import json
import os
from typing import Any, Dict, Tuple

import dash_auth
import pandas as pd
from app_styles import header_style
from dash import (
    Dash,
    Input,
    Output,
    State,
    callback,
    dash_table,
    dcc,
    get_asset_url,
    html,
    no_update,
)
from dash.exceptions import PreventUpdate
from data_chat import send_message
from sql_utils import execute_query, test_db_connection

external_stylesheets = ["https://codepen.io/chriddyp/pen/bWLwgP.css"]

app = Dash(__name__, external_stylesheets=external_stylesheets)
auth = dash_auth.BasicAuth(
    app,
    {os.getenv("APP_UNAME"): os.getenv("APP_PW")},
)
app.index_string = header_style

notification_md = """
**Hinweise:**

Aufgrund des sparsamen pricing Tiers kann es einige Sekunden dauern, bis die
Verbindung zur Datenbank hergestellt wird. Im Falle eines Fehlers gern ein-zwei mal erneut
versuchen.

GPT-4o kann einige Fehler machen. Sollte dies passieren wird eine Fehlermeldung angezeigt.
In diesem Fall lohnt es sich oft, die Anfrage leicht verändert erneut zu stellen und evtl
zusätzliche Informationen zu geben.

Das Modell ist dazu aufgefordert, den Output stets auf 100 Zeilen zu begrenzen.

Alle Daten sind komplett zufällig generiert und haben keine Beziehung zu realen Personen.

**Beispielfragen**:
- Wie viele Kunden haben wir in Hannover?
- Zeige alle Kunden in Bremen.
- Berechne den gesamten Stromverbrauch aller Kunden in Magdeburg.
- Zeige alle Kunden, die zwischen 2021 und 2022 mindestens 200 Kubikmeter Gas verbraucht haben.
- Wie viele Kunden haben zwischen 2021 und 2022 weniger Strom verbraucht als zwischen 2022
und 2023?

Weitere Informationen zu den Daten, dem Code sowie zur Nutzung befinden sich in der README im
[GiTea Repository](https://gitea.captain.particlephysics.de/quadfaselt/grid_application).
"""

err_style = {
    "height": "0px",
    "overflow": "hidden",
    "transition": "height 0.5s ease-in-out",
    "border-radius": "15px",
    "background-color": "#FFCCCB",
    "text-align": "center",
    "color": "#FF6B6B",
    "margin-top": "20px",
    "margin-left": "20px",
    "margin-right": "20px",
    "font-weight": "bold",
    "display": "flex",
    "justify-content": "center",
    "align-items": "center",
}


def render_table(df: pd.DataFrame) -> dash_table.DataTable:
    """Create a Dash DataTable from a pandas DataFrame.

    Parameters
    ----------
    df : pd.DataFrame
        The input DataFrame to be rendered as a table.

    Returns
    -------
    dash_table.DataTable
        A Dash DataTable component with styled layout and pagination.
    """
    tab = dash_table.DataTable(
        id="table",
        columns=[{"name": i, "id": i} for i in df.columns],
        data=df.to_dict("records"),
        page_size=10,
        style_table={
            "overflowX": "auto",
            "margin": "auto",
            "width": "96%",
            "margin-top": "20px",
        },
        style_cell={
            "minWidth": "100px",
            "width": "150px",
            "maxWidth": "300px",
            "overflow": "hidden",
            "textOverflow": "ellipsis",
        },
        style_header={
            "backgroundColor": "lightblue",
            "fontWeight": "bold",
            "color": "black",
        },
    )
    return tab


def get_layout() -> html.Div:
    """Generate the layout for a Dash application.

    This function creates a complex layout for a database chat interface
    and a direct SQL query interface. It includes various Dash components
    such as text areas, buttons, and a loading spinner.

    The layout consists of:
    - A header with title and logo
    - A textarea for user input (database chat)
    - A submit button for the database chat
    - A Notification about the connection time and LLM performance
    - An error message area
    - A loading spinner and output area for database responses
    - A section for direct SQL queries, including a textarea and submit button
    - An output area for SQL query results

    Returns
    -------
    html.Div
        A Dash html.Div component containing the entire layout of the application.
    """
    global err_style
    tmp_style = err_style.copy()
    tmp_style["height"] = "0px"

    start_value = "Stelle deine Frage an die Datenbank..."

