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/judges.py Normal file
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from .models import RailResult
from .llm_client import LLMClient
from .tracing import span
_client=LLMClient()
def classificar_sentimento(text:str)->RailResult:
with span("judge.CSI", mechanism="llm_judge"):
out=_client.classify("CSI", {"text":text}); return RailResult(True,out.get("reason",""),text,"CSI","llm_judge",{"sentimento":out.get("label"),**out})
def avaliar_alucinacao(resposta:str, dados_reais:str)->RailResult:
with span("judge.ALUC", mechanism="llm_judge"):
out=_client.classify("ALUC", {"resposta":resposta,"dados_reais":dados_reais}); return RailResult(out["allowed"],out.get("reason",""),resposta,"ALUC","llm_judge",{"alucinacao":out.get("label")=="ALUCINACAO",**out})
def avaliar_qualidade_resposta(pergunta:str, resposta:str)->RailResult:
with span("judge.RQLT", mechanism="llm_judge"):
out=_client.classify("RQLT", {"pergunta":pergunta,"resposta":resposta}); return RailResult(True,out.get("reason",""),resposta,"RQLT","llm_judge",out)
def avaliar_tom_de_voz(text:str)->RailResult:
with span("judge.VCTN", mechanism="llm_judge"):
out=_client.classify("VCTN", {"text":text}); return RailResult(out["allowed"],out.get("reason",""),text,"VCTN","llm_judge",{"aderente":out["allowed"],**out})