Spaces:
Runtime error
Runtime error
Jose Benitez
commited on
Commit
·
025cc15
1
Parent(s):
c3fc33a
clean code
Browse files- gradio_app.py +52 -82
- routes.py +0 -11
- static/html/landing.html +16 -16
- utils/file_utils.py +6 -0
gradio_app.py
CHANGED
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@@ -1,40 +1,35 @@
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import gradio as gr
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import os
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import json
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import zipfile
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from pathlib import Path
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from services.image_generation import generate_image
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from services.train_lora import lora_pipeline
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from utils.image_utils import url_to_pil_image
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if not isinstance(lora_models, list):
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raise ValueError("Expected loras_models to be a list of dictionaries.")
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if login_css_path.is_file(): # Check if the file exists
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with login_css_path.open() as file:
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login_css = file.read()
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if main_css_path.is_file(): # Check if the file exists
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with main_css_path.open() as file:
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main_css = file.read()
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if landing_html_path.is_file():
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with landing_html_path.open() as file:
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landin_page = file.read()
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def load_user_models(request: gr.Request):
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user = request.session.get('user')
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@@ -49,10 +44,10 @@ def update_selection(evt: gr.SelectData, gallery_type: str, width, height):
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if gallery_type == "user":
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selected_lora = {"lora_name": "custom", "trigger_word": "custom"}
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else:
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selected_lora =
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new_placeholder = f"
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trigger_word = selected_lora["trigger_word"]
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updated_text = f"####
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if "aspect" in selected_lora:
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if selected_lora["aspect"] == "portrait":
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@@ -64,14 +59,14 @@ def update_selection(evt: gr.SelectData, gallery_type: str, width, height):
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def compress_and_train(request: gr.Request, files, model_name, trigger_word, train_steps, lora_rank, batch_size, learning_rate):
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if not files:
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return "No
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user = request.session.get('user')
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_, training_credits = get_user_credits(user['id'])
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if training_credits <= 0:
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raise gr.Error("
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if not user:
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raise gr.Error("User not authenticated. Please log in.")
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@@ -111,7 +106,7 @@ def compress_and_train(request: gr.Request, files, model_name, trigger_word, tra
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user['training_credits'] = new_training_credits
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request.session['user'] = user
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return gr.Info("
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def run_lora(request: gr.Request, prompt, cfg_scale, steps, selected_index, selected_gallery, width, height, lora_scale, progress=gr.Progress(track_tqdm=True)):
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user = request.session.get('user')
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@@ -179,9 +174,9 @@ def greet(request: gr.Request):
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return f"{greeting}\n"
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return "OBTU AI. Please log in."
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with gr.Blocks(theme=gr.themes.Soft(), css=
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with gr.Column(elem_id="google-btn-container", elem_classes="google-btn-container svelte-vt1mxs gap"):
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btn = gr.Button("
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_js_redirect = """
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() => {
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url = '/login' + window.location.search;
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@@ -189,16 +184,16 @@ with gr.Blocks(theme=gr.themes.Soft(), css=login_css) as login_demo:
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}
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"""
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btn.click(None, js=_js_redirect)
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gr.HTML(
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header = '<script src="https://cdn.lordicon.com/lordicon.js"></script>'
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with gr.Blocks(theme=gr.themes.Soft(), head=header, css=
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title = gr.HTML(
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with gr.Column(elem_id="logout-btn-container"):
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gr.Button("
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greetings = gr.Markdown("Loading user information...")
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with gr.Column():
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train_credits_display = gr.Number(label="Training Credits", precision=0, interactive=False)
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with gr.Column():
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gr.Button("
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with gr.Tabs():
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with gr.TabItem('
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with gr.Row():
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with gr.Column(scale=3):
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prompt = gr.Textbox(label="Prompt",
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lines=1,
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placeholder="
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info='
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with gr.Column(scale=1, elem_id="gen_column"):
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generate_button = gr.Button("Generate", variant="primary", elem_id="gen_btn")
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@@ -230,17 +225,17 @@ with gr.Blocks(theme=gr.themes.Soft(), head=header, css=main_css) as main_demo:
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result = gr.Image(label="Imagen Generada")
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with gr.Column(scale=3):
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with gr.Accordion("
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selected_info = gr.Markdown("")
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gallery = gr.Gallery(
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[(item["image_url"], item["model_name"]) for item in
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label="
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allow_preview=False,
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columns=3,
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elem_id="gallery"
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)
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with gr.Accordion("
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user_model_gallery = gr.Gallery(
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label="Galeria de Modelos",
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allow_preview=False,
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gallery_type = gr.State("Public")
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with gr.Accordion("
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with gr.Row():
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cfg_scale = gr.Slider(label="CFG Scale", minimum=1, maximum=20, step=0.5, value=3.5)
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steps = gr.Slider(label="Steps", minimum=1, maximum=50, step=1, value=28)
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@@ -279,54 +274,29 @@ with gr.Blocks(theme=gr.themes.Soft(), head=header, css=main_css) as main_demo:
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outputs=[result, generation_credits_display]
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)
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with gr.TabItem("
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gr.Markdown("#
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gr.Markdown("
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with gr.Row():
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with gr.Column():
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train_dataset = gr.Gallery(columns=4, interactive=True, label="Tus Imagenes")
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model_name = gr.Textbox(label="
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trigger_word = gr.Textbox(label="
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info="
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)
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train_button = gr.Button("
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with gr.Accordion("
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train_steps = gr.Slider(label="Training Steps", minimum=100, maximum=10000, step=100, value=1000)
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lora_rank = gr.Number(label='lora_rank', value=16)
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batch_size = gr.Number(label='batch_size', value=1)
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learning_rate = gr.Number(label='learning_rate', value=0.0004)
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training_status = gr.Textbox(label="Training Status")
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def fake_train(train_dataset, model_name, trigger_word, train_steps, lora_rank, batch_size, learning_rate):
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print(f'fake training for test')
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new_training_credits = 0
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if new_training_credits <= 0:
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raise gr.Error("Ya no tienes creditos disponibles. Compra para continuar.")
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return gr.Info("Tu modelo esta entrenando, En unos 20 minutos estará listo para que lo pruebes en 'Generación'."), new_training_credits
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train_button.click(
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fake_train,
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inputs=[train_dataset, model_name, trigger_word, train_steps, lora_rank, batch_size, learning_rate],
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outputs=[training_status,train_credits_display]
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)
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#main_demo.load(greet, None, title)
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#main_demo.load(greet, None, greetings)
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#main_demo.load((greet, display_credits), None, [greetings, generation_credits_display, train_credits_display])
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main_demo.load(load_user_models, None, user_model_gallery)
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main_demo.load(load_greet_and_credits, None, [greetings, generation_credits_display, train_credits_display])
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# TODO:
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'''
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- resolver mostrar bien los nombres de los modelos en la galeria
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- Training con creditos.
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- Stripe(?)
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- Mejorar boton de login/logout
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- Retoque landing page
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'''
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import os
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import zipfile
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from pathlib import Path
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import gradio as gr
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from database import (
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get_user_credits,
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update_user_credits,
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get_lora_models_info,
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get_user_lora_models
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)
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from services.image_generation import generate_image
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from services.train_lora import lora_pipeline
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from utils.image_utils import url_to_pil_image
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from utils.file_utils import load_file_content
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LORA_MODELS = get_lora_models_info()
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if not isinstance(LORA_MODELS, list):
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raise ValueError("Expected loras_models to be a list of dictionaries.")
