Ai
Showing 36 of 429 projects
A single-file memory layer for AI agents, replacing complex RAG pipelines with serverless, instant retrieval and long-term memory.
A customizable AI chatbot agent that ingests PDF documents, stores embeddings in a vector database, and answers user queries using LangChain and LangGraph.
🦉 Data Versioning and ML Experiments
A terminal-based AI coding agent that plans and executes large coding tasks across multiple files with smart context management.
An open-source platform for building and deploying GPT/LLM-powered chatbots and AI assistants.
A browser extension that enhances ChatGPT's data security, prevents network errors, and adds productivity features for a smoother AI experience.
GPU-accelerated neural network library for JavaScript, running in browsers and Node.js.
An open-source simulator built on Unreal Engine for developing, training, and validating autonomous driving systems.
A reliable PyTorch implementation of reinforcement learning algorithms for research and industry.
A modular, open-source visual editor for React.js that enables custom drag-and-drop page building with your own components.
An open-source, AI-powered code review agent that automates pull request reviews, improvements, and Q&A across multiple git platforms.
An open-source autonomous AI trading assistant that selects models, fetches data, and executes trades across multiple markets with USDC micropayments.
A curated list of modern Generative AI projects, services, models, and resources across text, image, video, audio, and coding.
An ultra-performant data transformation framework for AI, with incremental processing and data lineage built-in.
An open-source LLMOps platform unifying gateway, observability, evaluation, optimization, and experimentation for industrial-grade LLM applications.
A research framework for fast prototyping of reinforcement learning algorithms, designed for easy experimentation and reproducibility.
An end-to-end AI agent engineering platform with an open-source TypeScript framework and a production-ready observability console.
An all-language AI-powered code completion backend that provides intelligent autocompletions across multiple editors.
A command-line interface tool that integrates multiple LLM providers, offering shell assistance, interactive chat, RAG, AI tools, and local server capabilities.
A CLI AI agent that autonomously writes, audits, and revises novels with human review gates.
A collection of 45 practical tips and scripts for maximizing productivity with Claude Code, from custom status lines to advanced container workflows.
A standardized, flexible project template for data science work using Cookiecutter to structure reproducible projects.
The Go implementation of LangChain, enabling developers to build LLM-powered applications through composable components.
An autonomous AI development loop for Claude Code with intelligent exit detection, rate limiting, and session management.
A command-line tool for red-teaming and vulnerability scanning of large language models (LLMs).
An open-source enterprise data warehouse built in Rust for AI agents, analytics, vector search, and full-text search.
Deep Lake is a multimodal data lake and vector store optimized for AI, enabling scalable data management, retrieval, and training for LLM and deep learning applications.
A low-code multi-agent AI framework that automates complex tasks with planning, research, coding, and delivery to messaging platforms.
An AI-powered WiFi security auditing tool that uses deep reinforcement learning to optimize capture of WPA handshakes.
A curated collection of over 4,000 awesome generative AI applications across 43 categories.
A CLI tool that automatically generates git commit messages using AI by analyzing staged changes.
A Rust library for building scalable, modular, and ergonomic LLM-powered applications.
A real-time terminal monitoring tool for Claude AI token usage with ML-based predictions, cost analysis, and a Rich UI.
A lightweight, modular, and scalable deep learning framework built on the original Caffe.
A collection of libraries to optimize AI model performance through inference acceleration, infrastructure efficiency, and fine-tuning optimization.
A collection of libraries to optimize AI model performance through inference, infrastructure, and fine-tuning techniques.
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