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Developer Tool • Mar 19, 2026
LlamaIndex Framework
Framework for building LLM apps with data connectors, RAG pipelines, agents, structured extraction, evaluation, and observability integrations.
What it helps you do
- Use this when the main challenge is connecting private documents, structured data, retrieval, agents, and evaluation into an LLM application.
Best fit users
- AI engineers, data engineers, RAG builders, knowledge-management teams, and companies building document-heavy AI products.
What to know first
- Python knowledge, understanding of embeddings and retrieval, access to target documents/data, and awareness of data privacy requirements.
Environment needed
- Python environment, vector store or database when needed, embedding/model provider access, document storage, and enough compute for indexing and retrieval workflows.
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