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fix:FFUF

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This commit is contained in:
SengokuCola
2025-04-24 14:19:26 +08:00
parent f8450f705a
commit 3075664480
13 changed files with 224 additions and 225 deletions
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68
src/heart_flow/sub_heartflow.py
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@@ -6,12 +6,10 @@ from src.config.config import global_config
import time
from typing import Optional, List, Dict, Callable
import traceback
from src.plugins.chat.utils import parse_text_timestamps
import enum
from src.common.logger import get_module_logger, LogConfig, SUB_HEARTFLOW_STYLE_CONFIG # noqa: E402
from src.individuality.individuality import Individuality
import random
from src.plugins.person_info.relationship_manager import relationship_manager
from ..plugins.utils.prompt_builder import Prompt, global_prompt_manager
from src.plugins.chat.message import MessageRecv
from src.plugins.chat.chat_stream import chat_manager
@@ -20,7 +18,7 @@ from src.plugins.heartFC_chat.heartFC_chat import HeartFChatting
from src.plugins.heartFC_chat.normal_chat import NormalChat
from src.do_tool.tool_use import ToolUser
from src.heart_flow.mai_state_manager import MaiStateInfo
from src.plugins.utils.json_utils import safe_json_dumps, process_llm_tool_response, normalize_llm_response, process_llm_tool_calls
from src.plugins.utils.json_utils import safe_json_dumps, normalize_llm_response, process_llm_tool_calls
# 定义常量 (从 interest.py 移动过来)
MAX_INTEREST = 15.0
@@ -114,8 +112,6 @@ class InterestChatting:
self.above_threshold = False
self.start_hfc_probability = 0.0
def add_interest_dict(self, message: MessageRecv, interest_value: float, is_mentioned: bool):
self.interest_dict[message.message_info.message_id] = (message, interest_value, is_mentioned)
@@ -293,7 +289,7 @@ class SubHeartflow:
)
self.log_prefix = chat_manager.get_stream_name(self.subheartflow_id) or self.subheartflow_id
self.structured_info = {}
async def add_time_current_state(self, add_time: float):
@@ -484,36 +480,36 @@ class SubHeartflow:
async def do_thinking_before_reply(self):
"""
在回复前进行思考，生成内心想法并收集工具调用结果
返回:
tuple: (current_mind, past_mind) 当前想法和过去的想法列表
"""
# 更新活跃时间
self.last_active_time = time.time()
# ---------- 1. 准备基础数据 ----------
# 获取现有想法和情绪状态
current_thinking_info = self.current_mind
mood_info = self.chat_state.mood
# 获取观察对象
observation = self._get_primary_observation()
if not observation:
logger.error(f"[{self.subheartflow_id}] 无法获取观察对象")
self.update_current_mind("(我没看到任何聊天内容...)")
return self.current_mind, self.past_mind
# 获取观察内容
chat_observe_info = observation.get_observe_info()
# ---------- 2. 准备工具和个性化数据 ----------
# 初始化工具
tool_instance = ToolUser()
tools = tool_instance._define_tools()
# 获取个性化信息
individuality = Individuality.get_instance()
# 构建个性部分
prompt_personality = f"你的名字是{individuality.personality.bot_nickname}，你"
prompt_personality += individuality.personality.personality_core
@@ -547,9 +543,7 @@ class SubHeartflow:
# 加权随机选择思考指导
hf_do_next = local_random.choices(
[option[0] for option in hf_options],
weights=[option[1] for option in hf_options],
k=1
[option[0] for option in hf_options], weights=[option[1] for option in hf_options], k=1
)[0]
# ---------- 4. 构建最终提示词 ----------
@@ -570,16 +564,16 @@ class SubHeartflow:
# ---------- 5. 执行LLM请求并处理响应 ----------
content = "" # 初始化内容变量
reasoning_content = "" # 初始化推理内容变量
try:
# 调用LLM生成响应
response = await self.llm_model.generate_response_tool_async(prompt=prompt, tools=tools)
# 标准化响应格式
success, normalized_response, error_msg = normalize_llm_response(
response, log_prefix=f"[{self.subheartflow_id}] "
)
if not success:
# 处理标准化失败情况
logger.warning(f"[{self.subheartflow_id}] {error_msg}")
@@ -588,23 +582,24 @@ class SubHeartflow:
# 从标准化响应中提取内容
if len(normalized_response) >= 2:
content = normalized_response[0]
reasoning_content = normalized_response[1] if len(normalized_response) > 1 else ""
_reasoning_content = normalized_response[1] if len(normalized_response) > 1 else ""
# 处理可能的工具调用
if len(normalized_response) == 3:
# 提取并验证工具调用
success, valid_tool_calls, error_msg = process_llm_tool_calls(
normalized_response, log_prefix=f"[{self.subheartflow_id}] "
)
if success and valid_tool_calls:
# 记录工具调用信息
tool_calls_str = ", ".join([
call.get("function", {}).get("name", "未知工具")
for call in valid_tool_calls
])
logger.info(f"[{self.subheartflow_id}] 模型请求调用{len(valid_tool_calls)}个工具: {tool_calls_str}")
tool_calls_str = ", ".join(
[call.get("function", {}).get("name", "未知工具") for call in valid_tool_calls]
)
logger.info(
f"[{self.subheartflow_id}] 模型请求调用{len(valid_tool_calls)}个工具: {tool_calls_str}"
)
# 收集工具执行结果
await self._execute_tool_calls(valid_tool_calls, tool_instance)
elif not success:
@@ -628,37 +623,34 @@ class SubHeartflow:
self.update_current_mind(content)
return self.current_mind, self.past_mind
async def _execute_tool_calls(self, tool_calls, tool_instance):
"""
执行一组工具调用并收集结果
参数:
tool_calls: 工具调用列表
tool_instance: 工具使用器实例
"""
tool_results = []
structured_info = {} # 动态生成键
# 执行所有工具调用
for tool_call in tool_calls:
try:
result = await tool_instance._execute_tool_call(tool_call)
if result:
tool_results.append(result)
# 使用工具名称作为键
tool_name = result["name"]
if tool_name not in structured_info:
structured_info[tool_name] = []
structured_info[tool_name].append({
"name": result["name"],
"content": result["content"]
})
structured_info[tool_name].append({"name": result["name"], "content": result["content"]})
except Exception as tool_e:
logger.error(f"[{self.subheartflow_id}] 工具执行失败: {tool_e}")
# 如果有工具结果，记录并更新结构化信息
if structured_info:
logger.debug(f"工具调用收集到结构化信息: {safe_json_dumps(structured_info, ensure_ascii=False)}")