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function index_v2

Maturity: 39

Flask route handler that renders the main DocChat interface with document collection statistics.

File:
/tf/active/vicechatdev/docchat/blueprint.py
Lines:
86 - 92
Complexity:
simple

Purpose

This function serves as the entry point for the DocChat application's main interface. It initializes the RAG (Retrieval-Augmented Generation) engine, retrieves statistics about the document collection, and renders the chat interface template with these statistics. This allows users to see information about indexed documents before starting a chat session.

Source Code

def index():
    """Main DocChat interface"""
    # Initialize RAG engine to get stats
    rag = DocChatRAG()
    stats = rag.get_collection_stats()
    
    return render_template('docchat/chat.html', stats=stats)

Return Value

Returns a rendered HTML template (Flask Response object) for 'docchat/chat.html' with collection statistics passed as template context. The stats variable contains metadata about the document collection such as document count, chunk count, or other collection metrics provided by the RAG engine.

Dependencies

  • flask
  • flask_login
  • werkzeug

Required Imports

from flask import render_template
from flask_login import login_required
from rag_engine import DocChatRAG

Usage Example

# This function is typically not called directly but accessed via Flask routing
# Example Flask app setup:
from flask import Flask
from flask_login import LoginManager

app = Flask(__name__)
app.config['SECRET_KEY'] = 'your-secret-key'

# Setup Flask-Login
login_manager = LoginManager()
login_manager.init_app(app)

# Register the blueprint containing this route
from your_module import docchat_bp
app.register_blueprint(docchat_bp, url_prefix='/docchat')

# Access via browser:
# Navigate to http://localhost:5000/docchat/ (assuming docchat_bp is registered at /docchat)
# User must be logged in to access this route

Best Practices

  • Ensure the DocChatRAG class is properly initialized with necessary configuration before deployment
  • Handle potential exceptions from rag.get_collection_stats() in production code to prevent 500 errors
  • Consider caching collection statistics if they are expensive to compute and don't change frequently
  • The login_required decorator ensures only authenticated users can access this route
  • Verify that the template 'docchat/chat.html' exists and properly handles the stats context variable
  • Consider adding error handling for cases where RAG initialization fails
  • In production, consider adding rate limiting to prevent abuse of the endpoint

Similar Components

AI-powered semantic similarity - components with related functionality:

  • function chat_v1 84.9% similar

    Flask route handler that renders the main chat interface with available collections and instruction templates, requiring authentication.

    From: /tf/active/vicechatdev/vice_ai/app.py
  • function index_v1 78.1% similar

    Flask route handler that renders the main application page with user session management, authentication checks, and document collection statistics.

    From: /tf/active/vicechatdev/docchat/app.py
  • function chat 77.2% similar

    Flask route handler that processes chat requests with RAG (Retrieval-Augmented Generation) capabilities, managing conversation sessions, chat history, and document-based question answering.

    From: /tf/active/vicechatdev/docchat/blueprint.py
  • function get_stats 71.5% similar

    Flask API endpoint that retrieves and returns statistics about a document collection from a RAG (Retrieval-Augmented Generation) system.

    From: /tf/active/vicechatdev/docchat/blueprint.py
  • function index_v5 71.5% similar

    Flask route handler that renders and serves the main application interface page.

    From: /tf/active/vicechatdev/full_smartstat/app.py
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