#Assistant created with API /Streaming

1 messages · Page 1 of 1 (latest)

woeful elm
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How do I get the assistant I created, not a customGPT, to stream the conversation so it doesn’t take so long to load for the user. Provide step by step instructions using node.js

strange skyBOT
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Hi @woeful elm. I'm kapa.ai, your friendly support bot. I will try to answer your question by searching through the knowledge base. :wave:

#

Based on the information provided in the extracts, it seems that you can use the OpenAI Node API Library to create a chat completion with the stream: true option. This will allow you to stream the conversation and potentially reduce loading times for the user. Here's a step-by-step guide based on the information available:

  1. First, you need to import the OpenAI library and initialize it with your API key:
import OpenAI from "openai";
const openai = new OpenAI({ apiKey: "your-openai-api-key" });
  1. Then, you can create a chat completion with the stream: true option:
const stream = await openai.beta.chat.completions.stream({
    model: "gpt-4-1106-preview", // replace with your model
    messages: messages, // replace with your messages
    tools: tools, // replace with your tools
    tool_choice: "auto",
    stream: true,
});
  1. You can then listen for messages from the stream and handle them as needed:
stream.on('message', async (message) => {
    // handle the message here
    console.log(message);
});
  1. Finally, you can return the stream to the client:
return Response(stream.toReadableStream());

Please note that this is a simplified example and you may need to adjust it to fit your specific use case. Also, the model "gpt-4-1106-preview" is used as an example, you should replace it with the model you are using.

Sources:


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@woeful elm kapa.ai is still learning and improving, please let us know how it did by reacting below

woeful elm
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@strange sky what about streaming an assistant using the assistant id?

strange skyBOT
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Let me check the knowledge base for you. One moment! :books:

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Based on the information provided in the extracts, it seems that streaming is not currently available for the Assistant API. The Assistant API is used in a flow where you create a thread, append a user message to the thread, create a run (passing the assistant_id you just created), then wait for the run to complete, and get the AI response from the thread's message list (source (https://community.openai.com/t/567107)).

However, it's mentioned in the OpenAI Cookbook (https://cookbook.openai.com/examples/assistants_api_overview_python#conclusion) that streaming is "coming soon". So, it might be a feature that OpenAI is planning to add in the future.

For now, you might need to use the existing flow of the Assistant API and handle any potential delays in the user interface of your application.

Note: you can ask me a follow up question by @ mentioning me again :speech_balloon:

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@woeful elm kapa.ai is still learning and improving, please let us know how it did by reacting below

woeful elm
#

@strange sky is there a way to reference a past chat from a customGPT to a new gpt when the chat gets too long and stops loading

strange skyBOT
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Let me check the knowledge base for you. One moment! :books:

#

Based on the information provided in the extracts, there doesn't seem to be a direct way to reference a past chat from a custom GPT to a new GPT when the chat gets too long and stops loading.

However, you might be able to manually save the conversation history and then load it into the new GPT. This would involve saving the messages from the old chat and then using them as input when starting a new chat with the new GPT.

Please note that this is a workaround and might not work in all cases. It's also important to be aware of any limitations on the number of tokens or messages that can be used in a single chat, as this could affect the ability to load a long conversation history.

For more detailed information or assistance, you might want to check the OpenAI documentation (https://platform.openai.com/docs) or ask a question on the OpenAI community forum (https://community.openai.com).

Note: you can ask me a follow up question by @ mentioning me again :speech_balloon: