Supercharge Your LLM Application Evaluations 🚀
- llm
- llmops
- evaluation
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Supercharge Your LLM Application Evaluations 🚀
A framework for few-shot evaluation of language models.
Model fingerprint detection with a shared Web and Bun CLI reference bank
GVS5H: Five Qwen3.8-27B Models Match Claude Fable 5 on LiveCodeBench Hard | Fable 5 Level Coding for a Fifth the Price - or on a Single GPU
Scikit-learn for Recursive Self-improvement (RSI). A modular framework for recursive harness evolution.
The first exam for code agents in the physical world: frozen robot tasks from many benchmark suites, each answered with a program and verified in a separate sandbox. Runs on Harbor.
Feather agent harness, training integrations, and evaluation tools for knowledge work
How many bugs can LMs find & fix in large codebases?
Evolved DSH plugin harnesses for five agent benchmarks, with versioned artifacts, evolution curves and Life-Harness comparisons
Test harness for voice agents. Import from Retell, VAPI, Bland, LiveKit. Run autonomous simulations. Evaluate with LLM judges.
Catch your AI agents when they lie about what they shipped — verifies claims against git instead of believing the agent.
Open-source simulation harness for testing AI agents. Simulate LLM and tool calls to test edge cases, failure paths, and agent logic without live API calls.
Framework-agnostic evaluation harness for Go — test your MCP servers and AI agents with scored, CI-ready checks.