feat: google-adk instrumentation.

README.md

@@ -46,6 +46,7 @@ OpenInference provides a set of instrumentations for popular machine learning SD
 | [`openinference-instrumentation-anthropic`](./python/instrumentation/openinference-instrumentation-anthropic)         | OpenInference Instrumentation for Anthropic.         | [![PyPI Version](https://img.shields.io/pypi/v/openinference-instrumentation-anthropic.svg)](https://pypi.python.org/pypi/openinference-instrumentation-anthropic)         |
 | [`openinference-instrumentation-beeai`](./python/instrumentation/openinference-instrumentation-beeai)                 | OpenInference Instrumentation for BeeAI.             | [![PyPI Version](https://img.shields.io/pypi/v/openinference-instrumentation-beeai.svg)](https://pypi.python.org/pypi/openinference-instrumentation-beeai)                 |
 | [`openinference-instrumentation-google-genai`](./python/instrumentation/openinference-instrumentation-google-genai)   | OpenInference Instrumentation for Google GenAI.      | [![PyPI Version](https://img.shields.io/pypi/v/openinference-instrumentation-google-genai.svg)](https://pypi.python.org/pypi/openinference-instrumentation-google-genai)   |
+| [`openinference-instrumentation-google-adk`](./python/instrumentation/openinference-instrumentation-google-adk)       | OpenInference Instrumentation for Google ADK.        | [![PyPI Version](https://img.shields.io/pypi/v/openinference-instrumentation-google-adk.svg)](https://pypi.python.org/pypi/openinference-instrumentation-google-adk)       |
 
 ### Examples
 

python/instrumentation/openinference-instrumentation-google-adk/LICENSE

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python/instrumentation/openinference-instrumentation-google-adk/README.md

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+# OpenInference Google ADK Instrumentation
+
+[![pypi](https://badge.fury.io/py/openinference-instrumentation-google-adk.svg)](https://pypi.org/project/openinference-instrumentation-google-adk/)
+
+Python auto-instrumentation library for Google ADK.
+
+The traces emitted by this instrumentation are fully OpenTelemetry compatible and can be sent to an OpenTelemetry collector for viewing, such as [`arize-phoenix`](https://github.com/Arize-ai/phoenix)
+
+## Installation
+
+```shell
+pip install openinference-instrumentation-google-adk
+```
+
+## Quickstart
+
+In this example we will instrument a small program that uses Gemini and observe the traces via [`arize-phoenix`](https://github.com/Arize-ai/phoenix).
+
+Install packages.
+
+```shell
+pip install openinference-instrumentation-google-adk arize-phoenix opentelemetry-sdk opentelemetry-exporter-otlp
+```
+
+Start the phoenix server so that it is ready to collect traces.
+The Phoenix server runs entirely on your machine and does not send data over the internet.
+
+```shell
+phoenix serve
+```
+
+In a python file, set up the `GoogleADKInstrumentor` and configure the tracer to send traces to Phoenix.
+
+```python
+import asyncio
+
+from google.adk.agents import Agent
+from google.adk.runners import InMemoryRunner
+from google.genai import types
+
+from openinference.instrumentation.google_adk import GoogleADKInstrumentor
+from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter
+from opentelemetry.sdk import trace as trace_sdk
+from opentelemetry.sdk.trace.export import ConsoleSpanExporter, SimpleSpanProcessor
+
+endpoint = "http://127.0.0.1:6006/v1/traces"
+tracer_provider = trace_sdk.TracerProvider()
+tracer_provider.add_span_processor(SimpleSpanProcessor(OTLPSpanExporter(endpoint)))
+# Optionally, you can also print the spans to the console.
+tracer_provider.add_span_processor(SimpleSpanProcessor(ConsoleSpanExporter()))
+
+GoogleADKInstrumentor().instrument(tracer_provider=tracer_provider)
+
+def get_weather(city: str) -> dict:
+    """Retrieves the current weather report for a specified city.
+
+    Args:
+        city (str): The name of the city for which to retrieve the weather report.
+
+    Returns:
+        dict: status and result or error msg.
+    """
+    if city.lower() == "new york":
+        return {
+            "status": "success",
+            "report": (
+                "The weather in New York is sunny with a temperature of 25 degrees"
+                " Celsius (77 degrees Fahrenheit)."
+            ),
+        }
+    else:
+        return {
+            "status": "error",
+            "error_message": f"Weather information for '{city}' is not available.",
+        }
+
+agent = Agent(
+   name="test_agent",
+   model="gemini-2.0-flash-exp",
+   description="Agent to answer questions using tools.",
+   instruction="You must use the available tools to find an answer.",
+   tools=[get_weather]
+)
+
+async def main():
+    app_name = "test_instrumentation"
+    user_id = "test_user"
+    session_id = "test_session"
+    runner = InMemoryRunner(agent=agent, app_name=app_name)
+    session_service = runner.session_service
+    session_service.create_session(
+        app_name=app_name,
+        user_id=user_id,
+        session_id=session_id
+    )
+    async for event in runner.run_async(
+        user_id=user_id,
+        session_id=session_id,
+        new_message=types.Content(role="user", parts=[
+            types.Part(text="What is the weather in New York?")]
+        )
+    ):
+        if event.is_final_response():
+            print(event.content.parts[0].text.strip())
+
+if __name__ == "__main__":
+    asyncio.run(main())
+```
+
+Since we are using Gemini, we must set the `GOOGLE_API_KEY` environment variable to authenticate with the Gemini API.
+
+```shell
+export GOOGLE_API_KEY=your-api-key
+```
+
+Now simply run the python file and observe the traces in Phoenix.
+
+```shell
+python your_file.py
+```

python/instrumentation/openinference-instrumentation-google-adk/examples/basic.py

@@ -0,0 +1,47 @@
+import asyncio
+
+from google.adk.agents import Agent
+from google.adk.runners import InMemoryRunner
+from google.genai import types
+from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter
+from opentelemetry.sdk import trace as trace_sdk
+from opentelemetry.sdk.trace.export import ConsoleSpanExporter, SimpleSpanProcessor
+
+from openinference.instrumentation.google_adk import GoogleADKInstrumentor
+
+endpoint = "http://127.0.0.1:6006/v1/traces"
+tracer_provider = trace_sdk.TracerProvider()
+tracer_provider.add_span_processor(SimpleSpanProcessor(OTLPSpanExporter(endpoint)))
+# Optionally, you can also print the spans to the console.
+tracer_provider.add_span_processor(SimpleSpanProcessor(ConsoleSpanExporter()))
+
+GoogleADKInstrumentor().instrument(tracer_provider=tracer_provider)
+
+agent = Agent(
+    name="Assistant",
+    model="gemini-2.0-flash-exp",
+    description="A helpful assistant.",
+    instruction="You are a helpful assistant.",
+)
+
+
+async def main():
+    app_name = "test_instrumentation"
+    user_id = "test_user"
+    session_id = "test_session"
+    runner = InMemoryRunner(agent=agent, app_name=app_name)
+    session_service = runner.session_service
+    session_service.create_session(app_name=app_name, user_id=user_id, session_id=session_id)
+    async for event in runner.run_async(
+        user_id=user_id,
+        session_id=session_id,
+        new_message=types.Content(
+            role="user", parts=[types.Part(text="Write a haiku about recursion in programming.")]
+        ),
+    ):
+        if event.is_final_response():
+            print(event.content.parts[0].text.strip())
+
+
+if __name__ == "__main__":
+    asyncio.run(main())