[BREAKING] Python: Add InvokeFunctionTool action for declarative workflows (#3716)

* add(declarative): Declarative workflow InvokeFunctionTool feature

* Cleanup

* Address PR feedback

* Remove InvokeTool kind, consolidate to InvokeFunctionTool

* Fix sample locations

* pin azure-ai-projects to 2.0.0b3 due to breaking changes

python/samples/03-workflows/declarative/invoke_function_tool/main.py

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+# Copyright (c) Microsoft. All rights reserved.
+
+"""Invoke Function Tool sample - demonstrates InvokeFunctionTool workflow actions.
+
+This sample shows how to:
+1. Define Python functions that can be called from workflows
+2. Register functions with WorkflowFactory.register_tool()
+3. Use the InvokeFunctionTool action in YAML to invoke registered functions
+4. Pass arguments using expression syntax (=Local.variable)
+5. Capture function output in workflow variables
+
+Run with:
+    python -m samples.03-workflows.declarative.invoke_function_tool.main
+"""
+
+import asyncio
+from pathlib import Path
+from typing import Any
+
+from agent_framework.declarative import WorkflowFactory
+
+
+# Define the function tools that will be registered with the workflow
+def get_weather(location: str, unit: str = "F") -> dict[str, Any]:
+    """Get weather information for a location.
+
+    This is a mock function that returns simulated weather data.
+    In a real application, this would call a weather API.
+
+    Args:
+        location: The city or location to get weather for.
+        unit: Temperature unit ("F" for Fahrenheit, "C" for Celsius).
+
+    Returns:
+        Dictionary with weather information.
+    """
+    # Simulated weather data
+    weather_data = {
+        "Seattle": {"temp": 55, "condition": "rainy"},
+        "New York": {"temp": 70, "condition": "partly cloudy"},
+        "Los Angeles": {"temp": 85, "condition": "sunny"},
+        "Chicago": {"temp": 60, "condition": "windy"},
+    }
+
+    data = weather_data.get(location, {"temp": 72, "condition": "unknown"})
+
+    # Convert to Celsius if requested
+    temp = data["temp"]
+    if unit.upper() == "C":
+        temp = round((temp - 32) * 5 / 9)  # type: ignore
+
+    return {
+        "location": location,
+        "temp": temp,
+        "unit": unit.upper(),
+        "condition": data["condition"],
+    }
+
+
+def format_message(template: str, data: dict[str, Any]) -> str:
+    """Format a message template with data.
+
+    Args:
+        template: A string template with {key} placeholders.
+        data: Dictionary of values to substitute.
+
+    Returns:
+        Formatted message string.
+    """
+    try:
+        return template.format(**data)
+    except KeyError as e:
+        return f"Error formatting message: missing key {e}"
+
+
+async def main():
+    """Run the invoke function tool workflow."""
+    # Get the path to the workflow YAML file
+    workflow_path = Path(__file__).parent / "workflow.yaml"
+
+    # Create the workflow factory and register our tool functions
+    factory = (
+        WorkflowFactory().register_tool("get_weather", get_weather).register_tool("format_message", format_message)
+    )
+
+    # Create the workflow from the YAML definition
+    workflow = factory.create_workflow_from_yaml_path(workflow_path)
+
+    print("=" * 60)
+    print("Invoke Function Tool Workflow Demo")
+    print("=" * 60)
+
+    # Test with different inputs - both location and unit must be provided
+    # as the workflow expects them in Workflow.Inputs
+    test_inputs = [
+        {"location": "Seattle", "unit": "F"},
+        {"location": "New York", "unit": "C"},
+        {"location": "Los Angeles", "unit": "F"},
+        {"location": "Chicago", "unit": "C"},
+    ]
+
+    for inputs in test_inputs:
+        print(f"\nInput: {inputs}")
+        print("-" * 40)
+
+        # Run the workflow
+        events = await workflow.run(inputs)
+
+        # Get the outputs
+        outputs = events.get_outputs()
+        for output in outputs:
+            print(f"Output: {output}")
+
+
+if __name__ == "__main__":
+    asyncio.run(main())

python/samples/03-workflows/declarative/invoke_function_tool/workflow.yaml

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+# Invoke Function Tool Workflow
+
+name: invoke_function_tool_demo
+description: Demonstrates the InvokeFunctionTool action for invoking registered functions
+
+actions:
+  # Set up input location
+  - kind: SetValue
+    id: set_location
+    path: Local.location
+    value: =If(IsBlank(inputs.location), "Seattle", inputs.location)
+
+  # Set up temperature unit
+  - kind: SetValue
+    id: set_unit
+    path: Local.unit
+    value: =If(IsBlank(inputs.unit), "F", inputs.unit)
+
+  # Invoke the get_weather function tool
+  - kind: InvokeFunctionTool
+    id: invoke_weather
+    functionName: get_weather
+    arguments:
+      location: =Local.location
+      unit: =Local.unit
+    output:
+      messages: Local.weatherToolCallItems
+      result: Local.weatherInfo
+      autoSend: true
+
+  # Format a human-readable message using another function
+  - kind: InvokeFunctionTool
+    id: format_output
+    functionName: format_message
+    arguments:
+      template: "The weather in {location} is {temp}°{unit}"
+      data: =Local.weatherInfo
+    output:
+      result: Local.formattedMessage
+
+  # Output the result
+  - kind: SendActivity
+    id: send_weather
+    activity:
+      text: =Local.formattedMessage
+
+  # Store the result in workflow outputs
+  - kind: SetValue
+    id: set_output
+    path: Workflow.Outputs.weather
+    value: =Local.weatherInfo