Learn Mistral: Elevating Mistral systems through embeddings, agents, RAG, AWS Bedrock, and Vertex AI

Learn Mistral: Elevating Mistral systems through embeddings, agents, RAG, AWS Bedrock, and Vertex AI book cover

Learn Mistral: Elevating Mistral systems through embeddings, agents, RAG, AWS Bedrock, and Vertex AI

Author(s): Pavlo Cherkashin (Author)

  • Publisher: Packt Publishing
  • Publication Date: October 10, 2025
  • Language: English
  • Print length: 528 pages
  • ISBN-10: 183588864X
  • ISBN-13: 9781835888650

Book Description

Unlock the power of Mistral models by building embeddings, RAG systems, and coding assistants that deliver real-world AI solutions.

Free with your book: DRM-free PDF version + access to Packt's next-gen Reader*

Key Features

  • Build secure local chat apps, multi-agent workflows, and coding assistants with Mistral
  • Master embeddings and advanced RAG techniques to create scalable, context-aware AI
  • Deploy compliant, production-ready AI on AWS Bedrock, Google Vertex AI, and beyond

Book Description

This is a practical, project-driven guide to turning open-source Mistral models into production-ready AI solutions. Through hands-on workshops and use cases, you’ll learn how to build private chat systems, semantic search engines, intelligent agents, coding assistants, and secure deployments that go beyond simple experimentation.

The journey begins by exploring where Mistral excels and where human oversight is essential. You’ll then learn to set up a secure, locally hosted chat system with Ollama, customize behavior with system prompts and parameters, and dive deep into embeddings to unlock semantic search with Pinecone. As you progress, you’ll build multi-agent workflows, unpack advanced Retrieval-Augmented Generation pipelines, and integrate Mistral with Codestral to accelerate coding. You'll also learn to apply Mistral to cybersecurity, be challenged with open-ended RAG projects, and be guided through deploying scalable AI on AWS Bedrock and Google Vertex AI.

By the end of this book, you will be ready to design and build AI systems that are innovative, compliant, and production-ready.

*Email sign-up and proof of purchase required

What you will learn

  • Build a secure local chat system with Ollama and Mistral
  • Tune prompts and parameters to control model behavior
  • Use embeddings and Pinecone for semantic search systems
  • Design agents and multi-agent workflows with Mistral
  • Implement advanced Retrieval-Augmented Generation pipelines
  • Create coding copilots with Codestral in VS Code
  • Deploy scalable AI on AWS Bedrock and Google Vertex AI

Who this book is for

This book is ideal for software developers, AI practitioners, data scientists, and technology enthusiasts who are keen to master Mistral models. Whether you're looking to deploy powerful AI systems, enhance your existing skills, or understand the intricacies of operating AI in regulated environments, this book provides the knowledge and practical insights needed to excel.

Table of Contents

  1. Strengths, Limitations, and Use Cases of Language Models
  2. Setting Up Your Own Chat
  3. Managing the Model
  4. Mastering Embeddings
  5. Agents: From Automation to Intelligence
  6. Unpacking RAG Workflows
  7. Coding with Mistral
  8. Building Smarter Defenses with Mistral
  9. Take-Home RAG Challenges
  10. Mistral on AWS Bedrock
  11. Harnessing Mistral's Power via Google Cloud Vertex AI

Editorial Reviews

About the Author

Pavel Cherkashin is a seasoned software craftsmanship expert with a focus on artificial intelligence and machine learning. He currently works as a consultant, helping organizations design and implement innovative AI solutions. Pavel's journey into AI began with a deep fascination for neural networks, and he has since dedicated his career to mastering and applying AI technologies. Along the way, he has contributed to major technology initiatives at companies such as Nike and Oracle. Pavel is also passionate about teaching, conducting workshops and training sessions to help professionals and enthusiasts understand and implement AI technologies effectively.

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