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> ML_LIBRARY // PROMPTFOO_v1.0

promptfoo

promptfoo — Developer-first CLI and CI/CD testing tool for prompt engineering, red teaming, and LLM evaluation.

evaluation-observabilityv0.90.1MITqualified
Official DocumentationSource Repository

Model Training

Not Supported

This library is a dedicated runtime engine for inference serving and does not train models.

Model Inference

Supported
Inference Accelerators:
CPU
Deployment Targets:server

What It Does

  • +Declarative YAML-based test suites testing prompts against hundreds of test cases and assertions
  • +Automated LLM red teaming detecting jailbreaks, prompt injections, PII leaks, and SSRF vulnerabilities
  • +Side-by-side local evaluation UI comparing outputs across providers (OpenAI, Anthropic, Bedrock, Ollama, HuggingFace)
  • +Turnkey assertion types: semantic similarity, regex, JSON schema validation, JavaScript functions, LLM-as-a-judge

What It Does Not Do

  • -Train or fine-tune neural model weights
  • -Act as a production model serving reverse proxy
  • -Process tabular database rows

>Suitable Work Types

  • Automated security red-teaming scans auditing generative AI chatbots for jailbreak vulnerabilities in CI/CD
  • Comparing model cost vs. accuracy tradeoffs between GPT-4o, Claude 3.5 Sonnet, and local Llama 3
  • Continuous regression testing ensuring system prompt revisions maintain required JSON output schemas

>Unsuitable Work Types

  • Classical statistical data analysis
  • Audio speech waveform manipulation
Data Residency Implications

Runs 100% locally. Tests can query internal Ollama or vLLM endpoints for zero data leakage.

Security Considerations

Permissive MIT license. Clean Node.js / TypeScript codebase.

Operational Profile & Known Limitations

Maturity:mature
Learning Curve:low
Ops Complexity:low
Cost Tier:free-oss
> Known Limitations:
  • Running massive matrix evaluations over dozens of prompts and models can trigger upstream API rate limits unless concurrency is constrained (maxConcurrency flag).

Associated Incident Patterns (Incidentpedia)

Enforce safeguards and monitoring to guard against these documented real-world failure modes:

training-serving-skew

> Primary Evidence & Benchmark Citations

promptfoo Documentationofficial-docs • >=0.85.0, <=0.90.x
2026-09-25HIGH