Arize log_evaluations_sync rate limits

arize_scratch_pad.py

import pandas as pd
from src.care_plan_generator.helpers.arize_instrumentation import (
    ARIZE_API_KEY,
    ARIZE_SPACE_ID,
    ARIZE_PROJECT_NAME,
)
from arize.pandas.logger import Client
from pydantic import BaseModel
from time import sleep


class Eval(BaseModel):
    label: str
    name: str
    explanation: str


def log_eval(span_id: str, eval: Eval):
    arize_client = Client(space_id=ARIZE_SPACE_ID, api_key=ARIZE_API_KEY)
    label_key = f"eval.{eval.name}.label"
    label_value = eval.label
    explanation_key = f"eval.{eval.name}.explanation"
    explanation_value = eval.explanation
    eval_data = {
        "context.span_id": [span_id],
        label_key: [label_value],
        explanation_key: [explanation_value],
    }
    eval_df = pd.DataFrame(eval_data)
    eval_df.head()
    arize_client.log_evaluations_sync(
        dataframe=eval_df, project_name=ARIZE_PROJECT_NAME
    )


def log_evals(span_id: str, evals: list[Eval]):
    for eval in evals:
        log_eval(span_id, eval)
        sleep(1)


if __name__ == "__main__":
    # component
    log_evals(
        span_id="obfuscated",
        evals=[
            Eval(
                label="pass",
                name="obfuscated",
                explanation="obfuscated",
            ),
            Eval(
                label="pass",
                name="obfuscated",
                explanation="obfuscated",
            ),
            Eval(
                label="pass",
                name="obfuscated",
                explanation="obfuscated",
            ),
            Eval(
                label="pass",
                name="obfuscated",
                explanation="obfuscated",
            ),
            Eval(
                label="pass",
                name="obfuscated",
                explanation="obfuscated",
            ),
            Eval(
                label="pass",
                name="obfuscated",
                explanation="obfuscated",
            ),
        ],
    )

error.log

Error logging evaluation data to Arize
Traceback (most recent call last):
  File "/Users/kinan/dev/care-plan-generator/.venv/lib/python3.12/site-packages/arize/pandas/logger.py", line 1777, in _log_arrow_flight
    with flight_writer:
         ^^^^^^^^^^^^^
  File "pyarrow/ipc.pxi", line 543, in pyarrow.lib._CRecordBatchWriter.__exit__
  File "pyarrow/_flight.pyx", line 1238, in pyarrow._flight.MetadataRecordBatchWriter.close
  File "pyarrow/_flight.pyx", line 64, in pyarrow._flight.check_flight_status
pyarrow._flight.FlightUnauthenticatedError: Flight returned unauthenticated error, with message: auth-error: rpc error: code = ResourceExhausted desc = Exceeds requests rate limit. gRPC client debug context: UNKNOWN:Error received from peer ipv4:xxx {grpc_message:"auth-error: rpc error: code = ResourceExhausted desc = Exceeds requests rate limit", grpc_status:16, created_time:"2025-07-17T16:55:59.364211-04:00"}. Client context: OK
Error logging evaluation data to Arize
Traceback (most recent call last):
  File "/Users/kinan/dev/care-plan-generator/.venv/lib/python3.12/site-packages/arize/pandas/logger.py", line 1777, in _log_arrow_flight
    with flight_writer:
         ^^^^^^^^^^^^^
  File "pyarrow/ipc.pxi", line 543, in pyarrow.lib._CRecordBatchWriter.__exit__
  File "pyarrow/_flight.pyx", line 1238, in pyarrow._flight.MetadataRecordBatchWriter.close
  File "pyarrow/_flight.pyx", line 64, in pyarrow._flight.check_flight_status
pyarrow._flight.FlightUnauthenticatedError: Flight returned unauthenticated error, with message: auth-error: rpc error: code = ResourceExhausted desc = Exceeds requests rate limit. gRPC client debug context: UNKNOWN:Error received from peer ipv4:xxx {created_time:"2025-07-17T16:56:01.942378-04:00", grpc_status:16, grpc_message:"auth-error: rpc error: code = ResourceExhausted desc = Exceeds requests rate limit"}. Client context: OK