Spaces:
Running
Running
Niki Zhang
commited on
Update app.py
Browse files
app.py
CHANGED
@@ -91,7 +91,7 @@ def validate_api_key(api_key):
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return False
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-
def init_openai_api_key(api_key=""):
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text_refiner = None
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visual_chatgpt = None
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if api_key and len(api_key) > 30:
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@@ -112,12 +112,13 @@ def init_openai_api_key(api_key=""):
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print(text_refiner)
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openai_available = text_refiner is not None
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if openai_available:
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-
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else:
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return [gr.update(visible=False)]*7 + [gr.update(visible=True)]*2 + [text_refiner, visual_chatgpt, 'Your OpenAI API Key is not available']
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def init_wo_openai_api_key():
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return [gr.update(visible=False)]*4 + [gr.update(visible=True)]
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def get_click_prompt(chat_input, click_state, click_mode):
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inputs = json.loads(chat_input)
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@@ -304,21 +305,20 @@ def submit_caption(image_input, state, generated_caption, text_refiner, visual_c
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input_points=input_points, input_labels=input_labels)
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try:
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waveform_visual, audio_output = tts.predict(new_cap, input_language, input_audio, input_mic, use_mic, agree)
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yield state, state, refined_image_input, click_index_state, input_mask_state, input_points_state, input_labels_state, out_state, waveform_visual, audio_output
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except Exception as e:
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state = state + [(None, f"Error during TTS prediction: {str(e)}")]
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print(f"Error during TTS prediction: {str(e)}")
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-
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else:
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try:
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waveform_visual, audio_output = tts.predict(generated_caption, input_language, input_audio, input_mic, use_mic, agree)
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-
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except Exception as e:
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state = state + [(None, f"Error during TTS prediction: {str(e)}")]
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print(f"Error during TTS prediction: {str(e)}")
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-
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@@ -421,7 +421,7 @@ def clear_chat_memory(visual_chatgpt, keep_global=False):
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visual_chatgpt.current_image = None
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visual_chatgpt.global_prompt = ""
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def cap_everything(image_input, visual_chatgpt, text_refiner):
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model = build_caption_anything_with_models(
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args,
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@@ -438,7 +438,8 @@ def cap_everything(image_input, visual_chatgpt, text_refiner):
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AI_prompt = "Received."
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visual_chatgpt.global_prompt = Human_prompt + 'AI: ' + AI_prompt
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visual_chatgpt.agent.memory.buffer = visual_chatgpt.agent.memory.buffer + visual_chatgpt.global_prompt
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-
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def get_style():
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@@ -494,6 +495,7 @@ def create_ui():
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input_mask_state = gr.State(np.zeros((1, 1)))
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input_points_state = gr.State([])
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input_labels_state = gr.State([])
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gr.Markdown(title)
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gr.Markdown(description)
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@@ -501,7 +503,13 @@ def create_ui():
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with gr.Row():
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with gr.Column(scale=1.0):
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with gr.Column(visible=False) as modules_not_need_gpt:
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with gr.Tab("
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image_input = gr.Image(type="pil", interactive=True, elem_id="image_upload")
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example_image = gr.Image(type="pil", interactive=False, visible=False)
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with gr.Row(scale=1.0):
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@@ -578,10 +586,13 @@ def create_ui():
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variant='primary')
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with gr.Column(visible=False) as module_notification_box:
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notification_box = gr.Textbox(lines=1, label="Notification", max_lines=5, show_label=False)
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-
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-
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with gr.Column(visible=False) as modules_not_need_gpt2:
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chatbot = gr.Chatbot(label="Chatbox", ).style(height=550, scale=0.5)
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with gr.Column(visible=False) as modules_need_gpt3:
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@@ -590,7 +601,8 @@ def create_ui():
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with gr.Row():
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clear_button_text = gr.Button(value="Clear Text", interactive=True)
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submit_button_text = gr.Button(value="Submit", interactive=True, variant="primary")
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-
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# TTS interface hidden initially
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with gr.Column(visible=False) as tts_interface:
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input_text = gr.Textbox(label="Text Prompt", value="Hello, World !, here is an example of light voice cloning. Try to upload your best audio samples quality")
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@@ -600,7 +612,7 @@ def create_ui():
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use_mic = gr.Checkbox(label="Check to use Microphone as Reference", value=False)
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agree = gr.Checkbox(label="Agree", value=True)
