litellm/tests/local_testing/test_config.py

290 lines
8.2 KiB
Python

# What is this?
## Unit tests for ProxyConfig class
import os
import sys
import traceback
from dotenv import load_dotenv
load_dotenv()
import io
import os
sys.path.insert(
0, os.path.abspath("../..")
) # Adds the parent directory to the system path
from typing import Literal
import pytest
from pydantic import BaseModel, ConfigDict
import litellm
from litellm.proxy.common_utils.encrypt_decrypt_utils import encrypt_value
from litellm.proxy.proxy_server import ProxyConfig
from litellm.proxy.utils import DualCache, ProxyLogging
from litellm.types.router import Deployment, LiteLLM_Params, ModelInfo
class DBModel(BaseModel):
model_id: str
model_name: str
model_info: dict
litellm_params: dict
model_config = ConfigDict(protected_namespaces=())
@pytest.mark.asyncio
async def test_delete_deployment():
"""
- Ensure the global llm router is not being reset
- Ensure invalid model is deleted
- Check if model id != model_info["id"], the model_info["id"] is picked
"""
import base64
litellm_params = LiteLLM_Params(
model="azure/chatgpt-v-2",
api_key=os.getenv("AZURE_API_KEY"),
api_base=os.getenv("AZURE_API_BASE"),
api_version=os.getenv("AZURE_API_VERSION"),
)
encrypted_litellm_params = litellm_params.dict(exclude_none=True)
master_key = "sk-1234"
setattr(litellm.proxy.proxy_server, "master_key", master_key)
for k, v in encrypted_litellm_params.items():
if isinstance(v, str):
encrypted_value = encrypt_value(v, master_key)
encrypted_litellm_params[k] = base64.b64encode(encrypted_value).decode(
"utf-8"
)
deployment = Deployment(model_name="gpt-3.5-turbo", litellm_params=litellm_params)
deployment_2 = Deployment(
model_name="gpt-3.5-turbo-2", litellm_params=litellm_params
)
llm_router = litellm.Router(
model_list=[
deployment.to_json(exclude_none=True),
deployment_2.to_json(exclude_none=True),
]
)
setattr(litellm.proxy.proxy_server, "llm_router", llm_router)
print(f"llm_router: {llm_router}")
pc = ProxyConfig()
db_model = DBModel(
model_id=deployment.model_info.id,
model_name="gpt-3.5-turbo",
litellm_params=encrypted_litellm_params,
model_info={"id": deployment.model_info.id},
)
db_models = [db_model]
deleted_deployments = await pc._delete_deployment(db_models=db_models)
assert deleted_deployments == 1
assert len(llm_router.model_list) == 1
"""
Scenario 2 - if model id != model_info["id"]
"""
llm_router = litellm.Router(
model_list=[
deployment.to_json(exclude_none=True),
deployment_2.to_json(exclude_none=True),
]
)
print(f"llm_router: {llm_router}")
setattr(litellm.proxy.proxy_server, "llm_router", llm_router)
pc = ProxyConfig()
db_model = DBModel(
model_id=deployment.model_info.id,
model_name="gpt-3.5-turbo",
litellm_params=encrypted_litellm_params,
model_info={"id": deployment.model_info.id},
)
db_models = [db_model]
deleted_deployments = await pc._delete_deployment(db_models=db_models)
assert deleted_deployments == 1
assert len(llm_router.model_list) == 1
@pytest.mark.asyncio
async def test_add_existing_deployment():
"""
- Only add new models
- don't re-add existing models
"""
import base64
litellm_params = LiteLLM_Params(
model="gpt-3.5-turbo",
api_key=os.getenv("AZURE_API_KEY"),
api_base=os.getenv("AZURE_API_BASE"),
api_version=os.getenv("AZURE_API_VERSION"),
)
deployment = Deployment(model_name="gpt-3.5-turbo", litellm_params=litellm_params)
deployment_2 = Deployment(
model_name="gpt-3.5-turbo-2", litellm_params=litellm_params
)
llm_router = litellm.Router(
model_list=[
deployment.to_json(exclude_none=True),
deployment_2.to_json(exclude_none=True),
]
)
