A Case Study on OpenAI API Usage and Billing by Tamzida

A Case Study on OpenAI API Usage and Billing by Tamzida

The growing prevalence of Artificial Intelligence (AI) in various industries has led to an increased reliance on tools like OpenAI to enhance products and services. With this increasing integration of AI, rigorous Quality Assurance (QA) becomes crucial to ensure accuracy, efficiency, and cost-effectiveness. In this blog, we will explore a recent case study by Tamzida, a QA expert from SJ Innovation, who demonstrated the importance of QA in managing OpenAI API usage and billing for internal projects with the aid of screenshots and actual test cases.

 

The Challenge

SJ Innovation experienced a sudden spike in OpenAI API usage and billing, with daily costs reaching $30 compared to less than $1 per day over the previous 30 days. This unexpected increase highlighted the importance of thorough QA in identifying the root cause and optimizing OpenAI API usage across internal projects.

 

Tamzida’s Approach

She started by creating a comprehensive test case to verify the OpenAI API usage and billing for SJ Innovation's internal projects. 

 

Testcases for Verifying Billing of OpenAI API

She used ChatGPT for generating the testcases. 

Prompt Used: Last 2 days it cost the owner 35$ where as earlier OpenAPI used to charge 1$.  I want to compare the bill of recent days. Create a Testcase for me to verify the usage limit and billing for a OpenAPI account where the account holder is the owner. Please include Pre condition, Test case, Test steps,  and Expected result.

 

Here is the output: 

Using chatgpt for generating testcases

Using chatgpt for generating testcases (2nd part)

Using chatgpt for generating testcases

She then executed the test case and documented her findings with screenshots, illustrating each step of the process:

 

Reviewing the OpenAI API dashboard and billing section to identify usage trends and sudden spikes. 

OpenAI API dashboard review

 

Investigating the number of tokens used in internal projects using the OpenAI API pricing to identify the increased usage. She took the pricing data from this website: https://openai.com/pricing 

verifying billing of openAI API

 

Comparing the expected usage of the OpenAI API in the project(s) with the actual usage and billing data to identify discrepancies.

Tamzida also compiled the actual test result with the expected result in a detailed report, showcasing the effectiveness of her QA efforts.

Compiled the actual test result with the expected result

 

The Importance of Quality Assurance

This case study, complete with screenshots and actual test cases, underscores the crucial role of QA in managing OpenAI API usage and billing. By conducting thorough QA, businesses can:

  • Ensure the accuracy of AI implementations, avoiding costly errors and inefficiencies.
  • Optimize AI usage to prevent exceeding billing thresholds and ensure cost-effectiveness.
  • Maintain the overall quality of products and services that rely on AI, resulting in higher customer satisfaction.

 

Recommendations for Companies Using OpenAI API

This case study serves as an essential reminder for any company using OpenAI to invest in Quality Assurance. OpenAPI offers multiple models, each with different capabilities and price points. Prices are per 1,000 tokens. You can think of tokens as pieces of words, where 1,000 tokens is about 750 words. 

 

To effectively manage OpenAI API usage, companies should:

Establish a dedicated QA team to regularly review and monitor OpenAI API usage for not facing any uncertain incident. Continuously analyze and optimize AI usage can ensure cost-effectiveness and prevent unexpected billing spikes.

Quality Assurance plays a vital role in ensuring the success of AI implementations, particularly when it comes to managing OpenAI API usage. By investing in thorough QA processes and providing visual documentation, companies can optimize their AI usage, prevent costly errors, and maintain the high quality of their products and services. Tamzida's case study, serves as an excellent example of the benefits that a dedicated QA team can bring to any organization leveraging the power of AI.

 

So don't let costly errors hold you back. Our UAT and QA experts optimize your OpenAI API usage and prevent unexpected billing spikes while never compromising on quality! The result? Successful AI implementations while maintaining the highest quality of your products and services. Get in touch with our QA and UAT tester experts today!

Suyog Kakodkar
Suyog Kakodkar
Assistant Manager
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