| import base64 |
| import uuid |
| from contextlib import asynccontextmanager |
|
|
| from authlib.integrations.starlette_client import OAuth |
| from authlib.oidc.core import UserInfo |
| import json |
| import time |
| import os |
| import sys |
| import logging |
| import aiohttp |
| import requests |
| import mimetypes |
| import shutil |
| import inspect |
|
|
| 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.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 app as socket_app, get_event_emitter, get_event_call |
| from apps.ollama.main import ( |
| app as ollama_app, |
| 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 |
|
|
|
|
| from pydantic import BaseModel |
| from typing import List, Optional |
|
|
| from apps.webui.models.auths import Auths |
| from apps.webui.models.models import Models |
| 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, |
| prepend_to_first_user_message_content, |
| parse_duration, |
| ) |
|
|
| from apps.rag.utils import get_rag_context, rag_template |
|
|
| from config import ( |
| WEBUI_NAME, |
| WEBUI_URL, |
| WEBUI_AUTH, |
| ENV, |
| VERSION, |
| CHANGELOG, |
| FRONTEND_BUILD_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, |
| ENABLE_ADMIN_CHAT_ACCESS, |
| AppConfig, |
| ) |
|
|
| 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 = ["*"] |
|
|
|
|
| |
| |
| |
| |
| |
|
|
|
|
| async def get_body_and_model_and_user(request): |
| |
| 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 Exception("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): |
| |
| task_model_id = default_model_id |
| |
| 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, |
| __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": str(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"] |
|
|
| |
| if response.background is not None: |
| await response.background() |
| else: |
| content = response["choices"][0]["message"]["content"] |
|
|
| if content is None: |
| return None, None, False |
|
|
| |
| print(f"content: {content}") |
| result = json.loads(content) |
| print(result) |
|
|
| citation = None |
|
|
| if "name" not in result: |
| return None, None, False |
|
|
| |
| if tool_id in webui_app.state.TOOLS: |
| toolkit_module = webui_app.state.TOOLS[tool_id] |
| else: |
| toolkit_module, _ = load_toolkit_module_by_id(tool_id) |
| webui_app.state.TOOLS[tool_id] = toolkit_module |
|
|
| file_handler = False |
| |
| 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: |
| |
| sig = inspect.signature(function) |
| params = result["parameters"] |
|
|
| |
| extra_params = { |
| "__model__": model, |
| "__id__": tool_id, |
| "__messages__": messages, |
| "__files__": files, |
| "__event_emitter__": __event_emitter__, |
| "__event_call__": __event_call__, |
| } |
|
|
| |
| for key, value in extra_params.items(): |
| if key in sig.parameters: |
| params[key] = value |
|
|
| if "__user__" in sig.parameters: |
| |
| __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 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) |
|
|
| |
| 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 not filter: |
| continue |
|
|
| if filter_id in webui_app.state.FUNCTIONS: |
| function_module = webui_app.state.FUNCTIONS[filter_id] |
| else: |
| function_module, _, _ = load_function_module_by_id(filter_id) |
| webui_app.state.FUNCTIONS[filter_id] = function_module |
|
|
| |
| 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 {}) |
| ) |
|
|
| if not hasattr(function_module, "inlet"): |
| continue |
|
|
| try: |
| inlet = function_module.inlet |
|
|
| |
| sig = inspect.signature(inlet) |
| params = {"body": body} |
|
|
| |
| extra_params = { |
| "__model__": model, |
| "__id__": filter_id, |
| "__event_emitter__": __event_emitter__, |
| "__event_call__": __event_call__, |
| } |
|
|
| |
| for key, value in extra_params.items(): |
| if key in sig.parameters: |
| params[key] = value |
|
|
| 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 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, user, __event_emitter__, __event_call__): |
| skip_files = None |
|
|
| contexts = [] |
| citations = None |
|
|
| task_model_id = get_task_model_id(body["model"]) |
|
|
| |
| 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, |
| __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)}, |
| ) |
|
|
| metadata = { |
| "chat_id": body.pop("chat_id", None), |
| "message_id": body.pop("id", None), |
| "session_id": body.pop("session_id", None), |
| "valves": body.pop("valves", None), |
| } |
|
|
| __event_emitter__ = get_event_emitter(metadata) |
