: Date.now(),
|
||||
model: req.body.model,
|
||||
usage: {
|
||||
prompt_tokens: req.promptTokens,
|
||||
completion_tokens: req.outputTokens,
|
||||
total_tokens: totalTokens,
|
||||
},
|
||||
choices: [
|
||||
{
|
||||
message: {
|
||||
role: "assistant",
|
||||
content: awsBody.completion?.trim(),
|
||||
},
|
||||
finish_reason: awsBody.stop_reason,
|
||||
index: 0,
|
||||
},
|
||||
],
|
||||
};
|
||||
}
|
||||
|
||||
const awsClaudeProxy = createQueuedProxyMiddleware({
|
||||
target: ({ signedRequest }) => {
|
||||
if (!signedRequest) throw new Error("Must sign request before proxying");
|
||||
return `${signedRequest.protocol}//${signedRequest.hostname}`;
|
||||
},
|
||||
mutations: [signAwsRequest, finalizeSignedRequest],
|
||||
blockingResponseHandler: awsBlockingResponseHandler,
|
||||
});
|
||||
|
||||
const nativeTextPreprocessor = createPreprocessorMiddleware(
|
||||
{ inApi: "anthropic-text", outApi: "anthropic-text", service: "aws" },
|
||||
{ afterTransform: [maybeReassignModel] }
|
||||
);
|
||||
|
||||
const textToChatPreprocessor = createPreprocessorMiddleware(
|
||||
{ inApi: "anthropic-text", outApi: "anthropic-chat", service: "aws" },
|
||||
{ afterTransform: [maybeReassignModel] }
|
||||
);
|
||||
|
||||
/**
|
||||
* Routes text completion prompts to aws anthropic-chat if they need translation
|
||||
* (claude-3 based models do not support the old text completion endpoint).
|
||||
*/
|
||||
const preprocessAwsTextRequest: RequestHandler = (req, res, next) => {
|
||||
if (req.body.model?.includes("claude-3")) {
|
||||
textToChatPreprocessor(req, res, next);
|
||||
} else {
|
||||
nativeTextPreprocessor(req, res, next);
|
||||
}
|
||||
};
|
||||
|
||||
const oaiToAwsTextPreprocessor = createPreprocessorMiddleware(
|
||||
{ inApi: "openai", outApi: "anthropic-text", service: "aws" },
|
||||
{ afterTransform: [maybeReassignModel] }
|
||||
);
|
||||
|
||||
const oaiToAwsChatPreprocessor = createPreprocessorMiddleware(
|
||||
{ inApi: "openai", outApi: "anthropic-chat", service: "aws" },
|
||||
{ afterTransform: [maybeReassignModel] }
|
||||
);
|
||||
|
||||
/**
|
||||
* Routes an OpenAI prompt to either the legacy Claude text completion endpoint
|
||||
* or the new Claude chat completion endpoint, based on the requested model.
|
||||
*/
|
||||
const preprocessOpenAICompatRequest: RequestHandler = (req, res, next) => {
|
||||
if (req.body.model?.includes("claude-3")) {
|
||||
oaiToAwsChatPreprocessor(req, res, next);
|
||||
} else {
|
||||
oaiToAwsTextPreprocessor(req, res, next);
|
||||
}
|
||||
};
|
||||
|
||||
const awsClaudeRouter = Router();
|
||||
// Native(ish) Anthropic text completion endpoint.
|
||||
awsClaudeRouter.post(
|
||||
"/v1/complete",
|
||||
ipLimiter,
|
||||
preprocessAwsTextRequest,
|
||||
awsClaudeProxy
|
||||
);
|
||||
// Native Anthropic chat completion endpoint.
|
||||
awsClaudeRouter.post(
|
||||
"/v1/messages",
|
||||
ipLimiter,
|
||||
createPreprocessorMiddleware(
|
||||
{ inApi: "anthropic-chat", outApi: "anthropic-chat", service: "aws" },
|
||||
{ afterTransform: [maybeReassignModel] }
|
||||
),
|
||||
awsClaudeProxy
|
||||
);
|
||||
|
||||
// OpenAI-to-AWS Anthropic compatibility endpoint.
|
||||
awsClaudeRouter.post(
|
||||
"/v1/chat/completions",
|
||||
ipLimiter,
|
||||
preprocessOpenAICompatRequest,
|
||||
awsClaudeProxy
|
||||
);
|
||||
|
||||
/**
|
||||
* Tries to deal with:
|
||||
* - frontends sending AWS model names even when they want to use the OpenAI-
|
||||
* compatible endpoint
|
||||
* - frontends sending Anthropic model names that AWS doesn't recognize
|
||||
* - frontends sending OpenAI model names because they expect the proxy to
|
||||
* translate them
|
||||
*
|
||||
* If client sends AWS model ID it will be used verbatim. Otherwise, various
|
||||
* strategies are used to try to map a non-AWS model name to AWS model ID.
|
||||
*/
|
||||
function maybeReassignModel(req: Request) {
|
||||
const model = req.body.model;
|
||||
|
||||
// If it looks like an AWS model, use it as-is
|
||||
if (model.includes("anthropic.claude")) {
|
||||
return;
|
||||
}
|
||||
|
||||
// Anthropic model names can look like:
|
||||
// - claude-v1
|
||||
// - claude-2.1
|
||||
// - claude-3-5-sonnet-20240620
|
||||
// - claude-3-opus-latest
|
||||
const pattern =
|
||||
/^(claude-)?(instant-)?(v)?(\d+)([.-](\d))?(-\d+k)?(-sonnet-|-opus-|-haiku-)?(latest|\d*)/i;
|
||||
const match = model.match(pattern);
|
||||
|
||||
if (!match) {
|
||||
throw new Error(`Provided model name (${model}) doesn't resemble a Claude model ID.`);
|
||||
}
|
||||
|
||||
const [_, _cl, instant, _v, major, _sep, minor, _ctx, rawName, rev] = match;
|
||||
|
||||
if (instant) {
|
||||
req.body.model = "anthropic.claude-instant-v1";
|
||||
return;
|
||||
}
|
||||
|
||||
const ver = minor ? `${major}.${minor}` : major;
|
||||
const name = rawName?.match(/([a-z]+)/)?.[1] || "";
|
||||
|
||||
switch (ver) {
|
||||
case "1":
|
||||
case "1.0":
|
||||
req.body.model = "anthropic.claude-v1";
|
||||
return;
|
||||
case "2":
|
||||
case "2.0":
|
||||
req.body.model = "anthropic.claude-v2";
|
||||
return;
|
||||
case "2.1":
|
||||
req.body.model = "anthropic.claude-v2:1";
|
||||
return;
|
||||
case "3":
|
||||
case "3.0":
|
||||
// there is only one snapshot for all Claude 3 models so there is no need
|
||||
// to check the revision
|
||||
switch (name) {
|
||||
case "sonnet":
|
||||
req.body.model = "anthropic.claude-3-sonnet-20240229-v1:0";
|
||||
return;
|
||||
case "haiku":
|
||||
req.body.model = "anthropic.claude-3-haiku-20240307-v1:0";
|
||||
return;
|
||||
case "opus":
|
||||
req.body.model = "anthropic.claude-3-opus-20240229-v1:0";
|
||||
return;
|
||||
}
|
||||
break;
|
||||
case "3.5":
|
||||
switch (name) {
|
||||
case "sonnet":
|
||||
switch (rev) {
|
||||
case "20241022":
|
||||
case "latest":
|
||||
req.body.model = "anthropic.claude-3-5-sonnet-20241022-v2:0";
|
||||
return;
|
||||
case "20240620":
|
||||
req.body.model = "anthropic.claude-3-5-sonnet-20240620-v1:0";
|
||||
return;
|
||||
}
|
||||
break;
|
||||
case "haiku":
|
||||
switch (rev) {
|
||||
case "20241022":
|
||||
case "latest":
|
||||
req.body.model = "anthropic.claude-3-5-haiku-20241022-v1:0";
|
||||
return;
|
||||
}
|
||||
case "opus":
|
||||
// Add after model id is announced never
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
throw new Error(`Provided model name (${model}) could not be mapped to a known AWS Claude model ID.`);
|
||||
}
|
||||
|
||||
export const awsClaude = awsClaudeRouter;
|
||||
@@ -1,95 +0,0 @@
|
||||
import { Request, Router } from "express";
|
||||
import {
|
||||
detectMistralInputApi,
|
||||
transformMistralTextToMistralChat,
|
||||
} from "./mistral-ai";
|
||||
import { ipLimiter } from "./rate-limit";
|
||||
import { ProxyResHandlerWithBody } from "./middleware/response";
|
||||
import {
|
||||
createPreprocessorMiddleware,
|
||||
finalizeSignedRequest,
|
||||
signAwsRequest,
|
||||
} from "./middleware/request";
|
||||
import { createQueuedProxyMiddleware } from "./middleware/request/proxy-middleware-factory";
|
||||
|
||||
const awsMistralBlockingResponseHandler: ProxyResHandlerWithBody = async (
|
||||
_proxyRes,
|
||||
req,
|
||||
res,
|
||||
body
|
||||
) => {
|
||||
if (typeof body !== "object") {
|
||||
throw new Error("Expected body to be an object");
|
||||
}
|
||||
|
||||
let newBody = body;
|
||||
if (req.inboundApi === "mistral-ai" && req.outboundApi === "mistral-text") {
|
||||
newBody = transformMistralTextToMistralChat(body);
|
||||
}
|
||||
// AWS does not always confirm the model in the response, so we have to add it
|
||||
if (!newBody.model && req.body.model) {
|
||||
newBody.model = req.body.model;
|
||||
}
|
||||
|
||||
res.status(200).json({ ...newBody, proxy: body.proxy });
|
||||
};
|
||||
|
||||
const awsMistralProxy = createQueuedProxyMiddleware({
|
||||
target: ({ signedRequest }) => {
|
||||
if (!signedRequest) throw new Error("Must sign request before proxying");
|
||||
return `${signedRequest.protocol}//${signedRequest.hostname}`;
|
||||
},
|
||||
mutations: [signAwsRequest,finalizeSignedRequest],
|
||||
blockingResponseHandler: awsMistralBlockingResponseHandler,
|
||||
});
|
||||
|
||||
function maybeReassignModel(req: Request) {
|
||||
const model = req.body.model;
|
||||
|
||||
// If it looks like an AWS model, use it as-is
|
||||
if (model.startsWith("mistral.")) {
|
||||
return;
|
||||
}
|
||||
// Mistral 7B Instruct
|
||||
else if (model.includes("7b")) {
|
||||
req.body.model = "mistral.mistral-7b-instruct-v0:2";
|
||||
}
|
||||
// Mistral 8x7B Instruct
|
||||
else if (model.includes("8x7b")) {
|
||||
req.body.model = "mistral.mixtral-8x7b-instruct-v0:1";
|
||||
}
|
||||
// Mistral Large (Feb 2024)
|
||||
else if (model.includes("large-2402")) {
|
||||
req.body.model = "mistral.mistral-large-2402-v1:0";
|
||||
}
|
||||
// Mistral Large 2 (July 2024)
|
||||
else if (model.includes("large")) {
|
||||
req.body.model = "mistral.mistral-large-2407-v1:0";
|
||||
}
|
||||
// Mistral Small (Feb 2024)
|
||||
else if (model.includes("small")) {
|
||||
req.body.model = "mistral.mistral-small-2402-v1:0";
|
||||
} else {
|
||||
throw new Error(
|
||||
`Can't map '${model}' to a supported AWS model ID; make sure you are requesting a Mistral model supported by Amazon Bedrock`
|
||||
);
|
||||
}
|
||||
}
|
||||
|
||||
const nativeMistralChatPreprocessor = createPreprocessorMiddleware(
|
||||
{ inApi: "mistral-ai", outApi: "mistral-ai", service: "aws" },
|
||||
{
|
||||
beforeTransform: [detectMistralInputApi],
|
||||
afterTransform: [maybeReassignModel],
|
||||
}
|
||||
);
|
||||
|
||||
const awsMistralRouter = Router();
|
||||
awsMistralRouter.post(
|
||||
"/v1/chat/completions",
|
||||
ipLimiter,
|
||||
nativeMistralChatPreprocessor,
|
||||
awsMistralProxy
|
||||
);
|
||||
|
||||
export const awsMistral = awsMistralRouter;
|
||||
@@ -1,77 +0,0 @@
|
||||
/* Shared code between AWS Claude and AWS Mistral endpoints. */
|
||||
|
||||
import { Request, Response, Router } from "express";
|
||||
import { config } from "../config";
|
||||
import { addV1 } from "./add-v1";
|
||||
import { awsClaude } from "./aws-claude";
|
||||
import { awsMistral } from "./aws-mistral";
|
||||
import { AwsBedrockKey, keyPool } from "../shared/key-management";
|
||||
|
||||
const awsRouter = Router();
|
||||
awsRouter.get(["/:vendor?/v1/models", "/:vendor?/models"], handleModelsRequest);
|
||||
awsRouter.use("/claude", addV1, awsClaude);
|
||||
awsRouter.use("/mistral", addV1, awsMistral);
|
||||
|
||||
const MODELS_CACHE_TTL = 10000;
|
||||
let modelsCache: Record<string, any> = {};
|
||||
let modelsCacheTime: Record<string, number> = {};
|
||||
function handleModelsRequest(req: Request, res: Response) {
|
||||
if (!config.awsCredentials) return { object: "list", data: [] };
|
||||
|
||||
const vendor = req.params.vendor?.length
|
||||
? req.params.vendor === "claude"
|
||||
? "anthropic"
|
||||
: req.params.vendor
|
||||
: "all";
|
||||
|
||||
const cacheTime = modelsCacheTime[vendor] || 0;
|
||||
if (new Date().getTime() - cacheTime < MODELS_CACHE_TTL) {
|
||||
return res.json(modelsCache[vendor]);
|
||||
}
|
||||
|
||||
const availableModelIds = new Set<string>();
|
||||
for (const key of keyPool.list()) {
|
||||
if (key.isDisabled || key.service !== "aws") continue;
|
||||
(key as AwsBedrockKey).modelIds.forEach((id) => availableModelIds.add(id));
|
||||
}
|
||||
|
||||
// https://docs.aws.amazon.com/bedrock/latest/userguide/model-ids.html
|
||||
const models = [
|
||||
"anthropic.claude-v2",
|
||||
"anthropic.claude-v2:1",
|
||||
"anthropic.claude-3-haiku-20240307-v1:0",
|
||||
"anthropic.claude-3-5-haiku-20241022-v1:0",
|
||||
"anthropic.claude-3-sonnet-20240229-v1:0",
|
||||
"anthropic.claude-3-5-sonnet-20240620-v1:0",
|
||||
"anthropic.claude-3-5-sonnet-20241022-v2:0",
|
||||
"anthropic.claude-3-opus-20240229-v1:0",
|
||||
"mistral.mistral-7b-instruct-v0:2",
|
||||
"mistral.mixtral-8x7b-instruct-v0:1",
|
||||
"mistral.mistral-large-2402-v1:0",
|
||||
"mistral.mistral-large-2407-v1:0",
|
||||
"mistral.mistral-small-2402-v1:0",
|
||||
]
|
||||
.filter((id) => availableModelIds.has(id))
|
||||
.map((id) => {
|
||||
const vendor = id.match(/^(.*)\./)?.[1];
|
||||
return {
|
||||
id,
|
||||
object: "model",
|
||||
created: new Date().getTime(),
|
||||
owned_by: vendor,
|
||||
permission: [],
|
||||
root: vendor,
|
||||
parent: null,
|
||||
};
|
||||
});
|
||||
|
||||
modelsCache[vendor] = {
|
||||
object: "list",
|
||||
data: models.filter((m) => vendor === "all" || m.root === vendor),
|
||||
};
|
||||
modelsCacheTime[vendor] = new Date().getTime();
|
||||
|
||||
return res.json(modelsCache[vendor]);
|
||||
}
|
||||
|
||||
export const aws = awsRouter;
|
||||
@@ -1,77 +0,0 @@
|
||||
import { RequestHandler, Router } from "express";
|
||||
import { config } from "../config";
|
||||
import { generateModelList } from "./openai";
|
||||
import { ipLimiter } from "./rate-limit";
|
||||
import {
|
||||
addAzureKey,
|
||||
createPreprocessorMiddleware,
|
||||
finalizeSignedRequest,
|
||||
} from "./middleware/request";
|
||||
import { ProxyResHandlerWithBody } from "./middleware/response";
|
||||
import { createQueuedProxyMiddleware } from "./middleware/request/proxy-middleware-factory";
|
||||
|
||||
let modelsCache: any = null;
|
||||
let modelsCacheTime = 0;
|
||||
|
||||
const handleModelRequest: RequestHandler = (_req, res) => {
|
||||
if (new Date().getTime() - modelsCacheTime < 1000 * 60) {
|
||||
return res.status(200).json(modelsCache);
|
||||
}
|
||||
|
||||
if (!config.azureCredentials) return { object: "list", data: [] };
|
||||
|
||||
const result = generateModelList("azure");
|
||||
|
||||
modelsCache = { object: "list", data: result };
|
||||
modelsCacheTime = new Date().getTime();
|
||||
res.status(200).json(modelsCache);
|
||||
};
|
||||
|
||||
const azureOpenaiResponseHandler: ProxyResHandlerWithBody = async (
|
||||
_proxyRes,
|
||||
req,
|
||||
res,
|
||||
body
|
||||
) => {
|
||||
if (typeof body !== "object") {
|
||||
throw new Error("Expected body to be an object");
|
||||
}
|
||||
|
||||
res.status(200).json({ ...body, proxy: body.proxy });
|
||||
};
|
||||
|
||||
const azureOpenAIProxy = createQueuedProxyMiddleware({
|
||||
target: ({ signedRequest }) => {
|
||||
if (!signedRequest) throw new Error("Must sign request before proxying");
|
||||
const { hostname, protocol } = signedRequest;
|
||||
return `${protocol}//${hostname}`;
|
||||
},
|
||||
mutations: [addAzureKey, finalizeSignedRequest],
|
||||
blockingResponseHandler: azureOpenaiResponseHandler,
|
||||
});
|
||||
|
||||
|
||||
const azureOpenAIRouter = Router();
|
||||
azureOpenAIRouter.get("/v1/models", handleModelRequest);
|
||||
azureOpenAIRouter.post(
|
||||
"/v1/chat/completions",
|
||||
ipLimiter,
|
||||
createPreprocessorMiddleware({
|
||||
inApi: "openai",
|
||||
outApi: "openai",
|
||||
service: "azure",
|
||||
}),
|
||||
azureOpenAIProxy
|
||||
);
|
||||
azureOpenAIRouter.post(
|
||||
"/v1/images/generations",
|
||||
ipLimiter,
|
||||
createPreprocessorMiddleware({
|
||||
inApi: "openai-image",
|
||||
outApi: "openai-image",
|
||||
service: "azure",
|
||||
}),
|
||||
azureOpenAIProxy
|
||||
);
|
||||
|
||||
export const azure = azureOpenAIRouter;
|
||||
@@ -21,7 +21,7 @@ kYuIJbnAGw5Oq0L6dXFW2DFwlcLz51kPVOmDc159FsQjyuPnta7NiZAANS8KM1CJ
|
||||
pwIDAQAB`;
|
||||
let IMPORTED_RISU_KEY: CryptoKey | null = null;
|
||||
|
||||
type RisuToken = { id: string; expiresIn: number };
|
||||
type RisuToken = { id: Uint8Array; expiresIn: number };
|
||||
type SignedToken = { data: RisuToken; sig: string };
|
||||
|
||||
(async () => {
|
||||
@@ -54,14 +54,14 @@ export async function checkRisuToken(
|
||||
try {
|
||||
const { valid, data } = await validCheck(header);
|
||||
|
||||
if (!valid || !data) {
|
||||
if (!valid) {
|
||||
req.log.warn(
|
||||
{ token: header, data },
|
||||
"Invalid RisuAI token; using IP instead"
|
||||
);
|
||||
} else {
|
||||
req.log.info("RisuAI token validated");
|
||||
req.risuToken = String(data.id);
|
||||
req.risuToken = header;
|
||||
}
|
||||
} catch (err) {
|
||||
req.log.warn(
|
||||
@@ -81,13 +81,12 @@ async function validCheck(header: string) {
|
||||
);
|
||||
} catch (err) {
|
||||
log.warn({ error: err.message }, "Provided unparseable RisuAI token");
|
||||
return { valid: false };
|
||||
return { valid: false, data: "[unparseable]" };
|
||||
}
|
||||
const data: RisuToken = tk.data;
|
||||
const sig = Buffer.from(tk.sig, "base64");
|
||||
|
||||
if (data.expiresIn < Math.floor(Date.now() / 1000)) {
|
||||
log.warn({ token: header }, "Provided expired RisuAI token");
|
||||
return { valid: false };
|
||||
}
|
||||
|
||||
@@ -98,9 +97,5 @@ async function validCheck(header: string) {
|
||||
Buffer.from(JSON.stringify(data))
|
||||
);
|
||||
|
||||
if (!valid) {
|
||||
log.warn({ token: header }, "RisuAI token failed signature check");
|
||||
}
|
||||
|
||||
return { valid, data };
|
||||
}
|
||||
|
||||
+15
-67
@@ -1,7 +1,6 @@
|
||||
import type { Request, Response, RequestHandler } from "express";
|
||||
import type { Request, RequestHandler } from "express";
|
||||
import { config } from "../config";
|
||||
import { authenticate, getUser } from "../shared/users/user-store";
|
||||
import { sendErrorToClient } from "./middleware/response/error-generator";
|
||||
|
||||
const GATEKEEPER = config.gatekeeper;
|
||||
const PROXY_KEY = config.proxyKey;
|
||||
@@ -12,7 +11,6 @@ function getProxyAuthorizationFromRequest(req: Request): string | undefined {
|
||||
// pass the _proxy_ key in this header too, instead of providing it as a
|
||||
// Bearer token in the Authorization header. So we need to check both.
|
||||
// Prefer the Authorization header if both are present.
|
||||
// Google AI uses a key querystring parameter.
|
||||
|
||||
if (req.headers.authorization) {
|
||||
const token = req.headers.authorization?.slice("Bearer ".length);
|
||||
@@ -25,12 +23,6 @@ function getProxyAuthorizationFromRequest(req: Request): string | undefined {
|
||||
delete req.headers["x-api-key"];
|
||||
return token;
|
||||
}
|
||||
|
||||
if (req.query.key) {
|
||||
const token = req.query.key?.toString();
|
||||
delete req.query.key;
|
||||
return token;
|
||||
}
|
||||
|
||||
return undefined;
|
||||
}
|
||||
@@ -54,65 +46,21 @@ export const gatekeeper: RequestHandler = (req, res, next) => {
|
||||
}
|
||||
|
||||
if (GATEKEEPER === "user_token" && token) {
|
||||
// RisuAI users all come from a handful of aws lambda IPs so we cannot use
|
||||
// IP alone to distinguish between them and prevent usertoken sharing.
|
||||
// Risu sends a signed token in the request headers with an anonymous user
|
||||
// ID that we can instead use to associate requests with an individual.
|
||||
const ip = req.risuToken?.length
|
||||
? `risu${req.risuToken}-${req.ip}`
|
||||
: req.ip;
|
||||
|
||||
const { user, result } = authenticate(token, ip);
|
||||
|
||||
switch (result) {
|
||||
case "success":
|
||||
req.user = user;
|
||||
return next();
|
||||
case "limited":
|
||||
return sendError(
|
||||
req,
|
||||
res,
|
||||
403,
|
||||
`Forbidden: no more IP addresses allowed for this user token`,
|
||||
{ currentIp: ip, maxIps: user?.maxIps }
|
||||
);
|
||||
case "disabled":
|
||||
const bannedUser = getUser(token);
|
||||
if (bannedUser?.disabledAt) {
|
||||
const reason = bannedUser.disabledReason || "User token disabled";
|
||||
return sendError(req, res, 403, `Forbidden: ${reason}`);
|
||||
}
|
||||
const user = authenticate(token, req.ip);
|
||||
if (user) {
|
||||
req.user = user;
|
||||
return next();
|
||||
} else {
|
||||
const maybeBannedUser = getUser(token);
|
||||
if (maybeBannedUser?.disabledAt) {
|
||||
return res.status(403).json({
|
||||
error: `Forbidden: ${
|
||||
maybeBannedUser.disabledReason || "Token disabled"
|
||||
}`,
|
||||
});
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
sendError(req, res, 401, "Unauthorized");
|
||||
res.status(401).json({ error: "Unauthorized" });
|
||||
};
|
||||
|
||||
function sendError(
|
||||
req: Request,
|
||||
res: Response,
|
||||
status: number,
|
||||
message: string,
|
||||
data: any = {}
|
||||
) {
|
||||
const isPost = req.method === "POST";
|
||||
const hasBody = isPost && req.body;
|
||||
const hasModel = hasBody && req.body.model;
|
||||
|
||||
if (!hasModel) {
|
||||
return res.status(status).json({ error: message });
|
||||
}
|
||||
|
||||
sendErrorToClient({
|
||||
req,
|
||||
res,
|
||||
options: {
|
||||
title: `Proxy gatekeeper error (HTTP ${status})`,
|
||||
message,
|
||||
format: "unknown",
|
||||
statusCode: status,
|
||||
reqId: req.id,
|
||||
obj: data,
|
||||
},
|
||||
});
|
||||
}
|
||||
|
||||
@@ -1,196 +0,0 @@
|
||||
import { Request, RequestHandler, Router } from "express";
|
||||
import { config } from "../config";
|
||||
import { transformAnthropicChatResponseToOpenAI } from "./anthropic";
|
||||
import { ipLimiter } from "./rate-limit";
|
||||
import {
|
||||
createPreprocessorMiddleware,
|
||||
finalizeSignedRequest,
|
||||
signGcpRequest,
|
||||
} from "./middleware/request";
|
||||
import { ProxyResHandlerWithBody } from "./middleware/response";
|
||||
import { createQueuedProxyMiddleware } from "./middleware/request/proxy-middleware-factory";
|
||||
|
||||
const LATEST_GCP_SONNET_MINOR_VERSION = "20240229";
|
||||
|
||||
let modelsCache: any = null;
|
||||
let modelsCacheTime = 0;
|
||||
|
||||
const getModelsResponse = () => {
|
||||
if (new Date().getTime() - modelsCacheTime < 1000 * 60) {
|
||||
return modelsCache;
|
||||
}
|
||||
|
||||
if (!config.gcpCredentials) return { object: "list", data: [] };
|
||||
|
||||
// https://docs.anthropic.com/en/docs/about-claude/models
|
||||
const variants = [
|
||||
"claude-3-haiku@20240307",
|
||||
"claude-3-5-haiku@20241022",
|
||||
"claude-3-sonnet@20240229",
|
||||
"claude-3-5-sonnet@20240620",
|
||||
"claude-3-5-sonnet-v2@20241022",
|
||||
"claude-3-opus@20240229",
|
||||
];
|
||||
|
||||
const models = variants.map((id) => ({
|
||||
id,
|
||||
object: "model",
|
||||
created: new Date().getTime(),
|
||||
owned_by: "anthropic",
|
||||
permission: [],
|
||||
root: "claude",
|
||||
parent: null,
|
||||
}));
|
||||
|
||||
modelsCache = { object: "list", data: models };
|
||||
modelsCacheTime = new Date().getTime();
|
||||
|
||||
return modelsCache;
|
||||
};
|
||||
|
||||
const handleModelRequest: RequestHandler = (_req, res) => {
|
||||
res.status(200).json(getModelsResponse());
|
||||
};
|
||||
|
||||
const gcpBlockingResponseHandler: ProxyResHandlerWithBody = async (
|
||||
_proxyRes,
|
||||
req,
|
||||
res,
|
||||
body
|
||||
) => {
|
||||
if (typeof body !== "object") {
|
||||
throw new Error("Expected body to be an object");
|
||||
}
|
||||
|
||||
let newBody = body;
|
||||
switch (`${req.inboundApi}<-${req.outboundApi}`) {
|
||||
case "openai<-anthropic-chat":
|
||||
req.log.info("Transforming Anthropic Chat back to OpenAI format");
|
||||
newBody = transformAnthropicChatResponseToOpenAI(body);
|
||||
break;
|
||||
}
|
||||
|
||||
res.status(200).json({ ...newBody, proxy: body.proxy });
|
||||
};
|
||||
|
||||
const gcpProxy = createQueuedProxyMiddleware({
|
||||
target: ({ signedRequest }) => {
|
||||
if (!signedRequest) throw new Error("Must sign request before proxying");
|
||||
return `${signedRequest.protocol}//${signedRequest.hostname}`;
|
||||
},
|
||||
mutations: [signGcpRequest, finalizeSignedRequest],
|
||||
blockingResponseHandler: gcpBlockingResponseHandler,
|
||||
});
|
||||
|
||||
const oaiToChatPreprocessor = createPreprocessorMiddleware(
|
||||
{ inApi: "openai", outApi: "anthropic-chat", service: "gcp" },
|
||||
{ afterTransform: [maybeReassignModel] }
|
||||
);
|
||||
|
||||
/**
|
||||
* Routes an OpenAI prompt to either the legacy Claude text completion endpoint
|
||||
* or the new Claude chat completion endpoint, based on the requested model.
