main.py 15.8 KB
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from contextlib import asynccontextmanager
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from bs4 import BeautifulSoup
import json
import markdown
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import time
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import os
import sys
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import logging
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import aiohttp
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import requests
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import mimetypes
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from fastapi import FastAPI, Request, Depends, status
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from fastapi.staticfiles import StaticFiles
from fastapi import HTTPException
from fastapi.middleware.wsgi import WSGIMiddleware
from fastapi.middleware.cors import CORSMiddleware
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from starlette.exceptions import HTTPException as StarletteHTTPException
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from starlette.middleware.base import BaseHTTPMiddleware
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from starlette.responses import StreamingResponse, Response
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from apps.ollama.main import app as ollama_app, get_all_models as get_ollama_models
from apps.openai.main import app as openai_app, get_all_models as get_openai_models
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from apps.litellm.main import (
    app as litellm_app,
    start_litellm_background,
    shutdown_litellm_background,
)
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from apps.audio.main import app as audio_app
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from apps.images.main import app as images_app
from apps.rag.main import app as rag_app
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from apps.web.main import app as webui_app
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import asyncio
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from pydantic import BaseModel
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from typing import List, Optional
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from apps.web.models.models import Models, ModelModel
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from utils.utils import get_admin_user, get_verified_user
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from apps.rag.utils import rag_messages
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from config import (
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    CONFIG_DATA,
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    WEBUI_NAME,
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    WEBUI_URL,
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    WEBUI_AUTH,
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    ENV,
    VERSION,
    CHANGELOG,
    FRONTEND_BUILD_DIR,
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    CACHE_DIR,
    STATIC_DIR,
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    ENABLE_OPENAI_API,
    ENABLE_OLLAMA_API,
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    ENABLE_LITELLM,
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    ENABLE_MODEL_FILTER,
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    MODEL_FILTER_LIST,
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    GLOBAL_LOG_LEVEL,
    SRC_LOG_LEVELS,
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    WEBHOOK_URL,
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    ENABLE_ADMIN_EXPORT,
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    RAG_WEB_SEARCH_ENABLED,
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    AppConfig,
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)
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from constants import ERROR_MESSAGES

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logging.basicConfig(stream=sys.stdout, level=GLOBAL_LOG_LEVEL)
log = logging.getLogger(__name__)
log.setLevel(SRC_LOG_LEVELS["MAIN"])
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class SPAStaticFiles(StaticFiles):
    async def get_response(self, path: str, scope):
        try:
            return await super().get_response(path, scope)
        except (HTTPException, StarletteHTTPException) as ex:
            if ex.status_code == 404:
                return await super().get_response("index.html", scope)
            else:
                raise ex


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print(
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    rf"""
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  ___                    __        __   _     _   _ ___ 
 / _ \ _ __   ___ _ __   \ \      / /__| |__ | | | |_ _|
| | | | '_ \ / _ \ '_ \   \ \ /\ / / _ \ '_ \| | | || | 
| |_| | |_) |  __/ | | |   \ V  V /  __/ |_) | |_| || | 
 \___/| .__/ \___|_| |_|    \_/\_/ \___|_.__/ \___/|___|
      |_|                                               

      
v{VERSION} - building the best open-source AI user interface.      
https://github.com/open-webui/open-webui
"""
)

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@asynccontextmanager
async def lifespan(app: FastAPI):
    if ENABLE_LITELLM:
        asyncio.create_task(start_litellm_background())
    yield
    if ENABLE_LITELLM:
        await shutdown_litellm_background()


app = FastAPI(
    docs_url="/docs" if ENV == "dev" else None, redoc_url=None, lifespan=lifespan
)
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app.state.config = AppConfig()
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app.state.config.ENABLE_OPENAI_API = ENABLE_OPENAI_API
app.state.config.ENABLE_OLLAMA_API = ENABLE_OLLAMA_API

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app.state.config.ENABLE_MODEL_FILTER = ENABLE_MODEL_FILTER
app.state.config.MODEL_FILTER_LIST = MODEL_FILTER_LIST
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app.state.config.WEBHOOK_URL = WEBHOOK_URL
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app.state.MODELS = {}

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origins = ["*"]

