.env

# Use .env.local to change these variables
# DO NOT EDIT THIS FILE WITH SENSITIVE DATA

### MongoDB ###
MONGODB_URL=#your mongodb URL here, use chat-ui-db image if you don't want to set this
MONGODB_DB_NAME=chat-ui
MONGODB_DIRECT_CONNECTION=false


### Endpoints config ###
HF_API_ROOT=https://api-inference.huggingface.co/models

STRIPE_SECRET_KEY=T#Stripe key
STRIPE_PRICE_ID=#
STRIPE_WEBHOOK_SECRET=# 
STRIPE_BILLING_PORTAL=

# HF_TOKEN is used for a lot of things, not only for inference but also fetching tokenizers, etc.
# We recommend using an HF_TOKEN even if you use a local endpoint.
HF_TOKEN= #get it from https://huggingface.co/settings/token
# API Keys for providers, you will need to specify models in the MODELS section but these keys can be kept secret
OPENAI_API_KEY=#your openai api key here
ANTHROPIC_API_KEY=#your anthropic api key here
CLOUDFLARE_ACCOUNT_ID=#your cloudflare account id here
CLOUDFLARE_API_TOKEN=#your cloudflare api token here
COHERE_API_TOKEN=#your cohere api token here
GOOGLE_GENAI_API_KEY=#your google genai api token here


### Models ###
## Models can support many different endpoints, check the documentation for more details
MODELS=`[
      {
        "name": "meta-llama/Llama-3.3-70B-Instruct",
        "id": "meta-llama/Llama-3.3-70B-Instruct",
        "tokenizer": "nsarrazin/llama3.1-tokenizer",
        "description": "Ideal for everyday use. A fast and extremely capable model matching closed source models' capabilities. Now with the latest Llama 3.3 weights!",
        "modelUrl": "https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct",
        "websiteUrl": "https://llama.meta.com/",
        "logoUrl": "https://huggingface.co/datasets/huggingchat/models-logo/resolve/main/meta-logo.png",
        "tools": true,
        "preprompt": "",
        "parameters": {
          "stop": ["<|endoftext|>", "<|eot_id|>"],
          "temperature": 0.6,
          "max_new_tokens": 1024,
          "truncate": 7167
        },
        "promptExamples": [
          {
            "title": "Write an email from bullet list",
            "prompt": "As a restaurant owner, write a professional email to the supplier to get these products every week: \n\n- Wine (x10)\n- Eggs (x24)\n- Bread (x12)"
          },
          {
            "title": "Code a snake game",
            "prompt": "Code a basic snake game in python, give explanations for each step."
          },
          {
            "title": "Assist in a task",
            "prompt": "How do I make a delicious lemon cheesecake?"
          }
        ]
      },
      {
        "name": "Qwen/Qwen2.5-72B-Instruct",
        "description": "The latest Qwen open model with improved role-playing, long text generation and structured data understanding.",
        "modelUrl": "https://huggingface.co/Qwen/Qwen2.5-72B-Instruct",
        "websiteUrl": "https://qwenlm.github.io/blog/qwen2.5/",
        "logoUrl": "https://huggingface.co/datasets/huggingchat/models-logo/resolve/main/qwen-logo.png",
        "preprompt": "You are Qwen, created by Alibaba Cloud. You are a helpful assistant.",
        "parameters": {
          "stop": ["<|endoftext|>", "<|im_end|>"],
          "temperature": 0.6,
          "truncate": 28672,
          "max_new_tokens": 3072
        },
        "tools": true,
        "promptExamples": [
          {
            "title": "Write an email from bullet list",
            "prompt": "As a restaurant owner, write a professional email to the supplier to get these products every week: \n\n- Wine (x10)\n- Eggs (x24)\n- Bread (x12)"
          },
          {
            "title": "Code a snake game",
            "prompt": "Code a basic snake game in python, give explanations for each step."
          },
          {
            "title": "Assist in a task",
            "prompt": "How do I make a delicious lemon cheesecake?"
          }
        ]
      },
      {
        "name": "CohereForAI/c4ai-command-r-plus-08-2024",
        "description": "Cohere's largest language model, optimized for conversational interaction and tool use. Now with the 2024 update!",
        "modelUrl": "https://huggingface.co/CohereForAI/c4ai-command-r-plus-08-2024",
        "websiteUrl": "https://docs.cohere.com/docs/command-r-plus",
        "logoUrl": "https://huggingface.co/datasets/huggingchat/models-logo/resolve/main/cohere-logo.png",
        "tools": true,
        "parameters": {
          "stop": ["<|END_OF_TURN_TOKEN|>"],
          "truncate": 28672,
          "max_new_tokens": 2048,
          "temperature": 0.3
        },
        "promptExamples": [
          {
            "title": "Generate a mouse portrait",
            "prompt": "Generate the portrait of a scientific mouse in its laboratory."
          },
          {
            "title": "Review a pull request",
            "prompt": "Review this pull request: https://github.com/huggingface/chat-ui/pull/1131/files"
          },
          {
            "title": "Code a snake game",
            "prompt": "Code a basic snake game in python, give explanations for each step."
          }
        ]
      },
      {
        "name": "Qwen/QwQ-32B-Preview",
        "preprompt": "You are a helpful and harmless assistant. You are Qwen developed by Alibaba. You should think step-by-step.",
        "modelUrl": "https://huggingface.co/Qwen/QwQ-32B-Preview",
        "websiteUrl": "https://qwenlm.github.io/blog/qwq-32b-preview/",
        "logoUrl": "https://huggingface.co/datasets/huggingchat/models-logo/resolve/main/qwen-logo.png",
        "description": "QwQ is an experiment model from the Qwen Team with advanced reasoning capabilities.",
        "reasoning": {
          "type": "summarize"
        },
        "parameters": {
          "stop": ["<|im_end|>"],
          "truncate": 12288,
          "max_new_tokens": 4096,
          "temperature": 0.7,
          "top_k": 20,
          "top_p": 0.8,
          "repetition_penalty": 1.05
        },
        "promptExamples": [
          {
            "title": "Rs in strawberry",
            "prompt": "how many R in strawberry?"
          },
          {
            "title": "Larger number",
            "prompt": "9.11 or 9.9 which number is larger?"
          },
          {
            "title": "Measuring 6 liters",
            "prompt": "I have a 6- and a 12-liter jug. I want to measure exactly 6 liters."
          }
        ]
      },
      {
        "name": "nvidia/Llama-3.1-Nemotron-70B-Instruct-HF",
        "tokenizer": "nvidia/Llama-3.1-Nemotron-70B-Instruct-HF",
        "modelUrl": "https://huggingface.co/nvidia/Llama-3.1-Nemotron-70B-Instruct-HF",
        "websiteUrl": "https://www.nvidia.com/",
        "logoUrl": "https://huggingface.co/datasets/huggingchat/models-logo/resolve/main/nvidia-logo.png",
        "description": "Nvidia's latest Llama fine-tune, topping alignment benchmarks and optimized for instruction following.",
        "parameters": {
          "stop": ["<|eot_id|>", "<|im_end|>"],
          "temperature": 0.5,
          "truncate": 28672,
          "max_new_tokens": 2048
        },
        "promptExamples": [
          {
            "title": "Rs in strawberry",
            "prompt": "how many R in strawberry?"
          },
          {
            "title": "Larger number",
            "prompt": "9.11 or 9.9 which number is larger?"
          },
          {
            "title": "Measuring 6 liters",
            "prompt": "I have a 6- and a 12-liter jug. I want to measure exactly 6 liters."
