kscz0000 AMAZON ALEXA — 使用 Claude 的智能语音
概述
Amazon Alexa 完整集成，用于创建智能语音技能、将 Alexa 转换为以 Claude 为大脑的助手（Auri 项目），以及与 AWS 生态系统集成（Lambda、DynamoDB、Polly、Transcribe、Lex、Smart Home）。
何时使用此技能
- 当你需要此领域的专业协助时
何时不使用此技能
- 任务与 Amazon Alexa 无关时
- 更简单、更具体的工具可以处理请求时
- 用户需要无领域专业知识的通用协助时
工作原理
你是 Alexa 和 AWS Voice 专家。使命：使用 Claude 作为 LLM 后端， 将任何 Alexa 设备转换为超智能助手，具备神经语音、持久记忆 和 Smart Home 控制。关键项目：AURI。
1. 生态系统概述
[Alexa Device] → [Alexa Cloud] → [AWS Lambda] → [Claude API]
语音 转录 逻辑 智能
↑ ↑ ↑ ↑
用户 Intent Handler Anthropic
+ DynamoDB
+ Polly TTS
+ APL Visual
Auri 架构组件
| 组件 | AWS 服务 | 功能 |
|---|---|---|
| 语音 → 文本 | Alexa ASR 原生 | 语音识别 |
| NLU | ASK Interaction Model + Lex V2 | 提取 intent 和 slots |
| 后端 | AWS Lambda (Python/Node.js) | 逻辑和编排 |
| LLM | Claude API (Anthropic) | 智能和响应 |
| 持久化 | Amazon DynamoDB | 历史和偏好 |
| 文本 → 语音 | Amazon Polly (neural) | Auri 自然语音 |
| 可视化界面 | APL (Alexa Presentation Language) | Echo Show 屏幕 |
| Smart Home | Alexa Smart Home API | 设备控制 |
| 自动化 | Alexa Routines API | 智能例程 |
2.1 前置要求
## Ask Cli
npm install -g ask-cli
ask configure
## Aws Cli
pip install awscli
aws configure
使用模板创建 Skill
ask new
--template hello-world
--skill-name auri
--language pt-BR
└── .Ask/Ask-Resources.Json
## 2.3 配置 Invocation Name
在文件 `models/pt-BR.json` 中：
```json
{
"interactionModel": {
"languageModel": {
"invocationName": "auri"
}
}
}
3.1 Auri 核心 Intents
{
"interactionModel": {
"languageModel": {
"invocationName": "auri",
"intents": [
{"name": "AMAZON.HelpIntent"},
{"name": "AMAZON.StopIntent"},
{"name": "AMAZON.CancelIntent"},
{"name": "AMAZON.FallbackIntent"},
{
"name": "ChatIntent",
"slots": [{"name": "query", "type": "AMAZON.SearchQuery"}],
"samples": [
"{query}",
"me ajuda com {query}",
"quero saber sobre {query}",
"o que voce sabe sobre {query}",
"explique {query}",
"pesquise {query}"
]
},
{
"name": "SmartHomeIntent",
"slots": [
{"name": "device", "type": "AMAZON.Room"},
{"name": "action", "type": "ActionType"}
],
"samples": [
"{action} a {device}",
"controla {device}",
"acende {device}",
"apaga {device}"
]
},
{
"name": "RoutineIntent",
"slots": [{"name": "routine", "type": "RoutineType"}],
"samples": [
"ativa rotina {routine}",
"executa {routine}",
"modo {routine}"
]
}
],
"types": [
{
"name": "ActionType",
"values": [
{"name": {"value": "liga", "synonyms": ["acende", "ativa", "liga"]}},
{"name": {"value": "desliga", "synonyms": ["apaga", "desativa", "desliga"]}}
]
},
{
"name": "RoutineType",
"values": [
{"name": {"value": "bom dia", "synonyms": ["acordar", "manhã"]}},
{"name": {"value": "boa noite", "synonyms": ["dormir", "descansar"]}},
{"name": {"value": "trabalho", "synonyms": ["trabalhar", "foco"]}},
{"name": {"value": "sair", "synonyms": ["saindo", "goodbye"]}}
]
}
]
}
}
}
4.1 Python 主 Handler
import os
import time
import anthropic
import boto3
from ask_sdk_core.skill_builder import SkillBuilder
from ask_sdk_core.handler_input import HandlerInput
from ask_sdk_core.utils import is_intent_name, is_request_type
from ask_sdk_model import Response
from ask_sdk_dynamodb_persistence_adapter import DynamoDbPersistenceAdapter
## ============================================================
@sb.request_handler(can_handle_func=is_request_type("LaunchRequest"))
def launch_handler(handler_input: HandlerInput) -> Response:
attrs = handler_input.attributes_manager.persistent_attributes
name = attrs.get("name", "")
greeting = f"Oi{', ' + name if name else ''}! Eu sou a Auri. Como posso ajudar?"
return (handler_input.response_builder
.speak(greeting).ask("Em que posso ajudar?").response)
@sb.request_handler(can_handle_func=is_intent_name("ChatIntent"))
def chat_handler(handler_input: HandlerInput) -> Response:
try:
# Obter query
slots = handler_input.request_envelope.request.intent.slots
query = slots["query"].value if slots.get("query") else None
if not query:
return (handler_input.response_builder
.speak("Pode repetir? Nao entendi bem.").ask("Pode repetir?").response)
# Carregar historico
attrs = handler_input.attributes_manager.persistent_attributes
history = attrs.get("history", [])
# Montar mensagens para Claude
messages = history[-MAX_HISTORY:]
messages.append({"role": "user", "content": query})
# Chamar Claude
client = anthropic.Anthropic(api_key=os.environ["ANTHROPIC_API_KEY"])
response = client.messages.create(
model=CLAUDE_MODEL,
max_tokens=512,
system=AURI_SYSTEM_PROMPT,
messages=messages
)
reply = response.content[0].text
# Truncar para nao exceder timeout
if len(reply) > MAX_RESPONSE_CHARS:
reply = reply[:MAX_RESPONSE_CHARS] + "... Quer que eu continue?"
# Salvar historico
history.append({"role": "user", "content": query})
history.append({"role": "assistant", "content": reply})
attrs["history"] = history[-50:] # Manter ultimas 50
handler_input.attributes_manager.persistent_attributes = attrs
handler_input.attributes_manager.save_persist
## 4.2 Lambda 环境变量
ANTHROPIC_API_KEY=sk-... (armazenar em Secrets Manager) DYNAMODB_TABLE=auri-users AWS_REGION=us-east-1
## 4.3 Requirements.Txt
ask-sdk-core>=1.19.0 ask-sdk-dynamodb-persistence-adapter>=1.19.0 anthropic>=0.40.0 boto3>=1.34.0
---
## 5.1 创建表
```bash
aws dynamodb create-table \
--table-name auri-users \
--attribute-definitions AttributeName=userId,AttributeType=S \
--key-schema AttributeName=userId,KeyType=HASH \
--billing-mode PAY_PER_REQUEST \
--region us-east-1
5.2 用户 Schema
{
"userId": "amzn1.ask.account.XXXXX",
"name": "Joao",
"history": [
{"role": "user", "content": "..."},
{"role": "assistant", "content": "..."}
],
"preferences": {
"language": "pt-BR",
"voice": "Vitoria",
"personality": "assistente profissional"
},
"smartHome": {
"devices": {},
"routines": {}
},
"updatedAt": 1740960000,
"ttl": 1748736000
}
5.3 自动 TTL（过期旧数据）
import time
## Adicionar Ttl De 180 Dias Ao Salvar
attrs["ttl"] = int(time.time()) + (180 * 24 * 3600)
6.1 可用语音（葡萄牙语）
| 语音 | 语言 | 类型 | 推荐 |
|---|---|---|---|
Vitoria |
pt-BR | Neural | ✅ Auri PT-BR |
Camila |
pt-BR | Neural | 备选 |
Ricardo |
pt-BR | Standard | 男声 |
Ines |
pt-PT | Neural | 葡萄牙 |
6.2 在响应中集成 Polly
import boto3
import base64
def synthesize_polly(text: str, voice_id: str = "Vitoria") -> str:
"""Retorna URL de audio Polly para usar em Alexa."""
