Build latest book artifacts / build (push) Canceled after 0s
dependency resolution / resolve (3.11) (push) Canceled after 0s
dependency resolution / resolve (3.13) (push) Canceled after 0s
deploy-pages / build (push) Canceled after 0s
deploy-pages / deploy (push) Canceled after 0s
i18n consistency check / check (push) Canceled after 0s
provider adoption tests / test (chapter2/context-compression) (push) Canceled after 0s
provider adoption tests / test (chapter2/prompt-injection) (push) Canceled after 0s
provider adoption tests / test (chapter2/system-hint) (push) Canceled after 0s
provider adoption tests / test (chapter3/log-sanitization) (push) Canceled after 0s
web-search-agent tests / test (push) Canceled after 0s
web-search-agent tests / agentbook (push) Canceled after 0s
Langchain Models (legacy)
This directory contains example of how to still use Langchain models with the new Browser Use chat models.
How to use
from langchain_openai import ChatOpenAI
from browser_use import Agent
from .chat import ChatLangchain
async def main():
"""Basic example using ChatLangchain with OpenAI through LangChain."""
# Create a LangChain model (OpenAI)
langchain_model = ChatOpenAI(
model='gpt-4.1-mini',
temperature=0.1,
)
# Wrap it with ChatLangchain to make it compatible with browser-use
llm = ChatLangchain(chat=langchain_model)
agent = Agent(
task="Go to google.com and search for 'browser automation with Python'",
llm=llm,
)
history = await agent.run()
print(history.history)