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Running
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File size: 24,841 Bytes
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import sqlite3
import gradio as gr
from typing import Generator
from dog_database import get_dog_description, dog_data
from breed_health_info import breed_health_info
from breed_noise_info import breed_noise_info
from scoring_calculation_system import UserPreferences, calculate_compatibility_score
from recommendation_html_format import format_recommendation_html, get_breed_recommendations
from search_history import create_history_tab, create_history_component
def create_custom_button_style():
return """
<style>
#find-match-btn {
background: linear-gradient(90deg, #ff5f6d 0%, #ffc371 100%);
border: none;
border-radius: 30px;
padding: 12px 24px;
color: white;
font-weight: bold;
cursor: pointer;
transition: all 0.3s ease;
box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
width: 100%;
margin: 20px 0;
font-size: 1.1em;
position: relative;
overflow: hidden;
}
#find-match-btn:hover {
background: linear-gradient(90deg, #ff4f5d 0%, #ffb361 100%);
box-shadow: 0 6px 8px rgba(0, 0, 0, 0.2);
transform: translateY(-1px);
}
#find-match-btn:active {
transform: translateY(1px);
box-shadow: 0 2px 4px rgba(0, 0, 0, 0.2);
}
#search-status {
text-align: center;
padding: 15px;
font-size: 1.1em;
color: #666;
margin: 10px 0;
border-radius: 8px;
background: rgba(255, 95, 109, 0.1);
}
</style>
"""
def create_recommendation_tab(UserPreferences, get_breed_recommendations, format_recommendation_html, history_component):
with gr.TabItem("Breed Recommendation"):
with gr.Tabs():
with gr.Tab("Find by Criteria"):
gr.HTML("""
<div style='
text-align: center;
position: relative;
padding: 20px 0;
margin: 15px 0;
background: linear-gradient(to right, rgba(66, 153, 225, 0.1), rgba(72, 187, 120, 0.1));
border-radius: 10px;
'>
<!-- BETA 標籤 -->
<div style='
position: absolute;
top: 10px;
right: 20px;
background: linear-gradient(90deg, #4299e1, #48bb78);
color: white;
padding: 4px 12px;
border-radius: 15px;
font-size: 0.85em;
font-weight: 600;
letter-spacing: 1px;
box-shadow: 0 2px 4px rgba(0,0,0,0.1);
'>BETA</div>
<!-- 主標題 -->
<p style='
font-size: 1.2em;
margin: 0;
padding: 0 20px;
line-height: 1.5;
background: linear-gradient(90deg, #4299e1, #48bb78);
-webkit-background-clip: text;
-webkit-text-fill-color: transparent;
font-weight: 600;
'>
Tell us about your lifestyle, and we'll recommend the perfect dog breeds for you!
</p>
<!-- 提示訊息 -->
<div style='
margin-top: 15px;
padding: 10px 20px;
background: linear-gradient(to right, rgba(66, 153, 225, 0.15), rgba(72, 187, 120, 0.15));
border-radius: 8px;
font-size: 0.9em;
color: #2D3748;
display: flex;
align-items: center;
justify-content: center;
gap: 8px;
'>
<span style="font-size: 1.2em;">🔬</span>
<span style="
letter-spacing: 0.3px;
line-height: 1.4;
"><strong>Beta Feature:</strong> Our matching algorithm is continuously improving. Results are for reference only.</span>
</div>
</div>
""")
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"
)
yard_access = gr.Radio(
choices=["no_yard", "shared_yard", "private_yard"],
label="Yard Access Type",
info="Available outdoor space",
value="no_yard"
)
exercise_time = gr.Slider(
minimum=0,
maximum=180,
value=60,
label="Daily exercise time (minutes)",
info="Consider walks, play time, and training"
)
exercise_type = gr.Radio(
choices=["light_walks", "moderate_activity", "active_training"],
label="Exercise Style",
info="What kind of activities do you prefer?",
value="moderate_activity"
)
grooming_commitment = gr.Radio(
choices=["low", "medium", "high"],
label="Grooming commitment level",
info="Low: monthly, Medium: weekly, High: daily",
value="medium"
)
with gr.Column():
size_preference = gr.Radio(
choices=["no_preference", "small", "medium", "large", "giant"],
label="Preference Dog Size",
info="Select your preferred dog size - this will strongly filter the recommendations",
value = "no_preference"
)
experience_level = gr.Radio(
choices=["beginner", "intermediate", "advanced"],
label="Dog ownership experience",
info="Be honest - this helps find the right match",
value="beginner"
)
time_availability = gr.Radio(
choices=["limited", "moderate", "flexible"],
label="Time Availability",
info="Time available for dog care daily",
value="moderate"
)
has_children = gr.Checkbox(
label="Have children at home",
info="Helps recommend child-friendly breeds"
)
children_age = gr.Radio(
choices=["toddler", "school_age", "teenager"],
label="Children's Age Group",
info="Helps match with age-appropriate breeds",
visible=False # 默認隱藏，只在has_children=True時顯示
)
noise_tolerance = gr.Radio(
choices=["low", "medium", "high"],
label="Noise tolerance level",
info="Some breeds are more vocal than others",
value="medium"
)
def update_children_age_visibility(has_children):
return gr.update(visible=has_children)
has_children.change(
fn=update_children_age_visibility,
inputs=has_children,
outputs=children_age
)
gr.HTML(create_custom_button_style())
search_status = gr.HTML(
'<div id="search-status">🔍 Sniffing out your perfect furry companion...</div>',
visible=False,
elem_id="search-status-container"
)
get_recommendations_btn = gr.Button(
"Find My Perfect Match! 🔍",
elem_id="find-match-btn" # 添加自定義ID
)
recommendation_output = gr.HTML(
label="Breed Recommendations",
visible=True, # 確保可見性
elem_id="recommendation-output"
)
def on_find_match_click(*args):
try:
print("Starting breed matching process...")
user_prefs = UserPreferences(
living_space=args[0],
yard_access=args[1],
exercise_time=args[2],
exercise_type=args[3],
grooming_commitment=args[4],
size_preference=args[5],
experience_level=args[6],
time_availability=args[7],
has_children=args[8],
children_age=args[9] if args[8] else None,
noise_tolerance=args[10],
space_for_play=True if args[0] != "apartment" else False,
other_pets=False,
climate="moderate",
health_sensitivity="medium",
barking_acceptance=args[10]
)
recommendations = get_breed_recommendations(user_prefs, top_n=15)
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]
history_component.save_search(
user_preferences={
'living_space': args[0],
'yard_access': args[1],
'exercise_time': args[2],
'exercise_type': args[3],
'grooming_commitment': args[4],
'size_preference': args[5],
'experience_level': args[6],
'time_availability': args[7],
'has_children': args[8],
'children_age': args[9] if args[8] else None,
'noise_tolerance': args[10],
'search_type': 'Criteria'
},
results=history_results
)
return [
format_recommendation_html(recommendations, is_description_search=False),
gr.HTML.update(visible=True) # 隱藏搜尋狀態
]
except Exception as e:
print(f"Error in find match: {str(e)}")
import traceback
print(traceback.format_exc())
return ["Error getting recommendations", gr.HTML.update(visible=False)]
def update_status_and_process(*args):
return [
"", # 清空現有結果
gr.HTML.update(visible=True) # 顯示載入狀態
]
get_recommendations_btn.click(
fn=on_find_match_click,
inputs=[
living_space,
yard_access,
exercise_time,
exercise_type,
grooming_commitment,
size_preference,
experience_level,
time_availability,
has_children,
children_age,
noise_tolerance
],
outputs=[recommendation_output, search_status]
)
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,
}
# def create_recommendation_tab(UserPreferences, get_breed_recommendations, format_recommendation_html, history_component):
