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100 lines
No EOL
3.8 KiB
Python
100 lines
No EOL
3.8 KiB
Python
import asyncio
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import json
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import logging
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from litellm import Choices
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import pytest
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from dotenv import load_dotenv
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import litellm
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from litellm._logging import verbose_logger, verbose_proxy_logger
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from litellm.integrations._types.open_inference import SpanAttributes
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from litellm.integrations.arize.arize import ArizeConfig, ArizeLogger
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load_dotenv()
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@pytest.mark.asyncio()
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async def test_async_otel_callback():
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litellm.set_verbose = True
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verbose_proxy_logger.setLevel(logging.DEBUG)
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verbose_logger.setLevel(logging.DEBUG)
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litellm.success_callback = ["arize"]
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await litellm.acompletion(
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model="gpt-3.5-turbo",
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messages=[{"role": "user", "content": "hi test from local arize"}],
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mock_response="hello",
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temperature=0.1,
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user="OTEL_USER",
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)
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await asyncio.sleep(2)
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@pytest.fixture
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def mock_env_vars(monkeypatch):
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monkeypatch.setenv("ARIZE_SPACE_KEY", "test_space_key")
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monkeypatch.setenv("ARIZE_API_KEY", "test_api_key")
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def test_get_arize_config(mock_env_vars):
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"""
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Use Arize default endpoint when no endpoints are provided
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"""
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config = ArizeLogger.get_arize_config()
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assert isinstance(config, ArizeConfig)
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assert config.space_key == "test_space_key"
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assert config.api_key == "test_api_key"
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assert config.endpoint == "https://otlp.arize.com/v1"
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assert config.protocol == "otlp_grpc"
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def test_get_arize_config_with_endpoints(mock_env_vars, monkeypatch):
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"""
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Use provided endpoints when they are set
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"""
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monkeypatch.setenv("ARIZE_ENDPOINT", "grpc://test.endpoint")
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monkeypatch.setenv("ARIZE_HTTP_ENDPOINT", "http://test.endpoint")
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config = ArizeLogger.get_arize_config()
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assert config.endpoint == "grpc://test.endpoint"
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assert config.protocol == "otlp_grpc"
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def test_arize_set_attributes():
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"""
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Test setting attributes for Arize
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"""
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from unittest.mock import MagicMock
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from litellm.types.utils import ModelResponse
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span = MagicMock()
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kwargs = {
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"role": "user",
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"content": "simple arize test",
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"model": "gpt-4o",
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"messages": [{"role": "user", "content": "basic arize test"}],
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"standard_logging_object": {"model_parameters": {"user": "test_user"}, "metadata": {"key": "value", "key2": None}},
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}
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response_obj = ModelResponse(usage={"total_tokens": 100, "completion_tokens": 60, "prompt_tokens": 40},
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choices=[Choices(message={"role": "assistant", "content": "response content"})])
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ArizeLogger.set_arize_attributes(span, kwargs, response_obj)
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assert span.set_attribute.call_count == 14
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span.set_attribute.assert_any_call(SpanAttributes.METADATA, json.dumps({"key": "value", "key2": None}))
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span.set_attribute.assert_any_call(SpanAttributes.LLM_MODEL_NAME, "gpt-4o")
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span.set_attribute.assert_any_call(SpanAttributes.OPENINFERENCE_SPAN_KIND, "LLM")
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span.set_attribute.assert_any_call(SpanAttributes.INPUT_VALUE, "basic arize test")
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span.set_attribute.assert_any_call("llm.input_messages.0.message.role", "user")
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span.set_attribute.assert_any_call("llm.input_messages.0.message.content", "basic arize test")
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span.set_attribute.assert_any_call(SpanAttributes.LLM_INVOCATION_PARAMETERS, '{"user": "test_user"}')
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span.set_attribute.assert_any_call(SpanAttributes.USER_ID, "test_user")
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span.set_attribute.assert_any_call(SpanAttributes.OUTPUT_VALUE, "response content")
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span.set_attribute.assert_any_call("llm.output_messages.0.message.role", "assistant")
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span.set_attribute.assert_any_call("llm.output_messages.0.message.content", "response content")
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span.set_attribute.assert_any_call(SpanAttributes.LLM_TOKEN_COUNT_TOTAL, 100)
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span.set_attribute.assert_any_call(SpanAttributes.LLM_TOKEN_COUNT_COMPLETION, 60)
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span.set_attribute.assert_any_call(SpanAttributes.LLM_TOKEN_COUNT_PROMPT, 40) |