Merge pull request #141 from Yazington/feature/other-storage

lightrag/lightrag.py

@@ -85,7 +85,9 @@ class LightRAG:
 
     # LLM
     llm_model_func: callable = gpt_4o_mini_complete  # hf_model_complete#
-    llm_model_name: str = "meta-llama/Llama-3.2-1B-Instruct"  #'meta-llama/Llama-3.2-1B'#'google/gemma-2-2b-it'
+    llm_model_name: str = (
+        "meta-llama/Llama-3.2-1B-Instruct"  #'meta-llama/Llama-3.2-1B'#'google/gemma-2-2b-it'
+    )
     llm_model_max_token_size: int = 32768
     llm_model_max_async: int = 16
 

lightrag/operate.py

@@ -160,7 +160,7 @@ async def _merge_nodes_then_upsert(
         description=description,
         source_id=source_id,
     )
-    await knwoledge_graph_inst.upsert_node(
+    await knowledge_graph_inst.upsert_node(
         entity_name,
         node_data=node_data,
     )
@@ -172,7 +172,7 @@ async def _merge_edges_then_upsert(
     src_id: str,
     tgt_id: str,
     edges_data: list[dict],
-    knwoledge_graph_inst: BaseGraphStorage,
+    knowledge_graph_inst: BaseGraphStorage,
     global_config: dict,
 ):
     already_weights = []
@@ -180,8 +180,8 @@ async def _merge_edges_then_upsert(
     already_description = []
     already_keywords = []
 
-    if await knwoledge_graph_inst.has_edge(src_id, tgt_id):
-        already_edge = await knwoledge_graph_inst.get_edge(src_id, tgt_id)
+    if await knowledge_graph_inst.has_edge(src_id, tgt_id):
+        already_edge = await knowledge_graph_inst.get_edge(src_id, tgt_id)
         already_weights.append(already_edge["weight"])
         already_source_ids.extend(
             split_string_by_multi_markers(already_edge["source_id"], [GRAPH_FIELD_SEP])
@@ -202,8 +202,8 @@ async def _merge_edges_then_upsert(
         set([dp["source_id"] for dp in edges_data] + already_source_ids)
     )
     for need_insert_id in [src_id, tgt_id]:
-        if not (await knwoledge_graph_inst.has_node(need_insert_id)):
-            await knwoledge_graph_inst.upsert_node(
+        if not (await knowledge_graph_inst.has_node(need_insert_id)):
+            await knowledge_graph_inst.upsert_node(
                 need_insert_id,
                 node_data={
                     "source_id": source_id,
@@ -214,7 +214,7 @@ async def _merge_edges_then_upsert(
     description = await _handle_entity_relation_summary(
         (src_id, tgt_id), description, global_config
     )
-    await knwoledge_graph_inst.upsert_edge(
+    await knowledge_graph_inst.upsert_edge(
         src_id,
         tgt_id,
         edge_data=dict(
@@ -237,7 +237,7 @@ async def _merge_edges_then_upsert(
 
 async def extract_entities(
     chunks: dict[str, TextChunkSchema],
-    knwoledge_graph_inst: BaseGraphStorage,
+    knowledge_graph_inst: BaseGraphStorage,
     entity_vdb: BaseVectorStorage,
     relationships_vdb: BaseVectorStorage,
     global_config: dict,
@@ -341,13 +341,13 @@ async def extract_entities(
             maybe_edges[tuple(sorted(k))].extend(v)
     all_entities_data = await asyncio.gather(
         *[
-            _merge_nodes_then_upsert(k, v, knwoledge_graph_inst, global_config)
+            _merge_nodes_then_upsert(k, v, knowledge_graph_inst, global_config)
             for k, v in maybe_nodes.items()
         ]
     )
     all_relationships_data = await asyncio.gather(
         *[
-            _merge_edges_then_upsert(k[0], k[1], v, knwoledge_graph_inst, global_config)
+            _merge_edges_then_upsert(k[0], k[1], v, knowledge_graph_inst, global_config)
             for k, v in maybe_edges.items()
         ]
     )
@@ -384,7 +384,7 @@ async def extract_entities(
         }
         await relationships_vdb.upsert(data_for_vdb)
 
-    return knwoledge_graph_inst
+    return knowledge_graph_inst
 
 
 async def local_query(