Eduard van Valkenburg
838a7fd61d
* 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
These are common instructions for setting up your environment for every sample in this directory. These samples illustrate the Durable extensibility for Agent Framework running in Azure Functions.
All of these samples are set up to run in Azure Functions. Azure Functions has a local development tool called CoreTools which we will set up to run these samples locally.
Environment Setup
1. Install dependencies and create appropriate services
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Install Azure Functions Core Tools 4.x
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Install Azurite storage emulator
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Create an Azure OpenAI resource. Note the Azure OpenAI endpoint, deployment name, and the key (or ensure you can authenticate with
AzureCliCredential). -
Install a tool to execute HTTP calls, for example the REST Client extension
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[Optionally] Create an Azure Function Python app to later deploy your app to Azure if you so desire.
2. Create and activate a virtual environment
Windows (PowerShell):
python -m venv .venv
.venv\Scripts\Activate.ps1
Linux/macOS:
python -m venv .venv
source .venv/bin/activate
3. Running the samples
-
Inside each sample:
-
Install Python dependencies – from the sample directory, run
pip install -r requirements.txt(or the equivalent in your active virtual environment). -
Copy
local.settings.json.templatetolocal.settings.json, then updateAZURE_OPENAI_ENDPOINTandAZURE_OPENAI_CHAT_DEPLOYMENT_NAMEfor Azure OpenAI authentication. The samples useAzureCliCredentialby default, so ensure you're logged in viaaz login.- Alternatively, you can use API key authentication by setting
AZURE_OPENAI_API_KEYand updating the code to useAzureOpenAIChatClient()without the credential parameter. - Keep
TASKHUB_NAMEset todefaultunless you plan to change the durable task hub name.
- Alternatively, you can use API key authentication by setting
-
Run the command
func startfrom the root of the sample -
Follow each sample's README for scenario-specific steps, and use its
demo.httpfile (or provided curl examples) to trigger the hosted HTTP endpoints.
-