|
||||
*/
|
||||
const preprocessOpenAICompatRequest: RequestHandler = (req, res, next) => {
|
||||
oaiToChatPreprocessor(req, res, next);
|
||||
};
|
||||
|
||||
const gcpRouter = Router();
|
||||
gcpRouter.get("/v1/models", handleModelRequest);
|
||||
// Native Anthropic chat completion endpoint.
|
||||
gcpRouter.post(
|
||||
"/v1/messages",
|
||||
ipLimiter,
|
||||
createPreprocessorMiddleware(
|
||||
{ inApi: "anthropic-chat", outApi: "anthropic-chat", service: "gcp" },
|
||||
{ afterTransform: [maybeReassignModel] }
|
||||
),
|
||||
gcpProxy
|
||||
);
|
||||
|
||||
// OpenAI-to-GCP Anthropic compatibility endpoint.
|
||||
gcpRouter.post(
|
||||
"/v1/chat/completions",
|
||||
ipLimiter,
|
||||
preprocessOpenAICompatRequest,
|
||||
gcpProxy
|
||||
);
|
||||
|
||||
/**
|
||||
* Tries to deal with:
|
||||
* - frontends sending GCP model names even when they want to use the OpenAI-
|
||||
* compatible endpoint
|
||||
* - frontends sending Anthropic model names that GCP doesn't recognize
|
||||
* - frontends sending OpenAI model names because they expect the proxy to
|
||||
* translate them
|
||||
*
|
||||
* If client sends GCP model ID it will be used verbatim. Otherwise, various
|
||||
* strategies are used to try to map a non-GCP model name to GCP model ID.
|
||||
*/
|
||||
function maybeReassignModel(req: Request) {
|
||||
const model = req.body.model;
|
||||
|
||||
// If it looks like an GCP model, use it as-is
|
||||
// if (model.includes("anthropic.claude")) {
|
||||
if (model.startsWith("claude-") && model.includes("@")) {
|
||||
return;
|
||||
}
|
||||
|
||||
// Anthropic model names can look like:
|
||||
// - claude-v1
|
||||
// - claude-2.1
|
||||
// - claude-3-5-sonnet-20240620-v1:0
|
||||
const pattern =
|
||||
/^(claude-)?(instant-)?(v)?(\d+)([.-](\d{1}))?(-\d+k)?(-sonnet-|-opus-|-haiku-)?(\d*)/i;
|
||||
const match = model.match(pattern);
|
||||
|
||||
// If there's no match, fallback to Claude3 Sonnet as it is most likely to be
|
||||
// available on GCP.
|
||||
if (!match) {
|
||||
req.body.model = `claude-3-sonnet@${LATEST_GCP_SONNET_MINOR_VERSION}`;
|
||||
return;
|
||||
}
|
||||
|
||||
const [_, _cl, instant, _v, major, _sep, minor, _ctx, name, rev] = match;
|
||||
|
||||
// TODO: rework this to function similarly to aws-claude.ts maybeReassignModel
|
||||
const ver = minor ? `${major}.${minor}` : major;
|
||||
switch (ver) {
|
||||
case "3":
|
||||
case "3.0":
|
||||
if (name.includes("opus")) {
|
||||
req.body.model = "claude-3-opus@20240229";
|
||||
} else if (name.includes("haiku")) {
|
||||
req.body.model = "claude-3-haiku@20240307";
|
||||
} else {
|
||||
req.body.model = "claude-3-sonnet@20240229";
|
||||
}
|
||||
return;
|
||||
case "3.5":
|
||||
switch (name) {
|
||||
case "sonnet":
|
||||
switch (rev) {
|
||||
case "20241022":
|
||||
case "latest":
|
||||
req.body.model = "claude-3-5-sonnet-v2@20241022";
|
||||
return;
|
||||
case "20240620":
|
||||
req.body.model = "claude-3-5-sonnet@20240620";
|
||||
return;
|
||||
}
|
||||
break;
|
||||
case "haiku":
|
||||
req.body.model = "claude-3-5-haiku@20241022";
|
||||
return;
|
||||
case "opus":
|
||||
// Add after model ids are announced late 2024
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
// Fallback to Claude3 Sonnet
|
||||
req.body.model = `claude-3-sonnet@${LATEST_GCP_SONNET_MINOR_VERSION}`;
|
||||
return;
|
||||
}
|
||||
|
||||
export const gcp = gcpRouter;
|
||||
@@ -1,176 +0,0 @@
|
||||
import { Request, RequestHandler, Router } from "express";
|
||||
import { v4 } from "uuid";
|
||||
import { GoogleAIKey, keyPool } from "../shared/key-management";
|
||||
import { config } from "../config";
|
||||
import { ipLimiter } from "./rate-limit";
|
||||
import {
|
||||
createPreprocessorMiddleware,
|
||||
finalizeSignedRequest,
|
||||
} from "./middleware/request";
|
||||
import { ProxyResHandlerWithBody } from "./middleware/response";
|
||||
import { addGoogleAIKey } from "./middleware/request/mutators/add-google-ai-key";
|
||||
import { createQueuedProxyMiddleware } from "./middleware/request/proxy-middleware-factory";
|
||||
|
||||
let modelsCache: any = null;
|
||||
let modelsCacheTime = 0;
|
||||
|
||||
// https://ai.google.dev/models/gemini
|
||||
// TODO: list models https://ai.google.dev/tutorials/rest_quickstart#list_models
|
||||
|
||||
const getModelsResponse = () => {
|
||||
if (new Date().getTime() - modelsCacheTime < 1000 * 60) {
|
||||
return modelsCache;
|
||||
}
|
||||
|
||||
if (!config.googleAIKey) return { object: "list", data: [] };
|
||||
|
||||
const keys = keyPool
|
||||
.list()
|
||||
.filter((k) => k.service === "google-ai") as GoogleAIKey[];
|
||||
if (keys.length === 0) {
|
||||
modelsCache = { object: "list", data: [] };
|
||||
modelsCacheTime = new Date().getTime();
|
||||
return modelsCache;
|
||||
}
|
||||
|
||||
const modelIds = Array.from(
|
||||
new Set(keys.map((k) => k.modelIds).flat())
|
||||
).filter((id) => id.startsWith("models/gemini"));
|
||||
const models = modelIds.map((id) => ({
|
||||
id,
|
||||
object: "model",
|
||||
created: new Date().getTime(),
|
||||
owned_by: "google",
|
||||
permission: [],
|
||||
root: "google",
|
||||
parent: null,
|
||||
}));
|
||||
|
||||
modelsCache = { object: "list", data: models };
|
||||
modelsCacheTime = new Date().getTime();
|
||||
|
||||
return modelsCache;
|
||||
};
|
||||
|
||||
const handleModelRequest: RequestHandler = (_req, res) => {
|
||||
res.status(200).json(getModelsResponse());
|
||||
};
|
||||
|
||||
const googleAIBlockingResponseHandler: ProxyResHandlerWithBody = async (
|
||||
_proxyRes,
|
||||
req,
|
||||
res,
|
||||
body
|
||||
) => {
|
||||
if (typeof body !== "object") {
|
||||
throw new Error("Expected body to be an object");
|
||||
}
|
||||
|
||||
let newBody = body;
|
||||
if (req.inboundApi === "openai") {
|
||||
req.log.info("Transforming Google AI response to OpenAI format");
|
||||
newBody = transformGoogleAIResponse(body, req);
|
||||
}
|
||||
|
||||
res.status(200).json({ ...newBody, proxy: body.proxy });
|
||||
};
|
||||
|
||||
function transformGoogleAIResponse(
|
||||
resBody: Record<string, any>,
|
||||
req: Request
|
||||
): Record<string, any> {
|
||||
const totalTokens = (req.promptTokens ?? 0) + (req.outputTokens ?? 0);
|
||||
const parts = resBody.candidates[0].content?.parts ?? [{ text: "" }];
|
||||
const content = parts[0].text.replace(/^(.{0,50}?): /, () => "");
|
||||
return {
|
||||
id: "goo-" + v4(),
|
||||
object: "chat.completion",
|
||||
created: Date.now(),
|
||||
model: req.body.model,
|
||||
usage: {
|
||||
prompt_tokens: req.promptTokens,
|
||||
completion_tokens: req.outputTokens,
|
||||
total_tokens: totalTokens,
|
||||
},
|
||||
choices: [
|
||||
{
|
||||
message: { role: "assistant", content },
|
||||
finish_reason: resBody.candidates[0].finishReason,
|
||||
index: 0,
|
||||
},
|
||||
],
|
||||
};
|
||||
}
|
||||
|
||||
const googleAIProxy = createQueuedProxyMiddleware({
|
||||
target: ({ signedRequest }) => {
|
||||
if (!signedRequest) throw new Error("Must sign request before proxying");
|
||||
const { protocol, hostname} = signedRequest;
|
||||
return `${protocol}//${hostname}`;
|
||||
},
|
||||
mutations: [addGoogleAIKey, finalizeSignedRequest],
|
||||
blockingResponseHandler: googleAIBlockingResponseHandler,
|
||||
});
|
||||
|
||||
const googleAIRouter = Router();
|
||||
googleAIRouter.get("/v1/models", handleModelRequest);
|
||||
|
||||
// Native Google AI chat completion endpoint
|
||||
googleAIRouter.post(
|
||||
"/v1beta/models/:modelId:(generateContent|streamGenerateContent)",
|
||||
ipLimiter,
|
||||
createPreprocessorMiddleware(
|
||||
{ inApi: "google-ai", outApi: "google-ai", service: "google-ai" },
|
||||
{ beforeTransform: [maybeReassignModel], afterTransform: [setStreamFlag] }
|
||||
),
|
||||
googleAIProxy
|
||||
);
|
||||
|
||||
// OpenAI-to-Google AI compatibility endpoint.
|
||||
googleAIRouter.post(
|
||||
"/v1/chat/completions",
|
||||
ipLimiter,
|
||||
createPreprocessorMiddleware(
|
||||
{ inApi: "openai", outApi: "google-ai", service: "google-ai" },
|
||||
{ afterTransform: [maybeReassignModel] }
|
||||
),
|
||||
googleAIProxy
|
||||
);
|
||||
|
||||
function setStreamFlag(req: Request) {
|
||||
const isStreaming = req.url.includes("streamGenerateContent");
|
||||
if (isStreaming) {
|
||||
req.body.stream = true;
|
||||
req.isStreaming = true;
|
||||
} else {
|
||||
req.body.stream = false;
|
||||
req.isStreaming = false;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Replaces requests for non-Google AI models with gemini-1.5-pro-latest.
|
||||
* Also strips models/ from the beginning of the model IDs.
|
||||
**/
|
||||
function maybeReassignModel(req: Request) {
|
||||
// Ensure model is on body as a lot of middleware will expect it.
|
||||
const model = req.body.model || req.url.split("/").pop()?.split(":").shift();
|
||||
if (!model) {
|
||||
throw new Error("You must specify a model with your request.");
|
||||
}
|
||||
req.body.model = model;
|
||||
|
||||
const requested = model;
|
||||
if (requested.startsWith("models/")) {
|
||||
req.body.model = requested.slice("models/".length);
|
||||
}
|
||||
|
||||
if (requested.includes("gemini")) {
|
||||
return;
|
||||
}
|
||||
|
||||
req.log.info({ requested }, "Reassigning model to gemini-1.5-pro-latest");
|
||||
req.body.model = "gemini-1.5-pro-latest";
|
||||
}
|
||||
|
||||
export const googleAI = googleAIRouter;
|
||||
@@ -0,0 +1,98 @@
|
||||
/* Pretends to be a KoboldAI API endpoint and translates incoming Kobold
|
||||
requests to OpenAI API equivalents. */
|
||||
|
||||
import { Request, Response, Router } from "express";
|
||||
import http from "http";
|
||||
import { createProxyMiddleware } from "http-proxy-middleware";
|
||||
import { config } from "../config";
|
||||
import { logger } from "../logger";
|
||||
import { ipLimiter } from "./rate-limit";
|
||||
import { handleProxyError } from "./middleware/common";
|
||||
import {
|
||||
addKey,
|
||||
createPreprocessorMiddleware,
|
||||
finalizeBody,
|
||||
languageFilter,
|
||||
transformKoboldPayload,
|
||||
} from "./middleware/request";
|
||||
import {
|
||||
createOnProxyResHandler,
|
||||
ProxyResHandlerWithBody,
|
||||
} from "./middleware/response";
|
||||
|
||||
export const handleModelRequest = (_req: Request, res: Response) => {
|
||||
res.status(200).json({ result: "Connected to OpenAI reverse proxy" });
|
||||
};
|
||||
|
||||
export const handleSoftPromptsRequest = (_req: Request, res: Response) => {
|
||||
res.status(200).json({ soft_prompts_list: [] });
|
||||
};
|
||||
|
||||
const rewriteRequest = (
|
||||
proxyReq: http.ClientRequest,
|
||||
req: Request,
|
||||
res: Response
|
||||
) => {
|
||||
req.body.stream = false;
|
||||
const rewriterPipeline = [
|
||||
addKey,
|
||||
transformKoboldPayload,
|
||||
languageFilter,
|
||||
finalizeBody,
|
||||
];
|
||||
|
||||
try {
|
||||
for (const rewriter of rewriterPipeline) {
|
||||
rewriter(proxyReq, req, res, {});
|
||||
}
|
||||
} catch (error) {
|
||||
logger.error(error, "Error while executing proxy rewriter");
|
||||
proxyReq.destroy(error as Error);
|
||||
}
|
||||
};
|
||||
|
||||
const koboldResponseHandler: ProxyResHandlerWithBody = async (
|
||||
_proxyRes,
|
||||
req,
|
||||
res,
|
||||
body
|
||||
) => {
|
||||
if (typeof body !== "object") {
|
||||
throw new Error("Expected body to be an object");
|
||||
}
|
||||
|
||||
const koboldResponse = {
|
||||
results: [{ text: body.choices[0].message.content }],
|
||||
model: body.model,
|
||||
...(config.promptLogging && {
|
||||
proxy_note: `Prompt logging is enabled on this proxy instance. See ${req.get(
|
||||
"host"
|
||||
)} for more information.`,
|
||||
}),
|
||||
};
|
||||
|
||||
res.send(JSON.stringify(koboldResponse));
|
||||
};
|
||||
|
||||
const koboldOaiProxy = createProxyMiddleware({
|
||||
target: "https://api.openai.com",
|
||||
changeOrigin: true,
|
||||
pathRewrite: {
|
||||
"^/api/v1/generate": "/v1/chat/completions",
|
||||
},
|
||||
on: {
|
||||
proxyReq: rewriteRequest,
|
||||
proxyRes: createOnProxyResHandler([koboldResponseHandler]),
|
||||
error: handleProxyError,
|
||||
},
|
||||
selfHandleResponse: true,
|
||||
logger,
|
||||
});
|
||||
|
||||
const koboldRouter = Router();
|
||||
koboldRouter.use((req, res) => {
|
||||
logger.warn(`Unhandled kobold request: ${req.method} ${req.path}`);
|
||||
res.status(404).json({ error: "Not found" });
|
||||
});
|
||||
|
||||
export const kobold = koboldRouter;
|
||||
+154
-257
@@ -1,302 +1,199 @@
|
||||
import { Request, Response } from "express";
|
||||
import http from "http";
|
||||
import { Socket } from "net";
|
||||
import httpProxy from "http-proxy";
|
||||
import { ZodError } from "zod";
|
||||
import { generateErrorMessage } from "zod-error";
|
||||
import { HttpError } from "../../shared/errors";
|
||||
import { APIFormat } from "../../shared/key-management";
|
||||
import { assertNever } from "../../shared/utils";
|
||||
import { QuotaExceededError } from "./request/preprocessors/apply-quota-limits";
|
||||
import { sendErrorToClient } from "./response/error-generator";
|
||||
import { QuotaExceededError } from "./request/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";
|
||||
const ANTHROPIC_MESSAGES_ENDPOINT = "/v1/messages";
|
||||
const ANTHROPIC_SONNET_COMPAT_ENDPOINT = "/v1/sonnet";
|
||||
const ANTHROPIC_OPUS_COMPAT_ENDPOINT = "/v1/opus";
|
||||
const GOOGLE_AI_COMPLETION_ENDPOINT = "/v1beta/models";
|
||||
|
||||
export function isTextGenerationRequest(req: Request) {
|
||||
/** 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
|
||||
return (
|
||||
req.method === "POST" &&
|
||||
[
|
||||
OPENAI_CHAT_COMPLETION_ENDPOINT,
|
||||
OPENAI_TEXT_COMPLETION_ENDPOINT,
|
||||
ANTHROPIC_COMPLETION_ENDPOINT,
|
||||
ANTHROPIC_MESSAGES_ENDPOINT,
|
||||
ANTHROPIC_SONNET_COMPAT_ENDPOINT,
|
||||
ANTHROPIC_OPUS_COMPAT_ENDPOINT,
|
||||
GOOGLE_AI_COMPLETION_ENDPOINT,
|
||||
].some((endpoint) => req.path.startsWith(endpoint))
|
||||
);
|
||||
}
|
||||
|
||||
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)
|
||||
);
|
||||
}
|
||||
|
||||
export function sendProxyError(
|
||||
export function writeErrorResponse(
|
||||
req: Request,
|
||||
res: Response,
|
||||
statusCode: number,
|
||||
statusMessage: string,
|
||||
errorPayload: Record<string, any>
|
||||
) {
|
||||
const msg =
|
||||
statusCode === 500
|
||||
? `The proxy encountered an error while trying to process your prompt.`
|
||||
: `The proxy encountered an error while trying to send your prompt to the API.`;
|
||||
const errorSource = errorPayload.error?.type?.startsWith("proxy")
|
||||
? "proxy"
|
||||
: "upstream";
|
||||
|
||||
sendErrorToClient({
|
||||
options: {
|
||||
format: req.inboundApi,
|
||||
title: `Proxy error (HTTP ${statusCode} ${statusMessage})`,
|
||||
message: `${msg} Further details are provided below.`,
|
||||
obj: errorPayload,
|
||||
reqId: req.id,
|
||||
model: req.body?.model,
|
||||
},
|
||||
req,
|
||||
res,
|
||||
});
|
||||
// If we're mid-SSE stream, send a data event with the error payload and end
|
||||
// the stream. Otherwise just send a normal error response.
|
||||
if (
|
||||
res.headersSent ||
|
||||
res.getHeader("content-type") === "text/event-stream"
|
||||
) {
|
||||
const errorContent =
|
||||
statusCode === 403
|
||||
? JSON.stringify(errorPayload)
|
||||
: JSON.stringify(errorPayload, null, 2);
|
||||
|
||||
const msg = buildFakeSseMessage(
|
||||
`${errorSource} error (${statusCode})`,
|
||||
errorContent,
|
||||
req
|
||||
);
|
||||
res.write(msg);
|
||||
res.write(`data: [DONE]\n\n`);
|
||||
res.end();
|
||||
} else {
|
||||
if (req.debug) {
|
||||
errorPayload.error.proxy_tokenizer_debug_info = req.debug;
|
||||
}
|
||||
res.status(statusCode).json(errorPayload);
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Handles errors thrown during preparation of a proxy request (before it is
|
||||
* sent to the upstream API), typically due to validation, quota, or other
|
||||
* pre-flight checks. Depending on the error class, this function will send an
|
||||
* appropriate error response to the client, streaming it if necessary.
|
||||
*/
|
||||
export const classifyErrorAndSend = (
|
||||
export const handleProxyError: httpProxy.ErrorCallback = (err, req, res) => {
|
||||
req.log.error({ err }, `Error during proxy request middleware`);
|
||||
handleInternalError(err, req as Request, res as Response);
|
||||
};
|
||||
|
||||
export const handleInternalError = (
|
||||
err: Error,
|
||||
req: Request,
|
||||
res: Response | Socket
|
||||
res: Response
|
||||
) => {
|
||||
if (res instanceof Socket) {
|
||||
// We should always have an Express response object here, but http-proxy's
|
||||
// ErrorCallback type says it could be just a Socket.
|
||||
req.log.error(err, "Caught error while proxying request to target but cannot send error response to client.");
|
||||
return res.destroy();
|
||||
}
|
||||
try {
|
||||
const { statusCode, statusMessage, userMessage, ...errorDetails } =
|
||||
classifyError(err);
|
||||
sendProxyError(req, res, statusCode, statusMessage, {
|
||||
error: { message: userMessage, ...errorDetails },
|
||||
});
|
||||
} catch (error) {
|
||||
req.log.error(error, `Error writing error response headers, giving up.`);
|
||||
res.end();
|
||||
if (err instanceof ZodError) {
|
||||
writeErrorResponse(req, res, 400, {
|
||||
error: {
|
||||
type: "proxy_validation_error",
|
||||
proxy_note: `Reverse proxy couldn't validate your request when trying to transform it. Your client may be sending invalid data.`,
|
||||
issues: err.issues,
|
||||
stack: err.stack,
|
||||
message: err.message,
|
||||
},
|
||||
});
|
||||
} else if (err.name === "ForbiddenError") {
|
||||
// Spoofs a vaguely threatening OpenAI error message. Only invoked by the
|
||||
// block-zoomers rewriter to scare off tiktokers.
|
||||
writeErrorResponse(req, res, 403, {
|
||||
error: {
|
||||
type: "organization_account_disabled",
|
||||
code: "policy_violation",
|
||||
param: null,
|
||||
message: err.message,
|
||||
},
|
||||
});
|
||||
} else if (err instanceof QuotaExceededError) {
|
||||
writeErrorResponse(req, res, 429, {
|
||||
error: {
|
||||
type: "proxy_quota_exceeded",
|
||||
code: "quota_exceeded",
|
||||
message: `You've exceeded your token quota for this model type.`,
|
||||
info: err.quotaInfo,
|
||||
stack: err.stack,
|
||||
},
|
||||
});
|
||||
} else {
|
||||
writeErrorResponse(req, res, 500, {
|
||||
error: {
|
||||
type: "proxy_internal_error",
|
||||
proxy_note: `Reverse proxy encountered an error before it could reach the upstream API.`,
|
||||
message: err.message,
|
||||
stack: err.stack,
|
||||
},
|
||||
});
|
||||
}
|
||||
} catch (e) {
|
||||
req.log.error(
|
||||
{ error: e },
|
||||
`Error writing error response headers, giving up.`
|
||||
);
|
||||
}
|
||||
};
|
||||
|
||||
function classifyError(err: Error): {
|
||||
/** HTTP status code returned to the client. */
|
||||
statusCode: number;
|
||||
/** HTTP status message returned to the client. */
|
||||
statusMessage: string;
|
||||
/** Message displayed to the user. */
|
||||
userMessage: string;
|
||||
/** Short error type, e.g. "proxy_validation_error". */
|
||||
type: string;
|
||||
} & Record<string, any> {
|
||||
const defaultError = {
|
||||
statusCode: 500,
|
||||
statusMessage: "Internal Server Error",
|
||||
userMessage: `Reverse proxy error: ${err.message}`,
|
||||
type: "proxy_internal_error",
|
||||
stack: err.stack,
|
||||
};
|
||||
export function buildFakeSseMessage(
|
||||
type: string,
|
||||
string: string,
|
||||
req: Request
|
||||
) {
|
||||
let fakeEvent;
|
||||
const useBackticks = !type.includes("403");
|
||||
const msgContent = useBackticks
|
||||
? `\`\`\`\n[${type}: ${string}]\n\`\`\`\n`
|
||||
: `[${type}: ${string}]`;
|
||||
|
||||
switch (err.constructor.name) {
|
||||
case "HttpError":
|
||||
const statusCode = (err as HttpError).status;
|
||||
return {
|
||||
statusCode,
|
||||
statusMessage: `HTTP ${statusCode} ${http.STATUS_CODES[statusCode]}`,
|
||||
userMessage: `Reverse proxy error: ${err.message}`,
|
||||
type: "proxy_http_error",
|
||||
};
|
||||
case "BadRequestError":
|
||||
return {
|
||||
statusCode: 400,
|
||||
statusMessage: "Bad Request",
|
||||
userMessage: `Request is not valid. (${err.message})`,
|
||||
type: "proxy_bad_request",
|
||||
};
|
||||
case "NotFoundError":
|
||||
return {
|
||||
statusCode: 404,
|
||||
statusMessage: "Not Found",
|
||||
userMessage: `Requested resource not found. (${err.message})`,
|
||||
type: "proxy_not_found",
|
||||
};
|
||||
case "PaymentRequiredError":
|
||||
return {
|
||||
statusCode: 402,
|
||||
statusMessage: "No Keys Available",
|
||||
userMessage: err.message,
|
||||
type: "proxy_no_keys_available",
|
||||
};
|
||||
case "ZodError":
|
||||
const userMessage = generateErrorMessage((err as ZodError).issues, {
|
||||
prefix: "Request validation failed. ",
|
||||
path: { enabled: true, label: null, type: "breadcrumbs" },
|
||||
code: { enabled: false },
|
||||
maxErrors: 3,
|
||||
transform: ({ issue, ...rest }) => {
|
||||
return `At '${rest.pathComponent}': ${issue.message}`;
|
||||
},
|
||||
});
|
||||
return {
|
||||
statusCode: 400,
|
||||
statusMessage: "Bad Request",
|
||||
userMessage,
|
||||
type: "proxy_validation_error",
|
||||
};
|
||||
case "ZoomerForbiddenError":
|
||||
// Mimics a ban notice from OpenAI, thrown when blockZoomerOrigins blocks
|
||||
// a request.
|
||||
return {
|
||||
statusCode: 403,
|
||||
statusMessage: "Forbidden",
|
||||
userMessage: `Your account has been disabled for violating our terms of service.`,
|
||||
type: "organization_account_disabled",
|
||||
code: "policy_violation",
|
||||
};
|
||||
case "ForbiddenError":
|
||||
return {
|
||||
statusCode: 403,
|
||||
statusMessage: "Forbidden",
|
||||
userMessage: `Request is not allowed. (${err.message})`,
|
||||
type: "proxy_forbidden",
|
||||
};
|
||||
case "QuotaExceededError":
|
||||
return {
|
||||
statusCode: 429,
|
||||
statusMessage: "Too Many Requests",
|
||||
userMessage: `You've exceeded your token quota for this model type.`,
|
||||
type: "proxy_quota_exceeded",
|
||||
info: (err as QuotaExceededError).quotaInfo,
|
||||
};
|
||||
case "Error":
|
||||
if ("code" in err) {
|
||||
switch (err.code) {
|
||||
case "ENOTFOUND":
|
||||
return {
|
||||
statusCode: 502,
|
||||
statusMessage: "Bad Gateway",
|
||||
userMessage: `Reverse proxy encountered a DNS error while trying to connect to the upstream service.`,
|
||||
type: "proxy_network_error",
|
||||
code: err.code,
|
||||
};
|
||||
case "ECONNREFUSED":
|
||||
return {
|
||||
statusCode: 502,
|
||||
statusMessage: "Bad Gateway",
|
||||
userMessage: `Reverse proxy couldn't connect to the upstream service.`,
|
||||
type: "proxy_network_error",
|
||||
code: err.code,
|
||||
};
|
||||
case "ECONNRESET":
|
||||
return {
|
||||
statusCode: 504,
|
||||
statusMessage: "Gateway Timeout",
|
||||
userMessage: `Reverse proxy timed out while waiting for the upstream service to respond.`,
|
||||
type: "proxy_network_error",
|
||||
code: err.code,
|
||||
};
|
||||
}
|
||||
}
|
||||
return defaultError;
|
||||
default:
|
||||
return defaultError;
|
||||
}
|
||||
}
|
||||
|
||||
export function getCompletionFromBody(req: Request, body: Record<string, any>) {
|
||||
const format = req.outboundApi;
|
||||
switch (format) {
|
||||
switch (req.inboundApi) {
|
||||
case "openai":
|
||||
case "mistral-ai":
|
||||
// Few possible values:
|
||||
// - choices[0].message.content
|
||||
// - choices[0].message with no content if model is invoking a tool
|
||||
return body.choices?.[0]?.message?.content || "";
|
||||
case "mistral-text":
|
||||
return body.outputs?.[0]?.text || "";
|
||||
fakeEvent = {
|
||||
id: "chatcmpl-" + req.id,
|
||||
object: "chat.completion.chunk",
|
||||
created: Date.now(),
|
||||
model: req.body?.model,
|
||||
choices: [
|
||||
{
|
||||
delta: { content: msgContent },
|
||||
index: 0,
|
||||
finish_reason: type,
|
||||
},
|
||||
],
|
||||
};
|
||||
break;
|
||||
case "openai-text":
|
||||
return body.choices[0].text;
|
||||
case "anthropic-chat":
|
||||
if (!body.content) {
|
||||
req.log.error(
|
||||
{ body: JSON.stringify(body) },
|
||||
"Received empty Anthropic chat completion"
|
||||
);
|
||||
return "";
|
||||
}
|
||||
return body.content
|
||||
.map(({ text, type }: { type: string; text: string }) =>
|
||||
type === "text" ? text : `[Unsupported content type: ${type}]`
|
||||
)
|
||||
.join("\n");
|
||||
case "anthropic-text":
|
||||
if (!body.completion) {
|
||||
req.log.error(
|
||||
{ body: JSON.stringify(body) },
|
||||
"Received empty Anthropic text completion"
|
||||
);
|
||||
return "";
|
||||
}
|
||||
return body.completion.trim();
|
||||
case "google-ai":
|
||||
if ("choices" in body) {
|
||||
return body.choices[0].message.content;
|
||||
}
|
||||
const text = body.candidates[0].content?.parts?.[0]?.text;
|
||||
if (!text) {
|
||||
req.log.warn(
|
||||
{ body: JSON.stringify(body) },
|
||||
"Received empty Google AI text completion"
|
||||
);
|
||||
return "";
|
||||
}
|
||||
return text;
|
||||
case "openai-image":
|
||||
return body.data?.map((item: any) => item.url).join("\n");
|
||||
fakeEvent = {
|
||||
id: "cmpl-" + req.id,
|
||||
object: "text_completion",
|
||||
created: Date.now(),
|
||||
choices: [
|
||||
{ text: msgContent, index: 0, logprobs: null, finish_reason: type },
|
||||
],
|
||||
model: req.body?.model,
|
||||
};
|
||||
break;
|
||||
case "anthropic":
|
||||
fakeEvent = {
|
||||
completion: msgContent,
|
||||
stop_reason: type,
|
||||
truncated: false, // I've never seen this be true
|
||||
stop: null,
|
||||
model: req.body?.model,
|
||||
log_id: "proxy-req-" + req.id,
|
||||
};
|
||||
break;
|
||||
case "google-palm":
|
||||
throw new Error("PaLM not supported as an inbound API format");
|
||||
default:
|
||||
assertNever(format);
|
||||
assertNever(req.inboundApi);
|
||||
}
|
||||
return `data: ${JSON.stringify(fakeEvent)}\n\n`;
|
||||
}
|
||||
|
||||
export function getModelFromBody(req: Request, resBody: Record<string, any>) {
|
||||
const format = req.outboundApi;
|
||||
switch (format) {
|
||||
export function getCompletionForService({
|
||||
service,
|
||||
body,
|
||||
req,
|
||||
}: {
|
||||
service: APIFormat;
|
||||
body: Record<string, any>;
|
||||
req?: Request;
|
||||
}): { completion: string; model: string } {
|
||||
switch (service) {
|
||||
case "openai":
|
||||
return { completion: body.choices[0].message.content, model: body.model };
|
||||
case "openai-text":
|
||||
return resBody.model;
|
||||
case "mistral-ai":
|
||||
case "mistral-text":
|
||||
case "openai-image":
|
||||
case "google-ai":
|
||||
// These formats don't have a model in the response body.
|
||||
return req.body.model;
|
||||
case "anthropic-chat":
|
||||
case "anthropic-text":
|
||||
// Anthropic confirms the model in the response, but AWS Claude doesn't.
|
||||
return resBody.model || req.body.model;
|
||||
return { completion: body.choices[0].text, model: body.model };
|
||||
case "anthropic":
|
||||
return { completion: body.completion.trim(), model: body.model };
|
||||
case "google-palm":
|
||||
return { completion: body.candidates[0].output, model: req?.body.model };
|
||||
default:
|
||||
assertNever(format);
|
||||
assertNever(service);
|
||||
}
|
||||
}
|
||||
|
||||
@@ -0,0 +1,49 @@
|
||||
import { AnthropicKey, Key } from "../../../shared/key-management";
|
||||
import { isCompletionRequest } from "../common";
|
||||
import { ProxyRequestMiddleware } from ".";
|
||||
|
||||
/**
|
||||
* 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 = (
|
||||
_proxyReq,
|
||||
req
|
||||
) => {
|
||||
if (!isCompletionRequest(req) || req.key?.service !== "anthropic") {
|
||||
return;
|
||||
}
|
||||
|
||||
assertAnthropicKey(req.key);
|
||||
|
||||
if (req.key.requiresPreamble) {
|
||||
let prompt = req.body.prompt;
|
||||
const preamble = prompt.startsWith("\n\nHuman:") ? "" : "\n\nHuman:";
|
||||
req.log.debug({ key: req.key.hash, preamble }, "Prompt requres preamble");
|
||||
prompt = preamble + prompt;
|
||||
|
||||
// Adds `Assistant:` to the end of the prompt if the turn closest to the
|
||||
// end is from the `Human:` persona.
|
||||
const humanIndex = prompt.lastIndexOf("\n\nHuman:");
|
||||
const assistantIndex = prompt.lastIndexOf("\n\nAssistant:");
|
||||
const shouldAddAssistant = humanIndex > assistantIndex;
|
||||
req.log.debug(
|
||||
{
|
||||
key: req.key.hash,
|
||||
shouldAdd: shouldAddAssistant,
|
||||
hIndex: humanIndex,
|
||||
aIndex: assistantIndex,
|
||||
},
|
||||
"Possibly adding Assistant: to prompt"
|
||||
);
|
||||
if (shouldAddAssistant) prompt += "\n\nAssistant:";
|
||||
req.body.prompt = prompt;
|
||||
}
|
||||
};
|
||||
|
||||
function assertAnthropicKey(key: Key): asserts key is AnthropicKey {
|
||||
if (key.service !== "anthropic") {
|
||||
throw new Error(`Expected an Anthropic key, got '${key.service}'`);
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,97 @@
|
||||
import { Key, OpenAIKey, keyPool } from "../../../shared/key-management";
|
||||
import { isCompletionRequest } from "../common";
|
||||
import { ProxyRequestMiddleware } from ".";
|
||||
import { assertNever } from "../../../shared/utils";
|
||||
|
||||
/** Add a key that can service this request to the request object. */
|
||||
export const addKey: ProxyRequestMiddleware = (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).
|
||||
// TODO: shouldn't even proxy /models to the upstream API, just fake it
|
||||
// using the models our key pool has available.
|
||||
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?"
|
||||
);
|
||||
req.log.error(
|
||||
{ in: req.inboundApi, out: req.outboundApi, path: req.path },
|
||||
err.message
|
||||
);
|
||||
throw err;
|
||||
}
|
||||
|
||||
if (!req.body?.model) {
|
||||
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 {
|
||||
switch (req.outboundApi) {
|
||||
// If we are translating between API formats we may need to select a model
|
||||
// for the user, because the provided model is for the inbound API.
|
||||
case "anthropic":
|
||||
assignedKey = keyPool.get("claude-v1");
|
||||
break;
|
||||
case "google-palm":
|
||||
assignedKey = keyPool.get("text-bison-001");
|
||||
delete req.body.stream;
|
||||
break;
|
||||
case "openai-text":
|
||||
assignedKey = keyPool.get("gpt-3.5-turbo-instruct");
|
||||
break;
|
||||
case "openai":
|
||||
throw new Error(
|
||||
"OpenAI Chat as an API translation target is not supported"
|
||||
);
|
||||
default:
|
||||
assertNever(req.outboundApi);
|
||||
}
|
||||
}
|
||||
|
||||
req.key = assignedKey;
|
||||
req.log.info(
|
||||
{
|
||||
key: assignedKey.hash,
|
||||
model: req.body?.model,
|
||||
fromApi: req.inboundApi,
|
||||
toApi: req.outboundApi,
|
||||
},
|
||||
"Assigned key to request"
|
||||
);
|
||||
|
||||
// TODO: KeyProvider should assemble all necessary headers
|
||||
switch (assignedKey.service) {
|
||||
case "anthropic":
|
||||
proxyReq.setHeader("X-API-Key", assignedKey.key);
|
||||
break;
|
||||
case "openai":
|
||||
case "openai-text":
|
||||
const key: OpenAIKey = assignedKey as OpenAIKey;
|
||||
if (key.organizationId) {
|
||||
proxyReq.setHeader("OpenAI-Organization", key.organizationId);
|
||||
}
|
||||
proxyReq.setHeader("Authorization", `Bearer ${assignedKey.key}`);
|
||||
break;
|
||||
case "google-palm":
|
||||
const originalPath = proxyReq.path;
|
||||
proxyReq.path = originalPath.replace(
|
||||
/(\?.*)?$/,
|
||||
`?key=${assignedKey.key}`
|
||||
);
|
||||
break;
|
||||
default:
|
||||
assertNever(assignedKey.service);
|
||||
}
|
||||
};
|
||||
@@ -0,0 +1,30 @@
|
||||
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,
|
||||
}
|
||||
);
|
||||
}
|
||||
};
|
||||
+10
-5
@@ -1,11 +1,12 @@
|
||||
import { RequestPreprocessor } from "../index";
|
||||
import { isCompletionRequest } from "../common";
|
||||
import { ProxyRequestMiddleware } from ".";
|
||||
|
||||
const DISALLOWED_ORIGIN_SUBSTRINGS = "janitorai.com,janitor.ai".split(",");
|
||||
|
||||
class ZoomerForbiddenError extends Error {
|
||||
class ForbiddenError extends Error {
|
||||
constructor(message: string) {
|
||||
super(message);
|
||||
this.name = "ZoomerForbiddenError";
|
||||
this.name = "ForbiddenError";
|
||||
}
|
||||
}
|
||||
|
||||
@@ -13,7 +14,11 @@ class ZoomerForbiddenError extends Error {
|
||||
* Blocks requests from Janitor AI users with a fake, scary error message so I
|
||||
* stop getting emails asking for tech support.
|
||||
*/
|
||||
export const blockZoomerOrigins: RequestPreprocessor = (req) => {
|
||||
export const blockZoomerOrigins: ProxyRequestMiddleware = (_proxyReq, req) => {
|
||||
if (!isCompletionRequest(req)) {
|
||||
return;
|
||||
}
|
||||
|
||||
const origin = req.headers.origin || req.headers.referer;
|
||||
if (origin && DISALLOWED_ORIGIN_SUBSTRINGS.some((s) => origin.includes(s))) {
|
||||
// Venus-derivatives send a test prompt to check if the proxy is working.
|
||||
@@ -22,7 +27,7 @@ export const blockZoomerOrigins: RequestPreprocessor = (req) => {
|
||||
return;
|
||||
}
|
||||
|
||||
throw new ZoomerForbiddenError(
|
||||
throw new ForbiddenError(
|
||||
`Your access was terminated due to violation of our policies, please check your email for more information. If you believe this is in error and would like to appeal, please contact us through our help center at help.openai.com.`
|
||||
);
|
||||
}
|
||||
@@ -0,0 +1,163 @@
|
||||
import { Request } from "express";
|
||||
import { z } from "zod";
|
||||
import { config } from "../../../config";
|
||||
import { OpenAIPromptMessage, countTokens } from "../../../shared/tokenization";
|
||||
import { RequestPreprocessor } from ".";
|
||||
import { assertNever } from "../../../shared/utils";
|
||||
|
||||
const CLAUDE_MAX_CONTEXT = config.maxContextTokensAnthropic;
|
||||
const OPENAI_MAX_CONTEXT = config.maxContextTokensOpenAI;
|
||||
const BISON_MAX_CONTEXT = 8100;
|
||||
|
||||
/**
|
||||
* Assigns `req.promptTokens` and `req.outputTokens` based on the request body
|
||||
* and outbound API format, which combined determine the size of the context.
|
||||
* If the context is too large, an error is thrown.
|
||||
* This preprocessor should run after any preprocessor that transforms the
|
||||
* request body.
|
||||
*/
|
||||
export const checkContextSize: RequestPreprocessor = async (req) => {
|
||||
const service = req.outboundApi;
|
||||
let result;
|
||||
|
||||
switch (service) {
|
||||
case "openai": {
|
||||
req.outputTokens = req.body.max_tokens;
|
||||
const prompt: OpenAIPromptMessage[] = req.body.messages;
|
||||
result = await countTokens({ req, prompt, service });
|
||||
break;
|
||||
}
|
||||
case "openai-text": {
|
||||
req.outputTokens = req.body.max_tokens;
|
||||
const prompt: string = req.body.prompt;
|
||||
result = await countTokens({ req, prompt, service });
|
||||
break;
|
||||
}
|
||||
case "anthropic": {
|
||||
req.outputTokens = req.body.max_tokens_to_sample;
|
||||
const prompt: string = req.body.prompt;
|
||||
result = await countTokens({ req, prompt, service });
|
||||
break;
|
||||
}
|
||||
case "google-palm": {
|
||||
req.outputTokens = req.body.maxOutputTokens;
|
||||
const prompt: string = req.body.prompt.text;
|
||||
result = await countTokens({ req, prompt, 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 };
|
||||
|
||||
maybeTranslateOpenAIModel(req);
|
||||
validateContextSize(req);
|
||||
};
|
||||
|
||||
function validateContextSize(req: Request) {
|
||||
assertRequestHasTokenCounts(req);
|
||||
const promptTokens = req.promptTokens;
|
||||
const outputTokens = req.outputTokens;
|
||||
const contextTokens = promptTokens + outputTokens;
|
||||
const model = req.body.model;
|
||||
|
||||
let proxyMax: number;
|
||||
switch (req.outboundApi) {
|
||||
case "openai":
|
||||
case "openai-text":
|
||||
proxyMax = OPENAI_MAX_CONTEXT;
|
||||
break;
|
||||
case "anthropic":
|
||||
proxyMax = CLAUDE_MAX_CONTEXT;
|
||||
break;
|
||||
case "google-palm":
|
||||
proxyMax = BISON_MAX_CONTEXT;
|
||||
break;
|
||||
default:
|
||||
assertNever(req.outboundApi);
|
||||
}
|
||||
proxyMax ||= Number.MAX_SAFE_INTEGER;
|
||||
|
||||
let modelMax = 0;
|
||||
if (model.match(/gpt-3.5-turbo-16k/)) {
|
||||
modelMax = 16384;
|
||||
} else if (model.match(/gpt-3.5-turbo/)) {
|
||||
modelMax = 4096;
|
||||
} else if (model.match(/gpt-4-32k/)) {
|
||||
modelMax = 32768;
|
||||
} else if (model.match(/gpt-4/)) {
|
||||
modelMax = 8192;
|
||||
} else if (model.match(/claude-(?:instant-)?v1(?:\.\d)?(?:-100k)/)) {
|
||||
modelMax = 100000;
|
||||
} else if (model.match(/claude-(?:instant-)?v1(?:\.\d)?$/)) {
|
||||
modelMax = 9000;
|
||||
} else if (model.match(/claude-2/)) {
|
||||
modelMax = 100000;
|
||||
} else if (model.match(/^text-bison-\d{3}$/)) {
|
||||
modelMax = BISON_MAX_CONTEXT;
|
||||
} 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;
|
||||
}
|
||||
|
||||
const finalMax = Math.min(proxyMax, modelMax);
|
||||
z.number()
|
||||
.int()
|
||||
.max(finalMax, {
|
||||
message: `Your request exceeds the context size limit for this model or proxy. (max: ${finalMax} tokens, requested: ${promptTokens} prompt + ${outputTokens} output = ${contextTokens} context tokens)`,
|
||||
})
|
||||
.parse(contextTokens);
|
||||
|
||||
req.log.debug(
|
||||
{ promptTokens, outputTokens, contextTokens, modelMax, proxyMax },
|
||||
"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;
|
||||
}
|
||||
|
||||
function assertRequestHasTokenCounts(
|
||||
req: Request
|
||||
): asserts req is Request & { promptTokens: number; outputTokens: number } {
|
||||
z.object({
|
||||
promptTokens: z.number().int().min(1),
|
||||
outputTokens: z.number().int().min(1),
|
||||
})
|
||||
.nonstrict()
|
||||
.parse({ promptTokens: req.promptTokens, outputTokens: req.outputTokens });
|
||||
}
|
||||
|
||||
/**
|
||||
* For OpenAI-to-Anthropic requests, users can't specify the model, so we need
|
||||
* to pick one based on the final context size. Ideally this would happen in
|
||||
* the `transformOutboundPayload` preprocessor, but we don't have the context
|
||||
* size at that point (and need a transformed body to calculate it).
|
||||
*/
|
||||
function maybeTranslateOpenAIModel(req: Request) {
|
||||
if (req.inboundApi !== "openai" || req.outboundApi !== "anthropic") {
|
||||
return;
|
||||
}
|
||||
|
||||
const bigModel = process.env.CLAUDE_BIG_MODEL || "claude-v1-100k";
|
||||
const contextSize = req.promptTokens! + req.outputTokens!;
|
||||
|
||||
if (contextSize > 8500) {
|
||||
req.log.debug(
|
||||
{ model: bigModel, contextSize },
|
||||
"Using Claude 100k model for OpenAI-to-Anthropic request"
|
||||
);
|
||||
req.body.model = bigModel;
|
||||
}
|
||||
// Small model is the default already set in `transformOutboundPayload`
|
||||
}
|
||||
@@ -0,0 +1,14 @@
|
||||
import { fixRequestBody } from "http-proxy-middleware";
|
||||
import type { ProxyRequestMiddleware } from ".";
|
||||
|
||||
/** Finalize the rewritten request body. Must be the last rewriter. */
|
||||
export const finalizeBody: ProxyRequestMiddleware = (proxyReq, req) => {
|
||||
if (["POST", "PUT", "PATCH"].includes(req.method ?? "") && req.body) {
|
||||
const updatedBody = JSON.stringify(req.body);
|
||||
proxyReq.setHeader("Content-Length", Buffer.byteLength(updatedBody));
|
||||
(req as any).rawBody = Buffer.from(updatedBody);
|
||||
|
||||
// body-parser and http-proxy-middleware don't play nice together
|
||||
fixRequestBody(proxyReq, req);
|
||||
}
|
||||
};
|
||||
@@ -1,38 +1,34 @@
|
||||
import type { Request } from "express";
|
||||
import type { ClientRequest } from "http";
|
||||
import type { ProxyReqCallback } from "http-proxy";
|
||||
|
||||
import { ProxyReqManager } from "./proxy-req-manager";
|
||||
export {
|
||||
createPreprocessorMiddleware,
|
||||
createEmbeddingsPreprocessorMiddleware,
|
||||
} from "./preprocessor-factory";
|
||||
// Express middleware (runs before http-proxy-middleware, can be async)
|
||||
export { applyQuotaLimits } from "./apply-quota-limits";
|
||||
export { createPreprocessorMiddleware } from "./preprocess";
|
||||
export { checkContextSize } from "./check-context-size";
|
||||
export { setApiFormat } from "./set-api-format";
|
||||
export { transformOutboundPayload } from "./transform-outbound-payload";
|
||||
|
||||
// Preprocessors (runs before request is queued, usually body transformation/validation)
|
||||
export { applyQuotaLimits } from "./preprocessors/apply-quota-limits";
|
||||
export { blockZoomerOrigins } from "./preprocessors/block-zoomer-origins";
|
||||
export { countPromptTokens } from "./preprocessors/count-prompt-tokens";
|
||||
export { languageFilter } from "./preprocessors/language-filter";
|
||||
export { setApiFormat } from "./preprocessors/set-api-format";
|
||||
export { transformOutboundPayload } from "./preprocessors/transform-outbound-payload";
|
||||
export { validateContextSize } from "./preprocessors/validate-context-size";
|
||||
export { validateModelFamily } from "./preprocessors/validate-model-family";
|
||||
export { validateVision } from "./preprocessors/validate-vision";
|
||||
|
||||
// Proxy request mutators (runs every time request is dequeued, before proxying, usually for auth/signing)
|
||||
export { addKey, addKeyForEmbeddingsRequest } from "./mutators/add-key";
|
||||
export { addAzureKey } from "./mutators/add-azure-key";
|
||||
export { finalizeBody } from "./mutators/finalize-body";
|
||||
export { finalizeSignedRequest } from "./mutators/finalize-signed-request";
|
||||
export { signAwsRequest } from "./mutators/sign-aws-request";
|
||||
export { signGcpRequest } from "./mutators/sign-vertex-ai-request";
|
||||
export { stripHeaders } from "./mutators/strip-headers";
|
||||
// HPM middleware (runs on onProxyReq, cannot be async)
|
||||
export { addKey } from "./add-key";
|
||||
export { addAnthropicPreamble } from "./add-anthropic-preamble";
|
||||
export { blockZoomerOrigins } from "./block-zoomer-origins";
|
||||
export { finalizeBody } from "./finalize-body";
|
||||
export { languageFilter } from "./language-filter";
|
||||
export { limitCompletions } from "./limit-completions";
|
||||
export { removeOriginHeaders } from "./remove-origin-headers";
|
||||
export { transformKoboldPayload } from "./transform-kobold-payload";
|
||||
|
||||
/**
|
||||
* Middleware that runs prior to the request being queued or handled by
|
||||
* http-proxy-middleware. You will not have access to the proxied
|
||||
* request/response objects since they have not yet been sent to the API.
|
||||
* Middleware that runs prior to the request being handled by http-proxy-
|
||||
* middleware.
|
||||
*
|
||||
* User will have been authenticated by the proxy's gatekeeper, but the request
|
||||
* won't have been assigned an upstream API key yet.
|
||||
* Async functions can be used here, but you will not have access to the proxied
|
||||
* request/response objects, nor the data set by ProxyRequestMiddleware
|
||||
* functions as they have not yet been run.
|
||||
*
|
||||
* User will have been authenticated by the time this middleware runs, but your
|
||||
* request won't have been assigned an API key yet.
|
||||
*
|
||||
* Note that these functions only run once ever per request, even if the request
|
||||
* is automatically retried by the request queue middleware.
