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chore: import upstream snapshot with attribution
2026-07-13 12:02:32 +08:00

52 lines
1.5 KiB
Python

import asyncio
from browser_use.llm import ContentText
from browser_use.llm.groq.chat import ChatGroq
from browser_use.llm.messages import SystemMessage, UserMessage
llm = ChatGroq(
model='meta-llama/llama-4-maverick-17b-128e-instruct',
temperature=0.5,
)
# llm = ChatOpenAI(model='gpt-4.1-mini')
async def main():
from pydantic import BaseModel
from browser_use.tokens.service import TokenCost
tk = TokenCost().register_llm(llm)
class Output(BaseModel):
reasoning: str
answer: str
message = [
SystemMessage(content='You are a helpful assistant that can answer questions and help with tasks.'),
UserMessage(
content=[
ContentText(
text=r"Why is the sky blue? write exactly this into reasoning make sure to output ' with exactly like in the input : "
),
ContentText(
text="""
The user's request is to find the lowest priced women's plus size one piece swimsuit in color black with a customer rating of at least 5 on Kohls.com. I am currently on the homepage of Kohls. The page has a search bar and various category links. To begin, I need to navigate to the women's section and search for swimsuits. I will start by clicking on the 'Women' category link."""
),
]
),
]
for i in range(10):
print('-' * 50)
print(f'start loop {i}')
response = await llm.ainvoke(message, output_format=Output)
completion = response.completion
print(f'start reasoning: {completion.reasoning}')
print(f'answer: {completion.answer}')
print('-' * 50)
if __name__ == '__main__':
asyncio.run(main())