mirror of
https://github.com/BerriAI/litellm.git
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382 lines
No EOL
13 KiB
Python
382 lines
No EOL
13 KiB
Python
#### What this tests ####
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# This tests error logging (with custom user functions) for the raw `completion` + `embedding` endpoints
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# Test Scenarios (test across completion, streaming, embedding)
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## 1: Pre-API-Call
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## 2: Post-API-Call
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## 3: On LiteLLM Call success
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## 4: On LiteLLM Call failure
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import sys, os, io
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import traceback, logging
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import pytest
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import dotenv
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dotenv.load_dotenv()
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# Create logger
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logger = logging.getLogger(__name__)
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logger.setLevel(logging.DEBUG)
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# Create a stream handler
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stream_handler = logging.StreamHandler(sys.stdout)
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logger.addHandler(stream_handler)
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# Create a function to log information
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def logger_fn(message):
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logger.info(message)
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sys.path.insert(
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0, os.path.abspath("../..")
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) # Adds the parent directory to the system path
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import litellm
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from litellm import embedding, completion
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from openai.error import AuthenticationError
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litellm.set_verbose = True
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score = 0
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user_message = "Hello, how are you?"
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messages = [{"content": user_message, "role": "user"}]
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# 1. On Call Success
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# normal completion
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## test on openai completion call
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def test_logging_success_completion():
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global score
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try:
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# Redirect stdout
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old_stdout = sys.stdout
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sys.stdout = new_stdout = io.StringIO()
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response = completion(model="gpt-3.5-turbo", messages=messages)
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# Restore stdout
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sys.stdout = old_stdout
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output = new_stdout.getvalue().strip()
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if "Logging Details Pre-API Call" not in output:
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raise Exception("Required log message not found!")
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elif "Logging Details Post-API Call" not in output:
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raise Exception("Required log message not found!")
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elif "Logging Details LiteLLM-Success Call" not in output:
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raise Exception("Required log message not found!")
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score += 1
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except Exception as e:
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pytest.fail(f"Error occurred: {e}")
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pass
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## test on non-openai completion call
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def test_logging_success_completion_non_openai():
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global score
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try:
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# Redirect stdout
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old_stdout = sys.stdout
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sys.stdout = new_stdout = io.StringIO()
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response = completion(model="claude-instant-1", messages=messages)
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# Restore stdout
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sys.stdout = old_stdout
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output = new_stdout.getvalue().strip()
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if "Logging Details Pre-API Call" not in output:
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raise Exception("Required log message not found!")
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elif "Logging Details Post-API Call" not in output:
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raise Exception("Required log message not found!")
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elif "Logging Details LiteLLM-Success Call" not in output:
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raise Exception("Required log message not found!")
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score += 1
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except Exception as e:
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pytest.fail(f"Error occurred: {e}")
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pass
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# # streaming completion
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# ## test on openai completion call
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# def test_logging_success_streaming_openai():
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# global score
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# try:
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# # litellm.set_verbose = False
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# def custom_callback(
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# kwargs, # kwargs to completion
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# completion_response, # response from completion
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# start_time, end_time # start/end time
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# ):
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# if "complete_streaming_response" in kwargs:
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# print(f"Complete Streaming Response: {kwargs['complete_streaming_response']}")
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# # Assign the custom callback function
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# litellm.success_callback = [custom_callback]
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# # Redirect stdout
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# old_stdout = sys.stdout
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# sys.stdout = new_stdout = io.StringIO()
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# response = completion(model="gpt-3.5-turbo", messages=messages, stream=True)
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# for chunk in response:
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# pass
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# # Restore stdout
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# sys.stdout = old_stdout
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# output = new_stdout.getvalue().strip()
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# if "Logging Details Pre-API Call" not in output:
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# raise Exception("Required log message not found!")
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# elif "Logging Details Post-API Call" not in output:
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# raise Exception("Required log message not found!")
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# elif "Logging Details LiteLLM-Success Call" not in output:
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# raise Exception("Required log message not found!")
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# elif "Complete Streaming Response:" not in output:
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# raise Exception("Required log message not found!")
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# score += 1
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# except Exception as e:
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# pytest.fail(f"Error occurred: {e}")
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# pass
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# # test_logging_success_streaming_openai()
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# ## test on non-openai completion call
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# def test_logging_success_streaming_non_openai():
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# global score
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# try:
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# # litellm.set_verbose = False
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# def custom_callback(
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# kwargs, # kwargs to completion
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# completion_response, # response from completion
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# start_time, end_time # start/end time
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# ):
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# # print(f"streaming response: {completion_response}")
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# if "complete_streaming_response" in kwargs:
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# print(f"Complete Streaming Response: {kwargs['complete_streaming_response']}")
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# # Assign the custom callback function
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# litellm.success_callback = [custom_callback]
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# # Redirect stdout
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# old_stdout = sys.stdout
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# sys.stdout = new_stdout = io.StringIO()
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# response = completion(model="claude-instant-1", messages=messages, stream=True)
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# for idx, chunk in enumerate(response):
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# pass
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# # Restore stdout
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# sys.stdout = old_stdout
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# output = new_stdout.getvalue().strip()
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# if "Logging Details Pre-API Call" not in output:
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# raise Exception("Required log message not found!")
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# elif "Logging Details Post-API Call" not in output:
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# raise Exception("Required log message not found!")
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# elif "Logging Details LiteLLM-Success Call" not in output:
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# raise Exception("Required log message not found!")
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# elif "Complete Streaming Response:" not in output:
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# raise Exception(f"Required log message not found! {output}")
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# score += 1
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# except Exception as e:
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# pytest.fail(f"Error occurred: {e}")
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# pass
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# # test_logging_success_streaming_non_openai()
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# # embedding
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# def test_logging_success_embedding_openai():
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# try:
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# # Redirect stdout
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# old_stdout = sys.stdout
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# sys.stdout = new_stdout = io.StringIO()
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# response = embedding(model="text-embedding-ada-002", input=["good morning from litellm"])
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# # Restore stdout
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# sys.stdout = old_stdout
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# output = new_stdout.getvalue().strip()
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# if "Logging Details Pre-API Call" not in output:
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# raise Exception("Required log message not found!")
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# elif "Logging Details Post-API Call" not in output:
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# raise Exception("Required log message not found!")
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# elif "Logging Details LiteLLM-Success Call" not in output:
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# raise Exception("Required log message not found!")
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# except Exception as e:
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# pytest.fail(f"Error occurred: {e}")
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# # ## 2. On LiteLLM Call failure
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# # ## TEST BAD KEY
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# # # normal completion
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# # ## test on openai completion call
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# # try:
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# # temporary_oai_key = os.environ["OPENAI_API_KEY"]
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# # os.environ["OPENAI_API_KEY"] = "bad-key"
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# # temporary_anthropic_key = os.environ["ANTHROPIC_API_KEY"]
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# # os.environ["ANTHROPIC_API_KEY"] = "bad-key"
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# # # Redirect stdout
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# # old_stdout = sys.stdout
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# # sys.stdout = new_stdout = io.StringIO()
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# # try:
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# # response = completion(model="gpt-3.5-turbo", messages=messages)
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# # except AuthenticationError:
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# # print(f"raised auth error")
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# # pass
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# # # Restore stdout
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# # sys.stdout = old_stdout
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# # output = new_stdout.getvalue().strip()
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# # print(output)
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# # if "Logging Details Pre-API Call" not in output:
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# # raise Exception("Required log message not found!")
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# # elif "Logging Details Post-API Call" not in output:
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# # raise Exception("Required log message not found!")
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# # elif "Logging Details LiteLLM-Failure Call" not in output:
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# # raise Exception("Required log message not found!")
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# # os.environ["OPENAI_API_KEY"] = temporary_oai_key
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# # os.environ["ANTHROPIC_API_KEY"] = temporary_anthropic_key
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# # score += 1
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# # except Exception as e:
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# # print(f"exception type: {type(e).__name__}")
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# # pytest.fail(f"Error occurred: {e}")
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# # pass
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# # ## test on non-openai completion call
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# # try:
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# # temporary_oai_key = os.environ["OPENAI_API_KEY"]
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# # os.environ["OPENAI_API_KEY"] = "bad-key"
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# # temporary_anthropic_key = os.environ["ANTHROPIC_API_KEY"]
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# # os.environ["ANTHROPIC_API_KEY"] = "bad-key"
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# # # Redirect stdout
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# # old_stdout = sys.stdout
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# # sys.stdout = new_stdout = io.StringIO()
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# # try:
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# # response = completion(model="claude-instant-1", messages=messages)
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# # except AuthenticationError:
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# # pass
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# # if "Logging Details Pre-API Call" not in output:
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# # raise Exception("Required log message not found!")
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# # elif "Logging Details Post-API Call" not in output:
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# # raise Exception("Required log message not found!")
