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https://github.com/microsoft/agent-framework.git
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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
This commit is contained in:
Eduard van Valkenburg
committed by
GitHub
Unverified
GitHub
parent
ef798629e5
commit
838a7fd61d
@@ -70,7 +70,7 @@ def search_hotels(
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"availability": "Available"
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}
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]
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return json.dumps({
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"location": location,
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"check_in": check_in,
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@@ -140,7 +140,7 @@ def get_hotel_details(
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"nearby_attractions": ["Eiffel Tower (0.2 mi)", "Seine River Cruise Dock (0.3 mi)", "Trocadéro (0.5 mi)"]
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}
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}
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details = hotel_details.get(hotel_name, {
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"name": hotel_name,
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"description": "Comfortable hotel with modern amenities",
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@@ -150,7 +150,7 @@ def get_hotel_details(
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"reviews": {"total": 0, "recent_comments": []},
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"nearby_attractions": []
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})
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return json.dumps({
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"hotel_name": hotel_name,
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"details": details
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@@ -270,7 +270,7 @@ def search_flights(
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"stops": "Nonstop"
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}
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]
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return json.dumps({
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"origin": origin,
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"destination": destination,
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@@ -317,7 +317,7 @@ def get_flight_details(
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},
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"amenities": ["WiFi", "In-flight entertainment", "Meals included"]
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}
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return json.dumps({
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"flight_details": mock_details
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})
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@@ -439,7 +439,7 @@ def search_activities(
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"booking_required": False
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}
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]
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if category:
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activities = [act for act in all_activities if act["category"] == category]
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else:
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@@ -456,7 +456,7 @@ def search_activities(
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"availability": "Daily at 10:00 AM and 2:00 PM"
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}
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]
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return json.dumps({
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"location": location,
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"date": date,
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@@ -523,7 +523,7 @@ def get_activity_details(
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"reviews_count": 2341
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}
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}
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details = activity_details_map.get(activity_name, {
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"name": activity_name,
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"description": "An immersive experience that showcases the best of local culture and attractions.",
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@@ -538,7 +538,7 @@ def get_activity_details(
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"rating": 4.5,
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"reviews_count": 100
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})
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return json.dumps({
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"activity_details": details
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})
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@@ -558,7 +558,7 @@ def confirm_booking(
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booking status, customer information, and next steps.
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"""
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confirmation_number = f"CONF-{booking_type.upper()}-{booking_id}"
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confirmation_data = {
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"confirmation_number": confirmation_number,
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"booking_type": booking_type,
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@@ -572,7 +572,7 @@ def confirm_booking(
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"Bring confirmation number and valid ID"
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]
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}
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return json.dumps({
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"confirmation": confirmation_data
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})
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@@ -595,7 +595,7 @@ def check_hotel_availability(
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and last checked timestamp.
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"""
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availability_status = "Available"
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availability_data = {
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"service_type": "hotel",
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"hotel_name": hotel_name,
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@@ -607,7 +607,7 @@ def check_hotel_availability(
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"price_per_night": "$185",
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"last_checked": datetime.now().isoformat()
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}
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return json.dumps({
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"availability": availability_data
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})
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@@ -629,7 +629,7 @@ def check_flight_availability(
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and last checked timestamp.
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"""
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availability_status = "Available"
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availability_data = {
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"service_type": "flight",
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"flight_number": flight_number,
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@@ -640,7 +640,7 @@ def check_flight_availability(
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"price_per_passenger": "$520",
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"last_checked": datetime.now().isoformat()
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}
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return json.dumps({
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"availability": availability_data
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})
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@@ -662,7 +662,7 @@ def check_activity_availability(
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and last checked timestamp.
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"""
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availability_status = "Available"
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availability_data = {
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"service_type": "activity",
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"activity_name": activity_name,
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@@ -673,7 +673,7 @@ def check_activity_availability(
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"price_per_person": "$45",
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"last_checked": datetime.now().isoformat()
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}
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return json.dumps({
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"availability": availability_data
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})
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@@ -694,7 +694,7 @@ def process_payment(
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payment method details, and receipt URL.
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"""
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transaction_id = f"TXN-{datetime.now().strftime('%Y%m%d%H%M%S')}"
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payment_result = {
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"transaction_id": transaction_id,
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"amount": amount,
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@@ -706,13 +706,12 @@ def process_payment(
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"timestamp": datetime.now().isoformat(),
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"receipt_url": f"https://payments.travelagency.com/receipt/{transaction_id}"
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}
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return json.dumps({
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"payment_result": payment_result
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})
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# Mock payment validation tool
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@tool(name="validate_payment_method", description="Validate a payment method before processing.")
