""" Personal Diary Chatbot Interface - Simplified Version A streamlined Streamlit-based web application for diary management and AI chat. """ import os import sys import re import hashlib import streamlit as st import random import time import subprocess from datetime import datetime from typing import Generator, List from backend.get_post_v3 import submit_text_to_database, load_entries_from_database, delete_diary_entry from auth_ui import AuthUI # Voice Input Dependencies try: from streamlit_webrtc import webrtc_streamer, WebRtcMode, RTCConfiguration import av import numpy as np import google.generativeai as genai import tempfile import threading import queue import concurrent.futures VOICE_AVAILABLE = True except ImportError as e: print(f"Voice input dependencies not available: {e}") VOICE_AVAILABLE = False # Load environment variables from dotenv import load_dotenv load_dotenv() # Add parent directory to path for RAG system import sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))) # Import RAG client try: from rag_client import RAGServiceClient rag_client = RAGServiceClient() RAG_AVAILABLE = True print("✅ RAG client imported successfully") except ImportError as e: print(f"Warning: RAG client not available: {e}") rag_client = None RAG_AVAILABLE = False # ======================================== # VOICE INPUT FUNCTIONS # ======================================== def get_user_audio_directory(user_id: int) -> str: """Get user-specific audio directory path.""" # Get project root directory (go up from src/streamlit_app/) current_dir = os.path.dirname(os.path.abspath(__file__)) project_root = os.path.dirname(os.path.dirname(current_dir)) audio_dir = os.path.join(project_root, "user_audio", f"user_{user_id}_audio") os.makedirs(audio_dir, exist_ok=True) return audio_dir def transcribe_audio_with_gemini_live(audio_data: bytes, user_id: int) -> str: """Transcribe audio using Gemini API.""" try: # Get API key api_key = os.getenv("GOOGLE_API_KEY") if not api_key: return "❌ Google API key not configured" # Configure Gemini genai.configure(api_key=api_key) # Save audio temporarily audio_dir = get_user_audio_directory(user_id) temp_audio_path = os.path.join(audio_dir, f"temp_audio_{int(time.time())}.wav") try: with open(temp_audio_path, 'wb') as f: f.write(audio_data) # Upload audio file to Gemini audio_file = genai.upload_file(path=temp_audio_path, mime_type="audio/wav") # Use Gemini model for transcription model = genai.GenerativeModel("gemini-2.5-flash-lite") prompt = """Convert speech to text. Please transcribe this audio recording accurately. Instructions: - Listen to the audio and convert the spoken words to text - Maintain proper grammar and punctuation - Return only the transcribed text, no additional commentary - If you cannot understand parts of the audio, indicate with [unclear] Transcription:""" response = model.generate_content([prompt, audio_file]) if response and response.text: # Clean up the uploaded file try: genai.delete_file(audio_file.name) except Exception: pass return response.text.strip() else: return "❌ No transcription received" finally: # Clean up temporary file if os.path.exists(temp_audio_path): try: os.remove(temp_audio_path) except Exception as e: print(f"Warning: Could not delete temp audio file: {e}") except PermissionError: return "⚠️ Vui lòng cấp quyền truy cập microphone" except Exception as e: print(f"Transcription error: {e}") return f"❌ Transcription failed: {str(e)}" class AudioProcessor: """Audio processor for real-time audio capture.""" def __init__(self): self.audio_frames = queue.Queue() self.is_recording = False def audio_frame_callback(self, frame): """Callback for processing audio frames.""" if self.is_recording: audio_array = frame.to_ndarray() self.audio_frames.put(audio_array) return frame def start_recording(self): """Start recording audio.""" self.is_recording = True self.audio_frames = queue.Queue() def stop_recording(self): """Stop recording and return audio