diff --git a/docs/docs/integrations/providers/aws.mdx b/docs/docs/integrations/providers/aws.mdx index 97bc1031fec..eff09acc865 100755 --- a/docs/docs/integrations/providers/aws.mdx +++ b/docs/docs/integrations/providers/aws.mdx @@ -28,7 +28,7 @@ pip install langchain-community boto3 > serverless, you don't have to manage any infrastructure, and you can securely integrate and deploy > generative AI capabilities into your applications using the AWS services you are already familiar with. -See a [usage example](/docs/integrations/chat/bedrock). +See a [usage example](/docs/docs/integrations/chat/bedrock.ipynb). ```python from langchain_aws import ChatBedrock @@ -56,7 +56,7 @@ from langchain_aws import ChatBedrockConverse ### Bedrock -See a [usage example](/docs/integrations/llms/bedrock). +See a [usage example](docs/docs/integrations/llms/bedrock.ipynb). ```python from langchain_aws import BedrockLLM @@ -76,7 +76,7 @@ from langchain_aws import BedrockLLM > You pay for the API calls you receive and the amount of data transferred out and, with the `API Gateway` > tiered pricing model, you can reduce your cost as your API usage scales. -See a [usage example](/docs/integrations/llms/amazon_api_gateway). +See a [usage example](/docs/docs/integrations/llms/amazon_api_gateway.ipynb). ```python from langchain_community.llms import AmazonAPIGateway @@ -89,7 +89,7 @@ from langchain_community.llms import AmazonAPIGateway We use `SageMaker` to host our model and expose it as the `SageMaker Endpoint`. -See a [usage example](/docs/integrations/llms/sagemaker). +See a [usage example](/docs/docs/integrations/llms/sagemaker.ipynb). ```python from langchain_aws import SagemakerEndpoint @@ -99,14 +99,14 @@ from langchain_aws import SagemakerEndpoint ### Bedrock -See a [usage example](/docs/integrations/text_embedding/bedrock). +See a [usage example](/docs/docs/integrations/text_embedding/bedrock.ipynb). ```python from langchain_aws import BedrockEmbeddings ``` ### SageMaker Endpoint -See a [usage example](/docs/integrations/text_embedding/sagemaker-endpoint). +See a [usage example](/docs/docs/integrations/text_embedding/sagemaker-endpoint.ipynb). ```python from langchain_community.embeddings import SagemakerEndpointEmbeddings from langchain_community.llms.sagemaker_endpoint import ContentHandlerBase @@ -121,9 +121,9 @@ from langchain_community.llms.sagemaker_endpoint import ContentHandlerBase >[AWS S3 Directory](https://docs.aws.amazon.com/AmazonS3/latest/userguide/using-folders.html) >[AWS S3 Buckets](https://docs.aws.amazon.com/AmazonS3/latest/userguide/UsingBucket.html) -See a [usage example for S3DirectoryLoader](/docs/integrations/document_loaders/aws_s3_directory). +See a [usage example for S3DirectoryLoader](/docs/docs/integrations/document_loaders/aws_s3_directory.ipynb). -See a [usage example for S3FileLoader](/docs/integrations/document_loaders/aws_s3_file). +See a [usage example for S3FileLoader](/docs/docs/integrations/document_loaders/aws_s3_file.ipynb). ```python from langchain_community.document_loaders import S3DirectoryLoader, S3FileLoader @@ -134,7 +134,7 @@ from langchain_community.document_loaders import S3DirectoryLoader, S3FileLoader >[Amazon Textract](https://docs.aws.amazon.com/managedservices/latest/userguide/textract.html) is a machine > learning (ML) service that automatically extracts text, handwriting, and data from scanned documents. -See a [usage example](/docs/integrations/document_loaders/amazon_textract). +See a [usage example](/docs/docs/integrations/document_loaders/amazon_textract.ipynb). ```python from langchain_community.document_loaders import AmazonTextractPDFLoader @@ -145,7 +145,7 @@ from langchain_community.document_loaders import AmazonTextractPDFLoader >[Amazon Athena](https://aws.amazon.com/athena/) is a serverless, interactive analytics service built >on open-source frameworks, supporting open-table and file formats. -See a [usage example](/docs/integrations/document_loaders/athena). +See a [usage example](/docs/docs/integrations/document_loaders/athena.ipynb). ```python from langchain_community.document_loaders.athena import AthenaLoader @@ -159,7 +159,7 @@ from langchain_community.document_loaders.athena import AthenaLoader > enabling various AWS services and your applications to query and connect > to the data they need efficiently. -See a [usage example](/docs/integrations/document_loaders/glue_catalog). +See a [usage example](/docs/docs/integrations/document_loaders/glue_catalog.ipynb). ```python from langchain_community.document_loaders.glue_catalog import GlueCatalogLoader @@ -182,7 +182,7 @@ We need to install several python libraries. pip install boto3 requests requests-aws4auth ``` -See a [usage example](/docs/integrations/vectorstores/opensearch#using-aos-amazon-opensearch-service). +See a [usage example](/docs/docs/integrations/vectorstores/opensearch.ipynb). ```python from langchain_community.vectorstores import OpenSearchVectorSearch @@ -196,7 +196,7 @@ from langchain_community.vectorstores import OpenSearchVectorSearch #### Installation and Setup -See [detail configuration instructions](/docs/integrations/vectorstores/documentdb). +See [detail configuration instructions](/docs/docs/integrations/vectorstores/documentdb.ipynb). We need to install the `pymongo` python package. @@ -210,7 +210,7 @@ pip install pymongo AWS offers services for computing, databases, storage, analytics, and other functionality. For an overview of all AWS services, see [Cloud Computing with Amazon Web Services](https://aws.amazon.com/what-is-aws/). -See a [usage example](/docs/integrations/vectorstores/documentdb). +See a [usage example](/docs/docs/integrations/vectorstores/documentdb.ipynb). ```python from langchain_community.vectorstores import DocumentDBVectorSearch @@ -232,7 +232,7 @@ vds = InMemoryVectorStore.from_documents( index_name=INDEX_NAME, ) ``` -See a [usage example](/docs/integrations/vectorstores/memorydb). +See a [usage example](/docs/docs/integrations/vectorstores/memorydb.ipynb). ## Retrievers @@ -254,7 +254,7 @@ We need to install the `langchain-aws` library. pip install langchain-aws ``` -See a [usage example](/docs/integrations/retrievers/amazon_kendra_retriever). +See a [usage example](/docs/docs/integrations/retrievers/amazon_kendra_retriever.ipynb). ```python from langchain_aws import AmazonKendraRetriever @@ -272,7 +272,7 @@ We need to install the `langchain-aws` library. pip install langchain-aws ``` -See a [usage example](/docs/integrations/retrievers/bedrock). +See a [usage example](/docs/docs/integrations/retrievers/bedrock.ipynb). ```python from langchain_aws import AmazonKnowledgeBasesRetriever @@ -294,7 +294,7 @@ We need to install `boto3` python library. pip install boto3 ``` -See a [usage example](/docs/integrations/tools/awslambda). +See a [usage example](/docs/docs/integrations/tools/awslambda.ipynb). ## Memory @@ -311,7 +311,7 @@ We need to install the `boto3` library. pip install boto3 ``` -See a [usage example](/docs/integrations/memory/aws_dynamodb). +See a [usage example](/docs/docs/integrations/memory/aws_dynamodb.ipynb). ```python from langchain_community.chat_message_histories import DynamoDBChatMessageHistory @@ -332,7 +332,7 @@ pip install langchain-aws ### Amazon Neptune with Cypher -See a [usage example](/docs/integrations/graphs/amazon_neptune_open_cypher). +See a [usage example](/docs/docs/integrations/graphs/amazon_neptune_open_cypher.ipynb). ```python from langchain_aws.graphs import NeptuneGraph @@ -342,7 +342,7 @@ from langchain_aws.chains import create_neptune_opencypher_qa_chain ### Amazon Neptune with SPARQL -See a [usage example](/docs/integrations/graphs/amazon_neptune_sparql). +See a [usage example](/docs/docs/integrations/graphs/amazon_neptune_sparql.ipynb). ```python from langchain_aws.graphs import NeptuneRdfGraph @@ -374,7 +374,7 @@ We need to install several python libraries. pip install google-search-results sagemaker ``` -See a [usage example](/docs/integrations/callbacks/sagemaker_tracking). +See a [usage example](/docs/docs/integrations/callbacks/sagemaker_tracking.ipynb). ```python from langchain_community.callbacks import SageMakerCallbackHandler