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Can we repair runs (or their repairs) manually? In the dashboard, it seems like we can only use a prompt to repair a run / sample. I have found the repair to be frustrating at times because the output often adds chatty text to the answer. It often outputs something like:
In one of my use cases, the model is asked to output data in CSV format. Sometimes it forgets a trailing separator or something like that - in such a case, it would be simpler for me to edit it than to explain it where the mistake is. If I write a prompt to repair it, it usually repairs it successfully, but it adds chatty text around the actual CSV so the repaired answer would still need some changes. Having manual repairing of a run (and / or manual repairing of a repair of a run) in the UI would allow fixing minor problems like that where the output is almost correct |
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Replies: 4 comments 4 replies
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I can actually just edit the JSON files, save, and reload the page. That is good enough for my particular problem - though doing it in the dashboard would be easier for non-technical people. |
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Manually editing certainly works for now, as you discovered. I'll see if I can adapt to auto-prompt to be more explicit about not including a pre-amble before the content. For a more "traditional fix", add the needed guidance to the repair instruction until it gets it right. Something like "Only include the result in your response, do not reply with any pre-amble". Then start using the "multi-shot repair" prompt, which will include your previous guidance in the prompt. After a few examples, it should start getting it right with extra help. I'm intentionally trying to capture what the LLM needs to get it right, so it can learn to improve quickly. It's a little faster at improving if it has LLM-comprehensible repair instructions, and not just in-out pairs. That said, both in the UI are a good idea. |
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You're 100% on the right path. You can use any valid JSON schema in the output_schema field, including arrays/objects/limits/etc. That will probably make everything run smoother. Just manually edit the task.kiln, or use the Python API. The UI will always lag behind what JSON schema can do (neatest arrays, objects, limits), but for more technical users you can just set it manually. |
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FYI: added UI to let you do this for new tasks, which will be in the next release. Manually works great for now. |
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Manually editing certainly works for now, as you discovered.
I'll see if I can adapt to auto-prompt to be more explicit about not including a pre-amble before the content.
For a more "traditional fix", add the needed guidance to the repair instruction until it gets it right. Something like "Only include the result in your response, do not reply with any pre-amble". Then start using the "multi-shot repair" prompt, which will include your previous guidance in the prompt. After a few examples, it should start getting it right with extra help.
I'm intentionally trying to capture what the LLM needs to get it right, so it can learn to improve quickly. It's a little faster at improving if it has…