evaluatorspk 0.0.1

A library for evaluating Retrieval-Augmented Generation (RAG) systems

RAG Evaluator

Overview

RAG Evaluator is a Python library for evaluating Retrieval-Augmented Generation (RAG) systems. It provides various metrics to evaluate the quality of generated text against reference text.

Installation

You can install the library using pip:

pip install evaluatorspk

Usage

Here's how to use the RAG Evaluator library:

from evaluatorspk import RAGEvaluator

# Initialize the evaluator
evaluator = RAGEvaluator()

# Input data
question = "What are the causes of climate change?"
response = "Climate change is caused by human activities."
reference = "Human activities such as burning fossil fuels cause climate change."

# Evaluate the response
metrics = evaluator.evaluate_all(question, response, reference)

# Print the results
print(metrics)

Streamlit Web App

To run the web app:

• cd into streamlit app folder.
• Create a virtual env
• Activate
• Install all dependencies
• and run

streamlit run app.py

Metrics

The following metrics are provided by the library:

• BLEU: Measures the overlap between the generated output and reference text based on n-grams.
• ROUGE-1: Measures the overlap of unigrams between the generated output and reference text.
• BERT Score: Evaluates the semantic similarity between the generated output and reference text using BERT embeddings.
• Perplexity: Measures how well a language model predicts the text.
• Diversity: Measures the uniqueness of bigrams in the generated output.
• Racial Bias: Detects the presence of biased language in the generated output.

Testing

To run the tests, use the following command:

python -m unittest discover -s rag_evaluator -p "test_*.py"