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docs: integrations/providers/microsoft update (#27055)
Added reference to the AzureCognitiveServicesToolkit. Fixed titles. --------- Co-authored-by: Erick Friis <erick@langchain.dev>
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@ -264,22 +264,20 @@ See a [usage example](/docs/integrations/document_loaders/url/#playwright-url-lo
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from langchain_community.document_loaders.onenote import OneNoteLoader
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```
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## AI Agent Memory System
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[AI agent](https://learn.microsoft.com/en-us/azure/cosmos-db/ai-agents) needs robust memory systems that support multi-modality, offer strong operational performance, and enable agent memory sharing as well as separation.
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## Vector Stores
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### Azure Cosmos DB
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AI agents can rely on Azure Cosmos DB as a unified [memory system](https://learn.microsoft.com/en-us/azure/cosmos-db/ai-agents#memory-can-make-or-break-agents) solution, enjoying speed, scale, and simplicity. This service successfully [enabled OpenAI's ChatGPT service](https://www.youtube.com/watch?v=6IIUtEFKJec&t) to scale dynamically with high reliability and low maintenance. Powered by an atom-record-sequence engine, it is the world's first globally distributed [NoSQL](https://learn.microsoft.com/en-us/azure/cosmos-db/distributed-nosql), [relational](https://learn.microsoft.com/en-us/azure/cosmos-db/distributed-relational), and [vector database](https://learn.microsoft.com/en-us/azure/cosmos-db/vector-database) service that offers a serverless mode.
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Below are two available Azure Cosmos DB APIs that can provide vector store functionalities.
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### Azure Cosmos DB for MongoDB (vCore)
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#### Azure Cosmos DB for MongoDB (vCore)
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>[Azure Cosmos DB for MongoDB vCore](https://learn.microsoft.com/en-us/azure/cosmos-db/mongodb/vcore/) makes it easy to create a database with full native MongoDB support.
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> You can apply your MongoDB experience and continue to use your favorite MongoDB drivers, SDKs, and tools by pointing your application to the API for MongoDB vCore account's connection string.
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> Use vector search in Azure Cosmos DB for MongoDB vCore to seamlessly integrate your AI-based applications with your data that's stored in Azure Cosmos DB.
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#### Installation and Setup
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##### Installation and Setup
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See [detail configuration instructions](/docs/integrations/vectorstores/azure_cosmos_db).
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@ -289,7 +287,7 @@ We need to install `pymongo` python package.
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pip install pymongo
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```
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#### Deploy Azure Cosmos DB on Microsoft Azure
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##### Deploy Azure Cosmos DB on Microsoft Azure
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Azure Cosmos DB for MongoDB vCore provides developers with a fully managed MongoDB-compatible database service for building modern applications with a familiar architecture.
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@ -303,7 +301,7 @@ See a [usage example](/docs/integrations/vectorstores/azure_cosmos_db).
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from langchain_community.vectorstores import AzureCosmosDBVectorSearch
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```
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### Azure Cosmos DB NoSQL
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#### Azure Cosmos DB NoSQL
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>[Azure Cosmos DB for NoSQL](https://learn.microsoft.com/en-us/azure/cosmos-db/nosql/vector-search) now offers vector indexing and search in preview.
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This feature is designed to handle high-dimensional vectors, enabling efficient and accurate vector search at any scale. You can now store vectors
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@ -312,7 +310,7 @@ but also high-dimensional vectors as other properties of the documents. This col
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as the vectors are stored in the same logical unit as the data they represent. This simplifies data management, AI application architectures, and the
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efficiency of vector-based operations.
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#### Installation and Setup
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##### Installation and Setup
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See [detail configuration instructions](/docs/integrations/vectorstores/azure_cosmos_db_no_sql).
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@ -322,7 +320,7 @@ We need to install `azure-cosmos` python package.
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pip install azure-cosmos
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```
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#### Deploy Azure Cosmos DB on Microsoft Azure
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##### Deploy Azure Cosmos DB on Microsoft Azure
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Azure Cosmos DB offers a solution for modern apps and intelligent workloads by being very responsive with dynamic and elastic autoscale. It is available
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in every Azure region and can automatically replicate data closer to users. It has SLA guaranteed low-latency and high availability.
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@ -336,6 +334,7 @@ from langchain_community.vectorstores import AzureCosmosDBNoSQLVectorSearch
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```
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### Azure Database for PostgreSQL
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>[Azure Database for PostgreSQL - Flexible Server](https://learn.microsoft.com/en-us/azure/postgresql/flexible-server/service-overview) is a relational database service based on the open-source Postgres database engine. It's a fully managed database-as-a-service that can handle mission-critical workloads with predictable performance, security, high availability, and dynamic scalability.
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See [set up instructions](https://learn.microsoft.com/en-us/azure/postgresql/flexible-server/quickstart-create-server-portal) for Azure Database for PostgreSQL.
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@ -446,6 +445,38 @@ The `azure_ai_services` toolkit includes the following tools:
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- Text to Speech: [AzureAiServicesTextToSpeechTool](https://python.langchain.com/api_reference/community/tools/langchain_community.tools.azure_ai_services.text_to_speech.AzureAiServicesTextToSpeechTool.html)
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- Text Analytics for Health: [AzureAiServicesTextAnalyticsForHealthTool](https://python.langchain.com/api_reference/community/tools/langchain_community.tools.azure_ai_services.text_analytics_for_health.AzureAiServicesTextAnalyticsForHealthTool.html)
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### Azure Cognitive Services
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We need to install several python packages.
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```bash
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pip install azure-ai-formrecognizer azure-cognitiveservices-speech azure-ai-vision-imageanalysis
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```
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See a [usage example](/docs/integrations/tools/azure_cognitive_services).
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```python
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from langchain_community.agent_toolkits import AzureCognitiveServicesToolkit
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```
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#### Azure AI Services individual tools
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The `azure_ai_services` toolkit includes the tools that queries the `Azure Cognitive Services`:
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- `AzureCogsFormRecognizerTool`: Form Recognizer API
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- `AzureCogsImageAnalysisTool`: Image Analysis API
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- `AzureCogsSpeech2TextTool`: Speech2Text API
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- `AzureCogsText2SpeechTool`: Text2Speech API
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- `AzureCogsTextAnalyticsHealthTool`: Text Analytics for Health API
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```python
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from langchain_community.tools.azure_cognitive_services import (
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AzureCogsFormRecognizerTool,
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AzureCogsImageAnalysisTool,
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AzureCogsSpeech2TextTool,
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AzureCogsText2SpeechTool,
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AzureCogsTextAnalyticsHealthTool,
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)
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```
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### Microsoft Office 365 email and calendar
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@ -465,11 +496,11 @@ from langchain_community.agent_toolkits import O365Toolkit
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#### Office 365 individual tools
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You can use individual tools from the Office 365 Toolkit:
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- `O365CreateDraftMessage`: tool for creating a draft email in Office 365
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- `O365SearchEmails`: tool for searching email messages in Office 365
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- `O365SearchEvents`: tool for searching calendar events in Office 365
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- `O365SendEvent`: tool for sending calendar events in Office 365
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- `O365SendMessage`: tool for sending an email in Office 365
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- `O365CreateDraftMessage`: creating a draft email in Office 365
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- `O365SearchEmails`: searching email messages in Office 365
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- `O365SearchEvents`: searching calendar events in Office 365
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- `O365SendEvent`: sending calendar events in Office 365
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- `O365SendMessage`: sending an email in Office 365
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```python
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from langchain_community.tools.office365 import O365CreateDraftMessage
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@ -497,9 +528,9 @@ from langchain_community.utilities.powerbi import PowerBIDataset
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#### PowerBI individual tools
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You can use individual tools from the Azure PowerBI Toolkit:
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- `InfoPowerBITool`: tool for getting metadata about a PowerBI Dataset
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- `ListPowerBITool`: tool for getting tables names
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- `QueryPowerBITool`: tool for querying a PowerBI Dataset
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- `InfoPowerBITool`: getting metadata about a PowerBI Dataset
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- `ListPowerBITool`: getting tables names
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- `QueryPowerBITool`: querying a PowerBI Dataset
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```python
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from langchain_community.tools.powerbi.tool import InfoPowerBITool
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