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Merge pull request #3101 from xinnan-tech/fix-title-summary
fix:修复PowerMem和Mem0AI记忆模型不会总结会话标题的问题
This commit is contained in:
wengzh
@@ -2,6 +2,7 @@ import json
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import traceback
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from ..base import MemoryProviderBase, logger
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from config.manage_api_client import generate_and_save_chat_summary
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from mem0 import MemoryClient
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from core.utils.util import check_model_key
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@@ -30,38 +31,40 @@ class MemoryProvider(MemoryProviderBase):
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self.use_mem0 = False
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async def save_memory(self, msgs, session_id=None):
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if not self.use_mem0:
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return None
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if len(msgs) < 2:
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return None
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try:
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# Format the content as a message list for mem0
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messages = []
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for message in msgs:
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if message.role == "system":
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continue
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if self.use_mem0 and len(msgs) >= 2:
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# Format the content as a message list for mem0
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messages = []
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for message in msgs:
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if message.role == "system":
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continue
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content = message.content
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content = message.content
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# Extract content from JSON format if present (for ASR with emotion/language tags)
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# Same logic as in query_memory method
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try:
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if content and content.strip().startswith("{") and content.strip().endswith("}"):
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data = json.loads(content)
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if "content" in data:
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content = data["content"]
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except (json.JSONDecodeError, KeyError, TypeError):
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# If parsing fails, use original content
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pass
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# Extract content from JSON format if present (for ASR with emotion/language tags)
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# Same logic as in query_memory method
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try:
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if content and content.strip().startswith("{") and content.strip().endswith("}"):
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data = json.loads(content)
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if "content" in data:
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content = data["content"]
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except (json.JSONDecodeError, KeyError, TypeError):
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# If parsing fails, use original content
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pass
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messages.append({"role": message.role, "content": content})
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messages.append({"role": message.role, "content": content})
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result = self.client.add(messages, user_id=self.role_id)
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logger.bind(tag=TAG).debug(f"Save memory result: {result}")
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result = self.client.add(messages, user_id=self.role_id)
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logger.bind(tag=TAG).debug(f"Save memory result: {result}")
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except Exception as e:
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logger.bind(tag=TAG).error(f"保存记忆失败: {str(e)}")
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return None
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# Generate and save chat summary (SLM summarizes session title)
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# This is independent of Mem0AI's memory saving
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if session_id:
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await generate_and_save_chat_summary(session_id)
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return None
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async def query_memory(self, query: str) -> str:
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if not self.use_mem0:
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@@ -16,6 +16,7 @@ import traceback
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from typing import Optional, Dict, Any
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from ..base import MemoryProviderBase, logger
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from config.manage_api_client import generate_and_save_chat_summary
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TAG = __name__
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@@ -162,59 +163,60 @@ class MemoryProvider(MemoryProviderBase):
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Returns:
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Result from PowerMem API or None if failed
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"""
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if not self.use_powermem or self.memory_client is None:
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logger.bind(tag=TAG).warning("PowerMem is not available, skipping save_memory")
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return None
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if len(msgs) < 2:
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logger.bind(tag=TAG).debug("Not enough messages to save (need at least 2)")
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return None
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try:
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# Format the content as a message list for PowerMem
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messages = []
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for message in msgs:
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if message.role == "system":
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continue
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if self.use_powermem and self.memory_client is not None and len(msgs) >= 2:
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# Format the content as a message list for PowerMem
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messages = []
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for message in msgs:
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if message.role == "system":
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continue
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content = message.content
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content = message.content
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# Extract content from JSON format if present (for ASR with emotion/language tags)
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# Same logic as in query_memory method
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try:
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if content and content.strip().startswith("{") and content.strip().endswith("}"):
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data = json.loads(content)
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if "content" in data:
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content = data["content"]
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except (json.JSONDecodeError, KeyError, TypeError):
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# If parsing fails, use original content
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pass
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# Extract content from JSON format if present (for ASR with emotion/language tags)
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# Same logic as in query_memory method
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try:
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if content and content.strip().startswith("{") and content.strip().endswith("}"):
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data = json.loads(content)
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if "content" in data:
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content = data["content"]
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except (json.JSONDecodeError, KeyError, TypeError):
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# If parsing fails, use original content
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pass
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messages.append({"role": message.role, "content": content})
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messages.append({"role": message.role, "content": content})
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# Add memory using PowerMem SDK
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result = self.memory_client.add(
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messages=messages,
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user_id=self.role_id
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)
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# Handle both sync and async returns
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if asyncio.iscoroutine(result):
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result = await result
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# Add memory using PowerMem SDK
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result = self.memory_client.add(
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messages=messages,
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user_id=self.role_id
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)
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# Handle both sync and async returns
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if asyncio.iscoroutine(result):
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result = await result
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logger.bind(tag=TAG).debug(f"Save memory result: {result}")
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# Cache user profile if UserMemory mode and profile was extracted
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if self.enable_user_profile and result:
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if result.get('profile_extracted'):
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self.last_profile_content = result.get('profile_content', '')
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logger.bind(tag=TAG).debug(f"User profile extracted: {self.last_profile_content}")
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return result
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logger.bind(tag=TAG).debug(f"Save memory result: {result}")
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# Cache user profile if UserMemory mode and profile was extracted
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if self.enable_user_profile and result:
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if result.get('profile_extracted'):
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self.last_profile_content = result.get('profile_content', '')
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logger.bind(tag=TAG).debug(f"User profile extracted: {self.last_profile_content}")
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else:
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if not self.use_powermem or self.memory_client is None:
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logger.bind(tag=TAG).warning("PowerMem is not available, skipping save_memory")
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elif len(msgs) < 2:
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logger.bind(tag=TAG).debug("Not enough messages to save (need at least 2)")
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except Exception as e:
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logger.bind(tag=TAG).error(f"Error saving memory: {str(e)}")
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logger.bind(tag=TAG).debug(f"Detailed error: {traceback.format_exc()}")
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return None
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# Generate and save chat summary (SLM summarizes session title)
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# This is independent of PowerMem's memory saving
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if session_id:
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await generate_and_save_chat_summary(session_id)
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return None
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async def query_memory(self, query: str) -> str:
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"""
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