Worfklow - Fix and updates following review

[paulnoirel]

Description

Following the review by the QA team:

PR to address the following:
PLT-2643 - User can create invalid workflow
PLT-2644 - Move check for workflow validity under update_config
PLT-2645 - User can delete default task queues
PLT-2646 - User can create node names longer than allowed char limit
PLT-2648 - User can create labeling task with negative "maximum labels per task"

Changes

• Validation enforced for max_contributions_per_user and nodes name

• No more need to check the validity of a workflow:
  Instead of the obscure

if not workflow.check_validity().get("errors"):
   updated_workflow = workflow.update_config(reposition=True)

One can use:

try:
    updated_workflow = workflow.update_config(reposition=True)
except ValueError as e:
    print(f"Validation failed: {e}")

- Replace "created_by" by "labeled_by" for clarify and consistency with other filters
- Add operators to increase clarify:
Before:
```python
labeled_by(["cly7gzohg07zz07v5fqs63zmx", "cl7k7a9x1764808vk6bm1hf8e", "ckruht2sob6xj0ybh7bu46mgo"]),
issue_category(["cmbgs41zu0k5u07y49o9p54o9"]),
dataset(["cm37vyets000z072314wxgt0l"]),
annotation(["cm37w0e0500lf0709ba7c42m9"]),

After:

labeled_by.is_one_of(["cly7gzohg07zz07v5fqs63zmx", "cl7k7a9x1764808vk6bm1hf8e", "ckruht2sob6xj0ybh7bu46mgo"]),
        issue_category.has_any_of(["cmbgs41zu0k5u07y49o9p54o9"]),
        dataset.is_one_of(["cm37vyets000z072314wxgt0l"]),
        annotation.has_any_of(["cm37w0e0500lf0709ba7c42m9"]),

• Replace "reset_config" by "reset_to_initial_nodes" to avoid problems with initial nodes and simplify workflows.

New logic:

import labelbox as lb
from labelbox.schema.workflow import NodeType

project_id = "cm85vrxbh0etn070d50dyei0g"

client = lb.Client(API_KEY)
project = client.get_project(project_id)

workflow = project.get_workflow()

initial_nodes = workflow.reset_to_initial_nodes()

done = workflow.add_node(type=NodeType.Done)

workflow.add_edge(initial_nodes.labeling, done)
workflow.add_edge(initial_nodes.rework, done)

try:
    updated_workflow = workflow.update_config()
    print("Workflow updated successfully!")
except ValueError as e:
    print(f"Validation failed: {e}")

or

import labelbox as lb
from labelbox.schema.workflow import (
    NodeType, 
    NodeOutput, 
    ProjectWorkflowFilter,
    LabelingConfig,
    ReworkConfig,
    labeled_by,
    metadata,
    sample,
    labeled_at,
    mp_condition,
    m_condition,
    labeling_time,
    review_time,
    issue_category,
    batch,
    dataset,
    annotation,
    consensus_average,
    model_prediction,
    natural_language,
    feature_consensus_average
)

from labelbox.schema.workflow.enums import IndividualAssignment, MatchFilters
from datetime import datetime

client = lb.Client(API_KEY)

project_id = "cm85vrxbh0etn070d50dyei0g"
project = client.get_project(project_id)

# Get workflow and create initial nodes with configs
workflow = project.get_workflow()

initial_nodes = workflow.reset_to_initial_nodes(
    labeling_config=LabelingConfig(
        instructions="This is the entry point",
        max_contributions_per_user=10
    ),
    rework_config=ReworkConfig(
        individual_assignment=[IndividualAssignment.LabelCreator]
    )
)

initial_labeling = initial_nodes.labeling
initial_rework = initial_nodes.rework

# Create other nodes
initial_review = workflow.add_node(
    type=NodeType.Review,
    name="Initial review task",
    group_assignment=["63a6a360-baa8-11ec-aedb-2592d52c761e",
                  "b3f89430-ea3a-11ef-b2a5-e1807377f8af"]
)

logic = workflow.add_node(
    type=NodeType.Logic,
    name="Logic node",
    match_filters=MatchFilters.Any,
    filters=ProjectWorkflowFilter([
        labeled_by.is_one_of(["cly7gzohg07zz07v5fqs63zmx", "cl7k7a9x1764808vk6bm1hf8e", "ckruht2sob6xj0ybh7bu46mgo"]),
        metadata([m_condition.contains("clo8t1njt00j807zkh5wz9uyt", ["test"])]),
        sample(23),
        labeled_at.between(datetime(2024, 3, 9, 5, 5, 42), datetime(2025, 4, 28, 13, 5, 42)),
        labeling_time.greater_than(1000),
        review_time.less_than_or_equal(100),
        issue_category.is_one_of(["cmbgs41zu0k5u07y49o9p54o9"]),
        batch.is_one_of(["ad210540-9d58-11ef-87dd-8501c518f349"]),
        dataset.is_one_of(["cm37vyets000z072314wxgt0l"]),
        annotation.is_one_of(["cm37w0e0500lf0709ba7c42m9"]),
        consensus_average(0.17, 0.61),
        model_prediction([mp_condition.is_one_of(["cm17qumj801ll07093toq47x3"], 1),
                          mp_condition.is_not_one_of(["cm4lbh7fv07q00709ewfk2b0o"], 2, 6),
                          mp_condition.is_none()]),
        natural_language("Birds in the sky/Blue sky/clouds/0.5", 0.178, 0.768),
        feature_consensus_average(0.17, 0.67, ["cm37w0e0500lf0709ba7c42m9"])
    ])
)

done = workflow.add_node(type=NodeType.Done)

custom_rework_1 = workflow.add_node(
    type=NodeType.CustomRework,
    name="Custom Rework 1",
    individual_assignment=IndividualAssignment.LabelCreator,
    group_assignment=["63a6a360-baa8-11ec-aedb-2592d52c761e",
              "b3f89430-ea3a-11ef-b2a5-e1807377f8af"]
)

review_2 = workflow.add_node(
    type=NodeType.Review,
    name="Review 2"
)

rework = workflow.add_node(
    type=NodeType.Rework,
    name="To rework"
)

custom_rework_2 = workflow.add_node(
    type=NodeType.CustomRework,
    name="Custom Rework 2",
    instructions="test"
)

done_2 = workflow.add_node(
    type=NodeType.Done,
    name="Well done"
)

# Create edges - updated to match screenshot
workflow.add_edge(initial_labeling, initial_review)
workflow.add_edge(initial_rework, initial_review)
workflow.add_edge(initial_review, logic, NodeOutput.Approved)
workflow.add_edge(initial_review, rework, NodeOutput.Rejected)
workflow.add_edge(logic, review_2, NodeOutput.If)
workflow.add_edge(logic, custom_rework_1, NodeOutput.Else)
workflow.add_edge(review_2, done, NodeOutput.Approved)
workflow.add_edge(review_2, custom_rework_2, NodeOutput.Rejected)
workflow.add_edge(custom_rework_2, done_2)

try:
    updated_workflow = workflow.update_config()
    print("Workflow updated successfully!")
except ValueError as e:
    print(f"Validation failed: {e}")

Fixes # see description

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)

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