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One of my workflows has 18 steps. It runs fine EXCEPT for when it hits Chat GPT. I always get timeout errors.
I think it’s the amount of data that I am feeding into Chat GPT. It’s a paid account.
I have already increased the memory to 1024.
What are your suggestions to get this to run correctly?
It seems like you’re encountering a timeout issue with your workflow. You’ve already increased the memory, which is a good step. Here are a couple of suggestions to address the timeout issue: 1. Check if there’s any delay or issue with the Chat GPT API response. If the API takes longer than expected to respond, it could cause the workflow to timeout. 2. If it’s expected that your workflow takes a longer time to run due to the amount of data being processed, you can increase the execution timeout limit for your workflow. You can change this limit in your workflow’s settings. If you still face issues or need further assistance, please visit https://pipedream.com/support for more support options.
you should decrease your memory – it’s not a memory issue, and you are just using up unnecessary credits on PipeDream. If you run out of memory, you will get an error message saying as much.
The issue is that the default time out settings are way too low on pipedream workflows. Go to your workflow, click the triple dots at the top right, and go to settings. Set your Timeout to 750s.
Basically, the “timeout” limit is not for individual steps, but for your whole workflow. So if it takes longer than X seconds (determined by your timeout settings) for the workflow to run, it will automatically time out.
and @U05N3KNK9UH
I received this error message today:
Message:
You've exceeded the default memory for this workflow. You can raise the memory in your workflow's Settings. See https://pipedream.com/docs/troubleshooting/#out-of-memoryTotal Duration:0 msCompute Time:76,463 msExecution Start:2023-09-07T17:38:06.985ZExecution End:nullSteps Executed:0 / 15Credits:1Version:46 (d_xRslxpKy)
I see that you’ve encountered an “Out of Memory” error in your workflow. This can happen when you load a large file or object into the workflow’s memory, or when you have many steps in your workflow. To resolve this issue, you can increase the memory limit for your workflow in its settings. 1. Go to your workflow in the Pipedream UI. 2. Click on the triple dots at the top right corner and select “Settings”. 3. In the “Memory” section, increase the memory limit as needed. Keep in mind that increasing the memory limit will also increase the number of credits charged per execution. You can find more information on memory limits and credit charges in the Pipedream documentation. If you still face issues or need further assistance, please visit https://pipedream.com/support for more support options.
I believe the problem is how much data I am stuffing into Chat GPT.
What I’m doing now is opening a GOOGLE DOC then taking the content and my Chat GPT instructions and then pushing it into Chat GPT for corrections.
Is there a code that I can run AFTER Chap GPT to determine how big is this data?
Yes, you can add a code step after the Chat GPT step in your workflow to calculate the size of the data returned by Chat GPT. Here’s an example code snippet that you can use: export default defineComponent({ async run({ steps }) { const chatGPTData = steps.chat_gpt_step_name.result; // Replace with your Chat GPT step name const dataSizeInBytes = Buffer.byteLength(JSON.stringify(chatGPTData), 'utf8'); const dataSizeInKilobytes = dataSizeInBytes / 1024; return { dataSizeInBytes, dataSizeInKilobytes, }; }, }); This code calculates the size of the data returned by the Chat GPT step in bytes and kilobytes. Make sure to replace chat_gpt_step_name with the actual name of your Chat GPT step in the workflow.
I have 4.875 for the instructions.
And then a total of 7.7587890625 for the instructions and the response.
It looks like you’re mentioning the data sizes for the instructions and the combined instructions and response from Chat GPT. The instructions size is 4.875 KB, and the total size for both instructions and response is 7.7587890625 KB. If you’re still facing issues with timeouts or memory, consider optimizing the data you’re sending to Chat GPT or breaking it into smaller chunks to process separately.
How do I continue a conversation in Chat GPT?
To continue a conversation in Chat GPT using Pipedream, you can follow these steps: 1. Use the OpenAI Chat action in your workflow. 2. Provide the User Message as your chat input. 3. If you want to give context or instructions to the Chat API, you can provide optional System Instructions. 4. To maintain the context of the conversation, pass the prior message history in the “Prior Message History” property. You can use the original_messages_with_assistant_response from the previous Chat action’s output. Here’s an example of how you can chain Chat actions to continue a conversation: 1. Add the OpenAI Chat action to your workflow. 2. Set the User Message and System Instructions (if needed). 3. Add another OpenAI Chat action to your workflow. 4. Set the User Message for the second Chat action. 5. In the “Prior Message History” property of the second Chat action, use the original_messages_with_assistant_response from the first Chat action’s output. You can continue to chain more Chat actions in the same manner, passing the original_messages_with_assistant_response from the previous Chat action to the next one. For a more detailed example, you can refer to the Pipedream blog post: Integrate ChatGPT with 1,000 other apps
I received the following error:
Configuration error
The following message doesn't have a "role" property:
It seems like you’re encountering a configuration error related to a missing “role” property in a message. This error typically occurs when using the OpenAI Chat API in a Pipedream workflow. To resolve this issue, make sure that each message in the “messages” array has a “role” property, which can be either “system”, “user”, or “assistant”. For example, when using the OpenAI Chat action, your message array should look like this: ```
on [ { “role”: “system”, “content”: “You are a helpful assistant.” }, { “role”: “user”, “content”: “What’s the weather like today?” } ]