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with gpt-trainer and Zip Archive API?
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Popular gpt-trainer and Zip Archive API Actions#
Create a chat session for a chatbot specified by chatbot UUID. See the documentation
Compress files provided through URLs into a zip folder. See the documentation
Creates a new chatbot that belongs to the authenticated user. See the documentation
Create a session message for a chatbot session specified by session UUID. See the documentation
Overview of gpt-trainer#
The gpt-trainer API is a tool designed to train, run, and manage custom GPT-2 and GPT-3 models. It provides endpoints for submitting training data, starting the training process, and generating text from the trained model. With Pipedream's serverless integration platform, you can automate workflows that interact with the gpt-trainer API. You can trigger workflows using webhooks, schedule them, or even run them in response to events from other apps. Integrate the gpt-trainer API with other services on Pipedream to create powerful applications such as automated content creation, personalized messaging, or AI-driven data analysis.
Connect gpt-trainer#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
gpt_trainer: {
type: "app",
app: "gpt_trainer",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://app.gpt-trainer.com/api/v1/chatbots`,
headers: {
Authorization: `Bearer ${this.gpt_trainer.$auth.api_key}`,
},
})
},
})
Overview of Zip Archive API#
The Zip Archive API allows you to manage zip archives programmatically. You can create, extract, and modify zip files, making it ideal for automating routine file management tasks. Integrating this API with Pipedream enables you to automate workflows that involve file compression or decompression, combine it with triggers from other apps, and process large batches of files efficiently, saving time and reducing manual effort.
Connect Zip Archive API#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
zip_archive_api: {
type: "app",
app: "zip_archive_api",
}
},
async run({steps, $}) {
const data = {
"file": `https://www.learningcontainer.com/wp-content/uploads/2020/05/sample-zip-file.zip`,
}
return await axios($, {
method: "post",
url: `https://api.archiveapi.com/extract`,
headers: {
"Accept": `text/plain`,
},
params: {
secret: `${this.zip_archive_api.$auth.secret}`,
},
data,
})
},
})
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