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Python: [Breaking] Simplified Content types to a single class with classmethod constructors. (#3252)

Browse Source 
* ported Content to a new model

* fixed linting

* fixes

* fixed data format handling

* fix for 3.10 mypy

* fix

* fix int test
This commit is contained in:
Eduard van Valkenburg
2026-01-20 23:09:39 +01:00
committed by GitHub
Unverified
parent 73761aa4a3
commit 83e6229c11
132 changed files with 3949 additions and 4741 deletions
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python/packages/devui/agent_framework_devui/_conversations.py
+1 -1
View File
@@ -321,7 +321,7 @@ class InMemoryConversationStore(ConversationStore):
# Convert ChatMessage contents to OpenAI TextContent format
message_content = []
for content_item in msg.contents:
if hasattr(content_item, "type") and content_item.type == "text":
if content_item.type == "text":
# Extract text from TextContent object
text_value = getattr(content_item, "text", "")
message_content.append(TextContent(type="text", text=text_value))
python/packages/devui/agent_framework_devui/_executor.py
+13 -19
View File
@@ -7,7 +7,7 @@ import logging
from collections.abc import AsyncGenerator
from typing import Any
from agent_framework import AgentProtocol
from agent_framework import AgentProtocol, Content
from agent_framework._workflows._events import RequestInfoEvent
from ._conversations import ConversationStore, InMemoryConversationStore
@@ -602,7 +602,7 @@ class AgentFrameworkExecutor:
"""
# Import Agent Framework types
try:
from agent_framework import ChatMessage, DataContent, Role, TextContent
from agent_framework import ChatMessage, Role
except ImportError:
# Fallback to string extraction if Agent Framework not available
return self._extract_user_message_fallback(input_data)
@@ -613,14 +613,12 @@ class AgentFrameworkExecutor:
# Handle OpenAI ResponseInputParam (List[ResponseInputItemParam])
if isinstance(input_data, list):
return self._convert_openai_input_to_chat_message(input_data, ChatMessage, TextContent, DataContent, Role)
return self._convert_openai_input_to_chat_message(input_data, ChatMessage, Role)
# Fallback for other formats
return self._extract_user_message_fallback(input_data)
def _convert_openai_input_to_chat_message(
self, input_items: list[Any], ChatMessage: Any, TextContent: Any, DataContent: Any, Role: Any
) -> Any:
def _convert_openai_input_to_chat_message(self, input_items: list[Any], ChatMessage: Any, Role: Any) -> Any:
"""Convert OpenAI ResponseInputParam to Agent Framework ChatMessage.
Processes text, images, files, and other content types from OpenAI format
@@ -629,14 +627,12 @@ class AgentFrameworkExecutor:
Args:
input_items: List of OpenAI ResponseInputItemParam objects (dicts or objects)
ChatMessage: ChatMessage class for creating chat messages
TextContent: TextContent class for text content
DataContent: DataContent class for data/media content
Role: Role enum for message roles
Returns:
ChatMessage with converted content
"""
contents = []
contents: list[Content] = []
# Process each input item
for item in input_items:
@@ -649,7 +645,7 @@ class AgentFrameworkExecutor:
# Handle both string content and list content
if isinstance(message_content, str):
contents.append(TextContent(text=message_content))
contents.append(Content.from_text(text=message_content))
elif isinstance(message_content, list):
for content_item in message_content:
# Handle dict content items
@@ -658,7 +654,7 @@ class AgentFrameworkExecutor:
if content_type == "input_text":
text = content_item.get("text", "")
contents.append(TextContent(text=text))
contents.append(Content.from_text(text=text))
elif content_type == "input_image":
image_url = content_item.get("image_url", "")
@@ -676,7 +672,7 @@ class AgentFrameworkExecutor:
media_type = "image/png"
else:
media_type = "image/png"
contents.append(DataContent(uri=image_url, media_type=media_type))
contents.append(Content.from_uri(uri=image_url, media_type=media_type))
elif content_type == "input_file":
# Handle file input
@@ -710,7 +706,7 @@ class AgentFrameworkExecutor:
# Assume file_data is base64, create data URI
data_uri = f"data:{media_type};base64,{file_data}"
contents.append(
DataContent(
Content.from_uri(
uri=data_uri,
media_type=media_type,
additional_properties=additional_props,
@@ -718,7 +714,7 @@ class AgentFrameworkExecutor:
)
elif file_url:
contents.append(
DataContent(
Content.from_uri(
uri=file_url,
media_type=media_type,
additional_properties=additional_props,
@@ -728,21 +724,19 @@ class AgentFrameworkExecutor:
elif content_type == "function_approval_response":
# Handle function approval response (DevUI extension)
try:
from agent_framework import FunctionApprovalResponseContent, FunctionCallContent
request_id = content_item.get("request_id", "")
approved = content_item.get("approved", False)
function_call_data = content_item.get("function_call", {})
# Create FunctionCallContent from the function_call data
function_call = FunctionCallContent(
function_call = Content.from_function_call(
call_id=function_call_data.get("id", ""),
name=function_call_data.get("name", ""),
arguments=function_call_data.get("arguments", {}),
)
# Create FunctionApprovalResponseContent with correct signature
approval_response = FunctionApprovalResponseContent(
approval_response = Content.from_function_approval_response(
approved, # positional argument
id=request_id, # keyword argument 'id', NOT 'request_id'
function_call=function_call, # FunctionCallContent object
@@ -764,7 +758,7 @@ class AgentFrameworkExecutor:
# If no contents found, create a simple text message
if not contents:
contents.append(TextContent(text=""))
contents.append(Content.from_text(text=""))
chat_message = ChatMessage(role=Role.USER, contents=contents)
python/packages/devui/agent_framework_devui/_mapper.py
+27 -33
View File
@@ -12,7 +12,7 @@ from datetime import datetime
from typing import Any, Union
from uuid import uuid4
from agent_framework import ChatMessage, TextContent
from agent_framework import ChatMessage, Content
from openai.types.responses import (
Response,
ResponseContentPartAddedEvent,
@@ -92,7 +92,7 @@ def _serialize_content_recursive(value: Any) -> Any:
if isinstance(value, (list, tuple)):
serialized = [_serialize_content_recursive(item) for item in value]
# For single-item lists containing text Content, extract just the text
# This handles the MCP case where result = [TextContent(text="Hello")]
# This handles the MCP case where result = [Content.from_text(text="Hello")]
# and we want output = "Hello" not output = '[{"type": "text", "text": "Hello"}]'
if len(serialized) == 1 and isinstance(serialized[0], dict) and serialized[0].get("type") == "text":
return serialized[0].get("text", "")
@@ -127,18 +127,18 @@ class MessageMapper:
# Register content type mappers for all 12 Agent Framework content types
self.content_mappers = {
"TextContent": self._map_text_content,
"TextReasoningContent": self._map_reasoning_content,
"FunctionCallContent": self._map_function_call_content,
"FunctionResultContent": self._map_function_result_content,
"ErrorContent": self._map_error_content,
"UsageContent": self._map_usage_content,
"DataContent": self._map_data_content,
"UriContent": self._map_uri_content,
"HostedFileContent": self._map_hosted_file_content,
"HostedVectorStoreContent": self._map_hosted_vector_store_content,
"FunctionApprovalRequestContent": self._map_approval_request_content,
"FunctionApprovalResponseContent": self._map_approval_response_content,
"text": self._map_text_content,
"text_reasoning": self._map_reasoning_content,
"function_call": self._map_function_call_content,
"function_result": self._map_function_result_content,
"error": self._map_error_content,
"usage": self._map_usage_content,
"data": self._map_data_content,
"uri": self._map_uri_content,
"hosted_file": self._map_hosted_file_content,
"hosted_vector_store": self._map_hosted_vector_store_content,
"function_approval_request": self._map_approval_request_content,
"function_approval_response": self._map_approval_response_content,
}
async def convert_event(self, raw_event: Any, request: AgentFrameworkRequest) -> Sequence[Any]:
@@ -603,7 +603,7 @@ class MessageMapper:
return events
# Check if we're streaming text content
has_text_content = any(isinstance(content, TextContent) for content in update.contents)
has_text_content = any(content.type == "text" for content in update.contents)
# Check if we're in an executor context with an existing item
executor_id = context.get("current_executor_id")
@@ -647,10 +647,8 @@ class MessageMapper:
# Process each content item
for content in update.contents:
content_type = content.__class__.__name__
# Special handling for TextContent to use proper delta events
if content_type == "TextContent" and "current_message_id" in context:
if content.type == "text" and "current_message_id" in context:
# Stream text content via proper delta events
events.append(
ResponseTextDeltaEvent(
@@ -663,9 +661,9 @@ class MessageMapper:
sequence_number=self._next_sequence(context),
)
)
elif content_type in self.content_mappers:
elif content.type in self.content_mappers:
# Use existing mappers for other content types
mapped_events = await self.content_mappers[content_type](content, context)
mapped_events = await self.content_mappers[content.type](content, context)
if mapped_events is not None: # Handle None returns (e.g., UsageContent)
if isinstance(mapped_events, list):
events.extend(mapped_events)
@@ -676,7 +674,7 @@ class MessageMapper:
events.append(await self._create_unknown_content_event(content, context))
# Don't increment content_index for text deltas within the same part
if content_type != "TextContent":
if content.type != "text":
context["content_index"] = context.get("content_index", 0) + 1
except Exception as e:
@@ -708,10 +706,8 @@ class MessageMapper:
for message in messages:
if hasattr(message, "contents") and message.contents:
for content in message.contents:
content_type = content.__class__.__name__
if content_type in self.content_mappers:
mapped_events = await self.content_mappers[content_type](content, context)
if content.type in self.content_mappers:
mapped_events = await self.content_mappers[content.type](content, context)
if mapped_events is not None: # Handle None returns (e.g., UsageContent)
if isinstance(mapped_events, list):
events.extend(mapped_events)
@@ -726,9 +722,7 @@ class MessageMapper:
# Add usage information if present
usage_details = getattr(response, "usage_details", None)
if usage_details:
from agent_framework import UsageContent
usage_content = UsageContent(details=usage_details)
usage_content = Content.from_usage(usage_details=usage_details)
await self._map_usage_content(usage_content, context)
# Note: _map_usage_content returns None - it accumulates usage for final Response.usage
@@ -1421,11 +1415,11 @@ class MessageMapper:
Returns:
None - no event emitted (usage goes in final Response.usage)
"""
# Extract usage from UsageContent.details (UsageDetails object)
details = getattr(content, "details", None)
total_tokens = getattr(details, "total_token_count", 0) or 0
prompt_tokens = getattr(details, "input_token_count", 0) or 0
completion_tokens = getattr(details, "output_token_count", 0) or 0
# Extract usage from UsageContent.usage_details (UsageDetails object)
details = content.usage_details or {}
total_tokens = details.get("total_token_count", 0)
prompt_tokens = details.get("input_token_count", 0)
completion_tokens = details.get("output_token_count", 0)
# Accumulate for final Response.usage
request_id = context.get("request_id", "default")
python/packages/devui/frontend/src/types/agent-framework.ts
+7 -7
View File
@@ -187,7 +187,7 @@ export interface HostedVectorStoreContent extends BaseContent {
}
// Union type for all content
export type Contents =
export type Content =
| TextContent
| FunctionCallContent
| FunctionResultContent
@@ -209,7 +209,7 @@ export interface UsageDetails {
// Agent run response update (streaming)
export interface AgentResponseUpdate {
contents: Contents[];
contents: Content[];
role?: Role;
author_name?: string;
response_id?: string;
@@ -233,7 +233,7 @@ export interface AgentResponse {
// Chat message
export interface ChatMessage {
contents: Contents[];
contents: Content[];
role?: Role;
author_name?: string;
message_id?: string;
@@ -244,7 +244,7 @@ export interface ChatMessage {
// Chat response update (model client streaming)
export interface ChatResponseUpdate {
contents: Contents[];
contents: Content[];
role?: Role;
author_name?: string;
response_id?: string;
@@ -330,18 +330,18 @@ export interface TraceSpan {
}
// Helper type guards for Agent Framework content types
export function isTextContent(content: Contents): content is TextContent {
export function isTextContent(content: Content): content is TextContent {
return content.type === "text";
}
export function isFunctionCallContent(
content: Contents
content: Content
): content is FunctionCallContent {
return content.type === "function_call";
}
export function isFunctionResultContent(
content: Contents
content: Content
): content is FunctionResultContent {
return content.type === "function_result";
}
python/packages/devui/frontend/src/types/index.ts
+1 -1
View File
@@ -188,7 +188,7 @@ export interface MetaResponse {
export interface ChatMessage {
id: string;
role: "user" | "assistant" | "system" | "tool";
contents: import("./agent-framework").Contents[];
contents: import("./agent-framework").Content[];
timestamp: string;
streaming?: boolean;
author_name?: string;
python/packages/devui/tests/test_cleanup_hooks.py
+4 -4
View File
@@ -7,7 +7,7 @@ import tempfile
from pathlib import Path
import pytest
from agent_framework import AgentResponse, ChatMessage, Role, TextContent
from agent_framework import AgentResponse, ChatMessage, Content, Role
from agent_framework_devui import register_cleanup
from agent_framework_devui._discovery import EntityDiscovery
@@ -36,7 +36,7 @@ class MockAgent:
async def run_stream(self, messages=None, *, thread=None, **kwargs):
"""Mock streaming run method."""
