mirror of
https://github.com/open-webui/open-webui
synced 2024-11-06 00:32:05 +00:00
1029 lines
31 KiB
Python
1029 lines
31 KiB
Python
from contextlib import asynccontextmanager
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from bs4 import BeautifulSoup
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import json
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import markdown
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import time
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import os
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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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import shutil
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import os
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import asyncio
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from fastapi import FastAPI, Request, Depends, status, UploadFile, File, Form
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from fastapi.staticfiles import StaticFiles
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from fastapi.responses import JSONResponse
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from fastapi import HTTPException
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from fastapi.middleware.wsgi import WSGIMiddleware
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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.socket.main import app as socket_app
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from apps.ollama.main import app as ollama_app, get_all_models as get_ollama_models
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from apps.openai.main import app as openai_app, get_all_models as get_openai_models
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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
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from apps.rag.main import app as rag_app
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from apps.webui.main import app as webui_app
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from pydantic import BaseModel
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from typing import List, Optional
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from apps.webui.models.models import Models, ModelModel
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from utils.utils import (
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get_admin_user,
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get_verified_user,
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get_current_user,
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get_http_authorization_cred,
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)
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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,
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VERSION,
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CHANGELOG,
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FRONTEND_BUILD_DIR,
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CACHE_DIR,
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STATIC_DIR,
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ENABLE_OPENAI_API,
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ENABLE_OLLAMA_API,
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ENABLE_MODEL_FILTER,
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MODEL_FILTER_LIST,
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GLOBAL_LOG_LEVEL,
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SRC_LOG_LEVELS,
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WEBHOOK_URL,
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ENABLE_ADMIN_EXPORT,
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AppConfig,
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WEBUI_BUILD_HASH,
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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)
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log = logging.getLogger(__name__)
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log.setLevel(SRC_LOG_LEVELS["MAIN"])
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class SPAStaticFiles(StaticFiles):
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async def get_response(self, path: str, scope):
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try:
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return await super().get_response(path, scope)
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except (HTTPException, StarletteHTTPException) as ex:
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if ex.status_code == 404:
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return await super().get_response("index.html", scope)
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else:
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raise ex
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print(
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rf"""
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___ __ __ _ _ _ ___
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/ _ \ _ __ ___ _ __ \ \ / /__| |__ | | | |_ _|
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| | | | '_ \ / _ \ '_ \ \ \ /\ / / _ \ '_ \| | | || |
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| |_| | |_) | __/ | | | \ V V / __/ |_) | |_| || |
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\___/| .__/ \___|_| |_| \_/\_/ \___|_.__/ \___/|___|
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|_|
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v{VERSION} - building the best open-source AI user interface.
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{f"Commit: {WEBUI_BUILD_HASH}" if WEBUI_BUILD_HASH != "dev-build" else ""}
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https://github.com/open-webui/open-webui
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"""
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)
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@asynccontextmanager
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async def lifespan(app: FastAPI):
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yield
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app = FastAPI(
