refactor: add black formatting

This commit is contained in:
Krrish Dholakia 2023-12-25 14:10:38 +05:30
parent b87d630b0a
commit 4905929de3
156 changed files with 19723 additions and 10869 deletions

View file

@ -1,9 +1,10 @@
#### What this tests ####
# This tests calling router with fallback models
# This tests calling router with fallback models
import sys, os, time
import traceback, asyncio
import pytest
sys.path.insert(
0, os.path.abspath("../..")
) # Adds the parent directory to the system path
@ -12,177 +13,204 @@ import litellm
from litellm import Router
from litellm.integrations.custom_logger import CustomLogger
class MyCustomHandler(CustomLogger):
success: bool = False
failure: bool = False
previous_models: int = 0
def log_pre_api_call(self, model, messages, kwargs):
def log_pre_api_call(self, model, messages, kwargs):
print(f"Pre-API Call")
def log_post_api_call(self, kwargs, response_obj, start_time, end_time):
print(f"Post-API Call - response object: {response_obj}; model: {kwargs['model']}")
def log_post_api_call(self, kwargs, response_obj, start_time, end_time):
print(
f"Post-API Call - response object: {response_obj}; model: {kwargs['model']}"
)
def log_stream_event(self, kwargs, response_obj, start_time, end_time):
print(f"On Stream")
def async_log_stream_event(self, kwargs, response_obj, start_time, end_time):
print(f"On Stream")
def log_success_event(self, kwargs, response_obj, start_time, end_time):
print(f"previous_models: {kwargs['litellm_params']['metadata']['previous_models']}")
self.previous_models += len(kwargs["litellm_params"]["metadata"]["previous_models"]) # {"previous_models": [{"model": litellm_model_name, "exception_type": AuthenticationError, "exception_string": <complete_traceback>}]}
print(f"self.previous_models: {self.previous_models}")
print(f"On Success")
async def async_log_success_event(self, kwargs, response_obj, start_time, end_time):
print(f"previous_models: {kwargs['litellm_params']['metadata']['previous_models']}")
self.previous_models += len(kwargs["litellm_params"]["metadata"]["previous_models"]) # {"previous_models": [{"model": litellm_model_name, "exception_type": AuthenticationError, "exception_string": <complete_traceback>}]}
def log_success_event(self, kwargs, response_obj, start_time, end_time):
print(
f"previous_models: {kwargs['litellm_params']['metadata']['previous_models']}"
)
self.previous_models += len(
kwargs["litellm_params"]["metadata"]["previous_models"]
) # {"previous_models": [{"model": litellm_model_name, "exception_type": AuthenticationError, "exception_string": <complete_traceback>}]}
print(f"self.previous_models: {self.previous_models}")
print(f"On Success")
def log_failure_event(self, kwargs, response_obj, start_time, end_time):
async def async_log_success_event(self, kwargs, response_obj, start_time, end_time):
print(
f"previous_models: {kwargs['litellm_params']['metadata']['previous_models']}"
)
self.previous_models += len(
kwargs["litellm_params"]["metadata"]["previous_models"]
) # {"previous_models": [{"model": litellm_model_name, "exception_type": AuthenticationError, "exception_string": <complete_traceback>}]}
print(f"self.previous_models: {self.previous_models}")
print(f"On Success")
def log_failure_event(self, kwargs, response_obj, start_time, end_time):
print(f"On Failure")
kwargs = {"model": "azure/gpt-3.5-turbo", "messages": [{"role": "user", "content":"Hey, how's it going?"}]}
kwargs = {
"model": "azure/gpt-3.5-turbo",
"messages": [{"role": "user", "content": "Hey, how's it going?"}],
}
def test_sync_fallbacks():
def test_sync_fallbacks():
try:
model_list = [
{ # list of model deployments
"model_name": "azure/gpt-3.5-turbo", # openai model name
"litellm_params": { # params for litellm completion/embedding call
"model": "azure/chatgpt-v-2",
{ # list of model deployments
"model_name": "azure/gpt-3.5-turbo", # openai model name
"litellm_params": { # params for litellm completion/embedding call
"model": "azure/chatgpt-v-2",
"api_key": "bad-key",
"api_version": os.getenv("AZURE_API_VERSION"),
"api_base": os.getenv("AZURE_API_BASE")
"api_base": os.getenv("AZURE_API_BASE"),
},
"tpm": 240000,
"rpm": 1800
},
{ # list of model deployments
"model_name": "azure/gpt-3.5-turbo-context-fallback", # openai model name
"litellm_params": { # params for litellm completion/embedding call
"model": "azure/chatgpt-v-2",
"rpm": 1800,
},
{ # list of model deployments
"model_name": "azure/gpt-3.5-turbo-context-fallback", # openai model name
"litellm_params": { # params for litellm completion/embedding call
"model": "azure/chatgpt-v-2",
"api_key": os.getenv("AZURE_API_KEY"),
"api_version": os.getenv("AZURE_API_VERSION"),
"api_base": os.getenv("AZURE_API_BASE")
"api_base": os.getenv("AZURE_API_BASE"),
},
"tpm": 240000,
"rpm": 1800
},
{
"model_name": "azure/gpt-3.5-turbo", # openai model name
"litellm_params": { # params for litellm completion/embedding call
"model": "azure/chatgpt-functioncalling",
"api_key": "bad-key",
"api_version": os.getenv("AZURE_API_VERSION"),
"api_base": os.getenv("AZURE_API_BASE")
},
"tpm": 240000,
"rpm": 1800
},
{
"model_name": "gpt-3.5-turbo", # openai model name
"litellm_params": { # params for litellm completion/embedding call
"model": "gpt-3.5-turbo",
"api_key": os.getenv("OPENAI_API_KEY"),
},
"tpm": 1000000,
"rpm": 9000
"rpm": 1800,
},
{
"model_name": "gpt-3.5-turbo-16k", # openai model name
"litellm_params": { # params for litellm completion/embedding call
"model": "gpt-3.5-turbo-16k",
"model_name": "azure/gpt-3.5-turbo", # openai model name
"litellm_params": { # params for litellm completion/embedding call
"model": "azure/chatgpt-functioncalling",
"api_key": "bad-key",
"api_version": os.getenv("AZURE_API_VERSION"),
"api_base": os.getenv("AZURE_API_BASE"),
},
"tpm": 240000,
"rpm": 1800,
},
{
"model_name": "gpt-3.5-turbo", # openai model name
"litellm_params": { # params for litellm completion/embedding call
"model": "gpt-3.5-turbo",
"api_key": os.getenv("OPENAI_API_KEY"),
},
"tpm": 1000000,
"rpm": 9000
}
"rpm": 9000,
},
{
"model_name": "gpt-3.5-turbo-16k", # openai model name
"litellm_params": { # params for litellm completion/embedding call
"model": "gpt-3.5-turbo-16k",
"api_key": os.getenv("OPENAI_API_KEY"),
},
"tpm": 1000000,
"rpm": 9000,
},
]
litellm.set_verbose = True
customHandler = MyCustomHandler()
litellm.callbacks = [customHandler]
router = Router(model_list=model_list,
fallbacks=[{"azure/gpt-3.5-turbo": ["gpt-3.5-turbo"]}],
context_window_fallbacks=[{"azure/gpt-3.5-turbo-context-fallback": ["gpt-3.5-turbo-16k"]}, {"gpt-3.5-turbo": ["gpt-3.5-turbo-16k"]}],
set_verbose=False)
router = Router(
model_list=model_list,
fallbacks=[{"azure/gpt-3.5-turbo": ["gpt-3.5-turbo"]}],
context_window_fallbacks=[
{"azure/gpt-3.5-turbo-context-fallback": ["gpt-3.5-turbo-16k"]},
{"gpt-3.5-turbo": ["gpt-3.5-turbo-16k"]},
],
set_verbose=False,
)
response = router.completion(**kwargs)
print(f"response: {response}")
time.sleep(0.05) # allow a delay as success_callbacks are on a separate thread
assert customHandler.previous_models == 1 # 0 retries, 1 fallback
time.sleep(0.05) # allow a delay as success_callbacks are on a separate thread
assert customHandler.previous_models == 1 # 0 retries, 1 fallback
print("Passed ! Test router_fallbacks: test_sync_fallbacks()")
router.reset()
except Exception as e:
print(e)
# test_sync_fallbacks()
# test_sync_fallbacks()
@pytest.mark.asyncio
async def test_async_fallbacks():
async def test_async_fallbacks():
litellm.set_verbose = False
model_list = [
{ # list of model deployments
"model_name": "azure/gpt-3.5-turbo", # openai model name
"litellm_params": { # params for litellm completion/embedding call
"model": "azure/chatgpt-v-2",
{ # list of model deployments
"model_name": "azure/gpt-3.5-turbo", # openai model name
