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Litellm ruff linting enforcement (#5992)

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* ci(config.yml): add a 'check_code_quality' step

Addresses https://github.com/BerriAI/litellm/issues/5991

* ci(config.yml): check why circle ci doesn't pick up this test

* ci(config.yml): fix to run 'check_code_quality' tests

* fix(__init__.py): fix unprotected import

* fix(__init__.py): don't remove unused imports

* build(ruff.toml): update ruff.toml to ignore unused imports

* fix: fix: ruff + pyright - fix linting + type-checking errors

* fix: fix linting errors

* fix(lago.py): fix module init error

* fix: fix linting errors

* ci(config.yml): cd into correct dir for checks

* fix(proxy_server.py): fix linting error

* fix(utils.py): fix bare except

causes ruff linting errors

* fix: ruff - fix remaining linting errors

* fix(clickhouse.py): use standard logging object

* fix(__init__.py): fix unprotected import

* fix: ruff - fix linting errors

* fix: fix linting errors

* ci(config.yml): cleanup code qa step (formatting handled in local_testing)

* fix(_health_endpoints.py): fix ruff linting errors

* ci(config.yml): just use ruff in check_code_quality pipeline for now

* build(custom_guardrail.py): include missing file

* style(embedding_handler.py): fix ruff check
This commit is contained in:
Krish Dholakia 2024-10-01 16:44:20 -07:00 • committed by GitHub
parent 3fc4ae0d65
commit d57be47b0f
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263 changed files with 1687 additions and 3320 deletions
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8
litellm/llms/nlp_cloud.py
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@ -120,7 +120,7 @@ def completion(
encoding,
api_key,
logging_obj,
optional_params=None,
optional_params: dict,
litellm_params=None,
logger_fn=None,
default_max_tokens_to_sample=None,
@ -164,7 +164,7 @@ def completion(
data=json.dumps(data),
stream=optional_params["stream"] if "stream" in optional_params else False,
)
if "stream" in optional_params and optional_params["stream"] == True:
if "stream" in optional_params and optional_params["stream"] is True:
return clean_and_iterate_chunks(response)
else:
## LOGGING
@ -178,7 +178,7 @@ def completion(
## RESPONSE OBJECT
try:
completion_response = response.json()
except:
except Exception:
raise NLPCloudError(message=response.text, status_code=response.status_code)
if "error" in completion_response:
raise NLPCloudError(
@ -191,7 +191,7 @@ def completion(
model_response.choices[0].message.content = ( # type: ignore
completion_response["generated_text"]
)
except:
except Exception:
raise NLPCloudError(
message=json.dumps(completion_response),
status_code=response.status_code,