fix chatvectordbchain to use pinecone namespace (#1139)

In the similarity search, the pinecone namespace is not used, which
makes the bot return _I don't know_ where the embeddings are stored in
the pinecone namespace. Now we can query by passing the namespace
optionally.
```result = qa({"question": query, "chat_history": chat_history, "namespace":"01gshyhjcfgkq1q5wxjtm17gjh"})```

langchain/chains/chat_vector_db/base.py

@@ -81,13 +81,14 @@ def from_llm(
     def _call(self, inputs: Dict[str, Any]) -> Dict[str, Any]:
         question = inputs["question"]
         chat_history_str = _get_chat_history(inputs["chat_history"])
+        vectordbkwargs = inputs.get("vectordbkwargs", {})
         if chat_history_str:
             new_question = self.question_generator.run(
                 question=question, chat_history=chat_history_str
             )
         else:
             new_question = question
-        docs = self.vectorstore.similarity_search(new_question, k=4)
+        docs = self.vectorstore.similarity_search(new_question, k=4, **vectordbkwargs)
         new_inputs = inputs.copy()
         new_inputs["question"] = new_question
         new_inputs["chat_history"] = chat_history_str
@@ -100,14 +101,15 @@ def _call(self, inputs: Dict[str, Any]) -> Dict[str, Any]:
     async def _acall(self, inputs: Dict[str, Any]) -> Dict[str, str]:
         question = inputs["question"]
         chat_history_str = _get_chat_history(inputs["chat_history"])
+        vectordbkwargs = inputs.get("vectordbkwargs", {})
         if chat_history_str:
             new_question = await self.question_generator.arun(
                 question=question, chat_history=chat_history_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)
+        docs = self.vectorstore.similarity_search(new_question, k=4, **vectordbkwargs)
         new_inputs = inputs.copy()
         new_inputs["question"] = new_question
         new_inputs["chat_history"] = chat_history_str