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Use this walkthrough to start an Agent Builder session, poll until the build finishes, and run the saved Agent.
Agent Builder is currently single-shot. Put the full request in your first prompt: URL, fields, pagination, authentication needs, output shape, and anything to skip.

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Before you start

Generate an API key from your Sequentum dashboard, then choose the prompt you want to send. 
import os
os.environ["SEQUENTUM_API_KEY"] = "sk-..."

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Start Agent Builder

Send your prompt to Agent Builder. Replace the URL and fields with your target; the response returns a sessionId. 
import os
import requests

prompt = "Get the shoe information from https://training.sequentum.com/ShoeStore/product.html?id=1"

response = requests.post(
    "https://dashboard.sequentum.com/api/v1/agent-builder/start",
    headers={"Authorization": f"ApiKey {os.environ['SEQUENTUM_API_KEY']}"},
    json={"prompt": prompt},
)

session = response.json()
print(session["sessionId"])

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Wait for the agent to build

Poll the session until status is completed. The completed response includes the saved Agent id. 
import os
import time
import requests

session_id = "ab_123..."

while True:
    response = requests.get(
        f"https://dashboard.sequentum.com/api/v1/agent-builder/{session_id}/status",
        headers={"Authorization": f"ApiKey {os.environ['SEQUENTUM_API_KEY']}"},
    )
    body = response.json()

    if body["status"] == "completed":
        agent_id = body.get("agentId") or body["configId"]
        print(f"Agent built: {agent_id}")
        break

    if body["status"] == "error":
        raise RuntimeError(body.get("error", "build failed"))

    time.sleep(5)

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Start a Run

Start the saved Agent asynchronously. The response returns a Run id you can poll. 
import os
import requests

agent_id = "12345"

response = requests.post(
    f"https://dashboard.sequentum.com/api/v1/agent/{agent_id}/start",
    headers={"Authorization": f"ApiKey {os.environ['SEQUENTUM_API_KEY']}"},
    json={"isRunSynchronously": False},
)

run = response.json()
run_id = run["id"]
print(run_id)

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Wait for the Run

Poll run status until the Run is finished. Completed and Success mean the Run finished successfully. 
import time

FINISHED = {6, 8, 9, 10, 11, "Failure", "Stopped", "Completed", "Success", "Skipped"}
SUCCESSFUL = {9, 10, "Completed", "Success"}

while True:
    response = requests.get(
        f"https://dashboard.sequentum.com/api/v1/agent/{agent_id}/run/{run_id}/status",
        headers={"Authorization": f"ApiKey {os.environ['SEQUENTUM_API_KEY']}"},
    )
    run = response.json()

    if run["status"] in FINISHED:
        if run["status"] not in SUCCESSFUL:
            raise RuntimeError(f"Run did not complete successfully: {run}")
        break

    time.sleep(5)

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List output files

After the Run finishes, list its output files and choose a file to download. 
files_response = requests.get(
    f"https://dashboard.sequentum.com/api/v1/agent/{agent_id}/run/{run_id}/files",
    headers={"Authorization": f"ApiKey {os.environ['SEQUENTUM_API_KEY']}"},
)
files = files_response.json()
file_id = files[0]["id"]
file_name = files[0].get("name") or f"run-{run_id}-output"

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Download an output file

Download endpoints redirect to the file content. Follow redirects when saving the file. 
download_response = requests.get(
    f"https://dashboard.sequentum.com/api/v1/agent/{agent_id}/run/{run_id}/file/{file_id}/download",
    headers={"Authorization": f"ApiKey {os.environ['SEQUENTUM_API_KEY']}"},
)

with open(file_name, "wb") as f:
    f.write(download_response.content)
Runs can produce multiple output files. List files again if the Agent writes separate datasets or downloads source files.

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What success looks like

When the build finishes, Agent Builder gives you a saved Agent. A good first build has:
  • A clear Agent name and description.
  • Fields that match your prompt.
  • A test run with records shaped like the entity you asked for.
For the ShoeStore prompt, the output file should contain records like this: 
[
  {
    "name": "Trail running shoe",
    "price": "$89.99",
    "sku": "SHOE-001",
    "availability": "In stock",
    "productUrl": "https://training.sequentum.com/ShoeStore/product.html?id=1"
  }
]
If the records are missing a field or include the wrong items, start a new build with a tighter prompt. Mention the missing field, the page pattern, and the section or records to skip.

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Write a good prompt

Start with the exact page or site section: “Extract product data from https://....”
Say “follow all paginated pages” or “first 50 pages only” — Agent Builder will scope the run.
Agent Builder can infer a schema, but naming fields gives you more predictable output. Ask for “one row per product” or “one row per invoice” when the page contains repeated records.

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What’s next

Agent Builder sessions

Understand session status, stopping a build, and the handoff to the saved Agent.

Schedule recurring runs

Run the saved Agent automatically on a cadence you define.