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# Custom middleware to add security headers
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# class SecurityHeadersMiddleware(BaseHTTPMiddleware):
#     async def dispatch(self, request: Request, call_next):
#         response: Response = await call_next(request)
#         response.headers["Cross-Origin-Opener-Policy"] = "same-origin"
#         response.headers["Cross-Origin-Embedder-Policy"] = "require-corp"
#         return response
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# app.add_middleware(SecurityHeadersMiddleware)
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class RAGMiddleware(BaseHTTPMiddleware):
    async def dispatch(self, request: Request, call_next):
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        return_citations = False

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        if request.method == "POST" and (
            "/api/chat" in request.url.path or "/chat/completions" in request.url.path
        ):
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            log.debug(f"request.url.path: {request.url.path}")
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            # Read the original request body
            body = await request.body()
            # Decode body to string
            body_str = body.decode("utf-8")
            # Parse string to JSON
            data = json.loads(body_str) if body_str else {}

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            return_citations = data.get("citations", False)
            if "citations" in data:
                del data["citations"]

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            # Example: Add a new key-value pair or modify existing ones
            # data["modified"] = True  # Example modification
            if "docs" in data:
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                data = {**data}
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                data["messages"], citations = rag_messages(
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                    docs=data["docs"],
                    messages=data["messages"],
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                    template=rag_app.state.config.RAG_TEMPLATE,
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                    embedding_function=rag_app.state.EMBEDDING_FUNCTION,
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                    k=rag_app.state.config.TOP_K,
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                    reranking_function=rag_app.state.sentence_transformer_rf,
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                    r=rag_app.state.config.RELEVANCE_THRESHOLD,
                    hybrid_search=rag_app.state.config.ENABLE_RAG_HYBRID_SEARCH,
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                )
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                del data["docs"]

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                log.debug(
                    f"data['messages']: {data['messages']}, citations: {citations}"
                )
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            modified_body_bytes = json.dumps(data).encode("utf-8")

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            # Replace the request body with the modified one
            request._body = modified_body_bytes

            # Set custom header to ensure content-length matches new body length
            request.headers.__dict__["_list"] = [
                (b"content-length", str(len(modified_body_bytes)).encode("utf-8")),
                *[
                    (k, v)
                    for k, v in request.headers.raw
                    if k.lower() != b"content-length"
                ],
            ]
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        response = await call_next(request)
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        if return_citations:
            # Inject the citations into the response
            if isinstance(response, StreamingResponse):
                # If it's a streaming response, inject it as SSE event or NDJSON line
                content_type = response.headers.get("Content-Type")
                if "text/event-stream" in content_type:
                    return StreamingResponse(
                        self.openai_stream_wrapper(response.body_iterator, citations),
                    )
                if "application/x-ndjson" in content_type:
                    return StreamingResponse(
                        self.ollama_stream_wrapper(response.body_iterator, citations),
                    )

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        return response

    async def _receive(self, body: bytes):
        return {"type": "http.request", "body": body, "more_body": False}

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    async def openai_stream_wrapper(self, original_generator, citations):
        yield f"data: {json.dumps({'citations': citations})}\n\n"
        async for data in original_generator:
            yield data

    async def ollama_stream_wrapper(self, original_generator, citations):
        yield f"{json.dumps({'citations': citations})}\n"
        async for data in original_generator:
            yield data

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app.add_middleware(RAGMiddleware)


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app.add_middleware(
    CORSMiddleware,
    allow_origins=origins,
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)


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@app.middleware("http")
async def check_url(request: Request, call_next):
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    if len(app.state.MODELS) == 0:
        await get_all_models()
    else:
        pass

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    start_time = int(time.time())
    response = await call_next(request)
    process_time = int(time.time()) - start_time
    response.headers["X-Process-Time"] = str(process_time)

    return response


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@app.middleware("http")
async def update_embedding_function(request: Request, call_next):
    response = await call_next(request)
    if "/embedding/update" in request.url.path:
        webui_app.state.EMBEDDING_FUNCTION = rag_app.state.EMBEDDING_FUNCTION
    return response
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# TODO: Deprecate LiteLLM
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app.mount("/litellm/api", litellm_app)
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app.mount("/ollama", ollama_app)
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app.mount("/openai", openai_app)
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app.mount("/images/api/v1", images_app)
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app.mount("/audio/api/v1", audio_app)
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app.mount("/rag/api/v1", rag_app)

