OpenAI's generative AI tool "ChatGPT" has enjoyed explosive popularity since its release in November 2022 due to its capability for advanced and flexible dialogue at the level of daily conversation.
In March 2023, the API for the GPT models used in ChatGPT was made available to developers, making it easy to integrate ChatGPT-like conversational AI interfaces into conventional systems and apps. This has further promoted the business utilization of ChatGPT.
However, some may have questions about the benefits of using the API instead of the Web version of ChatGPT.
This article provides a detailed explanation of the safety and pricing structure of using ChatGPT via API, as well as what can be done with the API, the benefits and drawbacks of utilizing it, and actual use cases. This is a highly valuable article for business owners considering the introduction of ChatGPT.
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The ChatGPT API is an interface provided by OpenAI for incorporating the functions of the conversational generative AI "ChatGPT" into external services and applications.
By using ChatGPT via API, developers do not need to develop advanced models like ChatGPT from scratch, allowing for easy introduction. Furthermore, it enables the provision of advanced and interactive Web services with ChatGPT functions.
Since many users are already accustomed to using ChatGPT, one of the benefits is saving the effort of explaining how to use it.
As of November 2024, APIs for OpenAI's latest models, GPT-4o and o1-preview, are also available. Because of the wide range of model choices, they are utilized by various companies, including AI development firms.
ChatGPT API costs are incurred in "token" units, which are small segments of text data. The fee is determined based on the number of tokens used and the type of model.
The pricing per 1M tokens for major models is set as follows:
| Model Name | Input Price (per 1M tokens) | Output Price (per 1M tokens) |
| GPT-4o | $2.5 | $10.00 |
| GPT-4-turbo | $10.00 | $30.00 |
| GPT-3.5-turbo-0125 | $0.50 | $1.50 |
| o1-preview | $15.00 | $60.00 |
| GPT-4o-mini | $0.15 | $0.6 |
(Reference: Pricing | OpenAI)
For example, "GPT-4o," which is a current model, is set at a unit price about 1/3 to 1/4 that of GPT-4-turbo, allowing for use at a lower cost.
Additionally, the usage fee for the ChatGPT API can be calculated by multiplying the number of input and output tokens by their unit prices, as shown in the following formula:
| Usage Fee = (Number of Input Tokens / 1M) × Input Fee + (Number of Output Tokens / 1M) × Output Fee |
Even within the same GPT series, fees vary between GPT-4-turbo and GPT-4 due to differences in token capacity and processing speed. The key is to balance cost and capability to choose the appropriate model.
Note that 2,500 tokens are provided for free at the start of use, allowing you to consider the optimal model while actually testing the API.
By introducing ChatGPT via API, you can obtain benefits not found in the Web version. Here, we introduce the benefits of introducing ChatGPT functions using the API.
ChatGPT boasts high natural language processing capabilities compared to similar generative AIs. Therefore, by linking ChatGPT with external systems via API, it becomes possible to respond to users' natural inquiries.
In particular, utilizing it for customer support or concierge services allows for quick and accurate responses to user inquiries and questions. Communication with users proceeds smoothly, ultimately leading to improved customer satisfaction.
Content entered using the Web version of ChatGPT is generally sent to OpenAI and used as learning data for development.
On the other hand, data entered via the API is not used as learning data by OpenAI. Therefore, the risk of information leakage is low even when entering customer data or confidential information, allowing for introduction with peace of mind regarding security.
Building an advanced generative AI like ChatGPT from scratch requires specialized technical skills and massive resources.
In contrast, by using the ChatGPT API, it is possible to incorporate conversational AI functions into in-house services through simple steps without going through complex processes. For example, in the development of image classification systems, the effort of annotation and code creation can be reduced, allowing the system to be built in a short period.
Consequently, rapid service provision becomes possible, which is a major advantage for companies lacking AI development know-how and resources.
ChatGPT can handle a wide range of natural language processing tasks, such as question answering, text generation, and multilingual translation. Therefore, by utilizing it via API, it can be applied to various tasks such as minutes creation, customer support assistance, and annotation creation.
For example, with the speech recognition function "Whisper" provided via ChatGPT API, high-precision transcription from Japanese audio is possible, making it easy to transcribe meetings. It can handle meetings requiring specialized knowledge flexibly, so it can be used in a wide range of meetings.
Furthermore, it can extract key points from transcribed text to create summaries. Therefore, it can streamline the creation of meeting minutes.
Since API integration enables automatic responses, there are many use cases in support systems such as customer support and internal IT support. By registering frequently asked questions and answers in the system, you can respond immediately to user inquiries, reducing the burden on support staff.
For instance, ChatGPT has higher natural language processing capabilities among generative AIs, and its advantage is the ability to handle irregular questions with typos like "What was that... thing again?" or questions in a casual conversational format.
Recently, there has been an increase in use cases for annotation support systems utilizing GPT via API. Annotation is the process of creating learning data used for AI model development.
While strict annotation is more difficult than that of a human annotator, it has become capable of handling relatively simple tasks such as positive/negative sentiment analysis and named entity extraction for names and dates, as well as more complex semantic annotation.
Therefore, when utilizing the ChatGPT API for annotation, hybrid approaches are being researched where ChatGPT first performs rough initial annotation, followed by human detailed verification and correction.
In this way, using the ChatGPT API streamlines annotation work, effectively utilizes large amounts of image data, and can contribute to improving the accuracy of AI models.
When introducing ChatGPT functions using the API, there are several precautions regarding costs and response times. Here, we introduce points to note when introducing ChatGPT functions via API.
With an internally built system, you can adjust data and parameters as needed to optimize output content. You can also freely implement settings such as saying "I cannot answer" for questions where the answer does not exist in the learning data or implementing a function to present reference materials.
On the other hand, in the case of API integration, the difficulty of controlling generated content and changing implementation details increases significantly. Therefore, there is a risk that inappropriate expressions may be output unintentionally.
There is also a risk (hallucination) where the AI outputs functions that do not exist in the in-house service as if they do. If that happens, erroneous information about the service could spread. If inappropriate content is communicated to users, it could adversely affect the reliability of the in-house service.
While ChatGPT is adjusted to not respond to inappropriate questions, it is important for the user side to implement countermeasures as well. For example, the risk can be reduced by providing usage instructions to users or by utilizing RAG (Retrieval-Augmented Generation) to refer the AI to appropriate information.
Since the ChatGPT API operates in the cloud, response speed tends to slow down as the number of inputs and outputs increases. Especially when access is concentrated, smooth responses may not be obtained, and delays of several tens of seconds may occur.
Therefore, it is considered difficult to apply in situations where real-time responses are always essential, such as for edge devices or object recognition in autonomous driving. Since this could affect the provided service and lead to a decline in customer satisfaction, countermeasures based on the usage scene are necessary.
When using the API, fees are incurred per token. If it is integrated into a service without any consideration, tokens can swell significantly, posing a risk of greatly increased costs.
In particular, Japanese tends to consume more tokens compared to English. Therefore, care is needed because unplanned use of the API may unintentionally result in high usage fees.
To control API usage fees, countermeasures focused on cost management, such as limiting the number of user questions, are important.
If you want to equip your in-house system with ChatGPT functions via API, you can easily introduce it with the following steps:
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First, create an account on the official OpenAI website. Since an OpenAI account is required to use the API, complete the registration first. Note that a paid subscription to ChatGPT is not required.
After creating the account, issue an API key from the OpenAI dashboard. This API key is a required authentication credential for connecting the system to ChatGPT and must be stored safely.
Next, call the API using a programming language such as Python to incorporate ChatGPT functions into the system.
By utilizing the official libraries and API references provided by OpenAI, it is possible to proceed with development efficiently.
By utilizing the ChatGPT API, advanced conversational generative AI can be easily introduced in a wide range of situations, such as FAQ support for employees, program code suggestions, and annotation creation.
This not only saves labor in employee tasks but also streamlines system development and data processing, contributing significantly to improved internal productivity. Flexible responses to complex questions and real-time information provision become possible, also improving operational quality.
Furthermore, because the ChatGPT API is provided in the cloud, another benefit is the ability to suppress initial investment while expanding resources as needed. Therefore, companies can utilize ChatGPT flexibly while managing costs, easily starting businesses that incorporate conversational AI.