--- title: "VectifyAI/PageIndex: πŸ“‘ PageIndex: Document Index for Vectorless, Reasoning-based RAG" source: "https://github.com/VectifyAI/PageIndex" author: - "[[rejojer]]" published: created: 2026-01-20 description: "πŸ“‘ PageIndex: Document Index for Vectorless, Reasoning-based RAG - VectifyAI/PageIndex" tags: - "clippings" - "webclipper" --- > [!info] Source > URL: https://github.com/VectifyAI/PageIndex > Title: VectifyAI/PageIndex: πŸ“‘ PageIndex: Document Index for Vectorless, Reasoning-based RAG > Clipped: **[PageIndex](https://github.com/VectifyAI/PageIndex)** Public πŸ“‘ PageIndex: Document Index for Vectorless, Reasoning-based RAG [pageindex.ai](https://pageindex.ai/ "https://pageindex.ai") [MIT license](https://github.com/VectifyAI/PageIndex/blob/main/LICENSE) [Open in github.dev](https://github.dev/) [Open in a new github.dev tab](https://github.dev/) [Open in codespace](https://github.com/codespaces/new/VectifyAI/PageIndex?resume=1) [![PageIndex Banner](https://private-user-images.githubusercontent.com/13518252/474974981-46201e72-675b-43bc-bfbd-081cc6b65a1d.png?jwt=eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.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.MYpYzCx3WDx7RmyRYnT9k62hAj0j4zutV7Yfz8t25x0)](https://vectify.ai/pageindex) [![VectifyAI%2FPageIndex | Trendshift](https://camo.githubusercontent.com/62b2c1c71f903121cb378334c98ab301cc540e0f76cdcd64497b4d2367fcaf07/68747470733a2f2f7472656e6473686966742e696f2f6170692f62616467652f7265706f7369746f726965732f3134373336)](https://trendshift.io/repositories/14736) **Reasoning-based RAG β—¦ No Vector DB β—¦ No Chunking β—¦ Human-like Retrieval** **πŸ”₯ Releases:** - [**PageIndex Chat**](https://chat.pageindex.ai/): The first human-like document-analysis agent [platform](https://chat.pageindex.ai/) built for professional long documents. Can also be integrated via [MCP](https://pageindex.ai/mcp) or [API](https://docs.pageindex.ai/quickstart) (beta). **πŸ“ Articles:** - [**PageIndex Framework**](https://pageindex.ai/blog/pageindex-intro): Introduces the PageIndex framework β€” an *agentic, in-context* *tree index* that enables LLMs to perform *reasoning-based*, *human-like retrieval* over long documents, without vector DB or chunking. **πŸ§ͺ Cookbooks:** - [Vectorless RAG](https://docs.pageindex.ai/cookbook/vectorless-rag-pageindex): A minimal, hands-on example of reasoning-based RAG using PageIndex. No vectors, no chunking, and human-like retrieval. - [Vision-based Vectorless RAG](https://docs.pageindex.ai/cookbook/vision-rag-pageindex): OCR-free, vision-only RAG with PageIndex's reasoning-native retrieval workflow that works directly over PDF page images. --- Are you frustrated with vector database retrieval accuracy for long professional documents? Traditional vector-based RAG relies on semantic *similarity* rather than true *relevance*. But **similarity β‰  relevance** β€” what we truly need in retrieval is **relevance**, and that requires **reasoning**. When working with professional documents that demand domain expertise and multi-step reasoning, similarity search often falls short. Inspired by AlphaGo, we propose **[PageIndex](https://vectify.ai/pageindex)** β€” a **vectorless**, **reasoning-based RAG** system that builds a **hierarchical tree index** from long documents and uses LLMs to **reason** *over that index* for **agentic, context-aware retrieval**. It simulates how *human experts* navigate and extract knowledge from complex documents through *tree search*, enabling LLMs to *think* and *reason* their way to the most relevant document sections. PageIndex performs retrieval in two steps: 1. Generate a β€œTable-of-Contents” **tree structure index** of documents 2. Perform reasoning-based retrieval through **tree search** [![](https://camo.githubusercontent.com/e9c3f93a4039fa4743b0655dc7a08eddd0eeb24ed1bfddfb03b6a0bf3c87cbdc/68747470733a2f2f646f63732e70616765696e6465782e61692f696d616765732f636f6f6b626f6f6b2f766563746f726c6573732d7261672e706e67)](https://pageindex.ai/blog/pageindex-intro "The PageIndex Framework") ### 🎯 Features Compared to traditional vector-based RAG, **PageIndex** features: - **No Vector DB**: Uses document structure and LLM reasoning for retrieval, instead of vector similarity search. - **No Chunking**: Documents are organized into natural sections, not artificial chunks. - **Human-like Retrieval**: Simulates how human experts navigate and extract knowledge from complex documents. - **Better Explainability and Traceability**: Retrieval is based on reasoning β€” traceable and interpretable, with page and section references. No more opaque, approximate vector search (β€œvibe retrieval”). PageIndex powers a reasoning-based RAG system that achieved **state-of-the-art** [98.7% accuracy](https://github.com/VectifyAI/Mafin2.5-FinanceBench) on FinanceBench, demonstrating superior performance over vector-based RAG solutions in professional document analysis (see our [blog post](https://vectify.ai/blog/Mafin2.5) for details). To learn more, please see a detailed introduction of the [PageIndex framework](https://pageindex.ai/blog/pageindex-intro). Check out this GitHub repo for open-source code, and the [cookbooks](https://docs.pageindex.ai/cookbook), [tutorials](https://docs.pageindex.ai/tutorials), and [blog](https://pageindex.ai/blog) for additional usage guides and examples. The PageIndex service is available as a ChatGPT-style [chat platform](https://chat.pageindex.ai/), or can be integrated via [MCP](https://pageindex.ai/mcp) or [API](https://docs.pageindex.ai/quickstart). - Self-host β€” run locally with this open-source repo. - Cloud Service β€” try instantly with our [Chat Platform](https://chat.pageindex.ai/), or integrate with [MCP](https://pageindex.ai/mcp) or [API](https://docs.pageindex.ai/quickstart). - *Enterprise* β€” private or on-prem deployment. [Contact us](https://ii2abc2jejf.typeform.com/to/tK3AXl8T) or [book a demo](https://calendly.com/pageindex/meet) for more details. - Try the [**Vectorless RAG**](https://github.com/VectifyAI/PageIndex/blob/main/cookbook/pageindex_RAG_simple.ipynb) notebook β€” a *minimal*, hands-on example of reasoning-based RAG using PageIndex. - Experiment with [*Vision-based Vectorless RAG*](https://github.com/VectifyAI/PageIndex/blob/main/cookbook/vision_RAG_pageindex.ipynb) β€” no OCR; a minimal, reasoning-native RAG pipeline that works directly over page images. --- PageIndex can transform lengthy PDF documents into a semantic **tree structure**, similar to a *"table of contents"* but optimized for use with Large Language Models (LLMs). It's ideal for: financial reports, regulatory filings, academic textbooks, legal or technical manuals, and any document that exceeds LLM context limits. Below is an example PageIndex tree structure. Also see more example [documents](https://github.com/VectifyAI/PageIndex/tree/main/tests/pdfs) and generated [tree structures](https://github.com/VectifyAI/PageIndex/tree/main/tests/results). You can generate the PageIndex tree structure with this open-source repo, or use our [API](https://docs.pageindex.ai/quickstart) --- You can follow these steps to generate a PageIndex tree from a PDF document. ``` pip3 install --upgrade -r requirements.txt ``` Create a `.env` file in the root directory and add your API key: ``` CHATGPT_API_KEY=your_openai_key_here ``` ``` python3 run_pageindex.py --pdf_path /path/to/your/document.pdf ``` **Optional parameters** You can customize the processing with additional optional arguments: ``` --model OpenAI model to use (default: gpt-4o-2024-11-20) --toc-check-pages Pages to check for table of contents (default: 20) --max-pages-per-node Max pages per node (default: 10) --max-tokens-per-node Max tokens per node (default: 20000) --if-add-node-id Add node ID (yes/no, default: yes) --if-add-node-summary Add node summary (yes/no, default: yes) --if-add-doc-description Add doc description (yes/no, default: yes) ``` **Markdown support** We also provide markdown support for PageIndex. You can use the \`-md\_path\` flag to generate a tree structure for a markdown file. ``` python3 run_pageindex.py --md_path /path/to/your/document.md ``` > Note: in this function, we use "#" to determine node heading and their levels. For example, "##" is level 2, "###" is level 3, etc. Make sure your markdown file is formatted correctly. If your Markdown file was converted from a PDF or HTML, we don't recommend using this function, since most existing conversion tools cannot preserve the original hierarchy. Instead, use our [PageIndex OCR](https://pageindex.ai/blog/ocr), which is designed to preserve the original hierarchy, to convert the PDF to a markdown file and then use this function. --- [Mafin 2.5](https://vectify.ai/mafin) is a reasoning-based RAG system for financial document analysis, powered by **PageIndex**. It achieved a state-of-the-art [**98.7% accuracy**](https://vectify.ai/blog/Mafin2.5) on the [FinanceBench](https://arxiv.org/abs/2311.11944) benchmark, significantly outperforming traditional vector-based RAG systems. PageIndex's hierarchical indexing and reasoning-driven retrieval enable precise navigation and extraction of relevant context from complex financial reports, such as SEC filings and earnings disclosures. Explore the full [benchmark results](https://github.com/VectifyAI/Mafin2.5-FinanceBench) and our [blog post](https://vectify.ai/blog/Mafin2.5) for detailed comparisons and performance metrics. [![](https://private-user-images.githubusercontent.com/8255061/440120069-571aa074-d803-43c7-80c4-a04254b782a3.png?jwt=eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.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.oiuAlY5zkAAemIDf-jl1jf89HL7uW6YBvZQHn-i-8VI)](https://github.com/VectifyAI/Mafin2.5-FinanceBench) --- ## 🧭 Resources - πŸ§ͺ [Cookbooks](https://docs.pageindex.ai/cookbook/vectorless-rag-pageindex): hands-on, runnable examples and advanced use cases. - πŸ“– [Tutorials](https://docs.pageindex.ai/doc-search): practical guides and strategies, including *Document Search* and *Tree Search*. - πŸ“ [Blog](https://pageindex.ai/blog): technical articles, research insights, and product updates. - πŸ”Œ [MCP setup](https://pageindex.ai/mcp#quick-setup) & [API docs](https://docs.pageindex.ai/quickstart): integration details and configuration options. --- Leave us a star 🌟 if you like our project. Thank you! [![](https://private-user-images.githubusercontent.com/13518252/481667856-eae4ff38-48ae-4a7c-b19f-eab81201d794.gif?jwt=eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.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.pSfTU0Lp63eIF6U3IbkEbdIwr2_U4ZL708xLqslt8uQ)](https://private-user-images.githubusercontent.com/13518252/481667856-eae4ff38-48ae-4a7c-b19f-eab81201d794.gif?jwt=eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.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.pSfTU0Lp63eIF6U3IbkEbdIwr2_U4ZL708xLqslt8uQ) --- Β© 2025 [Vectify AI](https://vectify.ai/) ## Releases No releases published ## Packages No packages published ## Languages - [Python 100.0%](https://github.com/VectifyAI/PageIndex/search?l=python)