AI 던전 게임
모듈 3: 스토리 API 구현
StoryApi는 Game
과 컨텍스트용 Action
목록을 입력받아 스토리를 진행하는 단일 API generate_story
로 구성됩니다. 이 API는 Python/FastAPI로 스트리밍 API로 구현되며, 생성된 코드를 목적에 맞게 수정하는 방법을 추가로 시연합니다.
API 구현
API를 생성하기 전에 먼저 몇 가지 추가 종속성을 설치해야 합니다.
boto3
는 Amazon Bedrock 호출에 사용됩니다.uvicorn
은 Lambda Web Adapter (LWA)와 함께 사용할 때 API 시작에 사용됩니다.copyfiles
는bundle
작업 업데이트 시 크로스 플랫폼 파일 복사를 지원하기 위한 npm 종속성입니다.
이 종속성들을 설치하려면 다음 명령어를 실행하세요:
pnpm nx run dungeon_adventure.story_api:add --args boto3 uvicorn
yarn nx run dungeon_adventure.story_api:add --args boto3 uvicorn
npx nx run dungeon_adventure.story_api:add --args boto3 uvicorn
bunx nx run dungeon_adventure.story_api:add --args boto3 uvicorn
pnpm add -Dw copyfiles
yarn add -D copyfiles
npm install --legacy-peer-deps -D copyfiles
bun install -D copyfiles
이제 packages/story_api/story_api
의 다음 파일 내용을 교체합니다:
import json
from boto3 import clientfrom fastapi.responses import PlainTextResponse, StreamingResponsefrom pydantic import BaseModel
from .init import app, lambda_handler
handler = lambda_handler
bedrock = client('bedrock-runtime')
class Action(BaseModel): role: str content: str
class StoryRequest(BaseModel): genre: str playerName: str actions: list[Action]
async def bedrock_stream(request: StoryRequest): messages = [ {"role": "user", "content": "Continue or create a new story..."} ]
for action in request.actions: messages.append({"role": action.role, "content": action.content})
response = bedrock.invoke_model_with_response_stream( modelId='anthropic.claude-3-sonnet-20240229-v1:0', body=json.dumps({ "system":f""" You are running an AI text adventure game in the {request.genre} genre. Player: {request.playerName}. Return less than 200 characters of text. """, "messages": messages, "max_tokens": 1000, "temperature": 0.7, "anthropic_version": "bedrock-2023-05-31" }) )
stream = response.get('body') if stream: for event in stream: chunk = event.get('chunk') if chunk: message = json.loads(chunk.get("bytes").decode()) if message['type'] == "content_block_delta": yield message['delta']['text'] or "" elif message['type'] == "message_stop": yield "\n"
@app.post("/story/generate", openapi_extra={'x-streaming': True}, response_class=PlainTextResponse)def generate_story(request: StoryRequest) -> str: return StreamingResponse(bedrock_stream(request), media_type="text/plain")
import osimport uuidfrom collections.abc import Callable
from aws_lambda_powertools import Logger, Metrics, Tracerfrom aws_lambda_powertools.metrics import MetricUnitfrom fastapi import FastAPI, Request, Responsefrom fastapi.openapi.utils import get_openapifrom fastapi.responses import JSONResponsefrom fastapi.routing import APIRoutefrom mangum import Mangumfrom pydantic import BaseModelfrom starlette.middleware.exceptions import ExceptionMiddleware
os.environ["POWERTOOLS_METRICS_NAMESPACE"] = "StoryApi"os.environ["POWERTOOLS_SERVICE_NAME"] = "StoryApi"
logger: Logger = Logger()metrics: Metrics = Metrics()tracer: Tracer = Tracer()
class InternalServerErrorDetails(BaseModel): detail: str
app = FastAPI( title="StoryApi", responses={ 500: {"model": InternalServerErrorDetails} })lambda_handler = Mangum(app)
# Add tracinglambda_handler.__name__ = "handler" # tracer requires __name__ to be setlambda_handler = tracer.capture_lambda_handler(lambda_handler)# Add logginglambda_handler = logger.inject_lambda_context(lambda_handler, clear_state=True)# Add metrics last to properly flush metrics.lambda_handler = metrics.log_metrics(lambda_handler, capture_cold_start_metric=True)
# Add exception middleware(s)app.add_middleware(ExceptionMiddleware, handlers=app.exception_handlers)
@app.exception_handler(Exception)async def unhandled_exception_handler(request, err): logger.exception("Unhandled exception")
metrics.add_metric(name="Failure", unit=MetricUnit.Count, value=1)
return JSONResponse(status_code=500, content=InternalServerErrorDetails( detail="Internal Server Error").model_dump())
@app.middleware("http")async def metrics_handler(request: Request, call_next): metrics.add_dimension("route", f"{request.method} {request.url.path}") metrics.add_metric(name="RequestCount", unit=MetricUnit.Count, value=1)
response = await call_next(request)
if response.status_code == 200: metrics.add_metric(name="Success", unit=MetricUnit.Count, value=1)
return response
# Add correlation id middleware@app.middleware("http")async def add_correlation_id(request: Request, call_next): # Get correlation id from X-Correlation-Id header corr_id = request.headers.get("x-correlation-id") if not corr_id and "aws.context" in request.scope: # If empty, use request id from aws context corr_id = request.scope["aws.context"].aws_request_id elif not corr_id: # If still empty, use uuid corr_id = uuid.uuid4().hex
# Add correlation id to logs logger.set_correlation_id(corr_id)
response = await call_next(request)
# Return correlation header in response response.headers["X-Correlation-Id"] = corr_id return response
class LoggerRouteHandler(APIRoute): def get_route_handler(self) -> Callable: original_route_handler = super().get_route_handler()
async def route_handler(request: Request) -> Response: # Add fastapi context to logs ctx = { "path": request.url.path, "route": self.path, "method": request.method, } logger.append_keys(fastapi=ctx) logger.info("Received request")
return await original_route_handler(request)
return route_handler
app.router.route_class = LoggerRouteHandler
def custom_openapi(): if app.openapi_schema: return app.openapi_schema for route in app.routes: if isinstance(route, APIRoute): route.operation_id = route.name openapi_schema = get_openapi( title=app.title, version=app.version, openapi_version=app.openapi_version, description=app.description, routes=app.routes, ) app.openapi_schema = openapi_schema return app.openapi_schema
app.openapi = custom_openapi
위 코드 분석:
- 클라이언트 SDK 생성 시 스트리밍 API임을 나타내기 위해
x-streaming
설정을 사용합니다. 이는 타입 안전성을 유지하면서 스트리밍 방식으로 API를 사용할 수 있게 합니다. - API는
media_type="text/plain"
과response_class=PlainTextResponse
로 정의된 텍스트 스트림을 반환합니다.
인프라
이전에 설정한 인프라는 모든 API가 Lambda 함수와 통합하는 API Gateway를 사용한다고 가정합니다. story_api
의 경우 스트리밍 응답을 지원하지 않는 API Gateway 대신 응답 스트리밍이 구성된 Lambda Function URL을 사용합니다.
이를 지원하기 위해 CDK 구성을 다음과 같이 업데이트합니다:
import { Duration, Stack, CfnOutput } from 'aws-cdk-lib';import { IGrantable, Grant } from 'aws-cdk-lib/aws-iam';import { Runtime, Code, Tracing, LayerVersion, FunctionUrlAuthType, InvokeMode, Function,} from 'aws-cdk-lib/aws-lambda';import { Construct } from 'constructs';import url from 'url';import { RuntimeConfig } from '../../core/runtime-config.js';
export class StoryApi extends Construct { public readonly handler: Function;
constructor(scope: Construct, id: string) { super(scope, id);
this.handler = new Function(this, 'Handler', { runtime: Runtime.PYTHON_3_12, handler: 'run.sh', code: Code.fromAsset( url.fileURLToPath( new URL( '../../../../../../dist/packages/story_api/bundle', import.meta.url, ), ), ), timeout: Duration.seconds(30), tracing: Tracing.ACTIVE, environment: { AWS_CONNECTION_REUSE_ENABLED: '1', }, });
const stack = Stack.of(this); this.handler.addLayers( LayerVersion.fromLayerVersionArn( this, 'LWALayer', `arn:aws:lambda:${stack.region}:753240598075:layer:LambdaAdapterLayerX86:24`, ), ); this.handler.addEnvironment('PORT', '8000'); this.handler.addEnvironment('AWS_LWA_INVOKE_MODE', 'response_stream'); this.handler.addEnvironment('AWS_LAMBDA_EXEC_WRAPPER', '/opt/bootstrap'); const functionUrl = this.handler.addFunctionUrl({ authType: FunctionUrlAuthType.AWS_IAM, invokeMode: InvokeMode.RESPONSE_STREAM, cors: { allowedOrigins: ['*'], allowedHeaders: [ 'authorization', 'content-type', 'x-amz-content-sha256', 'x-amz-date', 'x-amz-security-token', ], }, });
new CfnOutput(this, 'StoryApiUrl', { value: functionUrl.url });
