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Delete plugins/filters/multi_model_context_merger.py

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Jeff
2026-01-15 00:28:14 +08:00
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plugins/filters/multi_model_context_merger.py
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"""
title: Multi-Model Context Merger
author: Fu-Jie
author_url: https://github.com/Fu-Jie/awesome-openwebui
funding_url: https://github.com/Fu-Jie/awesome-openwebui
version: 0.1.0
description: Automatically merges context from multiple model responses in the previous turn.
"""
import asyncio
from typing import List, Optional, Dict
from pydantic import BaseModel, Field
from fastapi import Request
from open_webui.models.chats import Chats
class Filter:
class Valves(BaseModel):
# 注入的系统消息的前缀
CONTEXT_PREFIX: str = Field(
default="下面是多个匿名AI模型给出的回答，使用<response>标签包裹：\n\n",
description="Prefix for the injected system message containing the raw merged context.",
)
def __init__(self):
self.valves = self.Valves()
self.toggle = True
self.type = "filter"
self.name = "合并回答"
self.description = "在用户提问时，自动注入之前多个模型回答的上下文。"
async def inlet(
self,
body: Dict,
__user__: Dict,
__metadata__: Dict,
__request__: Request,
__event_emitter__,
):
"""
此方法是过滤器的入口点。它会检查上一回合是否为多模型响应，
如果是，则将这些响应直接格式化，并将格式化后的上下文作为系统消息注入到当前请求中。
"""
print(f"*********** Filter '{self.name}' triggered ***********")
chat_id = __metadata__.get("chat_id")
if not chat_id:
print(
f"DEBUG: Filter '{self.name}' skipped: chat_id not found in metadata."
)
return body
print(f"DEBUG: Chat ID found: {chat_id}")
# 1. 从数据库获取完整的聊天历史
try:
chat = await asyncio.to_thread(Chats.get_chat_by_id, chat_id)
if (
not chat
or not hasattr(chat, "chat")
or not chat.chat.get("history")
or not chat.chat.get("history").get("messages")
):
print(
f"DEBUG: Filter '{self.name}' skipped: Chat history not found or empty for chat_id: {chat_id}"
)
return body
messages_map = chat.chat["history"]["messages"]
print(
f"DEBUG: Successfully loaded {len(messages_map)} messages from history."
)
# Count the number of user messages in the history
user_message_count = sum(
1 for msg in messages_map.values() if msg.get("role") == "user"
)
# If there are less than 2 user messages, there's no previous turn to merge.
if user_message_count < 2:
print(
f"DEBUG: Filter '{self.name}' skipped: Not enough user messages in history to have a previous turn (found {user_message_count}, required >= 2)."
)
return body
except Exception as e:
print(
f"ERROR: Filter '{self.name}' failed to get chat history from DB: {e}"
)
return body
# This filter rebuilds the entire chat history to consolidate all multi-response turns.
# 1. Get all messages from history and sort by timestamp
all_messages = list(messages_map.values())
all_messages.sort(key=lambda x: x.get("timestamp", 0))
# 2. Pre-group all assistant messages by their parentId for efficient lookup
assistant_groups = {}
for msg in all_messages:
if msg.get("role") == "assistant":
parent_id = msg.get("parentId")
if parent_id:
if parent_id not in assistant_groups:
assistant_groups[parent_id] = []
assistant_groups[parent_id].append(msg)
final_messages = []
processed_parent_ids = set()
# 3. Iterate through the sorted historical messages to build the final, clean list
for msg in all_messages:
msg_id = msg.get("id")
role = msg.get("role")
parent_id = msg.get("parentId")
if role == "user":
# Add user messages directly
final_messages.append(msg)
elif role == "assistant":
# If this assistant's parent group has already been processed, skip it
if parent_id in processed_parent_ids:
continue
# Process the group of siblings for this parent_id
if parent_id in assistant_groups:
siblings = assistant_groups[parent_id]
# Only perform a merge if there are multiple siblings
if len(siblings) > 1:
print(
f"DEBUG: Found a group of {len(siblings)} siblings for parent_id {parent_id}. Merging..."
)
# --- MERGE LOGIC ---
merged_content = None
merged_message_id = None
# Sort siblings by timestamp before processing
siblings.sort(key=lambda s: s.get("timestamp", 0))
merged_message_timestamp = siblings[0].get("timestamp", 0)
# Case A: Check for system pre-merged content (merged.status: true and content not empty)
merged_content_msg = next(
(
s
for s in siblings
if s.get("merged", {}).get("status")
and s.get("merged", {}).get("content")
),
None,
)
if merged_content_msg:
merged_content = merged_content_msg["merged"]["content"]
merged_message_id = merged_content_msg["id"]
merged_message_timestamp = merged_content_msg.get(
"timestamp", merged_message_timestamp
)
print(
f"DEBUG: Using pre-merged content from message ID: {merged_message_id}"
)
else:
# Case B: Manually merge content
combined_content = []
first_sibling_id = None
counter = 0
for s in siblings:
if not first_sibling_id:
first_sibling_id = s["id"]
content = s.get("content", "")
if (
content
and content
!= "The requested model is not supported."
):
response_id = chr(ord("a") + counter)
combined_content.append(
f'<response id="{response_id}">\n{content}\n</response>'
)
counter += 1
if combined_content:
merged_content = "\n\n".join(combined_content)
merged_message_id = first_sibling_id or parent_id
if merged_content:
merged_message = {
"id": merged_message_id,
"parentId": parent_id,
"role": "assistant",
"content": f"{self.valves.CONTEXT_PREFIX}{merged_content}",
"timestamp": merged_message_timestamp,
}
final_messages.append(merged_message)
else:
# If there's only one sibling, add it directly
final_messages.append(siblings[0])
# Mark this group as processed
processed_parent_ids.add(parent_id)
# 4. The new user message from the current request is not in the historical messages_map,
# so we need to append it to our newly constructed message list.
if body.get("messages"):
new_user_message_from_body = body["messages"][-1]
# Ensure we don't add a historical message that might be in the body for context
if new_user_message_from_body.get("id") not in messages_map:
final_messages.append(new_user_message_from_body)
# 5. Replace the original message list with the new, cleaned-up list
body["messages"] = final_messages
print(
f"DEBUG: Rebuilt message history with {len(final_messages)} messages, consolidating all multi-response turns."
)
print(f"*********** Filter '{self.name}' finished successfully ***********")
return body