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#### What this tests ####
#This tests litellm router

import sys, os, time
import traceback, asyncio
import pytest
sys.path.insert(
    0, os.path.abspath("../..")
)  # Adds the parent directory to the system path
import litellm
from litellm import Router
from concurrent.futures import ThreadPoolExecutor
from collections import defaultdict
from dotenv import load_dotenv
load_dotenv()

def test_exception_raising():
	# this tests if the router raises an exception when invalid params are set
	# in this test both deployments have bad keys - Keep this test. It validates if the router raises the most recent exception
	litellm.set_verbose=True
	import openai
	try:
		print("testing if router raises an exception")
		old_api_key = os.environ["AZURE_API_KEY"]
		os.environ["AZURE_API_KEY"] = ""
		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": "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": { #
					"model": "gpt-3.5-turbo", 
					"api_key": "bad-key",
				},
				"tpm": 240000,
				"rpm": 1800
			}
		]
		router = Router(model_list=model_list, 
					redis_host=os.getenv("REDIS_HOST"), 
					redis_password=os.getenv("REDIS_PASSWORD"), 
					redis_port=int(os.getenv("REDIS_PORT")), 
					routing_strategy="simple-shuffle",
					set_verbose=False,
					num_retries=1) # type: ignore
		response = router.completion(
			model="gpt-3.5-turbo",
			messages=[
				{
					"role": "user",
					"content": "hello this request will fail"
				}
			]
		)
		os.environ["AZURE_API_KEY"] = old_api_key
		pytest.fail(f"Should have raised an Auth Error")
	except openai.AuthenticationError:
		print("Test Passed: Caught an OPENAI AUTH Error, Good job. This is what we needed!")
		os.environ["AZURE_API_KEY"] = old_api_key
		router.reset()
	except Exception as e:
		os.environ["AZURE_API_KEY"] = old_api_key
		print("Got unexpected exception on router!", e)
# test_exception_raising()


def test_reading_key_from_model_list():
	# this tests if the router raises an exception when invalid params are set
	# DO NOT REMOVE THIS TEST. It's an IMP ONE. Speak to Ishaan, if you are tring to remove this
	litellm.set_verbose=False
	import openai
	try:
		print("testing if router raises an exception")
		old_api_key = os.environ["AZURE_API_KEY"]
		os.environ.pop("AZURE_API_KEY", None)
		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": old_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, 
					redis_host=os.getenv("REDIS_HOST"), 
					redis_password=os.getenv("REDIS_PASSWORD"), 
					redis_port=int(os.getenv("REDIS_PORT")), 
					routing_strategy="simple-shuffle",
					set_verbose=True,
					num_retries=1) # type: ignore
		response = router.completion(
			model="gpt-3.5-turbo",
			messages=[
				{
					"role": "user",
					"content": "hello this request will fail"
				}
			]
		)
		os.environ["AZURE_API_KEY"] = old_api_key
		router.reset()
	except Exception as e:
		os.environ["AZURE_API_KEY"] = old_api_key
		print(f"FAILED TEST")
		pytest.fail(f"Got unexpected exception on router! - {e}")
# test_reading_key_from_model_list()


### FUNCTION CALLING 

def test_function_calling(): 
	model_list = [
		{
			"model_name": "gpt-3.5-turbo-0613",
			"litellm_params": {
				"model": "gpt-3.5-turbo-0613",
				"api_key": os.getenv("OPENAI_API_KEY"),
			},
			"tpm": 100000,
			"rpm": 10000,
		},
	]

	messages = [
		{"role": "user", "content": "What is the weather like in Boston?"}
	]
	functions = [
		{
		"name": "get_current_weather",
		"description": "Get the current weather in a given location",
		"parameters": {
			"type": "object",
			"properties": {
			"location": {
				"type": "string",
				"description": "The city and state, e.g. San Francisco, CA"
			},
			"unit": {
				"type": "string",
				"enum": ["celsius", "fahrenheit"]
			}
			},
			"required": ["location"]
		}
		}
	]

	router = Router(model_list=model_list, routing_strategy="latency-based-routing")
	response = router.completion(model="gpt-3.5-turbo-0613", messages=messages, functions=functions)
	router.reset()
	print(response)

