Evaluate prompts in the Anthropic Console

Anthropic
9 Jul 202403:20

TLDRThe Anthropic Workbench has been enhanced to streamline prompt development for Claude, featuring an updated prompt generator that converts task descriptions into detailed templates. Claude 3.5 Sonnet is utilized to create a prompt for customer support request triage, which is then tested with automatically generated realistic data. The Evaluate feature allows for extensive testing with customizable test cases and comparison of results to refine prompts. This iterative process ensures high-quality prompts that provide detailed justifications and effective triage decisions.

Takeaways

  • 🛠️ The Anthropic Workbench has been improved to facilitate the development and deployment of high-quality prompts for Claude.
  • 📝 The prompt generator can convert a high-level task description into a detailed prompt template using Claude 3.5 Sonnet.
  • 🆘 An example task given is to triage customer support requests, with Claude generating a prompt based on this task.
  • 📈 Before deploying the prompt, it's important to test its performance with realistic customer data.
  • 🔁 Claude can also generate realistic input data for testing, saving time compared to creating test data manually.
  • ✅ The prompt is tested with a specific customer support request and provides a justification and triage decision.
  • 📊 The Evaluate feature allows setting up multiple test cases to ensure the prompt works in various scenarios.
  • 📋 Test cases can be generated or uploaded from a CSV, with customizable logic to fit specific requirements.
  • 🔄 Based on evaluation, the prompt can be refined, such as extending justifications from one to two sentences.
  • 🔄 After refinement, the prompt can be rerun against the old test set to ensure consistency and improvement.
  • 📊 Comparing new and old results side by side shows the impact of refinements, such as longer justifications and improved grading.

Q & A

  • What improvements have been made to the Anthropic Workbench?

    -The Anthropic Workbench has been updated with features that simplify the development and deployment of high-quality prompts for Claude, including an improved prompt generator.

  • How does the prompt generator work in the Anthropic Workbench?

    -The prompt generator converts a high-level task description into a detailed prompt template using Claude 3.5 Sonnet, which is tailored to the specific task at hand.

  • What is the purpose of the prompt generator in the context of customer support requests?

    -The prompt generator is used to create detailed and specific prompts to assist with triaging customer support requests, ensuring they are handled efficiently and effectively.

  • 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 practical scenarios and helps identify any potential issues before it is used in a live environment.

  • How can Claude help with generating realistic test data?

    -Claude can automatically generate realistic input data based on the prompt, which can be particularly useful for creating customer support requests for testing purposes.

  • What is the Evaluate feature in the Anthropic Workbench and how does it help?

    -The Evaluate feature allows users to set up multiple test cases to assess the performance of the prompt across a broad range of scenarios, ensuring its reliability and effectiveness.

  • Can users customize the test case generation logic in the Evaluate feature?

    -Yes, users can customize the test case generation logic to adapt to their existing test set or to meet highly specific requirements, even allowing direct editing of the generation logic.

  • How does the Evaluate feature help in improving the quality of the prompt?

    -By grading the quality of the results from the test cases, users can identify areas for improvement in the prompt, such as the length of justifications, and make necessary adjustments.

  • What is the process for updating the prompt based on evaluation results?

    -After identifying areas for improvement, such as the need for longer justifications, users can go back to the prompt, update the relevant sections, and rerun the prompt to see the changes in action.

  • How can users ensure the updated prompt is better than the previous version?

    -Users can compare the new results against the old ones side by side to see the differences, such as longer justifications, and assess whether the overall grading and triage decisions have improved.

Outlines

00:00

🛠️ Claude Prompt Generator Update

The Anthropic Workbench has been enhanced to streamline the creation and deployment of high-quality prompts for Claude. The script introduces a prompt generator that can transform a task description into a detailed prompt template using Claude 3.5 Sonnet. The example task involves triaging customer support requests, and Claude generates a specific prompt that is then tested with realistic customer data. The script highlights the time-consuming nature of creating test data and introduces a feature to automate this process. The prompt is evaluated with the generated data, and the results are assessed for quality and justification.

