| import streamlit as st | |
| import requests | |
| import os | |
| st.title("My Hugging Face Model Interface") | |
| input_text = st.text_area("Enter your text:", "") | |
| HF_TOKEN = os.getenv("HF_TOKEN") # Loaded from Hugging Face Secrets | |
| if st.button("Get Prediction") and input_text: | |
| headers = {"Authorization": f"Bearer {HF_TOKEN}"} if HF_TOKEN else {} | |
| response = requests.post( | |
| "https://api-inference.huggingface.co/models/rajan3208/uzmi-gpt", | |
| headers=headers, | |
| json={"inputs": input_text} | |
| ) | |
| if response.status_code == 200: | |
| st.success("Prediction:") | |
| st.write(response.json()[0]['generated_text']) | |
| else: | |
| st.error(f"Error {response.status_code}: {response.text}") | |