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import streamlit as st
import time
import os
import sys
import json
from datetime import datetime
from pathlib import Path
sys.path.append(str(Path(__file__).parent))
# Import our new handler
from src.ui.chat_handler import chat_handler
from utils.config import config
from core.session import session_manager
from core.memory import check_redis_health
from core.errors import translate_error
from core.personality import personality
from src.analytics.user_logger import user_logger
from src.analytics.session_analytics import session_analytics
import logging
# Set up logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
# Initialize session state
if "messages" not in st.session_state:
st.session_state.messages = []
if "is_processing" not in st.session_state:
st.session_state.is_processing = False
if "ngrok_url_temp" not in st.session_state:
st.session_state.ngrok_url_temp = st.session_state.get("ngrok_url", "https://7bcc180dffd1.ngrok-free.app")
if "cosmic_mode" not in st.session_state:
st.session_state.cosmic_mode = True
if "show_welcome" not in st.session_state:
st.session_state.show_welcome = True
if "session_id" not in st.session_state:
st.session_state.session_id = f"sess_{int(time.time())}_{os.urandom(4).hex()}"
if "last_processed_message" not in st.session_state:
st.session_state.last_processed_message = ""
# Start session tracking
session_analytics.start_session_tracking("default_user", st.session_state.session_id)
st.set_page_config(page_title="CosmicCat AI Assistant", page_icon="π±", layout="wide")
# Log page view
session_analytics.track_interaction("default_user", st.session_state.session_id, "page_view", {
"page": "main_chat"
})
# Sidebar
with st.sidebar:
st.title("π± CosmicCat AI Assistant")
st.markdown("Your personal AI-powered assistant with a cosmic twist.")
# 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,
on_change=lambda: session_analytics.track_interaction("default_user", st.session_state.session_id, "model_selection", {
"selected_model": st.session_state.selected_model if 'selected_model' in st.session_state else model_options[list(model_options.keys())[0]]
})
)
st.session_state.selected_model = model_options[selected_model_name]
# Log model selection
session_analytics.track_interaction("default_user", st.session_state.session_id, "model_selection", {
"selected_model": st.session_state.selected_model
})
# Cosmic mode toggle
st.session_state.cosmic_mode = st.checkbox("Enable Cosmic Mode", value=st.session_state.cosmic_mode,
on_change=lambda: session_analytics.track_interaction("default_user", st.session_state.session_id, "cosmic_mode_toggle", {
"enabled": st.session_state.cosmic_mode
}))
st.divider()
# Configuration
st.subheader("βοΈ Configuration")
ngrok_url_input = st.text_input(
"Ollama Server URL",
value=st.session_state.ngrok_url_temp,
help="Enter your ngrok URL",
on_change=lambda: session_analytics.track_interaction("default_user", st.session_state.session_id, "url_update", {
"url_changed": ngrok_url_input != st.session_state.ngrok_url_temp
})
)
if ngrok_url_input != st.session_state.ngrok_url_temp:
st.session_state.ngrok_url_temp = ngrok_url_input
st.success("β
URL updated!")
session_analytics.track_interaction("default_user", st.session_state.session_id, "url_updated", {
"new_url": ngrok_url_input
})
if st.button("π‘ Test Connection"):
start_time = time.time()
session_analytics.track_interaction("default_user", st.session_state.session_id, "test_connection_click")
try:
from core.providers.ollama import OllamaProvider
ollama_provider = OllamaProvider(st.session_state.selected_model)
is_valid = ollama_provider.validate_model()
end_time = time.time()
if is_valid:
st.success("β
Connection successful!")
session_analytics.track_interaction("default_user", st.session_state.session_id, "connection_success", {
"response_time": end_time - start_time
})
user_logger.log_performance_metric("default_user", "connection_test", end_time - start_time)
else:
st.error("β Model validation failed")
session_analytics.track_interaction("default_user", st.session_state.session_id, "connection_failed", {
"error": "model_validation_failed"
})
except Exception as e:
end_time = time.time()
st.error(f"β Error: {str(e)[:50]}...")
session_analytics.track_interaction("default_user", st.session_state.session_id, "connection_error", {
"error": str(e)[:100],
"response_time": end_time - start_time
})
user_logger.log_error("default_user", "connection_test", str(e))
if st.button("ποΈ Clear History"):
session_analytics.track_interaction("default_user", st.session_state.session_id, "clear_history_click")
st.session_state.messages = []
st.session_state.last_processed_message = ""
# Also clear backend session
session_manager.clear_session("default_user")
st.success("History cleared!")