def test_acompletion_on_router(): 
	try:
		litellm.set_verbose = False
		model_list = [
			{
				"model_name": "gpt-3.5-turbo",
				"litellm_params": {
					"model": "gpt-3.5-turbo-0613",
					"api_key": os.getenv("OPENAI_API_KEY"),
				},
				"tpm": 100000,
				"rpm": 10000,
			},
			{
				"model_name": "gpt-3.5-turbo",
				"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")
				},
				"tpm": 100000,
				"rpm": 10000,
			}
		]

		messages = [
			{"role": "user", "content": f"write a one sentence poem {time.time()}?"}
		]
		start_time = time.time()
		router = Router(model_list=model_list, 
				redis_host=os.environ["REDIS_HOST"], 
				redis_password=os.environ["REDIS_PASSWORD"], 
				redis_port=os.environ["REDIS_PORT"], 
				cache_responses=True, 
				timeout=30,
				routing_strategy="simple-shuffle")
		async def get_response(): 
			response1 = await router.acompletion(model="gpt-3.5-turbo", messages=messages)
			print(f"response1: {response1}")
			response2 = await router.acompletion(model="gpt-3.5-turbo", messages=messages)
			print(f"response2: {response2}")
			assert response1.id == response2.id
			assert len(response1.choices[0].message.content) > 0
			assert response1.choices[0].message.content == response2.choices[0].message.content
		asyncio.run(get_response())
		router.reset()
	except litellm.Timeout as e: 
		end_time = time.time()
		print(f"timeout error occurred: {end_time - start_time}")
		pass
	except Exception as e:
		traceback.print_exc()
		pytest.fail(f"Error occurred: {e}")

# test_acompletion_on_router() 

def test_function_calling_on_router(): 
	try: 
		litellm.set_verbose = True
		model_list = [
            {
                "model_name": "gpt-3.5-turbo",
                "litellm_params": {
                    "model": "gpt-3.5-turbo-0613",
                    "api_key": os.getenv("OPENAI_API_KEY"),
                },
            },
        ]
		function1 = [
            {
                "name": "get_current_weather",
                "description": "Get the current weather in a given location",
                "parameters": {
                    "type": "object",
                    "properties": {
                        "location": {
                            "type": "string",
                            "description": "The city and state, e.g. San Francisco, CA",
                        },
                        "unit": {"type": "string", "enum": ["celsius", "fahrenheit"]},
                    },
                    "required": ["location"],
                },
            }
        ]
		router = Router(
			model_list=model_list,
			redis_host=os.getenv("REDIS_HOST"),
			redis_password=os.getenv("REDIS_PASSWORD"),
			redis_port=os.getenv("REDIS_PORT")
		)
		messages=[
                {
                    "role": "user",
                    "content": "what's the weather in boston"
                }
            ]
		response = router.completion(model="gpt-3.5-turbo", messages=messages, functions=function1)
		print(f"final returned response: {response}")
		router.reset()
		assert isinstance(response["choices"][0]["message"]["function_call"], dict)
	except Exception as e: 
		print(f"An exception occurred: {e}")

# test_function_calling_on_router()

def test_aembedding_on_router():
	litellm.set_verbose = True
	try:
		model_list = [
			{
				"model_name": "text-embedding-ada-002",
				"litellm_params": {
					"model": "text-embedding-ada-002",
				},
				"tpm": 100000,
				"rpm": 10000,
			},
		]

		async def embedding_call():
			router = Router(model_list=model_list)
			response = await router.aembedding(
				model="text-embedding-ada-002",
				input=["good morning from litellm", "this is another item"],
			)
			print(response)
			router.reset()
		asyncio.run(embedding_call())
	except Exception as e:
		traceback.print_exc()
		pytest.fail(f"Error occurred: {e}")
# test_aembedding_on_router()


def test_azure_aembedding_on_router():
	litellm.set_verbose = True
	try:
		model_list = [
			{
				"model_name": "text-embedding-ada-002",
				"litellm_params": {
					"model": "azure/azure-embedding-model",
					"api_key":os.environ['AZURE_API_KEY'],
					"api_base": os.environ['AZURE_API_BASE']
				},
				"tpm": 100000,
				"rpm": 10000,
			},
		]

		async def embedding_call():
			router = Router(model_list=model_list)
			response = await router.aembedding(
				model="text-embedding-ada-002",
				input=["good morning from litellm"]
			)
			print(response)
			router.reset()
		asyncio.run(embedding_call())
	except Exception as e:
		traceback.print_exc()
		pytest.fail(f"Error occurred: {e}")
# test_azure_aembedding_on_router()

	#### What this tests ####
	#This tests litellm router

	import sys, os, time
	import traceback, asyncio
	import pytest
	sys.path.insert(
	0, os.path.abspath("../..")
	) # Adds the parent directory to the system path
	import litellm
	from litellm import Router
	from concurrent.futures import ThreadPoolExecutor
	from collections import defaultdict
	from dotenv import load_dotenv
	load_dotenv()

	def test_exception_raising():
	# this tests if the router raises an exception when invalid params are set
	# in this test both deployments have bad keys - Keep this test. It validates if the router raises the most recent exception
	litellm.set_verbose=True
	import openai
	try:
	print("testing if router raises an exception")
	old_api_key = os.environ["AZURE_API_KEY"]
	os.environ["AZURE_API_KEY"] = ""
	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": "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": { #
	"model": "gpt-3.5-turbo",
	"api_key": "bad-key",
	},
	"tpm": 240000,
	"rpm": 1800
	}
	]
	router = Router(model_list=model_list,
	redis_host=os.getenv("REDIS_HOST"),
	redis_password=os.getenv("REDIS_PASSWORD"),
	redis_port=int(os.getenv("REDIS_PORT")),
	routing_strategy="simple-shuffle",
	set_verbose=False,
	num_retries=1) # type: ignore
	response = router.completion(
	model="gpt-3.5-turbo",
	messages=[
	{
	"role": "user",
	"content": "hello this request will fail"
	}
	]
	)
	os.environ["AZURE_API_KEY"] = old_api_key
	pytest.fail(f"Should have raised an Auth Error")
	except openai.AuthenticationError:
	print("Test Passed: Caught an OPENAI AUTH Error, Good job. This is what we needed!")
	os.environ["AZURE_API_KEY"] = old_api_key
	router.reset()
	except Exception as e:
	os.environ["AZURE_API_KEY"] = old_api_key
	print("Got unexpected exception on router!", e)
	# test_exception_raising()


	def test_reading_key_from_model_list():
	# this tests if the router raises an exception when invalid params are set
	# DO NOT REMOVE THIS TEST. It's an IMP ONE. Speak to Ishaan, if you are tring to remove this
	litellm.set_verbose=False
	import openai
	try:
	print("testing if router raises an exception")
	old_api_key = os.environ["AZURE_API_KEY"]
	os.environ.pop("AZURE_API_KEY", None)
	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": old_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,
	redis_host=os.getenv("REDIS_HOST"),
	redis_password=os.getenv("REDIS_PASSWORD"),
	redis_port=int(os.getenv("REDIS_PORT")),
	routing_strategy="simple-shuffle",
	set_verbose=True,
	num_retries=1) # type: ignore
	response = router.completion(
	model="gpt-3.5-turbo",
	messages=[
	{
	"role": "user",
	"content": "hello this request will fail"
	}
	]
	)
	os.environ["AZURE_API_KEY"] = old_api_key
	router.reset()
	except Exception as e:
	os.environ["AZURE_API_KEY"] = old_api_key
	print(f"FAILED TEST")
	pytest.fail(f"Got unexpected exception on router! - {e}")
	# test_reading_key_from_model_list()


	### FUNCTION CALLING

	def test_function_calling():
	model_list = [
	{
	"model_name": "gpt-3.5-turbo-0613",
	"litellm_params": {
	"model": "gpt-3.5-turbo-0613",
	"api_key": os.getenv("OPENAI_API_KEY"),
	},
	"tpm": 100000,
	"rpm": 10000,
	},
	]

	messages = [
	{"role": "user", "content": "What is the weather like in Boston?"}
	]
	functions = [
	{
	"name": "get_current_weather",
	"description": "Get the current weather in a given location",
	"parameters": {
	"type": "object",
	"properties": {
	"location": {
	"type": "string",
	"description": "The city and state, e.g. San Francisco, CA"
	},
	"unit": {
	"type": "string",
	"enum": ["celsius", "fahrenheit"]
	}
	},
	"required": ["location"]
	}
	}
	]

	router = Router(model_list=model_list, routing_strategy="latency-based-routing")
	response = router.completion(model="gpt-3.5-turbo-0613", messages=messages, functions=functions)
	router.reset()
	print(response)

