RFP_Analyzer_Agent_backup

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Update app.py

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# app.py

import streamlit as st
import os
from pathlib import Path
from typing import Dict, List, Optional, Any
from datetime import datetime
from threading import Lock
from dataclasses import dataclass
from langchain.text_splitter import RecursiveCharacterTextSplitter
from langchain.vectorstores import FAISS
from langchain_community.embeddings import HuggingFaceEmbeddings
from langchain_community.chat_models import ChatOpenAI
from langchain.prompts import ChatPromptTemplate, MessagesPlaceholder  # MessagesPlaceholder from here
from langchain_core.messages import HumanMessage, AIMessage, SystemMessage  # Remove MessagesPlaceholder from here
from langchain.chains import ConversationalRetrievalChain
from langchain_core.runnables import RunnablePassthrough
from langchain.memory import ConversationBufferMemory

from utils.database import (
    # Base database operations
    create_connection,
    create_tables,
    get_all_documents,
    force_recreate_collections_tables,
    
    # Collection operations
    get_collections,
    create_collection,
    add_document_to_collection,
    remove_from_collection,
    update_collection,
    get_collection_documents,
    handle_document_upload,
    verify_database_tables,
    initialize_qa_system,
    get_embeddings_model,
    # Search functionality
    search_documents
)

# Component imports
from components.chat import display_chat_interface
from components.collection_manager import (
    display_enhanced_collections,
    show_collection_creation_dialog
)

# Optional analytics import if you're using it
from utils.analytics import display_analytics_dashboard

from components.chat import display_chat_interface
from components.document_store import display_documents_tab

# Create locks for thread-safe operations
conn_lock = Lock()
if not os.path.exists('/data'):
    try:
        from setup import setup_directories
        if not setup_directories():
            raise Exception("Failed to set up directories")
    except Exception as e:
        st.error(f"Setup error: {e}")
        st.stop()
        
def handle_chat_state_change():
    """Handle changes in chat state when switching tabs or collections."""
    if st.session_state.get('chat_ready'):
        # Check if we need to reinitialize with new documents
        if st.session_state.get('reinitialize_chat'):
            initialize_chat_from_collection()
            st.session_state.reinitialize_chat = False
            
def verify_database_tables(conn):
    """Verify that all required tables exist."""
    try:
        cursor = conn.cursor()
        # Get list of all tables
        cursor.execute("SELECT name FROM sqlite_master WHERE type='table'")
        tables = [table[0] for table in cursor.fetchall()]
        
        # Check for required tables
        required_tables = {
            'documents', 'queries', 'annotations', 
            'collections', 'document_collections', 'chats', 'chat_messages'
        }
        
        missing_tables = required_tables - set(tables)
        
        # If collections table doesn't exist, force recreate it
        if 'collections' not in tables:
            if force_recreate_collections_tables(conn):
                st.session_state.show_debug = True
            else:
                st.error("Failed to create required database tables.")
                return False
            
        return True
            
    except Exception as e:
        st.error(f"Error verifying database tables: {e}")
        return False

def initialize_database():
    """Initialize database with persistent storage."""
    try:
        if 'db_conn' not in st.session_state:
            # Get storage path
            if os.path.exists('/data'):
                base_path = Path('/data')
            else:
                base_path = Path(os.getcwd()) / 'data'
                
            # Ensure data directory exists
            base_path.mkdir(parents=True, exist_ok=True)
            
            # Create database path
            db_path = base_path / 'rfp_analysis.db'
            
            try:
                # Ensure file can be created
                db_path.touch(exist_ok=True)
            except Exception as e:
                st.error(f"Failed to create database file: {e}")
                return False
            
            # Create connection
            conn = create_connection(str(db_path))
            if conn is not None:
                # Create all tables (includes collection tables)
                create_tables(conn)
                st.session_state.db_conn = conn
                
                # Verify tables were created
                verify_database_tables(conn)
                return True
            else:
                return False
        else:
            # Verify tables exist in existing connection
            verify_database_tables(st.session_state.db_conn)
            return True

    except Exception as e:
        st.error(f"Database initialization error: {e}")
        return False

@dataclass
class SessionStateDefaults:
    """Default values for session state variables."""
    # Collection Management
    show_collection_dialog: bool = False
    selected_collection: Optional[Dict] = None
    current_collection: Optional[Dict] = None
    
    # Chat System
    chat_ready: bool = False
    messages: Optional[List] = None  # Changed from list[BaseMessage]
    current_chat_id: Optional[int] = None
    
    # Document Processing
    vector_store: Optional[Any] = None
    qa_system: Optional[Any] = None
    
    # State Management
    reinitialize_chat: bool = False
    debug_mode: bool = False

def initialize_session_state() -> None:
    """
    Initialize all session state variables with proper typing and documentation.
    """
    defaults = SessionStateDefaults()
    
