Update app.py

app.py

@@ -1,17 +1,15 @@
-
 import gradio as gr
+from fastapi import FastAPI, Request
+import uvicorn
 from sentence_transformers import SentenceTransformer, util
 import torch
 import requests
-from fastapi import FastAPI, Request
-from gradio.routes import App
-import uvicorn
+import threading
 
-# 🔐 Konfigurasi Supabase
+# 🔐 Supabase setup
 SUPABASE_URL = "https://olbjfxlclotxtnpjvpfj.supabase.co"
 SUPABASE_KEY = "eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJzdXBhYmFzZSIsInJlZiI6Im9sYmpmeGxjbG90eHRucGp2cGZqIiwicm9sZSI6ImFub24iLCJpYXQiOjE3NTIyMzYwMDEsImV4cCI6MjA2NzgxMjAwMX0.7q_o5DCFEAAysnWXMChH4MI5qNhIVc4OgpT5JvgYxc0"
 
-# 🧠 Load model
 model = SentenceTransformer('all-MiniLM-L6-v2')
 
 def get_faq_from_supabase(uid):
@@ -33,7 +31,7 @@ def get_faq_from_supabase(uid):
 def chatbot(uid, question):
     faqs = get_faq_from_supabase(uid)
     if not faqs:
-        return "Tidak ada data FAQ untuk pengguna ini."
+        return "Tidak ada data FAQ."
 
     questions = [f["q"] for f in faqs]
     answers = [f["a"] for f in faqs]
@@ -45,20 +43,30 @@ def chatbot(uid, question):
     best_idx = torch.argmax(scores).item()
     return answers[best_idx]
 
-# 🎛️ Buat UI untuk testing
-demo = gr.Interface(fn=chatbot, inputs=["text", "text"], outputs="text", title="Chatbot")
-
-# 🚀 Tambahkan FastAPI app agar bisa menerima POST request
+# 🌐 FastAPI app
 app = FastAPI()
-app = App(app, demo)
 
-# ✅ Endpoint khusus untuk Flutter/Postman
 @app.post("/predict")
 async def predict(request: Request):
-    try:
-        payload = await request.json()
-        uid, question = payload["data"]
-        result = chatbot(uid, question)
-        return {"data": [result]}
-    except Exception as e:
-        return {"error": str(e)}
+    payload = await request.json()
+    uid, question = payload.get("data", [None, None])
+    if not uid or not question:
+        return {"error": "UID dan pertanyaan diperlukan."}
+    
+    answer = chatbot(uid, question)
+    return {"data": [answer]}
+
+# 🌈 Gradio UI (opsional)
+def launch_gradio():
+    demo = gr.Interface(
+        fn=chatbot,
+        inputs=["text", "text"],
+        outputs="text",
+        title="Biruu Chatbot",
+        examples=[["uid123", "Apakah bisa bayar di tempat?"]],
+        allow_flagging="never"
+    )
+    demo.launch(share=True)
+
+# ▶️ Jalankan Gradio di thread terpisah agar tidak bentrok dengan FastAPI
+threading.Thread(target=launch_gradio).start()