Tricoder/backend/app/services/stub_orchestrator_service.py

from app.schemas.observation import ObservationSummary
from app.schemas.orchestration import (
    Hypothesis,
    OrchestratorPlan,
    PlannedExperiment,
    PlannedNode,
    StopDecision,
)


class StubOrchestratorService:
    def create_initial_plan(self, observation: ObservationSummary) -> OrchestratorPlan:
        tags = set(observation.tags)
        looks_periodic = "periodic" in tags or observation.duration_ms >= 4500
        looks_mixed = "mixed" in tags

        hypotheses = [
            Hypothesis(
                id="periodic-alert-h1",
                label="Periodic alert tone",
                rationale=(
                    "Observation metadata and initial capture profile suggest a "
                    "repeatable alert-like signal rather than a diffuse ambient event."
                ),
                confidence=0.78 if looks_periodic else 0.56,
                related_signal_profiles=["periodic_pulse", "steady_tonal"],
            ),
            Hypothesis(
                id="mechanical-sequence-h2",
                label="Mechanical click sequence",
                rationale=(
                    "A secondary possibility is a short repeating mechanical event "
                    "pattern with less tonal stability."
                ),
                confidence=0.33 if looks_periodic else 0.48,
                related_signal_profiles=["multi_event_sequence", "transient_event"],
            ),
        ]

        if looks_mixed:
            hypotheses.append(
                Hypothesis(
                    id="mixed-source-h3",
                    label="Mixed source contamination",
                    rationale=(
                        "Capture tags indicate the possibility of overlapping sources, "
                        "which could distort classifier confidence."
                    ),
                    confidence=0.42,
                    related_signal_profiles=["mixed_source"],
                )
            )

        experiments = [
            PlannedExperiment(
                hypothesis_id="periodic-alert-h1",
                goal="Validate periodic repeat structure",
                preferred_chain_id="periodic_validation_chain",
                pipeline=[
                    PlannedNode(module_id="segment_repeat_based", params={}),
                    PlannedNode(
                        module_id="autocorrelation_period_check",
                        params={"window_ms": 1200},
                    ),
                    PlannedNode(
                        module_id="cepstrum_period_check",
                        params={"min_interval_ms": 200, "max_interval_ms": 1000},
                    ),
                ],
                expected_evidence=[
                    "repeat_interval_ms",
                    "repeat_stability",
                    "periodicity_confidence",
                ],
                stop_if=["repeat_stability >= 0.85"],
            ),
            PlannedExperiment(
                hypothesis_id="periodic-alert-h1",
                goal="Check tonal stability of the leading hypothesis",
                preferred_chain_id="harmonic_validation_chain",
                pipeline=[
                    PlannedNode(module_id="spectrogram_extract", params={}),
                    PlannedNode(
                        module_id="f0_tracking",
                        params={"frame_hop_ms": 20},
                    ),
                    PlannedNode(
                        module_id="harmonicity_check",
                        params={"harmonic_threshold": 0.65},
                    ),
                ],
                expected_evidence=[
                    "f0_track",
                    "harmonic_ratio",
                    "tonal_stability",
                ],
                stop_if=["tonal_stability >= 0.70"],
            ),
        ]

        if looks_mixed:
            experiments.append(
                PlannedExperiment(
                    hypothesis_id="mixed-source-h3",
                    goal="Check whether source separation improves confidence",
                    preferred_chain_id="mixed_source_chain",
                    pipeline=[
                        PlannedNode(module_id="denoise_basic", params={}),
                        PlannedNode(
                            module_id="source_separation_basic",
                            params={"max_sources": 2},
                        ),
                        PlannedNode(
                            module_id="reclassify_with_alt_window",
                            params={"window_ms": 800},
                        ),
                    ],
                    expected_evidence=[
                        "mixed_source_probability",
                        "post_separation_top_k",
                    ],
                    stop_if=["mixed_source_probability >= 0.60"],
                )
            )

        return OrchestratorPlan(
            hypotheses=hypotheses,
            experiments=experiments,
            stop_decision=StopDecision(
                should_stop=False,
                reason="Initial plan created. Probe and validation experiments should run first.",
            ),
            notes=[
                "Stub orchestrator generated a plan from observation metadata and tags.",
            ],
        )