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A NodeJS RAG framework to easily work with LLMs and embeddings

SDK monorepo for Ethora chat / messaging platform. (1) Pick an SDK for your frontend stack. (2) Integrate manually or using ethora-setup. (3) Optionally configure app settings, deploy AI agents etc. Server: ethora.com cloud [free]. Dedicated server + SLA option for enterprise customers.

Giselle: AI App Builder. Open Source.

Talk to any ArXiv paper using ChatGPT

🕵️‍♂️ Library designed for developers eager to explore the potential of Large Language Models (LLMs) and other generative AI through a clean, effective, and Go-idiomatic approach.

RESTai is an AIaaS (AI as a Service) open-source platform. Supports many public and local LLM suported by Ollama/vLLM/etc. Precise embeddings usage, tuning, analytics etc. Built-in image/audio generation with dynamic loading generators. Live chat deployment. Built-in block based graphical language. Prompt versioning and much more...

RAG-GPT, leveraging LLM and RAG technology, learns from user-customized knowledge bases to provide contextually relevant answers for a wide range of queries, ensuring rapid and accurate information retrieval.

Enterprise IM Solution with AI powered omni-channel customer service & team im，alternative to slack + zendesk/intercom

Give your AI agents persistent memory.

RAG evaluation without the need for "golden answers"

Config-driven engine that turns JSON into production-grade AI agents. Multi-agent orchestration, 12+ LLM providers, MCP/A2A protocols, RAG, persistent memory, and enterprise compliance (EU AI Act, GDPR, HIPAA). Built on Quarkus.

Integrated AI environment in the terminal. Build, test and instruct agents.

Text2Text Language Modeling Toolkit

BookWith – A New Reading Experience with AI. A next-generation conversational reading platform that goes beyond traditional e-book readers

An enterprise-grade AI retriever designed to streamline AI integration into your applications, ensuring cutting-edge accuracy.

🦀 Prevents outdated Rust code suggestions from AI assistants. This MCP server fetches current crate docs, uses embeddings/LLMs, and provides accurate context via a tool call.

An MCP server implementation that provides tools for retrieving and processing documentation through vector search, enabling AI assistants to augment their responses with relevant documentation context.

Human-like memory for AI agents — semantic, episodic & procedural. Experience-driven procedures that learn from failures. Free API, Python & JS SDKs, LangChain, CrewAI & OpenClaw integrations.

A production-ready FastAPI platform with modular components and a built-in control plane.

A python library for creating AI assistants with Vectara, using Agentic RAG

MCP server for AI agent for cybersecurity: automate assessment of documents, questionnaires & reports. Multi-format parsing, RAG knowledge base,Risks, compliance gaps, remediations.

AI-powered text compression library for RAG systems and API calls. Reduce token usage by up to 50-60% while preserving semantic meaning with advanced compression strategies.

A High-Efficiency System of Large Language Model Based Search Agents

Django BM25 full-text search using PostgreSQL - a lightweight Elasticsearch alternative

CLI + Local MCP - A shared structured memory store across Claude Code, Cursor, Windsurf, Antigravity, and every MCP client. Semantically queryable.

One memory, three terminals. Shared memory layer for Claude Code, Codex, and Gemini CLI — hybrid retrieval (vector + BM25 + KG), session continuity, 40 MCP tools. Local-first, LanceDB-backed.

Open-source, self-hosted knowledge backend for AI agents — hybrid search (vector + keyword), MCP server, 5 connectors, Docker-ready

MCP server for Apple Notes. Semantic search, full CRUD, works with MCP clients.

LLM readiness linter for websites. Audits robots.txt, llms.txt, Schema.org, and content density on a 0-100 scale. Includes MCP server. Published on PyPI: pip install context-cli.

Fast Python web crawler for RAG and AI ingestion. Extracts clean Markdown from any site for LLMs and vector stores.