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LlamaIndex
Core details
Title
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Description
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LlamaIndex (formerly GPT Index) is a framework for building LLM-powered apps, focusing on data ingestion, indexing, and retrieval for RAG (Retrieval-Augmented Generation). It connects LLMs to custom data sources like PDFs or databases.
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Usage & Trade-offs
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When to use it
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Use LlamaIndex when: - Creating chatbots or search over private documents. - Implementing RAG for accurate, grounded responses. - Indexing structured/unstructured data for LLMs. - Prototyping knowledge bases quickly.
Pros
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- Simplifies data connectors and vector stores. - Modular for custom indexes and query engines. - Integrates with LangChain and OpenAI. - Handles chunking and embedding efficiently. - Open-source with growing ecosystem.
Cons
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- Dependent on embedding model quality. - Compute-intensive for large indexes. - Learning curve for advanced routers. - Potential hallucinations if retrieval fails. - Storage costs for vector DBs at scale.
Notes
Note: Use VectorStoreIndex for simple setups. Optimize chunk sizes for relevance. Evaluate with faithfulness metrics.
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