0.0.33

a2a-llm-tracker

Track LLM usage and costs across providers (OpenAI, Gemini, Anthropic, etc.) from a single place.

Installation

pip install a2a-llm-tracker

Quick Start (Recommended Pattern)

For applications making multiple LLM calls, use a singleton pattern to initialize once and reuse everywhere.

Step 1: Create a tracking module

Create tracking.py in your project:

# tracking.py
from dotenv import load_dotenv
import os
import asyncio
import concurrent.futures

load_dotenv()

_meter = None

def get_meter():
    """Get or initialize the global meter singleton."""
    global _meter
    if _meter is None:
        try:
            from a2a_llm_tracker import init

            client_id = os.getenv("CLIENT_ID", "")
            client_secret = os.getenv("CLIENT_SECRET", "")
            client_server = os.getenv("CLIENT_SERVER", "https://a2aorchestra.com")

            with concurrent.futures.ThreadPoolExecutor() as executor:
                future = executor.submit(
                    asyncio.run,
                    init(client_id, client_secret, "my-app", client_server)
                )
                _meter = future.result(timeout=5)

        except Exception as e:
            print(f"LLM tracking initialization failed: {e}")
            return None
    return _meter

Step 2: Use it anywhere

import os
from openai import OpenAI
from tracking import get_meter

def call_openai(prompt: str):
    client = OpenAI()
    response = client.chat.completions.create(
        model="gpt-4o-mini",
        messages=[{"role": "user", "content": prompt}],
    )

    # Track usage
    try:
        from a2a_llm_tracker import analyze_response, ResponseType

        meter = get_meter()
        agent_id = os.getenv("AGENT_ID")  # Add AGENT_ID to your .env file

        if meter:
            analyze_response(response, ResponseType.OPENAI, meter, agent_id=int(agent_id))
    except Exception as e:
        print("LLM tracking skipped")

    return response

Environment Variables

Set your credentials in .env file or export them:

CLIENT_ID=your_client_id
CLIENT_SECRET=your_client_secret
CLIENT_SERVER=https://a2aorchestra.com  # optional, this is the default
AGENT_ID=my-agent  # optional, for tracking which agent made the call
OPENAI_API_KEY=sk-xxxxx

Query Total Usage & Costs

Retrieve your accumulated costs and token usage from CCS:

import os
import asyncio
from a2a_llm_tracker import init
from a2a_llm_tracker.sources import CCSSource

async def get_total_usage():
    client_id = os.getenv("CLIENT_ID")
    client_secret = os.getenv("CLIENT_SECRET")

    await init(
        client_id=client_id,
        client_secret=client_secret,
        application_name="my-app",
    )

    source = CCSSource(int(client_id))
    total_cost = await source.count_cost()
    total_tokens = await source.count_total_tokens()

    print(f"Total cost: ${total_cost:.4f}")
    print(f"Total tokens: {total_tokens}")

asyncio.run(get_total_usage())

Request Tracking (Multiple LLM Calls per Request)

Track multiple LLM calls as a single request using set_request_id and set_session_id. These work with any framework - no Starlette required.

Basic Usage (Any Framework)

from a2a_llm_tracker import set_request_id, set_session_id, generate_id

def handle_request():
    # Set at the start of each request - all LLM calls get these IDs automatically
    set_request_id(generate_id())
    set_session_id("user-session-123")

    # All LLM calls anywhere in this request share the same IDs
    step_one()
    step_two()
    step_three()

Flask

from flask import Flask, request
from a2a_llm_tracker import set_request_id, set_session_id, generate_id

app = Flask(__name__)

@app.before_request
def before_request():
    set_request_id(request.headers.get("X-Request-ID") or generate_id())
    set_session_id(request.headers.get("X-Session-ID") or generate_id())

Django

# middleware.py
from a2a_llm_tracker import set_request_id, set_session_id, generate_id

class LLMTrackerMiddleware:
    def __init__(self, get_response):
        self.get_response = get_response

    def __call__(self, request):
        set_request_id(request.headers.get("X-Request-ID") or generate_id())
        set_session_id(request.headers.get("X-Session-ID") or generate_id())
        return self.get_response(request)

