Deterministic, non-LLM grounding & hallucination classifier for agent loops.
Project description
reshimu-shor
Deterministic, non-LLM grounding & hallucination classifier for agent loops.
Python port of @reshimu/shor. Functionally identical to the TypeScript implementation — same input produces the same classification. Sub-50ms. Zero runtime dependencies (stdlib only).
This is the minimal README. The full README ships at the project root in a later step.
Install
pip install reshimu-shor
Quick start
from reshimu_shor import classify
result = classify(
output="According to the report, Q3 revenue was $4.2M from 47 customers.",
context="...the conversation history, tool outputs, documents the agent saw...",
)
print(result.level) # 'GROUNDED' | 'PARTIAL' | 'UNGROUNDED' | 'INDETERMINATE'
print(result.score) # [0, 1]
print(result.entities) # per-entity lookup ledger
print(result.flag_for_review) # True for PARTIAL and UNGROUNDED
License
MIT
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