Ollama in Action: Building Safe, Private AI with LLMs, Function Calling and Agents
Ollama in Action: Building Safe, Private AI with LLMs, Function Calling and Agents
About the Book
Use Ollama to run powerful LLMs on your home computer and on-premises computers at work to maintain data privacy and control of your tech stack. Clear Python code examples and recommendations for effectively using Ollama will get you started quickly if you are new to LLMs and if you are a seasoned professional you will learn a few useful tips and techniques.
License
About the Author
Table of Contents
- Preface
- About the Author
- Requests from the Author
- Why Should We Care About Privacy?
- Setting Up Your Computing Environment for Using Ollama and Using Book Example Programs
- Python Build Tools
- Using Ollama From the Command Line
- Using JSON Format
- Analysis of Images
- Analysis of Source Code Files
- Short Examples
- Using The Ollama Python SDK with Image and Text Prompts
- Using the OpenAI Compatibility APIs with Local Models Running on Ollama
- LLM Tool Calling with Ollama
- Example Showing the Use of Tools Developed Later in this Chapter
- Tool for Reading and Writing File Contents
- Tool for Getting File Directory Contents
- Tool for Accessing SQLite Databases Using Natural Language Queries
- Tool for Summarizing Text
- Tool for Web Search and Fetching Web Pages
- Tools Wrap Up
- Automatic Evaluation of LLM Results: More Tool Examples
- Tool For Judging LLM Results
- Evaluating LLM Responses Given a Chat History
- A Tool for Detecting Hallucinations
- Wrap Up
- Building Agents with Ollama and the Hugging Face Smolagents Library
- Choosing Specific LLMs for Writing Agents
- Installation notes
- Overview of the Hugging Face Smolagents Library
- Overview for LLM Agents (optional section)
- Let’s Write Some Code
- Output from Third Example: “Read the text in the file ‘data/economics.txt’ file and then summarize this text.”
- Agents Wrap Up
- Using AG2 Open-Source AgentOS LLM-Based Agent Framework for Generating and Executing Python Code
- Example Implementation
- Example Output
- Wrap Up for Using AG2’s Agent Framework for Generating and Executing Python Code
- Using the Unsloth Library on Google Colab to FineTune Models for Ollama
- Colab Notebook 1: A Quick Test of Fine Tuning and Deployment to Ollama on a Laptop
- Fine Tuning Using a Fun Things To Do in Arizona Data Set
- Third Colab Notebook That Fine Tunes a Larger Model
- Fine Tuning Wrap Up
- Reasoning with Large Language Models
- A Simple Example
- Key Features of Marco-o1
- A More Complex Example: City Traffic Planning
- Using Property Graph Database with Ollama
- Overview of Property Graphs
- Example Using Ollama, LangChain, and the Kuzu Property Graph Database
- Using LLMs to Create Graph Databases from Text Data
- Using the Open Codex Command Line Interface Coding Agent
- Example Use Cases
- Open Codex Wrap Up
- Long Term Persistence Using Mem0 and Chroma
- Code Example Using Mem0 and Chroma
- Example Output
- Using Ollama Cloud Services
- Ollama Cloud Services: Power and Knowledge on Demand
- Augmenting Models with the Web Search API
- Wrap-Up: A Unified Local and Cloud Strategy
- Book Wrap Up
- Preface
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