feat(lightrag): Implement mix search mode combining knowledge graph and vector retrieval

- Add 'mix' mode to QueryParam for hybrid search functionality
- Implement mix_kg_vector_query to combine knowledge graph and vector search results
- Update LightRAG class to handle 'mix' mode queries
- Enhance README with examples and explanations for the new mix search mode
- Introduce new prompt structure for generating responses based on combined search results

lightrag/lightrag.py

@@ -16,6 +16,7 @@ from .operate import (
     # local_query,global_query,hybrid_query,
     kg_query,
     naive_query,
+    mix_kg_vector_query,
 )
 
 from .utils import (
@@ -630,6 +631,25 @@ class LightRAG:
                     embedding_func=None,
                 ),
             )
+        elif param.mode == "mix":
+            response = await mix_kg_vector_query(
+                query,
+                self.chunk_entity_relation_graph,
+                self.entities_vdb,
+                self.relationships_vdb,
+                self.chunks_vdb,
+                self.text_chunks,
+                param,
+                asdict(self),
+                hashing_kv=self.llm_response_cache
+                if self.llm_response_cache
+                and hasattr(self.llm_response_cache, "global_config")
+                else self.key_string_value_json_storage_cls(
+                    namespace="llm_response_cache",
+                    global_config=asdict(self),
+                    embedding_func=None,
+                ),
+            )
         else:
             raise ValueError(f"Unknown mode {param.mode}")
         await self._query_done()