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# # elif "Logging Details LiteLLM-Failure Call" not in output:
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# # raise Exception("Required log message not found!")
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# # os.environ["OPENAI_API_KEY"] = temporary_oai_key
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# # os.environ["ANTHROPIC_API_KEY"] = temporary_anthropic_key
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# # score += 1
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# # except Exception as e:
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# # print(f"exception type: {type(e).__name__}")
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# # # Restore stdout
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# # sys.stdout = old_stdout
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# # output = new_stdout.getvalue().strip()
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# # print(output)
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# # pytest.fail(f"Error occurred: {e}")
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# # # streaming completion
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# # ## test on openai completion call
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# # try:
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# # temporary_oai_key = os.environ["OPENAI_API_KEY"]
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# # os.environ["OPENAI_API_KEY"] = "bad-key"
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# # temporary_anthropic_key = os.environ["ANTHROPIC_API_KEY"]
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# # os.environ["ANTHROPIC_API_KEY"] = "bad-key"
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# # # Redirect stdout
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# # old_stdout = sys.stdout
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# # sys.stdout = new_stdout = io.StringIO()
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# # try:
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# # response = completion(model="gpt-3.5-turbo", messages=messages)
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# # except AuthenticationError:
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# # pass
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# # # Restore stdout
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# # sys.stdout = old_stdout
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# # output = new_stdout.getvalue().strip()
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# # print(output)
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# # if "Logging Details Pre-API Call" not in output:
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# # raise Exception("Required log message not found!")
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# # elif "Logging Details Post-API Call" not in output:
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# # raise Exception("Required log message not found!")
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# # elif "Logging Details LiteLLM-Failure Call" not in output:
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# # raise Exception("Required log message not found!")
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# # os.environ["OPENAI_API_KEY"] = temporary_oai_key
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# # os.environ["ANTHROPIC_API_KEY"] = temporary_anthropic_key
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# # score += 1
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# # except Exception as e:
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# # print(f"exception type: {type(e).__name__}")
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# # pytest.fail(f"Error occurred: {e}")
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# # ## test on non-openai completion call
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# # try:
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# # temporary_oai_key = os.environ["OPENAI_API_KEY"]
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# # os.environ["OPENAI_API_KEY"] = "bad-key"
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# # temporary_anthropic_key = os.environ["ANTHROPIC_API_KEY"]
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# # os.environ["ANTHROPIC_API_KEY"] = "bad-key"
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# # # Redirect stdout
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# # old_stdout = sys.stdout
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# # sys.stdout = new_stdout = io.StringIO()
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# # try:
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# # response = completion(model="claude-instant-1", messages=messages)
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# # except AuthenticationError:
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# # pass
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# # # Restore stdout
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# # sys.stdout = old_stdout
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# # output = new_stdout.getvalue().strip()
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# # print(output)
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# # if "Logging Details Pre-API Call" not in output:
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# # raise Exception("Required log message not found!")
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# # elif "Logging Details Post-API Call" not in output:
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# # raise Exception("Required log message not found!")
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# # elif "Logging Details LiteLLM-Failure Call" not in output:
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# # raise Exception("Required log message not found!")
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# # score += 1
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# # except Exception as e:
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# # print(f"exception type: {type(e).__name__}")
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# # pytest.fail(f"Error occurred: {e}")
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# # # embedding
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# # try:
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# # temporary_oai_key = os.environ["OPENAI_API_KEY"]
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# # os.environ["OPENAI_API_KEY"] = "bad-key"
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# # temporary_anthropic_key = os.environ["ANTHROPIC_API_KEY"]
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# # os.environ["ANTHROPIC_API_KEY"] = "bad-key"
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# # # Redirect stdout
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# # old_stdout = sys.stdout
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# # sys.stdout = new_stdout = io.StringIO()
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# # try:
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# # response = embedding(model="text-embedding-ada-002", input=["good morning from litellm"])
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# # except AuthenticationError:
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# # pass
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# # # Restore stdout
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# # sys.stdout = old_stdout
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# # output = new_stdout.getvalue().strip()
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# # print(output)
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# # if "Logging Details Pre-API Call" not in output:
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# # raise Exception("Required log message not found!")
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# # elif "Logging Details Post-API Call" not in output:
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# # raise Exception("Required log message not found!")
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# # elif "Logging Details LiteLLM-Failure Call" not in output:
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# # raise Exception("Required log message not found!")
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# # except Exception as e:
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# # print(f"exception type: {type(e).__name__}")
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# # pytest.fail(f"Error occurred: {e}") |