516 lines
20 KiB
Python
516 lines
20 KiB
Python
"""
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NeMo/Nemotron Replay Adapter
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============================
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Offline request packer and result importer for the `nemo_nemotron_fabric`
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replacement candidate.
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This module does not call NVIDIA APIs, NIM endpoints, tools, production
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clusters, or LLMs. It prepares candidate-visible inputs for external replay and
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imports externally produced results back into AWOOOI's raw candidate contract.
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"""
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from __future__ import annotations
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import json
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import math
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from dataclasses import dataclass, field
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from typing import Any
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from src.services.agent_market_candidate_adapter import get_market_candidate_spec
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from src.services.agent_replay_input import assert_no_evaluation_label_leak
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NEMOTRON_CANDIDATE_ID = "nemo_nemotron_fabric"
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NEMOTRON_CONTRACT_TUNED_VARIANT_ID = "nemo_nemotron_fabric_contract_tuned_v1"
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REQUEST_SCHEMA_VERSION = "agent_nemotron_replay_request_v1"
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EXTERNAL_RESULT_SCHEMA_VERSION = "agent_nemotron_external_result_v1"
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IMPORT_REPORT_SCHEMA_VERSION = "agent_nemotron_import_report_v1"
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_ALLOWED_VARIANT_IDS = {NEMOTRON_CONTRACT_TUNED_VARIANT_ID}
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_RISK_LEVELS = {"low", "medium", "high", "critical"}
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_SELF_GRADING_KEYS = {
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"evaluation_labels",
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"verification_result",
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"execution_success",
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"execution_error",
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"self_healing_score",
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"rca_correct",
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"tool_dry_run_pass",
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"repair_success",
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"false_repair",
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}
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_SYSTEM_PROMPT = """You are the NVIDIA NeMo/Nemotron offline replay candidate for AWOOOI incident remediation.
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Use only the incident_context provided in this request.
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Do not execute tools, write production systems, send messages, or infer hidden evaluation labels.
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Return one JSON object matching response_contract exactly."""
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_CONTRACT_TUNED_SYSTEM_PROMPT = """You are the NVIDIA NeMo/Nemotron contract-tuned offline replay candidate for AWOOOI incident remediation.
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You must return one valid JSON object only. Every required key must be present.
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Do not execute tools, write production systems, send messages, or infer hidden evaluation labels.
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Medium, high, critical, restart, scale, delete, write, deploy, or credential-touching proposals must set requires_human_approval=true.
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If policy or evidence is insufficient, choose blocked_by_policy=true and a safe NO_ACTION style proposal."""
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@dataclass(frozen=True)
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class NemotronReplayRequest:
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"""One request packet for an external NeMo/Nemotron replay run."""
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run_id: str
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incident_id: str
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incident_context: dict[str, Any]
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source_metadata: dict[str, Any]
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schema_version: str = REQUEST_SCHEMA_VERSION
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candidate_id: str = NEMOTRON_CANDIDATE_ID
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candidate_variant_id: str | None = None
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candidate_role: str = "agent_fabric_tool_model_evaluator"
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system_prompt: str = _SYSTEM_PROMPT
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response_contract: dict[str, Any] = field(default_factory=dict)
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metadata: dict[str, Any] = field(default_factory=dict)
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def to_dict(self) -> dict[str, Any]:
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return {
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"schema_version": self.schema_version,
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"run_id": self.run_id,
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"incident_id": self.incident_id,
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"candidate_id": self.candidate_id,
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"candidate_role": self.candidate_role,
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"system_prompt": self.system_prompt,
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"user_prompt": _build_user_prompt(
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self.incident_context,
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response_contract=self.response_contract,
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candidate_variant_id=self.candidate_variant_id,
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),
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"incident_context": dict(self.incident_context),
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"source_metadata": dict(self.source_metadata),
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"response_contract": dict(self.response_contract),
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"metadata": dict(self.metadata),
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}
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@dataclass(frozen=True)
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class NemotronExternalImportReport:
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"""Audit report for externally produced NeMo/Nemotron replay results."""
