'commit'

dsRagAnything/T3_Start.py

@@ -38,29 +38,8 @@ logger.addHandler(console_handler)
 
 
 async def lifespan(app: FastAPI):
-    # 初始化RAG组件
-    llm_model_func = create_llm_model_func()
-    vision_model_func = create_vision_model_func(llm_model_func)
-    embedding_func = create_embedding_func()
-
-    lightrag_instance = LightRAG(
-        working_dir=WORKING_PATH,
-        llm_model_func=llm_model_func,
-        embedding_func=embedding_func
-    )
-
-    await lightrag_instance.initialize_storages()
-    await initialize_pipeline_status()
-
-    # 创建RAG实例并保存到app.state
-    app.state.rag = RAGAnything(
-        lightrag=lightrag_instance,
-        vision_model_func=vision_model_func,
-    )
     yield
 
-    # 清理资源
-    await app.state.rag.finalize_storages()
 
 
 async def print_stream(stream):
@@ -90,6 +69,25 @@ async def rag(request: fastapi.Request):
 
     async def generate_response_stream(query: str):
         try:
+            # 初始化RAG组件
+            llm_model_func = create_llm_model_func()
+            vision_model_func = create_vision_model_func(llm_model_func)
+            embedding_func = create_embedding_func()
+
+            lightrag_instance = LightRAG(
+                working_dir=WORKING_PATH,
+                llm_model_func=llm_model_func,
+                embedding_func=embedding_func
+            )
+
+            await lightrag_instance.initialize_storages()
+            await initialize_pipeline_status()
+
+            # 创建RAG实例并保存到app.state
+            app.state.rag = RAGAnything(
+                lightrag=lightrag_instance,
+                vision_model_func=vision_model_func,
+            )
             # 直接使用app.state中已初始化的rag实例
             resp = await app.state.rag.aquery(
                 query=query,
@@ -105,6 +103,9 @@ async def rag(request: fastapi.Request):
         except Exception as e:
             yield f"data: {json.dumps({'error': str(e)})}\n\n"
             logger.error(f"处理查询时出错: {query}. 错误: {str(e)}")
+        finally:
+            # 清理资源
+            await app.state.rag.lightrag.finalize_storages()
 
     return EventSourceResponse(generate_response_stream(query=query))
 

dsRagAnything/Topic/Chinese/kv_store_llm_response_cache.json

@@ -2211,6 +2211,16 @@
       "embedding_min": null,
       "embedding_max": null,
       "original_prompt": "苏轼的家人都有谁？\n 不要输出参考资料！"
+    },
+    "5c5ee10a1a6deda17447c905118427e3": {
+      "return": "{\"high_level_keywords\": [\"\\u82cf\\u8f7c\", \"\\u597d\\u53cb\", \"\\u4eba\\u9645\\u5173\\u7cfb\"], \"low_level_keywords\": [\"\\u9ec4\\u5ead\\u575a\", \"\\u79e6\\u89c2\", \"\\u7c73\\u82be\", \"\\u4f5b\\u5370\", \"\\u6587\\u4eba\\u4ea4\\u5f80\"]}",
+      "cache_type": "keywords",
+      "chunk_id": null,
+      "embedding": null,
+      "embedding_shape": null,
+      "embedding_min": null,
+      "embedding_max": null,
+      "original_prompt": "苏轼的好朋友都有谁？\n 不要输出参考资料！"
     }
   }
 }