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The "Medicine Recommendation System" is designed to provide suggestions for alternative or substitute medications based on a search query, with the primary goal of offering viable replacements for the specified medicine.

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anurag-b72/medicine-recommendation-system

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Medicine-Recommendation-System 💊

medicine-image

This recommendation system is supposed to recommend any medicine/drug on the basis of the search result. The main aim is to recommend any alternative/substitute to be used in place of the searched medicine.

Steps to Open Localhost for application: 🌐

  1. Clone Github Repository.
  2. Extract pickle-files.rar it will extract "similarity.pkl" & "medicine_dict.pkl" pickle files. Make sure the files should be present in the root directory where the app.py is present
  3. Download Pycharm IDE and Open this application folder in it.
  4. Open Termial.
  5. Import Libraries: streamlit, pandas and pickle.
  6. Type- streamlit run app.py
  7. if the application does not start then type python -m streamlit run app.py

Note Special Instruction if terminal throws an error "streamlit is not recognized as an internal or external command" still after importing all libraries.

  • ➡ Recreate a new Python Project, then import all libraries (streamlit, pandas and pickle) and include css & images folder along with the extracted pickle-files.

Deployment and Data Files 📦

To facilitate deployment and address GitHub's file size limit of 100 MB, we have reduced the size of the similarity.pkl file. However, the original data files required for the application are available in the pickle-files.rar archive.

Here's how to handle the deployment and retrieve the original data files:

  1. Reduced similarity.pkl File: The reduced similarity.pkl file is provided in the root directory of this repository. This file is optimized for deployment and may contain a smaller subset of data. It is suitable for running the application in a production environment.

  2. Original Data Files: To obtain the original data files used for development and testing, you will need to extract them from the pickle-files.rar archive. These files, similarity.pkl and medicine_dict.pkl, should be placed in the same directory as the application script app.py for full functionality.

    You can extract the files using various tools such as WinRAR, 7-Zip, or the unrar command-line utility:

Make sure the extracted data files are present in the root directory alongside app.py to ensure the application works with the complete dataset.

By following these instructions, you can deploy the application with the reduced similarity.pkl file while having access to the original data files when needed.


Video Demonstration:- ▶

Demo for Medicine Recommendation System Click Here for Proper Demonstration of Application.


Kaggle Dataset 📊

Click Here to Access Dataset.


Contact 📝

Anurag Biswal -

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The "Medicine Recommendation System" is designed to provide suggestions for alternative or substitute medications based on a search query, with the primary goal of offering viable replacements for the specified medicine.

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