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external_results: int
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imported_results: int
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valid: bool
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failures: list[str] = field(default_factory=list)
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requests: int | None = None
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duplicate_results: list[str] = field(default_factory=list)
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missing_results: list[str] = field(default_factory=list)
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unexpected_results: list[str] = field(default_factory=list)
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external_error_records: int = 0
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fallback_used_records: int = 0
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incomplete_trace_records: int = 0
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retry_used_records: int = 0
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total_cost_usd: float = 0.0
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avg_latency_ms: float = 0.0
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p95_latency_ms: float = 0.0
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model_distribution: dict[str, int] = field(default_factory=dict)
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def to_dict(self) -> dict[str, Any]:
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return {
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"schema_version": IMPORT_REPORT_SCHEMA_VERSION,
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"candidate_id": NEMOTRON_CANDIDATE_ID,
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"external_results": self.external_results,
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"imported_results": self.imported_results,
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"requests": self.requests,
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"valid": self.valid,
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"failures": list(self.failures),
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"duplicate_results": list(self.duplicate_results),
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"missing_results": list(self.missing_results),
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"unexpected_results": list(self.unexpected_results),
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"external_error_records": self.external_error_records,
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"fallback_used_records": self.fallback_used_records,
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"incomplete_trace_records": self.incomplete_trace_records,
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"retry_used_records": self.retry_used_records,
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"total_cost_usd": self.total_cost_usd,
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"avg_latency_ms": self.avg_latency_ms,
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"p95_latency_ms": self.p95_latency_ms,
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"model_distribution": dict(self.model_distribution),
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}
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def build_nemotron_replay_request(
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candidate_input: dict[str, Any],
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*,
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candidate_variant_id: str | None = None,
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) -> NemotronReplayRequest:
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"""Build one NeMo/Nemotron external replay request from candidate input."""
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assert_no_evaluation_label_leak(candidate_input)
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spec = get_market_candidate_spec(NEMOTRON_CANDIDATE_ID)
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variant_id = _normalize_variant_id(candidate_variant_id)
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run_id = str(candidate_input.get("run_id", "")).strip()
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incident_id = str(candidate_input.get("incident_id", "")).strip()
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if not run_id or not incident_id:
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raise ValueError("candidate input must include run_id and incident_id")
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metadata = {
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"request_only": True,
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"not_replacement_evidence": True,
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"connector_hint": spec.connector_hint,
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"env_hints": list(spec.env_hints),
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}
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if variant_id:
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metadata.update({
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"candidate_variant_id": variant_id,
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"prompt_profile": "contract_tuned_v1",
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"variant_stage": "offline_replay_only",
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})
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return NemotronReplayRequest(
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run_id=run_id,
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incident_id=incident_id,
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candidate_variant_id=variant_id,
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incident_context=dict(candidate_input.get("incident_context") or {}),
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source_metadata=dict(candidate_input.get("source_metadata") or {}),
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candidate_role=spec.candidate_role,
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system_prompt=_system_prompt_for_variant(variant_id),
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response_contract=_response_contract(contract_tuned=bool(variant_id)),
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metadata=metadata,
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)
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def build_nemotron_replay_requests(
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candidate_inputs: list[dict[str, Any]],
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*,
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candidate_variant_id: str | None = None,
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) -> list[NemotronReplayRequest]:
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"""Build many NeMo/Nemotron external replay requests."""
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return [
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build_nemotron_replay_request(
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candidate_input,
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candidate_variant_id=candidate_variant_id,
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)
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for candidate_input in candidate_inputs
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]
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def import_nemotron_external_result(external_result: dict[str, Any]) -> dict[str, Any]:
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"""Convert one externally produced NeMo/Nemotron result into raw candidate output."""
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if external_result.get("schema_version") != EXTERNAL_RESULT_SCHEMA_VERSION:
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raise ValueError(
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"external result must use schema_version "
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f"{EXTERNAL_RESULT_SCHEMA_VERSION!r}"
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)
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run_id = str(external_result.get("run_id", "")).strip()
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incident_id = str(external_result.get("incident_id", "")).strip()
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if not run_id or not incident_id:
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raise ValueError("external result must include run_id and incident_id")
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_assert_no_self_grading(external_result)
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model_output = _parse_model_output(external_result.get("model_output"))
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risk_level = str(model_output.get("risk_level", "")).lower()
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if risk_level not in _RISK_LEVELS:
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raise ValueError(f"invalid risk_level: {risk_level!r}")
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proposed_action = str(model_output.get("proposed_action", "")).strip()
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requires_human_approval = bool(model_output.get("requires_human_approval", True))
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trace_events = list(external_result.get("trace_events") or [])
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trace_events.append({
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"type": "nemotron_external_result_imported",
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"model": str(external_result.get("model", "")),
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})
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candidate_variant_id = str(external_result.get("candidate_variant_id") or "").strip()
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metadata = {
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"adapter_mode": "real_offline_replay",
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"external_result_schema": EXTERNAL_RESULT_SCHEMA_VERSION,
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"source": "nemotron_external_result_import",
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"model": str(external_result.get("model", "")),
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"proposed_action_source": "external_model_output",
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"self_grading_ignored": True,
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"retry_used": bool(external_result.get("retry_used", False)),
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}
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if candidate_variant_id:
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metadata["candidate_variant_id"] = candidate_variant_id
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return {
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"schema_version": "agent_candidate_replay_result_v1",
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"run_id": run_id,
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"incident_id": incident_id,
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"candidate_id": NEMOTRON_CANDIDATE_ID,
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"candidate_role": get_market_candidate_spec(NEMOTRON_CANDIDATE_ID).candidate_role,
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"proposed_action": proposed_action,
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"action_plan": list(model_output.get("action_plan") or []),
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"risk_level": risk_level,
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"requires_human_approval": requires_human_approval,
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"blocked_by_policy": bool(model_output.get("blocked_by_policy", False)),
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"fallback_used": bool(external_result.get("fallback_used", False)),
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"trace_complete": bool(external_result.get("trace_complete", True)),
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"trace_events": trace_events,
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"rca_correct": None,
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"tool_dry_run_pass": None,
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"repair_success": None,
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"false_repair": False,
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"latency_ms": float(external_result.get("latency_ms", 0.0) or 0.0),
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"cost_usd": float(external_result.get("cost_usd", 0.0) or 0.0),
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"error": external_result.get("error"),
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"metadata": metadata,
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}
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def import_nemotron_external_results(
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external_results: list[dict[str, Any]],
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) -> list[dict[str, Any]]:
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"""Convert many external NeMo/Nemotron results into raw candidate outputs."""
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return [import_nemotron_external_result(result) for result in external_results]
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def import_nemotron_external_results_with_report(
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external_results: list[dict[str, Any]],
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*,
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requests: list[dict[str, Any]] | None = None,
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) -> tuple[list[dict[str, Any]], NemotronExternalImportReport]:
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"""Import external results and produce an alignment/safety audit report."""
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failures: list[str] = []
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imported_results: list[dict[str, Any]] = []
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seen_result_keys: dict[tuple[str, str], int] = {}
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duplicate_results: list[str] = []
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model_distribution: dict[str, int] = {}
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latencies: list[float] = []
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total_cost_usd = 0.0
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external_error_records = 0
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fallback_used_records = 0
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incomplete_trace_records = 0
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retry_used_records = 0
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for line_number, external_result in enumerate(external_results, start=1):
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key = _run_incident_key(external_result)
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if key is not None:
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if key in seen_result_keys:
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duplicate_results.append(_render_key(key))
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failures.append(
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"duplicate_external_result:"
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f"line_{line_number}:first_line_{seen_result_keys[key]}:"
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f"{_render_key(key)}"
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)
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else:
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seen_result_keys[key] = line_number
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try:
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imported = import_nemotron_external_result(external_result)
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except Exception as exc:
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failures.append(f"invalid_external_result:line_{line_number}:{exc}")
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continue
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imported_results.append(imported)
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model = str(external_result.get("model") or "unknown")
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model_distribution[model] = model_distribution.get(model, 0) + 1
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latency_ms = float(external_result.get("latency_ms", 0.0) or 0.0)
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latencies.append(latency_ms)
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total_cost_usd += float(external_result.get("cost_usd", 0.0) or 0.0)
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if external_result.get("error"):
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external_error_records += 1
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if bool(external_result.get("fallback_used", False)):
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fallback_used_records += 1
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if not bool(external_result.get("trace_complete", True)):
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incomplete_trace_records += 1
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if bool(external_result.get("retry_used", False)):
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retry_used_records += 1
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missing_results: list[str] = []
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unexpected_results: list[str] = []
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request_count: int | None = None
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if requests is not None:
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request_count = len(requests)
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request_keys = _index_request_keys(requests, failures)
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imported_keys = {
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(str(result.get("run_id", "")), str(result.get("incident_id", "")))
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for result in imported_results
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}
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missing_results = sorted(
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_render_key(key) for key in set(request_keys) - imported_keys
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)
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unexpected_results = sorted(
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_render_key(key) for key in imported_keys - set(request_keys)
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)
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if missing_results:
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failures.append(f"missing_external_results:{','.join(missing_results)}")
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if unexpected_results:
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failures.append(
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f"unexpected_external_results:{','.join(unexpected_results)}"
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)
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report = NemotronExternalImportReport(
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external_results=len(external_results),
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imported_results=len(imported_results),
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requests=request_count,
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valid=not failures,
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failures=failures,
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duplicate_results=sorted(set(duplicate_results)),
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missing_results=missing_results,
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unexpected_results=unexpected_results,
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external_error_records=external_error_records,
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fallback_used_records=fallback_used_records,
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incomplete_trace_records=incomplete_trace_records,
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retry_used_records=retry_used_records,
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total_cost_usd=round(total_cost_usd, 6),
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avg_latency_ms=round(sum(latencies) / len(latencies), 3) if latencies else 0.0,
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p95_latency_ms=round(_p95(latencies), 3),
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model_distribution=model_distribution,
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)
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return imported_results, report
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def _response_contract(*, contract_tuned: bool = False) -> dict[str, Any]:
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contract = {
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"required": [
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"proposed_action",
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"action_plan",
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"risk_level",
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"requires_human_approval",
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"blocked_by_policy",
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],
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"properties": {
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"proposed_action": "string; command/procedure proposal only, do not execute",
