Search Git commits in natural language

Overview

NaLCoS - NAtural Language COmmit Search

Search commit messages in your repository in natural language.

GitHub Issues Stargazers License Code style: black
GitHub release (latest by date) PyPi
All contributors


NaLCoS (NAtural Language COmmit Search) is a command-line tool for searching commit messages in your repository in natural language.

The key features are:

  • Search commit messages in both local and remote GitHub repositories.
  • Search for commits in a specific branch.
  • Restrict the number of commits to look back in history while searching.
  • Increase the number of retrieved results.

image

Internally, NaLCoS uses Sentence Transformers with pre-trained weights from multi-qa-MiniLM-L6-cos-v1. I chose this particular model because it has a good Performance vs Speed tradeoff. Since this model was designed for semantic search and has been pre-trained on 215M (question, answer) pairs from diverse sources, it is a good choice for tasks such as finding similarity between two sentences.

NaLCoS encodes the query string and all the commits into their corresponding vector embeddings and computes the cosine similarity between the query and all the commits. This is then used to rank the commits.

Why did I build this?

Most of the times when I've used Machine Learning till now, has been in dedicated environments such as Google Colab or Kaggle. I had been learning Natural Language Processing for a while and wanted to use transformers to build something different that is not very resource (read GPU) intensive and can be used like an everyday tool.

Though many Transformer models are far from fitting this description, I found that distilled models are not as hungry as their older siblings are infamous for. Searching for Git commits using natural language was something on which I could not find any pre-existing tool and thus decided to give this a shot.

Though there are various improvements left, I'm happy with what this initially turned out to be. I'm eager to see what further enhancements can be made to this to make it more efficient and useful.

Requirements

NaLCoS uses the following packages:

Installation

Installing with pip (Recommended)

Install with pip or your favourite PyPi manager:

$ pip install nalcos

Run NaLCoS with the --help flag to see all the available options:

$ nalcos --help

Note: When you run the nalcos command for the first time, it will, download the model which would be cached and used the next time you run NaLCoS.

Installing bleeding edge from the GitHub repository

  • Clone the repository:
$ git clone https://github.com/thepushkarp/nalcos.git

This also downloads the model weights stored in the nalcos/models directory so you don't have to download them while running the model for the first time.

  • Create a virtual environment (click here to read about activating virtualenv):
$ virtualenv venv
  • Activate virtualenv (for Linux and MacOS):
  $ source ./venv/bin/activate
  • Activate virtualenv (for Windows):
   $ cd venv/Scripts/
   $ activate
  • Install the requirements:
$ pip install -r requirements.txt
  • Change directory to the nalcos directory:
$ cd nalcos/
  • Run NaLCoS with the --help flag to see all the available options:
$ python nalcos.py --help

Usage

A detailed information about the usage of NaLCoS can be found below:

usage: nalcos [-h] [-g] [-n N_MATCHES] [-b BRANCH] [-l LOOK_PAST] [-v] query location

Search a commit in your git repository using natural language.

positional arguments:
  query                 The query to search for similar commit messages.
  location              The repository path to search in. If `-g` flag is not passed, searches locally in the path specified, else
                        takes in a remote GitHub repository name in the format '{owner}/{repo_name}'

optional arguments:
  -h, --help            show this help message and exit
  -g, --github          Flag to search on GitHub instead of searching in a local repository. Due to API limits currently this
                        allows for around 15 lookups per hour from your IP.
  -n N_MATCHES, --n-matches N_MATCHES
                        The number of matching results to return. Default 10.
  -b BRANCH, --branch BRANCH
                        The branch to search in. If not specified, the current branch will be used by default.
  -l LOOK_PAST, --look-past LOOK_PAST
                        Look back this many commits. Default 100.
  -v, --version         show program's version number and exit

Examples

  • Input:
$ python nalcos.py "improve language" "github/docs" --github
  • Output:
Found 100 commits.

