litellm-mirror/litellm/tests/test_proxy_server_keys.py
2024-01-10 20:58:29 +05:30

270 lines
9.1 KiB
Python

import sys, os, time
import traceback
from dotenv import load_dotenv
load_dotenv()
import os, io
# this file is to test litellm/proxy
sys.path.insert(
0, os.path.abspath("../..")
) # Adds the parent directory to the system path
import pytest, logging
import litellm
from litellm import embedding, completion, completion_cost, Timeout
from litellm import RateLimitError
import sys, os, time
import traceback
from dotenv import load_dotenv
load_dotenv()
import os, io
# this file is to test litellm/proxy
from concurrent.futures import ThreadPoolExecutor
sys.path.insert(
0, os.path.abspath("../..")
) # Adds the parent directory to the system path
import pytest, logging, requests
import litellm
from litellm import embedding, completion, completion_cost, Timeout
from litellm import RateLimitError
from github import Github
import subprocess
# Function to execute a command and return the output
def run_command(command):
process = subprocess.Popen(command, stdout=subprocess.PIPE, shell=True)
output, _ = process.communicate()
return output.decode().strip()
# Retrieve the current branch name
branch_name = run_command("git rev-parse --abbrev-ref HEAD")
# GitHub personal access token (with repo scope) or use username and password
access_token = os.getenv("GITHUB_ACCESS_TOKEN")
# Instantiate the PyGithub library's Github object
g = Github(access_token)
# Provide the owner and name of the repository where the pull request is located
repository_owner = "BerriAI"
repository_name = "litellm"
# Get the repository object
repo = g.get_repo(f"{repository_owner}/{repository_name}")
# Iterate through the pull requests to find the one related to your branch
for pr in repo.get_pulls():
print(f"in here! {pr.head.ref}")
if pr.head.ref == branch_name:
pr_number = pr.number
break
print(f"The pull request number for branch {branch_name} is: {pr_number}")
def test_add_new_key():
max_retries = 3
retry_delay = 1 # seconds
for retry in range(max_retries + 1):
try:
# Your test data
test_data = {
"models": ["gpt-3.5-turbo", "gpt-4", "claude-2", "azure-model"],
"aliases": {"mistral-7b": "gpt-3.5-turbo"},
"duration": "20m",
}
print("testing proxy server")
# Your bearer token
token = os.getenv("PROXY_MASTER_KEY")
headers = {"Authorization": f"Bearer {token}"}
endpoint = f"https://litellm-litellm-pr-{pr_number}.up.railway.app"
# Make a request to the staging endpoint
response = requests.post(
endpoint + "/key/generate", json=test_data, headers=headers
)
print(f"response: {response.text}")
if response.status_code == 200:
result = response.json()
break # Successful response, exit the loop
elif response.status_code == 503 and retry < max_retries:
print(
f"Retrying in {retry_delay} seconds... (Retry {retry + 1}/{max_retries})"
)
time.sleep(retry_delay)
else:
assert False, f"Unexpected response status code: {response.status_code}"
except Exception as e:
print(traceback.format_exc())
pytest.fail(f"An error occurred {e}")
def test_update_new_key():
try:
# Your test data
test_data = {
"models": ["gpt-3.5-turbo", "gpt-4", "claude-2", "azure-model"],
"aliases": {"mistral-7b": "gpt-3.5-turbo"},
"duration": "20m",
}
print("testing proxy server")
# Your bearer token
token = os.getenv("PROXY_MASTER_KEY")
headers = {"Authorization": f"Bearer {token}"}
endpoint = f"https://litellm-litellm-pr-{pr_number}.up.railway.app"
# Make a request to the staging endpoint
response = requests.post(
endpoint + "/key/generate", json=test_data, headers=headers
)
assert response.status_code == 200
result = response.json()
assert result["key"].startswith("sk-")
def _post_data():
json_data = {"models": ["bedrock-models"], "key": result["key"]}
response = requests.post(
endpoint + "/key/generate", json=json_data, headers=headers
)
print(f"response text: {response.text}")
assert response.status_code == 200
return response
_post_data()
print(f"Received response: {result}")
except Exception as e:
pytest.fail(f"LiteLLM Proxy test failed. Exception: {str(e)}")
# def test_add_new_key_max_parallel_limit():
# try:
# # Your test data
# test_data = {"duration": "20m", "max_parallel_requests": 1}
# # Your bearer token
# token = os.getenv("PROXY_MASTER_KEY")
# headers = {"Authorization": f"Bearer {token}"}
# endpoint = f"https://litellm-litellm-pr-{pr_number}.up.railway.app"
# print(f"endpoint: {endpoint}")
# # Make a request to the staging endpoint
# response = requests.post(
# endpoint + "/key/generate", json=test_data, headers=headers
# )
# assert response.status_code == 200
# result = response.json()
# # load endpoint with model
# model_data = {
# "model_name": "azure-model",
# "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")
# }
# }
# response = requests.post(endpoint + "/model/new", json=model_data, headers=headers)
# assert response.status_code == 200
# print(f"response text: {response.text}")
# def _post_data():
# json_data = {
# "model": "azure-model",
# "messages": [
# {
# "role": "user",
# "content": f"this is a test request, write a short poem {time.time()}",
# }
# ],
# }
# # Your bearer token
# response = requests.post(
# endpoint + "/chat/completions", json=json_data, headers={"Authorization": f"Bearer {result['key']}"}
# )
# return response
# def _run_in_parallel():
# with ThreadPoolExecutor(max_workers=2) as executor:
# future1 = executor.submit(_post_data)
# future2 = executor.submit(_post_data)
# # Obtain the results from the futures
# response1 = future1.result()
# print(f"response1 text: {response1.text}")
# response2 = future2.result()
# print(f"response2 text: {response2.text}")
# if response1.status_code == 429 or response2.status_code == 429:
# pass
# else:
# raise Exception()
# _run_in_parallel()
# except Exception as e:
# pytest.fail(f"LiteLLM Proxy test failed. Exception: {str(e)}")
# def test_add_new_key_max_parallel_limit_streaming():
# try:
# # Your test data
# test_data = {"duration": "20m", "max_parallel_requests": 1}
# # Your bearer token
# token = os.getenv("PROXY_MASTER_KEY")
# headers = {"Authorization": f"Bearer {token}"}
# endpoint = f"https://litellm-litellm-pr-{pr_number}.up.railway.app"
# # Make a request to the staging endpoint
# response = requests.post(
# endpoint + "/key/generate", json=test_data, headers=headers
# )
# print(f"response: {response.text}")
# assert response.status_code == 200
# result = response.json()
# def _post_data():
# json_data = {
# "model": "azure-model",
# "messages": [
# {
# "role": "user",
# "content": f"this is a test request, write a short poem {time.time()}",
# }
# ],
# "stream": True,
# }
# response = requests.post(
# endpoint + "/chat/completions", json=json_data, headers={"Authorization": f"Bearer {result['key']}"}
# )
# return response
# def _run_in_parallel():
# with ThreadPoolExecutor(max_workers=2) as executor:
# future1 = executor.submit(_post_data)
# future2 = executor.submit(_post_data)
# # Obtain the results from the futures
# response1 = future1.result()
# response2 = future2.result()
# if response1.status_code == 429 or response2.status_code == 429:
# pass
# else:
# raise Exception()
# _run_in_parallel()
# except Exception as e:
# pytest.fail(f"LiteLLM Proxy test failed. Exception: {str(e)}")