Benjamin Admin
978052b5a2
Fix B of the pre-#59 semantic correction. The Silent Pass had only TWO effective states though the data
carries three: a `detected` mapping (a concrete artifact) AND a `partial` mapping (an indicative signal,
e.g. a CI pipeline -> secure-development-lifecycle) both flowed through capability_ids() and were fed to
the Advisor as already-present — so a weak indication silently removed a question, exactly the Welt-1/
Welt-2 transparency we want to keep.
Now three distinct states:
- detected -> reduces the delta immediately (auto_detected, not asked). [unchanged]
- partial -> raises assumption strength but does NOT replace the question (surfaced as `indications`,
the capability stays in the delta and is still asked).
- requirement-> describes a target, never the present state (already handled by Fix A's kind split).
Changes (data + thin wiring, no new architecture):
- SilentIntakeResult.capability_ids() returns only relationship==detected; new indicative_capability_ids()
returns the partial ones.
- advisor_start() gains indicative_capabilities (NOT fed into the profile) and surfaces result.indications
= indicative ∩ required − auto_detected.
- AdvisorResult / AdvisorResponse gain `indications` (additive, contract-safe); the service passes the
indicative ids through.
Tests: a partial CI signal is indicative-not-detected and does NOT shrink the delta; end-to-end it appears
in `indications`, not `auto_detected`, and the gap is still asked. 28 onboarding tests pass, mypy --strict
clean on the onboarding modules, demo runs, check-loc 0. Runtime effect -> deploy + smoke.
65 lines
2.8 KiB
Python
65 lines
2.8 KiB
Python
"""Schemas for the Smart Onboarding Advisor — the onboarding RUNTIME step.
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DTOs only. The Advisor ORCHESTRATES the existing engines (Company 2A, RS-005, optimization,
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completeness) — no new reasoning engine, no new capability registry, no new meta-model. Welt-1
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discipline: a certificate yields PROBABLE capabilities (verification required), never "erfüllt".
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Python 3.9 compatible (no `|` unions).
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"""
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from __future__ import annotations
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from typing import List, Optional
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from pydantic import BaseModel, Field
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class OnboardingInput(BaseModel):
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company: str = ""
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industry: Optional[str] = None
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products: List[str] = Field(default_factory=list)
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markets: List[str] = Field(default_factory=list)
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certifications: List[str] = Field(default_factory=list)
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known_evidence: List[str] = Field(default_factory=list)
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target: List[str] = Field(default_factory=list) # informational; the delta uses injected requirements
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class InferredAssumption(BaseModel):
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certification: str
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capabilities: List[str] = Field(default_factory=list) # RELEVANT-to-target caps the cert probably provides
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verification_required: bool = True # Welt-1: never auto-satisfied
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statement: str = ""
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class RejectedAssumption(BaseModel):
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certification: Optional[str] = None
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statement: str = ""
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reason: str = "" # e.g. "relevance(evidence, target) = 0"
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class AdvisorQuestion(BaseModel):
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capability_id: str
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question_intent: str
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why: str # every question explains itself
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information_value: float = 0.0 # deterministic rank score
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priority: str = "medium"
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class AdvisorMeasure(BaseModel):
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capability_id: str
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leverage: int = 0
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closes: List[str] = Field(default_factory=list)
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class AdvisorResult(BaseModel):
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inferred_assumptions: List[InferredAssumption] = Field(default_factory=list)
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rejected_assumptions: List[RejectedAssumption] = Field(default_factory=list)
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auto_detected: List[str] = Field(default_factory=list) # detected (concrete artifact): recognised w/o asking
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indications: List[str] = Field(default_factory=list) # partial signal: raises assumption strength, STILL asked
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next_best_questions: List[AdvisorQuestion] = Field(default_factory=list) # max 5
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capability_delta: List[str] = Field(default_factory=list)
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top_measures: List[AdvisorMeasure] = Field(default_factory=list)
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evidence_requests: List[str] = Field(default_factory=list)
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unsupported_domains: List[str] = Field(default_factory=list)
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completeness_summary: str = ""
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headline: str = "" # "N erkannt, M wahrscheinlich abgedeckt, K zu klären"
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