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Respect REDIS_DISABLE_SSL setting and fix Streamlit toast compatibility
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import streamlit as st
import time
import os
import sys
from datetime import datetime
from pathlib import Path
sys.path.append(str(Path(__file__).parent))
from utils.config import config
from core.llm import send_to_ollama, send_to_hf
from core.session import session_manager
from core.memory import check_redis_health
st.set_page_config(page_title="AI Life Coach", page_icon="🧠", layout="wide")
# Initialize session state
if "messages" not in st.session_state:
st.session_state.messages = []
if "last_error" not in st.session_state:
st.session_state.last_error = ""
if "last_ollama_call_success" not in st.session_state:
st.session_state.last_ollama_call_success = None
if "last_ollama_call_time" not in st.session_state:
st.session_state.last_ollama_call_time = ""
if "last_ollama_response_preview" not in st.session_state:
st.session_state.last_ollama_response_preview = ""
if "last_hf_call_success" not in st.session_state:
st.session_state.last_hf_call_success = None
if "last_hf_call_time" not in st.session_state:
st.session_state.last_hf_call_time = ""
if "last_hf_response_preview" not in st.session_state:
st.session_state.last_hf_response_preview = ""
# Sidebar
with st.sidebar:
st.title("AI Life Coach")
st.markdown("Your personal AI-powered life development assistant")
# Model selection
model_options = {
"Mistral 7B (Local)": "mistral:latest",
"Llama 2 7B (Local)": "llama2:latest",
"OpenChat 3.5 (Local)": "openchat:latest"
}
selected_model_name = st.selectbox(
"Select Model",
options=list(model_options.keys()),
index=0
)
st.session_state.selected_model = model_options[selected_model_name]
# Ollama URL input
st.session_state.ngrok_url = st.text_input(
"Ollama Server URL",
value=st.session_state.get("ngrok_url", "http://localhost:11434"),
help="Enter the URL to your Ollama server"
)
# Conversation history
st.subheader("Conversation History")
if st.button("Clear History"):
st.session_state.messages = []
st.success("History cleared!")
# Debug info
with st.sidebar.expander("πŸ”§ Debug Info"):
st.write(f"**OLLAMA_HOST**: {st.session_state.ngrok_url}")
st.write(f"**Selected Model**: {st.session_state.selected_model}")
st.write(f"Fallback Mode: {'βœ… On' if config.use_fallback else '❌ Off'}")
st.write(f"Redis Status: {'βœ… Healthy' if check_redis_health() else '⚠️ Unavailable'}")
st.write(f"Env Detected As: {'☁️ HF Space' if config.is_hf_space else '🏠 Local'}")
st.write(f"HF Token Set: {'βœ… Yes' if config.hf_token else '❌ No'}")
if st.session_state.last_error:
st.warning(f"Last Error: {st.session_state.last_error}")
# Ollama API Call Tracking
if st.session_state.last_ollama_call_success is not None:
status_icon = "βœ… Success" if st.session_state.last_ollama_call_success else "❌ Failed"
st.write(f"Last Ollama Call: {status_icon}")
st.write(f"At: {st.session_state.last_ollama_call_time}")
if st.session_state.last_ollama_response_preview:
st.code(st.session_state.last_ollama_response_preview[:200] + ("..." if len(st.session_state.last_ollama_response_preview) > 200 else ""), language="text")
# Hugging Face API Call Tracking
if st.session_state.last_hf_call_success is not None:
status_icon = "βœ… Success" if st.session_state.last_hf_call_success else "❌ Failed"
st.write(f"Last HF Call: {status_icon}")
st.write(f"At: {st.session_state.last_hf_call_time}")
if st.session_state.last_hf_response_preview:
st.code(st.session_state.last_hf_response_preview[:200] + ("..." if len(st.session_state.last_hf_response_preview) > 200 else ""), language="text")
# Manual Refresh Button
if st.button("πŸ”„ Refresh Ollama Status"):
from services.ollama_monitor import check_ollama_status
status = check_ollama_status()
# Fix Streamlit toast issue - replace with compatible function
st.sidebar.info(f"Ollama Status: {'Running' if status['running'] else 'Unavailable'}")
# Main chat interface
st.title("🧠 AI Life Coach")
st.markdown("Ask me anything about personal development, goal setting, or life advice!")
# Display chat messages
for message in st.session_state.messages:
with st.chat_message(message["role"]):
st.markdown(message["content"])
# Chat input and send button
col1, col2 = st.columns([4, 1])
with col1:
user_input = st.text_input(
"Your message...",
key="user_message_input",
placeholder="Type your message here...",
label_visibility="collapsed"
)
with col2:
send_button = st.button("Send", key="send_message_button", use_container_width=True)
if send_button and user_input.strip():
# Display user message
with st.chat_message("user"):
st.markdown(user_input)
# Add user message to history
st.session_state.messages.append({"role": "user", "content": user_input})
# Reset error state
st.session_state.last_error = ""
# Get conversation history
user_session = session_manager.get_session("default_user")
conversation = user_session.get("conversation", [])
conversation_history = conversation[-5:] # Last 5 messages
conversation_history.append({"role": "user", "content": user_input})
# Send to backend
with st.chat_message("assistant"):
with st.spinner("AI Coach is thinking..."):
ai_response = None
backend_used = ""
error_msg = ""
# Try Ollama first if not falling back
if not config.use_fallback:
try:
ai_response = send_to_ollama(
user_input, conversation_history,
st.session_state.ngrok_url, st.session_state.selected_model
)
backend_used = "Ollama"
# Capture success metadata
st.session_state.last_ollama_call_success = True
st.session_state.last_ollama_call_time = str(datetime.utcnow())
st.session_state.last_ollama_response_preview = ai_response[:200] if ai_response else ""
except Exception as e:
error_msg = f"Ollama error: {str(e)}"
# Capture failure metadata
st.session_state.last_ollama_call_success = False
st.session_state.last_ollama_call_time = str(datetime.utcnow())
st.session_state.last_ollama_response_preview = str(e)[:200]
# Fallback to Hugging Face if not ai_response and config.hf_token
if not ai_response and config.hf_token:
try:
ai_response = send_to_hf(user_input, conversation_history)
backend_used = "Hugging Face"
# Capture success metadata
st.session_state.last_hf_call_success = True
st.session_state.last_hf_call_time = str(datetime.utcnow())
st.session_state.last_hf_response_preview = ai_response[:200] if ai_response else ""
except Exception as e:
error_msg = f"Hugging Face error: {str(e)}"
# Capture failure metadata
st.session_state.last_hf_call_success = False
st.session_state.last_hf_call_time = str(datetime.utcnow())
st.session_state.last_hf_response_preview = str(e)[:200]
if ai_response:
st.markdown(f"{ai_response}")
# Update conversation history
conversation.append({"role": "user", "content": user_input})
conversation.append({"role": "assistant", "content": ai_response})
# Update session using the correct method
user_session["conversation"] = conversation
session_manager.update_session("default_user", user_session)
# Add assistant response to history
st.session_state.messages.append({"role": "assistant", "content": ai_response})
else:
st.error("Failed to get response from both providers.")
st.session_state.last_error = error_msg or "No response from either provider"
# Clear input by forcing rerun
st.experimental_rerun()