feat: Add BigQuery vs Cloud Logging comparison demo

contributing/samples/bq_vs_cloud_logging_demo/__init__.py

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+# Copyright 2025 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""Side-by-side demo comparing BigQuery Agent Analytics vs Cloud Logging.
+
+This demo shows how to log ADK agent events using two different approaches:
+1. BigQuery Agent Analytics Plugin - Full analytics with SQL queries
+2. Cloud Logging via OpenTelemetry - Distributed tracing integration
+
+See README.md for detailed comparison and usage instructions.
+"""
+
+from . import agent

contributing/samples/bq_vs_cloud_logging_demo/agent.py

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+# Copyright 2025 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""Shared agent definition for BQ vs Cloud Logging comparison demo.
+
+This agent demonstrates typical patterns that generate diverse telemetry:
+- LLM requests/responses (token usage tracking)
+- Tool calls (success/failure rates)
+- Multi-modal content handling (image analysis)
+
+Run with either:
+- BigQuery Analytics: python run_with_bq_analytics.py
+- Cloud Logging: python run_with_cloud_logging.py
+"""
+
+from __future__ import annotations
+
+import os
+import random
+from typing import Any
+
+from google.adk import Agent
+from google.adk.apps import App
+from google.adk.models.google_llm import Gemini
+from google.adk.tools.function_tool import FunctionTool
+
+# Default Vertex AI settings
+os.environ.setdefault("GOOGLE_GENAI_USE_VERTEXAI", "true")
+os.environ.setdefault("GOOGLE_CLOUD_PROJECT", os.getenv("PROJECT_ID", ""))
+os.environ.setdefault("GOOGLE_CLOUD_LOCATION", "us-central1")
+
+
+# =============================================================================
+# TOOLS - Designed to generate diverse telemetry data
+# =============================================================================
+
+
+def get_weather(city: str) -> dict[str, Any]:
+  """Get current weather for a city.
+
+  This tool demonstrates successful tool calls with structured output.
+  """
+  weather_data = {
+      "Tokyo": {"temp_c": 22, "condition": "Partly cloudy", "humidity": 65},
+      "Paris": {"temp_c": 18, "condition": "Sunny", "humidity": 55},
+      "New York": {"temp_c": 25, "condition": "Clear", "humidity": 70},
+      "Sydney": {"temp_c": 28, "condition": "Sunny", "humidity": 60},
+      "London": {"temp_c": 15, "condition": "Rainy", "humidity": 80},
+  }
+  if city in weather_data:
+    return {"city": city, **weather_data[city], "status": "success"}
+  return {"city": city, "error": "City not found", "status": "not_found"}
+
+
+def calculate_trip_cost(
+    city: str,
+    days: int,
+    hotel_class: str = "mid-range",
+) -> dict[str, Any]:
+  """Calculate estimated trip cost.
+
+  This tool demonstrates numeric calculations and multiple parameters.
+  """
+  daily_rates = {
+      "budget": {"hotel": 80, "food": 40, "transport": 20},
+      "mid-range": {"hotel": 150, "food": 70, "transport": 40},
+      "luxury": {"hotel": 400, "food": 150, "transport": 80},
+  }
+  rates = daily_rates.get(hotel_class, daily_rates["mid-range"])
+  total = days * sum(rates.values())
+  return {
+      "city": city,
+      "days": days,
+      "hotel_class": hotel_class,
+      "daily_breakdown": rates,
+      "total_estimate_usd": total,
+  }
+
+
+def flaky_api_call(operation: str) -> dict[str, Any]:
+  """Simulates an unreliable external API (fails 30% of the time).
+
+  This tool is intentionally flaky to demonstrate error tracking and
+  tool failure rate analysis.
+  """
+  if random.random() < 0.3:
+    raise RuntimeError(
+        f"External API temporarily unavailable for operation: {operation}"
+    )
+  return {
+      "operation": operation,
+      "status": "success",
+      "data": f"Result for {operation}",
+  }
+
+
+def analyze_sentiment(text: str) -> dict[str, Any]:
+  """Analyze sentiment of provided text.
+
+  Demonstrates longer text processing for token usage analysis.
+  """
+  word_count = len(text.split())
+  # Simple mock sentiment analysis
+  positive_words = {"good", "great", "excellent", "amazing", "wonderful"}
+  negative_words = {"bad", "terrible", "awful", "poor", "disappointing"}
+  words = set(text.lower().split())
+  pos_count = len(words & positive_words)
+  neg_count = len(words & negative_words)
+
+  if pos_count > neg_count:
+    sentiment = "positive"
+  elif neg_count > pos_count:
+    sentiment = "negative"
+  else:
+    sentiment = "neutral"
+
+  return {
+      "sentiment": sentiment,
+      "word_count": word_count,
+      "positive_indicators": pos_count,
+      "negative_indicators": neg_count,
+  }
+
+
+# Create FunctionTool instances
+weather_tool = FunctionTool(get_weather)
+trip_cost_tool = FunctionTool(calculate_trip_cost)
+flaky_tool = FunctionTool(flaky_api_call)
+sentiment_tool = FunctionTool(analyze_sentiment)
+
+
+# =============================================================================
+# AGENT DEFINITION
+# =============================================================================
+
+MODEL = Gemini(model="gemini-2.0-flash")
+
+root_agent = Agent(
+    name="telemetry_demo_agent",
+    model=MODEL,
+    instruction="""You are a helpful travel assistant that can:
+1. Check weather in major cities using the get_weather tool
+2. Calculate trip costs using the calculate_trip_cost tool
+3. Analyze text sentiment using the analyze_sentiment tool
+4. Make external API calls using the flaky_api_call tool (this may fail sometimes)
+
+When helping users, actively use your tools to provide accurate information.
+If a tool fails, acknowledge the error and try again or suggest alternatives.
+
+Keep responses concise and actionable.""",
+    description="A demo agent for comparing BigQuery Analytics vs Cloud Logging",
+    tools=[
+        weather_tool,
+        trip_cost_tool,
+        flaky_tool,
+        sentiment_tool,
+    ],
+)
+
+
+def create_app_with_plugins(plugins: list | None = None) -> App:
+  """Create an App instance with optional plugins.
+
+  Args:
+    plugins: List of plugins to attach (e.g., BigQueryAgentAnalyticsPlugin)
+
+  Returns:
+    Configured App instance
+  """
+  return App(
+      name="bq_vs_cloud_logging_demo",
+      root_agent=root_agent,
+      plugins=plugins or [],
+  )
+
+
+# Default app without plugins (for Cloud Logging via --otel_to_cloud)
+app = create_app_with_plugins()