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Ryan Orban

Ryan Orban

Subject
4 entries

Llamaindex

Bookmarks

  1. Dense-X-Retrieval: Proposition-Level RAG

    Dense-X-Retrieval is a LlamaIndex pack implementing proposition-level retrieval — splitting documents into atomic factual propositions rather than chunks, then retrieving at proposition granularity. Improves precision by matching query semantics at a finer level than paragraph chunks.

  2. LlamaIndex Retrieval and Chunk Evaluation Notebook

    A LlamaIndex Google Colab notebook for evaluating retrieval quality and chunk size in RAG pipelines — demonstrating how to measure retrieval hit rate and MRR across different chunk sizes. Practical tooling for the underappreciated problem of RAG evaluation.

  3. LlamaIndex: Composable Indices and Query Decomposition

    A LlamaIndex notebook demonstrating composable indices with query decomposition on city data — showing how to break complex queries into sub-queries across multiple document indices and synthesize the results. An early tutorial on the multi-hop retrieval patterns LlamaIndex specialized in.

  4. Llama Hub: LlamaIndex Data Connector Marketplace

    Llama Hub is the LlamaIndex community marketplace for data loaders — connectors that pull data from Notion, Slack, GitHub, databases, APIs, and more into LlamaIndex for RAG pipelines. The npm registry equivalent for LLM data connectors.

All bookmarks