    # Dictionary mapping state variables to their descriptions
    state_vars: Dict[str, Dict[str, Any]] = {
        'show_collection_dialog': {
            'default': defaults.show_collection_dialog,
            'desc': 'Controls visibility of collection creation dialog'
        },
        'selected_collection': {
            'default': defaults.selected_collection,
            'desc': 'Currently selected collection for viewing/editing'
        },
        'current_collection': {
            'default': defaults.current_collection,
            'desc': 'Active collection for chat/analysis'
        },
        'chat_ready': {
            'default': defaults.chat_ready,
            'desc': 'Indicates if chat system is initialized and ready'
        },
        'messages': {
            'default': [] if defaults.messages is None else defaults.messages,
            'desc': 'List of chat messages in the current session'
        },
        'current_chat_id': {
            'default': defaults.current_chat_id,
            'desc': 'ID of the current chat session'
        },
        'vector_store': {
            'default': defaults.vector_store,
            'desc': 'FAISS vector store for document embeddings'
        },
        'qa_system': {
            'default': defaults.qa_system,
            'desc': 'Initialized QA system for chat'
        },
        'reinitialize_chat': {
            'default': defaults.reinitialize_chat,
            'desc': 'Flag to trigger chat system reinitialization'
        },
        'debug_mode': {
            'default': defaults.debug_mode,
            'desc': 'Enable/disable debug information'
        }
    }
    
    # Initialize each state variable if not already present
    for var_name, config in state_vars.items():
        if var_name not in st.session_state:
            st.session_state[var_name] = config['default']

def reset_chat_state() -> None:
    """Reset chat-related session state variables to defaults."""
    st.session_state.messages = []
    st.session_state.current_chat_id = None
    st.session_state.chat_ready = False
    st.session_state.qa_system = None

def reset_collection_state() -> None:
    """Reset collection-related session state variables to defaults."""
    st.session_state.selected_collection = None
    st.session_state.current_collection = None
    st.session_state.show_collection_dialog = False

def get_current_state() -> Dict[str, Any]:
    """
    Get the current state of all session variables.
    Useful for debugging and state management.
    """
    return {
        key: value for key, value in st.session_state.items()
        if not key.startswith('_')  # Exclude internal Streamlit states
    }

def display_top_bar():
    """Display the application's top navigation bar."""
    col1, col2, col3 = st.columns([1, 3, 1])
    
    with col1:
        if os.path.exists("img/logo.png"):
            st.image("img/logo.png", width=100)
        else:
            st.warning("Logo not found at img/logo.png")
    
    with col2:
        st.title("Synaptyx.AI - RFP Analysis Agent")
    
    with col3:
        if st.session_state.current_collection:
            st.info(f"📁 Active Collection: {st.session_state.current_collection['name']}")

def initialize_chat_from_existing():
    """Initialize chat system from existing documents in database."""
    if not st.session_state.get('chat_ready'):
        try:
            documents = get_all_documents(st.session_state.db_conn)
            if documents:
                # Initialize vector store and QA system with existing documents
                embeddings = get_embeddings_model()
                chunks = []
                for doc in documents:
                    doc_chunks = text_splitter.split_text(doc['content'])
                    for chunk in doc_chunks:
                        chunks.append({
                            'content': chunk,
                            'metadata': {'source': doc['name'], 'document_id': doc['id']}
                        })
                
                vector_store = FAISS.from_texts(
                    [chunk['content'] for chunk in chunks],
                    embeddings,
                    [chunk['metadata'] for chunk in chunks]
                )
                
                st.session_state.vector_store = vector_store
                st.session_state.qa_system = initialize_qa_system(vector_store)
                st.session_state.chat_ready = True
                return True
        except Exception as e:
            st.error(f"Error initializing chat: {e}")
    return False

def initialize_chat_from_collection():
    """Initialize chat system with vector store reuse."""
    try:
        documents = None
        if st.session_state.get('current_collection'):
            documents = get_collection_documents(st.session_state.db_conn, 
                                              st.session_state.current_collection['id'])
        else:
            documents = get_all_documents(st.session_state.db_conn)

        if documents:
            document_ids = [doc['id'] for doc in documents]
            
            # Check for existing vector store
            vector_store = get_existing_vector_store(document_ids)
            
            if vector_store:
                # Reuse existing vector store
                st.session_state.vector_store = vector_store
                st.session_state.qa_system = initialize_qa_system(vector_store)
                return True
            
