Sample code and notebooks for Generative AI on Google Cloud, with Gemini on Vertex AI - GoogleCloudPlatform/generative-ai

Sample code and notebooks for Generative AI on Google Cloud, with Gemini on Vertex AI - GoogleCloudPlatform/generative-ai

Authors: Marcus Lin, Shawn Yang, Ivan Nardini TLDR: We’re introducing Inline Source Deployment for Vertex AI Agent Engine. Now, you can deploy agents directly from your source files—bypassing the need to provision and manage Cloud Storage buckets entirely. This method aligns your agents with standard engineering requirements, enabling support for Git version control, CI/CD pipelines, and security scanning. It’s the definitive shift from “works in my notebook” to “deploy my agent”. Introduct...

Sample code and notebooks for Generative AI on Google Cloud, with Gemini on Vertex AI - GoogleCloudPlatform/generative-ai

Google ADK v1.18.0 introduced the Visual Agent Builder — a browser-based interface that lets you design, configure, and test complex…

Announcing new capabilities across the entire agent lifecycle to help developers build, scale, and govern AI agents using Vertex AI Agent Builder. Get started today.

Sample code and notebooks for Generative AI on Google Cloud, with Gemini on Vertex AI - GoogleCloudPlatform/generative-ai

Welcome to The Agent Factory, a podcast that goes beyond the hype and dives into building production ready AI agents. Join hosts Shir Meir Lador and Ivan as ...

By: Ekaterina Sirazitdinova, NVIDIA and Ivan Nardini, Google Cloud TL;DR: A technical guide to AI model formats for AI inference. Learn the trade-offs: use Safetensors for fast, secure serialization (replacing .bin), GGUF for quantized local/CPU inference (e.g., llama.cpp), TensorRT for compiled, high-performance NVIDIA GPU engines, and ONNX for graph-level framework interoperability. For further learning and hands-on experience with foundational inference workloads on Google Cloud, conside...