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Promptfoo

Open-source CLI and library for testing, evaluating, and red-teaming LLM prompts, models, and RAG pipelines — runs locally on your machine or in CI.

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In Plain English

Open-source CLI and library for testing, evaluating, and red-teaming LLM prompts, models, and RAG pipelines — runs locally on your machine or in CI.

OverviewFeaturesPricingUse CasesLimitationsFAQAlternatives

Overview

Promptfoo is an open-source tool that has become the most popular CLI for evaluating LLM prompts and applications. You write a YAML config that lists prompts, providers, test cases, and assertions and Promptfoo runs the matrix locally, caches results, and shows a web UI diff between configurations.

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Key Features

Feature information is available on the official website.

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Pricing Plans

Open Source

Free (MIT)

    Promptfoo Cloud

    Custom / usage-based

      Enterprise

      Custom

        See Full Pricing →Free vs Paid →Is it worth it? →

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        Best Use Cases

        🎯

        Engineering teams testing prompt and model changes in CI

        ⚡

        Security teams red-teaming LLM applications before launch

        🔧

        RAG evaluation comparing chunking, embedding, and retrieval choices

        🚀

        Open-source projects benchmarking models on standard test suites

        Limitations & What It Can't Do

        We believe in transparent reviews. Here's what Promptfoo doesn't handle well:

        • ⚠Red-teaming requires API calls that incur costs
        • ⚠Not a production monitoring tool (use with observability tools)
        • ⚠Complex multi-step agent flows need careful test design
        • ⚠Results storage requires local or cloud infrastructure

        Pros & Cons

        ✓ Pros

        • ✓Truly local — prompts and datasets never leave your machine
        • ✓MIT licensed core means no vendor lock-in or runtime cost
        • ✓Red-team mode generates real OWASP-aligned attack suites automatically
        • ✓Excellent provider coverage including Bedrock, Vertex, and self-hosted models
        • ✓Config-as-code fits cleanly into existing CI/CD pipelines

        ✗ Cons

        • ✗YAML configs get unwieldy for very large eval suites without discipline
        • ✗LLM-as-judge assertions can be flaky without careful grader prompts
        • ✗Cloud tier pricing is not transparent on the public site
        • ✗Web UI is meant for local inspection, not multi-user dashboards

        Frequently Asked Questions

        How does Promptfoo differ from LangSmith?+

        Promptfoo focuses on systematic testing and evaluation with assertions and red-teaming, while LangSmith focuses on tracing and observability. They're complementary — use Promptfoo for pre-deployment testing and LangSmith for production monitoring.

        Can Promptfoo test AI agent tool usage?+

        Yes. You can test whether agents call the right tools with correct parameters by asserting on function call outputs and tool selection patterns.

        Does the red-teaming feature work with any model?+

        Yes. Promptfoo generates adversarial inputs that work against any LLM provider. It uses a separate model to generate attacks and evaluates target model responses.

        Can I run Promptfoo in CI/CD?+

        Yes. Promptfoo provides a CLI that exits with appropriate status codes based on pass/fail thresholds, making it easy to integrate into any CI/CD pipeline.
        🦞

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        Alternatives to Promptfoo

        Braintrust

        LLM Observability

        AI observability platform for evals, production tracing, prompt management, and regression detection.

        LangSmith

        AI Observability

        LangSmith is LangChain's commercial observability, evaluation and prompt management platform for LLM apps and agents in production.

        Humanloop

        LLM evaluation and governance

        an LLM development platform for prompt management, evaluations, logging, and trustworthy AI product iteration; the homepage announces the team joining Anthropic.

        DeepEval

        Testing & Quality

        Open-source LLM evaluation framework with 50+ research-backed metrics including hallucination detection, tool use correctness, and conversational quality. Pytest-style testing for AI agents with CI/CD integration.

        View All Alternatives & Detailed Comparison →

        User Reviews

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        Quick Info

        Category

        AI Evaluation

        Website

        www.promptfoo.dev
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        More about Promptfoo

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