Ollama in Action: Building Safe, Private AI with LLMs, Function Calling and Agents

Course overview

Use Ollama to run LLMs locally for privacy and control of your tech stack. We look at Tools/function calling and agents in detail.

24 chapters
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The Book

Ollama in Action: Building Safe, Private AI with LLMs, Function Calling and Agents24 chapters

Begin
  1. Preface

  2. Acknowledgements

  3. Setting Up Your Computing Environment for Using Ollama and Using Book Example Programs

  4. Using Ollama From the Command Line

  5. Short Examples

  6. LLM Tool Calling with Ollama

  7. Pydantic AI Experiments

  8. Automatic Evaluation of LLM Results: More Tool Examples

  9. Prompt Caching

  10. Building Agents with Ollama and the Hugging Face Smolagents Library

  11. Using AG2 Open-Source AgentOS LLM-Based Agent Framework for Generating and Executing Python Code

  12. Using the Unsloth Library on Google Colab to FineTune Models for Ollama

  13. DSP Experiments

  14. Reasoning with Large Language Models

  15. Using Property Graph Database with Ollama

  16. LangGraph

  17. Using the Open Codex Command Line Interface Coding Agent

  18. Long Term Persistence Using Mem0 and Chroma

  19. Using Ollama Cloud Services

  20. Using AI Coding Agents with Local Ollama Models and Ollama Cloud

  21. Semantic Navigator App Using Gradio

  22. RAG Using zvec Vector Datastore and Local Model

  23. Benchmarking Model Inference Speeds

  24. Book Wrap Up