forked from phoenix/litellm-mirror
test(test_router.py): reintegrate router testing
This commit is contained in:
Krrish Dholakia
parent
c75e90663c
commit
3dcbf6197a
1 changed files with 277 additions and 277 deletions
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@ -1,294 +1,294 @@
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# #### What this tests ####
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# # This tests calling batch_completions by running 100 messages together
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#### What this tests ####
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# This tests calling batch_completions by running 100 messages together
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# import sys, os, time
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# import traceback, asyncio
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# import pytest
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# sys.path.insert(
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# 0, os.path.abspath("../..")
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# ) # Adds the parent directory to the system path
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# import litellm
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# from litellm import Router
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# from concurrent.futures import ThreadPoolExecutor
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# from dotenv import load_dotenv
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# load_dotenv()
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import sys, os, time
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import traceback, asyncio
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import pytest
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sys.path.insert(
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0, os.path.abspath("../..")
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) # Adds the parent directory to the system path
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import litellm
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from litellm import Router
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from concurrent.futures import ThreadPoolExecutor
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from dotenv import load_dotenv
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load_dotenv()
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# def test_exception_raising():
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# # this tests if the router raises an exception when invalid params are set
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# # in this test both deployments have bad keys - Keep this test. It validates if the router raises the most recent exception
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# litellm.set_verbose=True
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# import openai
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# try:
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# print("testing if router raises an exception")
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# old_api_key = os.environ["AZURE_API_KEY"]
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# os.environ["AZURE_API_KEY"] = ""
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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": "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", # openai model name
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# "litellm_params": { #
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# "model": "gpt-3.5-turbo",
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# "api_key": "bad-key",
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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,
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# redis_host=os.getenv("REDIS_HOST"),
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# redis_password=os.getenv("REDIS_PASSWORD"),
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# redis_port=int(os.getenv("REDIS_PORT")),
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# routing_strategy="simple-shuffle",
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# set_verbose=False,
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# num_retries=1) # type: ignore
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# response = router.completion(
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# model="gpt-3.5-turbo",
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# messages=[
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# {
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# "role": "user",
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# "content": "hello this request will fail"
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# }
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# ]
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# )
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# os.environ["AZURE_API_KEY"] = old_api_key
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# pytest.fail(f"Should have raised an Auth Error")
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# except openai.AuthenticationError:
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# print("Test Passed: Caught an OPENAI AUTH Error, Good job. This is what we needed!")
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# os.environ["AZURE_API_KEY"] = old_api_key
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# router.flush_cache()
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# except Exception as e:
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# os.environ["AZURE_API_KEY"] = old_api_key
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# print("Got unexpected exception on router!", e)
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# # test_exception_raising()
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def test_exception_raising():
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# this tests if the router raises an exception when invalid params are set
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# in this test both deployments have bad keys - Keep this test. It validates if the router raises the most recent exception
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litellm.set_verbose=True
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import openai
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try:
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print("testing if router raises an exception")
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old_api_key = os.environ["AZURE_API_KEY"]
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os.environ["AZURE_API_KEY"] = ""
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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": "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", # openai model name
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"litellm_params": { #
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"model": "gpt-3.5-turbo",
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"api_key": "bad-key",
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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,
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redis_host=os.getenv("REDIS_HOST"),
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redis_password=os.getenv("REDIS_PASSWORD"),
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redis_port=int(os.getenv("REDIS_PORT")),
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routing_strategy="simple-shuffle",
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set_verbose=False,
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num_retries=1) # type: ignore
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response = router.completion(
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model="gpt-3.5-turbo",
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messages=[
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{
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"role": "user",
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"content": "hello this request will fail"
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}
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]
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)
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os.environ["AZURE_API_KEY"] = old_api_key
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pytest.fail(f"Should have raised an Auth Error")
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except openai.AuthenticationError:
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print("Test Passed: Caught an OPENAI AUTH Error, Good job. This is what we needed!")
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os.environ["AZURE_API_KEY"] = old_api_key
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router.flush_cache()
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except Exception as e:
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os.environ["AZURE_API_KEY"] = old_api_key
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print("Got unexpected exception on router!", e)
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# test_exception_raising()
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# def test_reading_key_from_model_list():
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# # this tests if the router raises an exception when invalid params are set
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# # DO NOT REMOVE THIS TEST. It's an IMP ONE. Speak to Ishaan, if you are tring to remove this
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# litellm.set_verbose=False
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# import openai
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# try:
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# print("testing if router raises an exception")
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# old_api_key = os.environ["AZURE_API_KEY"]
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# os.environ.pop("AZURE_API_KEY", None)
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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": old_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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def test_reading_key_from_model_list():
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# this tests if the router raises an exception when invalid params are set
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# DO NOT REMOVE THIS TEST. It's an IMP ONE. Speak to Ishaan, if you are tring to remove this
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litellm.set_verbose=False
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import openai
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try:
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print("testing if router raises an exception")
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old_api_key = os.environ["AZURE_API_KEY"]
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os.environ.pop("AZURE_API_KEY", None)
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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": old_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,
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# redis_host=os.getenv("REDIS_HOST"),
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# redis_password=os.getenv("REDIS_PASSWORD"),
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# redis_port=int(os.getenv("REDIS_PORT")),
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# routing_strategy="simple-shuffle",
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# set_verbose=True,
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# num_retries=1) # type: ignore
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# response = router.completion(
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# model="gpt-3.5-turbo",
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# messages=[
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# {
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# "role": "user",
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# "content": "hello this request will fail"
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# }
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# ]
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# )
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# os.environ["AZURE_API_KEY"] = old_api_key
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# router.flush_cache()
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# except Exception as e:
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# os.environ["AZURE_API_KEY"] = old_api_key
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# print(f"FAILED TEST")
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# pytest.fail("Got unexpected exception on router!", e)
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# # test_reading_key_from_model_list()
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router = Router(model_list=model_list,
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redis_host=os.getenv("REDIS_HOST"),
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redis_password=os.getenv("REDIS_PASSWORD"),
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redis_port=int(os.getenv("REDIS_PORT")),
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routing_strategy="simple-shuffle",
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set_verbose=True,
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num_retries=1) # type: ignore
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response = router.completion(
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model="gpt-3.5-turbo",
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messages=[
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{
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"role": "user",
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"content": "hello this request will fail"
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}
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]
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)
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os.environ["AZURE_API_KEY"] = old_api_key
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router.flush_cache()
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except Exception as e:
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os.environ["AZURE_API_KEY"] = old_api_key
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print(f"FAILED TEST")
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pytest.fail("Got unexpected exception on router!", e)
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# test_reading_key_from_model_list()
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# ### FUNCTION CALLING
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### FUNCTION CALLING
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# def test_function_calling():
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# model_list = [
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# {
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# "model_name": "gpt-3.5-turbo-0613",
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# "litellm_params": {
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# "model": "gpt-3.5-turbo-0613",
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# "api_key": os.getenv("OPENAI_API_KEY"),
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# },
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# "tpm": 100000,
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# "rpm": 10000,
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# },
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# ]
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def test_function_calling():
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model_list = [
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{
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"model_name": "gpt-3.5-turbo-0613",
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"litellm_params": {
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"model": "gpt-3.5-turbo-0613",
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"api_key": os.getenv("OPENAI_API_KEY"),
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},
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"tpm": 100000,
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"rpm": 10000,
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},
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]
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# messages = [
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# {"role": "user", "content": "What is the weather like in Boston?"}
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# ]
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# functions = [
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# {
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# "name": "get_current_weather",
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# "description": "Get the current weather in a given location",
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# "parameters": {
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# "type": "object",
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# "properties": {
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# "location": {
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# "type": "string",
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# "description": "The city and state, e.g. San Francisco, CA"
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# },
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# "unit": {
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# "type": "string",
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# "enum": ["celsius", "fahrenheit"]
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# }
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# },
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# "required": ["location"]
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# }
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# }
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# ]
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messages = [
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{"role": "user", "content": "What is the weather like in Boston?"}
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]
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functions = [
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{
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"name": "get_current_weather",
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"description": "Get the current weather in a given location",
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"parameters": {
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"type": "object",
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"properties": {
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"location": {
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"type": "string",
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"description": "The city and state, e.g. San Francisco, CA"
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},
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"unit": {
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"type": "string",
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"enum": ["celsius", "fahrenheit"]
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}
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},
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"required": ["location"]
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}
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}
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]
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# router = Router(model_list=model_list, routing_strategy="latency-based-routing")
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# response = router.completion(model="gpt-3.5-turbo-0613", messages=messages, functions=functions)
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# print(response)
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router = Router(model_list=model_list, routing_strategy="latency-based-routing")
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response = router.completion(model="gpt-3.5-turbo-0613", messages=messages, functions=functions)
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print(response)
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# def test_acompletion_on_router():
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# try:
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# litellm.set_verbose = False
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# model_list = [
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# {
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# "model_name": "gpt-3.5-turbo",
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# "litellm_params": {
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# "model": "gpt-3.5-turbo-0613",
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# "api_key": os.getenv("OPENAI_API_KEY"),
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# },
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# "tpm": 100000,
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# "rpm": 10000,
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# },
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# {
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# "model_name": "gpt-3.5-turbo",
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# "litellm_params": {
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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_base": os.getenv("AZURE_API_BASE"),
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# "api_version": os.getenv("AZURE_API_VERSION")
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# },
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# "tpm": 100000,
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# "rpm": 10000,
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# }
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# ]
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def test_acompletion_on_router():
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try:
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litellm.set_verbose = False
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model_list = [
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{
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"model_name": "gpt-3.5-turbo",
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"litellm_params": {
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"model": "gpt-3.5-turbo-0613",
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"api_key": os.getenv("OPENAI_API_KEY"),
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},
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"tpm": 100000,
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"rpm": 10000,
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},
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{
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"model_name": "gpt-3.5-turbo",
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"litellm_params": {
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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_base": os.getenv("AZURE_API_BASE"),
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"api_version": os.getenv("AZURE_API_VERSION")
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},
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"tpm": 100000,
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"rpm": 10000,
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}
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]
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# messages = [
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# {"role": "user", "content": f"write a one sentence poem {time.time()}?"}
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# ]
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# start_time = time.time()
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# router = Router(model_list=model_list,
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# redis_host=os.environ["REDIS_HOST"],
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# redis_password=os.environ["REDIS_PASSWORD"],
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# redis_port=os.environ["REDIS_PORT"],
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# cache_responses=True,
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# timeout=30,
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# routing_strategy="simple-shuffle")
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# async def get_response():
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# response1 = await router.acompletion(model="gpt-3.5-turbo", messages=messages)
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# print(f"response1: {response1}")
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# response2 = await router.acompletion(model="gpt-3.5-turbo", messages=messages)
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# print(f"response2: {response2}")
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# assert response1.id == response2.id
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# assert len(response1.choices[0].message.content) > 0
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# assert response1.choices[0].message.content == response2.choices[0].message.content
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# asyncio.run(get_response())
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# except litellm.Timeout as e:
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# end_time = time.time()
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# print(f"timeout error occurred: {end_time - start_time}")
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# pass
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# except Exception as e:
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# traceback.print_exc()
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# pytest.fail(f"Error occurred: {e}")
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messages = [
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{"role": "user", "content": f"write a one sentence poem {time.time()}?"}
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]
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start_time = time.time()
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router = Router(model_list=model_list,
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redis_host=os.environ["REDIS_HOST"],
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redis_password=os.environ["REDIS_PASSWORD"],
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redis_port=os.environ["REDIS_PORT"],
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cache_responses=True,
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timeout=30,
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routing_strategy="simple-shuffle")
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async def get_response():
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response1 = await router.acompletion(model="gpt-3.5-turbo", messages=messages)
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print(f"response1: {response1}")
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response2 = await router.acompletion(model="gpt-3.5-turbo", messages=messages)
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print(f"response2: {response2}")
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assert response1.id == response2.id
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assert len(response1.choices[0].message.content) > 0
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assert response1.choices[0].message.content == response2.choices[0].message.content
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asyncio.run(get_response())
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except litellm.Timeout as e:
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end_time = time.time()
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print(f"timeout error occurred: {end_time - start_time}")
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pass
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except Exception as e:
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traceback.print_exc()
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pytest.fail(f"Error occurred: {e}")
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# test_acompletion_on_router()
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test_acompletion_on_router()
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# def test_function_calling_on_router():
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# try:
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# litellm.set_verbose = True
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# model_list = [
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# {
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# "model_name": "gpt-3.5-turbo",
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# "litellm_params": {
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# "model": "gpt-3.5-turbo-0613",
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# "api_key": os.getenv("OPENAI_API_KEY"),
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# },
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# },
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# ]
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# function1 = [
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# {
|
||||
# "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}")
|
||||
# assert isinstance(response["choices"][0]["message"]["function_call"], dict)
|
||||
# except Exception as e:
|
||||
# print(f"An exception occurred: {e}")
|
||||
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}")
|
||||
assert isinstance(response["choices"][0]["message"]["function_call"], dict)
|
||||
except Exception as e:
|
||||
print(f"An exception occurred: {e}")
|
||||
|
||||
# # test_function_calling_on_router()
|
||||
# test_function_calling_on_router()
|
||||
|
||||
# def test_aembedding_on_router():
|
||||
# try:
|
||||
# model_list = [
|
||||
# {
|
||||
# "model_name": "text-embedding-ada-002",
|
||||
# "litellm_params": {
|
||||
# "model": "text-embedding-ada-002",
|
||||
# },
|
||||
# "tpm": 100000,
|
||||
# "rpm": 10000,
|
||||
# },
|
||||
# ]
|
||||
def test_aembedding_on_router():
|
||||
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)
|
||||
# asyncio.run(embedding_call())
|
||||
# except Exception as e:
|
||||
# traceback.print_exc()
|
||||
# pytest.fail(f"Error occurred: {e}")
|
||||
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)
|
||||
asyncio.run(embedding_call())
|
||||
except Exception as e:
|
||||
traceback.print_exc()
|
||||
pytest.fail(f"Error occurred: {e}")
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue