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}") | |