Python: [BREAKING] Types API Review improvements (#3647)

* Replace Role and FinishReason classes with NewType + Literal

- Remove EnumLike metaclass from _types.py
- Replace Role class with NewType('Role', str) + RoleLiteral
- Replace FinishReason class with NewType('FinishReason', str) + FinishReasonLiteral
- Update all usages across codebase to use string literals
- Remove .value access patterns (direct string comparison now works)
- Add backward compatibility for legacy dict serialization format
- Update tests to reflect new string-based types

Addresses #3591, #3615

* Simplify ChatResponse and AgentResponse type hints (#3592)

- Remove overloads from ChatResponse.__init__
- Remove text parameter from ChatResponse.__init__
- Remove | dict[str, Any] from finish_reason and usage_details params
- Remove **kwargs from AgentResponse.__init__
- Both now accept ChatMessage | Sequence[ChatMessage] | None for messages
- Update docstrings and examples to reflect changes
- Fix tests that were using removed kwargs
- Fix Role type hint usage in ag-ui utils

* Remove text parameter from ChatResponseUpdate and AgentResponseUpdate (#3597)

- Remove text parameter from ChatResponseUpdate.__init__
- Remove text parameter from AgentResponseUpdate.__init__
- Remove **kwargs from both update classes
- Simplify contents parameter type to Sequence[Content] | None
- Update all usages to use contents=[Content.from_text(...)] pattern
- Fix imports in test files
- Update docstrings and examples

* Rename from_chat_response_updates to from_updates (#3593)

- ChatResponse.from_chat_response_updates → ChatResponse.from_updates
- ChatResponse.from_chat_response_generator → ChatResponse.from_update_generator
- AgentResponse.from_agent_run_response_updates → AgentResponse.from_updates

* Remove try_parse_value method from ChatResponse and AgentResponse (#3595)

- Remove try_parse_value method from ChatResponse
- Remove try_parse_value method from AgentResponse
- Remove try_parse_value calls from from_updates and from_update_generator methods
- Update samples to use try/except with response.value instead
- Update tests to use response.value pattern
- Users should now use response.value with try/except for safe parsing

* Add agent_id to AgentResponse and clarify author_name documentation (#3596)

- Add agent_id parameter to AgentResponse class
- Document that author_name is on ChatMessage objects, not responses
- Update ChatResponse docstring with author_name note
- Update AgentResponse docstring with author_name note

* Simplify ChatMessage.__init__ signature (#3618)

- Make contents a positional argument accepting Sequence[Content | str]
- Auto-convert strings in contents to TextContent
- Remove overloads, keep text kwarg for backward compatibility with serialization
- Update _parse_content_list to handle string items
- Update all usages across codebase to use new format: ChatMessage("role", ["text"])

* Allow Content as input on run and get_response

- Update prepare_messages and normalize_messages to accept Content
- Update type signatures in _agents.py and _clients.py
- Add tests for Content input handling

* Fix ChatMessage usage across packages and samples

Update all remaining ChatMessage(role=..., text=...) to use new
ChatMessage('role', ['text']) signature.

* Fix Role string usage and response format parsing

- Fix redis provider: remove .value access on string literals
- Fix durabletask ensure_response_format: set _response_format before accessing .value

* Fix ollama .value and ai_model_id issues, handle None in content list

- Fix ollama _chat_client: remove .value on string literals
- Fix ollama _chat_client: rename ai_model_id to model_id
- Fix _parse_content_list: skip None values gracefully

* Fix A2AAgent type signature to include Content

* Fix Role/FinishReason NewType dict annotations and improve test coverage to 95%

* Fix mypy errors for Role/FinishReason NewType usage

* Fix Role.TOOL and Role.ASSISTANT usage in _orchestrator_helpers.py

* Fix Role NewType usage in durabletask _models.py

python/samples/getting_started/agents/azure_ai/azure_ai_basic.py

@@ -4,10 +4,10 @@ import asyncio
 from random import randint
 from typing import Annotated
 
+from agent_framework import tool
 from agent_framework.azure import AzureAIProjectAgentProvider
 from azure.identity.aio import AzureCliCredential
 from pydantic import Field
-from agent_framework import tool
 
 """
 Azure AI Agent Basic Example
@@ -16,6 +16,7 @@ This sample demonstrates basic usage of AzureAIProjectAgentProvider.
 Shows both streaming and non-streaming responses with function tools.
 """
 
+
 # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py.
 @tool(approval_mode="never_require")
 def get_weather(

python/samples/getting_started/agents/azure_ai/azure_ai_provider_methods.py

@@ -5,12 +5,12 @@ import os
 from random import randint
 from typing import Annotated
 
