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Update app.py
Browse files
app.py
CHANGED
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@@ -299,19 +299,22 @@ def _generate_video_segment(input_image_path: str, output_image_path: str, promp
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return result[0]["video"]
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def unified_image_generator(prompt: str, images: Optional[List[str]], previous_video_path: Optional[str], last_frame_path: Optional[str], aspect_ratio: str, model_selection: str, manual_token: str, oauth_token: Optional[gr.OAuthToken]) -> tuple:
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if not (verify_pro_status(oauth_token) or verify_pro_status(manual_token)):
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raise gr.Error("Access Denied.")
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# Determine if using PRO model based on radio selection
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use_pro_model = (model_selection == "Nano Banana PRO")
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# Check rate limit
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username = get_username(oauth_token) or get_username(manual_token)
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if not username:
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raise gr.Error("Could not identify user.")
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can_generate = check_and_update_usage(username, use_pro_model)
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if not can_generate:
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# Check if user has quota on the other model
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@@ -320,10 +323,16 @@ def unified_image_generator(prompt: str, images: Optional[List[str]], previous_v
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model_name = "Nano Banana PRO" if use_pro_model else "Nano Banana"
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other_model_name = "Nano Banana" if use_pro_model else "Nano Banana PRO"
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if remaining_other > 0:
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gr.Info(f"You've reached your daily limit for {model_name}
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raise gr.Error(f"
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try:
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contents = [Image.open(image_path[0]) for image_path in images] if images else []
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@@ -332,18 +341,38 @@ def unified_image_generator(prompt: str, images: Optional[List[str]], previous_v
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# Select model based on radio selection
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model_name = GEMINI_PRO_MODEL_NAME if use_pro_model else GEMINI_MODEL_NAME
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# Create config with aspect ratio
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if
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else:
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)
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response = client.models.generate_content(
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model=model_name,
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@@ -428,25 +457,25 @@ with gr.Blocks(theme=gr.themes.Citrus(), css=css) as demo:
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model_radio = gr.Radio(
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choices=["Nano Banana", "Nano Banana PRO"],
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value="Nano Banana",
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label="Model Selection",
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info="PRO: Higher quality, slower generation (50/day) | Standard: Faster generation (75/day)"
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)
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# Resolution selection for PRO model
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resolution_dropdown = gr.Dropdown(
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label="Resolution (Nano Banana PRO only)",
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choices=["1K (1 credit)", "2K (2 credits)", "4K (4 credits)"],
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value="1K (1 credit)",
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interactive=True,
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visible=False
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)
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generate_button = gr.Button("Generate", variant="primary")
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with gr.Column(scale=1):
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@@ -463,10 +492,20 @@ with gr.Blocks(theme=gr.themes.Citrus(), css=css) as demo:
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login_button = gr.LoginButton()
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gr.on(
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triggers=[generate_button.click, prompt_input.submit],
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fn=unified_image_generator,
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inputs=[prompt_input, image_input_gallery, previous_video_state, last_frame_of_video_state, aspect_ratio_dropdown, model_radio, manual_token],
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outputs=[output_image, create_video_button, extend_video_button, video_group],
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api_name=False
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)
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@@ -513,4 +552,4 @@ with gr.Blocks(theme=gr.themes.Citrus(), css=css) as demo:
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demo.load(control_access, inputs=None, outputs=[main_interface, pro_message])
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if __name__ == "__main__":
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demo.queue(max_size=None, default_concurrency_limit=None).launch(show_error=True)
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)
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return result[0]["video"]
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def unified_image_generator(prompt: str, images: Optional[List[str]], previous_video_path: Optional[str], last_frame_path: Optional[str], aspect_ratio: str, model_selection: str, resolution: str, manual_token: str, oauth_token: Optional[gr.OAuthToken]) -> tuple:
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if not (verify_pro_status(oauth_token) or verify_pro_status(manual_token)):
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raise gr.Error("Access Denied.")
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# Determine if using PRO model based on radio selection
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use_pro_model = (model_selection == "Nano Banana PRO")
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# Calculate credit cost based on resolution (only for PRO model)
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credits_to_use = get_credit_cost(resolution) if use_pro_model else 1
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# Check rate limit
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username = get_username(oauth_token) or get_username(manual_token)
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if not username:
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raise gr.Error("Could not identify user.")