| __event_call__ = get_event_call(metadata) |
|
|
| |
| data_items = [] |
|
|
| |
| 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, 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 len(contexts) > 0: |
| context_string = "/n".join(contexts).strip() |
| prompt = get_last_user_message(body["messages"]) |
|
|
| |
| |
| if model["owned_by"] == "ollama": |
| body["messages"] = prepend_to_first_user_message_content( |
| rag_template( |
| rag_app.state.config.RAG_TEMPLATE, context_string, prompt |
| ), |
| body["messages"], |
| ) |
| else: |
| body["messages"] = add_or_update_system_message( |
| rag_template( |
| rag_app.state.config.RAG_TEMPLATE, context_string, prompt |
| ), |
| body["messages"], |
| ) |
|
|
| |
| if len(citations) > 0: |
| data_items.append({"citations": citations}) |
|
|
| body["metadata"] = metadata |
| modified_body_bytes = json.dumps(body).encode("utf-8") |
| |
| request._body = modified_body_bytes |
| |
| 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): |
| |
| 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 |
|
|
| |
| 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) |
|
|
| |
| |
| |
| |
| |
|
|
|
|
| def get_sorted_filters(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"]) |
| return sorted_filters |
|
|
|
|
| def filter_pipeline(payload, user): |
| user = {"id": user.id, "email": user.email, "name": user.name, "role": user.role} |
| model_id = payload["model"] |
| sorted_filters = get_sorted_filters(model_id) |
|
|
| 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: |
| |
| print(f"Connection error: {e}") |
|
|
| if r is not None: |
| res = r.json() |
| if "detail" in res: |
| raise Exception(r.status_code, res["detail"]) |
|
|
| 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}") |
|
|
| |
| body = await request.body() |
| |
| body_str = body.decode("utf-8") |
| |
| 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") |
| |
| request._body = modified_body_bytes |
| |
| 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 |
|
|
| global_action_ids = [ |
| function.id for function in Functions.get_global_action_functions() |
| ] |
| enabled_action_ids = [ |
| function.id |
| for function in Functions.get_functions_by_type("action", active_only=True) |
| ] |
|
|
| custom_models = Models.get_all_models() |
| for custom_model in custom_models: |
| if custom_model.base_model_id is 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() |
|
|
| action_ids = [] |
| if "info" in model and "meta" in model["info"]: |
| action_ids.extend(model["info"]["meta"].get("actionIds", [])) |
|
|
| model["action_ids"] = action_ids |
| else: |
| owned_by = "openai" |
| pipe = None |
| action_ids = [] |
|
|
| 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"] |
|
|
| if "info" in model and "meta" in model["info"]: |
| action_ids.extend(model["info"]["meta"].get("actionIds", [])) |
| 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 {}), |
| "action_ids": action_ids, |
| } |
| ) |
|
|
| for model in models: |
| action_ids = [] |
| if "action_ids" in model: |
| action_ids = model["action_ids"] |
| del model["action_ids"] |
|
|
| action_ids = action_ids + global_action_ids |
| action_ids = list(set(action_ids)) |
| action_ids = [ |
| action_id for action_id in action_ids if action_id in enabled_action_ids |
| ] |
|
|
| model["actions"] = [] |
| for action_id in action_ids: |
| action = Functions.get_function_by_id(action_id) |
|
|
| if action_id in webui_app.state.FUNCTIONS: |
| function_module = webui_app.state.FUNCTIONS[action_id] |
| else: |
| function_module, _, _ = load_function_module_by_id(action_id) |
| webui_app.state.FUNCTIONS[action_id] = function_module |
|
|
| if hasattr(function_module, "actions"): |
| actions = function_module.actions |
| model["actions"].extend( |
| [ |
| { |
| "id": f"{action_id}.{_action['id']}", |
| "name": _action.get( |
| "name", f"{action.name} ({_action['id']})" |
| ), |
| "description": action.meta.description, |
| "icon_url": _action.get( |
| "icon_url", action.meta.manifest.get("icon_url", None) |
| ), |
| } |
| for _action in actions |
| ] |
| ) |
| else: |
| model["actions"].append( |
| { |
| "id": action_id, |
| "name": action.name, |
| "description": action.meta.description, |
| "icon_url": action.meta.manifest.get("icon_url", None), |
| } |
| ) |
|
|
| 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() |
|
|
| |
| 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] |
|
|
| |
| task = None |
| if "task" in form_data: |
| task = form_data["task"] |
| del form_data["task"] |
|
|
| if task: |
| if "metadata" in form_data: |
