genai

Convenience scripts to finetune (chat-)LLaMa3 and other models for any language

The RAG Experiment Accelerator is a versatile tool designed to expedite and facilitate the process of conducting experiments and evaluations using Azure Cognitive Search and RAG pattern.

An intentionally vulnerable OWASP LLM Top 10 training platform for AI Security, Prompt Injection, RAG Security, Agent Security, and GenAI penetration testing.

Build, evaluate and observe LLM apps

This MCP server provides documentation about Strands Agents to your GenAI tools, so you can use your favorite AI coding assistant to vibe-code Strands Agents.

A set of lessons aimed at anyone learning LLM and generative AI concepts, with sections on operations and security, as well as development.

Accelerate your Gen AI with NVIDIA NIM and NVIDIA AI Workbench

The AI framework for Go developers. Build powerful AI applications and agents using our free, open-source library. From Jetify, the creators of TestPilot.

Your commands control the browser - made easy | Chrome Extension and RESTful API for Browser-Use

An open source implementation of LFMs from Liquid AI: Liquid Foundation Models

RAG with langchain using Amazon Bedrock and Amazon OpenSearch

⚡ GUI for editing LLM vector embeddings. No more blind chunking. Upload content in any file extension, join and split chunks, edit metadata and embedding tokens + remove stop-words and punctuation with one click, add images, and download in .veml to share it with your team.

Deforum based on flux-dev by XLabs-AI

Boot your PC straight into an LLM. Rust, UEFI-resident, no operating system underneath.

A curated list of useful Generative AI APIs for developers

A command-line interface (CLI) for Google Gemini

Prompt Engineering Jumpstart: The simplest beginner's guide to talking with AI. Learn universal prompt engineering principles with simple analogies & copy-paste examples for ChatGPT & DALL-E. No tech skills needed. Free, open-source eBook.

A curated, comprehensive collection of open-source AI tools, frameworks, datasets, courses, and seminal papers.

Fully managed RAG solution implemented using Knowledge Bases for Amazon Bedrock

Automatic Prompt Optimization Framework