How to Build a Responsible AI Chatbot Using Open Technologies 7 Sections35 Lessons5 QuizzesLifetime

Curriculum

7 Sections
35 Lessons
Lifetime

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Introduction
2 Items
- 1.1
  The CABot Story
- 1.2
  How to Do This Course
Module 1 - Understanding AI
9 Items
Large Language Models (LLMs) generate language, not truth. Explore tokens, prompts, context windows and hallucinations, then examine why Retrieval-Augmented Generation (RAG) grounds responses in trusted knowledge.
Module 2 - Building the Knowledge Base
9 Items
Understand how to transform a digital resource (e.g. a book) into semantic knowledge through chunking, embeddings and vector search. Learn why CABot uses ChromaDB and metadata rather than retraining models.
Module 3 - Choosing Your Architecture
5 Items
Compare hosted APIs, local models, vector databases and orchestration frameworks. Rather than recommending one stack, this module helps you choose technologies appropriate to your own community.
Module 4 - Building the Chatbot
8 Items
In this module, we follow a learner's question from a browser prompt to asynchronous RAG orchestration. We aim to understand asynchronous architecture and browser-first deployment.
Module 5 - Responsible & Multilingual AI
5 Items
Responsible AI begins with trustworthy knowledge, not simply powerful models. Explore transparency, source attribution, multilingual retrieval, privacy, accessibility and environmentally conscious AI.
Course Conclusion & Next Steps
2 Items
- 7.1
  Lessons learned
- 7.2
  Recap: Practical workflow for building a responsible chatbot

The Climate Academy ingestion journey

Before students can chat, the repository performs a one-time preparation process:

Climate Academy+ Encylcopedia HTML → identify sections → extract text → create overlapping chunks → embed each chunk → store vectors and metadata in ChromaDB

The book is divided into multiple chunks and stored in the vector database. Each chunk is associated with section information, enabling the chatbot to retrieve relevant content and provide appropriate references in its responses.