FilterlessCook 0.1.7

Generate LaTeX formatted food recipes using the ollama library.

FILTERLESSCOOK

Unique Data Recipes, No Filters Needed!

Table of Contents

• Overview
• Getting Started
  • Installation
  • Usage
    • Basic Usage
    • Options
    • Example
• Features
• Repository Structure
• Modules
• License

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Overview

FilterlessCook is an innovative open-source Python package that streamlines recipe generation by eliminating the need for prefilters, offering a unique approach to data processing. This projects central module, filterlesscook.py, utilizes the ollama library and an AI assistant model for creating LaTeX-formatted recipes based on user prompts. With a focus on developer productivity, FilterlessCook allows developers to quickly create and save custom LaTeX documents using a single command, operating in an alpha stage under the MIT license. By using the FilterlessCook package, users can efficiently generate personalized food recipes without worrying about complicated setup or licensing issues.

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Getting Started

System Requirements:

• Python: version 3.6+

Installation

To install the FilterlessCook package, follow the instructions below:

pip install filterlesscook

If you want to use a specific version of the "dolphin-mixtral" model please preinstall, otherwise the tool will attempt to pull the newest version if none is already installed.

Usage

To generate food recipes formatted as LaTeX using the filterless-cook command line tool, follow the instructions below:

Basic Usage

filterless-cook food

Replace food with the name of the food or product you want the recipe for.

Options

-h, --help: Show the help message and exit.

filterless-cook -h

-p PROMPT, --prompt PROMPT: Use a user-defined prompt for recipe generation.

filterless-cook food -p "Your custom prompt here"

-f FILE, --file FILE: Save the generated LaTeX document to the specified file path.

filterless-cook food -f /path/to/save/recipe.tex

-m, --measurement MEASUREMENT: Specify the type of measurement to be used in the recipes. Choose either 'metric' or 'imperial'. The default is 'metric'.

filterless-cook food -m imperial

--debug: Enable debug logging to see detailed log output.

filterless-cook food --debug

Example

To generate a chocolate cake recipe with a custom prompt and save it to chocolate_cake.tex with debug logging enabled:

filterless-cook "chocolate cake" -p "You are an expert baker with special experience in european cakes." -f chocolate_cake.tex --debug

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Features

Feature	Description
⚙️ Architecture	The project is a Python package with central functionality in filterlesscook.py. It utilizes the OLLAMA library for LaTeX document creation and interacts with AI assistants through chat interaction.
🔩 Code Quality	Well-organized code structure using Python, with adherence to the MIT license. Uses setup.py for distribution and easy installation via pip.
📄 Documentation	Provides essential documentation in both README.md and an informative LICENSE file. It explains usage, requirements, and development processes.
🔌 Integrations	Utilizes OLLAMA library for LaTeX document creation, and incorporates user-defined prompts and chat interactions to generate recipes.
⚡️ Performance	Efficient LaTeX document generation, with potential room for improvement based on user's AI assistant model and requirements.
🛡️ Security	Utilizes local uncensored AI assistant models (dolphin-mixtral) to generate recipe text while prioritizing user privacy.
📦 Dependencies	Key external libraries include OLLAMA for LaTeX document creation, chat interaction interfaces and debug logging libraries.

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Repository Structure

└── filterlesscook/
    ├── LISENCE
    ├── MANIFEST.in
    ├── filterlesscook
    │   ├── __init__.py
    │   └── filterlesscook.py
    └── setup.py

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Modules

filterlesscook

File	Summary
filterlesscook.py	LaTeX documents for recipes using ollama library and chat interaction, user-defined prompts, and saved to specified file paths. Utilizes debug logging and employs an uncensored AI assistant model (dolphin-mixtral) to generate recipe text, ensuring no kittens are harmed.

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License

This project is protected under the MIT License. For more details, refer to the LICENSE file.

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