regllm
Offline regression testing for Large Language Model responses using Ollama and Zod.
Pricing
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—Overview
What is regllm?
regllm is a library that enables developers to run offline regression tests on Large Language Model (LLM) responses, ensuring consistency and reliability in AI-driven applications. It leverages Ollama and Zod for robust validation and testing.
Key differentiator
“regllm stands out as the only library providing offline regression testing capabilities specifically tailored for Large Language Models, ensuring robust and reliable model performance in controlled environments.”
Capability profile
Strength Radar
Honest assessment
Strengths & Weaknesses
↑ Strengths
Fit analysis
Who is it for?
✓ Best for
Developers who need to ensure the reliability of Large Language Models in offline environments
Teams working on applications that require consistent and validated LLM responses
Projects where regression testing is critical for maintaining model performance
✕ Not a fit for
Real-time or online testing scenarios requiring immediate feedback
Applications that do not have a need for offline validation of AI models
Cost structure
Pricing
Free Tier
None
Starts at
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Model
Flat rate
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Performance benchmarks
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Next step
Get Started with regllm
Step-by-step setup guide with code examples and common gotchas.