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要遵循本指南，您需要：
ANTHROPIC_API_KEY 环境变量）安装所需的软件包：
pip install anthropic streamlit python-dotenv以下是一些关键指标，表明您应该使用像 Claude 这样的 LLM 来自动化部分客户支持流程：
选择 Claude 而非其他 LLM 的一些考虑因素：
概述一个理想的客户交互，以定义您期望客户如何以及何时与 Claude 交互。这个概述将有助于确定您解决方案的技术需求。
以下是汽车保险客户支持的聊天交互示例：
客户支持聊天是多个不同任务的集合，从问题回答到信息检索再到对请求采取行动，所有这些都包含在单个客户交互中。在开始构建之前，将您理想的客户交互分解为您希望 Claude 能够执行的每个任务。这可以确保您能够针对每个任务对 Claude 进行提示和评估，并让您很好地了解在编写测试用例时需要考虑的交互范围。
以下是与保险交互示例相关的关键任务：
问候和一般指导
产品信息
对话管理
报价生成
与您的支持团队合作，定义成功标准并编写详细的评估，包含可衡量的基准和目标。
以下是可用于评估 Claude 执行既定任务成功程度的标准和基准：
以下是可用于评估使用 Claude 进行支持的业务影响的标准和基准：
模型的选择取决于成本、准确性和响应时间之间的权衡。
对于客户支持聊天，Claude Opus 5 非常适合平衡智能、延迟和成本，包括需要在长时间、多步骤对话中进行深度推理的最复杂的支持场景。但是，对于包含 RAG、工具使用或长上下文提示等多个提示的对话流程，Claude Haiku 4.5 可能更适合优化延迟。
使用 Claude 进行客户支持需要 Claude 有足够的指导和上下文来做出适当的回应，同时有足够的灵活性来处理广泛的客户询问。
首先编写强大提示的各个元素，从系统提示开始。创建一个名为 config.py 的文件，并将以下每个代码块添加到其中：
IDENTITY = """You are Eva, a friendly and knowledgeable AI assistant for Acme Insurance
Company. Your role is to warmly welcome customers and provide information on
Acme's insurance offerings, which include car insurance and electric car
insurance. You can also help customers get quotes for their insurance needs."""User 轮次中时效果最好（唯一的例外是角色提示）。请阅读通过系统提示赋予 Claude 角色了解更多信息。最好将复杂的提示分解为子部分，一次编写一部分。对于每个任务，您可能会发现遵循逐步流程来定义 Claude 完成该任务所需的提示部分会更成功。对于这个汽车保险客户支持示例，您将从"问候和一般指导"任务开始，逐步编写提示的所有部分。这也使调试提示更容易，因为您可以更快地调整整体提示的各个部分。
STATIC_GREETINGS_AND_GENERAL = """
<static_context>
Acme Auto Insurance: Your Trusted Companion on the Road
About:
At Acme Insurance, we understand that your vehicle is more than just a mode of transportation—it's your ticket to life's adventures.
Since 1985, we've been crafting auto insurance policies that give drivers the confidence to explore, commute, and travel with peace of mind.
Whether you're navigating city streets or embarking on cross-country road trips, Acme is there to protect you and your vehicle.
Our innovative auto insurance policies are designed to adapt to your unique needs, covering everything from fender benders to major collisions.
With Acme's award-winning customer service and swift claim resolution, you can focus on the joy of driving while we handle the rest.
We're not just an insurance provider—we're your co-pilot in life's journeys.
Choose Acme Auto Insurance and experience the assurance that comes with superior coverage and genuine care. Because at Acme, we don't just
insure your car—we fuel your adventures on the open road.
Note: We also offer specialized coverage for electric vehicles, ensuring that drivers of all car types can benefit from our protection.
Acme Insurance offers the following products:
- Car insurance
- Electric car insurance
- Two-wheeler insurance
Business hours: Monday-Friday, 9 AM - 5 PM EST
Customer service number: 1-800-123-4567
</static_context>
"""然后对您的汽车保险和电动汽车保险信息执行相同的操作。
STATIC_CAR_INSURANCE = """
<static_context>
Car Insurance Coverage:
Acme's car insurance policies typically cover:
1. Liability coverage: Pays for bodily injury and property damage you cause to others.
2. Collision coverage: Pays for damage to your car in an accident.
3. Comprehensive coverage: Pays for damage to your car from non-collision incidents.
4. Medical payments coverage: Pays for medical expenses after an accident.
5. Uninsured/underinsured motorist coverage: Protects you if you're hit by a driver with insufficient insurance.
Optional coverages include:
- Rental car reimbursement
- Roadside assistance
- New car replacement
</static_context>
"""
STATIC_ELECTRIC_CAR_INSURANCE = """
<static_context>
Electric Car Insurance:
Our specialized electric car insurance goes beyond traditional auto coverage,
offering tailored protection for your high-tech investment. In addition to standard coverages, we offer:
- Safeguarding expensive battery systems
- Covering home charging equipment
- Adapting to the rapidly evolving world of electric vehicles
Whether you're driving a Rivian, Nissan Leaf, Chevrolet Bolt,
or any other electric vehicle, our knowledgeable agents are ready to craft a policy
that gives you the confidence to enjoy every electron-powered mile.
</static_context>
"""现在您已经有了静态内容，添加至少 4-5 个"良好"交互示例来指导 Claude 的回复。这些示例应该代表您理想的客户交互，并且可以包括护栏、工具调用等。
EXAMPLES = """
Here are a few examples of how you can interact with customers:
<example 1>
H: Hi, do you offer commercial insurance for small businesses?
A: Ah! Unfortunately, we don't offer commercial insurance at this time.
However, we do provide a range of personal insurance products including car insurance and electric car insurance.
Would you like to know more about these offerings?
</example 1>
<example 2>
H: Hi, what are your business hours?
A: Our business hours are Monday to Friday, 9 AM to 5 PM EST.
If you have any questions or need assistance, feel free to reach out during those times.
How else can I assist you today?
</example 2>
<example 3>
H: I'm shopping for car insurance. What does Acme offer?
A: Great choice! Acme's car insurance policies typically include:
- Liability coverage: Protects you if you're at fault in an accident
- Collision coverage: Pays for damage to your car in an accident
- Comprehensive coverage: Covers non-collision incidents like theft or vandalism
- Medical payments coverage: Pays for medical expenses after an accident
- Uninsured/underinsured motorist coverage: Protects you from drivers with insufficient insurance
We also offer optional coverages like rental car reimbursement, roadside assistance, and new car replacement.
Would you like more details on any of these coverages, or do you have specific questions about insuring your vehicle?
</example 3>
<example 4>
H: I'd like to hear about your electric car insurance.
A: Certainly! Our electric car insurance is specially designed to meet the unique needs of electric vehicle owners.
In addition to all the standard coverages we offer for regular cars, our electric car policies include:
- Battery coverage: Protection against damage or degradation of your vehicle's expensive battery system
- Tech package: Covers repairs or replacement of advanced electronics and onboard computer systems
- Charging station coverage: Protects both home and portable charging equipment
- Cybersecurity protection: Coverage against hacking or digital threats
- Specialized roadside assistance: Includes flatbed towing to protect the vehicle's undercarriage
We cover a wide range of electric vehicles, including popular models from Tesla, Rivian, Nissan, Chevrolet, and more.
Is there a specific electric vehicle you're looking to insure, or would you like more details on any of these coverages?
</example 4>
<example 5>
H: I'd like to get a quote for my car insurance.
A: Certainly! I'd be happy to help you get a quote for your car insurance.
To provide you with an accurate quote, I'll need to collect some information about your vehicle and the primary driver.
Let's start with the basics:
1. What is the make and model of your vehicle?
2. What year was it manufactured?
3. Approximately how many miles have you driven?
4. What is the age of the primary driver?
Once you provide this information, I'll use our quoting tool to generate a personalized insurance quote for you.
</example 5>
"""您还需要包含任何重要的指令，概述 Claude 与客户交互时应该做什么和不应该做什么。 这可能来自品牌护栏或支持政策。
ADDITIONAL_GUARDRAILS = """Please adhere to the following guardrails:
1. Only provide information about insurance types listed in our offerings.
2. If asked about an insurance type we don't offer, politely state
that we don't provide that service.
3. Do not speculate about future product offerings or company plans.
4. Don't make promises or enter into agreements it's not authorized to make.
You only provide information and guidance.
