maticlib 0.2.1

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.

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Documentation

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

• Getting Started
• API Reference
• Example Gallery

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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]"

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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

Quick Start: Context Engineering (RAG)

from maticlib.io.file import TextLoader
from maticlib.core.text.chunkers import HierarchicalChunker

chunker = HierarchicalChunker(target_size=500)
loader = TextLoader(chunker=chunker)

segments = list(loader.load("data.txt"))
print(f"Loaded {len(segments)} segments!")

Quick Start: Text2SQL

from maticlib.core.text2sql.guards import SQLInjectionGuard
from maticlib.core.text2sql.executors import SQLAlchemyExecutor

guard = SQLInjectionGuard(allowed_dialect="sqlite")
executor = SQLAlchemyExecutor("sqlite:///my_db.db", read_only=True)

query = guard.validate_and_format("SELECT * FROM users LIMIT 10")
cols, rows = executor.execute(query)

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Project Leadership

Maticlib is developed and maintained by Arvoh Software.

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

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License

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