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+from flask import Flask, request, send_from_directory, render_template
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+import speech_recognition as sr
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+import openai
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+import os
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+import json
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+import tiktoken
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+from gtts import gTTS
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+import uuid
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+import subprocess
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+
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+from pydub import AudioSegment
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+
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+# from OpenSSL import SSL
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+
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+app = Flask(__name__)
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+app.config['UPLOAD_FOLDER'] = "files"
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+PROJECT_ABSPATH = os.path.abspath(".")
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+WAV2LIP_ABSPATH = "/home/maronakins/Documents/Wav2Lip"
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+# ALLOWED_EXTENSIONS = {'mp3', 'wav'}
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+
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+# context = SSL.Context(SSL.TLSv1_2_METHOD)
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+# context.load_cert_chain('certificate.crt', 'private.key')
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+
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+
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+with open('open_ai_key') as f:
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+ openai.api_key = f.readline()
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+
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+chat_messages = [
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+ {"role": "system", "content": "Kamu adalah asisten yang baik hati, tapi jawaban nya jangan panjang-panjang ya"}
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+]
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+
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+encoding = tiktoken.encoding_for_model("gpt-3.5-turbo")
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+
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+
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+def verify_token(token):
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+ # Verify that the token is valid (e.g. by checking against a database)
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+ return True
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+
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+
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+@app.route('/', methods=['GET', 'POST'])
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+def index():
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+ if request.method == 'GET':
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+ return render_template("index.html")
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+ else:
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+ return "Unsupported request", 415
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+
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+
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+@app.route('/process', methods=['POST'])
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+def process_input():
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+ if request.is_json:
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+ msg_json = request.get_json(force=True)
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+ print(msg_json)
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+ else:
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+ return "Unsupported request", 415
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+ # result = process_input(msg_json)
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+ # Verify the token
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+ # token = request.headers.get('Authorization')
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+ # if not verify_token(token):
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+ # return 'Invalid token', 401
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+
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+ req_id = str(uuid.uuid4())
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+ use_video = True if msg_json["use_video"] == "1" else False
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+ print(msg_json)
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+ payload = msg_json["payload"]
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+ msg = chat_messages.copy()
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+ for i in payload:
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+ msg.append(i)
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+ print(msg)
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+ completed = False
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+ completion = None
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+ chat_response = ""
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+ while not completed:
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+ try:
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+ completion = openai.ChatCompletion.create(
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+ model="gpt-3.5-turbo",
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+ messages=msg,
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+ max_tokens=400
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+ )
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+ chat_response = completion.choices[0].message.content
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+ completed = True
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+ except openai.error.RateLimitError as e:
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+ pass
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+ print(f'{completion["usage"]["prompt_tokens"]} prompt tokens counted by the OpenAI API.')
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+ print(f'{completion["usage"]["completion_tokens"]} completion tokens counted by the OpenAI API.')
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+ print(f'{completion["usage"]["total_tokens"]} total tokens counted by the OpenAI API.')
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+ print(f'ChatGPT: {chat_response}')
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+ language = 'id'
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+ myobj = gTTS(text=chat_response, lang=language, slow=False)
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+ audio_filename = f"chat-{req_id}.mp3"
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+ video_filename = ""
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+ myobj.save(os.path.join(app.config["UPLOAD_FOLDER"], audio_filename))
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+ try:
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+ if use_video:
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+ video_filename = f"video-{req_id}.mp4"
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+ wavlip_python = os.path.join(WAV2LIP_ABSPATH, "venv", "bin", "python")
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+ wavlip_pyfile = os.path.join(WAV2LIP_ABSPATH, "inference.py")
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+ wavlip_checkpoint = os.path.join(WAV2LIP_ABSPATH, "checkpoints", "wav2lip_gan.pth")
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+ wavlip_temp = os.path.join(WAV2LIP_ABSPATH, "temp")
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+ wavlip_face = os.path.join(WAV2LIP_ABSPATH, "ganjarstill.mp4")
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+ wavlip_audio = os.path.join(PROJECT_ABSPATH, "files", audio_filename)
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+ wavlip_outfile = os.path.join(PROJECT_ABSPATH, "files", video_filename)
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+ subprocess.run([wavlip_python, wavlip_pyfile,
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+ "--checkpoint_path", wavlip_checkpoint,
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+ "--temp", wavlip_temp,
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+ "--face_det_batch_size", "64", "--resize_factor", "2",
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+ "--face", wavlip_face,
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+ "--audio", wavlip_audio,
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+ "--outfile", wavlip_outfile], check=True)
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+ except Exception as e:
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+ print(str(e))
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+ video_filename = ""
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+ return {"role": "assistant", "content": f'{chat_response}', "audio": audio_filename, "video": video_filename}
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+
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+
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+@app.route('/files/<filename>', methods=["GET"])
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+def files(filename):
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+ return send_from_directory(directory=app.config["UPLOAD_FOLDER"], path=filename)
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+
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+
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+if __name__ == '__main__':
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+ app.run(debug=True, host='0.0.0.0', port=46294)
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+ # app.run(debug=True, host='0.0.0.0', port=8080, ssl_context=context)
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