Update vector query methods to support ID filtering in PostgreSQL

- Modified `mix_kg_vector_query` in operate.py to pass optional IDs to vector search
- Updated PostgreSQL SQL template to filter results using document IDs instead of chunk_id
- Improved query flexibility by allowing precise document selection during vector search

lightrag/kg/postgres_impl.py

@@ -1597,7 +1597,7 @@ SQL_TEMPLATES = {
                 SELECT id, 1 - (content_vector <=> '[{embedding_string}]'::vector) as distance
                 FROM LIGHTRAG_DOC_CHUNKS 
                 where workspace=$1
-                AND chunk_id IN (SELECT chunk_id FROM relevant_chunks)
+                AND id IN (SELECT chunk_id FROM relevant_chunks)
             )
             WHERE distance>$2 
             ORDER BY distance DESC 

lightrag/operate.py

@@ -892,7 +892,8 @@ async def mix_kg_vector_query(
         try:
             # Reduce top_k for vector search in hybrid mode since we have structured information from KG
             mix_topk = min(10, query_param.top_k)
-            results = await chunks_vdb.query(augmented_query, top_k=mix_topk)
+            # TODO: add ids to the query
+            results = await chunks_vdb.query(augmented_query, top_k=mix_topk, ids = query_param.ids)
             if not results:
                 return None