yield AgentResponse(
messages=[ChatMessage(role=Role.ASSISTANT, contents=[TextContent(text="Test response")])],
messages=[ChatMessage(role=Role.ASSISTANT, contents=[Content.from_text(text="Test response")])],
)
@@ -259,7 +259,7 @@ async def test_cleanup_with_file_based_discovery():
# Write agent module with cleanup registration
agent_file = agent_dir / "__init__.py"
agent_file.write_text("""
from agent_framework import AgentResponse, ChatMessage, Role, TextContent
from agent_framework import AgentResponse, ChatMessage, Role, Content
from agent_framework_devui import register_cleanup
class MockCredential:
@@ -279,7 +279,7 @@ class TestAgent:
async def run_stream(self, messages=None, *, thread=None, **kwargs):
yield AgentResponse(
messages=[ChatMessage(role=Role.ASSISTANT, content=[TextContent(text="Test")])],
messages=[ChatMessage(role=Role.ASSISTANT, content=[Content.from_text(text="Test")])],
inner_messages=[],
)
python/packages/devui/tests/test_discovery.py
+3 -3
View File
@@ -84,7 +84,7 @@ async def test_discovery_accepts_agents_with_only_run():
init_file = agent_dir / "__init__.py"
init_file.write_text("""
from agent_framework import AgentResponse, AgentThread, ChatMessage, Role, TextContent
from agent_framework import AgentResponse, AgentThread, ChatMessage, Role, Content
class NonStreamingAgent:
id = "non_streaming"
@@ -95,7 +95,7 @@ class NonStreamingAgent:
return AgentResponse(
messages=[ChatMessage(
role=Role.ASSISTANT,
contents=[TextContent(text="response")]
contents=[Content.from_text(text="response")]
)],
response_id="test"
)
@@ -210,7 +210,7 @@ class TestAgent:
async def run(self, messages=None, *, thread=None, **kwargs):
return AgentResponse(
messages=[ChatMessage(role=Role.ASSISTANT, contents=[TextContent(text="test")])],
messages=[ChatMessage(role=Role.ASSISTANT, contents=[Content.from_text(text="test")])],
response_id="test"
)
python/packages/devui/tests/test_execution.py
+4 -2
View File
@@ -566,7 +566,7 @@ def test_extract_workflow_hil_responses_handles_stringified_json():
async def test_executor_handles_non_streaming_agent():
"""Test executor can handle agents with only run() method (no run_stream)."""
from agent_framework import AgentResponse, AgentThread, ChatMessage, Role, TextContent
from agent_framework import AgentResponse, AgentThread, ChatMessage, Content, Role
class NonStreamingAgent:
"""Agent with only run() method - does NOT satisfy full AgentProtocol."""
