Create Chatbot with gpt-trainer API

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Create Chatbot with the gpt-trainer API

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Getting Started#

Create a workflow to Create Chatbot with the gpt-trainer API. When you configure and deploy the workflow, it will run on Pipedream's servers 24x7 for free.

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
Select a trigger to run your workflow on HTTP requests, schedules or app events
Deploy the workflow
Send a test event to validate your setup
Turn on the trigger

Integrations#

Create Chatbot with gpt-trainer API on New Requests (Payload Only) from HTTP / Webhook API

HTTP / Webhook + gpt-trainer

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Create Chatbot with gpt-trainer API on New Submission from Typeform API

Typeform + gpt-trainer

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Create Chatbot with gpt-trainer API on New Submission (Instant) from Jotform API

Jotform + gpt-trainer

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

Pipedream + gpt-trainer

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Create Chatbot with gpt-trainer API on npm Download Counts from npm API

npm + gpt-trainer

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Details#

This is a pre-built, source-available component from Pipedream's GitHub repo. The component is 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.

Create Chatbot on gpt-trainer

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

View on GitHub

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;
  },
};

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.

Label	Prop	Type	Description
gpt-trainer	`app`	`app`	This component uses the gpt-trainer app.
Name	`name`	`string`	The name of the chatbot
Prompt	`prompt`	`string`	The prompt for the chatbot
Temperature	`temperature`	`string`	The temperature setting for the chatbot
Model	`model`	`string`	Select a value from the drop down menu:`gpt-3.5-turbogpt-3.5-turbo-16kgpt-4`
Visibility	`visibility`	`string`	Select a value from the drop down menu:`publicprivatehybrid`
Rate Limit Message	`rateLimitMessage`	`string`	The rate limit message for the chatbot. Eg. `Too many messages in a row.`
Show Citations	`showCitations`	`boolean`	Whether the chatbot should show citations