Update app.py

app.py

@@ -1,46 +1,17 @@
-from fastapi import FastAPI
-from fastapi.middleware.cors import CORSMiddleware
+import os
+import google.generativeai as genai
 import gradio as gr
-import uvicorn
-from executor import recursive_executor
 
-# Create FastAPI app
-app = FastAPI(title="Recursive AI Executor")
+# Get Gemini API key from Hugging Face Secrets
+genai.configure(api_key=os.getenv("GEMINI_API_KEY"))
 
-# Enable CORS
-app.add_middleware(
-    CORSMiddleware,
-    allow_origins=["*"],
-    allow_credentials=True,
-    allow_methods=["*"],
-    allow_headers=["*"],
-)
+# Simple test function
+def ask_gemini(prompt):
+    model = genai.GenerativeModel("gemini-1.5-flash")
+    response = model.generate_content(prompt)
+    return response.text
 
-# Root endpoint
-@app.get("/")
-def root():
-    return {"message": "🚀 Recursive AI Executor is running on Hugging Face!"}
+demo = gr.Interface(fn=ask_gemini, inputs="text", outputs="text")
 
-# Run recursive executor for Gradio
-def run_executor(task: str):
-    try:
-        result = recursive_executor(task)
-        return result
-    except Exception as e:
-        return f"❌ Error: {e}"
-
-# Build Gradio UI
-demo = gr.Interface(
-    fn=run_executor,
-    inputs=gr.Textbox(label="Enter your task", placeholder="e.g. Write Python code for Fibonacci"),
-    outputs=gr.Textbox(label="Result"),
-    title="Recursive AI Executor",
-    description="Enter a task and let the AI recursively break it down and solve it."
-)
-
-# Mount Gradio app inside FastAPI
-app = gr.mount_gradio_app(app, demo, path="/app")
-
-# Run server
 if __name__ == "__main__":
-    uvicorn.run(app, host="0.0.0.0", port=7860)
+    demo.launch()