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LLM Engineer’s Handbook

An official Python repository accompanying the LLM Engineer's Handbook, with code for end-to-end LLM and RAG systems.

Independent OpenViST project profile, based on linked sources.

LLM Engineer's Handbook — OpenViST project profile in AI Developer Tools & SDKs.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use it when a project needs practical code covering the LLM lifecycle from data and training through application development and operational evaluation.

Who it is for

  • Engineers learning production-oriented LLM development
  • Developers building or adapting LLM and RAG applications
  • Practitioners exploring LLM training, fine-tuning, evaluation, monitoring, and AWS deployment

Documented uses

  • Study an end-to-end LLM engineering workflow
  • Create a simple retrieval-augmented generation application
  • Organize model and data work into ZenML pipelines
  • Prepare testing, evaluation, and monitoring practices
  • Adapt deployment examples for AWS
Before you choose

Requirements & limits

The repository is public and MIT-licensed. The documented local setup uses Python 3.11, Poetry, Docker, AWS CLI, and Git; several cloud services are part of the project environment.

  • The repository is Python-based and organized around a core package, ZenML pipelines, reusable steps, tools, and tests.
  • The scope extends beyond RAG to training, fine-tuning, deployment, monitoring, and evaluation.
  • AWS is the documented cloud deployment focus.
  • The project depends on a multi-service environment including AWS, Hugging Face, Comet ML, Opik, ZenML, MongoDB, Qdrant, and GitHub Actions.
  • The README warns that repository code may be newer than the accompanying book.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Set up the repository's local development environment

Prepare the documented local tools and obtain the repository code.

Before you start

  • Python 3.11
  • Poetry version 1.8.3 or later and below 2.0
  • Docker version 27.1.1 or later
  • AWS CLI version 2.15.42 or later
  • Git version 2.44.0 or later

Steps

  1. Install the documented local dependencies.

  2. Clone https://github.com/PacktPublishing/LLM-Engineers-Handbook.git.

  3. Change into the LLM-Engineers-Handbook directory.

  4. Continue with the repository's installation and deployment sections for the remaining setup.

Expected outcome

The repository is available locally with the documented development tools prepared.

Evidence and transparency

Sources & review

Source record details
Source availability
Active
Sources checked
1 October 2026
Original website title
PacktPublishing/LLM-Engineers-Handbook · Official homepage title · retained in its source language