# app.py
from __future__ import annotations
import os, time, json
from pathlib import Path
from datetime import datetime
from typing import List, Tuple, Dict, Any
import gradio as gr
from lexie.call_agent import route as call_route
from lexie.pdf_reporter import generate_report

BASE_DIR = Path(__file__).resolve().parent
RUNTIME_BASE = Path("/data/lexie") if Path("/data").exists() else (BASE_DIR / "runtime")
RUNTIME_LOGS = RUNTIME_BASE / "logs"
RUNTIME_OUT  = RUNTIME_BASE / "outputs"

MAX_PDF_MB   = 10
DEFAULT_POLICIES = ["gdpr", "ai_act"]

def _ensure_dirs() -> None:
    RUNTIME_LOGS.mkdir(parents=True, exist_ok=True)
    RUNTIME_OUT.mkdir(parents=True, exist_ok=True)

def _ts() -> str:
    return datetime.now().strftime("%Y%m%d-%H%M%S")

def _risk_badge(result: Dict[str, Any]) -> str:
    score = int(result.get("risk_score", 0))
    level = str(result.get("risk_level", "unknown")).lower()
    color = {"low": "green", "medium": "orange", "high": "red"}.get(level, "gray")
    fname = result.get("document_name") or ""
    file_str = f" — **File:** `{fname}`" if fname else ""
    return f"**Risk:** <span style='color:{color};font-weight:bold'>{level.upper()}</span> — **Score:** {score}/100{file_str}"

def _violations_table(result):
    rows = []
    vios  = result.get("violations", []) or []
    cites = result.get("citations", []) or []
    for i, v in enumerate(vios):
        page = cites[i].get("page") if i < len(cites) else None
        page = page if page not in (None, "", "?") else "—"
        rows.append([
            v.get("law", ""),
            v.get("article", "—"),
            v.get("title", ""),
            v.get("reason", ""),
            page,
        ])
    return rows

def _save_json(result: Dict[str, Any]) -> Path:
    _ensure_dirs()
    p = RUNTIME_LOGS / f"result-{_ts()}.json"
    p.write_text(json.dumps(result, ensure_ascii=False, indent=2), encoding="utf-8")
    print(f"[saved JSON] {p}")
    return p

def _gen_pdf(result: Dict[str, Any]) -> Path:
    _ensure_dirs()
    p = RUNTIME_OUT / f"report_{_ts()}.pdf"
    generate_report(result, str(p))
    print(f"[saved PDF] {p}")
    return p

def analyze_interface(
    input_text: str,
    input_pdf_path: str | None,
    policies: List[str],
    top_k: int,
) -> Tuple[str, List[Dict[str, Any]], str | None]:
    if not os.getenv("OPENAI_API_KEY"):
        return ("`OPENAI_API_KEY` is missing. Set it and retry.", [], None)

    input_text = (input_text or "").strip()
    if not input_pdf_path and not input_text:
        return ("Please provide a PDF or some text.", [], None)

    if input_pdf_path:
        try:
            size_mb = os.path.getsize(input_pdf_path) / (1024 * 1024)
        except OSError:
            return ("Uploaded PDF is not readable. Try another file.", [], None)
        if size_mb > MAX_PDF_MB:
            return (f"PDF too large: {size_mb:.1f} MB. Max {MAX_PDF_MB} MB.", [], None)
        payload = {
            "mode": "document",
            "document_path": input_pdf_path,
            "user_text": "",
            "policies": policies or DEFAULT_POLICIES,
            "top_k": int(top_k),
        }
    else:
        payload = {
            "mode": "free_text",
            "document_path": "",
            "user_text": input_text,
            "policies": policies or DEFAULT_POLICIES,
            "top_k": int(top_k),
        }

    result = call_route(payload)

    # Nome file per il badge se PDF
    try:
        if input_pdf_path and payload.get("mode") == "document":
            fname = os.path.basename(input_pdf_path)
            result.setdefault("document_name", fname)
            result.setdefault("document_path", input_pdf_path)
    except Exception:
        pass

    if os.getenv("LEXIE_SAVE_JSON", "0") == "1":
        _save_json(result)

    # Genera PDF scaricabile
    try:
        pdf_path = _gen_pdf(result)
    except Exception:
        badge = _risk_badge(result)
        table = _violations_table(result)
        return (badge + " — PDF generation failed.", table, None)

    badge = _risk_badge(result)
    table = _violations_table(result)
    return (badge, table, str(pdf_path))


def build_ui() -> gr.Blocks:
    _ensure_dirs()
    with gr.Blocks(title="Lexie — Compliance Copilot") as demo:
        gr.Markdown("# Lexie — Compliance Copilot (MVP)")
        gr.Markdown("Upload a **PDF** (≤ 10 MB) or paste **free text**. Policies default to GDPR + AI Act.")

        with gr.Row():
            txt = gr.Textbox(label="Free text", placeholder="Paste your text here...", lines=8)
            pdf = gr.File(label="PDF upload", file_types=[".pdf"], type="filepath")

        with gr.Row():
            policies = gr.CheckboxGroup(choices=["gdpr", "ai_act"], value=DEFAULT_POLICIES, label="Policies")
            topk = gr.Slider(1, 12, value=8, step=1, label="Top-K")

        btn = gr.Button("Analyze", variant="primary")

        out_badge = gr.Markdown(label="Risk")
        out_table = gr.Dataframe(
            headers=["Law", "Article", "Title", "Reason", "Page"],
            label="Violations",
            interactive=False
        )
        out_pdf = gr.File(label="Download report (PDF)")

        btn.click(analyze_interface, inputs=[txt, pdf, policies, topk], outputs=[out_badge, out_table, out_pdf])

        # Nota rimossa: niente messaggi fuorvianti sul salvataggio del PDF
    return demo

if __name__ == "__main__":
    print("Starting Lexie UI...")
    ui = build_ui()
    ui.launch()