"""Gradio front end for Commute Copilot (this is the Hugging Face Space entry point)."""

import os

import gradio as gr

from commute_copilot import CommuteConfig, ask, build_config
from commute_copilot.config import LINES, line_stations

DEFAULT = CommuteConfig()

EXAMPLES = [
    "I need to head downtown. When should I leave, and do I need a jacket?",
    "Is anything wrong with the trains right now?",
    "Should I bring an umbrella this afternoon?",
]


def station_choices(route: str):
    try:
        return [(name, stop_id) for stop_id, name, _, _ in line_stations(route)]
    except Exception:
        return [(DEFAULT.stop_name, DEFAULT.stop_id)] if route == DEFAULT.route else []


def on_line_change(route):
    choices = station_choices(route)
    value = DEFAULT.stop_id if route == DEFAULT.route else (choices[0][1] if choices else None)
    return gr.Dropdown(choices=choices, value=value)


def respond(message, history, route, stop_id, walk_minutes, mode):
    if not os.environ.get("OPENROUTER_API_KEY"):
        return ("OPENROUTER_API_KEY is not set. On Hugging Face, add it under Settings -> "
                "Variables and secrets, then restart the Space.", "")
    try:
        cfg = (DEFAULT if (route, stop_id, int(walk_minutes)) == (DEFAULT.route, DEFAULT.stop_id,
                                                                  DEFAULT.walk_minutes)
               else build_config(route, stop_id, walk_minutes))
    except Exception as e:
        return f"Could not load that station from the MBTA ({e}).", ""
    try:
        result = ask(message, cfg, mode="multi" if mode.startswith("3") else "single",
                     history=history)
    except Exception as e:
        # Most often a 429 from the free OpenRouter tier (20/min, 50/day)
        return f"The model call failed: {type(e).__name__}: {e}", ""
    answer = result.answer
    if result.invented_times:
        answer += ("\n\n⚠️ Guardrail 3: these times did not come from live data, so treat "
                   f"them as unverified: {', '.join(result.invented_times)}")
    return answer, result.summary()


with gr.Blocks(title="Commute Copilot") as demo:
    gr.Markdown(
        "# 🚇 Commute Copilot\n"
        "Tells you **when to walk out the door** for the next MBTA train and **whether the "
        "weather changes the plan**. Uses live MBTA predictions, MBTA service alerts and "
        "Open-Meteo forecasts. Built with LangChain and LangGraph.")
    with gr.Row():
        line = gr.Dropdown(LINES, value=DEFAULT.route, label="Line")
        station = gr.Dropdown(station_choices(DEFAULT.route), value=DEFAULT.stop_id, label="Station")
        walk = gr.Slider(0, 30, value=DEFAULT.walk_minutes, step=1, label="Walk to platform (min)")
        mode = gr.Radio(["Single agent", "3-agent graph"], value="Single agent", label="Architecture")
    line.change(on_line_change, line, station)

    details = gr.Textbox(label="Run details: ReAct trace, tokens, guardrails", lines=14,
                         render=False)
    gr.ChatInterface(
        respond,
        additional_inputs=[line, station, walk, mode],
        additional_outputs=[details],
        examples=[[q] for q in EXAMPLES],
        cache_examples=False,
    )
    with gr.Accordion("Run details", open=False):
        details.render()

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