概要
PageIndex converts long documents into a semantic tree resembling a table of contents, with sections, page ranges, summaries, and optional node identifiers. An LLM or agent can search this structure to identify relevant sections using document context rather than vector similarity. The repository reports 34,965 stars, 3,064 forks, and 143 open issues; it is active rather than archived.
主な機能
- Vectorless retrieval based on document structure and LLM reasoning
- Hierarchical tree indexes with section and page references
- Natural-section organization without artificial chunking
- Context-aware, reasoning-driven tree search
- Optional node identifiers, summaries, and document descriptions
- PDF and Markdown input support
- Preview PageIndex Flash mode for heuristic PDF structure extraction
- Self-hosted agentic RAG example using the OpenAI Agents SDK
- Vision-based vectorless RAG notebook
- Hosted chat, MCP, API, and enterprise deployment options
要件、インストール、クイックスタート
使用方法
モデルの互換性とユースケース
Multiple LLM providers are supported through LiteLLM. The documented default model is `gpt-4o-2024-11-20`, and the setup example uses an OpenAI API key. The agentic demo uses the OpenAI Agents SDK. A complete list of tested or supported models is not stated in the repository metadata.
ライセンスとリスクに関する注意事項
The repository metadata identifies the license as MIT. License reference: https://api.github.com/licenses/mit. No additional license exceptions or dependency-license details are stated in the supplied repository record.
リリースとメンテナンス
The README highlights an agentic vectorless RAG example using self-hosted PageIndex and the OpenAI Agents SDK, PageIndex File System for corpus-level indexing, PageIndex Chat, MCP/API access, and PageIndex Flash as a preview feature. Formal tagged release names, versions, and release dates are not stated in the repository metadata.