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def validate_payment_method(
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@@ -725,11 +724,11 @@ def validate_payment_method(
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validation messages, supported currencies, and processing fee information.
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"""
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method_type = payment_method.get("type", "credit_card")
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# Validation logic
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is_valid = True
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validation_messages = []
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if method_type == "credit_card":
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if not payment_method.get("number"):
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is_valid = False
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@@ -740,7 +739,7 @@ def validate_payment_method(
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if not payment_method.get("cvv"):
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is_valid = False
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validation_messages.append("CVV is required")
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validation_result = {
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"is_valid": is_valid,
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"payment_method_type": method_type,
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@@ -748,7 +747,7 @@ def validate_payment_method(
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"supported_currencies": ["USD", "EUR", "GBP", "JPY"],
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"processing_fee": "2.5%"
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}
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return json.dumps({
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"validation_result": validation_result
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})
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@@ -51,13 +51,11 @@ from agent_framework import (
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AgentRunUpdateEvent,
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ChatMessage,
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Executor,
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Role,
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WorkflowBuilder,
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WorkflowContext,
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WorkflowOutputEvent,
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executor,
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handler,
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tool,
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)
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from agent_framework.azure import AzureAIClient
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from azure.ai.projects.aio import AIProjectClient
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@@ -71,7 +69,7 @@ load_dotenv()
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@executor(id="start_executor")
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async def start_executor(input: str, ctx: WorkflowContext[list[ChatMessage]]) -> None:
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"""Initiates the workflow by sending the user query to all specialized agents."""
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await ctx.send_message([ChatMessage(role="user", text=input)])
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await ctx.send_message([ChatMessage("user", [input])])
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class ResearchLead(Executor):
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@@ -107,11 +105,11 @@ class ResearchLead(Executor):
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# Generate comprehensive travel plan summary
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messages = [
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ChatMessage(
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role=Role.SYSTEM,
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role="system",
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text="You are a travel planning coordinator. Summarize findings from multiple specialized travel agents and provide a clear, comprehensive travel plan based on the user's query.",
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),
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ChatMessage(
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role=Role.USER,
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role="user",
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text=f"Original query: {user_query}\n\nFindings from specialized travel agents:\n{summary_text}\n\nPlease provide a comprehensive travel plan based on these findings.",
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),
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]
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@@ -136,7 +134,7 @@ class ResearchLead(Executor):
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findings = []
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if response.agent_response and response.agent_response.messages:
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for msg in response.agent_response.messages:
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if msg.role == Role.ASSISTANT and msg.text and msg.text.strip():
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if msg.role == "assistant" and msg.text and msg.text.strip():
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findings.append(msg.text.strip())
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if findings:
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@@ -16,16 +16,15 @@ import time
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from azure.ai.projects import AIProjectClient
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from azure.identity import DefaultAzureCredential
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from dotenv import load_dotenv
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from create_workflow import create_and_run_workflow
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from dotenv import load_dotenv
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def print_section(title: str):
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"""Print a formatted section header."""
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print(f"\n{'='*80}")
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print(f"\n{'=' * 80}")
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print(f"{title}")
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print(f"{'='*80}")
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print(f"{'=' * 80}")
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async def run_workflow():
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@@ -37,9 +36,9 @@ async def run_workflow():
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print_section("Step 1: Running Workflow")
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print("Executing multi-agent travel planning workflow...")
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print("This may take a few minutes...")
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workflow_data = await create_and_run_workflow()
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print("Workflow execution completed")
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return workflow_data
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@@ -47,31 +46,31 @@ async def run_workflow():
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def display_response_summary(workflow_data: dict):
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"""Display summary of response data."""
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print_section("Step 2: Response Data Summary")
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print(f"Query: {workflow_data['query']}")
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print(f"\nAgents tracked: {len(workflow_data['agents'])}")
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for agent_name, agent_data in workflow_data['agents'].items():
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response_count = agent_data['response_count']
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for agent_name, agent_data in workflow_data["agents"].items():
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response_count = agent_data["response_count"]
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print(f" {agent_name}: {response_count} response(s)")
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def fetch_agent_responses(openai_client, workflow_data: dict, agent_names: list):
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"""Fetch and display final responses from specified agents."""
