Skip to content

index.md

Latest commit

 

History

History
238 lines (172 loc) · 8.14 KB

index.md

File metadata and controls

238 lines (172 loc) · 8.14 KB
title Vector Bot Documentation
description Complete documentation for Vector Bot - a local RAG pipeline using LlamaIndex and Ollama
audience all
level overview
keywords
vector-bot
rag
ollama
llamaindex
documentation
local-ai
related_docs
user/getting-started.md
admin/configuration.md
reference/faq.md

Vector Bot Documentation

Welcome to the complete documentation for Vector Bot - a fully local Retrieval-Augmented Generation (RAG) pipeline that lets you ask natural language questions about your documents, completely offline.

What is Vector Bot?

Vector Bot transforms your documents into a searchable knowledge base using AI, without sending any data to the cloud. It uses:

  • LlamaIndex for document processing and retrieval
  • Ollama for local AI models (chat and embeddings)
  • Multi-format support for PDF, Markdown, text, JSON, and CSV files
  • Persistent storage for fast subsequent queries

Quick Navigation

🚀 New Users Start Here

Getting Started Journey:

  1. Installation Guide - Install Vector Bot and prerequisites
  2. Getting Started - Your first 10 minutes with Vector Bot
  3. Basic Usage - Essential commands and workflows
  4. Basic Configuration - Simple customization

Need Help?

📚 User Documentation

Guide Description Best For
Installation Multiple install methods (pip, npm, executable) First-time users
Getting Started Quick setup and first queries New users
Basic Usage Daily workflows and commands Regular users
Basic Configuration Essential settings All users
Advanced Features Power user capabilities Experienced users
Examples Real-world use cases All users
Troubleshooting Problem solving Users with issues

⚙️ Administrator Documentation

Guide Description Best For
Configuration Comprehensive configuration management System admins
Deployment Multi-environment deployment DevOps teams
Security Security considerations Security teams

📖 Reference Documentation

Reference Description Best For
Configuration Variables Complete variable reference Developers
FAQ Frequently asked questions All users
Glossary Terms and definitions All users
Quick Reference Command cheat sheet All users

🔧 Developer Documentation

Guide Description Best For
Contributing Contribution guidelines Contributors
Architecture System architecture Developers
Testing Testing documentation Developers
Claude Guidelines AI-assisted development AI developers

User Journey Pathways

🔰 "I'm Brand New to Vector Bot"

Path: Complete Beginner → Productive User

  1. Start → Installation

    • Choose your install method (npm recommended)
    • Install Ollama and models
    • Verify everything works

  2. Learn → Getting Started

    • First document indexing
    • First successful query
    • Understanding the workflow

  3. Practice → Basic Usage

    • Daily commands
    • Document management
    • Query optimization

  4. Customize → Basic Configuration

    • Essential settings
    • Model selection
    • Path configuration

  5. Explore → Examples

    • Real-world scenarios
    • Different document types
    • Advanced query patterns

Stuck? → Troubleshooting or FAQ

🎯 "I Want to Deploy Vector Bot"

Path: Installation → Production Deployment

  1. Plan → Configuration

    • Environment strategy
    • Path planning
    • Performance considerations

  2. Deploy → Deployment Guide

    • Multi-environment setup
    • Docker deployment
    • Production optimization

  3. Secure → Security Guide

    • Security checklist
    • Access controls
    • Vulnerability management

  4. Monitor → Troubleshooting

    • Health checks
    • Performance tuning
    • Issue resolution

🔍 "I Need Quick Information"

Path: Direct Access to Specific Information

🚀 "I'm Experienced, Show Me Advanced Features"

Path: Expert-Level Usage

  1. Advanced Usage → Advanced Features

    • Batch processing
    • Custom environments
    • Integration patterns

  2. Deep Configuration → Configuration

    • Advanced settings
    • Performance tuning
    • Multi-environment setup

  3. Development → Contributing

    • Development setup
    • Testing framework
    • Contribution process

Documentation Features

🏷️ Document Metadata

Each documentation page includes metadata for:

  • Audience: Who should read this (user, admin, developer, all)
  • Level: Difficulty level (beginner, intermediate, advanced, overview)
  • Keywords: Searchable terms
  • Related: Cross-referenced documents

🔗 Cross-References

All documentation includes:

  • Related sections at the bottom
  • In-text links to relevant topics
  • User journey navigation paths
  • Quick navigation menus

📱 Multi-Format Support

  • Progressive disclosure - basic → advanced information
  • Audience-specific content organization
  • Quick reference cards and cheat sheets
  • Real-world examples and use cases

Getting Help

📚 Self-Service Resources

  1. FAQ - Quick answers to common questions
  2. Troubleshooting - Step-by-step problem solving
  3. Examples - Real-world usage patterns
  4. Glossary - Definitions and terminology

🛠️ Diagnostic Tools

# Check system health
vector-bot doctor

# Show current configuration
vector-bot --config-info

# Verify installation
vector-bot --version

🏗️ Development Resources

Project Status

CI Security Test Coverage Tests

  • 135 tests with 99% code coverage
  • Multi-platform support (Windows, macOS, Linux)
  • Multiple distributions (pip, npm, standalone executables)
  • Production-ready with comprehensive CI/CD

This documentation is organized around user journeys and progressive disclosure. Start with your role and experience level, then navigate deeper as needed.

Found an issue with this documentation? See Contributing for how to help improve it.