Ella is a chat bot designed to operate with a custom dataset, tailored for specific requirements. This README provides an overview of Ella, its features, how to set it up, and guidelines for using a custom dataset.
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Customization: Ella is highly customizable, allowing users to fine-tune its behavior based on specific needs and preferences.
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Natural Language Understanding: Ella is designed to understand and respond to natural language queries effectively.
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Ease of Integration: Integration with a custom dataset is straightforward, enabling users to train Ella on domain-specific knowledge.
- Python 3.x
- Dependencies listed in
requirements.txt
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Clone this repository:
git clone https://github.com/your-username/ella-custom-chat-bot.git
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Navigate to the project directory:
cd ella-custom-chat-bot
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Install dependencies:
pip install -r requirements.txt
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Configure the custom dataset:
- Replace the placeholder data in
custom_dataset.json
with your own dataset.
- Replace the placeholder data in
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Run the bot:
python ella_bot.py
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Interact with Ella by providing natural language queries.
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Observe and analyze the responses. Fine-tune the model as needed based on the feedback.
Ella's performance heavily relies on the quality of the custom dataset. Ensure that the dataset is formatted correctly with a clear structure:
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Input: User queries or statements in natural language.
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Output: Corresponding responses or actions.
[
{"input": "How does X work?", "output": "X works by..."},
{"input": "Tell me about Y.", "output": "Y is..."},
...
]
To retrain Ella on an updated dataset, run:
python train_ella.py --dataset custom_dataset.json
Feel free to contribute to the development of Ella by submitting pull requests. If you encounter any issues or have suggestions, please open an issue on the repository.