Evaluate prompts in the Anthropic Console
TLDRThe Anthropic Workbench has been enhanced with a prompt generator that uses Claude 3.5 Sonnet to convert task descriptions into detailed templates. This tool is showcased in a video where it's used to create a prompt for triaging customer support requests. The video demonstrates the ability to generate realistic test data and evaluate the prompt's performance across various scenarios. It also highlights the customization of the prompt for improved justifications and the reevaluation process to ensure quality, showcasing the iterative improvement of the prompt based on feedback.
Takeaways
- 🛠️ The Anthropic Workbench has been improved for prompt development and deployment for Claude, an AI assistant.
- 📝 A prompt generator is available to convert high-level task descriptions into detailed prompt templates using Claude 3.5 Sonnet.
- 🆘 The script demonstrates the process of creating a prompt for triaging customer support requests.
- 📈 Before deployment, it's important to test the prompt with realistic customer data to ensure its effectiveness.
- 🔁 Claude can automatically generate realistic input data for testing prompts, saving time and effort.
- 📊 The Evaluate feature allows setting up multiple test cases to assess the prompt's performance across various scenarios.
- 📋 Test cases can be generated automatically or uploaded from a CSV file, with customizable generation logic.
- 📝 Direct editing of the test case generation logic is possible for specific requirements.
- 📊 After generating results, the quality of the prompt's outputs can be graded and evaluated.
- 🔄 Feedback from evaluations can be used to refine the prompt, such as making justifications longer.
- 🔄 The Evaluate tab retains the test suite for rerunning the updated prompt against the existing data set.
- 📈 Comparing new and old results helps in assessing improvements, such as longer justifications and better grading.
Q & A
What improvements have been made to the Anthropic Workbench?
-The Anthropic Workbench has been updated with a prompt generator that can convert high-level task descriptions into detailed prompt templates using Claude 3.5 Sonnet, making it easier to develop and deploy prompts for Claude.
How does the prompt generator work?
-The prompt generator uses Claude 3.5 Sonnet to create a detailed and specific prompt based on the high-level description of a task provided by the user.
Why is it important to test the prompt before deploying it to production?
-Testing the prompt with realistic customer data ensures that it performs well in various scenarios and is not just a one-time success.
What feature can be used to generate realistic input data for testing the prompt?
-Claude can automatically generate realistic input data based on the provided prompt, which can be used to simulate customer support requests or other relevant scenarios.
How can one ensure the prompt works across a broad range of scenarios?
-The new Evaluate feature allows users to set up multiple test cases and assess the prompt's performance across a wide range of scenarios.
Can test cases be generated automatically or do they need to be manually created?
-Test cases can be automatically generated by Claude, and users can also upload test cases from a CSV file if they have existing test data.
How customizable is the test case generation logic?
-The test case generation logic is highly customizable and can be adapted to the user's existing test set. Users can also directly edit the generation logic if they have specific requirements.
What can be done if the initial evaluation of the prompt's results is not satisfactory?
-If the initial evaluation reveals issues such as brief justifications, the prompt can be revised accordingly, and then rerun to see the updated results.
How can the Evaluate feature help in refining the prompt?
-The Evaluate feature allows users to compare new results against old ones, providing a side-by-side comparison to see improvements and make further adjustments as needed.
What is the benefit of being able to compare new and old results side by side?
-Comparing new and old results side by side helps users to visually assess the impact of their changes to the prompt and ensures that improvements are being made effectively.
How does the process of refining the prompt and re-evaluating it work within the Anthropic Console?
-After refining the prompt, users can rerun it against the existing test suite within the Evaluate tab, allowing for a quick assessment of the updated prompt's performance.
Outlines
🛠️ Improving the Anthropic Workbench
The Anthropic Workbench has been enhanced to facilitate the development and deployment of high-quality prompts for Claude. The script introduces the updated prompt generator, which can convert a task description into a detailed prompt template using Claude 3.5 Sonnet. The example task involves triaging customer support requests, and the script demonstrates how Claude can generate a prompt, test it with realistic data, and refine it based on evaluation results. The process includes generating test data, evaluating the prompt's performance, customizing test case generation, and iterating on the prompt based on feedback.
Mindmap
Keywords
💡Anthropic Workbench
💡Prompt Generator
💡Claude 3.5 Sonnet
💡Triage
💡Realistic Test Data
💡Evaluate Feature
💡Test Cases
💡Justification
💡Triage Decision
💡Grading Quality
💡Comparing Results
Highlights
Anthropic Workbench has been improved for easier development and deployment of high-quality prompts for Claude.
A prompt generator has been updated to convert high-level task descriptions into detailed prompt templates using Claude 3.5 Sonnet.
The prompt generator is demonstrated with a task to triage customer support requests.
Claude automatically writes a detailed and specific prompt based on the given task.
Testing the prompt with realistic customer data is recommended before deployment.
Generating realistic test data can be time-consuming and often longer than writing the prompt.
Claude can automatically generate realistic input data based on the prompt.
A customer support request is generated as an example of realistic input data.
The prompt is tested with the generated support request, providing justification and a triage decision.
The Evaluate feature is introduced to test the prompt's performance across a broad range of scenarios.
Test cases can be set up and generated using the Evaluate page.
Representative test cases can be generated or uploaded from a CSV file.
Test case generation logic is customizable and can be directly edited for specific requirements.
A new test suite can be generated with the prepared test cases.
The quality of the results can be graded to evaluate the prompt's effectiveness.
Prompt adjustments can be made based on evaluation feedback, such as extending justification length.
The updated prompt can be rerun against the old test set data for comparison.
New results can be compared side by side with old results to assess improvements.
Grading the new outputs shows an improvement in quality and longer justifications.