	def test_acompletion_on_router():
	try:
	litellm.set_verbose = False
	model_list = [
	{
	"model_name": "gpt-3.5-turbo",
	"litellm_params": {
	"model": "gpt-3.5-turbo-0613",
	"api_key": os.getenv("OPENAI_API_KEY"),
	},
	"tpm": 100000,
	"rpm": 10000,
	},
	{
	"model_name": "gpt-3.5-turbo",
	"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")
	},
	"tpm": 100000,
	"rpm": 10000,
	}
	]

	messages = [
	{"role": "user", "content": f"write a one sentence poem {time.time()}?"}
	]
	start_time = time.time()
	router = Router(model_list=model_list,
	redis_host=os.environ["REDIS_HOST"],
	redis_password=os.environ["REDIS_PASSWORD"],
	redis_port=os.environ["REDIS_PORT"],
	cache_responses=True,
	timeout=30,
	routing_strategy="simple-shuffle")
	async def get_response():
	response1 = await router.acompletion(model="gpt-3.5-turbo", messages=messages)
	print(f"response1: {response1}")
	response2 = await router.acompletion(model="gpt-3.5-turbo", messages=messages)
	print(f"response2: {response2}")
	assert response1.id == response2.id
	assert len(response1.choices[0].message.content) > 0
	assert response1.choices[0].message.content == response2.choices[0].message.content
	asyncio.run(get_response())
	router.reset()
	except litellm.Timeout as e:
	end_time = time.time()
	print(f"timeout error occurred: {end_time - start_time}")
	pass
	except Exception as e:
	traceback.print_exc()
	pytest.fail(f"Error occurred: {e}")

	# test_acompletion_on_router()

	def test_function_calling_on_router():
	try:
	litellm.set_verbose = True
	model_list = [
	{
	"model_name": "gpt-3.5-turbo",
	"litellm_params": {
	"model": "gpt-3.5-turbo-0613",
	"api_key": os.getenv("OPENAI_API_KEY"),
	},
	},
	]
	function1 = [
	{
	"name": "get_current_weather",
	"description": "Get the current weather in a given location",
	"parameters": {
	"type": "object",
	"properties": {
	"location": {
	"type": "string",
	"description": "The city and state, e.g. San Francisco, CA",
	},
	"unit": {"type": "string", "enum": ["celsius", "fahrenheit"]},
	},
	"required": ["location"],
	},
	}
	]
	router = Router(
	model_list=model_list,
	redis_host=os.getenv("REDIS_HOST"),
	redis_password=os.getenv("REDIS_PASSWORD"),
	redis_port=os.getenv("REDIS_PORT")
	)
	messages=[
	{
	"role": "user",
	"content": "what's the weather in boston"
	}
	]
	response = router.completion(model="gpt-3.5-turbo", messages=messages, functions=function1)
	print(f"final returned response: {response}")
	router.reset()
	assert isinstance(response["choices"][0]["message"]["function_call"], dict)
	except Exception as e:
	print(f"An exception occurred: {e}")

	# test_function_calling_on_router()

	def test_aembedding_on_router():
	litellm.set_verbose = True
	try:
	model_list = [
	{
	"model_name": "text-embedding-ada-002",
	"litellm_params": {
	"model": "text-embedding-ada-002",
	},
	"tpm": 100000,
	"rpm": 10000,
	},
	]

	async def embedding_call():
	router = Router(model_list=model_list)
	response = await router.aembedding(
	model="text-embedding-ada-002",
	input=["good morning from litellm", "this is another item"],
	)
	print(response)
	router.reset()
	asyncio.run(embedding_call())
	except Exception as e:
	traceback.print_exc()
	pytest.fail(f"Error occurred: {e}")
	# test_aembedding_on_router()


	def test_azure_aembedding_on_router():
	litellm.set_verbose = True
	try:
	model_list = [
	{
	"model_name": "text-embedding-ada-002",
	"litellm_params": {
	"model": "azure/azure-embedding-model",
	"api_key":os.environ['AZURE_API_KEY'],
	"api_base": os.environ['AZURE_API_BASE']
	},
	"tpm": 100000,
	"rpm": 10000,
	},
	]

	async def embedding_call():
	router = Router(model_list=model_list)
	response = await router.aembedding(
	model="text-embedding-ada-002",
	input=["good morning from litellm"]
	)
	print(response)
	router.reset()
	asyncio.run(embedding_call())
	except Exception as e:
	traceback.print_exc()
	pytest.fail(f"Error occurred: {e}")
	# test_azure_aembedding_on_router()