""" title: Multi Model Conversations author: Haervwe author_url: https://github.com/Haervwe funding_url: https://github.com/Haervwe/open-webui-tools version: 0.7.1 """ import logging import json import asyncio from typing import Dict, List, Callable, Awaitable, Union from pydantic import BaseModel, Field from dataclasses import dataclass from open_webui.constants import TASKS from open_webui.main import generate_chat_completions from open_webui.models.users import User name = "Conversation" def setup_logger(): logger = logging.getLogger(name) if not logger.handlers: logger.setLevel(logging.DEBUG) handler = logging.StreamHandler() handler.set_name(name) formatter = logging.Formatter( "%(asctime)s - %(name)s - %(levelname)s - %(message)s" ) handler.setFormatter(formatter) logger.addHandler(handler) logger.propagate = False return logger logger = setup_logger() class Pipe: __current_event_emitter__: Callable[[dict], Awaitable[None]] __user__: User __model__: str class Valves(BaseModel): NUM_PARTICIPANTS: int = Field( default=1, description="Number of participants in the conversation (1-5)", ge=1, le=5, ) ROUNDS_PER_CONVERSATION: int = Field( default=3, description="Number of rounds in the entire conversation", ge=1, ) Participant1Model: str = Field( default="", description="Model tag for Participant 1" ) Participant1Alias: str = Field( default="", description="Alias tag for Participant 1" ) Participant1SystemMessage: str = Field( default="", description="Character sheet for Participant 1" ) Participant2Model: str = Field( default="", description="Model tag for Participant 2" ) Participant2Alias: str = Field( default="", description="Alias tag for Participant 2" ) Participant2SystemMessage: str = Field( default="", description="Character sheet for Participant 2" ) Participant3Model: str = Field( default="", description="Model tag for Participant 3" ) Participant3Alias: str = Field( default="", description="Alias tag for Participant 3" ) Participant3SystemMessage: str = Field( default="", description="Character sheet for Participant 3" ) Participant4Model: str = Field( default="", description="Model tag for Participant 4" ) Participant4Alias: str = Field( default="", description="Alias tag for Participant 4" ) Participant4SystemMessage: str = Field( default="", description="Character sheet for Participant 4" ) Participant5Model: str = Field( default="", description="Model tag for Participant 5" ) Participant5Alias: str = Field( default="", description="Alias tag for Participant 5" ) Participant5SystemMessage: str = Field( default="", description="Character sheet for Participant 5" ) AllParticipantsApendedMessage: str = Field( default="Respond only as your specified character and never use your name as title, just output the response as if you really were talking(no one says his name before a phrase), do not go off character in any situation, Your acted response as", description="Appended message to all participants internally to prime them properly to not go off character", ) UseGroupChatManager: bool = Field( default=False, description="Use Group Chat Manager" ) ManagerModel: str = Field(default="", description="Model for the Manager") ManagerSystemMessage: str = Field( default="You are a group chat manager. Your role is to decide who should speak next in a multi-participant conversation. You will be given the conversation history and a list of participant aliases. Choose the alias of the participant who is most likely to provide a relevant and engaging response to the latest message. Consider the context of the conversation, the personalities of the participants, and avoid repeatedly selecting the same participant.", description="System message for the Manager", ) ManagerSelectionPrompt: str = Field( default="Conversation History:\n{history}\n\nThe last speaker was '{last_speaker}'. Based on the flow of the conversation, who should speak next? Choose exactly one from the following list of participants: {participant_list}\n\nRespond with ONLY the alias of your choice, and nothing else.", description="Template for the Manager's selection prompt. Use {history}, {last_speaker}, and {participant_list}.", ) Temperature: float = Field(default=1, description="Models temperature") Top_k: int = Field(default=50, description="Models top_k") Top_p: float = Field(default=0.8, description="Models top_p") def __init__(self): self.type = "manifold" self.conversation_history = [] self.valves = self.Valves() def pipes(self) -> list[dict[str, str]]: return [{"id": f"{name}-pipe", "name": f"{name} Pipe"}] async def get_streaming_completion( self, messages, model: str, ): try: form_data = { "model": model, "messages": messages, "stream": True, "temperature": self.valves.Temperature, "top_k": self.valves.Top_k, "top_p": self.valves.Top_p, } response = await generate_chat_completions( self.__request__, form_data, user=self.