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- import os
- from autogen import UserProxyAgent, config_list_from_json
- from autogen.agentchat.contrib.web_surfer import WebSurferAgent
-
-
- def main():
- # Load LLM inference endpoints from an env variable or a file
- # See https://microsoft.github.io/autogen/docs/FAQ#set-your-api-endpoints
- # and OAI_CONFIG_LIST_sample.
- # For example, if you have created a OAI_CONFIG_LIST file in the current working directory, that file will be used.
- config_list = config_list_from_json(env_or_file="OAI_CONFIG_LIST")
-
- # Create the agent that uses the LLM.
- web_surfer = WebSurferAgent(
- "web_surfer",
- llm_config={"config_list": config_list},
- summarizer_llm_config={"config_list": config_list},
- browser_config={
- "headless": "playwright",
- "viewport_size": 1024 * 2,
- "downloads_folder": os.getcwd(),
- "bing_api_key": os.environ.get("BING_API_KEY"),
- },
- )
-
- # Create the agent that represents the user in the conversation.
- user_proxy = UserProxyAgent("user", code_execution_config=False)
-
- # Let the assistant start the conversation. It will end when the user types exit.
- web_surfer.initiate_chat(user_proxy, message="How can I help you today?")
-
-
- if __name__ == "__main__":
- main()
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