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zihanjian
2025-10-13 15:26:24 +08:00
parent 472b8a1d5a
commit fc5369a930
2 changed files with 277 additions and 137 deletions
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226
commands/handlers.py
View File

@@ -166,17 +166,16 @@ def handle_chitchat(ctx: 'MessageContext', match: Optional[Match]) -> bool:
"function": {
"name": "search_chat_history",
"description": (
"Search recent conversation history for specific keywords. "
"Returns at most 20 recent segments, each including the matched message "
"with five surrounding messages (if available) and timestamps. "
"Use this tool when you need precise historical context."
"Search older conversation history (excluding the most recent 30 messages) using multiple related keywords. "
"Provide 2-4 diverse keywords or short phrases that capture the user's intent; synonyms and key names greatly improve recall. "
"The tool returns up to 20 recent segments, each containing deduplicated context lines that have already been formatted."
),
"parameters": {
"type": "object",
"properties": {
"keywords": {
"type": "array",
"description": "List of keywords to search for in message content.",
"description": "Diverse keywords or short phrases (2-4 recommended) for fuzzy searching message content.",
"items": {"type": "string"},
"minItems": 1
},
@@ -202,83 +201,186 @@ def handle_chitchat(ctx: 'MessageContext', match: Optional[Match]) -> bool:
}
}
range_history_tool = {
"type": "function",
"function": {
"name": "fetch_chat_history_range",
"description": (
"Retrieve a slice of older conversation by specifying two offsets counted from the latest message "
"(e.g., start_offset=60, end_offset=120 fetches messages between the 60th and 120th most recent). "
"Both offsets must be greater than 30 so that only unseen history is retrieved. "
"Use when you need a contiguous block of messages instead of keyword search."
),
"parameters": {
"type": "object",
"properties": {
"start_offset": {
"type": "integer",
"description": "Smaller offset counted from the latest message (must be >30)."
},
"end_offset": {
"type": "integer",
"description": "Larger offset counted from the latest message (must be > start_offset and >30)."
}
},
"required": ["start_offset", "end_offset"],
"additionalProperties": False
}
}
}
def handle_tool_call(tool_name: str, arguments: Dict[str, Any]) -> str:
if tool_name != "search_chat_history":
return json.dumps({"error": f"Unknown tool '{tool_name}'"}, ensure_ascii=False)
try:
keywords = arguments.get("keywords", [])
if isinstance(keywords, str):
keywords = [keywords]
elif not isinstance(keywords, list):
keywords = []
if tool_name == "search_chat_history":
keywords = arguments.get("keywords", [])
if isinstance(keywords, str):
keywords = [keywords]
elif not isinstance(keywords, list):
keywords = []
query = arguments.get("query")
if isinstance(query, str) and query.strip():
query_keywords = [segment for segment in query.strip().split() if segment]
keywords.extend(query_keywords)
query = arguments.get("query")
if isinstance(query, str) and query.strip():
query_keywords = [
segment
for segment in re.split(r"[,\s，。；;]+", query.strip())
if segment
]
keywords.extend(query_keywords)
cleaned_keywords = []
for kw in keywords:
if kw is None:
continue
kw_str = str(kw).strip()
if kw_str:
cleaned_keywords.append(kw_str)
cleaned_keywords = []
for kw in keywords:
if kw is None:
continue
kw_str = str(kw).strip()
if kw_str:
if len(kw_str) == 1 and not kw_str.isdigit():
continue
cleaned_keywords.append(kw_str)
# 去重同时保持顺序
seen = set()
deduped_keywords = []
for kw in cleaned_keywords:
lower_kw = kw.lower()
if lower_kw not in seen:
seen.add(lower_kw)
deduped_keywords.append(kw)
# 去重同时保持顺序
seen = set()
deduped_keywords = []
for kw in cleaned_keywords:
lower_kw = kw.lower()
if lower_kw not in seen:
seen.add(lower_kw)
deduped_keywords.append(kw)
if not deduped_keywords:
return json.dumps({"error": "No valid keywords provided.", "results": []}, ensure_ascii=False)
if not deduped_keywords:
return json.dumps({"error": "No valid keywords provided.", "results": []}, ensure_ascii=False)
context_window = arguments.get("context_window", 5)
max_results = arguments.get("max_results", 20)
context_window = arguments.get("context_window", 5)
max_results = arguments.get("max_results", 20)
print(f"[search_chat_history] chat_id={chat_id}, keywords={deduped_keywords}, "
f"context_window={context_window}, max_results={max_results}")
if ctx.logger:
ctx.logger.info(
f"[search_chat_history] keywords={deduped_keywords}, "
f"context_window={context_window}, max_results={max_results}"
print(f"[search_chat_history] chat_id={chat_id}, keywords={deduped_keywords}, "
f"context_window={context_window}, max_results={max_results}")
if ctx.logger:
ctx.logger.info(
f"[search_chat_history] keywords={deduped_keywords}, "
f"context_window={context_window}, max_results={max_results}"
)
search_results = message_summary.search_messages_with_context(
chat_id=chat_id,
keywords=deduped_keywords,
context_window=context_window,
max_groups=max_results
)
search_results = message_summary.search_messages_with_context(
chat_id=chat_id,
keywords=deduped_keywords,
context_window=context_window,
max_groups=max_results
)
segments = []
lines_seen = set()
for segment in search_results:
formatted = []
for line in segment.get("formatted_messages", []):
if line not in lines_seen:
lines_seen.add(line)
formatted.append(line)
if not formatted:
continue
segments.append({
"matched_keywords": segment.get("matched_keywords", []),
"messages": formatted
})
response_payload = {
"results": search_results,
"returned_groups": len(search_results),
"keywords": deduped_keywords
}
response_payload = {
"segments": segments,
"returned_groups": len(segments),
"keywords": deduped_keywords
}
print(f"[search_chat_history] returned_groups={len(search_results)}")
if ctx.logger:
ctx.logger.info(f"[search_chat_history] returned_groups={len(search_results)}")
print(f"[search_chat_history] returned_groups={len(segments)}")
if ctx.logger:
ctx.logger.info(f"[search_chat_history] returned_groups={len(segments)}")
if not search_results:
response_payload["notice"] = "No messages matched the provided keywords."
if not segments:
response_payload["notice"] = "No messages matched the provided keywords."
return json.dumps(response_payload, ensure_ascii=False)
elif tool_name == "fetch_chat_history_range":
if "start_offset" not in arguments or "end_offset" not in arguments:
return json.dumps({"error": "start_offset and end_offset are required."}, ensure_ascii=False)
start_offset = arguments.get("start_offset")
end_offset = arguments.get("end_offset")
try:
start_offset = int(start_offset)
end_offset = int(end_offset)
except (TypeError, ValueError):
return json.dumps({"error": "start_offset and end_offset must be integers."}, ensure_ascii=False)
if start_offset <= 30 or end_offset <= 30:
return json.dumps({"error": "Offsets must be greater than 30 to avoid visible messages."}, ensure_ascii=False)
if start_offset > end_offset:
start_offset, end_offset = end_offset, start_offset
print(f"[fetch_chat_history_range] chat_id={chat_id}, start_offset={start_offset}, "
f"end_offset={end_offset}")
if ctx.logger:
ctx.logger.info(
f"[fetch_chat_history_range] start_offset={start_offset}, "
f"end_offset={end_offset}"
)
range_result = message_summary.get_messages_by_reverse_range(
chat_id=chat_id,
start_offset=start_offset,
end_offset=end_offset
)
response_payload = {
"start_offset": range_result.get("start_offset"),
"end_offset": range_result.get("end_offset"),
"messages": range_result.get("messages", []),
"returned_count": range_result.get("returned_count", 0),
"total_messages": range_result.get("total_messages", 0)
}
print(f"[fetch_chat_history_range] returned_count={response_payload['returned_count']}")
if ctx.logger:
ctx.logger.info(
f"[fetch_chat_history_range] returned_count={response_payload['returned_count']}"
)
if response_payload["returned_count"] == 0:
response_payload["notice"] = "No messages available in the requested range."
