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| __import__('pysqlite3') | |
| import sys | |
| sys.modules['sqlite3'] = sys.modules.pop('pysqlite3') | |
| import streamlit as st | |
| import os | |
| # --- PATH SETUP --- | |
| current_dir = os.getcwd() # Should be /home/user/app in Docker | |
| load_dir = os.path.join(current_dir, "src", "load") | |
| sys.path.append(load_dir) | |
| # Import your agent creator | |
| try: | |
| from mshauri_demo import create_mshauri_agent | |
| except ImportError as e: | |
| st.error(f"Critical Error: Could not import mshauri_demo. Paths checked: {sys.path}. Details: {e}") | |
| st.stop() | |
| st.set_page_config(page_title="Mshauri Fedha", page_icon="🦁") | |
| st.title("🦁 Mshauri Fedha") | |
| st.markdown("### AI Financial Advisor for Kenya") | |
| # Initialize Session State | |
| if "messages" not in st.session_state: | |
| st.session_state.messages = [] | |
| if "agent" not in st.session_state: | |
| with st.spinner("Initializing Mshauri Brain (Loading Models & Data)..."): | |
| # SQLAlchemy requires a URI starting with sqlite:/// | |
| # We use 4 slashes (sqlite:////) because it is an absolute path on Linux | |
| sql_path = f"sqlite:///{os.path.join(current_dir, 'mshauri_fedha_v6.db')}" | |
| vector_path = os.path.join(current_dir, "mshauri_fedha_chroma_db") | |
| # Check if data exists (Debugging for Space deployment) | |
| real_db_path = os.path.join(current_dir, "mshauri_fedha_v6.db") | |
| if not os.path.exists(real_db_path): | |
| st.error(f"Database not found at {real_db_path}. Did the clone fail?") | |
| st.stop() | |
| try: | |
| # mshauri_demo.py to intelligently pick the API or Local model. | |
| st.session_state.agent = create_mshauri_agent( | |
| sql_db_path=sql_path, | |
| vector_db_path=vector_path | |
| ) | |
| st.success("System Ready!") | |
| except Exception as e: | |
| st.error(f"Failed to initialize agent: {e}") | |
| # Display Chat History | |
| for message in st.session_state.messages: | |
| with st.chat_message(message["role"]): | |
| st.markdown(message["content"]) | |
| # Handle Input | |
| if prompt := st.chat_input("Ask about inflation, exchange rates, or economic trends..."): | |
| 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("Analyzing..."): | |
| try: | |
| if st.session_state.agent: | |
| response = st.session_state.agent.invoke({"input": prompt}) | |
| output_text = response.get("output", "Error generating response.") | |
| st.markdown(output_text) | |
| st.session_state.messages.append({"role": "assistant", "content": output_text}) | |
| else: | |
| st.error("Agent failed to initialize. Please refresh the page.") | |
| except Exception as e: | |
| st.error(f"An error occurred: {e}") |