A Python library for generating new text from existing samples.

Overview

PyPI version

ReMarkov is a Python library for generating text from existing samples using Markov chains. You can use it to customize all sorts of writing from birthday messages, horoscopes, Wikipedia articles, or the utterances of your game's NPCs. Everything works without an omnipotent "AI" - it is dead-simple code and therefore fast.

Check out the examples and feel free to contribute!


Installation

pip3 install remarkov

Example

Scrape the Wikipedia page for "Computer Programming" and generate a new text from it:

./tools/scrape-wiki.py Computer_programming | remarkov build | remarkov generate

You can also use remarkov programmatically:

from remarkov import create_model

model = create_model()
model.add_text("This is a sample text and this is another.")

print(model.generate().text())
# "This is a sample text and this is a sample text and this is a sample text ..."

Development

Make sure you run pytest as module. This will add the current directory to the import path:

python3 -m pytest

This project uses black for source code formatting:

black .

Generate documentation for the project (this uses the original pdoc at pdoc.dev):

git checkout gh-pages
pdoc -t pdoc/template -o public/docs <path_to_remarkov_module>

Run type checks using mypy:

mypy -p remarkov

Publishing is done like this (don't forget to bump the version in setup.py):

pip3 install twine # optional

git tag -a <version>
git push --tags

python3 setup.py clean --all
python3 setup.py sdist bdist_wheel
twine check "dist/*"
twine upload "dist/*"
You might also like...
 Qimera: Data-free Quantization with Synthetic Boundary Supporting Samples
Qimera: Data-free Quantization with Synthetic Boundary Supporting Samples

Qimera: Data-free Quantization with Synthetic Boundary Supporting Samples This repository is the official implementation of paper [Qimera: Data-free Q

The Malware Open-source Threat Intelligence Family dataset contains 3,095 disarmed PE malware samples from 454 families

MOTIF Dataset The Malware Open-source Threat Intelligence Family (MOTIF) dataset contains 3,095 disarmed PE malware samples from 454 families, labeled

Final project for machine learning (CSC 590). Detection of hepatitis C and progression through blood samples.

Hepatitis C Blood Based Detection Final project for machine learning (CSC 590). Dataset from Kaggle. Using data from previous hepatitis C blood panels

Analysis of Antarctica sequencing samples contaminated with SARS-CoV-2

Analysis of SARS-CoV-2 reads in sequencing of 2018-2019 Antarctica samples in PRJNA692319 The samples analyzed here are described in this preprint, wh

Deep Text Search is an AI-powered multilingual text search and recommendation engine with state-of-the-art transformer-based multilingual text embedding (50+ languages).
Deep Text Search is an AI-powered multilingual text search and recommendation engine with state-of-the-art transformer-based multilingual text embedding (50+ languages).

Deep Text Search - AI Based Text Search & Recommendation System Deep Text Search is an AI-powered multilingual text search and recommendation engine w

TAP: Text-Aware Pre-training for Text-VQA and Text-Caption, CVPR 2021 (Oral)
TAP: Text-Aware Pre-training for Text-VQA and Text-Caption, CVPR 2021 (Oral)

TAP: Text-Aware Pre-training TAP: Text-Aware Pre-training for Text-VQA and Text-Caption by Zhengyuan Yang, Yijuan Lu, Jianfeng Wang, Xi Yin, Dinei Flo

Pytorch re-implementation of Paper: SwinTextSpotter: Scene Text Spotting via Better Synergy between Text Detection and Text Recognition (CVPR 2022)
Pytorch re-implementation of Paper: SwinTextSpotter: Scene Text Spotting via Better Synergy between Text Detection and Text Recognition (CVPR 2022)

SwinTextSpotter This is the pytorch implementation of Paper: SwinTextSpotter: Scene Text Spotting via Better Synergy between Text Detection and Text R

A PyTorch implementation of
A PyTorch implementation of "From Two to One: A New Scene Text Recognizer with Visual Language Modeling Network" (ICCV2021)

From Two to One: A New Scene Text Recognizer with Visual Language Modeling Network The official code of VisionLAN (ICCV2021). VisionLAN successfully a

An example project demonstrating how the Autonomous Learning Library can be used to build new reinforcement learning agents.
An example project demonstrating how the Autonomous Learning Library can be used to build new reinforcement learning agents.

About This repository shows how Autonomous Learning Library can be used to build new reinforcement learning agents. In particular, it contains a model

Comments
  • Release schedule

    Release schedule

    • [x] Add source code documentation
    • [x] Improve explanation on website
    • [x] Adapt syntax highlighting in docs
    • [x] Generate samples for showcase
      • [x] Articles
      • [x] Birthday
      • [x] Horoscope
      • [x] Utterance
    • [x] Enable gh-pages
    opened by lausek 0
Releases(v0.2.3)
Owner
python + rust is all you need.
This is a repository of our model for weakly-supervised video dense anticipation.

Introduction This is a repository of our model for weakly-supervised video dense anticipation. More results on GTEA, Epic-Kitchens etc. will come soon

2 Apr 09, 2022
Network Pruning That Matters: A Case Study on Retraining Variants (ICLR 2021)

Network Pruning That Matters: A Case Study on Retraining Variants (ICLR 2021)

Duong H. Le 18 Jun 13, 2022
Tgbox-bench - Simple TGBOX upload speed benchmark

TGBOX Benchmark This script will benchmark upload speed to TGBOX storage. Build

Non 1 Jan 09, 2022
DECA: Detailed Expression Capture and Animation (SIGGRAPH 2021)

DECA: Detailed Expression Capture and Animation (SIGGRAPH2021) input image, aligned reconstruction, animation with various poses & expressions This is

Yao Feng 1.5k Jan 02, 2023
Implementation of Basic Machine Learning Algorithms on small datasets using Scikit Learn.

Basic Machine Learning Algorithms All the basic Machine Learning Algorithms are implemented in Python using libraries Acknowledgements Machine Learnin

Piyal Banik 47 Oct 16, 2022
Centroid-UNet is deep neural network model to detect centroids from satellite images.

Centroid UNet - Locating Object Centroids in Aerial/Serial Images Introduction Centroid-UNet is deep neural network model to detect centroids from Aer

GIC-AIT 19 Dec 08, 2022
Transfer-Learn is an open-source and well-documented library for Transfer Learning.

Transfer-Learn is an open-source and well-documented library for Transfer Learning. It is based on pure PyTorch with high performance and friendly API. Our code is pythonic, and the design is consist

THUML @ Tsinghua University 2.2k Jan 03, 2023
SparseML is a libraries for applying sparsification recipes to neural networks with a few lines of code, enabling faster and smaller models

SparseML is a toolkit that includes APIs, CLIs, scripts and libraries that apply state-of-the-art sparsification algorithms such as pruning and quantization to any neural network. General, recipe-dri

Neural Magic 1.5k Dec 30, 2022
DockStream: A Docking Wrapper to Enhance De Novo Molecular Design

DockStream Description DockStream is a docking wrapper providing access to a collection of ligand embedders and docking backends. Docking execution an

AstraZeneca - Molecular AI 72 Jan 02, 2023
Aquarius - Enabling Fast, Scalable, Data-Driven Virtual Network Functions

Aquarius Aquarius - Enabling Fast, Scalable, Data-Driven Virtual Network Functions NOTE: We are currently going through the open-source process requir

Zhiyuan YAO 0 Jun 02, 2022
pytorch implementation of trDesign

trdesign-pytorch This repository is a PyTorch implementation of the trDesign paper based on the official TensorFlow implementation. The initial port o

Learn Ventures Inc. 41 Dec 29, 2022
Regularized Frank-Wolfe for Dense CRFs: Generalizing Mean Field and Beyond

CRF - Conditional Random Fields A library for dense conditional random fields (CRFs). This is the official accompanying code for the paper Regularized

Đ.Khuê Lê-Huu 21 Nov 26, 2022
Implementation of "Semi-supervised Domain Adaptive Structure Learning"

Semi-supervised Domain Adaptive Structure Learning - ASDA This repo contains the source code and dataset for our ASDA paper. Illustration of the propo

3 Dec 13, 2021
Human Pose estimation with TensorFlow framework

Human Pose Estimation with TensorFlow Here you can find the implementation of the Human Body Pose Estimation algorithm, presented in the DeeperCut and

Eldar Insafutdinov 1.1k Dec 29, 2022
Deep Learning applied to Integral data analysis

DeepIntegralCompton Deep Learning applied to Integral data analysis Module installation Move to the root directory of the project and execute : pip in

Thomas Vuillaume 1 Dec 10, 2021
Unsupervised Pre-training for Person Re-identification (LUPerson)

LUPerson Unsupervised Pre-training for Person Re-identification (LUPerson). The repository is for our CVPR2021 paper Unsupervised Pre-training for Per

143 Dec 24, 2022
Platform-agnostic AI Framework 🔥

🇬🇧 TensorLayerX is a multi-backend AI framework, which can run on almost all operation systems and AI hardwares, and support hybrid-framework progra

TensorLayer Community 171 Jan 06, 2023
This is the 3D Implementation of 《Inconsistency-aware Uncertainty Estimation for Semi-supervised Medical Image Segmentation》

CoraNet This is the 3D Implementation of 《Inconsistency-aware Uncertainty Estimation for Semi-supervised Medical Image Segmentation》 Environment pytor

25 Nov 08, 2022
Dynamics-aware Adversarial Attack of 3D Sparse Convolution Network

Leaded Gradient Method (LGM) This repository contains the PyTorch implementation for paper Dynamics-aware Adversarial Attack of 3D Sparse Convolution

An Tao 2 Oct 18, 2022
Using OpenAI's CLIP to upscale and enhance images

CLIP Upscaler and Enhancer Using OpenAI's CLIP to upscale and enhance images Based on nshepperd's JAX CLIP Guided Diffusion v2.4 Sample Results Viewpo

Tripp Lyons 5 Jun 14, 2022