Update app.py

app.py

@@ -1,22 +1,15 @@
 import streamlit as st
 import requests
 from transformers import pipeline
-import urllib3
 import os
 
-# Disable warnings
-urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)
-
-# Create a custom session
-session = requests.Session()
-session.verify = False  # Disable SSL verification
-
 # Load the token from Hugging Face secrets
-HUGGINGFACE_TOKEN = os.environ.get("hf_token")  # Set the default to empty if not found
+HUGGINGFACE_TOKEN = os.environ.get("hf_token")  # Ensure this token is correctly set
+print("Hugging Face Token:", HUGGINGFACE_TOKEN)  # Debugging line
 
 # Set up the text generation pipeline with the token
 pipe = pipeline("text-generation", model="mistralai/Mistral-7B-v0.1", 
-                use_auth_token=HUGGINGFACE_TOKEN, request_session=session)
+                use_auth_token=HUGGINGFACE_TOKEN)
 
 # Streamlit application
 st.title("Text Generation with Hugging Face")
@@ -26,8 +19,7 @@ user_input = st.text_input("You: ", "Who are you?")
 
 if st.button("Generate Response"):
     if user_input:
-        messages = [{"role": "user", "content": user_input}]
-        response = pipe(messages)
+        response = pipe(user_input)
         generated_text = response[0]['generated_text']  # Adjust according to the response format
         st.text_area("Bot:", generated_text, height=200)
     else: