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Add new endpoints for workflows and prepare for future deprecation #336

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PawelPeczek-Roboflow
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@PawelPeczek-Roboflow PawelPeczek-Roboflow commented Mar 27, 2024

Description

There were couple of changes in this PR:

Changes in workflows endpoints

image

Adjusted sdk client to changes

image

Maintained backward compatibility of endpoints

  • old endpoints are still alive, sunset day is set in docs
  • there is deprecation warning on old methods
  • API docs also contain deprecation warning

Provided self-descriptive capabilities for workflows blocks and endpoints to describe all loaded steps

image
  • introduced notion of reference kinds - which is simple type-system on referred values
  • without detailed knowledge of steps, just based on definitions we can do multiple things:
    • deduce which step can be connected to which other:
    • it is possible to prepare generic entities builder
image image

Provided endpoint to validate workflows JSON definitions

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Improved significantly workflows syntax validation by establishing typedefs with constraint checks in pydantic

OLD:
image

NEW:
image

Thanks to that: ➖ 900 lines of code

Registered workflows in InferencePipeline

image

Fixed couple of bugs

  • YoloWorld in workflows at hosted platform
  • wrong definition of detection filter filtering claims

Type of change

Please delete options that are not relevant.

  • Bug fix (non-breaking change which fixes an issue)
  • New feature (non-breaking change which adds functionality)
  • This change requires a documentation update

How has this change been tested, please provide a testcase or example of how you tested the change?

  • CI still 🟢 - most importantly our validators for syntax and semantic of workflows - which means that we shall not expect breaking change in that
  • new tests added for new functionality
  • deployed and tested @ staging (with load tests and tests of new functionalities executed)

Any specific deployment considerations

  • tested at staging, postponing PROD deployment to next week due to holidays
  • should not be breaking in terms of workflows contract

Docs

  • Docs updated? What were the changes: workflows, InferencePipeline inference_sdk

@PawelPeczek-Roboflow PawelPeczek-Roboflow marked this pull request as ready for review March 29, 2024 11:45
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Only got partway through reviewing but have to go into meetings for a bit. Will finish later but wanted to get these comments out there.

inference/core/interfaces/stream/inference_pipeline.py Outdated Show resolved Hide resolved
description="Parameter to decide if Active Learning data sampling is disabled for the model",
examples=[True, "$inputs.disable_active_learning"],
)
active_learning_target_dataset: Union[
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Would be useful to add an array of tag strings that get added to the uploaded images.

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would be, but this is also possible in AL config that can be declared in-place. We can add this feature, but I would put that into to-do for next iteration

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this is also possible in AL config that can be declared in-place

Can you clarify? I don't think I understand what this is

I would put that into to-do for next iteration

Sounds good

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this is also possible in AL config that can be declared in-place -> you can request specific tags to be added via config of AL that can be defined either at project level or in-place

@@ -432,31 +511,44 @@ def validate_field_binding(self, field_name: str, value: Any) -> None:


class InstanceSegmentationModel(ObjectDetectionModel):
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Is there an easy way to know from the manifest whether something is a subclass of BaseModel? I think right now I just check if the name ends in _model

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do you mean BaseModel or RoboflowModel.
If the former - each manifest class must be derived after pydantic.BaseModel
If the latter - no way now - I feel like additional metadata about steps can be held in

model_config = ConfigDict(
        json_schema_extra={
            "description": "This block represents inference from Roboflow multi-class classification model.",
            "docs": "https://inference.roboflow.com/workflows/classify_objects", <- additional keys here
        }
    )

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Is that in the manifest? I don't see BaseModel or base_model in there anywhere.

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no it is not, that's just required for pydantic to work

inference/enterprise/workflows/entities/steps.py Outdated Show resolved Hide resolved
@@ -676,15 +855,26 @@ def validate_field_binding(self, field_name: str, value: Any) -> None:


class BarcodeDetection(BaseModel, StepInterface):
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Should we rename this BarcodeModel since it inherits from BaseModel? (At the least should be BarcodeDetector vs Detection to match the part of speech of other blocks)

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that's pydantic.BaseModel.
BarcodeDetector is fine, we would also need to change QRCodeDetection in the same way

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ok, changed.
Also made the change non-breaking by double-aliasing step type - we will sun-set old ones in some time

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Also wonder if eg YoloWorld should be called YoloWorldModel

inference/enterprise/workflows/entities/steps.py Outdated Show resolved Hide resolved
@PawelPeczek-Roboflow
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I am branching out from this ref. point to re-structure the workflows steps - I propose to only fix issues in this PR, additional feature requests I will implement later

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Read through the rest & looks good!

@@ -432,31 +511,44 @@ def validate_field_binding(self, field_name: str, value: Any) -> None:


class InstanceSegmentationModel(ObjectDetectionModel):
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Is that in the manifest? I don't see BaseModel or base_model in there anywhere.

@PawelPeczek-Roboflow PawelPeczek-Roboflow merged commit e095fc7 into main Apr 3, 2024
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@PawelPeczek-Roboflow PawelPeczek-Roboflow deleted the feature/adjust_workflows_endpoints_add_descriptive_and_validation_capabilities branch April 3, 2024 18:29
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2 participants