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()