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### What this tests #### | |
## This test asserts the type of data passed into each method of the custom callback handler | |
import sys, os, time, inspect, asyncio, traceback | |
from datetime import datetime | |
import pytest | |
sys.path.insert(0, os.path.abspath("../..")) | |
from typing import Optional, Literal, List | |
from litellm import Router, Cache | |
import litellm | |
from litellm.integrations.custom_logger import CustomLogger | |
# Test Scenarios (test across completion, streaming, embedding) | |
## 1: Pre-API-Call | |
## 2: Post-API-Call | |
## 3: On LiteLLM Call success | |
## 4: On LiteLLM Call failure | |
## fallbacks | |
## retries | |
# Test cases | |
## 1. Simple Azure OpenAI acompletion + streaming call | |
## 2. Simple Azure OpenAI aembedding call | |
## 3. Azure OpenAI acompletion + streaming call with retries | |
## 4. Azure OpenAI aembedding call with retries | |
## 5. Azure OpenAI acompletion + streaming call with fallbacks | |
## 6. Azure OpenAI aembedding call with fallbacks | |
# Test interfaces | |
## 1. router.completion() + router.embeddings() | |
## 2. proxy.completions + proxy.embeddings | |
class CompletionCustomHandler( | |
CustomLogger | |
): # https://docs.litellm.ai/docs/observability/custom_callback#callback-class | |
""" | |
The set of expected inputs to a custom handler for a | |
""" | |
# Class variables or attributes | |
def __init__(self): | |
self.errors = [] | |
self.states: Optional[ | |
List[ | |
Literal[ | |
"sync_pre_api_call", | |
"async_pre_api_call", | |
"post_api_call", | |
"sync_stream", | |
"async_stream", | |
"sync_success", | |
"async_success", | |
"sync_failure", | |
"async_failure", | |
] | |
] | |
] = [] | |
def log_pre_api_call(self, model, messages, kwargs): | |
try: | |
print(f"received kwargs in pre-input: {kwargs}") | |
self.states.append("sync_pre_api_call") | |
## MODEL | |
assert isinstance(model, str) | |
## MESSAGES | |
assert isinstance(messages, list) | |
## KWARGS | |
assert isinstance(kwargs["model"], str) | |
assert isinstance(kwargs["messages"], list) | |
assert isinstance(kwargs["optional_params"], dict) | |
assert isinstance(kwargs["litellm_params"], dict) | |
assert isinstance(kwargs["start_time"], (datetime, type(None))) | |
assert isinstance(kwargs["stream"], bool) | |
assert isinstance(kwargs["user"], (str, type(None))) | |
### ROUTER-SPECIFIC KWARGS | |
assert isinstance(kwargs["litellm_params"]["metadata"], dict) | |
assert isinstance(kwargs["litellm_params"]["metadata"]["model_group"], str) | |
assert isinstance(kwargs["litellm_params"]["metadata"]["deployment"], str) | |
assert isinstance(kwargs["litellm_params"]["model_info"], dict) | |
assert isinstance(kwargs["litellm_params"]["model_info"]["id"], str) | |
assert isinstance( | |
kwargs["litellm_params"]["proxy_server_request"], (str, type(None)) | |
) | |
assert isinstance( | |
kwargs["litellm_params"]["preset_cache_key"], (str, type(None)) | |
) | |
assert isinstance(kwargs["litellm_params"]["stream_response"], dict) | |
except Exception as e: | |
print(f"Assertion Error: {traceback.format_exc()}") | |
self.errors.append(traceback.format_exc()) | |
def log_post_api_call(self, kwargs, response_obj, start_time, end_time): | |
try: | |
self.states.append("post_api_call") | |
## START TIME | |
assert isinstance(start_time, datetime) | |
## END TIME | |
assert end_time == None | |
## RESPONSE OBJECT | |
assert response_obj == None | |
## KWARGS | |
assert isinstance(kwargs["model"], str) | |
assert isinstance(kwargs["messages"], list) | |
assert isinstance(kwargs["optional_params"], dict) | |
assert isinstance(kwargs["litellm_params"], dict) | |
assert isinstance(kwargs["start_time"], (datetime, type(None))) | |
assert isinstance(kwargs["stream"], bool) | |
assert isinstance(kwargs["user"], (str, type(None))) | |
assert isinstance(kwargs["input"], (list, dict, str)) | |
assert isinstance(kwargs["api_key"], (str, type(None))) | |
assert ( | |
isinstance( | |
kwargs["original_response"], (str, litellm.CustomStreamWrapper) | |
) | |
or inspect.iscoroutine(kwargs["original_response"]) | |
or inspect.isasyncgen(kwargs["original_response"]) | |
) | |
assert isinstance(kwargs["additional_args"], (dict, type(None))) | |
assert isinstance(kwargs["log_event_type"], str) | |
### ROUTER-SPECIFIC KWARGS | |
assert isinstance(kwargs["litellm_params"]["metadata"], dict) | |
assert isinstance(kwargs["litellm_params"]["metadata"]["model_group"], str) | |
assert isinstance(kwargs["litellm_params"]["metadata"]["deployment"], str) | |
assert isinstance(kwargs["litellm_params"]["model_info"], dict) | |
assert isinstance(kwargs["litellm_params"]["model_info"]["id"], str) | |
assert isinstance( | |
kwargs["litellm_params"]["proxy_server_request"], (str, type(None)) | |
) | |
assert isinstance( | |
kwargs["litellm_params"]["preset_cache_key"], (str, type(None)) | |
) | |
assert isinstance(kwargs["litellm_params"]["stream_response"], dict) | |
except: | |
print(f"Assertion Error: {traceback.format_exc()}") | |
self.errors.append(traceback.format_exc()) | |
async def async_log_stream_event(self, kwargs, response_obj, start_time, end_time): | |
try: | |
self.states.append("async_stream") | |
## START TIME | |
assert isinstance(start_time, datetime) | |
## END TIME | |
assert isinstance(end_time, datetime) | |
## RESPONSE OBJECT | |
assert isinstance(response_obj, litellm.ModelResponse) | |
## KWARGS | |
assert isinstance(kwargs["model"], str) | |
assert isinstance(kwargs["messages"], list) and isinstance( | |
kwargs["messages"][0], dict | |
) | |
assert isinstance(kwargs["optional_params"], dict) | |
assert isinstance(kwargs["litellm_params"], dict) | |
assert isinstance(kwargs["start_time"], (datetime, type(None))) | |
assert isinstance(kwargs["stream"], bool) | |
assert isinstance(kwargs["user"], (str, type(None))) | |
assert ( | |
isinstance(kwargs["input"], list) | |
and isinstance(kwargs["input"][0], dict) | |
) or isinstance(kwargs["input"], (dict, str)) | |
assert isinstance(kwargs["api_key"], (str, type(None))) | |
assert ( | |
isinstance( | |
kwargs["original_response"], (str, litellm.CustomStreamWrapper) | |
) | |
or inspect.isasyncgen(kwargs["original_response"]) | |
or inspect.iscoroutine(kwargs["original_response"]) | |
) | |
assert isinstance(kwargs["additional_args"], (dict, type(None))) | |
assert isinstance(kwargs["log_event_type"], str) | |
except: | |
print(f"Assertion Error: {traceback.format_exc()}") | |
self.errors.append(traceback.format_exc()) | |
def log_success_event(self, kwargs, response_obj, start_time, end_time): | |
try: | |
self.states.append("sync_success") | |
## START TIME | |
assert isinstance(start_time, datetime) | |
## END TIME | |
assert isinstance(end_time, datetime) | |
## RESPONSE OBJECT | |
assert isinstance(response_obj, litellm.ModelResponse) | |
## KWARGS | |
assert isinstance(kwargs["model"], str) | |
