{"repo":"ca-srg/ragent","free":true,"listed":false,"github":"https://github.com/ca-srg/ragent","clone":"git clone https://github.com/ca-srg/ragent.git","description":"CLI tool for building production RAG systems from Markdown, CSV, and PDF documents using hybrid search (BM25 + vector) with OpenSearch. Features MCP server, Slack bot, Web UI, multi-source ingestion (local/S3/GitHub), and multi-provider embeddings (Bedrock/Gemini).","language":"Go","stars":13,"topics":["rag","vector","aws","bedrock","markdown","opensearch","s3-vectors","cli","csv","gemini"],"license":null,"category":"cli-tools","readme_excerpt":"- Features RAGent - RAG System Builder for Markdown Documents 日本語版 (Japanese) / 日本語 README RAGent is a CLI tool for building a RAG (Retrieval-Augmented Generation) system from markdown documents using hybrid search capabilities (BM25 + vector search) with Amazon S3 Vectors and OpenSearch. Table of Contents - Features - Slack Search Integration - Embedding-Agnostic RAG - Environment Variable Setup Guide - Architecture Overview - Prerequisites - Required Environment Variables - Installation - Releases - Commands - vectorize - Vectorization and S3 Storage - query - Semantic Search - list - List Vectors - chat - Interactive RAG Chat - slack-bot - Slack Bot for RAG Search - mcp-server - MCP Server for Claude Desktop Integration - webui - Web UI for Vectorization Monitoring - Development - Typical Workflow - Troubleshooting - AWS Secrets Manager Integration - OpenSearch RAG Configuration - Automated Setup (setup.sh) - License - MCP Server Integration - Contributing Features - Vectorization : Convert source files (markdown, CSV, and PDF) from local directories, S3, or GitHub repositories to embeddings using Amazon Bedrock - GitHub Data Source : Clone GitHub repositories and vectorize their markdown/CSV files with auto-generated metadata - S3 Vector Integration : Store generated vectors in Amazon S3 Vectors - Hybrid Search : Combined BM25 + vector search using OpenSearch - Slack Search Integration : Blend document results with Slack conversations via an iterative enrichment pipeline ","default_branch":null,"files":null,"tree":[],"storefront":"/r/ca-srg","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/ca-srg/ragent/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}