# with gr.TabItem("Breed Recommendation"):
# with gr.Tabs():
# with gr.Tab("Find by Criteria"):
# gr.HTML("""
# <div style='
# text-align: center;
# position: relative;
# padding: 20px 0;
# margin: 15px 0;
# background: linear-gradient(to right, rgba(66, 153, 225, 0.1), rgba(72, 187, 120, 0.1));
# border-radius: 10px;
# '>
# <!-- BETA 標籤 -->
# <div style='
# position: absolute;
# top: 10px;
# right: 20px;
# background: linear-gradient(90deg, #4299e1, #48bb78);
# color: white;
# padding: 4px 12px;
# border-radius: 15px;
# font-size: 0.85em;
# font-weight: 600;
# letter-spacing: 1px;
# box-shadow: 0 2px 4px rgba(0,0,0,0.1);
# '>BETA</div>
# <!-- 主標題 -->
# <p style='
# font-size: 1.2em;
# margin: 0;
# padding: 0 20px;
# line-height: 1.5;
# background: linear-gradient(90deg, #4299e1, #48bb78);
# -webkit-background-clip: text;
# -webkit-text-fill-color: transparent;
# font-weight: 600;
# '>
# Tell us about your lifestyle, and we'll recommend the perfect dog breeds for you!
# </p>
# <!-- 提示訊息 -->
# <div style='
# margin-top: 15px;
# padding: 10px 20px;
# background: linear-gradient(to right, rgba(66, 153, 225, 0.15), rgba(72, 187, 120, 0.15));
# border-radius: 8px;
# font-size: 0.9em;
# color: #2D3748;
# display: flex;
# align-items: center;
# justify-content: center;
# gap: 8px;
# '>
# <span style="font-size: 1.2em;">🔬</span>
# <span style="
# letter-spacing: 0.3px;
# line-height: 1.4;
# "><strong>Beta Feature:</strong> Our matching algorithm is continuously improving. Results are for reference only.</span>
# </div>
# </div>
# """)
# 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"
# )
# yard_access = gr.Radio(
# choices=["no_yard", "shared_yard", "private_yard"],
# label="Yard Access Type",
# info="Available outdoor space",
# value="no_yard"
# )
# exercise_time = gr.Slider(
# minimum=0,
# maximum=180,
# value=60,
# label="Daily exercise time (minutes)",
# info="Consider walks, play time, and training"
# )
# exercise_type = gr.Radio(
# choices=["light_walks", "moderate_activity", "active_training"],
# label="Exercise Style",
# info="What kind of activities do you prefer?",
# value="moderate_activity"
# )
# grooming_commitment = gr.Radio(
# choices=["low", "medium", "high"],
# label="Grooming commitment level",
# info="Low: monthly, Medium: weekly, High: daily",
# value="medium"
# )
# with gr.Column():
# size_preference = gr.Radio(
# choices=["no_preference", "small", "medium", "large", "giant"],
# label="Preference Dog Size",
# info="Select your preferred dog size - this will strongly filter the recommendations",
# value = "no_preference"
# )
# experience_level = gr.Radio(
# choices=["beginner", "intermediate", "advanced"],
# label="Dog ownership experience",
# info="Be honest - this helps find the right match",
# value="beginner"
# )
# time_availability = gr.Radio(
# choices=["limited", "moderate", "flexible"],
# label="Time Availability",
# info="Time available for dog care daily",
# value="moderate"
# )
# has_children = gr.Checkbox(
# label="Have children at home",
# info="Helps recommend child-friendly breeds"
# )
# children_age = gr.Radio(
# choices=["toddler", "school_age", "teenager"],
# label="Children's Age Group",
# info="Helps match with age-appropriate breeds",
# visible=False # 默認隱藏，只在has_children=True時顯示
# )
# noise_tolerance = gr.Radio(
# choices=["low", "medium", "high"],
# label="Noise tolerance level",
# info="Some breeds are more vocal than others",
# value="medium"
# )
# def update_children_age_visibility(has_children):
# return gr.update(visible=has_children)
# has_children.change(
# fn=update_children_age_visibility,
# inputs=has_children,
# outputs=children_age
# )
# get_recommendations_btn = gr.Button("Find My Perfect Match! 🔍", variant="primary")
# recommendation_output = gr.HTML(
# label="Breed Recommendations",
# visible=True, # 確保可見性
# elem_id="recommendation-output"
# )
# def on_find_match_click(*args):
# try:
# user_prefs = UserPreferences(
# living_space=args[0],
# yard_access=args[1],
# exercise_time=args[2],
# exercise_type=args[3],
# grooming_commitment=args[4],
# size_preference=args[5],
# experience_level=args[6],
# time_availability=args[7],
# has_children=args[8],
# children_age=args[9] if args[8] else None,
# noise_tolerance=args[10],
# space_for_play=True if args[0] != "apartment" else False,
# other_pets=False,
# climate="moderate",
# health_sensitivity="medium",
# barking_acceptance=args[10]
# )
# recommendations = get_breed_recommendations(user_prefs, top_n=15)
# 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]
# history_component.save_search(
# user_preferences={
# 'living_space': args[0],
# 'yard_access': args[1],
# 'exercise_time': args[2],
# 'exercise_type': args[3],
# 'grooming_commitment': args[4],
# 'size_preference': args[5],
# 'experience_level': args[6],
# 'time_availability': args[7],
# 'has_children': args[8],
# 'children_age': args[9] if args[8] else None,
# 'noise_tolerance': args[10],
# 'search_type': 'Criteria'
# },
# results=history_results
# )
# return format_recommendation_html(recommendations, is_description_search=False)
# 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,
# yard_access,
# exercise_time,
# exercise_type,
# grooming_commitment,
# size_preference,
# experience_level,
# time_availability,
# has_children,
# children_age,
# 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,
# } |