import anthropic

client = anthropic.Anthropic(
    api_key='your-derouter-api-key',
    base_url='https://api.derouter.ai/proxy/v1'
)

# 系统 Prompt（客服核心，精心设计）
SYSTEM_PROMPT = '''You are a customer service agent for an e-commerce brand.

Rules:
1. Respond in the SAME language the customer writes in
2. Be empathetic but concise (under 150 words)
3. For order issues: ask for order number if not provided
4. For returns: explain the 30-day return policy, provide steps
5. For complaints: apologize sincerely, offer solution
6. If unsure: say you'll escalate to a specialist (don't make up answers)
7. Never discuss competitor products
8. Always end with: \

def classify_intent(message):
    '''用 Haiku 分类意图（最便宜的模型）'''
    msg = client.messages.create(
        model='claude-haiku-4-5-20251001',  # Haiku: $0.23/百万tokens
        max_tokens=50,
        messages=[{
            'role': 'user',
            'content': f'''Classify this customer message into ONE category:
- ORDER_STATUS (tracking, delivery time)
- RETURN_REFUND (returns, refunds, exchanges)
- PRODUCT_QUESTION (specs, compatibility, usage)
- COMPLAINT (damaged, wrong item, bad experience)
- GENERAL (greetings, thanks, other)

Message: \

def handle_message(message, order_db, conversation_history=[]):
    '''根据意图路由到不同处理逻辑'''
    intent = classify_intent(message)

    if intent == 'ORDER_STATUS':
        # 查询订单数据库，注入上下文
        order_info = order_db.lookup(message)
        enhanced_message = f'{message}

[System: Order info: {order_info}]'
        return chat(enhanced_message, conversation_history)

    elif intent == 'COMPLAINT':
        # 投诉用 Opus 处理（更 empathetic，更细致）
        msg = client.messages.create(
            model='claude-opus-4-6',
            max_tokens=1024,
            system=SYSTEM_PROMPT + '
This is a COMPLAINT. Be extra empathetic. Offer concrete solution.',
            messages=conversation_history + [{'role': 'user', 'content': message}]
        )
        reply = msg.content[0].text
        # 同时标记人工跟进
        flag_for_human_review(message, reply)
        return reply, conversation_history

    elif intent == 'RETURN_REFUND':
        return chat(message, conversation_history)

    else:
        return chat(message, conversation_history)

def analyze_sentiment(message):
    '''分析客户情绪，决定响应优先级'''
    msg = client.messages.create(
        model='claude-haiku-4-5-20251001',
        max_tokens=30,
        messages=[{
            'role': 'user',
            'content': f'''Rate the sentiment of this customer message on a scale:
ANGRY / FRUSTRATED / NEUTRAL / HAPPY

Message: \

# 简单知识库（实际项目建议用向量数据库）
KNOWLEDGE_BASE = {
    'shipping': '''
    US orders: Free shipping on orders over $50. Standard 3-5 business days.
    EU orders: €5.99 flat rate. 5-10 business days. Free over €80.
    Tracking: Sent via email within 24 hours of shipment.
    ''',
    'returns': '''
    30-day return policy. Item must be unused and in original packaging.
    Free return shipping label provided.
    Refund processed within 5-7 business days after receiving the return.
    Exchange: Same process, new item ships when return is received.
    ''',
    'warranty': '''
    1-year warranty covering manufacturing defects.
    Does not cover: normal wear, misuse, modifications.
    Claim process: Email photo of defect + order number.
    '''
}

def get_relevant_knowledge(intent):
    '''根据意图获取相关知识'''
    mapping = {
        'ORDER_STATUS': KNOWLEDGE_BASE['shipping'],
        'RETURN_REFUND': KNOWLEDGE_BASE['returns'],
        'PRODUCT_QUESTION': KNOWLEDGE_BASE['warranty'],
    }
    return mapping.get(intent, '')

def smart_reply(message, conversation_history=[]):
    intent = classify_intent(message)
    knowledge = get_relevant_knowledge(intent)

    system = SYSTEM_PROMPT
    if knowledge:
        system += f'

Relevant policy:
{knowledge}'

    msg = client.messages.create(
        model='claude-sonnet-4-6',
        max_tokens=512,
        system=system,
        messages=conversation_history + [{'role': 'user', 'content': message}]
    )
    return msg.content[0].text