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A powerful and intelligent plagiarism detection system designed to uphold academic integrity and ensure the authenticity of written works. Named after Heimdallr, the all-seeing Norse god, this system possesses unparalleled vigilance and a watchful eye over the realm of academic content.

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Heimdallr

A powerful and intelligent plagiarism detection system designed to uphold academic integrity and ensure the authenticity of written works. Named after Heimdallr, the all-seeing Norse god, this system possesses unparalleled vigilance and a watchful eye over the realm of academic content.

More information Heimdallr.

Content

Key Features

  • Comprehensive Plagiarism Detection: Heimdallr scans through a vast array of sources, including web content, books, papers, photographs, and previous student works, leaving no room for undetected plagiarism.
  • Precise Location Identification: It doesn't just flag potential instances of plagiarism; Heimdallr provides pinpoint accuracy by highlighting the exact lines or words in question, enabling users to swiftly address the issue.
  • Source Attribution: The system not only detects plagiarism but also identifies the source that is being plagiarized, whether it's a website, a specific publication, or the work of another student.

Why Heimdallr?

Heimdallr stands as a guardian of academic integrity, inspired by the mythological figure known for his unwavering vigilance. With its advanced detection capabilities and user-friendly interface, Heimdallr is the ultimate solution for educational institutions, researchers, and students to maintain the highest standards of academic honesty and originality.

Environment Variables

  • Variables prefixed with FASTAPI_ are used to configure the API UI.
Name Description Default Value
FASTAPI_DEBUG Debug Mode False
FASTAPI_PROJECT_NAME Swagger Title Heimdallr
FASTAPI_PROJECT_DESCRIPTION Swagger Description ...
FASTAPI_PROJECT_LICENSE License info ...
FASTAPI_PROJECT_CONTACT Contact details ...
FASTAPI_VERSION Application Version template.version
FASTAPI_DOCS_URL Swagger Endpoint /docs
FASTAPI_MODEL_PATH Trained model path /app/models/topic_predictor.joblib
FASTAPI_DETECT_PLAGIARISM Whether to detect plagiarism or not True
FASTAPI_SIMILARITY_THRESHOLD Minimum similarity percentage 0.95
  • Variables prefixed with UVICORN_ are used to configure the server.
Name Description Default Value
UVICORN_HOST Server Host '127.0.0.1'
UVICORN_PORT Server Port 8000
UVICORN_LOG_LEVEL Log Level 'info'
UVICORN_RELOAD Enable/Disable Reload False
  • Variables prefixed with MONGO_ are used for MongoDB connection.
Name Description Default Value
MONGO_CLIENT Server Host 'mongodb://localhost:27017'
MONGO_DATABASE Server Database 'heimdallr-local'
MONGO_USER User LogIn credentials None
MONGO_PASSWORD User credentials None

Continuous Integration

This project uses make as an adaptation layer.

Run make help to see all available commands.

Quick set up

HIGHLY RECOMMENDED: Use docker-compose to run the application locally.

  1. Run:

    docker-compose up

    This will:

    • Build the application image
    • Start a MongoDB server
    • Start the application
    • Train a model for topic prediction
    • Run DB migrations

  2. Go to http://localhost:8000/docs to see the API documentation.

  3. Use the Verify Assignment POST method to verify a document. You can use the rifkin_test document as an example.

  4. See the logs for the heimdallr service to see the results. e.g:

    INFO:     Started server process [1]
INFO:     Waiting for application startup.
INFO:     Loading model from /app/models/topic_predictor_dev.joblib
INFO:     Application startup complete.![img.png](img.png)
INFO:     Uvicorn running on http://0.0.0.0:8000 (Press CTRL+C to quit)
INFO:     172.20.0.1:52912 - "POST /api/v1/assignments HTTP/1.1" 202 Accepted
INFO:     Read Assignment(id=32750af8-bdfe-4508-a37a-5aa9718a1188, author=Franco Zanette)
INFO:     Similar(0.992015) to Assignment(id=891bdd47-5ec0-40cf-ad42-9e7c99a78648, author=David Choren)
INFO:     Similar(0.994410) to Assignment(id=4bdd4797-1617-45be-8b64-bd36b97908ff, author=Levy Nazareno Isaac)
INFO:     Similar(0.991231) to Assignment(id=35cc1575-ea46-416c-95cd-260cb7efda75, author=Leon Peralta)

