import requests
import streamlit as st

# Load API key from Streamlit secrets
API_URL = "https://api-inference.huggingface.co/models/meta-llama/Meta-Llama-3-8B"
global api_key
headers = {"Authorization": f"Bearer {api_key}"}

# Function to query the model
def query_model(input_text):
    payload = {"inputs": input_text}
    response = requests.post(API_URL, headers=headers, json=payload)
    return response.json()

# Streamlit interface
st.title("Hugging Face Inference with Streamlit")

# Input from the user
user_input = st.text_area("Enter your prompt:", "")

if st.button("Generate Response"):
    if user_input:
        with st.spinner('Generating response...'):
            result = query_model(user_input)
            # Display the result
            if "error" in result:
                st.error(f"Error: {result['error']}")
            else:
                st.success("Response generated successfully!")
                st.write(result[0]["generated_text"])
    else:
        st.error("Please enter a prompt to generate a response.")