DataVerse Chatbot Documentation

DataVerse ChatBot is a powerful Python-based application that enables real-time, AI-driven chat interactions by extracting and processing data from virtually any source—web pages, nearly all file formats, and more.

The system combines advanced web crawling, multi-format data extraction, and Retrieval-Augmented Generation (RAG) techniques, integrating with leading Large Language Models (LLMs) to deliver context-aware responses.

Contents:

• Overview
  • System Architecture
  • Key Components
  • Technology Stack
• Installation
  • Requirements
  • Quick Installation
  • Manual Installation
  • API Key Configuration
  • Directory Structure
• Usage Guide
  • Getting Started
  • Running the CLI Interface
  • Data Ingestion Methods
  • Creating a RAG System
  • Deploying as a Web Interface
  • Deploying as a Telegram Bot
  • Deploying as a WhatsApp Bot
  • Running the Admin Dashboard
  • Advanced Features
• Chatbot Module
  • RAG (Retrieval-Augmented Generation)
  • Embeddings
  • Crawler
  • Configuration
  • Utilities
• Web Interfaces
  • Chat Web Application
  • Chat Web Template
  • Admin Dashboard
• Bot Implementations
  • Telegram Bot
  • WhatsApp Bot
  • Common Bot Features
  • Implementation Details
  • Deployment Recommendations
• API Reference
  • chatbot Package
  • web Package
  • Bot Implementations
• Examples
  • Basic Usage

Key Features

• Web Crawling: Extracts content from specified web sources with customizable parameters

• Multi-Format Data Extraction: Processes data from PDFs, text files, documents, spreadsheets, and more

• Monitoring and Uncertainty Detection: Tracks responses and uses trained classifiers to detect uncertain answers

• LLM Integration: Works with multiple leading models (OpenAI, Claude, Cohere, DeepSeek, Gemini, Grok, Mistral)

• Multiple Chat Interfaces: Deployable as WhatsApp and Telegram bots or embedded via an iframe

Indices and tables

• Index

• Module Index

• Search Page