import os

import gradio as gr
from gradio_modal import Modal

from content import HEADER_MARKDOWN, LEADERBOARD_TAB_TITLE_MARKDOWN, SUBMISSION_TAB_TITLE_MARKDOWN, \
    ADDITIONAL_NOTES_MARKDOWN, LEADERBOARD_CSS
from leaderboard_server import LeaderboardServer

# Initialize server and task list
DATA_ROOT = os.environ.get("DATA_ROOT")
server = LeaderboardServer(local_leaderboard_path=DATA_ROOT)
TASKS = list(server.tasks_metadata.keys())
EXPECTED_TOKEN = os.environ.get("SUBMISSION_TOKEN")


def get_datasets_for_task(task):
    path = os.path.join("references", task)
    if not os.path.exists(path):
        return []
    return [f.replace(".json", "") for f in os.listdir(path) if f.endswith(".json")]


def update_datasets(task):
    return gr.CheckboxGroup(choices=get_datasets_for_task(task), value=get_datasets_for_task(task))


def submit_model(task, datasets, hyp_file, submitted_by, model_id, model_link_input, token, normalize):
    if not hyp_file:
        return gr.update(visible=True, value="⚠️ Please upload a hypothesis file.")

    if not submitted_by.strip() or not model_id.strip() or not model_link_input.strip() or not token.strip():
        return gr.update(visible=True, value="⚠️ All fields are required.")

    if token.strip() != EXPECTED_TOKEN:
        return gr.update(visible=True, value="❌ Invalid submission token.")

    metadata = {
        "submitted_by": submitted_by.strip(),
        "model_id": model_id.strip(),
        "model_link": model_link_input.strip(),
        "normalize": normalize  # Include normalization info in metadata if needed
    }

    leaderboard_df = server.get_leaderboard(task)
    if len(leaderboard_df) > 0:
        existing = leaderboard_df[
            (leaderboard_df["Submitted by"] == submitted_by.strip()) &
            (leaderboard_df["Model ID"] == model_id.strip())
            ]
        # TODO: Uncomment this after testing done
        # if not existing.empty:
        #     return gr.update(value="❌ A submission with this name and model ID already exists.", visible=True)

    try:
        server.prepare_model_for_submission(
            hyp_file.name, metadata, task, datasets, normalize=normalize
        )
        return gr.update(visible=True, value="✅ Submission successful!")
    except Exception as e:
        print(e)
        return gr.update(visible=True, value=f"❌ Error: {str(e)}")


def get_leaderboard_df(task):
    return server.get_leaderboard(task)


# Gradio UI
with gr.Blocks(css=LEADERBOARD_CSS) as demo:
    gr.Markdown(HEADER_MARKDOWN)

    with gr.Tabs(selected=0) as tabs:
        with gr.Tab("📈 Leaderboard"):
            gr.Markdown(LEADERBOARD_TAB_TITLE_MARKDOWN)
            leaderboard_task_dropdown = gr.Dropdown(choices=TASKS, value=TASKS[0], label="Select Task for Leaderboard")
            leaderboard_output = gr.components.Dataframe(
                datatype=["markdown", "markdown", "float", "float", "float", "float", "float", "float"],
                value=lambda: get_leaderboard_df(TASKS[0]),
                interactive=False,
                label="Leaderboard"
            )
            leaderboard_task_dropdown.change(fn=get_leaderboard_df, inputs=leaderboard_task_dropdown,
                                             outputs=leaderboard_output)

        with gr.Tab("📤 Submit"):
            gr.Markdown(SUBMISSION_TAB_TITLE_MARKDOWN)

            with gr.Row():
                task_dropdown = gr.Dropdown(choices=TASKS, value=TASKS[0], label="Select Task")
                dataset_checkboxes = gr.CheckboxGroup(choices=get_datasets_for_task(TASKS[0]), label="Select Datasets",
                                                      value=get_datasets_for_task(TASKS[0]))
            task_dropdown.change(fn=update_datasets, inputs=task_dropdown, outputs=dataset_checkboxes)

            with gr.Row():
                submitted_by_input = gr.Text(label="Submitted by")
                model_id_input = gr.Text(label="Model Identifier")
                model_link_input = gr.Text(label="Model Link", placeholder="Link to model or code repository")
                token_input = gr.Text(label="Submission Token", type="password")

            hyp_file_upload = gr.File(label="Upload Hypothesis JSON", file_types=[".json"])

            normalize_checkbox = gr.Checkbox(label="Apply Chime-8 Normalization", value=True)

            submit_btn = gr.Button("Submit")

            with Modal("Submission Feedback", visible=False) as loading_msg:
                feedback_text = gr.Text(visible=True, label="⏳ Processing your submission...")
            gr.Markdown(ADDITIONAL_NOTES_MARKDOWN)

            submit_btn.click(
                lambda: gr.update(visible=True),  # Show loading
                outputs=loading_msg
            ).then(
                fn=submit_model,
                inputs=[task_dropdown, dataset_checkboxes, hyp_file_upload,
                        submitted_by_input, model_id_input, model_link_input, token_input, normalize_checkbox],
                outputs=[feedback_text],
            ).then(
                fn=lambda task: get_leaderboard_df(task),
                inputs=task_dropdown,
                outputs=leaderboard_output
            )

if __name__ == "__main__":
    demo.launch()