@@ -577,7 +577,9 @@ async def test_executor_handles_non_streaming_agent():
async def run(self, messages=None, *, thread=None, **kwargs):
return AgentResponse(
messages=[ChatMessage(role=Role.ASSISTANT, contents=[TextContent(text=f"Processed: {messages}")])],
messages=[
ChatMessage(role=Role.ASSISTANT, contents=[Content.from_text(text=f"Processed: {messages}")])
],
response_id="test_123",
)
python/packages/devui/tests/test_helpers.py
+15 -17
View File
@@ -28,11 +28,9 @@ from agent_framework import (
ChatResponse,
ChatResponseUpdate,
ConcurrentBuilder,
FunctionCallContent,
FunctionResultContent,
Content,
Role,
SequentialBuilder,
TextContent,
use_chat_middleware,
)
from agent_framework._clients import TOptions_co
@@ -93,7 +91,7 @@ class MockChatClient:
for update in self.streaming_responses.pop(0):
yield update
else:
yield ChatResponseUpdate(text=TextContent(text="test streaming response"), role="assistant")
yield ChatResponseUpdate(text=Content.from_text(text="test streaming response"), role="assistant")
@use_chat_middleware
@@ -141,10 +139,10 @@ class MockBaseChatClient(BaseChatClient[TOptions_co], Generic[TOptions_co]):
yield update
else:
# Simulate realistic streaming chunks
yield ChatResponseUpdate(text=TextContent(text="Mock "), role="assistant")
yield ChatResponseUpdate(text=TextContent(text="streaming "), role="assistant")
yield ChatResponseUpdate(text=TextContent(text="response "), role="assistant")
yield ChatResponseUpdate(text=TextContent(text="from ChatAgent"), role="assistant")
yield ChatResponseUpdate(text=Content.from_text(text="Mock "), role="assistant")
yield ChatResponseUpdate(text=Content.from_text(text="streaming "), role="assistant")
yield ChatResponseUpdate(text=Content.from_text(text="response "), role="assistant")
yield ChatResponseUpdate(text=Content.from_text(text="from ChatAgent"), role="assistant")
# =============================================================================
@@ -175,7 +173,7 @@ class MockAgent(BaseAgent):
) -> AgentResponse:
self.call_count += 1
return AgentResponse(
messages=[ChatMessage(role=Role.ASSISTANT, contents=[TextContent(text=self.response_text)])]
messages=[ChatMessage(role=Role.ASSISTANT, contents=[Content.from_text(text=self.response_text)])]
)
async def run_stream(
@@ -187,7 +185,7 @@ class MockAgent(BaseAgent):
) -> AsyncIterable[AgentResponseUpdate]:
self.call_count += 1
for chunk in self.streaming_chunks:
yield AgentResponseUpdate(contents=[TextContent(text=chunk)], role=Role.ASSISTANT)
yield AgentResponseUpdate(contents=[Content.from_text(text=chunk)], role=Role.ASSISTANT)
class MockToolCallingAgent(BaseAgent):
@@ -217,13 +215,13 @@ class MockToolCallingAgent(BaseAgent):
self.call_count += 1
# First: text
yield AgentResponseUpdate(
contents=[TextContent(text="Let me search for that...")],
contents=[Content.from_text(text="Let me search for that...")],
role=Role.ASSISTANT,
)
# Second: tool call
yield AgentResponseUpdate(
contents=[
FunctionCallContent(
Content.from_function_call(
call_id="call_123",
name="search",
arguments={"query": "weather"},
@@ -234,7 +232,7 @@ class MockToolCallingAgent(BaseAgent):
# Third: tool result
yield AgentResponseUpdate(
contents=[
FunctionResultContent(
Content.from_function_result(
call_id="call_123",
result={"temperature": 72, "condition": "sunny"},
)
@@ -243,7 +241,7 @@ class MockToolCallingAgent(BaseAgent):
)
# Fourth: final text
yield AgentResponseUpdate(
contents=[TextContent(text="The weather is sunny, 72°F.")],
contents=[Content.from_text(text="The weather is sunny, 72°F.")],
role=Role.ASSISTANT,
)
@@ -297,7 +295,7 @@ def create_mock_tool_agent(id: str = "tool_agent", name: str = "ToolAgent") -> M
def create_agent_run_response(text: str = "Test response") -> AgentResponse:
"""Create an AgentResponse with the given text."""
