open-webui/backend/main.py

from contextlib import asynccontextmanager
from bs4 import BeautifulSoup
import json
import markdown
import time
import os
import sys
import logging
import aiohttp
import requests
import mimetypes

from fastapi import FastAPI, Request, Depends, status
from fastapi.staticfiles import StaticFiles
from fastapi import HTTPException
from fastapi.middleware.wsgi import WSGIMiddleware
from fastapi.middleware.cors import CORSMiddleware
from starlette.exceptions import HTTPException as StarletteHTTPException
from starlette.middleware.base import BaseHTTPMiddleware
from starlette.responses import StreamingResponse, Response

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

from apps.audio.main import app as audio_app
from apps.images.main import app as images_app
from apps.rag.main import app as rag_app
from apps.web.main import app as webui_app

import asyncio
from pydantic import BaseModel
from typing import List, Optional

from apps.web.models.models import Models, ModelModel
from utils.utils import get_admin_user, get_verified_user
from apps.rag.utils import rag_messages

from config import (
    CONFIG_DATA,
    WEBUI_NAME,
    WEBUI_URL,
    WEBUI_AUTH,
    ENV,
    VERSION,
    CHANGELOG,
    FRONTEND_BUILD_DIR,
    CACHE_DIR,
    STATIC_DIR,
    ENABLE_OPENAI_API,
    ENABLE_OLLAMA_API,
    ENABLE_MODEL_FILTER,
    MODEL_FILTER_LIST,
    GLOBAL_LOG_LEVEL,
    SRC_LOG_LEVELS,
    WEBHOOK_URL,
    ENABLE_ADMIN_EXPORT,
    AppConfig,
)
from constants import ERROR_MESSAGES

logging.basicConfig(stream=sys.stdout, level=GLOBAL_LOG_LEVEL)
log = logging.getLogger(__name__)
log.setLevel(SRC_LOG_LEVELS["MAIN"])


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


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

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


@asynccontextmanager
async def lifespan(app: FastAPI):
    yield


app = FastAPI(
    docs_url="/docs" if ENV == "dev" else None, redoc_url=None, lifespan=lifespan
)

app.state.config = AppConfig()

app.state.config.ENABLE_OPENAI_API = ENABLE_OPENAI_API
app.state.config.ENABLE_OLLAMA_API = ENABLE_OLLAMA_API

app.state.config.ENABLE_MODEL_FILTER = ENABLE_MODEL_FILTER
app.state.config.MODEL_FILTER_LIST = MODEL_FILTER_LIST


app.state.config.WEBHOOK_URL = WEBHOOK_URL


app.state.MODELS = {}

origins = ["*"]


# Custom middleware to add security headers
# 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


# app.add_middleware(SecurityHeadersMiddleware)


class RAGMiddleware(BaseHTTPMiddleware):
    async def dispatch(self, request: Request, call_next):
        return_citations = False

        if request.method == "POST" and (
            "/api/chat" in request.url.path or "/chat/completions" in request.url.path
        ):
            log.debug(f"request.url.path: {request.url.path}")

            # 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 {}

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

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

                log.debug(
                    f"data['messages']: {data['messages']}, citations: {citations}"
                )

            modified_body_bytes = json.dumps(data).encode("utf-8")

            # 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"
                ],
            ]

        response = await call_next(request)

        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),
                    )

        return response

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

    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


app.add_middleware(RAGMiddleware)


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


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

    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


@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


app.mount("/ollama", ollama_app)
app.mount("/openai", openai_app)

app.mount("/images/api/v1", images_app)
app.mount("/audio/api/v1", audio_app)
app.mount("/rag/api/v1", rag_app)

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

webui_app.state.EMBEDDING_FUNCTION = rag_app.state.EMBEDDING_FUNCTION


async def get_all_models():
    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:
                if (
                    custom_model.id == model["id"]
                    or custom_model.id == model["id"].split(":")[0]
                ):
                    model["name"] = custom_model.name
                    model["info"] = custom_model.model_dump()
        else:
            owned_by = "openai"
            for model in models:
                if (
                    custom_model.base_model_id == model["id"]
                    or custom_model.base_model_id == model["id"].split(":")[0]
                ):
                    owned_by = model["owned_by"]
                    break

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

    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()
    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}


@app.get("/api/config")
async def get_app_config():
    # Checking and Handling the Absence of 'ui' in CONFIG_DATA

    default_locale = "en-US"
    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
    return {
        "status": True,
        "name": WEBUI_NAME,
        "version": VERSION,
        "auth": WEBUI_AUTH,
        "default_locale": default_locale,
        "images": images_app.state.config.ENABLED,
        "default_models": webui_app.state.config.DEFAULT_MODELS,
        "default_prompt_suggestions": webui_app.state.config.DEFAULT_PROMPT_SUGGESTIONS,
        "trusted_header_auth": bool(webui_app.state.AUTH_TRUSTED_EMAIL_HEADER),
        "admin_export_enabled": ENABLE_ADMIN_EXPORT,
    }


@app.get("/api/config/model/filter")
async def get_model_filter_config(user=Depends(get_admin_user)):
    return {
        "enabled": app.state.config.ENABLE_MODEL_FILTER,
        "models": app.state.config.MODEL_FILTER_LIST,
    }


class ModelFilterConfigForm(BaseModel):
    enabled: bool
    models: List[str]


@app.post("/api/config/model/filter")
async def update_model_filter_config(
    form_data: ModelFilterConfigForm, user=Depends(get_admin_user)
):
    app.state.config.ENABLE_MODEL_FILTER = form_data.enabled
    app.state.config.MODEL_FILTER_LIST = form_data.models

    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

    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

    return {
        "enabled": app.state.config.ENABLE_MODEL_FILTER,
        "models": app.state.config.MODEL_FILTER_LIST,
    }


@app.get("/api/webhook")
async def get_webhook_url(user=Depends(get_admin_user)):
    return {
        "url": app.state.config.WEBHOOK_URL,
    }


class UrlForm(BaseModel):
    url: str


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

    webui_app.state.WEBHOOK_URL = app.state.config.WEBHOOK_URL

    return {
        "url": app.state.config.WEBHOOK_URL,
    }


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


@app.get("/api/changelog")
async def get_app_changelog():
    return {key: CHANGELOG[key] for idx, key in enumerate(CHANGELOG) if idx < 5}


@app.get("/api/version/updates")
async def get_app_latest_release_version():
    try:
        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:
        raise HTTPException(
            status_code=status.HTTP_503_SERVICE_UNAVAILABLE,
            detail=ERROR_MESSAGES.RATE_LIMIT_EXCEEDED,
        )


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


@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")


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


app.mount("/static", StaticFiles(directory=STATIC_DIR), name="static")
app.mount("/cache", StaticFiles(directory=CACHE_DIR), name="cache")

if os.path.exists(FRONTEND_BUILD_DIR):
    mimetypes.add_type("text/javascript", ".js")
    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."
    )