{"id":20433359,"url":"https://github.com/jpcadena/autochain-bot","last_synced_at":"2026-04-11T06:43:54.595Z","repository":{"id":187340335,"uuid":"676662828","full_name":"jpcadena/autochain-bot","owner":"jpcadena","description":"This project is dedicated to building an intelligent data processing pipeline using AutoChain LLM and BERT 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autochain-bot\n\n\u003c!-- Improved compatibility of back to top link: See: https://github.com/othneildrew/Best-README-Template/pull/73 --\u003e\n\u003ca name=\"readme-top\"\u003e\u003c/a\u003e\n\n\u003c!-- PROJECT SHIELDS --\u003e\n\u003c!--\n*** Markdown \"reference style\" links for readability.\n*** Reference links are enclosed in brackets [ ] instead of parentheses ( ).\n--\u003e\n\n\n\u003c!-- PROJECT LOGO --\u003e\n\u003cbr /\u003e\n\u003cdiv align=\"center\"\u003e\n  \u003ca href=\"https://github.com/othneildrew/Best-README-Template\"\u003e\n    \u003cimg src=\"assets/static/images/logo.png\" alt=\"Logo\" width=\"80\" height=\"80\"\u003e\n  \u003c/a\u003e\n\n\u003ch3 align=\"center\"\u003eAutochain bot\u003c/h3\u003e\n\n  \u003cp align=\"center\"\u003e\n    Autochain bot\n    \u003cbr /\u003e\n    \u003ca href=\"https://github.com/jpcadena/autochain-bot\"\u003e\u003cstrong\u003eExplore the docs »\u003c/strong\u003e\u003c/a\u003e\n    \u003cbr /\u003e\n  \u003c/p\u003e\n\u003c/div\u003e\n\n\n\u003c!-- TABLE OF CONTENTS --\u003e\n\u003cdetails\u003e\n  \u003csummary\u003eTable of Contents\u003c/summary\u003e\n  \u003col\u003e\n    \u003cli\u003e\n      \u003ca href=\"#about-the-project\"\u003eAbout The Project\u003c/a\u003e\n      \u003cul\u003e\n        \u003cli\u003e\u003ca href=\"#built-with\"\u003eBuilt With\u003c/a\u003e\u003c/li\u003e\n      \u003c/ul\u003e\n    \u003c/li\u003e\n    \u003cli\u003e\n      \u003ca href=\"#getting-started\"\u003eGetting Started\u003c/a\u003e\n      \u003cul\u003e\n        \u003cli\u003e\u003ca href=\"#prerequisites\"\u003ePrerequisites\u003c/a\u003e\u003c/li\u003e\n        \u003cli\u003e\u003ca href=\"#installation\"\u003eInstallation\u003c/a\u003e\u003c/li\u003e\n      \u003c/ul\u003e\n    \u003c/li\u003e\n    \u003cli\u003e\u003ca href=\"#usage\"\u003eUsage\u003c/a\u003e\u003c/li\u003e\n    \u003cli\u003e\u003ca href=\"#testing\"\u003eTesting\u003c/a\u003e\u003c/li\u003e\n    \u003cli\u003e\u003ca href=\"#contributing\"\u003eContributing\u003c/a\u003e\u003c/li\u003e\n    \u003cli\u003e\u003ca href=\"#security\"\u003eSecurity\u003c/a\u003e\u003c/li\u003e\n    \u003cli\u003e\u003ca href=\"#code-of-conduct\"\u003eCode of Conduct\u003c/a\u003e\u003c/li\u003e\n    \u003cli\u003e\u003ca href=\"#license\"\u003eLicense\u003c/a\u003e\u003c/li\u003e\n    \u003cli\u003e\u003ca href=\"#contact\"\u003eContact\u003c/a\u003e\u003c/li\u003e\n  \u003c/ol\u003e\n\u003c/details\u003e\n\n\n\n\u003c!-- ABOUT THE PROJECT --\u003e\n\n## About The Project\n\n![Project][project-screenshot]\n\nThis project is dedicated to building an intelligent data processing pipeline,\nintegrating state-of-the-art machine learning models like BERT and AutoChain.\nThe pipeline encompasses various stages including data preparation, engineering,\nanalysis, and configuration of AutoChain, forming a comprehensive and robust\ndata analytics solution.\n\nThe project involves several key phases:\n\nData Preparation: Extracting and loading the raw data, followed by cleaning, and\npreprocessing.\nData Engineering: Features are extracted and transformed for better insights and\nmodel compatibility.\nData Analysis: Including both numerical analysis and visual analytics for\nin-depth data understanding.\nFeature Engineering: Selecting and crafting the best attributes that will\nenhance the modeling.