67 lines
1.9 KiB
Python
67 lines
1.9 KiB
Python
import json
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import tempfile
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import requests
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from flask import request, Flask
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app = Flask(__name__)
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# .WAV (i.e.) FILE REQUEST
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@app.route("/process_audio_request_file", methods=['POST'])
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def process_audio_request_android():
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print("[" + request.remote_addr + "] - New STT request")
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audio_temp_file = tempfile.NamedTemporaryFile(prefix='jarvis-audio_', suffix='_client')
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audio_temp_file.write(request.data)
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print(audio_temp_file.name)
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return {"transcription": text_recognition_whisperasr(audio_temp_file.name), "answer": "WIP"}
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# send request to whisper-asr server (docker)
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def text_recognition_whisperasr(audio_file):
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headers = {
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'accept': 'application/json',
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# 'Content-Type': 'multipart/form-data',
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}
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params = {
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'task': 'transcribe',
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# TODO: add to config
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'language': 'fr',
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'output': 'json',
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}
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files = {
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'audio_file': open(audio_file, 'rb'),
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}
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# TODO: add to config
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response = requests.post('https://whisper.broillet.ch/asr', params=params, headers=headers, files=files)
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return json.loads(response.text)['text']
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# NOT IMPLEMENTED RIGHT NOW / to use with local whisper cpp (cpu)
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"""
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def local_recognition(audio_file, time_of_request):
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path = os.path.dirname(get_path_file.__file__)
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print("Loading model and recognition")
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model = path + "/whisper/models/" + "ggml-small.bin"
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os.system(path + "/whisper/main -l fr -t 8 -m " + model + " -f " + audio_file + " -otxt") # + "> /dev/null 2>&1")
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output = open(audio_file + ".txt").read()
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# time_of_resolution = time.perf_counter()
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# print(output + f" - {time_of_resolution - time_of_request:0.4f} seconds")
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return jsonify(transcription=output, time=5, answer="WIP...")
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"""
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def start_server():
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app.config['JSON_AS_ASCII'] = False
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# TODO: add to config
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app.run(port=5000, debug=False, host='0.0.0.0', threaded=True)
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