app.py

import gradio as gr
from nlp_transform import extract_conditions
from area_calculator import calculate_area, get_missing_keys


def chat(user_input, history):
    try:
        result = extract_conditions(user_input)
        print("🧠 NLP 萃取結果：", result)

        response_lines = []

        # 檢查缺失欄位
        missing = get_missing_keys(result)

        # 顯示已抓到欄位
        if "site_area" in result:
            response_lines.append(f"📏 基地面積：{result['site_area']} m²")
        if "BCR" in result:
            response_lines.append(f"🏗️ 建蔽率：{result['BCR']}%")
        if "FAR" in result:
            response_lines.append(f"🏙️ 容積率：{result['FAR']}%")
        if "bonus_far" in result:
            response_lines.append(f"🎁 容積獎勵：{result['bonus_far']}%")

        # 如果資料齊全 → 計算面積
        if not missing:
            area_result = calculate_area(result)
            response_lines.append(area_result["summary"])
        else:
            response_lines.append("⚠️ 缺少以下資料：" + "、".join(missing))

        final_response = "\n".join(response_lines) if response_lines else "⚠️ 無法辨識有用資訊，請重新描述～"

        # 更新歷史
        new_history = history + [
            {"role": "user", "content": user_input},
            {"role": "assistant", "content": final_response},
        ]
        return new_history, new_history, ""

    except Exception as e:
        print("❌ 錯誤訊息：", e)
        error_msg = f"❌ 發生錯誤：{str(e)}"
        new_history = history + [
            {"role": "user", "content": user_input},
            {"role": "assistant", "content": error_msg},
        ]
        return new_history, new_history, ""


# ✅ Gradio 介面區塊
with gr.Blocks() as demo:
    gr.Markdown("## 🏗️ 建築條件助理")
    chatbot = gr.Chatbot(label="條件分析助手", type="messages")
    msg = gr.Textbox(label="請輸入建築條件", placeholder="例：基地面積2000平方公尺，容積率200%，建蔽率50%", lines=2)
    send_btn = gr.Button("📨 傳送")
    state = gr.State([])

    def handle_input(user_input, history):
        return chat(user_input, history)

    msg.submit(handle_input, [msg, state], [chatbot, state, msg])
    send_btn.click(handle_input, [msg, state], [chatbot, state, msg])

# ✅ 執行 Gradio 介面
demo.launch(share=True)