    NOTE: The POST method returns a 202 Accepted response. This means that the document is being verified in the background

  5. When verification is complete you should a log similar to:

    INFO:     Finished comparison with Assignment(id=4bdd4797-1617-45be-8b64-bd36b97908ff, author=Levy Nazareno Isaac) in 117.274768 seconds.
INFO:     Finished comparison with Assignment(id=35cc1575-ea46-416c-95cd-260cb7efda75, author=Leon Peralta) in 107.669727 seconds.
INFO:     Finished comparison with Assignment(id=891bdd47-5ec0-40cf-ad42-9e7c99a78648, author=David Choren) in 147.236305 seconds.
INFO:    Assignment e68d59ff-d725-4dfc-940a-b5ab449cf98c verified.

    NOTE: Verification time depends on the size of the document and the number of documents in the database. It may mate take a while.

  6. Retrieve the assignment with the GET method, with its UUID as parameter. e.g:

    {
"data": {
"id": "32750af8-bdfe-4508-a37a-5aa9718a1188",
"title": "TP5-Franco Zanette.docx.docx",
"topic": "Emerging Systems",
"author": "Franco Zanette",
"similarities": [
{
"id": "4bdd4797-1617-45be-8b64-bd36b97908ff",
"author": "Levy Nazareno Isaac",
"plagiarism": 0.19135095761849497,
"similarities": [
{
"present": "Puede describir el vínculo entre las leyes de la termodinámica de Newton y la “factura entrópica”.",
"compared": "Puede describir el vínculo entre las leyes de la termodinámica de Newton y la “factura entrópica”.",
"plagiarism": 1
},
{
"present": "Qué dice Rifkin que la “internet de las cosas IOT” le aportará a la 3ra revolución industrial?",
"compared": "Qué dice Rifkin que la “internet de las cosas IOT” le aportará a la 3ra revolución industrial?",
"plagiarism": 1
},
{
"present": "NOTA: las respuestas no deberán superar en su conjunto a 2 páginas del mismo formato que esta guía.",
"compared": "NOTA: las respuestas no deberán superar en su conjunto a 2 páginas del mismo formato que esta guía.",
"plagiarism": 1
},
{
"present": "Podría caracterizar la Primera y Segunda revolución industrial al decir de Rifkin?",
"compared": "Podría caracterizar la Primera y Segunda revolución industrial al decir de Rifkin?",
"plagiarism": 1
},
{
"present": "Qué inventos son las metáforas de cada infraestructura en cada una de esas etapas.",
"compared": "Qué inventos son las metáforas de cada infraestructura en cada una de esas etapas.",
"plagiarism": 1
},
{
"present": "Qué ejemplos actuales de “procomunes” se le ocurren?",
"compared": "Qué ejemplos actuales de “procomunes” se le ocurren?",
"plagiarism": 1
},
{
"present": "Qué límites le ve Ud. a los procomunes como forma de producción?",
"compared": "Qué límites le ve Ud. a los procomunes como forma de producción?",
"plagiarism": 1
},
{
"present": "qué estaría faltando?",
"compared": "qué estaría faltando?",
"plagiarism": 1
},
{
"present": "La principal limitación de los procomunes como forma de producción la incapacidad de la sociedad de proteger los recursos procomunes de la sobreexplotación por parte un individuo",
"compared": "El internet de las cosas permitirá unificar la comunicación, la energía y la logística posibilitando la optimización de los procesos .",
"plagiarism": 0.9502497961617389
},
{
"present": "E. intangible o “sin peso”",
"compared": "E. intangible o “sin peso”",
"plagiarism": 1
}
]
},
{
"id": "35cc1575-ea46-416c-95cd-260cb7efda75",
"author": "Leon Peralta",