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BASE_DIR = Path(__file__).parent
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LOGIN_CSS_PATH = BASE_DIR / 'static/css/login.css'
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MAIN_CSS_PATH = BASE_DIR / 'static/css/main.css'
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LANDING_HTML_PATH = BASE_DIR / 'static/html/landing.html'
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MAIN_HEADER_PATH = BASE_DIR / 'static/html/main_header.html'
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LOGIN_CSS = load_file_content(LOGIN_CSS_PATH)
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MAIN_CSS = load_file_content(MAIN_CSS_PATH)
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LANDING_PAGE = load_file_content(LANDING_HTML_PATH)
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MAIN_HEADER = load_file_content(MAIN_HEADER_PATH)
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def load_user_models(request: gr.Request):
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user = request.session.get('user')
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if gallery_type == "user":
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selected_lora = {"lora_name": "custom", "trigger_word": "custom"}
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else:
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selected_lora = LORA_MODELS[evt.index]
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new_placeholder = f"Enter a prompt for {selected_lora['lora_name']}"
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trigger_word = selected_lora["trigger_word"]
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updated_text = f"#### Trigger Word: {trigger_word} ✨"
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if "aspect" in selected_lora:
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if selected_lora["aspect"] == "portrait":
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def compress_and_train(request: gr.Request, files, model_name, trigger_word, train_steps, lora_rank, batch_size, learning_rate):
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if not files:
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return "No Images. Please, upload some images to start training"
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user = request.session.get('user')
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_, training_credits = get_user_credits(user['id'])
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if training_credits <= 0:
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raise gr.Error("You ran out of credtis. Please buy more to continue")
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if not user:
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raise gr.Error("User not authenticated. Please log in.")
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user['training_credits'] = new_training_credits
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request.session['user'] = user
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return gr.Info("Your model is training. In about 20 minutes, it will be ready for you to test in 'Generation"), new_training_credits
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def run_lora(request: gr.Request, prompt, cfg_scale, steps, selected_index, selected_gallery, width, height, lora_scale, progress=gr.Progress(track_tqdm=True)):
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user = request.session.get('user')
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return f"{greeting}\n"
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return "OBTU AI. Please log in."
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with gr.Blocks(theme=gr.themes.Soft(), css=LOGIN_CSS) as login_demo:
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with gr.Column(elem_id="google-btn-container", elem_classes="google-btn-container svelte-vt1mxs gap"):
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btn = gr.Button("Sign In with Google", elem_classes="login-with-google-btn")
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_js_redirect = """
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() => {
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url = '/login' + window.location.search;
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}
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"""
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btn.click(None, js=_js_redirect)
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gr.HTML(LANDING_PAGE)
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header = '<script src="https://cdn.lordicon.com/lordicon.js"></script>'
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with gr.Blocks(theme=gr.themes.Soft(), head=header, css=MAIN_CSS) as main_demo:
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title = gr.HTML(MAIN_HEADER)
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with gr.Column(elem_id="logout-btn-container"):
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gr.Button("Logout", link="/logout", elem_id="logout_btn")
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greetings = gr.Markdown("Loading user information...")
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with gr.Column():
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train_credits_display = gr.Number(label="Training Credits", precision=0, interactive=False)
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with gr.Column():
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gr.Button("Buy Credits 💳", link="/buy_credits")
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with gr.Tabs():
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with gr.TabItem('Create'):
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with gr.Row():
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with gr.Column(scale=3):
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prompt = gr.Textbox(label="Prompt",
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lines=1,
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placeholder="Enter Your Prompt to start creating 📷",
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info='Some public models may experience longer processing times due to server availability and queue management.')
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with gr.Column(scale=1, elem_id="gen_column"):
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generate_button = gr.Button("Generate", variant="primary", elem_id="gen_btn")
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result = gr.Image(label="Imagen Generada")
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with gr.Column(scale=3):
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with gr.Accordion("Public Models"):
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selected_info = gr.Markdown("")
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gallery = gr.Gallery(
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[(item["image_url"], item["model_name"]) for item in LORA_MODELS],
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label="Public Models",
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allow_preview=False,
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columns=3,
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elem_id="gallery"
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)
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with gr.Accordion("Your Models"):
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user_model_gallery = gr.Gallery(
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label="Galeria de Modelos",
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allow_preview=False,
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gallery_type = gr.State("Public")
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with gr.Accordion("Advanced Settings", open=False):
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with gr.Row():
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cfg_scale = gr.Slider(label="CFG Scale", minimum=1, maximum=20, step=0.5, value=3.5)
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steps = gr.Slider(label="Steps", minimum=1, maximum=50, step=1, value=28)
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outputs=[result, generation_credits_display]
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)
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with gr.TabItem("Train"):
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gr.Markdown("# Train your own model 🧠")
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gr.Markdown("In this section, you can train your own model using your images.")
