Add Curated Knowledge Base Search

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prerequisites
basic web concepts • intermediate Python
skills learned
query rephrasing • knowledge retrieval
Jeremie Charlet
1 week · 2-4 hours per week · INTERMEDIATE
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Look inside
In this second liveProject, you’ll add Retrieval Augmented Generation (RAG) to a pre-existing chatbot so that it can provide up-to-date and reliable responses to questions fielded by the pet refuge. First, you’ll connect your chatbot to a document store and test it on real pet care questions to ensure answers are grounded in reliable sources. Then, you’ll improve retrieval quality by expanding the knowledge base, refining queries to better capture user intent, and adding smart filters for more relevant, precise results.
This project is designed for learning purposes and is not a complete, production-ready application or solution.

project author

Jeremie Charlet
Jeremie Charlet is a freelance data science consultant specializing in NLP, MLOps, and generative AI product strategy. He has over a decade of experience delivering AI-powered solutions for startups, scaleups, and the UK government. As a startup founder, he is currently focusing on applying AI to support people with meditation and mental health. In addition, he teaches data science and generative AI in leading French business and engineering schools and has mentored ML practitioners through study groups and professional communities.

prerequisites

This liveProject is for Python programmers ready to develop basic chatbots into sophisticated AI agents with accurate personas. You should be comfortable with Python scripting and eager to learn advanced prompt engineering, custom tool development, and agent frameworks.


TOOLS
  • Intermediate Python
  • Basics of Jupyter Notebook
TECHNIQUES
  • Basics of text processing
  • Basics of file management
  • Basics of data structures
  • Basics of prompt engineering
  • Basics of API Integration
  • Basics of Retrieval Augmented Generation

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