<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"><channel><title>Callum Macpherson</title><description>AI engineer writing about production ML, language models, retrieval systems, and the engineering details that decide whether demos survive contact with users.</description><link>https://callumjmac.github.io/</link><item><title>Advanced Retrieval for Retrieval-Augmented Generation</title><link>https://callumjmac.github.io/posts/advanced-retrieval-rag/</link><guid isPermaLink="true">https://callumjmac.github.io/posts/advanced-retrieval-rag/</guid><description>Query expansion, cross-encoder re-ranking, and embedding adaptors for improving RAG retrieval quality.</description><pubDate>Tue, 21 May 2024 00:00:00 GMT</pubDate></item><item><title>LLMs Evals: A General Framework for Custom Evaluations</title><link>https://callumjmac.github.io/posts/llm-evals-framework/</link><guid isPermaLink="true">https://callumjmac.github.io/posts/llm-evals-framework/</guid><description>A general framework for building rule-based and model-graded evaluations for LLM-based applications.</description><pubDate>Tue, 07 May 2024 00:00:00 GMT</pubDate></item><item><title>Implementing RAG in LangChain with Chroma: A Step-by-Step Guide</title><link>https://callumjmac.github.io/posts/rag-langchain-intro/</link><guid isPermaLink="true">https://callumjmac.github.io/posts/rag-langchain-intro/</guid><description>A step-by-step guide to building a Retrieval-Augmented Generation system using LangChain, Chroma, and OpenAI embeddings.</description><pubDate>Wed, 24 Apr 2024 00:00:00 GMT</pubDate></item><item><title>Malicious LLM Prompt Detection in Python</title><link>https://callumjmac.github.io/posts/malicious-llm-prompt-detection/</link><guid isPermaLink="true">https://callumjmac.github.io/posts/malicious-llm-prompt-detection/</guid><description>Building a malicious prompt detector using traditional ML classifiers in sklearn, trained on Deepset&apos;s prompt-injection dataset.</description><pubDate>Mon, 22 Apr 2024 00:00:00 GMT</pubDate></item><item><title>Continual Learning: Which metrics are important?</title><link>https://callumjmac.github.io/posts/continual-learning-metrics/</link><guid isPermaLink="true">https://callumjmac.github.io/posts/continual-learning-metrics/</guid><description>Ranking the most valuable metrics for monitoring deployed ML models, from user feedback to distribution drift.</description><pubDate>Tue, 16 Apr 2024 00:00:00 GMT</pubDate></item></channel></rss>