FastAPI/Starlette (Optional)

If you have Starlette installed, you can use the built-in middleware:

from fastapi import FastAPI
from a2a_llm_tracker import TrackerMiddleware

app = FastAPI()
app.add_middleware(TrackerMiddleware)

TrackerMiddleware now also reads and propagates call-lineage headers when present:

• X-Call-ID
• X-Parent-Call-ID
• X-Sequence-Number

Calling Backend Proxy Agents With Tracking IDs

Use call_agent to call your backend agent URL and automatically forward the current tracking IDs:

• X-Request-ID
• X-Session-ID
• X-Trace-ID

from a2a_llm_tracker import call_agent, set_request_id, set_session_id, set_context

set_request_id("req-123")
set_session_id("sess-123")
set_context(trace_id="trace-123")

response = call_agent(
    "https://my-backend-agent.example.com/run",
    payload={"task": "summarize this"},
)

Async usage:

from a2a_llm_tracker import call_agent_async

response = await call_agent_async(
    "https://my-backend-agent.example.com/run",
    payload={"task": "summarize this"},
)

High-Level A2A/Orchestra Agent Call (Recommended)

Use call_orchestra_agent when you just want to pass text (or parts) and let the SDK:

• build JSON-RPC payload
• handle message/send vs message/stream
• parse response text
• persist returned tracking headers
• auto-generate call lineage headers (X-Call-ID, X-Parent-Call-ID, X-Sequence-Number)
• automatically send bearer auth using CCS token when available (or user_token override)

from a2a_llm_tracker import call_orchestra_agent

result = call_orchestra_agent(
    input_message="Summarize this contract in 3 bullet points.",
    agent_url="https://node.a2aorchestra.com/api/v1/agents/sendmessage/123/.well-known/agent-card.json",
    stream=False,
    debug=True,  # include request headers + payload in result (auth redacted)
)

print(result["success"], result["text"])
print(result["trace_id"], result["session_id"], result["request_id"])
print(result["call_id"], result["parent_call_id"], result["sequence_number"])

Streaming mode (SSE parsed automatically):

result = call_orchestra_agent(
    agent_id="123",  # optional if agent_url already includes agent path
    input_message="Write a short poem.",
    stream=True,
)

print(result["text"])      # aggregated text
print(len(result["events"]))  # parsed SSE events

Override parent linkage manually (optional):

result = call_orchestra_agent(
    agent_id="123",
    input_message="Next step",
    parent_call_id="my-parent-call-id",
)

Multimodal call (text/image/video parts) by passing parts directly:

result = call_orchestra_agent(
    agent_id="123",
    parts=[
        {"kind": "text", "text": "Describe this image"},
        {"kind": "image", "url": "https://example.com/image.jpg"},
    ],
    stream=False,
)

Google ADK Integration

Track LLM usage in Google Agent Development Kit (ADK) agents using the built-in callback:

from google.adk.agents import LlmAgent
from a2a_llm_tracker import create_adk_callback
from tracking import get_meter

meter = get_meter()

agent = LlmAgent(
    name="my_agent",
    model="gemini-2.0-flash",
    instruction="You are a helpful assistant.",
    after_model_callback=create_adk_callback(
        meter=meter,
        agent_id=123,  # Your agent concept ID (integer)
    ),
)

The callback automatically extracts token usage from ADK's LlmResponse.usage_metadata and records it to CCS.

Supported Providers

Documentation

Full documentation available on GitHub:

• LiteLLM Wrapper - Auto-tracking via LiteLLM
• CCS Integration - Centralized tracking setup
• Response Analysis - Direct SDK tracking
• Pricing - Custom pricing configuration
• Building - Development and publishing

What This Package Does NOT Do

• Guess exact billing from raw text
• Replace provider SDKs
• Upload data anywhere automatically
• Require a backend or SaaS