update

app.py

@@ -2,10 +2,12 @@ import streamlit as st
 import pinecone
 from makechain import get_chain
 from langchain.vectorstores.pinecone import Pinecone
-from env import PINECONE_INDEX_NAME, PINECONE_ENVIRONMENT, PINECONE_API_KEY, OPENAI_API_KEY
 from langchain.embeddings.openai import OpenAIEmbeddings
-
-
+import os
+PINECONE_INDEX_NAME = os.environ.get("PINECONE_INDEX_NAME")
+PINECONE_ENVIRONMENT = os.environ.get("PINECONE_ENVIRONMENT")
+PINECONE_API_KEY = os.environ.get("PINECONE_API_KEY")
+OPENAI_API_KEY = os.environ.get("OPENAI_API_KEY")
 st.title("Ask the Black@Stanford Exhibit")
 st.sidebar.header("You can ask questions of interviews with Black Stanford students and faculty from the University "
                   "Archives")
@@ -19,11 +21,11 @@ st.sidebar.info(
 
 # create Vectorstore
 pinecone.init(
-    api_key=st.secrets["PINECONE_API_KEY"],  # find at app.pinecone.io
-    environment=st.secrets["PINECONE_ENVIRONMENT"]  # next to api key in console
+    api_key=PINECONE_API_KEY,  # find at app.pinecone.io
+    environment=PINECONE_ENVIRONMENT  # next to api key in console
 )
-index = pinecone.Index(index_name=st.secrets["PINECONE_INDEX_NAME"])
-embed = OpenAIEmbeddings(openai_api_key=st.secrets["OPENAI_API_KEY"])
+index = pinecone.Index(index_name=PINECONE_INDEX_NAME)
+embed = OpenAIEmbeddings(openai_api_key=OPENAI_API_KEY)
 text_field = "text"
 vectorStore = Pinecone(
     index, embed.embed_query, text_field

makechain.py

@@ -0,0 +1,14 @@
+from langchain.chat_models import ChatOpenAI
+from langchain.vectorstores.pinecone import Pinecone
+import openai
+from langchain.chains import RetrievalQAWithSourcesChain
+import os
+OPENAI_API_KEY = os.environ.get("OPENAI_API_KEY")
+def get_chain(vectorstore: Pinecone):
+    openai.api_key = OPENAI_API_KEY
+    llm = ChatOpenAI(temperature=0, model_name="gpt-3.5-turbo")
+
+    qa_chain = RetrievalQAWithSourcesChain.from_chain_type(llm=llm, chain_type="stuff",
+                                                           retriever=vectorstore.as_retriever())
+
+    return qa_chain