Update app.py

app.py

@@ -4,6 +4,9 @@
 import os, time, importlib.util
 import gradio as gr
 from huggingface_hub import hf_hub_download
+from datetime import datetime
+from datetime import date
+from upstash_redis import Redis
 
 # ----------------------------------------------------------------------
 # Helper to read secrets from the HF Space environment
@@ -20,9 +23,12 @@ def _secret(key: str, fallback: str = None) -> str:
 # 1. Configuration & Constants
 # ----------------------------------------------------------------------
 REPO_ID = _secret("REPO_ID")
-FILES_TO_DOWNLOAD = ["index.faiss", "index.pkl", "agent_logic.py"]
+FILES_TO_DOWNLOAD = ["index.faiss", "index.pkl", "agent_logic.py","prec_hyde_agent.txt","prec_rag_agent.txt"]
 LOCAL_DOWNLOAD_DIR = "downloaded_assets"
 EMBEDDING_MODEL_NAME = "google/embeddinggemma-300m"
+redis = Redis(url=_secret("UPSTASH_REDIS_URL")
+              , token= _secret("UPSTASH_TOKEN")
+             )
 
 # ----------------------------------------------------------------------
 # 2. Bootstrap Phase – download assets and import the RAG engine
@@ -62,14 +68,30 @@ def respond(message: str, history: list[dict[str, str]]):
     Called by Gradio for each user message.
     Streams the response back to the UI.
     """
-    final_response = engine.get_response(message, history)
-
-    # Simple "typing" effect – yield partial strings
-    response = ""
-    for char in final_response:
-        response += char
-        time.sleep(0.01)          # tweak speed if you like
-        yield response
+    try:
+        # Check expiration
+        end_date = datetime.strptime(_secret("END_DATE"), "%Y-%m-%d").date()
+        if date.today() > end_date:
+            return "Chatbot sudah expired."  # Direct return for errors
+
+        # Check request limit  
+        remaining_requests = redis.decr("request_limit")
+        if remaining_requests < 0:
+            return "Kuota chat sudah habis."  # Direct return for errors
+
+        # If we pass all checks, then stream the response
+        final_response = engine.get_response(message, history)
+    
+        # Stream the response with typing effect
+        response = ""
+        for char in final_response:
+            response += char
+            time.sleep(0.01)
+            yield response
+            
+    except Exception as e:
+        print(f"Error in respond function: {e}")
+        return "Terjadi error saat memproses permintaan. Silakan coba lagi."
 
 # ----------------------------------------------------------------------
 # 4. UI Layout – Tips + Chat + Footer
@@ -82,7 +104,7 @@ tips_md = r"""
   AI Agent yang menggunakan Retrieval‑Augmented Generation (RAG) untuk menjawab pertanyaan dari dokumentasi PRECISE (disimpan dalam FAISS storage).  
 - **Perbedaan dengan chatbot sebelumnya :**  
   • Dengan menggunakan agentic RAG, agent hanya mengambil dokumentasi yang dibutuhkan.  
-  • Karena efisiensi konteks dan efisiensi design, dapat menggunakan model kecerdasan rendah, sehingga cost turun sekitar 75% dibanding versi non RAG yang sebelumnya.  
+  • Karena efisiensi konteks dan efisiensi design, dapat menggunakan model kecerdasan rendah, sehingga cost turun sekitar 95% dibanding versi non RAG yang sebelumnya.  
 - **Tips untuk menggunakan**  
   • Usahakan pertanyaan Anda spesifik agar jawaban lebih akurat.  
   • Jika jawaban kurang mengena, coba reset chat atau tanyakan ulang dengan bahasa berbeda.  
@@ -94,9 +116,9 @@ tips_md = r"""
 # 4.2  Footer – the old description / notes
 footer_md = r"""
 ---  
-**Frameworks**: LangChain + FAISS  
-**Model**: gpt‑oss‑20b, gemma‑3‑3n4B  
-*Updated 07 Sep 2025 – YOI*  
+**Komponen**: LangChain + FAISS  + Redis
+**Models**: Qwen3-4B-Thinking-2507, Qwen3-4B-Instruct-2507  
+*Updated 25 Sep 2025 – YOI*  
 
 """
 
@@ -104,7 +126,7 @@ footer_md = r"""
 chatbot = gr.ChatInterface(
     respond,
     type="messages",
-    title="PRECISE RAG Agent",
+    title="PRECISE RAG Agent (Expired 1 April 2026)",
     examples=[
         ["Jelaskan konsep PRECISE secara sederhana."],
         ["Berapa keuntungan finansial yang didapat menggunakan PRECISE?"],