From dca0a5ad0fb8807a2b96c6a4cdf64abea939a798 Mon Sep 17 00:00:00 2001 From: ishaan-jaff Date: Fri, 24 Nov 2023 17:14:44 -0800 Subject: [PATCH] (test) load test embedding: proxy --- litellm/proxy/tests/error_log.txt | 0 litellm/proxy/tests/load_test_embedding.py | 101 +++++++++++++++++++++ litellm/proxy/tests/request_log.txt | 0 3 files changed, 101 insertions(+) create mode 100644 litellm/proxy/tests/error_log.txt create mode 100644 litellm/proxy/tests/load_test_embedding.py create mode 100644 litellm/proxy/tests/request_log.txt diff --git a/litellm/proxy/tests/error_log.txt b/litellm/proxy/tests/error_log.txt new file mode 100644 index 00000000000..e69de29bb2d diff --git a/litellm/proxy/tests/load_test_embedding.py b/litellm/proxy/tests/load_test_embedding.py new file mode 100644 index 00000000000..097dcf2c543 --- /dev/null +++ b/litellm/proxy/tests/load_test_embedding.py @@ -0,0 +1,101 @@ +# test time it takes to make 100 concurrent embedding requests to OpenaI + +import sys, os +import traceback +from dotenv import load_dotenv + +load_dotenv() +import os, io + +sys.path.insert( + 0, os.path.abspath("../..") +) # Adds the parent directory to the system path +import pytest + + +import litellm +litellm.set_verbose=False + + + +question = "embed this very long text" * 100 + + +# make X concurrent calls to litellm.completion(model=gpt-35-turbo, messages=[]), pick a random question in questions array. +# Allow me to tune X concurrent calls.. Log question, output/exception, response time somewhere +# show me a summary of requests made, success full calls, failed calls. For failed calls show me the exceptions + +import concurrent.futures +import random +import time + + +# Function to make concurrent calls to OpenAI API +def make_openai_completion(question): + try: + start_time = time.time() + import openai + client = openai.OpenAI(api_key=os.environ['OPENAI_API_KEY']) #base_url="http://0.0.0.0:8000", + response = client.embeddings.create( + model="text-embedding-ada-002", + input=[question], + ) + print(response) + end_time = time.time() + + # Log the request details + # with open("request_log.txt", "a") as log_file: + # log_file.write( + # f"Question: {question[:100]}\nResponse ID:{response.id} Content:{response.choices[0].message.content[:10]}\nTime: {end_time - start_time:.2f} seconds\n\n" + # ) + + return response + except Exception as e: + # Log exceptions for failed calls + # with open("error_log.txt", "a") as error_log_file: + # error_log_file.write( + # f"\nException: {str(e)}\n\n" + # ) + return None + +start_time = time.time() +# Number of concurrent calls (you can adjust this) +concurrent_calls = 500 + +# List to store the futures of concurrent calls +futures = [] + +# Make concurrent calls +with concurrent.futures.ThreadPoolExecutor(max_workers=concurrent_calls) as executor: + for _ in range(concurrent_calls): + futures.append(executor.submit(make_openai_completion, question)) + +# Wait for all futures to complete +concurrent.futures.wait(futures) + +# Summarize the results +successful_calls = 0 +failed_calls = 0 + +for future in futures: + if future.result() is not None: + successful_calls += 1 + else: + failed_calls += 1 + +end_time = time.time() +# Calculate the duration +duration = end_time - start_time + +print(f"Load test Summary:") +print(f"Total Requests: {concurrent_calls}") +print(f"Successful Calls: {successful_calls}") +print(f"Failed Calls: {failed_calls}") +print(f"Total Time: {duration:.2f} seconds") + +# Display content of the logs +with open("request_log.txt", "r") as log_file: + print("\nRequest Log:\n", log_file.read()) + +with open("error_log.txt", "r") as error_log_file: + print("\nError Log:\n", error_log_file.read()) diff --git a/litellm/proxy/tests/request_log.txt b/litellm/proxy/tests/request_log.txt new file mode 100644 index 00000000000..e69de29bb2d