with gpt-trainer and Writesonic?
Create a chat session for a chatbot specified by chatbot UUID. 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
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.
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}`,
},
})
},
})
The Writesonic API taps into the prowess of AI to craft compelling written content, from blog posts to marketing copy. By integrating this API with Pipedream, you can automate content creation, enrich your applications with dynamic text, and streamline various writing tasks. It’s perfect for when you need high-quality writing done swiftly and at scale.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
writesonic: {
type: "app",
app: "writesonic",
}
},
async run({steps, $}) {
const data = {
"topic": `{your_topic}`,
}
return await axios($, {
method: "post",
url: `https://api.writesonic.com/v2/business/content/blog-ideas`,
headers: {
"X-API-KEY": `${this.writesonic.$auth.api_key}`,
"Accept": `application/json`,
"Content-Type": `application/json`,
},
params: {
engine: `economy`,
language: `en`,
num_copies: `1`,
},
data,
})
},
})