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**Break Your LLM before your users do! With our framework, you can build a comprehensive suite of tests that rigorously test your LLM against your guidelines.**
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## Overview
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This is a comprehensive framework designed for testing and evaluating language models, particularly in the field of Natural Language Processing (NLP). This toolset provides functionalities for running tests, calculating performance metrics, and visualizing results to assess the quality of language models.
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## Table of Contents
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-[Features](#features)
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-[Technologies](#technologies)
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-[Installation](#installation)
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-[Usage](#usage)
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-[Codebase Organization](#codebase-organization)
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-[Contributing](#contributing)
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-[License](#license)
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## Features
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-**Model Testing**: Execute tests on various language models.
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-**Metrics Calculation**: Calculate metrics such as accuracy, hallucination rate, and more.
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-**Result Visualization**: Visualize test results for better analysis.
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-**Configurable**: Easily configure settings through YAML and environment files.
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## Technologies
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-**Languages**: Python
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-**Frameworks/Libraries**:
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- OpenAI
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- Pandas
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- NumPy
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- PyYAML
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- Requests
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-**Tools**:
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- Pydantic
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- Python-dotenv
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## Installation
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autoapi/index
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To get started with this project, follow these steps:
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