maticlib 0.1.9

A Python Automation Library for Creating Agents

A high-performance Python Automation Library for Creating Agents.

Maticlib is a developer-centric library designed to build complex, stateful AI workflows with ease. Whether you need a simple chat completion or a multi-node parallel execution graph, Maticlib provides the primitives to build it with a focus on type safety and performance.

---

Documentation

For complete documentation, visit: https://arvohsoft.github.io/maticlib/

• Getting Started
• API Reference
• Example Gallery

---

Installation

From PyPI

pip install maticlib

From Source (Local Development)

# Clone the repository
git clone https://github.com/arvohsoft/maticlib.git
cd maticlib

# Create and activate a virtual environment
python -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

# Install in editable mode with dev dependencies
pip install -e ".[dev]"

---

Quick Start

from maticlib.llm.openai import OpenAIClient

# Initialize client (uses OPENAI_API_KEY from environment)
client = OpenAIClient()

# Make a request
response = client.complete("Explain quantum computing in one sentence.")
print(client.get_text_response(response))

Quick Start: Embeddings

from maticlib import OpenAIEmbeddings

# Initialize the client
embed_client = OpenAIEmbeddings()

# Embed single query
res = embed_client.embed_query("Core features of Maticlib")
print(res.vector[:5])      # List[float]
print(res.prompt_tokens)   # Total prompt tokens used

---

Project Leadership

Maticlib is developed and maintained by Arvoh Software.

• Lead Maintainer: Anubroto Ghose
• Organization: Arvoh Software
• Contact: [e-mail]

---

License

This project is licensed under the MIT License - see the LICENSE file for details.