LlamaIndex
llm framework
Framework for RAG and data-augmented LLM apps
Supported languages
Concepts
indexesquery-enginesretrieversnodes
Pros and Cons
Ventajas
- + Specialized in RAG
- + Powerful indexing
- + Multiple data types
- + Flexible query engines
- + Specialization in RAG and data
- + Connectors for many data sources
- + Optimized indexes for LLMs
- + Integration with multiple LLM providers
- + Powerful query engines
- + High-level abstractions
Desventajas
- - Less flexible than LangChain
- - Focused only on data augmentation
- - Can be overkill for simple cases
- - Abstractions may limit control
- - Documentation constantly changing
- - Versions may break compatibility
- - Less flexible than LangChain for some cases
Casos de Uso
- RAG applications
- Q&A on documents
- Knowledge bases
- Semantic search
- RAG systems (Retrieval Augmented Generation)
- Document Q&A
- Chatbots with custom knowledge
- Enterprise semantic search
- Agents with data access
- Knowledge base indexing