import requests
import json
import gradio as gr

def calculate1(course_input, course_profile, course_hour):
    url = "https://ai-knowledge-navigator.onrender.com/process"

    headers = {
        "Content-Type": "application/json"
    }

    data = {
        "title": course_input,
        "content": course_profile,
        "hour": course_hour
    }

    try:
        response = requests.post(url, json=data, headers=headers, timeout=50)

        if response.status_code == 200:
            try:
                response_json = response.json()
                # 解析回傳結果
                success = response_json.get("success", False)
                title = response_json.get("title", "未知課程")
                competencies = response_json.get("competencies", ["未能成功匹配"])

                if success:
                    return f"課程 '{title}' 職能匹配成功！", ", ".join(competencies)
                else:
                    return "匹配失敗，請稍後再試", "無職能項目"

            except json.JSONDecodeError:
                return "錯誤: 伺服器回應非 JSON 格式", "無職能項目"

        else:
            return f"錯誤: 伺服器返回 HTTP {response.status_code}", "無職能項目"

    except requests.exceptions.Timeout:
        return "錯誤: 伺服器回應超時", "無職能項目"
    except requests.exceptions.RequestException as e:
        return f"請求失敗: {str(e)}", "無職能項目"

def setup_gradio_interface():
    with gr.Blocks() as demo:
        with gr.Row():
            course_input = gr.Textbox(label="課程名稱", placeholder="請輸入課程名稱")
            course_hour = gr.Textbox(label="課程時數", placeholder="請輸入課程時數")
        with gr.Row():
            course_profile = gr.Textbox(label="課程簡介", placeholder="請輸入課程簡介")
        with gr.Row():
            submit_button = gr.Button("計算職能項目")
        with gr.Row():
            txt_response = gr.Textbox(label="計算狀態", placeholder="計算結果")
            course_competencies = gr.Textbox(label="職能項目", placeholder="職能項目")

        # 修正 inputs 和 outputs
        submit_button.click(
            calculate1,
            inputs=[course_input, course_profile, course_hour],
            outputs=[txt_response, course_competencies]
        )

    return demo

try:
    import gradio as gr
except ImportError:
    import sys
    import gradio as gr

# Run the interface
if __name__ == "__main__":
    demo = setup_gradio_interface()
    #port = int(os.environ.get("PORT", 7860))
    demo.launch()
    #demo.launch(server_name="0.0.0.0", server_port=port)