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app.mount("/api/v1", webui_app)

webui_app.state.EMBEDDING_FUNCTION = rag_app.state.EMBEDDING_FUNCTION

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async def get_all_models():
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    openai_models = []
    ollama_models = []

    if app.state.config.ENABLE_OPENAI_API:
        openai_models = await get_openai_models()

        openai_models = openai_models["data"]

    if app.state.config.ENABLE_OLLAMA_API:
        ollama_models = await get_ollama_models()

        ollama_models = [
            {
                "id": model["model"],
                "name": model["name"],
                "object": "model",
                "created": int(time.time()),
                "owned_by": "ollama",
                "ollama": model,
            }
            for model in ollama_models["models"]
        ]

    models = openai_models + ollama_models
    custom_models = Models.get_all_models()

    for custom_model in custom_models:
        if custom_model.base_model_id == None:
            for model in models:
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                if (
                    custom_model.id == model["id"]
                    or custom_model.id == model["id"].split(":")[0]
                ):
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                    model["name"] = custom_model.name
                    model["info"] = custom_model.model_dump()
        else:
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            owned_by = "openai"
            for model in models:
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                if (
                    custom_model.base_model_id == model["id"]
                    or custom_model.base_model_id == model["id"].split(":")[0]
                ):
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                    owned_by = model["owned_by"]
                    break

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            models.append(
                {
                    "id": custom_model.id,
                    "name": custom_model.name,
                    "object": "model",
                    "created": custom_model.created_at,
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                    "owned_by": owned_by,
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                    "info": custom_model.model_dump(),
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                    "preset": True,
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                }
            )

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    app.state.MODELS = {model["id"]: model for model in models}

    webui_app.state.MODELS = app.state.MODELS

    return models


@app.get("/api/models")
async def get_models(user=Depends(get_verified_user)):
    models = await get_all_models()
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    if app.state.config.ENABLE_MODEL_FILTER:
        if user.role == "user":
            models = list(
                filter(
                    lambda model: model["id"] in app.state.config.MODEL_FILTER_LIST,
                    models,
                )
            )
            return {"data": models}

    return {"data": models}


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@app.get("/api/config")
async def get_app_config():
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    # Checking and Handling the Absence of 'ui' in CONFIG_DATA
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    default_locale = "en-US"
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    if "ui" in CONFIG_DATA:
        default_locale = CONFIG_DATA["ui"].get("default_locale", "en-US")

    # The Rest of the Function Now Uses the Variables Defined Above
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    return {
        "status": True,
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        "name": WEBUI_NAME,
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        "version": VERSION,
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        "auth": WEBUI_AUTH,
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        "default_locale": default_locale,
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        "images": images_app.state.config.ENABLED,
        "default_models": webui_app.state.config.DEFAULT_MODELS,
        "default_prompt_suggestions": webui_app.state.config.DEFAULT_PROMPT_SUGGESTIONS,
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        "trusted_header_auth": bool(webui_app.state.AUTH_TRUSTED_EMAIL_HEADER),
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        "admin_export_enabled": ENABLE_ADMIN_EXPORT,
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        "websearch": RAG_WEB_SEARCH_ENABLED,
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    }


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@app.get("/api/config/model/filter")
async def get_model_filter_config(user=Depends(get_admin_user)):
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    return {
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        "enabled": app.state.config.ENABLE_MODEL_FILTER,
        "models": app.state.config.MODEL_FILTER_LIST,
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    }
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class ModelFilterConfigForm(BaseModel):
    enabled: bool
    models: List[str]


