Looking at React Native in 2025
“Ten years, three articles, and one more trip through MobileNativeJavaScript land.”
RAG Time: Cooking Up Smart Recipe Suggestions with AI and a Dash of Retrieval
This article explores how Retrieval Augmented Generation (RAG) can be used with large language models to suggest recipes based on user-provided ingredients. It walks through building a recipe recommendation system using embeddings, vector search, and prompt engineering, complete with code examples and a simple web interface.
Serving the Cookbook: Creating an Endpoint for Recipe Recommendations
The post describes creating a FastAPI endpoint to return recipes based on input ingredients, using a prebuilt model and saved artifacts. It covers setup, artifact loading, sanity checks, and cluster-to-index mappings for quick lookups.
Clustering the Cookbook: A Taste of Unsupervised Learning
This post introduces unsupervised learning, focusing on clustering and its use for grouping recipes by ingredient similarity. It describes vectorizing ingredients with TF-IDF and applying k-means to form clusters.
Can a Tiny LLM Beat A Supervised Model?
We compare a compact fine-tuned LLM against a lightweight supervised model for parsing recipes from noisy web pages. The article outlines experiments with commercial LLMs, local open-source models, and cost-performance considerations.