return json.dumps(response_payload, ensure_ascii=False)
else:
return json.dumps({"error": f"Unknown tool '{tool_name}'"}, ensure_ascii=False)
return json.dumps(response_payload, ensure_ascii=False)
except Exception as tool_exc:
if ctx.logger:
ctx.logger.error(f"搜索历史工具调用失败: {tool_exc}", exc_info=True)
ctx.logger.error(f"历史搜索工具调用失败: {tool_exc}", exc_info=True)
return json.dumps(
{"error": f"Search failed: {tool_exc.__class__.__name__}"},
{"error": f"History tool failed: {tool_exc.__class__.__name__}"},
ensure_ascii=False
)
tools = [search_history_tool]
tools = [search_history_tool, range_history_tool]
tool_handler = handle_tool_call
rsp = chat_model.get_answer(

188
function/func_summary.py
View File

@@ -240,7 +240,14 @@ class MessageSummary:
return messages
def search_messages_with_context(self, chat_id, keywords, context_window=5, max_groups=20):
def search_messages_with_context(
self,
chat_id,
keywords,
context_window=5,
max_groups=20,
exclude_recent=30
):
"""根据关键词搜索消息，返回包含前后上下文的结果
Args:
@@ -248,6 +255,7 @@ class MessageSummary:
keywords (Union[str, list[str]]): 需要搜索的关键词或关键词列表
context_window (int): 每条匹配消息前后额外提供的消息数量
max_groups (int): 返回的最多结果组数（按时间倒序，优先最新消息）
exclude_recent (int): 跳过最近的若干条消息（默认30条）
Returns:
list[dict]: 搜索结果列表，每个元素包含匹配关键词、锚点消息及上下文消息
@@ -285,18 +293,32 @@ class MessageSummary:
if not messages:
return []
try:
exclude_recent = int(exclude_recent)
except (TypeError, ValueError):
exclude_recent = 30
exclude_recent = max(0, exclude_recent)
results = []
total_messages = len(messages)
cutoff_index = total_messages - exclude_recent
if cutoff_index <= 0:
return []
used_indices = set()
for idx in range(total_messages - 1, -1, -1):
for idx in range(cutoff_index - 1, -1, -1):
message = messages[idx]
content = message.get("content", "")
if not content:
continue
lower_content = content.lower()
matched_keywords = [orig for orig, lower in normalized_keywords if lower in lower_content]
matched_keywords = [
orig
for orig, lower in normalized_keywords
if lower in lower_content
]
if not matched_keywords:
continue
@@ -306,9 +328,16 @@ class MessageSummary:
start = max(0, idx - context_window)
end = min(total_messages, idx + context_window + 1)
segment_messages = []
formatted_lines = []
seen_lines = set()
for pos in range(start, end):
msg = messages[pos]
line = f"{msg.get('time')} {msg.get('sender')} {msg.get('content')}"
if line not in seen_lines:
seen_lines.add(line)
formatted_lines.append(line)
segment_messages.append({
"time": msg.get("time"),
"sender": msg.get("sender"),
@@ -324,7 +353,8 @@ class MessageSummary:
"anchor_time": message.get("time"),
"anchor_sender": message.get("sender"),
"anchor_sender_wxid": message.get("sender_wxid"),
"messages": segment_messages
"messages": segment_messages,
"formatted_messages": formatted_lines
})
for off in range(start, end):
@@ -335,6 +365,85 @@ class MessageSummary:
return results
def get_messages_by_reverse_range(
self,
chat_id,
start_offset,
end_offset,
max_messages_limit=500
):
"""按倒数范围获取消息
Args:
chat_id (str): 聊天ID（群ID或用户ID）
start_offset (int): 离最新消息的起始偏移（倒数 start_offset 条，必须 > 0）
end_offset (int): 离最新消息的结束偏移（倒数 end_offset 条，必须 >= start_offset）
max_messages_limit (int): 内部限制，防止一次返回过多消息
Returns:
dict: 包含请求范围信息和格式化消息行
"""
try:
start_offset = int(start_offset)
end_offset = int(end_offset)
except (TypeError, ValueError):
raise ValueError("start_offset 和 end_offset 必须是整数")
