Feature: Optional Handit.ai integration to auto-fix prompts after Ragas evaluations

[ccgomezn]

Feature: Optional Handit.ai integration to auto-fix prompts after Ragas evaluations

Hi team 👋

Love what you’ve built with Ragas — it’s become a go-to tool for evaluating LLM apps.

We’ve been thinking about an optional feature that could make Ragas evaluations even more actionable: integrating Handit.ai, our open-source “autonomous engineer” that monitors and fixes AI 24/7.

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Problem / Opportunity

Ragas gives developers great evaluation metrics, but acting on failed/low-scoring results often means a manual process.
This slows down iteration and keeps improvements separate from the evaluation workflow.

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Proposed Solution

Add an optional parameter (e.g., handit_enabled=True) that:

1. Sends low-scoring/failed evaluation samples + context to Handit.
2. Handit automatically suggests or applies prompt/agent improvements.
3. Users can review or auto-apply fixes.

With one extra flag, users could go from just evaluating → to evaluating and fixing automatically.

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Benefits

• Speeds up the evaluation → improvement cycle.
• No extra setup for Ragas users.
• 100% opt-in.
• Integration maintained by the Handit team (no added load for Ragas maintainers).

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Next Steps

If the team is open to it, we can prepare a PR adding this as an optional enhancement.

What do you think?

— Cristhian @ Handit.ai

[anistark]

Sounds interesting integration @ccgomezn

Please check out the newer metrics collections approach using instructor via llm_factory and feel free to open a PR for this integration following that :)
Would be happy to merge it.