Update app.py

app.py

@@ -1,57 +1,46 @@
 from fastapi import FastAPI
-from pydantic import BaseModel
-import google.generativeai as genai
-import subprocess
-import re
-
-# 🔑 Configure Gemini API
-genai.configure(api_key="AIzaSyAdvERSmk7q02T2pLNPoERqDD-QPuW4RTs")
-
-# Pick a model
-model = genai.GenerativeModel("gemini-1.5-flash")
-
-app = FastAPI()
-
-class TaskRequest(BaseModel):
-    task: str
-
-def extract_code(response_text):
-    """Extracts Python code from Gemini's response (removes ``` fences)."""
-    code_match = re.findall(r"```(?:python)?\n(.*?)```", response_text, re.DOTALL)
-    if code_match:
-        return code_match[0]
-    return response_text.strip()
+from fastapi.middleware.cors import CORSMiddleware
+import gradio as gr
+import uvicorn
+from executor import recursive_executor
+
+# Create FastAPI app
+app = FastAPI(title="Recursive AI Executor")
+
+# Enable CORS
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+# Root endpoint
+@app.get("/")
+def root():
+    return {"message": "🚀 Recursive AI Executor is running on Hugging Face!"}
 
-def run_code(code):
-    """Executes code and returns output or error."""
+# Run recursive executor for Gradio
+def run_executor(task: str):
     try:
-        result = subprocess.run(
-            ["python3", "-c", code],
-            capture_output=True,
-            text=True,
-            timeout=10
-        )
-        return result.stdout if result.stdout else result.stderr
+        result = recursive_executor(task)
+        return result
     except Exception as e:
-        return str(e)
-
-def recursive_ai_executor(task, depth=1):
-    """Recursive AI Executor with auto-run + visible output."""
-    prompt = f"Write Python code to {task}. Always include a sample call (like print(...)) so output is shown."
-    response = model.generate_content(prompt)
-    code = extract_code(response.text)
-    output = run_code(code)
-
-    # Retry if failure
-    if ("Traceback" in output or output.strip() == "") and depth < 3:
-        return recursive_ai_executor(f"Fix the error: {output}", depth+1)
-
-    return {"generated_code": code, "execution_output": output}
-
-@app.post("/run-task")
-def run_task(request: TaskRequest):
-    return recursive_ai_executor(request.task)
-
-@app.get("/")
-def home():
-    return {"message": "🚀 Recursive AI Executor is running on Hugging Face!"}
+        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)