Vectorless, Reasoning-Based Retrieval-Augmented Generation (RAG)
-
Updated
Mar 26, 2026 - Python
Vectorless, Reasoning-Based Retrieval-Augmented Generation (RAG)
Extends pageIndex into an AI document workspace with multi-format parsing, OCR, visual TOC, custom models, citations, and agentic QA.
PageIndex-inspired agentic RAG app for vectorless document QA, FastAPI, multi-document retrieval, context compaction, and self-hosted AI workspaces.
Atlas - Enterprise document indexing plugin for OpenClaw. Vectorless RAG using PageIndex with async indexing, incremental updates, and smart caching. Scales from 10 to 5000+ documents. Perfect for financial reports, legal docs, technical manuals, and research papers.
Ziglang eXtensiable Builder for SQL or JSON, zig version, sql or json query builder, extensible custom for any database, for any orm framework
12-week, project-driven Obsidian curriculum: cloud/infra engineer → AI Agent/LLM engineer. Companion narrative + interview prep for shaneliuyx/agent-prep labs.
Modular RAG library for Python. Swap any component — LLM, vectorstore, reranker — with one line in a YAML file. No code changes. Just config.
AI-first manual checklist builder using PageIndex-style vectorless retrieval + local Gemma4 to generate grounded maintenance checklists with strict citations.
Local-first MCP server for indexing and querying PDF/Markdown files using PageIndex — no cloud APIs required
Evidence RAG Citation traceability for high-stakes documents. Built on a private hybrid evidence retrieval engine.
A vectorless RAG pipeline that navigates PDF documents using a PageIndex tree structure and Gemini 2.0 Flash — no vector database, just LLM-guided tree search with auto-cited answers.
A fully private, local RAG system for selectable-text PDFs using hierarchical tree search and D3 spatial graphs.
问道 wendao - high-performance knowledge and link-graph engine, AI RAG.
A free chatbot you run on your own server. Upload your documents, train a bot on them, and paste one line of code into your website. Visitors ask questions, and the bot answers using your documents.
🔍 Empower efficient retrieval with PageIndex, a reasoning-based system that eliminates the need for vector databases and chunking for human-like results.
Implements a vectorless RAG architecture using PageIndex APIs and Groq LLMs, enabling efficient document retrieval and response generation without traditional vector databases.
Local first AI assistant for your workspace & messaging. Zero data leakage, local storage, and fast CLI controls.
PostgreSQL extension for PageIndex: PDF/Markdown document trees, tree search, JSONB API (pageindex schema). C + Go c-shared bridge; PGXS; MIT licensed.
To associate your repository with the pageindex topic, visit your repo's landing page and select "manage topics."