Workflow API Documentation

A Workflow in Slate is a flexible, visual representation of a process or automation. It consists of interconnected nodes (steps, triggers, actions, outputs) and edges (connections between nodes), allowing you to design and execute complex logic flows.

Key Concepts

Workflow: A schema consisting of nodes and edges that defines the sequence of actions.
Node: A step in the process (e.g., trigger, LLM request, data processing, output).
Edge: Connects two nodes, defining the direction of the flow.
Data: The structure describing all nodes, edges, the start node, and viewport parameters.

Workflow Data Structure Example

{
  "id": 6,
  "project": 307,
  "title": "New workflow",
  "data": {
    "edges": [
      {
        "id": "xy-edge__3d63f846-0f6a-478c-b91c-5921259429c1-a67fef47-c844-4489-9024-ff894b5d7465",
        "type": "custom-edge",
        "source": "3d63f846-0f6a-478c-b91c-5921259429c1",
        "target": "a67fef47-c844-4489-9024-ff894b5d7465",
        "style": \{"stroke": "#76A9FA", "strokeWidth": 2\},
        "animated": false,
        "markerEnd": "edge-target",
        "markerStart": "edge-source"
      }
    ],
    "nodes": [
      {
        "id": "3d63f846-0f6a-478c-b91c-5921259429c1",
        "type": "trigger-node",
        "data": \{ ... \},
        ...
      },
      {
        "id": "a67fef47-c844-4489-9024-ff894b5d7465",
        "type": "basic-node",
        "data": \{ ... \},
        ...
      },
      {
        "id": "2dfa426d-4233-49f2-8532-4b82f57640b6",
        "type": "output-node",
        "data": \{ ... \},
        ...
      }
    ],
    "viewport": \{"x": 0.25, "y": 152.25, "zoom": 0.5\},
    "start_node": "a67fef47-c844-4489-9024-ff894b5d7465"
  }
}

API Endpoints

Create a Workflow

Python
import requests

url = "https://scriptrun.ai/api/v1/workflows/"
headers = \{"X-Api-Key": "<Your API Key>"\}
data = {
    "project": 307,
    "title": "New workflow",
    "data": \{ ... \}  # see structure above
}

response = requests.post(url, headers=headers, json=data)
print(response.json())

Shell
curl -X POST "https://scriptrun.ai/api/v1/workflows/" \
-H "X-Api-Key: <Your API Key>" \
-H "Content-Type: application/json" \
-d '{
  "project": 307,
  "title": "New workflow",
  "data": \{ ... \}
}'

POST `/api/v1/workflows/`

Summary: Creates a new workflow.

Request Body:

Name	Type	Required	Description
`project`	`integer`	Yes	Project ID to which the workflow belongs.
`title`	`string`	Yes	Name/title of the workflow.
`data`	`object`	Yes	Workflow structure (nodes, edges, viewport)

Responses:

201: Workflow successfully created.
400: Invalid input or missing required parameters.

Retrieve Workflows

Python
url = "https://scriptrun.ai/api/v1/workflows/"
headers = \{"X-Api-Key": "<Your API Key>"\}
params = \{"project": 307\}

response = requests.get(url, headers=headers, params=params)
print(response.json())

Shell
curl -X GET "https://scriptrun.ai/api/v1/workflows/?project=307" \
-H "X-Api-Key: <Your API Key>"

GET `/api/v1/workflows/`

Summary: Retrieves a list of workflows, optionally filtered by project.

Parameters:

Name	In	Type	Required	Description
`project`	query	`integer`	No	Filter workflows by project ID.
`title`	query	`string`	No	Filter by workflow title (case-insensitive).
`page`	query	`integer`	No	Page number for pagination.

Responses:

200: Returns a paginated list of workflows.

Retrieve a Specific Workflow

Python
url = "https://scriptrun.ai/api/v1/workflows/6/"
headers = \{"X-Api-Key": "<Your API Key>"\}

response = requests.get(url, headers=headers)
print(response.json())

Shell
curl -X GET "https://scriptrun.ai/api/v1/workflows/6/" \
-H "X-Api-Key: <Your API Key>"

GET `/api/v1/workflows/\{id\}/`

Summary: Retrieves the details of a specific workflow by its ID.

Parameters:

Name	In	Type	Required	Description
`id`	path	`integer`	Yes	ID of the workflow to fetch.

Responses:

200: Returns the workflow details.
404: Workflow not found.

Update a Workflow

Python
url = "https://scriptrun.ai/api/v1/workflows/6/"
headers = \{"X-Api-Key": "<Your API Key>"\}
data = {
    "title": "Updated Workflow Title",
    "data": \{ ... \}
}

response = requests.patch(url, headers=headers, json=data)
print(response.json())

Shell
curl -X PATCH "https://scriptrun.ai/api/v1/workflows/6/" \
-H "X-Api-Key: <Your API Key>" \
-H "Content-Type: application/json" \
-d '{
  "title": "Updated Workflow Title",
  "data": \{ ... \}
}'

PATCH `/api/v1/workflows/\{id\}/`

Summary: Updates an existing workflow.

