litellm-mirror/litellm/tests/test_completion.py
2023-09-18 13:44:19 -07:00

789 lines
27 KiB
Python

import sys, os
import traceback
from dotenv import load_dotenv
load_dotenv()
import os
sys.path.insert(
0, os.path.abspath("../..")
) # Adds the parent directory to the system path
import pytest
import litellm
from litellm import embedding, completion, text_completion, completion_cost
user_message = "Write a short poem about the sky"
messages = [{"content": user_message, "role": "user"}]
def logger_fn(user_model_dict):
print(f"user_model_dict: {user_model_dict}")
def test_completion_custom_provider_model_name():
try:
response = completion(
model="together_ai/togethercomputer/llama-2-70b-chat",
messages=messages,
logger_fn=logger_fn,
)
# Add any assertions here to check the response
print(response)
print(response['choices'][0]['finish_reason'])
except Exception as e:
pytest.fail(f"Error occurred: {e}")
# test_completion_custom_provider_model_name()
def test_completion_claude():
try:
response = completion(
model="claude-instant-1", messages=messages, logger_fn=logger_fn
)
# Add any assertions here to check the response
print(response)
except Exception as e:
pytest.fail(f"Error occurred: {e}")
# test_completion_claude()
# aleph alpha
# def test_completion_aleph_alpha():
# try:
# response = completion(
# model="luminous-base", messages=messages, logger_fn=logger_fn
# )
# # Add any assertions here to check the response
# print(response)
# except Exception as e:
# pytest.fail(f"Error occurred: {e}")
# test_completion_aleph_alpha()
# def test_completion_aleph_alpha_control_models():
# try:
# response = completion(
# model="luminous-base-control", messages=messages, logger_fn=logger_fn
# )
# # Add any assertions here to check the response
# print(response)
# except Exception as e:
# pytest.fail(f"Error occurred: {e}")
# test_completion_aleph_alpha_control_models()
def test_completion_with_litellm_call_id():
try:
litellm.use_client = False
response = completion(
model="gpt-3.5-turbo", messages=messages)
print(response)
if 'litellm_call_id' in response:
pytest.fail(f"Error occurred: litellm_call_id in response objects")
litellm.use_client = True
response2 = completion(
model="gpt-3.5-turbo", messages=messages)
if 'litellm_call_id' not in response2:
pytest.fail(f"Error occurred: litellm_call_id not in response object when use_client = True")
# Add any assertions here to check the response
print(response2)
except Exception as e:
pytest.fail(f"Error occurred: {e}")
# commenting out as this is a flaky test on circle ci
# def test_completion_nlp_cloud():
# try:
# messages = [
# {"role": "system", "content": "You are a helpful assistant."},
# {
# "role": "user",
# "content": "how does a court case get to the Supreme Court?",
# },
# ]
# response = completion(model="dolphin", messages=messages, logger_fn=logger_fn)
# print(response)
# except Exception as e:
# pytest.fail(f"Error occurred: {e}")
# test_completion_nlp_cloud()
# def test_completion_hf_api():
# try:
# user_message = "write some code to find the sum of two numbers"
# messages = [{ "content": user_message,"role": "user"}]
# api_base = "https://a8l9e3ucxinyl3oj.us-east-1.aws.endpoints.huggingface.cloud"
# response = completion(model="huggingface/meta-llama/Llama-2-7b-chat-hf", messages=messages, api_base=api_base, logger_fn=logger_fn)
# # Add any assertions here to check the response
# print(response)
# except Exception as e:
# if "loading" in str(e):
# pass
# pytest.fail(f"Error occurred: {e}")
# test_completion_hf_api()
# def test_completion_hf_deployed_api():
# try:
# user_message = "There's a llama in my garden 😱 What should I do?"
# messages = [{ "content": user_message,"role": "user"}]
# response = completion(model="huggingface/https://ji16r2iys9a8rjk2.us-east-1.aws.endpoints.huggingface.cloud", messages=messages, logger_fn=logger_fn)
# # Add any assertions here to check the response
# print(response)
# except Exception as e:
# pytest.fail(f"Error occurred: {e}")
# using Non TGI or conversational LLMs
# def hf_test_completion():
# try:
# # litellm.set_verbose=True
# user_message = "My name is Merve and my favorite"
# messages = [{ "content": user_message,"role": "user"}]
# response = completion(
# model="huggingface/roneneldan/TinyStories-3M",
# messages=messages,
# api_base="https://p69xlsj6rpno5drq.us-east-1.aws.endpoints.huggingface.cloud",
# task=None,
# )
# # Add any assertions here to check the response
# print(response)
# except Exception as e:
# pytest.fail(f"Error occurred: {e}")
# hf_test_completion()
def test_completion_cohere(): # commenting for now as the cohere endpoint is being flaky
try:
response = completion(
model="command-nightly",
messages=messages,
max_tokens=100,
logit_bias={40: 10},
logger_fn=logger_fn
)
# Add any assertions here to check the response
print(response)
response_str = response["choices"][0]["message"]["content"]
response_str_2 = response.choices[0].message.content
if type(response_str) != str:
pytest.fail(f"Error occurred: {e}")
if type(response_str_2) != str:
pytest.fail(f"Error occurred: {e}")
except Exception as e:
pytest.fail(f"Error occurred: {e}")
# test_completion_cohere()
def test_completion_openai():
try:
litellm.api_key = os.environ['OPENAI_API_KEY']
response = completion(model="gpt-3.5-turbo", messages=messages)
response_str = response["choices"][0]["message"]["content"]
response_str_2 = response.choices[0].message.content
print("response\n", response)
cost = completion_cost(completion_response=response)
print("Cost for completion call with gpt-3.5-turbo: ", f"${float(cost):.10f}")
assert response_str == response_str_2
assert type(response_str) == str
assert len(response_str) > 1
litellm.api_key = None
except Exception as e:
pytest.fail(f"Error occurred: {e}")
# test_completion_openai()
def test_completion_openai_prompt():
try:
response = text_completion(
model="gpt-3.5-turbo", prompt="What's the weather in SF?"
)
response_str = response["choices"][0]["message"]["content"]
response_str_2 = response.choices[0].message.content
print(response)
assert response_str == response_str_2
assert type(response_str) == str
assert len(response_str) > 1
except Exception as e:
pytest.fail(f"Error occurred: {e}")
def test_completion_text_openai():
try:
# litellm.set_verbose=True
response = completion(model="text-davinci-003", messages=messages)
# Add any assertions here to check the response
print(response)
except Exception as e:
pytest.fail(f"Error occurred: {e}")
def test_completion_gpt_instruct():
try:
response = completion(model="gpt-3.5-turbo-instruct", messages=messages)
print(response)
except Exception as e:
pytest.fail(f"Error occurred: {e}")
# test_completion_gpt_instruct()
def test_completion_openai_with_optional_params():
try:
response = completion(
model="gpt-3.5-turbo",
messages=messages,
temperature=0.5,
top_p=0.1,
user="ishaan_dev@berri.ai",
)
# Add any assertions here to check the response
print(response)
except Exception as e:
pytest.fail(f"Error occurred: {e}")
def test_completion_openai_litellm_key():
try:
litellm.api_key = os.environ['OPENAI_API_KEY']
# ensure key is set to None in .env and in openai.api_key
os.environ['OPENAI_API_KEY'] = ""
import openai
openai.api_key = ""
##########################################################
response = completion(
model="gpt-3.5-turbo",
messages=messages,
temperature=0.5,
top_p=0.1,
max_tokens=10,
user="ishaan_dev@berri.ai",
)
# Add any assertions here to check the response
print(response)
###### reset environ key
os.environ['OPENAI_API_KEY'] = litellm.api_key
##### unset litellm var
litellm.api_key = None
except Exception as e:
pytest.fail(f"Error occurred: {e}")
# test_completion_openai_litellm_key()
# commented out for now, as openrouter is quite flaky - causing our deployments to fail. Please run this before pushing changes.
# def test_completion_openrouter():
# try:
# response = completion(
# model="google/palm-2-chat-bison",
# messages=messages,
# temperature=0.5,
# top_p=0.1,
# )
# # Add any assertions here to check the response
# print(response)
# except Exception as e:
# pytest.fail(f"Error occurred: {e}")
def test_completion_openai_with_more_optional_params():
try:
response = completion(
model="gpt-3.5-turbo",
messages=messages,
temperature=0.5,
top_p=0.1,
n=2,
max_tokens=150,
presence_penalty=0.5,
frequency_penalty=-0.5,
logit_bias={123: 5},
user="ishaan_dev@berri.ai",
)
# Add any assertions here to check the response
print(response)
response_str = response["choices"][0]["message"]["content"]
response_str_2 = response.choices[0].message.content
print(response["choices"][0]["message"]["content"])
print(response.choices[0].message.content)
if type(response_str) != str:
pytest.fail(f"Error occurred: {e}")
if type(response_str_2) != str:
pytest.fail(f"Error occurred: {e}")
except Exception as e:
pytest.fail(f"Error occurred: {e}")
# def test_completion_openai_azure_with_functions():
# 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"],
# },
# }
# ]
# try:
# response = completion(
# model="azure/chatgpt-functioncalling", messages=messages, stream=True
# )
# # Add any assertions here to check the response
# print(response)
# for chunk in response:
# print(chunk)
# print(chunk["choices"][0]["finish_reason"])
# except Exception as e:
# pytest.fail(f"Error occurred: {e}")
# test_completion_openai_azure_with_functions()
def test_completion_azure():
try:
print("azure gpt-3.5 test\n\n")
response = completion(
model="azure/chatgpt-v-2",
messages=messages,
)
# Add any assertions here to check the response
print(response)
except Exception as e:
pytest.fail(f"Error occurred: {e}")
# test_completion_azure()
# new azure test for using litellm. vars,
# use the following vars in this test and make an azure_api_call
# litellm.api_type = self.azure_api_type
# litellm.api_base = self.azure_api_base
# litellm.api_version = self.azure_api_version
# litellm.api_key = self.api_key
def test_completion_azure_with_litellm_key():
try:
print("azure gpt-3.5 test\n\n")
import openai
#### set litellm vars
litellm.api_type = "azure"
litellm.api_base = os.environ['AZURE_API_BASE']
litellm.api_version = os.environ['AZURE_API_VERSION']
litellm.api_key = os.environ['AZURE_API_KEY']
######### UNSET ENV VARs for this ################
os.environ['AZURE_API_BASE'] = ""
os.environ['AZURE_API_VERSION'] = ""
os.environ['AZURE_API_KEY'] = ""
######### UNSET OpenAI vars for this ##############
openai.api_type = ""
openai.api_base = "gm"
openai.api_version = "333"
openai.api_key = "ymca"
response = completion(
model="azure/chatgpt-v-2",
messages=messages,
)
# Add any assertions here to check the response
print(response)
######### RESET ENV VARs for this ################
os.environ['AZURE_API_BASE'] = litellm.api_base
os.environ['AZURE_API_VERSION'] = litellm.api_version
os.environ['AZURE_API_KEY'] = litellm.api_key
######### UNSET litellm vars
litellm.api_type = None
litellm.api_base = None
litellm.api_version = None
litellm.api_key = None
except Exception as e:
pytest.fail(f"Error occurred: {e}")
# test_completion_azure()
def test_completion_azure_deployment_id():
try:
response = completion(
deployment_id="chatgpt-v-2",
model="gpt-3.5-turbo",
messages=messages,
)
# Add any assertions here to check the response
print(response)
except Exception as e:
pytest.fail(f"Error occurred: {e}")
# test_completion_azure_deployment_id()
# def test_completion_anthropic_litellm_proxy():
# try:
# response = completion(
# model="claude-2",
# messages=messages,
# api_key="sk-litellm-1234"
# )
# # Add any assertions here to check the response
# print(response)
# except Exception as e:
# pytest.fail(f"Error occurred: {e}")
# test_completion_anthropic_litellm_proxy()
# def test_hf_conversational_task():
# try:
# messages = [{ "content": "There's a llama in my garden 😱 What should I do?","role": "user"}]
# # e.g. Call 'facebook/blenderbot-400M-distill' hosted on HF Inference endpoints
# response = completion(model="huggingface/facebook/blenderbot-400M-distill", messages=messages, task="conversational")
# print(f"response: {response}")
# except Exception as e:
# pytest.fail(f"Error occurred: {e}")
# test_hf_conversational_task()
# Replicate API endpoints are unstable -> throw random CUDA errors -> this means our tests can fail even if our tests weren't incorrect.
# def test_completion_replicate_llama_2():
# model_name = "replicate/llama-2-70b-chat:2796ee9483c3fd7aa2e171d38f4ca12251a30609463dcfd4cd76703f22e96cdf"
# try:
# response = completion(
# model=model_name,
# messages=messages,
# max_tokens=20,
# custom_llm_provider="replicate"
# )
# print(response)
# cost = completion_cost(completion_response=response)
# print("Cost for completion call with llama-2: ", f"${float(cost):.10f}")
# # Add any assertions here to check the response
# response_str = response["choices"][0]["message"]["content"]
# print(response_str)
# if type(response_str) != str:
# pytest.fail(f"Error occurred: {e}")
# except Exception as e:
# pytest.fail(f"Error occurred: {e}")
# test_completion_replicate_llama_2()
def test_completion_replicate_vicuna():
model_name = "replicate/vicuna-13b:6282abe6a492de4145d7bb601023762212f9ddbbe78278bd6771c8b3b2f2a13b"
try:
response = completion(
model=model_name,
messages=messages,
custom_llm_provider="replicate",
temperature=0.1,
max_tokens=20,
)
print(response)
# Add any assertions here to check the response
response_str = response["choices"][0]["message"]["content"]
print(response_str)
if type(response_str) != str:
pytest.fail(f"Error occurred: {e}")
except Exception as e:
pytest.fail(f"Error occurred: {e}")
# def test_completion_replicate_stability_stream():
# model_name = "stability-ai/stablelm-tuned-alpha-7b:c49dae362cbaecd2ceabb5bd34fdb68413c4ff775111fea065d259d577757beb"
# try:
# response = completion(
# model=model_name,
# messages=messages,
# # stream=True,
# custom_llm_provider="replicate",
# )
# # print(response)
# # Add any assertions here to check the response
# # for chunk in response:
# # print(chunk["choices"][0]["delta"])
# print(response)
# except Exception as e:
# pytest.fail(f"Error occurred: {e}")
# test_completion_replicate_stability_stream()
######## Test TogetherAI ########
def test_completion_together_ai():
model_name = "togethercomputer/llama-2-70b-chat"
try:
response = completion(model=model_name, messages=messages, max_tokens=256, logger_fn=logger_fn)
# Add any assertions here to check the response
print(response)
cost = completion_cost(completion_response=response)
print("Cost for completion call together-computer/llama-2-70b: ", f"${float(cost):.10f}")
except Exception as e:
pytest.fail(f"Error occurred: {e}")
# test_completion_together_ai()
# def test_customprompt_together_ai():
# try:
# litellm.register_prompt_template(
# model="OpenAssistant/llama2-70b-oasst-sft-v10",
# roles={"system":"<|im_start|>system", "assistant":"<|im_start|>assistant", "user":"<|im_start|>user"}, # tell LiteLLM how you want to map the openai messages to this model
# pre_message_sep= "\n",
# post_message_sep= "\n"
# )
# response = completion(model="together_ai/OpenAssistant/llama2-70b-oasst-sft-v10", messages=messages)
# print(response)
# except Exception as e:
# pytest.fail(f"Error occurred: {e}")
def test_completion_sagemaker():
try:
response = completion(
model="sagemaker/jumpstart-dft-meta-textgeneration-llama-2-7b",
messages=messages,
temperature=0.2,
max_tokens=80,
logger_fn=logger_fn
)
# Add any assertions here to check the response
print(response)
except Exception as e:
pytest.fail(f"Error occurred: {e}")
def test_completion_bedrock_titan():
try:
response = completion(
model="bedrock/amazon.titan-tg1-large",
messages=messages,
temperature=0.2,
max_tokens=200,
top_p=0.8,
logger_fn=logger_fn
)
# Add any assertions here to check the response
print(response)
except Exception as e:
pytest.fail(f"Error occurred: {e}")
# test_completion_bedrock_titan()
def test_completion_bedrock_ai21():
try:
litellm.set_verbose = False
response = completion(
model="bedrock/ai21.j2-mid",
messages=messages,
temperature=0.2,
top_p=0.2,
max_tokens=20
)
# Add any assertions here to check the response
print(response)
except Exception as e:
pytest.fail(f"Error occurred: {e}")
######## Test VLLM ########
# def test_completion_vllm():
# try:
# response = completion(
# model="vllm/facebook/opt-125m",
# messages=messages,
# temperature=0.2,
# max_tokens=80,
# )
# print(response)
# except Exception as e:
# pytest.fail(f"Error occurred: {e}")
# test_completion_vllm()
# def test_completion_hosted_chatCompletion():
# # this tests calling a server where vllm is hosted
# # this should make an openai.Completion() call to the specified api_base
# # send a request to this proxy server: https://replit.com/@BerriAI/openai-proxy#main.py
# # it checks if model == facebook/opt-125m and returns test passed
# try:
# litellm.set_verbose = True
# response = completion(
# model="facebook/opt-125m",
# messages=messages,
# temperature=0.2,
# max_tokens=80,
# api_base="https://openai-proxy.berriai.repl.co",
# custom_llm_provider="openai"
# )
# print(response)
# if response['choices'][0]['message']['content'] != "passed":
# # see https://replit.com/@BerriAI/openai-proxy#main.py
# pytest.fail(f"Error occurred: proxy server did not respond")
# except Exception as e:
# pytest.fail(f"Error occurred: {e}")
# test_completion_hosted_chatCompletion()
# def test_completion_custom_api_base():
# try:
# response = completion(
# model="custom/meta-llama/Llama-2-13b-hf",
# messages=messages,
# temperature=0.2,
# max_tokens=10,
# api_base="https://api.autoai.dev/inference",
# request_timeout=300,
# )
# # Add any assertions here to check the response
# print("got response\n", response)
# except Exception as e:
# pytest.fail(f"Error occurred: {e}")
# test_completion_custom_api_base()
# def test_vertex_ai():
# litellm.vertex_project = "hardy-device-386718"
# litellm.vertex_location = "us-central1"
# test_models = litellm.vertex_chat_models + litellm.vertex_code_chat_models + litellm.vertex_text_models + litellm.vertex_code_text_models
# for model in test_models:
# try:
# print("making request", model)
# response = completion(model=model, messages=[{"role": "user", "content": "write code for saying hi"}])
# print(response)
# except Exception as e:
# pytest.fail(f"Error occurred: {e}")
# test_vertex_ai()
# def test_vertex_ai_stream():
# litellm.vertex_project = "hardy-device-386718"
# litellm.vertex_location = "us-central1"
# test_models = litellm.vertex_chat_models + litellm.vertex_code_chat_models + litellm.vertex_text_models + litellm.vertex_code_text_models
# for model in test_models:
# try:
# print("making request", model)
# response = completion(model=model, messages=[{"role": "user", "content": "write code for saying hi"}], stream=True)
# print(response)
# for chunk in response:
# print(chunk)
# # pass
# except Exception as e:
# pytest.fail(f"Error occurred: {e}")
# test_vertex_ai_stream()
def test_completion_with_fallbacks():
fallbacks = ["gpt-3.5-turb", "gpt-3.5-turbo", "command-nightly"]
try:
response = completion(
model="bad-model", messages=messages, force_timeout=120, fallbacks=fallbacks
)
# Add any assertions here to check the response
print(response)
except Exception as e:
pytest.fail(f"Error occurred: {e}")
# def test_baseten():
# try:
# response = completion(model="baseten/7qQNLDB", messages=messages, logger_fn=logger_fn)
# # Add any assertions here to check the response
# print(response)
# except Exception as e:
# pytest.fail(f"Error occurred: {e}")
# test_baseten()
# def test_baseten_falcon_7bcompletion():
# model_name = "qvv0xeq"
# try:
# response = completion(model=model_name, messages=messages, custom_llm_provider="baseten")
# # Add any assertions here to check the response
# print(response)
# except Exception as e:
# pytest.fail(f"Error occurred: {e}")
# test_baseten_falcon_7bcompletion()
# def test_baseten_falcon_7bcompletion_withbase():
# model_name = "qvv0xeq"
# litellm.api_base = "https://app.baseten.co"
# try:
# response = completion(model=model_name, messages=messages)
# # Add any assertions here to check the response
# print(response)
# except Exception as e:
# pytest.fail(f"Error occurred: {e}")
# litellm.api_base = None
# test_baseten_falcon_7bcompletion_withbase()
# def test_baseten_wizardLMcompletion_withbase():
# model_name = "q841o8w"
# litellm.api_base = "https://app.baseten.co"
# try:
# response = completion(model=model_name, messages=messages)
# # Add any assertions here to check the response
# print(response)
# except Exception as e:
# pytest.fail(f"Error occurred: {e}")
# test_baseten_wizardLMcompletion_withbase()
# def test_baseten_mosaic_ML_completion_withbase():
# model_name = "31dxrj3"
# litellm.api_base = "https://app.baseten.co"
# try:
# response = completion(model=model_name, messages=messages)
# # Add any assertions here to check the response
# print(response)
# except Exception as e:
# pytest.fail(f"Error occurred: {e}")
#### Test A121 ###################
def test_completion_ai21():
model_name = "j2-light"
try:
response = completion(model=model_name, messages=messages)
# Add any assertions here to check the response
print(response)
except Exception as e:
pytest.fail(f"Error occurred: {e}")
# test_completion_ai21()
# test config file with completion #
# def test_completion_openai_config():
# try:
# litellm.config_path = "../config.json"
# litellm.set_verbose = True
# response = litellm.config_completion(messages=messages)
# # Add any assertions here to check the response
# print(response)
# litellm.config_path = None
# except Exception as e:
# pytest.fail(f"Error occurred: {e}")
# import asyncio
# def test_completion_together_ai_stream():
# user_message = "Write 1pg about YC & litellm"
# messages = [{ "content": user_message,"role": "user"}]
# try:
# response = completion(model="togethercomputer/llama-2-70b-chat", messages=messages, stream=True, max_tokens=800)
# print(response)
# asyncio.run(get_response(response))
# # print(string_response)
# except Exception as e:
# pytest.fail(f"Error occurred: {e}")
# async def get_response(generator):
# async for elem in generator:
# print(elem)
# return
# test_completion_together_ai_stream()