|
||||
@@ -40,14 +36,14 @@ export { stripHeaders } from "./mutators/strip-headers";
|
||||
export type RequestPreprocessor = (req: Request) => void | Promise<void>;
|
||||
|
||||
/**
|
||||
* Middleware that runs immediately before the request is proxied to the
|
||||
* upstream API, after dequeueing the request from the request queue.
|
||||
* Middleware that runs immediately before the request is sent to the API in
|
||||
* response to http-proxy-middleware's `proxyReq` event.
|
||||
*
|
||||
* Because these middleware may be run multiple times per request if a retryable
|
||||
* error occurs and the request put back in the queue, they must be idempotent.
|
||||
* A change manager is provided to allow the middleware to make changes to the
|
||||
* request which can be automatically reverted.
|
||||
* Async functions cannot be used here as HPM's event emitter is not async and
|
||||
* will not wait for the promise to resolve before sending the request.
|
||||
*
|
||||
* Note that these functions may be run multiple times per request if the
|
||||
* first attempt is rate limited and the request is automatically retried by the
|
||||
* request queue middleware.
|
||||
*/
|
||||
export type ProxyReqMutator = (
|
||||
changeManager: ProxyReqManager
|
||||
) => void | Promise<void>;
|
||||
export type ProxyRequestMiddleware = ProxyReqCallback<ClientRequest, Request>;
|
||||
|
||||
@@ -0,0 +1,56 @@
|
||||
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);
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,16 @@
|
||||
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 ${originalN} to 1`);
|
||||
}
|
||||
}
|
||||
};
|
||||
@@ -1,84 +0,0 @@
|
||||
import {
|
||||
APIFormat,
|
||||
AzureOpenAIKey,
|
||||
keyPool,
|
||||
} from "../../../../shared/key-management";
|
||||
import { ProxyReqMutator } from "../index";
|
||||
|
||||
export const addAzureKey: ProxyReqMutator = async (manager) => {
|
||||
const req = manager.request;
|
||||
const validAPIs: APIFormat[] = ["openai", "openai-image"];
|
||||
const apisValid = [req.outboundApi, req.inboundApi].every((api) =>
|
||||
validAPIs.includes(api)
|
||||
);
|
||||
const serviceValid = req.service === "azure";
|
||||
|
||||
if (!apisValid || !serviceValid) {
|
||||
throw new Error("addAzureKey called on invalid request");
|
||||
}
|
||||
|
||||
if (!req.body?.model) {
|
||||
throw new Error("You must specify a model with your request.");
|
||||
}
|
||||
|
||||
const model = req.body.model.startsWith("azure-")
|
||||
? req.body.model
|
||||
: `azure-${req.body.model}`;
|
||||
// TODO: untracked mutation to body, I think this should just be a
|
||||
// RequestPreprocessor because we don't need to do it every dequeue.
|
||||
req.body.model = model;
|
||||
|
||||
const key = keyPool.get(model, "azure");
|
||||
manager.setKey(key);
|
||||
|
||||
// Handles the sole Azure API deviation from the OpenAI spec (that I know of)
|
||||
// TODO: this should also probably be a RequestPreprocessor
|
||||
const notNullOrUndefined = (x: any) => x !== null && x !== undefined;
|
||||
if ([req.body.logprobs, req.body.top_logprobs].some(notNullOrUndefined)) {
|
||||
// OpenAI wants logprobs: true/false and top_logprobs: number
|
||||
// Azure seems to just want to combine them into logprobs: number
|
||||
// if (typeof req.body.logprobs === "boolean") {
|
||||
// req.body.logprobs = req.body.top_logprobs || undefined;
|
||||
// delete req.body.top_logprobs
|
||||
// }
|
||||
|
||||
// Temporarily just disabling logprobs for Azure because their model support
|
||||
// is random: `This model does not support the 'logprobs' parameter.`
|
||||
delete req.body.logprobs;
|
||||
delete req.body.top_logprobs;
|
||||
}
|
||||
|
||||
req.log.info(
|
||||
{ key: key.hash, model },
|
||||
"Assigned Azure OpenAI key to request"
|
||||
);
|
||||
|
||||
const cred = req.key as AzureOpenAIKey;
|
||||
const { resourceName, deploymentId, apiKey } = getCredentialsFromKey(cred);
|
||||
|
||||
const operation =
|
||||
req.outboundApi === "openai" ? "/chat/completions" : "/images/generations";
|
||||
const apiVersion =
|
||||
req.outboundApi === "openai" ? "2023-09-01-preview" : "2024-02-15-preview";
|
||||
|
||||
manager.setSignedRequest({
|
||||
method: "POST",
|
||||
protocol: "https:",
|
||||
hostname: `${resourceName}.openai.azure.com`,
|
||||
path: `/openai/deployments/${deploymentId}${operation}?api-version=${apiVersion}`,
|
||||
headers: {
|
||||
["host"]: `${resourceName}.openai.azure.com`,
|
||||
["content-type"]: "application/json",
|
||||
["api-key"]: apiKey,
|
||||
},
|
||||
body: JSON.stringify(req.body),
|
||||
});
|
||||
};
|
||||
|
||||
function getCredentialsFromKey(key: AzureOpenAIKey) {
|
||||
const [resourceName, deploymentId, apiKey] = key.key.split(":");
|
||||
if (!resourceName || !deploymentId || !apiKey) {
|
||||
throw new Error("Assigned Azure OpenAI key is not in the correct format.");
|
||||
}
|
||||
return { resourceName, deploymentId, apiKey };
|
||||
}
|
||||
@@ -1,44 +0,0 @@
|
||||
import { keyPool } from "../../../../shared/key-management";
|
||||
import { ProxyReqMutator } from "../index";
|
||||
|
||||
export const addGoogleAIKey: ProxyReqMutator = (manager) => {
|
||||
const req = manager.request;
|
||||
const inboundValid =
|
||||
req.inboundApi === "openai" || req.inboundApi === "google-ai";
|
||||
const outboundValid = req.outboundApi === "google-ai";
|
||||
|
||||
const serviceValid = req.service === "google-ai";
|
||||
if (!inboundValid || !outboundValid || !serviceValid) {
|
||||
throw new Error("addGoogleAIKey called on invalid request");
|
||||
}
|
||||
|
||||
const model = req.body.model;
|
||||
const key = keyPool.get(model, "google-ai");
|
||||
manager.setKey(key);
|
||||
|
||||
req.log.info(
|
||||
{ key: key.hash, model, stream: req.isStreaming },
|
||||
"Assigned Google AI API key to request"
|
||||
);
|
||||
|
||||
// https://generativelanguage.googleapis.com/v1beta/models/$MODEL_ID:generateContent?key=$API_KEY
|
||||
// https://generativelanguage.googleapis.com/v1beta/models/$MODEL_ID:streamGenerateContent?key=${API_KEY}
|
||||
const payload = { ...req.body, stream: undefined, model: undefined };
|
||||
|
||||
// TODO: this isn't actually signed, so the manager api is a little unclear
|
||||
// with the ProxyReqManager refactor, it's probably no longer necesasry to
|
||||
// do this because we can modify the path using Manager.setPath.
|
||||
manager.setSignedRequest({
|
||||
method: "POST",
|
||||
protocol: "https:",
|
||||
hostname: "generativelanguage.googleapis.com",
|
||||
path: `/v1beta/models/${model}:${
|
||||
req.isStreaming ? "streamGenerateContent?alt=sse&" : "generateContent?"
|
||||
}key=${key.key}`,
|
||||
headers: {
|
||||
["host"]: `generativelanguage.googleapis.com`,
|
||||
["content-type"]: "application/json",
|
||||
},
|
||||
body: JSON.stringify(payload),
|
||||
});
|
||||
};
|
||||
@@ -1,130 +0,0 @@
|
||||
import { AnthropicChatMessage } from "../../../../shared/api-schemas";
|
||||
import { containsImageContent } from "../../../../shared/api-schemas/anthropic";
|
||||
import { Key, OpenAIKey, keyPool } from "../../../../shared/key-management";
|
||||
import { isEmbeddingsRequest } from "../../common";
|
||||
import { assertNever } from "../../../../shared/utils";
|
||||
import { ProxyReqMutator } from "../index";
|
||||
|
||||
export const addKey: ProxyReqMutator = (manager) => {
|
||||
const req = manager.request;
|
||||
|
||||
let assignedKey: Key;
|
||||
const { service, inboundApi, outboundApi, body } = req;
|
||||
|
||||
if (!inboundApi || !outboundApi) {
|
||||
const err = new Error(
|
||||
"Request API format missing. Did you forget to add the request preprocessor to your router?"
|
||||
);
|
||||
req.log.error({ inboundApi, outboundApi, path: req.path }, err.message);
|
||||
throw err;
|
||||
}
|
||||
|
||||
if (!body?.model) {
|
||||
throw new Error("You must specify a model with your request.");
|
||||
}
|
||||
|
||||
let needsMultimodal = false;
|
||||
if (outboundApi === "anthropic-chat") {
|
||||
needsMultimodal = containsImageContent(
|
||||
body.messages as AnthropicChatMessage[]
|
||||
);
|
||||
}
|
||||
|
||||
if (inboundApi === outboundApi) {
|
||||
assignedKey = keyPool.get(body.model, service, needsMultimodal);
|
||||
} else {
|
||||
switch (outboundApi) {
|
||||
// If we are translating between API formats we may need to select a model
|
||||
// for the user, because the provided model is for the inbound API.
|
||||
// TODO: This whole else condition is probably no longer needed since API
|
||||
// translation now reassigns the model earlier in the request pipeline.
|
||||
case "anthropic-text":
|
||||
case "anthropic-chat":
|
||||
case "mistral-ai":
|
||||
case "mistral-text":
|
||||
case "google-ai":
|
||||
assignedKey = keyPool.get(body.model, service);
|
||||
break;
|
||||
case "openai-text":
|
||||
assignedKey = keyPool.get("gpt-3.5-turbo-instruct", service);
|
||||
break;
|
||||
case "openai-image":
|
||||
assignedKey = keyPool.get("dall-e-3", service);
|
||||
break;
|
||||
case "openai":
|
||||
throw new Error(
|
||||
`Outbound API ${outboundApi} is not supported for ${inboundApi}`
|
||||
);
|
||||
default:
|
||||
assertNever(outboundApi);
|
||||
}
|
||||
}
|
||||
|
||||
manager.setKey(assignedKey);
|
||||
req.log.info(
|
||||
{ key: assignedKey.hash, model: body.model, inboundApi, outboundApi },
|
||||
"Assigned key to request"
|
||||
);
|
||||
|
||||
// TODO: KeyProvider should assemble all necessary headers
|
||||
switch (assignedKey.service) {
|
||||
case "anthropic":
|
||||
manager.setHeader("X-API-Key", assignedKey.key);
|
||||
if (!manager.request.headers["anthropic-version"]) {
|
||||
manager.setHeader("anthropic-version", "2023-06-01");
|
||||
}
|
||||
break;
|
||||
case "openai":
|
||||
const key: OpenAIKey = assignedKey as OpenAIKey;
|
||||
if (key.organizationId && !key.key.includes("svcacct")) {
|
||||
manager.setHeader("OpenAI-Organization", key.organizationId);
|
||||
}
|
||||
manager.setHeader("Authorization", `Bearer ${assignedKey.key}`);
|
||||
break;
|
||||
case "mistral-ai":
|
||||
manager.setHeader("Authorization", `Bearer ${assignedKey.key}`);
|
||||
break;
|
||||
case "azure":
|
||||
const azureKey = assignedKey.key;
|
||||
manager.setHeader("api-key", azureKey);
|
||||
break;
|
||||
case "aws":
|
||||
case "gcp":
|
||||
case "google-ai":
|
||||
throw new Error("add-key should not be used for this service.");
|
||||
default:
|
||||
assertNever(assignedKey.service);
|
||||
}
|
||||
};
|
||||
|
||||
/**
|
||||
* Special case for embeddings requests which don't go through the normal
|
||||
* request pipeline.
|
||||
*/
|
||||
export const addKeyForEmbeddingsRequest: ProxyReqMutator = (manager) => {
|
||||
const req = manager.request;
|
||||
if (!isEmbeddingsRequest(req)) {
|
||||
throw new Error(
|
||||
"addKeyForEmbeddingsRequest called on non-embeddings request"
|
||||
);
|
||||
}
|
||||
|
||||
if (req.inboundApi !== "openai") {
|
||||
throw new Error("Embeddings requests must be from OpenAI");
|
||||
}
|
||||
|
||||
manager.setBody({ input: req.body.input, model: "text-embedding-ada-002" });
|
||||
|
||||
const key = keyPool.get("text-embedding-ada-002", "openai") as OpenAIKey;
|
||||
|
||||
manager.setKey(key);
|
||||
req.log.info(
|
||||
{ key: key.hash, toApi: req.outboundApi },
|
||||
"Assigned Turbo key to embeddings request"
|
||||
);
|
||||
|
||||
manager.setHeader("Authorization", `Bearer ${key.key}`);
|
||||
if (key.organizationId) {
|
||||
manager.setHeader("OpenAI-Organization", key.organizationId);
|
||||
}
|
||||
};
|
||||
@@ -1,22 +0,0 @@
|
||||
import type { ProxyReqMutator } from "../index";
|
||||
|
||||
/** Finalize the rewritten request body. Must be the last mutator. */
|
||||
export const finalizeBody: ProxyReqMutator = (manager) => {
|
||||
const req = manager.request;
|
||||
|
||||
if (["POST", "PUT", "PATCH"].includes(req.method ?? "") && req.body) {
|
||||
// For image generation requests, remove stream flag.
|
||||
if (req.outboundApi === "openai-image") {
|
||||
delete req.body.stream;
|
||||
}
|
||||
// For anthropic text to chat requests, remove undefined prompt.
|
||||
if (req.outboundApi === "anthropic-chat") {
|
||||
delete req.body.prompt;
|
||||
}
|
||||
|
||||
const serialized =
|
||||
typeof req.body === "string" ? req.body : JSON.stringify(req.body);
|
||||
manager.setHeader("Content-Length", String(Buffer.byteLength(serialized)));
|
||||
manager.setBody(serialized);
|
||||
}
|
||||
};
|
||||
@@ -1,32 +0,0 @@
|
||||
import { ProxyReqMutator } from "../index";
|
||||
|
||||
/**
|
||||
* For AWS/GCP/Azure/Google requests, the body is signed earlier in the request
|
||||
* pipeline, before the proxy middleware. This function just assigns the path
|
||||
* and headers to the proxy request.
|
||||
*/
|
||||
export const finalizeSignedRequest: ProxyReqMutator = (manager) => {
|
||||
const req = manager.request;
|
||||
if (!req.signedRequest) {
|
||||
throw new Error("Expected req.signedRequest to be set");
|
||||
}
|
||||
|
||||
// The path depends on the selected model and the assigned key's region.
|
||||
manager.setPath(req.signedRequest.path);
|
||||
|
||||
// Amazon doesn't want extra headers, so we need to remove all of them and
|
||||
// reassign only the ones specified in the signed request.
|
||||
const headers = req.signedRequest.headers;
|
||||
Object.keys(headers).forEach((key) => {
|
||||
manager.removeHeader(key);
|
||||
});
|
||||
Object.entries(req.signedRequest.headers).forEach(([key, value]) => {
|
||||
manager.setHeader(key, value);
|
||||
});
|
||||
const serialized =
|
||||
typeof req.signedRequest.body === "string"
|
||||
? req.signedRequest.body
|
||||
: JSON.stringify(req.signedRequest.body);
|
||||
manager.setHeader("Content-Length", String(Buffer.byteLength(serialized)));
|
||||
manager.setBody(serialized);
|
||||
};
|
||||
@@ -1,148 +0,0 @@
|
||||
import express, { Request } from "express";
|
||||
import { Sha256 } from "@aws-crypto/sha256-js";
|
||||
import { SignatureV4 } from "@smithy/signature-v4";
|
||||
import { HttpRequest } from "@smithy/protocol-http";
|
||||
import {
|
||||
AnthropicV1TextSchema,
|
||||
AnthropicV1MessagesSchema,
|
||||
} from "../../../../shared/api-schemas";
|
||||
import { AwsBedrockKey, keyPool } from "../../../../shared/key-management";
|
||||
import {
|
||||
AWSMistralV1ChatCompletionsSchema,
|
||||
AWSMistralV1TextCompletionsSchema,
|
||||
} from "../../../../shared/api-schemas/mistral-ai";
|
||||
import { ProxyReqMutator } from "../index";
|
||||
|
||||
const AMZ_HOST =
|
||||
process.env.AMZ_HOST || "bedrock-runtime.%REGION%.amazonaws.com";
|
||||
|
||||
/**
|
||||
* Signs an outgoing AWS request with the appropriate headers modifies the
|
||||
* request object in place to fix the path.
|
||||
* This happens AFTER request transformation.
|
||||
*/
|
||||
export const signAwsRequest: ProxyReqMutator = async (manager) => {
|
||||
const req = manager.request;
|
||||
const { model, stream } = req.body;
|
||||
const key = keyPool.get(model, "aws") as AwsBedrockKey;
|
||||
manager.setKey(key);
|
||||
|
||||
const credential = getCredentialParts(req);
|
||||
const host = AMZ_HOST.replace("%REGION%", credential.region);
|
||||
|
||||
// AWS only uses 2023-06-01 and does not actually check this header, but we
|
||||
// set it so that the stream adapter always selects the correct transformer.
|
||||
manager.setHeader("anthropic-version", "2023-06-01");
|
||||
|
||||
// If our key has an inference profile compatible with the requested model,
|
||||
// we want to use the inference profile instead of the model ID when calling
|
||||
// InvokeModel as that will give us higher rate limits.
|
||||
const profile =
|
||||
key.inferenceProfileIds.find((p) => p.includes(model)) || model;
|
||||
|
||||
// Uses the AWS SDK to sign a request, then modifies our HPM proxy request
|
||||
// with the headers generated by the SDK.
|
||||
const newRequest = new HttpRequest({
|
||||
method: "POST",
|
||||
protocol: "https:",
|
||||
hostname: host,
|
||||
path: `/model/${profile}/invoke${stream ? "-with-response-stream" : ""}`,
|
||||
headers: {
|
||||
["Host"]: host,
|
||||
["content-type"]: "application/json",
|
||||
},
|
||||
body: JSON.stringify(getStrictlyValidatedBodyForAws(req)),
|
||||
});
|
||||
|
||||
if (stream) {
|
||||
newRequest.headers["x-amzn-bedrock-accept"] = "application/json";
|
||||
} else {
|
||||
newRequest.headers["accept"] = "*/*";
|
||||
}
|
||||
|
||||
const { body, inboundApi, outboundApi } = req;
|
||||
req.log.info(
|
||||
{ key: key.hash, model: body.model, profile, inboundApi, outboundApi },
|
||||
"Assigned AWS credentials to request"
|
||||
);
|
||||
|
||||
manager.setSignedRequest(await sign(newRequest, getCredentialParts(req)));
|
||||
};
|
||||
|
||||
type Credential = {
|
||||
accessKeyId: string;
|
||||
secretAccessKey: string;
|
||||
region: string;
|
||||
};
|
||||
|
||||
function getCredentialParts(req: express.Request): Credential {
|
||||
const [accessKeyId, secretAccessKey, region] = req.key!.key.split(":");
|
||||
|
||||
if (!accessKeyId || !secretAccessKey || !region) {
|
||||
req.log.error(
|
||||
{ key: req.key!.hash },
|
||||
"AWS_CREDENTIALS isn't correctly formatted; refer to the docs"
|
||||
);
|
||||
throw new Error("The key assigned to this request is invalid.");
|
||||
}
|
||||
|
||||
return { accessKeyId, secretAccessKey, region };
|
||||
}
|
||||
|
||||
async function sign(request: HttpRequest, credential: Credential) {
|
||||
const { accessKeyId, secretAccessKey, region } = credential;
|
||||
|
||||
const signer = new SignatureV4({
|
||||
sha256: Sha256,
|
||||
credentials: { accessKeyId, secretAccessKey },
|
||||
region,
|
||||
service: "bedrock",
|
||||
});
|
||||
|
||||
return signer.sign(request);
|
||||
}
|
||||
|
||||
function getStrictlyValidatedBodyForAws(req: Readonly<Request>): unknown {
|
||||
// AWS uses vendor API formats but imposes additional (more strict) validation
|
||||
// rules, namely that extraneous parameters are not allowed. We will validate
|
||||
// using the vendor's zod schema but apply `.strip` to ensure that any
|
||||
// extraneous parameters are removed.
|
||||
let strippedParams: Record<string, unknown> = {};
|
||||
switch (req.outboundApi) {
|
||||
case "anthropic-text":
|
||||
strippedParams = AnthropicV1TextSchema.pick({
|
||||
prompt: true,
|
||||
max_tokens_to_sample: true,
|
||||
stop_sequences: true,
|
||||
temperature: true,
|
||||
top_k: true,
|
||||
top_p: true,
|
||||
})
|
||||
.strip()
|
||||
.parse(req.body);
|
||||
break;
|
||||
case "anthropic-chat":
|
||||
strippedParams = AnthropicV1MessagesSchema.pick({
|
||||
messages: true,
|
||||
system: true,
|
||||
max_tokens: true,
|
||||
stop_sequences: true,
|
||||
temperature: true,
|
||||
top_k: true,
|
||||
top_p: true,
|
||||
})
|
||||
.strip()
|
||||
.parse(req.body);
|
||||
strippedParams.anthropic_version = "bedrock-2023-05-31";
|
||||
break;
|
||||
case "mistral-ai":
|
||||
strippedParams = AWSMistralV1ChatCompletionsSchema.parse(req.body);
|
||||
break;
|
||||
case "mistral-text":
|
||||
strippedParams = AWSMistralV1TextCompletionsSchema.parse(req.body);
|
||||
break;
|
||||
default:
|
||||
throw new Error("Unexpected outbound API for AWS.");
|
||||
}
|
||||
return strippedParams;
|
||||
}
|
||||
@@ -1,75 +0,0 @@
|
||||
import { AnthropicV1MessagesSchema } from "../../../../shared/api-schemas";
|
||||
import { GcpKey, keyPool } from "../../../../shared/key-management";
|
||||
import { ProxyReqMutator } from "../index";
|
||||
import {
|
||||
getCredentialsFromGcpKey,
|
||||
refreshGcpAccessToken,
|
||||
} from "../../../../shared/key-management/gcp/oauth";
|
||||
|
||||
const GCP_HOST = process.env.GCP_HOST || "%REGION%-aiplatform.googleapis.com";
|
||||
|
||||
export const signGcpRequest: ProxyReqMutator = async (manager) => {
|
||||
const req = manager.request;
|
||||
const serviceValid = req.service === "gcp";
|
||||
if (!serviceValid) {
|
||||
throw new Error("addVertexAIKey called on invalid request");
|
||||
}
|
||||
|
||||
if (!req.body?.model) {
|
||||
throw new Error("You must specify a model with your request.");
|
||||
}
|
||||
|
||||
const { model } = req.body;
|
||||
const key: GcpKey = keyPool.get(model, "gcp") as GcpKey;
|
||||
|
||||
if (!key.accessToken || Date.now() > key.accessTokenExpiresAt) {
|
||||
const [token, durationSec] = await refreshGcpAccessToken(key);
|
||||
keyPool.update(key, {
|
||||
accessToken: token,
|
||||
accessTokenExpiresAt: Date.now() + durationSec * 1000 * 0.95,
|
||||
} as GcpKey);
|
||||
// nb: key received by `get` is a clone and will not have the new access
|
||||
// token we just set, so it must be manually updated.
|
||||
key.accessToken = token;
|
||||
}
|
||||
|
||||
manager.setKey(key);
|
||||
req.log.info({ key: key.hash, model }, "Assigned GCP key to request");
|
||||
|
||||
// TODO: This should happen in transform-outbound-payload.ts
|
||||
// TODO: Support tools
|
||||
let strippedParams: Record<string, unknown>;
|
||||
strippedParams = AnthropicV1MessagesSchema.pick({
|
||||
messages: true,
|
||||
system: true,
|
||||
max_tokens: true,
|
||||
stop_sequences: true,
|
||||
temperature: true,
|
||||
top_k: true,
|
||||
top_p: true,
|
||||
stream: true,
|
||||
})
|
||||
.strip()
|
||||
.parse(req.body);
|
||||
strippedParams.anthropic_version = "vertex-2023-10-16";
|
||||
|
||||
const credential = await getCredentialsFromGcpKey(key);
|
||||
|
||||
const host = GCP_HOST.replace("%REGION%", credential.region);
|
||||
// GCP doesn't use the anthropic-version header, but we set it to ensure the
|
||||
// stream adapter selects the correct transformer.
|
||||
manager.setHeader("anthropic-version", "2023-06-01");
|
||||
|
||||
manager.setSignedRequest({
|
||||
method: "POST",
|
||||
protocol: "https:",
|
||||
hostname: host,
|
||||
path: `/v1/projects/${credential.projectId}/locations/${credential.region}/publishers/anthropic/models/${model}:streamRawPredict`,
|
||||
headers: {
|
||||
["host"]: host,
|
||||
["content-type"]: "application/json",
|
||||
["authorization"]: `Bearer ${key.accessToken}`,
|
||||
},
|
||||
body: JSON.stringify(strippedParams),
|
||||
});
|
||||
};
|
||||
@@ -1,33 +0,0 @@
|
||||
import { ProxyReqMutator } from "../index";
|
||||
|
||||
/**
|
||||
* Removes origin and referer headers before sending the request to the API for
|
||||
* privacy reasons.
|
||||
*/
|
||||
export const stripHeaders: ProxyReqMutator = (manager) => {
|
||||
manager.removeHeader("origin");
|
||||
manager.removeHeader("referer");
|
||||
|
||||
// Some APIs refuse requests coming from browsers to discourage embedding
|
||||
// API keys in client-side code, so we must remove all CORS/fetch headers.
