Update app.py

app.py

@@ -1,15 +1,22 @@
+import os
 import gradio as gr
 from langchain_community.vectorstores import FAISS
 from langchain.embeddings import HuggingFaceEmbeddings
 from groq import Groq
 
 # Load FAISS index
-vector_store = FAISS.load_local("robohome_faiss", HuggingFaceEmbeddings())
+vector_store = FAISS.load_local("faiss_index/robohome_faiss", HuggingFaceEmbeddings())  # Pastikan path benar
+
+# Load API Key dari variabel lingkungan
+GROQ_API_KEY = os.getenv("GROQ_API_KEY")  
+if not GROQ_API_KEY:
+    raise ValueError("⚠️ API Key Groq tidak ditemukan! Setel variabel lingkungan 'GROQ_API_KEY'.")
 
 # Inisialisasi API Groq
-client = Groq(api_key="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")
+client = Groq(api_key=GROQ_API_KEY)
 
-def retrieve_and_generate(query):
+def retrieve_and_generate(query, history=[]):
+    """Retrieve knowledge base & generate response."""
     # Retrieve top 3 documents
     docs = vector_store.similarity_search(query, k=3)
     context = "\n\n".join([doc.page_content for doc in docs])
@@ -25,15 +32,18 @@ def retrieve_and_generate(query):
         max_tokens=200
     )
 
-    return response.choices[0].message.content
+    # Return hasil dalam format chat
+    bot_response = response.choices[0].message.content
+    history.append((query, bot_response))  # Simpan ke history chat
+    return history, history
 
 # UI dengan Gradio
-iface = gr.Interface(
+iface = gr.ChatInterface(
     fn=retrieve_and_generate,
-    inputs=gr.Textbox(label="Ajukan pertanyaan tentang RoboHome"),
-    outputs=gr.Textbox(label="Jawaban"),
+    chatbot=gr.Chatbot(label="Jawaban RoboHome"),
+    textbox=gr.Textbox(label="Ajukan pertanyaan tentang RoboHome"),
     title="RoboHome RAG Chatbot",
     description="Chatbot ini menjawab pertanyaan berdasarkan dokumentasi RoboHome.",
 )
 
-iface.launch()
+iface.launch(share=True)  # Share=True untuk membuat link publik