SACommunityChatbot

A sample Python backend code for my contribution to the SACommunity Chatbot project.

Project Background

This chatbot originated from a recommendation by a dear friend with extensive knowledge of the latest trends in AI. He introduced us to LangChain, which played a key role in the success of this project.

The chatbot was initially challenging to deploy due to an outdated interface. To overcome this, we containerized the Python code using Docker.

Requirements

• Python 3.10 or higher
• Install dependencies using:

  pip install -r requirements.txt

• Docker (if deploying via containerization)

⚠ Note: The data and vectorstore is not included due to data ownership by Connecting Up.

Learning & Development Process

To build this chatbot, I explored and learned LangChain from various sources. Here's a recommended step-by-step approach for learning LangChain:

1. DeepLearning.ai Short Courses

   • LangChain for LLM Application Development
   • LangChain Chat with Your Data
   • Functions, Tools, and Agents with LangChain

2. LangChain Official YouTube Tutorials

   • RAG from Scratch by LangChain

3. Hands-on Coding

   • Start coding along with tutorials.

4. Customization

   • Once you grasp the basics, modify the code to fit your project needs.

5. Documentation Reference

   • The LangChain official documentation provides extensive guides and API references.

More Details

For a full report on how this chatbot was developed, check out my blog on SACommunity:
🔗 SACommunity Blog Post