| form_data["metadata"]["task"] = task |
| else: |
| form_data["metadata"] = {"task": task} |
|
|
| if model.get("pipe"): |
| return await generate_function_chat_completion(form_data, user=user) |
| if model["owned_by"] == "ollama": |
| print("generate_ollama_chat_completion") |
| 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] |
|
|
| sorted_filters = get_sorted_filters(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, |
| "email": user.email, |
| "role": user.role, |
| }, |
| "body": data, |
| }, |
| ) |
|
|
| r.raise_for_status() |
| data = r.json() |
| except Exception as e: |
| |
| 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 Exception: |
| pass |
|
|
| else: |
| pass |
|
|
| __event_emitter__ = get_event_emitter( |
| { |
| "chat_id": data["chat_id"], |
| "message_id": data["id"], |
| "session_id": data["session_id"], |
| } |
| ) |
|
|
| __event_call__ = get_event_call( |
| { |
| "chat_id": data["chat_id"], |
| "message_id": data["id"], |
| "session_id": data["session_id"], |
| } |
| ) |
|
|
| 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) |
|
|
| for filter_id in filter_ids: |
| filter = Functions.get_function_by_id(filter_id) |
| if not filter: |
| continue |
|
|
| if filter_id in webui_app.state.FUNCTIONS: |
| function_module = webui_app.state.FUNCTIONS[filter_id] |
| else: |
| function_module, _, _ = 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 {}) |
| ) |
|
|
| if not hasattr(function_module, "outlet"): |
| continue |
| try: |
| outlet = function_module.outlet |
|
|
| |
| sig = inspect.signature(outlet) |
| params = {"body": data} |
|
|
| |
| extra_params = { |
| "__model__": model, |
| "__id__": filter_id, |
| "__event_emitter__": __event_emitter__, |
| "__event_call__": __event_call__, |
| } |
|
|
| |
| for key, value in extra_params.items(): |
| if key in sig.parameters: |
| params[key] = value |
|
|
| 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 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 |
|
|
|
|
| @app.post("/api/chat/actions/{action_id}") |
| async def chat_action(action_id: str, form_data: dict, user=Depends(get_verified_user)): |
| if "." in action_id: |
| action_id, sub_action_id = action_id.split(".") |
| else: |
| sub_action_id = None |
|
|
| action = Functions.get_function_by_id(action_id) |
| if not action: |
| raise HTTPException( |
| status_code=status.HTTP_404_NOT_FOUND, |
| detail="Action not found", |
| ) |
|
|
| 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] |
|
|
| __event_emitter__ = get_event_emitter( |
| { |
| "chat_id": data["chat_id"], |
| "message_id": data["id"], |
| "session_id": data["session_id"], |
| } |
| ) |
| __event_call__ = get_event_call( |
| { |
| "chat_id": data["chat_id"], |
| "message_id": data["id"], |
| "session_id": data["session_id"], |
| } |
| ) |
|
|
| if action_id in webui_app.state.FUNCTIONS: |
| function_module = webui_app.state.FUNCTIONS[action_id] |
| else: |
| function_module, _, _ = load_function_module_by_id(action_id) |
| webui_app.state.FUNCTIONS[action_id] = function_module |
|
|
| if hasattr(function_module, "valves") and hasattr(function_module, "Valves"): |
| valves = Functions.get_function_valves_by_id(action_id) |
| function_module.valves = function_module.Valves(**(valves if valves else {})) |
|
|
| if hasattr(function_module, "action"): |
| try: |
| action = function_module.action |
|
|
| |
| sig = inspect.signature(action) |
| params = {"body": data} |
|
|
| |
| extra_params = { |
| "__model__": model, |
| "__id__": sub_action_id if sub_action_id is not None else action_id, |
| "__event_emitter__": __event_emitter__, |
| "__event_call__": __event_call__, |
| } |
|
|
| |
| for key, value in extra_params.items(): |
| if key in sig.parameters: |
| params[key] = value |
|
|
| 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( |
| action_id, user.id |
| ) |
| ) |
| except Exception as e: |
| print(e) |
|
|
| params = {**params, "__user__": __user__} |
|
|
| if inspect.iscoroutinefunction(action): |
| data = await action(**params) |
| else: |
| data = action(**params) |
|
|
| except Exception as e: |
| print(f"Error: {e}") |
| return JSONResponse( |
| status_code=status.HTTP_400_BAD_REQUEST, |
| content={"detail": str(e)}, |
| ) |
|
|
| return data |
|
|
|
|
| |
| |
| |
| |
| |
|
|
|
|
| |
|
|
|
|
| @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", |
| ) |
|
|
| |
| |
| model_id = get_task_model_id(model_id) |
|
|
| print(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": str(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", |