return AgentResponse(messages=[ChatMessage(role=Role.ASSISTANT, contents=[TextContent(text=text)])])
return AgentResponse(messages=[ChatMessage(role=Role.ASSISTANT, contents=[Content.from_text(text=text)])])
def create_agent_executor_response(
@@ -310,8 +308,8 @@ def create_agent_executor_response(
executor_id=executor_id,
agent_response=agent_response,
full_conversation=[
ChatMessage(role=Role.USER, contents=[TextContent(text="User input")]),
ChatMessage(role=Role.ASSISTANT, contents=[TextContent(text=response_text)]),
ChatMessage(role=Role.USER, contents=[Content.from_text(text="User input")]),
ChatMessage(role=Role.ASSISTANT, contents=[Content.from_text(text=response_text)]),
],
)
python/packages/devui/tests/test_mapper.py
+19 -20
View File
@@ -14,11 +14,8 @@ import pytest
# Import Agent Framework types
from agent_framework._types import (
AgentResponseUpdate,
ErrorContent,
FunctionCallContent,
FunctionResultContent,
Content,
Role,
TextContent,
)
# Import real workflow event classes - NOT mocks!
@@ -71,15 +68,17 @@ def test_request() -> AgentFrameworkRequest:
def create_test_content(content_type: str, **kwargs: Any) -> Any:
"""Create test content objects."""
if content_type == "text":
return TextContent(text=kwargs.get("text", "Hello, world!"))
return Content.from_text(text=kwargs.get("text", "Hello, world!"))
if content_type == "function_call":
return FunctionCallContent(
return Content.from_function_call(
call_id=kwargs.get("call_id", "test_call_id"),
name=kwargs.get("name", "test_func"),
arguments=kwargs.get("arguments", {"param": "value"}),
)
if content_type == "error":
return ErrorContent(message=kwargs.get("message", "Test error"), error_code=kwargs.get("code", "test_error"))
return Content.from_error(
message=kwargs.get("message", "Test error"), error_code=kwargs.get("code", "test_error")
)
raise ValueError(f"Unknown content type: {content_type}")
@@ -162,7 +161,7 @@ async def test_function_result_content_with_string_result(
mapper: MessageMapper, test_request: AgentFrameworkRequest
) -> None:
"""Test FunctionResultContent with plain string result (regular tools)."""
content = FunctionResultContent(
content = Content.from_function_result(
call_id="test_call_123",
result="Hello, World!",
)
@@ -182,9 +181,9 @@ async def test_function_result_content_with_nested_content_objects(
mapper: MessageMapper, test_request: AgentFrameworkRequest
) -> None:
"""Test FunctionResultContent with nested Content objects (MCP tools case)."""
content = FunctionResultContent(
content = Content.from_function_result(
call_id="mcp_call_456",
result=[TextContent(text="Hello from MCP!")],
result=[Content.from_text(text="Hello from MCP!")],
)
update = create_test_agent_update([content])
@@ -451,12 +450,12 @@ async def test_magentic_agent_run_update_event_with_agent_delta_metadata(
This tests the ACTUAL event format Magentic emits - not a fake MagenticAgentDeltaEvent class.
Magentic uses AgentRunUpdateEvent with additional_properties containing magentic_event_type.
"""
from agent_framework._types import AgentResponseUpdate, Role, TextContent
from agent_framework._types import AgentResponseUpdate, Role
from agent_framework._workflows._events import AgentRunUpdateEvent
# Create the REAL event format that Magentic emits
update = AgentResponseUpdate(
contents=[TextContent(text="Hello from agent")],
contents=[Content.from_text(text="Hello from agent")],
role=Role.ASSISTANT,
author_name="Writer",
additional_properties={
@@ -482,12 +481,12 @@ async def test_magentic_orchestrator_message_event(mapper: MessageMapper, test_r
Magentic emits orchestrator planning/instruction messages using AgentRunUpdateEvent
with additional_properties containing magentic_event_type='orchestrator_message'.
"""
from agent_framework._types import AgentResponseUpdate, Role, TextContent
from agent_framework._types import AgentResponseUpdate, Role
from agent_framework._workflows._events import AgentRunUpdateEvent
# Create orchestrator message event (REAL format from Magentic)
update = AgentResponseUpdate(
contents=[TextContent(text="Planning: First, the writer will create content...")],
contents=[Content.from_text(text="Planning: First, the writer will create content...")],
role=Role.ASSISTANT,
author_name="Orchestrator",
additional_properties={
@@ -518,20 +517,20 @@ async def test_magentic_events_use_same_event_class_as_other_workflows(
additional_properties. Any mapper code checking for 'MagenticAgentDeltaEvent'
class names is dead code.
