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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([ | |
| # {"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, test): | |
| stringIn = test | |
| audio_file = open(audio, "rb") | |
| # Call the transcribe method with the file-like object | |
| transcript = openai.Audio.transcribe("whisper-1", audio_file) | |
| #msg_contents.append({"role": "user", "content": transcript["text"]}) | |
| #chat_transcript = "" | |
| #for message in msg_contents: | |
| # if (message["role"] != "system"): | |
| # chat_transcript += message["role"] + ": " + message["content"] + "\n\n" | |
| return transcript | |
| def botResponse(chat_log, msg_contents): | |
| response = openai.ChatCompletion.create( | |
| model="gpt-3.5-turbo", | |
| messages=msg_contents) | |
| system_message = response["choices"][0]["message"]["content"] | |
| msg_contents.append({"role": "assistant", "content": system_message}) | |
| chat_transcript = chat_log | |
| for message in msg_contents: | |
| if (message["role"] != "system"): | |
| chat_transcript += message["role"] + ": " + message["content"] + "\n\n" | |
| return system_message | |
| 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") | |
| submit2_btn = gr.Button(value="Bot Response") | |
| submit3_btn = gr.Button(value="Give Voice") | |
| with gr.Column(): | |
| #gpt_response = gr.Audio(label="Voice Response") | |
| gpt_transcript = gr.Text(label="Generate Transcript") | |
| gpt_transcript2 = gr.Text(label="Bot Response") | |
| gpt_response = gr.Audio(label="Voice Response") | |
| submit_btn.click(transcribe, inputs=[user_audio, "test"] outputs=gpt_transcript) | |
| demo.launch(share=False) |