// Register the API URL in runtime configuration for client discovery RuntimeConfig.ensure(this).config.apis = { ...RuntimeConfig.ensure(this).config.apis!, StoryApi: functionUrl.url, }; }
public grantInvokeAccess(grantee: IGrantable) { Grant.addToPrincipal({ grantee, actions: ['lambda:InvokeFunctionUrl'], resourceArns: [this.handler.functionArn], conditions: { StringEquals: { 'lambda:FunctionUrlAuthType': 'AWS_IAM', }, }, }); }}
import { GameApi, GameUI, StoryApi, UserIdentity,} from ':dungeon-adventure/common-constructs';import * as cdk from 'aws-cdk-lib';import { Construct } from 'constructs';import { ElectrodbDynamoTable } from '../constructs/electrodb-table.js';import { PolicyStatement, Effect } from 'aws-cdk-lib/aws-iam';
export class ApplicationStack extends cdk.Stack { constructor(scope: Construct, id: string, props?: cdk.StackProps) { super(scope, id, props);
// The code that defines your stack goes here const userIdentity = new UserIdentity(this, 'UserIdentity');
const electroDbTable = new ElectrodbDynamoTable(this, 'ElectroDbTable');
const gameApi = new GameApi(this, 'GameApi', { integrations: GameApi.defaultIntegrations(this) .withDefaultOptions({ environment: { TABLE_NAME: electroDbTable.tableName, }, }) .build(), });
// Grant read/write access to each procedure's lambda handler according to the permissions it requires // Grant read/write access to each handler depending on the permissions it requires electroDbTable.grantReadData(gameApi.integrations['actions.query'].handler); electroDbTable.grantReadData(gameApi.integrations['games.query'].handler); electroDbTable.grantReadWriteData( gameApi.integrations['actions.save'].handler, ); electroDbTable.grantReadWriteData( gameApi.integrations['games.save'].handler, );
const storyApi = new StoryApi(this, 'StoryApi', { integrations: StoryApi.defaultIntegrations(this).build(), }); const storyApi = new StoryApi(this, 'StoryApi'); storyApi.handler.addToRolePolicy( new PolicyStatement({ effect: Effect.ALLOW, actions: ['bedrock:InvokeModelWithResponseStream'], resources: [ 'arn:aws:bedrock:*::foundation-model/anthropic.claude-3-sonnet-20240229-v1:0', ], }), );
// grant our authenticated role access to invoke our APIs [storyApi, gameApi].forEach((api) => api.grantInvokeAccess(userIdentity.identityPool.authenticatedRole), );
// Ensure this is instantiated last so our runtime-config.json can be automatically configured new GameUI(this, 'GameUI'); }}
이제 Lambda Web Adapter 배포를 지원하도록 story_api
를 업데이트합니다.
#!/bin/bash
PATH=$PATH:$LAMBDA_TASK_ROOT/bin \ PYTHONPATH=$PYTHONPATH:/opt/python:$LAMBDA_RUNTIME_DIR \ exec python -m uvicorn --port=$PORT story_api.main:app
{ "name": "dungeon_adventure.story_api", ... "targets": { ... "bundle": { "cache": true, "executor": "nx:run-commands", "outputs": ["{workspaceRoot}/dist/packages/story_api/bundle"], "options": { "commands": [ "uv export --frozen --no-dev --no-editable --project story_api -o dist/packages/story_api/bundle/requirements.txt", "uv pip install -n --no-installer-metadata --no-compile-bytecode --python-platform x86_64-manylinux2014 --target dist/packages/story_api/bundle -r dist/packages/story_api/bundle/requirements.txt", "copyfiles -f packages/story_api/run.sh dist/packages/story_api/bundle" ], "parallel": false }, "dependsOn": ["compile"] }, ... }}
배포 및 테스트
먼저 코드베이스를 빌드합니다:
pnpm nx run-many --target build --all
yarn nx run-many --target build --all
npx nx run-many --target build --all
bunx nx run-many --target build --all
이제 다음 명령어로 애플리케이션을 배포할 수 있습니다:
pnpm nx run @dungeon-adventure/infra:deploy dungeon-adventure-infra-sandbox
yarn nx run @dungeon-adventure/infra:deploy dungeon-adventure-infra-sandbox
npx nx run @dungeon-adventure/infra:deploy dungeon-adventure-infra-sandbox
bunx nx run @dungeon-adventure/infra:deploy dungeon-adventure-infra-sandbox
이 배포는 완료까지 약 2분 정도 소요됩니다.
