RecipeReduce: Simplified Recipe Processing for Lazy Programmers

Overview

RecipeReduce

GitHub stars GitHub license Black

This repo will help you figure out the amount of ingredients to buy for a certain number of meals with selected recipes.

Getting Started

Installation

pip install -e .

Usage

To start, create a menu in desired language (available options: en / zh):

python -m recipe_reduce.menu --fname input.json --lang en

Open input.json, fill in the number of meals you would like to have for each recipe. Then, run the following command to get the list of ingredients:

python -m recipe_reduce.main --fname input.json --lang en

Examples

Input

{
  "甜粘三文鱼 配 烤蔬菜和米饭": 1,
  "柠檬刺山柑猪排和帕尔马玉米粥 配 迷迭香和大蒜烤青豆": 1
}

Output

[("rice", 2.5), ("green_beans", 0.5), ("bell_pepper", 0.5), ("garlic", 1.0), ("sesame", 0.125), ("tamari", 0.25), ("salmon", 5), ("sweet_chili_sauce", 1.5), ("lime", 0.5), ("chives", 0.125), ("rosemary", 0.125), ("lemon", 0.5), ("parmesan", 0.375), ("polenta", 1.5), ("pork", 6), ("turkey_broth_con", 0.5), ("caper", 0.5)]

More Recipes!

Add a New Recipe

To add a new recipe, have a look at recipe_reduce/recipe.py, create and add your own recipe to ALL_RECIPES.

Add New Ingredients

You might also want to add new ingredents, open data/items.csv and fill in the item information. Then, add a constant string in recipe_reduce/constants.py consistent with the item id in the csv.

TODOs

  • Print detailed item information from csv
  • Automatically add to WholeFoods cart with item url and amount
Owner
Qibin Chen
Rebooting.
Qibin Chen
Code associated with the "Data Augmentation using Pre-trained Transformer Models" paper

Data Augmentation using Pre-trained Transformer Models Code associated with the Data Augmentation using Pre-trained Transformer Models paper Code cont

44 Dec 31, 2022
Behavioral Testing of Clinical NLP Models

Behavioral Testing of Clinical NLP Models This repository contains code for testing the behavior of clinical prediction models based on patient letter

Betty van Aken 2 Sep 20, 2022
[EMNLP 2021] Mirror-BERT: Converting Pretrained Language Models to universal text encoders without labels.

[EMNLP 2021] Mirror-BERT: Converting Pretrained Language Models to universal text encoders without labels.

Cambridge Language Technology Lab 61 Dec 10, 2022
ALIbaba's Collection of Encoder-decoders from MinD (Machine IntelligeNce of Damo) Lab

AliceMind AliceMind: ALIbaba's Collection of Encoder-decoders from MinD (Machine IntelligeNce of Damo) Lab This repository provides pre-trained encode

Alibaba 1.4k Jan 04, 2023
A combination of autoregressors and autoencoders using XLNet for sentiment analysis

A combination of autoregressors and autoencoders using XLNet for sentiment analysis Abstract In this paper sentiment analysis has been performed in or

James Zaridis 2 Nov 20, 2021
Use Tensorflow2.7.0 Build OpenAI'GPT-2

TF2_GPT-2 Use Tensorflow2.7.0 Build OpenAI'GPT-2 使用最新tensorflow2.7.0构建openai官方的GPT-2 NLP模型 优点 使用无监督技术 拥有大量词汇量 可实现续写(堪比“xx梦续写”) 实现对话后续将应用于FloatTech的Bot

Watermelon 9 Sep 13, 2022
Levenshtein and Hamming distance computation

distance - Utilities for comparing sequences This package provides helpers for computing similarities between arbitrary sequences. Included metrics ar

112 Dec 22, 2022
A method for cleaning and classifying text using transformers.

NLP Translation and Classification The repository contains a method for classifying and cleaning text using NLP transformers. Overview The input data

Ray Chamidullin 0 Nov 15, 2022
Checking spelling of form elements

Checking spelling of form elements. You can check the source files of external workflows/reports and configuration files

СКБ Контур (команда 1с) 15 Sep 12, 2022
Twitter bot that uses NLP models to summarize news articles referenced in a user's twitter timeline

Twitter-News-Summarizer Twitter bot that uses NLP models to summarize news articles referenced in a user's twitter timeline 1.) Extracts all tweets fr

Rohit Govindan 1 Jan 27, 2022
code for modular summarization work published in ACL2021 by Krishna et al

This repository contains the code for running modular summarization pipelines as described in the publication Krishna K, Khosla K, Bigham J, Lipton ZC

Kundan Krishna 6 Jun 04, 2021
Original implementation of the pooling method introduced in "Speaker embeddings by modeling channel-wise correlations"

Speaker-Embeddings-Correlation-Pooling This is the original implementation of the pooling method introduced in "Speaker embeddings by modeling channel

Themos Stafylakis 10 Apr 30, 2022
Pattern Matching in Python

Pattern Matching finalmente chega no Python 3.10. E daí? "Pattern matching", ou "correspondência de padrões" como é conhecido no Brasil. Algumas pesso

Fabricio Werneck 6 Feb 16, 2022
xFormers is a modular and field agnostic library to flexibly generate transformer architectures by interoperable and optimized building blocks.

Description xFormers is a modular and field agnostic library to flexibly generate transformer architectures by interoperable and optimized building bl

Facebook Research 2.3k Jan 08, 2023
SummerTime - Text Summarization Toolkit for Non-experts

A library to help users choose appropriate summarization tools based on their specific tasks or needs. Includes models, evaluation metrics, and datasets.

Yale-LILY 213 Jan 04, 2023
Semantic search through a vectorized Wikipedia (SentenceBERT) with the Weaviate vector search engine

Semantic search through Wikipedia with the Weaviate vector search engine Weaviate is an open source vector search engine with build-in vectorization a

SeMI Technologies 191 Dec 26, 2022
A Paper List for Speech Translation

Keyword: Speech Translation, Spoken Language Processing, Natural Language Processing

138 Dec 24, 2022
CVSS: A Massively Multilingual Speech-to-Speech Translation Corpus

CVSS: A Massively Multilingual Speech-to-Speech Translation Corpus CVSS is a massively multilingual-to-English speech-to-speech translation corpus, co

Google Research Datasets 118 Jan 06, 2023
An easy to use, user-friendly and efficient code for extracting OpenAI CLIP (Global/Grid) features from image and text respectively.

Extracting OpenAI CLIP (Global/Grid) Features from Image and Text This repo aims at providing an easy to use and efficient code for extracting image &

Jianjie(JJ) Luo 13 Jan 06, 2023
Code for EMNLP'21 paper "Types of Out-of-Distribution Texts and How to Detect Them"

Code for EMNLP'21 paper "Types of Out-of-Distribution Texts and How to Detect Them"

Udit Arora 19 Oct 28, 2022