What is it
Promptfoo is a JavaScript library designed to assess the effectiveness of Language Model Mathematics (LLM) prompts. It enables users to test, enhance, and objectively compare LLM prompts to optimize model outputs.
Key features
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Test case creation:
Facilitate the creation of test cases using representative user inputs, reducing subjectivity in prompt fine-tuning.
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Evaluation metrics:
Enable users to customize evaluation metrics to align with specific requirements, providing flexibility in prompt evaluation.
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Prompt and model comparison:
Provide users with the ability to compare prompts and model outputs side-by-side, aiding in prompt and model selection.
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Integration-friendly:
Seamlessly integrate into existing testing or continuous integration (CI) workflows for smooth and efficient evaluation processes.
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Web viewer and CLI:
Offer both a web viewer and a command-line interface (CLI) to cater to diverse user preferences and needs.
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Proven trustworthiness:
Trusted by LLM applications serving over 10 million users, demonstrating reliability and popularity within the LLM community.
Pros
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Quality assurance:
Rigorous prompt assessments enhance model outputs, ensuring optimal performance.
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Custom metrics:
Tailor evaluation metrics to specific objectives, providing targeted insights into prompt effectiveness.
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Objective decision-making:
Eliminate subjectivity in prompt and model selection through objective comparisons and data-driven analysis.
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Seamless integration:
Effortless integration into existing workflows streamlines the evaluation process, saving time and resources.
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User-friendly interface:
Choose between a web viewer or command-line interface for convenient and efficient use.
Cons
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May require technical expertise to fully utilize its capabilities.
Summary
Promptfoo is a comprehensive tool for LLM prompt testing and enhancement. It empowers users to create test cases, customize evaluation metrics, compare prompts and models, and integrate seamlessly into their workflows. Trusted by a substantial user base, Promptfoo enables objective decision-making and the optimization of prompt quality for superior model outputs.