Slides

The following tutorials are mainly based on the excellent course “LangChain for LLM Application Development” provided by Harrison Chase and Andrew Ng

Take a look at the slides tutorial to learn how to use all slide options.

You have several options to start code development:

  1. Colab: Click on one of the links “💻 Jupyter Notebook” to start a Colab session.

  2. Local: Click on one of the links “💻 Jupyter Notebook” below, go to the Colab menu and choose “File” > “Download” > “Download .ipynb”

  3. Cloud Codespace: Work in a fully configured dev environment in the cloud with a GitHub Codespace VS Code Browser environment.

  4. Local VS Code with Codespace: Use GitHub Codespaces in your local Visual Studio Code environment.

1 Models, Prompts and Output Parsers

In this tutorial, you’ll learn how to call LLMs, providing prompts and parsing the response.

2 Memories for LLMs

Use memories to store conversations and manage limited context space.

3 Chains

Creating sequences of operations.

4 Q&A over Documents

Apply LLMs to your proprietary data and use case requirements.

5 Evaluation

Example generation, manual evaluation (and debuging), LLM-assisted evaluation & LangChain evaluation platform.

6 Agents

Explore the powerful emerging development of LLM as reasoning agents.

7 LangChain-Teacher

Learn the basics of LangChain with an interactive chat-based learning interface. The app offers two teaching styles: Instructional, which provides step-by-step instructions, and Interactive lessons with questions, which prompts users with questions to assess their understanding:

🤖 LangChain Teacher