feat: add Google GenAI instrumentation (#1500)

Co-authored-by: harrison <harrison@arize.com>
Co-authored-by: Mikyo King <mikyo@arize.com>

Author: 3 people

README.md

@@ -45,6 +45,7 @@ OpenInference provides a set of instrumentations for popular machine learning SD
 | [`openinference-instrumentation-instructor`](./python/instrumentation/openinference-instrumentation-instructor)       | OpenInference Instrumentation for Instructor.        | [![PyPI Version](https://img.shields.io/pypi/v/openinference-instrumentation-instructor.svg)](https://pypi.python.org/pypi/openinference-instrumentation-instructor)       |
 | [`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)   |
 
 ### Examples
 

python/instrumentation/openinference-instrumentation-google-genai/CHANGELOG.md

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python/instrumentation/openinference-instrumentation-google-genai/LICENSE

@@ -0,0 +1,59 @@
+# OpenInference Google GenAI Instrumentation
+
+Python auto-instrumentation library for GenAI SDK. Traces are fully OpenTelemetry compatible and can be sent to any OpenTelemetry collector for viewing, such as [Arize Phoenix](https://github.com/Arize-ai/phoenix).
+
+## Installation
+
+```shell
+pip install -Uqqq openinference-instrumentation-google-genai
+```
+
+## Quickstart
+
+Install `openinference-instrumentation-google-genai` and `arize-phoenix`.
+
+```shell
+pip install -U \
+    openinference-instrumentation-google-genai \
+    arize-phoenix \
+    opentelemetry-sdk \
+    opentelemetry-exporter-otlp \
+    "opentelemetry-proto>=1.12.0"
+```
+
+Start the `phoenix` server so that it is ready to receive traces.
+The `phoenix` server runs entirely on your machine and does not send data over the internet.
+
+```shell
+phoenix serve
+```
+
+Instrumenting `genai` is simple.
+
+```python
+from openinference.instrumentation.google-genai import GoogleGenAIInstrumentor
+from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import OTLPSpanExporter
+from opentelemetry.sdk.trace import TracerProvider
+from opentelemetry.sdk.trace.export import SimpleSpanProcessor
+
+endpoint = "http://127.0.0.1:4317"
+tracer_provider = TracerProvider()
+tracer_provider.add_span_processor(SimpleSpanProcessor(OTLPSpanExporter(endpoint)))
+
+GoogleGenAIInstrumentor().instrument(tracer_provider=tracer_provider)
+```
+
+Now, all calls by `generate_content` are instrumented and can be viewed in the `phoenix` UI.
+
+## Progress
+
+This instrumentation is a work in progress
+
+-   [x] parse messages and invocation
+-   [ ] capture tool definitions
+
+## More Info
+
+-   [More info on OpenInference and Phoenix](https://docs.arize.com/phoenix)
+-   [How to customize spans to track sessions, metadata, etc.](https://github.com/Arize-ai/openinference/tree/main/python/openinference-instrumentation#customizing-spans)
+-   [How to account for private information and span payload customization](https://github.com/Arize-ai/openinference/tree/main/python/openinference-instrumentation#tracing-configuration)

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

@@ -0,0 +1,85 @@
+import asyncio
+import os
+
+from google import genai
+from google.genai.types import Content, GenerateContentConfig, Part
+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_genai import GoogleGenAIInstrumentor
+
+endpoint = "http://localhost:6006/v1/traces"
+tracer_provider = trace_sdk.TracerProvider()
+tracer_provider.add_span_processor(SimpleSpanProcessor(OTLPSpanExporter(endpoint)))
+tracer_provider.add_span_processor(SimpleSpanProcessor(ConsoleSpanExporter()))
+
+# Make sure to set the GEMINI_API_KEY environment variable
+
+
+def generate_content_sync(model_name: str = "gemini-2.0-flash-001") -> str:
+    try:
+        client = genai.Client(
+            api_key=os.getenv("GEMINI_API_KEY"),
+        )
+        response = client.models.generate_content(model=model_name, contents="Why is the sky blue?")
+        print(response.text)
+
+        config = GenerateContentConfig(
+            system_instruction=(
+                "You are a helpful assistant that can answer questions and help with tasks."
+            )
+        )
+        content = Content(
+            role="user",
+            parts=[
+                Part.from_text(text="Why is the sky blue?"),
+                Part.from_text(text="What is the capital of France?"),
+            ],
+        )
+        response = client.models.generate_content(
+            model=model_name,
+            contents=content,
+            config=config,
+        )
+
+        return response.text or ""
+
+    except Exception as e:
+        return f"Error generating response: {str(e)}"
+
+
+async def generate_content_async(model_name: str = "gemini-2.0-flash-001") -> str:
+    try:
+        client = genai.Client(
+            api_key=os.getenv("GEMINI_API_KEY"),
+        ).aio
+
+        config = GenerateContentConfig(
+            system_instruction=(
+                "You are a helpful assistant that can answer questions and help with tasks."
+            )
+        )
+        content = Content(
+            role="user",
+            parts=[
+                Part.from_text(text="Why is the sky blue?"),
+                Part.from_text(text="What is the capital of France?"),
+            ],
+        )
+
+        async_response = await client.models.generate_content(
+            model=model_name, contents=content, config=config
+        )
+        return async_response.text or ""
+    except Exception as e:
+        return f"Error generating response: {str(e)}"
+
+
+if __name__ == "__main__":
+    GoogleGenAIInstrumentor().instrument(tracer_provider=tracer_provider)
+    response = generate_content_sync("gemini-2.0-flash-001")
+    print(response)
+
+    async_response = asyncio.run(generate_content_async("gemini-2.0-flash-001"))
+    print(async_response)

python/instrumentation/openinference-instrumentation-google-genai/examples/generate_content.py

@@ -0,0 +1 @@
+google-genai >= 1.8.0

python/instrumentation/openinference-instrumentation-google-genai/examples/requirements.txt

@@ -0,0 +1,30 @@
+import os
+
+from google import genai
+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_genai import GoogleGenAIInstrumentor
+
+endpoint = "http://0.0.0.0:6006/v1/traces"
+tracer_provider = trace_sdk.TracerProvider()
+tracer_provider.add_span_processor(SimpleSpanProcessor(OTLPSpanExporter(endpoint)))
+tracer_provider.add_span_processor(SimpleSpanProcessor(ConsoleSpanExporter()))
+
+
+def send_message_multi_turn() -> tuple[str, str]:
+    client = genai.Client(api_key=os.environ["GEMINI_API_KEY"])
+    chat = client.chats.create(model="gemini-2.0-flash-001")
+    response1 = chat.send_message("What is the capital of France?")
+    response2 = chat.send_message("Why is the sky blue?")
+
+    return response1.text or "", response2.text or ""
+
+
+if __name__ == "__main__":
+    GoogleGenAIInstrumentor().instrument(tracer_provider=tracer_provider)
+
+    response1, response2 = send_message_multi_turn()
+    print(response1)
+    print(response2)