session_analytics.track_interaction("default_user", st.session_state.session_id, "history_cleared")
st.divider()
# System Status with enhanced HF monitoring
with st.expander("π System Status", expanded=True):
st.subheader("π Status")
# Ollama Status
try:
from services.ollama_monitor import check_ollama_status
ollama_status = check_ollama_status()
if ollama_status.get("running"):
st.success("π¦ Ollama: Running")
else:
st.warning("π¦ Ollama: Not running")
except:
st.info("π¦ Ollama: Unknown")
# HF Endpoint Status (Enhanced with initialization info)
try:
from src.services.hf_monitor import hf_monitor
status_message = hf_monitor.get_human_readable_status()
# Display appropriate status icon
if "π’" in status_message:
st.success(status_message)
elif "π‘" in status_message:
st.warning(status_message)
elif "π΄" in status_message:
st.error(status_message)
elif "β" in status_message:
st.error(status_message)
elif "β³" in status_message:
st.info(status_message)
else:
st.info(status_message)
# Show initialization progress if applicable
init_progress = hf_monitor.get_initialization_progress()
if init_progress:
st.info(init_progress)
# Add wake-up button if scaled to zero or initializing
if "scaled to zero" in status_message.lower() or "initializing" in status_message.lower():
if st.button("β‘ Wake Up HF Endpoint", key="wake_up_hf"):
session_analytics.track_interaction("default_user", st.session_state.session_id, "wake_up_hf_click")
with st.spinner("Attempting to wake up HF endpoint... This may take 2-4 minutes during initialization..."):
start_time = time.time()
if hf_monitor.attempt_wake_up():
end_time = time.time()
st.success("β
Wake-up request sent! The endpoint should be initializing now. Try your request again in a moment.")
session_analytics.track_interaction("default_user", st.session_state.session_id, "hf_wake_up_success", {
"response_time": end_time - start_time
})
user_logger.log_performance_metric("default_user", "hf_wake_up", end_time - start_time)
time.sleep(3)
st.experimental_rerun()
else:
end_time = time.time()
st.error("β Failed to send wake-up request. Please try again or wait for initialization to complete.")
session_analytics.track_interaction("default_user", st.session_state.session_id, "hf_wake_up_failed", {
"response_time": end_time - start_time
})
user_logger.log_error("default_user", "hf_wake_up", "Failed to wake up HF endpoint")
except Exception as e:
st.info(f"π€ HF Endpoint: Error checking status - {str(e)}")
session_analytics.track_interaction("default_user", st.session_state.session_id, "hf_status_error", {
"error": str(e)
})
user_logger.log_error("default_user", "hf_status_check", str(e))
# Redis Status
try:
if check_redis_health():
st.success("πΎ Redis: Connected")
else:
st.error("πΎ Redis: Disconnected")
except:
st.info("πΎ Redis: Unknown")
st.divider()
# Feedback Section
st.subheader("β Feedback")
rating = st.radio("How would you rate your experience?", [1, 2, 3, 4, 5], horizontal=True)
feedback_comment = st.text_area("Additional comments (optional):")
if st.button("Submit Feedback"):
user_logger.log_feedback("default_user", rating, feedback_comment)
session_analytics.track_interaction("default_user", st.session_state.session_id, "feedback_submitted", {
"rating": rating,
"has_comment": bool(feedback_comment)
})
st.success("Thank you for your feedback! π")
st.divider()
# Debug Info
st.subheader("π Debug Info")
st.markdown(f"**Environment:** {'HF Space' if config.is_hf_space else 'Local'}")
st.markdown(f"**Model:** {st.session_state.selected_model}")
st.markdown(f"**Session ID:** {st.session_state.session_id}")
# Main interface
st.title("π± CosmicCat AI Assistant")
st.markdown("Ask me anything!")
# Welcome message
if st.session_state.show_welcome:
with st.chat_message("assistant"):
greeting = personality.get_greeting(cosmic_mode=st.session_state.cosmic_mode)
st.markdown(greeting)
st.session_state.show_welcome = False
# Display conversation history
for message in st.session_state.messages:
with st.chat_message(message["role"]):
st.markdown(message["content"])
if "timestamp" in message:
provider_info = f" (via {message.get('provider', 'unknown')})" if message["role"] == "assistant" else ""
st.caption(f"π {message['timestamp']}{provider_info}")
# Chat input with enhanced processing
user_input = st.chat_input("Type your message here...", key="chat_input")
# Process message when received
if user_input and user_input.strip():
# Prevent processing if already processing
if not getattr(chat_handler, 'is_processing', False):
chat_handler.process_user_message(user_input, selected_model_name)
else:
st.warning("Still processing your previous request...")
# About tab
st.divider()
tab1, = st.tabs(["βΉοΈ About"])
with tab1:
st.header("βΉοΈ About CosmicCat AI Assistant")
st.markdown("""
The CosmicCat AI Assistant is a sophisticated conversational AI with a cosmic theme.
### π§ Core Features
- **Local AI processing** with Ollama models
- **Persistent memory** using Redis
- **Space-themed personality** for fun interactions
- **HF Endpoint integration** for advanced capabilities
### π Cosmic Mode
When enabled, the AI responds with space-themed language and metaphors.
### π οΈ Technical Architecture
- **Primary model**: Ollama (local processing)
- **Secondary model**: HF Endpoint (advanced processing)
- **Memory system**: Redis-based session management
""")
# Log about page view
session_analytics.track_interaction("default_user", st.session_state.session_id, "about_page_view")
# End session tracking when app closes
def on_session_end():
session_analytics.end_session_tracking("default_user", st.session_state.session_id)
# Register cleanup function
import atexit
atexit.register(on_session_end)
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