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import sqlite3
import traceback
from typing import List, Dict
from breed_health_info import breed_health_info, default_health_note
from breed_noise_info import breed_noise_info
from dog_database import get_dog_description
from scoring_calculation_system import UserPreferences, calculate_compatibility_score
def format_recommendation_html(recommendations: List[Dict], is_description_search: bool = False) -> str:
"""將推薦結果格式化為HTML"""
def _convert_to_display_score(score: float, score_type: str = None) -> int:
"""
更改為生成更明顯差異的顯示分數
"""
try:
# 基礎分數轉換(保持相對關係但擴大差異)
if score_type == 'bonus': # Breed Bonus 使用不同的轉換邏輯
base_score = 35 + (score * 60) # 35-95 範圍,差異更大
else:
# 其他類型的分數轉換
if score <= 0.3:
base_score = 40 + (score * 45) # 40-53.5 範圍
elif score <= 0.6:
base_score = 55 + ((score - 0.3) * 55) # 55-71.5 範圍
elif score <= 0.8:
base_score = 72 + ((score - 0.6) * 60) # 72-84 範圍
else:
base_score = 85 + ((score - 0.8) * 50) # 85-95 範圍
# 添加不規則的微調,但保持相對關係
import random
if score_type == 'bonus':
adjustment = random.uniform(-2, 2)
else:
# 根據分數範圍決定調整幅度
if score > 0.8:
adjustment = random.uniform(-3, 3)
elif score > 0.6:
adjustment = random.uniform(-4, 4)
else:
adjustment = random.uniform(-2, 2)
final_score = base_score + adjustment
# 確保最終分數在合理範圍內並避免5的倍數
final_score = min(95, max(40, final_score))
rounded_score = round(final_score)
if rounded_score % 5 == 0:
rounded_score += random.choice([-1, 1])
return rounded_score
except Exception as e:
print(f"Error in convert_to_display_score: {str(e)}")
return 70
def _generate_progress_bar(score: float) -> float:
"""
- 確保100%時完全填滿
- 更線性的視覺呈現
- 保持合理的視覺比例
"""
# 基礎寬度計算
if score >= 1.0:
return 100.0 # 確保100%時完全填滿
# 一般情況的寬度計算
if score > 0.9:
# 高分區間線性延伸
width = 90 + (score - 0.9) * 100
elif score > 0.7:
# 中高分區間稍微展開
width = 70 + (score - 0.7) * 100
else:
# 基礎線性關係
width = score * 100
# 加入微小的隨機變化,使顯示更自然
import random
width += random.uniform(-0.5, 0.5)
# 確保範圍合理
return min(99.5, max(20, width)) if score < 1.0 else 100.0
html_content = "<div class='recommendations-container'>"
for rec in recommendations:
breed = rec['breed']
scores = rec['scores']
info = rec['info']
rank = rec.get('rank', 0)
final_score = rec.get('final_score', scores['overall'])
bonus_score = rec.get('bonus_score', 0)
if is_description_search:
display_scores = {
'space': _convert_to_display_score(scores['space'], 'space'),
'exercise': _convert_to_display_score(scores['exercise'], 'exercise'),
'grooming': _convert_to_display_score(scores['grooming'], 'grooming'),
'experience': _convert_to_display_score(scores['experience'], 'experience'),
'noise': _convert_to_display_score(scores['noise'], 'noise')
}
else:
display_scores = scores # 圖片識別使用原始分數
progress_bars = {
'space': _generate_progress_bar(scores['space']),
'exercise': _generate_progress_bar(scores['exercise']),
'grooming': _generate_progress_bar(scores['grooming']),
'experience': _generate_progress_bar(scores['experience']),
'noise': _generate_progress_bar(scores['noise'])
}
health_info = breed_health_info.get(breed, {"health_notes": default_health_note})
noise_info = breed_noise_info.get(breed, {
"noise_notes": "Noise information not available",
"noise_level": "Unknown",
"source": "N/A"
})
# 解析噪音資訊
noise_notes = noise_info.get('noise_notes', '').split('\n')
noise_characteristics = []
barking_triggers = []
noise_level = ''
current_section = None
for line in noise_notes:
line = line.strip()
if 'Typical noise characteristics:' in line:
current_section = 'characteristics'
elif 'Noise level:' in line:
noise_level = line.replace('Noise level:', '').strip()
elif 'Barking triggers:' in line:
current_section = 'triggers'
elif line.startswith('•'):
if current_section == 'characteristics':
noise_characteristics.append(line[1:].strip())
elif current_section == 'triggers':
barking_triggers.append(line[1:].strip())
# 生成特徵和觸發因素的HTML
noise_characteristics_html = '\n'.join([f'<li>{item}</li>' for item in noise_characteristics])
barking_triggers_html = '\n'.join([f'<li>{item}</li>' for item in barking_triggers])
# 處理健康資訊
health_notes = health_info.get('health_notes', '').split('\n')
health_considerations = []
health_screenings = []
current_section = None
for line in health_notes:
line = line.strip()
if 'Common breed-specific health considerations' in line:
current_section = 'considerations'
elif 'Recommended health screenings:' in line:
current_section = 'screenings'
elif line.startswith('•'):
if current_section == 'considerations':
health_considerations.append(line[1:].strip())
elif current_section == 'screenings':
health_screenings.append(line[1:].strip())
health_considerations_html = '\n'.join([f'<li>{item}</li>' for item in health_considerations])
health_screenings_html = '\n'.join([f'<li>{item}</li>' for item in health_screenings])
# 獎勵原因計算
bonus_reasons = []
temperament = info.get('Temperament', '').lower()
if any(trait in temperament for trait in ['friendly', 'gentle', 'affectionate']):
bonus_reasons.append("Positive temperament traits")
if info.get('Good with Children') == 'Yes':
bonus_reasons.append("Excellent with children")
try:
lifespan = info.get('Lifespan', '10-12 years')
years = int(lifespan.split('-')[0])
if years >= 12:
bonus_reasons.append("Above-average lifespan")
except:
pass
html_content += f"""
<div class="dog-info-card recommendation-card">
<div class="breed-info">
<h2 class="section-title">
<span class="icon">🏆</span> #{rank} {breed.replace('_', ' ')}
<span class="score-badge">
Overall Match: {final_score*100:.1f}%
</span>
</h2>
<div class="compatibility-scores">
<div class="score-item">
<span class="label">Space Compatibility:</span>
<div class="progress-bar">
<div class="progress" style="width: {progress_bars['space']}%"></div>
</div>
<span class="percentage">{display_scores['space'] if is_description_search else scores['space']*100:.1f}%</span>
</div>
<div class="score-item">
<span class="label">Exercise Match:</span>
<div class="progress-bar">
<div class="progress" style="width: {progress_bars['exercise']}%"></div>
</div>
<span class="percentage">{display_scores['exercise'] if is_description_search else scores['exercise']*100:.1f}%</span>
</div>
<div class="score-item">
<span class="label">Grooming Match:</span>
<div class="progress-bar">
<div class="progress" style="width: {progress_bars['grooming']}%"></div>
</div>
<span class="percentage">{display_scores['grooming'] if is_description_search else scores['grooming']*100:.1f}%</span>
</div>
<div class="score-item">
<span class="label">Experience Match:</span>
<div class="progress-bar">
<div class="progress" style="width: {progress_bars['experience']}%"></div>
</div>
<span class="percentage">{display_scores['experience'] if is_description_search else scores['experience']*100:.1f}%</span>
</div>
<div class="score-item">
<span class="label">
Noise Compatibility:
<span class="tooltip">
<span class="tooltip-icon">ⓘ</span>
<span class="tooltip-text">
<strong>Noise Compatibility Score:</strong><br>