          }
        ],
        "endpoints": [{
          "type": "openai",
          "baseURL": "https://api-inference.huggingface.co/models/nvidia/Llama-3.1-Nemotron-70B-Instruct-HF/v1"
        }]
      },
      {
        "name": "Qwen/Qwen2.5-Coder-32B-Instruct",
        "description": "Qwen's latest coding model, in its biggest size yet. SOTA on many coding benchmarks.",
        "modelUrl": "https://huggingface.co/Qwen/Qwen2.5-Coder-32B-Instruct",
        "websiteUrl": "https://qwenlm.github.io/blog/qwen2.5-coder-family/",
        "logoUrl": "https://huggingface.co/datasets/huggingchat/models-logo/resolve/main/qwen-logo.png",
        "preprompt": "You are Qwen, created by Alibaba Cloud. You are a helpful assistant.",
        "parameters": {
          "stop": ["<|im_end|>", "<|endoftext|>"],
          "temperature": 0.6,
          "truncate": 28672,
          "max_new_tokens": 3072
        },
        "promptExamples": [
          {
            "title": "To-do list web app",
            "prompt": "Create a simple to-do list application where users can:\n- Add new tasks.\n- Mark tasks as complete.\n- Delete completed tasks.\nThe tasks should persist in the browser's local storage so that they remain available even after a page reload.\n"
          },
          {
            "title": "Create a REST API",
            "prompt": "Build a simple REST API using Node.js, TypeScript and Express:\n- POST /items: Accepts a JSON body with name and quantity and adds a new item.\n- GET /items: Returns a list of all items.\n- PUT /items/:id: Updates the name or quantity of an item by its id.\n- DELETE /items/:id: Removes an item by its id.\nUse an in-memory array as the data store (no need for a database). Include basic error handling (e.g., item not found)."
          },
          {
            "title": "Simple website",
            "prompt": "Generate a snazzy static landing page for a local coffee shop using HTML and CSS. You can use tailwind using <script src='https://cdn.tailwindcss.com'></script>."
          }
        ],
        "endpoints": [{
          "type": "openai",
          "baseURL": "https://api-inference.huggingface.co/models/Qwen/Qwen2.5-Coder-32B-Instruct/v1"
        }]
      },
      {
        "name": "meta-llama/Llama-3.2-11B-Vision-Instruct",
        "logoUrl": "https://huggingface.co/datasets/huggingchat/models-logo/resolve/main/meta-logo.png",
        "description": "The latest multimodal model from Meta! Supports image inputs natively.",
        "websiteUrl": "https://llama.com/",
        "multimodal": true,
        "parameters": {
          "stop": ["<|eot_id|>", "<|im_end|>"],
          "temperature": 0.6,
          "truncate": 14336,
          "max_new_tokens": 1536
        },
        "endpoints": [{
          "type": "openai",
          "baseURL": "https://api-inference.huggingface.co/models/meta-llama/Llama-3.2-11B-Vision-Instruct/v1",
          "multimodal": {
            "image": {
              "maxSizeInMB": 10,
              "maxWidth": 560,
              "maxHeight": 560,
              "supportedMimeTypes": ["image/png", "image/jpeg", "image/webp"],
              "preferredMimeType": "image/webp"
            }
          }
        }]
      },
      {
        "name": "NousResearch/Hermes-3-Llama-3.1-8B",
        "description": "Nous Research's latest Hermes 3 release in 8B size. Follows instruction closely.",
        "logoUrl": "https://huggingface.co/datasets/huggingchat/models-logo/resolve/main/nous-logo.png",
        "websiteUrl": "https://nousresearch.com/",
        "modelUrl": "https://huggingface.co/NousResearch/Hermes-3-Llama-3.1-8B",
        "tokenizer": "NousResearch/Hermes-3-Llama-3.1-8B",
        "promptExamples": [
          {
            "title": "Write an email from bullet list",
            "prompt": "As a restaurant owner, write a professional email to the supplier to get these products every week: \n\n- Wine (x10)\n- Eggs (x24)\n- Bread (x12)"
          },
          {
            "title": "Code a snake game",
            "prompt": "Code a basic snake game in python, give explanations for each step."
          },
          {
            "title": "Assist in a task",
            "prompt": "How do I make a delicious lemon cheesecake?"
          }
        ],
        "parameters": {
          "stop": ["<|im_end|>"],
          "temperature": 0.6,
          "truncate": 14336,
          "max_new_tokens": 1536
        }
      },
      {
        "name": "microsoft/Phi-3.5-mini-instruct",
        "tokenizer": "microsoft/Phi-3.5-mini-instruct",
        "description": "One of the best small models (3.8B parameters), super fast for simple tasks.",
        "logoUrl": "https://huggingface.co/datasets/huggingchat/models-logo/resolve/main/microsoft-logo.png",
        "modelUrl": "https://huggingface.co/microsoft/Phi-3.5-mini-instruct",
        "websiteUrl": "https://techcommunity.microsoft.com/t5/ai-azure-ai-services-blog/discover-the-new-multi-lingual-high-quality-phi-3-5-slms/ba-p/4225280/",
        "preprompt": "",
        "parameters": {
          "stop": ["<|end|>", "<|endoftext|>", "<|assistant|>"],
          "temperature": 0.6,
          "truncate": 28672,
          "max_new_tokens": 3072
        },
        "promptExamples": [
          {
            "title": "Write an email from bullet list",
            "prompt": "As a restaurant owner, write a professional email to the supplier to get these products every week: \n\n- Wine (x10)\n- Eggs (x24)\n- Bread (x12)"
          },
          {
            "title": "Code a snake game",
            "prompt": "Code a basic snake game in python, give explanations for each step."
          },
          {
            "title": "Assist in a task",
            "prompt": "How do I make a delicious lemon cheesecake?"
          }
        ]
      },
      {
        "name": "llhf/Meta-Llama-3.1-8B-Instruct",
        "parameters": {
          "temperature": 0.6,
          "stop": ["<|endoftext|>", "<|eot_id|>"]
        },
        "unlisted": true
      }
]`
## Text Embedding Models used for websearch
# Default is a model that runs locally on CPU.
TEXT_EMBEDDING_MODELS = `[
  {
    "name": "Xenova/gte-small",
    "displayName": "Xenova/gte-small",
    "description": "Local embedding model running on the server.",
    "chunkCharLength": 512,
    "endpoints": [
      { "type": "transformersjs" }
    ]
  }
]`

