Develop Reference

Amazon Lex V2 Lambda python code to get intent name or any response back from lambda is not working

'''
Trying to get response back as name of the intent from lambda for Amazon Lex v2. It can be string or any response back in simple program.
I have referred the V2 Lex documentation but I can come-up with below code which shows error after several attempts. https://docs.aws.amazon.com/lexv2/latest/dg/lambda.html
error : "Invalid Lambda Response: Received error response from Lambda: Unhandled"
'''
def lambda_handler(event, context):
entity = event["currentIntent"]["slots"]["Nm"].title()
intent = event["currentIntent"]["name"]
response = {
'sessionState': {
'dialogAction': {
'type': 'Close'
},
'state': 'Fulfilled'
},
'messages': [
'contentType': 'PlainText',
'content': "The intent you are in now is "+intent+"!"
],
}
return response

The 'messages' field is an array of objects, not an array of strings. It should be declared as follows:
'messages': [
{
'contentType': 'PlainText',
'content': "The intent you are in now is "+intent+"!"
}
]
Reference:
Amazon Lex - Lambda Response format

I faced the same issue. The solution that worked for me is like below
var response = {};
response.messages = [
message
];
response.sessionState = {
sessionAttributes:sessionAttributes,
intent : {
name : intentRequest.interpretations[0].intent.name,
state : 'Fulfilled'
},
dialogAction: {
type: "Close",
fulfillmentState: "Fulfilled"
}
};
Refer to lex v2 developer guide page 69 Response format
https://docs.aws.amazon.com/lexv2/latest/dg/lex2.0.pdf

CDK WAF Python Multiple Statement velues error

I have AWS WAF CDK that is working with rules, and now I'm trying to add a rule in WAF with multiple statements, but I'm getting this error:
Resource handler returned message: "Error reason: You have used none or multiple values for a field that requires exactly one value., field: STATEMENT, parameter: Statement (Service: Wafv2, Status Code: 400, Request ID: 6a36bfe2-543c-458a-9571-e929142f5df1, Extended Request ID: null)" (RequestToken: b751ae12-bb60-bb75-86c0-346926687ea4, HandlerErrorCode: InvalidRequest)
My Code:
{
'name': 'ruleName',
'priority': 3,
'statement': {
'orStatement': {
'statements': [
{
'iPSetReferenceStatement': {
'arn': 'arn:myARN'
}
},
{
'iPSetReferenceStatement': {
'arn': 'arn:myARN'
}
}
]
}
},
'action': {
'allow': {}
},
'visibilityConfig': {
'sampledRequestsEnabled': True,
'cloudWatchMetricsEnabled': True,
'metricName': 'ruleName'
}
},

There are two things going on there:
Firstly, your capitalization is off. iPSetReferenceStatement cannot be parsed and creates an empty statement reference. The correct key is ipSetReferenceStatement.
However, as mentioned here, there is a jsii implementation bug causing some issues with the IPSetReferenceStatementProperty. This causes it not to be parsed properly resulting in a jsii error when synthesizing.
You can fix it by using the workaround mentioned in the post.
Add to your file containing the construct:
import jsii
from aws_cdk import aws_wafv2 as wafv2 # just for clarity, you might already have this imported
#jsii.implements(wafv2.CfnRuleGroup.IPSetReferenceStatementProperty)
class IPSetReferenceStatement:
#property
def arn(self):
return self._arn
#arn.setter
def arn(self, value):
self._arn = value
Then define your ip reference statement as follows:
ip_set_ref_stmnt = IPSetReferenceStatement()
ip_set_ref_stmnt.arn = "arn:aws:..."
ip_set_ref_stmnt_2 = IPSetReferenceStatement()
ip_set_ref_stmnt_2.arn = "arn:aws:..."
Then in the rules section of the webacl, you can use it as follows:
...
rules=[
{
'name': 'ruleName',
'priority': 3,
'statement': {
'orStatement': {
'statements': [
wafv2.CfnWebACL.StatementProperty(
ip_set_reference_statement=ip_set_ref_stmnt
),
wafv2.CfnWebACL.StatementProperty(
ip_set_reference_statement=ip_set_ref_stmnt_2
),
]
}
},
'action': {
'allow': {}
},
'visibilityConfig': {
'sampledRequestsEnabled': True,
'cloudWatchMetricsEnabled': True,
'metricName': 'ruleName'
}
}
]
...
This should synthesize your stack as expected.

Why we have to specify the attribute type when use boto3 client and not in resource?

#app.route("/companies/<string:companyId>/<string:name>/")
def get_search(companyId,name):
resp = client.get_item(
TableName=COMPANIES_TABLE,
Key={
'companyId': { 'S': companyId },
'name': { 'S': name }
}
)
item = resp.get('Item')
if not item:
return jsonify({'error': 'Company does not exist'}), 404
return jsonify({
'companyId': item.get('companyId').get('S'),
'name': item.get('name').get('S'),
'region': item.get('region').get('S')
})
The response from a DynamoDB resource object looks doesn't require me to parse the low level data structure from DynamoDB, but when I use the boto3 client I have to do that, why is that?
response = table.scan(
FilterExpression=Attr('name').eq(name)
)
item = response['Items']
import pdb;pdb.set_trace()
if not item:
return jsonify({'error': 'Company does not exist'}), 404
return jsonify({
'companyId': item.get('companyId'),
'name': item.get('name'),
'region': item.get('region')
})

In general the resource API in boto3 is a higher level abstraction from the underlying client API. It tries to hide some of the implementation details of the underlying client calls, but comes at a performance cost.
You can also use the deserializer that comes with boto3 to turn the values from client.get_item() into a Python object.
from boto3.dynamodb.types import TypeDeserializer
def main():
dynamodb_item = {
"PK": {
"S": "key"
},
"SK": {
"S": "value"
}
}
deserializer = TypeDeserializer()
deserialized = {
key: deserializer.deserialize(dynamodb_item[key])
for key in dynamodb_item.keys()
}
print(deserialized) # {'PK': 'key', 'SK': 'value'}
if __name__ == "__main__":
main()

Python AWS Lambda Event JSON

I am trying to parse event data of AWS Lambda, I have connected it to SQS and I am sending the JSON format using SQS.
This is my AWS Lambda Function
import json
def lambda_handler(event, context):
# print(event)
# print(event['Records'][0])
x = event['Records'][0]['body']
print(x)
print(type(x))
Following is the event data
{
"Records":[
{
"messageId":"916f5e95-b2f6-4148-9c62-2ac8e764f06c",
"receiptHandle":"AQEBmLuoGWtLtFFgvyCFdSPMJh2HKgHOIPWNUq22EOwCzGT8iILZm97CE6j4J6oR71ZpDr3sgxQcJyVZ+dmmvGl+fFftT9GCJqZYrjMGsR2Q6WsMd8ciI8bTtDXyvsk8ektd7UGfh4gxIZoFp7WUKVRcMEeBkubKd8T4/Io81D0l/AK7MxcEfCj40vWEsex1kkGmMRlBtdSeGyy7fJgUq5CFAYWciiWtbSit8S0Y38xZPmsIFhoxP0egQRoJcW4aUgMi469Gj5+khizetybtgC8vux5NCg/IejxcCueXkQ7LKVF8kfRdqRSUYB6DsOrGgfmZpK4wpXIarByNz0R2p7J88meYpj2IVULv/emXsSYaKG4rXnpbH4J9ijbLWckYLAd7wPDzCYri1ZSTgAz0kchsEw==",
"body":"{\n\"name\": \"aniket\",\n\"tag\": \"hello\"\n}",
"attributes":{
"ApproximateReceiveCount":"1",
"SentTimestamp":"1602046897707",
"SenderId":"AIDAR3BXDV4FCWXL56NUU",
"ApproximateFirstReceiveTimestamp":"1602046897712"
},
"messageAttributes":{
},
"md5OfBody":"98da683a47692b39c1d43bd4fa21ed89",
"eventSource":"aws:sqs",
"eventSourceARN":"arn:aws:sqs:ap-south-1:126817120010:documentation",
"awsRegion":"ap-south-1"
}
]
}
I am trying to access the body of the data.
this is what I am getting
"{\n\"name\": \"aniket\",\n\"tag\": \"hello\"\n}"
And it's type is string.
What do I need to do convert it into a proper JSON format?
I also tried the following:
import json
def lambda_handler(event, context):
data = json.dumps(event['Records'][0]['body'])
print(data)
This is the output
"{\n\"name\": \"aniket\",\n\"tag\": \"hello\"\n}"
But this time the type is JSON.
The expected format is
{
"name": "aniket",
"tag": "hello"
}

You have to use json.loads not json.dumps.
Try this:
import json
event = {
"Records":[
{
"messageId":"916f5e95-b2f6-4148-9c62-2ac8e764f06c",
"receiptHandle":"AQEBmLuoGWtLtFFgvyCFdSPMJh2HKgHOIPWNUq22EOwCzGT8iILZm97CE6j4J6oR71ZpDr3sgxQcJyVZ+dmmvGl+fFftT9GCJqZYrjMGsR2Q6WsMd8ciI8bTtDXyvsk8ektd7UGfh4gxIZoFp7WUKVRcMEeBkubKd8T4/Io81D0l/AK7MxcEfCj40vWEsex1kkGmMRlBtdSeGyy7fJgUq5CFAYWciiWtbSit8S0Y38xZPmsIFhoxP0egQRoJcW4aUgMi469Gj5+khizetybtgC8vux5NCg/IejxcCueXkQ7LKVF8kfRdqRSUYB6DsOrGgfmZpK4wpXIarByNz0R2p7J88meYpj2IVULv/emXsSYaKG4rXnpbH4J9ijbLWckYLAd7wPDzCYri1ZSTgAz0kchsEw==",
"body":"{\n\"name\": \"aniket\",\n\"tag\": \"hello\"\n}",
"attributes":{
"ApproximateReceiveCount":"1",
"SentTimestamp":"1602046897707",
"SenderId":"AIDAR3BXDV4FCWXL56NUU",
"ApproximateFirstReceiveTimestamp":"1602046897712"
},
"messageAttributes":{
},
"md5OfBody":"98da683a47692b39c1d43bd4fa21ed89",
"eventSource":"aws:sqs",
"eventSourceARN":"arn:aws:sqs:ap-south-1:126817120010:documentation",
"awsRegion":"ap-south-1"
}
]
}
parsed = json.loads(event['Records'][0]['body'])
print(json.dumps(parsed, indent=4, sort_keys=True))
Output:
{
"name": "aniket",
"tag": "hello"
}

Try using json.loads(string) to deserialize the json.
Also, I don't believe you need to specify the index [0] since 'body' is an object and not an array.

