* 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.
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_KEYin the environment
Container naming behavior:
- Container name is configured on the provider (
container_nameorAZURE_COSMOS_CONTAINER_NAME) session_idis 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
Managed Identity / RBAC (recommended for production)
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 AzureTokenCredential - Account key: Pass a key string via
credentialparameter - Environment variables: Set
AZURE_COSMOS_ENDPOINT,AZURE_COSMOS_DATABASE_NAME,AZURE_COSMOS_CONTAINER_NAME, andAZURE_COSMOS_KEY(key not required when using Azure credentials) - Pre-created client: Pass an existing
CosmosClientorContainerProxy
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.