Create app.py

app.py

@@ -0,0 +1,50 @@
+# app cơ bản để demo RAG chatbot, sử dụng streamlit để đơn giản hoá phần frontend/U
+import sys
+import os
+import streamlit as st
+from time import time
+import logging
+sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
+os.environ['ROOT_PATH'] = os.path.dirname(os.path.abspath(os.path.dirname(__file__)))
+from api.engine import ChatEngine
+
+logging.basicConfig(stream=sys.stdout, level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
+
+st.title("Smart Chabot for Organic Crop powered by Eco Footprint")
+
+@st.cache_resource
+def initialize():
+    return ChatEngine(vector_index="chroma", force_new_db=False)
+
+engine = initialize()
+
+
+if "messages" not in st.session_state:
+    st.session_state.messages = []
+
+for message in st.session_state.messages:
+    with st.chat_message(message["role"]):
+        st.markdown(message["content"])
+
+if user_input := st.chat_input("Bạn muốn hỏi điều gì?"):
+    st.session_state.messages.append({"role": "user", "content": user_input})
+    with st.chat_message("user"):
+        st.markdown(user_input)
+
+    with st.chat_message("assistant"):
+        message_placeholder = st.empty()
+
+        response_content = ""
+        with st.spinner("Thinking..."):
+            start = time()
+            streaming_response = engine.query_streaming(user_input)
+            # Stream kết quả và cập nhật lên giao diện
+            query_end = time()
+            print(f"Query time calculated: {round(query_end-start,4)}")
+            for chunk in streaming_response.response_gen:
+                response_content += chunk
+                message_placeholder.markdown(f"{response_content} ▌")
+            end = time()
+            print(f"Response time calculated: {round(end-start,4)}")
+    message_placeholder.markdown(response_content)
+    st.session_state.messages.append({"role": "assistant", "content": response_content})