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from fastapi import FastAPI, Query
import asyncio
import uvicorn
import os
from tracks import get_top_tracks_for_user, get_users_with_track_interactions
from recommender import get_recommendations_for_user
# custom_accuracy needs to be imported to the global namespace for Learner to load
from learner import setup_learner, custom_accuracy
app = FastAPI()
model_filename = 'data/model.pkl'
learn = None
@app.on_event("startup")
async def startup_event():
global learn
tasks = [asyncio.ensure_future(setup_learner(model_filename))] # assign some task
learn = (await asyncio.gather(*tasks))[0]
@app.get("/users")
async def get_users(limit: int = Query(10)):
return get_users_with_track_interactions(limit=limit)
@app.get('/users/{user_id}')
async def get_user_track_history(user_id: str, limit:int = Query(5)):
user_history = get_top_tracks_for_user(user_id, limit)
return {"user_id": user_id, "history": user_history}
@app.get("/recommend/{user_id}")
async def get_recommendations(user_id: str, limit: int = Query(5)):
return get_recommendations_for_user(learn, user_id, limit)
if __name__ == "__main__":
uvicorn.run(app, host="0.0.0.0", port=int(os.getenv("PORT", 7860)))
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