c1602587c1
* fix(tests): drop module-level test calls that break local_testing collection Several files in tests/local_testing invoked their test functions at module scope (e.g. test_register_model.py ran test_update_model_cost_via_completion() at the bottom of the file). Those calls execute during pytest collection, so they fire real network requests at import time. test_register_model.py's call hit an OpenAI 429 and raised, turning into a collection error. A collection error aborts the whole session for every job that globs tests/local_testing/**/test_*.py, which is why unrelated jobs like langfuse_logging_unit_tests (-k langfuse) and litellm_assistants_api_testing (-k assistants) both failed even though neither touches register_model; the -k filter only applies after collection. pytest discovers and runs these test_* functions on its own, so the top-level calls were dead and harmful. Removes them from test_register_model.py, test_wandb.py, test_lunary.py, and test_multiple_deployments.py, and adds a regression test that scans the directory for module-level test invocations. * test(local_testing): skip unparseable files in module-scope invocation guardrail A syntax error in any tests/local_testing file would make ast.parse raise an unhandled SyntaxError, so the guardrail itself would crash with a confusing traceback instead of its assertion message. Such a file already fails pytest collection on its own, which is the clearer signal, so the guardrail now skips files it cannot parse and stays focused on detecting module-scope test calls. Reads files as utf-8 for deterministic behavior across platforms.
70 lines
1.7 KiB
Python
70 lines
1.7 KiB
Python
import sys
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import os
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import io, asyncio
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# import logging
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# logging.basicConfig(level=logging.DEBUG)
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sys.path.insert(0, os.path.abspath("../.."))
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from litellm import completion
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import litellm
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litellm.num_retries = 3
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litellm.success_callback = ["wandb"]
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import time
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import pytest
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def test_wandb_logging_async():
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try:
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litellm.set_verbose = False
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async def _test_langfuse():
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from litellm import Router
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model_list = [
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{ # list of model deployments
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"model_name": "gpt-3.5-turbo",
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"litellm_params": { # params for litellm completion/embedding call
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"model": "gpt-3.5-turbo",
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"api_key": os.getenv("OPENAI_API_KEY"),
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},
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}
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]
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router = Router(model_list=model_list)
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# openai.ChatCompletion.create replacement
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response = await router.acompletion(
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model="gpt-3.5-turbo",
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messages=[
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{"role": "user", "content": "this is a test with litellm router ?"}
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],
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)
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print(response)
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response = asyncio.run(_test_langfuse())
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print(f"response: {response}")
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except litellm.Timeout as e:
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pass
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except Exception as e:
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pass
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def test_wandb_logging():
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try:
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response = completion(
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model="claude-3-5-haiku-20241022",
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messages=[{"role": "user", "content": "Hi 👋 - i'm claude"}],
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max_tokens=10,
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temperature=0.2,
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)
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print(response)
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except litellm.Timeout as e:
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pass
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except Exception as e:
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print(e)
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# test_wandb_logging()
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