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README.md
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README.md
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#### 🚨 New Releases:
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- 📖 [**PageIndex Chat**](https://chat.pageindex.ai): The first human-like document analyst agent, designed for professional long documents.
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- 🔌 [**PageIndex MCP**](https://pageindex.ai/mcp): Bring PageIndex into Claude, Cursor, or any MCP-enabled agent. Chat with long PDFs the reasoning-based, human-like way.
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- 🔌 [**PageIndex MCP**](https://pageindex.ai/mcp): Bring PageIndex into Claude, Cursor, or any MCP-enabled agent. Chat with long PDFs in a reasoning-based, human-like way.
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#### 📢 Recent Updates
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* ["Do We Still Need OCR?"](https://pageindex.ai/blog/do-we-need-ocr): Explores how vision-based, reasoning-native RAG challenges the traditional OCR pipeline, and why the future of document AI might be *vectorless* and *vision-based*.
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**🧪 Cookbooks:**
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* [**Vectorless RAG**](https://github.com/VectifyAI/PageIndex/blob/main/cookbook/pageindex_RAG_simple.ipynb): A minimal, hands-on example of reasoning-based RAG using **PageIndex** — no vectors, no chunking, and human-like retrieval.
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* [Vision-based Vectorless RAG](https://github.com/VectifyAI/PageIndex/blob/main/cookbook/vision_RAG_pageindex.ipynb): Experience OCR-free document understanding through PageIndex’s visual retrieval workflow — retrieving and reasoning directly over PDF page images.
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* [**Vectorless RAG notebook**](https://github.com/VectifyAI/PageIndex/blob/main/cookbook/pageindex_RAG_simple.ipynb): A minimal, hands-on example of reasoning-based RAG using **PageIndex** — no vectors, no chunking, and human-like retrieval.
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* [Vision-based Vectorless RAG notebook](https://github.com/VectifyAI/PageIndex/blob/main/cookbook/vision_RAG_pageindex.ipynb): Experience OCR-free document understanding through PageIndex’s visual retrieval workflow — retrieving and reasoning directly over PDF page images.
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# 📑 Introduction to PageIndex
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@ -58,12 +58,12 @@ Inspired by AlphaGo, we propose **[PageIndex](https://vectify.ai/pageindex)**
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### 🧩 Features
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Compared to traditional *vector-based RAG*, **PageIndex** features:
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- **No Vectors Needed**: Uses document structure and LLM reasoning for retrieval.
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- **No Vector DB Needed**: Uses document structure and LLM reasoning for retrieval, instead of vector search.
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- **No Chunking Needed**: Documents are organized into natural sections, not artificial chunks.
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- **Human-like Retrieval**: Simulates how human experts navigate and extract knowledge from complex documents.
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- **Transparent Retrieval Process**: Retrieval based on reasoning — traceable and interpretable. Say goodbye to approximate vector search ("vibe retrieval").
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PageIndex powers a reasoning-based RAG system that achieved [98.7% accuracy](https://github.com/VectifyAI/Mafin2.5-FinanceBench) on FinanceBench, showing state-of-the-art performance in professional document analysis (see our [blog post](https://vectify.ai/blog/Mafin2.5) for details).
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PageIndex powers a reasoning-based RAG system that achieved [98.7% accuracy](https://github.com/VectifyAI/Mafin2.5-FinanceBench) on FinanceBench, demonstrating **state-of-the-art** performance in professional document analysis (see our [blog post](https://vectify.ai/blog/Mafin2.5) for details).
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### ⚙️ Deployment Options
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- 🛠️ Self-host — run locally with this open-source repo.
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- Try the [_**Vectorless RAG Notebook**_](https://github.com/VectifyAI/PageIndex/blob/main/cookbook/pageindex_RAG_simple.ipynb) — a *minimal*, hands-on example of reasoning-based RAG using **PageIndex**.
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- Experiment with the [*Vision-based Vectorless RAG*](https://github.com/VectifyAI/PageIndex/blob/main/cookbook/vision_RAG_pageindex.ipynb) — no OCR; a minimal, reasoning-native RAG pipeline that works directly over page images.
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<p align="center">
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<div align="center">
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<a href="https://colab.research.google.com/github/VectifyAI/PageIndex/blob/main/cookbook/pageindex_RAG_simple.ipynb" target="_blank" rel="noopener">
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Here is an example output. See more [example documents](https://github.com/VectifyAI/PageIndex/tree/main/tests/pdfs) and [generated trees](https://github.com/VectifyAI/PageIndex/tree/main/tests/results).
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```python
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```jsonc
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...
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{
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"title": "Financial Stability",
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<details>
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<summary><strong>Markdown support</strong></summary>
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<br>
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We also provide a markdown support for PageIndex. You can use the `-md` flag to generate a tree structure for a markdown file.
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We also provide a markdown support for PageIndex. You can use the `-md_path` flag to generate a tree structure for a markdown file.
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```bash
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python3 run_pageindex.py --md_path /path/to/your/document.md
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# 📈 Case Study: SOTA on Finance QA Benchmark
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[Mafin 2.5](https://vectify.ai/mafin) is a reasoing-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.
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[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.
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PageIndex's hierarchical indexing enabled precise navigation and extraction of relevant content from complex financial reports, such as SEC filings and earnings disclosures.
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Leave a star if you like our project. Thank you!
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<p>
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<img src="https://github.com/user-attachments/assets/eae4ff38-48ae-4a7c-b19f-eab81201d794" width="70%">
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<img src="https://github.com/user-attachments/assets/eae4ff38-48ae-4a7c-b19f-eab81201d794" width="80%">
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</p>
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### Connect with Us
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