            # If no existing vector store, create new one
            with st.spinner("Initializing chat system..."):
                embeddings = get_embeddings_model()
                text_splitter = RecursiveCharacterTextSplitter(
                    chunk_size=500,
                    chunk_overlap=50,
                    length_function=len,
                    separators=["\n\n", "\n", " ", ""]
                )
                
                chunks = []
                for doc in documents:
                    doc_chunks = text_splitter.split_text(doc['content'])
                    for chunk in doc_chunks:
                        chunks.append({
                            'content': chunk,
                            'metadata': {'source': doc['name'], 'document_id': doc['id']}
                        })
                
                vector_store = FAISS.from_texts(
                    [chunk['content'] for chunk in chunks],
                    embeddings,
                    [chunk['metadata'] for chunk in chunks]
                )
                
                st.session_state.vector_store = vector_store
                st.session_state.qa_system = initialize_qa_system(vector_store)
                return True
                
        return False
        
    except Exception as e:
        st.error(f"Error initializing chat: {e}")
        return False

def display_collection_sidebar():
    """Display enhanced sidebar with collection management."""
    with st.sidebar:
        st.title("💬 Chat Controls")
        
        if st.button("🔄 Start New Chat", use_container_width=True):
            st.session_state.messages = []
            st.session_state.current_chat_id = None
            if st.session_state.chat_ready:
                st.rerun()
        
        st.divider()
        
        # Collection Management
        st.title("📚 Collections")
        collections = get_collections(st.session_state.db_conn)
        
        if st.button("➕ Create Collection", use_container_width=True):
            st.session_state.show_collection_dialog = True
        
        # Collection selection with document preview
        if collections:
            selected = st.selectbox(
                "Select Collection",
                options=["All Documents"] + [c['name'] for c in collections],
                key="collection_select"
            )
            
            if selected != "All Documents":
                collection = next((c for c in collections if c['name'] == selected), None)
                if collection:
                    documents = get_collection_documents(st.session_state.db_conn, collection['id'])
                    if documents:
                        st.markdown("### Documents in Collection")
                        for doc in documents:
                            with st.expander(f"📄 {doc['name']}", expanded=False):
                                st.caption(f"Uploaded: {doc['upload_date']}")
                                if st.button("Use for Chat", key=f"use_{doc['id']}"):
                                    initialize_chat_for_document(doc['id'])

def display_collection_dialog():
    """Display the create collection dialog."""
    with st.sidebar:
        st.subheader("Create New Collection")
        name = st.text_input("Collection Name", key="sidebar_collection_name")
        description = st.text_area("Description", key="sidebar_collection_desc")
        
        col1, col2 = st.columns(2)
        with col1:
            if st.button("Create", key="sidebar_create_btn"):
                if name:
                    if create_collection(st.session_state.db_conn, name, description):
                        st.success(f"Collection '{name}' created!")
                        st.session_state.show_collection_dialog = False
                        st.rerun()
                else:
                    st.error("Please enter a collection name")
        
        with col2:
            if st.button("Cancel", key="sidebar_cancel_btn"):
                st.session_state.show_collection_dialog = False
                st.rerun()

def display_welcome_screen():
    """Display the welcome screen with getting started information and enhanced features."""
    st.title("🤖 Welcome to SYNAPTYX")
    st.markdown("### Your AI-powered RFP Analysis Assistant")
    
    # Check for existing documents
    documents = get_all_documents(st.session_state.db_conn)
    collections = get_collections(st.session_state.db_conn)
    
    col1, col2 = st.columns(2)
    with col1:
        st.markdown("""
        #### Getting Started:
        1. Upload your RFP documents using the sidebar
        2. Organize documents into collections
        3. Start analyzing with AI!
        
        You can:
        - Create multiple collections
        - Upload documents to specific collections
        - Search across all documents
        - Get AI-powered insights and summaries
        """)
        
        # Add action buttons if documents exist
        if documents:
            st.success(f"🎉 You have {len(documents)} documents ready for analysis!")
            col_a, col_b = st.columns(2)
            with col_a:
                if st.button("Start Chatting", use_container_width=True):
                    if initialize_chat_from_collection():
                        st.session_state.chat_ready = True
                        st.rerun()
            with col_b:
                if st.button("View Documents", use_container_width=True):
                    st.session_state.show_document_store = True
                    st.rerun()
    
    with col2:
        st.markdown("#### Example Questions:")
        examples = [
            "📊 Summarize the main points of the document",
            "📝 Draft a 'Why Us' section based on the document",
            "🎯 Extract key success metrics and outcomes",
            "💡 What are the innovative solutions mentioned?",
            "🤝 Analyze the partnership benefits described",
            "📈 Compare requirements across documents",
            "🔍 Find similar sections across RFPs"
        ]
        for example in examples:
            st.markdown(f"• {example}")
        
        # Add collection stats if they exist
        if collections:
            st.markdown("---")
            st.markdown("#### Your Collections:")
            for collection in collections[:3]:  # Show top 3 collections
                with st.container():
                    st.markdown(f"""
                    🗂️ **{collection['name']}**  
                    Documents: {collection['doc_count']}
                    """)
            if len(collections) > 3:
                st.caption("... and more collections")

def display_chat_area():
    """Display the main chat interface or welcome screen with proper state management."""
    if not st.session_state.chat_ready:
        display_welcome_screen()
    else:
        col1, col2 = st.columns([3, 1])
        with col1:
            display_chat_interface()
        with col2:
            # Document context panel
            st.markdown("### Current Context")
            if st.session_state.current_collection:
                st.info(f"📁 Using Collection: {st.session_state.current_collection['name']}")
            else:
                st.info("📚 Using All Documents")
            
            # Quick actions
            st.markdown("### Quick Actions")
            if st.button("🔄 New Chat", use_container_width=True):
                reset_chat_state()
                st.rerun()
            if st.button("📋 Export Chat", use_container_width=True):
                export_chat_history()
            
            # Example questions for quick reference
            with st.expander("💡 Question Examples", expanded=False):
                examples = [
                    "Summarize main points",
                    "Extract requirements",
                    "Compare solutions",
                    "Analyze pricing"
                ]
                for example in examples:
                    if st.button(example, key=f"example_{example}"):
                        # Set the example as the current question
                        st.session_state.current_question = example
                        st.rerun()

def export_chat_history():
    """Export current chat history."""
    if st.session_state.messages:
        chat_text = "\n\n".join([
            f"{'User' if isinstance(m, HumanMessage) else 'Assistant'}: {m.content}"
            for m in st.session_state.messages
        ])
        st.download_button(
            "Download Chat History",
            chat_text,
            file_name=f"chat_export_{datetime.now().strftime('%Y%m%d_%H%M%S')}.txt",
            mime="text/plain"
        )

def main():
    """Main application function."""
    # Page configuration
    st.set_page_config(
        layout="wide",
        page_title="SYNAPTYX - RFP Analysis Agent",
        initial_sidebar_state="expanded"
    )
    
    # Initialize database and session state
    if not initialize_database():
        st.error("Failed to initialize database. Please contact support.")
        return

    initialize_session_state()
    
    # Top bar with larger logo
    col1, col2, col3 = st.columns([1.5, 4, 1])
    with col1:
        if os.path.exists("img/logo.png"):
            st.image("img/logo.png", width=200)  # Increased logo size
        else:
            st.info("Logo not found")
    with col2:
        st.title("SYNAPTYX - RFP Analysis Agent")
    with col3:
        if st.session_state.current_collection:
            st.info(f"📁 Active Collection: {st.session_state.current_collection['name']}")
    
    # Sidebar
    with st.sidebar:
        # Chat Controls Section
        st.title("💬 Chat Controls")
        
        # New Chat button
        if st.button("🔄 Start New Chat", use_container_width=True):
            reset_chat_state()
            st.rerun()
        
        st.divider()
        
        # Document Manager Section
        st.title("📚 Document Manager")
        
        # Collection Creation Button
        if st.button("➕ Create New Collection", use_container_width=True):
            st.session_state.show_collection_dialog = True

        # Collection Selection
        collections = get_collections(st.session_state.db_conn)
        if collections:
            selected = st.selectbox(
                "Select Collection",
                options=["All Documents"] + [c['name'] for c in collections],
                key="collection_select"
            )
            
            if selected != "All Documents":
                collection = next((c for c in collections if c['name'] == selected), None)
                if collection:
                    st.session_state.current_collection = collection
                    display_collection_documents(collection['id'])
        
        # Upload Section
        st.header("Upload Documents")
        uploaded_files = st.file_uploader(
            "Upload PDF documents",
            type=['pdf'],
            accept_multiple_files=True,
            help="Limit 200MB per file • PDF"
        )

        if uploaded_files:
            handle_document_upload(uploaded_files, 
                                 collection_id=st.session_state.current_collection.get('id') if st.session_state.current_collection else None)
    
    # Show collection creation dialog if triggered
    if st.session_state.show_collection_dialog:
        show_collection_creation_dialog()
    
    # Main content area
    if st.session_state.chat_ready:
        display_chat_interface()
    else:
        display_welcome_screen()

    # Debug mode (if enabled)
    if st.session_state.debug_mode and st.sidebar.checkbox("Show Debug Info"):
        st.sidebar.write("Current State:", get_current_state())

def display_collection_documents(collection_id: int):
    """Display documents in the selected collection."""
    documents = get_collection_documents(st.session_state.db_conn, collection_id)
    if documents:
        st.markdown("### Documents in Collection")
        for doc in documents:
            with st.expander(f"📄 {doc['name']}", expanded=False):
                st.caption(f"Uploaded: {doc['upload_date']}")
                col1, col2 = st.columns(2)
                with col1:
                    if st.button("Preview", key=f"preview_{doc['id']}"):
                        st.text_area(
                            "Content Preview",
                            value=doc['content'][:500] + "..." if len(doc['content']) > 500 else doc['content'],
                            height=100,
                            disabled=True
                        )
                with col2:
                    if st.button("Use for Chat", key=f"chat_{doc['id']}"):
                        initialize_chat_from_collection()
                        st.rerun()

if __name__ == "__main__":
    main()