Parameters:

Name	In	Type	Required	Description
`id`	path	`integer`	Yes	ID of the workflow to update.

Request Body:

Name	Type	Required	Description
`title`	`string`	No	Updated workflow title.
`data`	`object`	No	Updated workflow structure.

Responses:

200: Workflow successfully updated.
404: Workflow not found.

Delete a Workflow

Python
url = "https://scriptrun.ai/api/v1/workflows/6/"
headers = \{"X-Api-Key": "<Your API Key>"\}

response = requests.delete(url, headers=headers)
print(response.status_code)

Shell
curl -X DELETE "https://scriptrun.ai/api/v1/workflows/6/" \
-H "X-Api-Key: <Your API Key>"

DELETE `/api/v1/workflows/\{id\}/`

Summary: Deletes a specific workflow by its ID.

Parameters:

Name	In	Type	Required	Description
`id`	path	`integer`	Yes	ID of the workflow to delete.

Responses:

204: Workflow successfully deleted.
404: Workflow not found.

Additional Workflow Endpoints

Check Workflow Structure

POST `/api/v1/workflows/check_workflow/`

Summary: Validates the structure of a workflow before saving or running it.

Python
import requests
url = "https://scriptrun.ai/api/v1/workflows/check_workflow/"
headers = \{"X-Api-Key": "<Your API Key>"\}
data = {
  "data": {
    "nodes": [...],
    "edges": [...],
    "viewport": \{"x": 0, "y": 0, "zoom": 1\},
    "start_node": "node-id-1"
  }
}
response = requests.post(url, headers=headers, json=data)
print(response.json())

Shell
curl -X POST "https://scriptrun.ai/api/v1/workflows/check_workflow/" \
  -H "X-Api-Key: <Your API Key>" \
  -H "Content-Type: application/json" \
  -d '{
    "data": {
      "nodes": [...],
      "edges": [...],
      "viewport": \{"x": 0, "y": 0, "zoom": 1\},
      "start_node": "node-id-1"
    }
  }'

Get Node Schemas for Frontend

GET `/api/v1/workflows/get_nodes/`

Summary: Retrieves the available node schemas for rendering and configuration in the frontend.

Python
import requests
url = "https://scriptrun.ai/api/v1/workflows/get_nodes/"
headers = \{"X-Api-Key": "<Your API Key>"\}
response = requests.get(url, headers=headers)
print(response.json())

Shell
curl -X GET "https://scriptrun.ai/api/v1/workflows/get_nodes/" \
  -H "X-Api-Key: <Your API Key>"

Run a Workflow

POST `/api/v1/workflows/run/`

Summary: Starts the execution of a workflow. Requires a task_id as a query parameter.

Python
import requests
url = "https://scriptrun.ai/api/v1/workflows/run/?task_id=123e4567-e89b-12d3-a456-426614174000"
headers = \{"X-Api-Key": "<Your API Key>"\}
data = {
  "data": {
    "nodes": [...],
    "edges": [...],
    "viewport": \{"x": 0, "y": 0, "zoom": 1\},
    "start_node": "node-id-1"
  }
}
response = requests.post(url, headers=headers, json=data)
print(response.json())

Shell
curl -X POST "https://scriptrun.ai/api/v1/workflows/run/?task_id=123e4567-e89b-12d3-a456-426614174000" \
  -H "X-Api-Key: <Your API Key>" \
  -H "Content-Type: application/json" \
  -d '{
    "data": {
      "nodes": [...],
      "edges": [...],
      "viewport": \{"x": 0, "y": 0, "zoom": 1\},
      "start_node": "node-id-1"
    }
  }'

Get Workflow Node Result

GET `/api/v1/workflows/workflow_result/`

Summary: Retrieves the result for a specific node in a workflow run.

Python
import requests
url = "https://scriptrun.ai/api/v1/workflows/workflow_result/?task_id=123e4567-e89b-12d3-a456-426614174000&node_id=a67fef47-c844-4489-9024-ff894b5d7465"
headers = \{"X-Api-Key": "<Your API Key>"\}
response = requests.get(url, headers=headers)
print(response.json())

Shell
curl -X GET "https://scriptrun.ai/api/v1/workflows/workflow_result/?task_id=123e4567-e89b-12d3-a456-426614174000&node_id=a67fef47-c844-4489-9024-ff894b5d7465" \
  -H "X-Api-Key: <Your API Key>"

Workflow Run History

GET `/api/v1/workflows/history/`

Summary: Retrieves the history of workflow runs.

Python
import requests
url = "https://scriptrun.ai/api/v1/workflows/history/?workflow_id=6&limit=10"
headers = \{"X-Api-Key": "<Your API Key>"\}
response = requests.get(url, headers=headers)
print(response.json())

Shell
curl -X GET "https://scriptrun.ai/api/v1/workflows/history/?workflow_id=6&limit=10" \
  -H "X-Api-Key: <Your API Key>"

Workflow Data Structure

nodes: List of nodes, each containing:
- id: Unique node identifier.
- type: Node type (e.g., "trigger-node", "basic-node", "output-node").
- data: Node parameters (name, settings, schema, messages, etc.).
- position, measured, selected, etc. — visualization parameters.
edges: List of connections between nodes, each containing:
- id: Unique edge identifier.
- source: Source node id.
- target: Target node id.
- type, style, markerEnd, markerStart, etc. — visualization parameters.
viewport: Viewport parameters (x, y, zoom).
start_node: id of the start node (usually the first action or trigger).

Summary

A Workflow is a visual process schema consisting of nodes and edges.
The API allows you to create, retrieve, update, and delete workflows.
The data structure supports complex scenarios, branching, parameters, and visualization.
For workflow execution , use the dedicated endpoints.я

Working with Input Data

Overview

When running a workflow, you can pass input_data that will be available in all nodes through variables. This is useful for parameterizing workflows and making them reusable with different inputs.

Key Features:

✅ Supports valid JSON (objects, arrays, primitives)
✅ Supports plain text (will be wrapped automatically)
✅ Access data in nodes using {{ input.field_name }} syntax
✅ Supports nested objects and arrays

POST `/api/v1/workflows/{id}/run/`

Summary: Runs a workflow with optional input data.

Parameters:

Name	In	Type	Required	Description
`id`	path	`integer`	Yes	ID of the workflow to run.

Request Body:

Name	Type	Required	Description
`input_data`	`object` / `array` / `string`	No	Input data accessible in nodes via `{{ input.* }}` variables.

Example 1: Object Input Data

Pass structured data as a JSON object:

Python
import requests

url = "https://scriptrun.ai/api/v1/workflows/6/run/"
headers = {"X-Api-Key": "<Your API Key>"}
data = {
  "input_data": {
    "user_name": "John Doe",
    "email": "[email protected]",
    "age": 30,
    "preferences": {
      "theme": "dark",
      "notifications": True
    },
    "tags": ["admin", "developer"]
  }
}

response = requests.post(url, headers=headers, json=data)
print(response.json())

Shell
curl -X POST "https://scriptrun.ai/api/v1/workflows/6/run/" \
  -H "X-Api-Key: <Your API Key>" \
  -H "Content-Type: application/json" \
  -d '{
    "input_data": {
      "user_name": "John Doe",
      "email": "[email protected]",
      "age": 30,
      "preferences": {
        "theme": "dark",
        "notifications": true
      },
      "tags": ["admin", "developer"]
    }
  }'

Accessing in nodes:

{{ input.user_name }}              → "John Doe"
{{ input.email }}                  → "[email protected]"
{{ input.age }}                    → 30
{{ input.preferences.theme }}      → "dark"
{{ input.tags[0] }}                → "admin"
{{ input.tags[1] }}                → "developer"

Example 2: Array Input Data

Pass an array of items:

Python
data = {
  "input_data": [
    {"id": 1, "name": "Alice", "role": "admin"},
    {"id": 2, "name": "Bob", "role": "user"}
  ]
}

response = requests.post(url, headers=headers, json=data)

Shell
curl -X POST "https://scriptrun.ai/api/v1/workflows/6/run/" \
  -H "X-Api-Key: <Your API Key>" \
  -H "Content-Type: application/json" \
  -d '{
    "input_data": [
      {"id": 1, "name": "Alice", "role": "admin"},
      {"id": 2, "name": "Bob", "role": "user"}
    ]
  }'

Accessing in nodes:

{{ input[0].name }}     → "Alice"
{{ input[1].role }}     → "user"
{{ input[0].id }}       → 1

Example 3: Plain Text Input

Pass plain text (will be wrapped automatically):

Python
data = {
  "input_data": "Hello, this is a simple text input"
}

response = requests.post(url, headers=headers, json=data)

Accessing in nodes:

{{ input.__raw_input__ }}    → "Hello, this is a simple text input"

Using Input Data in Nodes

In HTTP Node

{
  "url": "https://api.example.com/users",
  "method": "POST",
  "headers": {
    "Authorization": "Bearer {{ input.api_token }}",
    "Content-Type": "application/json"
  },
  "body": {
    "name": "{{ input.user_name }}",
    "email": "{{ input.email }}",
    "age": "{{ input.age }}"
  }
}