"plagiarism": 0.11538461538461539,
"similarities": [
{
"present": "Qué dice Rifkin que la “internet de las cosas IOT” le aportará a la 3ra revolución industrial?",
"compared": "Qué dice Rifkin que la “internet de las cosas IOT” le aportará a la 3ra revolución industrial?",
"plagiarism": 1
},
{
"present": "Podría caracterizar la Primera y Segunda revolución industrial al decir de Rifkin?",
"compared": "Podría caracterizar la Primera y Segunda revolución industrial al decir de Rifkin?",
"plagiarism": 1
},
{
"present": "Qué inventos son las metáforas de cada infraestructura en cada una de esas etapas.",
"compared": "Qué inventos son las metáforas de cada infraestructura en cada una de esas etapas.",
"plagiarism": 1
},
{
"present": "Qué límites le ve Ud. a los procomunes como forma de producción?",
"compared": "Qué límites le ve Ud. a los procomunes como forma de producción?",
"plagiarism": 1
},
{
"present": "Qué ejemplos actuales de “procomunes” se le ocurren?",
"compared": "Qué ejemplos actuales de “procomunes” se le ocurren?",
"plagiarism": 1
},
{
"present": "qué estaría faltando?",
"compared": "qué estaría faltando?",
"plagiarism": 1
}
]
},
{
"id": "891bdd47-5ec0-40cf-ad42-9e7c99a78648",
"author": "David Choren",
"plagiarism": 0.1519146892150015,
"similarities": [
{
"present": "Las plataformas tecnológicas de la primera y segunda revolución industrial estaban centralizadas y sometidas a un control jerarquizado y su explotación estaba basada en la idea de que los recursos de la Tierra están para el servicio de la personas y el lucro..",
"compared": "Las plataformas tecnológicas de la primera  y la segunda revoluciones industriales estaban centralizadas y sometidas a un control jerarquizado.",
"plagiarism": 0.9535765262616537
},
{
"present": "3.¿Qué dice Rifkin que la “internet de las cosas IOT” le aportará a la 3ra revolución industrial?",
"compared": "Qué dice Rifkin que la “internet de las cosas IOT” le aportará a la 3ra revolución industrial?",
"plagiarism": 0.992672017325718
},
{
"present": "Qué límites le ve Ud. a los procomunes como forma de producción?",
"compared": "Qué límites le ve Ud. a los procomunes como forma de producción?",
"plagiarism": 1
},
{
"present": "NOTA: ​las respuestas no deberán superar en su conjunto a 2 páginas del mismo formato que esta guía.",
"compared": "NOTA: las respuestas no deberán superar en su conjunto a 2 páginas del mismo formato que esta guía.",
"plagiarism": 0.9813714487124504
},
{
"present": "qué estaría faltando?",
"compared": "qué estaría faltando?",
"plagiarism": 1
},
{
"present": "2.¿Podría caracterizar la Primera y Segunda revolución industrial al decir de Rifkin?",
"compared": "Podría caracterizar la Primera y Segunda revolución industrial al decir de Rifkin?",
"plagiarism": 0.989975333730042
},
{
"present": "E. intangible o “sin peso”",
"compared": "E. intangible o “sin peso”",
"plagiarism": 1
},
{
"present": "5.¿Qué ejemplos actuales de “procomunes” se le ocurren?",
"compared": "Qué ejemplos actuales de “procomunes” se le ocurren?",
"plagiarism": 0.9819685131502129
}
]
}
]
}
}

  7. To stop the application run:

    docker-compose down

Development Environment

Installing Poetry

This package uses poetry for dependency management and Python 3.10 as interpreter.

Install poetry in the system site_packages. DO NOT INSTALL IT in a virtual environment itself.

