MultiOn Python Library

The MultiOn Python Library provides convenient access to the MultiOn API from applications written in Python.

Documentation

API reference documentation is available here.

Installation

Add this dependency to your project's build file:

pip install multion
# or
poetry add multion

Usage

Simply import MultiOn and start making calls to our API.

import os
from multion.client import MultiOn

client = MultiOn(
    api_key="YOUR_API_KEY" # defaults to os.getenv("MULTION_API_KEY")
)
response = client.browse(
    url="https://google.com"
)

Async Client

The SDK also exports an async client so that you can make non-blocking calls to our API.

import asyncio
from multion.client import AsyncMultiOn

client = AsyncMultiOn(
    api_key="YOUR_API_KEY" # defaults to os.getenv("MULTION_API_KEY")
)

async def main() -> None:
    response = await client.browse(
        url="https://google.com"
    )

asyncio.run(main())

Exception Handling

All errors thrown by the SDK will be subclasses of ApiError.

import multion

try:
  client.browse(...)
except multion.core.ApiError as e: # Handle all errors
  print(e.status_code)
  print(e.body)

Agent Tracing and Observability

MultiOn uses AgentOps to provide session replays, metrics, and monitoring for AI agents. MultiOn runs are automatically tracked when an AgentOps API key is provided. You can find your API key in the AgentOps dashboard.

import os
from multion.client import MultiOn
multion = MultiOn(
    api_key=os.environ.get("MULTION_API_KEY"),
    agentops_api_key=os.environ.get("AGENTOPS_API_KEY"),
)

At a high level, AgentOps gives you the ability to monitor LLM calls, costs, latency, agent failures, multi-agent interactions, tool usage session-wide statistics, and more. For more info, check out the AgentOps Repo.

Examples

AgentOps provides session drilldowns for viewing MultiOn browse events, LLM calls, and tool usage in real-time. This feature is useful for debugging and understanding how agents interact with users as well as other agents.

Autonomous Web Browsing

Web Browser Agent Tracking

Step-by-Step Web Browsing

Webpage Data Retrieval

Advanced

Retries

The MultiOn SDK is instrumented with automatic retries with exponential backoff. A request will be retried as long as the request is deemed retriable and the number of retry attempts has not grown larger than the configured retry limit.

A request is deemed retriable when any of the following HTTP status codes is returned:

• 408 (Timeout)
• 429 (Too Many Requests)
• 5XX (Internal Server Errors)

Use the max_retries request option to configure this behavior.

from multion.client import MultiOn

client = MultiOn()

# Override retries for a specific method
client.browse(url="https://google.com", {
    max_retries=1
})

Timeouts

By default, requests time out after 60 seconds. You can configure this with a timeout option at the client or request level.

from multion.client import MultiOn

client = MultiOn(
    # All timeouts are 20 seconds
    timeout=20.0,
)

# Override timeout for a specific method
client.browse(url="https://google.com", {
    timeout_in_seconds=20.0
})

Custom HTTP client

You can override the httpx client to customize it for your use-case. Some common use-cases include support for proxies and transports.

import httpx

from multion.client import MultiOn

client = MultiOn(
    http_client=httpx.Client(
        proxies="http://my.test.proxy.example.com",
        transport=httpx.HTTPTransport(local_address="0.0.0.0"),
    ),
)

Beta Status

This SDK is in beta, and there may be breaking changes between versions without a major version update. Therefore, we recommend pinning the package version to a specific version. This way, you can install the same version each time without breaking changes.

Contributing

While we value open-source contributions to this SDK, this library is generated programmatically. Additions made directly to this library would have to be moved over to our generation code, otherwise they would be overwritten upon the next generated release. Feel free to open a PR as a proof of concept, but know that we will not be able to merge it as-is. We suggest opening an issue first to discuss with us!

On the other hand, contributions to the README are always very welcome!