import time import logging import sys import asyncio from aiocache import cached from typing import Any, Optional import random import json import inspect from uuid import uuid4 from concurrent.futures import ThreadPoolExecutor from fastapi import Request from fastapi import BackgroundTasks from starlette.responses import Response, StreamingResponse from open_webui.models.chats import Chats from open_webui.models.users import Users from open_webui.socket.main import ( get_event_call, get_event_emitter, get_user_id_from_session_pool, ) from open_webui.routers.tasks import ( generate_queries, generate_title, generate_chat_tags, ) from open_webui.routers.retrieval import process_web_search, SearchForm from open_webui.utils.webhook import post_webhook from open_webui.models.users import UserModel from open_webui.models.functions import Functions from open_webui.models.models import Models from open_webui.retrieval.utils import get_sources_from_files from open_webui.utils.chat import generate_chat_completion from open_webui.utils.task import ( get_task_model_id, rag_template, tools_function_calling_generation_template, ) from open_webui.utils.misc import ( get_message_list, add_or_update_system_message, get_last_user_message, prepend_to_first_user_message_content, ) from open_webui.utils.tools import get_tools from open_webui.utils.plugin import load_function_module_by_id from open_webui.tasks import create_task from open_webui.config import DEFAULT_TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE from open_webui.env import ( SRC_LOG_LEVELS, GLOBAL_LOG_LEVEL, BYPASS_MODEL_ACCESS_CONTROL, WEBUI_URL, ) from open_webui.constants import TASKS logging.basicConfig(stream=sys.stdout, level=GLOBAL_LOG_LEVEL) log = logging.getLogger(__name__) log.setLevel(SRC_LOG_LEVELS["MAIN"]) async def chat_completion_filter_functions_handler(request, body, model, extra_params): skip_files = None 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"): # TODO: Fix FunctionModel 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 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 request.app.state.FUNCTIONS: function_module = request.app.state.FUNCTIONS[filter_id] else: function_module, _, _ = load_function_module_by_id(filter_id) request.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 # Apply valves to the function 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 hasattr(function_module, "inlet"): try: inlet = function_module.inlet # Create a dictionary of parameters to be passed to the function params = {"body": body} | { k: v for k, v in { **extra_params, "__model__": model, "__id__": filter_id, }.items() if k in inspect.signature(inlet).parameters } if "__user__" in params and hasattr(function_module, "UserValves"): try: params["__user__"]["valves"] = function_module.UserValves( **Functions.get_user_valves_by_id_and_user_id( filter_id, params["__user__"]["id"] ) ) except Exception as e: print(e) 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 and "files" in body.get("metadata", {}): del body["metadata"]["files"] return body, {} async def chat_completion_tools_handler( request: Request, body: dict, user: UserModel, models, extra_params: dict ) -> tuple[dict, dict]: async def get_content_from_response(response) -> Optional[str]: 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"] return content def get_tools_function_calling_payload(messages, task_model_id, content): user_message = get_last_user_message(messages) history = "\n".join( f"{message['role'].upper()}: \"\"\"{message['content']}\"\"\"" for message in messages[::-1][:4] ) prompt = f"History:\n{history}\nQuery: {user_message}" return { "model": task_model_id, "messages": [ {"role": "system", "content": content}, {"role": "user", "content": f"Query: {prompt}"}, ], "stream": False, "metadata": {"task": str(TASKS.FUNCTION_CALLING)}, } # If tool_ids field is present, call the functions metadata = body.get("metadata", {}) tool_ids = metadata.get("tool_ids", None) log.debug(f"{tool_ids=}") if not tool_ids: return body, {} skip_files = False sources = [] task_model_id = get_task_model_id( body["model"], request.app.state.config.TASK_MODEL, request.app.state.config.TASK_MODEL_EXTERNAL, models, ) tools = get_tools( request, tool_ids, user, { **extra_params, "__model__": models[task_model_id], "__messages__": body["messages"], "__files__": metadata.get("files", []), }, ) log.info(f"{tools=}") specs = [tool["spec"] for tool in tools.values()] tools_specs = json.dumps(specs) if request.app.state.config.TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE != "": template = request.app.state.config.TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE else: template = DEFAULT_TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE tools_function_calling_prompt = tools_function_calling_generation_template( template, tools_specs ) log.info(f"{tools_function_calling_prompt=}") payload = get_tools_function_calling_payload( body["messages"], task_model_id, tools_function_calling_prompt ) try: response = await generate_chat_completion(request, form_data=payload, user=user) log.debug(f"{response=}") content = await get_content_from_response(response) log.debug(f"{content=}") if not content: return body, {} try: content = content[content.find("{") : content.rfind("}") + 1] if not content: raise Exception("No JSON object found in the response") result = json.loads(content) tool_function_name = result.get("name", None) if tool_function_name not in tools: return body, {} tool_function_params = result.get("parameters", {}) try: required_params = ( tools[tool_function_name] .get("spec", {}) .get("parameters", {}) .get("required", []) ) tool_function = tools[tool_function_name]["callable"] tool_function_params = { k: v for k, v in tool_function_params.items() if k in required_params } tool_output = await tool_function(**tool_function_params) except Exception as e: tool_output = str(e) if isinstance(tool_output, str): if tools[tool_function_name]["citation"]: sources.append( { "source": { "name": f"TOOL:{tools[tool_function_name]['toolkit_id']}/{tool_function_name}" }, "document": [tool_output], "metadata": [ { "source": f"TOOL:{tools[tool_function_name]['toolkit_id']}/{tool_function_name}" } ], } ) else: sources.append( { "source": {}, "document": [tool_output], "metadata": [ { "source": f"TOOL:{tools[tool_function_name]['toolkit_id']}/{tool_function_name}" } ], } ) if tools[tool_function_name]["file_handler"]: skip_files = True except Exception as e: log.exception(f"Error: {e}") content = None except Exception as e: log.exception(f"Error: {e}") content = None log.debug(f"tool_contexts: {sources}") if skip_files and "files" in body.get("metadata", {}): del body["metadata"]["files"] return body, {"sources": sources} async def chat_web_search_handler( request: Request, form_data: dict, extra_params: dict, user ): event_emitter = extra_params["__event_emitter__"] await event_emitter( { "type": "status", "data": { "action": "web_search", "description": "Generating search query", "done": False, }, } ) messages = form_data["messages"] user_message = get_last_user_message(messages) queries = [] try: res = await generate_queries( request, { "model": form_data["model"], "messages": messages, "prompt": user_message, "type": "web_search", }, user, ) response = res["choices"][0]["message"]["content"] try: bracket_start = response.find("{") bracket_end = response.rfind("}") + 1 if bracket_start == -1 or bracket_end == -1: raise Exception("No JSON object found in the response") response = response[bracket_start:bracket_end] queries = json.loads(response) queries = queries.get("queries", []) except Exception as e: queries = [response] except Exception as e: log.exception(e) queries = [user_message] if len(queries) == 0: await event_emitter( { "type": "status", "data": { "action": "web_search", "description": "No search query generated", "done": True, }, } ) return searchQuery = queries[0] await event_emitter( { "type": "status", "data": { "action": "web_search", "description": 'Searching "{{searchQuery}}"', "query": searchQuery, "done": False, }, } ) try: # Offload process_web_search to a separate thread loop = asyncio.get_running_loop() with ThreadPoolExecutor() as executor: results = await loop.run_in_executor( executor, lambda: process_web_search( request, SearchForm( **{ "query": searchQuery, } ), user, ), ) if results: await event_emitter( { "type": "status", "data": { "action": "web_search", "description": "Searched {{count}} sites", "query": searchQuery, "urls": results["filenames"], "done": True, }, } ) files = form_data.get("files", []) files.append( { "collection_name": results["collection_name"], "name": searchQuery, "type": "web_search_results", "urls": results["filenames"], } ) form_data["files"] = files else: await event_emitter( { "type": "status", "data": { "action": "web_search", "description": "No search results found", "query": searchQuery, "done": True, "error": True, }, } ) except Exception as e: log.exception(e) await event_emitter( { "type": "status", "data": { "action": "web_search", "description": 'Error searching "{{searchQuery}}"', "query": searchQuery, "done": True, "error": True, }, } ) return form_data async def chat_completion_files_handler( request: Request, body: dict, user: UserModel ) -> tuple[dict, dict[str, list]]: sources = [] if files := body.get("metadata", {}).get("files", None): try: queries_response = await generate_queries( { "model": body["model"], "messages": body["messages"], "type": "retrieval", }, user, ) queries_response = queries_response["choices"][0]["message"]["content"] try: bracket_start = queries_response.find("{") bracket_end = queries_response.rfind("}") + 1 if bracket_start == -1 or bracket_end == -1: raise Exception("No JSON object found in the response") queries_response = queries_response[bracket_start:bracket_end] queries_response = json.loads(queries_response) except