To install poetry, run:

pip install poetry

Building the Development Environment

  1. Clone the repository

    git clone "[email protected]:tomasanchez/heimdallr.git"

  2. Install dependencies

    cd cosmic-fastapi && poetry install

    Note that poetry doesn't activate the virtual environment for you. You have to do it manually. Or prefix subsequent the commands with

    poetry run

    You can view the environment that poetry uses with

    poetry env info

    To activate run:

    poetry shell

  3. Download spaCy trained Spanish Model

    poetry run python -m spacy download es_core_news_lg

  4. Train model for topic prediction (Optional)

    • Run script
     poetry run python -m heimdallr.train
    • Update FASTAPI_MODEL_PATH environment variable with the new model path 
      export FASTAPI_MODEL_PATH=/path/to/new/model

  5. Activate pre-commit hooks (Optional)

    Using pre-commit to run some checks before committing is highly recommended.

    To activate the pre-commit hooks run:

    pre-commit install

    To run the checks manually run:

    poetry run pre-commit run --all-files

    The following checks are run: black, flake8, isort, mypy, pylint.

Running Local

  1. Either:

    poetry run python -m heimdallr.main

    NOTE: AMongoDB server running to verify documents. docker-compose.yml contains a service configured for that.

  2. Go to http://localhost:8000/docs to see the API documentation.

MSWord Document Support

For supporting .doc files you must have antiword installed. Otherwise, the API will not verify .doc files, but It will still work for .pdf and

If using Ubuntu, run:

sudo apt-get update -y && sudo apt-get install -y antiword

If using Mac OSX, run:

brew install antiword

Using Docker (Recommended)

Run the application in docker. Requires no further configuration.

  1. Run: 
    docker-compose up
  2. Go to http://localhost:8000/docs to see the API documentation.

Running Tests

You can run the tests with:

poetry run pytest

or with the make command:

make test

To generate a coverage report add --cov src.

poetry run pytest --cov src

Or with the make command:

make cover

Updating Dependencies

To update the dependencies run:

poetry update

What's missing?

  • Performance improvements:
    • Maybe filter documents by topic. Right now, all documents are being compared.
    • There is a lot to improve about processing speed. A possible solution is to use a Celery task queue to process documents in the background, as using spaCy is CPU intensive.
    • Better response management. Right now, if a document is being processed, the API will return a 202 Accepted response, but it is impossible to know any errors that may occur during processing. It's only possible to know when the process is finished by checking the logs. Or if by retrieving its ID it doesn't return a 404 Not Found.
  • Interesting Topics: their definition was more related to what were the assignment requirements.
  • Internet scrapping: It was not implemented due to time constraints. It would be a great addition to the system. Also, it would relative easy to implement: an Adapter capable of scrapping the web and returning an Assignment will do the job.
  • Batch Processing
  • Title Identification: Only file names are used to identify documents. More NLP domain knowledge is needed to identify titles.
  • Better Author recognition: Right now is using the first identified name. Some documents don't include authors name, others aren't their name first mentioned. Sometimes another token is wrongly recognized as a PER token.
  • Requirements Identification: Requirements are being considered as plagiarism. A better approach would be to identify them and exclude them from the comparison like for each topic have a list of requirements and exclude them.

Recommended Readings

License

This project is licensed under the terms of the MIT license unless otherwise specified. See LICENSE for more details or visit https://mit-license.org/.

Acknowledgements

This project was designed and developed by Tomás Sánchez <[email protected]>.

If you find this project useful, please consider supporting its development by sponsoring it.

About

A powerful and intelligent plagiarism detection system designed to uphold academic integrity and ensure the authenticity of written works. Named after Heimdallr, the all-seeing Norse god, this system possesses unparalleled vigilance and a watchful eye over the realm of academic content.

Topics

python nlp ml utn spacy nltk plagiarism-detection utn-frba fastapi

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v1.1.1 Latest
Nov 10, 2023
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