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As AI/ML becomes a first-class citizen in modern applications, running models reliably, securely, and efficiently is no longer optional. Docker introduced Model Runner and Offload Containers to solve real-world AI deployment pain points. This blog pr...

In the field of conversational AI, an intent represents the user's goal or objective when formulating a request. For example, in a Dungeons & Dragons-style role-playing game, a player might express the intent/intention to "launch an attack" or "speak...

Prerequisites: please read the previous post: Snippet Management and Generation with cagent An extremely interesting feature of cagent is the ability to have multiple agents interact with each other. This means you can define multiple agents in the s...

Today, I'm going to tell you about cagent: it's a tool developed by Docker that allows you to easily create and run specialized AI agents. It serves as an engine for orchestrating multiple agents with different capabilities and tools, to solve comple...

Prerequisites: Having read the previous blog post First Contact with Genkit and Docker Model Runtime Having this model: ai/qwen2.5:0.5B-F16 (use the command docker model pull ai/qwen2.5:0.5B-F16) Introduction: what are Flows? Genkit "flows" are con...

It's no secret that I have multiple "technological" addictions. Particularly Generative AI (mainly with Docker Model Runner) and the Go language. Last night, I discovered Genkit Go which is a Go SDK from Google to facilitate the development of genera...