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output_waveform = gr.Video(label="Waveform Visual")
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output_audio = gr.Audio(label="Synthesised Audio")
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with gr.Row():
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submit_tts = gr.Button(value="Submit", interactive=True)
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@@ -625,10 +637,10 @@ def create_ui():
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)
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openai_api_key.submit(init_openai_api_key, inputs=[openai_api_key],
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outputs=[modules_need_gpt0, modules_need_gpt1, modules_need_gpt2, modules_need_gpt3, modules_not_need_gpt,
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modules_not_need_gpt2, tts_interface,module_key_input ,module_notification_box, text_refiner, visual_chatgpt, notification_box])
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enable_chatGPT_button.click(init_openai_api_key, inputs=[openai_api_key],
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outputs=[modules_need_gpt0, modules_need_gpt1, modules_need_gpt2, modules_need_gpt3,
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modules_not_need_gpt,
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modules_not_need_gpt2, tts_interface,module_key_input,module_notification_box, text_refiner, visual_chatgpt, notification_box])
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@@ -652,7 +664,8 @@ def create_ui():
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show_progress=False
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)
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cap_everything_button.click(cap_everything, [origin_image, visual_chatgpt, text_refiner],
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clear_button_click.click(
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lambda x: ([[], [], []], x),
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@@ -688,6 +701,10 @@ def create_ui():
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)
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image_input.clear(clear_chat_memory, inputs=[visual_chatgpt])
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image_input.upload(upload_callback, [image_input, state, visual_chatgpt],
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@@ -705,8 +722,36 @@ def create_ui():
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example_image.change(upload_callback, [example_image, state, visual_chatgpt],
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[chatbot, state, origin_image, click_state, image_input, sketcher_input,
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image_embedding, original_size, input_size])
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example_image.change(clear_chat_memory, inputs=[visual_chatgpt])
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image_input.select(
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inference_click,
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inputs=[
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@@ -746,6 +791,11 @@ def create_ui():
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show_progress=False, queue=True
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)
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return False
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+
def init_openai_api_key(gpt_state,api_key=""):
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text_refiner = None
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visual_chatgpt = None
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if api_key and len(api_key) > 30:
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print(text_refiner)
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openai_available = text_refiner is not None
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if openai_available:
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gpt_state.set(1)
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return [gr.update(visible=True)]+[gr.update(visible=False)]+[gr.update(visible=True)]*3+[gr.update(visible=False)]+ [gr.update(visible=True)]+ [gr.update(visible=False)]*2 + [text_refiner, visual_chatgpt, None]
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else:
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return [gr.update(visible=False)]*7 + [gr.update(visible=True)]*2 + [text_refiner, visual_chatgpt, 'Your OpenAI API Key is not available']
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def init_wo_openai_api_key():
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return [gr.update(visible=False)]*4 + [gr.update(visible=True)]+ [gr.update(visible=False)]+[gr.update(visible=True)]+[gr.update(visible=False)]*2 + [None, None, None]
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def get_click_prompt(chat_input, click_state, click_mode):
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inputs = json.loads(chat_input)
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input_points=input_points, input_labels=input_labels)
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try:
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waveform_visual, audio_output = tts.predict(new_cap, input_language, input_audio, input_mic, use_mic, agree)
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return state, state, refined_image_input, click_index_state, input_mask_state, input_points_state, input_labels_state, out_state, waveform_visual, audio_output
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except Exception as e:
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state = state + [(None, f"Error during TTS prediction: {str(e)}")]
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print(f"Error during TTS prediction: {str(e)}")
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return state, state, refined_image_input, click_index_state, input_mask_state, input_points_state, input_labels_state, out_state, None, None
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else:
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try:
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waveform_visual, audio_output = tts.predict(generated_caption, input_language, input_audio, input_mic, use_mic, agree)
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return state, state, image_input, click_index_state, input_mask_state, input_points_state, input_labels_state, out_state, waveform_visual, audio_output
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except Exception as e:
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state = state + [(None, f"Error during TTS prediction: {str(e)}")]
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print(f"Error during TTS prediction: {str(e)}")
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return state, state, image_input, click_index_state, input_mask_state, input_points_state, input_labels_state, out_state, None, None
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visual_chatgpt.current_image = None
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visual_chatgpt.global_prompt = ""
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def cap_everything(image_input, visual_chatgpt, text_refiner,input_language, input_audio, input_mic, use_mic, agree):
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model = build_caption_anything_with_models(
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args,
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AI_prompt = "Received."