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with gr.Row():
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with gr.Column():
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train_dataset = gr.Gallery(columns=4, interactive=True, label="Tus Imagenes")
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model_name = gr.Textbox(label="Model Name",)
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trigger_word = gr.Textbox(label="Trigger Word",
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info="This will be a keyword to later instruct the model when to use these new capabilities we're going to teach it",
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)
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train_button = gr.Button("Start Training")
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with gr.Accordion("Advanced Settings", open=False):
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train_steps = gr.Slider(label="Training Steps", minimum=100, maximum=10000, step=100, value=1000)
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lora_rank = gr.Number(label='lora_rank', value=16)
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batch_size = gr.Number(label='batch_size', value=1)
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learning_rate = gr.Number(label='learning_rate', value=0.0004)
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training_status = gr.Textbox(label="Training Status")
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train_button.click(
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compress_and_train,
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inputs=[train_dataset, model_name, trigger_word, train_steps, lora_rank, batch_size, learning_rate],
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outputs=[training_status,train_credits_display]
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)
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main_demo.load(load_user_models, None, user_model_gallery)
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main_demo.load(load_greet_and_credits, None, [greetings, generation_credits_display, train_credits_display])
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routes.py
CHANGED
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@@ -105,17 +105,6 @@ async def stripe_webhook(request: Request):
|
|
| 105 |
|
| 106 |
return {"status": "success"}
|
| 107 |
|
| 108 |
-
# @router.get("/success")
|
| 109 |
-
# async def payment_success(request: Request):
|
| 110 |
-
# print("Payment successful")
|
| 111 |
-
# user = request.session.get('user')
|
| 112 |
-
# print(user)
|
| 113 |
-
# if user:
|
| 114 |
-
# updated_user = get_user_by_id(user['id'])
|
| 115 |
-
# if updated_user:
|
| 116 |
-
# request.session['user'] = updated_user
|
| 117 |
-
# return RedirectResponse(url='/gradio', status_code=303)
|
| 118 |
-
# return RedirectResponse(url='/login', status_code=303)
|
| 119 |
|
| 120 |
@router.get("/cancel")
|
| 121 |
async def payment_cancel(request: Request):
|
|
|
|
| 105 |
|
| 106 |
return {"status": "success"}
|
| 107 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 108 |
|
| 109 |
@router.get("/cancel")
|
| 110 |
async def payment_cancel(request: Request):
|
static/html/landing.html
CHANGED
|
@@ -135,7 +135,7 @@
|
|
| 135 |
<div class="header-content">
|
| 136 |
<div class="logo">🎨 ObtuAI</div>
|
| 137 |