+from agent_framework import tool
 from agent_framework.azure import AzureAIProjectAgentProvider
 from azure.ai.projects.aio import AIProjectClient
 from azure.ai.projects.models import AgentReference, PromptAgentDefinition
 from azure.identity.aio import AzureCliCredential
 from pydantic import Field
-from agent_framework import tool
 
 """
 Azure AI Project Agent Provider Methods Example
@@ -26,6 +26,7 @@ with different configurations, which is efficient for multi-agent scenarios.
 Each method returns a ChatAgent that can be used for conversations.
 """
 
+
 # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py.
 @tool(approval_mode="never_require")
 def get_weather(

python/samples/getting_started/agents/azure_ai/azure_ai_use_latest_version.py

@@ -4,10 +4,10 @@ import asyncio
 from random import randint
 from typing import Annotated
 
+from agent_framework import tool
 from agent_framework.azure import AzureAIProjectAgentProvider
 from azure.identity.aio import AzureCliCredential
 from pydantic import Field
-from agent_framework import tool
 
 """
 Azure AI Agent Latest Version Example
@@ -17,6 +17,7 @@ instead of creating a new agent version on each instantiation. The first call cr
 while subsequent calls with `get_agent()` reuse the latest agent version.
 """
 
+
 # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py.
 @tool(approval_mode="never_require")
 def get_weather(

python/samples/getting_started/agents/azure_ai/azure_ai_with_code_interpreter_file_generation.py

@@ -5,7 +5,6 @@ import asyncio
 from agent_framework import (
     AgentResponseUpdate,
     HostedCodeInterpreterTool,
-    tool,
 )
 from agent_framework.azure import AzureAIProjectAgentProvider
 from azure.identity.aio import AzureCliCredential

python/samples/getting_started/agents/azure_ai/azure_ai_with_existing_conversation.py

@@ -4,11 +4,11 @@ import os
 from random import randint
 from typing import Annotated
 
+from agent_framework import tool
 from agent_framework.azure import AzureAIProjectAgentProvider
 from azure.ai.projects.aio import AIProjectClient
 from azure.identity.aio import AzureCliCredential
 from pydantic import Field
-from agent_framework import tool
 
 """
 Azure AI Agent Existing Conversation Example
@@ -16,6 +16,7 @@ Azure AI Agent Existing Conversation Example
 This sample demonstrates usage of AzureAIProjectAgentProvider with existing conversation created on service side.
 """
 
+
 # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py.
 @tool(approval_mode="never_require")
 def get_weather(

python/samples/getting_started/agents/azure_ai/azure_ai_with_explicit_settings.py

@@ -5,10 +5,10 @@ import os
 from random import randint
 from typing import Annotated
 
+from agent_framework import tool
 from agent_framework.azure import AzureAIProjectAgentProvider
 from azure.identity.aio import AzureCliCredential
 from pydantic import Field
-from agent_framework import tool
 
 """
 Azure AI Agent with Explicit Settings Example
@@ -17,6 +17,7 @@ This sample demonstrates creating Azure AI Agents with explicit configuration
 settings rather than relying on environment variable defaults.
 """
 
+
 # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py.
 @tool(approval_mode="never_require")
 def get_weather(

python/samples/getting_started/agents/azure_ai/azure_ai_with_hosted_mcp.py

@@ -25,10 +25,10 @@ async def handle_approvals_without_thread(query: str, agent: "AgentProtocol") ->
                 f"User Input Request for function from {agent.name}: {user_input_needed.function_call.name}"
                 f" with arguments: {user_input_needed.function_call.arguments}"
             )
-            new_inputs.append(ChatMessage(role="assistant", contents=[user_input_needed]))
+            new_inputs.append(ChatMessage("assistant", [user_input_needed]))
             user_approval = input("Approve function call? (y/n): ")
             new_inputs.append(
-                ChatMessage(role="user", contents=[user_input_needed.to_function_approval_response(user_approval.lower() == "y")])
+                ChatMessage("user", [user_input_needed.to_function_approval_response(user_approval.lower() == "y")])
             )
 
         result = await agent.run(new_inputs, store=False)

python/samples/getting_started/agents/azure_ai/azure_ai_with_response_format.py

@@ -41,12 +41,13 @@ async def main() -> None:
         print(f"User: {query}")
         result = await agent.run(query)
 
-        if release_brief := result.try_parse_value(ReleaseBrief):
+        try:
+            release_brief = result.value
             print("Agent:")
             print(f"Feature: {release_brief.feature}")
             print(f"Benefit: {release_brief.benefit}")
             print(f"Launch date: {release_brief.launch_date}")
-        else:
+        except Exception:
             print(f"Failed to parse response: {result.text}")