Update app.py

app.py

@@ -1,17 +1,23 @@
+import os
 from fastapi import FastAPI, Request
 from sentence_transformers import SentenceTransformer, util
 import torch
 import requests
-import os
-os.environ["TRANSFORMERS_CACHE"] = "/tmp/hf"  # atau path lain yang bisa ditulis
 
+# 🛡️ Pastikan cache bisa ditulis
+os.environ["TRANSFORMERS_CACHE"] = "/tmp/hf"
+
+# 🔐 Supabase config
 SUPABASE_URL = "https://olbjfxlclotxtnpjvpfj.supabase.co"
-SUPABASE_KEY = "eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJzdXBhYmFzZSIsInJlZiI6Im9sYmpmeGxjbG90eHRucGp2cGZqIiwicm9sZSI6ImFub24iLCJpYXQiOjE3NTIyMzYwMDEsImV4cCI6MjA2NzgxMjAwMX0.7q_o5DCFEAAysnWXMChH4MI5qNhIVc4OgpT5JvgYxc0"  # isi dengan key kamu
+SUPABASE_KEY = "eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9..."
 
+# 🔍 Load model sekali
 model = SentenceTransformer("all-MiniLM-L6-v2")
 
+# 🚀 FastAPI app
 app = FastAPI()
 
+# 🔽 Ambil data FAQ dari Supabase
 def get_faq_from_supabase(uid):
     url = f"{SUPABASE_URL}/rest/v1/faq_texts?uid=eq.{uid}"
     headers = {
@@ -32,10 +38,10 @@ def get_faq_from_supabase(uid):
 async def predict(request: Request):
     body = await request.json()
     uid, question = body.get("data", [None, None])
-    
+
     if not uid or not question:
         return {"data": ["UID atau pertanyaan tidak valid."]}
-    
+
     faqs = get_faq_from_supabase(uid)
     if not faqs:
         return {"data": ["FAQ tidak ditemukan untuk UID ini."]}
@@ -49,10 +55,4 @@ async def predict(request: Request):
     similarity = util.pytorch_cos_sim(query_embedding, embeddings)
     best_idx = torch.argmax(similarity).item()
 
-    return {"data": [answers[best_idx]]}
-
-# Jalankan Gradio opsional di thread terpisah
-if __name__ == "__main__":
-    import threading
-    threading.Thread(target=launch_gradio).start()
-    uvicorn.run(app, host="0.0.0.0", port=7860)
+    return {"data": [answers[best_idx]]}