mirror of
https://github.com/BerriAI/litellm.git
synced 2025-04-26 11:14:04 +00:00
270 lines
9.1 KiB
Python
270 lines
9.1 KiB
Python
import sys, os, time
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import traceback
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from dotenv import load_dotenv
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load_dotenv()
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import os, io
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# this file is to test litellm/proxy
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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 pytest, logging
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import litellm
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from litellm import embedding, completion, completion_cost, Timeout
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from litellm import RateLimitError
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import sys, os, time
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import traceback
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from dotenv import load_dotenv
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load_dotenv()
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import os, io
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# this file is to test litellm/proxy
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from concurrent.futures import ThreadPoolExecutor
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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 pytest, logging, requests
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import litellm
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from litellm import embedding, completion, completion_cost, Timeout
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from litellm import RateLimitError
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from github import Github
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import subprocess
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# Function to execute a command and return the output
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def run_command(command):
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process = subprocess.Popen(command, stdout=subprocess.PIPE, shell=True)
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output, _ = process.communicate()
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return output.decode().strip()
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# Retrieve the current branch name
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branch_name = run_command("git rev-parse --abbrev-ref HEAD")
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# GitHub personal access token (with repo scope) or use username and password
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access_token = os.getenv("GITHUB_ACCESS_TOKEN")
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# Instantiate the PyGithub library's Github object
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g = Github(access_token)
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# Provide the owner and name of the repository where the pull request is located
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repository_owner = "BerriAI"
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repository_name = "litellm"
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# Get the repository object
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repo = g.get_repo(f"{repository_owner}/{repository_name}")
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# Iterate through the pull requests to find the one related to your branch
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for pr in repo.get_pulls():
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print(f"in here! {pr.head.ref}")
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if pr.head.ref == branch_name:
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pr_number = pr.number
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break
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print(f"The pull request number for branch {branch_name} is: {pr_number}")
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def test_add_new_key():
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max_retries = 3
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retry_delay = 1 # seconds
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for retry in range(max_retries + 1):
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try:
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# Your test data
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test_data = {
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"models": ["gpt-3.5-turbo", "gpt-4", "claude-2", "azure-model"],
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"aliases": {"mistral-7b": "gpt-3.5-turbo"},
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"duration": "20m",
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}
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print("testing proxy server")
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# Your bearer token
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token = os.getenv("PROXY_MASTER_KEY")
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headers = {"Authorization": f"Bearer {token}"}
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endpoint = f"https://litellm-litellm-pr-{pr_number}.up.railway.app"
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# Make a request to the staging endpoint
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response = requests.post(
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endpoint + "/key/generate", json=test_data, headers=headers
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)
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print(f"response: {response.text}")
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if response.status_code == 200:
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result = response.json()
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break # Successful response, exit the loop
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elif response.status_code == 503 and retry < max_retries:
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print(
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f"Retrying in {retry_delay} seconds... (Retry {retry + 1}/{max_retries})"
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)
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time.sleep(retry_delay)
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else:
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assert False, f"Unexpected response status code: {response.status_code}"
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except Exception as e:
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print(traceback.format_exc())
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pytest.fail(f"An error occurred {e}")
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def test_update_new_key():
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try:
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# Your test data
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test_data = {
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"models": ["gpt-3.5-turbo", "gpt-4", "claude-2", "azure-model"],
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"aliases": {"mistral-7b": "gpt-3.5-turbo"},
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"duration": "20m",
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}
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print("testing proxy server")
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# Your bearer token
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token = os.getenv("PROXY_MASTER_KEY")
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headers = {"Authorization": f"Bearer {token}"}
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endpoint = f"https://litellm-litellm-pr-{pr_number}.up.railway.app"
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# Make a request to the staging endpoint
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response = requests.post(
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endpoint + "/key/generate", json=test_data, headers=headers
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)
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assert response.status_code == 200
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result = response.json()
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assert result["key"].startswith("sk-")
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def _post_data():
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json_data = {"models": ["bedrock-models"], "key": result["key"]}
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response = requests.post(
