microsoft-agents-storage-blob 1.2.0.dev10

A blob storage library for Microsoft Agents

Microsoft Agents Storage - Blob

Azure Blob Storage integration for Microsoft 365 Agents SDK. This library provides persistent storage for conversation state, user data, and custom agent information using Azure Blob Storage.

This library implements the storage interface for the Microsoft 365 Agents SDK using Azure Blob Storage as the backend. It enables your agents to persist conversation state, user preferences, and custom data across sessions. Perfect for production deployments where you need reliable, scalable cloud storage.

What is this?

This library is part of the Microsoft 365 Agents SDK for Python - a comprehensive framework for building enterprise-grade conversational AI agents. The SDK enables developers to create intelligent agents that work across multiple platforms including Microsoft Teams, M365 Copilot, Copilot Studio, and web chat, with support for third-party integrations like Slack, Facebook Messenger, and Twilio.

Release Notes

Version	Date	Release Notes
1.1.0	2026-06-19	1.1.0 Release Notes
1.0.0	2026-05-22	1.0.0 Release Notes
0.9.0	2026-04-15	0.9.0 Release Notes
0.8.0	2026-02-23	0.8.0 Release Notes
0.7.0	2026-01-21	0.7.0 Release Notes
0.6.1	2025-12-01	0.6.1 Release Notes
0.6.0	2025-11-18	0.6.0 Release Notes
0.5.0	2025-10-22	0.5.0 Release Notes

Packages Overview

We offer the following PyPI packages to create conversational experiences based on Agents:

Package Name	PyPI Version	Description
microsoft-agents-activity		Types and validators implementing the Activity protocol spec.
microsoft-agents-hosting-core		Core library for Microsoft Agents hosting.
microsoft-agents-hosting-aiohttp		Configures aiohttp to run the Agent.
microsoft-agents-hosting-teams		Provides classes to host an Agent for Teams.
microsoft-agents-hosting-dialogs		Dialog system with waterfall dialogs, prompts, and multi-turn conversation management.
microsoft-agents-storage-blob		Extension to use Azure Blob as storage.
microsoft-agents-storage-cosmos		Extension to use CosmosDB as storage.
microsoft-agents-authentication-msal		MSAL-based authentication for Microsoft Agents.

Additionally we provide a Copilot Studio Client, to interact with Agents created in CopilotStudio:

Package Name	PyPI Version	Description
microsoft-agents-copilotstudio-client		Direct to Engine client to interact with Agents created in CopilotStudio

Installation

pip install microsoft-agents-storage-blob

Benefits:

• ✅ No secrets in code
• ✅ Managed Identity support
• ✅ Automatic token renewal
• ✅ Fine-grained access control via Azure RBAC

Configuration Parameters

Parameter	Type	Required	Description
container_name	str	Yes	Name of the blob container to use
connection_string	str	No*	Storage account connection string
url	str	No*	Blob service URL (e.g., https://account.blob.core.windows.net)
credential	TokenCredential	No**	Azure credential for authentication

*Either connection_string OR (url + credential) must be provided
**Required when using url

Azure Managed Identity

When running in Azure (App Service, Functions, Container Apps), use Managed Identity:

from azure.identity import ManagedIdentityCredential

config = BlobStorageConfig(
    container_name="agent-storage",
    url="https://myaccount.blob.core.windows.net",
    credential=ManagedIdentityCredential()
)

Azure RBAC Roles Required:

• Storage Blob Data Contributor - For read/write access
• Storage Blob Data Reader - For read-only access

Benefits of switching to BlobStorage:

• ✅ Data persists across restarts
• ✅ Scalable to millions of items
• ✅ Multi-instance support (load balancing)
• ✅ Automatic backups and geo-replication
• ✅ Built-in monitoring and diagnostics

Best Practices

1. Use Token Authentication in Production - Avoid storing connection strings; use Managed Identity or DefaultAzureCredential
2. Initialize Once - Call storage.initialize() during app startup, not on every request
3. Implement Retry Logic - Handle transient failures with exponential backoff
4. Monitor Performance - Use Azure Monitor to track storage operations
5. Set Lifecycle Policies - Configure automatic cleanup of old data in Azure Portal
6. Use Consistent Naming - Establish key naming conventions (e.g., user:{id}, conversation:{id})
7. Batch Operations - Read/write multiple items together when possible

Key Classes Reference

• BlobStorage - Main storage implementation using Azure Blob Storage
• BlobStorageConfig - Configuration settings for connection and authentication
• StoreItem - Base class for data models (inherit to create custom types)

Quick Links

• 📦 All SDK Packages on PyPI
• 📖 Complete Documentation
• 💡 Python Samples Repository
• 🐛 Report Issues

Sample Applications

Name	Description	README
Quickstart	Simplest agent	Quickstart
Auto Sign In	Simple OAuth agent using Graph and GitHub	auto-signin
OBO Authorization	OBO flow to access a Copilot Studio Agent	obo-authorization
Semantic Kernel Integration	A weather agent built with Semantic Kernel	semantic-kernel-multiturn
Streaming Agent	Streams OpenAI responses	azure-ai-streaming
Copilot Studio Client	Console app to consume a Copilot Studio Agent	copilotstudio-client
Cards Agent	Agent that uses rich cards to enhance conversation design	cards