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""" |
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Automated news analysis and sentiment scoring using Bedrock. |
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@dev Ensure AWS environment variables are set correctly for Bedrock access. |
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""" |
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import os |
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import sys |
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from langchain_aws import ChatBedrock |
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sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))) |
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import argparse |
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import asyncio |
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from browser_use import Agent |
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from browser_use.browser.browser import Browser, BrowserConfig |
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from browser_use.controller.service import Controller |
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def get_llm(): |
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return ChatBedrock( |
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model_id="us.anthropic.claude-3-5-sonnet-20241022-v2:0", |
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temperature=0.0, |
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max_tokens=None, |
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) |
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task = ( |
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"Visit cnn.com, navigate to the 'World News' section, and identify the latest headline. " |
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"Open the first article and summarize its content in 3-4 sentences. " |
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"Additionally, analyze the sentiment of the article (positive, neutral, or negative) " |
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"and provide a confidence score for the sentiment. Present the result in a tabular format." |
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) |
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parser = argparse.ArgumentParser() |
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parser.add_argument('--query', type=str, help='The query for the agent to execute', default=task) |
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args = parser.parse_args() |
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llm = get_llm() |
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browser = Browser( |
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config=BrowserConfig( |
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) |
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) |
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agent = Agent( |
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task=args.query, llm=llm, controller=Controller(), browser=browser, validate_output=True, |
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) |
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async def main(): |
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await agent.run(max_steps=30) |
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await browser.close() |
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asyncio.run(main()) |
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