assert isinstance(kwargs["messages"], list) and isinstance( | |
kwargs["messages"][0], dict | |
) | |
assert isinstance(kwargs["optional_params"], dict) | |
assert isinstance(kwargs["litellm_params"], dict) | |
assert isinstance(kwargs["start_time"], (datetime, type(None))) | |
assert isinstance(kwargs["stream"], bool) | |
assert isinstance(kwargs["user"], (str, type(None))) | |
assert ( | |
isinstance(kwargs["input"], list) | |
and isinstance(kwargs["input"][0], dict) | |
) or isinstance(kwargs["input"], (dict, str)) | |
assert isinstance(kwargs["api_key"], (str, type(None))) | |
assert isinstance( | |
kwargs["original_response"], (str, litellm.CustomStreamWrapper) | |
) | |
assert isinstance(kwargs["additional_args"], (dict, type(None))) | |
assert isinstance(kwargs["log_event_type"], str) | |
assert kwargs["cache_hit"] is None or isinstance(kwargs["cache_hit"], bool) | |
except: | |
print(f"Assertion Error: {traceback.format_exc()}") | |
self.errors.append(traceback.format_exc()) | |
def log_failure_event(self, kwargs, response_obj, start_time, end_time): | |
try: | |
self.states.append("sync_failure") | |
## START TIME | |
assert isinstance(start_time, datetime) | |
## END TIME | |
assert isinstance(end_time, datetime) | |
## RESPONSE OBJECT | |
assert response_obj == None | |
## KWARGS | |
assert isinstance(kwargs["model"], str) | |
assert isinstance(kwargs["messages"], list) and isinstance( | |
kwargs["messages"][0], dict | |
) | |
assert isinstance(kwargs["optional_params"], dict) | |
assert isinstance(kwargs["litellm_params"], dict) | |
assert isinstance(kwargs["start_time"], (datetime, type(None))) | |
assert isinstance(kwargs["stream"], bool) | |
assert isinstance(kwargs["user"], (str, type(None))) | |
assert ( | |
isinstance(kwargs["input"], list) | |
and isinstance(kwargs["input"][0], dict) | |
) or isinstance(kwargs["input"], (dict, str)) | |
assert isinstance(kwargs["api_key"], (str, type(None))) | |
assert ( | |
isinstance( | |
kwargs["original_response"], (str, litellm.CustomStreamWrapper) | |
) | |
or kwargs["original_response"] == None | |
) | |
assert isinstance(kwargs["additional_args"], (dict, type(None))) | |
assert isinstance(kwargs["log_event_type"], str) | |
except: | |
print(f"Assertion Error: {traceback.format_exc()}") | |
self.errors.append(traceback.format_exc()) | |
async def async_log_pre_api_call(self, model, messages, kwargs): | |
try: | |
""" | |
No-op. | |
Not implemented yet. | |
""" | |
pass | |
except Exception as e: | |
print(f"Assertion Error: {traceback.format_exc()}") | |
self.errors.append(traceback.format_exc()) | |
async def async_log_success_event(self, kwargs, response_obj, start_time, end_time): | |
try: | |
self.states.append("async_success") | |
## START TIME | |
assert isinstance(start_time, datetime) | |
## END TIME | |
assert isinstance(end_time, datetime) | |
## RESPONSE OBJECT | |
assert isinstance( | |
response_obj, (litellm.ModelResponse, litellm.EmbeddingResponse) | |
) | |
## KWARGS | |
assert isinstance(kwargs["model"], str) | |
assert isinstance(kwargs["messages"], list) | |
assert isinstance(kwargs["optional_params"], dict) | |
assert isinstance(kwargs["litellm_params"], dict) | |
assert isinstance(kwargs["start_time"], (datetime, type(None))) | |
assert isinstance(kwargs["stream"], bool) | |
assert isinstance(kwargs["user"], (str, type(None))) | |
assert isinstance(kwargs["input"], (list, dict, str)) | |
