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* docs(cli): document device-code login and config reset guidance; renumber sections * docs(cli): fix duplicate numbering (renumber Login/API Keys/Configuration sections) * docs: Fix webhook documentation to include meta dict in all webhook payloads - Add note explaining that meta objects from kickoff requests are included in all webhook payloads - Update webhook examples to show proper payload structure including meta field - Fix webhook examples to match actual API implementation - Apply changes to English, Korean, and Portuguese documentation Resolves the documentation gap where meta dict passing to webhooks was not documented despite being implemented in the API. * WIP: CrewAI docs theme, changelog, GEO, localization * docs(cli): fix merge markers; ensure mode: "wide"; convert ASCII tables to Markdown (en/pt-BR/ko) * docs: add group icons across locales; split Automation/Integrations; update tools overviews and links
50 lines
2.6 KiB
Plaintext
50 lines
2.6 KiB
Plaintext
---
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title: Testing
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description: Learn how to test your CrewAI Crew and evaluate their performance.
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icon: vial
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mode: "wide"
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---
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## Overview
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Testing is a crucial part of the development process, and it is essential to ensure that your crew is performing as expected. With crewAI, you can easily test your crew and evaluate its performance using the built-in testing capabilities.
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### Using the Testing Feature
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We added the CLI command `crewai test` to make it easy to test your crew. This command will run your crew for a specified number of iterations and provide detailed performance metrics. The parameters are `n_iterations` and `model`, which are optional and default to 2 and `gpt-4o-mini` respectively. For now, the only provider available is OpenAI.
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```bash
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crewai test
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```
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If you want to run more iterations or use a different model, you can specify the parameters like this:
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```bash
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crewai test --n_iterations 5 --model gpt-4o
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```
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or using the short forms:
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```bash
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crewai test -n 5 -m gpt-4o
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```
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When you run the `crewai test` command, the crew will be executed for the specified number of iterations, and the performance metrics will be displayed at the end of the run.
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A table of scores at the end will show the performance of the crew in terms of the following metrics:
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<center>**Tasks Scores (1-10 Higher is better)**</center>
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| Tasks/Crew/Agents | Run 1 | Run 2 | Avg. Total | Agents | Additional Info |
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|:------------------|:-----:|:-----:|:----------:|:------------------------------:|:---------------------------------|
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| Task 1 | 9.0 | 9.5 | **9.2** | Professional Insights | |
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| | | | | Researcher | |
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| Task 2 | 9.0 | 10.0 | **9.5** | Company Profile Investigator | |
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| Task 3 | 9.0 | 9.0 | **9.0** | Automation Insights | |
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| | | | | Specialist | |
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| Task 4 | 9.0 | 9.0 | **9.0** | Final Report Compiler | Automation Insights Specialist |
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| Crew | 9.00 | 9.38 | **9.2** | | |
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| Execution Time (s) | 126 | 145 | **135** | | |
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The example above shows the test results for two runs of the crew with two tasks, with the average total score for each task and the crew as a whole.
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