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endpoint + "/key/generate", json=json_data, headers=headers
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)
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print(f"response text: {response.text}")
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assert response.status_code == 200
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return response
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_post_data()
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print(f"Received response: {result}")
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except Exception as e:
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pytest.fail(f"LiteLLM Proxy test failed. Exception: {str(e)}")
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# def test_add_new_key_max_parallel_limit():
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# try:
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# # Your test data
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# test_data = {"duration": "20m", "max_parallel_requests": 1}
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# # Your bearer token
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# token = os.getenv("PROXY_MASTER_KEY")
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# headers = {"Authorization": f"Bearer {token}"}
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# endpoint = f"https://litellm-litellm-pr-{pr_number}.up.railway.app"
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# print(f"endpoint: {endpoint}")
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# # Make a request to the staging endpoint
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# response = requests.post(
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# endpoint + "/key/generate", json=test_data, headers=headers
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# )
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# assert response.status_code == 200
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# result = response.json()
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# # load endpoint with model
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# model_data = {
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# "model_name": "azure-model",
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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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# }
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# response = requests.post(endpoint + "/model/new", json=model_data, headers=headers)
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# assert response.status_code == 200
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# print(f"response text: {response.text}")
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# def _post_data():
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# json_data = {
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# "model": "azure-model",
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# "messages": [
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# {
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# "role": "user",
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# "content": f"this is a test request, write a short poem {time.time()}",
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# }
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# ],
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# }
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# # Your bearer token
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# response = requests.post(
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# endpoint + "/chat/completions", json=json_data, headers={"Authorization": f"Bearer {result['key']}"}
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# )
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# return response
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# def _run_in_parallel():
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# with ThreadPoolExecutor(max_workers=2) as executor:
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# future1 = executor.submit(_post_data)
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# future2 = executor.submit(_post_data)
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# # Obtain the results from the futures
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# response1 = future1.result()
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# print(f"response1 text: {response1.text}")
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# response2 = future2.result()
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# print(f"response2 text: {response2.text}")
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# if response1.status_code == 429 or response2.status_code == 429:
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# pass
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# else:
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# raise Exception()
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# _run_in_parallel()
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# except Exception as e:
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# pytest.fail(f"LiteLLM Proxy test failed. Exception: {str(e)}")
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# def test_add_new_key_max_parallel_limit_streaming():
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# try:
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# # Your test data
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# test_data = {"duration": "20m", "max_parallel_requests": 1}
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# # Your bearer token
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# token = os.getenv("PROXY_MASTER_KEY")
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# headers = {"Authorization": f"Bearer {token}"}
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# endpoint = f"https://litellm-litellm-pr-{pr_number}.up.railway.app"
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# # Make a request to the staging endpoint
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# response = requests.post(
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# endpoint + "/key/generate", json=test_data, headers=headers
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# )
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# print(f"response: {response.text}")
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# assert response.status_code == 200
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# result = response.json()
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# def _post_data():
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# json_data = {
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# "model": "azure-model",
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# "messages": [
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# {
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# "role": "user",
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# "content": f"this is a test request, write a short poem {time.time()}",
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# }
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# ],
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# "stream": True,
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# }
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# response = requests.post(
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# endpoint + "/chat/completions", json=json_data, headers={"Authorization": f"Bearer {result['key']}"}
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# )
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# return response
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# def _run_in_parallel():
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# with ThreadPoolExecutor(max_workers=2) as executor:
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# future1 = executor.submit(_post_data)
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# future2 = executor.submit(_post_data)
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# # Obtain the results from the futures
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# response1 = future1.result()
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# response2 = future2.result()
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# if response1.status_code == 429 or response2.status_code == 429:
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# pass
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# else:
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# raise Exception()
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# _run_in_parallel()
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# except Exception as e:
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# pytest.fail(f"LiteLLM Proxy test failed. Exception: {str(e)}")
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