5. Do not mention any competitor's products or services.
"""现在将所有这些部分组合成一个字符串，用作您的提示。
TASK_SPECIFIC_INSTRUCTIONS = " ".join(
[
STATIC_GREETINGS_AND_GENERAL,
STATIC_CAR_INSURANCE,
STATIC_ELECTRIC_CAR_INSURANCE,
EXAMPLES,
ADDITIONAL_GUARDRAILS,
]
)Claude 能够使用客户端工具使用功能动态地采取行动和检索信息。首先列出提示应该使用的任何外部工具或 API。
对于此示例，从一个用于计算报价的工具开始。
将模型名称、工具定义和存根实现添加到 config.py：
import time
MODEL = "claude-opus-5"
TOOLS = [
{
"name": "get_quote",
"description": "Calculate the insurance quote based on user input. Returned value is per month premium.",
"input_schema": {
"type": "object",
"properties": {
"make": {"type": "string", "description": "The make of the vehicle."},
"model": {"type": "string", "description": "The model of the vehicle."},
"year": {
"type": "integer",
"description": "The year the vehicle was manufactured.",
},
"mileage": {
"type": "integer",
"description": "The mileage on the vehicle.",
},
"driver_age": {
"type": "integer",
"description": "The age of the primary driver.",
},
},
"required": ["make", "model", "year", "mileage", "driver_age"],
},
}
]
def get_quote(make, model, year, mileage, driver_age):
"""Returns the premium per month in USD"""
# 您可以调用 http 端点或数据库来获取报价。
# 这里我们模拟 1 秒的延迟，并返回固定报价 100。
time.sleep(1)
return 100如果不在测试生产环境中部署提示并运行评估，就很难知道您的提示效果如何。使用提示、Anthropic SDK 和 Streamlit 构建一个小型应用程序作为用户界面。
在一个名为 chatbot.py 的文件（或您所用语言中的等效模块）中，设置 ChatBot 类，它将封装与 Anthropic SDK 的交互。
该类应该有两个主要方法：一个调用 API 生成消息，另一个处理每个传入的用户输入。
# 在您的 chatbot.py 中，从上面编写的 config.py 导入以下内容：
# from config import IDENTITY, TOOLS, MODEL, get_quote
from anthropic import Anthropic
from dotenv import load_dotenv
load_dotenv()
class ChatBot:
def __init__(self, session_state):
self.anthropic = Anthropic()
self.session_state = session_state
def generate_message(
self,
messages,
max_tokens,
):
try:
response = self.anthropic.messages.create(
model=MODEL,
system=IDENTITY,
max_tokens=max_tokens,
messages=messages,
tools=TOOLS,
)
return response
except Exception as e:
return {"error": str(e)}
def process_user_input(self, user_input):
self.session_state.messages.append({"role": "user", "content": user_input})
response_message = self.generate_message(
messages=self.session_state.messages,
max_tokens=2048,
)
if "error" in response_message:
return f"An error occurred: {response_message['error']}"
if response_message.content[-1].type == "tool_use":
tool_use = response_message.content[-1]
func_name = tool_use.name
func_params = tool_use.input
tool_use_id = tool_use.id
result = self.handle_tool_use(func_name, func_params)
self.session_state.messages.append(
{"role": "assistant", "content": response_message.content}
)
self.session_state.messages.append(
{
"role": "user",
"content": [
{
"type": "tool_result",
"tool_use_id": tool_use_id,
"content": f"{result}",
}
],
}
)
follow_up_response = self.generate_message(
messages=self.session_state.messages,
max_tokens=2048,
)
if "error" in follow_up_response:
return f"An error occurred: {follow_up_response['error']}"
response_text = next(
(block.text for block in follow_up_response.content if block.type == "text"),
None,
)
if response_text is None:
raise Exception("An error occurred: Unexpected response type")
self.session_state.messages.append(
{"role": "assistant", "content": response_text}
)
return response_text
text_block = next(
(block for block in response_message.content if block.type == "text"), None
)
if text_block is not None:
response_text = text_block.text
self.session_state.messages.append(
{"role": "assistant", "content": response_text}
)
return response_text
raise Exception("An error occurred: Unexpected response type")
def handle_tool_use(self, func_name, func_params):
if func_name == "get_quote":
premium = get_quote(**func_params)
return f"Quote generated: ${premium:.2f} per month"
raise Exception("An unexpected tool was used")使用 main 方法通过 Streamlit 测试部署此代码。这个 main() 函数设置了一个基于 Streamlit 的聊天界面。Streamlit 是一个 Python 框架，因此本演练的这一部分仅以 Python 展示；上面的 ChatBot 类是您可以移植到任何语言的部分。
在一个名为 app.py 的文件中执行此操作
import streamlit as st
from chatbot import ChatBot
from config import TASK_SPECIFIC_INSTRUCTIONS
def main():
st.title("Chat with Eva, Acme Insurance Company's Assistant🤖")
if "messages" not in st.session_state:
st.session_state.messages = [
{"role": "user", "content": TASK_SPECIFIC_INSTRUCTIONS},
{"role": "assistant", "content": "Understood"},
]
chatbot = ChatBot(st.session_state)
# 显示用户和助手消息，跳过前两条
for message in st.session_state.messages[2:]:
# 忽略工具使用块
if isinstance(message["content"], str):
with st.chat_message(message["role"]):
st.markdown(message["content"])
if user_msg := st.chat_input("Type your message here..."):
st.chat_message("user").markdown(user_msg)
with st.chat_message("assistant"):
with st.spinner("Eva is thinking..."):
response_placeholder = st.empty()
full_response = chatbot.process_user_input(user_msg)
response_placeholder.markdown(full_response)
if __name__ == "__main__":
main()使用以下命令运行程序：
streamlit run app.py提示通常需要测试和优化才能达到生产就绪状态。要确定您的解决方案是否就绪，请使用结合定量和定性方法的系统化流程来评估聊天机器人的性能。基于您定义的成功标准创建强大的实证评估将使您能够优化您的提示。
在复杂的场景中，除了标准的提示工程技术和护栏实现策略之外，考虑其他策略来提高性能可能会有所帮助。以下是一些常见场景：
在处理大量静态和动态上下文时，将所有信息都包含在提示中可能会导致高成本、较慢的响应时间以及达到上下文窗口限制。在这种情况下，实现 "Retrieval Augmented Generation"（检索增强生成），即 RAG 技术可以提高性能和效率。
通过使用像 Voyage 这样的嵌入模型将信息转换为向量表示，您可以创建一个更具可扩展性和响应性的系统。这种方法允许根据当前查询动态检索相关信息，而不是在每个提示中包含所有可能的上下文。
在具有大量上下文需求的系统中，为支持用例实现 RAG 已被证明可以提高准确性、减少响应时间并降低 API 成本。请参阅 RAG 示例了解实际案例。
在处理需要实时信息的查询（例如账户余额或保单详情）时，基于嵌入的 RAG 方法是不够的。相反，工具使用可以增强您的聊天机器人提供准确、实时响应的能力。例如，您可以使用工具使用来查找客户信息、检索订单详情以及代表客户取消订单。
这种方法（在工具使用：客户服务代理示例中概述）让您可以将实时数据集成到 Claude 的回复中，并提供更个性化和高效的客户体验。
在部署聊天机器人时，尤其是在客户服务场景中，防止与滥用、超出范围的查询和不当回复相关的风险非常重要。虽然 Claude 本身对此类场景具有弹性，但以下是加强聊天机器人护栏的额外步骤：
在处理可能较长的回复时，实现流式传输可以提高用户参与度和满意度。在这种情况下，用户会逐步收到答案，而不是等待整个回复生成完毕。
以下是实现流式传输的方法：
在某些情况下，流式传输使得可以使用具有更高基础延迟的更高级模型，因为渐进式显示减轻了较长处理时间的影响。
随着聊天机器人复杂性的增长，您的应用程序架构可以相应地演进。在向架构添加更多层之前，请考虑以下不太详尽的选项：
如果您的聊天机器人处理非常多样化的任务，您可能需要考虑添加一个单独的意图分类器来路由初始客户查询。对于现有应用程序，这将涉及创建一个决策树，通过分类器路由客户查询，然后路由到专门的对话（具有自己的一组工具和系统提示）。请注意，此方法需要额外调用 Claude，这可能会增加延迟。
虽然这些示例侧重于在 Streamlit 环境中可调用的 Python 函数，但部署 Claude 用于实时支持聊天机器人需要一个 API 服务。
以下是您可以采取的方法：
创建 API 包装器：围绕您的分类函数开发一个简单的 API 包装器。例如，您可以使用 Flask API 或 Fast API 将您的代码包装成 HTTP 服务。您的 HTTP 服务可以接受用户输入并完整返回 Assistant 的回复。因此，您的服务可以具有以下特性：
构建 Web 界面：实现一个用户友好的 Web UI，用于与由 Claude 驱动的代理进行交互。
让 Claude 访问您的 API，以便它可以代表客户采取行动。
构建评估，以根据您定义的成功标准衡量您的支持代理。
流式传输响应，让客户在答案生成时即可看到。
优化您的系统提示和示例，以获得更好的任务性能。
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