#custom GPTs alternative

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tepid raven
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what is the most relavent thing of custom GPTs that can work same and data cen be fed there and also be availabel via api to use in different application . in open ai

abstract drumBOT
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Hi @tepid raven. I'm kapa.ai, your friendly support bot. I will try to answer your question by searching through the knowledge base. :wave:

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The most relevant alternative to Custom GPTs in OpenAI that can be used in different applications via API is the Assistants API. While Custom GPTs are designed to be accessed only via the ChatGPT interfaces and cannot be automated by external APIs, the Assistants API offers this flexibility.

With the Assistants API, you can create an assistant that can interact with your application, process data, and return responses. However, it's important to note that the results from an Assistant might not be exactly the same as a Custom GPT, as they are different tools with different capabilities.

For more information, you can refer to the Assistants API documentation (https://platform.openai.com/docs/assistants/overview).

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tepid raven
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okay .by working same , i meant the quality of the response should be same. as i will fed same data. is it possible

tepid raven
abstract drumBOT
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Let me check the knowledge base for you. One moment! :books:

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Yes, it is possible to achieve similar quality of responses between your Custom GPT and an Assistant, especially if you're feeding the same data. However, there might be some differences due to the inherent variability in AI models and the specific configurations you use for each tool.

To ensure the best possible results, you should:

  1. Use the same model version for both your Custom GPT and Assistant. For example, if you trained your Custom GPT with GPT-4, you should use GPT-4 for your Assistant as well.

  2. Use the same parameters for both tools, such as temperature and max tokens.

  3. Make sure to format your prompts in a way that the model understands. For example, if you're using the chat models, you should format your prompts as a list of messages.

  4. Experiment with different ways of priming or conditioning the model. For example, one developer discovered an increase in accuracy when they inserted a user message that said "Great job so far, these have been perfect" to help condition the model into providing higher quality responses.

  5. Use the seed parameter to make your outputs consistent. If specified, OpenAI's system will make a best effort to sample deterministically, such that repeated requests with the same seed and parameters should return the same result.

Remember that AI models are probabilistic and there's always a degree of randomness in their responses. Therefore, even with the same data and parameters, you might not get exactly the same results every time.