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import os, time, wave
import openai
import gradio as gr
import requests
from pydub import AudioSegment as am
from xml.etree import ElementTree
api_base = "https://mvp-azureopenai.openai.azure.com/"
api_key = os.getenv("OPENAI_API_KEY")
openai.api_type = "azure"
openai.api_base = api_base
openai.api_version = "2023-03-15-preview"
openai.api_key = api_key
messages_gpt = []
messages_chat = [
{"role": "system", "content": "You are an AI assistant that helps people find information."},
]
prompts = ""
response_walle = []
messages_vchat = [
{"role": "system", "content": "You are an AI assistant that helps people find information and just response with SSML."},
]
with gr.Blocks() as page:
with gr.Tabs():
with gr.TabItem("GPT Playgroud"):
ui_chatbot_gpt = gr.Chatbot(label="GPT Playground:")
with gr.Row():
with gr.Column(scale=0.9):
ui_prompt_gpt = gr.Textbox(placeholder="Please enter your prompt here.", show_label=False).style(container=False)
with gr.Column(scale=0.1, min_width=100):
ui_clear_gpt = gr.Button("Clear Input", )
with gr.Accordion("Expand to config parameters:", open=False):
gr.Markdown("Look at me...")
with gr.Row():
ui_temp_gpt = gr.Slider(0.1, 1.0, 0.9, step=0.1, label="Temperature", interactive=True)
ui_max_tokens_gpt = gr.Slider(100, 4000, 1000, step=100, label="Max Tokens", interactive=True)
ui_top_p_gpt = gr.Slider(0.1, 1.0, 0.5, step=0.1, label="Top P", interactive=True)
with gr.Accordion("Select radio button to see detail:", open=False):
ui_res_radio_gpt = gr.Radio(["Response from OpenAI Model", "Prompt messages history"], label="Show OpenAI response:", interactive=True)
ui_response_gpt = gr.TextArea(show_label=False, interactive=False).style(container=False)
def get_parameters_gpt(slider_1, slider_2, slider_3):
ui_temp_gpt.value = slider_1
ui_max_tokens_gpt.value = slider_2
ui_top_p_gpt.value = slider_3
print("Log - Updated GPT parameters: Temperature=", ui_temp_gpt.value,
" Max Tokens=", ui_max_tokens_gpt.value, " Top_P=", ui_top_p_gpt.value)
def select_response_gpt(radio):
if radio == "Response from OpenAI Model":
return gr.update(value=gpt_x)
else:
return gr.update(value=messages_gpt)
def user_gpt(user_message, history):
global prompts
prompts = user_message
messages_gpt.append(prompts)
return "", history + [[user_message, None]]
def bot_gpt(history):
global gpt_x
gpt_x = openai.Completion.create(
engine="mvp-text-davinci-003",
prompt=prompts,
temperature=0.6,
max_tokens=1000,
top_p=1,
frequency_penalty=0,
presence_penalty=0,
best_of=1,
stop=None
)
gpt_reply = gpt_x.choices[0].text
messages_gpt.append(gpt_reply)
history[-1][1] = gpt_reply
return history
ui_temp_gpt.change(get_parameters_gpt, [ui_temp_gpt, ui_max_tokens_gpt, ui_top_p_gpt])
ui_max_tokens_gpt.change(get_parameters_gpt, [ui_temp_gpt, ui_max_tokens_gpt, ui_top_p_gpt])
ui_top_p_gpt.change(get_parameters_gpt, [ui_temp_gpt, ui_max_tokens_gpt, ui_top_p_gpt])
ui_prompt_gpt.submit(user_gpt, [ui_prompt_gpt, ui_chatbot_gpt], [ui_prompt_gpt, ui_chatbot_gpt], queue=False).then(
bot_gpt, ui_chatbot_gpt, ui_chatbot_gpt
)
ui_clear_gpt.click(lambda: None, None, ui_chatbot_gpt, queue=False)
ui_res_radio_gpt.change(select_response_gpt, ui_res_radio_gpt, ui_response_gpt)
with gr.TabItem("ChatGPT"):
ui_chatbot_chat = gr.Chatbot(label="ChatGPT:")
with gr.Row():
with gr.Column(scale=0.9):
ui_prompt_chat = gr.Textbox(placeholder="Please enter your prompt here.", show_label=False).style(container=False)
with gr.Column(scale=0.1, min_width=100):
ui_clear_chat = gr.Button("Clear Chat")
with gr.Blocks():
with gr.Accordion("Expand to config parameters:", open=False):
gr.Markdown("Here is the default system prompt, you can change it to your own prompt.")
ui_prompt_sys = gr.Textbox(value="You are an AI assistant that helps people find information.", show_label=False, interactive=True).style(container=False)
with gr.Row():
ui_temp_chat = gr.Slider(0.1, 1.0, 0.7, step=0.1, label="Temperature", interactive=True)
ui_max_tokens_chat = gr.Slider(100, 8000, 800, step=100, label="Max Tokens", interactive=True)
ui_top_p_chat = gr.Slider(0.05, 1.0, 0.9, step=0.1, label="Top P", interactive=True)
with gr.Accordion("Select radio button to see detail:", open=False):
ui_res_radio_chat = gr.Radio(["Response from OpenAI Model", "Prompt messages history"], label="Show OpenAI response:", interactive=True)
ui_response_chat = gr.TextArea(show_label=False, interactive=False).style(container=False)
def get_parameters_chat(slider_1, slider_2, slider_3):
ui_temp_chat.value = slider_1
ui_max_tokens_chat.value = slider_2
ui_top_p_chat.value = slider_3
print("Log - Updated chatGPT parameters: Temperature=", ui_temp_chat.value,
" Max Tokens=", ui_max_tokens_chat.value, " Top_P=", ui_top_p_chat.value)
def select_response_chat(radio):
if radio == "Response from OpenAI Model":
return gr.update(value=chat_x)
else:
return gr.update(value=messages_chat)
def user_chat(user_message, history):
messages_chat.append({"role": "user", "content": user_message})
return "", history + [[user_message, None]]
def bot_chat(history):
global chat_x
chat_x = openai.ChatCompletion.create(
engine="mvp-gpt-35-turbo", messages=messages_chat,
temperature=ui_temp_chat.value,
max_tokens=ui_max_tokens_chat.value,
top_p=ui_top_p_chat.value,
frequency_penalty=0,
presence_penalty=0,
stop=None
)
ui_response_chat.value= chat_x
print(ui_response_chat.value)
chat_reply = chat_x.choices[0].message.content
messages_chat.append({"role": "assistant", "content": chat_reply})
history[-1][1] = chat_reply
return history
def reset_sys(sysmsg):
global messages_chat
messages_chat = [
{"role": "system", "content": sysmsg},
]
ui_res_radio_chat.change(select_response_chat, ui_res_radio_chat, ui_response_chat)
ui_temp_chat.change(get_parameters_chat, [ui_temp_chat, ui_max_tokens_chat, ui_top_p_chat])
ui_max_tokens_chat.change(get_parameters_chat, [ui_temp_chat, ui_max_tokens_chat, ui_top_p_chat])
ui_top_p_chat.change(get_parameters_chat, [ui_temp_chat, ui_max_tokens_chat, ui_top_p_chat])
ui_prompt_sys.submit(reset_sys, ui_prompt_sys)
ui_prompt_chat.submit(user_chat, [ui_prompt_chat, ui_chatbot_chat], [ui_prompt_chat, ui_chatbot_chat], queue=False).then(
bot_chat, ui_chatbot_chat, ui_chatbot_chat
)
ui_clear_chat.click(lambda: None, None, ui_chatbot_chat, queue=False).then(reset_sys, ui_prompt_sys)
with gr.TabItem("WALL路E 2"):
ui_prompt_walle = gr.Textbox(placeholder="Please enter your prompt here to generate image.", show_label=False).style(container=False)
ui_image_walle = gr.Image()
with gr.Accordion("Select radio button to see detail:", open=False):
ui_response_walle = gr.TextArea(show_label=False, interactive=False).style(container=False)
def get_image_walle(prompt_walle):
global response_walle
walle_api_version = '2022-08-03-preview'
url = "{}dalle/text-to-image?api-version={}".format(api_base, walle_api_version)
headers= { "api-key": api_key, "Content-Type": "application/json" }
body = {
"caption": prompt_walle,
"resolution": "1024x1024"
}
submission = requests.post(url, headers=headers, json=body)
response_walle.append(submission.json())
print("Log - WALL路E status: {}".format(submission.json()))
operation_location = submission.headers['Operation-Location']
retry_after = submission.headers['Retry-after']
status = ""
while (status != "Succeeded"):
time.sleep(int(retry_after))
response = requests.get(operation_location, headers=headers)
response_walle.append(response.json())
print("Log - WALL路E status: {}".format(response.json()))
status = response.json()['status']
image_url_walle = response.json()['result']['contentUrl']
return gr.update(value=image_url_walle)
def get_response_walle():
global response_walle
return gr.update(value=response_walle)
ui_prompt_walle.submit(get_image_walle, ui_prompt_walle, ui_image_walle, queue=False).then(get_response_walle, None, ui_response_walle)
with gr.TabItem("VoiceChat"):
with gr.Row():
with gr.Column():
with gr.Accordion("Expand to config parameters:", open=False):
ui_prompt_sys_vchat = gr.Textbox(value="You are an AI assistant that helps people find information and just response with SSML.", show_label=False, interactive=True).style(container=False)
ui_voice_inc_vchat = gr.Audio(source="microphone", type="filepath")
ui_voice_out_vchat = gr.Audio(value=None, type="filepath", interactive=False).style(container=False)
with gr.Accordion("Expand to config parameters:", open=False):
with gr.Row():
ui_temp_vchat = gr.Slider(0.1, 1.0, 0.7, step=0.1, label="Temperature", interactive=True)
ui_max_tokens_vchat = gr.Slider(100, 8000, 800, step=100, label="Max Tokens", interactive=True)
ui_top_p_vchat = gr.Slider(0.05, 1.0, 0.9, step=0.1, label="Top P", interactive=True)
with gr.Column():
ui_chatbot_vchat = gr.Chatbot(label="Voice to ChatGPT:")
with gr.Accordion("Select radio button to see detail:", open=False):
ui_res_radio_vchat = gr.Radio(["Response from OpenAI Model", "Prompt messages history"], label="Show OpenAI response:", interactive=True)
ui_response_vchat = gr.TextArea(show_label=False, interactive=False).style(container=False)
def get_parameters_vchat(slider_1, slider_2, slider_3):
ui_temp_vchat.value = slider_1
ui_max_tokens_vchat.value = slider_2
ui_top_p_vchat.value = slider_3
print("Log - Updated chatGPT parameters: Temperature=", ui_temp_vchat.value,
" Max Tokens=", ui_max_tokens_vchat.value, " Top_P=", ui_top_p_vchat.value)
def select_response_vchat(radio):
if radio == "Response from OpenAI Model":
return gr.update(value=vchat_x)
else:
return gr.update(value=messages_vchat)
def speech_to_text(voice_message):
# Downsample input voice to 16kHz
voice_wav = am.from_file(voice_message, format='wav')
voice_wav = voice_wav.set_frame_rate(16000)
voice_wav.export(voice_message, format='wav')
# STT
OASK_Speech = os.getenv("OASK_Speech")
service_region = "westus"
base_url = "https://"+service_region+".stt.speech.microsoft.com/"
path = 'speech/recognition/conversation/cognitiveservices/v1'
constructed_url = base_url + path
params = {
'language': 'zh-CN',
'format': 'detailed'
}
headers = {
'Ocp-Apim-Subscription-Key': OASK_Speech,
'Content-Type': 'audio/wav; codecs=audio/pcm; samplerate=16000',
'Accept': 'application/json;text/xml'
}
body = open(voice_message,'rb').read()
response = requests.post(constructed_url, params=params, headers=headers, data=body)
if response.status_code == 200:
rs = response.json()
if rs != '':
print(rs)
else:
print("\nLog - Status code: " + str(response.status_code) + "\nSomething went wrong. Check your subscription key and headers.\n")
print("Reason: " + str(response.reason) + "\n")
sst_text = rs['DisplayText']
return sst_text
def text_to_speech():
OASK_Speech = os.getenv("OASK_Speech")
service_region = "westus"
base_url = "https://"+service_region+".tts.speech.microsoft.com/"
path = 'cognitiveservices/v1'
constructed_url = base_url + path
headers = {
'Ocp-Apim-Subscription-Key': OASK_Speech,
'Content-Type': 'application/ssml+xml',
'X-Microsoft-OutputFormat': 'riff-24khz-16bit-mono-pcm',
'User-Agent': 'Voice ChatGPT'
}
xml_body = ElementTree.Element('speak', version='1.0')
xml_body.set('{http://www.w3.org/XML/1998/namespace}lang', 'zh-cn')
voice = ElementTree.SubElement(xml_body, 'voice')
voice.set('{http://www.w3.org/XML/1998/namespace}lang', 'zh-cn')
voice.set('name', 'zh-CN-XiaoxiaoNeural')
voice.text = vchat_reply
body = ElementTree.tostring(xml_body)
response = requests.post(constructed_url, headers=headers, data=body)
if response.status_code == 200:
with open('chatgpt.wav', 'wb') as audio:
audio.write(response.content)
print("\nStatus code: " + str(response.status_code) + "\nYour TTS is ready for playback.\n")
else:
print("\nStatus code: " + str(response.status_code) + "\nSomething went wrong. Check your subscription key and headers.\n")
print("Reason: " + str(response.reason) + "\n")
tts_file = "chatgpt.wav"
return gr.update(value=tts_file, interactive=True)
def user_vchat(user_voice_message, history):
user_message = speech_to_text(user_voice_message)
messages_vchat.append({"role": "user", "content": user_message})
return history + [[user_message, None]]
def bot_vchat(history):
global vchat_x, vchat_reply
vchat_x = openai.ChatCompletion.create(
engine="mvp-gpt-35-turbo", messages=messages_vchat,
temperature=ui_temp_chat.value,
max_tokens=ui_max_tokens_chat.value,
top_p=ui_top_p_chat.value,
frequency_penalty=0,
presence_penalty=0,
stop=None
)
ui_response_vchat.value= vchat_x
print(ui_response_vchat.value)
vchat_reply = vchat_x.choices[0].message.content
messages_vchat.append({"role": "assistant", "content": vchat_reply})
history[-1][1] = vchat_reply
return history
ui_res_radio_chat.change(select_response_chat, ui_res_radio_chat, ui_response_chat)
ui_temp_chat.change(get_parameters_chat, [ui_temp_chat, ui_max_tokens_chat, ui_top_p_chat])
ui_max_tokens_chat.change(get_parameters_chat, [ui_temp_chat, ui_max_tokens_chat, ui_top_p_chat])
ui_top_p_chat.change(get_parameters_chat, [ui_temp_chat, ui_max_tokens_chat, ui_top_p_chat])
ui_voice_inc_vchat.change(user_vchat, [ui_voice_inc_vchat, ui_chatbot_vchat], ui_chatbot_vchat, queue=False).then(
bot_vchat, ui_chatbot_vchat, ui_chatbot_vchat, queue=False).then(text_to_speech, None, ui_voice_out_vchat)
page.launch(share=False)
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