LlamaIndex
Data framework for building LLM applications with custom data sources
⭐ 4.6
freemium open-source development
#ai-framework
#rag
#data-ingestion
#llm
#search
#open-source
Overview
LlamaIndex is a comprehensive data framework designed to help developers build LLM applications that can work with custom data sources. It provides the tools needed to ingest, structure, and query data for retrieval-augmented generation (RAG) applications, making it easy to build chatbots, Q&A systems, and knowledge management tools.
Key Features
Data Ingestion
- 100+ Data Connectors: Support for files, databases, APIs, and web sources
- Multi-modal Support: Text, images, audio, and structured data
- Incremental Updates: Efficient data refreshing and synchronization
- Custom Parsers: Extensible parsing for specialized data formats
Indexing and Storage
- Vector Indexing: Semantic search with embedding models
- Graph Indexing: Knowledge graphs for complex relationships
- Hierarchical Indexing: Multi-level document organization
- Hybrid Search: Combining keyword and semantic search
Query Engines
- Natural Language Queries: Ask questions in plain English
- Multi-step Reasoning: Complex query decomposition
- Context-aware Responses: Maintaining conversation history
- Streaming Responses: Real-time answer generation
Enterprise Features
- Security: Data encryption and access controls
- Observability: Detailed logging and monitoring
- Scalability: Distributed processing capabilities
- Compliance: SOC 2, GDPR, and other standards
Use Cases
- Document Q&A: Build systems that answer questions about your documents
- Knowledge Management: Create searchable knowledge bases
- Customer Support: AI-powered help desks and chatbots
- Research Assistants: Tools for academic and business research
- Content Discovery: Intelligent content recommendation systems
- Data Analysis: Natural language interfaces for databases
Architecture
Core Components
- Data Loaders: Connectors for various data sources
- Node Parsers: Text chunking and preprocessing
- Embeddings: Vector representations of content
- Indices: Storage and retrieval structures
- Query Engines: Question-answering interfaces
- Chat Engines: Conversational interfaces
LlamaCloud Platform
- Managed Infrastructure: Hosted version with enterprise features
- Advanced Parsing: Improved document processing
- Collaboration Tools: Team management and sharing
- Analytics Dashboard: Usage insights and performance metrics
Getting Started
- Install LlamaIndex:
pip install llama-index - Load Your Data: Use built-in connectors or custom loaders
- Create an Index: Choose the appropriate indexing strategy
- Build Query Engine: Set up question-answering capabilities
- Deploy Your App: Integrate with your preferred framework
Pricing
- Open Source: Free access to the core framework
- LlamaCloud Starter: Free tier with basic managed services
- LlamaCloud Pro: Advanced features and higher limits
- Enterprise: Custom solutions with dedicated support
LlamaIndex has become the leading framework for building production-ready RAG applications, trusted by thousands of developers and enterprises worldwide for connecting LLMs with private data sources.