import gradio as gr
import requests
import os

hf_token = os.getenv("HF_TOKEN")
if hf_token is None:
    raise ValueError("HF_TOKEN is not set. Please add it as a secret in your Space settings.")

API_URL = "https://api-inference.huggingface.co/models/gabehubner/trained-distilbert-model"
headers = {"Authorization": f"Bearer {hf_token}"}

def classify_text(text):
    response = requests.post(API_URL, headers=headers, json={"inputs": text})
    if response.status_code != 200:
        return f"Error: {response.text}"
    
    results = response.json()
    if isinstance(results, list) and results and isinstance(results[0], list) and results[0]:
        prediction = results[0][0]  # Get the first prediction from the inner list
        return f"Label: {prediction['label']} (Confidence: {prediction['score']:.2f})"
    else:
        return f"Unexpected response format: {results}"

interface = gr.Interface(
    fn=classify_text,
    inputs=gr.Textbox(placeholder="Enter text here..."),
    outputs="text",
    title="Sentiment Classifier",
    description="Enter text and see whether it's classified as positive or negative!",
)

if __name__ == "__main__":
    interface.launch()