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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}") |