Delete app.py

app.py

@@ -1,57 +0,0 @@
-from flask import Flask, request, jsonify
-from transformers import Wav2Vec2ForCTC, Wav2Vec2Tokenizer, pipeline
-from pydub import AudioSegment
-import torch
-import torchaudio
-from datetime import datetime, time
-import pytz
-
-app = Flask(__name__)
-
-# Load speech recognition model and tokenizer
-tokenizer = Wav2Vec2Tokenizer.from_pretrained("facebook/wav2vec2-base-960h")
-model = Wav2Vec2ForCTC.from_pretrained("facebook/wav2vec2-base-960h")
-
-# Load translation model explicitly
-translation_model = "Helsinki-NLP/opus-mt-en-hi"
-translation_pipeline = pipeline("translation", model=translation_model)
-
-# Function to preprocess audio
-def preprocess_audio(audio_file):
-    audio = AudioSegment.from_file(audio_file)
-    audio = audio.set_frame_rate(16000)
-    audio.export("processed.wav", format="wav")
-    waveform, sample_rate = torchaudio.load("processed.wav")
-    return waveform
-
-# Function to check if the current time is after 6 PM IST
-def is_after_6pm_ist():
-    ist = pytz.timezone('Asia/Kolkata')
-    current_time = datetime.now(ist).time()
-    return current_time >= time(18, 0)
-
-@app.route('/translate', methods=['POST'])
-def translate():
-    if not is_after_6pm_ist():
-        return jsonify({"error": "Service is available only after 6 PM IST"}), 403
-
-    if 'audio' not in request.files:
-        return jsonify({"error": "No audio file provided"}), 400
-
-    audio_file = request.files['audio']
-    waveform = preprocess_audio(audio_file)
-    
-    input_values = tokenizer(waveform.squeeze().numpy(), return_tensors="pt").input_values
-    logits = model(input_values).logits
-    predicted_ids = torch.argmax(logits, dim=-1)
-    transcription = tokenizer.batch_decode(predicted_ids)[0]
-
-    translation = translation_pipeline(transcription)
-    translated_text = translation[0]['translation_text']
-
-    return jsonify({"transcription": transcription, "translation": translated_text})
-
-if __name__ == '__main__':
-    app.run(debug=True, host='0.0.0.0', port=8080)
-
-