Dave67350/First_agent_template

1# tools/dma_transparency_log.py2 3import datetime4import re5from fpdf import FPDF6from langdetect import detect7import gradio as gr8from tools.common import prepend_metadata_questions9 10# === PDF Export Function ===11def export_text_to_pdf(text, metadata=None, output_path=None, language="en"):12    if output_path is None:13        timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")14        output_path = f"dma_transparency_log_{timestamp}.pdf"15 16    pdf = FPDF()17    pdf.add_page()18    pdf.set_auto_page_break(auto=True, margin=15)19 20    # Title21    pdf.set_font("Arial", 'B', 16)22    pdf.set_text_color(0, 51, 102)23    title = "DMA Transparency Log" if language == "en" else "Journal de Transparence DMA"24    pdf.cell(0, 15, title, ln=True, align='C')25    pdf.ln(10)26 27    # Metadata Section28    if metadata:29        pdf.set_font("Arial", '', 12)30        pdf.set_text_color(90, 90, 90)31        pdf.multi_cell(0, 10, f"Organization: {metadata.get('organization', 'N/A')}")32        pdf.multi_cell(0, 10, f"Completed by: {metadata.get('name', 'N/A')} ({metadata.get('role', 'N/A')})")33        pdf.multi_cell(0, 10, f"Timestamp: {metadata.get('timestamp', 'N/A')}")34        pdf.ln(5)35 36    # Main Content37    pdf.set_font("Arial", '', 12)38    pdf.set_text_color(0, 0, 0)39 40    for line in text.strip().split('\n'):41        if line.startswith("## "):42            section = line.replace("## ", "").strip()43            pdf.set_font("Arial", 'B', 13)44            pdf.set_text_color(30, 30, 120)45            pdf.ln(8)46            pdf.cell(0, 10, section, ln=True)47            pdf.set_font("Arial", '', 12)48            pdf.set_text_color(0, 0, 0)49        elif line.startswith("- **"):50            match = re.match(r"- \*\*(.+?)\*\*: (.+)", line)51            if match:52                label, value = match.groups()53                pdf.set_font("Arial", 'B', 12)54                pdf.cell(0, 10, f"{label}:", ln=True)55                pdf.set_font("Arial", '', 12)56                pdf.multi_cell(0, 10, value)57        else:58            pdf.multi_cell(0, 10, line)59 60    pdf.output(output_path)61    return output_path62 63# === Questions ===64QUESTIONS = prepend_metadata_questions([65    ("purpose", "What was the purpose of the communication or update?"),66    ("audience", "Who was the target audience (e.g. regulators, users, public)?"),67    ("content_summary", "Provide a brief summary of the information disclosed."),68    ("disclosure_date", "When was this information disclosed?"),69    ("channel", "Through what channel was the disclosure made (e.g. website, press release)?"),70    ("legal_reference", "Which DMA article or obligation does it correspond to?")71])72 73def get_questions():74    return QUESTIONS75 76# === Run Tool ===77def run_tool():78    state = {"step": 0, "answers": {}}79 80    def step_by_step_agent(user_input, state):81        step = state["step"]82        answers = state["answers"]83 84        if step > 0:85            key, _ = QUESTIONS[step - 1]86            answers[key] = user_input87 88        if step < len(QUESTIONS):89            next_q = QUESTIONS[step][1]90            state["step"] += 191            return next_q, state, None92 93        # Compile content94        content = "\n".join([f"- **{label}**: {answers.get(key, '')}" for key, label in QUESTIONS])95        language = detect(content) if len(content.strip()) > 3 else "en"96        metadata = {97            "organization": answers.get("organization_name", "N/A"),98            "name": answers.get("user_name", "N/A"),99            "role": answers.get("user_role", "N/A"),100            "timestamp": datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")101        }102        pdf_path = export_text_to_pdf(content, metadata=metadata, language=language)103        return "✅ Transparency log completed. Download your PDF below.", {"done": True}, pdf_path104 105    # Gradio Interface106    with gr.Blocks(title="DMA Transparency Log") as demo:107        chatbot = gr.Chatbot(label="🔍 Transparency Log Assistant", value=[{"role": "assistant", "content": QUESTIONS[0][1]}], type="messages")108        msg = gr.Textbox(label="Your answer")109        state_var = gr.State(state)110        file_output = gr.File(label="Download PDF")111        reset_btn = gr.Button("🔁 Restart")112 113        def chat_logic(msg_in, state_in):114            reply, updated_state, file = step_by_step_agent(msg_in, state_in)115            messages = [{"role": "user", "content": msg_in}]116            if reply:117                messages.append({"role": "assistant", "content": reply})118            return messages, updated_state, file119 120        def reset():121            return [{"role": "assistant", "content": QUESTIONS[0][1]}], {"step": 0, "answers": {}}, None122 123        msg.submit(chat_logic, [msg, state_var], [chatbot, state_var, file_output])124        reset_btn.click(reset, outputs=[chatbot, state_var, file_output])125 126    demo.launch(show_api=False)127