import logging import sys import inspect import json from pydantic import BaseModel from typing import AsyncGenerator, Generator, Iterator from fastapi import ( Depends, FastAPI, File, Form, HTTPException, Request, UploadFile, status, ) from starlette.responses import Response, StreamingResponse from open_webui.socket.main import ( get_event_call, get_event_emitter, ) from open_webui.models.functions import Functions from open_webui.models.models import Models from open_webui.utils.plugin import load_function_module_by_id from open_webui.utils.tools import get_tools from open_webui.utils.access_control import has_access from open_webui.env import SRC_LOG_LEVELS, GLOBAL_LOG_LEVEL from open_webui.utils.misc import ( add_or_update_system_message, get_last_user_message, prepend_to_first_user_message_content, openai_chat_chunk_message_template, openai_chat_completion_message_template, ) from open_webui.utils.payload import ( apply_model_params_to_body_openai, apply_model_system_prompt_to_body, ) logging.basicConfig(stream=sys.stdout, level=GLOBAL_LOG_LEVEL) log = logging.getLogger(__name__) log.setLevel(SRC_LOG_LEVELS["MAIN"]) def get_function_module_by_id(request: Request, pipe_id: str): # Check if function is already loaded if pipe_id not in request.app.state.FUNCTIONS: function_module, _, _ = load_function_module_by_id(pipe_id) request.app.state.FUNCTIONS[pipe_id] = function_module else: function_module = request.app.state.FUNCTIONS[pipe_id] if hasattr(function_module, "valves") and hasattr(function_module, "Valves"): valves = Functions.get_function_valves_by_id(pipe_id) function_module.valves = function_module.Valves(**(valves if valves else {})) return function_module async def get_function_models(request): pipes = Functions.get_functions_by_type("pipe", active_only=True) pipe_models = [] for pipe in pipes: function_module = get_function_module_by_id(request, pipe.id) # Check if function is a manifold if hasattr(function_module, "pipes"): sub_pipes = [] # Check if pipes is a function or a list try: if callable(function_module.pipes): sub_pipes = function_module.pipes() else: sub_pipes = function_module.pipes except Exception as e: log.exception(e) sub_pipes = [] log.debug( f"get_function_models: function '{pipe.id}' is a manifold of {sub_pipes}" ) for p in sub_pipes: sub_pipe_id = f'{pipe.id}.{p["id"]}' sub_pipe_name = p["name"] if hasattr(function_module, "name"): sub_pipe_name = f"{function_module.name}{sub_pipe_name}" pipe_flag = {"type": pipe.type} pipe_models.append( { "id": sub_pipe_id, "name": sub_pipe_name, "object": "model", "created": pipe.created_at, "owned_by": "openai", "pipe": pipe_flag, } ) else: pipe_flag = {"type": "pipe"} log.debug( f"get_function_models: function '{pipe.id}' is a single pipe {{ 'id': {pipe.id}, 'name': {pipe.name} }}" ) pipe_models.append( { "id": pipe.id, "name": pipe.name, "object": "model", "created": pipe.created_at, "owned_by": "openai", "pipe": pipe_flag, } ) return pipe_models async def generate_function_chat_completion( request, form_data, user, models: dict = {} ): async def execute_pipe(pipe, params): if inspect.iscoroutinefunction(pipe): return await pipe(**params) else: return pipe(**params) async def get_message_content(res: str | Generator | AsyncGenerator) -> str: if isinstance(res, str): return res if isinstance(res, Generator): return "".join(map(str, res)) if isinstance(res, AsyncGenerator): return "".join([str(stream) async for stream in res]) def process_line(form_data: dict, line): if isinstance(line, BaseModel): line = line.model_dump_json() line = f"data: {line}" if isinstance(line, dict): line = f"data: {json.dumps(line)}" try: line = line.decode("utf-8") except Exception: pass if line.startswith("data:"): return f"{line}\n\n" else: line = openai_chat_chunk_message_template(form_data["model"], line) return f"data: {json.dumps(line)}\n\n" def