Huggingface Model Deployer

[dudeperf3ct]

Describe changes

I implemented ModelDeployer component to work with Huggingface repos.

Pre-requisites

Please ensure you have done the following:

• [x] I have read the CONTRIBUTING.md document.
• [x] If my change requires a change to docs, I have updated the documentation accordingly.
• [x] I have added tests to cover my changes.
• [x] I have based my new branch on develop and the open PR is targeting develop. If your branch wasn't based on develop read Contribution guide on rebasing branch to develop.
• [ ] If my changes require changes to the dashboard, these changes are communicated/requested.

Types of changes

• [ ] Bug fix (non-breaking change which fixes an issue)
• [x] New feature (non-breaking change which adds functionality)
• [ ] Breaking change (fix or feature that would cause existing functionality to change)
• [ ] Other (add details above)

Summary by CodeRabbit

• New Features
  • Introduced Huggingface integration for deploying machine learning models using Huggingface's infrastructure.
  • Added support for configuring and managing Huggingface inference endpoints.
  • New deployment functionality for Huggingface models, including creation, update, and stopping of model deployment services.
  • Implemented a pipeline step for continuous deployment with Huggingface Inference Endpoint.

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Walkthrough

The update introduces Huggingface integration into ZenML, allowing for deploying machine learning models using Huggingface's infrastructure. It adds necessary configurations, implements a model deployer with methods for managing deployments, and provides a deployment service for handling inference endpoints. This integration facilitates continuous deployment pipelines within ZenML, leveraging Huggingface's capabilities for model serving.

Changes

File(s)	Change Summary
src/zenml/integrations/huggingface/__init__.py	Introduced imports and constants for Huggingface integration, including model deployer flavor and service artifact constants. Updated requirements to include "huggingface_hub".
src/zenml/integrations/huggingface/flavors/...	Added classes for Huggingface integration flavors, including model deployer configuration and base config.
src/zenml/integrations/huggingface/model_deployers/...	Launched Huggingface Model Deployer with methods for deployment management.
src/zenml/integrations/huggingface/services/...	Initiated Huggingface Service, implementing deployment and management functionality for Huggingface models.
src/zenml/integrations/huggingface/steps/...	Implemented a deployment step for continuous deployment with Huggingface, including service configuration and deployment logic.

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[htahir1]

@coderabbit review

[htahir1]

@coderabbitai review

[strickvl]

@dudeperf3ct can you check the CI errors and update as appropriate? there's some linting issues and also some docstrings to be added as far as I can see.

[dudeperf3ct]

@strickvl I have addressed the CI errors.

Re: Docs and Testing. I have added docs for the new deployer. I am not sure about using https://github.com/huggingface/hf-endpoints-emulator repo / package for testing.

Should I implement an example under tests/integration/examples for this new deployer? As part of running this step, an endpoint should be provisioned. Should I mock creating endpoint and use the emulated endpoint instead?

[strickvl]

@dudeperf3ct yeah that was sort of my idea. Either way works IMO, but some kind of an end-to-end example for this would be great that we can test in the integration tests runners.

[dudeperf3ct]

@strickvl Re: CI error and dependencies. huggingface_hub dependency is added as part of hugggingface integration.

According to docs, the minimal version of huggingface_hub package supporting Inference Endpoints API is v0.19.0.

Not sure what can be done to avoid the dependency conflict on fsspec package raised while setting up the environment.

[strickvl]

@dudeperf3ct that seems to be coming from the Azure dependency and adlfs which we have pinned down quite hard to one specific version (2021.10.0) via the Azure integration. It seems due a bump anyway. I'll work on freeing you up that way. Will make a PR but for now maybe just try https://github.com/zenml-io/zenml/blob/d216c662fb65e5abfaad6729b0f2d826f0611408/src/zenml/integrations/azure/init.py#L42-L43 as >= instead of ==?

[strickvl]

Looks like S3FS will need to be bumped as well...

[strickvl]

@dudeperf3ct #2402 looks on the surface of things to be ok, so maybe just add the change for S3FS into this PR and let's see if we can get it to work here too? (Hopefully will get that PR merged soon too, but in the interests of time...)