Ragas: Evals for RAG & Memory - AI Build & Learn #10

​Welcome to AI Build & Learn a weekly AI engineering stream where we pick a new topic and learn by building together.

​​​​This event is about evaluating LLM and RAG applications with Ragas, an open-source Python toolkit for objective, automated evals instead of vibes-based testing.

​We'll explore Ragas metrics for retrieval and generation quality, automated test data generation, and how to wire evals into a feedback loop so production data drives continuous improvement.

​Some things to look up to get started:

• ​Ragas GitHub: https://github.com/vibrantlabsai/ragas

• ​Ragas docs: https://docs.ragas.io/

​Reources

• ​​​​GitHub: https://github.com/sagecodes/ai-build-and-learn

• ​​​​Events Calendar: https://luma.com/ai-builders-and-learners

• ​​​​Slack (Discuss during the week): Flyte Slack Group

• ​​​​Hosted by Sage Elliott: https://www.linkedin.com/in/sageelliott/

​​​​In this stream

• ​Intro to topic

• ​​​​​Community Discussion

• ​Practical examples

​​​​​Community challenge (optional)

​​​​​Try spending 30–90 minutes during the week learning or building something related to the topic, then share what you’re working on in Slack.

​​​​​Note on Flyte / Union

​​​​​You may see Flyte used in some demos. Flyte is an open-source AI orchestration platform maintained by Union (where I work) for building scalable, durable, and observable AI workflows. You do not need to use Flyte to participate.

• ​​​​​Union: https://www.union.ai/

• ​​​​​Flyte: https://flyte.org/

​​​​​Drop a comment with ideas for future topics (agents, RAG, MLOps, robotics, frameworks, and more).