@app.post("/api/config/model/filter")
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async def update_model_filter_config(
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    form_data: ModelFilterConfigForm, user=Depends(get_admin_user)
):
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    app.state.config.ENABLE_MODEL_FILTER = form_data.enabled
    app.state.config.MODEL_FILTER_LIST = form_data.models
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    ollama_app.state.config.ENABLE_MODEL_FILTER = app.state.config.ENABLE_MODEL_FILTER
    ollama_app.state.config.MODEL_FILTER_LIST = app.state.config.MODEL_FILTER_LIST
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    openai_app.state.config.ENABLE_MODEL_FILTER = app.state.config.ENABLE_MODEL_FILTER
    openai_app.state.config.MODEL_FILTER_LIST = app.state.config.MODEL_FILTER_LIST
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    litellm_app.state.ENABLE_MODEL_FILTER = app.state.config.ENABLE_MODEL_FILTER
    litellm_app.state.MODEL_FILTER_LIST = app.state.config.MODEL_FILTER_LIST
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    return {
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        "enabled": app.state.config.ENABLE_MODEL_FILTER,
        "models": app.state.config.MODEL_FILTER_LIST,
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    }
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@app.get("/api/webhook")
async def get_webhook_url(user=Depends(get_admin_user)):
    return {
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        "url": app.state.config.WEBHOOK_URL,
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    }


class UrlForm(BaseModel):
    url: str


@app.post("/api/webhook")
async def update_webhook_url(form_data: UrlForm, user=Depends(get_admin_user)):
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    app.state.config.WEBHOOK_URL = form_data.url
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    webui_app.state.WEBHOOK_URL = app.state.config.WEBHOOK_URL
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    return {
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        "url": app.state.config.WEBHOOK_URL,
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    }


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@app.get("/api/version")
async def get_app_config():
    return {
        "version": VERSION,
    }


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@app.get("/api/changelog")
async def get_app_changelog():
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    return {key: CHANGELOG[key] for idx, key in enumerate(CHANGELOG) if idx < 5}
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@app.get("/api/version/updates")
async def get_app_latest_release_version():
    try:
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        async with aiohttp.ClientSession() as session:
            async with session.get(
                "https://api.github.com/repos/open-webui/open-webui/releases/latest"
            ) as response:
                response.raise_for_status()
                data = await response.json()
                latest_version = data["tag_name"]

                return {"current": VERSION, "latest": latest_version[1:]}
    except aiohttp.ClientError as e:
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        raise HTTPException(
            status_code=status.HTTP_503_SERVICE_UNAVAILABLE,
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            detail=ERROR_MESSAGES.RATE_LIMIT_EXCEEDED,
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        )

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@app.get("/manifest.json")
async def get_manifest_json():
    return {
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        "name": WEBUI_NAME,
        "short_name": WEBUI_NAME,
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        "start_url": "/",
        "display": "standalone",
        "background_color": "#343541",
        "theme_color": "#343541",
        "orientation": "portrait-primary",
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        "icons": [{"src": "/static/logo.png", "type": "image/png", "sizes": "500x500"}],
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    }

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@app.get("/opensearch.xml")
async def get_opensearch_xml():
    xml_content = rf"""
    <OpenSearchDescription xmlns="http://a9.com/-/spec/opensearch/1.1/" xmlns:moz="http://www.mozilla.org/2006/browser/search/">
    <ShortName>{WEBUI_NAME}</ShortName>
    <Description>Search {WEBUI_NAME}</Description>
    <InputEncoding>UTF-8</InputEncoding>
    <Image width="16" height="16" type="image/x-icon">{WEBUI_URL}/favicon.png</Image>
    <Url type="text/html" method="get" template="{WEBUI_URL}/?q={"{searchTerms}"}"/>
    <moz:SearchForm>{WEBUI_URL}</moz:SearchForm>
    </OpenSearchDescription>
    """
    return Response(content=xml_content, media_type="application/xml")


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@app.get("/health")
async def healthcheck():
    return {"status": True}


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app.mount("/static", StaticFiles(directory=STATIC_DIR), name="static")
app.mount("/cache", StaticFiles(directory=CACHE_DIR), name="cache")
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if os.path.exists(FRONTEND_BUILD_DIR):
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    mimetypes.add_type("text/javascript", ".js")
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    app.mount(
        "/",
        SPAStaticFiles(directory=FRONTEND_BUILD_DIR, html=True),
        name="spa-static-files",
    )
else:
    log.warning(
        f"Frontend build directory not found at '{FRONTEND_BUILD_DIR}'. Serving API only."
    )