PromptInspector is an advanced tool designed to streamline testing and refining AI-generated conversations and prompts. By enabling users to interact with OpenAI’s GPT models, evaluate their outputs, and leverage a unique Reflection Mechanism, it empowers researchers, developers, and educators to enhance the quality and performance of AI responses. PromptInspector also provides insights into cost-performance trade-offs by comparing older models with newer ones using the Reflection Mechanism.
- Prompt Testing: Compare custom prompts across multiple OpenAI GPT models.
- Interactive Chatbot: Engage in real-time conversations to test prompt and response quality.
Reflection Mechanism: Enhance AI outputs by allowing the model to refine its own responses. - Model Comparison: Evaluate cost-effectiveness by testing if older models with reflection can match the performance of newer, more expensive models.
- Customizable Settings: Fine-tune model selection, reflection capabilities, and prompt behavior.
To use PromptInspector, you need an OpenAI API key. Follow these steps to create one:
- Sign in to your OpenAI account.
- Navigate to the API Keys section in the OpenAI dashboard.
- Click Create New Secret Key and copy the generated key.
Keep this key secure as it provides access to your OpenAI account.
Visit the live demo of PromptInspector:
👉 promptinspector.streamlit.app
- Enter your OpenAI API key in the sidebar input field to unlock the tool.
- Choose between:
- Prompt Testing: Test a prompt on one or more models and optionally enable reflection for enhanced results.
- Interactive Chatbot: Interact with a model in real-time for conversational testing.
The Reflection Mechanism is a unique feature that allows a model to evaluate its own responses and refine them. This serves several purposes:
- Problem: Newer models like GPT-4 are powerful but come at a higher cost. Older models like GPT-3.5 or GPT-4-turbo may still perform well for specific tasks, especially with some refinement.
- Solution: Reflection enables users to see if older models can achieve comparable performance to newer models by refining their outputs. This helps make cost-effective decisions when choosing a model.
- Reflected responses from older models might provide results that are "good enough" compared to newer models, making them a viable alternative in scenarios where cost is a significant factor.
- Reflection prompts the model to reconsider its initial response and refine it. This ensures the most coherent, accurate, and well-thought-out results, regardless of the model used.
- Reflection allows models to adapt better to complex tasks, making them more reliable for applications like customer support, creative writing, and educational tools.
- Test prompts for customer service bots to ensure natural, empathetic, and accurate responses.
- Compare different models and assess how reflection improves their outputs.
- Evaluate if older models with reflection can replace newer, more expensive models without sacrificing quality.
- Use reflection to explain model reasoning or to refine outputs for educational content.
- Use GPT-4 for initial testing and compare its performance to GPT-3.5-turbo with reflection enabled.
- Determine whether the cheaper GPT-3.5-turbo provides satisfactory results after refinement.
- Feed a story prompt to the models, then refine the responses using the Reflection Mechanism to ensure logical consistency and depth.
- Test complex tasks like multi-turn conversations or creative content generation on both older and newer models.
- Use results to decide which model offers the best balance of quality and cost for the application.
PromptInspector was designed with the following principles in mind:
- Streamlit Framework: Provides a lightweight, interactive, and scalable front-end for rapid prototyping.
- Modular Design: Divides functionality into components (
main.py,openai_client.py,ui.py) to ensure flexibility and maintainability.
- Reflection Mechanism: Enables older models to refine their responses, allowing users to compare their performance with newer models.
- Custom CSS Styling: Enhances readability and creates an intuitive chat interface.
- Session State Management: Retains user inputs and chat history for a smooth conversational experience.
Component Overview:
- API Integration:
openai_client.pyhandles communication with the OpenAI API. - UI Design:
ui.pydefines both the Prompt Testing and Interactive Chatbot interfaces. - Main Controller:
main.pyorchestrates user navigation and ties the UI to the backend.
Ready to try PromptInspector?
👉 promptinspector.streamlit.app
PromptInspector bridges the gap between cost and performance, giving you the tools to make informed decisions about AI model selection while enhancing the quality of AI-generated content. Whether you’re a developer, researcher, or educator, PromptInspector helps you harness the full potential of OpenAI’s GPT models efficiently and effectively.