init_len_list = len(llm_router.model_list)
print(f"llm_router: {llm_router}")
master_key = "sk-1234"
setattr(litellm.proxy.proxy_server, "llm_router", llm_router)
setattr(litellm.proxy.proxy_server, "master_key", master_key)
pc = ProxyConfig()
encrypted_litellm_params = litellm_params.dict(exclude_none=True)
for k, v in encrypted_litellm_params.items():
if isinstance(v, str):
encrypted_value = encrypt_value(v, master_key)
encrypted_litellm_params[k] = base64.b64encode(encrypted_value).decode(
"utf-8"
)
db_model = DBModel(
model_id=deployment.model_info.id,
model_name="gpt-3.5-turbo",
litellm_params=encrypted_litellm_params,
model_info={"id": deployment.model_info.id},
)
db_models = [db_model]
num_added = pc._add_deployment(db_models=db_models)
assert init_len_list == len(llm_router.model_list)
litellm_params = LiteLLM_Params(
model="azure/chatgpt-v-2",
api_key=os.getenv("AZURE_API_KEY"),
api_base=os.getenv("AZURE_API_BASE"),
api_version=os.getenv("AZURE_API_VERSION"),
)
deployment = Deployment(model_name="gpt-3.5-turbo", litellm_params=litellm_params)
deployment_2 = Deployment(model_name="gpt-3.5-turbo-2", litellm_params=litellm_params)
def _create_model_list(flag_value: Literal[0, 1], master_key: str):
"""
0 - empty list
1 - list with an element
"""
import base64
new_litellm_params = LiteLLM_Params(
model="azure/chatgpt-v-2-3",
api_key=os.getenv("AZURE_API_KEY"),
api_base=os.getenv("AZURE_API_BASE"),
api_version=os.getenv("AZURE_API_VERSION"),
)
encrypted_litellm_params = new_litellm_params.dict(exclude_none=True)
for k, v in encrypted_litellm_params.items():
if isinstance(v, str):
encrypted_value = encrypt_value(v, master_key)
encrypted_litellm_params[k] = base64.b64encode(encrypted_value).decode(
"utf-8"
)
db_model = DBModel(
model_id="12345",
model_name="gpt-3.5-turbo",
litellm_params=encrypted_litellm_params,
model_info={"id": "12345"},
)
db_models = [db_model]
if flag_value == 0:
return []
elif flag_value == 1:
return db_models
@pytest.mark.parametrize(
"llm_router",
[
None,
litellm.Router(),
litellm.Router(
model_list=[
deployment.to_json(exclude_none=True),
deployment_2.to_json(exclude_none=True),
]
),
],
)
@pytest.mark.parametrize(
"model_list_flag_value",
[0, 1],
)
@pytest.mark.asyncio
async def test_add_and_delete_deployments(llm_router, model_list_flag_value):
"""
Test add + delete logic in 3 scenarios
- when router is none
- when router is init but empty
- when router is init and not empty
"""
master_key = "sk-1234"
setattr(litellm.proxy.proxy_server, "llm_router", llm_router)
setattr(litellm.proxy.proxy_server, "master_key", master_key)
pc = ProxyConfig()
pl = ProxyLogging(DualCache())
async def _monkey_patch_get_config(*args, **kwargs):
print(f"ENTERS MP GET CONFIG")
if llm_router is None:
return {}
else:
print(f"llm_router.model_list: {llm_router.model_list}")
return {"model_list": llm_router.model_list}
pc.get_config = _monkey_patch_get_config
model_list = _create_model_list(
flag_value=model_list_flag_value, master_key=master_key
)
if llm_router is None:
prev_llm_router_val = None
else:
prev_llm_router_val = len(llm_router.model_list)
await pc._update_llm_router(new_models=model_list, proxy_logging_obj=pl)
llm_router = getattr(litellm.proxy.proxy_server, "llm_router")
if model_list_flag_value == 0:
if prev_llm_router_val is None:
assert prev_llm_router_val == llm_router
else:
assert prev_llm_router_val == len(llm_router.model_list)
else:
if prev_llm_router_val is None:
assert len(llm_router.model_list) == len(model_list)
else:
assert len(llm_router.model_list) == len(model_list) + prev_llm_router_val