chunk split retry

lightrag/lightrag.py

@@ -268,7 +268,7 @@ class LightRAG:
                 self.llm_model_func,
                 hashing_kv=self.llm_response_cache
                 if self.llm_response_cache
-                   and hasattr(self.llm_response_cache, "global_config")
+                and hasattr(self.llm_response_cache, "global_config")
                 else self.key_string_value_json_storage_cls(
                     namespace="llm_response_cache",
                     global_config=asdict(self),
@@ -316,7 +316,9 @@ class LightRAG:
 
     def insert(self, string_or_strings, split_by_character=None):
         loop = always_get_an_event_loop()
-        return loop.run_until_complete(self.ainsert(string_or_strings, split_by_character))
+        return loop.run_until_complete(
+            self.ainsert(string_or_strings, split_by_character)
+        )
 
     async def ainsert(self, string_or_strings, split_by_character):
         """Insert documents with checkpoint support
@@ -357,10 +359,10 @@ class LightRAG:
         # Process documents in batches
         batch_size = self.addon_params.get("insert_batch_size", 10)
         for i in range(0, len(new_docs), batch_size):
-            batch_docs = dict(list(new_docs.items())[i: i + batch_size])
+            batch_docs = dict(list(new_docs.items())[i : i + batch_size])
 
             for doc_id, doc in tqdm_async(
-                    batch_docs.items(), desc=f"Processing batch {i // batch_size + 1}"
+                batch_docs.items(), desc=f"Processing batch {i // batch_size + 1}"
             ):
                 try:
                     # Update status to processing
@@ -548,7 +550,7 @@ class LightRAG:
                 # Check if nodes exist in the knowledge graph
                 for need_insert_id in [src_id, tgt_id]:
                     if not (
-                            await self.chunk_entity_relation_graph.has_node(need_insert_id)
+                        await self.chunk_entity_relation_graph.has_node(need_insert_id)
                     ):
                         await self.chunk_entity_relation_graph.upsert_node(
                             need_insert_id,
@@ -597,9 +599,9 @@ class LightRAG:
                         "src_id": dp["src_id"],
                         "tgt_id": dp["tgt_id"],
                         "content": dp["keywords"]
-                                   + dp["src_id"]
-                                   + dp["tgt_id"]
-                                   + dp["description"],
+                        + dp["src_id"]
+                        + dp["tgt_id"]
+                        + dp["description"],
                     }
                     for dp in all_relationships_data
                 }
@@ -624,7 +626,7 @@ class LightRAG:
                 asdict(self),
                 hashing_kv=self.llm_response_cache
                 if self.llm_response_cache
-                   and hasattr(self.llm_response_cache, "global_config")
+                and hasattr(self.llm_response_cache, "global_config")
                 else self.key_string_value_json_storage_cls(
                     namespace="llm_response_cache",
                     global_config=asdict(self),
@@ -640,7 +642,7 @@ class LightRAG:
                 asdict(self),
                 hashing_kv=self.llm_response_cache
                 if self.llm_response_cache
-                   and hasattr(self.llm_response_cache, "global_config")
+                and hasattr(self.llm_response_cache, "global_config")
                 else self.key_string_value_json_storage_cls(
                     namespace="llm_response_cache",
                     global_config=asdict(self),
@@ -659,7 +661,7 @@ class LightRAG:
                 asdict(self),
                 hashing_kv=self.llm_response_cache
                 if self.llm_response_cache
-                   and hasattr(self.llm_response_cache, "global_config")
+                and hasattr(self.llm_response_cache, "global_config")
                 else self.key_string_value_json_storage_cls(
                     namespace="llm_response_cache",
                     global_config=asdict(self),
@@ -900,7 +902,7 @@ class LightRAG:
                         dp
                         for dp in self.entities_vdb.client_storage["data"]
                         if chunk_id
-                           in (dp.get("source_id") or "").split(GRAPH_FIELD_SEP)
+                        in (dp.get("source_id") or "").split(GRAPH_FIELD_SEP)
                     ]
                     if entities_with_chunk:
                         logger.error(
@@ -912,7 +914,7 @@ class LightRAG:
                         dp
                         for dp in self.relationships_vdb.client_storage["data"]
                         if chunk_id
-                           in (dp.get("source_id") or "").split(GRAPH_FIELD_SEP)
+                        in (dp.get("source_id") or "").split(GRAPH_FIELD_SEP)
                     ]
                     if relations_with_chunk:
                         logger.error(
@@ -929,7 +931,7 @@ class LightRAG:
         return asyncio.run(self.adelete_by_doc_id(doc_id))
 
     async def get_entity_info(
-            self, entity_name: str, include_vector_data: bool = False
+        self, entity_name: str, include_vector_data: bool = False
     ):
         """Get detailed information of an entity
 
@@ -980,7 +982,7 @@ class LightRAG:
             tracemalloc.stop()
 
     async def get_relation_info(
-            self, src_entity: str, tgt_entity: str, include_vector_data: bool = False
+        self, src_entity: str, tgt_entity: str, include_vector_data: bool = False
     ):
         """Get detailed information of a relationship
 
@@ -1022,7 +1024,7 @@ class LightRAG:
         return result
 
     def get_relation_info_sync(
-            self, src_entity: str, tgt_entity: str, include_vector_data: bool = False
+        self, src_entity: str, tgt_entity: str, include_vector_data: bool = False
     ):
         """Synchronous version of getting relationship information