Empty dictionary on AnnotationConsolidation lambda event for aws Sagemaker

I am starting to use aws sagemaker on the development of my machine learning model and I'm trying to build a lambda function to process the responses of a sagemaker labeling job. I already created my own lambda function but when I try to read the event contents I can see that the event dict is completely empty, so I'm not getting any data to read.
I have already given enough permissions to the role of the lambda function. Including:
- AmazonS3FullAccess.
- AmazonSagemakerFullAccess.
- AWSLambdaBasicExecutionRole
I've tried using this code for the Post-annotation Lambda (adapted for python 3.6):
https://docs.aws.amazon.com/sagemaker/latest/dg/sms-custom-templates-step2-demo1.html#sms-custom-templates-step2-demo1-post-annotation
As well as this one in this git repository:
https://github.com/aws-samples/aws-sagemaker-ground-truth-recipe/blob/master/aws_sagemaker_ground_truth_sample_lambda/annotation_consolidation_lambda.py
But none of them seemed to work.
For creating the labeling job I'm using boto3's functions for sagemaker:
https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/sagemaker.html#SageMaker.Client.create_labeling_job
This is the code i have for creating the labeling job:
def create_labeling_job(client,bucket_name ,labeling_job_name, manifest_uri, output_path):
print("Creating labeling job with name: %s"%(labeling_job_name))
response = client.create_labeling_job(
LabelingJobName=labeling_job_name,
LabelAttributeName='annotations',
InputConfig={
'DataSource': {
'S3DataSource': {
'ManifestS3Uri': manifest_uri
}
},
'DataAttributes': {
'ContentClassifiers': [
'FreeOfAdultContent',
]
}
},
OutputConfig={
'S3OutputPath': output_path
},
RoleArn='arn:aws:myrolearn',
LabelCategoryConfigS3Uri='s3://'+bucket_name+'/config.json',
StoppingConditions={
'MaxPercentageOfInputDatasetLabeled': 100,
},
LabelingJobAlgorithmsConfig={
'LabelingJobAlgorithmSpecificationArn': 'arn:image-classification'
},
HumanTaskConfig={
'WorkteamArn': 'arn:my-private-workforce-arn',
'UiConfig': {
'UiTemplateS3Uri':'s3://'+bucket_name+'/templatefile'
},
'PreHumanTaskLambdaArn': 'arn:aws:lambda:us-east-1:432418664414:function:PRE-BoundingBox',
'TaskTitle': 'Title',
'TaskDescription': 'Description',
'NumberOfHumanWorkersPerDataObject': 1,
'TaskTimeLimitInSeconds': 600,
'AnnotationConsolidationConfig': {
'AnnotationConsolidationLambdaArn': 'arn:aws:my-custom-post-annotation-lambda'
}
}
)
return response
And this is the one i have for the lambda function:
print("Received event: " + json.dumps(event, indent=2))
print("event: %s"%(event))
print("context: %s"%(context))
print("event headers: %s"%(event["headers"]))
parsed_url = urlparse(event['payload']['s3Uri']);
print("parsed_url: ",parsed_url)
labeling_job_arn = event["labelingJobArn"]
label_attribute_name = event["labelAttributeName"]
label_categories = None
if "label_categories" in event:
label_categories = event["labelCategories"]
print(" Label Categories are : " + label_categories)
payload = event["payload"]
role_arn = event["roleArn"]
output_config = None # Output s3 location. You can choose to write your annotation to this location
if "outputConfig" in event:
output_config = event["outputConfig"]
# If you specified a KMS key in your labeling job, you can use the key to write
# consolidated_output to s3 location specified in outputConfig.
kms_key_id = None
if "kmsKeyId" in event:
kms_key_id = event["kmsKeyId"]
# Create s3 client object
s3_client = S3Client(role_arn, kms_key_id)
# Perform consolidation
return do_consolidation(labeling_job_arn, payload, label_attribute_name, s3_client)
I've tried debugging the event object with:
print("Received event: " + json.dumps(event, indent=2))
But it just prints an empty dictionary: Received event: {}
I expect the output to be something like:
#Content of an example event:
{
"version": "2018-10-16",
"labelingJobArn": <labelingJobArn>,
"labelCategories": [<string>], # If you created labeling job using aws console, labelCategories will be null
"labelAttributeName": <string>,
"roleArn" : "string",
"payload": {
"s3Uri": <string>
}
"outputConfig":"s3://<consolidated_output configured for labeling job>"
}
Lastly, when I try yo get the labeling job ARN with:
labeling_job_arn = event["labelingJobArn"]
I just get a KeyError (which makes sense because the dictionary is empty).

I am doing the same but in Labeled object section I am getting failed result and inside my output objects I am getting following error from Post Lambda function:
"annotation-case0-test3-metadata": {
"retry-count": 1,
"failure-reason": "ClientError: The JSON output from the AnnotationConsolidationLambda function could not be read. Check the output of the Lambda function and try your request again.",
"human-annotated": "true"
}
}

I found the problem, I needed to add the ARN of the role used by my Lamda function as a Trusted Entity on the Role used for the Sagemaker Labeling Job.
I just went to Roles > MySagemakerExecutionRole > Trust Relationships and added:
{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Principal": {
"AWS": [
"arn:aws:iam::xxxxxxxxx:role/My-Lambda-Role",
...
],
"Service": [
"lambda.amazonaws.com",
"sagemaker.amazonaws.com",
...
]
},
"Action": "sts:AssumeRole"
}
]
}
This made it work for me.