LlamaIndex
Introduction
LlamaIndex (formerly GPT Index) is a data framework designed to help you build LLM applications over your private data. It provides a simple interface to connect your data with Large Language Models (LLMs), enabling you to:
- Ingest and index your existing data
- Create knowledge-based applications
- Structure your data for various LLM tasks
Features
- Data Connectors: Import data from various sources (PDFs, APIs, databases, etc.)
- Data Indexes: Efficiently structure and store your data
- Query Interface: Natural language querying of your data
- Application Integrations: Easy integration with LangChain and other frameworks
- Flexible LLM Support: Works with OpenAI, Anthropic, Hugging Face models, and more
Installation
Basic Usage
1. Setting up
2. Loading Documents
3. Querying
Key Concepts
1. Data Connectors
LlamaIndex provides various data connectors to load your data:
- File readers (PDF, Word, Text, etc.)
- Database connectors
- API connectors
- Web scrapers
2. Data Indexes
Different types of indexes available:
- Vector Store Index
- List Index
- Tree Index
- Keyword Table Index
3. Query Types
- Natural language queries
- Structured queries
- Hybrid queries
Advanced Features
- Data Agents: Automated reasoning over your data
- Evaluation Framework: Tools to evaluate response quality
- Customization: Custom prompts, embeddings, and node parsers
- Streaming Support: Real-time response streaming
- Multi-modal: Support for text, images, and other data types
Best Practices
- Choose appropriate index structures based on your use case
- Implement proper error handling
- Monitor token usage
- Use caching when possible
- Consider chunking strategies for large documents
Resources