Update app.py

app.py

@@ -9,7 +9,7 @@ from langchain.memory import ConversationBufferMemory
 from langchain.chains import ConversationalRetrievalChain
 from htmlTemplates import css, bot_template, user_template
 from langchain.llms import HuggingFaceHub
-
+from langchain.llms import OpenAI
 
 def get_pdf_text(pdf_docs):
     text = ""
@@ -41,10 +41,11 @@ def get_vectorstore(text_chunks):
 
 
 def get_conversation_chain(vectorstore):
-    llm = HuggingFaceHub(
-        repo_id="mistralai/Mixtral-8x7B-Instruct-v0.1",
-        model_kwargs={"temperature": 0.5, "max_length": 1048},
-    )
+    llm = OpenAI(temperature=0.7, openai_api_key=openai_api_key)
+    # llm = HuggingFaceHub(
+    #     repo_id="mistralai/Mixtral-8x7B-Instruct-v0.1",
+    #     model_kwargs={"temperature": 0.5, "max_length": 1048},
+    # )
 
     memory = ConversationBufferMemory(memory_key="chat_history", return_messages=True)
     conversation_chain = ConversationalRetrievalChain.from_llm(
@@ -73,10 +74,11 @@ def main():
     st.markdown("# Chat💬 with multiple PDFs 📄")
 
     st.write(css, unsafe_allow_html=True)
-
-    huggingface_token = st.text_input("Enter your HuggingFace Hub token", type="password")
-
-    os.environ["HUGGINGFACEHUB_API_TOKEN"] = huggingface_token
+    
+    openai_api_key = st.sidebar.text_input('OpenAI API Key',type="password")
+    os.environ["OpenAI_Key"] = huggingface_token
+    #huggingface_token = st.text_input("Enter your HuggingFace Hub token", type="password")
+    #os.environ["HUGGINGFACEHUB_API_TOKEN"] = huggingface_token
 
 
     if "conversation" not in st.session_state: