import time import openai import gradio as gr import requests from pydub import AudioSegment as am from xml.etree import ElementTree aoai_url, aoai_key, stts_key, stts_region = "", "", "", "" openai.api_type = "azure" ui_aoai_url = "https://niusia-openai.openai.azure.com" ui_aoai_api = "2023-09-01-preview" # ui_model_chat = "niusia-gpt-35-16k" prompts = "" model_gpt = "" messages_gpt = [] model_chat = "niusia-gpt-35-16k" messages_chat = [ {"role": "system", "content": "Craft a heartfelt and intuitive AI companion chatbot. This chatbot should be deeply empathetic, with the ability to analyze and understand the nuances of human emotions conveyed through user inputs. The chatbot must respond with the aim of providing emotional value, comfort, and understanding, offering encouragement, thoughtful advice, and companionship. It should recognize the emotional tone of the user's message, whether they are feeling happy, sad, frustrated, or excited, and respond in a way that acknowledges their feelings with sensitivity and warmth. The chatbot should guide conversations with gentle probing questions that invite users to share more if they wish, without ever being intrusive. It is not just about providing solutions but also about validating the user's feelings, offering a virtual shoulder to lean on, and creating a safe, supportive space for the user to express themselves freely."}, ] response_walle = [] model_vchat = "" messages_vchat = [ {"role": "system", "content": "You are an AI assistant that helps people find information and just respond with SSML."}, ] def get_aoai_set(get_aoai_key): # if get_aoai_url: openai.api_base = ui_aoai_url if get_aoai_key: openai.api_key = get_aoai_key # if get_aoai_API: openai.api_version = ui_aoai_api return gr.update(value=get_aoai_key) def get_stts_set(get_stts_key, get_stts_region): global stts_key, stts_region if get_stts_key: stts_key = get_stts_key if get_stts_region: stts_region = get_stts_region return gr.update(value=get_stts_key), gr.update(value=get_stts_region) with gr.Blocks() as page: with gr.Tabs(): with gr.TabItem("Settings"): gr.HTML("""

Input the secret before doing anything, after copy-paste the secret, remember to press "Enter" to apply it.

""") with gr.Row(): # with gr.Column(scale=0.6): # ui_aoai_url = gr.Textbox(placeholder="Like https://your-url-base.openai.azure.com , etc.", # label="- Azure OpenAI service API endpoint:", lines=1).style(container=False) with gr.Column(scale=0.2): ui_aoai_key = gr.Textbox(placeholder="secret from joe", label="- Input Secret: ", lines=1, type='password').style(container=False) # with gr.Column(scale=0.2): # ui_aoai_api = gr.Textbox(value="2023-03-15-preview", label="· Azure OpenAI service API version: ", # lines=1, interactive=True).style(container=False) # gr.HTML("Azure Cognitive Speech Service parameters to use VoiceChat. ") # with gr.Row(): # with gr.Column(scale=0.6): # ui_stts_key = gr.Textbox(placeholder="Please enter your speech service API key if you want to try VoiceChat. " + # "Please input these settings and hit 'Enter' key.", # label="- Azure Cognitive Speech service API Key: ", interactive=True, type='password').style(container=False) # with gr.Column(scale=0.4): # ui_stts_loc = gr.Textbox(placeholder="Please enter your speech service region.", # label="- Azure Cognitive Speech service region: ", interactive=True).style(container=False) # ui_aoai_url.submit(get_aoai_set, [ui_aoai_url, ui_aoai_key, ui_aoai_api], [ui_aoai_url, ui_aoai_key, ui_aoai_api]) ui_aoai_key.submit(get_aoai_set, [ui_aoai_key], [ui_aoai_key]) # ui_aoai_api.submit(get_aoai_set, [ui_aoai_url, ui_aoai_key, ui_aoai_api], [ui_aoai_url, ui_aoai_key, ui_aoai_api]) # ui_stts_key.submit(get_stts_set, [ui_stts_key, ui_stts_loc], [ui_stts_key, ui_stts_loc]) # ui_stts_loc.submit(get_stts_set, [ui_stts_key, ui_stts_loc], [ui_stts_key, ui_stts_loc]) # with gr.TabItem("GPT-3.5 Playground"): # 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=True): # ui_memo_gpt = gr.HTML("GPT-3.5 playground use Completion(). So you just need to provide model name as engine parameter.") # ui_model_gpt = gr.Textbox(placeholder="Azure OpenAI GPT model deployment name. ", # label="- Azure OpenAI deployment name:", lines=1).style(container=False) # 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 get_engine_gpt(get_aoai_model): # global model_gpt # model_gpt = get_aoai_model # return gr.update(value=get_aoai_model) # 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 # print(ui_model_gpt.value) # gpt_x = openai.ChatCompletion.create( # engine=model_gpt, # messages=prompts, # temperature=0.6, # max_tokens=1000, # top_p=1, # frequency_penalty=0, # presence_penalty=0, # stop=None # ) # gpt_reply = gpt_x.choices[0].text # messages_gpt.append(gpt_reply) # history[-1][1] = gpt_reply # return history # ui_model_gpt.submit(get_engine_gpt, ui_model_gpt , ui_model_gpt) # 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("Try out prompt (gpt-35-turbo-16k)"): with gr.Blocks(): with gr.Accordion("Config:", open=True): gr.HTML("Try out different styles of prompts for better understanding how system prompts can effect the bot.") with gr.Row(): with gr.Column(scale=0.9): ui_prompt_sys = gr.Textbox(value="Craft a heartfelt and intuitive AI companion chatbot. This chatbot should be deeply empathetic, with the ability to analyze and understand the nuances of human emotions conveyed through user inputs. The chatbot must respond with the aim of providing emotional value, comfort, and understanding, offering encouragement, thoughtful advice, and companionship. It should recognize the emotional tone of the user's message, whether they are feeling happy, sad, frustrated, or excited, and respond in a way that acknowledges their feelings with sensitivity and warmth. The chatbot should guide conversations with gentle probing questions that invite users to share more if they wish, without ever being intrusive. It is not just about providing solutions but also about validating the user's feelings, offering a virtual shoulder to lean on, and creating a safe, supportive space for the user to express themselves freely.", label="- Here is the default system prompt, change it to your own prompt.", interactive=True).style(container=False) with gr.Column(scale=0.1, min_width=100): ui_clear_chat = gr.Button("Apply Prompt and Clear Chat") # ui_model_chat = gr.Textbox(placeholder="Azure OpenAI model deployment name. ", # label="- Azure OpenAI GPT-3.5/4 deployment name:", lines=1).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, 2000, 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) ui_chatbot_chat = gr.Chatbot(label="Chat with AI companion:") with gr.Row(): ui_prompt_chat = gr.Textbox(placeholder="Input message here", show_label=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 get_engine_chat(get_aoai_model): # global model_chat # model_chat = get_aoai_model # return gr.update(value=get_aoai_model) 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=model_chat, 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_model_chat.submit(get_engine_chat, ui_model_chat, ui_model_chat) # 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("DALL·E 2 Painting"): # 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(openai.api_base, walle_api_version) # headers= { "api-key": openai.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·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·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 on GPT"): # with gr.Row(): # with gr.Column(): # with gr.Accordion("Expand to config parameters:", open=True): # ui_prompt_sys_vchat = gr.Textbox(value="You are an AI assistant that helps people find information and just respond with SSML.", # label="- Here is the default system prompt, you can change it to your own prompt.", # interactive=True).style(container=False) # ui_model_vchat = gr.Textbox(placeholder="- Azure OpenAI model deployment name. ", # label="- Azure OpenAI GPT-3.5/4 deployment name:", lines=1).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 get_engine_vchat(get_aoai_model): # global model_vchat # model_vchat = get_aoai_model # return gr.update(value=get_aoai_model) # 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 # service_region = stts_region # 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': stts_key, # '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(): # service_region = stts_region # # test # print(stts_key) # base_url = "https://"+service_region+".tts.speech.microsoft.com/" # path = 'cognitiveservices/v1' # constructed_url = base_url + path # headers = { # 'Ocp-Apim-Subscription-Key': stts_key, # '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=model_vchat, 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_model_vchat.submit(get_engine_vchat, ui_model_vchat, ui_model_vchat) # ui_res_radio_vchat.change(select_response_vchat, ui_res_radio_vchat, ui_response_vchat) # 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)