Update app.py

app.py

@@ -9,7 +9,6 @@ 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 = ""
@@ -41,11 +40,10 @@ def get_vectorstore(text_chunks):
 
 
 def get_conversation_chain(vectorstore):
-    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},
-    # )
+    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(
@@ -75,10 +73,8 @@ def main():
 
     st.write(css, unsafe_allow_html=True)
     
-    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
+    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: