Stars
🚀 PR-Agent (Qodo Merge open-source): An AI-Powered 🤖 Tool for Automated Pull Request Analysis, Feedback, Suggestions and More! 💻🔍
"Context engineering is the delicate art and science of filling the context window with just the right information for the next step." — Andrej Karpathy. A frontier, first-principles handbook inspi…
Vibetest MCP - automated QA testing using Browser-Use agents
An MCP server for interacting with Sentry via LLMs.
Qodo Commands Playbooks. Customize Qodo Command for your specific use case!
Python SDK, Proxy Server (LLM Gateway) to call 100+ LLM APIs in OpenAI format - [Bedrock, Azure, OpenAI, VertexAI, Cohere, Anthropic, Sagemaker, HuggingFace, Replicate, Groq]
Universal AI agent configuration parser and converter
The Qodo Gen CLI lets you interact with the Qodo platform from your terminal for automation, advanced AI workflows, or CI/CD integration.
Development environments for coding agents. Enable multiple agents to work safely and independently with your preferred stack.
Public backup of my ChatGPT Deep Research docs
A FastAPI server that turns markdown prompt files into API endpoints with minimal configuration.
LLM abstractions that aren't obstructions
End-to-end GenAI framework with built-in evaluation, security, and modular productivity tooling.
A modular, local-first AI assistant built with llama-cpp-python.
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/
AG-UI: the Agent-User Interaction Protocol. Bring Agents into Frontend Applications.
Examples on how to get started with the Galileo SDKs for AI Evaluation and Observability (both in Python and Typescript)
Free MLOps course from DataTalks.Club
Qodo-Cover: An AI-Powered Tool for Automated Test Generation and Code Coverage Enhancement! 💻🤖🧪🐞
Open Source Application for Advanced LLM + Diffusion Engineering: interact, train, fine-tune, and evaluate large language models on your own computer.
What are the principles we can use to build LLM-powered software that is actually good enough to put in the hands of production customers?
A repository for all ZenML projects that are specific production use-cases.
DSPy: The framework for programming—not prompting—language models
The open LLM Ops platform - Traces, Analytics, Evaluations, Datasets and Prompt Optimization ✨
Context7 MCP Server -- Up-to-date code documentation for LLMs and AI code editors