	# app.py

	import streamlit as st
	import os
	from pathlib import Path
	from typing import Dict, List, Optional, Any
	from datetime import datetime
	from threading import Lock
	from dataclasses import dataclass
	from langchain.text_splitter import RecursiveCharacterTextSplitter
	from langchain.vectorstores import FAISS
	from langchain_community.embeddings import HuggingFaceEmbeddings
	from langchain_community.chat_models import ChatOpenAI
	from langchain.prompts import ChatPromptTemplate, MessagesPlaceholder # MessagesPlaceholder from here
	from langchain_core.messages import HumanMessage, AIMessage, SystemMessage # Remove MessagesPlaceholder from here
	from langchain.chains import ConversationalRetrievalChain
	from langchain_core.runnables import RunnablePassthrough
	from langchain.memory import ConversationBufferMemory

	from utils.database import (
	# Base database operations
	create_connection,
	create_tables,
	get_all_documents,
	force_recreate_collections_tables,

	# Collection operations
	get_collections,
	create_collection,
	add_document_to_collection,
	remove_from_collection,
	update_collection,
	get_collection_documents,
	handle_document_upload,
	verify_database_tables,
	initialize_qa_system,
	get_embeddings_model,
	# Search functionality
	search_documents
	)

	# Component imports
	from components.chat import display_chat_interface
	from components.collection_manager import (
	display_enhanced_collections,
	show_collection_creation_dialog
	)

	# Optional analytics import if you're using it
	from utils.analytics import display_analytics_dashboard

	from components.chat import display_chat_interface
	from components.document_store import display_documents_tab

	# Create locks for thread-safe operations
	conn_lock = Lock()
	if not os.path.exists('/data'):
	try:
	from setup import setup_directories
	if not setup_directories():
	raise Exception("Failed to set up directories")
	except Exception as e:
	st.error(f"Setup error: {e}")
	st.stop()

	def handle_chat_state_change():
	"""Handle changes in chat state when switching tabs or collections."""
	if st.session_state.get('chat_ready'):
	# Check if we need to reinitialize with new documents
	if st.session_state.get('reinitialize_chat'):
	initialize_chat_from_collection()
	st.session_state.reinitialize_chat = False

	def verify_database_tables(conn):
	"""Verify that all required tables exist."""
	try:
	cursor = conn.cursor()
	# Get list of all tables
	cursor.execute("SELECT name FROM sqlite_master WHERE type='table'")
	tables = [table[0] for table in cursor.fetchall()]

	# Check for required tables
	required_tables = {
	'documents', 'queries', 'annotations',
	'collections', 'document_collections', 'chats', 'chat_messages'
	}

	missing_tables = required_tables - set(tables)

	# If collections table doesn't exist, force recreate it
	if 'collections' not in tables:
	if force_recreate_collections_tables(conn):
	st.session_state.show_debug = True
	else:
	st.error("Failed to create required database tables.")
	return False

	return True

	except Exception as e:
	st.error(f"Error verifying database tables: {e}")
	return False

	def initialize_database():
	"""Initialize database with persistent storage."""
	try:
	if 'db_conn' not in st.session_state:
	# Get storage path
	if os.path.exists('/data'):
	base_path = Path('/data')
	else:
	base_path = Path(os.getcwd()) / 'data'

	# Ensure data directory exists
	base_path.mkdir(parents=True, exist_ok=True)

	# Create database path
	db_path = base_path / 'rfp_analysis.db'

	try:
	# Ensure file can be created
	db_path.touch(exist_ok=True)
	except Exception as e:
	st.error(f"Failed to create database file: {e}")
	return False

	# Create connection
	conn = create_connection(str(db_path))
	if conn is not None:
	# Create all tables (includes collection tables)
	create_tables(conn)
	st.session_state.db_conn = conn

	# Verify tables were created
	verify_database_tables(conn)
	return True
	else:
	return False
	else:
	# Verify tables exist in existing connection
	verify_database_tables(st.session_state.db_conn)
	return True

	except Exception as e:
	st.error(f"Database initialization error: {e}")
	return False

	@dataclass
	class SessionStateDefaults:
	"""Default values for session state variables."""
	# Collection Management
	show_collection_dialog: bool = False
	selected_collection: Optional[Dict] = None
	current_collection: Optional[Dict] = None

	# Chat System
	chat_ready: bool = False
	messages: Optional[List] = None # Changed from list[BaseMessage]
	current_chat_id: Optional[int] = None

	# Document Processing
	vector_store: Optional[Any] = None
	qa_system: Optional[Any] = None

	# State Management
	reinitialize_chat: bool = False
	debug_mode: bool = False

	def initialize_session_state() -> None:
	"""
	Initialize all session state variables with proper typing and documentation.
	"""
	defaults = SessionStateDefaults()

