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Courses/Local MLOps and model deployment/llama.cpp server locally

llama.cpp server locally

llama.cpp server is a straightforward way to serve GGUF models locally. It's lightweight, controllable, and perfect for learning what it means to have a model behind your own API.

  • Build or install llama.cpp and start a local server.
  • Test an HTTP request without relying on a graphical interface.
  • Record the model, port, context, and parameters used.

Minimal server

Terminal
git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build --config Release

./build/bin/llama-server \
  -m models/modelo.gguf \
  --host 127.0.0.1 \
  --port 8080 \
  -c 4096

Test with curl

Terminal
curl http://127.0.0.1:8080/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{
    "model": "local-gguf",
    "messages": [
      {"role": "user", "content": "Explain what a queue is in MLOps AI in 3 sentences"}
    ],
    "temperature": 0.2
  }'

Service manifest

Terminal
servicio: llama-server-local
modelo: models/modelo.gguf
hash_modelo: sha256:...
host: 127.0.0.1
puerto: 8080
contexto: 4096
cuantizacion: Q4_K_M
uso: local development
fecha: 2026-07-03
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Complete Aulafy map

How all courses connect

This is not a checklist. Start with the foundation, choose an outcome, and go deeper only when your project needs more control.

  1. 1Understand
  2. 2Apply or build
  3. 3Operate with confidence
01

Choose an application

Turn the foundation into a visible outcome: a website, a business improvement, media, or an interactive experience.

Continue into the technical branch when you need to maintain code, data, or infrastructure.

02

Build with code

Prepare your environment, work with coding agents, and run models while keeping control of your projects.

This branch prepares you to design and operate reliable AI systems.

03

Take systems to production

Combine retrieval, agents, evaluation, security, deployment, and model adaptation when the problem requires it.

You do not need every course: choose the component your system needs and return as it grows.

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