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visual_chatgpt.global_prompt = Human_prompt + 'AI: ' + AI_prompt
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visual_chatgpt.agent.memory.buffer = visual_chatgpt.agent.memory.buffer + visual_chatgpt.global_prompt
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waveform_visual, audio_output=tts.predict(paragraph, input_language, input_audio, input_mic, use_mic, agree)
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return paragraph,waveform_visual, audio_output
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def get_style():
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input_mask_state = gr.State(np.zeros((1, 1)))
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input_points_state = gr.State([])
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input_labels_state = gr.State([])
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gpt_state = gr.State(0)
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gr.Markdown(title)
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gr.Markdown(description)
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with gr.Row():
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with gr.Column(scale=1.0):
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with gr.Column(visible=False) as modules_not_need_gpt:
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with gr.Tab("Base(GPT Power)",visible=False) as base_tab:
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image_input_base = gr.Image(type="pil", interactive=True, elem_id="image_upload")
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example_image = gr.Image(type="pil", interactive=False, visible=False)
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with gr.Tab("Click") as click_tab:
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modules_not_need_gpt2=True
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image_input = gr.Image(type="pil", interactive=True, elem_id="image_upload")
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example_image = gr.Image(type="pil", interactive=False, visible=False)
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with gr.Row(scale=1.0):
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variant='primary')
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with gr.Column(visible=False) as module_notification_box:
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notification_box = gr.Textbox(lines=1, label="Notification", max_lines=5, show_label=False)
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with gr.Column():
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with gr.Column(visible=False) as modules_need_gpt2:
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paragraph_output = gr.Textbox(lines=7, label="Describe Everything", max_lines=7)
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with gr.Column(visible=False) as modules_need_gpt0:
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cap_everything_button = gr.Button(value="Caption Everything in a Paragraph", interactive=True)
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with gr.Column(visible=False) as modules_not_need_gpt2:
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chatbot = gr.Chatbot(label="Chatbox", ).style(height=550, scale=0.5)
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with gr.Column(visible=False) as modules_need_gpt3:
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with gr.Row():
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clear_button_text = gr.Button(value="Clear Text", interactive=True)
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submit_button_text = gr.Button(value="Submit", interactive=True, variant="primary")
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+
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with gr.Column(scale=0.5):
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# TTS interface hidden initially
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with gr.Column(visible=False) as tts_interface:
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input_text = gr.Textbox(label="Text Prompt", value="Hello, World !, here is an example of light voice cloning. Try to upload your best audio samples quality")
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use_mic = gr.Checkbox(label="Check to use Microphone as Reference", value=False)
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agree = gr.Checkbox(label="Agree", value=True)
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output_waveform = gr.Video(label="Waveform Visual")
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output_audio = gr.Audio(label="Synthesised Audio",autoplay=True)
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with gr.Row():
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submit_tts = gr.Button(value="Submit", interactive=True)
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)
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openai_api_key.submit(init_openai_api_key, inputs=[gpt_state,openai_api_key],
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outputs=[modules_need_gpt0, modules_need_gpt1, modules_need_gpt2, modules_need_gpt3, modules_not_need_gpt,
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modules_not_need_gpt2, tts_interface,module_key_input ,module_notification_box, text_refiner, visual_chatgpt, notification_box])
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enable_chatGPT_button.click(init_openai_api_key, inputs=[gpt_state,openai_api_key],
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outputs=[modules_need_gpt0, modules_need_gpt1, modules_need_gpt2, modules_need_gpt3,
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modules_not_need_gpt,
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modules_not_need_gpt2, tts_interface,module_key_input,module_notification_box, text_refiner, visual_chatgpt, notification_box])
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show_progress=False
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)
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cap_everything_button.click(cap_everything, [origin_image, visual_chatgpt, text_refiner,input_language, input_audio, input_mic, use_mic, agree],
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[paragraph_output,output_waveform, output_audio])
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clear_button_click.click(
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lambda x: ([[], [], []], x),
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)
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image_input.clear(clear_chat_memory, inputs=[visual_chatgpt])
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image_input_base.upload(upload_callback, [image_input_base, state, visual_chatgpt],
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[chatbot, state, origin_image, click_state, image_input_base, sketcher_input,
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image_embedding, original_size, input_size])
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image_input.upload(upload_callback, [image_input, state, visual_chatgpt],
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example_image.change(upload_callback, [example_image, state, visual_chatgpt],
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[chatbot, state, origin_image, click_state, image_input, sketcher_input,
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image_embedding, original_size, input_size])
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example_image.change(upload_callback, [example_image, state, visual_chatgpt],
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[chatbot, state, origin_image, click_state, image_input_base, sketcher_input,
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image_embedding, original_size, input_size])
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example_image.change(clear_chat_memory, inputs=[visual_chatgpt])
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def on_click_tab_selected():
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if gpt_state ==1:
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print(gpt_state)
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print("using gpt")
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return [gr.update(visible=True)]*2+[gr.update(visible=False)]*2
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else:
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print("no gpt")
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return [gr.update(visible=False)]+[gr.update(visible=True)]+[gr.update(visible=False)]*2
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def on_base_selected():
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if gpt_state ==1:
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print(gpt_state)
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print("using gpt")
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return [gr.update(visible=True)]*2+[gr.update(visible=False)]*2
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else:
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print("no gpt")
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return [gr.update(visible=False)]*4
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click_tab.select(on_click_tab_selected, outputs=[modules_need_gpt1,modules_not_need_gpt2,modules_need_gpt0,modules_need_gpt2])
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base_tab.select(on_base_selected, outputs=[modules_need_gpt0,modules_need_gpt2,modules_not_need_gpt2,modules_need_gpt1])
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image_input.select(
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inference_click,
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inputs=[
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show_progress=False, queue=True
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)
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def update_output_audio():
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return gr.update(autoplay=True)
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output_audio.change(update_output_audio,outputs=[output_audio])
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