Prompt playground

The Prompt Playground is a feature that enables you to experiment with, optimize, and compare prompts for improved performance

Whether you're fine-tuning prompt phrasing, benchmarking model responses, or automating prompt improvement, the Prompt Playground provides powerful features to refine your interactions with language models.

Key capabilities include running multiple prompts simultaneously, storing and versioning prompts, and evaluating their performance through automated metrics. This feature is designed to support both novice and expert users in creating, testing, and perfecting prompt strategies for diverse applications.

Overview

The Prompt Playground empowers you to:

• Optimize prompts by running and comparing multiple versions simultaneously.

• Store and version prompts automatically for future reference and iteration.

• Use existing datasets on the platform or upload your own CSV datasets for testing.

• Switch between a Standard View for an overview of prompts, datasets, and outputs, and a Detailed View to examine individual dataset entries and their corresponding model outputs.

• Automatically improve prompts using AI-driven methods, including:

  • Regular Improvement: Provide inputs and expected outputs to refine performance.

  • AI Optimization: Let an AI model generate improved prompts.

  • Edge Case Handling: Define specific scenarios to address unique challenges.

  • Input-output prompting: Just set the input and expected output to generate a prompt

• Evaluate prompt performance with built-in tools and metrics.

• Create benchmarks to compare model outputs against accurate annotations, including manual validation of annotations.

Supported Data Sources

Prompt Playground supports multiple data sources for testing and optimization:

• Platform Datasets: Use datasets already available within the platform.

• Uploaded CSV Datasets: Upload custom datasets to simulate real-world scenarios for prompts.

Automated Prompt Improvement

The Prompt Playground includes tools for automatically refining prompts:

1. Regular Improvement:

   • Let the system iterate on your prompts for improved performance.

2. Edge Case Handling:

   • Specify edge cases to improve prompt coverage for unique scenarios.

   
3. Input-output prompting:

   • Just set the input and expected output to generate a prompt

   
4. AI Optimization:

   • Enable an AI model to suggest improvements to your prompts.

   

Performance Evaluation

The Playground provides detailed metrics for assessing prompt effectiveness:

• Evaluation Tools: Run evaluators to judge model performance on prompts.

• Benchmark Creation: Compare model outputs to accurate annotations.

• Manual Validation: Validate annotations manually for additional precision.

Metrics and Insights

Prompt performance is automatically recorded and analyzed, providing the following metrics:

• Prompt Name: Identifier for each tested prompt.

• Evaluation Method: Method used for evaluating the prompt.

• Success Rate: Percentage of successful outputs based on benchmarks.

• Time per Request: Average time taken for the model to respond.

• Input Tokens: Number of tokens in the input prompt.

• Output Tokens: Number of tokens in the model's response.

• Rows: Number of dataset rows processed.

How to Use the Prompt Playground

Accessing the Prompt Playground

1. Login: Sign in to your account.

2. Navigate: Click on the Prompt Playground tab from the main menu.

Running and Comparing Prompts

1. Select Dataset: Choose a dataset from the platform or upload your own CSV file.

2. Enter Prompts: Add prompts to test.

3. Run Simultaneously: Execute multiple prompts at once to compare their outputs.

4. View Results: Switch between the Standard View for an overview and the Detailed View for entry-level analysis.

Improving Prompts

1. Select Improvement Type: Choose Regular Improvement, Edge Case Handling, Input-output prompt generation, or AI Optimization.

2. Set Parameters: Describt the improvement you're looking for, set the input and expected output, or edge cases.

3. Run Improvement: Let the Playground refine the prompts automatically.

4. Run the updated prompt

5. Evaluate Results: Review the optimized prompts and outputs.

Evaluating Prompt Performance

1. Run Evaluators: Write an evaluator prompt, and run it over the dataset to measure its performance.

2. Create Benchmarks: Compare model outputs against already annotated data in the dataset.

3. Validate Annotations: Manually validate or refine annotations for accuracy.

Use Cases

Prompt Optimization

• Test multiple prompt variations to determine which yields the best performance.

• Refine prompts to handle complex user inputs and edge cases effectively.

Model Evaluation

• Use evaluators to assess the success rate and efficiency of prompts.

• Benchmark prompts against annotated datasets for objective performance metrics.

Dataset Testing

• Upload real-world datasets to test prompt performance in practical scenarios.

• Use the Detailed View to examine the impact of prompts on specific data entries.

Collaborative Workflow

• Store and version prompts automatically, enabling teams to collaborate and track changes.

• Share prompt configurations and benchmarks with team members for joint analysis.

Tips for Effective Use

• Leverage Views: Use the Standard View for high-level comparisons and the Detailed View for deeper analysis.

• Automate Improvements: Save time by using AI-driven prompt optimization tools.

• Validate Regularly: Periodically validate annotations and benchmarks to ensure the highest accuracy.

• Experiment Freely: Run multiple prompts simultaneously to explore new ideas and strategies.

• Save Configurations: Keep track of successful configurations by saving them for future use.

The Prompt Playground is your all-in-one solution for testing, optimizing, and perfecting prompts for any application. With these powerful tools and detailed analytics, you can refine your prompt strategies and achieve continuous performance, quickly.