app/schemas.py

"""
Pydantic schemas for YouTube analysis endpoints.
"""

from __future__ import annotations

from typing import Dict, List, Literal, Optional

from pydantic import BaseModel, Field


class YouTubeAnalyzeRequest(BaseModel):
    url: str = Field(..., description="YouTube video URL")
    include_raw: bool = Field(
        default=False,
        description="Include raw service responses in output",
    )


class YouTubeSource(BaseModel):
    url: str
    normalized_url: str
    video_id: str
    start_time_sec: Optional[int] = None
    title: Optional[str] = None
    duration_sec: Optional[float] = None
    audio_format: Optional[str] = None


class AnalysisSummary(BaseModel):
    """Summary of AI detection result."""

    is_ai_generated: bool
    confidence: float = Field(..., ge=0.0, le=1.0)
    decision_source: str
    model_version: str
    indicators: List[str]


class ServiceResult(BaseModel):
    available: bool
    response: Optional[Dict[str, object]] = None
    error: Optional[str] = None


class YouTubeAnalyzeResponse(BaseModel):
    request_id: str
    status: Literal["ok", "partial"]
    source: YouTubeSource
    summary: AnalysisSummary
    music_ai: ServiceResult
    ses_analizi: ServiceResult
    warnings: List[str]
    errors: List[str]
    timings: Dict[str, float]


class AudioAugmentationOptions(BaseModel):
    model_config = {"populate_by_name": True}

    pitch_shift: bool = Field(default=False, alias="pitchShift", description="Apply random pitch shifting")
    speed_change: bool = Field(default=False, alias="speedChange", description="Apply random speed change")
    bass_boost: bool = Field(default=False, alias="bassBoost", description="Apply bass boost equalization")
    trim_silence: bool = Field(default=False, alias="trimSilence", description="Trim leading and trailing silence")
    mix_audio: bool = Field(default=False, alias="mixAudio", description="Mix with a second uploaded audio track")
    add_noise: bool = Field(default=False, alias="addNoise", description="Add Gaussian noise")


AudioTargetFormat = Literal["wav", "mp3", "flac", "ogg"]


class AudioConvertOptions(BaseModel):
    model_config = {"populate_by_name": True}

    target_format: AudioTargetFormat = Field(
        default="wav", alias="targetFormat", description="Output container/codec to convert to"
    )
    bitrate_kbps: int = Field(
        default=192, alias="bitrateKbps", ge=64, le=320,
        description="Target bitrate for lossy formats (mp3/ogg); ignored for wav/flac"
    )


class DatasetEntryMetadata(BaseModel):
    model_config = {"populate_by_name": True}

    duration_sec: float = Field(alias="durationSec")
    tempo_bpm: float = Field(alias="tempoBpm")
    key: str
    loudness_db: float = Field(alias="loudnessDb")
    tags: List[str]


class DreamAnalysisRequest(BaseModel):
    dream_text: str = Field(..., alias="dreamText", min_length=1, max_length=4000)
    language: str = Field(default="English", description="Output language for the interpretation")

    model_config = {"populate_by_name": True}


class DreamAnalysisResponse(BaseModel):
    model_config = {"populate_by_name": True}

    emotions: List[str]
    themes: List[str]
    symbols: List[str]
    interpretation: str
    lucidity_indicator: bool = Field(alias="lucidityIndicator")


RemixCrossfadeCurve = Literal["equal_power", "linear"]


class RemixOptions(BaseModel):
    """Options for the Creator Studio AI Remix engine — auto tempo/key
    matching plus a crossfade blend between two uploaded tracks."""

    model_config = {"populate_by_name": True}

    match_tempo: bool = Field(
        default=True, alias="matchTempo",
        description="Time-stretch the second track to the first track's detected BPM"
    )
    match_key: bool = Field(
        default=False, alias="matchKey",
        description="Pitch-shift the second track to the first track's detected key"
    )
    crossfade_seconds: float = Field(
        default=4.0, alias="crossfadeSeconds", ge=0.5, le=30.0,
        description="Length of the crossfade transition between the two tracks"
    )
    crossfade_curve: RemixCrossfadeCurve = Field(
        default="equal_power", alias="crossfadeCurve",
        description="Crossfade power curve — equal_power avoids a volume dip at the midpoint"
    )


class RemixAnalysis(BaseModel):
    """Reports what the remix engine actually detected/did to each track,
    so the UI can show real numbers instead of a black box."""

    model_config = {"populate_by_name": True}

    track_a_bpm: float = Field(alias="trackABpm")
    track_b_bpm: float = Field(alias="trackBBpm")
    track_a_key: str = Field(alias="trackAKey")
    track_b_key: str = Field(alias="trackBKey")
    applied_stretch_rate: float = Field(alias="appliedStretchRate")
    applied_pitch_shift_semitones: float = Field(alias="appliedPitchShiftSemitones")
    output_duration_sec: float = Field(alias="outputDurationSec")


class MultitrackChannelSettings(BaseModel):
    """Per-track mix settings for the Creator Studio Multitrack mixer.
    Index-matched to the uploaded files (channel 0 -> first file, etc.)."""

    model_config = {"populate_by_name": True}

    gain_db: float = Field(
        default=0.0, alias="gainDb", ge=-60.0, le=12.0,
        description="Gain applied to this track before mixing, in dB"
    )
    pan: float = Field(
        default=0.0, ge=-1.0, le=1.0,
        description="Stereo position: -1.0 full left, 0.0 center, 1.0 full right"
    )
    muted: bool = Field(default=False, description="Exclude this track from the mix entirely")


class MultitrackOptions(BaseModel):
    model_config = {"populate_by_name": True}

    channels: List[MultitrackChannelSettings] = Field(
        default_factory=list,
        description="Per-track settings, index-matched to the uploaded files"
    )
    normalize_output: bool = Field(
        default=True, alias="normalizeOutput",
        description="Peak-normalize the final mix to prevent clipping"
    )


class MultitrackChannelReport(BaseModel):
    """What actually happened to one channel during mixdown."""

    model_config = {"populate_by_name": True}

    index: int
    duration_sec: float = Field(alias="durationSec")
    applied_gain_db: float = Field(alias="appliedGainDb")
    pan: float
    muted: bool
    peak_level: float = Field(alias="peakLevel")


class MultitrackAnalysis(BaseModel):
    model_config = {"populate_by_name": True}

    channels: List[MultitrackChannelReport]
    output_duration_sec: float = Field(alias="outputDurationSec")
    output_peak_level: float = Field(alias="outputPeakLevel")
    clipping_prevented: bool = Field(alias="clippingPrevented")