FlirtyHuh is a fun and interactive flirt bot that brings a touch of humor and charm to your conversations. This project involves creating a custom dataset, fine-tuning a T5-small model, and developing a user-friendly front-end using HTML, CSS, and JavaScript.
- A custom-trained T5-small model for generating flirty responses.
- User-friendly interface built with HTML, CSS, and JavaScript.
- Fun and engaging interaction with users.
- Responsive design for accessibility across various devices.
- Real-time message exchange with dynamic bot responses.
- Created a custom dataset tailored for flirtatious responses.
- The dataset includes a variety of prompts and witty replies designed to emulate a charming conversationalist.
- Employed techniques to ensure diversity and creativity in the dataset.
- Fine-tuned the T5-small model using the custom dataset.
- Leveraged Hugging Face Transformers library for training and evaluation.
- Optimized the model to generate creative, relevant, and engaging responses.
- Incorporated evaluation metrics such as BLEU and Rouge to measure response quality.
- Designed a clean and intuitive front-end using HTML, CSS, and JavaScript.
- Implemented a responsive design for seamless usage across desktops, tablets, and smartphones.
- Built features to send messages, display bot responses dynamically, and manage session states.
- Model: T5-small
- Libraries: Hugging Face Transformers, PyTorch
- Front-End: HTML, CSS, JavaScript
- Backend: Flask or FastAPI (for hosting the bot logic)
- Clone the repository:
git clone <repository-url> cd flirtyhuh
- Install dependencies:
pip install torch transformers flask
- Load the fine-tuned T5 model and set up the backend script.
- Run the backend server:
python app.py
- Open the
frontend
folder. - Edit the
config.js
file to point to the backend server URL if necessary. - Open
bot.html
in a web browser. - Start chatting with the bot and enjoy!
- Open the web interface.
- Type a message into the input box and hit send.
- The bot will respond with a witty or flirty reply in real time.
- Add support for multiple languages to cater to a wider audience.
- Integrate with popular messaging platforms like WhatsApp and Telegram.
- Expand the dataset for more nuanced and varied responses.
- Implement additional personality modes for the bot (e.g., humorous, poetic, etc.).
- Add user analytics to improve bot performance and user satisfaction.
Feel free to contribute to FlirtyHuh! If you have suggestions for improvement or encounter any issues, please submit a pull request or create an issue in the repository.
This project is licensed under the MIT License. See the LICENSE file for details.
Enjoy chatting with FlirtyHuh and spread the charm!