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docs_url="/docs" if ENV == "dev" else None, redoc_url=None, lifespan=lifespan
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)
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app.state.config = AppConfig()
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app.state.config.ENABLE_OPENAI_API = ENABLE_OPENAI_API
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app.state.config.ENABLE_OLLAMA_API = ENABLE_OLLAMA_API
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app.state.config.ENABLE_MODEL_FILTER = ENABLE_MODEL_FILTER
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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):
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# async def dispatch(self, request: Request, call_next):
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# response: Response = await call_next(request)
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# response.headers["Cross-Origin-Opener-Policy"] = "same-origin"
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# response.headers["Cross-Origin-Embedder-Policy"] = "require-corp"
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# return response
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# app.add_middleware(SecurityHeadersMiddleware)
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class RAGMiddleware(BaseHTTPMiddleware):
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async def dispatch(self, request: Request, call_next):
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return_citations = False
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if request.method == "POST" and (
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"/ollama/api/chat" in request.url.path
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or "/chat/completions" in request.url.path
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):
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log.debug(f"request.url.path: {request.url.path}")
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# Read the original request body
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body = await request.body()
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# Decode body to string
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body_str = body.decode("utf-8")
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# Parse string to JSON
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data = json.loads(body_str) if body_str else {}
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return_citations = data.get("citations", False)
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if "citations" in data:
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del data["citations"]
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# Example: Add a new key-value pair or modify existing ones
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# data["modified"] = True # Example modification
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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"],
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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,
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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(
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f"data['messages']: {data['messages']}, citations: {citations}"
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)
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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
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request._body = modified_body_bytes
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# Set custom header to ensure content-length matches new body length
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request.headers.__dict__["_list"] = [
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(b"content-length", str(len(modified_body_bytes)).encode("utf-8")),
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*[
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(k, v)
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for k, v in request.headers.raw
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if k.lower() != b"content-length"
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],
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]
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response = await call_next(request)
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if return_citations:
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# Inject the citations into the response
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if isinstance(response, StreamingResponse):
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# If it's a streaming response, inject it as SSE event or NDJSON line
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content_type = response.headers.get("Content-Type")
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if "text/event-stream" in content_type:
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return StreamingResponse(
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self.openai_stream_wrapper(response.body_iterator, citations),
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)
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if "application/x-ndjson" in content_type:
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return StreamingResponse(
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self.ollama_stream_wrapper(response.body_iterator, citations),
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)
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return response
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async def _receive(self, body: bytes):
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return {"type": "http.request", "body": body, "more_body": False}
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async def openai_stream_wrapper(self, original_generator, citations):
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yield f"data: {json.dumps({'citations': citations})}\n\n"
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async for data in original_generator:
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yield data
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async def ollama_stream_wrapper(self, original_generator, citations):
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yield f"{json.dumps({'citations': citations})}\n"
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async for data in original_generator:
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yield data
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app.add_middleware(RAGMiddleware)
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class PipelineMiddleware(BaseHTTPMiddleware):
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async def dispatch(self, request: Request, call_next):
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if request.method == "POST" and (
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"/ollama/api/chat" in request.url.path
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or "/chat/completions" in request.url.path
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):
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log.debug(f"request.url.path: {request.url.path}")
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# Read the original request body
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body = await request.body()
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# Decode body to string
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body_str = body.decode("utf-8")
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# Parse string to JSON
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data = json.loads(body_str) if body_str else {}
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model_id = data["model"]
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filters = [
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model
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for model in app.state.MODELS.values()
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if "pipeline" in model
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and "type" in model["pipeline"]
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and model["pipeline"]["type"] == "filter"
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and (
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model["pipeline"]["pipelines"] == ["*"]
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or any(
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model_id == target_model_id
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for target_model_id in model["pipeline"]["pipelines"]
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)
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)
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]
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sorted_filters = sorted(filters, key=lambda x: x["pipeline"]["priority"])
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user = None
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if len(sorted_filters) > 0:
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try:
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user = get_current_user(
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get_http_authorization_cred(
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request.headers.get("Authorization")
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)
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)
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user = {"id": user.id, "name": user.name, "role": user.role}
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except:
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pass
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model = app.state.MODELS[model_id]
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if "pipeline" in model:
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sorted_filters.append(model)
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for filter in sorted_filters:
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r = None
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try:
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urlIdx = filter["urlIdx"]
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url = openai_app.state.config.OPENAI_API_BASE_URLS[urlIdx]
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key = openai_app.state.config.OPENAI_API_KEYS[urlIdx]
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if key != "":
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headers = {"Authorization": f"Bearer {key}"}
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r = requests.post(
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f"{url}/{filter['id']}/filter/inlet",
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headers=headers,
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json={
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"user": user,
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"body": data,
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},
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)
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r.raise_for_status()
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data = r.json()
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except Exception as e:
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# Handle connection error here
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print(f"Connection error: {e}")
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if r is not None:
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try:
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res = r.json()
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if "detail" in res:
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return JSONResponse(
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status_code=r.status_code,
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content=res,
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)
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except:
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pass
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else:
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pass
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if "pipeline" not in app.state.MODELS[model_id]:
