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feat：优化工具调用的得到的信息调用和缓存

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This commit is contained in:
SengokuCola
2025-05-02 00:58:55 +08:00
parent f4616afb3a
commit f30d472c0b
14 changed files with 154 additions and 113 deletions
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98
src/heart_flow/sub_mind.py
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@@ -1,4 +1,4 @@
from .observation import Observation
from .observation import Observation, ChattingObservation
from src.plugins.models.utils_model import LLMRequest
from src.config.config import global_config
import time
@@ -114,7 +114,7 @@ def calculate_replacement_probability(similarity: float) -> float:
class SubMind:
def __init__(self, subheartflow_id: str, chat_state: ChatStateInfo, observations: Observation):
def __init__(self, subheartflow_id: str, chat_state: ChatStateInfo, observations: ChattingObservation):
self.last_active_time = None
self.subheartflow_id = subheartflow_id
@@ -130,10 +130,41 @@ class SubMind:
self.current_mind = ""
self.past_mind = []
self.structured_info = {}
self.structured_info = []
self.structured_info_str = ""
name = chat_manager.get_stream_name(self.subheartflow_id)
self.log_prefix = f"[{name}] "
self._update_structured_info_str()
def _update_structured_info_str(self):
"""根据 structured_info 更新 structured_info_str"""
if not self.structured_info:
self.structured_info_str = ""
return
lines = ["【信息】"]
for item in self.structured_info:
# 简化展示，突出内容和类型，包含TTL供调试
type_str = item.get('type', '未知类型')
content_str = item.get('content', '')
ttl = item.get('ttl', '?')
if type_str == "info":
lines.append(f"刚刚: {content_str}")
elif type_str == "memory":
lines.append(f"{content_str}")
elif type_str == "comparison_result":
lines.append(f"数字大小比较结果: {content_str}")
elif type_str == "time_info":
lines.append(f"{content_str}")
elif type_str == "lpmm_knowledge":
lines.append(f"你知道：{content_str}")
else:
lines.append(f"{type_str}的信息: {content_str}")
self.structured_info_str = "\n".join(lines)
logger.debug(f"{self.log_prefix} 更新 structured_info_str: \n{self.structured_info_str}")
async def do_thinking_before_reply(self, history_cycle: list[CycleInfo] = None):
"""
@@ -145,19 +176,36 @@ class SubMind:
# 更新活跃时间
self.last_active_time = time.time()
# ---------- 0. 更新和清理 structured_info ----------
if self.structured_info:
logger.debug(f"{self.log_prefix} 更新前的 structured_info: {safe_json_dumps(self.structured_info, ensure_ascii=False)}")
updated_info = []
for item in self.structured_info:
item['ttl'] -= 1
if item['ttl'] > 0:
updated_info.append(item)
else:
logger.debug(f"{self.log_prefix} 移除过期的 structured_info 项: {item['id']}")
self.structured_info = updated_info
logger.debug(f"{self.log_prefix} 更新后的 structured_info: {safe_json_dumps(self.structured_info, ensure_ascii=False)}")
self._update_structured_info_str()
logger.debug(f"{self.log_prefix} 当前完整的 structured_info: {safe_json_dumps(self.structured_info, ensure_ascii=False)}")
# ---------- 1. 准备基础数据 ----------
# 获取现有想法和情绪状态
previous_mind = self.current_mind if self.current_mind else ""
mood_info = self.chat_state.mood
# 获取观察对象
observation = self.observations[0] if self.observations else None
observation: ChattingObservation = self.observations[0] if self.observations else None
if not observation or not hasattr(observation, "is_group_chat"): # Ensure it's ChattingObservation or similar
logger.error(f"{self.log_prefix} 无法获取有效的观察对象或缺少聊天类型信息")
self.update_current_mind("(观察出错了...)")
return self.current_mind, self.past_mind
is_group_chat = observation.is_group_chat
# logger.debug(f"is_group_chat: {is_group_chat}")
chat_target_info = observation.chat_target_info
chat_target_name = "对方" # Default for private
if not is_group_chat and chat_target_info:
@@ -277,10 +325,11 @@ class SubMind:
# ---------- 4. 构建最终提示词 ----------
# --- Choose template based on chat type ---
logger.debug(f"is_group_chat: {is_group_chat}")
if is_group_chat:
template_name = "sub_heartflow_prompt_before"
prompt = (await global_prompt_manager.get_prompt_async(template_name)).format(
extra_info="",
extra_info=self.structured_info_str,
prompt_personality=prompt_personality,
relation_prompt=relation_prompt,
bot_name=individuality.name,
@@ -295,7 +344,7 @@ class SubMind:
else: # Private chat
template_name = "sub_heartflow_prompt_private_before"
prompt = (await global_prompt_manager.get_prompt_async(template_name)).format(
extra_info="",
extra_info=self.structured_info_str,
prompt_personality=prompt_personality,
relation_prompt=relation_prompt, # Might need adjustment for private context
bot_name=individuality.name,
@@ -447,7 +496,7 @@ class SubMind:
tool_instance: 工具使用器实例
"""
tool_results = []
structured_info = {} # 动态生成键
new_structured_items = [] # 收集新产生的结构化信息
# 执行所有工具调用
for tool_call in tool_calls:
@@ -455,23 +504,34 @@ class SubMind:
result = await tool_instance._execute_tool_call(tool_call)
if result:
tool_results.append(result)
# 创建新的结构化信息项
new_item = {
"type": result.get("type", "unknown_type"), # 使用 'type' 键
"id": result.get("id", f"fallback_id_{time.time()}"), # 使用 'id' 键
"content": result.get("content", ""), # 'content' 键保持不变
"ttl": 3
}
new_structured_items.append(new_item)
# 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"]})
except Exception as tool_e:
logger.error(f"[{self.subheartflow_id}] 工具执行失败: {tool_e}")
logger.error(traceback.format_exc()) # 添加 traceback 记录
# 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)}")
self.structured_info = structured_info
# 如果有新的工具结果，记录并更新结构化信息
if new_structured_items:
self.structured_info.extend(new_structured_items) # 添加到现有列表
logger.debug(f"工具调用收集到新的结构化信息: {safe_json_dumps(new_structured_items, ensure_ascii=False)}")
# logger.debug(f"当前完整的 structured_info: {safe_json_dumps(self.structured_info, ensure_ascii=False)}") # 可以取消注释以查看完整列表
self._update_structured_info_str() # 添加新信息后，更新字符串表示
def update_current_mind(self, response):
self.past_mind.append(self.current_mind)
if self.current_mind: # 只有当 current_mind 非空时才添加到 past_mind
self.past_mind.append(self.current_mind)
# 可以考虑限制 past_mind 的大小，例如:
# max_past_mind_size = 10
# if len(self.past_mind) > max_past_mind_size:
# self.past_mind.pop(0) # 移除最旧的
self.current_mind = response