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