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if "chat_id" in data:
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del data["chat_id"]
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if "title" in data:
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del data["title"]
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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
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request._body = modified_body_bytes
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# Set custom header to ensure content-length matches new body length
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request.headers.__dict__["_list"] = [
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(b"content-length", str(len(modified_body_bytes)).encode("utf-8")),
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*[
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(k, v)
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for k, v in request.headers.raw
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if k.lower() != b"content-length"
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],
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]
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response = await call_next(request)
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return response
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async def _receive(self, body: bytes):
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return {"type": "http.request", "body": body, "more_body": False}
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app.add_middleware(PipelineMiddleware)
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app.add_middleware(
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CORSMiddleware,
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allow_origins=origins,
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allow_credentials=True,
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allow_methods=["*"],
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allow_headers=["*"],
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)
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@app.middleware("http")
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async def check_url(request: Request, call_next):
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if len(app.state.MODELS) == 0:
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await get_all_models()
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else:
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pass
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start_time = int(time.time())
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response = await call_next(request)
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process_time = int(time.time()) - start_time
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response.headers["X-Process-Time"] = str(process_time)
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return response
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@app.middleware("http")
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async def update_embedding_function(request: Request, call_next):
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response = await call_next(request)
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if "/embedding/update" in request.url.path:
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webui_app.state.EMBEDDING_FUNCTION = rag_app.state.EMBEDDING_FUNCTION
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return response
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app.mount("/ws", socket_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)
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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 = []
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ollama_models = []
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if app.state.config.ENABLE_OPENAI_API:
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openai_models = await get_openai_models()
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openai_models = openai_models["data"]
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if app.state.config.ENABLE_OLLAMA_API:
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ollama_models = await get_ollama_models()
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ollama_models = [
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{
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"id": model["model"],
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"name": model["name"],
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"object": "model",
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"created": int(time.time()),
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"owned_by": "ollama",
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"ollama": model,
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}
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for model in ollama_models["models"]
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]
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models = openai_models + ollama_models
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custom_models = Models.get_all_models()
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for custom_model in custom_models:
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if custom_model.base_model_id == None:
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for model in models:
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if (
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custom_model.id == model["id"]
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or custom_model.id == model["id"].split(":")[0]
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):
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model["name"] = custom_model.name
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model["info"] = custom_model.model_dump()
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else:
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owned_by = "openai"
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for model in models:
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if (
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custom_model.base_model_id == model["id"]
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or custom_model.base_model_id == model["id"].split(":")[0]
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):
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owned_by = model["owned_by"]
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break
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|
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models.append(
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{
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"id": custom_model.id,
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"name": custom_model.name,
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"object": "model",
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|
"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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)
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|
|
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app.state.MODELS = {model["id"]: model for model in models}
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|
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webui_app.state.MODELS = app.state.MODELS
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|
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return models
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|
|
|
|
|
@app.get("/api/models")
|
|
async def get_models(user=Depends(get_verified_user)):
|
|
models = await get_all_models()
|
|
|
|
# Filter out filter pipelines
|
|
models = [
|
|
model
|
|
for model in models
|
|
if "pipeline" not in model or model["pipeline"].get("type", None) != "filter"
|
|
]
|
|
|
|
if app.state.config.ENABLE_MODEL_FILTER:
|
|
if user.role == "user":
|
|
models = list(
|
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filter(
|
|
lambda model: model["id"] in app.state.config.MODEL_FILTER_LIST,
|
|
models,
|
|
)
|
|
)
|
|
return {"data": models}
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|
|
|
return {"data": models}
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|
|
|
|
|
@app.post("/api/chat/completed")
|
|
async def chat_completed(form_data: dict, user=Depends(get_verified_user)):
|
|
data = form_data
|
|
model_id = data["model"]
|
|
|
|
filters = [
|
|
model
|
|
for model in app.state.MODELS.values()
|
|
if "pipeline" in model
|
|
and "type" in model["pipeline"]
|
|
and model["pipeline"]["type"] == "filter"
|
|
and (
|
|
model["pipeline"]["pipelines"] == ["*"]
|
|
or any(
|
|
model_id == target_model_id
|
|
for target_model_id in model["pipeline"]["pipelines"]
|
|
)
|
|
)
|
|
]
|
|
sorted_filters = sorted(filters, key=lambda x: x["pipeline"]["priority"])
|
|
|
|
print(model_id)
|
|
|
|
if model_id in app.state.MODELS:
|
|
model = app.state.MODELS[model_id]
|
|
if "pipeline" in model:
|
|
sorted_filters = [model] + sorted_filters
|
|
|
|
for filter in sorted_filters:
|
|
r = None
|
|
try:
|
|
urlIdx = filter["urlIdx"]
|
|
|
|
url = openai_app.state.config.OPENAI_API_BASE_URLS[urlIdx]
|
|
key = openai_app.state.config.OPENAI_API_KEYS[urlIdx]
|
|
|
|
if key != "":
|
|
headers = {"Authorization": f"Bearer {key}"}
|
|
r = requests.post(
|
|
f"{url}/{filter['id']}/filter/outlet",
|
|
headers=headers,
|
|
json={
|
|
"user": {"id": user.id, "name": user.name, "role": user.role},
|
|
"body": data,
|
|
},
|
|
)
|
|
|
|
r.raise_for_status()
|
|
data = r.json()
|
|
except Exception as e:
|
|
# Handle connection error here
|
|
print(f"Connection error: {e}")
|
|
|
|
if r is not None:
|
|
try:
|
|
res = r.json()
|
|
if "detail" in res:
|
|
return JSONResponse(
|
|
status_code=r.status_code,
|
|
content=res,
|
|
)
|
|
except:
|
|
pass
|
|
|
|
else:
|
|
pass
|
|
|
|
return data
|
|
|
|
|
|
@app.get("/api/pipelines/list")
|
|
async def get_pipelines_list(user=Depends(get_admin_user)):
|
|
responses = await get_openai_models(raw=True)
|
|
|
|
print(responses)
|
|
urlIdxs = [
|
|
idx
|
|
for idx, response in enumerate(responses)
|
|
if response != None and "pipelines" in response
|
|
]
|
|
|
|
return {
|
|
"data": [
|
|
{
|
|
"url": openai_app.state.config.OPENAI_API_BASE_URLS[urlIdx],
|
|
"idx": urlIdx,
|
|
}
|
|
for urlIdx in urlIdxs
|
|
]
|
|
}
|
|
|
|
|
|
@app.post("/api/pipelines/upload")
|
|
async def upload_pipeline(
|
|
urlIdx: int = Form(...), file: UploadFile = File(...), user=Depends(get_admin_user)
|
|
):
|
|
print("upload_pipeline", urlIdx, file.filename)
|
|
# Check if the uploaded file is a python file
|
|
if not file.filename.endswith(".py"):
|
|
raise HTTPException(
|
|
status_code=status.HTTP_400_BAD_REQUEST,
|
|
detail="Only Python (.py) files are allowed.",
|
|
)
|
|
|
|
upload_folder = f"{CACHE_DIR}/pipelines"
|
|
os.makedirs(upload_folder, exist_ok=True)
|
|
file_path = os.path.join(upload_folder, file.filename)
|
|
|
|
try:
|
|
# Save the uploaded file
|
|
with open(file_path, "wb") as buffer:
|
|
shutil.copyfileobj(file.file, buffer)
|
|
|
|
url = openai_app.state.config.OPENAI_API_BASE_URLS[urlIdx]
|
|
key = openai_app.state.config.OPENAI_API_KEYS[urlIdx]
|
|
|
|
headers = {"Authorization": f"Bearer {key}"}
|
|
|
|
with open(file_path, "rb") as f:
|
|
files = {"file": f}
|
|
r = requests.post(f"{url}/pipelines/upload", headers=headers, files=files)
|
|
|
|
r.raise_for_status()
|
|
data = r.json()
|
|
|
|
return {**data}
|
|
except Exception as e:
|
|
# Handle connection error here
|
|
print(f"Connection error: {e}")
|
|
|
|
detail = "Pipeline not found"
|
|
if r is not None:
|
|
try:
|
|
res = r.json()
|
|
if "detail" in res:
|
|
detail = res["detail"]
|
|
except:
|
|
pass
|
|
|
|
raise HTTPException(
|
|
status_code=(r.status_code if r is not None else status.HTTP_404_NOT_FOUND),
|
|
detail=detail,
|
|
)
|
|
finally:
|
|
# Ensure the file is deleted after the upload is completed or on failure
|
|
if os.path.exists(file_path):
|
|
os.remove(file_path)
|
|
|
|
|
|
class AddPipelineForm(BaseModel):
|
|
url: str
|
|
urlIdx: int
|
|
|
|
|
|
@app.post("/api/pipelines/add")
|
|
async def add_pipeline(form_data: AddPipelineForm, user=Depends(get_admin_user)):
|
|
|
|
r = None
|
|
try:
|
|
urlIdx = form_data.urlIdx
|
|
|
|
url = openai_app.state.config.OPENAI_API_BASE_URLS[urlIdx]
|
|
