Python: Add Cosmos DB NoSQL Checkpoint Storage for Python Workflows (#4916)

* Add CosmosCheckpointStorage for Python workflow checkpointing

Add native Cosmos DB NoSQL support for workflow checkpoint storage in the
Python agent-framework-azure-cosmos package, achieving parity with the
existing .NET CosmosCheckpointStore.

New files:
- _checkpoint_storage.py: CosmosCheckpointStorage implementing the
  CheckpointStorage protocol with 6 methods (save, load, list_checkpoints,
  delete, get_latest, list_checkpoint_ids)
- test_cosmos_checkpoint_storage.py: Unit and integration tests
- workflow_checkpointing.py: Sample demonstrating Cosmos DB-backed
  workflow checkpoint/resume

Auth support:
- Managed identity / RBAC via Azure credential objects
  (DefaultAzureCredential, ManagedIdentityCredential, etc.)
- Key-based auth via account key string or AZURE_COSMOS_KEY env var
- Pre-created CosmosClient or ContainerProxy

Key design decisions:
- Partition key: /workflow_name for efficient per-workflow queries
- Serialization: Reuses encode/decode_checkpoint_value for full Python
  object fidelity (hybrid JSON + pickle approach)
- Container auto-creation via create_container_if_not_exists

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Adding cosmos checkpointer

* Resolving comments

* Fixing builds

* Adding sample for history provider and checkpoint storage

* Resolving comments

* fixing builds

* Resolving comments

---------

Co-authored-by: Aayush Kataria <aayushkataria@Aayushs-MacBook-Pro-2.local>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Co-authored-by: Evan Mattson <35585003+moonbox3@users.noreply.github.com>

python/samples/02-agents/conversations/README.md

@@ -9,6 +9,9 @@ These samples demonstrate different approaches to managing conversation history
 | [`suspend_resume_session.py`](suspend_resume_session.py) | Suspend and resume conversation sessions, comparing service-managed sessions (Azure AI Foundry) with in-memory sessions (OpenAI). |
 | [`custom_history_provider.py`](custom_history_provider.py) | Implement a custom history provider by extending `HistoryProvider`, enabling conversation persistence in your preferred storage backend. |
 | [`cosmos_history_provider.py`](cosmos_history_provider.py) | Use Azure Cosmos DB as a history provider for durable conversation storage with `CosmosHistoryProvider`. |
+| [`cosmos_history_provider_conversation_persistence.py`](cosmos_history_provider_conversation_persistence.py) | Persist and resume conversations across application restarts using `CosmosHistoryProvider` — serialize session state, restore it, and continue with full Cosmos DB history. |
+| [`cosmos_history_provider_messages.py`](cosmos_history_provider_messages.py) | Direct message history operations — retrieve stored messages as a transcript, clear session history, and verify data deletion. |
+| [`cosmos_history_provider_sessions.py`](cosmos_history_provider_sessions.py) | Multi-session and multi-tenant management — per-tenant session isolation, `list_sessions()` to enumerate, switch between sessions, and resume specific conversations. |
 | [`redis_history_provider.py`](redis_history_provider.py) | Use Redis as a history provider for persistent conversation history storage across sessions. |
 
 ## Prerequisites
@@ -22,7 +25,7 @@ These samples demonstrate different approaches to managing conversation history
 **For `custom_history_provider.py`:**
 - `OPENAI_API_KEY`: Your OpenAI API key
 
-**For `cosmos_history_provider.py`:**
+**For Cosmos DB samples (`cosmos_history_provider*.py`):**
 - `FOUNDRY_PROJECT_ENDPOINT`: Your Azure AI Foundry project endpoint
 - `FOUNDRY_MODEL`: The Foundry model deployment name
 - `AZURE_COSMOS_ENDPOINT`: Your Azure Cosmos DB account endpoint