litellm/tests/local_testing/test_rules.py
Krish Dholakia d57be47b0f
Litellm ruff linting enforcement (#5992)
* 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
2024-10-01 19:44:20 -04:00

147 lines
4.5 KiB
Python

#### What this tests ####
# This tests setting rules before / after making llm api calls
import asyncio
import os
import sys
import time
import traceback
import pytest
sys.path.insert(
0, os.path.abspath("../..")
) # Adds the parent directory to the system path
import litellm
from litellm import acompletion, completion
def my_pre_call_rule(input: str):
print(f"input: {input}")
print(f"INSIDE MY PRE CALL RULE, len(input) - {len(input)}")
if len(input) > 10:
return False
return True
## Test 1: Pre-call rule
def test_pre_call_rule():
try:
litellm.pre_call_rules = [my_pre_call_rule]
### completion
response = completion(
model="gpt-3.5-turbo",
messages=[{"role": "user", "content": "say something inappropriate"}],
)
pytest.fail(f"Completion call should have been failed. ")
except Exception:
pass
### async completion
async def test_async_response():
user_message = "Hello, how are you?"
messages = [{"content": user_message, "role": "user"}]
try:
response = await acompletion(model="gpt-3.5-turbo", messages=messages)
pytest.fail(f"acompletion call should have been failed. ")
except Exception as e:
pass
asyncio.run(test_async_response())
litellm.pre_call_rules = []
def my_post_call_rule(input: str):
input = input.lower()
print(f"input: {input}")
print(f"INSIDE MY POST CALL RULE, len(input) - {len(input)}")
if len(input) < 200:
return {
"decision": False,
"message": "This violates LiteLLM Proxy Rules. Response too short",
}
return {"decision": True}
def my_post_call_rule_2(input: str):
input = input.lower()
print(f"input: {input}")
print(f"INSIDE MY POST CALL RULE, len(input) - {len(input)}")
if len(input) < 200 and len(input) > 0:
return {
"decision": False,
"message": "This violates LiteLLM Proxy Rules. Response too short",
}
return {"decision": True}
# test_pre_call_rule()
# Test 2: Post-call rule
# commenting out of ci/cd since llm's have variable output which was causing our pipeline to fail erratically.
def test_post_call_rule():
try:
litellm.pre_call_rules = []
litellm.post_call_rules = [my_post_call_rule]
### completion
response = completion(
model="gpt-3.5-turbo",
messages=[{"role": "user", "content": "say sorry"}],
max_tokens=2,
)
pytest.fail(f"Completion call should have been failed. ")
except Exception as e:
print("Got exception", e)
print(type(e))
print(vars(e))
assert e.message == "This violates LiteLLM Proxy Rules. Response too short"
pass
# print(f"MAKING ACOMPLETION CALL")
# litellm.set_verbose = True
### async completion
# async def test_async_response():
# messages=[{"role": "user", "content": "say sorry"}]
# try:
# response = await acompletion(model="gpt-3.5-turbo", messages=messages)
# pytest.fail(f"acompletion call should have been failed.")
# except Exception as e:
# pass
# asyncio.run(test_async_response())
litellm.pre_call_rules = []
litellm.post_call_rules = []
# test_post_call_rule()
def test_post_call_rule_streaming():
try:
litellm.pre_call_rules = []
litellm.post_call_rules = [my_post_call_rule_2]
### completion
response = completion(
model="gpt-3.5-turbo",
messages=[{"role": "user", "content": "say sorry"}],
max_tokens=2,
stream=True,
)
for chunk in response:
print(f"chunk: {chunk}")
pytest.fail(f"Completion call should have been failed. ")
except Exception as e:
print("Got exception", e)
print(type(e))
print(vars(e))
assert "This violates LiteLLM Proxy Rules. Response too short" in e.message
@pytest.mark.asyncio
async def test_post_call_processing_error_async_response():
try:
response = await acompletion(
model="command-nightly", # Just used as an example
messages=[{"content": "Hello, how are you?", "role": "user"}],
api_base="https://openai-proxy.berriai.repl.co", # Just used as an example
custom_llm_provider="openai",
)
pytest.fail("This call should have failed")
except Exception as e:
pass