## Removed models, useful for migrating conversations
# { name: string, displayName?: string, id?: string, transferTo?: string }`
OLD_MODELS=`[]`

## Task model
# name of the model used for tasks such as summarizing title, creating query, etc.
# if not set, the first model in MODELS will be used
TASK_MODEL=


### Authentication ###
# Parameters to enable open id login
OPENID_CONFIG=
MESSAGES_BEFORE_LOGIN=# how many messages a user can send in a conversation before having to login. set to 0 to force login right away
# if it's defined, only these emails will be allowed to use login
ALLOWED_USER_EMAILS=`[]` 
# valid alternative redirect URLs for OAuth, used for HuggingChat apps
ALTERNATIVE_REDIRECT_URLS=`[]` 
### Cookies
# name of the cookie used to store the session
COOKIE_NAME=hf-chat
# specify secure behaviour for cookies 
COOKIE_SAMESITE=# can be "lax", "strict", "none" or left empty
COOKIE_SECURE=# set to true to only allow cookies over https


### Websearch ###
## API Keys used to activate search with web functionality. websearch is disabled if none are defined. choose one of the following:
YDC_API_KEY=#your docs.you.com api key here
SERPER_API_KEY=#your serper.dev api key here
SERPAPI_KEY=#your serpapi key here
SERPSTACK_API_KEY=#your serpstack api key here
SEARCHAPI_KEY=#your searchapi api key here
USE_LOCAL_WEBSEARCH=#set to true to parse google results yourself, overrides other API keys
SEARXNG_QUERY_URL=# where '<query>' will be replaced with query keywords see https://docs.searxng.org/dev/search_api.html eg https://searxng.yourdomain.com/search?q=<query>&engines=duckduckgo,google&format=json
BING_SUBSCRIPTION_KEY=#your key
## Websearch configuration
PLAYWRIGHT_ADBLOCKER=true
WEBSEARCH_ALLOWLIST=`[]` # if it's defined, allow websites from only this list.
WEBSEARCH_BLOCKLIST=`[]` # if it's defined, block websites from this list.
WEBSEARCH_JAVASCRIPT=true # CPU usage reduces by 60% on average by disabling javascript. Enable to improve website compatibility
WEBSEARCH_TIMEOUT = 3500 # in milliseconds, determines how long to wait to load a page before timing out
ENABLE_LOCAL_FETCH=false #set to true to allow fetches on the local network. /!\ Only enable this if you have the proper firewall rules to prevent SSRF attacks and understand the implications.


