Jogo de Dungeons com IA

Módulo 3: Implementação da API de Story

Cuidado

Certifique-se de ter concedido acesso ao modelo Anthropic Claude 3.5 Sonnet v2 seguindo as etapas descritas neste guia.

A StoryApi consiste em uma única API generate_story que, dado um Game e uma lista de Actions como contexto, irá progredir uma história. Esta API será implementada como uma API de streaming em Python/FastAPI e também demonstrará como alterações podem ser feitas no código gerado para atender ao propósito.

Implementação da API

Para criar nossa API, primeiro precisamos instalar algumas dependências adicionais:

• boto3 será usado para chamar o Amazon Bedrock;
• uvicorn será usado para iniciar nossa API em conjunto com o Lambda Web Adapter (LWA);
• copyfiles é uma dependência npm que precisaremos para suportar a cópia de arquivos multiplataforma ao atualizar nossa tarefa bundle.

Para instalar estas dependências, execute os seguintes comandos:

pnpm

pnpm nx run dungeon_adventure.story_api:add --args boto3 uvicorn

yarn

yarn nx run dungeon_adventure.story_api:add --args boto3 uvicorn

npm

npx nx run dungeon_adventure.story_api:add --args boto3 uvicorn

bun

bunx nx run dungeon_adventure.story_api:add --args boto3 uvicorn

pnpm

pnpm add -Dw copyfiles

yarn

yarn add -D copyfiles

npm

npm install --legacy-peer-deps -D copyfiles

bun

bun install -D copyfiles

Agora vamos substituir o conteúdo dos seguintes arquivos em packages/story_api/story_api:

main.py

import json

from boto3 import client
from fastapi.responses import PlainTextResponse, StreamingResponse
from 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")

init.py

import os
import uuid
from collections.abc import Callable

from aws_lambda_powertools import Logger, Metrics, Tracer
from aws_lambda_powertools.metrics import MetricUnit
from fastapi import FastAPI, Request, Response
from fastapi.openapi.utils import get_openapi
from fastapi.responses import JSONResponse
from fastapi.routing import APIRoute
from mangum import Mangum
from pydantic import BaseModel
from 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 tracing
lambda_handler.__name__ = "handler"  # tracer requires __name__ to be set
lambda_handler = tracer.capture_lambda_handler(lambda_handler)
# Add logging
lambda_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

Nota

A alteração acima no init.py simplesmente remove o middleware CORS para evitar conflitos com o tratamento próprio de cabeçalhos CORS do Lambda Function URL.

Analisando o código acima:

• Usamos a configuração x-streaming para indicar que esta é uma API de streaming quando gerarmos nosso client SDK. Isso permitirá consumir esta API de forma streaming mantendo a segurança de tipos!
• Nossa API simplesmente retorna um fluxo de texto conforme definido por media_type="text/plain" e response_class=PlainTextResponse

Nota

Sempre que fizer alterações em seu FastAPI, você precisará reconstruir seu projeto para ver essas alterações refletidas no client gerado em seu website.

Faremos mais algumas alterações abaixo antes de reconstruir.

Infraestrutura

A infraestrutura que configuramos anteriormente assume que todas as APIs têm um API Gateway integrado com funções Lambda. Para nossa story_api, não queremos usar API Gateway pois ele não suporta respostas streaming. Em vez disso, usaremos um Lambda Function URL configurado com response streaming.

Para suportar isso, primeiro atualizaremos nossos constructs CDK da seguinte forma:

story-api.ts

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';
import { suppressRules } from '../../core/checkov.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',
        ],
      },
    });
    suppressRules(
      this.handler,
      ['CKV2_AWS_75'],
      'Allowing all origins for this use case',
      () => true,
    );

    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',
        },
      },
    });
  }
}

application-stack.ts

stacks/application-stack.ts

import {
  GameApi,
  GameUI,
  StoryApi,
  UserIdentity,
} from ':dungeon-adventure/common-constructs';
import * as cdk from 'aws-cdk-lib';
import { Stack, StackProps } 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) {
export class ApplicationStack extends Stack {
  constructor(scope: Construct, id: string, props?: 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');
  }
}

