Permission denied saving recordings in Flask app on Hugging Face Spaces ("[Errno 13] Permission denied: 'temp/recording_.mp3'")

Question

I'm encountering a "permission denied" error when saving recordings in my Flask app deployed on Hugging Face Spaces. I'd appreciate any guidance on resolving this issue.

Error message:

[Errno 13] Permission denied: 'temp/recording_.mp3'

Experimented with file paths: I attempted using absolute paths and different directory names to rule out path-related issues, but it didn't resolve the problem

Expected:

The audio_file.save(filename) function should successfully save the recording to the temp directory without any permission errors.

Actual Result:

The app throws a [Errno 13] Permission denied: 'temp/recording_.mp3' error when attempting to save the recording.

app/server.py:

import os
os.environ['TRANSFORMERS_CACHE'] = "./cache"
from flask import Flask, request, jsonify, render_template
from flask_cors import CORS
import random
import glob
from modules import Module


UPLOAD_DIR = 'temp'
model = Module()
model.warmup(UPLOAD_DIR)

app = Flask(__name__)
CORS(app)

# Set path to temporary directory

# Ensure directory exists
if not os.path.exists(UPLOAD_DIR):
  os.makedirs(UPLOAD_DIR)


@app.route('/')
def home():
  print("Entering home function...")
  return render_template('index.html')


@app.route('/save_recording', methods=['POST'])
def save_recording():
  try:
    print("Received POST request to save recording...")
    audio_file = request.files['audio']
    filename = os.path.join(UPLOAD_DIR, 'recording_' + '.mp3')
    audio_file.save(filename)
    

    # Optionally trigger prediction with saved filename
    text, emotion = generate(filename)
    print("Recording saved successfully")
    return jsonify({'status': 'success', 'filename': filename, 'text': text, 'emotion': emotion})
  except Exception as e:
    return jsonify({'status': 'error', 'message': str(e)})


@app.route('/generate', methods=['GET'])
def generate(filename=None):
  if not filename:
    # Get latest recording if filename not provided
    list_of_files = glob.glob(os.path.join(UPLOAD_DIR, '*.mp3'))
    latest_file = max(list_of_files, key=os.path.getctime) if list_of_files else None
    if not latest_file:
      return jsonify({'status': 'error', 'message': 'No recorded audio found'})
    filename = latest_file

  # Perform prediction using specified filename
  text, emotion = model.predict(audio_path=filename, upload_dir=UPLOAD_DIR)
  
  print("text:", text)
  print("emotion:", emotion)

  return jsonify({'status': 'success', 'text': text, 'emotion': emotion})


if __name__ == '__main__':
  app.run(debug=True, port=7860, host='0.0.0.0')

`

app/modules/init.py

import os
import time

from modules.emotion import Emotion
from modules.transcription import Transcription

transcription_model = os.getenv("TRANSCRIPTION_MODEL", "/models/distil-medium.en/")
emotion_model = os.getenv("EMOTION_MODEL", "/models/distilbert-base-uncased-go-emotions-student/")

transcription_obj = Transcription(model_name=transcription_model)
emotion_obj = Emotion(model_name=emotion_model)

class Module:
    
    def warmup(self, upload_dir: str):
        UPLOAD_DIR = '/home/adarsh/bardproject/app/temp' 
        text, emotion = self.predict(audio_path=os.path.join(upload_dir, 'recording_.mp3'), upload_dir=upload_dir)  # Pass upload_dir
        print("text: ", text)
        print("emotion: ", emotion)

    def predict(self, audio_path: str, upload_dir: str) -> str:
        """Loads audio, gets transcription and detects emotion
        Args:
            audio_path (str): path to the audio file
        Returns:
            str: emotion
        """
        print("Getting transcription...")
        start_time = time.time()
        if text := transcription_obj.transcribe(audio_path=audio_path):
            print("Text: ", text, time.time() - start_time)
            
            start_time = time.time()
            emotion = emotion_obj.detect_emotion(text=text)
            print("Emotion: ", emotion, time.time() - start_time)
            return text, emotion
        return None