Control LLM output with response type and schema

 Posted on 15 July 2024

Introduction Large language models (LLMs) are great at generating content but the output format you get back can be a hit or miss sometimes. For example, you ask for a JSON output in certain format and you might get free-form text or a JSON wrapped in markdown string or a proper JSON but with some required fields missing. If your application requires a strict format, this can be a real problem. Read More →
GenAI  VertexAI  Gemini  Google Cloud Platform 

RAG API powered by LlamaIndex on Vertex AI

 Posted on 8 July 2024

Introduction Recently, I talked about why grounding LLMs is important and how to ground LLMs with public data using Google Search (Vertex AI’s Grounding with Google Search: how to use it and why) and with private data using Vertex AI Search (Grounding LLMs with your own data using Vertex AI Search). In today’s post, I want to talk about another more flexible and customizable way of grounding your LLMs with private data: the RAG API powered by LlamaIndex on Vertex AI. Read More →
GenAI  VertexAI  Gemini  Google Cloud Platform 

Grounding LLMs with your own data using Vertex AI Search

 Posted on 1 July 2024

Introduction In my previous Vertex AI’s Grounding with Google Search: how to use it and why post, I explained why you need grounding with large language models (LLMs) and how Vertex AI’s grounding with Google Search can help to ground LLMs with public up-to-date data. That’s great but you sometimes need to ground LLMs with your own private data. How can you do that? There are many ways but Vertex AI Search is the easiest way and that’s what I want to talk about today with a simple use case. Read More →
GenAI  VertexAI  Gemini  Google Cloud Platform 

Give your LLM a quick lie detector test

 Posted on 6 June 2024

Introduction It’s no secret that LLMs sometimes lie and they do so in a very confident kind of way. This might be OK for some applications but it can be a real problem if your application requires high levels of accuracy. I remember when the first LLMs emerged back in early 2023. I tried some of the early models and it felt like they were hallucinating half of the time. More recently, it started feeling like LLMs are getting better at giving more factual answers. Read More →
GenAI  VertexAI  Gemini  Google Cloud Platform 

Vertex AI's Grounding with Google Search - how to use it and why

 Posted on 29 May 2024

Introduction Once in a while, you come across a feature that is so easy to use and so useful that you don’t know how you lived without it before. For me, Vertex AI’s Grounding with Google Search is one of those features. In this blog post, I explain why you need grounding with large language models (LLMs) and how Vertex AI’s Grounding with Google Search can help with minimal effort on your part. Read More ↗︎
GenAI  VertexAI  Gemini  Google Cloud Platform 

A tour of Gemini 1.5 Pro samples

 Posted on 7 May 2024

Introduction Back in February, Google announced Gemini 1.5 Pro with its impressive 1 million token context window. Larger context size means that Gemini 1.5 Pro can process vast amounts of information in one go — 1 hour of video, 11 hours of audio, 30,000 lines of code or over 700,000 words and the good news is that there’s good language support. In this blog post, I will point out some samples utilizing Gemini 1. Read More →
GenAI  VertexAI  Gemini  Google Cloud Platform 

C# and Vertex AI Gemini streaming API bug and workaround

 Posted on 1 May 2024

A user recently reported an intermittent error with C# and Gemini 1.5 model on Vertex AI’s streaming API. In this blog post, I want to outline what the error is, what causes it, and how to avoid it with the hopes of saving some frustration for someone out there. Error The user reported using Google.Cloud.AIPlatform.V1 library with version 2.27.0 to use Gemini 1.5 via Vertex AI’s streaming API and running into an intermittent System. Read More →
GenAI  VertexAI  Gemini  DotNet  Google Cloud Platform 

A Tour of Gemini Code Assist - Slides and Demos

 Posted on 24 April 2024

This week, I’m speaking at 3 meetups on Gemini Code Assist. My talk has a little introduction to GenAI and Gemini, followed by a series of hands-on demos that showcase different features of Gemini Code Assist. In the demos, I setup Gemini Code Assist in Cloud Code IDE plugin in Visual Studio Code. Then, I show how to design and create an application, explain, run, generate, test, transform code, and finish with understanding logs with the help of Gemini. Read More →
GenAI  VertexAI  Gemini  Google Cloud Platform 

Vertex AI Gemini generateContent (non-streaming) API

 Posted on 26 February 2024

Introduction In my recent blog post, I’ve been exploring Vertex AI’s Gemini REST API and mainly talked about the streamGenerateContent method which is a streaming API. Recently, a new method appeared in Vertex AI docs: generateContent which is the non-streaming (unary) version of the API. In this short blog post, I take a closer look at the new non-streaming generateContent API and explain why it makes sense to use as a simpler API when the latency is not super critical. Read More →
GenAI  VertexAI  Gemini  Google Cloud Platform 

Using Vertex AI Gemini from GAPIC libraries (C#)

 Posted on 14 February 2024

Introduction In my previous Using Vertex AI Gemini REST API post, I showed how to use the Gemini REST API from languages without SDK support yet such as C# and Rust. There’s actually another way to use Gemini from languages without SDK support: GAPIC libraries. In this post, I show you how to use Vertex AI Gemini from GAPIC libraries, using C# as an example. What is GAPIC? At this point, you might be wondering: What’s GAPIC? Read More →
GenAI  VertexAI  Gemini  Google Cloud Platform