Fiddler Google ADK SDK

# Step 1: Install (uv recommended)
uv add fiddler-adk
# or: pip install fiddler-adk

# Step 2: Set up instrumentation
from fiddler_otel import FiddlerClient
from fiddler_adk import GoogleADKInstrumentor

client = FiddlerClient(
    api_key="YOUR_FIDDLER_API_KEY",
    application_id="YOUR_APPLICATION_UUID",
    url="https://your-fiddler-instance.com",
)
GoogleADKInstrumentor(client).instrument()

# Step 3: Create your ADK agent as usual
from google.adk.agents.llm_agent import Agent

agent = Agent(
    model="gemini-2.5-flash",
    name="my_agent",
    description="A helpful assistant",
    instruction="You are a helpful assistant. Be concise.",
)

# Step 4: Agent calls are automatically traced
# (use Runner to execute the agent — see Quick Start Guide for full example)

from fiddler_otel import FiddlerClient
from fiddler_adk import GoogleADKInstrumentor

client = FiddlerClient(
    api_key="YOUR_FIDDLER_API_KEY",
    application_id="YOUR_APPLICATION_UUID",  # UUID4 from Fiddler GenAI Applications
    url="https://your-fiddler-instance.com",
)
GoogleADKInstrumentor(client).instrument()

# All agents created after this point are automatically instrumented

# Option A: Gemini API key
export GOOGLE_API_KEY="your-gemini-api-key"

# Option B: Vertex AI (uses gcloud Application Default Credentials)
export GOOGLE_GENAI_USE_VERTEXAI=1
export GOOGLE_CLOUD_PROJECT="your-gcp-project-id"
export GOOGLE_CLOUD_LOCATION="us-central1"

export ADK_CAPTURE_MESSAGE_CONTENT_IN_SPANS=false

import asyncio
from fiddler_otel import FiddlerClient
from fiddler_adk import GoogleADKInstrumentor
from google.adk.agents.llm_agent import Agent
from google.adk.runners import Runner
from google.adk.sessions import InMemorySessionService
from google.genai import types

# Set up Fiddler instrumentation
client = FiddlerClient(
    api_key="YOUR_FIDDLER_API_KEY",
    application_id="YOUR_APPLICATION_UUID",
    url="https://your-fiddler-instance.com",
)
GoogleADKInstrumentor(client).instrument()


# Define tools
def classify_document(doc_type: str, content: str) -> dict:
    """Classify a document into a known category."""
    return {"category": "Credit Memo", "confidence": 0.95}


def extract_fields(document_id: str) -> dict:
    """Extract structured fields from a document."""
    return {"supplier": "McKesson", "total": "$12,450.00"}


# Create agent with tools
agent = Agent(
    model="gemini-2.5-flash",
    name="doc_processor",
    description="Document processing assistant",
    instruction="You classify and extract fields from medical documents.",
    tools=[classify_document, extract_fields],
)


async def main():
    session_service = InMemorySessionService()
    runner = Runner(agent=agent, app_name="demo", session_service=session_service)
    session = await session_service.create_session(app_name="demo", user_id="user1")

    message = types.Content(
        role="user",
        parts=[types.Part(text="Classify this credit memo: supplier McKesson, amount $5000")],
    )

    async for event in runner.run_async(
        user_id="user1", session_id=session.id, new_message=message
    ):
        if hasattr(event, "content") and event.content:
            parts = getattr(event.content, "parts", []) or []
            text = "".join(p.text for p in parts if getattr(p, "text", None))
            if text:
                print(f"Agent: {text}")

    # Flush traces to Fiddler before exit
    client.force_flush(timeout_millis=5000)


asyncio.run(main())

from fiddler_otel import FiddlerClient

client = FiddlerClient(
    api_key="YOUR_KEY",
    application_id="YOUR_APP_UUID",
    url="https://your-instance.com",
)
# If credentials are wrong, you'll see 401 errors in logs

import logging
logging.basicConfig(level=logging.INFO)
# Look for: "Google ADK instrumentation enabled"

# ADK agents run async — ensure flush before process exits
client.force_flush(timeout_millis=10000)