Delete app.py

app.py

@@ -1,66 +0,0 @@
-import sys
-import os
-import uvicorn
-import numpy as np
-import gradio as gr
-from fastapi import FastAPI
-from env import EmailTriageEnv, URGENCY_LABELS, ROUTING_LABELS, RESOLUTION_LABELS
-
-app = FastAPI()
-
-# --- Agent Logic ---
-def smart_agent_logic(desc):
-    desc = desc.lower()
-    if any(x in desc for x in ["password", "hacked", "breach", "phish", "threat", "ransomware"]):
-        return [2, 2, 2] if "threat" in desc or "ransomware" in desc else [2, 1, 2]
-    if any(x in desc for x in ["billing", "refund", "dispute", "invoice", "payment"]):
-        return [1, 2, 2]
-    if any(x in desc for x in ["support", "routine", "slow", "error"]):
-        return [0, 1, 1]
-    return [0, 0, 0]
-
-# --- Core Function ---
-def run_demo(task):
-    try:
-        env = EmailTriageEnv(task=task)
-        env.reset()
-        results = []
-        total_reward = 0
-        print(f"[START] Task: {task}")
-        for i, email in enumerate(env._queue):
-            action = smart_agent_logic(email['description'])
-            _, reward, _, _, _ = env.step(action)
-            total_reward += reward
-            print(f"[STEP] Index: {i} | Action: {action} | Reward: {reward}")
-            status = "✅ MATCH" if reward >= 1.0 else "❌ MISMATCH"
-            results.append(f"#{i+1} [{task.upper()}] {email['description'][:30]}... | {status}")
-        score = total_reward / len(env._queue) if env._queue else 0
-        print(f"[END] Final Score: {score}")
-        return "\n".join(results) + f"\n\n--- FINAL SCORE: {score:.3f} / 1.000 ---"
-    except Exception as e:
-        return f"Error: {str(e)}"
-
-# --- API for Validator ---
-@app.post("/reset")
-async def reset_endpoint():
-    return {"status": "success", "message": "Environment Reset OK"}
-
-@app.get("/status")
-async def health_check():
-    return {"status": "online"}
-
-# --- Gradio UI ---
-with gr.Blocks(title="Email Gatekeeper AI") as demo:
-    gr.Markdown("# 📧 Email Gatekeeper AI")
-    with gr.Row():
-        diff = gr.Dropdown(choices=["easy", "medium", "hard"], value="easy", label="Select Difficulty")
-        btn = gr.Button("Analyze Emails", variant="primary")
-    out = gr.Textbox(label="Evaluation Logs", lines=12)
-    btn.click(run_demo, inputs=diff, outputs=out)
-
-# IS LINE KO DHAYAN SE DEKHO: Humne path="/" kar diya hai
-app = gr.mount_gradio_app(app, demo, path="/")
-
-if __name__ == "__main__":
-    # Hugging Face hamesha port 7860 use karta hai
-    uvicorn.run(app, host="0.0.0.0", port=7860)