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"

prompts = ""
model_gpt = ""
messages_gpt = []
model_chat = ""
messages_chat = [
    {"role": "system", "content": "You are an AI assistant that helps people find information."},
]
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_url, get_aoai_key, get_aoai_API):
    if get_aoai_url:
        openai.api_base = get_aoai_url
    if get_aoai_key:
        openai.api_key = get_aoai_key
    if get_aoai_API:
        openai.api_version = get_aoai_API
    return gr.update(value=get_aoai_url), gr.update(value=get_aoai_key), gr.update(value=get_aoai_API)

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("""
                <p>Please read and set parameters before switching to another tab.</p> <br>Your Azure OpenAI Key and other Azure Cognitive Service Keys
                 will not be saved or viewed by anyone. <br><br>
                 You can find these parameters in Azure Portal. Select Azure OpenAI resource or Cognitive Service resource like Speech, and then select 
                 'Keys and Endpoint' from left panel. <br> For Azure OpenAI service, you need to provide the resource URL and key for REST API. You also 
                 need to set the API version or just use the default value. The Azure OpenAI model which is deployed needs to be set in each tab. Because 
                 you may need to run different models at the same time. Don't forget to hit 'Enter' with every input. <br> For Azure Cognitive services, 
                 you need to provide a Key for REST API, and also need to provide a service region, for example, 'westus'. The app will create the endpoint
                 URL by itself. <br><br>Thank you.<br><br><br> Azure OpenAI Service parameters for ChatGPT/GPT. Please input these settings and hit the 
                 'Enter' key.
                 """)
            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="Please enter your Azure OpenAI API key here.", 
                                             label="- Azure OpenAI service API Key: ", 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_url, ui_aoai_key, ui_aoai_api], [ui_aoai_url, ui_aoai_key, ui_aoai_api])
            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.Completion.create(
                    engine=model_gpt,
                    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_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("ChatGPT on GPT-4"):
            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=True):
                    gr.HTML("ChatGPT use ChatCompletion(). 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.", 
                                               label="- Here is the default system prompt, you can change it to your own prompt.", 
                                               interactive=True).style(container=False)
                    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)

            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, debug=True)