support elasticsearch text only

metagpt/rag/factories/base.py

@@ -41,7 +41,7 @@ class ConfigBasedFactory(GenericFactory):
         if creator:
             return creator(key, **kwargs)
 
-        raise ValueError(f"Unknown config: {key}")
+        raise ValueError(f"Unknown config: `{type(key)}`, {key}")
 
     @staticmethod
     def _val_from_config_or_kwargs(key: str, config: object = None, **kwargs) -> Any:

metagpt/rag/factories/index.py

@@ -14,6 +14,7 @@ from metagpt.rag.schema import (
     BM25IndexConfig,
     ChromaIndexConfig,
     ElasticsearchIndexConfig,
+    ElasticsearchKeywordIndexConfig,
     FAISSIndexConfig,
 )
 from metagpt.rag.vector_stores.chroma import ChromaVectorStore
@@ -26,6 +27,7 @@ class RAGIndexFactory(ConfigBasedFactory):
             ChromaIndexConfig: self._create_chroma,
             BM25IndexConfig: self._create_bm25,
             ElasticsearchIndexConfig: self._create_es,
+            ElasticsearchKeywordIndexConfig: self._create_es,
         }
         super().__init__(creators)
 

metagpt/rag/factories/retriever.py

@@ -20,6 +20,7 @@ from metagpt.rag.schema import (
     BaseRetrieverConfig,
     BM25RetrieverConfig,
     ChromaRetrieverConfig,
+    ElasticsearchKeywordRetrieverConfig,
     ElasticsearchRetrieverConfig,
     FAISSRetrieverConfig,
     IndexRetrieverConfig,
@@ -36,6 +37,7 @@ class RetrieverFactory(ConfigBasedFactory):
             BM25RetrieverConfig: self._create_bm25_retriever,
             ChromaRetrieverConfig: self._create_chroma_retriever,
             ElasticsearchRetrieverConfig: self._create_es_retriever,
+            ElasticsearchKeywordRetrieverConfig: self._create_es_retriever,
         }
         super().__init__(creators)
 

metagpt/rag/schema.py

@@ -59,12 +59,19 @@ class ElasticsearchStoreConfig(BaseModel):
 
 
 class ElasticsearchRetrieverConfig(IndexRetrieverConfig):
-    """Config for Elasticsearch-based retrievers."""
+    """Config for Elasticsearch-based retrievers. Support both vector and text."""
 
     store_config: ElasticsearchStoreConfig = Field(..., description="ElasticsearchStore config.")
     vector_store_query_mode: VectorStoreQueryMode = VectorStoreQueryMode.DEFAULT
 
 
+class ElasticsearchKeywordRetrieverConfig(ElasticsearchRetrieverConfig):
+    """Config for Elasticsearch-based retrievers. Support text only."""
+
+    _no_embedding: bool = PrivateAttr(default=True)
+    vector_store_query_mode: VectorStoreQueryMode = VectorStoreQueryMode.TEXT_SEARCH
+
+
 class BaseRankerConfig(BaseModel):
     """Common config for rankers.
 
@@ -129,6 +136,12 @@ class ElasticsearchIndexConfig(VectorIndexConfig):
     persist_path: Union[str, Path] = ""
 
 
+class ElasticsearchKeywordIndexConfig(ElasticsearchIndexConfig):
+    """Config for es-based index. no embedding."""
+
+    _no_embedding: bool = PrivateAttr(default=True)
+
+
 class ObjectNodeMetadata(BaseModel):
     """Metadata of ObjectNode."""