Update server/app.py

server/app.py

@@ -1,17 +1,12 @@
-import sys
-import os
-import numpy as np
 from fastapi import FastAPI, Request
 import gradio as gr
-
-# Environment ko dhoondne ke liye rasta sahi karna (agar env.py bahar hai)
-sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
-
+import numpy as np
 from env import (
-    EmailTriageEnv, URGENCY_LABELS, ROUTING_LABELS, RESOLUTION_LABELS,
+    EmailTriageEnv, TASK_SPLITS,
+    URGENCY_LABELS, ROUTING_LABELS, RESOLUTION_LABELS,
 )
 
-# 1. FastAPI instance banana
+# 1. FastAPI App Setup
 app = FastAPI()
 
 # --- Hackathon Grader Endpoints ---
@@ -37,7 +32,8 @@ def _classify(email: dict) -> np.ndarray:
             return np.array([2, 2, 2], dtype=np.int64)
         return np.array([2, 1, 2], dtype=np.int64)
     if context == "billing":
-        return np.array([1, 2, 2] if kw & _BILLING_ESCALATE_KW else [1, 0, 1], dtype=np.int64)
+        return np.array([1, 2, 2] if kw & _BILLING_ESCALATE_KW
+                        else [1, 0, 1], dtype=np.int64)
     if context == "tech" or kw & {"crash", "error", "bug", "slow"}:
         return np.array([0, 1, 1], dtype=np.int64)
     return np.array([0, 0, 0], dtype=np.int64)
@@ -57,28 +53,48 @@ def run_task_demo(task: str) -> str:
         cumulative += norm_reward
         raw = info["raw_reward"]
         ca  = info["correct_actions"]
-        verdict = ("✅ EXACT" if raw >= 1.0 else "🔶 PARTIAL" if raw > 0 else "🚨 SECURITY MISS" if raw < 0 else "❌ WRONG")
-        lines.append(f"#{step+1:02d} [{email['difficulty'].upper()}] {email['description'][:40]}\n"
-                     f"      Predicted : {URGENCY_LABELS[action[0]]} | {ROUTING_LABELS[action[1]]} | {RESOLUTION_LABELS[action[2]]}\n"
-                     f"      Correct   : {URGENCY_LABELS[ca[0]]} | {ROUTING_LABELS[ca[1]]} | {RESOLUTION_LABELS[ca[2]]}\n"
-                     f"      Reward    : {raw:+.1f}  {verdict}\n")
+        verdict = ("✅ EXACT" if raw >= 1.0 else
+                   "🔶 PARTIAL" if raw > 0 else
+                   "🚨 SECURITY MISS" if raw < 0 else "❌ WRONG")
+        lines.append(
+            f"#{step+1:02d} [{email['difficulty'].upper()}] "
+            f"{email['description'][:40]}\n"
+            f"      Predicted : {URGENCY_LABELS[action[0]]} | "
+            f"{ROUTING_LABELS[action[1]]} | {RESOLUTION_LABELS[action[2]]}\n"
+            f"      Correct   : {URGENCY_LABELS[ca[0]]} | "
+            f"{ROUTING_LABELS[ca[1]]} | {RESOLUTION_LABELS[ca[2]]}\n"
+            f"      Reward    : {raw:+.1f}  {verdict}\n"
+        )
         step += 1
     final = max(0.0, min(1.0, cumulative))
-    lines.append(f"\n{'─'*50}\nFinal Score : {final:.3f} / 1.0")
+    lines.append(f"\n{'─'*50}")
+    lines.append(f"Final Score : {final:.3f} / 1.0")
     return "\n".join(lines)
 
-# 3. Gradio Interface Setup
+# 3. Gradio Interface (Iska naam 'demo' hai)
 with gr.Blocks(title="Email Gatekeeper RL") as demo:
-    gr.Markdown("# 📧 Email Gatekeeper — RL Environment Demo")
+    gr.Markdown("""
+# 📧 Email Gatekeeper — RL Environment Demo
+**Meta x PyTorch Hackathon** | Gymnasium-based email triage agent
+""")
     with gr.Row():
-        task_dropdown = gr.Dropdown(choices=["easy", "medium", "hard"], value="easy", label="Select Task")
+        task_dropdown = gr.Dropdown(
+            choices=["easy", "medium", "hard"],
+            value="easy",
+            label="Select Task",
+        )
         run_btn = gr.Button("▶ Run Episode", variant="primary")
-    output_box = gr.Textbox(label="Episode Results", lines=25)
+    output_box = gr.Textbox(
+        label="Episode Results",
+        lines=30,
+        max_lines=50,
+    )
     run_btn.click(fn=run_task_demo, inputs=task_dropdown, outputs=output_box)
 
-# 4. FastAPI aur Gradio ko jodna (Isse 'app' variable finalize hoga)
+# 4. SABSE IMPORTANT: Mount Gradio to FastAPI (Yahan 'demo' exist karta hai)
 app = gr.mount_gradio_app(app, demo, path="/")
 
 if __name__ == "__main__":
     import uvicorn
+    # Hugging Face ke liye server_port 7860 zaroori hai
     uvicorn.run(app, host="0.0.0.0", port=7860)