client = boto3.client("polly", region_name="us-east-1")
response = client.synthesize_speech(
Text=text,
OutputFormat="mp3",
VoiceId=voice_id,
Engine="neural"
)
# Salvar em S3 e retornar URL
# (necessario para usar audio customizado no Alexa)
return upload_to_s3(response["AudioStream"].read())
def speak_with_polly(handler_input, text, voice_id="Vitoria"):
"""Retornar resposta usando voz Polly customizada via SSML."""
audio_url = synthesize_polly(text, voice_id)
ssml = f'<speak><audio src="{audio_url}"/></speak>'
return handler_input.response_builder.speak(ssml)
6.3 语音控制 SSML
<speak>
<prosody rate="90%" pitch="+5%">
Oi! Eu sou a Auri.
</prosody>
<break time="0.5s"/>
<emphasis level="moderate">Como posso ajudar?</emphasis>
</speak>
7.1 聊天模板
{
"type": "APL",
"version": "2023.3",
"theme": "dark",
"mainTemplate": {
"parameters": ["payload"],
"items": [{
"type": "Container",
"width": "100%",
"height": "100%",
"backgroundColor": "#1a1a2e",
"items": [
{
"type": "Text",
"text": "AURI",
"fontSize": "32px",
"color": "#e94560",
"textAlign": "center",
"paddingTop": "20px"
},
{
"type": "Text",
"text": "${payload.lastResponse}",
"fontSize": "24px",
"color": "#ffffff",
"padding": "20px",
"maxLines": 8,
"grow": 1
},
{
"type": "Text",
"text": "Diga algo para continuar...",
"fontSize": "18px",
"color": "#888888",
"textAlign": "center",
"paddingBottom": "20px"
}
]
}]
}
}
7.2 在响应中添加 APL
@sb.request_handler(can_handle_func=is_intent_name("ChatIntent"))
def chat_with_apl(handler_input: HandlerInput) -> Response:
# ... obter reply do Claude ...
# Verificar se device suporta APL
supported = handler_input.request_envelope.context.system.device.supported_interfaces
has_apl = getattr(supported, "alexa_presentation_apl", None) is not None
if has_apl:
apl_directive = {
"type": "Alexa.Presentation.APL.RenderDocument",
"token": "auri-chat",
"document": CHAT_APL_DOCUMENT,
"datasources": {"payload": {"lastResponse": reply}}
}
handler_input.response_builder.add_directive(apl_directive)
return handler_input.response_builder.speak(reply).ask("Mais alguma coisa?").response
8.1 启用 Smart Home Skill
在 skill.json 中添加：
{
"apis": {
"smartHome": {
"endpoint": {
"uri": "arn:aws:lambda:us-east-1:123456789:function:auri-smart-home"
}
}
}
}
8.2 Smart Home Handler
def handle_smart_home_directive(event, context):
namespace = event["directive"]["header"]["namespace"]
name = event["directive"]["header"]["name"]
endpoint_id = event["directive"]["endpoint"]["endpointId"]
if namespace == "Alexa.PowerController":
state = "ON" if name == "TurnOn" else "OFF"
# Chamar sua API de smart home
control_device(endpoint_id, {"power": state})
return build_smart_home_response(endpoint_id, "powerState", state)
elif namespace == "Alexa.BrightnessController":
brightness = event["directive"]["payload"]["brightness"]
control_device(endpoint_id, {"brightness": brightness})
return build_smart_home_response(endpoint_id, "brightness", brightness)
8.3 设备发现
def handle_discovery(event, context):
return {
"event": {
"header": {
"namespace": "Alexa.Discovery",
"name": "Discover.Response",
"payloadVersion": "3"
},
"payload": {
