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| ## Project overview | ||
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| AiiDA is a workflow manager for computational science with a strong focus on provenance, performance, and extensibility. | ||
| It is written in Python (3.9–3.13) and uses PostgreSQL/SQLite for metadata storage, [`disk-objectstore`](https://github.com/aiidateam/disk-objectstore) for file storage, and RabbitMQ as a message broker. |
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| It is written in Python (3.9–3.13) and uses PostgreSQL/SQLite for metadata storage, [`disk-objectstore`](https://github.com/aiidateam/disk-objectstore) for file storage, and RabbitMQ as a message broker. | |
| It is written in Python (3.10–3.13) and uses PostgreSQL/SQLite for metadata storage, [`disk-objectstore`](https://github.com/aiidateam/disk-objectstore) for file storage, and RabbitMQ as a message broker. |
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danielhollas
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Very cool. Just had a very brief look at the CONTRIBUTING.md
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TODO: As mentioned by @agoscinski, if this file is loaded automatically into the context of the agent, we should make sure it's not too extensive, or at least ensure that if it is, it does not cause unwanted side effects (e.g., degradation due to context pollution). I'd still need to check and verify this myself. Also, trying out a few LLM-generated PRs, with the file in place. |
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agoscinski
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My understanding is that it is not automatically loaded so people can still choose to not use it. In case it does not provide additional benefit, it can be ignored. I think the overall shape looks good but I don't know how well it works in practice. I saw that one can do tests by give it an agent and compare token consumption. I personally don't have such a workflow yet so I suggest to merge it for testing and do QA in the future.
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@GeigerJ2 , worth a read: |
Thanks for sharing, @khsrali! Interesting, I wasn't aware of that. Seems like the landscape changes every day :D If I understand correctly, the key distinction is that I'd still like to have As this PR has been open for way too long for what it does, I suggest, we open an issue on adding a EDIT: Adding distributed skills via |
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OK, guys, we've come full circle ^^
Would really appricate if you other passengers on the AI hype train, @agoscinski, @khsrali, @mbercx, could have a final look, and we can merge this soon. Doesn't have to be perfect, we can see how the agents perform with this file in place, and then further refine. What stayed (and why)
What was condensed to one-liners
What was removed entirely
Small consistency fixes along the way
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ok, just looked this up here, and it is not auto-loaded indeed. One can add a tiny |
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Thanks a lot @GeigerJ2! I've finally started looking a bit into how to optimize these tools. I'll try to give a proper review next week, based on what I learned. One thing I did come across while researching this is the following paper: https://arxiv.org/abs/2602.11988 I only read the abstract, but it seems like they tried to gauge the effectiveness of having an |
Co-authored-by: Alexander Goscinski <alex.goscinski@posteo.de>
The ORM is planned for restructuring, so the detailed class diagrams would go stale quickly. They might also pollute the LLM context, and class hierarchies can be easily inspected from the source code, when required. Keep only the Process/Node duality table.
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Rendered view here:
https://github.com/GeigerJ2/aiida-core/blob/docs/agents_contributing/AGENTS.md