import io
import json
import os
import tempfile
from pathlib import Path

import pandas as pd
import plotly.express as px
import streamlit as st
from dotenv import load_dotenv

from extractor import Invoice, extract_invoice_data

load_dotenv()

GROQ_API_KEY = os.getenv("GROQ_API_KEY", "")
GROQ_MODEL = os.getenv("GROQ_MODEL", "llama-3.1-8b-instant")
SAMPLE_DATA = Path(__file__).parent / "sample_data.json"

st.set_page_config(page_title="Procesador de Facturas IA", page_icon="🧾", layout="wide")
st.title("🧾 Procesador de Facturas con IA")
st.caption("Sube tus facturas en PDF y obtén un dashboard completo en segundos.")

# ── Sidebar ──────────────────────────────────────────────────────────────────
with st.sidebar:
    st.header("⚙️ Configuración")
    model = st.selectbox("Modelo Groq", ["llama-3.1-8b-instant", "llama-3.3-70b-versatile"], index=0)
    st.divider()
    uploaded_files = st.file_uploader(
        "📂 Sube tus facturas (PDF)",
        type=["pdf"],
        accept_multiple_files=True,
    )
    process_btn = st.button("🚀 Procesar Facturas", use_container_width=True, type="primary",
                            disabled=not uploaded_files)
    st.divider()
    if st.button("🔄 Cargar datos de ejemplo", use_container_width=True):
        st.session_state.pop("invoices_df", None)
        st.session_state["use_sample"] = True
        st.rerun()

# ── Load sample data on first visit ──────────────────────────────────────────
if "invoices_df" not in st.session_state and not uploaded_files:
    if SAMPLE_DATA.exists():
        records = json.loads(SAMPLE_DATA.read_text(encoding="utf-8"))
        st.session_state["invoices_df"] = pd.DataFrame(records)
        st.session_state["is_sample"] = True

# ── Process uploaded files ────────────────────────────────────────────────────
if process_btn and uploaded_files:
    if not GROQ_API_KEY:
        st.error("No se encontró GROQ_API_KEY. Añádela al fichero .env", icon="🔑")
        st.stop()

    from groq import Groq
    client = Groq(api_key=GROQ_API_KEY)
    invoices: list[Invoice] = []

    progress = st.progress(0, text="Procesando facturas...")
    for i, uploaded_file in enumerate(uploaded_files):
        progress.progress((i + 1) / len(uploaded_files), text=f"Procesando {uploaded_file.name}...")
        tmp_path = Path(tempfile.gettempdir()) / uploaded_file.name
        tmp_path.write_bytes(uploaded_file.read())
        invoice = extract_invoice_data(str(tmp_path), client, GROQ_MODEL)
        invoices.append(invoice)
        tmp_path.unlink(missing_ok=True)

    progress.empty()
    df = pd.DataFrame([inv.model_dump() for inv in invoices])
    df.insert(0, "archivo", [f.name for f in uploaded_files])
    st.session_state["invoices_df"] = df
    st.session_state["is_sample"] = False
    st.success(f"✅ {len(invoices)} facturas procesadas correctamente.")

# ── Dashboard ─────────────────────────────────────────────────────────────────
if "invoices_df" not in st.session_state:
    st.stop()

df: pd.DataFrame = st.session_state["invoices_df"]

if st.session_state.get("is_sample"):
    st.info("Mostrando datos de ejemplo. Sube tus propias facturas PDF para analizarlas.", icon="📊")

# ── KPI Cards ──
col1, col2, col3, col4 = st.columns(4)
col1.metric("💶 Gasto Total", f"{df['total'].sum():,.2f} €")
col2.metric("🏦 IVA Total", f"{df['iva_importe'].sum():,.2f} €")
col3.metric("📄 Facturas", len(df))
col4.metric("🏢 Proveedores", df["proveedor"].nunique())

st.divider()

# ── Charts ──
col_left, col_right = st.columns(2)

with col_left:
    st.subheader("Gasto por Categoría")
    cat_df = df.groupby("categoria")["total"].sum().reset_index()
    fig_cat = px.pie(cat_df, values="total", names="categoria", hole=0.4,
                     color_discrete_sequence=px.colors.qualitative.Set3)
    fig_cat.update_traces(textposition="inside", textinfo="percent+label")
    st.plotly_chart(fig_cat, use_container_width=True)

with col_right:
    st.subheader("Gasto por Proveedor")
    prov_df = df.groupby("proveedor")["total"].sum().reset_index().sort_values("total", ascending=True)
    fig_prov = px.bar(prov_df, x="total", y="proveedor", orientation="h",
                      color="total", color_continuous_scale="Blues",
                      labels={"total": "Importe (€)", "proveedor": ""})
    fig_prov.update_layout(coloraxis_showscale=False)
    st.plotly_chart(fig_prov, use_container_width=True)

# Timeline chart
df_dates = df.dropna(subset=["fecha"]).copy()
if not df_dates.empty:
    st.subheader("Evolución de Gastos por Fecha")
    df_dates["fecha"] = pd.to_datetime(df_dates["fecha"], errors="coerce")
    df_dates = df_dates.dropna(subset=["fecha"]).sort_values("fecha")
    fig_time = px.bar(df_dates, x="fecha", y="total", color="categoria",
                      labels={"total": "Importe (€)", "fecha": "Fecha"},
                      color_discrete_sequence=px.colors.qualitative.Set2)
    st.plotly_chart(fig_time, use_container_width=True)

# ── Data Table ──
st.subheader("📋 Detalle de Facturas")
display_cols = ["archivo", "proveedor", "numero_factura", "fecha", "concepto",
                "categoria", "subtotal", "iva_porcentaje", "iva_importe", "total", "moneda"]
st.dataframe(
    df[display_cols].style.format({
        "subtotal": "{:.2f}",
        "iva_importe": "{:.2f}",
        "total": "{:.2f}",
        "iva_porcentaje": "{:.1f}%",
    }, na_rep="—"),
    use_container_width=True,
    hide_index=True,
)

# ── Export ──
st.subheader("⬇️ Exportar")
col_e1, col_e2 = st.columns(2)

with col_e1:
    csv = df.to_csv(index=False).encode("utf-8")
    st.download_button("📥 Descargar CSV", csv, "facturas.csv", "text/csv", use_container_width=True)

with col_e2:
    excel_buf = io.BytesIO()
    with pd.ExcelWriter(excel_buf, engine="openpyxl") as writer:
        df.to_excel(writer, index=False, sheet_name="Facturas")
        cat_df.to_excel(writer, index=False, sheet_name="Por Categoría")
        prov_df.to_excel(writer, index=False, sheet_name="Por Proveedor")
    st.download_button(
        "📊 Descargar Excel",
        excel_buf.getvalue(),
        "facturas.xlsx",
        "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
        use_container_width=True,
    )