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feat：可选，由llm执行回复

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This commit is contained in:
SengokuCola
2025-12-31 00:43:08 +08:00
parent 67c24f84cd
commit 71a85667e3
5 changed files with 57 additions and 26 deletions
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38
src/chat/heart_flow/heartFC_chat.py
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@@ -244,12 +244,14 @@ class HeartFChatting:
thinking_id,
actions,
selected_expressions: Optional[List[int]] = None,
quote_message: Optional[bool] = None,
) -> Tuple[Dict[str, Any], str, Dict[str, float]]:
with Timer("回复发送", cycle_timers):
reply_text = await self._send_response(
reply_set=response_set,
message_data=action_message,
selected_expressions=selected_expressions,
quote_message=quote_message,
)
# 获取 platform，如果不存在则从 chat_stream 获取，如果还是 None 则使用默认值
@@ -526,15 +528,22 @@ class HeartFChatting:
reply_set: "ReplySetModel",
message_data: "DatabaseMessages",
selected_expressions: Optional[List[int]] = None,
quote_message: Optional[bool] = None,
) -> str:
new_message_count = message_api.count_new_messages(
chat_id=self.chat_stream.stream_id, start_time=self.last_read_time, end_time=time.time()
)
need_reply = new_message_count >= random.randint(2, 3)
if need_reply:
logger.info(f"{self.log_prefix} 从思考到回复，共有{new_message_count}条新消息，使用引用回复")
# 根据 llm_quote 配置决定是否使用 quote_message 参数
if global_config.chat.llm_quote and quote_message is not None:
# 如果配置为 true，使用 llm_quote 参数决定是否引用回复
need_reply = quote_message
if need_reply:
logger.info(f"{self.log_prefix} LLM 决定使用引用回复")
else:
# 如果配置为 false，使用原来的模式
new_message_count = message_api.count_new_messages(
chat_id=self.chat_stream.stream_id, start_time=self.last_read_time, end_time=time.time()
)
need_reply = new_message_count >= random.randint(2, 3)
if need_reply:
logger.info(f"{self.log_prefix} 从思考到回复，共有{new_message_count}条新消息，使用引用回复")
reply_text = ""
first_replied = False
@@ -640,6 +649,7 @@ class HeartFChatting:
# 从 Planner 的 action_data 中提取未知词语列表（仅在 reply 时使用）
unknown_words = None
quote_message = None
if isinstance(action_planner_info.action_data, dict):
uw = action_planner_info.action_data.get("unknown_words")
if isinstance(uw, list):
@@ -651,6 +661,17 @@ class HeartFChatting:
cleaned_uw.append(s)
if cleaned_uw:
unknown_words = cleaned_uw
# 从 Planner 的 action_data 中提取 quote_message 参数
qm = action_planner_info.action_data.get("quote_message")
if qm is not None:
# 支持多种格式：true/false, "true"/"false", 1/0
if isinstance(qm, bool):
quote_message = qm
elif isinstance(qm, str):
quote_message = qm.lower() in ("true", "1", "yes")
elif isinstance(qm, (int, float)):
quote_message = bool(qm)
success, llm_response = await generator_api.generate_reply(
chat_stream=self.chat_stream,
@@ -682,6 +703,7 @@ class HeartFChatting:
thinking_id=thinking_id,
actions=chosen_action_plan_infos,
selected_expressions=selected_expressions,
quote_message=quote_message,
)
self.last_active_time = time.time()
return {