config_id字段改成UUID，与develop校对恢复

api/app/core/agent/langchain_agent.py

@@ -145,33 +145,36 @@ class LangChainAgent:
         messages.append(HumanMessage(content=user_content))
 
         return messages
-    async def term_memory_save(self,messages,end_user_end,aimessages):
-        '''短长期存储redis，为不影响正常使用6句一段话，存储用户名加一个前缀，当数据存够6条返回给neo4j'''
-        end_user_end=f"Term_{end_user_end}"
-        print(messages)
-        print(aimessages)
-        session_id = store.save_session(
-                        userid=end_user_end,
-                        messages=messages,
-                        apply_id=end_user_end,
-                        end_user_id=end_user_end,
-                        aimessages=aimessages
-                    )
-        store.delete_duplicate_sessions()
-        # logger.info(f'Redis_Agent:{end_user_end};{session_id}')
-        return session_id
-    async def term_memory_redis_read(self,end_user_end):
-        end_user_end = f"Term_{end_user_end}"
-        history = store.find_user_apply_group(end_user_end, end_user_end, end_user_end)
-        # logger.info(f'Redis_Agent:{end_user_end};{history}')
-        messagss_list=[]
-        retrieved_content=[]
-        for messages in history:
-            query = messages.get("Query")
-            aimessages = messages.get("Answer")
-            messagss_list.append(f'用户:{query}。AI回复:{aimessages}')
-            retrieved_content.append({query: aimessages})
-        return messagss_list,retrieved_content
+# TODO 乐力齐 - 累积多组对话批量写入功能已禁用
+    # async def term_memory_save(self,messages,end_user_end,aimessages):
+    #     '''短长期存储redis，为不影响正常使用6句一段话，存储用户名加一个前缀，当数据存够6条返回给neo4j'''
+    #     end_user_end=f"Term_{end_user_end}"
+    #     print(messages)
+    #     print(aimessages)
+    #     session_id = store.save_session(
+    #                     userid=end_user_end,
+    #                     messages=messages,
+    #                     apply_id=end_user_end,
+    #                     group_id=end_user_end,
+    #                     aimessages=aimessages
+    #                 )
+    #     store.delete_duplicate_sessions()
+    #     # logger.info(f'Redis_Agent:{end_user_end};{session_id}')
+    #     return session_id
+
+# TODO 乐力齐 - 累积多组对话批量写入功能已禁用
+    # async def term_memory_redis_read(self,end_user_end):
+    #     end_user_end = f"Term_{end_user_end}"
+    #     history = store.find_user_apply_group(end_user_end, end_user_end, end_user_end)
+    #     # logger.info(f'Redis_Agent:{end_user_end};{history}')
+    #     messagss_list=[]
+    #     retrieved_content=[]
+    #     for messages in history:
+    #         query = messages.get("Query")
+    #         aimessages = messages.get("Answer")
+    #         messagss_list.append(f'用户:{query}。AI回复:{aimessages}')
+    #         retrieved_content.append({query: aimessages})
+    #     return messagss_list,retrieved_content
 
     async def write(self, storage_type, end_user_id, user_message, ai_message, user_rag_memory_id, actual_end_user_id, actual_config_id):
         """

api/app/core/memory/agent/langgraph_graph/write_graph.py

@@ -34,11 +34,17 @@ async def make_write_graph():
         end_user_id: Group identifier
         memory_config: MemoryConfig object containing all configuration
     """
+    # workflow = StateGraph(WriteState)
+    # workflow.add_node("content_input", content_input_write)
+    # workflow.add_node("save_neo4j", write_node)
+    # workflow.add_edge(START, "content_input")
+    # workflow.add_edge("content_input", "save_neo4j")
+    # workflow.add_edge("save_neo4j", END)
+    #
+    # graph = workflow.compile()
     workflow = StateGraph(WriteState)
-    workflow.add_node("content_input", content_input_write)
     workflow.add_node("save_neo4j", write_node)
-    workflow.add_edge(START, "content_input")
-    workflow.add_edge("content_input", "save_neo4j")
+    workflow.add_edge(START, "save_neo4j")
     workflow.add_edge("save_neo4j", END)
 