	# Dictionary mapping state variables to their descriptions
	state_vars: Dict[str, Dict[str, Any]] = {
	'show_collection_dialog': {
	'default': defaults.show_collection_dialog,
	'desc': 'Controls visibility of collection creation dialog'
	},
	'selected_collection': {
	'default': defaults.selected_collection,
	'desc': 'Currently selected collection for viewing/editing'
	},
	'current_collection': {
	'default': defaults.current_collection,
	'desc': 'Active collection for chat/analysis'
	},
	'chat_ready': {
	'default': defaults.chat_ready,
	'desc': 'Indicates if chat system is initialized and ready'
	},
	'messages': {
	'default': [] if defaults.messages is None else defaults.messages,
	'desc': 'List of chat messages in the current session'
	},
	'current_chat_id': {
	'default': defaults.current_chat_id,
	'desc': 'ID of the current chat session'
	},
	'vector_store': {
	'default': defaults.vector_store,
	'desc': 'FAISS vector store for document embeddings'
	},
	'qa_system': {
	'default': defaults.qa_system,
	'desc': 'Initialized QA system for chat'
	},
	'reinitialize_chat': {
	'default': defaults.reinitialize_chat,
	'desc': 'Flag to trigger chat system reinitialization'
	},
	'debug_mode': {
	'default': defaults.debug_mode,
	'desc': 'Enable/disable debug information'
	}
	}

	# Initialize each state variable if not already present
	for var_name, config in state_vars.items():
	if var_name not in st.session_state:
	st.session_state[var_name] = config['default']

	def reset_chat_state() -> None:
	"""Reset chat-related session state variables to defaults."""
	st.session_state.messages = []
	st.session_state.current_chat_id = None
	st.session_state.chat_ready = False
	st.session_state.qa_system = None

	def reset_collection_state() -> None:
	"""Reset collection-related session state variables to defaults."""
	st.session_state.selected_collection = None
	st.session_state.current_collection = None
	st.session_state.show_collection_dialog = False

	def get_current_state() -> Dict[str, Any]:
	"""
	Get the current state of all session variables.
	Useful for debugging and state management.
	"""
	return {
	key: value for key, value in st.session_state.items()
	if not key.startswith('_') # Exclude internal Streamlit states
	}

	def display_top_bar():
	"""Display the application's top navigation bar."""
	col1, col2, col3 = st.columns([1, 3, 1])

	with col1:
	if os.path.exists("img/logo.png"):
	st.image("img/logo.png", width=100)
	else:
	st.warning("Logo not found at img/logo.png")

	with col2:
	st.title("Synaptyx.AI - RFP Analysis Agent")

	with col3:
	if st.session_state.current_collection:
	st.info(f"📁 Active Collection: {st.session_state.current_collection['name']}")

	def initialize_chat_from_existing():
	"""Initialize chat system from existing documents in database."""
	if not st.session_state.get('chat_ready'):
	try:
	documents = get_all_documents(st.session_state.db_conn)
	if documents:
	# Initialize vector store and QA system with existing documents
	embeddings = get_embeddings_model()
	chunks = []
	for doc in documents:
	doc_chunks = text_splitter.split_text(doc['content'])
	for chunk in doc_chunks:
	chunks.append({
	'content': chunk,
	'metadata': {'source': doc['name'], 'document_id': doc['id']}
	})

	vector_store = FAISS.from_texts(
	[chunk['content'] for chunk in chunks],
	embeddings,
	[chunk['metadata'] for chunk in chunks]
	)

	st.session_state.vector_store = vector_store
	st.session_state.qa_system = initialize_qa_system(vector_store)
	st.session_state.chat_ready = True
	return True
	except Exception as e:
	st.error(f"Error initializing chat: {e}")
	return False

	def initialize_chat_from_collection():
	"""Initialize chat system with vector store reuse."""
	try:
	documents = None
	if st.session_state.get('current_collection'):
	documents = get_collection_documents(st.session_state.db_conn,
	st.session_state.current_collection['id'])
	else:
	documents = get_all_documents(st.session_state.db_conn)

	if documents:
	document_ids = [doc['id'] for doc in documents]

	# Check for existing vector store
	vector_store = get_existing_vector_store(document_ids)

	if vector_store:
	# Reuse existing vector store
	st.session_state.vector_store = vector_store
	st.session_state.qa_system = initialize_qa_system(vector_store)
	return True