if start_offset <= 0 or end_offset <= 0:
raise ValueError("start_offset 和 end_offset 必须为正整数")
if start_offset > end_offset:
start_offset, end_offset = end_offset, start_offset
try:
max_messages_limit = int(max_messages_limit)
except (TypeError, ValueError):
max_messages_limit = 500
max_messages_limit = max(1, min(max_messages_limit, 1000))
messages = self.get_messages(chat_id)
total_messages = len(messages)
if total_messages == 0:
return {
"start_offset": start_offset,
"end_offset": end_offset,
"messages": [],
"returned_count": 0,
"total_messages": 0
}
start_offset = min(start_offset, total_messages)
end_offset = min(end_offset, total_messages)
start_index = max(total_messages - end_offset, 0)
end_index = min(total_messages - start_offset, total_messages - 1)
if end_index < start_index:
return {
"start_offset": start_offset,
"end_offset": end_offset,
"messages": [],
"returned_count": 0,
"total_messages": total_messages
}
selected = messages[start_index:end_index + 1]
if len(selected) > max_messages_limit:
selected = selected[-max_messages_limit:]
formatted_lines = [
f"{msg.get('time')} {msg.get('sender')} {msg.get('content')}"
for msg in selected
]
return {
"start_offset": start_offset,
"end_offset": end_offset,
"messages": formatted_lines,
"returned_count": len(formatted_lines),
"total_messages": total_messages
}
def _basic_summarize(self, messages):
"""基本的消息总结逻辑，不使用AI
@@ -354,77 +463,6 @@ class MessageSummary:
return "\n".join(res)
def _ai_summarize(self, messages, chat_model, chat_id):
"""使用AI模型生成消息总结
Args:
messages: 消息列表 (格式同 get_messages 返回值)
chat_model: AI聊天模型对象
chat_id: 聊天ID
Returns:
str: 消息总结
"""
if not messages:
return "没有可以总结的历史消息。"
formatted_msgs = []
for msg in messages:
# 使用新的时间格式和发送者
formatted_msgs.append(f"[{msg['time']}]{msg['sender']}: {msg['content']}")
# 构建提示词 ... (保持不变)
prompt = (
"你是泡泡，请仔细阅读并分析以下聊天记录，生成一简要的、结构清晰且抓住重点的摘要。\n\n"
"摘要格式要求：\n"
"1. 使用数字编号列表 (例如 1., 2., 3.) 来组织内容，每个编号代表一个独立的主要讨论主题，不要超过3个主题。\n"
"2. 在每个编号的主题下，写成一段不带格式的文字，每个主题单独成段并空行，需包含以下内容：\n"
" - 这个讨论的核心的简要描述。\n"
" - 该讨论的关键成员 (用括号 [用户名] 格式) 和他们的关键发言内容、成员之间的关键互动。\n"
" - 该讨论的讨论结果。\n"
"3. 总结需客观、精炼、简短精悍，直接呈现最核心且精简的事实，尽量不要添加额外的评论或分析，不要总结有关自己的事情。\n"
"4. 不要暴露出格式，不要说核心是xxx参与者是xxx结果是xxx，自然一点。\n\n"
"聊天记录如下：\n" + "\n".join(formatted_msgs)
)
try:
# 调用AI部分保持不变，但现在AI模型内部应使用数据库历史记录
# 确保调用 get_answer 时，AI模型实例已经关联了 MessageSummary
summary = chat_model.get_answer(prompt, f"summary_{chat_id}") # 使用特殊 wxid 避免冲突
if not summary:
return self._basic_summarize(messages)
return summary
except Exception as e:
self.LOG.error(f"使用AI生成总结失败: {e}")
return self._basic_summarize(messages)
def summarize_messages(self, chat_id, chat_model=None):
"""生成消息总结
Args:
chat_id: 聊天ID（群ID或用户ID）
chat_model: AI聊天模型对象，如果为None则使用基础总结
Returns:
str: 消息总结
"""
messages = self.get_messages(chat_id)
if not messages:
return "没有可以总结的历史消息。"
if chat_model:
# 检查 chat_model 是否具有 get_answer 方法并且已经初始化了 message_summary
if hasattr(chat_model, 'get_answer') and hasattr(chat_model, 'message_summary') and chat_model.message_summary:
return self._ai_summarize(messages, chat_model, chat_id)
else:
self.LOG.warning(f"提供的 chat_model ({type(chat_model)}) 不支持基于数据库历史的总结或未正确初始化。将使用基础总结。")
return self._basic_summarize(messages)
else:
return self._basic_summarize(messages)
def process_message_from_wxmsg(self, msg, wcf, all_contacts, bot_wxid=None):
"""从微信消息对象中处理并记录与总结相关的文本消息
记录所有群聊和私聊的文本(1)和App/卡片(49)消息。