|
||||
Object.keys(manager.request.headers).forEach((key) => {
|
||||
if (key.startsWith("sec-")) {
|
||||
manager.removeHeader(key);
|
||||
}
|
||||
});
|
||||
|
||||
manager.removeHeader("tailscale-user-login");
|
||||
manager.removeHeader("tailscale-user-name");
|
||||
manager.removeHeader("tailscale-headers-info");
|
||||
manager.removeHeader("tailscale-user-profile-pic");
|
||||
manager.removeHeader("cf-connecting-ip");
|
||||
manager.removeHeader("cf-ray");
|
||||
manager.removeHeader("cf-visitor");
|
||||
manager.removeHeader("cf-warp-tag-id");
|
||||
manager.removeHeader("forwarded");
|
||||
manager.removeHeader("true-client-ip");
|
||||
manager.removeHeader("x-forwarded-for");
|
||||
manager.removeHeader("x-forwarded-host");
|
||||
manager.removeHeader("x-forwarded-proto");
|
||||
manager.removeHeader("x-real-ip");
|
||||
};
|
||||
@@ -0,0 +1,36 @@
|
||||
import { RequestHandler } from "express";
|
||||
import { handleInternalError } from "../common";
|
||||
import {
|
||||
RequestPreprocessor,
|
||||
checkContextSize,
|
||||
setApiFormat,
|
||||
transformOutboundPayload,
|
||||
} from ".";
|
||||
|
||||
/**
|
||||
* Returns a middleware function that processes the request body into the given
|
||||
* API format, and then sequentially runs the given additional preprocessors.
|
||||
*/
|
||||
export const createPreprocessorMiddleware = (
|
||||
apiFormat: Parameters<typeof setApiFormat>[0],
|
||||
additionalPreprocessors?: RequestPreprocessor[]
|
||||
): RequestHandler => {
|
||||
const preprocessors: RequestPreprocessor[] = [
|
||||
setApiFormat(apiFormat),
|
||||
...(additionalPreprocessors ?? []),
|
||||
transformOutboundPayload,
|
||||
checkContextSize,
|
||||
];
|
||||
|
||||
return async function executePreprocessors(req, res, next) {
|
||||
try {
|
||||
for (const preprocessor of preprocessors) {
|
||||
await preprocessor(req);
|
||||
}
|
||||
next();
|
||||
} catch (error) {
|
||||
req.log.error(error, "Error while executing request preprocessor");
|
||||
handleInternalError(error as Error, req, res);
|
||||
}
|
||||
};
|
||||
};
|
||||
@@ -1,176 +0,0 @@
|
||||
import { RequestHandler } from "express";
|
||||
import { ZodIssue } from "zod";
|
||||
import { initializeSseStream } from "../../../shared/streaming";
|
||||
import { classifyErrorAndSend } from "../common";
|
||||
import {
|
||||
RequestPreprocessor,
|
||||
blockZoomerOrigins,
|
||||
countPromptTokens,
|
||||
languageFilter,
|
||||
setApiFormat,
|
||||
transformOutboundPayload,
|
||||
validateContextSize,
|
||||
validateModelFamily,
|
||||
validateVision,
|
||||
applyQuotaLimits,
|
||||
} from ".";
|
||||
|
||||
type RequestPreprocessorOptions = {
|
||||
/**
|
||||
* Functions to run before the request body is transformed between API
|
||||
* formats. Use this to change the behavior of the transformation, such as for
|
||||
* endpoints which can accept multiple API formats.
|
||||
*/
|
||||
beforeTransform?: RequestPreprocessor[];
|
||||
/**
|
||||
* Functions to run after the request body is transformed and token counts are
|
||||
* assigned. Use this to perform validation or other actions that depend on
|
||||
* the request body being in the final API format.
|
||||
*/
|
||||
afterTransform?: RequestPreprocessor[];
|
||||
};
|
||||
|
||||
/**
|
||||
* Returns a middleware function that processes the request body into the given
|
||||
* API format, and then sequentially runs the given additional preprocessors.
|
||||
* These should be used for validation and transformations that only need to
|
||||
* happen once per request.
|
||||
*
|
||||
* These run first in the request lifecycle, a single time per request before it
|
||||
* is added to the request queue. They aren't run again if the request is
|
||||
* re-attempted after a rate limit.
|
||||
*
|
||||
* To run functions against requests every time they are re-attempted, write a
|
||||
* ProxyReqMutator and pass it to createQueuedProxyMiddleware instead.
|
||||
*/
|
||||
export const createPreprocessorMiddleware = (
|
||||
apiFormat: Parameters<typeof setApiFormat>[0],
|
||||
{ beforeTransform, afterTransform }: RequestPreprocessorOptions = {}
|
||||
): RequestHandler => {
|
||||
const preprocessors: RequestPreprocessor[] = [
|
||||
setApiFormat(apiFormat),
|
||||
blockZoomerOrigins,
|
||||
...(beforeTransform ?? []),
|
||||
transformOutboundPayload,
|
||||
countPromptTokens,
|
||||
languageFilter,
|
||||
...(afterTransform ?? []),
|
||||
validateContextSize,
|
||||
validateVision,
|
||||
validateModelFamily,
|
||||
applyQuotaLimits,
|
||||
];
|
||||
return async (...args) => executePreprocessors(preprocessors, args);
|
||||
};
|
||||
|
||||
/**
|
||||
* Returns a middleware function that specifically prepares requests for
|
||||
* OpenAI's embeddings API. Tokens are not counted because embeddings requests
|
||||
* are basically free.
|
||||
*/
|
||||
export const createEmbeddingsPreprocessorMiddleware = (): RequestHandler => {
|
||||
const preprocessors: RequestPreprocessor[] = [
|
||||
setApiFormat({ inApi: "openai", outApi: "openai", service: "openai" }),
|
||||
(req) => void (req.promptTokens = req.outputTokens = 0),
|
||||
];
|
||||
return async (...args) => executePreprocessors(preprocessors, args);
|
||||
};
|
||||
|
||||
async function executePreprocessors(
|
||||
preprocessors: RequestPreprocessor[],
|
||||
[req, res, next]: Parameters<RequestHandler>
|
||||
) {
|
||||
handleTestMessage(req, res, next);
|
||||
if (res.headersSent) return;
|
||||
|
||||
try {
|
||||
for (const preprocessor of preprocessors) {
|
||||
await preprocessor(req);
|
||||
}
|
||||
next();
|
||||
} catch (error) {
|
||||
if (error.constructor.name === "ZodError") {
|
||||
const issues = error?.issues
|
||||
?.map((issue: ZodIssue) => `${issue.path.join(".")}: ${issue.message}`)
|
||||
.join("; ");
|
||||
req.log.warn({ issues }, "Prompt failed preprocessor validation.");
|
||||
} 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.
|
||||
const { stream } = req.body;
|
||||
const isStreaming = stream === "true" || stream === true;
|
||||
if (isStreaming && !res.headersSent) {
|
||||
initializeSseStream(res);
|
||||
}
|
||||
classifyErrorAndSend(error as Error, req, res);
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Bypasses the API call and returns a test message response if the request body
|
||||
* is a known test message from SillyTavern. Otherwise these messages just waste
|
||||
* API request quota and confuse users when the proxy is busy, because ST always
|
||||
* makes them with `stream: false` (which is not allowed when the proxy is busy)
|
||||
*/
|
||||
const handleTestMessage: RequestHandler = (req, res) => {
|
||||
const { method, body } = req;
|
||||
if (method !== "POST") {
|
||||
return;
|
||||
}
|
||||
|
||||
if (isTestMessage(body)) {
|
||||
req.log.info({ body }, "Received test message. Skipping API call.");
|
||||
res.json({
|
||||
id: "test-message",
|
||||
object: "chat.completion",
|
||||
created: Date.now(),
|
||||
model: body.model,
|
||||
// openai chat
|
||||
choices: [
|
||||
{
|
||||
message: { role: "assistant", content: "Hello!" },
|
||||
finish_reason: "stop",
|
||||
index: 0,
|
||||
},
|
||||
],
|
||||
// anthropic text
|
||||
completion: "Hello!",
|
||||
// anthropic chat
|
||||
content: [{ type: "text", text: "Hello!" }],
|
||||
// gemini
|
||||
candidates: [
|
||||
{
|
||||
content: { parts: [{ text: "Hello!" }] },
|
||||
finishReason: "stop",
|
||||
},
|
||||
],
|
||||
proxy_note:
|
||||
"SillyTavern connection test detected. Your prompt was not sent to the actual model and this response was generated by the proxy.",
|
||||
});
|
||||
}
|
||||
};
|
||||
|
||||
function isTestMessage(body: any) {
|
||||
const { messages, prompt, contents } = body;
|
||||
|
||||
if (messages) {
|
||||
return (
|
||||
messages.length === 1 &&
|
||||
messages[0].role === "user" &&
|
||||
messages[0].content === "Hi"
|
||||
);
|
||||
} else if (contents) {
|
||||
return contents.length === 1 && contents[0].parts[0]?.text === "Hi";
|
||||
} else {
|
||||
return (
|
||||
prompt?.trim() === "Human: Hi\n\nAssistant:" ||
|
||||
prompt?.startsWith("Hi\n\n")
|
||||
);
|
||||
}
|
||||
}
|
||||
@@ -1,37 +0,0 @@
|
||||
import { hasAvailableQuota } from "../../../../shared/users/user-store";
|
||||
import { isImageGenerationRequest, isTextGenerationRequest } from "../../common";
|
||||
import { RequestPreprocessor } 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: RequestPreprocessor = (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,
|
||||
}
|
||||
);
|
||||
}
|
||||
};
|
||||
@@ -1,77 +0,0 @@
|
||||
import { RequestPreprocessor } from "../index";
|
||||
import { countTokens } from "../../../../shared/tokenization";
|
||||
import { assertNever } from "../../../../shared/utils";
|
||||
import {
|
||||
GoogleAIChatMessage,
|
||||
MistralAIChatMessage,
|
||||
OpenAIChatMessage,
|
||||
} from "../../../../shared/api-schemas";
|
||||
|
||||
/**
|
||||
* Given a request with an already-transformed body, counts the number of
|
||||
* tokens and assigns the count to the request.
|
||||
*/
|
||||
export const countPromptTokens: RequestPreprocessor = async (req) => {
|
||||
const service = req.outboundApi;
|
||||
let result;
|
||||
|
||||
switch (service) {
|
||||
case "openai": {
|
||||
req.outputTokens = req.body.max_completion_tokens || req.body.max_tokens;
|
||||
const prompt: OpenAIChatMessage[] = req.body.messages;
|
||||
result = await countTokens({ req, prompt, service });
|
||||
break;
|
||||
}
|
||||
case "openai-text": {
|
||||
req.outputTokens = req.body.max_tokens;
|
||||
const prompt: string = req.body.prompt;
|
||||
result = await countTokens({ req, prompt, service });
|
||||
break;
|
||||
}
|
||||
case "anthropic-chat": {
|
||||
req.outputTokens = req.body.max_tokens;
|
||||
let system = req.body.system ?? "";
|
||||
if (Array.isArray(system)) {
|
||||
system = system
|
||||
.map((m: { type: string; text: string }) => m.text)
|
||||
.join("\n");
|
||||
}
|
||||
const prompt = { system, messages: req.body.messages };
|
||||
result = await countTokens({ req, prompt, service });
|
||||
break;
|
||||
}
|
||||
case "anthropic-text": {
|
||||
req.outputTokens = req.body.max_tokens_to_sample;
|
||||
const prompt: string = req.body.prompt;
|
||||
result = await countTokens({ req, prompt, service });
|
||||
break;
|
||||
}
|
||||
case "google-ai": {
|
||||
req.outputTokens = req.body.generationConfig.maxOutputTokens;
|
||||
const prompt: GoogleAIChatMessage[] = req.body.contents;
|
||||
result = await countTokens({ req, prompt, service });
|
||||
break;
|
||||
}
|
||||
case "mistral-ai":
|
||||
case "mistral-text": {
|
||||
req.outputTokens = req.body.max_tokens;
|
||||
const prompt: string | MistralAIChatMessage[] =
|
||||
req.body.messages ?? req.body.prompt;
|
||||
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;
|
||||
|
||||
req.log.debug({ result: result }, "Counted prompt tokens.");
|
||||
req.tokenizerInfo = req.tokenizerInfo ?? {};
|
||||
req.tokenizerInfo = { ...req.tokenizerInfo, ...result };
|
||||
};
|
||||
@@ -1,94 +0,0 @@
|
||||
import { Request } from "express";
|
||||
import { z } from "zod";
|
||||
import { config } from "../../../../config";
|
||||
import { assertNever } from "../../../../shared/utils";
|
||||
import { RequestPreprocessor } from "../index";
|
||||
import { BadRequestError } from "../../../../shared/errors";
|
||||
import {
|
||||
MistralAIChatMessage,
|
||||
OpenAIChatMessage,
|
||||
flattenAnthropicMessages,
|
||||
} from "../../../../shared/api-schemas";
|
||||
import { GoogleAIV1GenerateContentSchema } from "../../../../shared/api-schemas/google-ai";
|
||||
|
||||
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 BadRequestError(config.rejectMessage);
|
||||
}
|
||||
};
|
||||
|
||||
/*
|
||||
TODO: this is not type safe and does not raise errors if request body zod schema
|
||||
is changed.
|
||||
*/
|
||||
function getPromptFromRequest(req: Request) {
|
||||
const service = req.outboundApi;
|
||||
const body = req.body;
|
||||
switch (service) {
|
||||
case "anthropic-chat":
|
||||
return flattenAnthropicMessages(body.messages);
|
||||
case "openai":
|
||||
case "mistral-ai":
|
||||
return body.messages
|
||||
.map((msg: OpenAIChatMessage | MistralAIChatMessage) => {
|
||||
const text = Array.isArray(msg.content)
|
||||
? msg.content
|
||||
.map((c) => {
|
||||
if ("text" in c) return c.text;
|
||||
})
|
||||
.join()
|
||||
: msg.content;
|
||||
return `${msg.role}: ${text}`;
|
||||
})
|
||||
.join("\n\n");
|
||||
case "anthropic-text":
|
||||
case "openai-text":
|
||||
case "openai-image":
|
||||
case "mistral-text":
|
||||
return body.prompt;
|
||||
case "google-ai": {
|
||||
const b = body as z.infer<typeof GoogleAIV1GenerateContentSchema>;
|
||||
return [
|
||||
b.systemInstruction?.parts.map((p) => p.text),
|
||||
...b.contents.flatMap((c) => c.parts.map((p) => p.text)),
|
||||
].join("\n");
|
||||
}
|
||||
default:
|
||||
assertNever(service);
|
||||
}
|
||||
}
|
||||
@@ -1,30 +0,0 @@
|
||||
import { Request } from "express";
|
||||
import { APIFormat } from "../../../../shared/key-management";
|
||||
import { LLMService } from "../../../../shared/models";
|
||||
import { RequestPreprocessor } from "../index";
|
||||
|
||||
export const setApiFormat = (api: {
|
||||
/**
|
||||
* The API format the user made the request in and expects the response to be
|
||||
* in.
|
||||
*/
|
||||
inApi: Request["inboundApi"];
|
||||
/**
|
||||
* The API format the proxy will make the request in and expects the response
|
||||
* to be in. If different from `inApi`, the proxy will transform the user's
|
||||
* request body to this format, and will transform the response body or stream
|
||||
* events from this format.
|
||||
*/
|
||||
outApi: APIFormat;
|
||||
/**
|
||||
* The service the request will be sent to, which determines authentication
|
||||
* and possibly the streaming transport.
|
||||
*/
|
||||
service: LLMService;
|
||||
}): RequestPreprocessor => {
|
||||
return function configureRequestApiFormat(req) {
|
||||
req.inboundApi = api.inApi;
|
||||
req.outboundApi = api.outApi;
|
||||
req.service = api.service;
|
||||
};
|
||||
};
|
||||
@@ -1,89 +0,0 @@
|
||||
import { Request } from "express";
|
||||
import {
|
||||
API_REQUEST_VALIDATORS,
|
||||
API_REQUEST_TRANSFORMERS,
|
||||
} from "../../../../shared/api-schemas";
|
||||
import { BadRequestError } from "../../../../shared/errors";
|
||||
import { fixMistralPrompt } from "../../../../shared/api-schemas/mistral-ai";
|
||||
import {
|
||||
isImageGenerationRequest,
|
||||
isTextGenerationRequest,
|
||||
} from "../../common";
|
||||
import { RequestPreprocessor } from "../index";
|
||||
|
||||
/** Transforms an incoming request body to one that matches the target API. */
|
||||
export const transformOutboundPayload: RequestPreprocessor = async (req) => {
|
||||
const alreadyTransformed = req.retryCount > 0;
|
||||
const notTransformable =
|
||||
!isTextGenerationRequest(req) && !isImageGenerationRequest(req);
|
||||
|
||||
if (alreadyTransformed) {
|
||||
return;
|
||||
} else if (notTransformable) {
|
||||
// This is probably an indication of a bug in the proxy.
|
||||
const { inboundApi, outboundApi, method, path } = req;
|
||||
req.log.warn(
|
||||
{ inboundApi, outboundApi, method, path },
|
||||
"`transformOutboundPayload` called on a non-transformable request."
|
||||
);
|
||||
return;
|
||||
}
|
||||
|
||||
applyMistralPromptFixes(req);
|
||||
|
||||
// Native prompts are those which were already provided by the client in the
|
||||
// target API format. We don't need to transform them.
|
||||
const isNativePrompt = req.inboundApi === req.outboundApi;
|
||||
if (isNativePrompt) {
|
||||
const result = API_REQUEST_VALIDATORS[req.inboundApi].parse(req.body);
|
||||
req.body = result;
|
||||
return;
|
||||
}
|
||||
|
||||
// Prompt requires translation from one API format to another.
|
||||
const transformation = `${req.inboundApi}->${req.outboundApi}` as const;
|
||||
const transFn = API_REQUEST_TRANSFORMERS[transformation];
|
||||
|
||||
if (transFn) {
|
||||
req.log.info({ transformation }, "Transforming request...");
|
||||
req.body = await transFn(req);
|
||||
return;
|
||||
}
|
||||
|
||||
throw new BadRequestError(
|
||||
`${transformation} proxying is not supported. Make sure your client is configured to send requests in the correct format and to the correct endpoint.`
|
||||
);
|
||||
};
|
||||
|
||||
// handles weird cases that don't fit into our abstractions
|
||||
function applyMistralPromptFixes(req: Request): void {
|
||||
if (req.inboundApi === "mistral-ai") {
|
||||
// Mistral Chat is very similar to OpenAI but not identical and many clients
|
||||
// don't properly handle the differences. We will try to validate the
|
||||
// mistral prompt and try to fix it if it fails. It will be re-validated
|
||||
// after this function returns.
|
||||
const result = API_REQUEST_VALIDATORS["mistral-ai"].parse(req.body);
|
||||
req.body.messages = fixMistralPrompt(result.messages);
|
||||
req.log.info(
|
||||
{ n: req.body.messages.length, prev: result.messages.length },
|
||||
"Applied Mistral chat prompt fixes."
|
||||
);
|
||||
|
||||
// If the prompt relies on `prefix: true` for the last message, we need to
|
||||
// convert it to a text completions request because AWS Mistral support for
|
||||
// this feature is broken.
|
||||
// On Mistral La Plateforme, we can't do this because they don't expose
|
||||
// a text completions endpoint.
|
||||
const { messages } = req.body;
|
||||
const lastMessage = messages && messages[messages.length - 1];
|
||||
if (lastMessage?.role === "assistant" && req.service === "aws") {
|
||||
// enable prefix if client forgot, otherwise the template will insert an
|
||||
// eos token which is very unlikely to be what the client wants.
|
||||
lastMessage.prefix = true;
|
||||
req.outboundApi = "mistral-text";
|
||||
req.log.info(
|
||||
"Native Mistral chat prompt relies on assistant message prefix. Converting to text completions request."
|
||||
);
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -1,141 +0,0 @@
|
||||
import { Request } from "express";
|
||||
import { z } from "zod";
|
||||
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;
|
||||
// todo: make configurable
|
||||
const GOOGLE_AI_MAX_CONTEXT = 2048000;
|
||||
const MISTRAL_AI_MAX_CONTENT = 131072;
|
||||
|
||||
/**
|
||||
* Assigns `req.promptTokens` and `req.outputTokens` based on the request body
|
||||
* and outbound API format, which combined determine the size of the context.
|
||||
* If the context is too large, an error is thrown.
|
||||
* This preprocessor should run after any preprocessor that transforms the
|
||||
* request body.
|
||||
*/
|
||||
export const validateContextSize: RequestPreprocessor = async (req) => {
|
||||
assertRequestHasTokenCounts(req);
|
||||
const promptTokens = req.promptTokens;
|
||||
const outputTokens = req.outputTokens;
|
||||
const contextTokens = promptTokens + outputTokens;
|
||||
const model = req.body.model;
|
||||
|
||||
let proxyMax: number;
|
||||
switch (req.outboundApi) {
|
||||
case "openai":
|
||||
case "openai-text":
|
||||
proxyMax = OPENAI_MAX_CONTEXT;
|
||||
break;
|
||||
case "anthropic-chat":
|
||||
case "anthropic-text":
|
||||
proxyMax = CLAUDE_MAX_CONTEXT;
|
||||
break;
|
||||
case "google-ai":
|
||||
proxyMax = GOOGLE_AI_MAX_CONTEXT;
|
||||
break;
|
||||
case "mistral-ai":
|
||||
case "mistral-text":
|
||||
proxyMax = MISTRAL_AI_MAX_CONTENT;
|
||||
break;
|
||||
case "openai-image":
|
||||
return;
|
||||
default:
|
||||
assertNever(req.outboundApi);
|
||||
}
|
||||
proxyMax ||= Number.MAX_SAFE_INTEGER;
|
||||
|
||||
if (req.user?.type === "special") {
|
||||
req.log.debug("Special user, not enforcing proxy context limit.");
|
||||
proxyMax = Number.MAX_SAFE_INTEGER;
|
||||
}
|
||||
|
||||
let modelMax: number;
|
||||
if (model.match(/gpt-3.5-turbo-16k/)) {
|
||||
modelMax = 16384;
|
||||
} else if (model.match(/^gpt-4o/)) {
|
||||
modelMax = 128000;
|
||||
} else if (model.match(/^chatgpt-4o/)) {
|
||||
modelMax = 128000;
|
||||
} else if (model.match(/gpt-4-turbo(-\d{4}-\d{2}-\d{2})?$/)) {
|
||||
modelMax = 131072;
|
||||
} else if (model.match(/gpt-4-turbo(-preview)?$/)) {
|
||||
modelMax = 131072;
|
||||
} else if (model.match(/gpt-4-(0125|1106)(-preview)?$/)) {
|
||||
modelMax = 131072;
|
||||
} else if (model.match(/^gpt-4(-\d{4})?-vision(-preview)?$/)) {
|
||||
modelMax = 131072;
|
||||
} else if (model.match(/^o1(-\d{4}-\d{2}-\d{2})?$/)) {
|
||||
modelMax = 200000;
|
||||
} else if (model.match(/^o1-mini(-\d{4}-\d{2}-\d{2})?$/)) {
|
||||
modelMax = 128000;
|
||||
} else if (model.match(/^o1-preview(-\d{4}-\d{2}-\d{2})?$/)) {
|
||||
modelMax = 128000;
|
||||
} else if (model.match(/gpt-3.5-turbo/)) {
|
||||
modelMax = 16384;
|
||||
} else if (model.match(/gpt-4-32k/)) {
|
||||
modelMax = 32768;
|
||||
} else if (model.match(/gpt-4/)) {
|
||||
modelMax = 8192;
|
||||
} else if (model.match(/^claude-(?:instant-)?v1(?:\.\d)?-100k/)) {
|
||||
modelMax = 100000;
|
||||
} else if (model.match(/^claude-(?:instant-)?v1(?:\.\d)?$/)) {
|
||||
modelMax = 9000;
|
||||
} else if (model.match(/^claude-2\.0/)) {
|
||||
modelMax = 100000;
|
||||
} else if (model.match(/^claude-2/)) {
|
||||
modelMax = 200000;
|
||||
} else if (model.match(/^claude-3/)) {
|
||||
modelMax = 200000;
|
||||
} else if (model.match(/^gemini-/)) {
|
||||
modelMax = 1024000;
|
||||
} else if (model.match(/^anthropic\.claude-3/)) {
|
||||
modelMax = 200000;
|
||||
} else if (model.match(/^anthropic\.claude-v2:\d/)) {
|
||||
modelMax = 200000;
|
||||
} else if (model.match(/^anthropic\.claude/)) {
|
||||
modelMax = 100000;
|
||||
} else if (model.match(/tral/)) {
|
||||
// catches mistral, mixtral, codestral, mathstral, etc. mistral models have
|
||||
// no name convention and wildly different context windows so this is a
|
||||
// catch-all
|
||||
modelMax = MISTRAL_AI_MAX_CONTENT;
|
||||
} else {
|
||||
req.log.warn({ model }, "Unknown model, using 200k token limit.");
|
||||
modelMax = 200000;
|
||||
}
|
||||
|
||||
const finalMax = Math.min(proxyMax, modelMax);
|
||||
z.object({
|
||||
tokens: z
|
||||
.number()
|
||||
.int()
|
||||
.max(finalMax, {
|
||||
message: `Your request exceeds the context size limit. (max: ${finalMax} tokens, requested: ${promptTokens} prompt + ${outputTokens} output = ${contextTokens} context tokens)`,
|
||||
}),
|
||||
}).parse({ tokens: contextTokens });
|
||||
|
||||
req.log.debug(
|
||||
{ promptTokens, outputTokens, contextTokens, modelMax, proxyMax },
|
||||
"Prompt size validated"
|
||||
);
|
||||
|
||||
req.tokenizerInfo.prompt_tokens = promptTokens;
|
||||
req.tokenizerInfo.completion_tokens = outputTokens;
|
||||
req.tokenizerInfo.max_model_tokens = modelMax;
|
||||
req.tokenizerInfo.max_proxy_tokens = proxyMax;
|
||||
};
|
||||
|
||||
function assertRequestHasTokenCounts(
|
||||
req: Request
|
||||
): asserts req is Request & { promptTokens: number; outputTokens: number } {
|
||||
z.object({
|
||||
promptTokens: z.number().int().min(1),
|
||||
outputTokens: z.number().int().min(1),
|
||||
})
|
||||
.nonstrict()
|
||||
.parse({ promptTokens: req.promptTokens, outputTokens: req.outputTokens });
|
||||
}
|
||||
@@ -1,16 +0,0 @@
|
||||
import { config } from "../../../../config";
|
||||
import { ForbiddenError } from "../../../../shared/errors";
|
||||
import { getModelFamilyForRequest } from "../../../../shared/models";
|
||||
import { RequestPreprocessor } from "../index";
|
||||
|
||||
/**
|
||||
* Ensures the selected model family is enabled by the proxy configuration.