📊 Testing and Evaluating Prompts

The script discusses the importance of testing prompts with a broad range of scenarios to ensure reliability. It introduces a new 'Evaluate' feature that allows for the setup of multiple test cases and the generation of a representative test suite. The feature supports customization of test case generation logic and the ability to upload test cases from a CSV file. The results of the test suite are then evaluated for quality, and if necessary, adjustments are made to the prompt, such as extending the length of justifications. The script demonstrates how to rerun the updated prompt against the existing test set and compare the results to ensure improvements.

Mindmap

Keywords

💡Anthropic Workbench

The Anthropic Workbench is a tool designed to facilitate the development and deployment of prompts for Claude, an AI system. It has been improved with new features to make prompt generation more efficient. In the video, it is used to convert a high-level task description into a detailed prompt template, which is essential for the AI to understand and execute the task properly.

💡Claude 3.5 Sonnet

Claude 3.5 Sonnet refers to the version of the AI system being used in the Anthropic Workbench. It is capable of generating detailed and specific prompts based on high-level task descriptions. The script demonstrates how Claude immediately starts writing a prompt once a task is described, showcasing its ability to assist in prompt creation.

💡Triage

In the context of the video, triage refers to the process of prioritizing and categorizing customer support requests. The prompt generated by Claude is designed to assist in this process, providing a justification and a decision on how to handle each request. This is a critical function in customer support to ensure that urgent issues are addressed promptly.

💡Realistic Test Data

Realistic test data is essential for evaluating the performance of a prompt in a real-world scenario. The script mentions that generating such data can be time-consuming, but it is a crucial step before deploying a prompt to production. The video highlights the feature that allows Claude to automatically generate this data, streamlining the testing process.

💡Evaluate Feature

The Evaluate feature is a new addition to the Anthropic Workbench that allows users to set up multiple test cases for their prompts. It is used to assess how well the prompt performs across a broad range of scenarios. The script emphasizes the importance of this feature in ensuring the reliability and effectiveness of the prompts before they are used in actual operations.

💡Test Cases

Test cases are specific scenarios or instances used to test the functionality of a system or, in this case, the effectiveness of a prompt. The video script describes how users can generate a broad range of representative test cases using Claude, or even upload them from a CSV file if available, to thoroughly evaluate the prompt.

💡Justification

In the context of the video, justification refers to the reasoning provided by the AI when making a triage decision for a customer support request. The script mentions that the initial prompts provided a one-sentence justification, but later iterations were updated to provide a two-sentence justification to give more detailed reasoning.

💡Grading Quality

Grading quality is the process of assessing the performance of the AI's responses to the test cases. In the video, after generating results for the test suite, the user grades the quality of the responses, considering factors such as the length and depth of the justifications provided by the AI.

💡Customizable Test Case Generation

The script mentions that the logic for generating test cases is highly customizable, allowing users to adapt it to their existing test set or specific requirements. This feature provides flexibility in creating test cases that are representative of the scenarios the AI will encounter in real-life applications.

💡Comparing Results

Comparing results is an important step in the evaluation process, where the new outputs generated by an updated prompt are compared against the old results. The script describes how the user can see side by side comparisons to determine if the changes made to the prompt have improved the AI's performance, such as providing longer justifications.

Highlights

Recent improvements to the Anthropic Workbench facilitate the development and deployment of high-quality prompts for Claude.

The prompt generator converts high-level task descriptions into detailed prompt templates using Claude 3.5 Sonnet.

Claude can automatically generate a prompt for triaging customer support requests.

Testing prompts with realistic customer data is crucial before deploying them to production.

Generating realistic test data can be time-consuming and sometimes more so than writing the prompt.

Claude can generate realistic input data based on a given prompt to assist in testing.

The Evaluate feature allows for setting up multiple test cases to assess prompt performance.

Test cases can be generated broadly or uploaded from a CSV file for customized testing.

Test case generation logic is customizable to fit specific requirements.

Users can directly edit the generation logic for highly specific test requirements.

A new test suite can be generated to assess the quality of the prompt's results.

Feedback on prompt performance can guide adjustments for improved output quality.

The prompt can be updated to provide longer justifications based on feedback.

Updated prompts can be rerun against the same test suite for direct comparison.

Comparing new and old results allows for a side-by-side evaluation of prompt improvements.

Grading the quality of outputs helps in determining the effectiveness of prompt adjustments.

The Evaluate feature provides a systematic approach to refining prompts for better performance.