opik vs ai-engineering-from-scratch
A neutral, constraint-first comparison - live GitHub stats and typed relationships, not marketing.
| opik | ai-engineering-from-scratch | |
|---|---|---|
| Tagline | Comprehensive tracing, automated evaluations, and production-ready dashboards for LLM applications. | Curriculum for building AI systems from scratch |
| Stars | 20k | 38k |
| Forks | 1.6k | 6.3k |
| Open issues | 147 | 94 |
| Language | Python | Python |
| License | Apache-2.0 | MIT |
| Last pushed | Jul 7, 2026 | Jun 25, 2026 |
| Categories | Evaluation & Observability | Inference & Serving, AI Agents, Evaluation & Observability, Model Training, Data & Retrieval, LLM Frameworks, Developer Tools, Speech & Audio, Computer Vision |
opik
Opik provides tools to debug, evaluate, monitor, trace, and optimize large language model (LLM) applications, retrieval-and-generation (RAG) systems, and agentic workflows. It supports the transition from prototype to production with full observability features.
Python
ai-engineering-from-scratch
A comprehensive curriculum covering over 500 lessons and 20 phases to build AI systems from foundational concepts to complex projects using Python, TypeScript, Rust, and Julia. Focuses on learning by doing, with a range of topics including machine learning, deep learning, NLP, computer vision, and more.
Python