data.""" self.is_recording = False # Collect all audio frames frames = [] while not self.audio_frames.empty(): try: frame = self.audio_frames.get_nowait() frames.append(frame) except queue.Empty: break if not frames: return None # Concatenate frames and ensure proper format audio_data = np.concatenate(frames, axis=0) # Ensure audio is mono (single channel) if audio_data.ndim > 1: audio_data = np.mean(audio_data, axis=1) # Normalize audio data to prevent distortion if np.max(np.abs(audio_data)) > 0: audio_data = audio_data / np.max(np.abs(audio_data)) * 0.8 # Convert to 16-bit PCM format audio_bytes = (audio_data * 32767).astype(np.int16).tobytes() return audio_bytes # ======================================== # HELPER FUNCTIONS # ======================================== def extract_title_from_content(content: str) -> str: """Extract title from content string.""" if not content: return "Untitled" lines = content.split('\n') for line in lines: if line.startswith('Title: '): return line[7:].strip() return "Untitled" def extract_content_from_entry(content: str) -> str: """Extract actual content from full content string.""" if not content: return "" lines = content.split('\n') content_start = False result_lines = [] for line in lines: if line.startswith('Content: '): content_start = True result_lines.append(line[9:]) elif content_start: result_lines.append(line) return '\n'.join(result_lines).strip() def extract_tags_from_content(content: str) -> List[str]: """Extract #tags from content string.""" if not content: return [] tag_pattern = r'#(\w+(?:[_-]\w+)*)' matches = re.findall(tag_pattern, content, re.IGNORECASE) return list(set([tag.lower() for tag in matches])) def parse_tags_input(tags_input: str) -> List[str]: """Parse comma-separated tags input.""" if not tags_input: return [] tags = [] for tag in tags_input.split(','): tag = tag.strip() if tag.startswith('#'): tag = tag[1:] if tag: tags.append(tag.lower()) return list(set(tags)) def generate_tag_color(tag: str) -> str: """Generate consistent color for a tag.""" hash_obj = hashlib.md5(tag.encode()) hash_hex = hash_obj.hexdigest() r = max(60, min(200, int(hash_hex[0:2], 16))) g = max(60, min(200, int(hash_hex[2:4], 16))) b = max(60, min(200, int(hash_hex[4:6], 16))) return f"rgb({r}, {g}, {b})" def render_tags(tags: List[str]) -> str: """Render tags as colored HTML badges.""" if not tags: return "" tag_html = [] for tag in tags: color = generate_tag_color(tag) tag_html.append(f'#{tag}') return "".join(tag_html) def check_rag_service(): """Check if RAG service is running.""" if rag_client: return rag_client.health_check() return False def check_ai_availability_detailed(user_id: int): """Check detailed AI availability status.""" if not rag_client: return {"overall_status": "error", "error": "RAG client not initialized"} return rag_client.check_ai_availability(user_id) def fix_ai_availability(user_id: int): """Attempt to fix AI availability issues.""" if not rag_client: return {"status": "error", "error": "RAG client not initialized"} return rag_client.fix_ai_availability(user_id) def render_ai_status_widget(user_id: int): """Render AI status widget with detailed diagnostics and fix options.""" st.markdown("### 🤖 AI Assistant Status") status = check_ai_availability_detailed(user_id) overall_status = status.get("overall_status", "unknown") # Overall status display if overall_status == "available": st.success("✅ AI Assistant is fully available!") elif overall_status == "partial": st.warning("⚠️ AI Assistant is partially available") elif overall_status == "unavailable": st.error("❌ AI Assistant is unavailable") elif overall_status == "not_configured": st.warning("⚠️ AI Assistant needs configuration") elif overall_status == "needs_indexing": st.info("ℹ️ AI Assistant needs initial indexing") elif overall_status == "empty_database": st.warning("⚠️ AI Assistant has no documents to search") elif overall_status == "checking": st.info("🔄 Checking AI Assistant status...") elif overall_status == "error": error_msg = status.get('error', 'Unknown error') st.error(f"❌ AI Assistant error: {error_msg}") else: st.warning(f"⚠️ Unknown AI status: {overall_status}") if 'error' in status: st.error(f"Details: {status.get('error', 'No details available')}") def initialize_rag_system(): """Initialize RAG system using service.""" current_user_id = getattr(st.session_state, 'current_user_id', 1) try: if not check_rag_service(): st.error("❌ RAG service is not running. Please start: `python start_rag_service.py`") st.session_state.rag_system_status = "service_unavailable" return False with st.spinner("🤖 Initializing AI Assistant..."): # Get user status status = rag_client.get_user_status(current_user_id) if status.get("status") == "not_indexed": st.info("🔄 Creating search index from your diary entries...") index_result = rag_client.index_user_data(current_user_id, clear_existing=True) if index_result.get("status") == "success": st.success(f"✅ Indexed {index_result.get('documents_processed', 0)} documents") st.session_state.rag_system_status = "initialized" return True else: st.error(f"❌ Indexing failed: {index_result.get('error', 'Unknown error')}") st.session_state.rag_system_status = "error" return False elif status.get("status") == "ready": st.success(f"✅ AI Assistant ready with {status.get('document_count', 0)} documents!") st.session_state.rag_system_status = "initialized" return True elif status.get("status") == "error": st.error(f"❌ RAG system error: {status.get('error', 'Unknown error')}") st.session_state.rag_system_status = "error" return False except Exception as e: st.error(f"❌ Cannot initialize AI Assistant: {str(e)}") st.session_state.rag_system_status = "error" return False def response_generator(user_query: str) -> Generator[str, None, None]: """Generate responses using RAG service.""" try: current_user_id = getattr(st.session_state, 'current_user_id', 1) if not check_rag_service(): response = "❌ RAG service is not available. Please start the service first." else: # Query RAG service chat_history = st.session_state.get('messages', []) fast_mode = st.session_state.get('fast_mode', False) result = rag_client.query_rag( user_id=current_user_id, query=user_query, fast_mode=fast_mode, chat_history=chat_history ) if result.get("status") == "error": response = f"❌ Error: {result.get('error', 'Unknown error')}" else: response = result.get("response", "No response generated") # Show processing time in sidebar processing_time = result.get("processing_time", 0) st.sidebar.success(f"✅ Response time: {processing_time:.2f}s") except Exception as e: response = f"❌ Error: {str(e)}" # Stream response words = response.split() delay = 0.01 if st.session_state.get('fast_mode', False) else 0.03 for word in words: yield word + " " time.sleep(delay) def run_auto_sync(user_id: int) -> bool: """Auto sync using RAG service after saving new entry.""" try: if not check_rag_service(): st.warning("⚠️ RAG service not available - entry saved but not indexed") return False # Use the new auto-index endpoint result = rag_client.auto_index_new_entry(user_id) status = result.get("status") if status == "initial_index_created": documents_processed = result.get('documents_processed', 0) st.success(f"✅ Created search index with {documents_processed} documents!") return True elif status == "incremental_update_success": documents_added = result.get('documents_added', 0) if documents_added > 0: st.success(f"🔄 Updated search index (+{documents_added} documents)") else: st.info("ℹ️ Search index is up to date") return True elif status == "full_rebuild_success": documents_processed = result.get('documents_processed', 0) st.success(f"🔄 Rebuilt search index with {documents_processed} documents") return True elif status == "skipped": reason = result.get('reason', 'Unknown reason') st.info(f"ℹ️ Indexing skipped: {reason}") return False elif status == "failed": error = result.get('error', 'Unknown error') st.warning(f"⚠️ Indexing failed: {error}") return False elif status == "error": error = result.get('error', 'Unknown error') st.error(f"❌ Indexing error: {error}") return False else: st.warning(f"⚠️ Unknown indexing status: {status}") return False except Exception as e: st.error(f"❌ Auto-sync error: {e}") return False def initialize_session_state() -> None: """Initialize session state variables.""" if "messages" not in st.session_state: st.session_state.messages = [] if "diary_entries" not in st.session_state: user_id = getattr(st.session_state, 'current_user_id', 1) try: st.session_state.diary_entries = load_entries_from_database(user_id) except Exception as e: st.error(f"Error loading diary entries: {e}") st.session_state.diary_entries = [] if "show_form" not in st.session_state: st.session_state.show_form = False if "rag_system" not in st.session_state: st.session_state.rag_system = None st.session_state.rag_system_status = "not_initialized" if RAG_AVAILABLE and os.getenv("GOOGLE_API_KEY"): st.session_state.rag_system_status = "ready_to_initialize" def display_chat_history() -> None: """Display chat history.""" for message in st.session_state.messages: with st.chat_message(message["role"]): st.markdown(message["content"]) def handle_chat_input() -> None: """Handle new chat input.""" if prompt := st.chat_input("Ask me about your diary..."): st.session_state.messages.append({"role": "user", "content": prompt}) with st.chat_message("user"): st.markdown(prompt) with st.chat_message("assistant"): response = st.write_stream(response_generator(prompt)) st.session_state.messages.append({"role": "assistant", "content": response}) def handle_entry_action(prompt): """Handle entry action prompts - generate full AI response.""" # Add user message st.session_state.messages.append({"role": "user", "content": prompt}) # Generate AI response immediately try: response = "" current_user_id = getattr(st.session_state, 'current_user_id', 1) if not check_rag_service(): response = "❌ RAG service is not available. Please start the service first." else: # Query RAG service chat_history = st.session_state.get('messages', [])[:-1] # Exclude the current message fast_mode = st.session_state.get('fast_mode', False) result = rag_client.query_rag( user_id=current_user_id, query=prompt, fast_mode=fast_mode, chat_history=chat_history ) if result.get("status") == "error": response = f"❌ Error: {result.get('error', 'Unknown error')}" else: response = result.get("response", "No response generated") # Add AI response to messages st.session_state.messages.append({"role": "assistant", "content": response}) except Exception as e: response = f"❌ Error generating response: {str(e)}" st.session_state.messages.append({"role": "assistant", "content": response}) # Close the menu and rerun to show the conversation st.session_state.show_entry_actions = False st.rerun() def check_and_sync_entries(): """Check and sync entries with RAG system.""" current_user_id = getattr(st.session_state, 'current_user_id', 1) try: if not check_rag_service(): st.sidebar.error("❌ RAG service offline") return with st.sidebar.spinner("🔄 Checking sync status..."): # Get current status status = rag_client.get_user_status(current_user_id) doc_count = status.get("document_count", 0) # Count actual diary entries actual_count = len(st.session_state.diary_entries) if doc_count != actual_count: st.sidebar.warning(f"⚠️ Sync issue: {doc_count} indexed vs {actual_count} entries") if st.sidebar.button("🔄 Fix Sync", key="fix_sync_btn"): with st.sidebar.spinner("🔄 Re-syncing..."): result = rag_client.index_user_data(current_user_id, clear_existing=True) if result.get("status") == "success": st.sidebar.success(f"✅ Synced {result.get('documents_processed', 0)} documents") else: st.sidebar.error("❌ Sync failed") else: st.sidebar.success(f"✅ Sync OK: {doc_count} documents") except Exception as e: st.sidebar.error(f"❌ Sync check error: {str(e)}") def render_sidebar() -> str: """Render sidebar with diary list and controls.""" st.sidebar.header("📖 Diary List") # Tag filter all_tags = set() for entry in st.session_state.diary_entries: entry_tags = entry.get('tags', '') if entry_tags: tags = [tag.strip() for tag in entry_tags.split(',') if tag.strip()] all_tags.update(tags) selected_tag_filter = "All" if all_tags: selected_tag_filter = st.sidebar.selectbox( "Filter by tag:", options=["All"] + sorted(list(all_tags)), key="tag_filter" ) # Filter entries filtered_entries = st.session_state.diary_entries if selected_tag_filter != "All": filtered_entries = [ entry for entry in st.session_state.diary_entries if selected_tag_filter in entry.get('tags', '').split(',') ] st.sidebar.markdown("---") # Add entry button - Always show this if st.sidebar.button("➕ Add New Entry"): st.session_state.show_form = not st.session_state.show_form st.rerun() # Show entry list only if there are entries if not filtered_entries: st.sidebar.warning("No entries found.") selected = None else: # Create entry options diary_options = [] for entry in filtered_entries: option_str = f"{entry.get('date', 'Unknown')} - {extract_title_from_content(entry.get('content', ''))}" diary_options.append(option_str) selected = st.sidebar.radio("Select Entry:", options=diary_options) # Enhanced Entry Actions Menu if st.sidebar.button("➕ Entry Actions", key="entry_actions_btn"): st.session_state.show_entry_actions = not st.session_state.get('show_entry_actions', False) st.rerun() # Show entry actions menu if toggled if st.session_state.get('show_entry_actions', False): with st.sidebar.expander("🎯 Smart Actions", expanded=True): st.markdown("**Essential AI Functions:**") # Row 1 col1, col2 = st.sidebar.columns(2) with col1: if st.button("🎯 Extract Key Points", use_container_width=True, key="extract_btn"): handle_entry_action("Summarize and extract the main key points from my diary entries. Focus on important decisions, lessons learned, significant events, and actionable insights.") if st.button("⚡ Next Actions", use_container_width=True, key="next_actions_btn"): handle_entry_action("Suggest concrete next actions and steps I should take based on my historical data, current goals, and diary patterns. What should I focus on this week?") if st.button("🎯 Goal Tracker", use_container_width=True, key="goals_btn"): handle_entry_action("Track my goals and objectives mentioned in diary entries. Analyze progress, identify stuck areas, and suggest ways to accelerate achievement.") with col2: if st.button("� Get Insights", use_container_width=True, key="insights_btn"): handle_entry_action("Analyze my diary data and provide deep insights about my behavior patterns, productivity cycles, emotional states, and areas for improvement.") if st.button("� Strategy Plan", use_container_width=True, key="strategy_btn"): handle_entry_action("Propose strategic plans and approaches based on the learned patterns from my diary. Help me create actionable strategies for achieving my goals.") if st.button("⏰ Deadline Alert", use_container_width=True, key="deadline_btn"): handle_entry_action("Review my diary for any mentioned deadlines, important dates, or time-sensitive tasks. Create alerts and reminders for upcoming important events.") # Close menu button if st.button("❌ Close Menu", use_container_width=True, key="close_entry_actions"): st.session_state.show_entry_actions = False st.rerun() # AI Status st.sidebar.markdown("---") st.sidebar.subheader("🤖 AI Status") # Check RAG service status service_running = check_rag_service() rag_status = st.session_state.get('rag_system_status', 'not_initialized') if not service_running: st.sidebar.error("❌ RAG Service Offline") st.sidebar.text("Start with: python start_rag_service.py") elif rag_status == "initialized": st.sidebar.success("✅ AI Active") if rag_client: current_user_id = getattr(st.session_state, 'current_user_id', 1) status = rag_client.get_user_status(current_user_id) if status.get("document_count"): st.sidebar.metric("Documents", status.get("document_count", 0)) # Fast mode toggle fast_mode = st.sidebar.checkbox( "Fast Mode", value=st.session_state.get('fast_mode', False) ) st.session_state.fast_mode = fast_mode elif rag_status == "ready_to_initialize": st.sidebar.info("🔄 AI Ready") if st.sidebar.button("🚀 Initialize AI"): initialize_rag_system() st.rerun() else: st.sidebar.warning("⚠️ AI Unavailable") if service_running and st.sidebar.button("🔄 Retry Initialize"): st.session_state.rag_system_status = "ready_to_initialize" st.rerun() # Detailed AI Diagnostics st.sidebar.markdown("---") current_user_id = getattr(st.session_state, 'current_user_id', 1) with st.sidebar.expander("🔍 Detailed Diagnostics"): if service_running and rag_client: try: status = check_ai_availability_detailed(current_user_id) overall_status = status.get("overall_status", "unknown") if "checks" in status: details = status["checks"] st.markdown("**Core Components:**") # RAG Modules rag_status = details.get("rag_modules", {}) if rag_status.get("available"): st.markdown("✅ RAG modules loaded") else: st.markdown("❌ RAG modules: Not available") # Google API Key api_status = details.get("google_api_key", {}) if api_status.get("configured"): st.markdown("✅ Google API key configured") else: st.markdown("❌ Google API: Not configured") st.markdown("**User Data:**") # Vector Database vector_status = details.get("vector_database", {}) if vector_status.get("exists"): st.markdown("✅ Vector database ready") else: st.markdown("❌ Vector DB: Not found") # Document Count doc_status = details.get("document_count", {}) count = doc_status.get("count", 0) if count > 0: st.markdown(f"✅ {count} documents indexed") else: st.markdown("❌ No documents indexed") # Issues and fixes issues = status.get("issues", []) if issues: st.markdown("**Issues Found:**") for issue in issues: st.markdown(f"⚠️ {issue}") fixes = status.get("suggested_fixes", []) if fixes: st.markdown("**Suggested Actions:**") for fix in fixes: st.markdown(f"🔧 {fix}") # Auto-fix button if st.button("🔧 Attempt Auto-Fix", type="primary", key="sidebar_autofix"): with st.spinner("Fixing AI availability issues..."): fix_result = fix_ai_availability(current_user_id) if fix_result.get("status") == "success": st.success("✅ AI availability issues fixed!") if fix_result.get("actions_taken"): st.info("Actions taken: " + ", ".join(fix_result["actions_taken"])) st.rerun() else: st.error(f"❌ Fix failed: {fix_result.get('error', 'Unknown error')}") else: st.warning("❌ Could not get detailed status") except Exception as e: st.error(f"❌ Diagnostics error: {str(e)}") else: st.warning("❌ RAG service not available") return selected def display_selected_diary_entry(selected: str) -> None: """Display selected diary entry.""" for entry in st.session_state.diary_entries: entry_identifier = f"{entry.get('date', 'Unknown')} - {extract_title_from_content(entry.get('content', ''))}" if entry_identifier == selected: # Header with delete button col1, col2 = st.columns([4, 1]) with col1: st.header(f"📝 {entry.get('date', 'Unknown')} - {extract_title_from_content(entry.get('content', ''))}") with col2: if st.button("🗑️ Delete", key=f"delete_{entry.get('id')}", type="secondary"): st.session_state.show_delete_confirm = entry.get('id') st.rerun() # Display tags entry_tags = entry.get('tags', '') if entry_tags: tag_list = [tag.strip() for tag in entry_tags.split(',') if tag.strip()] if tag_list: st.markdown("**Tags:**") st.markdown(render_tags(tag_list), unsafe_allow_html=True) # Display content st.markdown("---") st.write(extract_content_from_entry(entry.get('content', ''))) # Handle deletion if (hasattr(st.session_state, 'show_delete_confirm') and st.session_state.show_delete_confirm == entry.get('id')): st.markdown("---") st.warning("⚠️ **Confirm Deletion**") st.write(f"Delete: **{extract_title_from_content(entry.get('content', ''))}**?") col1, col2 = st.columns(2) with col1: if st.button("✅ Yes, Delete", type="primary"): user_id = getattr(st.session_state, 'current_user_id', 1) with st.spinner("🗑️ Deleting entry and rebuilding search index..."): # Step 1: Delete the diary entry from database success = delete_diary_entry(entry.get('id'), user_id) if success: # Step 2: Delete vector database to ensure clean rebuild if rag_client and check_rag_service(): try: st.info("🔄 Clearing vector database...") delete_result = rag_client.delete_vector_db(user_id) if delete_result.get("status") == "success": st.info("✅ Vector database cleared successfully") else: st.warning(f"⚠️ Vector DB deletion warning: {delete_result.get('error', 'Unknown')}") except Exception as e: st.warning(f"⚠️ Could not clear vector database: {str(e)}") # Step 3: Full re-indexing of all remaining documents st.info("🔄 Rebuilding search index from all remaining entries...") try: index_result = rag_client.index_user_data(user_id, clear_existing=True) if index_result.get("status") == "success": docs_count = index_result.get('documents_processed', 0) st.success(f"✅ Search index rebuilt with {docs_count} documents") else: st.warning(f"⚠️ Re-indexing failed: {index_result.get('error', 'Unknown error')}") except Exception as e: st.error(f"❌ Re-indexing error: {str(e)}") else: st.warning("⚠️ RAG service not available - entry deleted but search index not updated") # Step 4: Refresh UI st.session_state.diary_entries = load_entries_from_database(user_id) del st.session_state.show_delete_confirm st.success("✅ Entry deleted and search index rebuilt!") st.rerun() else: st.error("❌ Failed to delete diary entry") with col2: if st.button("❌ Cancel"): del st.session_state.show_delete_confirm st.rerun() break def render_diary_entry_form() -> None: """Render diary entry form.""" st.header("✍️ Add New Diary Entry") st.markdown("---") date = st.date_input("📅 Date", value=datetime.now().date()) title = st.text_input("📌 Title", placeholder="Enter title...") audio = st.audio_input("Record your audio") # Prevent infinite rerun loop by using a flag if audio and not st.session_state.get('voice_transcribed_content') and not st.session_state.get('audio_transcribed_once'): with open("./temp/recorded_audio.wav", "wb") as f: f.write(audio.getbuffer()) st.success("Audio recorded and saved successfully!") user_id = getattr(st.session_state, 'current_user_id', 1) with st.spinner("🔄 Transcribing audio..."): transcribed_text = transcribe_audio_with_gemini_live(audio.getbuffer(), user_id) if transcribed_text and not transcribed_text.startswith("❌") and not transcribed_text.startswith("⚠️"): st.session_state.voice_transcribed_content = transcribed_text st.session_state.audio_transcribed_once = True st.success("✅ Voice transcribed successfully!") st.rerun() else: st.session_state.audio_transcribed_once = True st.error(transcribed_text or "Failed to transcribe audio") # Reset the flag if no audio is present if not audio and st.session_state.get('audio_transcribed_once'): st.session_state.audio_transcribed_once = False # Content textarea - use transcribed content if available content_value = st.session_state.get('voice_transcribed_content', '') if not content_value: content_value = st.session_state.get('current_content', '') content = st.text_area( "📖 Content", value=content_value, placeholder="Write your diary entry... Use #tags! Or use voice input above.", height=150, key="diary_content_input" ) # Clear transcribed content after user sees it if 'voice_transcribed_content' in st.session_state: del st.session_state.voice_transcribed_content # Also reset the transcribed_once flag so next audio triggers transcription st.session_state.audio_transcribed_once = False # Tags st.markdown("### 🏷️ Tags") tags_input = st.text_input( "Tags (comma-separated)", placeholder="work, travel, family" ) # Combine manual and auto tags manual_tags = parse_tags_input(tags_input) auto_tags = extract_tags_from_content(content) if content else [] all_tags = list(set(manual_tags + auto_tags)) # Show preview of all tags if all_tags: st.markdown("**Tags Preview:**") st.markdown(render_tags(all_tags), unsafe_allow_html=True) # Action buttons col1, col2 = st.columns(2) with col1: if st.button("💾 Save Entry", type="primary"): if title and content: user_id = getattr(st.session_state, 'current_user_id', 1) # Format content with title formatted_content = f"Title: {title}\nContent: {content}" tags_str = ','.join(all_tags) if all_tags else '' try: # Tạo entry dictionary theo format mà function cần entry = { "date": date.strftime('%Y-%m-%d'), "content": formatted_content, "tags": tags_str } # Call function với đúng format success = submit_text_to_database(entry=entry, user_id=user_id) if success: # Auto-sync after adding run_auto_sync(user_id) # Refresh entries st.session_state.diary_entries = load_entries_from_database(user_id) st.session_state.show_form = False # Clear any remaining voice content if 'voice_transcribed_content' in st.session_state: del st.session_state.voice_transcribed_content st.success("✅ Diary entry saved successfully!") st.rerun() else: st.error("❌ Failed to save diary entry.") except Exception as e: st.error(f"❌ Error saving entry: {str(e)}") else: st.warning("⚠️ Please fill in both title and content.") with col2: if st.button("❌ Cancel"): st.session_state.show_form = False # Clear any voice content if 'voice_transcribed_content' in st.session_state: del st.session_state.voice_transcribed_content st.rerun() # ======================================== # MAIN APPLICATION # ======================================== def main() -> None: """Main application function.""" # Initialize authentication auth_ui = AuthUI() # Check if user is authenticated if not auth_ui.check_authentication(): auth_ui.render_auth_page() return # Get current user info try: current_user_id = auth_ui.get_current_user_id() current_username = auth_ui.get_current_username() if current_user_id is None: current_user_id = 1 if current_username is None: current_username = "User" except Exception as e: st.error(f"❌ Error getting user info: {str(e)}") current_user_id = 1 current_username = "User" # Check if user changed - reset RAG system for data isolation if hasattr(st.session_state, 'current_user_id') and st.session_state.current_user_id != current_user_id: st.session_state.rag_system = None st.session_state.rag_system_status = "ready_to_initialize" if os.getenv("GOOGLE_API_KEY") else "no_api_key" st.session_state.messages = [] st.session_state.diary_entries = [] st.warning(f"🔄 Switched to user {current_username}. RAG system reset for data isolation.") st.session_state.current_user_id = current_user_id st.session_state.current_username = current_username # App title st.title("🤖 Diary Chat Bot") st.markdown(f"*Welcome back, **{current_username}**! Your AI companion for managing diary entries*") # AI Status Widget if check_rag_service(): render_ai_status_widget(current_user_id) else: st.error("❌ **RAG Service is offline**") st.info("💡 Start the service with: `python start_rag_service.py`") st.markdown("---") # Initialize session state initialize_session_state() # Force reload diary entries for current user if not st.session_state.diary_entries: st.session_state.diary_entries = load_entries_from_database(current_user_id) # Initialize RAG system if ready if st.session_state.get('rag_system_status') == 'ready_to_initialize': initialize_rag_system() # Render sidebar and get selected entry auth_ui.render_user_profile() selected_entry = render_sidebar() # Display selected diary entry st.markdown("---") if st.session_state.diary_entries and selected_entry: display_selected_diary_entry(selected_entry) elif not st.session_state.diary_entries: st.info("📝 No diary entries found. Click '➕ Add New Entry' in the sidebar to get started!") else: st.info("📖 Select a diary entry from the sidebar to view its content.") # Chat section st.markdown("---") st.subheader("💬 Chat with your AI Assistant") display_chat_history() handle_chat_input() # Diary entry form if st.session_state.show_form: st.markdown("---") render_diary_entry_form() if __name__ == "__main__": main()