Use Bedrock chat

chain.py

@@ -4,10 +4,9 @@
 import streamlit as st
 from langchain.chains import ConversationalRetrievalChain, LLMChain
 from langchain.chains.question_answering import load_qa_chain
-from langchain.chat_models import ChatOpenAI
+from langchain.chat_models import ChatOpenAI, BedrockChat
 from langchain.embeddings.openai import OpenAIEmbeddings
 from langchain.llms import OpenAI
-from langchain.llms.bedrock import Bedrock
 from langchain.vectorstores import SupabaseVectorStore
 from pydantic import BaseModel, validator
 from supabase.client import Client, create_client
@@ -36,8 +35,10 @@ def __init__(self, config: ModelConfig):
         self.model_type = config.model_type
         self.secrets = config.secrets
         self.callback_handler = config.callback_handler
-        account_tag = self.secrets['CF_ACCOUNT_TAG']
-        self.gateway_url = f"https://gateway.ai.cloudflare.com/v1/{account_tag}/k-1-gpt/openai"
+        account_tag = self.secrets["CF_ACCOUNT_TAG"]
+        self.gateway_url = (
+            f"https://gateway.ai.cloudflare.com/v1/{account_tag}/k-1-gpt/openai"
+        )
         self.setup()
 
     def setup(self):
@@ -54,7 +55,7 @@ def setup_gpt(self):
             api_key=self.secrets["OPENAI_API_KEY"],
             model_name="gpt-3.5-turbo-16k",
             max_tokens=500,
-            base_url=self.gateway_url
+            base_url=self.gateway_url,
         )
 
         self.llm = ChatOpenAI(
@@ -64,7 +65,7 @@ def setup_gpt(self):
             max_tokens=500,
             callbacks=[self.callback_handler],
             streaming=True,
-            base_url=self.gateway_url
+            base_url=self.gateway_url,
         )
 
     def setup_mixtral(self):
@@ -99,10 +100,11 @@ def setup_claude(self):
             "temperature": 0,
             "top_p": 0.9,
         }
-        self.q_llm = Bedrock(
+        self.q_llm = BedrockChat(
             model_id="anthropic.claude-instant-v1", client=bedrock_runtime
         )
-        self.llm = Bedrock(
+
+        self.llm = BedrockChat(
             model_id="anthropic.claude-instant-v1",
             client=bedrock_runtime,
             callbacks=[self.callback_handler],