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Have plans to update my metadata software to pull matching model hashes into a yaml file and was just curious if you block or slow down automated queries?
Summary: the metadata scanner scans a library, reads the metadata and outputs it to file. Then we read the metadata and using civitAI API, we would then query models that we find, insert a URL for each model with the title of the model so that you can see how a model was put together, or find the model on civitAI.
When scanning a library, it will scan all files - and if this gains popularity then potentially it might create bandwidth issues for you guys. So when I do update my software to integrate with you guys here at CivitAI, if you don't reduce the numbers of connections per second per client, what could you suggest that I reduce my queries so that it is both efficient and doesn't overly tax your resources?
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if we use API calls to query a bunch of hashes, (https://github.com/civitai/civitai/wiki/REST-API-Reference#get-apiv1models-versionsby-hashhash) do you have a bandwidth or query limit that I should know about?
Have plans to update my metadata software to pull matching model hashes into a yaml file and was just curious if you block or slow down automated queries?
Summary: the metadata scanner scans a library, reads the metadata and outputs it to file. Then we read the metadata and using civitAI API, we would then query models that we find, insert a URL for each model with the title of the model so that you can see how a model was put together, or find the model on civitAI.
When scanning a library, it will scan all files - and if this gains popularity then potentially it might create bandwidth issues for you guys. So when I do update my software to integrate with you guys here at CivitAI, if you don't reduce the numbers of connections per second per client, what could you suggest that I reduce my queries so that it is both efficient and doesn't overly tax your resources?
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