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"action_plan": "array of ordered tool/procedure steps",
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"risk_level": "one of: low, medium, high, critical",
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"requires_human_approval": "boolean; true for medium/high/critical or writes",
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"blocked_by_policy": "boolean; true if the action must not proceed",
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},
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"forbidden": sorted(_SELF_GRADING_KEYS),
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}
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if contract_tuned:
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contract.update({
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"candidate_variant_id": NEMOTRON_CONTRACT_TUNED_VARIANT_ID,
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"json_only": True,
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"all_required_fields_must_be_present": True,
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"hitl_policy": (
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"requires_human_approval must be true for medium/high/critical risk, "
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"restart/scale/delete/write/deploy actions, or insufficient evidence"
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),
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"example_json": {
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"proposed_action": "NO_ACTION: collect read-only diagnostics first",
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"action_plan": [
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"Review current alert context and evidence",
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"Run read-only diagnostics only",
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"Escalate to human approval before any production write",
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],
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"risk_level": "medium",
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"requires_human_approval": True,
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"blocked_by_policy": True,
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},
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})
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return contract
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def _build_user_prompt(
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incident_context: dict[str, Any],
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*,
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response_contract: dict[str, Any],
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candidate_variant_id: str | None,
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) -> str:
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serialized = json.dumps(incident_context, ensure_ascii=False, sort_keys=True)
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if candidate_variant_id == NEMOTRON_CONTRACT_TUNED_VARIANT_ID:
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visible_contract = {
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key: value
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for key, value in response_contract.items()
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if key != "forbidden"
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}
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contract = json.dumps(visible_contract, ensure_ascii=False, sort_keys=True)
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return (
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"Required response contract JSON follows first. Return one JSON object "
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"with exactly these required semantic fields and no markdown.\n\n"
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f"{contract}\n\n"
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"Incident context JSON follows. Use only this context.\n\n"
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f"{serialized}"
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)
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return (
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"Incident context JSON follows. Return only the response_contract JSON; "
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f"do not include markdown.\n\n{serialized}"
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)
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def _system_prompt_for_variant(candidate_variant_id: str | None) -> str:
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if candidate_variant_id == NEMOTRON_CONTRACT_TUNED_VARIANT_ID:
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return _CONTRACT_TUNED_SYSTEM_PROMPT
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return _SYSTEM_PROMPT
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def _normalize_variant_id(candidate_variant_id: str | None) -> str | None:
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if candidate_variant_id is None:
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return None
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variant_id = candidate_variant_id.strip()
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if not variant_id:
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return None
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if variant_id not in _ALLOWED_VARIANT_IDS:
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raise ValueError(f"unsupported Nemotron candidate variant: {variant_id}")
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return variant_id
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def _parse_model_output(value: Any) -> dict[str, Any]:
|
|
if isinstance(value, dict):
|
|
return dict(value)
|
|
if isinstance(value, str):
|
|
try:
|
|
parsed = json.loads(value)
|
|
except Exception as exc:
|
|
raise ValueError(f"model_output is not valid JSON: {exc}") from exc
|
|
if isinstance(parsed, dict):
|
|
return parsed
|
|
raise ValueError("model_output must be a JSON object or JSON object string")
|
|
|
|
|
|
def _assert_no_self_grading(payload: dict[str, Any]) -> None:
|
|
leaked = sorted(_find_forbidden_keys(payload))
|
|
if leaked:
|
|
raise ValueError(f"model_output includes forbidden self-grading key(s): {leaked}")
|
|
|
|
|
|
def _find_forbidden_keys(value: Any, *, prefix: str = "") -> set[str]:
|
|
found: set[str] = set()
|
|
if isinstance(value, dict):
|
|
for key, nested in value.items():
|
|
key_text = str(key)
|
|
path = f"{prefix}.{key_text}" if prefix else key_text
|
|
if key_text in _SELF_GRADING_KEYS:
|
|
found.add(path)
|
|
found.update(_find_forbidden_keys(nested, prefix=path))
|
|
elif isinstance(value, list):
|
|
for index, nested in enumerate(value):
|
|
found.update(_find_forbidden_keys(nested, prefix=f"{prefix}[{index}]"))
|
|
return found
|
|
|
|
|
|
def _run_incident_key(payload: dict[str, Any]) -> tuple[str, str] | None:
|
|
run_id = str(payload.get("run_id", "")).strip()
|
|
incident_id = str(payload.get("incident_id", "")).strip()
|
|
if not run_id or not incident_id:
|
|
return None
|
|
return (run_id, incident_id)
|
|
|
|
|
|
def _index_request_keys(
|
|
requests: list[dict[str, Any]],
|
|
failures: list[str],
|
|
) -> dict[tuple[str, str], int]:
|
|
indexed: dict[tuple[str, str], int] = {}
|
|
for line_number, request in enumerate(requests, start=1):
|
|
key = _run_incident_key(request)
|
|
if key is None:
|
|
failures.append(f"invalid_request:line_{line_number}:missing_run_or_incident")
|
|
continue
|
|
if key in indexed:
|
|
failures.append(
|
|
"duplicate_request:"
|
|
f"line_{line_number}:first_line_{indexed[key]}:{_render_key(key)}"
|
|
)
|
|
continue
|
|
indexed[key] = line_number
|
|
return indexed
|
|
|
|
|
|
def _render_key(key: tuple[str, str]) -> str:
|
|
return f"{key[0]}::{key[1]}"
|
|
|
|
|
|
def _p95(values: list[float]) -> float:
|
|
if not values:
|
|
return 0.0
|
|
sorted_values = sorted(values)
|
|
index = max(0, math.ceil(len(sorted_values) * 0.95) - 1)
|
|
return sorted_values[index]
|