"endpoints": [
{
"endpointId": "light-sala-001",
"friendlyName": "Luz da Sala",
"displayCategories": ["LIGHT"],
"capabilities": [
{
"type": "AlexaInterface",
"interface": "Alexa.PowerController",
"version": "3"
},
{
"type": "AlexaInterface",
"interface": "Alexa.BrightnessController",
"version": "3"
}
]
}
]
}
}
}
完整部署（Skill + Lambda）
cd auri/ ask deploy
验证状态
ask status
在模拟器中测试
ask dialog --locale pt-BR
测试特定 Intent
ask simulate
--text "abrir auri"
--locale pt-BR
--skill-id amzn1.ask.skill.YOUR-SKILL-ID
## 手动创建 Lambda
aws lambda create-function \
--function-name auri-skill \
--runtime python3.11 \
--role arn:aws:iam::ACCOUNT:role/auri-lambda-role \
--handler lambda_function.handler \
--timeout 8 \
--memory-size 512 \
--zip-file fileb://function.zip
## 添加 Alexa 触发器
aws lambda add-permission \
--function-name auri-skill \
--statement-id alexa-skill-trigger \
--action lambda:InvokeFunction \
--principal alexa-appkit.amazon.com \
--event-source-token amzn1.ask.skill.YOUR-SKILL-ID
使用 Secrets Manager
aws secretsmanager create-secret
--name auri/anthropic-key
--secret-string '{"ANTHROPIC_API_KEY": "sk-..."}'
Lambda 通过 SDK 访问：
import boto3, json def get_secret(secret_name): client = boto3.client('secretsmanager') response = client.get_secret_value(SecretId=secret_name) return json.loads(response['SecretString'])
---
## 阶段 1 — 设置（第 1 天）
[ ] Amazon Developer 账户已创建 [ ] AWS 账户已配置（free tier） [ ] ASK CLI 已安装和配置 [ ] IAM Role 已创建，权限包括：Lambda、DynamoDB、Polly、Logs [ ] Anthropic API key 已存储在 Secrets Manager
## 阶段 2 — Skill 基础（第 2-3 天）
[ ] ask new --template hello-world --skill-name auri [ ] Interaction model 已定义（pt-BR.json） [ ] LaunchRequest handler 正常工作 [ ] ChatIntent handler 已集成 Claude [ ] ask deploy 正常工作 [ ] 在 ASK simulator 中基础测试通过
## 阶段 3 — 持久化（第 4 天）
[ ] DynamoDB 表已创建 [ ] 历史持久化正常工作 [ ] TTL 已配置 [ ] 用户偏好已保存
## 阶段 4 — Polly + APL（第 5-6 天）
[ ] Polly 已集成 Vitoria 语音（neural） [ ] APL 聊天模板已创建 [ ] APL 在 Echo Show 模拟器中渲染
## 阶段 5 — Smart Home（可选）
[ ] Smart Home skill 已启用 [ ] 设备发现正常工作 [ ] PowerController 已实现 [ ] 使用真实设备测试
## 阶段 6 — 发布
[ ] 所有功能完整测试 [ ] 性能 OK（< 8s timeout） [ ] Amazon 认证已提交 [ ] 已在 Alexa Skills Store 发布
---
## 11. 快速命令
| 操作 | 命令 |
|------|------|
| 创建 skill | `ask new --template hello-world` |
| 部署 | `ask deploy` |
| 模拟 | `ask simulate --text "abre a auri"` |
| 交互式对话 | `ask dialog --locale pt-BR` |
| 查看日志 | `ask smapi get-skill-simulation` |
| 验证模型 | `ask validate --locales pt-BR` |
| 导出 skill | `ask smapi export-package --skill-id ID` |
| 列出 skills | `ask list skills` |
---
## 12. 参考资料
- 完整 Python 样板：`assets/boilerplate/lambda_function.py`
- PT-BR Interaction model：`assets/interaction-models/pt-BR.json`
- APL 聊天模板：`assets/apl-templates/chat-interface.json`
- Smart Home 示例：`references/smart-home-api.md`
- ASK SDK Python 文档：https://github.com/alexa/alexa-skills-kit-sdk-for-python
- Claude + Alexa 指南：https://www.anthropic.com/news/claude-and-alexa-plus
## 最佳实践
- 提供清晰、具体的项目上下文和需求
- 在将建议应用于生产代码前进行审查
- 结合其他互补技能进行全面分析
## 常见陷阱
- 将此技能用于其领域专业范围之外的任务
- 在不了解具体上下文的情况下应用建议
- 未提供足够的项目上下文以进行准确分析
## 局限性
- 仅当任务明显符合上述描述的范围时使用此技能。
- 不要将输出视为环境特定验证、测试或专家审查的替代品。
- 如果缺少必需的输入、权限、安全边界或成功标准，请停下来请求澄清。