                                        Commits related to "improve language" in "github/docs"
┏━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━┓
┃ No. ┃ Commit ID ┃ Commit Message                                                        ┃ Commit Author      ┃ Commit Date          ┃
┡━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━┩
│  1. │ 51bfdbb95 │ Merge branch 'main' into fatenhealy-fix-supportedlanguage             │ Faten Healy        │ 2021-09-12T22:26:31Z │
│  2. │ a9c2c8eea │ fix deprecation label spelling (#21474)                               │ Rachael Sewell     │ 2021-09-13T18:12:03Z │
│  3. │ 94e3c092d │ English search sync (#21446)                                          │ Rachael Sewell     │ 2021-09-13T17:30:08Z │
│  4. │ b048e27e9 │ Merge pull request #9909 from github/fatenhealy-fix-supportedlanguage │ Ramya Parimi       │ 2021-09-12T22:35:19Z │
│  5. │ 73c2717f7 │ Fix typo                                                              │ Adrian Mato        │ 2021-09-13T06:35:27Z │
│  6. │ 86b571982 │ Export changes to a branch for codespaces (#21462)                    │ Matthew Isabel     │ 2021-09-13T14:55:50Z │
│  7. │ 969288662 │ Update diff limit to 500KB (#20616)                                   │ jjkennedy3         │ 2021-09-11T09:12:38Z │
│  8. │ f28ee46d4 │ Update OpenAPI Descriptions (#21447)                                  │ github-openapi-bot │ 2021-09-11T09:22:28Z │
│  9. │ 92af3a469 │ update search indexes                                                 │ GitHub Actions     │ 2021-09-12T09:50:46Z │
│ 10. │ e6018f2aa │ update search indexes                                                 │ GitHub Actions     │ 2021-09-11T02:05:19Z │
└─────┴───────────┴───────────────────────────────────────────────────────────────────────┴────────────────────┴──────────────────────┘

Future plans

Please visit the NaLCoS To Do Project Board to see current status and future plans.

Known issues

Not all retrieved results are always relevant. I could think of two primary reasons for this:

  • The data the model was pre-trained on is not representative of how people write commit messages. Since commit messages usually contain technical jargon, merge commit messages, abbreviations and other non-common terms, the model (which has a limited vocabulary) is not able to generalize well to this data.
  • Two commits may be related even when their commit messages may not be similar and similarly two commit messages maybe unrelated even when their commit messages are similar. We often need more metadata (such as lines changes, files changed) etc. to make the predictions more accurate.

Contributing

Any suggestions, improvements or bug reports are welcome.

Contributors

Thanks goes to these wonderful people (emoji key):


Pushkar Patel

💻 📖 🚧

This project follows the all-contributors specification. Contributions of any kind welcome!

License

This project is licensed under the terms of the MIT license.

Comments
  • Patches

    Patches

    • :truck: Renames .cache directory to models and add Project Board link in README
    • Adds version.py
    • Adds contributing section in README
    • :lipstick: Add black code style
    • Adds back torch cuda support
    • :zap: Improve similarity computation
    • :tada: Upload to PyPi
    opened by thepushkarp 3
  • Version 0.2: Visual changes

    Version 0.2: Visual changes

    • Fix status message typo
    • :sparkles: Adds a flag to show similarity scores of the result
    • :sparkles: Adds an flag to display the entire commit message
    • Module error fixes
    • :sparkles: Adds commit links for results from GitHub
    • :art: Improve download prograss bar display when loading for first time
    • :bookmark: Bump version to 0.2
    opened by thepushkarp 1
  • Add a flag to download the model

    Add a flag to download the model

    Currently, if the model is not downloaded, the program downloads it during the first run, in the middle of the "Retrieving the commits ..." status mesage.

    This can be improved by adding a flag through which the user can download/redownload the model when they need it.

    Additionally, the program should prompt the user when it is run without downloading the weights with a choice to download it now or to abort the program.

    opened by thepushkarp 1
  • Use a Python Wrapper to the GitHub API

    Use a Python Wrapper to the GitHub API

    We can use some Python Wrapper of the GitHub API such as ghapi or PyGitHub instead of using the requests library.

    Additional Reference: https://docs.github.com/en/rest/overview/libraries#python

    This can help with #11

    opened by thepushkarp 1
  • Visual improvements

    Visual improvements

    • :sparkles: Adds a flag to show similarity scores of the result
    • :sparkles: Adds an flag to display the entire commit message
    • Module error fixes
    • :sparkles: Adds commit links for results from GitHub
    opened by thepushkarp 0
  • Add Automated Testing

    Add Automated Testing

    AUtomate the testing of the module (preferably with GitHub Actions for CI).