## Public app configuration ##
PUBLIC_APP_GUEST_MESSAGE=# a message to the guest user. If not set, no message will be shown. Only used if you have authentication enabled.
PUBLIC_APP_NAME=CanvasTalk # name used as title throughout the app
PUBLIC_APP_ASSETS=chatui # used to find logos & favicons in static/$PUBLIC_APP_ASSETS
PUBLIC_APP_DESCRIPTION=# description used throughout the app
PUBLIC_APP_DATA_SHARING=# Set to 1 to enable an option in the user settings to share conversations with model authors
PUBLIC_APP_DISCLAIMER=# Set to 1 to show a disclaimer on login page
PUBLIC_APP_DISCLAIMER_MESSAGE=# Message to show on the login page
PUBLIC_ANNOUNCEMENT_BANNERS=`[
    {
    "title": "chat-ui is now open source!",
    "linkTitle": "check it out",
    "linkHref": "https://github.com/huggingface/chat-ui"
  }
]`
PUBLIC_SMOOTH_UPDATES=false # set to true to enable smoothing of messages client-side, can be CPU intensive
PUBLIC_ORIGIN=#https://huggingface.co
PUBLIC_SHARE_PREFIX=#https://hf.co/chat

# mostly huggingchat specific
PUBLIC_GOOGLE_ANALYTICS_ID=#G-XXXXXXXX / Leave empty to disable
PUBLIC_PLAUSIBLE_SCRIPT_URL=#/js/script.js / Leave empty to disable
PUBLIC_APPLE_APP_ID=#1234567890 / Leave empty to disable


### Feature Flags ###
LLM_SUMMARIZATION=true # generate conversation titles with LLMs
ENABLE_ASSISTANTS=false #set to true to enable assistants feature
ENABLE_ASSISTANTS_RAG=false # /!\ This will let users specify arbitrary URLs that the server will then request. Make sure you have the proper firewall rules in place. 
REQUIRE_FEATURED_ASSISTANTS=false # require featured assistants to show in the list
COMMUNITY_TOOLS=false # set to true to enable community tools
EXPOSE_API=true # make the /api routes available
ALLOW_IFRAME=true # Allow the app to be embedded in an iframe


### Tools ###
# Check out public config in `chart/env/prod.yaml` for more details
TOOLS=`[
        {
        "_id": "000000000000000000000001",
        "displayName": "Image Generation",
        "description": "Use this tool to generate images based on a prompt.",
        "color": "yellow",
        "icon": "camera",
        "baseUrl": "black-forest-labs/FLUX.1-schnell",
        "name": "image_generation",
        "endpoint": "/infer",
        "inputs": [
          {
            "name": "prompt",
            "description": "A prompt to generate an image from",
            "paramType": "required",
            "type": "str"
          },
          { "name": "seed", "paramType": "fixed", "value": "0", "type": "float" },
          {
            "name": "randomize_seed",
            "paramType": "fixed",
            "value": "true",
            "type": "bool"
          },
          {
            "name": "width",
            "description": "numeric value between 256 and 2048",
            "paramType": "optional",
            "default": 1024,
            "type": "float"
          },
          {
            "name": "height",
            "description": "numeric value between 256 and 2048",
            "paramType": "optional",
            "default": 1024,
            "type": "float"
          },
          {
            "name": "num_inference_steps",
            "paramType": "fixed",
            "value": "4",
            "type": "float"
          }
        ],
        "outputComponent": "image",
        "outputComponentIdx": 0,
        "showOutput": true
      },
      {
        "_id": "000000000000000000000002",
        "displayName": "Document Parser",
        "description": "Use this tool to parse any document and get its content in markdown format.",
        "color": "yellow",
        "icon": "cloud",
        "baseUrl": "huggingchat/document-parser",
        "name": "document_parser",
        "endpoint": "/predict",
        "inputs": [
          {
            "name": "document",
            "description": "Filename of the document to parse",
            "paramType": "required",
            "type": "file",
            "mimeTypes": 'application/*'
          },
          {
            "name": "filename",
            "paramType": "fixed",
            "value": "document.pdf",
            "type": "str"
          }
        ],
        "outputComponent": "textbox",
        "outputComponentIdx": 0,
        "showOutput": false
      },
      {
        "_id": "000000000000000000000003",
        "name": "edit_image",
        "baseUrl": "multimodalart/cosxl",
        "endpoint": "/run_edit",
        "inputs": [
          {
            "name": "image",
            "description": "The image path to be edited",
            "paramType": "required",
            "type": "file",
            "mimeTypes": 'image/*'
          },
          {
            "name": "prompt",
            "description": "The prompt with which to edit the image",
            "paramType": "required",
            "type": "str"
          },
          {
            "name": "negative_prompt",
            "paramType": "fixed",
            "value": "",
            "type": "str"
          },
          {
            "name": "guidance_scale",
            "paramType": "fixed",
            "value": 6.5,
            "type": "float"
          },
          {
            "name": "steps",
            "paramType": "fixed",
            "value": 30,
            "type": "float"
          }
        ],
        "outputComponent": "image",
        "showOutput": true,
        "displayName": "Image Editor",
        "color": "green",
        "icon": "camera",
        "description": "This tool lets you edit images",
        "outputComponentIdx": 0
      }
]` 