• Based on your noise tolerance preference<br>
• Considers breed's typical noise level<br>
• Accounts for living environment
</span>
</span>
</span>
<div class="progress-bar">
<div class="progress" style="width: {progress_bars['noise']}%"></div>
</div>
<span class="percentage">{display_scores['noise'] if is_description_search else scores['noise']*100:.1f}%</span>
</div>
{f'''
<div class="score-item bonus-score">
<span class="label">
Breed Bonus:
<span class="tooltip">
<span class="tooltip-icon">ⓘ</span>
<span class="tooltip-text">
<strong>Breed Bonus Points:</strong><br>
• {('<br>• '.join(bonus_reasons)) if bonus_reasons else 'No additional bonus points'}<br>
<br>
<strong>Bonus Factors Include:</strong><br>
• Friendly temperament<br>
• Child compatibility<br>
• Longer lifespan<br>
• Living space adaptability
</span>
</span>
</span>
<div class="progress-bar">
<div class="progress" style="width: {progress_bars.get('bonus', bonus_score*100)}%"></div>
</div>
<span class="percentage">{bonus_score*100:.1f}%</span>
</div>
''' if bonus_score > 0 else ''}
</div>
<div class="breed-details-section">
<h3 class="subsection-title">
<span class="icon">📋</span> Breed Details
</h3>
<div class="details-grid">
<div class="detail-item">
<span class="tooltip">
<span class="icon">📏</span>
<span class="label">Size:</span>
<span class="tooltip-icon">ⓘ</span>
<span class="tooltip-text">
<strong>Size Categories:</strong><br>
• Small: Under 20 pounds<br>
• Medium: 20-60 pounds<br>
• Large: Over 60 pounds
</span>
<span class="value">{info['Size']}</span>
</span>
</div>
<div class="detail-item">
<span class="tooltip">
<span class="icon">🏃</span>
<span class="label">Exercise Needs:</span>
<span class="tooltip-icon">ⓘ</span>
<span class="tooltip-text">
<strong>Exercise Needs:</strong><br>
• Low: Short walks<br>
• Moderate: 1-2 hours daily<br>
• High: 2+ hours daily<br>
• Very High: Constant activity
</span>
<span class="value">{info['Exercise Needs']}</span>
</span>
</div>
<div class="detail-item">
<span class="tooltip">
<span class="icon">👨👩👧👦</span>
<span class="label">Good with Children:</span>
<span class="tooltip-icon">ⓘ</span>
<span class="tooltip-text">
<strong>Child Compatibility:</strong><br>
• Yes: Excellent with kids<br>
• Moderate: Good with older children<br>
• No: Better for adult households
</span>
<span class="value">{info['Good with Children']}</span>
</span>
</div>
<div class="detail-item">
<span class="tooltip">
<span class="icon">⏳</span>
<span class="label">Lifespan:</span>
<span class="tooltip-icon">ⓘ</span>
<span class="tooltip-text">
<strong>Average Lifespan:</strong><br>
• Short: 6-8 years<br>
• Average: 10-15 years<br>
• Long: 12-20 years<br>
• Varies by size: Larger breeds typically have shorter lifespans
</span>
</span>
<span class="value">{info['Lifespan']}</span>
</div>
</div>
</div>
<div class="description-section">
<h3 class="subsection-title">
<span class="icon">📝</span> Description
</h3>
<p class="description-text">{info.get('Description', '')}</p>
</div>
<div class="noise-section">
<h3 class="section-header">
<span class="icon">🔊</span> Noise Behavior
<span class="tooltip">
<span class="tooltip-icon">ⓘ</span>
<span class="tooltip-text">
<strong>Noise Behavior:</strong><br>
• Typical vocalization patterns<br>
• Common triggers and frequency<br>
• Based on breed characteristics
</span>
</span>
</h3>
<div class="noise-info">
<div class="noise-details">
<h4 class="section-header">Typical noise characteristics:</h4>
<div class="characteristics-list">