    NOTE: Considering the large installation size and time of the Torch and HuggingFace modules, the resources allocated may go over the GH Actions limit. This is something we have to take care of.

    Follow up of #13

    opened by thepushkarp 0
  • Adds README and some bug fixes

    Adds README and some bug fixes

    • Adds API limit exceeded warnning
    • :zap: Reverts back to using whole commit msg for serarch; displays only title
    • :memo: Add README
    • :zap: Reduces default value of look_past from 1000 to 100
    • :bug: Retrieves all branch names for GitHub repos and add branch not found Exception
    opened by thepushkarp 0
  • Try out other models.

    Try out other models.

    Currently, we are using multi-qa-MiniLM-L6-cos-v1, which has a speed (sentences encoded/sec on 1 V100 GPU) of 14200 and a model size of 80 MB. We should try out other models to see if we can get better performance and speed out of them.

    Additionally, we can also try using other types of tokenizers.

    Further reading:

    • https://www.sbert.net/docs/pretrained_models.html
    • https://huggingface.co/sentence-transformers
    • https://huggingface.co/transformers/tokenizer_summary.html
    help wanted 
    opened by thepushkarp 0
  • Add personal API token support

    Add personal API token support

    Do #28 before this

    Currently, the project is using an unauthenticated GH API which is capped to 60 requests per hour from an IP address.

    We can add the option to add a user's personal API access token to increase this limit.

    enhancement 
    opened by thepushkarp 0
Releases(v0.2)
  • v0.2(Sep 18, 2021)

    Changelog

    • Adds an option of showing the similarity score for the results using the -s flag.
    • Adds option of viewing the entire commit message instead of just the commit title using the -v flag.
    • Commits in results retrieved from GitHub have links to the commits
    • Improved the model download progress bar display when loading model for the first time
    Source code(tar.gz)
    Source code(zip)
  • v0.1.1(Sep 14, 2021)

    Changelog

    • Make similarity computation more efficient
    • Add support for computation on CUDA
    • Add Black Code style in requirements
    • Published to PyPi at https://pypi.org/project/nalcos/ 🥳
    Source code(tar.gz)
    Source code(zip)
  • v0.1(Sep 13, 2021)

    Features ✨

    • Search commit messages in both local and remote GitHub repositories.
    • Search for commits in a specific branch.
    • Restrict the number of commits to look back in history while searching.
    • Increase the number of retrieved results.
    Source code(tar.gz)
    Source code(zip)
Owner
Pushkar Patel
Research Intern at SPIRE Labs, IISC Bangalore | GitHub Campus Expert @iiitv
Pushkar Patel
The Internet Archive Research Assistant - Daily search Internet Archive for new items matching your keywords

The Internet Archive Research Assistant - Daily search Internet Archive for new items matching your keywords

Kay Savetz 60 Dec 25, 2022
Natural language processing summarizer using 3 state of the art Transformer models: BERT, GPT2, and T5

NLP-Summarizer Natural language processing summarizer using 3 state of the art Transformer models: BERT, GPT2, and T5 This project aimed to provide in

Samuel Sharkey 1 Feb 07, 2022
Idea is to build a model which will take keywords as inputs and generate sentences as outputs.

keytotext Idea is to build a model which will take keywords as inputs and generate sentences as outputs. Potential use case can include: Marketing Sea

Gagan Bhatia 364 Jan 03, 2023
Disfl-QA: A Benchmark Dataset for Understanding Disfluencies in Question Answering

Disfl-QA is a targeted dataset for contextual disfluencies in an information seeking setting, namely question answering over Wikipedia passages. Disfl-QA builds upon the SQuAD-v2 (Rajpurkar et al., 2

Google Research Datasets 52 Jun 21, 2022
📜 GPT-2 Rhyming Limerick and Haiku models using data augmentation

Well-formed Limericks and Haikus with GPT2 📜 GPT-2 Rhyming Limerick and Haiku models using data augmentation In collaboration with Matthew Korahais &

Bardia Shahrestani 2 May 26, 2022
QVHighlights: Detecting Moments and Highlights in Videos via Natural Language Queries

