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| import gradio as gr | |
| import joblib | |
| from huggingface_hub import hf_hub_download | |
| # ==================== LOAD MODEL ==================== | |
| def load_model_package(): | |
| """Load the complete model package""" | |
| try: | |
| # Try to load the model from a local path first | |
| package = joblib.load("exoplanet_final_model.joblib") | |
| print("✅ Loaded model from local file.") | |
| return package | |
| except FileNotFoundError: | |
| print("ℹ️ Model file not found locally. Attempting to download from Hugging Face Hub...") | |
| try: | |
| # Download from Hugging Face Hub | |
| model_path = hf_hub_download( | |
| repo_id="Nugget-cloud/nasa-space-apps-exoplanet", | |
| filename="exoplanet_final_model.joblib" | |
| ) | |
| package = joblib.load(model_path) | |
| print("✅ Model successfully downloaded and loaded from Hugging Face Hub.") | |
| return package | |
| except Exception as hub_e: | |
| print(f"❌ Failed to download or load model from Hugging Face Hub: {hub_e}") | |
| return None | |
| except Exception as e: | |
| print(f"❌ An unexpected error occurred while loading the model: {e}") | |
| return None | |
| # Load model | |
| package = load_model_package() | |
| if package is None: | |
| raise SystemExit("Model could not be loaded. Please check your setup.") | |
| model = package['ensemble_model'] | |
| # ==================== DEFINE PREDICTION FUNCTION ==================== | |
| def classify_exoplanet( | |
| koi_period, koi_duration, koi_depth, koi_prad, koi_teq, koi_insol, koi_steff | |
| ): | |
| """ | |
| Run the trained model on the input features. | |
| """ | |
| try: | |
| # Convert inputs to the expected 2D array format for the model | |
| features = [[ | |
| float(koi_period), | |
| float(koi_duration), | |
| float(koi_depth), | |
| float(koi_prad), | |
| float(koi_teq), | |
| float(koi_insol), | |
| float(koi_steff) | |
| ]] | |
| prediction = model.predict(features)[0] | |
| label = "🌍 Likely Exoplanet" if prediction == 1 else "❌ Not an Exoplanet Candidate" | |
| return label | |
| except Exception as e: | |
| return f"Error during prediction: {e}" | |
| # ==================== BUILD GRADIO INTERFACE ==================== | |
| with gr.Blocks(title="Exoplanet Classification 🌌") as demo: | |
| gr.Markdown( | |
| """ | |
| # 🌌 **NASA Exoplanet Classifier** | |
| Enter the Kepler Object of Interest (KOI) parameters to classify whether it's likely an exoplanet. | |
| """ | |
| ) | |
| with gr.Row(): | |
| koi_period = gr.Number(label="Orbital Period (days)", value=10.0) | |
| koi_duration = gr.Number(label="Transit Duration (hrs)", value=5.0) | |
| koi_depth = gr.Number(label="Transit Depth (ppm)", value=1000.0) | |
| koi_prad = gr.Number(label="Planet Radius (Earth radii)", value=1.0) | |
| koi_teq = gr.Number(label="Equilibrium Temperature (K)", value=300.0) | |
| koi_insol = gr.Number(label="Insolation Flux (Earth flux)", value=1.0) | |
| koi_steff = gr.Number(label="Stellar Effective Temperature (K)", value=5700.0) | |
| predict_btn = gr.Button("🚀 Classify") | |
| output = gr.Textbox(label="Prediction", placeholder="Result will appear here...") | |
| predict_btn.click( | |
| classify_exoplanet, | |
| inputs=[koi_period, koi_duration, koi_depth, koi_prad, koi_teq, koi_insol, koi_steff], | |
| outputs=output | |
| ) | |
| # ==================== LAUNCH ==================== | |
| if __name__ == "__main__": | |
| demo.launch( | |
| server_name="0.0.0.0", | |
| server_port=7860, | |
| share=True | |
| ) |