Create Chatbot with gpt-trainer API on Ticket Updated (Instant) from Zendesk API

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Ticket Updated (Instant) from the Zendesk 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 Zendesk trigger and gpt-trainer action. When you configure and deploy the workflow, it will run on Pipedream's servers 24x7 for free.

Select this integration
Configure the Ticket Updated (Instant) trigger
1. Connect your Zendesk account
2. Optional- Select a Trigger Category ID
3. Optional- Configure Custom Subdomain
4. Optional- Select one or more Fields
5. Optional- Configure JSON Body
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
Deploy the workflow
Send a test event to validate your setup
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#

Ticket Updated (Instant) on Zendesk

Description:Emit new event when a ticket has been updated

Version:0.2.8

Key:zendesk-ticket-updated

View on GitHub

Zendesk Overview#

The Zendesk API enables seamless integration of Zendesk's customer service platform with your existing business processes and third-party applications. By leveraging this API with Pipedream, you can automate ticket tracking, sync customer data, escalate issues, and streamline communication across multiple channels. This can significantly increase efficiency, accelerate response times, and enhance the overall customer experience. Automations can range from simple notifications to complex workflows involving data transformation and multi-step actions across various services.

Trigger Code#

import common from "../common/ticket.mjs";

export default {
  ...common,
  name: "Ticket Updated (Instant)",
  key: "zendesk-ticket-updated",
  type: "source",
  description: "Emit new event when a ticket has been updated",
  version: "0.2.8",
  dedupe: "unique",
  methods: {
    ...common.methods,
    getWebhookName() {
      return "Ticket Updated Webhook";
    },
    getTriggerTitle() {
      return "Ticket Updated Trigger";
    },
    getTriggerConditions() {
      return {
        all: [
          {
            field: "update_type",
            value: "Change",
          },
        ],
      };
    },
  },
};

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.

Label	Prop	Type	Description
Zendesk	`app`	`app`	This component uses the Zendesk app.
N/A	`db`	`$.service.db`	This component uses `$.service.db` to maintain state between executions.
N/A	`http`	`$.interface.http`	This component uses `$.interface.http` to generate a unique URL when the component is first instantiated. Each request to the URL will trigger the `run()` method of the component.
Trigger Category ID	`categoryId`	`string`	Select a value from the drop down menu.
Custom Subdomain	`customSubdomain`	`string`	For Enterprise Zendesk accounts: optionally specify the subdomain to use. This will override the subdomain that was provided when connecting your Zendesk account to Pipedream. For example, if you Zendesk URL is https://examplehelp.zendesk.com, your subdomain is `examplehelp`
Fields	`fields`	`string[]`	Select a value from the drop down menu.
JSON Body	`jsonBody`	`string`	Custom JSON Body of the incoming payload. Setting `jsonBody` will overwrite the `fields` prop

Trigger Authentication#

Zendesk uses OAuth authentication. When you connect your Zendesk account, Pipedream will open a popup window where you can sign into Zendesk and grant Pipedream permission to connect to your account. Pipedream securely stores and automatically refreshes the OAuth tokens so you can easily authenticate any Zendesk API.

Pipedream requests the following authorization scopes when you connect your account:

triggers:writewebhooks:writereadtickets:writetickets:readusers:writeorganizations:readorganizations:write

About Zendesk#

Zendesk is award-winning customer service software trusted by 200K+ customers. Make customers happy via text, mobile, phone, email, live chat, social media.

Action#

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:0.0.2

Key:gpt_trainer-create-chatbot

View on GitHub

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: "0.0.2",
  annotations: {
    destructiveHint: false,
    openWorldHint: true,
    readOnlyHint: false,
  },
  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.

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

Create Chatbot with gpt-trainer API on Ticket Updated (Instant) from Zendesk API

Pipedream makes it easy to connect APIs for gpt-trainer, Zendesk and 2,900+ other apps remarkably fast.

Trusted by 1,000,000+ developers from startups to Fortune 500 companies

Developers ♥ Pipedream

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