Moment-DETR QVHighlights: Detecting Moments and Highlights in Videos via Natural Language Queries Jie Lei, Tamara L. Berg, Mohit Bansal For dataset de

Jie Lei 雷杰 133 Dec 22, 2022
Crowd sourced training data for Rasa NLU models

NLU Training Data Crowd-sourced training data for the development and testing of Rasa NLU models. If you're interested in grabbing some data feel free

Rasa 169 Dec 26, 2022
Implementation of Multistream Transformers in Pytorch

Multistream Transformers Implementation of Multistream Transformers in Pytorch. This repository deviates slightly from the paper, where instead of usi

Phil Wang 47 Jul 26, 2022
Resources for "Natural Language Processing" Coursera course.

Natural Language Processing course resources This github contains practical assignments for Natural Language Processing course by Higher School of Eco

Advanced Machine Learning specialisation by HSE 1.1k Jan 01, 2023
A minimal code for fairseq vq-wav2vec model inference.

vq-wav2vec inference A minimal code for fairseq vq-wav2vec model inference. Runs without installing the fairseq toolkit and its dependencies. Usage ex

Vladimir Larin 7 Nov 15, 2022
Addon for adding subtitle files to blender VSE as Text sequences. Using pysub2 python module.

Import Subtitles for Blender VSE Addon for adding subtitle files to blender VSE as Text sequences. Using pysub2 python module. Supported formats by py

4 Feb 27, 2022
Code for EMNLP20 paper: "ProphetNet: Predicting Future N-gram for Sequence-to-Sequence Pre-training"

ProphetNet-X This repo provides the code for reproducing the experiments in ProphetNet. In the paper, we propose a new pre-trained language model call

Microsoft 394 Dec 17, 2022
Code for our paper "Mask-Align: Self-Supervised Neural Word Alignment" in ACL 2021

Mask-Align: Self-Supervised Neural Word Alignment This is the implementation of our work Mask-Align: Self-Supervised Neural Word Alignment. @inproceed

THUNLP-MT 46 Dec 15, 2022
DensePhrases provides answers to your natural language questions from the entire Wikipedia in real-time

DensePhrases provides answers to your natural language questions from the entire Wikipedia in real-time. While it efficiently searches the answers out of 60 billion phrases in Wikipedia, it is also v

Jinhyuk Lee 543 Jan 08, 2023
PyTorch implementation of "data2vec: A General Framework for Self-supervised Learning in Speech, Vision and Language" from Meta AI

data2vec-pytorch PyTorch implementation of "data2vec: A General Framework for Self-supervised Learning in Speech, Vision and Language" from Meta AI (F

Aryan Shekarlaban 105 Jan 04, 2023
Code for papers "Generation-Augmented Retrieval for Open-Domain Question Answering" and "Reader-Guided Passage Reranking for Open-Domain Question Answering", ACL 2021

This repo provides the code of the following papers: (GAR) "Generation-Augmented Retrieval for Open-domain Question Answering", ACL 2021 (RIDER) "Read

morning 49 Dec 26, 2022
SimBERT升级版(SimBERTv2)!

RoFormer-Sim RoFormer-Sim,又称SimBERTv2,是我们之前发布的SimBERT模型的升级版。 介绍 https://kexue.fm/archives/8454 训练 tensorflow 1.14 + keras 2.3.1 + bert4keras 0.10.6 下载

317 Dec 23, 2022
In this Notebook I've build some machine-learning and deep-learning to classify corona virus tweets, in both multi class classification and binary classification.

Hello, This Notebook Contains Example of Corona Virus Tweets Multi Class Classification. - Classes is: Extremely Positive, Positive, Extremely Negativ

Khaled Tofailieh 3 Dec 06, 2022
DaCy: The State of the Art Danish NLP pipeline using SpaCy

DaCy: A SpaCy NLP Pipeline for Danish DaCy is a Danish preprocessing pipeline trained in SpaCy. At the time of writing it has achieved State-of-the-Ar

Kenneth Enevoldsen 71 Jan 06, 2023
This repository contains examples of Task-Informed Meta-Learning

Task-Informed Meta-Learning This repository contains examples of Task-Informed Meta-Learning (paper). We consider two tasks: Crop Type Classification

10 Dec 19, 2022