Stars
A file-over-app knowledge base of the entire Y Combinator YouTube channel, queryable in Claude Code — ask startup questions, get answers cited to the exact video + timestamp. 618 talks distilled in…
Build cross-platform desktop apps with JavaScript, HTML, and CSS
🤗 smolagents: a barebones library for agents that think in code.
the first library to let you embed a developer agent in your own app!
Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
ByteRover CLI (brv) - The portable memory layer for autonomous coding agents (formerly Cipher)
AI Agent Framework, the Pydantic way
[DEPRECATED] Repo for exploring multi-task learning approaches to learning sentence representations
Holistic Evaluation of Language Models (HELM) is an open source Python framework created by the Center for Research on Foundation Models (CRFM) at Stanford for holistic, reproducible and transparen…
Beyond the Imitation Game collaborative benchmark for measuring and extrapolating the capabilities of language models
🚀 The fast, Pythonic way to build MCP servers and clients.
Agent2Agent (A2A) is an open protocol enabling communication and interoperability between opaque agentic applications.
Fair-code workflow automation platform with native AI capabilities. Combine visual building with custom code, self-host or cloud, 400+ integrations.
Cognee is the open-source AI memory platform for agents. Give your AI agents persistent long-term memory across sessions with a self-hosted knowledge graph engine.
Build Real-Time Knowledge Graphs for AI Agents
Magnificent app which corrects your previous console command.
[Project ended] rkt is a pod-native container engine for Linux. It is composable, secure, and built on standards.
Production-Ready MCP Server Framework • Build, deploy & scale secure AI agent infrastructure • Includes Auth, Observability, Debugger, Telemetry & Runtime • Run real-world MCPs powering AI Agents
A Chinese Translation of Stanford CS229 notes 斯坦福机器学习CS229课程讲义的中文翻译
Build applications that make decisions (chatbots, agents, simulations, etc...). Monitor, trace, persist, and execute on your own infrastructure.
The long-term memory for your Superagents 🥷and LLMs 🤖. Built with GraphRAG, Knowledge graphs and autonomous ai agents
Pulumi - Infrastructure as Code in any programming language 🚀