Update app.py

app.py

@@ -7,8 +7,8 @@ from apify_client import ApifyClient
 
 # --- 1. KONFIGURASI API ---
 APIFY_TOKEN = os.getenv("APIFY_TOKEN")
-GEMINI_KEY = os.getenv("GEMINI_KEY")
 HF_TOKEN = os.getenv("HF_TOKEN")
+GROQ_API_KEY = os.getenv("GROQ_API_KEY")
 
 # Validasi token saat startup
 if not HF_TOKEN:
@@ -18,8 +18,7 @@ if not GEMINI_KEY:
 if not APIFY_TOKEN:
     print("⚠️ WARNING: APIFY_TOKEN is not set! Scraping will fail.")
 
-# Gemini REST API — bypass SDK entirely (using Gemini 2.5 Flash, stable free tier)
-GEMINI_URL = f"https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash:generateContent?key={GEMINI_KEY}"
+GROQ_URL = "https://api.groq.com/openai/v1/chat/completions"
 
 apify_client = ApifyClient(APIFY_TOKEN)
 app = FastAPI()
@@ -107,14 +106,14 @@ def analyze_sentiment(ulasan_list):
             
     return raw_scores
 
-# --- 3. FUNGSI REKOMENDASI (GEMINI REST API) ---
+# --- 3. FUNGSI REKOMENDASI (GROQ LLAMA 3) ---
 def get_advanced_insights(ulasan_list):
     try:
-        # Kirim ulasan lebih banyak ke Gemini (8 ulasan) untuk analisis lebih tajam
         gabungan_ulasan = " | ".join(ulasan_list[:8])
+        # Prompt disesuaikan sedikit agar Llama 3 lebih menurut
         prompt = f"""
-        Analisis ulasan restoran ini: {gabungan_ulasan}.
-        Berikan respon JSON murni:
+        Kamu adalah analis bisnis restoran. Analisis ulasan berikut: {gabungan_ulasan}.
+        Kamu WAJIB mengembalikan respon HANYA dalam format JSON murni ini:
         {{
           "kata_kunci_positif": ["kata1", "kata2"],
           "kata_kunci_negatif": ["kata1", "kata2"],
@@ -123,28 +122,37 @@ def get_advanced_insights(ulasan_list):
           ]
         }}
         """
+        
+        headers = {
+            "Authorization": f"Bearer {GROQ_API_KEY}",
+            "Content-Type": "application/json"
+        }
+        
         payload = {
-            "contents": [{"parts": [{"text": prompt}]}],
-            "generationConfig": {"temperature": 0.7}
+            "model": "llama3-8b-8192", # Model Llama 3 yang sangat cepat
+            "messages": [{"role": "user", "content": prompt}],
+            "response_format": {"type": "json_object"}, # Memaksa output berupa JSON
+            "temperature": 0.5
         }
-        response = requests.post(GEMINI_URL, json=payload, timeout=30)
+        
+        response = requests.post(GROQ_URL, headers=headers, json=payload, timeout=20)
+        
         if response.status_code == 200:
             data = response.json()
-            t = data["candidates"][0]["content"]["parts"][0]["text"]
-            # Menghapus tag markdown jika ada
-            t = t.replace('```json', '').replace('```', '').strip()
+            # Parsing output khas arsitektur OpenAI/Groq
+            t = data["choices"][0]["message"]["content"]
             return json.loads(t)
         else:
-            print(f"Gemini REST Error: {response.status_code} - {response.text[:200]}")
-            raise Exception(f"Gemini API returned {response.status_code}")
+            raise Exception(f"Groq API Error {response.status_code}")
+            
     except Exception as e:
-        print(f"Gemini Logic Error: {e}")
+        print(f"LLM Error: {e}")
         return {
-            "kata_kunci_positif": ["Rasa Enak", "Porsi Kenyang"], 
-            "kata_kunci_negatif": ["Antrean"], 
-            "rekomendasi": [{"judul": "Layanan", "deskripsi": "Tingkatkan kecepatan staf.", "prioritas": "Medium"}]
+            "kata_kunci_positif": ["Coba Lagi"], 
+            "kata_kunci_negatif": ["Server Sibuk"], 
+            "rekomendasi": [{"judul": "Gunakan Fallback", "deskripsi": "Server LLM sedang sibuk.", "prioritas": "Low"}]
         }
-
+        
 # --- 4. ENDPOINT ---
 @app.post("/analyze")
 async def analyze_realtime(request: Request):