| import streamlit as st | |
| import sys | |
| import os | |
| # 1. Fix Path | |
| sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), '../../'))) | |
| from src.retrieval.rag_chain import build_rag_chain | |
| st.set_page_config(page_title="RAG Observability Platform", layout="wide") | |
| st.title("π€ RAG Observability Platform") | |
| if "messages" not in st.session_state: | |
| st.session_state.messages = [] | |
| def load_chain(): | |
| return build_rag_chain() | |
| rag_chain = load_chain() | |
| for message in st.session_state.messages: | |
| with st.chat_message(message["role"]): | |
| st.markdown(message["content"]) | |
| if prompt := st.chat_input("Ask a question..."): | |
| st.session_state.messages.append({"role": "user", "content": prompt}) | |
| with st.chat_message("user"): | |
| st.markdown(prompt) | |
| with st.chat_message("assistant"): | |
| with st.spinner("Thinking (M4 GPU)..."): | |
| # LCEL Invoke (Direct String) | |
| response = rag_chain.invoke(prompt) | |
| st.markdown(response) | |
| st.session_state.messages.append({"role": "assistant", "content": response}) | |