breed_recommendation.py

import gradio as gr
from recommendation_html_format import format_recommendation_html, get_breed_recommendations

def create_recommendation_tab(UserPreferences, get_breed_recommendations, format_recommendation_html, history_component):
    """创建品种推荐标签页

    Args:
        UserPreferences: 用户偏好类
        get_breed_recommendations: 获取品种推荐的函数
        format_recommendation_html: 格式化推荐结果的函数
        history_component: 历史记录组件
    """
    with gr.TabItem("Breed Recommendation"):
        gr.HTML("<p style='text-align: center;'>Tell us about your lifestyle, and we'll recommend the perfect dog breeds for you!</p>")

        with gr.Row():
            with gr.Column():
                living_space = gr.Radio(
                    choices=["apartment", "house_small", "house_large"],
                    label="What type of living space do you have?",
                    info="Choose your current living situation",
                    value="apartment"
                )

                exercise_time = gr.Slider(
                    minimum=0,
                    maximum=180,
                    value=60,
                    label="Daily exercise time (minutes)",
                    info="Consider walks, play time, and training"
                )

                grooming_commitment = gr.Radio(
                    choices=["low", "medium", "high"],
                    label="Grooming commitment level",
                    info="Low: monthly, Medium: weekly, High: daily",
                    value="medium"
                )

            with gr.Column():
                experience_level = gr.Radio(
                    choices=["beginner", "intermediate", "advanced"],
                    label="Dog ownership experience",
                    info="Be honest - this helps find the right match",
                    value="beginner"
                )

                has_children = gr.Checkbox(
                    label="Have children at home",
                    info="Helps recommend child-friendly breeds"
                )

                noise_tolerance = gr.Radio(
                    choices=["low", "medium", "high"],
                    label="Noise tolerance level",
                    info="Some breeds are more vocal than others",
                    value="medium"
                )

        get_recommendations_btn = gr.Button("Find My Perfect Match! 🔍", variant="primary")
        recommendation_output = gr.HTML(label="Breed Recommendations")

        def on_find_match_click(*args):
            try:
                user_prefs = UserPreferences(
                    living_space=args[0],
                    exercise_time=args[1],
                    grooming_commitment=args[2],
                    experience_level=args[3],
                    has_children=args[4],
                    noise_tolerance=args[5],
                    space_for_play=True if args[0] != "apartment" else False,
                    other_pets=False,
                    climate="moderate",
                    health_sensitivity="medium",  # 新增: 默認中等敏感度
                    barking_acceptance=args[5]    # 使用 noise_tolerance 作為 barking_acceptance
                )

                recommendations = get_breed_recommendations(user_prefs, top_n=10)

                history_results = [{
                    'breed': rec['breed'],
                    'rank': rec['rank'],
                    'overall_score': rec['final_score'],
                    'base_score': rec['base_score'],
                    'bonus_score': rec['bonus_score'],
                    'scores': rec['scores']
                } for rec in recommendations]

                # 保存到歷史記錄，也需要更新保存的偏好設定
                history_component.save_search(
                    user_preferences={
                        'living_space': args[0],
                        'exercise_time': args[1],
                        'grooming_commitment': args[2],
                        'experience_level': args[3],
                        'has_children': args[4],
                        'noise_tolerance': args[5],
                        'health_sensitivity': "medium",
                        'barking_acceptance': args[5]
                    },
                    results=history_results
                )

                return format_recommendation_html(recommendations)

            except Exception as e:
                print(f"Error in find match: {str(e)}")
                import traceback
                print(traceback.format_exc())
                return "Error getting recommendations"

        get_recommendations_btn.click(
            fn=on_find_match_click,
            inputs=[
                living_space,
                exercise_time,
                grooming_commitment,
                experience_level,
                has_children,
                noise_tolerance
            ],
            outputs=recommendation_output
        )

    return {
        'living_space': living_space,
        'exercise_time': exercise_time,
        'grooming_commitment': grooming_commitment,
        'experience_level': experience_level,
        'has_children': has_children,
        'noise_tolerance': noise_tolerance,
        'get_recommendations_btn': get_recommendations_btn,
        'recommendation_output': recommendation_output
    }