    layout = html.Div(
        [
            html.Div(
                [
                    html.H1("Datenbank-Chat", className="heading"),
                    html.Img(src=get_asset_url("logo.png"), className="logo"),
                ],
                className="header-container",
            ),  # Header
            html.Div(
                "Ganz ohne SQL-Kenntnisse Daten zu Zählerstandmessungen unserer Kunden abrufen!",
                style={"margin-left": "20px", "font-weight": "bold", "font-size": "20px"},
            ),
            dcc.Store(
                id="tmp-value", data=start_value, storage_type="memory"
            ),  # Store previous prompt
            dcc.Textarea(
                id="input-field",
                value=start_value,
                style={"width": "96%", "height": 200, "margin-left": "20px"},
            ),  # Input field
            html.Div([]),  # Needed for keeping the layout clean
            html.Button(
                "Abschicken",
                id="submit-button",
                n_clicks=0,
                disabled=False,
                style={"margin-left": "20px"},
            ),  # Submit button
            dcc.Markdown(
                notification_md,
                style={
                    "margin-left": "20px",
                    "margin-top": "20px",
                    "margin-right": "10px",
                    "background-color": "#C7E6F5",
                    "border-radius": "5px",
                    "padding": "10px",
                },
            ),
            html.Div(
                [html.P("Bitte eine neue Anfrage eingeben.")], id="error", style=tmp_style
            ),  # Error message (only visible if input is not updated but submit button is clicked)
            dcc.Loading(
                id="loading",
                type="default",
                children=[
                    html.Div(
                        "Hier erscheint die Antwort des KI-Modells.",
                        id="text-output",
                        style={
                            "whiteSpace": "pre-line",
                            "margin-top": "30px",
                            "margin-left": "20px",
                            "margin-right": "20px",
                            "border": "2px solid #86bc25",
                            "border-radius": "15px",
                            "padding": "20px",
                        },
                    )
                ],
            ),
            html.H2(
                "Direkte SQL-Abfrage",
                style={"margin-left": "20px", "margin-top": "50px", "font-size": 24},
            ),  # SQL Header
            html.Div(
                (
                    "Hier kann der ausgegebene SQL-Code getestet oder mit selbst"
                    "geschriebenen Code verglichen werden."
                ),
                style={"margin-left": "20px", "font-weight": "bold", "font-size": "16px"},
            ),
            dcc.Textarea(
                id="sql-input-field",
                value="(Microsoft) SQL-Abfrage eingeben...",
                style={"width": "96%", "height": 200, "margin-left": "20px"},
            ),  # SQL Input field
            html.Div([]),  # Needed for keeping the layout clean
            html.Button(
                "Abschicken",
                id="sql-submit-button",
                n_clicks=0,
                disabled=False,
                style={"margin-left": "20px"},
            ),  # Submit button
            html.Div(id="sql-output", style={"margin-top": "10px"}),  # SQL Output
        ],
        className="container",
    )

    return layout


app.layout = html.Div([get_layout()])


@callback(
    Output("text-output", "children"),
    Output("tmp-value", "data"),
    Output("error", "style"),
    Output("error", "children"),
    Input("submit-button", "n_clicks"),
    State("input-field", "value"),
    State("tmp-value", "data"),
    prevent_initial_call=True,
    running=[
        (Output("submit-button", "disabled"), True, False),
        (
            Output("submit-button", "style"),
            {"opacity": 0.5, "margin-left": "20px"},
            {"opacity": 1.0, "margin-left": "20px"},
        ),
    ],
)
def update_output(n_clicks: int, value: str, data: str) -> Tuple[Any, Any, Dict[str, str], Any]:
    """Update the output based on user input and button clicks.

    Parameters
    ----------
    n_clicks : int
        Number of times the submit button has been clicked.
    value : str
        Current value of the input field.
    data : str
        Previously stored value.

    Returns
    -------
    Tuple[str, str, Dict[str, Any]]
        Updated output text, new stored value, and error style.
    """
    global err_style
    db_connected = test_db_connection()
    if n_clicks > 0 and value != data and db_connected:
        result = send_message(value)
        err_style["height"] = "0px"

        # parse LLM response to dict, then try to execute the query
        try:
            parsed_result = json.loads(result, strict=False)

            result_table = execute_query(parsed_result["query"])
            children = [
                html.P([html.B("Zusammenfassung: "), f"{parsed_result['summary']}"]),
                html.P([html.B("SQL Abfrage: "), f"{parsed_result['query']}"]),
                render_table(result_table),
            ]
            return children, value, err_style, html.P("")
        except Exception as e:
            err_style["height"] = "400px"
            err_child = html.Div(f"Folgender Fehler ist aufgetreten: {e}.LLM Output: {result}.")

            return no_update, value, err_style, err_child

    elif not db_connected:
        err_style["height"] = "50px"
        err_child = html.P(
            (
                "Fehler beim Herstellen der Verbindung zur "
                "Datenbank. Bitte versuche es später erneut."
            )
        )
        return no_update, no_update, err_style, err_child

    elif value == data:

        err_style["height"] = "50px"
        err_child = html.P("Bitte eine neue Anfrage eingeben.")
        return no_update, no_update, err_style, err_child

    raise PreventUpdate


@callback(
    Output("sql-output", "children"),
    Input("sql-submit-button", "n_clicks"),
    State("sql-input-field", "value"),
    prevent_initial_call=True,
)
def run_sql_query(n_clicks: int, value: str) -> str:
    """Run a SQL query and return the results.

    Parameters
    ----------
    n_clicks : int
        Number of times the submit button has been clicked.
    value : str
        Current value of the input field.

    Returns
    -------
    str
        The results of the SQL query.
    """
    if n_clicks > 0:
        result = execute_query(value)
        if isinstance(result, str):
            global err_style
            tmp_style = err_style.copy()
            tmp_style["height"] = "100px"
            tmp_style["padding"] = "20px"
            err_child = html.Div(
                [html.P(f"Fehler bei der Ausführung der Abfrage: {result}")], style=tmp_style
            )
            return err_child
        else:
            return render_table(result)
    raise PreventUpdate


server = app.server

if __name__ == "__main__":
    app.run(debug=True)