# Microsoft All functionality related to Microsoft ## LLM ### Azure OpenAI >[Microsoft Azure](https://en.wikipedia.org/wiki/Microsoft_Azure), often referred to as `Azure` is a cloud computing platform run by `Microsoft`, which offers access, management, and development of applications and services through global data centers. It provides a range of capabilities, including software as a service (SaaS), platform as a service (PaaS), and infrastructure as a service (IaaS). `Microsoft Azure` supports many programming languages, tools, and frameworks, including Microsoft-specific and third-party software and systems. >[Azure OpenAI](https://learn.microsoft.com/en-us/azure/cognitive-services/openai/) is an `Azure` service with powerful language models from `OpenAI` including the `GPT-3`, `Codex` and `Embeddings model` series for content generation, summarization, semantic search, and natural language to code translation. ```bash pip install openai tiktoken ``` Set the environment variables to get access to the `Azure OpenAI` service. ```python import os os.environ["OPENAI_API_TYPE"] = "azure" os.environ["OPENAI_API_BASE"] = "https://[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 Files](https://learn.microsoft.com/en-us/azure/storage/files/storage-files-introduction) offers fully managed > file shares in the cloud that are accessible via the industry standard Server Message Block (`SMB`) protocol, > Network File System (`NFS`) protocol, and `Azure Files REST API`. `Azure Files` are based on the `Azure Blob Storage`. `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. ```bash pip install azure-storage-blob ``` See a [usage example for the Azure Blob Storage](/docs/integrations/document_loaders/azure_blob_storage_container.html). ```python from langchain.document_loaders import AzureBlobStorageContainerLoader ``` See a [usage example for the Azure Files](/docs/integrations/document_loaders/azure_blob_storage_file.html). ```python from langchain.document_loaders import AzureBlobStorageFileLoader ``` ### Microsoft OneDrive >[Microsoft OneDrive](https://en.wikipedia.org/wiki/OneDrive) (formerly `SkyDrive`) is a file-hosting service operated by Microsoft. First, you need to install a python package. ```bash pip install o365 ``` See a [usage example](/docs/integrations/document_loaders/microsoft_onedrive). ```python from langchain.document_loaders import OneDriveLoader ``` ### Microsoft Word >[Microsoft Word](https://www.microsoft.com/en-us/microsoft-365/word) is a word processor developed by Microsoft. See a [usage example](/docs/integrations/document_loaders/microsoft_word). ```python from langchain.document_loaders import UnstructuredWordDocumentLoader ``` ## Retriever ### Azure Cognitive Search >[Azure Cognitive Search](https://learn.microsoft.com/en-us/azure/search/search-what-is-azure-search) (formerly known as `Azure Search`) is a cloud search service that gives developers infrastructure, APIs, and tools for building a rich search experience over private, heterogeneous content in web, mobile, and enterprise applications. >Search is foundational to any app that surfaces text to users, where common scenarios include catalog or document search, online retail apps, or data exploration over proprietary content. When you create a search service, you'll work with the following capabilities: >- A search engine for full text search over a search index containing user-owned content >- Rich indexing, with lexical analysis and optional AI enrichment for content extraction and transformation >- Rich query syntax for text search, fuzzy search, autocomplete, geo-search and more >- Programmability through REST APIs and client libraries in Azure SDKs >- Azure integration at the data layer, machine learning layer, and AI (Cognitive Services) See [set up instructions](https://learn.microsoft.com/en-us/azure/search/search-create-service-portal). See a [usage example](/docs/integrations/retrievers/azure_cognitive_search). ```python from langchain.retrievers import AzureCognitiveSearchRetriever ```