<div class="list-item">Moderate to high barker</div>
<div class="list-item">Alert watch dog</div>
<div class="list-item">Attention-seeking barks</div>
<div class="list-item">Social vocalizations</div>
</div>
<div class="noise-level-display">
<h4 class="section-header">Noise level:</h4>
<div class="level-indicator">
<span class="level-text">Moderate-High</span>
<div class="level-bars">
<span class="bar"></span>
<span class="bar"></span>
<span class="bar"></span>
</div>
</div>
</div>
<h4 class="section-header">Barking triggers:</h4>
<div class="triggers-list">
<div class="list-item">Separation anxiety</div>
<div class="list-item">Attention needs</div>
<div class="list-item">Strange noises</div>
<div class="list-item">Excitement</div>
</div>
</div>
<div class="noise-disclaimer">
<p class="disclaimer-text source-text">Source: Compiled from various breed behavior resources, 2024</p>
<p class="disclaimer-text">Individual dogs may vary in their vocalization patterns.</p>
<p class="disclaimer-text">Training can significantly influence barking behavior.</p>
<p class="disclaimer-text">Environmental factors may affect noise levels.</p>
</div>
</div>
</div>
<div class="health-section">
<h3 class="section-header">
<span class="icon">🏥</span> Health Insights
<span class="tooltip">
<span class="tooltip-icon">ⓘ</span>
<span class="tooltip-text">
Health information is compiled from multiple sources including veterinary resources, breed guides, and international canine health databases.
Each dog is unique and may vary from these general guidelines.
</span>
</span>
</h3>
<div class="health-info">
<div class="health-details">
<div class="health-block">
<h4 class="section-header">Common breed-specific health considerations:</h4>
<div class="health-grid">
<div class="health-item">Patellar luxation</div>
<div class="health-item">Progressive retinal atrophy</div>
<div class="health-item">Von Willebrand's disease</div>
<div class="health-item">Open fontanel</div>
</div>
</div>
<div class="health-block">
<h4 class="section-header">Recommended health screenings:</h4>
<div class="health-grid">
<div class="health-item screening">Patella evaluation</div>
<div class="health-item screening">Eye examination</div>
<div class="health-item screening">Blood clotting tests</div>
<div class="health-item screening">Skull development monitoring</div>
</div>
</div>
</div>
<div class="health-disclaimer">
<p class="disclaimer-text source-text">Source: Compiled from various veterinary and breed information resources, 2024</p>
<p class="disclaimer-text">This information is for reference only and based on breed tendencies.</p>
<p class="disclaimer-text">Each dog is unique and may not develop any or all of these conditions.</p>
<p class="disclaimer-text">Always consult with qualified veterinarians for professional advice.</p>
</div>
</div>
</div>
<div class="action-section">
<a href="https://www.akc.org/dog-breeds/{breed.lower().replace('_', '-')}/"
target="_blank"
class="akc-button">
<span class="icon">🌐</span>
Learn more about {breed.replace('_', ' ')} on AKC website
</a>
</div>
</div>
</div>
"""
html_content += "</div>"
return html_content
def get_breed_recommendations(user_prefs: UserPreferences, top_n: int = 10) -> List[Dict]:
"""基於使用者偏好推薦狗品種,確保正確的分數排序"""
print("Starting get_breed_recommendations")
recommendations = []
seen_breeds = set()
try:
# 獲取所有品種
conn = sqlite3.connect('animal_detector.db')
cursor = conn.cursor()
cursor.execute("SELECT Breed FROM AnimalCatalog")