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can_generate = check_and_update_usage(username, use_pro_model, credits_to_use)
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if not can_generate:
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# Check if user has quota on the other model
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model_name = "Nano Banana PRO" if use_pro_model else "Nano Banana"
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other_model_name = "Nano Banana" if use_pro_model else "Nano Banana PRO"
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# Get remaining credits for current model
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remaining_current = get_remaining_generations(username, use_pro_model)
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if use_pro_model and remaining_current > 0 and remaining_current < credits_to_use:
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gr.Info(f"You need {credits_to_use} credits for {get_resolution_value(resolution)} but only have {remaining_current} credits remaining. Try a lower resolution or use Nano Banana.")
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if remaining_other > 0:
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gr.Info(f"You've reached your daily limit for {model_name}. You still have {remaining_other} generations left with {other_model_name}!")
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raise gr.Error(f"Insufficient credits. You need {credits_to_use} credits for this generation.")
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try:
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contents = [Image.open(image_path[0]) for image_path in images] if images else []
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# Select model based on radio selection
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model_name = GEMINI_PRO_MODEL_NAME if use_pro_model else GEMINI_MODEL_NAME
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# Create config with aspect ratio and resolution (for PRO model)
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if use_pro_model:
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# PRO model: use both aspect_ratio and image_size
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resolution_value = get_resolution_value(resolution)
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if aspect_ratio == "Auto":
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generate_content_config = types.GenerateContentConfig(
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response_modalities=["IMAGE", "TEXT"],
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image_config=types.ImageConfig(
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image_size=resolution_value,
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),
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)
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else:
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generate_content_config = types.GenerateContentConfig(
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response_modalities=["IMAGE", "TEXT"],
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image_config=types.ImageConfig(
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aspect_ratio=aspect_ratio,
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image_size=resolution_value,
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),
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)
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else:
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# Standard model: only aspect_ratio
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if aspect_ratio == "Auto":
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generate_content_config = types.GenerateContentConfig(
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response_modalities=["IMAGE", "TEXT"],
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)
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else:
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generate_content_config = types.GenerateContentConfig(
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response_modalities=["IMAGE", "TEXT"],
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image_config=types.ImageConfig(
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aspect_ratio=aspect_ratio,
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),
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)
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response = client.models.generate_content(
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model=model_name,
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model_radio = gr.Radio(
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choices=["Nano Banana", "Nano Banana PRO"],
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value="Nano Banana",
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)
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with gr.Row():
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aspect_ratio_dropdown = gr.Dropdown(
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label="Aspect Ratio",
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choices=["Auto", "1:1", "9:16", "16:9", "3:4", "4:3", "3:2", "2:3", "5:4", "4:5", "21:9"],
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value="Auto",
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interactive=True
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)
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resolution_dropdown = gr.Dropdown(
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label="Resolution (Nano Banana PRO only)",
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choices=["1K", "2K", "4K"],
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value="1K",
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interactive=True,
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visible=False
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)
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generate_button = gr.Button("Generate", variant="primary")
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with gr.Column(scale=1):
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login_button = gr.LoginButton()
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# Show/hide resolution dropdown based on model selection
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def update_resolution_visibility(model_selection):
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return gr.update(visible=(model_selection == "Nano Banana PRO"))
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model_radio.change(
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fn=update_resolution_visibility,
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inputs=[model_radio],
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outputs=[resolution_dropdown]
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)
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gr.on(
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triggers=[generate_button.click, prompt_input.submit],
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fn=unified_image_generator,
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inputs=[prompt_input, image_input_gallery, previous_video_state, last_frame_of_video_state, aspect_ratio_dropdown, model_radio, resolution_dropdown, manual_token],
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outputs=[output_image, create_video_button, extend_video_button, video_group],
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api_name=False
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)
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demo.load(control_access, inputs=None, outputs=[main_interface, pro_message])
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if __name__ == "__main__":
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demo.queue(max_size=None, default_concurrency_limit=None).launch(show_error=True)
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