Update app.py

app.py

@@ -1,27 +1,46 @@
-import os from fastapi import FastAPI, Request from sentence_transformers import SentenceTransformer, util import torch import requests
+import os
+from fastapi import FastAPI, Request
+from sentence_transformers import SentenceTransformer, util
+import torch
+import requests
 
+# ✅ Atur path cache agar tidak kena permission error
+os.environ["TRANSFORMERS_CACHE"] = "/tmp/hf"
+os.makedirs("/tmp/hf", exist_ok=True)
 
+# 🔐 Supabase setup
+SUPABASE_URL = "https://olbjfxlclotxtnpjvpfj.supabase.co"
+SUPABASE_KEY = "eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJzdXBhYmFzZSIsInJlZiI6Im9sYmpmeGxjbG90eHRucGp2cGZqIiwicm9sZSI6ImFub24iLCJpYXQiOjE3NTIyMzYwMDEsImV4cCI6MjA2NzgxMjAwMX0.7q_o5DCFEAAysnWXMChH4MI5qNhIVc4OgpT5JvgYxc0"
 
-os.environ["TRANSFORMERS_CACHE"] = "/tmp/hf" os.makedirs("/tmp/hf", exist_ok=True)
-
-
-
-SUPABASE_URL = "https://olbjfxlclotxtnpjvpfj.supabase.co" SUPABASE_KEY = "eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJzdXBhYmFzZSIsInJlZiI6Im9sYmpmeGxjbG90eHRucGp2cGZqIiwicm9sZSI6ImFub24iLCJpYXQiOjE3NTIyMzYwMDEsImV4cCI6MjA2NzgxMjAwMX0.7q_o5DCFEAAysnWXMChH4MI5qNhIVc4OgpT5JvgYxc0"
-
-
-model = SentenceTransformer("paraphrase-MiniLM-L3-v2")
-
-
+# 🔄 Gunakan model yang lebih ringan agar tidak error runtime
+model = SentenceTransformer("sentence-transformers/paraphrase-MiniLM-L3-v2")
 
 app = FastAPI()
 
-def get_faq_from_supabase(uid): url = f"{SUPABASE_URL}/rest/v1/faq_texts?uid=eq.{uid}" headers = { "apikey": SUPABASE_KEY, "Authorization": f"Bearer {SUPABASE_KEY}", "Content-Type": "application/json" } try: r = requests.get(url, headers=headers) r.raise_for_status() data = r.json() return [{"q": d["question"], "a": d["answer"]} for d in data] except Exception as e: print("❌ Supabase error:", e) return []
-
-@app.post("/predict") async def predict(request: Request): try: body = await request.json() uid, question = body.get("data", [None, None])
-
-if not uid or not question:
+def get_faq_from_supabase(uid):
+    url = f"{SUPABASE_URL}/rest/v1/faq_texts?uid=eq.{uid}"
+    headers = {
+        "apikey": SUPABASE_KEY,
+        "Authorization": f"Bearer {SUPABASE_KEY}",
+        "Content-Type": "application/json"
+    }
+    try:
+        r = requests.get(url, headers=headers)
+        r.raise_for_status()
+        data = r.json()
+        return [{"q": d["question"], "a": d["answer"]} for d in data]
+    except Exception as e:
+        print("❌ Supabase error:", e)
+        return []
+
+@app.post("/predict")
+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."]}
@@ -35,8 +54,4 @@ if not uid or not question:
     similarity = util.pytorch_cos_sim(query_embedding, embeddings)
     best_idx = torch.argmax(similarity).item()
 
-    return {"data": [answers[best_idx]]}
-
-except Exception as e:
-    print("❌ Error processing request:", e)
-    return {"data": ["Terjadi kesalahan pada server."]}
+    return {"data": [answers[best_idx]]}