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46 lines
1.6 KiB
Python
46 lines
1.6 KiB
Python
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import os
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from autogen import UserProxyAgent, config_list_from_json
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from autogen.agentchat.contrib.web_surfer import WebSurferAgent
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from autogen.browser_utils import (
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BingMarkdownSearch,
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PlaywrightMarkdownBrowser,
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RequestsMarkdownBrowser,
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SeleniumMarkdownBrowser,
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)
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def main():
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# Load LLM inference endpoints from an env variable or a file
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# See https://microsoft.github.io/autogen/docs/FAQ#set-your-api-endpoints
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# and OAI_CONFIG_LIST_sample.
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# For example, if you have created a OAI_CONFIG_LIST file in the current working directory, that file will be used.
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config_list = config_list_from_json(env_or_file="OAI_CONFIG_LIST")
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browser = RequestsMarkdownBrowser(
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# PlaywrightMarkdownBrowser(
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viewport_size=1024 * 3,
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downloads_folder=os.getcwd(),
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search_engine=BingMarkdownSearch(bing_api_key=os.environ["BING_API_KEY"]),
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# launch_args={"channel": "msedge", "headless": False},
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)
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web_surfer = WebSurferAgent(
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"web_surfer",
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llm_config={"config_list": config_list},
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summarizer_llm_config={"config_list": config_list},
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is_termination_msg=lambda x: x.get("content", "").rstrip().find("TERMINATE") >= 0,
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code_execution_config=False,
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browser=browser,
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)
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# Create the agent that represents the user in the conversation.
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user_proxy = UserProxyAgent("user", code_execution_config=False)
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# Let the assistant start the conversation. It will end when the user types exit.
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web_surfer.initiate_chat(user_proxy, message="How can I help you today?")
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if __name__ == "__main__":
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main()
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