Language-agnostic correctness checker for scientific numerical code
Project description
AgentBible
Language-agnostic correctness checker for scientific numerical code.
SPEC.md is the mathematical source of truth for every implementation in this repository.
Install
| Language | Command |
|---|---|
| Python | pip install agentbible |
| Rust | cargo add agentbible |
| Julia | julia -e 'using Pkg; Pkg.add("AgentBible")' |
| C++ | CPMAddPackage("gh:rylanmalarchick/research-code-principles@cpp-v0.1.0") |
Python Example
Without validation, a normalization bug can quietly propagate:
import numpy as np
def probabilities(logits: np.ndarray) -> np.ndarray:
return np.exp(logits)
With AgentBible, the same bug fails at the boundary where it matters:
import numpy as np
from agentbible import validate_finite, validate_normalized_l1, validate_probabilities
@validate_finite
@validate_probabilities
@validate_normalized_l1()
def probabilities(logits: np.ndarray) -> np.ndarray:
return np.exp(logits)
The invalid output raises immediately instead of silently contaminating later results.
CLI
Validate Python-produced data directly:
bible validate results.npy --check normalized_l1
Inspect a non-Python provenance record through the unified interface:
bible validate --lang rust results.json
Generate a Markdown provenance summary:
bible report results.json
Repository Layout
agentbible/: Python package, CLI, provenance, context retrievallanguages/rust/: Rust workspacelanguages/cpp/: header-only C++ librarylanguages/julia/: Julia packageschema/provenance_v1.json: cross-language provenance schema
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