Update Gradio_UI.py

Gradio_UI.py

@@ -1,38 +1,112 @@
-# Gradio_UI.py
+# gradio_UI.py
 import gradio as gr
 from fpdf import FPDF
 from langdetect import detect
 import time
 
-def export_text_to_pdf(text, lang="en"):
+# === Define documents/questions structure ===
+DOCUMENTS = {
+    "AI Act": {
+        "Compliance Register": [
+            ("organization_name", "What is the name of your organization?"),
+            ("responsible_person", "Who is responsible for this AI system?"),
+            ("deployment_date", "When is the AI system scheduled to be deployed?"),
+            ("ai_type", "What type of AI system is it?"),
+            ("ai_description", "What does the system do?"),
+            ("risk_level", "What is the risk level?"),
+            ("risk_justification", "Why this level?"),
+        ],
+        "High-Risk System Record": [
+            ("organization_name", "Organization name?"),
+            ("system_purpose", "Purpose of the high-risk AI system?"),
+            ("annex_category", "Which Annex III category applies?"),
+            ("risk_controls", "Risk mitigation measures?"),
+        ]
+    },
+    "GDPR": {
+        "Data Processing Record": [
+            ("data_controller", "Who is the data controller?"),
+            ("legal_basis", "Legal basis for processing?"),
+            ("data_subjects", "Categories of data subjects?"),
+            ("data_retention", "Retention period for data?"),
+        ]
+    }
+}
+
+# === PDF Export ===
+def export_pdf(title, answers, lang="en"):
     pdf = FPDF()
     pdf.add_page()
-    pdf.set_font("Arial", size=12)
-    title = "AI Act Compliance Register" if lang == "en" else "Registre de Conformité AI Act"
-    pdf.multi_cell(0, 10, title + "\n\n" + text)
-    
-    # Make filename unique
-    filename = f"ai_act_register_{int(time.time())}.pdf"
-    output_path = f"./{filename}"
-    pdf.output(output_path)
-    return output_path
-
-def handle_message(user_input):
-    response = f"📋 Received: {user_input}\n\n✅ Here's your compliance summary."
-    pdf_path = export_text_to_pdf(response, lang=detect(user_input))
-    return response, pdf_path
-
-# Gradio app to be called from Django
-demo = gr.Interface(
-    fn=handle_message,
-    inputs=gr.Textbox(label="Your Message"),
-    outputs=[
-        gr.Text(label="Reply"),
-        gr.File(label="Download PDF")
-    ],
-    title="AI Act Assistant (via Proxy)",
-    allow_flagging="never"
-)
-
-if __name__ == "__main__":
-    demo.launch()
+    pdf.set_auto_page_break(auto=True, margin=15)
+    pdf.set_font("Arial", 'B', 16)
+    pdf.set_text_color(0, 51, 102)
+    pdf.cell(0, 10, title, ln=True, align='C')
+    pdf.ln(10)
+
+    pdf.set_font("Arial", '', 12)
+    pdf.set_text_color(0, 0, 0)
+    for label, value in answers.items():
+        pdf.set_font("Arial", 'B', 12)
+        pdf.multi_cell(0, 10, f"{label}:", align='L')
+        pdf.set_font("Arial", '', 12)
+        pdf.multi_cell(0, 10, value)
+        pdf.ln(5)
+
+    filename = f"{title.replace(' ', '_')}_{int(time.time())}.pdf"
+    pdf.output(filename)
+    return filename
+
+# === App State ===
+conversation_state = {
+    "step": 0,
+    "questions": [],
+    "answers": {},
+    "title": "",
+    "lang": "en"
+}
+
+def start_conversation(reg, doc):
+    conversation_state["step"] = 0
+    conversation_state["answers"] = {}
+    conversation_state["questions"] = DOCUMENTS[reg][doc]
+    conversation_state["title"] = f"{reg} - {doc}"
+    return f"📋 {conversation_state['questions'][0][1]}"
+
+def continue_conversation(user_input):
+    step = conversation_state["step"]
+    if step < len(conversation_state["questions"]):
+        key, question = conversation_state["questions"][step]
+        conversation_state["answers"][question] = user_input
+        conversation_state["step"] += 1
+        conversation_state["lang"] = detect(user_input)
+
+    if conversation_state["step"] < len(conversation_state["questions"]):
+        next_question = conversation_state["questions"][conversation_state["step"]][1]
+        return f"🧠 {next_question}", None
+    else:
+        pdf_path = export_pdf(conversation_state["title"], conversation_state["answers"], lang=conversation_state["lang"])
+        return "✅ Done! Your document is ready to download.", pdf_path
+
+# === Gradio UI ===
+with gr.Blocks(title="Regulatory Compliance Generator") as demo:
+    gr.Markdown("## 📑 Regulation Document Generator")
+
+    with gr.Row():
+        reg_dropdown = gr.Dropdown(choices=list(DOCUMENTS.keys()), label="Select Regulation")
+        doc_dropdown = gr.Dropdown(label="Select Document Type")
+
+    reg_dropdown.change(lambda r: list(DOCUMENTS[r].keys()), inputs=reg_dropdown, outputs=doc_dropdown)
+
+    start_btn = gr.Button("🚀 Start")
+    chatbox = gr.Chatbot(label="🧑‍⚖️ Legalbot")
+    user_input = gr.Textbox(label="Your answer")
+    pdf_output = gr.File(label="Download PDF", visible=True)
+
+    def reset():
+        return "", "", "", [], None
+
+    start_btn.click(start_conversation, inputs=[reg_dropdown, doc_dropdown], outputs=chatbox)
+    user_input.submit(continue_conversation, inputs=user_input, outputs=[chatbox, pdf_output])
+    user_input.submit(lambda: "", None, user_input)
+
+demo.launch()