cristiano.hoshikawa/nemo_guardrails_configuration
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Cristiano Hoshikawa
2026-05-01 14:12:53 -03:00
parent a170a09cbd
commit 171e0bb3af
52 changed files with 1727 additions and 0 deletions
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final_pkg/company_nemo_guardrails/llm_rails.py Normal file
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from .models import RailResult
from .llm_client import LLMClient
from .tracing import span
_client=LLMClient()
def detectar_toxicidade(text:str)->RailResult:
with span("rail.TOX", mechanism="llm_rail"):
out=_client.classify("TOX", {"text":text}); return RailResult(out["allowed"],out.get("reason",""),text,"TOX","llm_rail",out)
def detectar_out_of_scope(text:str)->RailResult:
with span("rail.OOS", mechanism="llm_rail"):
out=_client.classify("OOS", {"text":text}); return RailResult(out["allowed"],out.get("reason",""),text,"OOS","llm_rail",out)
def verbalizacao_prematura(text:str, context:dict)->RailResult:
with span("rail.REVPREC", mechanism="llm_rail"):
out=_client.classify("REVPREC", {"text":text,"context":context}); return RailResult(out["allowed"],out.get("reason",""),text,"REVPREC","llm_rail",out)
def validar_groundedness(resposta:str, context:dict)->RailResult:
with span("rail.GND", mechanism="llm_rail"):
out=_client.classify("GND", {"resposta":resposta,"context":context}); return RailResult(out["allowed"],out.get("reason",""),resposta,"GND","llm_rail",out)
def supervisor_vas_avulso(payload:dict)->RailResult:
with span("supervisor.REVPREC_SUP", mechanism="llm_supervisor"):
out=_client.classify("SUPERVISOR_VAS", payload); return RailResult(out["allowed"],out.get("reason",""),code="REVPREC_SUP",mechanism="llm_supervisor",data=out)