For the most recent article discussing the xLLM web API, follow this link.
I discuss version 2.0 of my enterprise multi-LLM system called xLLM. Version 1.0 was presented in my recent article entitled “Custom Enterprise LLM/RAG with Real-Time Fine-Tuning”, posted here. Since version 2.0 is backward-compatible and consists of several important additions, I included all the relevant material from the previous article, in this paper. New additions include multi-token distillation when processing prompts, agents to meet user intent, more NLP, and a command prompt menu accepting both standard prompts and various actions, see Figure 1.
I also added several illustrations, featuring xLLM in action with a full session and sample commands to fine-tune in real-time. All the code, input sources (anonymized corporate corpus from fortune 100 company), contextual backend tables including embeddings, are on GitHub, accessible from the technical paper. My system has zero weight, no transformer, and no neural network. It relies on explainable AI, does not require training, is fully reproducible, and fits in memory. Yet your prompts can retrieve relevant full text entities from the corpus with no latency — including URLs, categories, titles, email addresses, and so on — thanks to well-designed architecture.
View article, get the code and data
The technical document is available on GitHub: see paper 45, here. It features detailed documentation with illustrations and the code. To get the clickable links to work, download the document and view it in any browser or PDF viewer, instead of directly viewing it on GitHub.
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About the Author
Vincent Granville is a pioneering GenAI scientist and machine learning expert, co-founder of Data Science Central (acquired by a publicly traded company in 2020), Chief AI Scientist at MLTechniques.com and GenAItechLab.com, former VC-funded executive, author (Elsevier) and patent owner — one related to LLM. Vincent’s past corporate experience includes Visa, Wells Fargo, eBay, NBC, Microsoft, and CNET. Follow Vincent on LinkedIn.