augllm 1.3

('A library for augmenting large language models',)

augllm

augllm is a wrapper library for operating Augmented Large Language Models (LLMs) using Ollama.
It provides an interface for utilizing external tools via Function Calling.
Note that the actual implementations of the tools are not included—users are expected to integrate their own external implementations as needed.

Repository: https://github.com/ToPo-ToPo-ToPo/augllm

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Table of Contents

1. Features / Overview
2. Requirements
3. Installation
4. Usage
   • Sample Programs
   • Integration with Function Calling
5. License

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1. Features / Overview

• Interact with LLMs (either local or cloud-based) through Ollama
• Support for tool integration using Function Calling
• Tools are defined as abstract interfaces; concrete implementations (e.g., API calls, local script execution) can be freely developed by the user
• Designed with extensibility in mind: easy integration with custom tools, chaining, and prompt engineering

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2. Requirements

• Python 3.11 or higher
• An environment where Ollama CLI or API client is available

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3. Installation

1. Create and activate a virtual environment

python -m venv env

On macOS, activate the virtual environment:

source env/bin/activate

2. Install the library

pip install augllm

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4. Usage

Sample Programs

A test/ directory is included in the repository.
Please refer to the two files inside as examples.

Integration with Function Calling

1. Provide function signatures in the prompt that represent expected tool calls
2. Receive the function call request returned by the model (tool name + arguments)
3. Invoke the corresponding tool interface’s run(...) method and obtain the result
4. Pass the result back to the model to obtain the final response

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5. License

This project is licensed under the Apache-2.0 License.
See the LICENSE file for details.