* 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 โ ChatResponse.from_updates
- ChatResponse.from_chat_response_generator โ ChatResponse.from_update_generator
- AgentResponse.from_agent_run_response_updates โ 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
Multimodal Input Examples
This folder contains examples demonstrating how to send multimodal content (images, audio, PDF files) to AI agents using the Agent Framework.
Examples
OpenAI Chat Client
- File:
openai_chat_multimodal.py - Description: Shows how to send images, audio, and PDF files to OpenAI's Chat Completions API
- Supported formats: PNG/JPEG images, WAV/MP3 audio, PDF documents
Azure OpenAI Chat Client
- File:
azure_chat_multimodal.py - Description: Shows how to send images to Azure OpenAI Chat Completions API
- Supported formats: PNG/JPEG images (PDF files are NOT supported by Chat Completions API)
Azure OpenAI Responses Client
- File:
azure_responses_multimodal.py - Description: Shows how to send images and PDF files to Azure OpenAI Responses API
- Supported formats: PNG/JPEG images, PDF documents (full multimodal support)
Environment Variables
Set the following environment variables before running the examples:
For OpenAI:
OPENAI_API_KEY: Your OpenAI API key
For Azure OpenAI:
AZURE_OPENAI_ENDPOINT: Your Azure OpenAI endpointAZURE_OPENAI_CHAT_DEPLOYMENT_NAME: The name of your Azure OpenAI chat model deploymentAZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME: The name of your Azure OpenAI responses model deployment
Optionally for Azure OpenAI:
AZURE_OPENAI_API_VERSION: The API version to use (default is2024-10-21)AZURE_OPENAI_API_KEY: Your Azure OpenAI API key (if not usingAzureCliCredential)
Note: You can also provide configuration directly in code instead of using environment variables:
# Example: Pass deployment_name directly
client = AzureOpenAIChatClient(
credential=AzureCliCredential(),
deployment_name="your-deployment-name",
endpoint="https://your-resource.openai.azure.com"
)
Authentication
The Azure example uses AzureCliCredential for authentication. Run az login in your terminal before running the example, or replace AzureCliCredential with your preferred authentication method (e.g., provide api_key parameter).
Running the Examples
# Run OpenAI example
python openai_chat_multimodal.py
# Run Azure Chat example (requires az login or API key)
python azure_chat_multimodal.py
# Run Azure Responses example (requires az login or API key)
python azure_responses_multimodal.py
Using Your Own Files
The examples include small embedded test files for demonstration. To use your own files:
Method 1: Data URIs (recommended)
import base64
# Load and encode your file
with open("path/to/your/image.jpg", "rb") as f:
image_data = f.read()
image_base64 = base64.b64encode(image_data).decode('utf-8')
image_uri = f"data:image/jpeg;base64,{image_base64}"
# Use in DataContent
Content.from_uri(
uri=image_uri,
media_type="image/jpeg"
)
Method 2: Raw bytes
# Load raw bytes
with open("path/to/your/image.jpg", "rb") as f:
image_bytes = f.read()
# Use in DataContent
Content.from_data(
data=image_bytes,
media_type="image/jpeg"
)
Supported File Types
| Type | Formats | Notes |
|---|---|---|
| Images | PNG, JPEG, GIF, WebP | Most common image formats |
| Audio | WAV, MP3 | For transcription and analysis |
| Documents | Text extraction and analysis |
API Differences
- OpenAI Chat Completions API: Supports images, audio, and PDF files
- Azure OpenAI Chat Completions API: Supports images only (no PDF/audio file types)
- Azure OpenAI Responses API: Supports images and PDF files (full multimodal support)
Choose the appropriate client based on your multimodal needs and available APIs.