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Vrinda Damani
Vrinda Damani

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Open Sourcing my AI Evaluation Library

#ai #machinelearning

Enterprise-Grade AI Evaluation, Now Open Source!
** pip install ai-evaluation → production ready insights under minutes **

I am excited to open-source something we've spent months perfecting at Future AGI: a robust AI Evaluation Library that meets the needs of modern GenAI teams in this probabilistic Agentic world, without black-box limitations.
AI evaluation remains the hardest unsolved problem in our field. How do you measure the accuracy of your eval pipeline? How do you evaluate the evaluator? How do you trust your metrics when the stakes are high?

Existing libraries like RAGAS, DeepEval, and AutoEval, etc have made valuable contributions to this space but still there are challenges like: time-consuming setup, need for constant upgradation of test cases, poor scalability and misleading scores that teams can't effectively debug. They force analysis paralysis with overwhelming metrics while still requiring expensive human annotation, creating evaluation bottlenecks that don’t scale for production.

How we solve this:

  1. Powered by our cutting-edge Turing models: Multimodal evaluation optimized for unmatched speed, accuracy, and pinpoint error localization - delivering reliable scores with clear explanations, not misleading metrics.

  2. Built-in Observability: Fully integrated observability stack from day one. Whether you are using LangChain, Langfuse, OpenAI etc, you can seamlessly integrate your existing observability tools right into our platform - eliminating complex setup dependencies and infrastructure barriers.

  3. Zero Latency Impact: Completely asynchronous by design, your performance won't take a hit - no more hardware crashes or resource bottlenecks that plague existing solutions.

  4. Best Practices Adhered To: We've baked in enterprise-level best practices directly into our eval-writing process, ensuring reliability and consistency - curated metrics that eliminate analysis paralysis and deliver actionable insights.

Plus, we're rolling out TypeScript support in just a few weeks, broadening accessibility and ease of integration.
Give it a spin, share your feedback, contribute or better yet - critique!

🔗 Check out the repo-
https://github.com/future-agi/ai-evaluation

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