"litellm_params": { # params for litellm completion/embedding call
"model": "azure/chatgpt-v-2",
"api_key": "bad-key",
"api_version": os.getenv("AZURE_API_VERSION"),
"api_base": os.getenv("AZURE_API_BASE")
"api_base": os.getenv("AZURE_API_BASE"),
},
"tpm": 240000,
"rpm": 1800
},
{ # list of model deployments
"model_name": "azure/gpt-3.5-turbo-context-fallback", # openai model name
"litellm_params": { # params for litellm completion/embedding call
"model": "azure/chatgpt-v-2",
"rpm": 1800,
},
{ # list of model deployments
"model_name": "azure/gpt-3.5-turbo-context-fallback", # openai model name
"litellm_params": { # params for litellm completion/embedding call
"model": "azure/chatgpt-v-2",
"api_key": os.getenv("AZURE_API_KEY"),
"api_version": os.getenv("AZURE_API_VERSION"),
"api_base": os.getenv("AZURE_API_BASE")
"api_base": os.getenv("AZURE_API_BASE"),
},
"tpm": 240000,
"rpm": 1800
},
{
"model_name": "azure/gpt-3.5-turbo", # openai model name
"litellm_params": { # params for litellm completion/embedding call
"model": "azure/chatgpt-functioncalling",
"api_key": "bad-key",
"api_version": os.getenv("AZURE_API_VERSION"),
"api_base": os.getenv("AZURE_API_BASE")
},
"tpm": 240000,
"rpm": 1800
},
{
"model_name": "gpt-3.5-turbo", # openai model name
"litellm_params": { # params for litellm completion/embedding call
"model": "gpt-3.5-turbo",
"api_key": os.getenv("OPENAI_API_KEY"),
},
"tpm": 1000000,
"rpm": 9000
"rpm": 1800,
},
{
"model_name": "gpt-3.5-turbo-16k", # openai model name
"litellm_params": { # params for litellm completion/embedding call
"model": "gpt-3.5-turbo-16k",
"model_name": "azure/gpt-3.5-turbo", # openai model name
"litellm_params": { # params for litellm completion/embedding call
"model": "azure/chatgpt-functioncalling",
"api_key": "bad-key",
"api_version": os.getenv("AZURE_API_VERSION"),
"api_base": os.getenv("AZURE_API_BASE"),
},
"tpm": 240000,
"rpm": 1800,
},
{
"model_name": "gpt-3.5-turbo", # openai model name
"litellm_params": { # params for litellm completion/embedding call
"model": "gpt-3.5-turbo",
"api_key": os.getenv("OPENAI_API_KEY"),
},
"tpm": 1000000,
"rpm": 9000
}
"rpm": 9000,
},
{
"model_name": "gpt-3.5-turbo-16k", # openai model name
"litellm_params": { # params for litellm completion/embedding call
"model": "gpt-3.5-turbo-16k",
"api_key": os.getenv("OPENAI_API_KEY"),
},
"tpm": 1000000,
"rpm": 9000,
},
]
router = Router(model_list=model_list,
fallbacks=[{"azure/gpt-3.5-turbo": ["gpt-3.5-turbo"]}],
context_window_fallbacks=[{"azure/gpt-3.5-turbo-context-fallback": ["gpt-3.5-turbo-16k"]}, {"gpt-3.5-turbo": ["gpt-3.5-turbo-16k"]}],
set_verbose=False)
router = Router(
model_list=model_list,
fallbacks=[{"azure/gpt-3.5-turbo": ["gpt-3.5-turbo"]}],
context_window_fallbacks=[
{"azure/gpt-3.5-turbo-context-fallback": ["gpt-3.5-turbo-16k"]},
{"gpt-3.5-turbo": ["gpt-3.5-turbo-16k"]},
],
set_verbose=False,
)
customHandler = MyCustomHandler()
litellm.callbacks = [customHandler]
user_message = "Hello, how are you?"
@ -190,152 +218,158 @@ async def test_async_fallbacks():
try:
response = await router.acompletion(**kwargs)
print(f"customHandler.previous_models: {customHandler.previous_models}")
await asyncio.sleep(0.05) # allow a delay as success_callbacks are on a separate thread
assert customHandler.previous_models == 1 # 0 retries, 1 fallback
await asyncio.sleep(
0.05
) # allow a delay as success_callbacks are on a separate thread
assert customHandler.previous_models == 1 # 0 retries, 1 fallback
router.reset()
except litellm.Timeout as e:
except litellm.Timeout as e:
pass
except Exception as e:
pytest.fail(f"An exception occurred: {e}")
finally:
router.reset()
# test_async_fallbacks()
def test_dynamic_fallbacks_sync():
def test_dynamic_fallbacks_sync():
"""
Allow setting the fallback in the router.completion() call.
Allow setting the fallback in the router.completion() call.
"""
try:
customHandler = MyCustomHandler()
litellm.callbacks = [customHandler]
model_list = [
{ # list of model deployments
"model_name": "azure/gpt-3.5-turbo", # openai model name
"litellm_params": { # params for litellm completion/embedding call
"model": "azure/chatgpt-v-2",
customHandler = MyCustomHandler()
litellm.callbacks = [customHandler]
model_list = [
{ # list of model deployments
"model_name": "azure/gpt-3.5-turbo", # openai model name
"litellm_params": { # params for litellm completion/embedding call
"model": "azure/chatgpt-v-2",
"api_key": "bad-key",
"api_version": os.getenv("AZURE_API_VERSION"),
"api_base": os.getenv("AZURE_API_BASE")
"api_base": os.getenv("AZURE_API_BASE"),
},
"tpm": 240000,
"rpm": 1800
},
{ # list of model deployments
"model_name": "azure/gpt-3.5-turbo-context-fallback", # openai model name
"litellm_params": { # params for litellm completion/embedding call
"model": "azure/chatgpt-v-2",
"rpm": 1800,
},
{ # list of model deployments
"model_name": "azure/gpt-3.5-turbo-context-fallback", # openai model name
"litellm_params": { # params for litellm completion/embedding call
"model": "azure/chatgpt-v-2",
"api_key": os.getenv("AZURE_API_KEY"),
"api_version": os.getenv("AZURE_API_VERSION"),
"api_base": os.getenv("AZURE_API_BASE")
"api_base": os.getenv("AZURE_API_BASE"),
},
"tpm": 240000,
"rpm": 1800
},
{
"model_name": "azure/gpt-3.5-turbo", # openai model name
"litellm_params": { # params for litellm completion/embedding call
"model": "azure/chatgpt-functioncalling",
"api_key": "bad-key",
"api_version": os.getenv("AZURE_API_VERSION"),
"api_base": os.getenv("AZURE_API_BASE")
},
"tpm": 240000,
"rpm": 1800
},
{
"model_name": "gpt-3.5-turbo", # openai model name
"litellm_params": { # params for litellm completion/embedding call
"model": "gpt-3.5-turbo",
"api_key": os.getenv("OPENAI_API_KEY"),
},
"tpm": 1000000,
"rpm": 9000
"rpm": 1800,
},
{
"model_name": "gpt-3.5-turbo-16k", # openai model name
"litellm_params": { # params for litellm completion/embedding call
"model": "gpt-3.5-turbo-16k",
"model_name": "azure/gpt-3.5-turbo", # openai model name
"litellm_params": { # params for litellm completion/embedding call
"model": "azure/chatgpt-functioncalling",
"api_key": "bad-key",
"api_version": os.getenv("AZURE_API_VERSION"),
"api_base": os.getenv("AZURE_API_BASE"),
},
"tpm": 240000,
"rpm": 1800,
},
{
"model_name": "gpt-3.5-turbo", # openai model name
"litellm_params": { # params for litellm completion/embedding call
"model": "gpt-3.5-turbo",
"api_key": os.getenv("OPENAI_API_KEY"),
},
"tpm": 1000000,
"rpm": 9000
}
"rpm": 9000,
},
{
"model_name": "gpt-3.5-turbo-16k", # openai model name
"litellm_params": { # params for litellm completion/embedding call
"model": "gpt-3.5-turbo-16k",
"api_key": os.getenv("OPENAI_API_KEY"),
},
"tpm": 1000000,
"rpm": 9000,
},
]
router = Router(model_list=model_list, set_verbose=True)
kwargs = {}
kwargs["model"] = "azure/gpt-3.5-turbo"
kwargs["messages"] = [{"role": "user", "content": "Hey, how's it going?"}]
kwargs["fallbacks"] = [{"azure/gpt-3.5-turbo": ["gpt-3.5-turbo"]}]
response = router.completion(**kwargs)
print(f"response: {response}")
time.sleep(0.05) # allow a delay as success_callbacks are on a separate thread
assert customHandler.previous_models == 1 # 0 retries, 1 fallback
router.reset()
router = Router(model_list=model_list, set_verbose=True)
kwargs = {}
kwargs["model"] = "azure/gpt-3.5-turbo"
kwargs["messages"] = [{"role": "user", "content": "Hey, how's it going?"}]
kwargs["fallbacks"] = [{"azure/gpt-3.5-turbo": ["gpt-3.5-turbo"]}]
response = router.completion(**kwargs)
print(f"response: {response}")
time.sleep(0.05) # allow a delay as success_callbacks are on a separate thread
assert customHandler.previous_models == 1 # 0 retries, 1 fallback
router.reset()
except Exception as e:
pytest.fail(f"An exception occurred - {e}")
# test_dynamic_fallbacks_sync()
@pytest.mark.asyncio
async def test_dynamic_fallbacks_async():
async def test_dynamic_fallbacks_async():
"""
Allow setting the fallback in the router.completion() call.
Allow setting the fallback in the router.completion() call.
"""
try:
try:
model_list = [
{ # list of model deployments
"model_name": "azure/gpt-3.5-turbo", # openai model name
"litellm_params": { # params for litellm completion/embedding call
"model": "azure/chatgpt-v-2",
{ # list of model deployments
"model_name": "azure/gpt-3.5-turbo", # openai model name
"litellm_params": { # params for litellm completion/embedding call
"model": "azure/chatgpt-v-2",
"api_key": "bad-key",
"api_version": os.getenv("AZURE_API_VERSION"),
"api_base": os.getenv("AZURE_API_BASE")
"api_base": os.getenv("AZURE_API_BASE"),
},
"tpm": 240000,
"rpm": 1800
},
{ # list of model deployments
"model_name": "azure/gpt-3.5-turbo-context-fallback", # openai model name
"litellm_params": { # params for litellm completion/embedding call
"model": "azure/chatgpt-v-2",
"rpm": 1800,
},
{ # list of model deployments
"model_name": "azure/gpt-3.5-turbo-context-fallback", # openai model name
"litellm_params": { # params for litellm completion/embedding call
"model": "azure/chatgpt-v-2",
"api_key": os.getenv("AZURE_API_KEY"),
"api_version": os.getenv("AZURE_API_VERSION"),
"api_base": os.getenv("AZURE_API_BASE")
"api_base": os.getenv("AZURE_API_BASE"),
},
"tpm": 240000,
"rpm": 1800
},
{
"model_name": "azure/gpt-3.5-turbo", # openai model name
"litellm_params": { # params for litellm completion/embedding call
"model": "azure/chatgpt-functioncalling",
"api_key": "bad-key",
"api_version": os.getenv("AZURE_API_VERSION"),
"api_base": os.getenv("AZURE_API_BASE")
},
"tpm": 240000,
"rpm": 1800
},
{
"model_name": "gpt-3.5-turbo", # openai model name
"litellm_params": { # params for litellm completion/embedding call
"model": "gpt-3.5-turbo",
"api_key": os.getenv("OPENAI_API_KEY"),
},
"tpm": 1000000,
"rpm": 9000
"rpm": 1800,
},
{
"model_name": "gpt-3.5-turbo-16k", # openai model name
"litellm_params": { # params for litellm completion/embedding call
"model": "gpt-3.5-turbo-16k",
"model_name": "azure/gpt-3.5-turbo", # openai model name
"litellm_params": { # params for litellm completion/embedding call
"model": "azure/chatgpt-functioncalling",
"api_key": "bad-key",
"api_version": os.getenv("AZURE_API_VERSION"),
"api_base": os.getenv("AZURE_API_BASE"),
},
"tpm": 240000,
"rpm": 1800,
},
{
"model_name": "gpt-3.5-turbo", # openai model name
"litellm_params": { # params for litellm completion/embedding call
"model": "gpt-3.5-turbo",
"api_key": os.getenv("OPENAI_API_KEY"),
},
"tpm": 1000000,
"rpm": 9000
}
"rpm": 9000,
},
{
"model_name": "gpt-3.5-turbo-16k", # openai model name
"litellm_params": { # params for litellm completion/embedding call
"model": "gpt-3.5-turbo-16k",
"api_key": os.getenv("OPENAI_API_KEY"),
},
"tpm": 1000000,
"rpm": 9000,
},
]
print()
@ -352,9 +386,13 @@ async def test_dynamic_fallbacks_async():
kwargs["fallbacks"] = [{"azure/gpt-3.5-turbo": ["gpt-3.5-turbo"]}]
response = await router.acompletion(**kwargs)
print(f"RESPONSE: {response}")
await asyncio.sleep(0.05) # allow a delay as success_callbacks are on a separate thread
assert customHandler.previous_models == 1 # 0 retries, 1 fallback
await asyncio.sleep(
0.05
) # allow a delay as success_callbacks are on a separate thread
assert customHandler.previous_models == 1 # 0 retries, 1 fallback
router.reset()
except Exception as e:
pytest.fail(f"An exception occurred - {e}")
# asyncio.run(test_dynamic_fallbacks_async())
# asyncio.run(test_dynamic_fallbacks_async())