	# If no existing vector store, create new one
	with st.spinner("Initializing chat system..."):
	embeddings = get_embeddings_model()
	text_splitter = RecursiveCharacterTextSplitter(
	chunk_size=500,
	chunk_overlap=50,
	length_function=len,
	separators=["\n\n", "\n", " ", ""]
	)

	chunks = []
	for doc in documents:
	doc_chunks = text_splitter.split_text(doc['content'])
	for chunk in doc_chunks:
	chunks.append({
	'content': chunk,
	'metadata': {'source': doc['name'], 'document_id': doc['id']}
	})

	vector_store = FAISS.from_texts(
	[chunk['content'] for chunk in chunks],
	embeddings,
	[chunk['metadata'] for chunk in chunks]
	)

	st.session_state.vector_store = vector_store
	st.session_state.qa_system = initialize_qa_system(vector_store)
	return True

	return False

	except Exception as e:
	st.error(f"Error initializing chat: {e}")
	return False

	def display_collection_sidebar():
	"""Display enhanced sidebar with collection management."""
	with st.sidebar:
	st.title("💬 Chat Controls")

	if st.button("🔄 Start New Chat", use_container_width=True):
	st.session_state.messages = []
	st.session_state.current_chat_id = None
	if st.session_state.chat_ready:
	st.rerun()

	st.divider()

	# Collection Management
	st.title("📚 Collections")
	collections = get_collections(st.session_state.db_conn)

	if st.button("➕ Create Collection", use_container_width=True):
	st.session_state.show_collection_dialog = True

	# Collection selection with document preview
	if collections:
	selected = st.selectbox(
	"Select Collection",
	options=["All Documents"] + [c['name'] for c in collections],
	key="collection_select"
	)

	if selected != "All Documents":
	collection = next((c for c in collections if c['name'] == selected), None)
	if collection:
	documents = get_collection_documents(st.session_state.db_conn, collection['id'])
	if documents:
	st.markdown("### Documents in Collection")
	for doc in documents:
	with st.expander(f"📄 {doc['name']}", expanded=False):
	st.caption(f"Uploaded: {doc['upload_date']}")
	if st.button("Use for Chat", key=f"use_{doc['id']}"):
	initialize_chat_for_document(doc['id'])

	def display_collection_dialog():
	"""Display the create collection dialog."""
	with st.sidebar:
	st.subheader("Create New Collection")
	name = st.text_input("Collection Name", key="sidebar_collection_name")
	description = st.text_area("Description", key="sidebar_collection_desc")

	col1, col2 = st.columns(2)
	with col1:
	if st.button("Create", key="sidebar_create_btn"):
	if name:
	if create_collection(st.session_state.db_conn, name, description):
	st.success(f"Collection '{name}' created!")
	st.session_state.show_collection_dialog = False
	st.rerun()
	else:
	st.error("Please enter a collection name")

	with col2:
	if st.button("Cancel", key="sidebar_cancel_btn"):
	st.session_state.show_collection_dialog = False
	st.rerun()

	def display_welcome_screen():
	"""Display the welcome screen with getting started information and enhanced features."""
	st.title("🤖 Welcome to SYNAPTYX")
	st.markdown("### Your AI-powered RFP Analysis Assistant")

	# Check for existing documents
	documents = get_all_documents(st.session_state.db_conn)
	collections = get_collections(st.session_state.db_conn)

	col1, col2 = st.columns(2)
	with col1:
	st.markdown("""
	#### Getting Started:
	1. Upload your RFP documents using the sidebar
	2. Organize documents into collections
	3. Start analyzing with AI!

	You can:
	- Create multiple collections
	- Upload documents to specific collections
	- Search across all documents
	- Get AI-powered insights and summaries
	""")

	# Add action buttons if documents exist
	if documents:
	st.success(f"🎉 You have {len(documents)} documents ready for analysis!")
	col_a, col_b = st.columns(2)
	with col_a:
	if st.button("Start Chatting", use_container_width=True):
	if initialize_chat_from_collection():
	st.session_state.chat_ready = True
	st.rerun()
	with col_b:
	if st.button("View Documents", use_container_width=True):
	st.session_state.show_document_store = True
	st.rerun()

	with col2:
	st.markdown("#### Example Questions:")
	examples = [
	"📊 Summarize the main points of the document",
	"📝 Draft a 'Why Us' section based on the document",
	"🎯 Extract key success metrics and outcomes",
	"💡 What are the innovative solutions mentioned?",
	"🤝 Analyze the partnership benefits described",
	"📈 Compare requirements across documents",
	"🔍 Find similar sections across RFPs"
	]
	for example in examples:
	st.markdown(f"• {example}")

	# Add collection stats if they exist
	if collections:
	st.markdown("---")
	st.markdown("#### Your Collections:")
	for collection in collections[:3]: # Show top 3 collections
	with st.container():
	st.markdown(f"""
	🗂️ {collection['name']}
	Documents: {collection['doc_count']}
	""")
	if len(collections) > 3:
	st.caption("... and more collections")

	def display_chat_area():
	"""Display the main chat interface or welcome screen with proper state management."""
	if not st.session_state.chat_ready:
	display_welcome_screen()
	else:
	col1, col2 = st.columns([3, 1])
	with col1:
	display_chat_interface()
	with col2:
	# Document context panel
	st.markdown("### Current Context")
	if st.session_state.current_collection:
	st.info(f"📁 Using Collection: {st.session_state.current_collection['name']}")
	else:
	st.info("📚 Using All Documents")