     graph = workflow.compile()

api/app/core/memory/evaluation/locomo/qwen_search_eval.py

@@ -30,7 +30,7 @@ from app.core.memory.storage_services.search import run_hybrid_search
 from app.core.memory.utils.config.definitions import (
     PROJECT_ROOT,
     SELECTED_EMBEDDING_ID,
-    SELECTED_end_user_id,
+    SELECTED_GROUP_ID,
     SELECTED_LLM_ID,
 )
 from app.core.memory.utils.llm.llm_utils import MemoryClientFactory

api/app/core/memory/evaluation/memsciqa/evaluate_qa.py

@@ -27,7 +27,7 @@ from app.core.memory.storage_services.search import run_hybrid_search
 from app.core.memory.utils.config.definitions import (
     PROJECT_ROOT,
     SELECTED_EMBEDDING_ID,
-    SELECTED_end_user_id,
+    SELECTED_GROUP_ID,
     SELECTED_LLM_ID,
 )
 from app.core.memory.utils.llm.llm_utils import MemoryClientFactory
@@ -136,7 +136,7 @@ def _combine_dialogues_for_hybrid(results: Dict[str, Any]) -> List[Dict[str, Any
 
 
 async def run_memsciqa_eval(sample_size: int = 1, end_user_id: str | None = None, search_limit: int = 8, context_char_budget: int = 4000, llm_temperature: float = 0.0, llm_max_tokens: int = 64, search_type: str = "hybrid", memory_config: "MemoryConfig" = None) -> Dict[str, Any]:
-    end_user_id = end_user_id or SELECTED_end_user_id
+    end_user_id = end_user_id or SELECTED_GROUP_ID
     # Load data
     data_path = os.path.join(PROJECT_ROOT, "data", "msc_self_instruct.jsonl")
     if not os.path.exists(data_path):

api/app/core/memory/evaluation/memsciqa/memsciqa-test.py

@@ -33,7 +33,7 @@ from app.core.memory.llm_tools.openai_embedder import OpenAIEmbedderClient
 from app.core.memory.utils.config.definitions import (
     PROJECT_ROOT,
     SELECTED_EMBEDDING_ID,
-    SELECTED_end_user_id,
+    SELECTED_GROUP_ID,
     SELECTED_LLM_ID,
 )
 from app.core.memory.utils.llm.llm_utils import MemoryClientFactory

api/app/core/memory/evaluation/run_eval.py

@@ -15,7 +15,7 @@ except Exception:
         return None
 
 from app.repositories.neo4j.neo4j_connector import Neo4jConnector
-from app.core.memory.utils.config.definitions import SELECTED_end_user_id, PROJECT_ROOT
+from app.core.memory.utils.config.definitions import SELECTED_GROUP_ID, PROJECT_ROOT
 
 from app.core.memory.evaluation.memsciqa.evaluate_qa import run_memsciqa_eval
 from app.core.memory.evaluation.longmemeval.qwen_search_eval import run_longmemeval_test
@@ -37,7 +37,7 @@ async def run(
     max_contexts_per_item: int | None = None,
 ) -> Dict[str, Any]:
     # 恢复原始风格：统一入口做路由，并沿用各数据集既有默认
-    end_user_id = end_user_id or SELECTED_end_user_id
+    end_user_id = end_user_id or SELECTED_GROUP_ID
 
     if reset_group:
         connector = Neo4jConnector()

api/app/core/memory/src/search.py

@@ -693,9 +693,6 @@ async def run_hybrid_search(
     # Start overall timing
     search_start_time = time.time()
     latency_metrics = {}
-    print(100*'-')
-    print(memory_config)
-    print(100 * '-')
     logger.info(f"using embedding_id:{memory_config.embedding_model_id}...")
 
     # Clean and normalize the incoming query before use/logging