Update tools/ai_act_generator.py

tools/ai_act_generator.py

@@ -2,23 +2,14 @@
 # coding=utf-8
 import csv
 import datetime
-import mimetypes
 import os
 import re
-import shutil
-from typing import Optional
-
-from smolagents.agent_types import AgentAudio, AgentImage, AgentText, handle_agent_output_types
-from smolagents.agents import ActionStep, MultiStepAgent
-from smolagents.memory import MemoryStep
-from smolagents.utils import _is_package_available
-
-import gradio as gr
 from fpdf import FPDF
+import gradio as gr
 from langdetect import detect
 
-# === PDF Export Function with Language Option ===
-def export_text_to_pdf(text, output_path=None, language="fr"):
+# === PDF Export Function with Metadata ===
+def export_text_to_pdf(text, output_path=None, language="fr", metadata=None):
     if output_path is None:
         timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
         output_path = f"ai_act_register_{timestamp}.pdf"
@@ -32,20 +23,21 @@ def export_text_to_pdf(text, output_path=None, language="fr"):
     pdf.set_text_color(0, 51, 102)
     title = "Documentation Record for High-Risk AI Systems" if language == "en" else "Registre de Conformité AI Act"
     pdf.cell(0, 15, title, ln=True, align='C')
-    pdf.ln(10)
+    pdf.ln(8)
 
-    # Subtitle
-    pdf.set_font("Arial", 'I', 12)
+    # Subtitle / Metadata
+    pdf.set_font("Arial", '', 12)
     pdf.set_text_color(90, 90, 90)
-    subtitle = f"Generated on {datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S')}"
-    pdf.cell(0, 10, subtitle, ln=True, align='C')
-    pdf.ln(5)
+    if metadata:
+        pdf.multi_cell(0, 10, f"🏢 Organization: {metadata.get('organization_name', 'N/A')}")
+        pdf.multi_cell(0, 10, f"👤 Completed by: {metadata.get('responsible_person', 'N/A')}")
+        pdf.multi_cell(0, 10, f"🕒 Completion Date: {metadata.get('timestamp', datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S'))}")
+        pdf.ln(5)
 
     # Reset style for body
     pdf.set_font("Arial", '', 12)
     pdf.set_text_color(0, 0, 0)
 
-    # Parse and format sections
     for line in text.strip().split('\n'):
         line = line.strip()
         if line.startswith("## "):
@@ -58,15 +50,15 @@ def export_text_to_pdf(text, output_path=None, language="fr"):
             pdf.set_font("Arial", '', 12)
             pdf.set_text_color(0, 0, 0)
         elif line.startswith("- **"):
-            key_value = re.match(r"- \*\*(.+?)\*\*: (.+)", line)
-            if key_value:
-                label, answer = key_value.groups()
+            match = re.match(r"- \*\*(.+?)\*\*: (.+)", line)
+            if match:
+                label, answer = 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, f"{answer}")
+                pdf.multi_cell(0, 10, answer)
                 pdf.ln(2)
-        elif line.strip() == "---":
+        elif line == "---":
             pdf.line(10, pdf.get_y(), 200, pdf.get_y())
             pdf.ln(5)
         else:
@@ -76,7 +68,7 @@ def export_text_to_pdf(text, output_path=None, language="fr"):
     pdf.output(output_path)
     return output_path
 
-# === Sequential Questions ===
+# === Questions ===
 QUESTIONS = [
     ("organization_name", "What is the name of your organization?"),
     ("responsible_person", "Who is responsible for this AI system?"),
@@ -93,9 +85,7 @@ QUESTIONS = [
     ("compliance_contact", "Who is the contact person for compliance (email or name)?")
 ]
 
-RESPONSES = {}
-
-# === Interactive Collection Flow ===
+# === Agent Logic ===
 def step_by_step_agent(user_input, state):
     if state is None:
         state = {"step": 0, "answers": {}}
@@ -110,7 +100,7 @@ def step_by_step_agent(user_input, state):
     if step < len(QUESTIONS):
         next_question = QUESTIONS[step][1]
         state["step"] += 1
-        return next_question, state, None  # Ensure return matches expected 3 outputs
+        return next_question, state, None
 
     filled_template = f"""
 # AI Act Compliance Register
@@ -140,14 +130,11 @@ def step_by_step_agent(user_input, state):
 Generated by AI Act Assistant.
 """
 
-    
-
     try:
         detected_lang = detect(filled_template)
     except:
         detected_lang = "en"
 
-    flag = "🇬🇧" if detected_lang == "en" else "🇫🇷"
     # Save to CSV
     csv_file = "ai_act_registers.csv"
     fieldnames = [key for key, _ in QUESTIONS] + ["timestamp"]
@@ -160,44 +147,43 @@ Generated by AI Act Assistant.
             writer.writeheader()
         writer.writerow(row_data)
 
-    pdf_path = export_text_to_pdf(filled_template, language=detected_lang)
-    return f"""{flag} Language detected: {detected_lang.upper()}
-✅ All answers received. Your PDF is ready below:
-👉 Click the download button to save your AI Act compliance register.""", {"done": True, "pdf": pdf_path}, pdf_path
+    # PDF Export
+    pdf_path = export_text_to_pdf(
+        filled_template,
+        language=detected_lang,
+        metadata={
+            "organization_name": answers.get("organization_name", ""),
+            "responsible_person": answers.get("responsible_person", ""),
+            "timestamp": datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S')
+        }
+    )
+
+    return f"✅ All answers received. Your PDF is ready below:", {"done": True, "pdf": pdf_path}, pdf_path
 
-# === UI for Step-by-Step Form ===
+# === Gradio UI ===
 def launch_step_by_step_ui():
-    with gr.Blocks(fill_height=True) as demo:
-        initial_question = QUESTIONS[0][1]
-        initial_message = gr.ChatMessage(role="assistant", content="""
-👋 Welcome! I will guide you through the AI Act compliance form.
-Let's begin with a few questions to generate your compliance register.
-
-What is the name of your organization?
-""")
-        stored_messages = [initial_message]
-        chatbot = gr.Chatbot(type="messages", value=stored_messages)
+    with gr.Blocks(title="AI Act Compliance Register") as demo:
+        chatbot = gr.Chatbot(label="📘 AI Act Assistant", type="messages")
         msg = gr.Textbox(label="Your answer")
         state = gr.State()
         file_output = gr.File(label="Download PDF", visible=True)
-        restart_button = gr.Button("🔁 Restart")
+        restart_btn = gr.Button("🔁 Restart")
 
-        def chat_logic(user_msg, state):
-            reply, updated_state, file_path = step_by_step_agent(user_msg, state)
-            messages = [gr.ChatMessage(role="user", content=user_msg)]
+        initial_q = QUESTIONS[0][1]
+        chatbot.value = [gr.ChatMessage(role="assistant", content=f"👋 Welcome! Let's begin.\n\n{initial_q}")]
 
-            if isinstance(reply, str):
+        def chat_logic(user_msg, state_in):
+            reply, state_out, file_path = step_by_step_agent(user_msg, state_in)
+            messages = [gr.ChatMessage(role="user", content=user_msg)]
+            if reply:
                 messages.append(gr.ChatMessage(role="assistant", content=reply))
+            return messages, state_out, file_path
 
-            if not file_path or not os.path.isfile(file_path):
-                file_path = None
-            return messages, updated_state, file_path
-
-        def restart_conversation():
-            return [initial_message], {"step": 0, "answers": {}}, None
+        def restart():
+            return [gr.ChatMessage(role="assistant", content=initial_q)], {"step": 0, "answers": {}}, None
 
         msg.submit(chat_logic, [msg, state], [chatbot, state, file_output])
-        restart_button.click(restart_conversation, outputs=[chatbot, state, file_output])
+        restart_btn.click(restart, outputs=[chatbot, state, file_output])
 
     demo.launch()
 
@@ -205,5 +191,4 @@ def get_questions():
     return QUESTIONS
 
 def run_tool():
-    return launch_step_by_step_ui()
-
+    launch_step_by_step_ui()