Create Prediction with Replicate API on New Recording from Screendesk API

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Trigger workflow on

New Recording from the Screendesk API

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Create Prediction with the Replicate API

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Getting Started#

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

Select this integration
Configure the New Recording trigger
1. Connect your Screendesk account
2. Configure Polling interval
Configure the Create Prediction action
1. Connect your Replicate account
2. Select a Collection Id
3. Select a Model Id
4. Select a Model Version
5. Configure Input
6. Optional- Configure Webhook
7. Optional- Select one or more Webhook Events Filter
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#

New Recording on Screendesk

Description:Emit new event when a new recording is created is sent or received.

Version:0.0.1

Key:screendesk-new-recording

View on GitHub

Screendesk Overview#

The Screendesk API lets you automate customer support tasks directly within your apps or websites. Imagine streamlining interactions like ticket creation, response tracking, and support analytics. With Pipedream, you can easily craft workflows that interact with the Screendesk API to enhance customer support efficiency, trigger actions based on ticket status, or synchronize support data with other tools.

Trigger Code#

import { DEFAULT_POLLING_SOURCE_TIMER_INTERVAL } from "@pipedream/platform";
import screendesk from "../../screendesk.app.mjs";
import sampleEmit from "./test-event.mjs";

export default {
  key: "screendesk-new-recording",
  name: "New Recording",
  version: "0.0.1",
  description: "Emit new event when a new recording is created is sent or received.",
  type: "source",
  dedupe: "unique",
  props: {
    screendesk,
    db: "$.service.db",
    timer: {
      label: "Polling interval",
      description: "Pipedream will poll the Screendesk on this schedule",
      type: "$.interface.timer",
      default: {
        intervalSeconds: DEFAULT_POLLING_SOURCE_TIMER_INTERVAL,
      },
    },
  },
  methods: {
    _getLastId() {
      return this.db.get("lastId") || 0;
    },
    _setLastId(lastId) {
      this.db.set("lastId", lastId);
    },
    async startEvent(maxResults = 0) {
      const { screendesk } = this;

      const lastId = this._getLastId();
      const items = screendesk.paginate({
        fn: screendesk.listRecordings,
        maxResults,
      });

      let responseArray = [];

      for await (const item of items) {
        if (item.id <= lastId) break;
        responseArray.push(item);
      }
      if (responseArray.length) this._setLastId(responseArray[0].id);

      for (const item of responseArray.reverse()) {
        this.$emit(
          item,
          {
            id: item.id,
            summary: `A new recording with id: "${item.id}" was ${item.recording_type.toLowerCase()}!`,
            ts: new Date(),
          },
        );
      }
    },
  },
  hooks: {
    async deploy() {
      await this.startEvent(25);
    },
  },
  async run() {
    await this.startEvent();
  },
  sampleEmit,
};

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
Screendesk	`screendesk`	`app`	This component uses the Screendesk app.
N/A	`db`	`$.service.db`	This component uses `$.service.db` to maintain state between executions.
Polling interval	`timer`	`$.interface.timer`	Pipedream will poll the Screendesk on this schedule

Trigger Authentication#

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

About Screendesk#

Making customer support teams more productive.

Action#

Create Prediction on Replicate

Description:Create a new prediction [See the documentation](https://replicate.com/docs/reference/http#predictions.create)

Version:0.0.1

Key:replicate-create-prediction

View on GitHub

Replicate Overview#

The Replicate API allows you to access a wide array of machine learning models for tasks such as image generation, text-to-image, and more. Using Pipedream, you can orchestrate these models to automate content creation, analyze media, or enhance data with AI-generated insights. Pipedream's serverless platform empowers you to create workflows that react to events, schedule tasks, and integrate with numerous other services, all harnessing the power of Replicate's AI models.

Action Code#

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

export default {
  key: "replicate-create-prediction",
  name: "Create Prediction",
  version: "0.0.1",
  description: "Create a new prediction [See the documentation](https://replicate.com/docs/reference/http#predictions.create)",
  type: "action",
  props: {
    replicate,
    collectionSlug: {
      propDefinition: [
        replicate,
        "collectionSlug",
      ],
    },
    modelId: {
      propDefinition: [
        replicate,
        "modelId",
        ({ collectionSlug }) => ({
          collectionSlug,
        }),
      ],
    },
    version: {
      propDefinition: [
        replicate,
        "modelVersion",
        ({ modelId }) => ({
          modelId,
        }),
      ],
    },
    input: {
      type: "string",
      label: "Input",
      description: "The model's input as a JSON object. The input depends on what model you are running. To see the available inputs, click the \"Run with API\" tab on the model you are running. For example, stability-ai/stable-diffusion takes prompt as an input.",
    },
    webhook: {
      type: "string",
      label: "Webhook",
      description: "An HTTPS URL for receiving a webhook when the prediction has new output.",
      optional: true,
    },
    webhookEventsFilter: {
      type: "string[]",
      label: "Webhook Events Filter",
      description: "By default, we will send requests to your webhook URL whenever there are new logs, new outputs, or the prediction has finished. [See de documentartion here](https://replicate.com/docs/reference/http#predictions.create--webhook_events_filter) for more details.",
      options: [
        "start",
        "output",
        "logs",
        "completed",
      ],
      optional: true,
    },
  },
  async run({ $ }) {
    const {
      replicate,
      version,
      input,
      webhook,
      webhookEventsFilter,
    } = this;

    const response = await replicate.createPrediction({
      $,
      data: {
        version,
        input: JSON.parse(input),
        webhook,
        webhook_events_filter: webhookEventsFilter,
      },
    });

    $.export("$summary", `A new prediction with Id: ${response.id} was successfully created!`);
    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
Replicate	`replicate`	`app`	This component uses the Replicate app.
Collection Id	`collectionSlug`	`string`	Select a value from the drop down menu.
Model Id	`modelId`	`string`	Select a value from the drop down menu.
Model Version	`version`	`string`	Select a value from the drop down menu.
Input	`input`	`string`	The model's input as a JSON object. The input depends on what model you are running. To see the available inputs, click the "Run with API" tab on the model you are running. For example, stability-ai/stable-diffusion takes prompt as an input.
Webhook	`webhook`	`string`	An HTTPS URL for receiving a webhook when the prediction has new output.
Webhook Events Filter	`webhookEventsFilter`	`string[]`	Select a value from the drop down menu:`startoutputlogscompleted`