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vihargadhesariya
Iron Contributor
Nov 05, 2025

Open-Source SDK for Evaluating AI Model Outputs (Sharing Resource)

Hi everyone,
I wanted to share a helpful open-source resource for developers working with LLMs, AI agents, or prompt-based applications.
One common challenge in AI development is evaluating model outputs in a consistent and structured way. Manual evaluation can be subjective and time-consuming.
The project below provides a framework to help with that:
AI-Evaluation SDK
 
https://github.com/future-agi/ai-evaluation
 
Key Features:
- Ready-to-use evaluation metrics
- Supports text, image, and audio evaluation
- Pre-defined prompt templates
- Quickstart examples available in Python and TypeScript
- Can integrate with workflows using toolkits like LangChain
Use Case:
If you are comparing different models or experimenting with prompt variations, this SDK helps standardize the evaluation process and reduces manual scoring effort.
If anyone has experience with other evaluation tools or best practices, I’d be interested to hear what approaches you use

1 Reply

  • hi vihargadhesariya​  Thanks for sharing this - evaluation is one of those areas everyone struggles with, especially once you move beyond simple demos.

    An SDK that standardizes evaluation across text, image, and audio is really useful, particularly when you're comparing prompts, models, or agent behaviors over time. I like that this focuses on repeatable metrics and templates, which helps reduce the "gut feel" aspect of manual reviews.

    For teams building with Azure OpenAI / agents, this kind of framework can also fit nicely into CI/CD or experimentation workflows, where you want consistent signals rather than ad-hoc human scoring.

    Curious to see how others here are approaching evaluation as well - especially around:

    • automated vs human-in-the-loop evaluation
    • confidence / hallucination detection
    • regression testing for prompts and agents

    Appreciate you sharing the resource with the community!

     

     

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