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The AI copilot can generate a complete workflow graph from a natural language description. You create a copilot session linked to a workflow, describe what you want, and the copilot generates the blocks and edges. You can iterate through multiple chat turns to refine the workflow.
Prerequisites:
  • Authentication configured (see Authentication guide)
1

Create a workflow

Create an empty workflow that the copilot will populate.Endpoint: POST /api/workflows
response = requests.post(
    f"{BASE_URL}/api/workflows",
    headers=headers,
    json={"name": "Email Classifier"},
)
workflow = response.json()
wf_id = workflow["id"]
2

Start a copilot session

Create a copilot session linked to the workflow.Endpoint: POST /api/copilot/sessions
response = requests.post(
    f"{BASE_URL}/api/copilot/sessions",
    headers=headers,
    json={"workflow_id": wf_id},
)
session = response.json()
session_id = session["id"]
3

Describe your workflow

Send a natural language description via the chat endpoint. The copilot responds with a streaming SSE response that includes the generated workflow graph.Endpoint: POST /api/copilot/sessions/{id}/chat
response = requests.post(
    f"{BASE_URL}/api/copilot/sessions/{session_id}/chat",
    headers=headers,
    json={
        "message": "Build a workflow that takes an email as input, classifies it as spam/not-spam using an LLM, and outputs the classification with confidence score.",
    },
    stream=True,
)

message_id = None
for line in response.iter_lines():
    if not line:
        continue
    text = line.decode("utf-8")
    if text.startswith("data: "):
        event = json.loads(text[6:])
        if event.get("message_id"):
            message_id = event["message_id"]
        if event["event"] == "chunk":
            print(event["content"], end="")
print(f"\nMessage ID: {message_id}")
4

Save the copilot's suggestion

Save the copilot’s generated workflow graph as a snapshot. This applies the blocks and edges to the workflow.Endpoint: POST /api/copilot/sessions/{id}/messages/{mid}/snapshot
response = requests.post(
    f"{BASE_URL}/api/copilot/sessions/{session_id}/messages/{message_id}/snapshot",
    headers=headers,
)
print(response.json())
5

Execute the workflow

Run the copilot-built workflow with input data.Endpoint: POST /api/workflows/{id}/execute
You can also build workflows programmatically via PUT /api/workflows/{id}/graph — see the Build Workflows Programmatically guide.
response = requests.post(
    f"{BASE_URL}/api/workflows/{wf_id}/execute",
    headers=headers,
    json={"variables": {"email": "Congratulations! You've won a free iPhone..."}},
)
print(response.json())

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What’s Next

Workflows (Programmatic)

Fine-tune workflows by editing the graph directly.

Workflows

Understand block types and graph execution.

Copilot API Reference

Full endpoint documentation.