From 9111f4ca8a1dde585198a2a2a81589169df27f5c Mon Sep 17 00:00:00 2001
From: kekayan <34229394+kekayan@users.noreply.github.com>
Date: Sun, 19 Feb 2023 00:28:48 +0530
Subject: [PATCH] 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 | 6 ++++--
 1 file changed, 4 insertions(+), 2 deletions(-)

diff --git a/langchain/chains/chat_vector_db/base.py b/langchain/chains/chat_vector_db/base.py
index 76789e6c2d..f9431baf5b 100644
--- a/langchain/chains/chat_vector_db/base.py
+++ b/langchain/chains/chat_vector_db/base.py
@@ -81,13 +81,14 @@ class ChatVectorDBChain(Chain, BaseModel):
     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
@@ -100,6 +101,7 @@ class ChatVectorDBChain(Chain, BaseModel):
     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
@@ -107,7 +109,7 @@ class ChatVectorDBChain(Chain, BaseModel):
         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