The best-benchmarked open-source AI memory system. And it's free.
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Local-first code intelligence graph for MCP and CLI. Builds a persistent map of your codebase so AI coding tools read only what matters, with benchmarked context reductions on reviews and large-repo workflows.
Write scalable load tests in plain Python 🚗💨
Code-first platform for workflows, apps and AI agents, on the fastest self-hostable orchestrator (benchmarked against Airflow, Prefect and Temporal). Business teams build with AI, engineers control what ships. Open-source alternative to Lovable, Retool and n8n.
This repo hosts Prowler OSS (CLI and Local Server). Prowler is the world’s most widely used open-source cloud security platform that automates security and compliance across any cloud environment for Humans and AI Agents.
Load and performance benchmark tool
A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Python scikit-learn, H2O, xgboost, Spark MLlib etc.) of the top machine learning algorithms for binary classification (random forests, gradient boosted trees, deep neural networks etc.).
A deep learning toolkit for healthcare AI: EHR (MIMIC, eICU, OMOP), clinical text, signals and imaging. 30+ models, reproducible pipelines.
Python Performance Benchmark Suite
The fastest automatic differentiation library for C++, with Python bindings. Forward, adjoint and higher-order derivatives, checkpointing, Eigen support and JIT. Reproducible benchmarks against CppAD, Adept and autodiff.
Browser automation engine benchmark - Test bypass rates, performance & stealth against Cloudflare, DataDome, reCAPTCHA, Kasada, Imperva, Akamai, PerimeterX and other bot detection systems. Find the best browser for scraping.
Ultra-fast websocket client and server for asyncio
ROS package for the Perception (Sensor Processing, Detection, Tracking and Evaluation) of the KITTI Vision Benchmark Suite
A collection of resources covering different aspects of Locust load testing tool usage.
Prompt-injection firewall for LLM applications — 33 input detectors, 9 output scanners, federated ed25519-signed threat-intel feed. Apache 2.0, 1040 tests, F1 96.0% with 0% false positives. Docker, GitHub Action, LangChain/LlamaIndex/CrewAI integrations.
UV-first benchmark for protein-ligand docking with reproducible annotation, pocket similarity, and HPC workflows.