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| import os | |
| import sys | |
| import subprocess | |
| # Ensure Backend modules are importable | |
| sys.path.insert(0, os.path.join(os.path.dirname(__file__), "Backend")) | |
| import spaces # REQUIRED for ZeroGPU | |
| import gradio as gr | |
| import uvicorn | |
| import nltk | |
| # Download required NLTK data before importing backend | |
| nltk.download('punkt') | |
| nltk.download('punkt_tab') | |
| nltk.download('wordnet') | |
| nltk.download('stopwords') | |
| nltk.download('omw-1.4') | |
| from Backend.api import app as fastapi_app | |
| # Create a minimal Gradio UI to satisfy ZeroGPU's requirements | |
| def dummy_gpu_task(): | |
| # ZeroGPU requires at least one GPU function to exist | |
| return "GPU is working!" | |
| with gr.Blocks() as demo: | |
| gr.Markdown("# Math Search Engine API") | |
| gr.Markdown("The React frontend is served via FastAPI at the root URL.") | |
| btn = gr.Button("Ping GPU") | |
| out = gr.Textbox() | |
| btn.click(dummy_gpu_task, outputs=out) | |
| # Mount FastAPI onto the Gradio app (or vice versa) | |
| # We serve Gradio at /gradio, and the rest is our FastAPI app (which serves React) | |
| app = gr.mount_gradio_app(fastapi_app, demo, path="/gradio") | |
| if __name__ == "__main__": | |
| port = os.getenv("PORT", "7860") | |
| # Use subprocess to run Uvicorn to hide it from ZeroGPU's patcher | |
| subprocess.Popen([sys.executable, "-m", "uvicorn", "app:app", "--host", "0.0.0.0", "--port", port]).wait() | |