from __future__ import annotations

from typing import cast

import gradio as gr

from core.app_logging import configure_app_logging
from core.deployment import current_policy
from models.model_catalog import load_model_catalog
from ui.agent_tab import build_agent_tab
from ui.chat_tab import build_chat_tab
from ui.dataset_tab import build_dataset_tab
from ui.export_tab import build_export_tab
from ui.notes_tab import build_notes_tab
from ui.status_tab import build_status_tab
from ui.traces_tab import build_traces_tab
from ui.train_tab import build_train_tab
from ui.vision_tab import build_vision_tab
from ui.vllm_tab import build_vllm_tab

APP_THEME = gr.themes.Soft(primary_hue="teal", neutral_hue="slate")
APP_CSS = """
.app-title {
  margin-bottom: 0.25rem;
}

.gradio-container {
  max-width: 1180px !important;
}

.tabs {
  overflow-x: auto;
}

button {
  min-height: 2.5rem;
}

textarea,
input,
.wrap {
  max-width: 100%;
}

@media (max-width: 720px) {
  .gradio-container {
    padding-left: 0.75rem !important;
    padding-right: 0.75rem !important;
  }

  .app-title h1 {
    font-size: 1.55rem;
    line-height: 1.2;
  }
}
"""


def build_app() -> gr.Blocks:
    configure_app_logging()
    policy = current_policy()
    catalog = load_model_catalog("config/models.yaml")

    with gr.Blocks(title="OpenBMB Local AI Workbench", analytics_enabled=False) as demo:
        gr.Markdown(
            """
            # OpenBMB Local AI Workbench
            Real small-model experimentation for Gradio + Hugging Face Spaces.
            """,
            elem_classes=["app-title"],
        )
        if policy.is_space:
            gr.Markdown(
                "Deployment mode: Space. Placeholder and demo inference are disabled; "
                "select a configured real backend before running model calls."
            )

        with gr.Tabs():
            with gr.Tab("Chat"):
                build_chat_tab(catalog, policy)
            with gr.Tab("Vision"):
                build_vision_tab(catalog, policy)
            with gr.Tab("Dataset"):
                build_dataset_tab()
            with gr.Tab("Train"):
                build_train_tab()
            with gr.Tab("vLLM"):
                build_vllm_tab(catalog)
            with gr.Tab("Export"):
                build_export_tab(catalog)
            with gr.Tab("Field Notes"):
                build_notes_tab(catalog)
            with gr.Tab("Traces"):
                build_traces_tab()
            with gr.Tab("Agent"):
                build_agent_tab()
            with gr.Tab("Status"):
                build_status_tab(catalog, policy)

    return cast(gr.Blocks, demo)


if __name__ == "__main__":
    build_app().launch(
        server_port=7860,
        share=False,
        theme=APP_THEME,
        css=APP_CSS,
        mcp_server=True,
    )