LlamaIndex provides data connectors and indexing for LLM applications. Connect to databases, APIs, and files. Multiple index types for different use cases. Query engines compose sophisticated retrieval.
Data Connectors
Load data from files, databases, APIs. Transform documents for indexing. Metadata enrichment improves retrieval. Incremental loading for large datasets.
- Use data loaders for various sources
- Configure document transformations
- Build appropriate index types for use case
- Compose query engines for complex retrieval
- Implement agents for dynamic data access
Query Engines
Vector indexes for semantic search. Keyword indexes for exact matching. Composite indexes combine approaches. Query routing selects appropriate indexes.