forked from phoenix/litellm-mirror
(test) load test queing
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015c7de549
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1 changed files with 46 additions and 35 deletions
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@ -91,13 +91,23 @@ def make_openai_completion(question):
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)
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)
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# polling the url
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# polling the url
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url = response["url"]
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while True:
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polling_url = f"http://0.0.0.0:8000{url}"
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try:
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print(f"POLLING JOB{polling_url}")
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print("entering the loop to poll")
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response = requests.get(polling_url)
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print("response", response)
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response = response.json()
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url = response["url"]
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status = response["status"]
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polling_url = f"http://0.0.0.0:8000{url}"
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print(f"POLLING JOB{polling_url}\nSTATUS: {status}, \n Response {response}")
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print(f"POLLING JOB{polling_url}")
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polling_response = requests.get(polling_url)
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print("\n RESPONSE FROM POLLING JoB", polling_response)
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polling_response = polling_response.json()
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print("\n RESPONSE FROM POLLING JoB", polling_response)
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status = polling_response["status"]
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print(f"POLLING JOB{polling_url}\nSTATUS: {status}, \n Response {polling_response}")
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time.sleep(0.5)
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except Exception as e:
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print("got exception in polling", e)
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break
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# if status == "finished":
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# if status == "finished":
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# print()
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# print()
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@ -111,41 +121,42 @@ def make_openai_completion(question):
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f"Question: {question[:100]}\nException: {str(e)}\n\n"
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f"Question: {question[:100]}\nException: {str(e)}\n\n"
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)
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)
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return None
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return None
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make_openai_completion("hello what's the time")
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# Number of concurrent calls (you can adjust this)
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# # Number of concurrent calls (you can adjust this)
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concurrent_calls = 100
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# concurrent_calls = 1
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# List to store the futures of concurrent calls
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# # List to store the futures of concurrent calls
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futures = []
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# futures = []
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# Make concurrent calls
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# # Make concurrent calls
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with concurrent.futures.ThreadPoolExecutor(max_workers=concurrent_calls) as executor:
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# with concurrent.futures.ThreadPoolExecutor(max_workers=concurrent_calls) as executor:
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for _ in range(concurrent_calls):
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# for _ in range(concurrent_calls):
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random_question = random.choice(questions)
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# random_question = random.choice(questions)
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futures.append(executor.submit(make_openai_completion, random_question))
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# futures.append(executor.submit(make_openai_completion, random_question))
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# Wait for all futures to complete
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# # Wait for all futures to complete
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concurrent.futures.wait(futures)
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# concurrent.futures.wait(futures)
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# Summarize the results
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# # Summarize the results
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successful_calls = 0
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# successful_calls = 0
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failed_calls = 0
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# failed_calls = 0
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for future in futures:
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# for future in futures:
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if future.result() is not None:
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# if future.result() is not None:
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successful_calls += 1
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# successful_calls += 1
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else:
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# else:
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failed_calls += 1
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# failed_calls += 1
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print(f"Load test Summary:")
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# print(f"Load test Summary:")
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print(f"Total Requests: {concurrent_calls}")
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# print(f"Total Requests: {concurrent_calls}")
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print(f"Successful Calls: {successful_calls}")
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# print(f"Successful Calls: {successful_calls}")
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print(f"Failed Calls: {failed_calls}")
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# print(f"Failed Calls: {failed_calls}")
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# Display content of the logs
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# # Display content of the logs
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with open("request_log.txt", "r") as log_file:
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# with open("request_log.txt", "r") as log_file:
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print("\nRequest Log:\n", log_file.read())
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# print("\nRequest Log:\n", log_file.read())
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with open("error_log.txt", "r") as error_log_file:
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# with open("error_log.txt", "r") as error_log_file:
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print("\nError Log:\n", error_log_file.read())
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# print("\nError Log:\n", error_log_file.read())
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