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Explore new advancements like ChatGPT’s function calling capability, and build a conversational agent using a new syntax called LangChain Expression Language (LCEL) for tasks like tagging, extraction, tool selection, and routing.

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The landscape of LLMs and the libraries that support them has evolved rapidly in recent months. This course is designed to keep you ahead of these changes.

You’ll explore new advancements like ChatGPT’s function calling capability, and build a conversational agent using a new syntax called LangChain Expression Language (LCEL) for tasks like tagging, extraction, tool selection, and routing.

After taking this course, you’ll know how to:

  • Generate structured output, including function calls, using LLMs;
  • Use LCEL, which simplifies the customization of chains and agents, to build applications;
  • Apply function calling to tasks like tagging and data extraction;
  • Understand tool selection and routing using LangChain tools and LLM function calling – and much more.

Start applying these new capabilities to build and improve your applications today.

Who should join?

Anyone who’s interested in learning about the latest tools to build LLM-based applications. Basic Python knowledge and a familiarity with writing prompts for LLMs is recommended.

Using Notebooks

  1. Install dependencies by running pip install -r requirements.txt (or you can install openai, langchain, pydantic, etc. manually).
  2. Setup the OpenAI key by running cp .env.sample .env and provide OpenAI token.

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Explore new advancements like ChatGPT’s function calling capability, and build a conversational agent using a new syntax called LangChain Expression Language (LCEL) for tasks like tagging, extraction, tool selection, and routing.

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