Welcome to the magical CrystalBall! This Python class allows you to harness the power of divination and answer questions using the HuggingFaces NLP (Natural Language Processing) LLM (Large Language Models)
CrystalBall is a versatile tool that utilizes the incredible capabilities of Hugging Face's Transformers library for question-answering tasks. With CrystalBall, you can unlock the secrets hidden within your documents and obtain answers to your burning questions.
To activate the enchanting powers of CrystalBall, follow these steps:
-
🧹 Create and activate a virtual environment:
python3 -m venv myenv source myenv/bin/activate -
✨ Install the required dependencies
pip3 install -r requirements.txt
To explore the mystical powers of CrystalBall, embark on a journey of question-answering with the following steps:
-
🔮 Prepare your document:
- Ensure your document is in the desired format (e.g., text or Markdown).
- Place your document in a suitable location.
-
🔍 Seek answers from CrystalBall:
- Create an instance of the CrystalBall class in your Python script.
- Use the
read_document()method to provide CrystalBall with the path to your document. - Invoke the
answer_question()method with your question of interest. - Marvel at the wisdom and insights revealed by CrystalBall.
Here's an example to get you started:
from transformers import pipeline
import re
class CrystalBall:
# ...
# Example usage
if __name__ == "__main__":
file_path = '/path/to/document.md'
question = "What is the main topic of the document?"
crystal_ball = CrystalBall()
crystal_ball.read_document(file_path, doc_type='md')
answers = crystal_ball.answer_question(question)
print("Top 3 likely answers:")
for answer in answers:
print("Answer:", answer['answer'])
print("Score:", answer['score'])
print()May the magic of CrystalBall guide you on your quest for knowledge and insights! ✨🔮🌙