import base64 import uuid import subprocess from contextlib import asynccontextmanager from authlib.integrations.starlette_client import OAuth from authlib.oidc.core import UserInfo from bs4 import BeautifulSoup import json import markdown import time import os import sys import logging import aiohttp import requests import mimetypes import shutil import os import uuid import inspect import asyncio from fastapi.concurrency import run_in_threadpool from fastapi import FastAPI, Request, Depends, status, UploadFile, File, Form from fastapi.staticfiles import StaticFiles from fastapi.responses import JSONResponse from fastapi import HTTPException from fastapi.middleware.wsgi import WSGIMiddleware from fastapi.middleware.cors import CORSMiddleware from sqlalchemy import text from starlette.exceptions import HTTPException as StarletteHTTPException from starlette.middleware.base import BaseHTTPMiddleware from starlette.middleware.sessions import SessionMiddleware from starlette.responses import StreamingResponse, Response, RedirectResponse from apps.socket.main import sio, app as socket_app from apps.ollama.main import ( app as ollama_app, OpenAIChatCompletionForm, get_all_models as get_ollama_models, generate_openai_chat_completion as generate_ollama_chat_completion, ) from apps.openai.main import ( app as openai_app, get_all_models as get_openai_models, generate_chat_completion as generate_openai_chat_completion, ) 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.webui.main import ( app as webui_app, get_pipe_models, generate_function_chat_completion, ) from apps.webui.internal.db import Session, SessionLocal from pydantic import BaseModel from typing import List, Optional, Iterator, Generator, Union from apps.webui.models.auths import Auths from apps.webui.models.models import Models, ModelModel from apps.webui.models.tools import Tools from apps.webui.models.functions import Functions from apps.webui.models.users import Users from apps.webui.utils import load_toolkit_module_by_id, load_function_module_by_id from utils.utils import ( get_admin_user, get_verified_user, get_current_user, get_http_authorization_cred, get_password_hash, create_token, ) from utils.task import ( title_generation_template, search_query_generation_template, tools_function_calling_generation_template, ) from utils.misc import ( get_last_user_message, add_or_update_system_message, stream_message_template, parse_duration, ) from apps.rag.utils import get_rag_context, rag_template from config import ( CONFIG_DATA, WEBUI_NAME, WEBUI_URL, WEBUI_AUTH, ENV, VERSION, CHANGELOG, FRONTEND_BUILD_DIR, UPLOAD_DIR, CACHE_DIR, STATIC_DIR, DEFAULT_LOCALE, ENABLE_OPENAI_API, ENABLE_OLLAMA_API, ENABLE_MODEL_FILTER, MODEL_FILTER_LIST, GLOBAL_LOG_LEVEL, SRC_LOG_LEVELS, WEBHOOK_URL, ENABLE_ADMIN_EXPORT, WEBUI_BUILD_HASH, TASK_MODEL, TASK_MODEL_EXTERNAL, TITLE_GENERATION_PROMPT_TEMPLATE, SEARCH_QUERY_GENERATION_PROMPT_TEMPLATE, SEARCH_QUERY_PROMPT_LENGTH_THRESHOLD, TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE, SAFE_MODE, OAUTH_PROVIDERS, ENABLE_OAUTH_SIGNUP, OAUTH_MERGE_ACCOUNTS_BY_EMAIL, WEBUI_SECRET_KEY, WEBUI_SESSION_COOKIE_SAME_SITE, WEBUI_SESSION_COOKIE_SECURE, AppConfig, BACKEND_DIR, DATABASE_URL, ) from constants import ERROR_MESSAGES, WEBHOOK_MESSAGES, TASKS from utils.webhook import post_webhook if SAFE_MODE: print("SAFE MODE ENABLED") Functions.deactivate_all_functions() 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. {f"Commit: {WEBUI_BUILD_HASH}" if WEBUI_BUILD_HASH != "dev-build" else ""} https://github.com/open-webui/open-webui """ ) def run_migrations(): try: from alembic.config import Config from alembic import command alembic_cfg = Config("alembic.ini") command.upgrade(alembic_cfg, "head") except Exception as e: print(f"Error: {e}") @asynccontextmanager async def lifespan(app: FastAPI): run_migrations() 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.config.TASK_MODEL = TASK_MODEL app.state.config.TASK_MODEL_EXTERNAL = TASK_MODEL_EXTERNAL app.state.config.TITLE_GENERATION_PROMPT_TEMPLATE = TITLE_GENERATION_PROMPT_TEMPLATE app.state.config.SEARCH_QUERY_GENERATION_PROMPT_TEMPLATE = ( SEARCH_QUERY_GENERATION_PROMPT_TEMPLATE ) app.state.config.SEARCH_QUERY_PROMPT_LENGTH_THRESHOLD = ( SEARCH_QUERY_PROMPT_LENGTH_THRESHOLD ) app.state.config.TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE = ( TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE ) app.state.MODELS = {} origins = ["*"] ################################## # # ChatCompletion Middleware # ################################## async def get_body_and_model_and_user(request): # Read the original request body body = await request.body() body_str = body.decode("utf-8") body = json.loads(body_str) if body_str else {} model_id = body["model"] if model_id not in app.state.MODELS: raise "Model not found" model = app.state.MODELS[model_id] user = get_current_user( request, get_http_authorization_cred(request.headers.get("Authorization")), ) return body, model, user def get_task_model_id(default_model_id): # Set the task model task_model_id = default_model_id # Check if the user has a custom task model and use that model if app.state.MODELS[task_model_id]["owned_by"] == "ollama": if ( app.state.config.TASK_MODEL and app.state.config.TASK_MODEL in app.state.MODELS ): task_model_id = app.state.config.TASK_MODEL else: if ( app.state.config.TASK_MODEL_EXTERNAL and app.state.config.TASK_MODEL_EXTERNAL in app.state.MODELS ): task_model_id = app.state.config.TASK_MODEL_EXTERNAL return task_model_id def get_filter_function_ids(model): def get_priority(function_id): function = Functions.get_function_by_id(function_id) if function is not None and hasattr(function, "valves"): return (function.valves if function.valves else {}).get("priority", 0) return 0 filter_ids = [function.id for function in Functions.get_global_filter_functions()] if "info" in model and "meta" in model["info"]: filter_ids.extend(model["info"]["meta"].get("filterIds", [])) filter_ids = list(set(filter_ids)) enabled_filter_ids = [ function.id for function in Functions.get_functions_by_type("filter", active_only=True) ] filter_ids = [ filter_id for filter_id in filter_ids if filter_id in enabled_filter_ids ] filter_ids.sort(key=get_priority) return filter_ids async def get_function_call_response( messages, files, tool_id, template, task_model_id, user, model, __event_emitter__=None, __event_call__=None, ): tool = Tools.get_tool_by_id(tool_id) tools_specs = json.dumps(tool.specs, indent=2) content = tools_function_calling_generation_template(template, tools_specs) user_message = get_last_user_message(messages) prompt = ( "History:\n" + "\n".join( [ f"{message['role'].upper()}: \"\"\"{message['content']}\"\"\"" for message in messages[::-1][:4] ] ) + f"\nQuery: {user_message}" ) print(prompt) payload = { "model": task_model_id, "messages": [ {"role": "system", "content": content}, {"role": "user", "content": f"Query: {prompt}"}, ], "stream": False, "task": TASKS.FUNCTION_CALLING, } try: payload = filter_pipeline(payload, user) except Exception as e: raise e model = app.state.MODELS[task_model_id] response = None try: response = await generate_chat_completions(form_data=payload, user=user) content = None if hasattr(response, "body_iterator"): async for chunk in response.body_iterator: data = json.loads(chunk.decode("utf-8")) content = data["choices"][0]["message"]["content"] # Cleanup any remaining background tasks if necessary if response.background is not None: await response.background() else: content = response["choices"][0]["message"]["content"] # Parse the function response if content is not None: print(f"content: {content}") result = json.loads(content) print(result) citation = None # Call the function if "name" in result: if tool_id in webui_app.state.TOOLS: toolkit_module = webui_app.state.TOOLS[tool_id] else: toolkit_module, frontmatter = load_toolkit_module_by_id(tool_id) webui_app.state.TOOLS[tool_id] = toolkit_module file_handler = False # check if toolkit_module has file_handler self variable if hasattr(toolkit_module, "file_handler"): file_handler = True print("file_handler: ", file_handler) if hasattr(toolkit_module, "valves") and hasattr( toolkit_module, "Valves" ): valves = Tools.get_tool_valves_by_id(tool_id) toolkit_module.valves = toolkit_module.Valves( **(valves if valves else {}) ) function = getattr(toolkit_module, result["name"]) function_result = None try: # Get the signature of the function sig = inspect.signature(function) params = result["parameters"] if "__user__" in sig.parameters: # Call the function with the '__user__' parameter included __user__ = { "id": user.id, "email": user.email, "name": user.name, "role": user.role, } try: if hasattr(toolkit_module, "UserValves"): __user__["valves"] = toolkit_module.UserValves( **Tools.get_user_valves_by_id_and_user_id( tool_id, user.id ) ) except Exception as e: print(e) params = {**params, "__user__": __user__} if "__messages__" in sig.parameters: # Call the function with the '__messages__' parameter included params = { **params, "__messages__": messages, } if "__files__" in sig.parameters: # Call the function with the '__files__' parameter included params = { **params, "__files__": files, } if "__model__" in sig.parameters: # Call the function with the '__model__' parameter included params = { **params, "__model__": model, } if "__id__" in sig.parameters: # Call the function with the '__id__' parameter included params = { **params, "__id__": tool_id, } if "__event_emitter__" in sig.parameters: # Call the function with the '__event_emitter__' parameter included params = { **params, "__event_emitter__": __event_emitter__, } if "__event_call__" in sig.parameters: # Call the function with the '__event_call__' parameter included params = { **params, "__event_call__": __event_call__, } if inspect.iscoroutinefunction(function): function_result = await function(**params) else: function_result = function(**params) if hasattr(toolkit_module, "citation") and toolkit_module.citation: citation = { "source": {"name": f"TOOL:{tool.name}/{result['name']}"}, "document": [function_result], "metadata": [{"source": result["name"]}], } except Exception as e: print(e) # Add the function result to the system prompt if function_result is not None: return function_result, citation, file_handler except Exception as e: print(f"Error: {e}") return None, None, False async def chat_completion_functions_handler( body, model, user, __event_emitter__, __event_call__ ): skip_files = None filter_ids = get_filter_function_ids(model) for filter_id in filter_ids: filter = Functions.get_function_by_id(filter_id) if filter: if filter_id in webui_app.state.FUNCTIONS: function_module = webui_app.state.FUNCTIONS[filter_id] else: function_module, function_type, frontmatter = ( load_function_module_by_id(filter_id) ) webui_app.state.FUNCTIONS[filter_id] = function_module # Check if the function has a file_handler variable if hasattr(function_module, "file_handler"): skip_files = function_module.file_handler if hasattr(function_module, "valves") and hasattr( function_module, "Valves" ): valves = Functions.get_function_valves_by_id(filter_id) function_module.valves = function_module.Valves( **(valves if valves else {}) ) try: if hasattr(function_module, "inlet"): inlet = function_module.inlet # Get the signature of the function sig = inspect.signature(inlet) params = {"body": body} if "__user__" in sig.parameters: __user__ = { "id": user.id, "email": user.email, "name": user.name, "role": user.role, } try: if hasattr(function_module, "UserValves"): __user__["valves"] = function_module.UserValves( **Functions.get_user_valves_by_id_and_user_id( filter_id, user.id ) ) except Exception as e: print(e) params = {**params, "__user__": __user__} if "__id__" in sig.parameters: params = { **params, "__id__": filter_id, } if "__model__" in sig.parameters: params = { **params, "__model__": model, } if "__event_emitter__" in sig.parameters: params = { **params, "__event_emitter__": __event_emitter__, } if "__event_call__" in sig.parameters: params = { **params, "__event_call__": __event_call__, } if inspect.iscoroutinefunction(inlet): body = await inlet(**params) else: body = inlet(**params) except Exception as e: print(f"Error: {e}") raise e if skip_files: if "files" in body: del body["files"] return body, {} async def chat_completion_tools_handler( body, model, user, __event_emitter__, __event_call__ ): skip_files = None contexts = [] citations = None task_model_id = get_task_model_id(body["model"]) # If tool_ids field is present, call the functions if "tool_ids" in body: print(body["tool_ids"]) for tool_id in body["tool_ids"]: print(tool_id) try: response, citation, file_handler = await get_function_call_response( messages=body["messages"], files=body.get("files", []), tool_id=tool_id, template=app.state.config.TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE, task_model_id=task_model_id, user=user, model=model, __event_emitter__=__event_emitter__, __event_call__=__event_call__, ) print(file_handler) if isinstance(response, str): contexts.append(response) if citation: if citations is None: citations = [citation] else: citations.append(citation) if file_handler: skip_files = True except Exception as e: print(f"Error: {e}") del body["tool_ids"] print(f"tool_contexts: {contexts}") if skip_files: if "files" in body: del body["files"] return body, { **({"contexts": contexts} if contexts is not None else {}), **({"citations": citations} if citations is not None else {}), } async def chat_completion_files_handler(body): contexts = [] citations = None if "files" in body: files = body["files"] del body["files"] contexts, citations = get_rag_context( files=files, messages=body["messages"], 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, ) log.debug(f"rag_contexts: {contexts}, citations: {citations}") return body, { **({"contexts": contexts} if contexts is not None else {}), **({"citations": citations} if citations is not None else {}), } class ChatCompletionMiddleware(BaseHTTPMiddleware): async def dispatch(self, request: Request, call_next): if request.method == "POST" and any( endpoint in request.url.path for endpoint in ["/ollama/api/chat", "/chat/completions"] ): log.debug(f"request.url.path: {request.url.path}") try: body, model, user = await get_body_and_model_and_user(request) except Exception as e: return JSONResponse( status_code=status.HTTP_400_BAD_REQUEST, content={"detail": str(e)}, ) # Extract