Amazon Bedrock Data Source syncing error

Hi,

Are you documents among the supported types listed here: https://docs.aws.amazon.com/bedrock/latest/userguide/knowledge-base-ds.html#kb-ds-supported-doc-formats-limits ?

Best,

Didier

To troubleshoot the "The server encountered an internal error while processing the request" error when ingesting a data source into an Amazon Bedrock knowledge base, you should check several aspects of your configuration and the setup process. Here are some steps and checks you can perform to identify and resolve the issue:

1. Validate S3 Data Source Ensure that the S3 bucket and the files you are trying to ingest are accessible and correctly configured.

Bucket Permissions: Check the IAM permissions to ensure that the Bedrock service has access to the S3 bucket and objects. The necessary permissions might include s3:GetObject, s3:ListBucket, etc. Bucket Policy Example Json:

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Effect": "Allow",
            "Principal": {
                "Service": "bedrock.amazonaws.com"
            },
            "Action": [
                "s3:GetObject",
                "s3:ListBucket"
            ],
            "Resource": [
                "arn:aws:s3:::your-bucket-name",
                "arn:aws:s3:::your-bucket-name/*"
            ]
        }
    ]
}

Validate Bedrock and OpenSearch Serverless Setup Ensure that Bedrock and OpenSearch Serverless are correctly set up and configured.

OpenSearch Index: Ensure the OpenSearch index exists and is configured correctly for Bedrock to write data to it. OpenSearch Permissions: Check that Bedrock has permissions to write to OpenSearch. 5. Review Logs and Metrics Check the logs and metrics for more detailed error information.

CloudWatch Logs: Check the CloudWatch logs for detailed error messages related to Bedrock and OpenSearch Serverless. OpenSearch Logs: If available, check the OpenSearch logs for any issues or errors related to data ingestion. 6. Error Handling Handle and log errors gracefully in your code to capture detailed error messages.

Sample Code with Proper Error Handling Here’s a basic example of how you might set up your Bedrock configuration with proper error handling and validation: python:

import boto3
from botocore.exceptions import ClientError

# Initialize the Bedrock client
bedrock_client = boto3.client('bedrock')

# Define configurations
knowledge_base_configuration = {
    "type": "VECTOR",
    "vectorKnowledgeBaseConfiguration": {
        "embeddingModelArn": "arn:aws:bedrock:region:account-id:model/model-name"
    }
}

storage_configuration = {
    "type": "OPENSEARCH_SERVERLESS",
    "opensearchServerlessConfiguration": {
        "domainName": "your-domain-name",
        "indexName": "your-index-name"
    }
}

chunking_strategy_configuration = {
    "chunkingStrategy": "FIXED_SIZE",
    "fixedSizeChunkingConfiguration": {
        "maxTokens": 500,
        "overlapPercentage": 10
    }
}

# Attempt to ingest data source
try:
    response = bedrock_client.ingest_data_source(
        DataSourceType='s3',
        KnowledgeBaseConfiguration=knowledge_base_configuration,
        StorageConfiguration=storage_configuration,
        ChunkingStrategyConfiguration=chunking_strategy_configuration
    )
    print("Data source ingestion initiated successfully:", response)
except ClientError as e:
    print("An error occurred during data source ingestion:", e.response['Error']['Message'])
    # Additional logging or error handling can be added here

Final Steps Re-run the Ingestion Process: After validating and correcting the configurations, try re-running the ingestion process. Contact AWS Support: If the issue persists, contact AWS Support for more detailed assistance. Provide them with the error logs and the configuration details you used. By following these steps and checking the configurations, you should be able to identify and resolve the issue with the Bedrock data source ingestion process.

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