\nModel Integration: Utilizing the BERT model for sequence processing and\nAutoChain for automating the machine learning pipeline.\nThe implemented system facilitates both exploratory data analysis (EDA) and\npredictive modeling, aligning with clean code principles, design patterns, and\nSOLID principles. Its modular architecture enables easy scalability and\nmaintainability.\n\nDesigned for efficiency and reliability, this project combines cutting-edge\ntechnologies and best practices to provide a powerful tool for data scientists,\nanalysts, and organizations seeking to derive actionable insights from complex\ndata sets. Its multifaceted nature makes it adaptable to various domains and\ndata types, showcasing the versatility and innovation at the heart of the\nsolution\n\n\u003cp align=\"right\"\u003e(\u003ca href=\"#readme-top\"\u003eback to top\u003c/a\u003e)\u003c/p\u003e\n\n### Built with\n\n[![Python][python-shield]][python-url] [![Pandas][pandas-shield]][pandas-url] [![OpenAI][openai-shield]][openai-url] [![Hugging Face Transformers][transformers-shield]][transformers-url] [![PyTorch][pytorch-shield]][pytorch-url] [![numpy][numpy-shield]][numpy-url] [![scikit-learn][scikit-learn-shield]][scikit-learn-url] [![Pydantic][pydantic-shield]][pydantic-url] [![Pytest][pytest-shield]][pytest-url] [![isort][isort-shield]][isort-url] [![Black][black-shield]][black-url] [![Ruff][ruff-shield]][ruff-url] [![MyPy][mypy-shield]][mypy-url][![pre-commit][pre-commit-shield]][pre-commit-url] [![GitHub Actions][github-actions-shield]][github-actions-url] [![Pycharm][pycharm-shield]][pycharm-url] [![Visual Studio Code][visual-studio-code-shield]][visual-studio-code-url] [![Markdown][markdown-shield]][markdown-url] [![License: MIT][license-shield]][license-url]\n\n\n\u003cp align=\"right\"\u003e(\u003ca href=\"#readme-top\"\u003eback to top\u003c/a\u003e)\u003c/p\u003e\n\n\n\u003c!-- GETTING STARTED --\u003e\n\n## Getting started\n\n### Prerequisites\n\n* [Python 3.11][python-url]\n\n### Installation\n\n1. Clone the **repository**\n    ```\n    git clone https://github.com/jpcadena/autochain-bot.git\n    ```\n2. Change the directory to **root project**\n    ```\n    cd autochain-bot\n    ```\n3. Create a **virtual environment** *venv*\n    ```\n    python3 -m venv venv\n    ```\n4. Activate **environment** in Windows\n    ```\n    .\\venv\\Scripts\\activate\n    ```\n5. Install requirements with PIP\n    ```\n    pip install -r requirements.txt\n    pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118\n    ```\n\n\u003cp align=\"right\"\u003e(\u003ca href=\"#readme-top\"\u003eback to top\u003c/a\u003e)\u003c/p\u003e\n\n\n\n\u003c!-- USAGE EXAMPLES --\u003e\n\n## Usage\n\n1. **Setting up environment variables:**\n\n   If you find a `.env.sample` in the project directory, make a copy of it and\n   rename to `.env`.\n\n   ```\n   cp .env.sample .env\n   ```\n\n   This `.env` file will be used to manage your application's environment\n   variables.\n\n2. **Configuring your credentials:**\n\n   Open the `.env` file in a text editor and replace the placeholder values with\n   your actual credentials.\n\n   ```\n   # .env file\n   POSTGRES_USER=your_database_user\n   SECRET_KEY=your_api_key\n   ```\n\n   Be sure to save the file after making these changes.\n\n3. **Executing the main script:**\n\n   To start the local project on your machine, run the following command in\n   your terminal:\n\n   ```\n   python main.py\n   ```\n\n\u003cp align=\"right\"\u003e(\u003ca href=\"#readme-top\"\u003eback to top\u003c/a\u003e)\u003c/p\u003e\n\n\n\u003c!