Xerj: Auto-Indexed Search Built for Agents
Xerj autoindexes code, docs, logs and PDFs for AI agent search, claims 40x fewer tokens than grep, and stays Elasticsearch compatible.
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18 posts tagged #rag
Browse 18 posts tagged Rag. Setup notes, reviews, comparisons, and workflow patterns.
Xerj autoindexes code, docs, logs and PDFs for AI agent search, claims 40x fewer tokens than grep, and stays Elasticsearch compatible.
production-agentic-rag-course is a Python and Jupyter course repo with Airflow, Docker Compose, and Gradio, MIT licensed, with 9,409 GitHub stars.
PageIndex is an MIT-licensed Python tool that indexes documents for reasoning-based RAG, replacing vector similarity search with an LLM reading a document tree.
WeKnora is Tencent's open-source LLM knowledge platform for turning raw documents into a queryable RAG, reasoning agent, and self-maintaining Wiki. Go, 25k stars trending.
A curated collection of 100+ open-source AI agent, agent skill, and RAG app examples in Python. Apache 2.0 licensed and actively maintained.
Open-source context retrieval layer connecting apps, databases, and documents to AI agents via unified search, SDKs, and MCP — 50+ integrations, self-hostable.
MemoryStack gives AI agents persistent memory, knowledge graphs, and semantic search. Free tier includes 500 memories/month with Python and Node.js SDKs.
Captain connects to S3, SharePoint, and 20+ sources to index video, images, PDFs, and audio, then serves AI agents via a clean REST API or MCP server. YC W26.
Deploy a self-hosted RAG pipeline with built-in MCP tools for PostgreSQL, MSSQL, MySQL, SSH, and filesystem indexing. Works with Claude Desktop, Cursor, and any OpenAI-compatible client.
A full-featured desktop AI assistant that runs locally, supports multi-user workspaces, and connects to any LLM provider. MIT licensed, with built-in agents and document chat.
Ragtoolina adds semantic codebase RAG to any MCP-compatible AI coding tool, cutting token usage by 63% with one line of config. Self-hosted option included.
Open-source platform for building multi-task AI agents with a no-code interface, PostgreSQL backend, and support for OpenAI, Anthropic, and Gemini models
Captain (YC W26) automates RAG pipeline setup for S3, GCS, and Google Drive. Index unstructured data in minutes with multimodal search across docs, images, and sheets.
ZeroEntropy (YC W25) builds embedding models, rerankers, and managed search APIs for RAG pipelines. Uses novel Elo-score training to outperform OpenAI and Cohere on retrieval benchmarks.
Crawl, chunk, and vectorize any website into a queryable knowledge base. REST API with collections, scheduled updates, and built-in RAG for LLM applications.
Ingest documents into persistent navigable memory — tree-like hierarchy reconstruction, multi-modal parsing, and agentic RAG with evidence-based citations.
Chonkie is a lightweight, fast RAG chunking library for Python and TypeScript. Up to 33x faster than LangChain, supports semantic, token, sentence, and code chunking.
Captain automates building and maintaining RAG pipelines for unstructured data. Index S3, GCS, and Google Drive in minutes with one API call.