assert isinstance(kwargs["api_key"], (str, type(None))) | |
assert ( | |
isinstance( | |
kwargs["original_response"], (str, litellm.CustomStreamWrapper) | |
) | |
or inspect.isasyncgen(kwargs["original_response"]) | |
or inspect.iscoroutine(kwargs["original_response"]) | |
) | |
assert isinstance(kwargs["additional_args"], (dict, type(None))) | |
assert isinstance(kwargs["log_event_type"], str) | |
assert kwargs["cache_hit"] is None or isinstance(kwargs["cache_hit"], bool) | |
### ROUTER-SPECIFIC KWARGS | |
assert isinstance(kwargs["litellm_params"]["metadata"], dict) | |
assert isinstance(kwargs["litellm_params"]["metadata"]["model_group"], str) | |
assert isinstance(kwargs["litellm_params"]["metadata"]["deployment"], str) | |
assert isinstance(kwargs["litellm_params"]["model_info"], dict) | |
assert isinstance(kwargs["litellm_params"]["model_info"]["id"], str) | |
assert isinstance( | |
kwargs["litellm_params"]["proxy_server_request"], (str, type(None)) | |
) | |
assert isinstance( | |
kwargs["litellm_params"]["preset_cache_key"], (str, type(None)) | |
) | |
assert isinstance(kwargs["litellm_params"]["stream_response"], dict) | |
except: | |
print(f"Assertion Error: {traceback.format_exc()}") | |
self.errors.append(traceback.format_exc()) | |
async def async_log_failure_event(self, kwargs, response_obj, start_time, end_time): | |
try: | |
print(f"received original response: {kwargs['original_response']}") | |
self.states.append("async_failure") | |
## START TIME | |
assert isinstance(start_time, datetime) | |
## END TIME | |
assert isinstance(end_time, datetime) | |
## RESPONSE OBJECT | |
assert response_obj == None | |
## KWARGS | |
assert isinstance(kwargs["model"], str) | |
assert isinstance(kwargs["messages"], list) | |
assert isinstance(kwargs["optional_params"], dict) | |
assert isinstance(kwargs["litellm_params"], dict) | |
assert isinstance(kwargs["start_time"], (datetime, type(None))) | |
assert isinstance(kwargs["stream"], bool) | |
assert isinstance(kwargs["user"], (str, type(None))) | |
assert isinstance(kwargs["input"], (list, str, dict)) | |
assert isinstance(kwargs["api_key"], (str, type(None))) | |
assert ( | |
isinstance( | |
kwargs["original_response"], (str, litellm.CustomStreamWrapper) | |
) | |
or inspect.isasyncgen(kwargs["original_response"]) | |
or inspect.iscoroutine(kwargs["original_response"]) | |
or kwargs["original_response"] == None | |
) | |
assert isinstance(kwargs["additional_args"], (dict, type(None))) | |
assert isinstance(kwargs["log_event_type"], str) | |
except: | |
print(f"Assertion Error: {traceback.format_exc()}") | |
self.errors.append(traceback.format_exc()) | |
# Simple Azure OpenAI call | |
## COMPLETION | |
async def test_async_chat_azure(): | |
try: | |
customHandler_completion_azure_router = CompletionCustomHandler() | |
customHandler_streaming_azure_router = CompletionCustomHandler() | |
customHandler_failure = CompletionCustomHandler() | |
litellm.callbacks = [customHandler_completion_azure_router] | |
model_list = [ | |
{ | |
"model_name": "gpt-3.5-turbo", # 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"), | |
}, | |
"tpm": 240000, | |
"rpm": 1800, | |
}, | |
] | |
router = Router(model_list=model_list) # type: ignore | |
response = await router.acompletion( | |
model="gpt-3.5-turbo", | |
messages=[{"role": "user", "content": "Hi ๐ - i'm openai"}], | |
) | |
await asyncio.sleep(2) | |
assert len(customHandler_completion_azure_router.errors) == 0 | |
assert ( | |
len(customHandler_completion_azure_router.states) == 3 | |
) # pre, post, success | |
# streaming | |
litellm.callbacks = [customHandler_streaming_azure_router] | |
router2 = Router(model_list=model_list) # type: ignore | |
response = await router2.acompletion( | |
model="gpt-3.5-turbo", | |
messages=[{"role": "user", "content": "Hi ๐ - i'm openai"}], | |
stream=True, | |
) | |
async for chunk in response: | |
print(f"async azure router chunk: {chunk}") | |
continue | |
await asyncio.sleep(1) | |
print(f"customHandler.states: {customHandler_streaming_azure_router.states}") | |
assert len(customHandler_streaming_azure_router.errors) == 0 | |
assert ( | |
len(customHandler_streaming_azure_router.states) >= 4 | |
) # pre, post, stream (multiple times), success | |
# failure | |
model_list = [ | |
{ | |
"model_name": "gpt-3.5-turbo", # openai model name | |
"litellm_params": { # params for litellm completion/embedding call | |
"model": "azure/chatgpt-v-2", | |
"api_key": "my-bad-key", | |
"api_version": os.getenv("AZURE_API_VERSION"), | |
"api_base": os.getenv("AZURE_API_BASE"), | |
}, | |
"tpm": 240000, | |
"rpm": 1800, | |
}, | |
] | |
litellm.callbacks = [customHandler_failure] | |
router3 = Router(model_list=model_list) # type: ignore | |
try: | |
response = await router3.acompletion( | |
model="gpt-3.5-turbo", | |
messages=[{"role": "user", "content": "Hi ๐ - i'm openai"}], | |
) | |
print(f"response in router3 acompletion: {response}") | |
except: | |
pass | |
await asyncio.sleep(1) | |
print(f"customHandler.states: {customHandler_failure.states}") | |
assert len(customHandler_failure.errors) == 0 | |
assert len(customHandler_failure.states) == 3 # pre, post, failure | |
assert "async_failure" in customHandler_failure.states | |
except Exception as e: | |
print(f"Assertion Error: {traceback.format_exc()}") | |
pytest.fail(f"An exception occurred - {str(e)}") | |
# asyncio.run(test_async_chat_azure()) | |
## EMBEDDING | |
async def test_async_embedding_azure(): | |
try: | |
customHandler = CompletionCustomHandler() | |
customHandler_failure = CompletionCustomHandler() | |
litellm.callbacks = [customHandler] | |
model_list = [ | |
{ | |
"model_name": "azure-embedding-model", # openai model name | |
"litellm_params": { # params for litellm completion/embedding call | |
"model": "azure/azure-embedding-model", | |
"api_key": os.getenv("AZURE_API_KEY"), | |
"api_version": os.getenv("AZURE_API_VERSION"), | |
"api_base": os.getenv("AZURE_API_BASE"), | |
}, | |
"tpm": 240000, | |
"rpm": 1800, | |
}, | |
] | |
router = Router(model_list=model_list) # type: ignore | |
response = await router.aembedding( | |
model="azure-embedding-model", input=["hello from litellm!"] | |
) | |
await asyncio.sleep(2) | |
assert len(customHandler.errors) == 0 | |
assert len(customHandler.states) == 3 # pre, post, success | |
# failure | |
model_list = [ | |
{ | |
"model_name": "azure-embedding-model", # openai model name | |
"litellm_params": { # params for litellm completion/embedding call | |
"model": "azure/azure-embedding-model", | |
"api_key": "my-bad-key", | |
"api_version": os.getenv("AZURE_API_VERSION"), | |
"api_base": os.getenv("AZURE_API_BASE"), | |
}, | |
"tpm": 240000, | |
"rpm": 1800, | |
}, | |
] | |
litellm.callbacks = [customHandler_failure] | |
router3 = Router(model_list=model_list) # type: ignore | |
try: | |
response = await router3.aembedding( | |
model="azure-embedding-model", input=["hello from litellm!"] | |
) | |
print(f"response in router3 aembedding: {response}") | |
except: | |
pass | |
await asyncio.sleep(1) | |
print(f"customHandler.states: {customHandler_failure.states}") | |
assert len(customHandler_failure.errors) == 0 | |
assert len(customHandler_failure.states) == 3 # pre, post, failure | |
assert "async_failure" in customHandler_failure.states | |
except Exception as e: | |
print(f"Assertion Error: {traceback.format_exc()}") | |
pytest.fail(f"An exception occurred - {str(e)}") | |
# asyncio.run(test_async_embedding_azure()) | |
# Azure OpenAI call w/ Fallbacks | |
## COMPLETION | |
async def test_async_chat_azure_with_fallbacks(): | |
try: | |
customHandler_fallbacks = CompletionCustomHandler() | |
litellm.callbacks = [customHandler_fallbacks] | |
# with fallbacks | |
model_list = [ | |
{ | |
"model_name": "gpt-3.5-turbo", # openai model name | |
"litellm_params": { # params for litellm completion/embedding call | |
"model": "azure/chatgpt-v-2", | |
"api_key": "my-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-16k", | |
"litellm_params": { | |
"model": "gpt-3.5-turbo-16k", | |
}, | |
"tpm": 240000, | |
"rpm": 1800, | |
}, | |
] | |
router = Router(model_list=model_list, fallbacks=[{"gpt-3.5-turbo": ["gpt-3.5-turbo-16k"]}]) # type: ignore | |
response = await router.acompletion( | |
model="gpt-3.5-turbo", | |
messages=[{"role": "user", "content": "Hi ๐ - i'm openai"}], | |
) | |
await asyncio.sleep(2) | |
print(f"customHandler_fallbacks.states: {customHandler_fallbacks.states}") | |
assert len(customHandler_fallbacks.errors) == 0 | |
assert ( | |
len(customHandler_fallbacks.states) == 6 | |
) # pre, post, failure, pre, post, success | |
litellm.callbacks = [] | |
except Exception as e: | |
print(f"Assertion Error: {traceback.format_exc()}") | |
pytest.fail(f"An exception occurred - {str(e)}") | |
# asyncio.run(test_async_chat_azure_with_fallbacks()) | |
# CACHING | |
## Test Azure - completion, embedding | |
async def test_async_completion_azure_caching(): | |
customHandler_caching = CompletionCustomHandler() | |
litellm.cache = Cache( | |
type="redis", | |
host=os.environ["REDIS_HOST"], | |
port=os.environ["REDIS_PORT"], | |
password=os.environ["REDIS_PASSWORD"], | |
) | |
litellm.callbacks = [customHandler_caching] | |
unique_time = time.time() | |
model_list = [ | |
{ | |
"model_name": "gpt-3.5-turbo", # 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"), | |
}, | |
"tpm": 240000, | |
"rpm": 1800, | |
}, | |
{ | |
"model_name": "gpt-3.5-turbo-16k", | |
"litellm_params": { | |
"model": "gpt-3.5-turbo-16k", | |
}, | |
"tpm": 240000, | |
"rpm": 1800, | |
}, | |
] | |
router = Router(model_list=model_list) # type: ignore | |
response1 = await router.acompletion( | |
model="gpt-3.5-turbo", | |
messages=[{"role": "user", "content": f"Hi ๐ - i'm async azure {unique_time}"}], | |
caching=True, | |
) | |
await asyncio.sleep(1) | |
print(f"customHandler_caching.states pre-cache hit: {customHandler_caching.states}") | |
response2 = await router.acompletion( | |
model="gpt-3.5-turbo", | |
messages=[{"role": "user", "content": f"Hi ๐ - i'm async azure {unique_time}"}], | |
caching=True, | |
) | |
await asyncio.sleep(1) # success callbacks are done in parallel | |
print( | |
f"customHandler_caching.states post-cache hit: {customHandler_caching.states}" | |
) | |
assert len(customHandler_caching.errors) == 0 | |
assert len(customHandler_caching.states) == 4 # pre, post, success, success | |