Files
Evan Mattson 0b69d7fd15 Python: Bump Python package versions for 1.2.0 release (#5468)
* Bump Python package versions for 1.2.0 release

Released tier bumps 1.1.1 -> 1.2.0 (core, openai, foundry, root) to
reflect additive public APIs landed since 1.1.0: functional workflow API
(#4238) and FunctionTool SKIP_PARSING sentinel (#5424). All beta packages
stamped 1.0.0b260424, alpha packages 1.0.0a260424. All 26 non-core
agent-framework-core floors raised to >=1.2.0,<2. CHANGELOG consolidates
the never-tagged 1.1.1 entries with the post-merge additions into [1.2.0].

* Update CHANGELOG footer links for 1.2.0

Advance [Unreleased] comparison base from python-1.1.0 to python-1.2.0
and add a [1.2.0] reference link comparing python-1.1.0...python-1.2.0
so the heading links resolve correctly.

* Fix CHANGELOG: restore [1.1.1] section and add proper [1.2.0]

Previous commit incorrectly renamed the [1.1.1] header to [1.2.0], which
wiped the historical 1.1.1 entries and wrongly attributed them to 1.2.0.
This restores [1.1.1] to its origin/main content and adds a new [1.2.0]
section above containing only the commits in python-1.1.1..HEAD:

- #4238 functional workflow API
- #5142 GitHub Copilot OpenTelemetry
- #2403 A2A bridge support
- #5070 oauth_consent_request events in Foundry clients
- #5447 FoundryAgent hosted agent sessions
- #5459 hosting server dependency upgrade + types
- #5389 AG-UI reasoning/multimodal parsing fix
- #5440 stop [TOOLBOXES] warning spam
- #5455 user agent prefix fix

Also corrects the [1.2.0] compare base to python-1.1.1 (not 1.1.0) and
adds the missing [1.1.1] reference link.
0b69d7fd15 · 2026-04-24 19:54:59 +09:00
History
..

Get Started with Microsoft Agent Framework Azure Cosmos DB

Please install this package via pip:

pip install agent-framework-azure-cosmos --pre

Azure Cosmos DB History Provider

The Azure Cosmos DB integration provides CosmosHistoryProvider for persistent conversation history storage.

Basic Usage Example

from azure.identity.aio import DefaultAzureCredential
from agent_framework_azure_cosmos import CosmosHistoryProvider

provider = CosmosHistoryProvider(
    endpoint="https://<account>.documents.azure.com:443/",
    credential=DefaultAzureCredential(),
    database_name="agent-framework",
    container_name="chat-history",
)

Credentials follow the same pattern used by other Azure connectors in the repository:

  • Pass a credential object (for example DefaultAzureCredential)
  • Or pass a key string directly
  • Or set AZURE_COSMOS_KEY in the environment

Container naming behavior:

  • Container name is configured on the provider (container_name or AZURE_COSMOS_CONTAINER_NAME)
  • session_id is used as the Cosmos partition key for reads/writes

See samples/02-agents/conversations/cosmos_history_provider.py for a runnable example.

Cosmos DB Workflow Checkpoint Storage

CosmosCheckpointStorage implements the CheckpointStorage protocol, enabling durable workflow checkpointing backed by Azure Cosmos DB NoSQL. Workflows can be paused and resumed across process restarts by persisting checkpoint state in Cosmos DB.

Basic Usage

from azure.identity.aio import DefaultAzureCredential
from agent_framework import WorkflowBuilder
from agent_framework_azure_cosmos import CosmosCheckpointStorage

checkpoint_storage = CosmosCheckpointStorage(
    endpoint="https://<account>.documents.azure.com:443/",
    credential=DefaultAzureCredential(),
    database_name="agent-framework",
    container_name="workflow-checkpoints",
)

Account Key

from agent_framework_azure_cosmos import CosmosCheckpointStorage

checkpoint_storage = CosmosCheckpointStorage(
    endpoint="https://<account>.documents.azure.com:443/",
    credential="<your-account-key>",
    database_name="agent-framework",
    container_name="workflow-checkpoints",
)

Then use with a workflow

from agent_framework import WorkflowBuilder

# Build a workflow with checkpointing enabled
workflow = WorkflowBuilder(
    start_executor=start,
    checkpoint_storage=checkpoint_storage,
).build()

# Run the workflow — checkpoints are automatically saved after each superstep
result = await workflow.run(message="input data")

# Resume from a checkpoint
latest = await checkpoint_storage.get_latest(workflow_name=workflow.name)
if latest:
    resumed = await workflow.run(checkpoint_id=latest.checkpoint_id)

Authentication Options

CosmosCheckpointStorage supports the same authentication modes as CosmosHistoryProvider:

  • Managed identity / RBAC (recommended): Pass DefaultAzureCredential(), ManagedIdentityCredential(), or any Azure TokenCredential
  • Account key: Pass a key string via credential parameter
  • Environment variables: Set AZURE_COSMOS_ENDPOINT, AZURE_COSMOS_DATABASE_NAME, AZURE_COSMOS_CONTAINER_NAME, and AZURE_COSMOS_KEY (key not required when using Azure credentials)
  • Pre-created client: Pass an existing CosmosClient or ContainerProxy

Database and Container Setup

The database and container are created automatically on first use (via create_database_if_not_exists and create_container_if_not_exists). The container uses /workflow_name as the partition key. You can also pre-create them in the Azure portal with this partition key configuration.

Environment Variables

Variable Description
AZURE_COSMOS_ENDPOINT Cosmos DB account endpoint
AZURE_COSMOS_DATABASE_NAME Database name
AZURE_COSMOS_CONTAINER_NAME Container name
AZURE_COSMOS_KEY Account key (optional if using Azure credentials)

See samples/03-workflows/checkpoint/cosmos_workflow_checkpointing.py for a standalone example, or samples/03-workflows/checkpoint/cosmos_workflow_checkpointing_foundry.py for an end-to-end example with Azure AI Foundry agents.