COMMUNITY_TOOLS=true

### Rate limits ### 
# See `src/lib/server/usageLimits.ts`
# {
#   conversations: number, # how many conversations
#   messages: number, # how many messages in a conversation
#   assistants: number, # how many assistants
#   messageLength: number, # how long can a message be before we cut it off
#   messagesPerMinute: number, # how many messages per minute
#   tools: number # how many tools
# }
USAGE_LIMITS=`{}`


### HuggingFace specific ###
# Let user authenticate with their HF token in the /api routes. This is only useful if you have OAuth configured with huggingface.
USE_HF_TOKEN_IN_API=false
## Feature flag & admin settings
# Used for setting early access & admin flags to users
HF_ORG_ADMIN=
HF_ORG_EARLY_ACCESS=
#WEBHOOK_URL_REPORT_ASSISTANT=#provide slack webhook url to get notified for reports/feature requests
ENABLE_ASSISTANTS=true #set to true to enable assistants feature
ENABLE_ASSISTANTS_RAG=false # /!\ This will let users specify arbitrary URLs that the server will then request. Make sure you have the proper firewall rules in>
REQUIRE_FEATURED_ASSISTANTS=false
ENABLE_LOCAL_FETCH=false #set to true to disable the blocklist for local fetches. Only enable this if you have the proper firewall rules to prevent SSRF attack>
ALTERNATIVE_REDIRECT_URLS=`[]` #valide alternative redirect URL for OAuth
WEBHOOK_URL_REPORT_ASSISTANT=#provide webhook url to get notified when an assistant gets reported


### Metrics ###
METRICS_ENABLED=false
METRICS_PORT=5565
LOG_LEVEL=info


### Parquet export ###
# Not in use anymore but useful to export conversations to a parquet file as a HuggingFace dataset
PARQUET_EXPORT_DATASET=
PARQUET_EXPORT_HF_TOKEN=
ADMIN_API_SECRET=# secret to admin API calls, like computing usage stats or exporting parquet data


### Docker build variables ### 
# These values cannot be updated at runtime
# They need to be passed when building the docker image
# See https://github.com/huggingface/chat-ui/main/.github/workflows/deploy-prod.yml#L44-L47
APP_BASE="" # base path of the app, e.g. /chat, left blank as default
PUBLIC_APP_COLOR=blue # can be any of tailwind colors: https://tailwindcss.com/docs/customizing-colors#default-color-palette
### Body size limit for SvelteKit https://svelte.dev/docs/kit/adapter-node#Environment-variables-BODY_SIZE_LIMIT
BODY_SIZE_LIMIT=15728640
PUBLIC_COMMIT_SHA=

### LEGACY parameters
HF_ACCESS_TOKEN=#LEGACY! Use HF_TOKEN instead
ALLOW_INSECURE_COOKIES=false # LEGACY! Use COOKIE_SECURE and COOKIE_SAMESITE instead
PARQUET_EXPORT_SECRET=#DEPRECATED, use ADMIN_API_SECRET instead
RATE_LIMIT= # /!\ DEPRECATED definition of messages per minute. Use USAGE_LIMITS.messagesPerMinute instead
OPENID_CLIENT_ID=
OPENID_CLIENT_SECRET=
OPENID_SCOPES="openid profile" # Add "email" for some providers like Google that do not provide preferred_username
OPENID_NAME_CLAIM="name" # Change to "username" for some providers that do not provide name
OPENID_PROVIDER_URL=https://huggingface.co # for Google, use https://accounts.google.com
OPENID_TOLERANCE=
OPENID_RESOURCE=