mirror of
https://github.com/bnair123/MusicAnalyser.git
synced 2026-02-25 11:46:07 +00:00
a97997a17a
- Created FastAPI backend structure. - Implemented Spotify Recently Played ingestion logic. - Set up SQLite database with SQLAlchemy models. - Added AI Service using Google Gemini. - Created helper scripts for auth and background worker. - Added Dockerfile and GitHub Actions workflow.
37 lines
1.2 KiB
Python
37 lines
1.2 KiB
Python
from fastapi import FastAPI, Depends
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from sqlalchemy.orm import Session
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from .database import engine, Base, get_db
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from .models import PlayHistory as PlayHistoryModel, Track as TrackModel
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from . import schemas
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from .ingest import ingest_recently_played
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import asyncio
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from typing import List
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from dotenv import load_dotenv
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load_dotenv()
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# Create tables
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Base.metadata.create_all(bind=engine)
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app = FastAPI(title="Music Analyser Backend")
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@app.get("/")
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def read_root():
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return {"status": "ok", "message": "Music Analyser API is running"}
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@app.get("/history", response_model=List[schemas.PlayHistory])
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def get_history(limit: int = 50, db: Session = Depends(get_db)):
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history = db.query(PlayHistoryModel).order_by(PlayHistoryModel.played_at.desc()).limit(limit).all()
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return history
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@app.post("/trigger-ingest")
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async def trigger_ingest(db: Session = Depends(get_db)):
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"""Manually trigger the ingestion process (useful for testing)"""
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await ingest_recently_played(db)
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return {"status": "Ingestion triggered"}
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@app.get("/tracks", response_model=List[schemas.Track])
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def get_tracks(limit: int = 50, db: Session = Depends(get_db)):
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tracks = db.query(TrackModel).limit(limit).all()
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return tracks
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