This article introduces a new Snap called the “Multi Pipeline Function Generator”. The Multi Pipeline Function Generator is designed to take existing Pipelines in your SnapLogic Project and turn their...
Introduction At a high level, the logic behind assistant tool calling and non-assistant tool calling is fundamentally the same: the model instructs the user to call specific function(s) in order to an...
Introduction OpenAI and Azure OpenAI assistants can invoke models and utilize tools to accomplish tasks. This article primarily focuses on constructing pipelines to leverage the tool-calling capabilit...
Introduction In this article, we will be introducing the following. Part 1: Four new classes of snaps for LLM function calling: Function Generator, Tool Calling, Function Result Generator, and Messag...
What is Retrieval-Augmented Generation (RAG)? Retrieval-Augmented Generation (RAG) is the process of enhancing the reference data used by language models (LLMs) through integrating them with tradition...
Why do we need LLM Observability? GenAI applications are great, they answer like how a human does. But how do you know if GPT isn’t being “too creative” to you when results from the LLM shows “Company...
What are embeddings Embeddings are numerical representations of real-world objects, like text, images or audio. They are generated by machine learning models as vectors, an array of numbers, where the...
msager
on:
Multi Pipeline Function Generator - Simplifies Age...
Jocelyn
on:
LLM response logging for analytics