session_id, chat_id and message_id from the request body session_id = None if "session_id" in body: session_id = body["session_id"] del body["session_id"] chat_id = None if "chat_id" in body: chat_id = body["chat_id"] del body["chat_id"] message_id = None if "id" in body: message_id = body["id"] del body["id"] async def __event_emitter__(data): await sio.emit( "chat-events", { "chat_id": chat_id, "message_id": message_id, "data": data, }, to=session_id, ) async def __event_call__(data): response = await sio.call( "chat-events", {"chat_id": chat_id, "message_id": message_id, "data": data}, to=session_id, ) return response # Initialize data_items to store additional data to be sent to the client data_items = [] # Initialize context, and citations contexts = [] citations = [] try: body, flags = await chat_completion_functions_handler( body, model, user, __event_emitter__, __event_call__ ) except Exception as e: return JSONResponse( status_code=status.HTTP_400_BAD_REQUEST, content={"detail": str(e)}, ) try: body, flags = await chat_completion_tools_handler( body, model, user, __event_emitter__, __event_call__ ) contexts.extend(flags.get("contexts", [])) citations.extend(flags.get("citations", [])) except Exception as e: print(e) pass try: body, flags = await chat_completion_files_handler(body) contexts.extend(flags.get("contexts", [])) citations.extend(flags.get("citations", [])) except Exception as e: print(e) pass # If context is not empty, insert it into the messages if len(contexts) > 0: context_string = "/n".join(contexts).strip() prompt = get_last_user_message(body["messages"]) body["messages"] = add_or_update_system_message( rag_template( rag_app.state.config.RAG_TEMPLATE, context_string, prompt ), body["messages"], ) # If there are citations, add them to the data_items if len(citations) > 0: data_items.append({"citations": citations}) modified_body_bytes = json.dumps(body).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 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, data_items), ) if "application/x-ndjson" in content_type: return StreamingResponse( self.ollama_stream_wrapper(response.body_iterator, data_items), ) return response else: return response # If it's not a chat completion request, just pass it through response = await call_next(request) 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, data_items): for item in data_items: yield f"data: {json.dumps(item)}\n\n" async for data in original_generator: yield data async def ollama_stream_wrapper(self, original_generator, data_items): for item in data_items: yield f"{json.dumps(item)}\n" async for data in original_generator: yield data app.add_middleware(ChatCompletionMiddleware) ################################## # # Pipeline Middleware # ################################## def filter_pipeline(payload, user): user = {"id": user.id, "email": user.email, "name": user.name, "role": user.role} model_id = payload["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"]) model = app.state.MODELS[model_id] if "pipeline" in model: sorted_filters.append(model) 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/inlet", headers=headers, json={ "user": user, "body": payload, }, ) r.raise_for_status() payload = r.json() except Exception as e: # Handle connection error here print(f"Connection error: {e}") if r is not None: try: res = r.json() except: pass if "detail" in res: raise Exception(r.status_code, res["detail"]) else: pass if "pipeline" not in app.state.MODELS[model_id]: if "task" in payload: del payload["task"] return payload class PipelineMiddleware(BaseHTTPMiddleware): async def dispatch(self, request: Request, call_next): if request.method == "POST" and ( "/ollama/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 {} user = get_current_user( request, get_http_authorization_cred(request.headers.get("Authorization")), ) try: data = filter_pipeline(data, user) except Exception as e: return JSONResponse( status_code=e.args[0], content={"detail": e.args[1]}, ) 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) return response async def _receive(self, body: bytes): return {"type": "http.request", "body": body, "more_body": False} app.add_middleware(PipelineMiddleware) app.add_middleware( CORSMiddleware, allow_origins=origins, allow_credentials=True, allow_methods=["*"], allow_headers=["*"], ) @app.middleware("http") async def commit_session_after_request(request: Request, call_next): response = await call_next(request) log.debug("Commit session after request") Session.commit() return response @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("/ws", socket_app) 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(): pipe_models = [] openai_models = [] ollama_models = [] pipe_models = await