AOAI-Prompt-Optimization-Tool

The Azure OpenAI Prompt Optimization Tool is an interactive Python application powered by OpenAI's GPT-3 technology and tkinter GUI framework. This tool evaluates user-provided prompts, optimizes them, and provides enhanced responses. It features dynamic input, response presentation, and user-friendly functionalities, all while leveraging the power of AI-driven language optimization.

Prerequisites

An existing Azure OpenAI resource and model deployment of a chat model (e.g. gpt-35-turbo, gpt-4)

Deploy the tool

Deploy from your local machine

1. Create an environment variables file .env with your API Key, Endpoint, and Deployed Model name.

• AZURE_OPENAI_API_KEY: your Azure OpenAI resource API key.
• AZURE_OPENAI_API_ENDPOINT: your Azure OpenAI resource endpoint.
• AZURE_OPENAI_DEPLOYED_MODEL: your Azure OpenAI deployment name.

2. Run the following command to install all dependencies.

pip install -r requirements.txt

3. Run app.py file.

How it works

The interface consists of four main elements:

• The prompt input text field to write your prompt.
• The response output window to see the omptimization recommendation.
• The Submit button to send the prompt for AI analysis.
• The Clear button to erase the prompt and start over.

Once you enter and submit a prompt, the following response will be generated:

• Grade: a grade describing how good the prompt is on a scale from 1 to 10.
• Reason for Grade: the analysis of the prompts highlighting missing key elements and how to improve it.
• Optimized Prompt: an example of an optimized prompt that will achieve the same goal in a more efficient way.

Optimization criteria

The tool analyzes the prompt to determine its optimization level based on several criteria that aim to make the prompt clear, effective, and well-structured for the intended purpose. Below are the criteria used to evaluate whether a prompt is optimized or not:

• Clarity: The prompt should be easy to understand without ambiguity. It should convey the desired task or question clearly, so that both human readers and AI models can comprehend it accurately.
• Conciseness: An optimized prompt is concise and to the point. Unnecessary or redundant words should be eliminated to ensure efficient communication of the task to the AI model.
• Relevance: The prompt should directly relate to the desired output. Irrelevant information can confuse the AI model and result in inaccurate or off-topic responses.
• Contextual Information: Including sufficient context in the prompt can help guide the AI model towards the desired response. Relevant details or examples can improve the quality of generated content.
• Specificity: A well-optimized prompt is specific about the expected format, details, or structure of the response. Clear instructions can guide the AI model in producing accurate and relevant output.
• Language Quality: The language used in the prompt should be grammatically correct, coherent, and free of jargon that might confuse the AI model.

Overall, prompt optimization involves balancing these criteria to create a prompt that maximizes the AI model's ability to produce accurate, relevant, and contextually appropriate responses while minimizing the potential for misunderstandings or errors.