Python: Enhanced documentation for dependency injection and serialization features (#1324)

* improvements in dep injection and sample * fix for falsy default * fix mypy * update to use a nested dict instead of a string. * clarify docs * Update python/packages/core/agent_framework/_tools.py Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * Update python/packages/core/agent_framework/_tools.py Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * Update python/packages/core/agent_framework/_tools.py Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * Update python/packages/core/agent_framework/_serialization.py Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * format --------- Co-authored-by: eavanvalkenburg <github@vanvalkenburg.eu> Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
2026-06-16 21:04:09 +08:00 · 2025-10-13 13:34:27 -07:00
parent fc12ab9fed
commit 9148392d00
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+# Copyright (c) Microsoft. All rights reserved.
+# type: ignore
+"""
+AIFunction Tool with Dependency Injection Example
+
+This example demonstrates how to create an AIFunction tool using the agent framework's
+dependency injection system. Instead of providing the function at initialization time,
+the actual callable function is injected during deserialization from a dictionary definition.
+
+Note:
+    The serialization and deserialization feature used in this example is currently
+    in active development. The API may change in future versions as we continue 
+    to improve and extend its functionality. Please refer to the latest documentation
+    for any updates to the dependency injection patterns.
+
+Usage:
+    Run this script to see how an AIFunction tool can be created from a dictionary
+    definition with the function injected at runtime. The agent will use this tool
+    to perform arithmetic operations.
+"""
+
+import asyncio
+
+from agent_framework import AIFunction
+from agent_framework.openai import OpenAIResponsesClient
+
+definition = {
+    "type": "ai_function",
+    "name": "add_numbers",
+    "description": "Add two numbers together.",
+    "input_model": {
+        "properties": {
+            "a": {"description": "The first number", "type": "integer"},
+            "b": {"description": "The second number", "type": "integer"},
+        },
+        "required": ["a", "b"],
+        "title": "func_input",
+        "type": "object",
+    },
+}
+
+
+async def main() -> None:
+    """Main function demonstrating creating a tool with an injected function."""
+
+    def func(a, b) -> int:
+        """Add two numbers together."""
+        return a + b
+
+    # Create the AIFunction tool using dependency injection
+    # The 'definition' dictionary contains the serialized tool configuration,
+    # while the actual function implementation is provided via dependencies.
+    # 
+    # Dependency structure: {"ai_function": {"name:add_numbers": {"func": func}}}
+    # - "ai_function": matches the tool type identifier
+    # - "name:add_numbers": instance-specific injection targeting tools with name="add_numbers"
+    # - "func": the parameter name that will receive the injected function
+    tool = AIFunction.from_dict(definition, dependencies={"ai_function": {"name:add_numbers": {"func": func}}})
+
+    agent = OpenAIResponsesClient().create_agent(
+        name="FunctionToolAgent", instructions="You are a helpful assistant.", tools=tool
+    )
+    response = await agent.run("What is 5 + 3?")
+    print(f"Response: {response.text}")
+
+
+if __name__ == "__main__":
+    asyncio.run(main())