Update app.py

app.py

@@ -1,16 +1,14 @@
-import gradio as gr
 from fastapi import FastAPI, Request
-import uvicorn
 from sentence_transformers import SentenceTransformer, util
 import torch
 import requests
-import threading
 
-# 🔐 Supabase setup
 SUPABASE_URL = "https://olbjfxlclotxtnpjvpfj.supabase.co"
-SUPABASE_KEY = "eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJzdXBhYmFzZSIsInJlZiI6Im9sYmpmeGxjbG90eHRucGp2cGZqIiwicm9sZSI6ImFub24iLCJpYXQiOjE3NTIyMzYwMDEsImV4cCI6MjA2NzgxMjAwMX0.7q_o5DCFEAAysnWXMChH4MI5qNhIVc4OgpT5JvgYxc0"
+SUPABASE_KEY = "eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJzdXBhYmFzZSIsInJlZiI6Im9sYmpmeGxjbG90eHRucGp2cGZqIiwicm9sZSI6ImFub24iLCJpYXQiOjE3NTIyMzYwMDEsImV4cCI6MjA2NzgxMjAwMX0.7q_o5DCFEAAysnWXMChH4MI5qNhIVc4OgpT5JvgYxc0"  # isi dengan key kamu
 
-model = SentenceTransformer('all-MiniLM-L6-v2')
+model = SentenceTransformer("all-MiniLM-L6-v2")
+
+app = FastAPI()
 
 def get_faq_from_supabase(uid):
     url = f"{SUPABASE_URL}/rest/v1/faq_texts?uid=eq.{uid}"
@@ -28,10 +26,17 @@ def get_faq_from_supabase(uid):
         print("❌ Supabase error:", e)
         return []
 
-def chatbot(uid, question):
+@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 "Tidak ada data FAQ."
+        return {"data": ["FAQ tidak ditemukan untuk UID ini."]}
 
     questions = [f["q"] for f in faqs]
     answers = [f["a"] for f in faqs]
@@ -39,37 +44,7 @@ def chatbot(uid, question):
     embeddings = model.encode(questions, convert_to_tensor=True)
     query_embedding = model.encode(question, convert_to_tensor=True)
 
-    scores = util.pytorch_cos_sim(query_embedding, embeddings)
-    best_idx = torch.argmax(scores).item()
-    return answers[best_idx]
-
-# 🌐 FastAPI app
-app = FastAPI()
-
-@app.post("/predict")
-async def predict(request: Request):
-    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()
+    similarity = util.pytorch_cos_sim(query_embedding, embeddings)
+    best_idx = torch.argmax(similarity).item()
 
-if _name_ == "_main_":
-    uvicorn.run("app:app", host="0.0.0.0", port=7860)
+    return {"data": [answers[best_idx]]}