Promptfoo alternatives for regression tests

Here are solid Promptfoo alternatives for regression testing LLM prompts and workflows, depending on what you mean by “regression tests”:

1. OpenAI Evals

• Good for: structured evals, benchmark-style regression testing
• Pros: flexible, reproducible, supported by OpenAI ecosystem
• Cons: more setup; best if you’re already comfortable with eval harnesses

2. LangSmith

• Good for: prompt/version tracking, datasets, test runs, traces
• Pros: great if you use LangChain; strong observability + evals
• Cons: more platform-oriented than lightweight CLI testing

3. DeepEval

• Good for: unit-test-like LLM evals in Python
• Pros: feels like pytest for LLMs, supports CI
• Cons: Python-centric; less convenient for prompt files alone

4. Giskard

• Good for: testing LLM apps for quality, robustness, and vulnerabilities
• Pros: good for both ML and LLM testing; useful safety checks
• Cons: more opinionated and heavier than simple prompt regression

5. Ragas

• Good for: RAG evaluation/regression
• Pros: strong for retrieval + answer quality metrics
• Cons: focused mainly on RAG, not general prompt regression

6. TruLens

• Good for: app-level evaluation, feedback functions, monitoring
• Pros: good observability and tracing
• Cons: more suited to ongoing evaluation than simple snapshot tests

7. pytest + custom harness

• Good for: simple, fully controlled regression tests
• Pros: easy to integrate with CI; no extra platform needed
• Cons: you build and maintain the eval logic yourself

8. LangGraph / custom workflow tests

• Good for: agent/workflow regression tests
• Pros: useful when you need step-by-step assertions
• Cons: not a ready-made eval suite by itself

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Quick recommendations

• If you want Promptfoo-like prompt regression in Python: DeepEval
• If you want RAG regression tests: Ragas
• If you want observability + evals + traces: LangSmith
• If you want simple CI tests with full control: pytest custom harness
• If you want broader LLM quality/safety testing: Giskard

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Minimal decision guide

• Prompt-only tests → DeepEval or pytest
• RAG apps → Ragas
• Production tracing + evals → LangSmith / TruLens
• Safety + robustness → Giskard
• Benchmark-style evaluation → OpenAI Evals

If you want, I can also give you:

1. a comparison table of Promptfoo vs these tools, or
2. a recommended stack for your exact use case (Python, JS, RAG, agent, CI, etc.).