Arize-ai/phoenix
Uncover insights, surface problems, monitor and fine tune your generative LLM, CV and tabular models.
Open source engineering platform to debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards. (Source Code)
Automatically apply SOTA optimization techniques to achieve the maximum inference speed-up on your hardware.
In-context learning framework that allows agents to learn from execution feedback.
An Easy-to-Use and High-Performance AI deployment framework.
Open source AI infrastructure layer. Eight agents run automatically: security, caching, memory, hallucination detection, and tamper-proof audit trail. Runs locally.
OpenCV has C++, C, Python, Java and MATLAB interfaces and supports Windows, Linux, Android and Mac OS.
A deep learning framework developed with cleanliness, readability, and speed in mind.
A real-time multi-person keypoint detection library for body, face, hands, and foot estimation
C++
