EmojifyAI

EmojifyAI is a Python package that suggests relevant emojis for a given input sentence using natural language processing techniques. It employs the BERT model to generate embeddings for the input sentence and the emojis' descriptions, and then finds the most similar emojis using cosine similarity.

Installation

To use EmojifyAI, you need to have the following libraries installed with Python 3.11:

1. transformers
2. torch
3. nltk
4. numpy
5. pandas
6. re
7. streamlit

Install Requirements

To install all the requirement of the project, simply type: pip install -r requirements.txt

You can install these dependencies using pip:

pip install transformers torch nltk numpy pandas

Usage

Here's an example of how to use EmojifyAI:

emoji_rec = EmojifyAI()  # Instantiate the EmojifyAI class
emoji_rec.generate_emoji_csv()  # Generate the emoji data CSV file

mean_tokens = emoji_rec.process_csv()  # Process the CSV and obtain mean tokens for emojis
torch.save(mean_tokens, 'checkpoint/token-all.pt')  # Save the mean tokens to a file

test_sentence = "I am going to the movies"
suggestEmojis(test_sentence)  # Suggest emojis for the test sentence

Emojify Class

The EmojifyAI class provides the following methods:

1. generate_emoji_csv(): Generates an emoji data CSV file from the raw emoji data.
2. process_csv(): Processes the emoji CSV file and calculates the mean tokens for the emojis' descriptions.
3. process_sentence(sentence: str): Processes the input sentence and returns the mean tokens for the sentence.
4. find_similarity(sentence_tokens, mean_tokens): Calculates the cosine similarity between the sentence tokens and the mean tokens of the emojis.

SuggestEmojis function

The suggestEmojis(sentence: str) function is a helper function that takes an input sentence and suggests the most relevant emojis for the sentence. It uses the EmojifyAI class to process the sentence and find the most similar emojis based on the cosine similarity between the sentence and emojis' descriptions.

Run Code

There are two files in this project:

1. To run EmojifyAI.ipynb, make sure to run it via Jupyter Noteebook.
2. To run EmojifyAI_SL.py, type this command on terminal (directory), streamlit run EmojifyAI_SL.py.

Output Demo

Contributing

If you'd like to contribute to the project or report a bug, please open an issue or submit a pull request on the GitHub repository.

Credits

1. Abdul Samie
2. Fatimah Noor

License

This project is licensed under the MIT License.