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@@ -246,14 +246,31 @@ The `s3_location` configuration block supports the following arguments:
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The `storage_configuration` configuration block supports the following arguments:
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*`type` - (Required) Vector store service in which the knowledge base is stored. Valid Values: `OPENSEARCH_SERVERLESS`, `OPENSEARCH_MANAGED_CLUSTER`, `PINECONE`, `REDIS_ENTERPRISE_CLOUD`, `RDS`, `S3_VECTORS`.
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*`type` - (Required) Vector store service in which the knowledge base is stored. Valid Values: `MONGO_DB_ATLAS`, `OPENSEARCH_SERVERLESS`, `OPENSEARCH_MANAGED_CLUSTER`, `PINECONE`, `REDIS_ENTERPRISE_CLOUD`, `RDS`, `S3_VECTORS`.
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*`mongo_db_atlas_configuration` – (Optional) The storage configuration of the knowledge base in MongoDB Atlas. See [`opensearch_managed_cluster_comongo_db_atlas_configurationnfiguration` block](#mongo_db_atlas_configuration-block) for details.
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*`opensearch_managed_cluster_configuration` - (Optional) The storage configuration of the knowledge base in Amazon OpenSearch Service Managed Cluster. See [`opensearch_managed_cluster_configuration` block](#opensearch_managed_cluster_configuration-block) for details.
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*`opensearch_serverless_configuration` - (Optional) The storage configuration of the knowledge base in Amazon OpenSearch Service Serverless. See [`opensearch_serverless_configuration` block](#opensearch_serverless_configuration-block) for details.
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*`pinecone_configuration` - (Optional) The storage configuration of the knowledge base in Pinecone. See [`pinecone_configuration` block](#pinecone_configuration-block) for details.
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*`rds_configuration` - (Optional) Details about the storage configuration of the knowledge base in Amazon RDS. For more information, see [Create a vector index in Amazon RDS](https://docs.aws.amazon.com/bedrock/latest/userguide/knowledge-base-setup.html). See [`rds_configuration` block](#rds_configuration-block) for details.
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*`redis_enterprise_cloud_configuration` - (Optional) The storage configuration of the knowledge base in Redis Enterprise Cloud. See [`redis_enterprise_cloud_configuration` block](#redis_enterprise_cloud_configuration-block) for details.
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*`s3_vectors_configuration` - (Optional) The storage configuration of the knowledge base in Amazon S3 Vectors. See [`s3_vectors_configuration` block](#s3_vectors_configuration-block) for details.
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### `mongo_db_atlas_configuration` block
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The `mongo_db_atlas_configuration` configuration block supports the following arguments:
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*`collection_name` – (Required) The name of the collection in the MongoDB Atlas database.
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*`credentials_secret_arn` – (Required) The ARN of the secret that you created in AWS Secrets Manager that is linked to your MongoDB Atlas database.
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*`database_name` – (Required) The name of the database in the MongoDB Atlas database.
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*`endpoint` – (Required) The endpoint URL of the MongoDB Atlas database.
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*`field_mapping` – (Required) Contains the names of the fields to which to map information about the vector store.
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*`metadata_field` – (Required) The name of the field in which Amazon Bedrock stores metadata about the vector store.
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*`text_field` – (Required) The name of the field in which Amazon Bedrock stores the raw text from your data. The text is split according to the chunking strategy you choose.
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*`vector_field` – (Required) The name of the field in which Amazon Bedrock stores the vector embeddings for your data sources.
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*`vector_index_name` – (Required) The name of the vector index.
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*`endpoint_service_name` – (Optional) The name of the service that hosts the MongoDB Atlas database.
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*`text_index_name` – (Optional) The name of the vector index.
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