Llamaindex
A comprehensive skill catalog for AI agents
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LlamaIndex data framework for LLMs. Use for RAG applications.
SKILL.md
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LlamaIndex
LlamaIndex (formerly GPT Index) connects LLMs to your data. 2025 introduces Workflows, an event-driven way to build complex RAG pipelines.
When to Use
- RAG (Retrieval Augmented Generation): Indexing PDFs, Docs, SQL to chat with them.
- Structured Data: Querying SQL/Pandas with natural language (
NLSQL). - Agents: Building research agents that browse the web and summarize.
Core Concepts
Workflows
Event-driven architecture for agents. Replace DAGs with event listeners (@step).
Query Engine
High-level API (index.as_query_engine()) to ask questions.
Data Loaders (LlamaHub)
Connectors for Notion, Slack, Discord, PDF, etc.
Best Practices (2025)
Do:
- Use Workflows: They are harder to learn but easier to debug than monolithic engines.
- Use Hybrid Search: BM25 (Keyword) + Vector Search for best retrieval accuracy.
- Use Rerankers: Always rerank retrieved nodes (Cohere/BGE) before sending to LLM.
Don't:
- Don't dump raw text: Use "Node Parsers" to chunk data intelligently (Markdown, Semantic).