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72e320d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 | # 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)
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