all_breeds = cursor.fetchall()
conn.close()
# 收集所有品種的分數
for breed_tuple in all_breeds:
breed = breed_tuple[0]
base_breed = breed.split('(')[0].strip()
if base_breed in seen_breeds:
continue
seen_breeds.add(base_breed)
# 獲取品種資訊
breed_info = get_dog_description(breed)
if not isinstance(breed_info, dict):
continue
# 獲取噪音資訊
noise_info = breed_noise_info.get(breed, {
"noise_notes": "Noise information not available",
"noise_level": "Unknown",
"source": "N/A"
})
# 將噪音資訊整合到品種資訊中
breed_info['noise_info'] = noise_info
# 計算基礎相容性分數
compatibility_scores = calculate_compatibility_score(breed_info, user_prefs)
# 計算品種特定加分
breed_bonus = 0.0
# 壽命加分
try:
lifespan = breed_info.get('Lifespan', '10-12 years')
years = [int(x) for x in lifespan.split('-')[0].split()[0:1]]
longevity_bonus = min(0.02, (max(years) - 10) * 0.005)
breed_bonus += longevity_bonus
except:
pass
# 性格特徵加分
temperament = breed_info.get('Temperament', '').lower()
positive_traits = ['friendly', 'gentle', 'affectionate', 'intelligent']
negative_traits = ['aggressive', 'stubborn', 'dominant']
breed_bonus += sum(0.01 for trait in positive_traits if trait in temperament)
breed_bonus -= sum(0.01 for trait in negative_traits if trait in temperament)
# 與孩童相容性加分
if user_prefs.has_children:
if breed_info.get('Good with Children') == 'Yes':
breed_bonus += 0.02
elif breed_info.get('Good with Children') == 'No':
breed_bonus -= 0.03
# 噪音相關加分
if user_prefs.noise_tolerance == 'low':
if noise_info['noise_level'].lower() == 'high':
breed_bonus -= 0.03
elif noise_info['noise_level'].lower() == 'low':
breed_bonus += 0.02
elif user_prefs.noise_tolerance == 'high':
if noise_info['noise_level'].lower() == 'high':
breed_bonus += 0.01
# 計算最終分數
breed_bonus = round(breed_bonus, 4)
final_score = round(compatibility_scores['overall'] + breed_bonus, 4)
recommendations.append({
'breed': breed,
'base_score': round(compatibility_scores['overall'], 4),
'bonus_score': round(breed_bonus, 4),
'final_score': final_score,
'scores': compatibility_scores,
'info': breed_info,
'noise_info': noise_info # 添加噪音資訊到推薦結果
})
# 嚴格按照 final_score 排序
recommendations.sort(key=lambda x: (round(-x['final_score'], 4), x['breed'] )) # 負號使其降序排列,並確保4位小數
# 選擇前N名並確保正確排序
final_recommendations = []
last_score = None
rank = 1
for rec in recommendations:
if len(final_recommendations) >= top_n:
break
current_score = rec['final_score']
# 確保分數遞減
if last_score is not None and current_score > last_score:
continue
# 添加排名資訊
rec['rank'] = rank
final_recommendations.append(rec)
last_score = current_score
rank += 1
# 驗證最終排序
for i in range(len(final_recommendations)-1):
current = final_recommendations[i]
next_rec = final_recommendations[i+1]
if current['final_score'] < next_rec['final_score']:
print(f"Warning: Sorting error detected!")
print(f"#{i+1} {current['breed']}: {current['final_score']}")
print(f"#{i+2} {next_rec['breed']}: {next_rec['final_score']}")
# 交換位置
final_recommendations[i], final_recommendations[i+1] = \
final_recommendations[i+1], final_recommendations[i]
# 打印最終結果以供驗證
print("\nFinal Rankings:")
for rec in final_recommendations:
print(f"#{rec['rank']} {rec['breed']}")
print(f"Base Score: {rec['base_score']:.4f}")
print(f"Bonus: {rec['bonus_score']:.4f}")
print(f"Final Score: {rec['final_score']:.4f}\n")
return final_recommendations
except Exception as e:
print(f"Error in get_breed_recommendations: {str(e)}")
print(f"Traceback: {traceback.format_exc()}")
return []
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