Integrate the AWS API with the gpt-trainer API

Setup the AWS API trigger to run a workflow which integrates with the gpt-trainer API. Pipedream's integration platform allows you to integrate AWS and gpt-trainer remarkably fast. Free for developers.

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Popular Ways to Connect AWS with gpt-trainer#

Create Chat Session with gpt-trainer API on New Scheduled Tasks from AWS API

AWS + gpt-trainer

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Create Chat Session with gpt-trainer API on New SNS Messages from AWS API

AWS + gpt-trainer

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Create Chatbot with gpt-trainer API on New Scheduled Tasks from AWS API

AWS + gpt-trainer

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Create Chatbot with gpt-trainer API on New SNS Messages from AWS API

AWS + gpt-trainer

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Create Message with gpt-trainer API on New Scheduled Tasks from AWS API

AWS + gpt-trainer

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Popular AWS and gpt-trainer Triggers#

New Scheduled Tasks from the AWS API

Creates a Step Function State Machine to publish a message to an SNS topic at a specific timestamp. The SNS topic delivers the message to this Pipedream source, and the source emits it as a new event.

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New SNS Messages from the AWS API

Creates an SNS topic in your AWS account. Messages published to this topic are emitted from the Pipedream source.

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New Inbound SES Emails from the AWS API

The source subscribes to all emails delivered to a specific domain configured in AWS SES. When an email is sent to any address at the domain, this event source emits that email as a formatted event. These events can trigger a Pipedream workflow and can be consumed via SSE or REST API.

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New Deleted S3 File from the AWS API

Emit new event when a file is deleted from a S3 bucket

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New DynamoDB Stream Event from the AWS API

Emit new event when a DynamoDB stream receives new events. See the docs here

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Popular AWS and gpt-trainer Actions#

Create Chat Session with the gpt-trainer API

Create a chat session for a chatbot specified by chatbot UUID. See the documentation

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Create Chatbot with the gpt-trainer API

Creates a new chatbot that belongs to the authenticated user. See the documentation

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Create Message with the gpt-trainer API

Create a session message for a chatbot session specified by session UUID. See the documentation

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CloudWatch Logs - Put Log Event with the AWS API

Uploads a log event to the specified log stream. See docs

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DynamoDB - Create Table with the AWS API

Creates a new table to your account. See docs

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Overview of AWS#

The AWS API unlocks endless possibilities for automation with Pipedream. With this powerful combo, you can manage your AWS services and resources, automate deployment workflows, process data, and react to events across your AWS infrastructure. Pipedream offers a serverless platform for creating workflows triggered by various events that can execute AWS SDK functions, making it an efficient tool to integrate, automate, and orchestrate tasks across AWS services and other apps.

Connect AWS#

import AWS from 'aws-sdk'

export default defineComponent({
  props: {
    aws: {
      type: "app",
      app: "aws",
    }
  },
  async run({steps, $}) {
    const { accessKeyId, secretAccessKey } = this.aws.$auth
    
    /* Now, pass the accessKeyId and secretAccessKey to the constructor for your desired service. For example:
    
    const dynamodb = new AWS.DynamoDB({
      accessKeyId, 
      secretAccessKey,
      region: 'us-east-1',
    })
    
    */
  },
})

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}`,
      },
    })
  },
})

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