# tools/gdpr_dpia_template.py
import datetime
import re
from fpdf import FPDF
from langdetect import detect
import gradio as gr
from tools.common import prepend_metadata_questions

# === PDF Export Function ===
def export_text_to_pdf(text, metadata=None, output_path=None, language="en"):
    if output_path is None:
        timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
        output_path = f"gdpr_dpia_{timestamp}.pdf"

    pdf = FPDF()
    pdf.add_page()
    pdf.set_auto_page_break(auto=True, margin=15)

    pdf.set_font("Arial", 'B', 16)
    pdf.set_text_color(0, 51, 102)
    title = "Data Protection Impact Assessment (DPIA)" if language == "en" else "Analyse d'Impact sur la Protection des Données (AIPD)"
    pdf.cell(0, 15, title, ln=True, align='C')
    pdf.ln(10)

    if metadata:
        pdf.set_font("Arial", '', 12)
        pdf.set_text_color(90, 90, 90)
        pdf.multi_cell(0, 10, f"Organization: {metadata.get('organization', 'N/A')}")
        pdf.multi_cell(0, 10, f"Completed by: {metadata.get('completed_by', 'N/A')} ({metadata.get('role', 'N/A')})")
        pdf.multi_cell(0, 10, f"Timestamp: {metadata.get('timestamp', 'N/A')}")
        pdf.ln(5)

    pdf.set_font("Arial", '', 12)
    pdf.set_text_color(0, 0, 0)
    for line in text.strip().split('\n'):
        line = line.strip()
        if line.startswith("## "):
            section = line.replace("## ", "").strip()
            pdf.set_font("Arial", 'B', 13)
            pdf.set_text_color(30, 30, 120)
            pdf.ln(8)
            pdf.cell(0, 10, section, ln=True)
            pdf.set_font("Arial", '', 12)
            pdf.set_text_color(0, 0, 0)
        elif line.startswith("- **"):
            match = re.match(r"- \*\*(.+?)\*\*: (.+)", line)
            if match:
                label, value = match.groups()
                pdf.set_font("Arial", 'B', 12)
                pdf.cell(0, 10, f"{label}:", ln=True)
                pdf.set_font("Arial", '', 12)
                pdf.multi_cell(0, 10, value)
        else:
            pdf.multi_cell(0, 10, line)

    pdf.output(output_path)
    return output_path

# === DPIA Questions ===
BASE_QUESTIONS = [
    ("processing_description", "Describe the processing activity and purpose."),
    ("necessity_proportionality", "Why is the processing necessary and proportionate?"),
    ("risks", "What are the data protection risks?"),
    ("measures", "What safeguards are implemented to mitigate risks?"),
    ("consultation", "Was the DPO or public consulted?"),
    ("outcome", "Summary of the assessment's outcome.")
]

QUESTIONS = prepend_metadata_questions(BASE_QUESTIONS)

def get_questions():
    return QUESTIONS

def run_tool():
    state = {"step": 0, "answers": {}}

    def step_by_step_agent(user_input, state):
        step = state["step"]
        answers = state["answers"]

        if step > 0:
            key, _ = QUESTIONS[step - 1]
            answers[key] = user_input

        if step < len(QUESTIONS):
            next_q = QUESTIONS[step][1]
            state["step"] += 1
            return next_q, state, None

        content = "\n".join([f"- **{label}**: {answers.get(key, '')}" for key, label in QUESTIONS])
        lang = detect(content)
        metadata = {
            "organization": answers.get("organization", "N/A"),
            "completed_by": answers.get("completed_by", "N/A"),
            "role": answers.get("role", "N/A"),
            "timestamp": datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
        }
        pdf_path = export_text_to_pdf(content, metadata=metadata, language=lang)
        return "✅ DPIA completed. Download below:", {"done": True}, pdf_path

    with gr.Blocks(title="GDPR DPIA Tool") as demo:
        chatbot = gr.Chatbot(label="🔍 GDPR DPIA Assistant", value=[{"role": "assistant", "content": QUESTIONS[0][1]}], type="messages")
        msg = gr.Textbox(label="Your answer")
        state_var = gr.State(state)
        file_output = gr.File(label="Download PDF")
        reset_btn = gr.Button("🔁 Restart")

        def chat_logic(msg_in, state_in):
            reply, updated_state, file = step_by_step_agent(msg_in, state_in)
            messages = [{"role": "user", "content": msg_in}]
            if reply:
                messages.append({"role": "assistant", "content": reply})
            return messages, updated_state, file

        def reset():
            return [{"role": "assistant", "content": QUESTIONS[0][1]}], {"step": 0, "answers": {}}, None

        msg.submit(chat_logic, [msg, state_var], [chatbot, state_var, file_output])
        reset_btn.click(reset, outputs=[chatbot, state_var, file_output])

    demo.launch(show_api=False)