| ) |
|
|
| |
| |
| model_id = get_task_model_id(model_id) |
|
|
| print(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": str(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", |
| ) |
|
|
| |
| |
| model_id = get_task_model_id(model_id) |
|
|
| print(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": str(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", |
| ) |
|
|
| |
| |
| model_id = get_task_model_id(model_id) |
|
|
| print(model_id) |
| template = app.state.config.TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE |
|
|
| try: |
| context, _, _ = 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]}, |
| ) |
|
|
|
|
| |
| |
| |
| |
| |
|
|
|
|
| |
|
|
|
|
| @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 is not 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) |
| |
| 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) |
|
|
| r = None |
| try: |
| |
| 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: |
| |
| print(f"Connection error: {e}") |
|
|
| detail = "Pipeline not found" |
| status_code = status.HTTP_404_NOT_FOUND |
| if r is not None: |
| status_code = r.status_code |
| try: |
| res = r.json() |
| if "detail" in res: |
| detail = res["detail"] |
| except Exception: |
| pass |
|
|
| raise HTTPException( |
| status_code=status_code, |
| detail=detail, |
| ) |
| finally: |
| |
| 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: |
| |
| 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 Exception: |
| 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: |
| |
| 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 Exception: |
| 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: |
| 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: |
| |
| 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 Exception: |
| 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), |
| ): |
| 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: |
| |
| 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), |
| ): |
| 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: |
| |
| 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 Exception: |
| 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), |
| ): |
| 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: |
| |
| 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 Exception: |
| 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(): |
| 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_login_form": webui_app.state.config.ENABLE_LOGIN_FORM, |
| "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, |
| "enable_admin_chat_access": ENABLE_ADMIN_CHAT_ACCESS, |
| }, |
| "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, |
| } |
|
|
|
|
| |
|
|
|
|
| @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_version(): |
| 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: |
| raise HTTPException( |
| status_code=status.HTTP_503_SERVICE_UNAVAILABLE, |
| detail=ERROR_MESSAGES.RATE_LIMIT_EXCEEDED, |
| ) |
|
|
|
|
| |
| |
| |
|
|
| 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"], |
| }, |
| redirect_uri=provider_config["redirect_uri"], |
| ) |
|
|
| |
| 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 = OAUTH_PROVIDERS[provider].get("redirect_uri") or request.url_for( |
| "oauth_callback", provider=provider |
| ) |
| return await oauth.create_client(provider).authorize_redirect(request, redirect_uri) |
|
|
|
|
| |
| |
| |
| |
| |
| |
| @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() |
| |
| if not email: |
| log.warning(f"OAuth callback failed, email is missing: {user_data}") |
| raise HTTPException(400, detail=ERROR_MESSAGES.INVALID_CRED) |
|
|
| |
| user = Users.get_user_by_oauth_sub(provider_sub) |
|
|
| if not user: |
| |
| if OAUTH_MERGE_ACCOUNTS_BY_EMAIL.value: |
| |
| user = Users.get_user_by_email(email) |
| if user: |
| |
| Users.update_user_oauth_sub_by_id(user.id, provider_sub) |
|
|
| if not user: |
| |
| if ENABLE_OAUTH_SIGNUP.value: |
| |
| 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: |
| |
| 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: |
| |
| 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()) |
| ), |
| 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), |
| ) |
|
|
| |
| response.set_cookie( |
| key="token", |
| value=jwt_token, |
| httponly=True, |
| ) |
|
|
| |
| 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""" |
| <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}/static/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.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." |
| ) |
|
|