"""
from agent_framework._types import AgentResponseUpdate, Role, TextContent
from agent_framework._types import AgentResponseUpdate, Role
from agent_framework._workflows._events import AgentRunUpdateEvent
# Create events the way different workflows do it
# 1. Regular workflow (no additional_properties)
regular_update = AgentResponseUpdate(
contents=[TextContent(text="Regular workflow response")],
contents=[Content.from_text(text="Regular workflow response")],
role=Role.ASSISTANT,
)
regular_event = AgentRunUpdateEvent(executor_id="regular_executor", data=regular_update)
# 2. Magentic workflow (with additional_properties)
magentic_update = AgentResponseUpdate(
contents=[TextContent(text="Magentic workflow response")],
contents=[Content.from_text(text="Magentic workflow response")],
role=Role.ASSISTANT,
additional_properties={"magentic_event_type": "agent_delta"},
)
@@ -599,13 +598,13 @@ async def test_workflow_output_event(mapper: MessageMapper, test_request: AgentF
async def test_workflow_output_event_with_list_data(mapper: MessageMapper, test_request: AgentFrameworkRequest) -> None:
"""Test WorkflowOutputEvent with list data (common for sequential/concurrent workflows)."""
from agent_framework import ChatMessage, Role, TextContent
from agent_framework import ChatMessage, Role
from agent_framework._workflows._events import WorkflowOutputEvent
# Sequential/Concurrent workflows often output list[ChatMessage]
messages = [
ChatMessage(role=Role.USER, contents=[TextContent(text="Hello")]),
ChatMessage(role=Role.ASSISTANT, contents=[TextContent(text="World")]),
ChatMessage(role=Role.USER, contents=[Content.from_text(text="Hello")]),
ChatMessage(role=Role.ASSISTANT, contents=[Content.from_text(text="World")]),
]
event = WorkflowOutputEvent(data=messages, executor_id="complete")
events = await mapper.convert_event(event, test_request)
python/packages/devui/tests/test_multimodal_workflow.py
+6 -6
View File
@@ -49,7 +49,7 @@ class TestMultimodalWorkflowInput:
def test_convert_openai_input_to_chat_message_with_image(self):
"""Test that OpenAI format with image is converted to ChatMessage with DataContent."""
from agent_framework import ChatMessage, DataContent, Role, TextContent
from agent_framework import ChatMessage, Role
discovery = MagicMock(spec=EntityDiscovery)
mapper = MagicMock(spec=MessageMapper)
@@ -78,11 +78,11 @@ class TestMultimodalWorkflowInput:
assert len(result.contents) == 2, f"Expected 2 contents, got {len(result.contents)}"
# First content should be text
assert isinstance(result.contents[0], TextContent)
assert result.contents[0].type == "text"
assert result.contents[0].text == "Describe this image"
# Second content should be image (DataContent)
assert isinstance(result.contents[1], DataContent)
assert result.contents[1].type == "data"
assert result.contents[1].media_type == "image/png"
assert result.contents[1].uri == TEST_IMAGE_DATA_URI
@@ -90,7 +90,7 @@ class TestMultimodalWorkflowInput:
"""Test that _parse_workflow_input correctly handles JSON string with multimodal content."""
import asyncio
from agent_framework import ChatMessage, DataContent, TextContent
from agent_framework import ChatMessage
discovery = MagicMock(spec=EntityDiscovery)
mapper = MagicMock(spec=MessageMapper)
@@ -120,11 +120,11 @@ class TestMultimodalWorkflowInput:
assert len(result.contents) == 2
# Verify text content
assert isinstance(result.contents[0], TextContent)
assert result.contents[0].type == "text"
assert result.contents[0].text == "What is in this image?"
# Verify image content
assert isinstance(result.contents[1], DataContent)
assert result.contents[1].type == "data"
assert result.contents[1].media_type == "image/png"
def test_parse_workflow_input_still_handles_simple_dict(self):