Basic Usage
To runperform-web-task asynchronously, set the async parameter to true in your request. The API will return immediately with a workflow_id that you can use to poll for results.
import { client, Tools } from 'anchorbrowser';
client.setConfig({ auth: () => process.env.ANCHORBROWSER_API_KEY });
// Start async task
const response = await Tools.performWebTask({
body: {
prompt: 'Extract the main heading and first paragraph from the page',
url: 'https://docs.anchorbrowser.io',
async: true
}
});
console.log('Workflow ID:', response.data.workflow_id);
console.log('Status:', response.data.status);
from anchorbrowser import Anchorbrowser
import os
anchor_client = Anchorbrowser(api_key=os.environ.get("ANCHORBROWSER_API_KEY"))
# Start async task
response = anchor_client.tools.perform_web_task(
prompt='Extract the main heading and first paragraph from the page',
url='https://docs.anchorbrowser.io',
async_=True
)
print('Workflow ID:', response.data.workflow_id)
print('Status:', response.data.status)
Show Parameters
Show Parameters
Parameters
The asyncperform-web-task accepts the following parameters:| Parameter | Type | Required | Description |
|---|---|---|---|
prompt | string | Yes | The task to be autonomously completed |
url | string | No | The URL of the webpage. If not provided, the tool will use the current page in the session |
sessionId | string | No | An optional browser session identifier to reference an existing running browser session. When passed, the tool will be executed on the provided browser session |
async | boolean | No | Whether to run the task asynchronously. If true, the task will be run asynchronously and the response will include a workflow ID. Defaults to false |
agent | string | No | The AI agent to use for task completion. Options: browser-use (default), openai-cua, gemini-computer-use, anthropic-cua |
provider | string | No | The AI provider to use for task completion. Options: openai, gemini, groq, azure, xai |
model | string | No | The specific model to use for task completion. See Available Models for more information |
detect_elements | boolean | No | Enable element detection for better interaction accuracy. Improves the agent’s ability to identify and interact with UI elements |
human_intervention | boolean | No | Allow human intervention during task execution. When enabled, the agent can request human input for ambiguous situations |
max_steps | integer | No | Maximum number of steps the agent can take to complete the task. Defaults to 200 |
secret_values | object | No | Secret values to pass to the agent for secure credential handling. Keys and values are passed as environment variables to the agent |
highlight_elements | boolean | No | Whether to highlight elements during task execution for better visibility |
output_schema | object | No | JSON Schema defining the expected structure of the output data |
Polling for Results
After starting an async task, you’ll receive aworkflow_id in the response. Use this ID to poll the status endpoint until the task completes.
Status Endpoint
const statusResponse = await Tools.getPerformWebTaskStatus({
path: { workflowId }
});
// Status can be: 'RUNNING', 'COMPLETED', or 'FAILED'
if (statusResponse.data.status === 'RUNNING') {
console.log('Still running...');
} else if (statusResponse.data.status === 'COMPLETED') {
console.log('Result:', statusResponse.data.result);
} else if (statusResponse.data.status === 'FAILED') {
console.error('Error:', statusResponse.data.error);
}
status_response = anchor_client.tools.get_perform_web_task_status(workflow_id)
# Status can be: 'RUNNING', 'COMPLETED', or 'FAILED'
if status_response.data.status == 'RUNNING':
print('Still running...')
elif status_response.data.status == 'COMPLETED':
print('Result:', status_response.data.result)
elif status_response.data.status == 'FAILED':
print('Error:', status_response.data.error)
Response Statuses
RUNNING: The workflow is currently executingCOMPLETED: The workflow has completed. Theresultfield contains the task output as a string.
The status will be
COMPLETED even if the agent fails to complete the task, since the workflow execution itself succeeded. Always check the result field to verify whether the agent completed the task successfully or encountered an error.FAILED: The workflow has failed. Theerrorfield contains the error message
Complete Example
import { client, Tools } from 'anchorbrowser';
(async () => {
client.setConfig({ auth: () => process.env.ANCHORBROWSER_API_KEY });
// Start multiple async tasks in parallel
const responses = await Promise.all([
Tools.performWebTask({
body: {
prompt: 'Extract the main heading',
url: 'https://docs.anchorbrowser.io',
async: true
}
}),
Tools.performWebTask({
body: {
prompt: 'Get the first paragraph',
url: 'https://example.com',
async: true
}
})
]);
const workflowIds = responses.map(response => response.data.workflow_id);
console.log('Started', workflowIds.length, 'tasks');
// Poll all tasks
const results = await Promise.all(
workflowIds.map(async (wokflowId) => {
let status = 'RUNNING';
while (status === 'RUNNING') {
await new Promise(resolve => setTimeout(resolve, 2000));
const statusResponse = await Tools.getPerformWebTaskStatus({
path: { workflowId: wokflowId }
});
status = statusResponse.data.status;
if (status === 'COMPLETED') {
return statusResponse.data.result;
} else if (status === 'FAILED') {
throw new Error(statusResponse.data.error);
}
}
})
);
console.log('All tasks completed:', results);
})();
from anchorbrowser import Anchorbrowser
import os
import time
import requests
anchor_client = Anchorbrowser(api_key=os.environ.get("ANCHORBROWSER_API_KEY"))
# Start multiple async tasks in parallel
responses = [
anchor_client.tools.perform_web_task(
prompt='Extract the main heading',
url='https://docs.anchorbrowser.io',
async_=True
),
anchor_client.tools.perform_web_task(
prompt='Get the first paragraph',
url='https://example.com',
async_=True
)
]
workflow_ids = [response.data.workflow_id for response in responses]
print('Started', len(workflow_ids), 'tasks')
# Poll all tasks
results = []
for workflow_id in workflow_ids:
status = 'RUNNING'
while status == 'RUNNING':
time.sleep(2)
status_response = anchor_client.tools.get_perform_web_task_status(workflow_id)
status = status_response.data.status
if status == 'COMPLETED':
results.append(status_response.data.result)
break
elif status == 'FAILED':
raise Exception(status_response.data.error)
print('All tasks completed:', results)