Fix ChatMessage API usage in docstrings and source

- Fix ChatMessage positional args in docstrings: _serialization.py, _threads.py, _middleware.py
- Fix ChatMessage in tau2 runner.py
- Fix role comparison in _orchestrator_helpers.py to use .value
- Fix role comparison in _group_chat.py docstring example
- Fix role assertions in test_durable_entities.py to use .value

Author: eavanvalkenburg

.github/workflows/python-merge-tests.yml

@@ -96,8 +96,7 @@ jobs:
         uses: ./.github/actions/azure-functions-integration-setup
         id: azure-functions-setup
       - name: Test with pytest
-        timeout-minutes: 15
-        run: uv run poe all-tests -n logical --dist loadfile --dist worksteal --timeout 60 --timeout_method thread --timeout-verbose --retries 2 --retry-delay 5
+        run: uv run poe all-tests -n logical --dist loadfile --dist worksteal --session-timeout=900 --timeout_method thread --retries 2 --retry-delay 5
         working-directory: ./python
       - name: Test core samples
         timeout-minutes: 10
@@ -154,7 +153,7 @@ jobs:
           subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}
       - name: Test with pytest
         timeout-minutes: 15
-        run: uv run --directory packages/azure-ai poe integration-tests -n logical --dist loadfile --dist worksteal --timeout 60 --timeout_method thread --timeout-verbose --retries 2 --retry-delay 5
+        run: uv run --directory packages/azure-ai poe integration-tests -n logical --dist loadfile --dist worksteal --session-timeout=900 --timeout_method thread --retries 2 --retry-delay 5
         working-directory: ./python
       - name: Test Azure AI samples
         timeout-minutes: 10

python/packages/core/agent_framework/_middleware.py

@@ -490,7 +490,7 @@ async def process(self, context: ChatContext, next):
                     # Add system prompt to messages
                     from agent_framework import ChatMessage
 
-                    context.messages.insert(0, ChatMessage("system", [self.system_prompt]))
+                    context.messages.insert(0, ChatMessage(role="system", text=self.system_prompt))
 
                     # Continue execution
                     await next(context)

python/packages/core/agent_framework/_serialization.py

@@ -38,7 +38,7 @@ class SerializationProtocol(Protocol):
 
 
             # ChatMessage implements SerializationProtocol via SerializationMixin
-            user_msg = ChatMessage("user", ["What's the weather like today?"])
+            user_msg = ChatMessage(role="user", text="What's the weather like today?")
 
             # Serialize to dictionary - automatic type identification and nested serialization
             msg_dict = user_msg.to_dict()
@@ -175,8 +175,8 @@ class SerializationMixin:
             # ChatMessageStoreState handles nested ChatMessage serialization
             store_state = ChatMessageStoreState(
                 messages=[
-                    ChatMessage("user", ["Hello agent"]),
-                    ChatMessage("assistant", ["Hi! How can I help?"]),
+                    ChatMessage(role="user", text="Hello agent"),
+                    ChatMessage(role="assistant", text="Hi! How can I help?"),
                 ]
             )
 

python/packages/core/agent_framework/_threads.py

@@ -202,7 +202,7 @@ class ChatMessageStore:
             store = ChatMessageStore()
 
             # Add messages
-            message = ChatMessage("user", ["Hello"])
+            message = ChatMessage(role="user", text="Hello")
             await store.add_messages([message])
 
             # Retrieve messages

python/packages/core/agent_framework/_workflows/_group_chat.py

@@ -782,7 +782,9 @@ def with_termination_condition(self, termination_condition: TerminationCondition
 
 
             def stop_after_two_calls(conversation: list[ChatMessage]) -> bool:
-                calls = sum(1 for msg in conversation if msg.role == "assistant" and msg.author_name == "specialist")
+                calls = sum(
+                    1 for msg in conversation if msg.role.value == "assistant" and msg.author_name == "specialist"
+                )
                 return calls >= 2
 
 

python/packages/lab/tau2/agent_framework_lab_tau2/runner.py

@@ -338,11 +338,11 @@ async def run(
         # Matches tau2's expected conversation start pattern
         logger.info(f"Starting workflow with hardcoded greeting: '{DEFAULT_FIRST_AGENT_MESSAGE}'")
 
-        first_message = ChatMessage("assistant", text=DEFAULT_FIRST_AGENT_MESSAGE)
+        first_message = ChatMessage(role="assistant", text=DEFAULT_FIRST_AGENT_MESSAGE)
         initial_greeting = AgentExecutorResponse(
             executor_id=ASSISTANT_AGENT_ID,
             agent_response=AgentResponse(messages=[first_message]),
-            full_conversation=[ChatMessage("assistant", text=DEFAULT_FIRST_AGENT_MESSAGE)],
+            full_conversation=[ChatMessage(role="assistant", text=DEFAULT_FIRST_AGENT_MESSAGE)],
         )
 
         # STEP 4: Execute the workflow and collect results