MusicAnalyser/backend/app/main.py

from fastapi import FastAPI, Depends, HTTPException, BackgroundTasks, Query
from sqlalchemy.orm import Session, joinedload
from datetime import datetime, timedelta
from typing import List, Optional
from dotenv import load_dotenv

from .database import engine, Base, get_db
from .models import (
    PlayHistory as PlayHistoryModel,
    Track as TrackModel,
    AnalysisSnapshot,
)
from . import schemas
from .ingest import ingest_recently_played
from .services.stats_service import StatsService
from .services.narrative_service import NarrativeService

load_dotenv()

Base.metadata.create_all(bind=engine)

from fastapi.middleware.cors import CORSMiddleware

app = FastAPI(title="Music Analyser Backend")

app.add_middleware(
    CORSMiddleware,
    allow_origins=["http://localhost:5173", "http://localhost:8991"],
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)


@app.get("/")
def read_root():
    return {"status": "ok", "message": "Music Analyser API is running"}


@app.get("/history", response_model=List[schemas.PlayHistory])
def get_history(limit: int = 50, db: Session = Depends(get_db)):
    history = (
        db.query(PlayHistoryModel)
        .order_by(PlayHistoryModel.played_at.desc())
        .limit(limit)
        .all()
    )
    return history


@app.get("/tracks", response_model=List[schemas.Track])
def get_tracks(limit: int = 50, db: Session = Depends(get_db)):
    tracks = db.query(TrackModel).limit(limit).all()
    return tracks


@app.post("/trigger-ingest")
async def trigger_ingest(
    background_tasks: BackgroundTasks, db: Session = Depends(get_db)
):
    """Triggers Spotify ingestion in the background."""
    background_tasks.add_task(ingest_recently_played, db)
    return {"status": "Ingestion started in background"}


@app.post("/trigger-analysis")
def trigger_analysis(
    days: int = 30,
    model_name: str = "gpt-5-mini-2025-08-07",
    db: Session = Depends(get_db),
):
    """
    Runs the full analysis pipeline (Stats + LLM) for the last X days.
    Returns the computed metrics and narrative immediately.
    """
    try:
        end_date = datetime.utcnow()
        start_date = end_date - timedelta(days=days)

        # 1. Compute Stats
        stats_service = StatsService(db)
        stats_json = stats_service.generate_full_report(start_date, end_date)

        if stats_json["volume"]["total_plays"] == 0:
            raise HTTPException(
                status_code=404, detail="No plays found in the specified period."
            )

        narrative_service = NarrativeService(model_name=model_name)
        narrative_json = narrative_service.generate_full_narrative(stats_json)

        # 3. Save Snapshot
        snapshot = AnalysisSnapshot(
            period_start=start_date,
            period_end=end_date,
            period_label=f"last_{days}_days",
            metrics_payload=stats_json,
            narrative_report=narrative_json,
            model_used=model_name,
        )
        db.add(snapshot)
        db.commit()
        db.refresh(snapshot)

        return {
            "status": "success",
            "snapshot_id": snapshot.id,
            "period": {"start": start_date, "end": end_date},
            "metrics": stats_json,
            "narrative": narrative_json,
        }

    except HTTPException:
        raise  # Re-raise HTTPExceptions as-is (404, etc.)
    except Exception as e:
        print(f"Analysis Failed: {e}")
        raise HTTPException(status_code=500, detail=str(e))


@app.get("/snapshots")
def get_snapshots(limit: int = 10, db: Session = Depends(get_db)):
    return (
        db.query(AnalysisSnapshot)
        .order_by(AnalysisSnapshot.date.desc())
        .limit(limit)
        .all()
    )


@app.get("/listening-log")
def get_listening_log(
    days: int = Query(default=7, ge=1, le=365),
    limit: int = Query(default=200, ge=1, le=1000),
    db: Session = Depends(get_db),
):
    end_date = datetime.utcnow()
    start_date = end_date - timedelta(days=days)

    plays = (
        db.query(PlayHistoryModel)
        .options(joinedload(PlayHistoryModel.track))
        .filter(
            PlayHistoryModel.played_at >= start_date,
            PlayHistoryModel.played_at <= end_date,
        )
        .order_by(PlayHistoryModel.played_at.desc())
        .limit(limit)
        .all()
    )

    result = []
    for i, play in enumerate(plays):
        track = play.track
        listened_ms = play.listened_ms
        skipped = play.skipped

        if listened_ms is None and i < len(plays) - 1:
            next_play = plays[i + 1]
            diff_seconds = (play.played_at - next_play.played_at).total_seconds()
            if track and track.duration_ms:
                duration_sec = track.duration_ms / 1000.0
                listened_ms = int(min(diff_seconds, duration_sec) * 1000)
                skipped = diff_seconds < 30

        result.append(
            {
                "id": play.id,
                "track_id": play.track_id,
                "track_name": track.name if track else "Unknown",
                "artist": track.artist if track else "Unknown",
                "album": track.album if track else "Unknown",
                "image": track.image_url if track else None,
                "played_at": play.played_at.isoformat(),
                "duration_ms": track.duration_ms if track else 0,
                "listened_ms": listened_ms,
                "skipped": skipped,
                "context_uri": play.context_uri,
                "source": play.source,
            }
        )

    return {
        "plays": result,
        "period": {"start": start_date.isoformat(), "end": end_date.isoformat()},
    }


@app.get("/sessions")
def get_sessions(
    days: int = Query(default=7, ge=1, le=365), db: Session = Depends(get_db)
):
    end_date = datetime.utcnow()
    start_date = end_date - timedelta(days=days)

    stats_service = StatsService(db)
    session_stats = stats_service.compute_session_stats(start_date, end_date)

    return {
        "sessions": session_stats.get("session_list", []),
        "summary": {
            "count": session_stats.get("count", 0),
            "avg_minutes": session_stats.get("avg_minutes", 0),
            "micro_rate": session_stats.get("micro_session_rate", 0),
            "marathon_rate": session_stats.get("marathon_session_rate", 0),
        },
    }