|
||||
*/
|
||||
export const validateModelFamily: RequestPreprocessor = (req) => {
|
||||
const family = getModelFamilyForRequest(req);
|
||||
if (!config.allowedModelFamilies.includes(family)) {
|
||||
throw new ForbiddenError(
|
||||
`Model family '${family}' is not enabled on this proxy`
|
||||
);
|
||||
}
|
||||
};
|
||||
@@ -1,44 +0,0 @@
|
||||
import { config } from "../../../../config";
|
||||
import { assertNever } from "../../../../shared/utils";
|
||||
import { RequestPreprocessor } from "../index";
|
||||
import { containsImageContent as containsImageContentOpenAI } from "../../../../shared/api-schemas/openai";
|
||||
import { containsImageContent as containsImageContentAnthropic } from "../../../../shared/api-schemas/anthropic";
|
||||
import { ForbiddenError } from "../../../../shared/errors";
|
||||
|
||||
/**
|
||||
* Rejects prompts containing images if multimodal prompts are disabled.
|
||||
*/
|
||||
export const validateVision: RequestPreprocessor = async (req) => {
|
||||
if (req.service === undefined) {
|
||||
throw new Error("Request service must be set before validateVision");
|
||||
}
|
||||
|
||||
if (req.user?.type === "special") return;
|
||||
if (config.allowedVisionServices.includes(req.service)) return;
|
||||
|
||||
// vision not allowed for req's service, block prompts with images
|
||||
let hasImage = false;
|
||||
switch (req.outboundApi) {
|
||||
case "openai":
|
||||
hasImage = containsImageContentOpenAI(req.body.messages);
|
||||
break;
|
||||
case "anthropic-chat":
|
||||
hasImage = containsImageContentAnthropic(req.body.messages);
|
||||
break;
|
||||
case "anthropic-text":
|
||||
case "google-ai":
|
||||
case "mistral-ai":
|
||||
case "mistral-text":
|
||||
case "openai-image":
|
||||
case "openai-text":
|
||||
return;
|
||||
default:
|
||||
assertNever(req.outboundApi);
|
||||
}
|
||||
|
||||
if (hasImage) {
|
||||
throw new ForbiddenError(
|
||||
"Prompts containing images are not permitted. Disable 'Send Inline Images' in your client and try again."
|
||||
);
|
||||
}
|
||||
};
|
||||
@@ -1,135 +0,0 @@
|
||||
import { Request, Response } from "express";
|
||||
import http from "http";
|
||||
import ProxyServer from "http-proxy";
|
||||
import { Readable } from "stream";
|
||||
import {
|
||||
createProxyMiddleware,
|
||||
Options,
|
||||
debugProxyErrorsPlugin,
|
||||
proxyEventsPlugin,
|
||||
} from "http-proxy-middleware";
|
||||
import { ProxyReqMutator, stripHeaders } from "./index";
|
||||
import { createOnProxyResHandler, ProxyResHandlerWithBody } from "../response";
|
||||
import { createQueueMiddleware } from "../../queue";
|
||||
import { getHttpAgents } from "../../../shared/network";
|
||||
import { classifyErrorAndSend } from "../common";
|
||||
|
||||
/**
|
||||
* Options for the `createQueuedProxyMiddleware` factory function.
|
||||
*/
|
||||
type ProxyMiddlewareFactoryOptions = {
|
||||
/**
|
||||
* Functions which receive a ProxyReqManager and can modify the request before
|
||||
* it is proxied. The modifications will be automatically reverted if the
|
||||
* request needs to be returned to the queue.
|
||||
*/
|
||||
mutations?: ProxyReqMutator[];
|
||||
/**
|
||||
* The target URL to proxy requests to. This can be a string or a function
|
||||
* which accepts the request and returns a string.
|
||||
*/
|
||||
target: string | Options<Request>["router"];
|
||||
/**
|
||||
* A function which receives the proxy response and the JSON-decoded request
|
||||
* body. Only fired for non-streaming responses; streaming responses are
|
||||
* handled in `handle-streaming-response.ts`.
|
||||
*/
|
||||
blockingResponseHandler?: ProxyResHandlerWithBody;
|
||||
};
|
||||
|
||||
/**
|
||||
* Returns a middleware function that accepts incoming requests and places them
|
||||
* into the request queue. When the request is dequeued, it is proxied to the
|
||||
* target URL using the given options and middleware. Non-streaming responses
|
||||
* are handled by the given `blockingResponseHandler`.
|
||||
*/
|
||||
export function createQueuedProxyMiddleware({
|
||||
target,
|
||||
mutations,
|
||||
blockingResponseHandler,
|
||||
}: ProxyMiddlewareFactoryOptions) {
|
||||
const hpmTarget = typeof target === "string" ? target : "https://setbyrouter";
|
||||
const hpmRouter = typeof target === "function" ? target : undefined;
|
||||
|
||||
const [httpAgent, httpsAgent] = getHttpAgents();
|
||||
const agent = hpmTarget.startsWith("http:") ? httpAgent : httpsAgent;
|
||||
|
||||
const proxyMiddleware = createProxyMiddleware<Request, Response>({
|
||||
target: hpmTarget,
|
||||
router: hpmRouter,
|
||||
agent,
|
||||
changeOrigin: true,
|
||||
toProxy: true,
|
||||
selfHandleResponse: typeof blockingResponseHandler === "function",
|
||||
// Disable HPM logger plugin (requires re-adding the other default plugins).
|
||||
// Contrary to name, debugProxyErrorsPlugin is not just for debugging and
|
||||
// fixes several error handling/connection close issues in http-proxy core.
|
||||
ejectPlugins: true,
|
||||
// Inferred (via Options<express.Request>) as Plugin<express.Request>, but
|
||||
// the default plugins only allow http.IncomingMessage for TReq. They are
|
||||
// compatible with express.Request, so we can use them. `Plugin` type is not
|
||||
// exported for some reason.
|
||||
plugins: [
|
||||
debugProxyErrorsPlugin,
|
||||
pinoLoggerPlugin,
|
||||
proxyEventsPlugin,
|
||||
] as any,
|
||||
on: {
|
||||
proxyRes: createOnProxyResHandler(
|
||||
blockingResponseHandler ? [blockingResponseHandler] : []
|
||||
),
|
||||
error: classifyErrorAndSend,
|
||||
},
|
||||
buffer: ((req: Request) => {
|
||||
// This is a hack/monkey patch and is not part of the official
|
||||
// http-proxy-middleware package. See patches/http-proxy+1.18.1.patch.
|
||||
let payload = req.body;
|
||||
if (typeof payload === "string") {
|
||||
payload = Buffer.from(payload);
|
||||
}
|
||||
const stream = new Readable();
|
||||
stream.push(payload);
|
||||
stream.push(null);
|
||||
return stream;
|
||||
}) as any,
|
||||
});
|
||||
|
||||
return createQueueMiddleware({
|
||||
mutations: [stripHeaders, ...(mutations ?? [])],
|
||||
proxyMiddleware,
|
||||
});
|
||||
}
|
||||
|
||||
type ProxiedResponse = http.IncomingMessage & Response & any;
|
||||
function pinoLoggerPlugin(proxyServer: ProxyServer<Request>) {
|
||||
proxyServer.on("error", (err, req, res, target) => {
|
||||
req.log.error(
|
||||
{ originalUrl: req.originalUrl, targetUrl: String(target), err },
|
||||
"Error occurred while proxying request to target"
|
||||
);
|
||||
});
|
||||
proxyServer.on("proxyReq", (proxyReq, req) => {
|
||||
const { protocol, host, path } = proxyReq;
|
||||
req.log.info(
|
||||
{
|
||||
from: req.originalUrl,
|
||||
to: `${protocol}//${host}${path}`,
|
||||
},
|
||||
"Sending request to upstream API..."
|
||||
);
|
||||
});
|
||||
proxyServer.on("proxyRes", (proxyRes: ProxiedResponse, req, _res) => {
|
||||
const { protocol, host, path } = proxyRes.req;
|
||||
req.log.info(
|
||||
{
|
||||
target: `${protocol}//${host}${path}`,
|
||||
status: proxyRes.statusCode,
|
||||
contentType: proxyRes.headers["content-type"],
|
||||
contentEncoding: proxyRes.headers["content-encoding"],
|
||||
contentLength: proxyRes.headers["content-length"],
|
||||
transferEncoding: proxyRes.headers["transfer-encoding"],
|
||||
},
|
||||
"Got response from upstream API."
|
||||
);
|
||||
});
|
||||
}
|
||||
@@ -1,112 +0,0 @@
|
||||
import { Request } from "express";
|
||||
import { Key } from "../../../shared/key-management";
|
||||
import { assertNever } from "../../../shared/utils";
|
||||
|
||||
/**
|
||||
* Represents a change to the request that will be reverted if the request
|
||||
* fails.
|
||||
*/
|
||||
interface ProxyReqMutation {
|
||||
target: "header" | "path" | "body" | "api-key" | "signed-request";
|
||||
key?: string;
|
||||
originalValue: any | undefined;
|
||||
}
|
||||
|
||||
/**
|
||||
* Manages a request's headers, body, and path, allowing them to be modified
|
||||
* before the request is proxied and automatically reverted if the request
|
||||
* needs to be retried.
|
||||
*/
|
||||
export class ProxyReqManager {
|
||||
private req: Request;
|
||||
private mutations: ProxyReqMutation[] = [];
|
||||
|
||||
/**
|
||||
* A read-only proxy of the request object. Avoid changing any properties
|
||||
* here as they will persist across retries.
|
||||
*/
|
||||
public readonly request: Readonly<Request>;
|
||||
|
||||
constructor(req: Request) {
|
||||
this.req = req;
|
||||
|
||||
this.request = new Proxy(req, {
|
||||
get: (target, prop) => {
|
||||
if (typeof prop === "string") return target[prop as keyof Request];
|
||||
return undefined;
|
||||
},
|
||||
});
|
||||
}
|
||||
|
||||
setHeader(name: string, newValue: string): void {
|
||||
const originalValue = this.req.get(name);
|
||||
this.mutations.push({ target: "header", key: name, originalValue });
|
||||
this.req.headers[name.toLowerCase()] = newValue;
|
||||
}
|
||||
|
||||
removeHeader(name: string): void {
|
||||
const originalValue = this.req.get(name);
|
||||
this.mutations.push({ target: "header", key: name, originalValue });
|
||||
delete this.req.headers[name.toLowerCase()];
|
||||
}
|
||||
|
||||
setBody(newBody: any): void {
|
||||
const originalValue = this.req.body;
|
||||
this.mutations.push({ target: "body", key: "body", originalValue });
|
||||
this.req.body = newBody;
|
||||
}
|
||||
|
||||
setKey(newKey: Key): void {
|
||||
const originalValue = this.req.key;
|
||||
this.mutations.push({ target: "api-key", key: "key", originalValue });
|
||||
this.req.key = newKey;
|
||||
}
|
||||
|
||||
setPath(newPath: string): void {
|
||||
const originalValue = this.req.path;
|
||||
this.mutations.push({ target: "path", key: "path", originalValue });
|
||||
this.req.url = newPath;
|
||||
}
|
||||
|
||||
setSignedRequest(newSignedRequest: typeof this.req.signedRequest): void {
|
||||
const originalValue = this.req.signedRequest;
|
||||
this.mutations.push({ target: "signed-request", key: "signedRequest", originalValue });
|
||||
this.req.signedRequest = newSignedRequest;
|
||||
}
|
||||
|
||||
hasChanged(): boolean {
|
||||
return this.mutations.length > 0;
|
||||
}
|
||||
|
||||
revert(): void {
|
||||
for (const mutation of this.mutations.reverse()) {
|
||||
switch (mutation.target) {
|
||||
case "header":
|
||||
if (mutation.originalValue === undefined) {
|
||||
delete this.req.headers[mutation.key!.toLowerCase()];
|
||||
continue;
|
||||
} else {
|
||||
this.req.headers[mutation.key!.toLowerCase()] =
|
||||
mutation.originalValue;
|
||||
}
|
||||
break;
|
||||
case "path":
|
||||
this.req.url = mutation.originalValue;
|
||||
break;
|
||||
case "body":
|
||||
this.req.body = mutation.originalValue;
|
||||
break;
|
||||
case "api-key":
|
||||
// We don't reset the key here because it's not a property of the
|
||||
// inbound request, so we'd only ever be reverting it to null.
|
||||
break;
|
||||
case "signed-request":
|
||||
this.req.signedRequest = mutation.originalValue;
|
||||
break;
|
||||
default:
|
||||
assertNever(mutation.target);
|
||||
}
|
||||
}
|
||||
this.mutations = [];
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,10 @@
|
||||
import { ProxyRequestMiddleware } from ".";
|
||||
|
||||
/**
|
||||
* Removes origin and referer headers before sending the request to the API for
|
||||
* privacy reasons.
|
||||
**/
|
||||
export const removeOriginHeaders: ProxyRequestMiddleware = (proxyReq) => {
|
||||
proxyReq.setHeader("origin", "");
|
||||
proxyReq.setHeader("referer", "");
|
||||
};
|
||||
@@ -0,0 +1,13 @@
|
||||
import { Request } from "express";
|
||||
import { APIFormat } from "../../../shared/key-management";
|
||||
import { RequestPreprocessor } from ".";
|
||||
|
||||
export const setApiFormat = (api: {
|
||||
inApi: Request["inboundApi"];
|
||||
outApi: APIFormat;
|
||||
}): RequestPreprocessor => {
|
||||
return (req) => {
|
||||
req.inboundApi = api.inApi;
|
||||
req.outboundApi = api.outApi;
|
||||
};
|
||||
};
|
||||
@@ -0,0 +1,112 @@
|
||||
/**
|
||||
* Transforms a KoboldAI payload into an OpenAI payload.
|
||||
* @deprecated Kobold input format isn't supported anymore as all popular
|
||||
* frontends support reverse proxies or changing their base URL. It adds too
|
||||
* many edge cases to be worth maintaining and doesn't work with newer features.
|
||||
*/
|
||||
import { logger } from "../../../logger";
|
||||
import type { ProxyRequestMiddleware } from ".";
|
||||
|
||||
// Kobold requests look like this:
|
||||
// body:
|
||||
// {
|
||||
// prompt: "Aqua is character from Konosuba anime. Aqua is a goddess, before life in the Fantasy World, she was a goddess of water who guided humans to the afterlife. Aqua looks like young woman with beauty no human could match. Aqua has light blue hair, blue eyes, slim figure, long legs, wide hips, blue waist-long hair that is partially tied into a loop with a spherical clip. Aqua's measurements are 83-56-83 cm. Aqua's height 157cm. Aqua wears sleeveless dark-blue dress with white trimmings, extremely short dark blue miniskirt, green bow around her chest with a blue gem in the middle, detached white sleeves with blue and golden trimmings, thigh-high blue heeled boots over white stockings with blue trimmings. Aqua is very strong in water magic, but a little stupid, so she does not always use it to the place. Aqua is high-spirited, cheerful, carefree. Aqua rarely thinks about the consequences of her actions and always acts or speaks on her whims. Because very easy to taunt Aqua with jeers or lure her with praises.\n" +
|
||||
// "Aqua's personality: high-spirited, likes to party, carefree, cheerful.\n" +
|
||||
// 'Circumstances and context of the dialogue: Aqua is standing in the city square and is looking for new followers\n' +
|
||||
// 'This is how Aqua should talk\n' +
|
||||
// 'You: Hi Aqua, I heard you like to spend time in the pub.\n' +
|
||||
// "Aqua: *excitedly* Oh my goodness, yes! I just love spending time at the pub! It's so much fun to talk to all the adventurers and hear about their exciting adventures! And you are?\n" +
|
||||
// "You: I'm a new here and I wanted to ask for your advice.\n" +
|
||||
// 'Aqua: *giggles* Oh, advice! I love giving advice! And in gratitude for that, treat me to a drink! *gives signals to the bartender*\n' +
|
||||
// 'This is how Aqua should talk\n' +
|
||||
// 'You: Hello\n' +
|
||||
// "Aqua: *excitedly* Hello there, dear! Are you new to Axel? Don't worry, I, Aqua the goddess of water, am here to help you! Do you need any assistance? And may I say, I look simply radiant today! *strikes a pose and looks at you with puppy eyes*\n" +
|
||||
// '\n' +
|
||||
// 'Then the roleplay chat between You and Aqua begins.\n' +
|
||||
// "Aqua: *She is in the town square of a city named Axel. It's morning on a Saturday and she suddenly notices a person who looks like they don't know what they're doing. She approaches him and speaks* \n" +
|
||||
// '\n' +
|
||||
// `"Are you new here? Do you need help? Don't worry! I, Aqua the Goddess of Water, shall help you! Do I look beautiful?" \n` +
|
||||
// '\n' +
|
||||
// '*She strikes a pose and looks at him with puppy eyes.*\n' +
|
||||
// 'You: test\n' +
|
||||
// 'You: test\n' +
|
||||
// 'You: t\n' +
|
||||
// 'You: test\n',
|
||||
// use_story: false,
|
||||
// use_memory: false,
|
||||
// use_authors_note: false,
|
||||
// use_world_info: false,
|
||||
// max_context_length: 2048,
|
||||
// max_length: 180,
|
||||
// rep_pen: 1.1,
|
||||
// rep_pen_range: 1024,
|
||||
// rep_pen_slope: 0.9,
|
||||
// temperature: 0.65,
|
||||
// tfs: 0.9,
|
||||
// top_a: 0,
|
||||
// top_k: 0,
|
||||
// top_p: 0.9,
|
||||
// typical: 1,
|
||||
// sampler_order: [
|
||||
// 6, 0, 1, 2,
|
||||
// 3, 4, 5
|
||||
// ],
|
||||
// singleline: false
|
||||
// }
|
||||
|
||||
// OpenAI expects this body:
|
||||
// { model: 'gpt-3.5-turbo', temperature: 0.65, top_p: 0.9, max_tokens: 180, messages }
|
||||
// there's also a frequency_penalty but it's not clear how that maps to kobold's
|
||||
// rep_pen.
|
||||
|
||||
// messages is an array of { role: "system" | "assistant" | "user", content: ""}
|
||||
// kobold only sends us the entire prompt. we can try to split the last two
|
||||
// lines into user and assistant messages, but that's not always correct. For
|
||||
// now it will have to do.
|
||||
|
||||
/**
|
||||
* Transforms a KoboldAI payload into an OpenAI payload.
|
||||
* @deprecated Probably doesn't work anymore, idk.
|
||||
**/
|
||||
export const transformKoboldPayload: ProxyRequestMiddleware = (
|
||||
_proxyReq,
|
||||
req
|
||||
) => {
|
||||
// if (req.inboundApi !== "kobold") {
|
||||
// throw new Error("transformKoboldPayload called for non-kobold request.");
|
||||
// }
|
||||
|
||||
const { body } = req;
|
||||
const { prompt, max_length, rep_pen, top_p, temperature } = body;
|
||||
|
||||
if (!max_length) {
|
||||
logger.error("KoboldAI request missing max_length.");
|
||||
throw new Error("You must specify a max_length parameter.");
|
||||
}
|
||||
|
||||
const promptLines = prompt.split("\n");
|
||||
// The very last line is the contentless "Assistant: " hint to the AI.
|
||||
// Tavern just leaves an empty line, Agnai includes the AI's name.
|
||||
const assistantHint = promptLines.pop();
|
||||
// The second-to-last line is the user's prompt, generally.
|
||||
const userPrompt = promptLines.pop();
|
||||
const messages = [
|
||||
{ role: "system", content: promptLines.join("\n") },
|
||||
{ role: "user", content: userPrompt },
|
||||
{ role: "assistant", content: assistantHint },
|
||||
];
|
||||
|
||||
// Kobold doesn't select a model. If the addKey rewriter assigned us a GPT-4
|
||||
// key, use that. Otherwise, use GPT-3.5-turbo.
|
||||
|
||||
const model = "gpt-4";
|
||||
const newBody = {
|
||||
model,
|
||||
temperature,
|
||||
top_p,
|
||||
frequency_penalty: rep_pen, // remove this if model turns schizo
|
||||
max_tokens: max_length,
|
||||
messages,
|
||||
};
|
||||
req.body = newBody;
|
||||
};
|
||||
@@ -0,0 +1,336 @@
|
||||
import { Request } from "express";
|
||||
import { z } from "zod";
|
||||
import { config } from "../../../config";
|
||||
import { OpenAIPromptMessage } from "../../../shared/tokenization";
|
||||
import { isCompletionRequest } from "../common";
|
||||
import { RequestPreprocessor } from ".";
|
||||
import { APIFormat } from "../../../shared/key-management";
|
||||
|
||||
const CLAUDE_OUTPUT_MAX = config.maxOutputTokensAnthropic;
|
||||
const OPENAI_OUTPUT_MAX = config.maxOutputTokensOpenAI;
|
||||
|
||||
// https://console.anthropic.com/docs/api/reference#-v1-complete
|
||||
const AnthropicV1CompleteSchema = z.object({
|
||||
model: z.string().regex(/^claude-/, "Model must start with 'claude-'"),
|
||||
prompt: z.string({
|
||||
required_error:
|
||||
"No prompt found. Are you sending an OpenAI-formatted request to the Claude endpoint?",
|
||||
}),
|
||||
max_tokens_to_sample: z.coerce
|
||||
.number()
|
||||
.int()
|
||||
.transform((v) => Math.min(v, CLAUDE_OUTPUT_MAX)),
|
||||
stop_sequences: z.array(z.string()).optional(),
|
||||
stream: z.boolean().optional().default(false),
|
||||
temperature: z.coerce.number().optional().default(1),
|
||||
top_k: z.coerce.number().optional().default(-1),
|
||||
top_p: z.coerce.number().optional().default(-1),
|
||||
metadata: z.any().optional(),
|
||||
});
|
||||
|
||||
// https://platform.openai.com/docs/api-reference/chat/create
|
||||
const OpenAIV1ChatCompletionSchema = z.object({
|
||||
model: z.string().regex(/^gpt/, "Model must start with 'gpt-'"),
|
||||
messages: z.array(
|
||||
z.object({
|
||||
role: z.enum(["system", "user", "assistant"]),
|
||||
content: z.string(),
|
||||
name: z.string().optional(),
|
||||
}),
|
||||
{
|
||||
required_error:
|
||||
"No `messages` found. Ensure you've set the correct completion endpoint.",
|
||||
invalid_type_error:
|
||||
"Messages were not formatted correctly. Refer to the OpenAI Chat API documentation for more information.",
|
||||
}
|
||||
),
|
||||
temperature: z.number().optional().default(1),
|
||||
top_p: z.number().optional().default(1),
|
||||
n: z
|
||||
.literal(1, {
|
||||
errorMap: () => ({
|
||||
message: "You may only request a single completion at a time.",
|
||||
}),
|
||||
})
|
||||
.optional(),
|
||||
stream: z.boolean().optional().default(false),
|
||||
stop: z.union([z.string(), z.array(z.string())]).optional(),
|
||||
max_tokens: z.coerce
|
||||
.number()
|
||||
.int()
|
||||
.nullish()
|
||||
.default(16)
|
||||
.transform((v) => Math.min(v ?? OPENAI_OUTPUT_MAX, OPENAI_OUTPUT_MAX)),
|
||||
frequency_penalty: z.number().optional().default(0),
|
||||
presence_penalty: z.number().optional().default(0),
|
||||
logit_bias: z.any().optional(),
|
||||
user: z.string().optional(),
|
||||
});
|
||||
|
||||
const OpenAIV1TextCompletionSchema = z
|
||||
.object({
|
||||
model: z
|
||||
.string()
|
||||
.regex(
|
||||
/^gpt-3.5-turbo-instruct/,
|
||||
"Model must start with 'gpt-3.5-turbo-instruct'"
|
||||
),
|
||||
prompt: z.string({
|
||||
required_error:
|
||||
"No `prompt` found. Ensure you've set the correct completion endpoint.",
|
||||
}),
|
||||
logprobs: z.number().int().nullish().default(null),
|
||||
echo: z.boolean().optional().default(false),
|
||||
best_of: z.literal(1).optional(),
|
||||
stop: z.union([z.string(), z.array(z.string()).max(4)]).optional(),
|
||||
suffix: z.string().optional(),
|
||||
})
|
||||
.merge(OpenAIV1ChatCompletionSchema.omit({ messages: true }));
|
||||
|
||||
// https://developers.generativeai.google/api/rest/generativelanguage/models/generateText
|
||||
const PalmV1GenerateTextSchema = z.object({
|
||||
model: z.string().regex(/^\w+-bison-\d{3}$/),
|
||||
prompt: z.object({ text: z.string() }),
|
||||
temperature: z.number().optional(),
|
||||
maxOutputTokens: z.coerce
|
||||
.number()
|
||||
.int()
|
||||
.optional()
|
||||
.default(16)
|
||||
.transform((v) => Math.min(v, 1024)), // TODO: Add config
|
||||
candidateCount: z.literal(1).optional(),
|
||||
topP: z.number().optional(),
|
||||
topK: z.number().optional(),
|
||||
safetySettings: z.array(z.object({})).max(0).optional(),
|
||||
stopSequences: z.array(z.string()).max(5).optional(),
|
||||
});
|
||||
|
||||
const VALIDATORS: Record<APIFormat, z.ZodSchema<any>> = {
|
||||
anthropic: AnthropicV1CompleteSchema,
|
||||
openai: OpenAIV1ChatCompletionSchema,
|
||||
"openai-text": OpenAIV1TextCompletionSchema,
|
||||
"google-palm": PalmV1GenerateTextSchema,
|
||||
};
|
||||
|
||||
/** Transforms an incoming request body to one that matches the target API. */
|
||||
export const transformOutboundPayload: RequestPreprocessor = async (req) => {
|
||||
const sameService = req.inboundApi === req.outboundApi;
|
||||
const alreadyTransformed = req.retryCount > 0;
|
||||
const notTransformable = !isCompletionRequest(req);
|
||||
|
||||
if (alreadyTransformed || notTransformable) {
|
||||
return;
|
||||
}
|
||||
|
||||
if (sameService) {
|
||||
const result = VALIDATORS[req.inboundApi].safeParse(req.body);
|
||||
if (!result.success) {
|
||||
req.log.error(
|
||||
{ issues: result.error.issues, body: req.body },
|
||||
"Request validation failed"
|
||||
);
|
||||
throw result.error;
|
||||
}
|
||||
req.body = result.data;
|
||||
return;
|
||||
}
|
||||
|
||||
if (req.inboundApi === "openai" && req.outboundApi === "anthropic") {
|
||||
req.body = openaiToAnthropic(req);
|
||||
return;
|
||||
}
|
||||
|
||||
if (req.inboundApi === "openai" && req.outboundApi === "google-palm") {
|
||||
req.body = openaiToPalm(req);
|
||||
return;
|
||||
}
|
||||
|
||||
if (req.inboundApi === "openai" && req.outboundApi === "openai-text") {
|
||||
req.body = openaiToOpenaiText(req);
|
||||
return;
|
||||
}
|
||||
|
||||
throw new Error(
|
||||
`'${req.inboundApi}' -> '${req.outboundApi}' request proxying is not supported. Make sure your client is configured to use the correct API.`
|
||||
);
|
||||
};
|
||||
|
||||
function openaiToAnthropic(req: Request) {
|
||||
const { body } = req;
|
||||
const result = OpenAIV1ChatCompletionSchema.safeParse(body);
|
||||
if (!result.success) {
|
||||
req.log.error(
|
||||
{ issues: result.error.issues, body },
|
||||
"Invalid OpenAI-to-Anthropic request"
|
||||
);
|
||||
throw result.error;
|
||||
}
|
||||
|
||||
// Anthropic has started versioning their API, indicated by an HTTP header
|
||||
// `anthropic-version`. The new June 2023 version is not backwards compatible
|
||||
// with our OpenAI-to-Anthropic transformations so we need to explicitly
|
||||
// request the older version for now. 2023-01-01 will be removed in September.
