import gradio as gr

from PIL import Image
import os

os.system("pip install openai")
import openai

#api_key = os.environ.get('api_key')


whisper = gr.Interface.load(name="spaces/sanchit-gandhi/whisper-large-v2")

from share_btn import community_icon_html, loading_icon_html, share_js

token = os.environ.get('HF_TOKEN')

tts = gr.Interface.load(name="spaces/Flux9665/IMS-Toucan")
talking_face = gr.Blocks.load(name="spaces/fffiloni/one-shot-talking-face", api_key=token)

def infer(audio, openai_api_key):
    
    whisper_result = whisper(audio, None, "translate", fn_index=0)
    
    gpt_response = try_api(whisper_result, openai_api_key)
    
    audio_response = tts(gpt_response[0], "English Text", "English Accent", "English Speaker's Voice", fn_index=0)
    
    portrait_link = talking_face("wise_woman_portrait.png", audio_response, fn_index=0)
    
    return gr.Textbox.update(value=whisper_result, visible=True), portrait_link, gr.Textbox.update(value=gpt_response[1], visible=True), gr.update(visible=True)

def try_api(message, openai_api_key):
    try:
        response = call_api(message, openai_api_key)
        return response, Fore.GREEN + "no error"
    except openai.error.Timeout as e:
        #Handle timeout error, e.g. retry or log
        print(f"OpenAI API request timed out: {e}")
        return "oups", f"OpenAI API request timed out: {e}"
    except openai.error.APIError as e:
        #Handle API error, e.g. retry or log
        print(f"OpenAI API returned an API Error: {e}")
        return "oups", f"OpenAI API returned an API Error: {e}"
    except openai.error.APIConnectionError as e:
        #Handle connection error, e.g. check network or log
        print(f"OpenAI API request failed to connect: {e}")
        return "oups", f"OpenAI API request failed to connect: {e}"
    except openai.error.InvalidRequestError as e:
        #Handle invalid request error, e.g. validate parameters or log
        print(f"OpenAI API request was invalid: {e}")
        return "oups", f"OpenAI API request was invalid: {e}"
    except openai.error.AuthenticationError as e:
        #Handle authentication error, e.g. check credentials or log
        print(f"OpenAI API request was not authorized: {e}")
        return "oups", f"OpenAI API request was not authorized: {e}"
    except openai.error.PermissionError as e:
        #Handle permission error, e.g. check scope or log
        print(f"OpenAI API request was not permitted: {e}")
        return "oups", f"OpenAI API request was not permitted: {e}"
    except openai.error.RateLimitError as e:
        #Handle rate limit error, e.g. wait or log
        print(f"OpenAI API request exceeded rate limit: {e}")
        return "oups", f"OpenAI API request exceeded rate limit: {e}"

def call_api(message, openai_api_key):
          
    print("starting open ai")
    
    openai.api_key = openai_api_key
    
    response = openai.Completion.create(
        model="text-davinci-003",
        prompt=message,
        temperature=0.5,
        max_tokens=2048,
        top_p=1,
        frequency_penalty=0,
        presence_penalty=0.6
    )

    return str(response.choices[0].text).split("\n",2)[2]

title = """
    <div style="text-align: center; max-width: 500px; margin: 0 auto;">
        <div
        style="
            display: inline-flex;
            align-items: center;
            gap: 0.8rem;
            font-size: 1.75rem;
            margin-bottom: 10px;
        "
        >
        <h1 style="font-weight: 600; margin-bottom: 7px;">
            GPT Talking Portrait
        </h1>
        </div>
        <p style="margin-bottom: 10px;font-size: 94%;font-weight: 100;line-height: 1.5em;">
        Use Whisper to ask, alive portrait responds  !
        </p>
    </div>
"""

with gr.Blocks(css="style.css") as demo:
    
    with gr.Column(elem_id="col-container"):
        
        gr.HTML(title)
        
        gpt_response = gr.Video(label="Talking Portrait response", elem_id="video_out")
        with gr.Group(elem_id="share-btn-container", visible=False) as share_group:
                community_icon = gr.HTML(community_icon_html)
                loading_icon = gr.HTML(loading_icon_html)
                share_button = gr.Button("Share to community", elem_id="share-btn")
        error_handler = gr.Textbox(visible=False, show_label=False)
             
    with gr.Column(elem_id="col-container-2"):
        with gr.Row():
            record_input = gr.Audio(source="microphone",type="filepath", label="Audio input", show_label=True, elem_id="record_btn")
            openai_api_key = gr.Textbox(max_lines=1, type="password", label="Your OpenAI API Key", placeholder="sk-123abc...")
        whisper_tr = gr.Textbox(label="whisper english translation", elem_id="text_inp", visible=False)

        send_btn = gr.Button("Send my request !")
       
    send_btn.click(infer, inputs=[record_input, openai_api_key], outputs=[whisper_tr, gpt_response, error_handler, share_group])
    share_button.click(None, [], [], _js=share_js)

demo.queue(max_size=32, concurrency_count=20).launch(debug=True)