Merge pull request #642 from dimatill/main

lightrag/operate.py

@@ -990,28 +990,35 @@ async def _build_query_context(
             query_param,
         )
     else:  # hybrid mode
+        ll_data, hl_data = await asyncio.gather(
+            _get_node_data(
+                ll_keywords,
+                knowledge_graph_inst,
+                entities_vdb,
+                text_chunks_db,
+                query_param,
+            ),
+            _get_edge_data(
+                hl_keywords,
+                knowledge_graph_inst,
+                relationships_vdb,
+                text_chunks_db,
+                query_param,
+            ),
+        )
+
         (
             ll_entities_context,
             ll_relations_context,
             ll_text_units_context,
-        ) = await _get_node_data(
-            ll_keywords,
-            knowledge_graph_inst,
-            entities_vdb,
-            text_chunks_db,
-            query_param,
-        )
+        ) = ll_data
+
         (
             hl_entities_context,
             hl_relations_context,
             hl_text_units_context,
-        ) = await _get_edge_data(
-            hl_keywords,
-            knowledge_graph_inst,
-            relationships_vdb,
-            text_chunks_db,
-            query_param,
-        )
+        ) = hl_data
+
         entities_context, relations_context, text_units_context = combine_contexts(
             [hl_entities_context, ll_entities_context],
             [hl_relations_context, ll_relations_context],
@@ -1045,28 +1052,31 @@ async def _get_node_data(
     if not len(results):
         return "", "", ""
     # get entity information
-    node_datas = await asyncio.gather(
-        *[knowledge_graph_inst.get_node(r["entity_name"]) for r in results]
+    node_datas, node_degrees = await asyncio.gather(
+        asyncio.gather(
+            *[knowledge_graph_inst.get_node(r["entity_name"]) for r in results]
+        ),
+        asyncio.gather(
+            *[knowledge_graph_inst.node_degree(r["entity_name"]) for r in results]
+        ),
     )
+
     if not all([n is not None for n in node_datas]):
         logger.warning("Some nodes are missing, maybe the storage is damaged")
 
-    # get entity degree
-    node_degrees = await asyncio.gather(
-        *[knowledge_graph_inst.node_degree(r["entity_name"]) for r in results]
-    )
     node_datas = [
         {**n, "entity_name": k["entity_name"], "rank": d}
         for k, n, d in zip(results, node_datas, node_degrees)
         if n is not None
     ]  # what is this text_chunks_db doing.  dont remember it in airvx.  check the diagram.
     # get entitytext chunk
-    use_text_units = await _find_most_related_text_unit_from_entities(
-        node_datas, query_param, text_chunks_db, knowledge_graph_inst
-    )
-    # get relate edges
-    use_relations = await _find_most_related_edges_from_entities(
-        node_datas, query_param, knowledge_graph_inst
+    use_text_units, use_relations = await asyncio.gather(
+        _find_most_related_text_unit_from_entities(
+            node_datas, query_param, text_chunks_db, knowledge_graph_inst
+        ),
+        _find_most_related_edges_from_entities(
+            node_datas, query_param, knowledge_graph_inst
+        ),
     )
     logger.info(
         f"Local query uses {len(node_datas)} entites, {len(use_relations)} relations, {len(use_text_units)} text units"
@@ -1156,22 +1166,30 @@ async def _find_most_related_text_unit_from_entities(
     }
 
     all_text_units_lookup = {}
+    tasks = []
     for index, (this_text_units, this_edges) in enumerate(zip(text_units, edges)):
         for c_id in this_text_units:
             if c_id not in all_text_units_lookup:
-                all_text_units_lookup[c_id] = {
-                    "data": await text_chunks_db.get_by_id(c_id),
-                    "order": index,
-                    "relation_counts": 0,
-                }
+                tasks.append((c_id, index, this_edges))
 
-            if this_edges:
-                for e in this_edges:
-                    if (
-                        e[1] in all_one_hop_text_units_lookup
-                        and c_id in all_one_hop_text_units_lookup[e[1]]
-                    ):
-                        all_text_units_lookup[c_id]["relation_counts"] += 1
+    results = await asyncio.gather(
+        *[text_chunks_db.get_by_id(c_id) for c_id, _, _ in tasks]
+    )
+
+    for (c_id, index, this_edges), data in zip(tasks, results):
+        all_text_units_lookup[c_id] = {
+            "data": data,
+            "order": index,
+            "relation_counts": 0,
+        }
+
+        if this_edges:
+            for e in this_edges:
+                if (
+                    e[1] in all_one_hop_text_units_lookup
+                    and c_id in all_one_hop_text_units_lookup[e[1]]
+                ):
+                    all_text_units_lookup[c_id]["relation_counts"] += 1
 
     # Filter out None values and ensure data has content
     all_text_units = [
@@ -1216,11 +1234,11 @@ async def _find_most_related_edges_from_entities(
                 seen.add(sorted_edge)
                 all_edges.append(sorted_edge)
 
-    all_edges_pack = await asyncio.gather(
-        *[knowledge_graph_inst.get_edge(e[0], e[1]) for e in all_edges]
-    )
-    all_edges_degree = await asyncio.gather(
-        *[knowledge_graph_inst.edge_degree(e[0], e[1]) for e in all_edges]
+    all_edges_pack, all_edges_degree = await asyncio.gather(
+        asyncio.gather(*[knowledge_graph_inst.get_edge(e[0], e[1]) for e in all_edges]),
+        asyncio.gather(
+            *[knowledge_graph_inst.edge_degree(e[0], e[1]) for e in all_edges]
+        ),
     )
     all_edges_data = [
         {"src_tgt": k, "rank": d, **v}
@@ -1250,15 +1268,21 @@ async def _get_edge_data(
     if not len(results):
         return "", "", ""
 
-    edge_datas = await asyncio.gather(
-        *[knowledge_graph_inst.get_edge(r["src_id"], r["tgt_id"]) for r in results]
+    edge_datas, edge_degree = await asyncio.gather(
+        asyncio.gather(
+            *[knowledge_graph_inst.get_edge(r["src_id"], r["tgt_id"]) for r in results]
+        ),
+        asyncio.gather(
+            *[
+                knowledge_graph_inst.edge_degree(r["src_id"], r["tgt_id"])
+                for r in results
+            ]
+        ),
     )
 
     if not all([n is not None for n in edge_datas]):
         logger.warning("Some edges are missing, maybe the storage is damaged")
-    edge_degree = await asyncio.gather(
-        *[knowledge_graph_inst.edge_degree(r["src_id"], r["tgt_id"]) for r in results]
-    )
+
     edge_datas = [
         {
             "src_id": k["src_id"],
@@ -1279,11 +1303,13 @@ async def _get_edge_data(
         max_token_size=query_param.max_token_for_global_context,
     )
 
-    use_entities = await _find_most_related_entities_from_relationships(
-        edge_datas, query_param, knowledge_graph_inst
-    )
-    use_text_units = await _find_related_text_unit_from_relationships(
-        edge_datas, query_param, text_chunks_db, knowledge_graph_inst
+    use_entities, use_text_units = await asyncio.gather(
+        _find_most_related_entities_from_relationships(
+            edge_datas, query_param, knowledge_graph_inst
+        ),
+        _find_related_text_unit_from_relationships(
+            edge_datas, query_param, text_chunks_db, knowledge_graph_inst
+        ),
     )
     logger.info(
         f"Global query uses {len(use_entities)} entites, {len(edge_datas)} relations, {len(use_text_units)} text units"
@@ -1356,12 +1382,19 @@ async def _find_most_related_entities_from_relationships(
             entity_names.append(e["tgt_id"])
             seen.add(e["tgt_id"])
 
-    node_datas = await asyncio.gather(
-        *[knowledge_graph_inst.get_node(entity_name) for entity_name in entity_names]
-    )
-
-    node_degrees = await asyncio.gather(
-        *[knowledge_graph_inst.node_degree(entity_name) for entity_name in entity_names]
+    node_datas, node_degrees = await asyncio.gather(
+        asyncio.gather(
+            *[
+                knowledge_graph_inst.get_node(entity_name)
+                for entity_name in entity_names
+            ]
+        ),
+        asyncio.gather(
+            *[
+                knowledge_graph_inst.node_degree(entity_name)
+                for entity_name in entity_names
+            ]
+        ),
     )
     node_datas = [
         {**n, "entity_name": k, "rank": d}
@@ -1389,16 +1422,22 @@ async def _find_related_text_unit_from_relationships(
     ]
     all_text_units_lookup = {}
 
+    async def fetch_chunk_data(c_id, index):
+        if c_id not in all_text_units_lookup:
+            chunk_data = await text_chunks_db.get_by_id(c_id)
+            # Only store valid data
+            if chunk_data is not None and "content" in chunk_data:
+                all_text_units_lookup[c_id] = {
+                    "data": chunk_data,
+                    "order": index,
+                }
+
+    tasks = []
     for index, unit_list in enumerate(text_units):
         for c_id in unit_list:
-            if c_id not in all_text_units_lookup:
-                chunk_data = await text_chunks_db.get_by_id(c_id)
-                # Only store valid data
-                if chunk_data is not None and "content" in chunk_data:
-                    all_text_units_lookup[c_id] = {
-                        "data": chunk_data,
-                        "order": index,
-                    }
+            tasks.append(fetch_chunk_data(c_id, index))
+
+    await asyncio.gather(*tasks)
 
     if not all_text_units_lookup:
         logger.warning("No valid text chunks found")