	# Quick actions
	st.markdown("### Quick Actions")
	if st.button("🔄 New Chat", use_container_width=True):
	reset_chat_state()
	st.rerun()
	if st.button("📋 Export Chat", use_container_width=True):
	export_chat_history()

	# Example questions for quick reference
	with st.expander("💡 Question Examples", expanded=False):
	examples = [
	"Summarize main points",
	"Extract requirements",
	"Compare solutions",
	"Analyze pricing"
	]
	for example in examples:
	if st.button(example, key=f"example_{example}"):
	# Set the example as the current question
	st.session_state.current_question = example
	st.rerun()

	def export_chat_history():
	"""Export current chat history."""
	if st.session_state.messages:
	chat_text = "\n\n".join([
	f"{'User' if isinstance(m, HumanMessage) else 'Assistant'}: {m.content}"
	for m in st.session_state.messages
	])
	st.download_button(
	"Download Chat History",
	chat_text,
	file_name=f"chat_export_{datetime.now().strftime('%Y%m%d_%H%M%S')}.txt",
	mime="text/plain"
	)

	def main():
	"""Main application function."""
	# Page configuration
	st.set_page_config(
	layout="wide",
	page_title="SYNAPTYX - RFP Analysis Agent",
	initial_sidebar_state="expanded"
	)

	# Initialize database and session state
	if not initialize_database():
	st.error("Failed to initialize database. Please contact support.")
	return

	initialize_session_state()

	# Top bar with larger logo
	col1, col2, col3 = st.columns([1.5, 4, 1])
	with col1:
	if os.path.exists("img/logo.png"):
	st.image("img/logo.png", width=200) # Increased logo size
	else:
	st.info("Logo not found")
	with col2:
	st.title("SYNAPTYX - RFP Analysis Agent")
	with col3:
	if st.session_state.current_collection:
	st.info(f"📁 Active Collection: {st.session_state.current_collection['name']}")

	# Sidebar
	with st.sidebar:
	# Chat Controls Section
	st.title("💬 Chat Controls")

	# New Chat button
	if st.button("🔄 Start New Chat", use_container_width=True):
	reset_chat_state()
	st.rerun()

	st.divider()

	# Document Manager Section
	st.title("📚 Document Manager")

	# Collection Creation Button
	if st.button("➕ Create New Collection", use_container_width=True):
	st.session_state.show_collection_dialog = True

	# Collection Selection
	collections = get_collections(st.session_state.db_conn)
	if collections:
	selected = st.selectbox(
	"Select Collection",
	options=["All Documents"] + [c['name'] for c in collections],
	key="collection_select"
	)

	if selected != "All Documents":
	collection = next((c for c in collections if c['name'] == selected), None)
	if collection:
	st.session_state.current_collection = collection
	display_collection_documents(collection['id'])

	# Upload Section
	st.header("Upload Documents")
	uploaded_files = st.file_uploader(
	"Upload PDF documents",
	type=['pdf'],
	accept_multiple_files=True,
	help="Limit 200MB per file • PDF"
	)

	if uploaded_files:
	handle_document_upload(uploaded_files,
	collection_id=st.session_state.current_collection.get('id') if st.session_state.current_collection else None)

	# Show collection creation dialog if triggered
	if st.session_state.show_collection_dialog:
	show_collection_creation_dialog()

	# Main content area
	if st.session_state.chat_ready:
	display_chat_interface()
	else:
	display_welcome_screen()

	# Debug mode (if enabled)
	if st.session_state.debug_mode and st.sidebar.checkbox("Show Debug Info"):
	st.sidebar.write("Current State:", get_current_state())

	def display_collection_documents(collection_id: int):
	"""Display documents in the selected collection."""
	documents = get_collection_documents(st.session_state.db_conn, collection_id)
	if documents:
	st.markdown("### Documents in Collection")
	for doc in documents:
	with st.expander(f"📄 {doc['name']}", expanded=False):
	st.caption(f"Uploaded: {doc['upload_date']}")
	col1, col2 = st.columns(2)
	with col1:
	if st.button("Preview", key=f"preview_{doc['id']}"):
	st.text_area(
	"Content Preview",
	value=doc['content'][:500] + "..." if len(doc['content']) > 500 else doc['content'],
	height=100,
	disabled=True
	)
	with col2:
	if st.button("Use for Chat", key=f"chat_{doc['id']}"):
	initialize_chat_from_collection()
	st.rerun()

	if __name__ == "__main__":
	main()