-- TESTING --\u003e\n\n## Testing\n\n1. **Running tests:**\n\n   To run all tests, you can simply run the following command in the root\n   directory of the project:\n\n   ```\n   pytest\n   ```\n\n2. **Running a specific test:**\n\n   If you want to run a specific test, you can do so by specifying the file and\n   test name. For example, the following command will only run\n   the `test_get_users` test in the `test_main.py` file:\n\n   ```\n   pytest tests/test_main.py::test_get_users\n   ```\n\n3. **Understanding test results:**\n\n   Pytest will provide a summary of the test results in the console. It will\n   tell you how many tests passed and how many failed. For each failed test,\n   Pytest will provide a detailed error message that can help you identify what\n   went wrong.\n\n4. **Writing new tests:**\n\n   When you add new features to the application, you should also write\n   corresponding test cases. Each test case should be a function that starts\n   with the word 'test'. Inside the function, you can use `assert` statements to\n   check that your code is working as expected. For example:\n\n   ```python\n   def test_add_user():\n       user = add_user(\"testuser\", \"testpass\")\n       assert user.name == \"testuser\"\n       assert user.password == \"testpass\"\n   ```\n\n   This function tests that the `add_user` function correctly creates a new user\n   with the given name and password.\n\nRemember to update your tests whenever you update your code. Maintaining a\ncomprehensive test suite will help ensure the reliability and robustness of your\napplication.\n\n\u003cp align=\"right\"\u003e(\u003ca href=\"#readme-top\"\u003eback to top\u003c/a\u003e)\u003c/p\u003e\n\n\n\u003c!-- CONTRIBUTING --\u003e\n\n## Contributing\n\n[![GitHub][github-shield]][github-url]\n\nPlease read our [contributing guide](CONTRIBUTING.md) for details on our code of\nconduct, and the process for submitting pull requests to us.\n\n\u003cp align=\"right\"\u003e(\u003ca href=\"#readme-top\"\u003eback to top\u003c/a\u003e)\u003c/p\u003e\n\n## Security\n\nFor security considerations and best practices, please refer to\nour [Security Guide](SECURITY.md) for a detailed guide.\n\n\u003cp align=\"right\"\u003e(\u003ca href=\"#readme-top\"\u003eback to top\u003c/a\u003e)\u003c/p\u003e\n\n\n\u003c!-- CODE_OF_CONDUCT --\u003e\n\n## Code of Conduct\n\nWe enforce a code of conduct for all maintainers and contributors. Please read\nour [Code of Conduct](CODE_OF_CONDUCT.md) to understand the expectations before\nmaking any contributions.\n\n\u003cp align=\"right\"\u003e(\u003ca href=\"#readme-top\"\u003eback to top\u003c/a\u003e)\u003c/p\u003e\n\n\n\u003c!-- LICENSE --\u003e\n\n## License\n\nDistributed under the MIT License. See [LICENSE](LICENSE) for more information.\n\n\u003cp align=\"right\"\u003e(\u003ca href=\"#readme-top\"\u003eback to top\u003c/a\u003e)\u003c/p\u003e\n\n\n\u003c!-- CONTACT --\u003e\n\n## Contact\n\n- [![LinkedIn][linkedin-shield]][linkedin-url]\n\n- [![Outlook][outlook-shield]](mailto:jpcadena@espol.edu.ec?subject=[GitHub]autochain-bot)\n\n\u003cp align=\"right\"\u003e(\u003ca href=\"#readme-top\"\u003eback to top\u003c/a\u003e)\u003c/p\u003e\n\n\n\n\u003c!-- MARKDOWN LINKS \u0026 IMAGES --\u003e\n\u003c!-- https://www.markdownguide.org/basic-syntax/#reference-style-links --\u003e\n\n[project-screenshot]: assets/static/images/project.png\n\n[//]: # \"Shields\"\n\n[linkedin-shield]: https://img.shields.io/badge/linkedin-%230077B5.svg?style=for-the-badge\u0026logo=linkedin\u0026logoColor=white\n\n[outlook-shield]: https://img.shields.io/badge/Microsoft_Outlook-0078D4?style=for-the-badge\u0026logo=microsoft-outlook\u0026logoColor=white\n\n[python-shield]: https://img.shields.io/badge/python-3670A0?style=for-the-badge\u0026logo=python\u0026logoColor=ffdd54\n\n[pydantic-shield]: https://img.shields.io/badge/Pydantic-FF43A1?style=for-the-badge\u0026logo=pydantic\u0026logoColor=white\n\n[pycharm-shield]: https://img.shields.io/badge/PyCharm-21D789?style=for-the-badge\u0026logo=pycharm\u0026logoColor=white\n\n[markdown-shield]: https://img.shields.io/badge/Markdown-000000?style=for-the-badge\u0026logo=markdown\u0026logoColor=white\n\n[github-shield]: https://img.shields.io/badge/github-%23121011.svg?style=for-the-badge\u0026logo=github\u0026logoColor=white\n\n[ruff-shield]: https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/charliermarsh/ruff/main/assets/badge/v1.json\n\n[black-shield]: https://img.shields.io/badge/code%20style-black-000000.svg?style=for-the-badge\u0026logo=appveyor\n\n[mypy-shield]: https://img.shields.io/badge/mypy-checked-2A6DB2.svg?style=for-the-badge\u0026logo=appveyor\n\n[pytest-shield]: https://img.shields.io/badge/Pytest-0A9EDC?style=for-the-badge\u0026logo=pytest\u0026logoColor=white\n\n[visual-studio-code-shield]: https://img.shields.io/badge/Visual_Studio_Code-007ACC?style=for-the-badge\u0026logo=visual-studio-code\u0026logoColor=white\n\n[poetry-shield]: https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/python-poetry/website/main/static/badge/v0.json\n\n[isort-shield]: https://img.shields.io/badge/%20imports-isort-%231674b1?style=flat\u0026labelColor=ef8336\n\n[github-actions-shield]: https://img.shields.io/badge/github%20actions-%232671E5.svg?style=for-the-badge\u0026logo=githubactions\u0026logoColor=white\n\n[pre-commit-shield]: https://img.shields.io/badge/pre--commit-F7B93E?style=for-the-badge\u0026logo=pre-commit\u0026logoColor=white\n\n[license-shield]: https://img.shields.io/badge/License-MIT-yellow.svg\n\n[pandas-shield]: https://img.shields.io/badge/pandas-%23150458.svg?style=for-the-badge\u0026logo=pandas\u0026logoColor=white\n\n[numpy-shield]: https://img.shields.io/badge/numpy-%23013243.svg?style=for-the-badge\u0026logo=numpy\u0026logoColor=white\n\n[scikit-Learn-shield]: https://img.shields.io/badge/scikit--learn-%23F7931E.svg?style=for-the-badge\u0026logo=scikit-learn\u0026logoColor=white\n\n[openai-shield]: https://img.shields.io/badge/OpenAI-ChatGPT-blue\n\n[transformers-shield]: https://img.shields.io/badge/Hugging%20Face-Transformers-brightgreen\n\n[pytorch-shield]: https://img.shields.io/badge/PyTorch-red\n\n[//]: # \"URL\"\n\n[linkedin-url]: https://linkedin.com/in/juanpablocadenaaguilar\n\n[python-url]: https://docs.python.org/3.11/\n\n[python-url]: https://www.python.org/\n\n[pydantic-url]: https://docs.pydantic.dev\n\n[pycharm-url]: https://www.jetbrains.com/pycharm/\n\n[markdown-url]: https://daringfireball.net/projects/markdown/\n\n[github-url]: https://github.com/jpcadena/autochain-bot\n\n[ruff-url]: https://beta.ruff.rs/docs/\n\n[black-url]: https://github.com/psf/black\n\n[mypy-url]: http://mypy-lang.org/\n\n[pytest-url]: https://docs.pytest.org/en/7.2.x/\n\n[visual-studio-code-url]: https://code.visualstudio.com/\n\n[poetry-url]: https://python-poetry.org/\n\n[isort-url]: https://pycqa.github.io/isort/\n\n[github-actions-url]: https://github.com/features/actions\n\n[pre-commit-url]: https://pre-commit.com/\n\n[license-url]: https://opensource.org/licenses/MIT\n\n[pandas-url]: https://pandas.pydata.org/docs/\n\n[numpy-url]: https://numpy.org/\n\n[scikit-learn-url]: https://scikit-learn.org/stable/\n\n[openai-url]: https://www.openai.com/\n\n[transformers-url]: https://huggingface.co/transformers/\n\n[pytorch-url]: https://pytorch.org/\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjpcadena%2Fautochain-bot","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjpcadena%2Fautochain-bot","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjpcadena%2Fautochain-bot/lists"}