Language Translation with Hugging Face API on New Task Completed from InfluxDB Cloud API

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Trigger workflow on

New Task Completed from the InfluxDB Cloud API

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Language Translation with the Hugging Face API

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Getting Started#

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

Select this integration
Configure the New Task Completed trigger
1. Connect your InfluxDB Cloud account
2. Configure timer
Configure the Language Translation action
1. Connect your Hugging Face account
2. Select a Model ID
3. Configure Text
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 Task Completed on InfluxDB Cloud

Description:Emit new event when a new task is completed. [See the documentation](https://docs.influxdata.com/influxdb3/cloud-serverless/api/v2/#operation/GetTasks)

Version:0.0.1

Key:influxdb_cloud-new-task-completed

View on GitHub

InfluxDB Cloud Overview#

Harness the power of InfluxDB Cloud API on Pipedream to build robust data workflows. InfluxDB Cloud, a time-series database, is ideal for managing high-velocity data and extracting insights in real-time. On Pipedream, you can easily trigger workflows based on InfluxDB data, automate data ingestion, and connect with countless other services to analyze, visualize, and act upon your data.

Trigger Code#

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

export default {
  ...common,
  key: "influxdb_cloud-new-task-completed",
  name: "New Task Completed",
  description: "Emit new event when a new task is completed. [See the documentation](https://docs.influxdata.com/influxdb3/cloud-serverless/api/v2/#operation/GetTasks)",
  version: "0.0.1",
  type: "source",
  dedupe: "unique",
  methods: {
    ...common.methods,
    getResourceFn() {
      return this.influxDbCloud.listTasks;
    },
    getResourceKey() {
      return "tasks";
    },
    getTsField() {
      return "latestCompleted";
    },
    getSummary(item) {
      return `Task ${item.name} Completed`;
    },
  },
};

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
InfluxDB Cloud	`influxDbCloud`	`app`	This component uses the InfluxDB Cloud app.
N/A	`db`	`$.service.db`	This component uses `$.service.db` to maintain state between executions.
	`timer`	`$.interface.timer`

Trigger Authentication#

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

About InfluxDB Cloud#

Focus on building software with an easy-to-use, scalable, serverless time series platform available on AWS, Azure, and Google Cloud.

Action#

Language Translation on Hugging Face

Description:This task is well known to translate text from one language to another. [See the docs](https://huggingface.co/docs/huggingface.js/inference/classes/HfInference#translation).

Version:0.0.1

Key:hugging_face-language-translation

View on GitHub

Hugging Face Overview#

The Hugging Face API provides access to a vast range of machine learning models, primarily for natural language processing (NLP) tasks like text classification, translation, summarization, and question answering. It lets you leverage pre-trained models and fine-tune them on your data. Using the API within Pipedream, you can automate workflows that involve language processing, integrate AI insights into your apps, or respond to events with AI-generated content.

Action Code#

import app from "../../hugging_face.app.mjs";
import tag from "../common/tag.mjs";

export default {
  key: "hugging_face-language-translation",
  name: "Language Translation",
  description: "This task is well known to translate text from one language to another. [See the docs](https://huggingface.co/docs/huggingface.js/inference/classes/HfInference#translation).",
  type: "action",
  version: "0.0.1",
  props: {
    app,
    modelId: {
      propDefinition: [
        app,
        "modelId",
        () => ({
          tagFilter: tag.TRANSLATION,
        }),
      ],
    },
    text: {
      type: "string",
      label: "Text",
      description: "The text to use for translation.",
    },
  },
  async run({ $: step }) {
    const {
      modelId,
      text,
    } = this;

    const response = await this.app.inference({
      step,
      modelId,
      data: {
        inputs: text,
      },
    });

    step.export("$summary", "Successfully translated text");

    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
Hugging Face	`app`	`app`	This component uses the Hugging Face app.
Model ID	`modelId`	`string`	Select a value from the drop down menu.
Text	`text`	`string`	The text to use for translation.

Action Authentication#

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

To retrieve your Access Tokens,

Navigate to your Hugging Face account and sign in
Go to “Settings” > “Access Tokens”

About Hugging Face#

Build, train and deploy state of the art models powered by the reference open source in machine learning.

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