Exception as e: queries_response = {"queries": [queries_response]} queries = queries_response.get("queries", []) except Exception as e: queries = [] if len(queries) == 0: queries = [get_last_user_message(body["messages"])] sources = get_sources_from_files( files=files, queries=queries, embedding_function=request.app.state.EMBEDDING_FUNCTION, k=request.app.state.config.TOP_K, reranking_function=request.app.state.rf, r=request.app.state.config.RELEVANCE_THRESHOLD, hybrid_search=request.app.state.config.ENABLE_RAG_HYBRID_SEARCH, ) log.debug(f"rag_contexts:sources: {sources}") return body, {"sources": sources} def apply_params_to_form_data(form_data, model): params = form_data.pop("params", {}) if model.get("ollama"): form_data["options"] = params if "format" in params: form_data["format"] = params["format"] if "keep_alive" in params: form_data["keep_alive"] = params["keep_alive"] else: if "seed" in params: form_data["seed"] = params["seed"] if "stop" in params: form_data["stop"] = params["stop"] if "temperature" in params: form_data["temperature"] = params["temperature"] if "top_p" in params: form_data["top_p"] = params["top_p"] if "frequency_penalty" in params: form_data["frequency_penalty"] = params["frequency_penalty"] return form_data async def process_chat_payload(request, form_data, metadata, user, model): form_data = apply_params_to_form_data(form_data, model) log.debug(f"form_data: {form_data}") event_emitter = get_event_emitter(metadata) event_call = get_event_call(metadata) extra_params = { "__event_emitter__": event_emitter, "__event_call__": event_call, "__user__": { "id": user.id, "email": user.email, "name": user.name, "role": user.role, }, "__metadata__": metadata, "__request__": request, } # Initialize events to store additional event to be sent to the client # Initialize contexts and citation models = request.app.state.MODELS events = [] sources = [] user_message = get_last_user_message(form_data["messages"]) model_knowledge = model.get("info", {}).get("meta", {}).get("knowledge", False) if model_knowledge: await event_emitter( { "type": "status", "data": { "action": "knowledge_search", "query": user_message, "done": False, }, } ) knowledge_files = [] for item in model_knowledge: if item.get("collection_name"): knowledge_files.append( { "id": item.get("collection_name"), "name": item.get("name"), "legacy": True, } ) elif item.get("collection_names"): knowledge_files.append( { "name": item.get("name"), "type": "collection", "collection_names": item.get("collection_names"), "legacy": True, } ) else: knowledge_files.append(item) files = form_data.get("files", []) files.extend(knowledge_files) form_data["files"] = files features = form_data.pop("features", None) if features: if "web_search" in features and features["web_search"]: form_data = await chat_web_search_handler( request, form_data, extra_params, user ) try: form_data, flags = await chat_completion_filter_functions_handler( request, form_data, model, extra_params ) except Exception as e: return Exception(f"Error: {e}") tool_ids = form_data.pop("tool_ids", None) files = form_data.pop("files", None) # Remove files duplicates if files: files = list({json.dumps(f, sort_keys=True): f for f in files}.values()) metadata = { **metadata, "tool_ids": tool_ids, "files": files, } form_data["metadata"] = metadata try: form_data, flags = await chat_completion_tools_handler( request, form_data, user, models, extra_params ) sources.extend(flags.get("sources", [])) except Exception as e: log.exception(e) try: form_data, flags = await chat_completion_files_handler(request, form_data, user) sources.extend(flags.get("sources", [])) except Exception as e: log.exception(e) # If context is not empty, insert it into the messages if len(sources) > 0: context_string = "" for source_idx, source in enumerate(sources): source_id = source.get("source", {}).get("name", "") if "document" in source: for doc_idx, doc_context in enumerate(source["document"]): metadata = source.get("metadata") doc_source_id = None if metadata: doc_source_id = metadata[doc_idx].get("source", source_id) if source_id: context_string += f"{doc_source_id if doc_source_id is not None else source_id}{doc_context}\n" else: # If there is no source_id, then do not include the source_id tag context_string += f"{doc_context}\n" context_string = context_string.strip() prompt = get_last_user_message(form_data["messages"]) if prompt is None: raise Exception("No user message found") if ( request.app.state.config.RELEVANCE_THRESHOLD == 0 and context_string.strip() == "" ): log.debug( f"With a 0 relevancy threshold for RAG, the context cannot be empty" ) # Workaround for Ollama 2.0+ system prompt issue # TODO: replace with add_or_update_system_message if model["owned_by"] == "ollama": form_data["messages"] = prepend_to_first_user_message_content( rag_template( request.app.state.config.RAG_TEMPLATE, context_string, prompt ), form_data["messages"], ) else: form_data["messages"] = add_or_update_system_message( rag_template( request.app.state.config.RAG_TEMPLATE, context_string, prompt ), form_data["messages"], ) # If there are citations, add them to the data_items sources = [source for source in sources if source.get("source", {}).get("name", "")] if len(sources) > 0: events.append({"sources": sources}) if model_knowledge: await event_emitter( { "type": "status", "data": { "action": "knowledge_search", "query": user_message, "done": True, "hidden": True, }, } ) print(f"form_data, events") return form_data, events async def process_chat_response(request, response, user, events, metadata, tasks): if not isinstance(response, StreamingResponse): return response if not any( content_type in response.headers["Content-Type"] for content_type in ["text/event-stream", "application/x-ndjson"] ): return response event_emitter = None if ( "session_id" in metadata and metadata["session_id"] and "chat_id" in metadata and metadata["chat_id"] and "message_id" in metadata and metadata["message_id"] ): event_emitter = get_event_emitter(metadata) if event_emitter: task_id = str(uuid4()) # Create a unique task ID. # Handle as a background task async def post_response_handler(response, events): try: for event in events: await event_emitter( { "type": "chat:completion", "data": event, } ) # Save message in the database Chats.upsert_message_to_chat_by_id_and_message_id( metadata["chat_id"], metadata["message_id"], { **event, }, ) content = "" async for line in response.body_iterator: line = line.decode("utf-8") if isinstance(line, bytes) else line data = line # Skip empty lines if not data.strip(): continue # "data: " is the prefix for each event if not data.startswith("data: "): continue # Remove the prefix data = data[len("data: ") :] try: data = json.loads(data) value = ( data.get("choices", [])[0].get("delta", {}).get("content") ) if value: content = f"{content}{value}" # Save message in the database Chats.upsert_message_to_chat_by_id_and_message_id( metadata["chat_id"], metadata["message_id"], { "content": content, }, ) except Exception as e: done = "data: [DONE]" in line title = Chats.get_chat_title_by_id(metadata["chat_id"]) if done: data = {"done": True, "content": content, "title": title} # Send a webhook notification if the user is not active if ( get_user_id_from_session_pool(metadata["session_id"]) is None ): webhook_url = Users.get_user_webhook_url_by_id(user.id) if webhook_url: post_webhook( webhook_url, f"{title} - {WEBUI_URL}/c/{metadata['chat_id']}\n\n{content}", { "action": "chat", "message": content, "title": title, "url": f"{WEBUI_URL}/c/{metadata['chat_id']}", }, ) else: continue await event_emitter( { "type": "chat:completion", "data": data, } ) message_map = Chats.get_messages_by_chat_id(metadata["chat_id"]) message = message_map.get(metadata["message_id"]) if message: messages = get_message_list(message_map, message.get("id")) if tasks: if TASKS.TITLE_GENERATION in tasks: if tasks[TASKS.TITLE_GENERATION]: res = await generate_title( request, { "model": message["model"], "messages": messages, "chat_id": metadata["chat_id"], }, user, ) if res and isinstance(res, dict): title = ( res.get("choices", [])[0] .get("message", {}) .get( "content", message.get("content", "New Chat"), ) ) Chats.update_chat_title_by_id( metadata["chat_id"], title ) await event_emitter( { "type": "chat:title", "data": title, } ) elif len(messages) == 2: title = messages[0].get("content", "New Chat") Chats.update_chat_title_by_id( metadata["chat_id"], title ) await event_emitter( { "type": "chat:title", "data": message.get("content", "New Chat"), } ) if ( TASKS.TAGS_GENERATION in tasks and tasks[TASKS.TAGS_GENERATION] ): res = await generate_chat_tags( request, { "model": message["model"], "messages": messages, "chat_id": metadata["chat_id"], }, user, ) if res and isinstance(res, dict): tags_string = ( res.get("choices", [])[0] .get("message", {}) .get("content", "") ) tags_string = tags_string[ tags_string.find("{") : tags_string.rfind("}") + 1 ] try: tags = json.loads(tags_string).get("tags", []) Chats.update_chat_tags_by_id( metadata["chat_id"], tags, user ) await event_emitter( { "type": "chat:tags", "data": tags, } ) except Exception as e: print(f"Error: {e}") except asyncio.CancelledError: print("Task was cancelled!") await event_emitter({"type": "task-cancelled"}) if response.background is not None: await response.background() # background_tasks.add_task(post_response_handler, response, events) task_id, _ = create_task(post_response_handler(response, events)) return {"status": True, "task_id": task_id} else: # Fallback to the original response async def stream_wrapper(original_generator, events): def wrap_item(item): return f"data: {item}\n\n" for event in events: yield wrap_item(json.dumps(event)) async for data in original_generator: yield data return StreamingResponse( stream_wrapper(response.body_iterator, events), headers=dict(response.headers), )