🚀 Enhanced GPT Response Generator with Gradio

Welcome to the Enhanced GPT Response Generator, an interactive web application built with Gradio that leverages the power of OpenAI's GPT models to generate, score, and refine responses to your prompts. This tool goes beyond simple generation by providing automated scoring, detailed reasoning, and feedback for optimal results.

✨ Features

• Multi-Response Generation: Generates multiple candidate responses to a given prompt using GPT-3.5 Turbo, GPT-4, or GPT-4 Turbo.
• Automated Scoring: Scores each generated response based on relevance, completeness, and coherence using GPT-3.5 Turbo.
• Best Response Selection: Automatically selects the highest-scoring response as the "best" answer.
• Detailed Reasoning: Explains the reasoning behind why the selected response is considered the best, using GPT-4. This helps you understand the AI's evaluation process.
• Feedback for Improvement: Provides constructive feedback on the selected response, suggesting potential enhancements, also using GPT-4.
• User-Friendly Interface: Built with Gradio for an intuitive and easy-to-use web experience.
• Logging: Includes detailed logging for debugging and understanding the response generation process.

⚙️ How It Works

1. The user provides a prompt and their OpenAI API key.
2. The application uses the specified GPT model (GPT-3.5 Turbo, GPT-4 or GPT-4 Turbo) to generate multiple responses to the prompt.
3. Each response is scored by GPT-3.5 Turbo on a scale of 0-100 based on relevance, completeness, and coherence.
4. The response with the highest score is selected as the best response.
5. GPT-4 provides a detailed explanation of why the selected response is considered the best.
6. GPT-4 also provides feedback and suggestions for improving the selected response.
7. The best response, reasoning, and feedback are displayed in the Gradio interface.

🛠️ Installation

1. Clone the Repository:

   git clone https://github.com/fabriziosalmi/gradios.git
   cd gradios

2. Install Dependencies:

   pip install -r requirements.txt

   Create a requirements.txt file with the following content:

   gradio
   openai
   

3. Set up your OpenAI API key:

   • You will need an OpenAI API key to use this application. You can obtain one from OpenAI's website.

🚀 Running the Application

1. Execute the script:

   python enhanced_gpt_response_generator.py  # Replace your_script_name.py with the actual name of your python script.

2. Access the Gradio Interface:

   • The application will launch a local web server. The address will be printed in the console (usually something like Running on local URL: http://127.0.0.1:7860).
   • Open this address in your web browser to access the Gradio interface.

📝 Usage

1. Enter your OpenAI API Key: Paste your API key into the "OpenAI API Key" textbox.
2. Enter your Prompt: Type your question or request into the "Enter your prompt here" textbox.
3. Select a Model: Choose the desired GPT model (GPT-3.5 Turbo, GPT-4, or GPT-4 Turbo) from the dropdown.
4. Click "Generate, Select Best Response, and Explain Reasoning": The script will generate responses, score them, select the best one, provide reasoning, and give feedback.
5. View Results: The "Best Response with Detailed Reasoning and Feedback" textbox will display the results.

💡 Example

Prompt: Explain the benefits of using Python for data science.

Expected Output (will vary depending on the model and API response):

Best Response:
Python's popularity in data science stems from its extensive libraries like NumPy, pandas, and scikit-learn, which simplify complex tasks such as data manipulation, analysis, and machine learning. Its clear syntax and large community support further enhance its appeal.

Reasoning:
This response effectively highlights the key advantages of Python, focusing on its rich ecosystem of data science libraries and its ease of use, making it suitable for both beginners and experienced practitioners.

Feedback:
Consider mentioning specific examples of how these libraries are used in data science workflows to further illustrate the benefits.

⚠️ Important Considerations

• OpenAI API Costs: Using the OpenAI API incurs costs. Be mindful of your API usage limits and pricing.
• Model Availability: Ensure that you have access to the GPT-4 model if you intend to use it, as access may be limited.
• API Key Security: Treat your OpenAI API key as a secret. Do not share it publicly or commit it to version control. Consider using environment variables for secure storage.
• Error Handling: The script includes basic error handling, but you may want to implement more robust error handling for production use.
• Rate Limits: Be aware of OpenAI's rate limits. The script generates multiple API calls, which could trigger rate limits if used heavily.

📄 License

This project is licensed under the MIT License. See the LICENSE file for details.