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Promptfoo

Freemium
llmdeveloper toolstestingopen sourceprompt engineeringevaluationragaici/cddevops

Promptfoo is an essential open-source tool for developers serious about building reliable LLM applications, offering a powerful way to test and compare prompts. However, it requires a developer mindset and comfort with YAML configuration to be used effectively.


A testing framework for prompts, models, and RAGs to systematically evaluate and improve LLM output quality.

Promptfoo is a tool for AI and LLM developers to test and evaluate the quality of their models, prompts, and Retrieval-Augmented Generation (RAG) setups. It provides a systematic way to create test cases, run evaluations against various LLM providers, and compare the outputs side-by-side in a unified web viewer. By defining expected outcomes and assertions in a simple configuration file, developers can automate the process of scoring outputs based on metrics like correctness, similarity, latency, and cost. Designed for individual developers and teams, promptfoo integrates directly into the development workflow. It can be run from the command line, incorporated into CI/CD pipelines to prevent quality regressions, and used to find the optimal combination of prompts and models for a specific task. Its support for a wide range of providers—from commercial APIs like OpenAI and Anthropic to open-source models run locally via Ollama—makes it a versatile solution for anyone building reliable AI-powered applications.

Pros

  • Open-source and free for local use
  • Supports a very wide range of LLM providers and local models
  • Provides a clear, systematic framework for reproducible tests
  • Automates output scoring with powerful, flexible assertions
  • Excellent for integrating into CI/CD pipelines to prevent regressions
  • Visual viewer makes it easy to analyze and compare results

Cons

  • Primarily a developer tool with a learning curve for non-programmers
  • Official hosted 'Team' collaboration features are not yet publicly available
  • Reliance on YAML files can become verbose for complex test suites
  • Can be complex to set up for some advanced evaluation scenarios

Key features

  • Side-by-side UI for comparing prompt and model outputs
  • Declarative test cases using a simple YAML configuration
  • Support for 30+ LLM providers including OpenAI, Anthropic, Gemini, and local models
  • Automated scoring with assertions like similarity, regex, and custom functions
  • Command-line interface for local use and CI/CD integration
  • Specialized support for evaluating RAG (retrieval-augmented generation) systems
  • Calculates and reports on metrics like latency and token cost
  • Shareable HTML reports and a hosted evaluation viewer

Integrations

OpenAIGoogle GeminiAnthropicMistralAzure OpenAIAmazon BedrockHuggingFaceReplicateOllamaLlama.cppLangChainLlamaIndex

Target audience

AI/ML developers and engineers building applications on top of Large Language Models (LLMs).


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Founded

2023

Pricing Tiers

Open Source

Free

Team

Coming Soon

Enterprise

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