← Schedule + gpt-trainer integrations

Create Chatbot with gpt-trainer API on Weekly schedule from Schedule API

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Trigger workflow on
Weekly schedule from the Schedule API
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Create Chatbot with the gpt-trainer API
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Getting Started

This integration creates a workflow with a Schedule trigger and gpt-trainer action. When you configure and deploy the workflow, it will run on Pipedream's servers 24x7 for free.

  1. Select this integration
  2. Configure the Weekly schedule trigger
    1. Connect your Schedule account
    2. Configure Cron Schedule
  3. Configure the Create Chatbot action
    1. Connect your gpt-trainer account
    2. Configure Name
    3. Optional- Configure Prompt
    4. Optional- Configure Temperature
    5. Optional- Select a Model
    6. Optional- Select a Visibility
    7. Optional- Configure Rate Limit Message
    8. Optional- Configure Show Citations
  4. Deploy the workflow
  5. Send a test event to validate your setup
  6. Turn on the trigger

Details

This integration uses pre-built, source-available components from Pipedream's GitHub repo. These components are developed by Pipedream and the community, and verified and maintained by Pipedream.

To contribute an update to an existing component or create a new component, create a PR on GitHub. If you're new to Pipedream component development, you can start with quickstarts for trigger span and action development, and then review the component API reference.

Trigger

Description:Trigger your workflow on one or more days each week at a specific time (with timezone support).
Version:0.0.1
Key:schedule-weekly

Schedule Overview

The Schedule app in Pipedream is a powerful tool that allows you to trigger workflows at regular intervals, ranging from every minute to once a year. This enables the automation of repetitive tasks and the scheduling of actions to occur without manual intervention. By leveraging this API, you can execute code, run integrations, and process data on a reliable schedule, all within Pipedream's serverless environment.

Trigger Code

import schedule from "../../schedule.app.mjs";

export default {
  name: "Weekly schedule",
  version: "0.0.1",
  key: "schedule-weekly",
  type: "source",
  description: "Trigger your workflow on one or more days each week at a specific time (with timezone support).",
  props: {
    schedule,
    cron: {
      propDefinition: [
        schedule,
        "cron",
      ],
      default: {
        cron: "0 10 * * 1",
      },
    },
  },
};

Trigger Configuration

This component may be configured based on the props defined in the component code. Pipedream automatically prompts for input values in the UI and CLI.
LabelPropTypeDescription
SchedulescheduleappThis component uses the Schedule app.
Cron Schedulecron$.interface.timer

Enter a cron expression

Trigger Authentication

The Schedule API does not require authentication.

About Schedule

Trigger workflows on an interval or cron schedule.

Action

Description:Creates a new chatbot that belongs to the authenticated user. [See the documentation](https://guide.gpt-trainer.com/api-reference/chatbots/create)
Version:0.0.1
Key:gpt_trainer-create-chatbot

gpt-trainer Overview

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.

Action Code

import app from "../../gpt_trainer.app.mjs";

export default {
  key: "gpt_trainer-create-chatbot",
  name: "Create Chatbot",
  description: "Creates a new chatbot that belongs to the authenticated user. [See the documentation](https://guide.gpt-trainer.com/api-reference/chatbots/create)",
  version: "0.0.1",
  type: "action",
  props: {
    app,
    name: {
      type: "string",
      label: "Name",
      description: "The name of the chatbot",
    },
    prompt: {
      type: "string",
      label: "Prompt",
      description: "The prompt for the chatbot",
      optional: true,
    },
    temperature: {
      type: "string",
      label: "Temperature",
      description: "The temperature setting for the chatbot",
      optional: true,
    },
    model: {
      type: "string",
      label: "Model",
      description: "The model of the chatbot",
      optional: true,
      default: "gpt-3.5-turbo",
      options: [
        "gpt-3.5-turbo",
        "gpt-3.5-turbo-16k",
        "gpt-4",
      ],
    },
    visibility: {
      type: "string",
      label: "Visibility",
      description: "The visibility of the chatbot",
      optional: true,
      default: "private",
      options: [
        "public",
        "private",
        "hybrid",
      ],
    },
    rateLimitMessage: {
      type: "string",
      label: "Rate Limit Message",
      description: "The rate limit message for the chatbot. Eg. `Too many messages in a row.`",
      optional: true,
    },
    showCitations: {
      type: "boolean",
      label: "Show Citations",
      description: "Whether the chatbot should show citations",
      optional: true,
    },
  },
  methods: {
    parseFloat(value) {
      const parsed = parseFloat(value);
      return isFinite(parsed)
        ? parsed
        : 0;
    },
    createChatbot(args = {}) {
      return this.app.post({
        path: "/chatbot/create",
        ...args,
      });
    },
  },
  async run({ $ }) {
    const {
      createChatbot,
      parseFloat,
      name,
      prompt,
      temperature,
      model,
      visibility,
      rateLimitMessage,
      showCitations,
    } = this;

    const response = await createChatbot({
      $,
      data: {
        name,
        temperature: parseFloat(temperature),
        prompt,
        model,
        visibility,
        show_citations: showCitations,
        rate_limit_message: rateLimitMessage,
      },
    });

    $.export("$summary", `Successfully created chatbot with UUID \`${response.uuid}\`.`);
    return response;
  },
};

Action Configuration

This component may be configured based on the props defined in the component code. Pipedream automatically prompts for input values in the UI.

LabelPropTypeDescription
gpt-trainerappappThis component uses the gpt-trainer app.
Namenamestring

The name of the chatbot

Promptpromptstring

The prompt for the chatbot

Temperaturetemperaturestring

The temperature setting for the chatbot

ModelmodelstringSelect a value from the drop down menu:gpt-3.5-turbogpt-3.5-turbo-16kgpt-4
VisibilityvisibilitystringSelect a value from the drop down menu:publicprivatehybrid
Rate Limit MessagerateLimitMessagestring

The rate limit message for the chatbot. Eg. Too many messages in a row.

Show CitationsshowCitationsboolean

Whether the chatbot should show citations

Action Authentication

gpt-trainer uses API keys for authentication. When you connect your gpt-trainer account, Pipedream securely stores the keys so you can easily authenticate to gpt-trainer APIs in both code and no-code steps.

About gpt-trainer

Create a personalized AI chatbot using your own data

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