UI Components API

from components.header import render_header

render_header()

import streamlit as st
from components.header import render_header

st.set_page_config(page_title="My ML App", layout="wide")
render_header()

from components.sidebar import render_sidebar

render_sidebar()

import streamlit as st
from components.sidebar import render_sidebar

st.set_page_config(layout="wide")

with st.sidebar:
    render_sidebar()

from components.model_card import render_model_card

model = {
    "id": "model_a3f8b2c1",
    "name": "ResNet50 Transfer",
    "model_type": "Transfer Learning",
    "created_at": "2026-03-04T10:30:00",
    "config": {
        "transfer_config": {
            "base_model": "ResNet50",
            "strategy": "Fine-tuning"
        }
    }
}

def handle_edit(model_id):
    print(f"Editing model: {model_id}")

def handle_delete(model_id):
    print(f"Deleting model: {model_id}")

clicked = render_model_card(
    model,
    on_edit=handle_edit,
    on_delete=handle_delete,
    is_selected=True
)

if clicked:
    print("Card was clicked for selection")

from components.model_card import render_model_library
from state.workflow import get_model_library

models = get_model_library()

def handle_select(model_id):
    st.session_state.selected_model = model_id
    st.rerun()

render_model_library(
    models=models,
    selected_id=st.session_state.get("selected_model"),
    on_select=handle_select,
    cards_per_row=3
)

from components.experiment_row import render_experiment_row
from state.workflow import get_experiments, get_model_library, get_training_library

experiments = get_experiments()
models = get_model_library()
trainings = get_training_library()

def handle_start(exp_id):
    # Start training logic
    pass

def handle_delete(exp_id):
    from state.workflow import delete_experiment
    delete_experiment(exp_id)
    st.rerun()

for exp in experiments:
    render_experiment_row(
        experiment=exp,
        models=models,
        trainings=trainings,
        on_start=handle_start,
        on_delete=handle_delete
    )

from components.theme import render_theme_settings

with st.sidebar:
    render_theme_settings()

from state.ui import set_theme_colors

# Set custom theme programmatically
set_theme_colors(
    primary="#FF6B6B",
    secondary="#4ECDC4",
    background="#1A1A2E"
)

from components.utils import get_compute_device

device = get_compute_device()
print(f"Type: {device['type']}")  # "CUDA", "MPS", or "CPU"
print(f"Name: {device['name']}")  # "NVIDIA RTX 3080", "Apple M1", etc.
print(f"Available: {device['available']}")  # True/False

from components.utils import get_gpu_memory

memory = get_gpu_memory()
print(memory)  # "4.2/8.0 GB" or "Unified" (MPS) or "N/A"

from components.utils import get_system_memory

memory = get_system_memory()
print(memory)  # "8.4/16.0 GB"

from components.utils import get_cpu_info

info = get_cpu_info()
print(f"Cores: {info['cores']}")  # Physical cores
print(f"Threads: {info['threads']}")  # Logical processors
print(f"Usage: {info['usage']}%")  # Current CPU usage

from components.utils import get_platform_info

platform = get_platform_info()
print(platform)  # "macOS 14.0", "Linux", "Windows 11", etc.

from components.utils import clear_session

clear_session()
# Session saved, state cleared, and reinitialized

from components.tooltips import HEADER_TOOLTIPS, SIDEBAR_TOOLTIPS

# Header tooltips
HEADER_TOOLTIPS = {
    "new_session": "Create a new session and start fresh"
}

# Sidebar tooltips
SIDEBAR_TOOLTIPS = {
    "system_resources": "Hardware resources available for training",
    "gpu_memory": "GPU memory usage (allocated/total)",
    "system_ram": "System RAM usage",
    "cpu_info": "CPU cores and threads",
    "platform": "Operating system information"
}

import streamlit as st
from components.tooltips import SIDEBAR_TOOLTIPS

st.caption("GPU Memory", help=SIDEBAR_TOOLTIPS["gpu_memory"])

from components.model_card import MODEL_ICONS

# Available model icons
MODEL_ICONS = {
    "Custom CNN": "🔧",
    "Transformer": "🧪",
    "Transfer Learning": "🎯",
}

# Usage
icon = MODEL_ICONS.get(model_type, "🧠")  # Default to brain emoji

from components.experiment_row import STATUS_CONFIG

# Available status configurations
STATUS_CONFIG = {
    "ready": {"icon": "⚪", "label": "Ready", "color": "gray"},
    "training": {"icon": "🔄", "label": "Training", "color": "blue"},
    "paused": {"icon": "⏸️", "label": "Paused", "color": "orange"},
    "completed": {"icon": "✅", "label": "Completed", "color": "green"},
    "failed": {"icon": "❌", "label": "Failed", "color": "red"},
}

# Usage
status = "training"
config = STATUS_CONFIG.get(status)
st.markdown(f"{config['icon']} {config['label']}")