for ChatVectorDBChain, add top_k_docs_for_context to allow control ho…

…w many chunks of context will be retrieved (#1155)

given that we allow user define chunk size, think it would be useful for
user to define how many chunks of context will be retrieved.

langchain/chains/chat_vector_db/base.py

@@ -32,6 +32,7 @@ class ChatVectorDBChain(Chain, BaseModel):
     question_generator: LLMChain
     output_key: str = "answer"
     return_source_documents: bool = False
+    top_k_docs_for_context: int = 4
     """Return the source documents."""
 
     @property
@@ -88,7 +89,9 @@ def _call(self, inputs: Dict[str, Any]) -> Dict[str, Any]:
             )
         else:
             new_question = question
-        docs = self.vectorstore.similarity_search(new_question, k=4, **vectordbkwargs)
+        docs = self.vectorstore.similarity_search(
+            new_question, k=self.top_k_docs_for_context, **vectordbkwargs
+        )
         new_inputs = inputs.copy()
         new_inputs["question"] = new_question
         new_inputs["chat_history"] = chat_history_str
@@ -109,7 +112,9 @@ async def _acall(self, inputs: Dict[str, Any]) -> Dict[str, str]:
         else:
             new_question = question
         # TODO: This blocks the event loop, but it's not clear how to avoid it.
-        docs = self.vectorstore.similarity_search(new_question, k=4, **vectordbkwargs)
+        docs = self.vectorstore.similarity_search(
+            new_question, k=self.top_k_docs_for_context, **vectordbkwargs
+        )
         new_inputs = inputs.copy()
         new_inputs["question"] = new_question
         new_inputs["chat_history"] = chat_history_str