Update app.py

app.py

@@ -11,8 +11,8 @@ APIFY_TOKEN = "apify_api_VEELKPpmSsIfcblSisaKkKk2YiocQb2bwaS1"
 GEMINI_KEY = "AIzaSyBoD_j_LG5rBA0wthWn9xCFl555p0hC5Pc"
 HF_TOKEN = os.getenv("HF_TOKEN")
 
-# Inisialisasi Klien Gemini SDK BARU
-gemini_client = genai.Client(api_key=GEMINI_KEY, http_options={'api_version': 'v1'})
+# PERBAIKAN GEMINI: Hapus batasan 'v1' agar SDK otomatis mencari versi API yang tepat!
+gemini_client = genai.Client(api_key=GEMINI_KEY)
 
 apify_client = ApifyClient(APIFY_TOKEN)
 app = FastAPI()
@@ -25,8 +25,8 @@ app.add_middleware(
     allow_headers=["*"],
 )
 
-# Jalur Router Baru Hugging Face
-HF_API_URL = "https://router.huggingface.co/hf-inference/models/MoritzLaurer/mDeBERTa-v3-base-mnli-xnli"
+# Kembali menggunakan URL utama HF (lebih stabil dari router jika token benar)
+HF_API_URL = "https://api-inference.huggingface.co/models/MoritzLaurer/mDeBERTa-v3-base-mnli-xnli"
 HF_HEADERS = {"Authorization": f"Bearer {HF_TOKEN}"}
 
 # --- 2. FUNGSI ANALISIS SENTIMEN (MDEBERTA) ---
@@ -34,13 +34,15 @@ def analyze_with_mdeberta(ulasan_list):
     aspek_list = ["Kualitas Makanan", "Pelayanan", "Kebersihan", "Harga", "Variasi Menu", "Waktu Tunggu"]
     raw_scores = {k: {"pos": 0, "neu": 0, "neg": 0} for k in aspek_list}
     
-    for teks in ulasan_list[:10]:
+    # PERBAIKAN KECEPATAN: Hanya ambil 5 ulasan teratas agar tidak lama loading!
+    for teks in ulasan_list[:5]:
         try:
             payload = {
                 "inputs": teks, 
                 "parameters": {"candidate_labels": ["positif", "netral", "negatif"]}
             }
-            response = requests.post(HF_API_URL, headers=HF_HEADERS, json=payload, timeout=20)
+            # PERBAIKAN TIMEOUT: Kurangi jadi 6 detik. Jika HF lemot, langsung skip agar Vercel tidak muter terus!
+            response = requests.post(HF_API_URL, headers=HF_HEADERS, json=payload, timeout=6)
             
             if response.status_code == 200:
                 res = response.json()
@@ -51,19 +53,19 @@ def analyze_with_mdeberta(ulasan_list):
                         elif sentiment == "negatif": raw_scores[asp]["neg"] += 1
                         else: raw_scores[asp]["neu"] += 1
             else:
-                print(f"HF API Error: {response.status_code}")
+                print(f"HF Error {response.status_code}: {response.text[:50]}")
         except Exception as e:
             print(f"mDeBERTa Error: {e}")
             
     return raw_scores
 
-# --- 3. FUNGSI REKOMENDASI (GEMINI SDK BARU) ---
+# --- 3. FUNGSI REKOMENDASI (GEMINI) ---
 def get_advanced_insights(ulasan_list):
     try:
-        gabungan_ulasan = " | ".join(ulasan_list[:8])
+        gabungan_ulasan = " | ".join(ulasan_list[:6])
         prompt = f"""
         Analisis ulasan restoran ini: {gabungan_ulasan}.
-        Berikan respon JSON murni:
+        Berikan respon JSON murni TANPA markdown/codeblock:
         {{
           "kata_kunci_positif": ["kata1", "kata2"],
           "kata_kunci_negatif": ["kata1", "kata2"],
@@ -73,13 +75,12 @@ def get_advanced_insights(ulasan_list):
         }}
         """
         
-        # Eksekusi menggunakan SDK Baru (menggunakan gemini-1.5-flash sebagai standar stabil)
+        # Eksekusi dengan Gemini 1.5 Flash
         response = gemini_client.models.generate_content(
             model='gemini-1.5-flash',
             contents=prompt,
         )
         
-        # Membersihkan tag markdown JSON
         t = response.text.replace('```json', '').replace('```', '').strip()
         return json.loads(t)
     except Exception as e:
@@ -87,10 +88,10 @@ def get_advanced_insights(ulasan_list):
         return {
             "kata_kunci_positif": ["Rasa Enak"], 
             "kata_kunci_negatif": ["Antrean"], 
-            "rekomendasi": [{"judul": "Layanan", "deskripsi": "Tingkatkan kecepatan staf.", "prioritas": "Medium"}]
+            "rekomendasi": [{"judul": "Sistem Layanan", "deskripsi": "Percepat respons staf.", "prioritas": "Medium"}]
         }
 
-# --- 4. ENDPOINT ---
+# --- 4. ENDPOINT UTAMA ---
 @app.post("/analyze")
 async def analyze_realtime(request: Request):
     try:
@@ -98,7 +99,7 @@ async def analyze_realtime(request: Request):
         target_url = body.get("url")
         
         run = apify_client.actor("compass/google-maps-reviews-scraper").call(
-            run_input={"startUrls": [{"url": target_url}], "maxReviews": 15, "language": "id"}
+            run_input={"startUrls": [{"url": target_url}], "maxReviews": 10, "language": "id"}
         )
         
         ulasan_lengkap = []
@@ -115,11 +116,10 @@ async def analyze_realtime(request: Request):
         if not ulasan_teks_saja:
             return {"status": "error", "message": "Ulasan tidak ditemukan."}
 
-        # Proses AI
+        # AI Processing
         raw_scores = analyze_with_mdeberta(ulasan_teks_saja)
         gemini_data = get_advanced_insights(ulasan_teks_saja)
         
-        # Kalkulasi
         sentiment_results = []
         tp = tn = tneu = 0
         for name, counts in raw_scores.items():