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Autogen tutorial - next-generation LLM agents framework
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Paper title: AutoGen: Enabling next-generation large language model applications.
AutoGen is the next generation custom LLM agent creation framework. Autogen enables creation of LLM agents easily in few lines of code.
AutoGen addresses the shortcomings of Langchain and similar LLM-enabling single-agent frameworks such as AutoGPT, ChatGPT+, and Transformers Agents. It enables seamless development of Multi-Agent Conversational AI systems.
Though communicative agent frameworks like CAMEL exist, they do not yet support tool-using and code execution. AutoGen has it all.
Hope this video is useful to learn about AutoGen.
TIMELINES
0:00 - Drawbacks of LangChain
0:56 - AutoGen
1:10 - Agents
1:45 - Multi-agent example one
3:30 - Developing multi-agent systems
4:10 - Multi-agent example two
5:05 - AutoGen Implementation
5:55 - AutoGen's auto-reply
6:40 - Dynamic Conversation
7:20 - AutoGen example code and notebooks
RELATED LINKS
🛠 🛠 🛠 MY SOFTWARE TOOLS 🛠 🛠 🛠
📚 📚 📚 BOOKS I HAVE READ, REFER AND RECOMMEND 📚 📚 📚
MY KEY LINKS
WHO AM I?
I am a Machine Learning Researcher/practitioner who has seen the grind of academia and start-ups equally. I started my career as a software engineer 15 years ago. Because of my love for Mathematics (coupled with a glimmer of luck), I graduated with a Master's in Computer Vision and Robotics in 2016 when the now happening AI revolution just started. Life has changed for the better ever since.
#machinelearning #deeplearning #aibites #transformers #llm #llms
AutoGen is the next generation custom LLM agent creation framework. Autogen enables creation of LLM agents easily in few lines of code.
AutoGen addresses the shortcomings of Langchain and similar LLM-enabling single-agent frameworks such as AutoGPT, ChatGPT+, and Transformers Agents. It enables seamless development of Multi-Agent Conversational AI systems.
Though communicative agent frameworks like CAMEL exist, they do not yet support tool-using and code execution. AutoGen has it all.
Hope this video is useful to learn about AutoGen.
TIMELINES
0:00 - Drawbacks of LangChain
0:56 - AutoGen
1:10 - Agents
1:45 - Multi-agent example one
3:30 - Developing multi-agent systems
4:10 - Multi-agent example two
5:05 - AutoGen Implementation
5:55 - AutoGen's auto-reply
6:40 - Dynamic Conversation
7:20 - AutoGen example code and notebooks
RELATED LINKS
🛠 🛠 🛠 MY SOFTWARE TOOLS 🛠 🛠 🛠
📚 📚 📚 BOOKS I HAVE READ, REFER AND RECOMMEND 📚 📚 📚
MY KEY LINKS
WHO AM I?
I am a Machine Learning Researcher/practitioner who has seen the grind of academia and start-ups equally. I started my career as a software engineer 15 years ago. Because of my love for Mathematics (coupled with a glimmer of luck), I graduated with a Master's in Computer Vision and Robotics in 2016 when the now happening AI revolution just started. Life has changed for the better ever since.
#machinelearning #deeplearning #aibites #transformers #llm #llms