Spaces:
Sleeping
Sleeping
File size: 12,924 Bytes
d26f860 6845777 d26f860 fe7a40d d26f860 3a0319c 2ec04df 3a0319c de532fe fc2b8a1 d26f860 840689b d26f860 840689b d26f860 840689b d26f860 6ceb202 d26f860 68e4cf6 d26f860 68e4cf6 fc2b8a1 d26f860 5fd68e6 d26f860 68e4cf6 d26f860 68e4cf6 fc2b8a1 68e4cf6 d26f860 fc2b8a1 68e4cf6 d26f860 fc2b8a1 38537cb fc2b8a1 38537cb d26f860 fc2b8a1 23894e6 5fd68e6 fc2b8a1 5fd68e6 fc2b8a1 de532fe fc2b8a1 de532fe d26f860 fc2b8a1 5fd68e6 fc2b8a1 d26f860 1aaf383 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 |
import sqlite3
import gradio as gr
import asyncio
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 filter_breed_matches(user_prefs: UserPreferences, top_n: int = 10):
"""
根據使用者偏好篩選並推薦狗狗品種。
Parameters:
user_prefs: 使用者偏好設定
top_n: 要返回的推薦數量
Returns:
List[Dict]: 排序後的推薦品種列表
"""
all_breeds = []
for breed_info in breed_database:
score = calculate_compatibility_score(breed_info, user_prefs)
if score is not None: # 只添加未被過濾的品種
all_breeds.append({
'breed': breed_info['Breed'],
'final_score': score['overall'],
'base_score': score.get('base_score', 0),
'bonus_score': score.get('bonus_score', 0),
'size': breed_info['Size'],
'scores': score
})
# 根據體型偏好過濾
if user_prefs.size_preference != "no_preference":
filtered_breeds = [b for b in all_breeds if b['size'].lower() == user_prefs.size_preference.lower()]
# 如果符合體型的品種太少,調整返回數量
if len(filtered_breeds) < 5: # 設定最少要有5種品種
top_n = len(filtered_breeds)
else:
filtered_breeds = all_breeds
# 為每個品種添加排名
sorted_breeds = sorted(filtered_breeds, key=lambda x: x['final_score'], reverse=True)
for i, breed in enumerate(sorted_breeds, 1):
breed['rank'] = i
return sorted_breeds[:top_n]
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=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]
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],
'experience_level': args[5],
'time_availability': args[6],
'has_children': args[7],
'children_age': args[8] if args[7] else None,
'noise_tolerance': args[9],
'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,
} |