get_pipe_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 = pipe_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" pipe = None 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"] if "pipe" in model: pipe = model["pipe"] 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, **({"pipe": pipe} if pipe is not None else {}), } ) 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() # 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( filter( lambda model: model["id"] in app.state.config.MODEL_FILTER_LIST, models, ) ) return {"data": models} return {"data": models} @app.post("/api/chat/completions") async def generate_chat_completions(form_data: dict, user=Depends(get_verified_user)): model_id = form_data["model"] if model_id not in app.state.MODELS: raise HTTPException( status_code=status.HTTP_404_NOT_FOUND, detail="Model not found", ) model = app.state.MODELS[model_id] pipe = model.get("pipe") if pipe: return await generate_function_chat_completion(form_data, user=user) if model["owned_by"] == "ollama": return await generate_ollama_chat_completion(form_data, user=user) else: return await generate_openai_chat_completion(form_data, user=user) @app.post("/api/chat/completed") async def chat_completed(form_data: dict, user=Depends(get_verified_user)): data = form_data model_id = data["model"] if model_id not in app.state.MODELS: raise HTTPException( status_code=status.HTTP_404_NOT_FOUND, detail="Model not found", ) model = app.state.MODELS[model_id] 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"]) 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, "email": user.email, "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 async def __event_emitter__(data): await sio.emit( "chat-events", { "chat_id": data["chat_id"], "message_id": data["id"], "data": data, }, to=data["session_id"], ) async def __event_call__(data): response = await sio.call( "chat-events", {"chat_id": data["chat_id"], "message_id": data["id"], "data": data}, to=data["session_id"], ) return response def get_priority(function_id): function = Functions.get_function_by_id(function_id) if function is not None and hasattr(function, "valves"): return (function.valves if function.valves else {}).get("priority", 0) return 0 filter_ids = [function.id for function in Functions.get_global_filter_functions()] if "info" in model and "meta" in model["info"]: filter_ids.extend(model["info"]["meta"].get("filterIds", [])) filter_ids = list(set(filter_ids)) enabled_filter_ids = [ function.id for function in Functions.get_functions_by_type("filter", active_only=True) ] filter_ids = [ filter_id for filter_id in filter_ids if filter_id in enabled_filter_ids ] # Sort filter_ids by priority, using the get_priority function filter_ids.sort(key=get_priority) for filter_id in filter_ids: filter = Functions.get_function_by_id(filter_id) if filter: if filter_id in webui_app.state.FUNCTIONS: function_module = webui_app.state.FUNCTIONS[filter_id] else: function_module, function_type, frontmatter = ( load_function_module_by_id(filter_id) ) webui_app.state.FUNCTIONS[filter_id] = function_module if hasattr(function_module, "valves") and hasattr( function_module, "Valves" ): valves = Functions.get_function_valves_by_id(filter_id) function_module.valves = function_module.Valves( **(valves if valves else {}) ) try: if hasattr(function_module, "outlet"): outlet = function_module.outlet # Get the signature of the function sig = inspect.signature(outlet) params = {"body": data} if "__user__" in sig.parameters: __user__ = { "id": user.id, "email": user.email, "name": user.name, "role": user.role, } try: if hasattr(function_module, "UserValves"): __user__["valves"] = function_module.UserValves( **Functions.get_user_valves_by_id_and_user_id( filter_id, user.id ) ) except Exception as e: print(e) params = {**params, "__user__": __user__} if "__id__" in sig.parameters: params = { **params, "__id__": filter_id, } if "__model__" in sig.parameters: params = { **params, "__model__": model, } if "__event_emitter__" in sig.parameters: params = { **params, "__event_emitter__": __event_emitter__, } if "__event_call__" in sig.parameters: params = { **params, "__event_call__": __event_call__, } if inspect.iscoroutinefunction(outlet): data = await outlet(**params) else: data = outlet(**params) except Exception as e: print(f"Error: {e}") return JSONResponse( status_code=status.HTTP_400_BAD_REQUEST, content={"detail": str(e)}, ) return data ################################## # # Task Endpoints # ################################## # TODO: Refactor task API endpoints below into a separate file @app.get("/api/task/config") async def get_task_config(user=Depends(get_verified_user)): return { "TASK_MODEL": app.state.config.TASK_MODEL, "TASK_MODEL_EXTERNAL": app.state.config.TASK_MODEL_EXTERNAL, "TITLE_GENERATION_PROMPT_TEMPLATE": app.state.config.TITLE_GENERATION_PROMPT_TEMPLATE, "SEARCH_QUERY_GENERATION_PROMPT_TEMPLATE": app.state.config.SEARCH_QUERY_GENERATION_PROMPT_TEMPLATE, "SEARCH_QUERY_PROMPT_LENGTH_THRESHOLD": app.state.config.SEARCH_QUERY_PROMPT_LENGTH_THRESHOLD, "TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE": app.state.config.TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE, } class TaskConfigForm(BaseModel): TASK_MODEL: Optional[str] TASK_MODEL_EXTERNAL: Optional[str] TITLE_GENERATION_PROMPT_TEMPLATE: str SEARCH_QUERY_GENERATION_PROMPT_TEMPLATE: str SEARCH_QUERY_PROMPT_LENGTH_THRESHOLD: int TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE: str @app.post("/api/task/config/update") async def update_task_config(form_data: TaskConfigForm, user=Depends(get_admin_user)): app.state.config.TASK_MODEL = form_data.TASK_MODEL app.state.config.TASK_MODEL_EXTERNAL = form_data.TASK_MODEL_EXTERNAL app.state.config.TITLE_GENERATION_PROMPT_TEMPLATE = ( form_data.TITLE_GENERATION_PROMPT_TEMPLATE ) app.state.config.SEARCH_QUERY_GENERATION_PROMPT_TEMPLATE = ( form_data.SEARCH_QUERY_GENERATION_PROMPT_TEMPLATE ) app.state.config.SEARCH_QUERY_PROMPT_LENGTH_THRESHOLD = ( form_data.SEARCH_QUERY_PROMPT_LENGTH_THRESHOLD ) app.state.config.TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE = ( form_data.TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE ) return { "TASK_MODEL": app.state.config.TASK_MODEL, "TASK_MODEL_EXTERNAL": app.state.config.TASK_MODEL_EXTERNAL, "TITLE_GENERATION_PROMPT_TEMPLATE": app.state.config.TITLE_GENERATION_PROMPT_TEMPLATE, "SEARCH_QUERY_GENERATION_PROMPT_TEMPLATE": app.state.config.SEARCH_QUERY_GENERATION_PROMPT_TEMPLATE, "SEARCH_QUERY_PROMPT_LENGTH_THRESHOLD": app.state.config.SEARCH_QUERY_PROMPT_LENGTH_THRESHOLD, "TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE": app.state.config.TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE, } @app.post("/api/task/title/completions") async def generate_title(form_data: dict, user=Depends(get_verified_user)): print("generate_title") model_id = form_data["model"] if model_id not in app.state.MODELS: raise HTTPException( status_code=status.HTTP_404_NOT_FOUND, detail="Model not found", ) # Check if the user has a custom task model # If the user has a custom task model, use that model if app.state.MODELS[model_id]["owned_by"] == "ollama": if app.state.config.TASK_MODEL: task_model_id = app.state.config.TASK_MODEL if task_model_id in app.state.MODELS: model_id = task_model_id else: if app.state.config.TASK_MODEL_EXTERNAL: task_model_id = app.state.config.TASK_MODEL_EXTERNAL if task_model_id in app.state.MODELS: model_id = task_model_id print(model_id) model = app.state.MODELS[model_id] template = app.state.config.TITLE_GENERATION_PROMPT_TEMPLATE content = title_generation_template( template, form_data["prompt"], { "name": user.name, "location": user.info.get("location") if user.info else None, }, ) payload = { "model": model_id, "messages": [{"role": "user", "content": content}], "stream": False, "max_tokens": 50, "chat_id": form_data.get("chat_id", None), "task": TASKS.TITLE_GENERATION, } log.debug(payload) try: payload = filter_pipeline(payload, user) except Exception as e: return JSONResponse( status_code=e.args[0], content={"detail": e.args[1]}, ) if "chat_id" in payload: del payload["chat_id"] return await generate_chat_completions(form_data=payload, user=user) @app.post("/api/task/query/completions") async def generate_search_query(form_data: dict, user=Depends(get_verified_user)): print("generate_search_query") if len(form_data["prompt"]) < app.state.config.SEARCH_QUERY_PROMPT_LENGTH_THRESHOLD: raise HTTPException( status_code=status.HTTP_400_BAD_REQUEST, detail=f"Skip search query generation for short prompts (< {app.state.config.SEARCH_QUERY_PROMPT_LENGTH_THRESHOLD} characters)", ) model_id = form_data["model"] if model_id not in app.state.MODELS: raise HTTPException( status_code=status.HTTP_404_NOT_FOUND, detail="Model not found", ) # Check if the user has a custom task model # If the user has a custom task model, use that model if app.state.MODELS[model_id]["owned_by"] == "ollama": if app.state.config.TASK_MODEL: task_model_id = app.state.config.TASK_MODEL if task_model_id in app.state.MODELS: model_id = task_model_id else: if app.state.config.TASK_MODEL_EXTERNAL: task_model_id = app.state.config.TASK_MODEL_EXTERNAL if task_model_id in app.state.MODELS: model_id = task_model_id print(model_id) model = app.state.MODELS[model_id] template = app.state.config.SEARCH_QUERY_GENERATION_PROMPT_TEMPLATE content = search_query_generation_template( template, form_data["prompt"], {"name": user.name} ) payload = { "model": model_id, "messages": [{"role": "user", "content": content}], "stream": False, "max_tokens": 30, "task": TASKS.QUERY_GENERATION, } print(payload) try: payload = filter_pipeline(payload, user) except Exception as e: return JSONResponse( status_code=e.args[0], content={"detail": e.args[1]}, ) if "chat_id" in payload: del payload["chat_id"] return await generate_chat_completions(form_data=payload, user=user) @app.post("/api/task/emoji/completions") async def generate_emoji(form_data: dict, user=Depends(get_verified_user)): print("generate_emoji") model_id = form_data["model"] if model_id not in app.state.MODELS: raise HTTPException( status_code=status.HTTP_404_NOT_FOUND, detail="Model not found", ) # Check if the user has a custom task model # If the user has a custom task model, use that model if app.state.MODELS[model_id]["owned_by"] == "ollama": if app.state.config.TASK_MODEL: task_model_id = app.state.config.TASK_MODEL if task_model_id in app.state.MODELS: model_id = task_model_id else: if app.state.config.TASK_MODEL_EXTERNAL: task_model_id = app.state.config.TASK_MODEL_EXTERNAL if task_model_id in app.state.MODELS: model_id = task_model_id print(model_id) model = app.state.MODELS[model_id] template = ''' Your task is to reflect the speaker's likely facial expression through a fitting emoji. Interpret emotions from the message and reflect their facial expression using fitting, diverse emojis (e.g., 😊, 😢, 😡, 😱). Message: """{{prompt}}""" ''' content = title_generation_template( template, form_data["prompt"], { "name": user.name, "location": user.info.get("location") if user.info else None, }, ) payload = { "model": model_id, "messages": [{"role": "user", "content": content}], "stream": False, "max_tokens": 4, "chat_id": form_data.get("chat_id", None), "task": TASKS.EMOJI_GENERATION, } log.debug(payload) try: payload = filter_pipeline(payload, user) except Exception as e: return JSONResponse( status_code=e.args[0], content={"detail": e.args[1]}, ) if "chat_id" in payload: del payload["chat_id"] return await generate_chat_completions(form_data=payload, user=user) @app.post("/api/task/tools/completions") async def get_tools_function_calling(form_data: dict, user=Depends(get_verified_user)): print("get_tools_function_calling") model_id = form_data["model"] if model_id not in app.state.MODELS: raise HTTPException( status_code=status.HTTP_404_NOT_FOUND, detail="Model not found", ) # Check if the user has a custom task model # If the user has a custom task model, use that model if app.state.MODELS[model_id]["owned_by"] == "ollama": if app.state.config.TASK_MODEL: task_model_id = app.state.config.TASK_MODEL if task_model_id in app.state.MODELS: model_id = task_model_id else: if app.state.config.TASK_MODEL_EXTERNAL: task_model_id = app.state.config.TASK_MODEL_EXTERNAL if task_model_id in app.state.MODELS: model_id = task_model_id print(model_id) template = app.state.config.TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE try: context, citation, file_handler = await get_function_call_response( form_data["messages"], form_data.get("files", []), form_data["tool_id"], template, model_id, user, ) return context except Exception as e: return JSONResponse( status_code=e.args[0], content={"detail": e.args[1]}, ) ################################## # # Pipelines Endpoints # ################################## # TODO: Refactor pipelines API endpoints below into a separate file @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, ) ################################## # # Config Endpoints # ################################## @app.get("/api/config") async def get_app_config(): return { "status": True, "name": WEBUI_NAME, "version": VERSION, "default_locale": str(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, }, "audio": { "tts": { "engine": audio_app.state.config.TTS_ENGINE, "voice": audio_app.state.config.TTS_VOICE, }, "stt": { "engine": audio_app.state.config.STT_ENGINE, }, }, "oauth": { "providers": { name: config.get("name", name) for name, config in OAUTH_PROVIDERS.items() } }, } @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, } # TODO: webhook endpoint should be under config endpoints @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, ) ############################ # OAuth Login & Callback ############################ oauth = OAuth() for provider_name, provider_config in OAUTH_PROVIDERS.items(): oauth.register( name=provider_name, client_id=provider_config["client_id"], client_secret=provider_config["client_secret"], server_metadata_url=provider_config["server_metadata_url"], client_kwargs={ "scope": provider_config["scope"], }, ) # SessionMiddleware is used by authlib for oauth if len(OAUTH_PROVIDERS) > 0: app.add_middleware( SessionMiddleware, secret_key=WEBUI_SECRET_KEY, session_cookie="oui-session", same_site=WEBUI_SESSION_COOKIE_SAME_SITE, https_only=WEBUI_SESSION_COOKIE_SECURE, ) @app.get("/oauth/{provider}/login") async def oauth_login(provider: str, request: Request): if provider not in OAUTH_PROVIDERS: raise HTTPException(404) redirect_uri = request.url_for("oauth_callback", provider=provider) return await oauth.create_client(provider).authorize_redirect(request, redirect_uri) # OAuth login logic is as follows: # 1. Attempt to find a user with matching subject ID, tied to the provider # 2. If OAUTH_MERGE_ACCOUNTS_BY_EMAIL is true, find a user with the email address provided via OAuth # - This is considered insecure in general, as OAuth providers do not always verify email addresses # 3. If there is no user, and ENABLE_OAUTH_SIGNUP is true, create a user # - Email addresses are considered unique, so we fail registration if the email address is alreayd taken @app.get("/oauth/{provider}/callback") async def oauth_callback(provider: str, request: Request, response: Response): if provider not in OAUTH_PROVIDERS: raise HTTPException(404) client = oauth.create_client(provider) try: token = await client.authorize_access_token(request) except Exception as e: log.warning(f"OAuth callback error: {e}") raise HTTPException(400, detail=ERROR_MESSAGES.INVALID_CRED) user_data: UserInfo = token["userinfo"] sub = user_data.get("sub") if not sub: log.warning(f"OAuth callback failed, sub is missing: {user_data}") raise HTTPException(400, detail=ERROR_MESSAGES.INVALID_CRED) provider_sub = f"{provider}@{sub}" email = user_data.get("email", "").lower() # We currently mandate that email addresses are provided if not email: log.warning(f"OAuth callback failed, email is missing: {user_data}") raise HTTPException(400, detail=ERROR_MESSAGES.INVALID_CRED) # Check if the user exists user = Users.get_user_by_oauth_sub(provider_sub) if not user: # If the user does not exist, check if merging is enabled if OAUTH_MERGE_ACCOUNTS_BY_EMAIL.value: # Check if the user exists by email user = Users.get_user_by_email(email) if user: # Update the user with the new oauth sub Users.update_user_oauth_sub_by_id(user.id, provider_sub) if not user: # If the user does not exist, check if signups are enabled if ENABLE_OAUTH_SIGNUP.value: # Check if an existing user with the same email already exists existing_user = Users.get_user_by_email(user_data.get("email", "").lower()) if existing_user: raise HTTPException(400, detail=ERROR_MESSAGES.EMAIL_TAKEN) picture_claim = webui_app.state.config.OAUTH_PICTURE_CLAIM picture_url = user_data.get(picture_claim, "") if picture_url: # Download the profile image into a base64 string try: async with aiohttp.ClientSession() as session: async with session.get(picture_url) as resp: picture = await resp.read() base64_encoded_picture = base64.b64encode(picture).decode( "utf-8" ) guessed_mime_type = mimetypes.guess_type(picture_url)[0] if guessed_mime_type is None: # assume JPG, browsers are tolerant enough of image formats guessed_mime_type = "image/jpeg" picture_url = f"data:{guessed_mime_type};base64,{base64_encoded_picture}" except Exception as e: log.error(f"Error downloading profile image '{picture_url}': {e}") picture_url = "" if not picture_url: picture_url = "/user.png" username_claim = webui_app.state.config.OAUTH_USERNAME_CLAIM role = ( "admin" if Users.get_num_users() == 0 else webui_app.state.config.DEFAULT_USER_ROLE ) user = Auths.insert_new_auth( email=email, password=get_password_hash( str(uuid.uuid4()) ), # Random password, not used name=user_data.get(username_claim, "User"), profile_image_url=picture_url, role=role, oauth_sub=provider_sub, ) if webui_app.state.config.WEBHOOK_URL: post_webhook( webui_app.state.config.WEBHOOK_URL, WEBHOOK_MESSAGES.USER_SIGNUP(user.name), { "action": "signup", "message": WEBHOOK_MESSAGES.USER_SIGNUP(user.name), "user": user.model_dump_json(exclude_none=True), }, ) else: raise HTTPException( status.HTTP_403_FORBIDDEN, detail=ERROR_MESSAGES.ACCESS_PROHIBITED ) jwt_token = create_token( data={"id": user.id}, expires_delta=parse_duration(webui_app.state.config.JWT_EXPIRES_IN), ) # Set the cookie token response.set_cookie( key="token", value=jwt_token, httponly=True, # Ensures the cookie is not accessible via JavaScript ) # Redirect back to the frontend with the JWT token redirect_url = f"{request.base_url}auth#token={jwt_token}" return RedirectResponse(url=redirect_url) @app.get("/manifest.json") async def get_manifest_json(): return { "name": WEBUI_NAME, "short_name": WEBUI_NAME, "start_url": "/", "display": "standalone", "background_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""" {WEBUI_NAME} Search {WEBUI_NAME} UTF-8 {WEBUI_URL}/static/favicon.png {WEBUI_URL} """ return Response(content=xml_content, media_type="application/xml") @app.get("/health") async def healthcheck(): return {"status": True} @app.get("/health/db") async def healthcheck_with_db(): Session.execute(text("SELECT 1;")).all() 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." )