|
||||
// https://docs.anthropic.com/claude/reference/versioning
|
||||
req.headers["anthropic-version"] = "2023-01-01";
|
||||
|
||||
const { messages, ...rest } = result.data;
|
||||
const prompt = openAIMessagesToClaudePrompt(messages);
|
||||
|
||||
let stops = rest.stop
|
||||
? Array.isArray(rest.stop)
|
||||
? rest.stop
|
||||
: [rest.stop]
|
||||
: [];
|
||||
// Recommended by Anthropic
|
||||
stops.push("\n\nHuman:");
|
||||
// Helps with jailbreak prompts that send fake system messages and multi-bot
|
||||
// chats that prefix bot messages with "System: Respond as <bot name>".
|
||||
stops.push("\n\nSystem:");
|
||||
// Remove duplicates
|
||||
stops = [...new Set(stops)];
|
||||
|
||||
return {
|
||||
...rest,
|
||||
// Model may be overridden in `calculate-context-size.ts` to avoid having
|
||||
// a circular dependency (`calculate-context-size.ts` needs an already-
|
||||
// transformed request body to count tokens, but this function would like
|
||||
// to know the count to select a model).
|
||||
model: process.env.CLAUDE_SMALL_MODEL || "claude-v1",
|
||||
prompt: prompt,
|
||||
max_tokens_to_sample: rest.max_tokens,
|
||||
stop_sequences: stops,
|
||||
};
|
||||
}
|
||||
|
||||
function openaiToOpenaiText(req: Request) {
|
||||
const { body } = req;
|
||||
const result = OpenAIV1ChatCompletionSchema.safeParse(body);
|
||||
if (!result.success) {
|
||||
req.log.error(
|
||||
{ issues: result.error.issues, body },
|
||||
"Invalid OpenAI-to-OpenAI-text request"
|
||||
);
|
||||
throw result.error;
|
||||
}
|
||||
|
||||
const { messages, ...rest } = result.data;
|
||||
const prompt = flattenOpenAiChatMessages(messages);
|
||||
|
||||
let stops = rest.stop
|
||||
? Array.isArray(rest.stop)
|
||||
? rest.stop
|
||||
: [rest.stop]
|
||||
: [];
|
||||
stops.push("\n\nUser:");
|
||||
stops = [...new Set(stops)];
|
||||
|
||||
const transformed = { ...rest, prompt: prompt, stop: stops };
|
||||
const validated = OpenAIV1TextCompletionSchema.parse(transformed);
|
||||
return validated;
|
||||
}
|
||||
|
||||
function openaiToPalm(req: Request): z.infer<typeof PalmV1GenerateTextSchema> {
|
||||
const { body } = req;
|
||||
const result = OpenAIV1ChatCompletionSchema.safeParse({
|
||||
...body,
|
||||
model: "text-bison-001",
|
||||
});
|
||||
if (!result.success) {
|
||||
req.log.error(
|
||||
{ issues: result.error.issues, body },
|
||||
"Invalid OpenAI-to-Palm request"
|
||||
);
|
||||
throw result.error;
|
||||
}
|
||||
|
||||
const { messages, ...rest } = result.data;
|
||||
const prompt = flattenOpenAiChatMessages(messages);
|
||||
|
||||
let stops = rest.stop
|
||||
? Array.isArray(rest.stop)
|
||||
? rest.stop
|
||||
: [rest.stop]
|
||||
: [];
|
||||
|
||||
stops.push("\n\nUser:");
|
||||
stops = [...new Set(stops)];
|
||||
|
||||
z.array(z.string()).max(5).parse(stops);
|
||||
|
||||
return {
|
||||
prompt: { text: prompt },
|
||||
maxOutputTokens: rest.max_tokens,
|
||||
stopSequences: stops,
|
||||
model: "text-bison-001",
|
||||
topP: rest.top_p,
|
||||
temperature: rest.temperature,
|
||||
safetySettings: [
|
||||
{ category: "HARM_CATEGORY_UNSPECIFIED", threshold: "BLOCK_NONE" },
|
||||
{ category: "HARM_CATEGORY_DEROGATORY", threshold: "BLOCK_NONE" },
|
||||
{ category: "HARM_CATEGORY_TOXICITY", threshold: "BLOCK_NONE" },
|
||||
{ category: "HARM_CATEGORY_VIOLENCE", threshold: "BLOCK_NONE" },
|
||||
{ category: "HARM_CATEGORY_SEXUAL", threshold: "BLOCK_NONE" },
|
||||
{ category: "HARM_CATEGORY_MEDICAL", threshold: "BLOCK_NONE" },
|
||||
{ category: "HARM_CATEGORY_DANGEROUS", threshold: "BLOCK_NONE" },
|
||||
],
|
||||
};
|
||||
}
|
||||
|
||||
export function openAIMessagesToClaudePrompt(messages: OpenAIPromptMessage[]) {
|
||||
return (
|
||||
messages
|
||||
.map((m) => {
|
||||
let role: string = m.role;
|
||||
if (role === "assistant") {
|
||||
role = "Assistant";
|
||||
} else if (role === "system") {
|
||||
role = "System";
|
||||
} else if (role === "user") {
|
||||
role = "Human";
|
||||
}
|
||||
// https://console.anthropic.com/docs/prompt-design
|
||||
// `name` isn't supported by Anthropic but we can still try to use it.
|
||||
return `\n\n${role}: ${m.name?.trim() ? `(as ${m.name}) ` : ""}${
|
||||
m.content
|
||||
}`;
|
||||
})
|
||||
.join("") + "\n\nAssistant:"
|
||||
);
|
||||
}
|
||||
|
||||
function flattenOpenAiChatMessages(messages: OpenAIPromptMessage[]) {
|
||||
// Temporary to allow experimenting with prompt strategies
|
||||
const PROMPT_VERSION: number = 1;
|
||||
switch (PROMPT_VERSION) {
|
||||
case 1:
|
||||
return (
|
||||
messages
|
||||
.map((m) => {
|
||||
// Claude-style human/assistant turns
|
||||
let role: string = m.role;
|
||||
if (role === "assistant") {
|
||||
role = "Assistant";
|
||||
} else if (role === "system") {
|
||||
role = "System";
|
||||
} else if (role === "user") {
|
||||
role = "User";
|
||||
}
|
||||
return `\n\n${role}: ${m.content}`;
|
||||
})
|
||||
.join("") + "\n\nAssistant:"
|
||||
);
|
||||
case 2:
|
||||
return messages
|
||||
.map((m) => {
|
||||
// Claude without prefixes (except system) and no Assistant priming
|
||||
let role: string = "";
|
||||
if (role === "system") {
|
||||
role = "System: ";
|
||||
}
|
||||
return `\n\n${role}${m.content}`;
|
||||
})
|
||||
.join("");
|
||||
default:
|
||||
throw new Error(`Unknown prompt version: ${PROMPT_VERSION}`);
|
||||
}
|
||||
}
|
||||
@@ -1,36 +0,0 @@
|
||||
import util from "util";
|
||||
import zlib from "zlib";
|
||||
import { PassThrough } from "stream";
|
||||
|
||||
const BUFFER_DECODER_MAP = {
|
||||
gzip: util.promisify(zlib.gunzip),
|
||||
deflate: util.promisify(zlib.inflate),
|
||||
br: util.promisify(zlib.brotliDecompress),
|
||||
text: (data: Buffer) => data,
|
||||
};
|
||||
|
||||
const STREAM_DECODER_MAP = {
|
||||
gzip: zlib.createGunzip,
|
||||
deflate: zlib.createInflate,
|
||||
br: zlib.createBrotliDecompress,
|
||||
text: () => new PassThrough(),
|
||||
};
|
||||
|
||||
type SupportedContentEncoding = keyof typeof BUFFER_DECODER_MAP;
|
||||
const isSupportedContentEncoding = (
|
||||
encoding: string
|
||||
): encoding is SupportedContentEncoding => encoding in BUFFER_DECODER_MAP;
|
||||
|
||||
export async function decompressBuffer(buf: Buffer, encoding: string = "text") {
|
||||
if (isSupportedContentEncoding(encoding)) {
|
||||
return (await BUFFER_DECODER_MAP[encoding](buf)).toString();
|
||||
}
|
||||
throw new Error(`Unsupported content-encoding: ${encoding}`);
|
||||
}
|
||||
|
||||
export function getStreamDecompressor(encoding: string = "text") {
|
||||
if (isSupportedContentEncoding(encoding)) {
|
||||
return STREAM_DECODER_MAP[encoding]();
|
||||
}
|
||||
throw new Error(`Unsupported content-encoding: ${encoding}`);
|
||||
}
|
||||
@@ -1,405 +0,0 @@
|
||||
import express from "express";
|
||||
import { APIFormat } from "../../../shared/key-management";
|
||||
import { assertNever } from "../../../shared/utils";
|
||||
import { initializeSseStream } from "../../../shared/streaming";
|
||||
import http from "http";
|
||||
|
||||
/**
|
||||
* Returns a Markdown-formatted message that renders semi-nicely in most chat
|
||||
* frontends. For example:
|
||||
*
|
||||
* **Proxy error (HTTP 404 Not Found)**
|
||||
* The proxy encountered an error while trying to send your prompt to the upstream service. Further technical details are provided below.
|
||||
* ***
|
||||
* *The requested Claude model might not exist, or the key might not be provisioned for it.*
|
||||
* ```
|
||||
* {
|
||||
* "type": "error",
|
||||
* "error": {
|
||||
* "type": "not_found_error",
|
||||
* "message": "model: some-invalid-model-id",
|
||||
* },
|
||||
* "proxy_note": "The requested Claude model might not exist, or the key might not be provisioned for it."
|
||||
* }
|
||||
* ```
|
||||
*/
|
||||
function getMessageContent(params: {
|
||||
title: string;
|
||||
message: string;
|
||||
obj?: Record<string, any>;
|
||||
}) {
|
||||
const { title, message, obj } = params;
|
||||
const note = obj?.proxy_note || obj?.error?.message || "";
|
||||
const header = `### **${title}**`;
|
||||
const friendlyMessage = note ? `${message}\n\n----\n\n*${note}*` : message;
|
||||
|
||||
const serializedObj = obj
|
||||
? ["```", JSON.stringify(obj, null, 2), "```"].join("\n")
|
||||
: "";
|
||||
|
||||
const { stack } = JSON.parse(JSON.stringify(obj ?? {}));
|
||||
let prettyTrace = "";
|
||||
if (stack && obj) {
|
||||
prettyTrace = [
|
||||
"Include this trace when reporting an issue.",
|
||||
"```",
|
||||
stack,
|
||||
"```",
|
||||
].join("\n");
|
||||
delete obj.stack;
|
||||
}
|
||||
|
||||
return [
|
||||
header,
|
||||
friendlyMessage,
|
||||
serializedObj,
|
||||
prettyTrace,
|
||||
"<!-- oai-proxy-error -->",
|
||||
].join("\n\n");
|
||||
}
|
||||
|
||||
type ErrorGeneratorOptions = {
|
||||
format: APIFormat | "unknown";
|
||||
title: string;
|
||||
message: string;
|
||||
obj?: Record<string, any>;
|
||||
reqId: string | number | object;
|
||||
model?: string;
|
||||
statusCode?: number;
|
||||
};
|
||||
|
||||
/**
|
||||
* Very crude inference of the request format based on the request body. Don't
|
||||
* rely on this to be very accurate.
|
||||
*/
|
||||
function tryInferFormat(body: any): APIFormat | "unknown" {
|
||||
if (typeof body !== "object" || !body.model) {
|
||||
return "unknown";
|
||||
}
|
||||
|
||||
if (body.model.includes("gpt")) {
|
||||
return "openai";
|
||||
}
|
||||
|
||||
if (body.model.includes("mistral")) {
|
||||
return "mistral-ai";
|
||||
}
|
||||
|
||||
if (body.model.includes("claude")) {
|
||||
return body.messages?.length ? "anthropic-chat" : "anthropic-text";
|
||||
}
|
||||
|
||||
if (body.model.includes("gemini")) {
|
||||
return "google-ai";
|
||||
}
|
||||
|
||||
return "unknown";
|
||||
}
|
||||
|
||||
/**
|
||||
* Redacts the hostname from the error message if it contains a DNS resolution
|
||||
* error. This is to avoid leaking upstream hostnames on DNS resolution errors,
|
||||
* as those may contain sensitive information about the proxy's configuration.
|
||||
*/
|
||||
function redactHostname(options: ErrorGeneratorOptions): ErrorGeneratorOptions {
|
||||
if (!options.message.includes("getaddrinfo")) return options;
|
||||
|
||||
const redacted = { ...options };
|
||||
redacted.message = "Could not resolve hostname";
|
||||
|
||||
if (typeof redacted.obj?.error === "object") {
|
||||
redacted.obj = {
|
||||
...redacted.obj,
|
||||
error: { message: "Could not resolve hostname" },
|
||||
};
|
||||
}
|
||||
|
||||
return redacted;
|
||||
}
|
||||
|
||||
/**
|
||||
* Generates an appropriately-formatted error response and sends it to the
|
||||
* client over their requested transport (blocking or SSE stream).
|
||||
*/
|
||||
export function sendErrorToClient(params: {
|
||||
options: ErrorGeneratorOptions;
|
||||
req: express.Request;
|
||||
res: express.Response;
|
||||
}) {
|
||||
const { req, res } = params;
|
||||
const options = redactHostname(params.options);
|
||||
const { statusCode, message, title, obj: details } = options;
|
||||
|
||||
// Since we want to send the error in a format the client understands, we
|
||||
// need to know the request format. `setApiFormat` might not have been called
|
||||
// yet, so we'll try to infer it from the request body.
|
||||
const format =
|
||||
options.format === "unknown" ? tryInferFormat(req.body) : options.format;
|
||||
if (format === "unknown") {
|
||||
// Early middleware error (auth, rate limit) so we can only send something
|
||||
// generic.
|
||||
const code = statusCode || 400;
|
||||
const hasDetails = details && Object.keys(details).length > 0;
|
||||
return res.status(code).json({
|
||||
error: {
|
||||
message,
|
||||
type: http.STATUS_CODES[code]!.replace(/\s+/g, "_").toLowerCase(),
|
||||
},
|
||||
...(hasDetails ? { details } : {}),
|
||||
});
|
||||
}
|
||||
|
||||
// Cannot modify headers if client opted into streaming and made it into the
|
||||
// proxy request queue, because that immediately starts an SSE stream.
|
||||
if (!res.headersSent) {
|
||||
res.setHeader("x-oai-proxy-error", title);
|
||||
res.setHeader("x-oai-proxy-error-status", statusCode || 500);
|
||||
}
|
||||
|
||||
// By this point, we know the request format. To get the error to display in
|
||||
// chat clients' UIs, we'll send it as a 200 response as a spoofed completion
|
||||
// from the language model. Depending on whether the client is streaming, we
|
||||
// will either send an SSE event or a JSON response.
|
||||
const isStreaming = req.isStreaming || String(req.body.stream) === "true";
|
||||
if (isStreaming) {
|
||||
// User can have opted into streaming but not made it into the queue yet,
|
||||
// in which case the stream must be started first.
|
||||
if (!res.headersSent) {
|
||||
initializeSseStream(res);
|
||||
}
|
||||
res.write(buildSpoofedSSE({ ...options, format }));
|
||||
res.write(`data: [DONE]\n\n`);
|
||||
res.end();
|
||||
} else {
|
||||
res.status(200).json(buildSpoofedCompletion({ ...options, format }));
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Returns a non-streaming completion object that looks like it came from the
|
||||
* service that the request is being proxied to. Used to send error messages to
|
||||
* the client and have them look like normal responses, for clients with poor
|
||||
* error handling.
|
||||
*/
|
||||
export function buildSpoofedCompletion({
|
||||
format,
|
||||
title,
|
||||
message,
|
||||
obj,
|
||||
reqId,
|
||||
model = "unknown",
|
||||
}: ErrorGeneratorOptions & { format: Exclude<APIFormat, "unknown"> }) {
|
||||
const id = String(reqId);
|
||||
const content = getMessageContent({ title, message, obj });
|
||||
|
||||
switch (format) {
|
||||
case "openai":
|
||||
case "mistral-ai":
|
||||
return {
|
||||
id: "error-" + id,
|
||||
object: "chat.completion",
|
||||
created: Date.now(),
|
||||
model,
|
||||
usage: { prompt_tokens: 0, completion_tokens: 0, total_tokens: 0 },
|
||||
choices: [
|
||||
{
|
||||
message: { role: "assistant", content },
|
||||
finish_reason: title,
|
||||
index: 0,
|
||||
},
|
||||
],
|
||||
};
|
||||
case "mistral-text":
|
||||
return {
|
||||
outputs: [{ text: content, stop_reason: title }],
|
||||
model,
|
||||
};
|
||||
case "openai-text":
|
||||
return {
|
||||
id: "error-" + id,
|
||||
object: "text_completion",
|
||||
created: Date.now(),
|
||||
model,
|
||||
usage: { prompt_tokens: 0, completion_tokens: 0, total_tokens: 0 },
|
||||
choices: [
|
||||
{ text: content, index: 0, logprobs: null, finish_reason: title },
|
||||
],
|
||||
};
|
||||
case "anthropic-text":
|
||||
return {
|
||||
id: "error-" + id,
|
||||
type: "completion",
|
||||
completion: content,
|
||||
stop_reason: title,
|
||||
stop: null,
|
||||
model,
|
||||
};
|
||||
case "anthropic-chat":
|
||||
return {
|
||||
id: "error-" + id,
|
||||
type: "message",
|
||||
role: "assistant",
|
||||
content: [{ type: "text", text: content }],
|
||||
model,
|
||||
stop_reason: title,
|
||||
stop_sequence: null,
|
||||
};
|
||||
case "google-ai":
|
||||
return {
|
||||
candidates: [
|
||||
{
|
||||
content: { parts: [{ text: content }], role: "model" },
|
||||
finishReason: title,
|
||||
index: 0,
|
||||
tokenCount: null,
|
||||
safetyRatings: [],
|
||||
},
|
||||
],
|
||||
};
|
||||
case "openai-image":
|
||||
return obj;
|
||||
default:
|
||||
assertNever(format);
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Returns an SSE message that looks like a completion event for the service
|
||||
* that the request is being proxied to. Used to send error messages to the
|
||||
* client in the middle of a streaming request.
|
||||
*/
|
||||
export function buildSpoofedSSE({
|
||||
format,
|
||||
title,
|
||||
message,
|
||||
obj,
|
||||
reqId,
|
||||
model = "unknown",
|
||||
}: ErrorGeneratorOptions & { format: Exclude<APIFormat, "unknown"> }) {
|
||||
const id = String(reqId);
|
||||
const content = getMessageContent({ title, message, obj });
|
||||
|
||||
let event;
|
||||
|
||||
switch (format) {
|
||||
case "openai":
|
||||
case "mistral-ai":
|
||||
event = {
|
||||
id: "chatcmpl-" + id,
|
||||
object: "chat.completion.chunk",
|
||||
created: Date.now(),
|
||||
model,
|
||||
choices: [{ delta: { content }, index: 0, finish_reason: title }],
|
||||
};
|
||||
break;
|
||||
case "mistral-text":
|
||||
event = {
|
||||
outputs: [{ text: content, stop_reason: title }],
|
||||
};
|
||||
break;
|
||||
case "openai-text":
|
||||
event = {
|
||||
id: "cmpl-" + id,
|
||||
object: "text_completion",
|
||||
created: Date.now(),
|
||||
choices: [
|
||||
{ text: content, index: 0, logprobs: null, finish_reason: title },
|
||||
],
|
||||
model,
|
||||
};
|
||||
break;
|
||||
case "anthropic-text":
|
||||
event = {
|
||||
completion: content,
|
||||
stop_reason: title,
|
||||
truncated: false,
|
||||
stop: null,
|
||||
model,
|
||||
log_id: "proxy-req-" + id,
|
||||
};
|
||||
break;
|
||||
case "anthropic-chat":
|
||||
event = {
|
||||
type: "content_block_delta",
|
||||
index: 0,
|
||||
delta: { type: "text_delta", text: content },
|
||||
};
|
||||
break;
|
||||
case "google-ai":
|
||||
// TODO: google ai supports two streaming transports, SSE and JSON.
|
||||
// we currently only support SSE.
|
||||
// return JSON.stringify({
|
||||
event = {
|
||||
candidates: [
|
||||
{
|
||||
content: { parts: [{ text: content }], role: "model" },
|
||||
finishReason: title,
|
||||
index: 0,
|
||||
tokenCount: null,
|
||||
safetyRatings: [],
|
||||
},
|
||||
],
|
||||
};
|
||||
break;
|
||||
case "openai-image":
|
||||
return JSON.stringify(obj);
|
||||
default:
|
||||
assertNever(format);
|
||||
}
|
||||
|
||||
if (format === "anthropic-text") {
|
||||
return (
|
||||
["event: completion", `data: ${JSON.stringify(event)}`].join("\n") +
|
||||
"\n\n"
|
||||
);
|
||||
}
|
||||
|
||||
// ugh.
|
||||
if (format === "anthropic-chat") {
|
||||
return (
|
||||
[
|
||||
[
|
||||
"event: message_start",
|
||||
`data: ${JSON.stringify({
|
||||
type: "message_start",
|
||||
message: {
|
||||
id: "error-" + id,
|
||||
type: "message",
|
||||
role: "assistant",
|
||||
content: [],
|
||||
model,
|
||||
},
|
||||
})}`,
|
||||
].join("\n"),
|
||||
[
|
||||
"event: content_block_start",
|
||||
`data: ${JSON.stringify({
|
||||
type: "content_block_start",
|
||||
index: 0,
|
||||
content_block: { type: "text", text: "" },
|
||||
})}`,
|
||||
].join("\n"),
|
||||
["event: content_block_delta", `data: ${JSON.stringify(event)}`].join(
|
||||
"\n"
|
||||
),
|
||||
[
|
||||
"event: content_block_stop",
|
||||
`data: ${JSON.stringify({ type: "content_block_stop", index: 0 })}`,
|
||||
].join("\n"),
|
||||
[
|
||||
"event: message_delta",
|
||||
`data: ${JSON.stringify({
|
||||
type: "message_delta",
|
||||
delta: { stop_reason: title, stop_sequence: null, usage: null },
|
||||
})}`,
|
||||
],
|
||||
[
|
||||
"event: message_stop",
|
||||
`data: ${JSON.stringify({ type: "message_stop" })}`,
|
||||
].join("\n"),
|
||||
].join("\n\n") + "\n\n"
|
||||
);
|
||||
}
|
||||
|
||||
return `data: ${JSON.stringify(event)}\n\n`;
|
||||
}
|
||||
@@ -1,70 +0,0 @@
|
||||
import { sendProxyError } from "../common";
|
||||
import type { RawResponseBodyHandler } from "./index";
|
||||
import { decompressBuffer } from "./compression";
|
||||
|
||||
/**
|
||||
* Handles the response from the upstream service and decodes the body if
|
||||
* necessary. If the response is JSON, it will be parsed and returned as an
|
||||
* object. Otherwise, it will be returned as a string. Does not handle streaming
|
||||
* responses.
|
||||
* @throws {Error} Unsupported content-encoding or invalid application/json body
|
||||
*/
|
||||
export const handleBlockingResponse: RawResponseBodyHandler = async (
|
||||
proxyRes,
|
||||
req,
|
||||
res
|
||||
) => {
|
||||
if (req.isStreaming) {
|
||||
const err = new Error(
|
||||
"handleBlockingResponse called for a streaming request."
|
||||
);
|
||||
req.log.error({ stack: err.stack, api: req.inboundApi }, err.message);
|
||||
throw err;
|
||||
}
|
||||
|
||||
return new Promise((resolve, reject) => {
|
||||
let chunks: Buffer[] = [];
|
||||
proxyRes.on("data", (chunk) => chunks.push(chunk));
|
||||
proxyRes.on("end", async () => {
|
||||
const contentEncoding = proxyRes.headers["content-encoding"];
|
||||
const contentType = proxyRes.headers["content-type"];
|
||||
let body: string | Buffer = Buffer.concat(chunks);
|
||||
const rejectWithMessage = function (msg: string, err: Error) {
|
||||
const error = `${msg} (${err.message})`;
|
||||
req.log.warn(
|
||||
{ msg: error, stack: err.stack },
|
||||
"Error in blocking response handler"
|
||||
);
|
||||
sendProxyError(req, res, 500, "Internal Server Error", { error });
|
||||
return reject(error);
|
||||
};
|
||||
|
||||
try {
|
||||
body = await decompressBuffer(body, contentEncoding);
|
||||
} catch (e) {
|
||||
return rejectWithMessage(`Could not decode response body`, e);
|
||||
}
|
||||
|
||||
try {
|
||||
return resolve(tryParseAsJson(body, contentType));
|
||||
} catch (e) {
|
||||
return rejectWithMessage("API responded with invalid JSON", e);
|
||||
}
|
||||
});
|
||||
});
|
||||
};
|
||||
|
||||
function tryParseAsJson(body: string, contentType?: string) {
|
||||
// If the response is declared as JSON, it must parse or we will throw
|
||||
if (contentType?.includes("application/json")) {
|
||||
return JSON.parse(body);
|
||||
}
|
||||
// If it's not declared as JSON, some APIs we'll try to parse it as JSON
|
||||
// anyway since some APIs return the wrong content-type header in some cases.