<div id="google-btn-container">
|
| 138 |
-
<!--
|
| 139 |
</div>
|
| 140 |
</div>
|
| 141 |
</div>
|
|
@@ -144,46 +144,46 @@
|
|
| 144 |
<div class="container">
|
| 145 |
<section class="hero">
|
| 146 |
<div class="hero-content">
|
| 147 |
-
<h1>🚀
|
| 148 |
-
<p>
|
| 149 |
</div>
|
| 150 |
</section>
|
| 151 |
|
| 152 |
<section class="features">
|
| 153 |
-
<h2>🌟
|
| 154 |
<div class="feature-grid">
|
| 155 |
<div class="feature">
|
| 156 |
-
<h3>
|
| 157 |
-
<p>
|
| 158 |
</div>
|
| 159 |
<div class="feature">
|
| 160 |
-
<h3>
|
| 161 |
-
<p>
|
| 162 |
</div>
|
| 163 |
<div class="feature">
|
| 164 |
-
<h3>
|
| 165 |
-
<p>
|
| 166 |
</div>
|
| 167 |
</div>
|
| 168 |
</section>
|
| 169 |
|
| 170 |
<section class="testimonials">
|
| 171 |
<div class="container">
|
| 172 |
-
<h2>💬
|
| 173 |
<div class="testimonial">
|
| 174 |
-
<p>"ObtuAI
|
| 175 |
-
<p><strong>- Ana,
|
| 176 |
</div>
|
| 177 |
<div class="testimonial">
|
| 178 |
-
<p>"
|
| 179 |
-
<p><strong>- Carlos,
|
| 180 |
</div>
|
| 181 |
</div>
|
| 182 |
</section>
|
| 183 |
</div>
|
| 184 |
|
| 185 |
<footer>
|
| 186 |
-
<p>ObtuAI -
|
| 187 |
</footer>
|
| 188 |
</body>
|
| 189 |
</html>
|
|
|
|
| 135 |
<div class="header-content">
|
| 136 |
<div class="logo">🎨 ObtuAI</div>
|
| 137 |
<div id="google-btn-container">
|
| 138 |
+
<!-- The button will be inserted here by Gradio -->
|
| 139 |
</div>
|
| 140 |
</div>
|
| 141 |
</div>
|
|
|
|
| 144 |
<div class="container">
|
| 145 |
<section class="hero">
|
| 146 |
<div class="hero-content">
|
| 147 |
+
<h1>🚀 Welcome to the Future of Visual Creation</h1>
|
| 148 |
+
<p>Create AI-generated images in seconds. Write your idea and watch it turn into art!</p>
|
| 149 |
</div>
|
| 150 |
</section>
|
| 151 |
|
| 152 |
<section class="features">
|
| 153 |
+
<h2>🌟 Discover the Power of AI Image Generation</h2>
|
| 154 |
<div class="feature-grid">
|
| 155 |
<div class="feature">
|
| 156 |
+
<h3>Customize</h3>
|
| 157 |
+
<p>Feed your model with your own images and styles.</p>
|
| 158 |
</div>
|
| 159 |
<div class="feature">
|
| 160 |
+
<h3>Train</h3>
|
| 161 |
+
<p>Our AI learns from your preferences.</p>
|
| 162 |
</div>
|
| 163 |
<div class="feature">
|
| 164 |
+
<h3>Create</h3>
|
| 165 |
+
<p>Generate images that reflect your unique vision.</p>
|
| 166 |
</div>
|
| 167 |
</div>
|
| 168 |
</section>
|
| 169 |
|
| 170 |
<section class="testimonials">
|
| 171 |
<div class="container">
|
| 172 |
+
<h2>💬 What Our Users Say</h2>
|
| 173 |
<div class="testimonial">
|
| 174 |
+
<p>"ObtuAI has revolutionized my creative process. Now I can visualize my wildest ideas in minutes!"</p>
|
| 175 |
+
<p><strong>- Ana, Graphic Designer</strong></p>
|
| 176 |
</div>
|
| 177 |
<div class="testimonial">
|
| 178 |
+
<p>"Training my own model was surprisingly easy. Now I create photos of myself and my clients in seconds."</p>
|
| 179 |
+
<p><strong>- Carlos, Professional Photographer</strong></p>
|
| 180 |
</div>
|
| 181 |
</div>
|
| 182 |
</section>
|
| 183 |
</div>
|
| 184 |
|
| 185 |
<footer>
|
| 186 |
+
<p>ObtuAI - Your wild ideas in pixels with AI.</p>
|
| 187 |
</footer>
|
| 188 |
</body>
|
| 189 |
</html>
|
utils/file_utils.py
ADDED
|
@@ -0,0 +1,6 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
# Load static files
|
| 2 |
+
def load_file_content(file_path):
|
| 3 |
+
if file_path.is_file():
|
| 4 |
+
with file_path.open() as file:
|
| 5 |
+
return file.read()
|
| 6 |
+
return ""
|