In LLM Node

{
  "messages": [
    {
      "role": "system",
      "message": "You are a helpful assistant"
    },
    {
      "role": "user",
      "message": "Create a welcome message for {{ input.user_name }} with email {{ input.email }}"
    }
  ]
}

Complex Example: Nested Structures

Python
data = {
  "input_data": {
    "company": {
      "name": "Acme Inc",
      "departments": [
        {
          "name": "IT",
          "employees": [
            {"name": "Alice", "role": "Developer"},
            {"name": "Bob", "role": "DevOps"}
          ]
        },
        {
          "name": "HR",
          "employees": [
            {"name": "Charlie", "role": "Manager"}
          ]
        }
      ]
    }
  }
}

Accessing nested data:

{{ input.company.name }}                          → "Acme Inc"
{{ input.company.departments[0].name }}           → "IT"
{{ input.company.departments[0].employees[0].name }} → "Alice"
{{ input.company.departments[0].employees[1].role }} → "DevOps"
{{ input.company.departments[1].employees[0].name }} → "Charlie"

Variable Syntax

ScriptRun supports flexible variable syntax for accessing input data:

Syntax	Description	Example
`{{ input.field }}`	Access object field	`{{ input.user_name }}`
`{{ input.nested.field }}`	Access nested field	`{{ input.preferences.theme }}`
`{{ input[0] }}`	Access array element by index	`{{ input[0] }}`
`{{ input.users[0].name }}`	Access field in array element	`{{ input.users[0].name }}`
`{{ input.tags[1] }}`	Access nested array element	`{{ input.tags[1] }}`

Both syntaxes work:

Dot notation: {{ input.tags.0 }}
Bracket notation: {{ input.tags[0] }}

Error Handling

Invalid JSON:

Plain text or invalid JSON is automatically wrapped in {"__raw_input__": "text"}
Access it via {{ input.__raw_input__ }}

Missing Fields:

If a field doesn't exist, it returns an empty value
Example: {{ input.nonexistent_field }} → {}

Empty Input:

If no input_data is provided, it defaults to {}

Best Practices

Use descriptive field names: user_name instead of n
Validate required fields: Use Trigger node with required input fields
Keep structure consistent: Use the same data structure for similar workflows
Test with sample data: Verify your variables work before running in production
Document your inputs: Add comments in your workflow about expected input structure

Responses

200: Workflow execution started successfully
400: Invalid input data or workflow structure
404: Workflow not found

Key Concepts​

Workflow Data Structure Example​

API Endpoints​

Create a Workflow​

POST /api/v1/workflows/​

Retrieve Workflows​

GET /api/v1/workflows/​

Retrieve a Specific Workflow​

GET /api/v1/workflows/\{id\}/​

Update a Workflow​

PATCH /api/v1/workflows/\{id\}/​

Delete a Workflow​

DELETE /api/v1/workflows/\{id\}/​

Additional Workflow Endpoints​

Check Workflow Structure​

POST /api/v1/workflows/check_workflow/​

Get Node Schemas for Frontend​

GET /api/v1/workflows/get_nodes/​

Run a Workflow​

POST /api/v1/workflows/run/​

Get Workflow Node Result​

GET /api/v1/workflows/workflow_result/​

Workflow Run History​

GET /api/v1/workflows/history/​

Workflow Data Structure​

Summary​

Working with Input Data​

Overview​

POST /api/v1/workflows/{id}/run/​

Example 1: Object Input Data​

Example 2: Array Input Data​

Example 3: Plain Text Input​

Using Input Data in Nodes​

In HTTP Node​

In LLM Node​

Complex Example: Nested Structures​

Variable Syntax​

Error Handling​

Best Practices​

Responses​

Key Concepts

Workflow Data Structure Example

API Endpoints

Create a Workflow

POST `/api/v1/workflows/`

Retrieve Workflows

GET `/api/v1/workflows/`

Retrieve a Specific Workflow

GET `/api/v1/workflows/\{id\}/`

Update a Workflow

PATCH `/api/v1/workflows/\{id\}/`

Delete a Workflow

DELETE `/api/v1/workflows/\{id\}/`

Additional Workflow Endpoints

Check Workflow Structure

POST `/api/v1/workflows/check_workflow/`

Get Node Schemas for Frontend

GET `/api/v1/workflows/get_nodes/`

Run a Workflow

POST `/api/v1/workflows/run/`

Get Workflow Node Result

GET `/api/v1/workflows/workflow_result/`

Workflow Run History

GET `/api/v1/workflows/history/`

Workflow Data Structure

Summary

Working with Input Data

Overview

POST `/api/v1/workflows/{id}/run/`

Example 1: Object Input Data

Example 2: Array Input Data

Example 3: Plain Text Input

Using Input Data in Nodes

In HTTP Node

In LLM Node

Complex Example: Nested Structures

Variable Syntax

Error Handling

Best Practices

Responses