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POST
/
v1
/
chat
/
completions
curl --request POST \
  --url https://api.yutori.com/v1/chat/completions \
  --header "Authorization: Bearer <api_key>" \
  --header "Content-Type: application/json" \
  --data '{
    "model": "n1.5-latest",
    "messages": [
      {
        "role": "user",
        "content": [
          {
            "type": "text",
            "text": "Click on the search bar and type Yutori."
          },
          {
            "type": "image_url",
            "image_url": {
              "url": "https://docs.yutori.com/assets/google_homepage_2024.jpg"
            }
          }
        ]
      }
    ]
  }'

{
  "id": "chatcmpl-abc123",
  "object": "chat.completion",
  "model": "n1.5-latest",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "I can see the Google homepage. I'll click on the search bar to begin searching for Yutori.",
        "tool_calls": [
          {
            "id": "chatcmpl-tool-abc123",
            "type": "function",
            "function": {
              "name": "left_click",
              "arguments": "{\"coordinates\": [640, 400]}"
            }
          }
        ]
      },
      "finish_reason": "tool_calls"
    }
  ],
  "usage": {
    "prompt_tokens": 1234,
    "completion_tokens": 56,
    "total_tokens": 1290
  },
  "request_id": "a1b2c3d4-e5f6-7890-abcd-ef1234567890"
}

curl --request POST \
  --url https://api.yutori.com/v1/chat/completions \
  --header "Authorization: Bearer <api_key>" \
  --header "Content-Type: application/json" \
  --data '{
    "model": "n1.5-latest",
    "messages": [
      {
        "role": "user",
        "content": [
          {
            "type": "text",
            "text": "Click on the search bar and type Yutori."
          },
          {
            "type": "image_url",
            "image_url": {
              "url": "https://docs.yutori.com/assets/google_homepage_2024.jpg"
            }
          }
        ]
      }
    ]
  }'

{
  "id": "chatcmpl-abc123",
  "object": "chat.completion",
  "model": "n1.5-latest",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "I can see the Google homepage. I'll click on the search bar to begin searching for Yutori.",
        "tool_calls": [
          {
            "id": "chatcmpl-tool-abc123",
            "type": "function",
            "function": {
              "name": "left_click",
              "arguments": "{\"coordinates\": [640, 400]}"
            }
          }
        ]
      },
      "finish_reason": "tool_calls"
    }
  ],
  "usage": {
    "prompt_tokens": 1234,
    "completion_tokens": 56,
    "total_tokens": 1290
  },
  "request_id": "a1b2c3d4-e5f6-7890-abcd-ef1234567890"
}

​
Overview

The API provides a computer-use model that predicts actions to interact with a browser. Given a task in natural language, the current screenshot, and the full action history, the model predicts the next action to take to accomplish the task. The API follows the OpenAI chat.completions format and supports multiple model versions:
Model FamilyLatest VersionDescription
n1.5n1.5-latestLatest generation with expanded action space, selectable tool sets, and JSON structured output. Details →
n1n1-latestStable first generation. Details →
Want to try browser use without writing code?
  • Browser Extension — test and explore in your own local browser
  • Yutori Local — Mac desktop app that gives our agents access to a browser on your computer, enabling login-required workflows and local browsing tasks

​
Screenshot Requirements

Screenshots should capture only the browser content itself. Do not include the operating system UI, window title bars, browser tabs, URL bars, or other chrome elements. For the best performance, render screenshots in WXGA (1280×800, 16:10). The model should generalize well to most other resolutions, but grounding accuracy may degrade with extreme aspect ratios. We recommend using the WebP format for screenshots, as it offers significantly better compression than PNG — especially for multi-step trajectories with many images. The Python SDK provides helpers that handle resizing, WebP conversion, and base64 encoding: 
pip install 'yutori[n1]'

from yutori.n1 import screenshot_to_data_url, playwright_screenshot_to_data_url

# From raw screenshot bytes (any format)
image_url = screenshot_to_data_url(screenshot_bytes)

# Or directly from a Playwright page
image_url = playwright_screenshot_to_data_url(page)

# Async variant also available
# image_url = await aplaywright_screenshot_to_data_url(page)
See yutori.n1.images for full options (custom resolution, quality settings).

​
Coordinate System

All models output normalized coordinates in a 1000×1000 space. Convert to absolute pixel coordinates before executing actions in your browser: 
from yutori.n1 import denormalize_coordinates

pixel_x, pixel_y = denormalize_coordinates(
    coordinates=[640, 400],
    width=viewport_width,
    height=viewport_height,
)
See yutori.n1.coordinates for the inverse normalize_coordinates function.

​
Response Format

Actions are returned via the tool_calls field in the response message: 
{
  "choices": [
    {
      "message": {
        "role": "assistant",
        "content": "I'll click on the search bar.",
        "tool_calls": [
          {
            "id": "chatcmpl-tool-abc123",
            "type": "function",
            "function": {
              "name": "left_click",
              "arguments": "{\"coordinates\": [640, 400]}"
            }
          }
        ]
      },
      "finish_reason": "tool_calls"
    }
  ]
}
The content field contains the model’s reasoning, tool_calls contains the predicted action(s), and request_id is a unique identifier useful for debugging. When the model intends to stop, it returns a response with only content text and no tool_calls. This content field is the model’s final response to the task.

​
Multi-Turn Conversations

The model expects full chat history to best predict the next action. We do not recommend removing any messages or screenshots when constructing requests. Include the assistant’s previous response with its tool_calls, followed by tool results with the new screenshot: 
response = client.chat.completions.create(
    model="n1.5-latest",
    messages=[
        # Initial user message with task and first screenshot
        {
            "role": "user",
            "content": [
                {"type": "text", "text": "Search for Yutori on Google."},
                {"type": "image_url", "image_url": {"url": f"data:image/webp;base64,{screenshot_1}"}}
            ]
        },
        # Assistant's response with tool call
        {
            "role": "assistant",
            "content": "I can see the Google homepage. I'll click on the search bar.",
            "tool_calls": [
                {
                    "id": "chatcmpl-tool-123",
                    "type": "function",
                    "function": {
                        "name": "left_click",
                        "arguments": "{\"coordinates\": [500, 465]}"
                    }
                }
            ]
        },
        # Tool result with current URL and new screenshot
        {
            "role": "tool",
            "tool_call_id": "chatcmpl-tool-123",
            "content": [
                {"type": "text", "text": "Clicked 1x with left\nCurrent URL: https://www.google.com/"},
                {"type": "image_url", "image_url": {"url": f"data:image/webp;base64,{screenshot_2}"}}
            ]
        }
    ]
)
The tool result can be a short description of what the tool did or whether it was successful. Including the current URL in the tool response is also recommended for better attribution of information sources. If the tool extracts additional information (e.g. extract_elements, execute_js), the raw output of the tool can be provided as the tool result so the model also has visibility of the extracted information.

​
Custom Tools

You can provide additional tools alongside the built-in browser actions using the tools parameter. Custom tools are appended after the default tool set. 
response = client.chat.completions.create(
    model="n1.5-latest",
    messages=[...],
    tools=[
        {
            "type": "function",
            "function": {
                "name": "extract_content_and_links",
                "description": "Extracts page content and hyperlinks relevant to the user task. This operation is strictly read-only and never interacts with or alters the page.",
                "parameters": {"type": "object", "properties": {}, "required": []}
            }
        }
    ]
)
Results of custom tool calls should also be provided as a tool response so the model can use it for subsequent decisions: 
{
    "role": "tool",
    "tool_call_id": "chatcmpl-tool-456",
    "content": [
        {
            "type": "text",
            "text": "Visible buttons and links:\n- About https://about.google/\n- Store https://store.google.com/\n- Gmail https://mail.google.com/\nCurrent page URL: https://www.google.com/"
        },
        {
            "type": "image_url",
            "image_url": {"url": f"data:image/webp;base64,{screenshot}"}
        }
    ]
}

​
Tool Choice

Control whether tool calls are parsed into the tool_calls array:
  • "auto" (default): Parses and returns tool calls as a structured tool_calls list
  • "none": Returns the raw model response as content text (tool calls may still appear inside <tool_call> XML tags in content)

​
Prompting Guidance

We use a default system prompt when none is provided, and generally do not recommend providing custom system prompts — extra behavioral instructions may degrade results. Instead, place additional instructions in the first user message, after the main task description: 
{
  "messages": [
    {
      "role": "user",
      "content": "Click the login button. Additional instructions: be careful with popups."
    }
  ]
}
We also recommend not interrupting trajectory execution with additional user messages, except to force the model to stop and summarize: 
messages.append({
    "role": "user",
    "content": f"Stop here. Summarize your current progress and list all findings relevant to: {task}"
})

​
Structured Decoding

By default, the API uses a structural_tag response format to enforce valid tool call generation via guided decoding. You do not need to provide this yourself — the API generates it automatically based on the active model and tool set. If custom tools are included in your request, their schemas are automatically incorporated. We do not recommend overriding the response_format unless you also set tool_choice="none" to work with the raw model output directly.

Authorizations

​
Authorization
string
header
required

Use Authorization: Bearer <api_key>

Body

application/json
​
messages
(ChatCompletionDeveloperMessageParam · object | ChatCompletionSystemMessageParam · object | ChatCompletionUserMessageParam · object | ChatCompletionAssistantMessageParam · object | ChatCompletionToolMessageParam · object | ChatCompletionFunctionMessageParam · object | ChatCompletionToolImageMessageParam · object | ChatCompletionObservationMessageParam · object)[]
​
model
enum<string>
Available options:
n1-latest,
n1-experimental,
n1-experimental-20260309,
n1-experimental-20260212,
n1-20260203,
n1.5-latest,
n1.5-20260403
​
max_completion_tokens
integer | null
​
temperature
number | null
default:0.3
​
top_p
number | null
​
tools
Tools · object[] | null

Additional tools to extend the default browser action tools. Tools are merged with the built-in browser actions (left_click, scroll, type, etc.).

​
tool_choice
default:auto

Controls whether tool calls are parsed from the response. Model always decides whether to call a tool. 'none' treats the response as text-only, but tool calls may be present inside <tool_call> tags, 'auto' (default) parses tool calls automatically as tool_calls list in response.

​
response_format
Response Format · object

An object specifying the format that the model must output.

​
tool_set
string | null

Named tool set (n1.5+ models only). 'browser_tools_core-20260403' (default): coordinate-based tools. 'browser_tools_expanded-20260403': adds extract_elements, find, set_element_value, execute_js.

​
disable_tools
string[] | null

List of tool names to remove from the selected tool set (n1.5+ models only).

​
json_schema
Json Schema · object

JSON Schema for structured output (n1.5+ models only). Appended to your task message. Model returns JSON in ```json fences, parsed and returned as 'parsed_json' in the response.

Response

Successful Response