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AutoGen from 
AutoGen from 
mention
@Microsoft
Microsoft
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 is crazy! 🚀 It's an open-source framework that allows LLM agents to chat with each other to solve your tasks. 🤖💬
 is crazy! 🚀 It's an open-source framework that allows LLM agents to chat with each other to solve your tasks. 🤖💬
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They use the Assistant-Agent and User-Proxy-Agent framework! 🛠️
They use the Assistant-Agent and User-Proxy-Agent framework! 🛠️
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As the name suggests, the Assistant-Agent does the work, and the User-Proxy-Agent behaves like a human, guiding the Assistant-Agent and double-checking its work! 🧑‍💻✅
As the name suggests, the Assistant-Agent does the work, and the User-Proxy-Agent behaves like a human, guiding the Assistant-Agent and double-checking its work! 🧑‍💻✅
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Both Assistant-Agent and User-Proxy-Agent can be the same or different LLMs. 🤔🔄
Both Assistant-Agent and User-Proxy-Agent can be the same or different LLMs. 🤔🔄
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AutoGen is an open-source programming framework for building AI agents and facilitating cooperation among multiple agents to solve tasks. 🌟
AutoGen is an open-source programming framework for building AI agents and facilitating cooperation among multiple agents to solve tasks. 🌟
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This is truly amazing for building agentic AI quickly! 🚀✨
This is truly amazing for building agentic AI quickly! 🚀✨
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GitHub: 
GitHub: 
link
https://github.com/microsoft/autogen
https://github.com/microsoft/autogen
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 🔗
 🔗
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```Python
from autogen import AssistantAgent, UserProxyAgent, config_list_from_json

#config
config_list = config_list_from_json(env_or_file="OAI_CONFIG_LIST")

assistant = AssistantAgent("assistant", llm_config={"config_list": config_list})
user_proxy = UserProxyAgent("user_proxy", code_execution_config={"work_dir": "coding", "use_docker": False}) 

user_proxy.initiate_chat(assistant, message="Plot a chart of NVDA and TESLA stock price change YTD.")
# This initiates an automated chat between the two agents to solve the task
```
from autogen import AssistantAgent, UserProxyAgent, config_list_from_json

#config
config_list = config_list_from_json(env_or_file="OAI_CONFIG_LIST")

assistant = AssistantAgent("assistant", llm_config={"config_list": config_list})
user_proxy = UserProxyAgent("user_proxy", code_execution_config={"work_dir": "coding", "use_docker": False}) 

user_proxy.initiate_chat(assistant, message="Plot a chart of NVDA and TESLA stock price change YTD.")
# This initiates an automated chat between the two agents to solve the task
Python
new_line
AutoGen from @Microsoft is crazy! 🚀 It's an open-source framework that allows LLM agents to chat with each other to solve your tasks. 🤖💬

They use the Assistant-Agent and User-Proxy-Agent framework! 🛠️

As the name suggests, the Assistant-Agent does the work, and the User-Proxy-Agent behaves like a human, guiding the Assistant-Agent and double-checking its work! 🧑‍💻✅

Both Assistant-Agent and User-Proxy-Agent can be the same or different LLMs. 🤔🔄

AutoGen is an open-source programming framework for building AI agents and facilitating cooperation among multiple agents to solve tasks. 🌟

This is truly amazing for building agentic AI quickly! 🚀✨

GitHub: https://github.com/microsoft/autogen 🔗


```Python
from autogen import AssistantAgent, UserProxyAgent, config_list_from_json

#config
config_list = config_list_from_json(env_or_file="OAI_CONFIG_LIST")

assistant = AssistantAgent("assistant", llm_config={"config_list": config_list})
user_proxy = UserProxyAgent("user_proxy", code_execution_config={"work_dir": "coding", "use_docker": False}) 

user_proxy.initiate_chat(assistant, message="Plot a chart of NVDA and TESLA stock price change YTD.")
# This initiates an automated chat between the two agents to solve the task
```

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