Spaces:
Running
Running
File size: 1,825 Bytes
b3b0738 5ea2a93 b3b0738 efbb364 1ef1929 b3b0738 efbb364 b3b0738 bb1f1b6 b5d3f3a 9a48a5d b3b0738 21bcfae b3b0738 98c64ba b3b0738 f0b4a59 0b794cc b3b0738 0b794cc b3b0738 50f2112 b3b0738 1ef1929 98c64ba 8fac9c0 1ef1929 98c64ba ace94cb b3b0738 99c65a9 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 |
import os
import gradio as gr
import openai
from gtts import gTTS
openai.api_key = os.environ["OPEN_AI_KEY"]
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):
response = openai.ChatCompletion.create(
model="gpt-3.5-turbo",
#messages=user_input)
messages=[
{"role": "system", "content": "You are a therapist. Respond in less than 5 sentences."},
{"role": "user", "content": user_input}
]
)
system_message = response["choices"][0]["message"]["content"]
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
def keepLog(gpt):
return "gpt"
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="GPT Transcript")
gpt_voice = gr.Audio(label="Voice Response")
chat_log = gr.Text(label="Chat Log")
submit_btn.click(transcribe, inputs=user_audio, outputs=user_transcript)
user_transcript.change(botResponse, inputs=user_transcript, outputs=gpt_transcript)
gpt_transcript.change(giveVoice, inputs=gpt_transcript, outputs=gpt_voice)
gpt_voice.change(keepLog, inputs=user_transcript, outputs=chat_log)
demo.launch(share=False) |