promptfoo
by Community
Test your prompts, agents, and RAGs. Red teaming/pentesting/vulnerability scanning for AI. Compare performance of GPT, Claude, Gemini, DeepSeek, and more. Simple declarative config
OSS
promptfoo
Added 1 June 2026
Overview
promptfoo is a testing framework for evaluating prompts, agents, and RAG systems across multiple LLM providers including GPT, Claude, Gemini, and DeepSeek. It runs comparative benchmarks, red team tests, and vulnerability scans using declarative YAML configs with CLI and CI/CD support.
Best for
Best for
Teams building LLM applications who need systematic prompt validation and security testing before deployment
Use cases
- Compare prompt performance across different LLM models before production
- Automate security testing and adversarial input scanning for AI applications
- Integrate prompt evaluation into CI/CD pipelines for continuous quality checks
Notes
promptfoo is a testing framework for evaluating prompts, agents, and RAG systems across multiple LLM providers including GPT, Claude, Gemini, and DeepSeek. It runs comparative benchmarks, red team tests, and vulnerability scans using declarative YAML configs with CLI and CI/CD support.
21,784 stars on GitHub. Last updated 2026-06-01. Licensed MIT.
Use cases
- Compare prompt performance across different LLM models before production
- Automate security testing and adversarial input scanning for AI applications
- Integrate prompt evaluation into CI/CD pipelines for continuous quality checks
Pros
- Multi-model comparison built in, reducing vendor lock-in risk
- Red teaming and vulnerability scanning included, not bolted on
- Declarative config approach makes tests reproducible and version-controllable
Cons
- Requires familiarity with YAML config syntax and CLI tooling
- Testing scope limited to prompt and agent behavior, not full application integration
- Costs scale with API calls to external LLM providers during test runs
Indexed from awesome-llm and enriched against its public facts.
Pros
- Multi-model comparison built in, reducing vendor lock-in risk
- Red teaming and vulnerability scanning included, not bolted on
- Declarative config approach makes tests reproducible and version-controllable
Cons
- Requires familiarity with YAML config syntax and CLI tooling
- Testing scope limited to prompt and agent behavior, not full application integration
- Costs scale with API calls to external LLM providers during test runs
Pairs with
Other entries in the index that connect to this one. Click through to see the chain.
OpenAI Evals
Community
Evals is a framework for evaluating LLMs and LLM systems, and an open-source registry of benchmarks.
lm-evaluation-harness
Community
A framework for few-shot evaluation of language models.
Agentic Radar
Community
A security scanner for your LLM agentic workflows
AI Gateway
Community
A blazing fast AI Gateway with integrated guardrails. Route to 1,600+ LLMs, 50+ AI Guardrails with 1 fast & friendly API.
awesome-hallucination-detection
Community
List of papers on hallucination detection in LLMs.
Awesome LLM Security
Community
A curation of awesome tools, documents and projects about LLM Security.
chatgpt-wrapper
Community
Power CLI and Workflow manager for LLMs (core package)
Instructor
Jason Liu (community)
Structured output for LLMs via Pydantic. The cleanest answer to 'just give me a typed object back'.
Language models are few-shot learners
Community
2020-05
MLflow
Community
MLflow - Open Source AI Platform for Agents, LLMs & Models
Agenta
Community
The open-source LLMOps platform: prompt playground, prompt management, LLM evaluation, and LLM observability all in one place.
Arthur Shield
Community
Open-source toolkit for building, testing, and monitoring AI agents. Version prompts, run experiments, trace workflows, and catch issues before users do.
Giskard
Community
🐢 Open-Source Evaluation & Testing library for LLM Agents
LangWatch
Community
The platform for LLM evaluations and AI agent testing
Opik
Community
Debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards.
PromptPerfect
Community
PromptPerfect - AI Prompt Generator and Optimizer
TensorZero
Community
TensorZero builds open-source tools for production-grade LLM applications: LLM gateway, observability, optimization, evaluations, and experimentation.
Get the free Developer’s Field Guide
A 27-page field guide to the AI coding workflow with Claude. Claude Code, MCP servers, the prompt patterns that work, and what to delegate. Free.
Enter your work email. We send it straight over, plus a few short notes worth knowing. Unsubscribe any time.