mirror of
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George Weale
d9e930e823
* docs(integrations): fix unresolvable imports and stale API claims * docs: apply style pass and drop out-of-scope import cleanup * docs(integrations): address review feedback on gcs, cloud-trace, reflect-and-retry Restore the gcs_ tool name prefixes in the GCS tool tables, since both toolsets set tool_name_prefix="gcs" and the tables list names as the model sees them. Use the current Agent Platform SDK name in cloud-trace prose, make the reflect-and-retry failure description language-neutral for Python and Go, and drop the redundant re-export clause. * docs(gcs): note that tool_filter matches unprefixed tool names Tool filtering runs inside get_tools() against the unprefixed name, and get_tools_with_prefix() applies the gcs_ prefix afterwards, so the names in the tables are not the names tool_filter expects. * docs(computer-use): drop unused Gemini and override imports --------- Co-authored-by: Kristopher Overholt <koverholt@google.com>
134 lines
4.3 KiB
Markdown
134 lines
4.3 KiB
Markdown
---
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catalog_title: Future AGI
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catalog_description: Trace, evaluate, and improve ADK agents with the traceAI OpenTelemetry integration
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catalog_icon: /integrations/assets/futureagi.png
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catalog_tags: ["observability", "evaluation"]
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---
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# Future AGI observability for ADK
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<div class="language-support-tag">
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<span class="lst-supported">Supported in ADK</span><span class="lst-python">Python</span>
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</div>
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[Future AGI](https://futureagi.com) is an observability and evaluation platform
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for AI agents. The
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[`traceai-google-adk`](https://pypi.org/project/traceai-google-adk/) package
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auto-instruments ADK agents and exports every agent run, model call, tool
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execution, and event-loop cycle to Future AGI as OpenTelemetry spans, where you
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can inspect the run tree, evaluate behavior, and run experiments.
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## Overview
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The `traceai-google-adk` package adds OpenTelemetry instrumentation for ADK,
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allowing you to:
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- **Trace agent runs:** Capture every agent invocation, tool call, model
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request, and response with prompts, completions, parameters, and token usage.
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- **Evaluate behavior:** Run pre-built or custom evaluators against the captured
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traces.
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- **Debug agents:** Drill into hierarchical run trees to find failed tool calls,
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latency hotspots, and unexpected branches.
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## Prerequisites
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1. Sign up at [app.futureagi.com](https://app.futureagi.com).
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2. Copy your `FI_API_KEY` and `FI_SECRET_KEY` from the dashboard.
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3. Set the environment variables:
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```bash
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export FI_API_KEY=<your-fi-api-key>
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export FI_SECRET_KEY=<your-fi-secret-key>
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export GOOGLE_API_KEY=<your-google-api-key>
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```
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## Installation
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```bash
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pip install traceai-google-adk
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```
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The `traceai-google-adk` package declares `google-adk` and `google-genai` as
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runtime dependencies, so they install transitively.
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## Sending Traces to Future AGI
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Register the Future AGI tracer once at startup and attach the
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`GoogleADKInstrumentor` **before** running any agent. Every subsequent ADK agent
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invocation is captured automatically.
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```python
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import asyncio
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from fi_instrumentation import register
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from fi_instrumentation.fi_types import ProjectType
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from google.adk.agents import Agent
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from google.adk.runners import InMemoryRunner
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from google.genai import types
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from traceai_google_adk import GoogleADKInstrumentor
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tracer_provider = register(
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project_type=ProjectType.OBSERVE,
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project_name="adk-weather-agent",
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)
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GoogleADKInstrumentor().instrument(tracer_provider=tracer_provider)
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def get_weather(city: str) -> dict:
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"""Retrieves the current weather report for a specified city."""
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if city.lower() == "new york":
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return {
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"status": "success",
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"report": "The weather in New York is sunny with a temperature of 25°C.",
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}
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return {
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"status": "error",
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"error_message": f"Weather information for '{city}' is not available.",
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}
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agent = Agent(
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name="weather_agent",
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model="gemini-flash-latest",
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description="Agent to answer weather questions.",
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instruction="You must use the available tools to find an answer.",
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tools=[get_weather],
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)
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async def main():
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runner = InMemoryRunner(agent=agent, app_name="weather_app")
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await runner.session_service.create_session(
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app_name="weather_app", user_id="user", session_id="session"
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)
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async for event in runner.run_async(
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user_id="user",
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session_id="session",
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new_message=types.Content(
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role="user",
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parts=[types.Part(text="What is the weather in New York?")],
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),
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):
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if event.is_final_response() and event.content and event.content.parts:
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print(event.content.parts[0].text.strip())
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if __name__ == "__main__":
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asyncio.run(main())
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```
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## View Traces in the Dashboard
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Run the agent, then open your project in the [Future AGI
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dashboard](https://app.futureagi.com). Each ADK agent run produces a
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hierarchical trace with prompts, completions, model parameters, token usage,
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tool inputs and outputs, and event-loop cycles laid out for inspection.
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## Resources
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- [`traceai-google-adk` on PyPI](https://pypi.org/project/traceai-google-adk/)
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- [`traceAI` on GitHub](https://github.com/future-agi/traceAI/tree/main/python/frameworks/google-adk)
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- [Future AGI documentation](https://docs.futureagi.com)
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