from browser_use_sdk.v4 import BrowserUse

client = BrowserUse()
workspace = client.workspaces.create(name="live-hn-data")

first = client.runs.create(
    """
    Open https://news.ycombinator.com/ and return the top five story titles and
    URLs as JSON.

    Save a script at scripts/extract_top_stories.py that collects the same
    fields. The script must send a fresh request to the live page every time it
    runs. Do not hard-code story titles, save the page HTML, or read an old
    result. Print JSON with source_url set to https://news.ycombinator.com/ and
    include fetched_at, source_sha256, and stories.

    Run the script twice and save the outputs as proof/run-1.json and
    proof/run-2.json. Confirm both outputs have a fresh fetched_at value and
    five stories. Add scripts/README.md with the command to run it again.
    """,
    model="gpt-5.6-luna",
    model_params={"reasoning": {"effort": "xhigh"}},
    workspace_id=workspace.id,
)
client.runs.wait_for_completion(first.id)

saved = client.workspaces.files(workspace.id, prefix="scripts/")
print([file.path for file in saved.files])
print(f"Keep this workspace ID: {workspace.id}")

import { BrowserUse } from "browser-use-sdk/v4";

const client = new BrowserUse();
const workspace = await client.workspaces.create({ name: "live-hn-data" });

const first = await client.runs.create({
  task: `
    Open https://news.ycombinator.com/ and return the top five story titles and
    URLs as JSON.

    Save a script at scripts/extract_top_stories.py that collects the same
    fields. The script must send a fresh request to the live page every time it
    runs. Do not hard-code story titles, save the page HTML, or read an old
    result. Print JSON with source_url set to https://news.ycombinator.com/ and
    include fetched_at, source_sha256, and stories.

    Run the script twice and save the outputs as proof/run-1.json and
    proof/run-2.json. Confirm both outputs have a fresh fetched_at value and
    five stories. Add scripts/README.md with the command to run it again.
  `,
  model: "gpt-5.6-luna",
  modelParams: { reasoning: { effort: "xhigh" } },
  workspaceId: workspace.id,
});
await client.runs.waitForCompletion(first.id);

const saved = await client.workspaces.files(workspace.id, {
  prefix: "scripts/",
});
console.log(saved.files.map((file) => file.path));
console.log(`Keep this workspace ID: ${workspace.id}`);

from browser_use_sdk.v4 import BrowserUse

client = BrowserUse()
workspace_id = "your-workspace-id"

later = client.runs.create(
    """
    Run python scripts/extract_top_stories.py and return its JSON. Check that
    fetched_at is current, source_url is https://news.ycombinator.com/, and it
    has five stories. If the script fails or the result is malformed, inspect
    the live page and repair the saved script before returning the new result.
    """,
    model="gpt-5.6-luna",
    model_params={"reasoning": {"effort": "xhigh"}},
    workspace_id=workspace_id,
)
result = client.runs.wait_for_completion(later.id)
print(result.result)

import { BrowserUse } from "browser-use-sdk/v4";

const client = new BrowserUse();
const workspaceId = "your-workspace-id";

const later = await client.runs.create({
  task: `
    Run python scripts/extract_top_stories.py and return its JSON. Check that
    fetched_at is current, source_url is https://news.ycombinator.com/, and it
    has five stories. If the script fails or the result is malformed, inspect
    the live page and repair the saved script before returning the new result.
  `,
  model: "gpt-5.6-luna",
  modelParams: { reasoning: { effort: "xhigh" } },
  workspaceId,
});
const result = await client.runs.waitForCompletion(later.id);
console.log(result.result);