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print_section("Step 3: Fetching Agent Responses")
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for agent_name in agent_names:
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if agent_name not in workflow_data['agents']:
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if agent_name not in workflow_data["agents"]:
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continue
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agent_data = workflow_data['agents'][agent_name]
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if not agent_data['response_ids']:
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agent_data = workflow_data["agents"][agent_name]
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if not agent_data["response_ids"]:
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continue
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final_response_id = agent_data['response_ids'][-1]
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final_response_id = agent_data["response_ids"][-1]
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print(f"\n{agent_name}")
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print(f" Response ID: {final_response_id}")
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try:
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response = openai_client.responses.retrieve(response_id=final_response_id)
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content = response.output[-1].content[-1].text
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@@ -84,9 +83,9 @@ def fetch_agent_responses(openai_client, workflow_data: dict, agent_names: list)
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def create_evaluation(openai_client, model_deployment: str):
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"""Create evaluation with multiple evaluators."""
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print_section("Step 4: Creating Evaluation")
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data_source_config = {"type": "azure_ai_source", "scenario": "responses"}
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testing_criteria = [
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{
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"type": "azure_ai_evaluator",
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@@ -113,33 +112,33 @@ def create_evaluation(openai_client, model_deployment: str):
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"initialization_parameters": {"deployment_name": model_deployment}
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},
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]
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eval_object = openai_client.evals.create(
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name="Travel Workflow Multi-Evaluator Assessment",
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data_source_config=data_source_config,
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testing_criteria=testing_criteria,
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)
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evaluator_names = [criterion["name"] for criterion in testing_criteria]
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print(f"Evaluation created: {eval_object.id}")
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print(f"Evaluators ({len(evaluator_names)}): {', '.join(evaluator_names)}")
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return eval_object
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def run_evaluation(openai_client, eval_object, workflow_data: dict, agent_names: list):
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"""Run evaluation on selected agent responses."""
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print_section("Step 5: Running Evaluation")
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selected_response_ids = []
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for agent_name in agent_names:
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if agent_name in workflow_data['agents']:
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agent_data = workflow_data['agents'][agent_name]
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if agent_data['response_ids']:
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selected_response_ids.append(agent_data['response_ids'][-1])
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if agent_name in workflow_data["agents"]:
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agent_data = workflow_data["agents"][agent_name]
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if agent_data["response_ids"]:
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selected_response_ids.append(agent_data["response_ids"][-1])
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print(f"Selected {len(selected_response_ids)} responses for evaluation")
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data_source = {
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"type": "azure_ai_responses",
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"item_generation_params": {
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@@ -151,24 +150,24 @@ def run_evaluation(openai_client, eval_object, workflow_data: dict, agent_names:
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},
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},
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}
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eval_run = openai_client.evals.runs.create(
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eval_id=eval_object.id,
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name="Multi-Agent Response Evaluation",
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data_source=data_source
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)
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print(f"Evaluation run created: {eval_run.id}")
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return eval_run
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def monitor_evaluation(openai_client, eval_object, eval_run):
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"""Monitor evaluation progress and display results."""
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print_section("Step 6: Monitoring Evaluation")
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print("Waiting for evaluation to complete...")
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while eval_run.status not in ["completed", "failed"]:
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eval_run = openai_client.evals.runs.retrieve(
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run_id=eval_run.id,
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@@ -176,7 +175,7 @@ def monitor_evaluation(openai_client, eval_object, eval_run):
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)
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print(f"Status: {eval_run.status}")
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time.sleep(5)
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if eval_run.status == "completed":
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print("\nEvaluation completed successfully")
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print(f"Result counts: {eval_run.result_counts}")
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@@ -188,31 +187,31 @@ def monitor_evaluation(openai_client, eval_object, eval_run):
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async def main():
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"""Main execution flow."""
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load_dotenv()
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print("Travel Planning Workflow Evaluation")
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workflow_data = await run_workflow()
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display_response_summary(workflow_data)
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project_client = AIProjectClient(
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endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"],
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credential=DefaultAzureCredential(),
|
||||
api_version="2025-11-15-preview"
|
||||
)
|
||||
openai_client = project_client.get_openai_client()
|
||||
|
||||
|
||||
agents_to_evaluate = ["hotel-search-agent", "flight-search-agent", "activity-search-agent"]
|
||||
|
||||
|
||||
fetch_agent_responses(openai_client, workflow_data, agents_to_evaluate)
|
||||
|
||||
|
||||
model_deployment = os.environ.get("AZURE_AI_MODEL_DEPLOYMENT_NAME", "gpt-4o-mini")
|
||||
eval_object = create_evaluation(openai_client, model_deployment)
|
||||
|
||||
|
||||
eval_run = run_evaluation(openai_client, eval_object, workflow_data, agents_to_evaluate)
|
||||
|
||||
|
||||
monitor_evaluation(openai_client, eval_object, eval_run)
|
||||
|
||||
|
||||
print_section("Complete")
|
||||
|
||||
|
||||
|
||||
Reference in New Issue
Block a user