gen_ai.choice log reports gen_ai.system=gemini for OpenAI and Groq models through LiteLlm #7631

import asyncio
import os

os.environ["ADK_TELEMETRY_SCHEMA_VERSION_OPT_IN"] = "1"

from opentelemetry import _logs, trace
from opentelemetry.sdk._logs import LoggerProvider
from opentelemetry.sdk._logs.export import InMemoryLogRecordExporter, SimpleLogRecordProcessor
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import SimpleSpanProcessor
from opentelemetry.sdk.trace.export.in_memory_span_exporter import InMemorySpanExporter

spans, logs = InMemorySpanExporter(), InMemoryLogRecordExporter()
tp = TracerProvider()
tp.add_span_processor(SimpleSpanProcessor(spans))
trace.set_tracer_provider(tp)
lp = LoggerProvider()
lp.add_log_record_processor(SimpleLogRecordProcessor(logs))
_logs.set_logger_provider(lp)

from google.adk.agents import Agent
from google.adk.models.lite_llm import LiteLlm
from google.adk.runners import InMemoryRunner
from google.genai import types


async def run(model_id):
  spans.clear()
  logs.clear()
  model = LiteLlm(model=model_id, mock_response="hi", api_key="unused")
  runner = InMemoryRunner(agent=Agent(name="a", model=model), app_name="p")
  session = await runner.session_service.create_session(app_name="p", user_id="u")
  msg = types.Content(role="user", parts=[types.Part(text="hello")])
  async for _ in runner.run_async(user_id="u", session_id=session.id, new_message=msg):
    pass
  await runner.close()
  span = next(s for s in spans.get_finished_spans() if s.name.startswith("generate_content"))
  print(model_id)
  print("   span gen_ai.system:", span.attributes.get("gen_ai.system"))
  for r in logs.get_finished_logs():
    rec = r.log_record
    print("  ", rec.event_name, "gen_ai.system:", rec.attributes.get("gen_ai.system"))


for m in ("openai/gpt-4o", "groq/llama-3.1-8b-instant", "anthropic/claude-sonnet-4-5"):
  asyncio.run(run(m))