Agent (v2)

V2 agent models and file handling.

Models

Model	API String	Cost per Step
Browser Use 2.0 (default)	browser-use-2.0	$0.006
Browser Use LLM	browser-use-llm	$0.002
O3	o3	$0.03
Gemini Flash Latest	gemini-flash-latest	$0.0075
Gemini Flash Lite Latest	gemini-flash-lite-latest	$0.005
Claude Sonnet 4.5	claude-sonnet-4-5-20250929	$0.05
Claude Sonnet 4.6	claude-sonnet-4.6	$0.05

Pass llm explicitly to select a model:

Python

result = await client.run("...", llm="browser-use-2.0")

const result = await client.run("...", { llm: "browser-use-2.0" });

---

Files

Upload images, PDFs, documents, and text files (10 MB max) to sessions, and download output files from completed tasks.

Upload a file

Get a presigned URL, then upload via POST.

Python

import httpx
from browser_use_sdk import AsyncBrowserUse

client = AsyncBrowserUse()
session = await client.sessions.create()

upload = await client.files.session_url(
    session.id,
    file_name="input.pdf",
    content_type="application/pdf",
    size_bytes=1024,
)

with open("input.pdf", "rb") as f:
    async with httpx.AsyncClient() as http:
        await http.post(upload.url, content=f.read(), headers={"Content-Type": "application/pdf"})

result = await client.run("Summarize the uploaded PDF", session_id=session.id)

import { BrowserUse } from "browser-use-sdk";
import { readFileSync } from "fs";

const client = new BrowserUse();
const session = await client.sessions.create();

const upload = await client.files.sessionUrl(session.id, {
  fileName: "input.pdf",
  contentType: "application/pdf",
  sizeBytes: 1024,
});

await fetch(upload.url, {
  method: "POST",
  body: readFileSync("input.pdf"),
  headers: { "Content-Type": "application/pdf" },
});

const result = await client.run("Summarize the uploaded PDF", { sessionId: session.id });

Presigned URLs expire after 120 seconds. Max file size: 10 MB.

Download task output files

Python

result = await client.tasks.get(task_id)
for file in result.output_files:
    output = await client.files.task_output(task_id, file.id)
    print(output.download_url)  # download URL

const result = await client.tasks.get(taskId);
for (const file of result.outputFiles) {
  const output = await client.files.taskOutput(taskId, file.id);
  console.log(output.downloadUrl);
}

---

Streaming steps

Use async for to yield steps as the agent works.

Python

from browser_use_sdk import AsyncBrowserUse

client = AsyncBrowserUse()
run = client.run("Find the most upvoted post on Reddit r/technology today")
async for step in run:
    print(f"Step {step.number}: {step.next_goal}")
    print(f"  URL: {step.url}")

print(run.result.output)  # final result after iteration

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

const client = new BrowserUse();
const run = client.run("Find the most upvoted post on Reddit r/technology today");
for await (const step of run) {
  console.log(`Step ${step.number}: ${step.nextGoal}`);
  console.log(`  URL: ${step.url}`);
}

console.log(run.result?.output);  // final result after iteration

---

Key parameters

Parameter	Type	Description
task	str	What you want the agent to do. 1-50,000 characters.
llm	str	Model override. Default: Browser Use 2.0.
output_schema / schema	Pydantic / Zod	Schema for structured output.
session_id	str	Reuse an existing session. Omit for auto-session.
start_url	str	Initial page URL. Saves steps — send the agent directly there.
secrets	dict	Domain-specific credentials. See Authentication.
allowed_domains	list[str]	Restrict agent to these domains only.
session_settings	SessionSettings	Proxy, profile, browser config. See Profiles.
flash_mode	bool	Faster but less careful navigation.
thinking	bool	Enable extended reasoning.
vision	bool | str	Enable screenshots for the agent.
highlight_elements	bool	Highlight interactive elements on the page.
system_prompt_extension	str	Append custom instructions to the system prompt.
judge	bool	Enable quality judge to verify output.
skill_ids	list[str]	Skills the agent can use during the task.
op_vault_id	str	1Password vault ID for auto-fill credentials and 2FA.
metadata	dict[str, str]	Custom metadata attached to the task.