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| import os | |
| import gradio as gr | |
| import openai | |
| from gtts import gTTS | |
| openai.api_key = os.environ["OPEN_AI_KEY"] | |
| messages = gr.State(value=[{"role": "system", "content": "You are a therapist. Respond in less than 5 sentences."}]) | |
| #messages = [{"role": "system", "content": "You are a therapist. Respond in less than 5 sentences."}] | |
| def transcribe(audio): | |
| audio_file = open(audio, "rb") | |
| # Call the transcribe method with the file-like object | |
| transcript = openai.Audio.transcribe("whisper-1", audio_file) | |
| return transcript["text"] | |
| def botResponse(user_input, messages): | |
| #global messages | |
| #messages = msg_contents | |
| messages.append({"role": "user", "content": user_input}) | |
| response = openai.ChatCompletion.create( | |
| model="gpt-3.5-turbo", | |
| messages=messages | |
| ) | |
| system_message = response["choices"][0]["message"]["content"] | |
| messages.append({"role": "assistant", "content": system_message}) | |
| chat_transcript = "" | |
| for message in messages: | |
| if (message["role"] != "system"): | |
| chat_transcript += message["role"] + ": " + message["content"] + "\n\n" | |
| return chat_transcript | |
| def giveVoice(bot_message): | |
| myobj = gTTS(text=bot_message) | |
| myobj.save("temp.mp3") | |
| dir = os.getcwd() | |
| new_path = os.path.join(dir, "temp.mp3") | |
| return new_path | |
| with gr.Blocks() as demo: | |
| with gr.Row(): | |
| with gr.Column(): | |
| user_audio = gr.Audio(source="microphone", type="filepath", label="Input Phrase") | |
| submit_btn = gr.Button(value="Transcribe") | |
| with gr.Column(): | |
| user_transcript = gr.Text(label="User Transcript") | |
| gpt_transcript = gr.Text(label="Chat Transcript") | |
| gpt_voice = gr.Audio(label="Voice Response") | |
| submit_btn.click(transcribe, inputs=user_audio, outputs=user_transcript) | |
| #user_transcript.change(botResponse, inputs=[user_transcript, messages], outputs=gpt_transcript) | |
| gpt_transcript.change(giveVoice, inputs=gpt_transcript, outputs=gpt_voice) | |
| demo.launch(share=False) |