|
||||
// If it fails to parse, we'll just return the raw body without throwing.
|
||||
try {
|
||||
return JSON.parse(body);
|
||||
} catch (e) {
|
||||
return body;
|
||||
}
|
||||
}
|
||||
@@ -1,194 +1,410 @@
|
||||
import express from "express";
|
||||
import { pipeline, Readable, Transform } from "stream";
|
||||
import { StringDecoder } from "string_decoder";
|
||||
import { promisify } from "util";
|
||||
import type { logger } from "../../../logger";
|
||||
import { BadRequestError, RetryableError } from "../../../shared/errors";
|
||||
import { APIFormat, keyPool } from "../../../shared/key-management";
|
||||
import {
|
||||
copySseResponseHeaders,
|
||||
initializeSseStream,
|
||||
} from "../../../shared/streaming";
|
||||
import { reenqueueRequest } from "../../queue";
|
||||
import type { RawResponseBodyHandler } from ".";
|
||||
import { handleBlockingResponse } from "./handle-blocking-response";
|
||||
import { buildSpoofedSSE, sendErrorToClient } from "./error-generator";
|
||||
import { getAwsEventStreamDecoder } from "./streaming/aws-event-stream-decoder";
|
||||
import { EventAggregator } from "./streaming/event-aggregator";
|
||||
import { SSEMessageTransformer } from "./streaming/sse-message-transformer";
|
||||
import { SSEStreamAdapter } from "./streaming/sse-stream-adapter";
|
||||
import { getStreamDecompressor } from "./compression";
|
||||
import { Request, Response } from "express";
|
||||
import * as http from "http";
|
||||
import { buildFakeSseMessage } from "../common";
|
||||
import { RawResponseBodyHandler, decodeResponseBody } from ".";
|
||||
import { assertNever } from "../../../shared/utils";
|
||||
|
||||
const pipelineAsync = promisify(pipeline);
|
||||
type OpenAiChatCompletionResponse = {
|
||||
id: string;
|
||||
object: string;
|
||||
created: number;
|
||||
model: string;
|
||||
choices: {
|
||||
message: { role: string; content: string };
|
||||
finish_reason: string | null;
|
||||
index: number;
|
||||
}[];
|
||||
};
|
||||
|
||||
type OpenAiTextCompletionResponse = {
|
||||
id: string;
|
||||
object: string;
|
||||
created: number;
|
||||
model: string;
|
||||
choices: {
|
||||
text: string;
|
||||
finish_reason: string | null;
|
||||
index: number;
|
||||
logprobs: null;
|
||||
}[];
|
||||
};
|
||||
|
||||
type AnthropicCompletionResponse = {
|
||||
completion: string;
|
||||
stop_reason: string;
|
||||
truncated: boolean;
|
||||
stop: any;
|
||||
model: string;
|
||||
log_id: string;
|
||||
exception: null;
|
||||
};
|
||||
|
||||
/**
|
||||
* `handleStreamedResponse` consumes a streamed response from the upstream API,
|
||||
* decodes chunk-by-chunk into a stream of events, transforms those events into
|
||||
* the client's requested format, and forwards the result to the client.
|
||||
* Consume the SSE stream and forward events to the client. Once the stream is
|
||||
* stream is closed, resolve with the full response body so that subsequent
|
||||
* middleware can work with it.
|
||||
*
|
||||
* After the entire stream has been consumed, it resolves with the full response
|
||||
* body so that subsequent middleware in the chain can process it as if it were
|
||||
* a non-streaming response (to count output tokens, track usage, etc).
|
||||
* Typically we would only need of the raw response handlers to execute, but
|
||||
* in the event a streamed request results in a non-200 response, we need to
|
||||
* fall back to the non-streaming response handler so that the error handler
|
||||
* can inspect the error response.
|
||||
*
|
||||
* In the event of an error, the request's streaming flag is unset and the
|
||||
* request is bounced back to the non-streaming response handler. If the error
|
||||
* is retryable, that handler will re-enqueue the request and also reset the
|
||||
* streaming flag. Unfortunately the streaming flag is set and unset in multiple
|
||||
* places, so it's hard to keep track of.
|
||||
* Currently most frontends don't support Anthropic streaming, so users can opt
|
||||
* to send requests for Claude models via an endpoint that accepts OpenAI-
|
||||
* compatible requests and translates the received Anthropic SSE events into
|
||||
* OpenAI ones, essentially pretending to be an OpenAI streaming API.
|
||||
*/
|
||||
export const handleStreamedResponse: RawResponseBodyHandler = async (
|
||||
proxyRes,
|
||||
req,
|
||||
res
|
||||
) => {
|
||||
const { headers, statusCode } = proxyRes;
|
||||
// If these differ, the user is using the OpenAI-compatibile endpoint, so
|
||||
// we need to translate the SSE events into OpenAI completion events for their
|
||||
// frontend.
|
||||
if (!req.isStreaming) {
|
||||
throw new Error("handleStreamedResponse called for non-streaming request.");
|
||||
const err = new Error(
|
||||
"handleStreamedResponse called for non-streaming request."
|
||||
);
|
||||
req.log.error({ stack: err.stack, api: req.inboundApi }, err.message);
|
||||
throw err;
|
||||
}
|
||||
|
||||
if (statusCode! > 201) {
|
||||
const key = req.key!;
|
||||
if (proxyRes.statusCode !== 200) {
|
||||
// Ensure we use the non-streaming middleware stack since we won't be
|
||||
// getting any events.
|
||||
req.isStreaming = false;
|
||||
req.log.warn(
|
||||
{ statusCode },
|
||||
{ statusCode: proxyRes.statusCode, key: key.hash },
|
||||
`Streaming request returned error status code. Falling back to non-streaming response handler.`
|
||||
);
|
||||
return handleBlockingResponse(proxyRes, req, res);
|
||||
return decodeResponseBody(proxyRes, req, res);
|
||||
}
|
||||
|
||||
req.log.debug({ headers }, `Starting to proxy SSE stream.`);
|
||||
return new Promise((resolve, reject) => {
|
||||
req.log.info({ key: key.hash }, `Starting to proxy SSE stream.`);
|
||||
|
||||
// Typically, streaming will have already been initialized by the request
|
||||
// queue to send heartbeat pings.
|
||||
if (!res.headersSent) {
|
||||
copySseResponseHeaders(proxyRes, res);
|
||||
initializeSseStream(res);
|
||||
}
|
||||
// Queued streaming requests will already have a connection open and headers
|
||||
// sent due to the heartbeat handler. In that case we can just start
|
||||
// streaming the response without sending headers.
|
||||
if (!res.headersSent) {
|
||||
res.setHeader("Content-Type", "text/event-stream");
|
||||
res.setHeader("Cache-Control", "no-cache");
|
||||
res.setHeader("Connection", "keep-alive");
|
||||
res.setHeader("X-Accel-Buffering", "no");
|
||||
copyHeaders(proxyRes, res);
|
||||
res.flushHeaders();
|
||||
}
|
||||
|
||||
const prefersNativeEvents = req.inboundApi === req.outboundApi;
|
||||
const streamOptions = {
|
||||
contentType: headers["content-type"],
|
||||
api: req.outboundApi,
|
||||
logger: req.log,
|
||||
};
|
||||
const originalEvents: string[] = [];
|
||||
let partialMessage = "";
|
||||
let lastPosition = 0;
|
||||
let eventCount = 0;
|
||||
|
||||
// While the request is streaming, aggregator collects all events so that we
|
||||
// can compile them into a single response object and publish that to the
|
||||
// remaining middleware. Because we have an OpenAI transformer for every
|
||||
// supported format, EventAggregator always consumes OpenAI events so that we
|
||||
// only have to write one aggregator (OpenAI input) for each output format.
|
||||
const aggregator = new EventAggregator(req);
|
||||
type ProxyResHandler<T extends unknown> = (...args: T[]) => void;
|
||||
function withErrorHandling<T extends unknown>(fn: ProxyResHandler<T>) {
|
||||
return (...args: T[]) => {
|
||||
try {
|
||||
fn(...args);
|
||||
} catch (error) {
|
||||
proxyRes.emit("error", error);
|
||||
}
|
||||
};
|
||||
}
|
||||
|
||||
const decompressor = getStreamDecompressor(headers["content-encoding"]);
|
||||
// Decoder reads from the response bytes to produce a stream of plaintext.
|
||||
const decoder = getDecoder({ ...streamOptions, input: proxyRes });
|
||||
// Adapter consumes the decoded text and produces server-sent events so we
|
||||
// have a standard event format for the client and to translate between API
|
||||
// message formats.
|
||||
const adapter = new SSEStreamAdapter(streamOptions);
|
||||
// Transformer converts server-sent events from one vendor's API message
|
||||
// format to another.
|
||||
const transformer = new SSEMessageTransformer({
|
||||
inputFormat: req.outboundApi, // The format of the upstream service's events
|
||||
outputFormat: req.inboundApi, // The format the client requested
|
||||
inputApiVersion: String(req.headers["anthropic-version"]),
|
||||
logger: req.log,
|
||||
requestId: String(req.id),
|
||||
requestedModel: req.body.model,
|
||||
})
|
||||
.on("originalMessage", (msg: string) => {
|
||||
if (prefersNativeEvents) res.write(msg);
|
||||
})
|
||||
.on("data", (msg) => {
|
||||
if (!prefersNativeEvents) res.write(`data: ${JSON.stringify(msg)}\n\n`);
|
||||
aggregator.addEvent(msg);
|
||||
});
|
||||
proxyRes.on(
|
||||
"data",
|
||||
withErrorHandling((chunk: Buffer) => {
|
||||
// We may receive multiple (or partial) SSE messages in a single chunk,
|
||||
// so we need to buffer and emit seperate stream events for full
|
||||
// messages so we can parse/transform them properly.
|
||||
const str = chunk.toString();
|
||||
|
||||
try {
|
||||
await Promise.race([
|
||||
handleAbortedStream(req, res),
|
||||
pipelineAsync(proxyRes, decompressor, decoder, adapter, transformer),
|
||||
]);
|
||||
req.log.debug(`Finished proxying SSE stream.`);
|
||||
res.end();
|
||||
return aggregator.getFinalResponse();
|
||||
} catch (err) {
|
||||
if (err instanceof RetryableError) {
|
||||
keyPool.markRateLimited(req.key!);
|
||||
await reenqueueRequest(req);
|
||||
} else if (err instanceof BadRequestError) {
|
||||
sendErrorToClient({
|
||||
req,
|
||||
res,
|
||||
options: {
|
||||
format: req.inboundApi,
|
||||
title: "Proxy streaming error (Bad Request)",
|
||||
message: `The API returned an error while streaming your request. Your prompt might not be formatted correctly.\n\n*${err.message}*`,
|
||||
reqId: req.id,
|
||||
model: req.body?.model,
|
||||
},
|
||||
});
|
||||
} else {
|
||||
const { message, stack, lastEvent } = err;
|
||||
const eventText = JSON.stringify(lastEvent, null, 2) ?? "undefined";
|
||||
const errorEvent = buildSpoofedSSE({
|
||||
format: req.inboundApi,
|
||||
title: "Proxy stream error",
|
||||
message: "An unexpected error occurred while streaming the response.",
|
||||
obj: { message, stack, lastEvent: eventText },
|
||||
reqId: req.id,
|
||||
model: req.body?.model,
|
||||
});
|
||||
res.write(errorEvent);
|
||||
res.write(`data: [DONE]\n\n`);
|
||||
// Anthropic uses CRLF line endings (out-of-spec btw)
|
||||
const fullMessages = (partialMessage + str).split(/\r?\n\r?\n/);
|
||||
partialMessage = fullMessages.pop() || "";
|
||||
|
||||
for (const message of fullMessages) {
|
||||
proxyRes.emit("full-sse-event", message);
|
||||
}
|
||||
})
|
||||
);
|
||||
|
||||
proxyRes.on(
|
||||
"full-sse-event",
|
||||
withErrorHandling((data) => {
|
||||
originalEvents.push(data);
|
||||
const { event, position } = transformEvent({
|
||||
data,
|
||||
requestApi: req.inboundApi,
|
||||
responseApi: req.outboundApi,
|
||||
lastPosition,
|
||||
index: eventCount++,
|
||||
});
|
||||
lastPosition = position;
|
||||
res.write(event + "\n\n");
|
||||
})
|
||||
);
|
||||
|
||||
proxyRes.on(
|
||||
"end",
|
||||
withErrorHandling(() => {
|
||||
let finalBody = convertEventsToFinalResponse(originalEvents, req);
|
||||
req.log.info({ key: key.hash }, `Finished proxying SSE stream.`);
|
||||
res.end();
|
||||
resolve(finalBody);
|
||||
})
|
||||
);
|
||||
|
||||
proxyRes.on("error", (err) => {
|
||||
req.log.error({ error: err, key: key.hash }, `Mid-stream error.`);
|
||||
const fakeErrorEvent = buildFakeSseMessage(
|
||||
"mid-stream-error",
|
||||
err.message,
|
||||
req
|
||||
);
|
||||
res.write(`data: ${JSON.stringify(fakeErrorEvent)}\n\n`);
|
||||
res.write("data: [DONE]\n\n");
|
||||
res.end();
|
||||
}
|
||||
|
||||
// At this point the response is closed. If the request resulted in any
|
||||
// tokens being consumed (suggesting a mid-stream error), we will resolve
|
||||
// and continue the middleware chain so tokens can be counted.
|
||||
if (aggregator.hasEvents()) {
|
||||
return aggregator.getFinalResponse();
|
||||
} else {
|
||||
// If there is nothing, then this was a completely failed prompt that
|
||||
// will not have billed any tokens. Throw to stop the middleware chain.
|
||||
throw err;
|
||||
}
|
||||
}
|
||||
reject(err);
|
||||
});
|
||||
});
|
||||
};
|
||||
|
||||
function handleAbortedStream(req: express.Request, res: express.Response) {
|
||||
return new Promise<void>((resolve) =>
|
||||
res.on("close", () => {
|
||||
if (!res.writableEnded) {
|
||||
req.log.info("Client prematurely closed connection during stream.");
|
||||
}
|
||||
resolve();
|
||||
})
|
||||
);
|
||||
}
|
||||
type SSETransformationArgs = {
|
||||
data: string;
|
||||
requestApi: string;
|
||||
responseApi: string;
|
||||
lastPosition: number;
|
||||
index: number;
|
||||
};
|
||||
|
||||
function getDecoder(options: {
|
||||
input: Readable;
|
||||
api: APIFormat;
|
||||
logger: typeof logger;
|
||||
contentType?: string;
|
||||
}) {
|
||||
const { contentType, input, logger } = options;
|
||||
if (contentType?.includes("application/vnd.amazon.eventstream")) {
|
||||
return getAwsEventStreamDecoder({ input, logger });
|
||||
} else if (contentType?.includes("application/json")) {
|
||||
throw new Error("JSON streaming not supported, request SSE instead");
|
||||
} else {
|
||||
// Ensures split chunks across multi-byte characters are handled correctly.
|
||||
const stringDecoder = new StringDecoder("utf8");
|
||||
return new Transform({
|
||||
readableObjectMode: true,
|
||||
writableObjectMode: false,
|
||||
transform(chunk, _encoding, callback) {
|
||||
const text = stringDecoder.write(chunk);
|
||||
if (text) this.push(text);
|
||||
callback();
|
||||
},
|
||||
});
|
||||
/**
|
||||
* Transforms SSE events from the given response API into events compatible with
|
||||
* the API requested by the client.
|
||||
*/
|
||||
function transformEvent(params: SSETransformationArgs) {
|
||||
const { data, requestApi, responseApi } = params;
|
||||
if (requestApi === responseApi) {
|
||||
return { position: -1, event: data };
|
||||
}
|
||||
|
||||
const trans = `${requestApi}->${responseApi}`;
|
||||
switch (trans) {
|
||||
case "openai->openai-text":
|
||||
return transformOpenAITextEventToOpenAIChat(params);
|
||||
case "openai->anthropic":
|
||||
// TODO: handle new anthropic streaming format
|
||||
return transformV1AnthropicEventToOpenAI(params);
|
||||
case "openai->google-palm":
|
||||
return transformPalmEventToOpenAI(params);
|
||||
default:
|
||||
throw new Error(`Unsupported streaming API transformation. ${trans}`);
|
||||
}
|
||||
}
|
||||
|
||||
function transformOpenAITextEventToOpenAIChat(params: SSETransformationArgs) {
|
||||
const { data, index } = params;
|
||||
|
||||
if (!data.startsWith("data:")) return { position: -1, event: data };
|
||||
if (data.startsWith("data: [DONE]")) return { position: -1, event: data };
|
||||
|
||||
const event = JSON.parse(data.slice("data: ".length));
|
||||
|
||||
// The very first event must be a role assignment with no content.
|
||||
|
||||
const createEvent = () => ({
|
||||
id: event.id,
|
||||
object: "chat.completion.chunk",
|
||||
created: event.created,
|
||||
model: event.model,
|
||||
choices: [
|
||||
{
|
||||
message: { role: "", content: "" } as {
|
||||
role?: string;
|
||||
content: string;
|
||||
},
|
||||
index: 0,
|
||||
finish_reason: null,
|
||||
},
|
||||
],
|
||||
});
|
||||
|
||||
let buffer = "";
|
||||
|
||||
if (index === 0) {
|
||||
const initialEvent = createEvent();
|
||||
initialEvent.choices[0].message.role = "assistant";
|
||||
buffer = `data: ${JSON.stringify(initialEvent)}\n\n`;
|
||||
}
|
||||
|
||||
const newEvent = {
|
||||
...event,
|
||||
choices: [
|
||||
{
|
||||
...event.choices[0],
|
||||
delta: { content: event.choices[0].text },
|
||||
text: undefined,
|
||||
},
|
||||
],
|
||||
};
|
||||
|
||||
buffer += `data: ${JSON.stringify(newEvent)}`;
|
||||
|
||||
return { position: -1, event: buffer };
|
||||
}
|
||||
|
||||
function transformV1AnthropicEventToOpenAI(params: SSETransformationArgs) {
|
||||
const { data, lastPosition } = params;
|
||||
// Anthropic sends the full completion so far with each event whereas OpenAI
|
||||
// only sends the delta. To make the SSE events compatible, we remove
|
||||
// everything before `lastPosition` from the completion.
|
||||
if (!data.startsWith("data:")) {
|
||||
return { position: lastPosition, event: data };
|
||||
}
|
||||
|
||||
if (data.startsWith("data: [DONE]")) {
|
||||
return { position: lastPosition, event: data };
|
||||
}
|
||||
|
||||
const event = JSON.parse(data.slice("data: ".length));
|
||||
const newEvent = {
|
||||
id: "ant-" + event.log_id,
|
||||
object: "chat.completion.chunk",
|
||||
created: Date.now(),
|
||||
model: event.model,
|
||||
choices: [
|
||||
{
|
||||
index: 0,
|
||||
delta: { content: event.completion?.slice(lastPosition) },
|
||||
finish_reason: event.stop_reason,
|
||||
},
|
||||
],
|
||||
};
|
||||
return {
|
||||
position: event.completion.length,
|
||||
event: `data: ${JSON.stringify(newEvent)}`,
|
||||
};
|
||||
}
|
||||
|
||||
function transformPalmEventToOpenAI({ data }: SSETransformationArgs) {
|
||||
throw new Error("PaLM streaming not yet supported.");
|
||||
return { position: -1, event: data };
|
||||
}
|
||||
|
||||
/** Copy headers, excluding ones we're already setting for the SSE response. */
|
||||
function copyHeaders(proxyRes: http.IncomingMessage, res: Response) {
|
||||
const toOmit = [
|
||||
"content-length",
|
||||
"content-encoding",
|
||||
"transfer-encoding",
|
||||
"content-type",
|
||||
"connection",
|
||||
"cache-control",
|
||||
];
|
||||
for (const [key, value] of Object.entries(proxyRes.headers)) {
|
||||
if (!toOmit.includes(key) && value) {
|
||||
res.setHeader(key, value);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Converts the list of incremental SSE events into an object that resembles a
|
||||
* full, non-streamed response from the API so that subsequent middleware can
|
||||
* operate on it as if it were a normal response.
|
||||
* Events are expected to be in the format they were received from the API.
|
||||
*/
|
||||
function convertEventsToFinalResponse(events: string[], req: Request) {
|
||||
switch (req.outboundApi) {
|
||||
case "openai": {
|
||||
let merged: OpenAiChatCompletionResponse = {
|
||||
id: "",
|
||||
object: "",
|
||||
created: 0,
|
||||
model: "",
|
||||
choices: [],
|
||||
};
|
||||
merged = events.reduce((acc, event, i) => {
|
||||
if (!event.startsWith("data: ")) return acc;
|
||||
if (event === "data: [DONE]") return acc;
|
||||
|
||||
const data = JSON.parse(event.slice("data: ".length));
|
||||
|
||||
// The first chat chunk only contains the role assignment and metadata
|
||||
if (i === 0) {
|
||||
return {
|
||||
id: data.id,
|
||||
object: data.object,
|
||||
created: data.created,
|
||||
model: data.model,
|
||||
choices: [
|
||||
{
|
||||
message: { role: data.choices[0].delta.role, content: "" },
|
||||
index: 0,
|
||||
finish_reason: null,
|
||||
},
|
||||
],
|
||||
};
|
||||
}
|
||||
|
||||
if (data.choices[0].delta.content) {
|
||||
acc.choices[0].message.content += data.choices[0].delta.content;
|
||||
}
|
||||
acc.choices[0].finish_reason = data.choices[0].finish_reason;
|
||||
return acc;
|
||||
}, merged);
|
||||
return merged;
|
||||
}
|
||||
case "openai-text": {
|
||||
let merged: OpenAiTextCompletionResponse = {
|
||||
id: "",
|
||||
object: "",
|
||||
created: 0,
|
||||
model: "",
|
||||
choices: [],
|
||||
// TODO: merge logprobs
|
||||
};
|
||||
merged = events.reduce((acc, event, i) => {
|
||||
if (!event.startsWith("data: ")) return acc;
|
||||
if (event === "data: [DONE]") return acc;
|
||||
|
||||
const data = JSON.parse(event.slice("data: ".length));
|
||||
|
||||
return {
|
||||
id: data.id,
|
||||
object: data.object,
|
||||
created: data.created,
|
||||
model: data.model,
|
||||
choices: [
|
||||
{
|
||||
text: acc.choices[0]?.text + data.choices[0].text,
|
||||
index: 0,
|
||||
finish_reason: data.choices[0].finish_reason,
|
||||
logprobs: null,
|
||||
},
|
||||
],
|
||||
};
|
||||
}, merged);
|
||||
return merged;
|
||||
}
|
||||
case "anthropic": {
|
||||
/*
|
||||
* Full complete responses from Anthropic are conveniently just the same as
|
||||
* the final SSE event before the "DONE" event, so we can reuse that
|
||||
*/
|
||||
const lastEvent = events[events.length - 2].toString();
|
||||
const data = JSON.parse(
|
||||
lastEvent.slice(lastEvent.indexOf("data: ") + "data: ".length)
|
||||
);
|
||||
const final: AnthropicCompletionResponse = { ...data, log_id: req.id };
|
||||
return final;
|
||||
}
|
||||
case "google-palm": {
|
||||
throw new Error("PaLM streaming not yet supported.");
|
||||
}
|
||||
default:
|
||||
assertNever(req.outboundApi);
|
||||
}
|
||||
}
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
@@ -1,81 +0,0 @@
|
||||
import { createHash } from "crypto";
|
||||
import { config } from "../../../config";
|
||||
import { eventLogger } from "../../../shared/prompt-logging";
|
||||
import { getModelFromBody, isTextGenerationRequest } from "../common";
|
||||
import { ProxyResHandlerWithBody } from ".";
|
||||
import {
|
||||
OpenAIChatMessage,
|
||||
AnthropicChatMessage,
|
||||
} from "../../../shared/api-schemas";
|
||||
|
||||
/** If event logging is enabled, logs a chat completion event. */
|
||||
export const logEvent: ProxyResHandlerWithBody = async (
|
||||
_proxyRes,
|
||||
req,
|
||||
_res,
|
||||
responseBody
|
||||
) => {
|
||||
if (!config.eventLogging) {
|
||||
return;
|
||||
}
|
||||
if (typeof responseBody !== "object") {
|
||||
throw new Error("Expected body to be an object");
|
||||
}
|
||||
if (!["openai", "anthropic-chat"].includes(req.outboundApi)) {
|
||||
// only chat apis are supported
|
||||
return;
|
||||
}
|
||||
if (!req.user) {
|
||||
return;
|
||||
}
|
||||
|
||||
const loggable = isTextGenerationRequest(req);
|
||||
if (!loggable) return;
|
||||
|
||||
const messages = req.body.messages as
|
||||
| OpenAIChatMessage[]
|
||||
| AnthropicChatMessage[];
|
||||
|
||||
let hashes = [];
|
||||
hashes.push(hashMessages(messages));
|
||||
for (
|
||||
let i = 1;
|
||||
i <= Math.min(config.eventLoggingTrim!, messages.length);
|
||||
i++
|
||||
) {
|
||||
hashes.push(hashMessages(messages.slice(0, -i)));
|
||||
}
|
||||
|
||||
const model = getModelFromBody(req, responseBody);
|
||||
const userToken = req.user!.token;
|
||||
const family = req.modelFamily!;
|
||||
eventLogger.logEvent({
|
||||
ip: req.ip,
|
||||
type: "chat_completion",
|
||||
model,
|
||||
family,
|
||||
hashes,
|
||||
userToken,
|
||||
inputTokens: req.promptTokens ?? 0,
|
||||
outputTokens: req.outputTokens ?? 0,
|
||||
});
|
||||
};
|
||||
|
||||
const hashMessages = (
|
||||
messages: OpenAIChatMessage[] | AnthropicChatMessage[]
|
||||
): string => {
|
||||
let hasher = createHash("sha256");
|
||||
let messageTexts = [];
|
||||
for (const msg of messages) {
|
||||
if (!["system", "user", "assistant"].includes(msg.role)) continue;
|
||||
if (typeof msg.content === "string") {
|
||||
messageTexts.push(msg.content);
|
||||
} else if (Array.isArray(msg.content)) {
|
||||
if (msg.content[0].type === "text") {
|
||||
messageTexts.push(msg.content[0].text);
|
||||
}
|
||||
}
|
||||
}
|
||||
hasher.update(messageTexts.join("<|im_sep|>"));
|
||||
return hasher.digest("hex");
|
||||
};
|
||||
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Reference in New Issue
Block a user