Browserbase

Browserbase is a developer platform to reliably run, manage, and monitor headless browsers.

Power your AI data retrievals with:

• Serverless Infrastructure providing reliable browsers to extract data from complex UIs
• Stealth Mode with included fingerprinting tactics and automatic captcha solving
• Session Debugger to inspect your Browser Session with networks timeline and logs
• Live Debug to quickly debug your automation

Installation and Setup

• Get an API key and Project ID from browserbase.com and set it in environment variables (BROWSERBASE_API_KEY, BROWSERBASE_PROJECT_ID).
• Install the Browserbase SDK:

% pip install browserbase

Loading documents

You can load webpages into LangChain using BrowserbaseLoader. Optionally, you can set text_content parameter to convert the pages to text-only representation.

from langchain_community.document_loaders import BrowserbaseLoader

API Reference:

• BrowserbaseLoader

loader = BrowserbaseLoader(
    urls=[
        "https://example.com",
    ],
    # Text mode
    text_content=False,
)

docs = loader.load()
print(docs[0].page_content[:61])

Loader Options

• urls Required. A list of URLs to fetch.
• text_content Retrieve only text content. Default is False.
• api_key Optional. Browserbase API key. Default is BROWSERBASE_API_KEY env variable.
• project_id Optional. Browserbase Project ID. Default is BROWSERBASE_PROJECT_ID env variable.
• session_id Optional. Provide an existing Session ID.
• proxy Optional. Enable/Disable Proxies.

Loading images

You can also load screenshots of webpages (as bytes) for multi-modal models.

Full example using GPT-4V:

from browserbase import Browserbase
from browserbase.helpers.gpt4 import GPT4VImage, GPT4VImageDetail
from langchain_core.messages import HumanMessage
from langchain_openai import ChatOpenAI

chat = ChatOpenAI(model="gpt-4-vision-preview", max_tokens=256)
browser = Browserbase()

screenshot = browser.screenshot("https://browserbase.com")

result = chat.invoke(
    [
        HumanMessage(
            content=[
                {"type": "text", "text": "What color is the logo?"},
                GPT4VImage(screenshot, GPT4VImageDetail.auto),
            ]
        )
    ]
)

print(result.content)

API Reference:

• HumanMessage
• ChatOpenAI