The Key to ChatGPT Cost Optimization

As the popularity of Generative AI grows, businesses are increasingly turning to ChatGPT to provide human-like responses. However, the costs of using ChatGPT can add up quickly, especially for businesses with a high volume of requests. OneAI offers a cost-effective solution by optimizing those costs through three methods.

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The cost of using generative AI models is based on the length of the input (‘prompt’) and the output, with prices set per token. To reduce costs, businesses can use shorter, smarter prompts. OneAI provides three ways to optimize ChatGPT costs:

OneAI pipeline allows for the creation of a smart workflow that extracts relevant information from any language data such as documents, video calls, transcripts and feeds only that information into ChatGPT. For example, businesses can use OneAI's Highlights Skill to extract the most important information from each article, which can then be fed into ChatGPT for further processing. Pipelines can be built and tuned directly in code, or by using the no-code Languge Studio.

CutGPT is a slim and task-oriented generative AI model that can be customized to fit a business's exact needs. This means that businesses can tune their own CutGPT on the input and output of their existing ChatGPT prompt, creating a more cost-effective solution that is tailored to their specific use case. CutGPT can be trained in just days and delivers predictable and structured output that is tailored to the business's requirements. More info here.

OneAI's Language Analytics breaks language into meaningful clusters, allowing businesses to quickly and easily identify the key themes and messages within their language data. By feeding the most relevant parts of this output into ChatGPT, businesses can provide it with the most relevant content to answer questions about the underlying text.

For example, if you're running a customer service operation, you can use this tool to analyze customer complaints and feedback, and then feed the most relevant parts of the resulting clusters into ChatGPT. This allows you to provide more accurate and helpful responses to customer queries, improving the overall customer experience and reducing the workload on your support staff.

Additional benefits of using OneAI in conjunction with ChatGPT

Write a meeting summary email based on meeting highlights:

```

import requests

import json

url = "https://api.oneai.com/api/v0/pipeline"

payload = json.dumps({

  "input": "John: Good morning, everyone. Let's get started. David and Lisa, how was your week? David: It was good. I had a few leads that I followed up on, and I was able to close a deal with one of them. Lisa: Same here. I had some good conversations with potential clients, and I'm optimistic that we'll be able to close some deals soon John: That's great to hear. Sarah, how are the overall sales numbers looking? Sarah: They're looking pretty good. We're on track to hit our quarterly targets, but there's still some work to be done. I think we need to focus more on following up with leads and closing deals quickly. John: Agreed. And what about our new product launch? How's the response been? Sarah: The response has been positive so far. We've had some good feedback from customers, and we're getting a lot of interest from new leads. John: That's excellent. Let's keep pushing on that front. And finally, I wanted to remind everyone about the upcoming sales conference. We need to make sure we're prepared for that and have our presentations ready. Sarah: Yes, I've already started working on mine, and I'll make sure everyone else is on track as well. John: Great. Any other topics for today's meeting? Lisa: I just wanted to mention that I think we should consider expanding into a new market. I've been doing some research, and I think there's a lot of potential there. John: That's an interesting idea. Let's discuss that further in our next meeting and see if we can come up with a plan. Sarah: Sounds good. John: Alright, that's it for today's meeting. Thanks, everyone.",

  "input_type": "article",

  "content_type": "application/json",

  "multilingual": {

    "enabled": True

  },

  "steps": [

{"skill": "highlights"},

 {"skill": "gpt", "params": {"prompt": "Please create a meeting summary email based on the following hishlights", "input_skill": "highlights"}}]})

headers = {'api-key':’<YOUR API KEY>’, 'Content-Type': 'application/json'}

response = requests.request("POST", url, headers=headers, data=payload)

print(response.text)

```

Here is the email that was generated:

Subject: Meeting Summary

Dear Team,

This is a summary of our meeting today. We discussed the need to focus more on following up with leads and closing deals quickly, and the response has been positive so far. Lisa suggested that we should consider expanding into a new market. David and Lisa, we asked how your week was going and what about our new product launch. Sarah, we asked how the overall sales numbers are looking. We are on track to hit our quarterly targets, but there's still some work to be done.

Let me know if you have any questions or need any further clarification.

Best,

[Your Name]

In conclusion, OneAI's capabilities allow for the optimization of OpenAI's ChatGPT costs, making it a cost-effective solution for businesses. Whether businesses choose to use OneAI's pipeline, CutGPT, or Language Analytics, they can be sure that they are getting a solution that is tailored to their specific needs and will help them achieve their goals more efficiently.

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