toolmate-sdk 0.0.14

ToolMate-SDK: a software developement kit for developing agentic AI applications that support 13 LLM backends and integrate tools and agents. (Developer: Eliran Wong)

# ToolMate AI - SDK

ToolMate-SDK: a software developement kit for developing agentic AI applications that support 13 LLM backends and integrate tools and agents. (Developer: Eliran Wong)

Supported backends: anthropic, azure, custom, deepseek, genai, github, googleai, groq, llamacpp, mistral, ollama, openai, vertexai, xai

# A Sibling Project

This SDK incorporates the best aspects of our favorite project, [Toolmate AI](https://github.com/eliranwong/toolmate), to create a library aimed at further advancing the development of AI applications.

# Supported backends

anthropic - [Anthropic API](https://console.anthropic.com/)

azure - [Azure OpenAI API](https://learn.microsoft.com/en-us/azure/ai-services/openai/reference)

custom - any openai-compatible backends

deepseek - [DeepSeek API](https://platform.deepseek.com/)

genai - [Vertex AI](https://cloud.google.com/vertex-ai) or [Google AI](https://ai.google.dev/)

github - [Github API](https://docs.github.com/en/github-models/prototyping-with-ai-models#experimenting-with-ai-models-using-the-api)

googleai - [Google AI](https://ai.google.dev/)

groq - [Groq Cloud API](https://console.groq.com)

llamacpp - [Llama.cpp Server](https://github.com/ggerganov/llama.cpp) - [locat setup](https://github.com/ggerganov/llama.cpp/blob/master/docs/build.md) required

mistral - [Mistral API](https://console.mistral.ai/api-keys/)

ollama - [Ollama](https://ollama.com/) - [local setup](https://ollama.com/download) required

openai - [OpenAI API](https://platform.openai.com/)

vertexai - [Vertex AI](https://cloud.google.com/vertex-ai)

xai - [XAI API](https://x.ai/api)

For simplicity, toolmate-sdk uses ollama as the default backend, if parameter backend is not specified. Ollama models are automatically downloaded if they have not already been downloaded.

# Installation

Basic:

> pip install –upgrade toolmate-sdk

Basic installation supports all AI backends mentioned above, except for vertexai.

Extras:

We support Vertex AI via [Google GenAI SDK](https://pypi.org/project/google-genai/). As this package supports most platforms, except for Android Termux, we separate this package google-genai as an extra. To support Vertex AI with toolmate-sdk, install with running:

> pip install –upgrade toolmate-sdk[genai]

# Usage

This SDK is designed to provide a single function for interacting with all AI backends, delivering a unified experience for generating AI responses. The main APIs are provided with the function generate located in this [file](https://github.com/eliranwong/toolmate-sdk/blob/main/toolmate_sdk/__init__.py#L29).

Find documentation at https://github.com/eliranwong/toolmate-sdk/blob/main/docs/README.md

# Examples

The following examples assumes [Ollama](https://ollama.com/) is [installed](https://ollama.com/download):

To import:

> from toolmate_sdk import generate

To generate, e.g.:

> generate(“What is AI?”)

> generate(“What is ToolMate AI?”, tool=”search_google”)

> generate(“How many ‘r’s are there in the word ‘strawberry’?”, tool=”task”)

> generate(“What time is it right now?”, tool=”task”)

> generate(“Open github.com in a web browser.”, tool=”task”)

> generate(“Convert file ‘music.wav’ into mp3 format.”, tool=”task”)

> generate(“Send an email to Eliran Wong at [e-mail] to express my gratitude for his work.”, tool=”send_gmail”)

> generate(“Is it better to drink wine in the morning, afternoon, or evening?”, context=”reflect”, stream=True)

> generate(“Is it better to drink wine in the morning, afternoon, or evening?”, context=”think”, follow_up_prompt=[“review”, “refine”], stream=True)

> generate(“Provide a detailed introduction to generative AI.”, system=[“create_agents”, “assign_agents”], follow_up_prompt=”Who is the best agent to contribute next?”, stream=True, model=”llama3.3:70b”)

To work collaboratively with different backends, e.g.

> messages = generate(“What is the most effective method for training AI models?”, backend=”openai”) > messages = generate(messages, backend=”googleai”, follow_up_prompt=”Can you give me some different options?”) > messages = generate(messages, backend=”xai”, follow_up_prompt=”What are the limitations or potential biases in this information?”) > generate(messages, backend=”mistral”, follow_up_prompt=”Please provide a summary of the discussion so far.”)

As you may see, the generate function returns the messages list, which is passed to the next generate function in turns.

Therefore, it is very simple to create a chatbot application, you can do it as few as five lines or less, e.g.:

> messages = [{“role”: “system”, “content”: “You are an AI assistant.”}] > user_input = “Hello!” > while user_input: > messages = generate(messages, follow_up_prompt=user_input, stream=True) > user_input = input(“Enter your query:n(enter a blank entry to exit)n>>> “)

These are just a few simple and straightforward examples. You may find more examples at:

https://github.com/eliranwong/toolmate-sdk/tree/main/toolmate-sdk/examples

# TODO

• add documentation about tool creation

• add examples

• convert availble ToolMate AI tools into tools that runable with this SDK

• added built-in system messages

• added built-in predefined contexts

• added built-in prompts

• add cli options for running simple inference, tools or testing

• improve code generation handling