__user__, ) if not hasattr(response, "body_iterator"): raise ValueError("Response does not support streaming") async for chunk in response.body_iterator: for part in self.get_chunk_content(chunk): yield part except Exception as e: raise RuntimeError(f"Streaming completion failed: {e}") def get_chunk_content(self, chunk): chunk_str = chunk.decode("utf-8") if isinstance(chunk, bytes) else chunk if chunk_str.startswith("data: "): chunk_str = chunk_str[6:] chunk_str = chunk_str.strip() if chunk_str == "[DONE]" or not chunk_str: return try: chunk_data = json.loads(chunk_str) if "choices" in chunk_data and len(chunk_data["choices"]) > 0: delta = chunk_data["choices"][0].get("delta", {}) if "content" in delta: yield delta["content"] except json.JSONDecodeError: logger.error(f'ChunkDecodeError: unable to parse "{chunk_str[:100]}"') async def emit_message(self, message: str): await self.__current_event_emitter__( {"type": "message", "data": {"content": message}} ) async def emit_status(self, level: str, message: str, done: bool): await self.__current_event_emitter__( { "type": "status", "data": { "status": "complete" if done else "in_progress", "level": level, "description": message, "done": done, }, } ) async def emit_model_title(self, model_name: str): """Helper function to emit the model title with a separator.""" await self.emit_message(f"\n\n---\n\n**{model_name}:**\n\n") async def pipe( self, body: dict, __user__: dict, __event_emitter__=None, __task__=None, __model__=None, __request__=None, ) -> str: self.__current_event_emitter__ = __event_emitter__ self.__user__ = User(**__user__) self.__model__ = __model__ self.__request__ = __request__ if __task__ and __task__ != TASKS.DEFAULT: model = self.valves.Participant1Model or self.__model__ response = await generate_chat_completions( self.__request__, {"model": model, "messages": body.get("messages"), "stream": False}, user=self.__user__, ) return f"{name}: {response['choices'][0]['message']['content']}" user_message = body.get("messages", [])[-1].get("content", "").strip() num_participants = self.valves.NUM_PARTICIPANTS participants = [] for i in range(1, num_participants + 1): model = getattr(self.valves, f"Participant{i}Model", "") alias = getattr(self.valves, f"Participant{i}Alias", "") or model system_message = getattr(self.valves, f"Participant{i}SystemMessage", "") if not model: logger.warning(f"No model set for Participant {i}, skipping.") continue participants.append( {"model": model, "alias": alias, "system_message": system_message} ) if not participants: await self.emit_status("error", "No valid participants configured.", True) return "Error: No participants configured. Please set at least one participant's model in the valves." self.conversation_history.append({"role": "user", "content": user_message}) last_speaker = None for round_num in range(self.valves.ROUNDS_PER_CONVERSATION): if self.valves.UseGroupChatManager: participant_aliases = [p["alias"] for p in participants] history_str = "\n".join( f"{msg['role']}: {msg['content']}" for msg in self.conversation_history ) manager_prompt = self.valves.ManagerSelectionPrompt.format( history=history_str, last_speaker=last_speaker or "None", participant_list=", ".join(participant_aliases), ) manager_messages = [ {"role": "system", "content": self.valves.ManagerSystemMessage}, {"role": "user", "content": manager_prompt}, ] manager_response = await generate_chat_completions( self.__request__, { "model": self.valves.ManagerModel, "messages": manager_messages, "stream": False, }, user=self.__user__, ) selected_alias = manager_response["choices"][0]["message"][ "content" ].strip() selected_participant = next( (p for p in participants if p["alias"] == selected_alias), None ) if not selected_participant or selected_alias == last_speaker: await self.emit_status( "info", f"Manager selection '{selected_alias}' was invalid or repeated. Using fallback.", False, ) last_speaker_index = next( ( i for i, p in enumerate(participants) if p["alias"] == last_speaker ), -1, ) # Pick the next participant in order, wrapping around fallback_index = (last_speaker_index + 1) % len(participants) selected_participant = participants[fallback_index] logger.warning( f"Manager failed. Fallback selected: {selected_participant['alias']}" ) # A single participant turn participants_to_run = [selected_participant] last_speaker = selected_participant["alias"] else: participants_to_run = participants for participant in participants_to_run: model = participant["model"] alias = participant["alias"] system_message = participant["system_message"] messages = [ {"role": "system", "content": system_message}, *self.conversation_history, { "role": "user", "content": f"{self.valves.AllParticipantsApendedMessage} {alias}", }, ] await self.emit_status( "info", f"Getting response from: {alias} ({model})...", False ) try: await self.emit_model_title(alias) full_response = "" async for chunk in self.get_streaming_completion( messages, model=model ): full_response += chunk await self.emit_message(chunk) cleaned_response = full_response.strip() self.conversation_history.append( {"role": "assistant", "content": cleaned_response} ) logger.debug(f"History updated with response from {alias}") except Exception as e: error_message = f"Error getting response from {model}: {e}" await self.emit_status("error", error_message, True) logger.error(f"Error with {model}: {e}", exc_info=True) await self.emit_status("success", "Conversation round completed.", True) return ""