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Currently distilabel can be only executed locally executing either a python script with the pipeline or using the CLI.
For future integrations with Argilla UI or deploying distilabel in services like HF Inference Endpoints, it would be nice to have a distilabel server that it's waiting for requests to execute certain pipeline.
The server will have a queue of pipeline executions. The queue will be filled from a POST requests to an HTTP server, that will contain the pipeline and the runtime parameters needed to execute the pipeline.
Adding a layer in distilabel allowing to generate statistics about the pipeline execution could allow to send back the pipeline execution information to a UI using SSE.
The text was updated successfully, but these errors were encountered:
Description
Currently
distilabel
can be only executed locally executing either a python script with the pipeline or using the CLI.For future integrations with Argilla UI or deploying
distilabel
in services like HF Inference Endpoints, it would be nice to have adistilabel
server that it's waiting for requests to execute certain pipeline.The server will have a queue of pipeline executions. The queue will be filled from a
POST
requests to an HTTP server, that will contain the pipeline and the runtime parameters needed to execute the pipeline.Adding a layer in
distilabel
allowing to generate statistics about the pipeline execution could allow to send back the pipeline execution information to a UI using SSE.The text was updated successfully, but these errors were encountered: