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Blazing fast local AI Agent for Python coding

Project description

Nemo Agent

PyPI - Version

Nemo Agent

Nemo Agent is a blazing fast local AI Agent for Python coding

Features

  • Runs blazing fast locally on an RTX 4070 or greater
  • Generates Python project structures automatically using poetry
  • Writes Python code based on task descriptions
  • Executes development tasks using AI-generated commands
  • Utilizes the mistral-nemo language model for intelligent code generation
  • Implements best practices in Python development automatically
  • Writes and runs passing tests up to 80%+ test coverage using pytest
  • Automatically fixes and styles code using pylint

Ability

Solves a leetcode hard with a set time complexity constraint in less than a minute with full tests on an RTX 4090

Installation

You can install Nemo Agent using pip:

pip install nemo-agent

Usage

After installation, you can use NemoAgent from the command line:

nemo-agent "Your task description here" If you run nemo-agent without any arguments, it will prompt you to enter a task.

Examples

Create a simple calculator:

nemo-agent "Create a simple calculator"

Generate a fizzbuzz program:

nemo-agent "Create a fizzbuzz script"

Cloud-Ready

  • RunPod is the recommended hosting provider for RTX 4090 compute - setup link

Limitations

  • LLM codegen issues mean that web APIs like Flask and FastAPI are not supported.

How It Works

Nemo Agent leverages mistral-nemo, Ollama, phidata, poetry, pytest, pylint, and other libraries to build a complete working solution for your task.

Requirements

  • Python 3.9 or higher
  • Ollama running mistral-nemo
  • Linux with a minimum of an RTX 4070

Contributing

Contributions to Nemo Agent are welcome! Please feel free to submit a Pull Request.

License

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

Disclaimer

Nemo Agent generates code using AI. While it strives for accuracy and best practices, the generated code should be reviewed and tested before being used in a production environment.

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