update

lightrag/operate.py

@@ -176,7 +176,6 @@ async def _merge_edges_then_upsert(
     already_weights = []
     already_source_ids = []
     already_description = []
-    ##################
     already_keywords = []
 
     if await knwoledge_graph_inst.has_edge(src_id, tgt_id):
@@ -186,7 +185,6 @@ async def _merge_edges_then_upsert(
             split_string_by_multi_markers(already_edge["source_id"], [GRAPH_FIELD_SEP])
         )
         already_description.append(already_edge["description"])
-        ############
         already_keywords.extend(
             split_string_by_multi_markers(already_edge["keywords"], [GRAPH_FIELD_SEP])
         )
@@ -195,7 +193,6 @@ async def _merge_edges_then_upsert(
     description = GRAPH_FIELD_SEP.join(
         sorted(set([dp["description"] for dp in edges_data] + already_description))
     )
-    ##########
     keywords = GRAPH_FIELD_SEP.join(
         sorted(set([dp["keywords"] for dp in edges_data] + already_keywords))
     )
@@ -403,7 +400,7 @@ async def local_query(
     except json.JSONDecodeError as e:
         # Handle parsing error
         print(f"JSON parsing error: {e}")
-        return PROMPTS["fail_response"], "None"
+        return PROMPTS["fail_response"]
     
     context = await _build_local_query_context(
         keywords,
@@ -415,7 +412,7 @@ async def local_query(
     if query_param.only_need_context:
         return context
     if context is None:
-        return PROMPTS["fail_response"], "None"
+        return PROMPTS["fail_response"]
     sys_prompt_temp = PROMPTS["rag_response"]
     sys_prompt = sys_prompt_temp.format(
         context_data=context, response_type=query_param.response_type
@@ -424,7 +421,7 @@ async def local_query(
         query,
         system_prompt=sys_prompt,
     )
-    return response, context
+    return response
 
 async def _build_local_query_context(
     query,
@@ -622,7 +619,7 @@ async def global_query(
     except json.JSONDecodeError as e:
         # Handle parsing error
         print(f"JSON parsing error: {e}")
-        return PROMPTS["fail_response"], "None"
+        return PROMPTS["fail_response"]
 
     context = await _build_global_query_context(
         keywords,
@@ -636,7 +633,7 @@ async def global_query(
     if query_param.only_need_context:
         return context
     if context is None:
-        return PROMPTS["fail_response"], "None"
+        return PROMPTS["fail_response"]
     
     sys_prompt_temp = PROMPTS["rag_response"]
     sys_prompt = sys_prompt_temp.format(
@@ -646,7 +643,7 @@ async def global_query(
         query,
         system_prompt=sys_prompt,
     )
-    return (response, context)
+    return response
 
 async def _build_global_query_context(
     keywords,
@@ -836,7 +833,7 @@ async def hybird_query(
     except json.JSONDecodeError as e:
         # Handle parsing error
         print(f"JSON parsing error: {e}")
-        return PROMPTS["fail_response"], "None"
+        return PROMPTS["fail_response"]
         
     low_level_context = await _build_local_query_context(
         ll_keywords,
@@ -860,7 +857,7 @@ async def hybird_query(
     if query_param.only_need_context:
         return context
     if context is None:
-        return PROMPTS["fail_response"], "None"
+        return PROMPTS["fail_response"]
     
     sys_prompt_temp = PROMPTS["rag_response"]
     sys_prompt = sys_prompt_temp.format(
@@ -870,7 +867,7 @@ async def hybird_query(
         query,
         system_prompt=sys_prompt,
     )
-    return (response, context)
+    return response
 
 def combine_contexts(high_level_context, low_level_context):
     # Function to extract entities, relationships, and sources from context strings
@@ -922,14 +919,14 @@ async def naive_query(
     use_model_func = global_config["llm_model_func"]
     results = await chunks_vdb.query(query, top_k=query_param.top_k)
     if not len(results):
-        return PROMPTS["fail_response"], "None"
+        return PROMPTS["fail_response"]
     chunks_ids = [r["id"] for r in results]
     chunks = await text_chunks_db.get_by_ids(chunks_ids)
 
     maybe_trun_chunks = truncate_list_by_token_size(
         chunks,
         key=lambda x: x["content"],
-        max_token_size=query_param.naive_max_token_for_text_unit,
+        max_token_size=query_param.max_token_for_text_unit,
     )
     logger.info(f"Truncate {len(chunks)} to {len(maybe_trun_chunks)} chunks")
     section = "--New Chunk--\n".join([c["content"] for c in maybe_trun_chunks])