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| import gradio as gr | |
| import openai, subprocess | |
| import os | |
| # import config | |
| # openai.api_key = config.OPENAI_API_KEY | |
| messages = [{"role": "system", "content": 'You are a therapist. Respond to all input in 25 words or less.'}] | |
| def transcribe(key, audio): | |
| openai.api_key = key | |
| global messages | |
| audio_filename_with_extension = audio + '.wav' | |
| os.rename(audio, audio_filename_with_extension) | |
| audio_file = open(audio_filename_with_extension, "rb") | |
| transcript = openai.Audio.transcribe("whisper-1", audio_file) | |
| messages.append({"role": "user", "content": transcript["text"]}) | |
| response = openai.ChatCompletion.create(model="gpt-3.5-turbo", messages=messages) | |
| system_message = response["choices"][0]["message"] | |
| messages.append(system_message) | |
| #subprocess.call(["say", system_message['content']]) | |
| print("output: " + system_message['content'] + "\n") | |
| chat_transcript = "" | |
| for message in messages: | |
| if message['role'] != 'system': | |
| chat_transcript += message['role'] + ": " + message['content'] + "\n\n" | |
| return chat_transcript | |
| # ui = gr.Interface(fn=transcribe, inputs=["text", gr.Audio(source="microphone", type="filepath")], outputs="text").launch() | |
| keyTxt = gr.Textbox( | |
| show_label=True, | |
| placeholder=f"Your API-key...", | |
| type="password", | |
| visible=True, | |
| label="API-Key", | |
| ) | |
| ui = gr.Interface(fn=transcribe, inputs=[keyTxt, gr.Audio(source="microphone", type="filepath")], outputs="text").launch() | |
| ui.launch() | |