Agora atualizaremos a story_api para suportar a implantação do Lambda Web Adapter.

run.sh

#!/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

project.json

packages/story_api/project.json

{
  "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 packages/story_api --package dungeon_adventure.story_api -o dist/packages/story_api/bundle/requirements.txt",
          "uv pip install -n --no-deps --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"]
    },
    ...
  }
}

Implantação e testes

Primeiro, vamos construir a base de código:

pnpm

pnpm nx run-many --target build --all

yarn

yarn nx run-many --target build --all

npm

npx nx run-many --target build --all

bun

bunx nx run-many --target build --all

Dica

Se encontrar erros de lint, você pode executar o seguinte comando para corrigi-los automaticamente.

pnpm

pnpm nx run-many --target lint --configuration=fix --all

yarn

yarn nx run-many --target lint --configuration=fix --all

npm

npx nx run-many --target lint --configuration=fix --all

bun

bunx nx run-many --target lint --configuration=fix --all

Sua aplicação agora pode ser implantada executando o seguinte comando:

pnpm

pnpm nx run @dungeon-adventure/infra:deploy dungeon-adventure-infra-sandbox/*

yarn

yarn nx run @dungeon-adventure/infra:deploy dungeon-adventure-infra-sandbox/*

npm

npx nx run @dungeon-adventure/infra:deploy dungeon-adventure-infra-sandbox/*

bun

bunx nx run @dungeon-adventure/infra:deploy dungeon-adventure-infra-sandbox/*

Esta implantação levará aproximadamente 2 minutos para ser concluída.

Após a conclusão da implantação, você verá algumas saídas similares às seguintes (alguns valores foram omitidos):

dungeon-adventure-infra-sandbox-Application
dungeon-adventure-infra-sandbox-Application: deploying... [2/2]

 ✅  dungeon-adventure-infra-sandbox-Application

✨  Tempo de implantação: 354s

Outputs:
dungeon-adventure-infra-sandbox-Application.ElectroDbTableTableNameXXX = dungeon-adventure-infra-sandbox-Application-ElectroDbTableXXX-YYY
dungeon-adventure-infra-sandbox-Application.GameApiEndpointXXX = https://xxx.execute-api.region.amazonaws.com/prod/
dungeon-adventure-infra-sandbox-Application.GameUIDistributionDomainNameXXX = xxx.cloudfront.net
dungeon-adventure-infra-sandbox-Application.StoryApiStoryApiUrlXXX = https://xxx.lambda-url.ap-southeast-2.on.aws/
dungeon-adventure-infra-sandbox-Application.UserIdentityUserIdentityIdentityPoolIdXXX = region:xxx
dungeon-adventure-infra-sandbox-Application.UserIdentityUserIdentityUserPoolIdXXX = region_xxx

Podemos testar nossa API de duas formas:

• Iniciando uma instância local do servidor FastAPI e invocando as APIs usando curl
• Chamando a API implantada diretamente usando curl com Sigv4

Local

Inicie seu servidor FastAPI local executando:

pnpm

pnpm nx run dungeon_adventure.story_api:serve

yarn

yarn nx run dungeon_adventure.story_api:serve

npm

npx nx run dungeon_adventure.story_api:serve

bun

bunx nx run dungeon_adventure.story_api:serve

Com o servidor FastAPI em execução, chame a API com:

curl -N -X POST http://127.0.0.1:8000/story/generate \
  -d '{"genre":"superhero", "actions":[], "playerName":"UnnamedHero"}' \
  -H "Content-Type: application/json"

Implantado

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"

Cuidado

Use o valor de saída dungeon-adventure-infra-sandbox-Application.StoryApiStoryApiUrlXXX do deploy CDK para substituir o placeholder de URL destacado e defina a região adequadamente.

Se o comando for executado com sucesso, você verá uma resposta sendo transmitida similar a:

UnnamedHero permaneceu imponente, sua capa ondulando ao vento....

Parabéns. Você construiu e implantou sua primeira API usando FastAPI! 🎉🎉🎉