배포 명령어
다음 명령어로 CDK 애플리케이션의 모든 스택을 배포할 수 있습니다:
pnpm nx run @dungeon-adventure/infra:deploy --all
yarn nx run @dungeon-adventure/infra:deploy --all
npx nx run @dungeon-adventure/infra:deploy --all
bunx nx run @dungeon-adventure/infra:deploy --all
인프라 프로덕션 환경을 별도 스택(infra-prod
등)으로 분리하는 경우 --all
플래그가 원치 않는 배포를 유발할 수 있으므로 권장하지 않습니다!
배포가 완료되면 다음과 유사한 출력을 확인할 수 있습니다(일부 값은 생략됨):
dungeon-adventure-infra-sandboxdungeon-adventure-infra-sandbox: deploying... [2/2]
✅ dungeon-adventure-infra-sandbox
✨ 배포 시간: 354초
Outputs:dungeon-adventure-infra-sandbox.ElectroDbTableTableNameXXX = dungeon-adventure-infra-sandbox-ElectroDbTableXXX-YYYdungeon-adventure-infra-sandbox.GameApiEndpointXXX = https://xxx.execute-api.region.amazonaws.com/prod/dungeon-adventure-infra-sandbox.GameUIDistributionDomainNameXXX = xxx.cloudfront.netdungeon-adventure-infra-sandbox.StoryApiStoryApiUrlXXX = https://xxx.lambda-url.ap-southeast-2.on.aws/dungeon-adventure-infra-sandbox.UserIdentityUserIdentityIdentityPoolIdXXX = region:xxxdungeon-adventure-infra-sandbox.UserIdentityUserIdentityUserPoolIdXXX = region_xxx
다음 방법으로 API를 테스트할 수 있습니다:
- FastApi 서버를 로컬에서 시작하고
curl
로 API 호출 - 배포된 API를 sigv4 활성화 curl로 직접 호출
Sigv4 활성화 curl
.bashrc
파일에 다음 스크립트를 추가하거나(추가 후source
실행) 명령어를 실행할 터미널에 직접 붙여넣으세요.~/.bashrc acurl () {REGION=$1SERVICE=$2shift; shift;curl --aws-sigv4 "aws:amz:$REGION:$SERVICE" --user "$(aws configure get aws_access_key_id):$(aws configure get aws_secret_access_key)" -H "X-Amz-Security-Token: $(aws configure get aws_session_token)" "$@"}sigv4 인증 curl 요청 예시:
API Gateway
Terminal window acurl ap-southeast-2 execute-api -X GET https://xxx스트리밍 Lambda function url
Terminal window acurl ap-southeast-2 lambda -N -X POST https://xxxPowerShell 프로필에 다음 함수를 추가하거나 현재 세션에 직접 붙여넣으세요.
Terminal window # PowerShell 프로필 또는 현재 세션function acurl {param([Parameter(Mandatory=$true)][string]$Region,[Parameter(Mandatory=$true)][string]$Service,[Parameter(ValueFromRemainingArguments=$true)][string[]]$CurlArgs)$AccessKey = aws configure get aws_access_key_id$SecretKey = aws configure get aws_secret_access_key$SessionToken = aws configure get aws_session_token& curl --aws-sigv4 "aws:amz:$Region`:$Service" --user "$AccessKey`:$SecretKey" -H "X-Amz-Security-Token: $SessionToken" @CurlArgs}sigv4 인증 curl 요청 예시:
API Gateway
Terminal window acurl ap-southeast-2 execute-api -X GET https://xxx스트리밍 Lambda function url
Terminal window acurl ap-southeast-2 lambda -N -X POST https://xxx
다음 명령어로 로컬 FastAPI 서버를 시작하세요:
pnpm nx run dungeon_adventure.story_api:serve
yarn nx run dungeon_adventure.story_api:serve
npx nx run dungeon_adventure.story_api:serve
bunx nx run dungeon_adventure.story_api:serve
서버가 실행되면 다음 명령어로 호출합니다:
curl -N -X POST http://127.0.0.1:8000/story/generate \ -d '{"genre":"superhero", "actions":[], "playerName":"UnnamedHero"}' \ -H "Content-Type: application/json"
acurl ap-southeast-2 lambda -N -X POST \ https://xxx.lambda-url.ap-southeast-2.on.aws/story/generate \ -d '{"genre":"superhero", "actions":[], "playerName":"UnnamedHero"}' \ -H "Content-Type: application/json"
명령어가 성공적으로 실행되면 다음과 유사한 스트리밍 응답을 확인할 수 있습니다:
UnnamedHero stood tall, his cape billowing in the wind....
축하합니다. FastAPI를 사용한 첫 번째 API를 성공적으로 구축하고 배포했습니다! 🎉🎉🎉