enable mmr search (#807)

langchain/chains/vector_db_qa/base.py

@@ -41,6 +41,8 @@ class VectorDBQA(Chain, BaseModel):
     """Return the source documents."""
     search_kwargs: Dict[str, Any] = Field(default_factory=dict)
     """Extra search args."""
+    search_type: str = "similarity"
+    """Search type to use over vectorstore. `similarity` or `mmr`."""
 
     class Config:
         """Configuration for this pydantic object."""
@@ -90,6 +92,15 @@ class VectorDBQA(Chain, BaseModel):
             values["combine_documents_chain"] = combine_documents_chain
         return values
 
+    @root_validator()
+    def validate_search_type(cls, values: Dict) -> Dict:
+        """Validate search type."""
+        if "search_type" in values:
+            search_type = values["search_type"]
+            if search_type not in ("similarity", "mmr"):
+                raise ValueError(f"search_type of {search_type} not allowed.")
+        return values
+
     @classmethod
     def from_llm(
         cls, llm: BaseLLM, prompt: PromptTemplate = PROMPT, **kwargs: Any
@@ -129,9 +140,16 @@ class VectorDBQA(Chain, BaseModel):
         """
         question = inputs[self.input_key]
 
-        docs = self.vectorstore.similarity_search(
-            question, k=self.k, **self.search_kwargs
-        )
+        if self.search_type == "similarity":
+            docs = self.vectorstore.similarity_search(
+                question, k=self.k, **self.search_kwargs
+            )
+        elif self.search_type == "mmr":
+            docs = self.vectorstore.max_marginal_relevance_search(
+                question, k=self.k, **self.search_kwargs
+            )
+        else:
+            raise ValueError(f"search_type of {self.search_type} not allowed.")
         answer, _ = self.combine_documents_chain.combine_docs(docs, question=question)
 
         if self.return_source_documents: