Browser-run Colab notebooks for systematic RAG optimization (chunking, retrieval, rerankers, prompts)

I coded a set of practical, browser-run Google Colab examples for people who want to systematically optimize their RAG pipelines, especially how to choose chunking strategies, retrieval parameters, rerankers, and prompts through structured evaluation instead of guesswork. You can run everything in the browser and also copy the notebook code into your own projects. Overview page: https://www.rapidfire.ai/solutions Use cases: Customer Support: https://www.rapidfire.ai/customer-support Finance: https://www.rapidfire.ai/solutions-finance Retail Chatbot: https://www.rapidfire.ai/retail-chatbot Healthcare Support: https://www.rapidfire.ai/healthcare-support Cybersecurity: https://www.rapidfire.ai/cybersecurity Content Safety: https://www.rapidfire.ai/content-safety PII Redaction: https://www.rapidfire.ai/pii-redaction EdTech Support: https://www.rapidfire.ai/edtech-support GitHub (library + code): https://github.com/RapidFireAI/rapidfireai If you are iterating on a RAG system, feel free to u