Create dora_ict_asset_register.py

tools/dora_ict_asset_register.py

@@ -1,4 +1,4 @@
-# tools/dora_ict_asset_register.py
+# dora_ict_asset_register.py
 import datetime
 import re
 from fpdf import FPDF
@@ -18,7 +18,7 @@ def export_text_to_pdf(text, metadata=None, output_path=None, language="en"):
 
     pdf.set_font("Arial", 'B', 16)
     pdf.set_text_color(0, 51, 102)
-    title = "ICT Asset Register - DORA" if language == "en" else "Registre des actifs TIC - DORA"
+    title = "ICT Asset Register - DORA" if language == "en" else "Registre des Actifs TIC - DORA"
     pdf.cell(0, 15, title, ln=True, align='C')
     pdf.ln(10)
 
@@ -33,6 +33,7 @@ def export_text_to_pdf(text, metadata=None, output_path=None, language="en"):
     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)
@@ -44,27 +45,27 @@ def export_text_to_pdf(text, metadata=None, output_path=None, language="en"):
         elif line.startswith("- **"):
             match = re.match(r"- \*\*(.+?)\*\*: (.+)", line)
             if match:
-                label, answer = match.groups()
+                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, answer)
+                pdf.multi_cell(0, 10, value)
+        elif line == "---":
+            pdf.line(10, pdf.get_y(), 200, pdf.get_y())
+            pdf.ln(5)
         else:
             pdf.multi_cell(0, 10, line)
     pdf.output(output_path)
     return output_path
 
-
 # === Questions ===
 QUESTIONS = prepend_metadata_questions([
-    ("asset_name", "What is the name of the ICT asset?"),
-    ("asset_type", "What type of asset is it (e.g., hardware, software)?"),
-    ("location", "Where is the asset located or hosted?"),
-    ("owner", "Who is the asset owner or custodian?"),
-    ("sensitivity", "What is the asset's sensitivity level (low, medium, high)?"),
-    ("dependencies", "Are there any system or data dependencies?"),
-    ("maintenance", "What is the maintenance or update policy?"),
-    ("retirement", "What is the asset's planned retirement date or process?")
+    ("ict_assets", "List all ICT assets supporting critical or important functions."),
+    ("ownership", "Who owns and manages each asset?"),
+    ("location", "Where are the assets physically or virtually located?"),
+    ("configuration", "Provide key configuration or setup details."),
+    ("maintenance_schedule", "What is the maintenance or review schedule?"),
+    ("security_measures", "What security controls are in place for each asset?")
 ])
 
 
@@ -88,13 +89,6 @@ def run_tool():
             state["step"] += 1
             return next_question, state, None
 
-        # Safe language detection
-        try:
-            content = "\n".join([f"- **{label}**: {answers.get(key, '')}" for key, label in QUESTIONS])
-            detected_lang = detect(content) if len(content.strip()) > 10 else "en"
-        except:
-            detected_lang = "en"
-
         metadata = {
             "user_name": answers.get("user_name", "N/A"),
             "user_role": answers.get("user_role", "N/A"),
@@ -102,11 +96,13 @@ def run_tool():
             "timestamp": datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
         }
 
-        pdf_path = export_text_to_pdf(content, metadata=metadata, language=detected_lang)
-        return "✅ ICT Asset Register completed. Download your PDF below.", {"done": True}, pdf_path
+        content = "\n".join([f"- **{label}**: {answers.get(key, '')}" for key, label in QUESTIONS])
+        lang = detect(content if len(content.strip()) > 3 else "This is a placeholder text.")
+        pdf_path = export_text_to_pdf(content, metadata=metadata, language=lang)
+        return "✅ Register created successfully. Download your PDF below.", {"done": True}, pdf_path
 
-    with gr.Blocks(title="DORA - ICT Asset Register") as demo:
-        chatbot = gr.Chatbot(label="🖥️ ICT Asset Assistant", value=[{"role": "assistant", "content": QUESTIONS[0][1]}], type="messages")
+    with gr.Blocks(title="DORA ICT Asset Register") as demo:
+        chatbot = gr.Chatbot(label="💻 ICT Asset Register 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")