Merge pull request #2005 from ArmDeveloperEcosystem/main

Production update

Author: jasonrandrews

.wordlist.txt

@@ -4184,4 +4184,20 @@ subgenre
 submodule
 subword
 techcrunch
-transformative
+transformative
+Aude
+Gian
+Iodice
+SmolLM
+VME
+Vuilliomenet
+cpus
+fLO
+invalidations
+libtensorflowlite
+macos
+multithreaded
+Wix's
+ngrok's
+qs
+qu

assets/contributors.csv

@@ -85,5 +85,9 @@ Yiyang Fan,Arm,,,,
 Julien Jayat,Arm,,,,
 Geremy Cohen,Arm,geremyCohen,geremyinanutshell,,
 Barbara Corriero,Arm,,,,
-Nina Drozd,Arm,,ninadrozd,,
+Nina Drozd,Arm,NinaARM,ninadrozd,,
 Jun He,Arm,JunHe77,jun-he-91969822,,
+Gian Marco Iodice,Arm,,,,
+Aude Vuilliomenet,Arm,,,,
+Andrew Kilroy,Arm,,,,
+Peter Harris,Arm,,,,

content/learning-paths/cross-platform/mcp-ai-agent/intro-to-mcp-uv.md

@@ -17,7 +17,7 @@ The Model Context Protocol (MCP) is an open specification designed to connect La
 
 - **Security by design:** MCP encourages running servers inside your own infrastructure, so sensitive data stays within your infrastructure unless explicitly shared.
 
-- **Cross-ecosystem momentum:** recent roll-outs from an official C# SDK to Wix’s production MCP server and Microsoft’s Azure support show the MCP spec is gathering real-world traction.
+- **Cross-ecosystem momentum:** recent roll-outs from an official C# SDK to Wix's production MCP server and Microsoft’s Azure support show the MCP spec is gathering real-world traction.
 
 ## What is uv?
 

content/learning-paths/cross-platform/mcp-ai-agent/mcp-server.md

@@ -115,7 +115,7 @@ INFO:     Uvicorn running on http://0.0.0.0:8000 (Press CTRL+C to quit)
 
 You will now use ngrok to expose your locally running MCP server to the public internet over HTTPS.
 
-1. Add ngrok’s repo to the apt package manager and install:
+1. Add ngrok's repo to the apt package manager and install:
 ```bash
 curl -sSL https://ngrok-agent.s3.amazonaws.com/ngrok.asc \
   | sudo tee /etc/apt/trusted.gpg.d/ngrok.asc >/dev/null \

content/learning-paths/embedded-and-microcontrollers/_index.md

@@ -61,6 +61,7 @@ tools_software_languages_filter:
 - GitHub: 3
 - GitLab: 1
 - Himax SDK: 1
+- Hugging Face: 3
 - IP Explorer: 4
 - Jupyter Notebook: 1
 - K3s: 1

content/learning-paths/embedded-and-microcontrollers/llama-python-cpu/_index.md

@@ -28,7 +28,7 @@ tools_software_languages:
     - GenAI
     - Raspberry Pi
     - Python
-
+    - Hugging Face
 
 further_reading:
     - resource:

content/learning-paths/embedded-and-microcontrollers/rpi-llama3/_index.md

@@ -31,6 +31,7 @@ tools_software_languages:
     - LLM
     - GenAI
     - Raspberry Pi
+    - Hugging Face
 
 
 

content/learning-paths/embedded-and-microcontrollers/yolo-on-himax/_index.md

@@ -32,6 +32,8 @@ armips:
 tools_software_languages:
     - Himax SDK
     - Python
+    - Hugging Face
+
 operatingsystems:
     - Linux
     - macOS

content/learning-paths/laptops-and-desktops/_index.md

@@ -10,11 +10,11 @@ operatingsystems_filter:
 - Android: 2
 - ChromeOS: 1
 - Linux: 31
-- macOS: 7
-- Windows: 43
+- macOS: 8
+- Windows: 44
 subjects_filter:
 - CI-CD: 5
-- Containers and Virtualization: 5
+- Containers and Virtualization: 6
 - Migration to Arm: 28
 - ML: 2
 - Performance and Architecture: 25
@@ -39,7 +39,7 @@ tools_software_languages_filter:
 - Coding: 16
 - CSS: 1
 - Daytona: 1
-- Docker: 4
+- Docker: 5
 - GCC: 10
 - Git: 1
 - GitHub: 3
@@ -52,6 +52,7 @@ tools_software_languages_filter:
 - JavaScript: 2
 - Kubernetes: 1
 - Linux: 1
+- LLM: 1
 - LLVM: 1
 - llvm-mca: 1
 - MSBuild: 1
@@ -62,7 +63,7 @@ tools_software_languages_filter:
 - ONNX Runtime: 1
 - OpenCV: 1
 - perf: 4
-- Python: 5
+- Python: 6
 - Qt: 2
 - Remote.It: 1
 - RME: 1

content/learning-paths/laptops-and-desktops/docker-models/_index.md

@@ -0,0 +1,53 @@
+---
+title: Learn how to use Docker Model Runner in AI applications
+
+draft: true
+cascade:
+    draft: true
+
+minutes_to_complete: 45
+
+who_is_this_for: This is for software developers and AI enthusiasts who want to run AI models using Docker Model Runner.
+
+learning_objectives:
+    - Run AI models locally using Docker Model Runner.
+    - Easily build containerized applications with LLMs.
+
+prerequisites:
+    - A computer with at least 16GB of RAM (recommended) and Docker Desktop installed (version 4.40 or later).
+    - Basic understanding of Docker.
+    - Familiarity with Large Language Model (LLM) concepts.
+
+author: Jason Andrews
+
+### Tags
+skilllevels: Introductory
+subjects: Containers and Virtualization
+armips:
+    - Neoverse
+    - Cortex-A
+operatingsystems:
+    - Windows
+    - macOS
+tools_software_languages:
+    - Docker
+    - Python
+    - LLM
+
+further_reading:
+    - resource:
+        title: Docker Model Runner Documentation
+        link: https://docs.docker.com/model-runner/
+        type: documentation
+    - resource:
+        title: Introducing Docker Model Runner
+        link: https://www.docker.com/blog/introducing-docker-model-runner/
+        type: blog
+
+### FIXED, DO NOT MODIFY
+# ================================================================================
+weight: 1                       # _index.md always has weight of 1 to order correctly
+layout: "learningpathall"       # All files under learning paths have this same wrapper
+learning_path_main_page: "yes"  # This should be surfaced when looking for related content. Only set for _index.md of learning path content.
+---
+