key = openai_app.state.config.OPENAI_API_KEYS[urlIdx]
|
|
|
|
headers = {"Authorization": f"Bearer {key}"}
|
|
r = requests.post(
|
|
f"{url}/pipelines/add", headers=headers, json={"url": form_data.url}
|
|
)
|
|
|
|
r.raise_for_status()
|
|
data = r.json()
|
|
|
|
return {**data}
|
|
except Exception as e:
|
|
# Handle connection error here
|
|
print(f"Connection error: {e}")
|
|
|
|
detail = "Pipeline not found"
|
|
if r is not None:
|
|
try:
|
|
res = r.json()
|
|
if "detail" in res:
|
|
detail = res["detail"]
|
|
except:
|
|
pass
|
|
|
|
raise HTTPException(
|
|
status_code=(r.status_code if r is not None else status.HTTP_404_NOT_FOUND),
|
|
detail=detail,
|
|
)
|
|
|
|
|
|
class DeletePipelineForm(BaseModel):
|
|
id: str
|
|
urlIdx: int
|
|
|
|
|
|
@app.delete("/api/pipelines/delete")
|
|
async def delete_pipeline(form_data: DeletePipelineForm, user=Depends(get_admin_user)):
|
|
|
|
r = None
|
|
try:
|
|
urlIdx = form_data.urlIdx
|
|
|
|
url = openai_app.state.config.OPENAI_API_BASE_URLS[urlIdx]
|
|
key = openai_app.state.config.OPENAI_API_KEYS[urlIdx]
|
|
|
|
headers = {"Authorization": f"Bearer {key}"}
|
|
r = requests.delete(
|
|
f"{url}/pipelines/delete", headers=headers, json={"id": form_data.id}
|
|
)
|
|
|
|
r.raise_for_status()
|
|
data = r.json()
|
|
|
|
return {**data}
|
|
except Exception as e:
|
|
# Handle connection error here
|
|
print(f"Connection error: {e}")
|
|
|
|
detail = "Pipeline not found"
|
|
if r is not None:
|
|
try:
|
|
res = r.json()
|
|
if "detail" in res:
|
|
detail = res["detail"]
|
|
except:
|
|
pass
|
|
|
|
raise HTTPException(
|
|
status_code=(r.status_code if r is not None else status.HTTP_404_NOT_FOUND),
|
|
detail=detail,
|
|
)
|
|
|
|
|
|
@app.get("/api/pipelines")
|
|
async def get_pipelines(urlIdx: Optional[int] = None, user=Depends(get_admin_user)):
|
|
r = None
|
|
try:
|
|
urlIdx
|
|
|
|
url = openai_app.state.config.OPENAI_API_BASE_URLS[urlIdx]
|
|
key = openai_app.state.config.OPENAI_API_KEYS[urlIdx]
|
|
|
|
headers = {"Authorization": f"Bearer {key}"}
|
|
r = requests.get(f"{url}/pipelines", headers=headers)
|
|
|
|
r.raise_for_status()
|
|
data = r.json()
|
|
|
|
return {**data}
|
|
except Exception as e:
|
|
# Handle connection error here
|
|
print(f"Connection error: {e}")
|
|
|
|
detail = "Pipeline not found"
|
|
if r is not None:
|
|
try:
|
|
res = r.json()
|
|
if "detail" in res:
|
|
detail = res["detail"]
|
|
except:
|
|
pass
|
|
|
|
raise HTTPException(
|
|
status_code=(r.status_code if r is not None else status.HTTP_404_NOT_FOUND),
|
|
detail=detail,
|
|
)
|
|
|
|
|
|
@app.get("/api/pipelines/{pipeline_id}/valves")
|
|
async def get_pipeline_valves(
|
|
urlIdx: Optional[int], pipeline_id: str, user=Depends(get_admin_user)
|
|
):
|
|
models = await get_all_models()
|
|
r = None
|
|
try:
|
|
|
|
url = openai_app.state.config.OPENAI_API_BASE_URLS[urlIdx]
|
|
key = openai_app.state.config.OPENAI_API_KEYS[urlIdx]
|
|
|
|
headers = {"Authorization": f"Bearer {key}"}
|
|
r = requests.get(f"{url}/{pipeline_id}/valves", headers=headers)
|
|
|
|
r.raise_for_status()
|
|
data = r.json()
|
|
|
|
return {**data}
|
|
except Exception as e:
|
|
# Handle connection error here
|
|
print(f"Connection error: {e}")
|
|
|
|
detail = "Pipeline not found"
|
|
|
|
if r is not None:
|
|
try:
|
|
res = r.json()
|
|
if "detail" in res:
|
|
detail = res["detail"]
|
|
except:
|
|
pass
|
|
|
|
raise HTTPException(
|
|
status_code=(r.status_code if r is not None else status.HTTP_404_NOT_FOUND),
|
|
detail=detail,
|
|
)
|
|
|
|
|
|
@app.get("/api/pipelines/{pipeline_id}/valves/spec")
|
|
async def get_pipeline_valves_spec(
|
|
urlIdx: Optional[int], pipeline_id: str, user=Depends(get_admin_user)
|
|
):
|
|
models = await get_all_models()
|
|
|
|
r = None
|
|
try:
|
|
url = openai_app.state.config.OPENAI_API_BASE_URLS[urlIdx]
|
|
key = openai_app.state.config.OPENAI_API_KEYS[urlIdx]
|
|
|
|
headers = {"Authorization": f"Bearer {key}"}
|
|
r = requests.get(f"{url}/{pipeline_id}/valves/spec", headers=headers)
|
|
|
|
r.raise_for_status()
|
|
data = r.json()
|
|
|
|
return {**data}
|
|
except Exception as e:
|
|
# Handle connection error here
|
|
print(f"Connection error: {e}")
|
|
|
|
detail = "Pipeline not found"
|
|
if r is not None:
|
|
try:
|
|
res = r.json()
|
|
if "detail" in res:
|
|
detail = res["detail"]
|
|
except:
|
|
pass
|
|
|
|
raise HTTPException(
|
|
status_code=(r.status_code if r is not None else status.HTTP_404_NOT_FOUND),
|
|
detail=detail,
|
|
)
|
|
|
|
|
|
@app.post("/api/pipelines/{pipeline_id}/valves/update")
|
|
async def update_pipeline_valves(
|
|
urlIdx: Optional[int],
|
|
pipeline_id: str,
|
|
form_data: dict,
|
|
user=Depends(get_admin_user),
|
|
):
|
|
models = await get_all_models()
|
|
|
|
r = None
|
|
try:
|
|
url = openai_app.state.config.OPENAI_API_BASE_URLS[urlIdx]
|
|
key = openai_app.state.config.OPENAI_API_KEYS[urlIdx]
|
|
|
|
headers = {"Authorization": f"Bearer {key}"}
|
|
r = requests.post(
|
|
f"{url}/{pipeline_id}/valves/update",
|
|
headers=headers,
|
|
json={**form_data},
|
|
)
|
|
|
|
r.raise_for_status()
|
|
data = r.json()
|
|
|
|
return {**data}
|
|
except Exception as e:
|
|
# Handle connection error here
|
|
print(f"Connection error: {e}")
|
|
|
|
detail = "Pipeline not found"
|
|
|
|
if r is not None:
|
|
try:
|
|
res = r.json()
|
|
if "detail" in res:
|
|
detail = res["detail"]
|
|
except:
|
|
pass
|
|
|
|
raise HTTPException(
|
|
status_code=(r.status_code if r is not None else status.HTTP_404_NOT_FOUND),
|
|
detail=detail,
|
|
)
|
|
|
|
|
|
@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,
|
|
"default_locale": default_locale,
|
|
"default_models": webui_app.state.config.DEFAULT_MODELS,
|
|
"default_prompt_suggestions": webui_app.state.config.DEFAULT_PROMPT_SUGGESTIONS,
|
|
"features": {
|
|
"auth": WEBUI_AUTH,
|
|
"auth_trusted_header": bool(webui_app.state.AUTH_TRUSTED_EMAIL_HEADER),
|
|
"enable_signup": webui_app.state.config.ENABLE_SIGNUP,
|
|
"enable_web_search": rag_app.state.config.ENABLE_RAG_WEB_SEARCH,
|
|
"enable_image_generation": images_app.state.config.ENABLED,
|
|
"enable_community_sharing": webui_app.state.config.ENABLE_COMMUNITY_SHARING,
|
|
"enable_admin_export": 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
|
|
|
|
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(trust_env=True) 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."
|
|
)
|