> ## Documentation Index
> Fetch the complete documentation index at: https://docs.langchain.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Azure blob storage loader integration

> Integrate with the Azure blob storage loader document loader using LangChain Python.

> [Azure Blob Storage](https://learn.microsoft.com/en-us/azure/storage/blobs/storage-blobs-introduction) is Microsoft's object storage solution for the cloud. Blob Storage is optimized for storing massive amounts of unstructured data. Unstructured data is data that doesn't adhere to a particular data model or definition, such as text or binary data.

`Azure Blob Storage` is designed for:

* Serving images or documents directly to a browser.
* Storing files for distributed access.
* Streaming video and audio.
* Writing to log files.
* Storing data for backup and restore, disaster recovery, and archiving.
* Storing data for analysis by an on-premises or Azure-hosted service.

This notebook covers how to load document objects from a container on `Azure Blob Storage`. For more detailed documentation on the document loader, see the [Azure Blob Storage Loader API Reference](https://reference.langchain.com/python/integrations/langchain_azure/storage/).

<Note>
  It is recommended to use this new loader over the previous [`AzureBlobStorageFileLoader`](https://reference.langchain.com/python/langchain-community/document_loaders/azure_blob_storage_file/AzureBlobStorageFileLoader) and [`AzureBlobStorageContainerLoader`](https://reference.langchain.com/python/langchain-community/document_loaders/azure_blob_storage_container/AzureBlobStorageContainerLoader) from `langchain_community`. For detailed instructions on migrating to the new loader, refer to the [migration guide](https://github.com/langchain-ai/langchain-azure/blob/main/libs/azure-storage/README.md#migrating-from-langchain-community-azure-storage-document-loaders)
</Note>

## Setup

```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
pip install -qU langchain-azure-storage
```

```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
from langchain_azure_storage.document_loaders import AzureBlobStorageLoader
```

## Load from container

The `AzureBlobStorageLoader` loads all blobs from a given container in Azure Blob Storage and requires an [account URL and container name](https://learn.microsoft.com/en-us/rest/api/storageservices/Naming-and-Referencing-Containers--Blobs--and-Metadata#resource-uri-syntax). The loader returns [`Document`](https://reference.langchain.com/python/langchain_core/documents/#langchain_core.documents.base.Document) objects containing the blob content (defaulting to UTF-8 encoding) and metadata including the blob URL, as shown in the example below.

No explicit credential configuration is needed, as it uses [`DefaultAzureCredential`](https://learn.microsoft.com/en-us/azure/developer/python/sdk/authentication/credential-chains?tabs=dac#defaultazurecredential-overview), which automatically retrieves [Microsoft Entra ID tokens](https://learn.microsoft.com/en-us/azure/storage/blobs/authorize-access-azure-active-directory) based on your current environment.

```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
loader = AzureBlobStorageLoader(
    "https://<storage-account-name>.blob.core.windows.net",
    "<container-name>",
)

for doc in loader.load():
    print(doc)
```

```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
page_content='Lorem ipsum dolor sit amet.' metadata={'source': 'https://<storage-account-name>.blob.core.windows.net/<container-name>/<blob-name>'}
```

You can also specify a prefix to only return blobs that start with that prefix.

```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
loader = AzureBlobStorageLoader(
    "https://<storage-account-name>.blob.core.windows.net",
    "<container-name>",
    prefix="<prefix>",
)
```

## Load from container by blob name

You can load documents from a list of blob names, which uses only the blobs provided instead of an API call to list blobs.

```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
loader = AzureBlobStorageLoader(
    "https://<storage-account-name>.blob.core.windows.net",
    "<container-name>",
    blob_names=["blob-1", "blob-2", "blob-3"],
)
```

## Override default credentials

By default, the document loader uses the [`DefaultAzureCredential`](https://learn.microsoft.com/en-us/azure/developer/python/sdk/authentication/credential-chains?tabs=dac#defaultazurecredential-overview). The examples below show how to override this:

```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
from azure.core.credentials import AzureSasCredential
from azure.identity import ManagedIdentityCredential
from langchain_azure_storage.document_loaders import AzureBlobStorageLoader

# Override with SAS token
loader = AzureBlobStorageLoader(
    "https://<storage-account-name>.blob.core.windows.net",
    "<container-name>",
    credential=AzureSasCredential("<sas-token>")
)

# Override with more specific token credential than the entire
# default credential chain (e.g., system-assigned managed identity)
loader = AzureBlobStorageLoader(
    "https://<storage-account-name>.blob.core.windows.net",
    "<container-name>",
    credential=ManagedIdentityCredential()
)
```

## Customize blob content parsing

Currently, the default when parsing each blob is to return the content as a single [`Document`](https://reference.langchain.com/python/langchain-core/documents/base/Document) object with UTF-8 encoding regardless of the file type. For file types that require specific parsing (e.g., PDFs, CSVs, etc.) or when you want to control the document content format, you can provide the `loader_factory` argument to take in an already existing document loader (e.g., PyPDFLoader, CSVLoader, etc.) or a customized loader.

This works by downloading the blob content to a temporary file. The `loader_factory` then gets called with the filepath to use the specified document loader to load/parse the file and return the [`Document`](https://reference.langchain.com/python/langchain-core/documents/base/Document) object(s).

Below shows how to override the default loader used to parse blobs as PDFs using the [PyPDFLoader](https://reference.langchain.com/python/langchain-community/document_loaders/pdf/PyPDFLoader):

<Warning>
  The `langchain-community` package is no longer maintained. Examples that import from `langchain_community` may be outdated or broken. Use with caution.
</Warning>

```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
from langchain_azure_storage.document_loaders import AzureBlobStorageLoader
from langchain_community.document_loaders import PyPDFLoader  # This example requires installing `langchain-community` and `pypdf`

loader = AzureBlobStorageLoader(
    "https://<storage-account-name>.blob.core.windows.net",
    "<container-name>",
    blob_names="<pdf-file.pdf>",
    loader_factory=PyPDFLoader,
)

for doc in loader.lazy_load():
    print(doc.page_content)  # Prints content of each page as a separate document
```

To provide additional configuration, you can define a callable that returns an instantiated document loader as shown below:

```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
from langchain_azure_storage.document_loaders import AzureBlobStorageLoader
from langchain_community.document_loaders import PyPDFLoader  # This example requires installing `langchain-community` and `pypdf`

def loader_factory(file_path: str) -> PyPDFLoader:
    return PyPDFLoader(
        file_path,
        mode="single",  # To return the PDF as a single document instead of extracting documents by page
    )

loader = AzureBlobStorageLoader(
    "https://<storage-account-name>.blob.core.windows.net",
    "<container-name>",
    blob_names="<pdf-file.pdf>",
    loader_factory=loader_factory,
)

for doc in loader.lazy_load():
    print(doc.page_content)
```

***

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