get_pipe_id(form_data: dict) -> str: pipe_id = form_data["model"] if "." in pipe_id: pipe_id, _ = pipe_id.split(".", 1) return pipe_id def get_function_params(function_module, form_data, user, extra_params=None): if extra_params is None: extra_params = {} pipe_id = get_pipe_id(form_data) # Get the signature of the function sig = inspect.signature(function_module.pipe) params = {"body": form_data} | { k: v for k, v in extra_params.items() if k in sig.parameters } if "__user__" in params and hasattr(function_module, "UserValves"): user_valves = Functions.get_user_valves_by_id_and_user_id(pipe_id, user.id) try: params["__user__"]["valves"] = function_module.UserValves(**user_valves) except Exception as e: log.exception(e) params["__user__"]["valves"] = function_module.UserValves() return params model_id = form_data.get("model") model_info = Models.get_model_by_id(model_id) metadata = form_data.pop("metadata", {}) files = metadata.get("files", []) tool_ids = metadata.get("tool_ids", []) # Check if tool_ids is None if tool_ids is None: tool_ids = [] __event_emitter__ = None __event_call__ = None __task__ = None __task_body__ = None if metadata: if all(k in metadata for k in ("session_id", "chat_id", "message_id")): __event_emitter__ = get_event_emitter(metadata) __event_call__ = get_event_call(metadata) __task__ = metadata.get("task", None) __task_body__ = metadata.get("task_body", None) extra_params = { "__event_emitter__": __event_emitter__, "__event_call__": __event_call__, "__task__": __task__, "__task_body__": __task_body__, "__files__": files, "__user__": { "id": user.id, "email": user.email, "name": user.name, "role": user.role, }, "__metadata__": metadata, "__request__": request, } extra_params["__tools__"] = get_tools( request, tool_ids, user, { **extra_params, "__model__": models.get(form_data["model"], None), "__messages__": form_data["messages"], "__files__": files, }, ) if model_info: if model_info.base_model_id: form_data["model"] = model_info.base_model_id params = model_info.params.model_dump() form_data = apply_model_params_to_body_openai(params, form_data) form_data = apply_model_system_prompt_to_body(params, form_data, user) pipe_id = get_pipe_id(form_data) function_module = get_function_module_by_id(request, pipe_id) pipe = function_module.pipe params = get_function_params(function_module, form_data, user, extra_params) if form_data.get("stream", False): async def stream_content(): try: res = await execute_pipe(pipe, params) # Directly return if the response is a StreamingResponse if isinstance(res, StreamingResponse): async for data in res.body_iterator: yield data return if isinstance(res, dict): yield f"data: {json.dumps(res)}\n\n" return except Exception as e: log.error(f"Error: {e}") yield f"data: {json.dumps({'error': {'detail':str(e)}})}\n\n" return if isinstance(res, str): message = openai_chat_chunk_message_template(form_data["model"], res) yield f"data: {json.dumps(message)}\n\n" if isinstance(res, Iterator): for line in res: yield process_line(form_data, line) if isinstance(res, AsyncGenerator): async for line in res: yield process_line(form_data, line) if isinstance(res, str) or isinstance(res, Generator): finish_message = openai_chat_chunk_message_template( form_data["model"], "" ) finish_message["choices"][0]["finish_reason"] = "stop" yield f"data: {json.dumps(finish_message)}\n\n" yield "data: [DONE]" return StreamingResponse(stream_content(), media_type="text/event-stream") else: try: res = await execute_pipe(pipe, params) except Exception as e: log.error(f"Error: {e}") return {"error": {"detail": str(e)}} if isinstance(res, StreamingResponse) or isinstance(res, dict): return res if isinstance(res, BaseModel): return res.model_dump() message = await get_message_content(res) return openai_chat_completion_message_template(form_data["model"], message)