Merge pull request #2285 from Avs163/dev

New serverless pattern - s3-lambda-bedrock-js-sam

s3-lambda-bedrock-js-sam/.gitignore

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+.aws-sam
+samconfig.toml

s3-lambda-bedrock-js-sam/example-pattern.json

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+{
+    "title": "Amazon S3 to AWS Lambda to Amazon Bedrock using AWS SAM",
+    "description": "This pattern facilitates generating vector embeddings for text data uploaded to S3.",
+    "language": "Node.js",
+    "level": "200",
+    "framework": "SAM",
+    "introBox": {
+      "headline": "How it works",
+      "text": [
+        "When a new object is uploaded to an S3 bucket, S3 detects the putObject event and invokes a Lambda function asynchronously, passing details about the uploaded object. The Lambda function then retrieves the object's content and sends it to the Amazon Bedrock Titan Embedding service, which generates vector embeddings representing the content's meaning and context."
+      ]
+    },
+    "gitHub": {
+      "template": {
+        "repoURL": "https://github.com/aws-samples/serverless-patterns/tree/main/s3-lambda-bedrock-js-sam",
+        "templateURL": "serverless-patterns/s3-lambda-bedrock-js-sam",
+        "projectFolder": "s3-lambda-bedrock-js-sam",
+        "templateFile": "template.yaml"
+      }
+    },
+    "resources": {
+      "bullets": [
+        {
+          "text": "Amazon S3",
+          "link": "https://docs.aws.amazon.com/AmazonS3/latest/userguide/Welcome.html"
+        },
+        {
+          "text": "AWS Lambda",
+          "link": "https://docs.aws.amazon.com/lambda/latest/dg/welcome.html"
+        },
+        {
+            "text": "Amazon Bedrock",
+            "link": "https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-bedrock.html"
+          }
+      ]
+    },
+    "deploy": {
+      "text": [
+        "sam build",
+        "sam deploy --guided"
+      ]
+    },
+    "testing": {
+      "text": [
+        "See the GitHub repo for detailed testing instructions."
+      ]
+    },
+    "cleanup": {
+      "text": [
+        "sam delete"
+      ]
+    },
+    "authors": [
+      {
+        "name": "Achintya Veer Singh",
+        "image": "https://avatars.githubusercontent.com/u/55053737?v=4",
+        "bio": "Solutions Architect @ AWS",
+        "linkedin": "www.linkedin.com/in/achintya-veer-singh-493403193",
+        "twitter": "achintya_veer"
+      },
+      {
+        "name": "Rohit Raj",
+        "image": "https://avatars.githubusercontent.com/u/69171887?v=4",
+        "bio": "Solutions Architect @ AWS",
+        "linkedin": "https://www.linkedin.com/in/rohitraj-11",
+        "twitter": "RohitRaj_11"
+      }
+    ]
+  }

s3-lambda-bedrock-js-sam/s3-lambda-bedrock-js-sam.json

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+{
+    "title": "Amazon S3 to AWS Lambda to Amazon Bedrock using AWS SAM",
+    "description": "This pattern facilitates generating vector embeddings for text data uploaded to S3.",
+    "language": "Node.js",
+    "level": "200",
+    "framework": "SAM",
+    "introBox": {
+        "headline": "How it works",
+        "text": [
+            "When a new object is uploaded to an S3 bucket, S3 detects the putObject event and invokes a Lambda function asynchronously, passing details about the uploaded object. The Lambda function then retrieves the object's content and sends it to the Amazon Bedrock Titan Embedding service, which generates vector embeddings representing the content's meaning and context."
+        ]
+    },
+    "gitHub": {
+        "template": {
+            "repoURL": "https://github.com/aws-samples/serverless-patterns/tree/main/s3-lambda-bedrock-js-sam",
+            "templateURL": "serverless-patterns/s3-lambda-bedrock-js-sam",
+            "projectFolder": "s3-lambda-bedrock-js-sam",
+            "templateFile": "template.yaml"
+        }
+    },
+    "resources": {
+        "bullets": [
+            {
+                "text": "Amazon S3",
+                "link": "https://docs.aws.amazon.com/AmazonS3/latest/userguide/Welcome.html"
+            },
+            {
+                "text": "AWS Lambda",
+                "link": "https://docs.aws.amazon.com/lambda/latest/dg/welcome.html"
+            },
+            {
+                "text": "Amazon Bedrock",
+                "link": "https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-bedrock.html"
+            }
+        ]
+    },
+    "deploy": {
+        "text": [
+            "sam build",
+            "sam deploy --guided"
+        ]
+    },
+    "testing": {
+        "text": [
+            "See the GitHub repo for detailed testing instructions."
+        ]
+    },
+    "cleanup": {
+        "text": [
+            "sam delete"
+        ]
+    },
+    "authors": [
+        {
+            "name": "Achintya Veer Singh",
+            "image": "https://avatars.githubusercontent.com/u/55053737?v=4",
+            "bio": "Solutions Architect @ AWS",
+            "linkedin": "achintya-veer-singh-493403193",
+            "twitter": "achintya_veer"
+        },
+        {
+            "name": "Rohit Raj",
+            "image": "https://avatars.githubusercontent.com/u/69171887?v=4",
+            "bio": "Solutions Architect @ AWS",
+            "linkedin": "rohitraj-11",
+            "twitter": "RohitRaj_11"
+        }
+    ],
+    "patternArch": {
+        "icon1": {
+            "x": 20,
+            "y": 50,
+            "service": "s3",
+            "label": "Amazon S3"
+        },
+        "icon2": {
+            "x": 50,
+            "y": 50,
+            "service": "lambda",
+            "label": "AWS Lambda"
+        },
+        "icon3": {
+            "x": 80,
+            "y": 50,
+            "service": "bedrock",
+            "label": "Amazon Bedrock"
+        },
+        "line1": {
+            "from": "icon1",
+            "to": "icon2"
+        },
+        "line2": {
+            "from": "icon2",
+            "to": "icon3"
+        }
+    }
+}

s3-lambda-bedrock-js-sam/sample.txt

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+Peace is a state of tranquility, calm, and harmony, free from violence, conflict, or hostility. 
+It is a fundamental human aspiration, as it allows for the flourishing of individuals, communities, and nations. 
+Achieving lasting peace requires a concerted effort to address the root causes of violence, foster understanding and respect among diverse groups, and promote justice, equality, and sustainable development.

s3-lambda-bedrock-js-sam/src/index.mjs

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+import { S3Client, GetObjectCommand } from "@aws-sdk/client-s3";
+import {
+      BedrockRuntimeClient,
+      InvokeModelCommand,
+} from "@aws-sdk/client-bedrock-runtime";
+
+const awsS3Client = new S3Client();
+const awsBedrockClient = new BedrockRuntimeClient();
+
+const fetchFileFromS3 = async (bucketName, fileKey) => {
+      const command = new GetObjectCommand({
+            Bucket: bucketName,
+            Key: fileKey,
+      });
+      const response = await awsS3Client.send(command);
+      const fileContent = response.Body
+            ? await response.Body.transformToString()
+            : "";
+      return fileContent;
+};
+
+export const handler = async (event) => {
+      if (!event || !event.Records) {
+            return {
+                  statusCode: 200,
+                  body: JSON.stringify({ message: "No S3 event detected" }),
+            };
+      }
+
+      const eventRecord = event.Records[0];
+      const bucketName = eventRecord.s3.bucket.name;
+      const fileName = decodeURIComponent(eventRecord.s3.object.key);
+      const fileContent = await fetchFileFromS3(bucketName, fileName);
+
+      const bedrockModelInput = {
+            modelId: "amazon.titan-embed-text-v1",
+            contentType: "application/json",
+            accept: "*/*",
+            body: JSON.stringify({ inputText: JSON.stringify(fileContent) }),
+      };
+      console.log("Input provided to Bedrock", bedrockModelInput);
+
+      const bedrockCommand = new InvokeModelCommand(bedrockModelInput);
+      const bedrockResponse = await awsBedrockClient.send(bedrockCommand);
+
+      const responseData = Buffer.from(bedrockResponse.body).toString();
+      console.log("Response data: ", responseData);
+
+      return {
+            statusCode: 200,
+            body: JSON.stringify(responseData),
+      };
+};

s3-lambda-bedrock-js-sam/template.yaml

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+AWSTemplateFormatVersion: "2010-09-09"
+Transform: AWS::Serverless-2016-10-31
+
+Description: This pattern facilitates intelligent document processing by generating vector embeddings for text data uploaded to S3.
+
+Parameters:
+  DocumentBucketName:
+    Type: String
+
+Resources:
+  DocumentBucket:
+    Type: AWS::S3::Bucket
+    Properties:
+      BucketName: !Ref DocumentBucketName
+
+  DocumentEmbeddingFunction:
+    Type: AWS::Serverless::Function
+    Properties:
+      CodeUri: src/
+      Handler: index.handler
+      FunctionName: DocumentEmbedding
+      Description: Lambda function to generate embeddings for uploaded documents
+      Runtime: nodejs18.x
+      Timeout: 10
+      MemorySize: 128
+      Role: !GetAtt DocumentEmbeddingFunctionExecutionRole.Arn
+      Events:
+        FileUpload:
+          Type: S3
+          Properties:
+            Bucket: !Ref DocumentBucket
+            Events: s3:ObjectCreated:*
+            Filter:
+              S3Key:
+                Rules:
+                  - Name: prefix
+                    Value: "content/"
+
+  DocumentEmbeddingFunctionExecutionRole:
+    Type: AWS::IAM::Role
+    Properties:
+      AssumeRolePolicyDocument:
+        Version: "2012-10-17"
+        Statement:
+          - Effect: Allow
+            Principal:
+              Service:
+                - lambda.amazonaws.com
+            Action:
+              - "sts:AssumeRole"
+      ManagedPolicyArns:
+        - arn:aws:iam::aws:policy/service-role/AWSLambdaBasicExecutionRole
+      Policies:
+        - PolicyName: CustomPolicy
+          PolicyDocument:
+            Version: "2012-10-17"
+            Statement:
+              - Effect: Allow
+                Action:
+                  - s3:GetObject
+                  - s3:ListBucket
+                Resource:
+                  - !Sub "arn:aws:s3:::${DocumentBucketName}/*"
+                  - !Sub "arn:aws:s3:::${DocumentBucketName}"
+              - Effect: Allow
+                Action:
+                  - bedrock:InvokeModel
+                Resource: "*"
+
+Outputs:
+  DocumentBucket:
+    Description: S3 bucket for storing documents
+    Value: !Ref DocumentBucket
+  DocumentEmbeddingFunction:
+    Value: !Ref DocumentEmbeddingFunction
+    Description: Lambda Function name for generating document embeddings
+  DocumentEmbeddingFunctionARN:
+    Value: !GetAtt DocumentEmbeddingFunction.Arn
+    Description: ARN of Lambda Function for generating document embeddings