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Radiobot - A Conversational AI for Radiology Enthusiasts

This repository contains a Python script (radiobot.py) that demonstrates the use of Hugging Face's Transformers library to create a conversational AI named Radiobot using the BlenderBot model (facebook/blenderbot-400M-distill). Radiobot is designed to maintain conversation context and handle multiple turns of dialogue, making it a helpful companion for radiology-related conversations or general chatting.

Features

  • Uses the facebook/blenderbot-400M-distill model for natural language understanding and generation.
  • Maintains conversation history to provide contextual responses.
  • Handles dynamic user inputs, allowing for an engaging chatbot experience.

Requirements

To run Radiobot, you'll need the following Python libraries:

  • transformers
  • torch

You can install these dependencies using pip:

pip install transformers torch

How to Use

  1. Clone the Repository:

    git clone https://github.com/Ajogeorge29/radiobot.git
cd radiobot

  2. Run the Script:

    You can run the script directly from the command line:

    python radiobot.py

  3. Interact with Radiobot:

    The script will start a simple conversation. You can continue to interact with Radiobot by entering your text input.

Example Usage

from transformers import BlenderbotTokenizer, BlenderbotForConditionalGeneration

# Load the model and tokenizer
model_name = "facebook/blenderbot-400M-distill"
tokenizer = BlenderbotTokenizer.from_pretrained(model_name)
model = BlenderbotForConditionalGeneration.from_pretrained(model_name)

# Start the conversation
user_input = "Hello, how are you?"
response = generate_response(user_input)
print("Radiobot:", response)

Customization

  • Change the Model: You can replace the BlenderBot model with any other conversational model available on Hugging Face's Model Hub by changing the model_name variable.
  • Modify Conversation History Handling: Adjust how conversation history is maintained to suit more complex applications or use cases.

Contributing

Contributions are welcome! If you have suggestions for improvements or new features, feel free to open an issue or create a pull request.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments