Dave67350/First_agent_template

1# dora_communication_tree.py2import datetime3import re4from fpdf import FPDF5from langdetect import detect6import gradio as gr7from tools.common import prepend_metadata_questions8 9# === PDF Export ===10def export_text_to_pdf(text, metadata=None, output_path=None, language="en"):11    if output_path is None:12        timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")13        output_path = f"communication_tree_{timestamp}.pdf"14 15    pdf = FPDF()16    pdf.add_page()17    pdf.set_auto_page_break(auto=True, margin=15)18 19    pdf.set_font("Arial", 'B', 16)20    pdf.set_text_color(0, 51, 102)21    title = "Communication Tree (Crisis) - DORA (Optional)" if language == "en" else "Arbre de Communication (Crise) - DORA"22    pdf.cell(0, 15, title, ln=True, align='C')23    pdf.ln(10)24 25    if metadata:26        pdf.set_font("Arial", '', 12)27        pdf.set_text_color(90, 90, 90)28        pdf.multi_cell(0, 10, f"Organization: {metadata.get('organization_name', 'N/A')}")29        pdf.multi_cell(0, 10, f"Completed by: {metadata.get('user_name', 'N/A')} ({metadata.get('user_role', 'N/A')})")30        pdf.multi_cell(0, 10, f"Timestamp: {metadata.get('timestamp', 'N/A')}")31        pdf.ln(5)32 33    pdf.set_font("Arial", '', 12)34    pdf.set_text_color(0, 0, 0)35    for line in text.strip().split('\n'):36        line = line.strip()37        if line.startswith("## "):38            section = line.replace("## ", "").strip()39            pdf.set_font("Arial", 'B', 13)40            pdf.set_text_color(30, 30, 120)41            pdf.ln(8)42            pdf.cell(0, 10, section, ln=True)43            pdf.set_font("Arial", '', 12)44            pdf.set_text_color(0, 0, 0)45        elif line.startswith("- **"):46            match = re.match(r"- \*\*(.+?)\*\*: (.+)", line)47            if match:48                label, value = match.groups()49                pdf.set_font("Arial", 'B', 12)50                pdf.cell(0, 10, f"{label}:", ln=True)51                pdf.set_font("Arial", '', 12)52                pdf.multi_cell(0, 10, value)53        elif line == "---":54            pdf.line(10, pdf.get_y(), 200, pdf.get_y())55            pdf.ln(5)56        else:57            pdf.multi_cell(0, 10, line)58    pdf.output(output_path)59    return output_path60 61# === Questions ===62QUESTIONS = prepend_metadata_questions([63    ("crisis_scenarios", "What are the possible crisis scenarios identified?"),64    ("primary_contacts", "Who are the primary individuals or roles in the communication chain?"),65    ("communication_channels", "What channels (email, phone, SMS, etc.) will be used?"),66    ("fallback_contacts", "Are there backup contacts for each role?"),67    ("timing_expectations", "What are the expected timeframes for each level of response?"),68    ("escalation_protocols", "Describe the escalation protocols in place."),69    ("documentation_method", "How will communication and responses be documented?")70])71 72 73def get_questions():74    return QUESTIONS75 76 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_question = QUESTIONS[step][1]90            state["step"] += 191            return next_question, state, None92 93        metadata = {94            "user_name": answers.get("user_name", "N/A"),95            "user_role": answers.get("user_role", "N/A"),96            "organization_name": answers.get("organization_name", "N/A"),97            "timestamp": datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")98        }99 100        content = "\n".join([f"- **{label}**: {answers.get(key, '')}" for key, label in QUESTIONS])101        lang = detect(content if len(content.strip()) > 3 else "Placeholder content")102        pdf_path = export_text_to_pdf(content, metadata=metadata, language=lang)103        return "✅ Communication Tree generated. Download your file below.", {"done": True}, pdf_path104 105    with gr.Blocks(title="DORA Communication Tree") as demo:106        chatbot = gr.Chatbot(label="📞 Communication Tree Assistant", value=[{"role": "assistant", "content": QUESTIONS[0][1]}], type="messages")107        msg = gr.Textbox(label="Your answer")108        state_var = gr.State(state)109        file_output = gr.File(label="Download PDF")110        reset_btn = gr.Button("🔁 Restart")111 112        def chat_logic(msg_in, state_in):113            reply, updated_state, file = step_by_step_agent(msg_in, state_in)114            messages = [{"role": "user", "content": msg_in}]115            if reply:116                messages.append({"role": "assistant", "content": reply})117            return messages, updated_state, file118 119        def reset():120            return [{"role": "assistant", "content": QUESTIONS[0][1]}], {"step": 0, "answers": {}}, None121 122        msg.submit(chat_logic, [msg, state_var], [chatbot, state_var, file_output])123        reset_btn.click(reset, outputs=[chatbot, state_var, file_output])124 125    demo.launch(show_api=False)126