init

app.py

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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·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·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"):
+            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)
+
+
+