Workflows - Deasy Labs

Workflows chain platform operations into scheduled, repeatable pipelines. Instead of manually re-running ingestion and classification as new documents arrive, define the sequence once and let it run on a cron cadence, or trigger it on demand.

Anatomy of a Workflow

Field	Description	Example
Name	Identifier shown in the UI’s workflow table	`"Nightly prepare: contracts"`
Cadence	Cron expression for the schedule	`"0 0 * * *"` (daily at midnight)
Stages	Ordered list, each stage runs after the previous completes	Ingest, then Classify
Jobs	API calls within a stage (endpoint + request body)	`/ocr/ingest`, `/classify_bulk`

Stages run sequentially; jobs inside a stage run together. Put ingestion and classification in separate stages so classification always sees the newly ingested documents.

Python SDK

Create Workflow
Run On Demand
List & Delete

from deasy import DeasyClient

client = DeasyClient(
    base_url="https://unstructured.your-company.com/rest/unstructured",
    username="your-username",
    password="your-password",
)

# Nightly ingest + classify pipeline (same shape the web UI creates)
result = client.workflows.upsert(
    workflow={
        "name": "Nightly prepare: contracts",
        "description": "Ingest new documents and re-classify every night",
        "cadence": "0 0 * * *",  # cron expression
        "stages": [
            {
                "jobs": [
                    {
                        "endpoint": "/ocr/ingest",
                        "endpoint_request_body": {
                            "data_connector_name": "my-s3-bucket",
                        },
                    },
                ],
            },
            {
                "jobs": [
                    {
                        "endpoint": "/classify_bulk",
                        "endpoint_request_body": {
                            "data_connector_name": "my-s3-bucket",
                        },
                    },
                ],
            },
        ],
    },
)

# Execute a workflow immediately instead of waiting for the cadence
client.workflows.execute(workflow_id="your-workflow-id")

# List workflows
workflows = client.workflows.list()

# Delete a workflow
client.workflows.delete(workflow_id="your-workflow-id")

API Reference

Upsert Workflow

Create or update a workflow

Execute Workflow

Trigger a workflow on demand

List Workflows

List all your workflows

Delete Workflow

Remove a workflow

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