← Typeform + Hugging Face integrations

Image Classification with Hugging Face API on New Submission from Typeform API

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New Submission from the Typeform API
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Image Classification with the Hugging Face API
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Getting Started

This integration creates a workflow with a Typeform trigger and Hugging Face 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 New Submission trigger
    1. Connect your Typeform account
    2. Select a Form
  3. Configure the Image Classification action
    1. Connect your Hugging Face account
    2. Select a Model ID
    3. Configure Image URL
  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:Emit new submission
Version:0.0.8
Key:typeform-new-submission

Typeform Overview

The Typeform API furnishes you with the means to create dynamic forms and collect user responses in real-time. By leveraging this API within Pipedream's serverless platform, you can automate workflows to process this data, integrate seamlessly with other services, and react to form submissions instantaneously. This empowers you to craft tailored responses, synchronize with databases, trigger email campaigns, or even manage event registrations without manual intervention.

Trigger Code

import { createHmac } from "crypto";
import sampleEmit from "./test-event.mjs";
import { uuid } from "uuidv4";
import common from "../common/common.mjs";
import constants from "../../constants.mjs";
import utils from "../common/utils.mjs";

const { typeform } = common.props;
const { parseIsoDate } = utils;

export default {
  ...common,
  key: "typeform-new-submission",
  name: "New Submission",
  version: "0.0.8",
  type: "source",
  description: "Emit new submission",
  props: {
    ...common.props,
    http: {
      type: "$.interface.http",
      customResponse: true,
    },
    db: "$.service.db",
    formId: {
      propDefinition: [
        typeform,
        "formId",
      ],
    },
  },
  methods: {
    ...common.methods,
    generateSecret() {
      return "" + Math.random();
    },
  },
  hooks: {
    ...common.hooks,
    async activate() {
      const secret = this.generateSecret();
      this._setSecret(secret);

      let tag = this._getTag();
      if (!tag) {
        tag = uuid();
        this._setTag(tag);
      }

      return await this.typeform.createHook({
        endpoint: this.http.endpoint,
        formId: this.formId,
        tag,
        secret,
      });
    },
    async deactivate() {
      const tag = this._getTag();

      return await this.typeform.deleteHook({
        formId: this.formId,
        tag,
      });
    },
  },
  async run(event) {
    const {
      body,
      headers,
    } = event;

    const { [constants.TYPEFORM_SIGNATURE]: typeformSignature } = headers;

    if (typeformSignature) {
      const secret = this._getSecret();

      const hmac =
        createHmac(constants.ALGORITHM, secret)
          .update(body)
          .digest(constants.ENCODING);

      const signature = `${constants.ALGORITHM}=${hmac}`;

      if (typeformSignature !== signature) {
        throw new Error("signature mismatch");
      }
    }

    let formResponseString = "";
    const data = Object.assign({}, body.form_response);
    data.form_response_parsed = {};

    for (let i = 0; i < body.form_response.answers.length; i++) {
      const field = body.form_response.definition.fields[i];
      const answer = body.form_response.answers[i];

      let parsedAnswer;
      let value = answer[answer.type];

      if (value.label) {
        parsedAnswer = value.label;

      } else if (value.labels) {
        parsedAnswer = value.labels.join();

      } else if (value.choice) {
        parsedAnswer = value.choice;

      } else if (value.choices) {
        parsedAnswer = value.choices.join();

      } else {
        parsedAnswer = value;
      }

      data.form_response_parsed[field.title] = parsedAnswer;
      formResponseString += `### ${field.title}\n${parsedAnswer}\n`;
    }

    data.form_response_string = formResponseString;
    data.raw_webhook_event = body;

    if (data.landed_at) {
      data.landed_at = parseIsoDate(data.landed_at);
    }

    if (data.submitted_at) {
      data.submitted_at = parseIsoDate(data.submitted_at);
    }

    data.form_title = body.form_response.definition.title;
    delete data.answers;
    delete data.definition;

    this.$emit(data, {
      summary: JSON.stringify(data),
      id: data.token,
    });

    this.http.respond({
      status: 200,
    });
  },
  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.
LabelPropTypeDescription
TypeformtypeformappThis component uses the Typeform app.
N/Ahttp$.interface.httpThis component uses $.interface.http to generate a unique URL when the component is first instantiated. Each request to the URL will trigger the run() method of the component.
N/Adb$.service.dbThis component uses $.service.db to maintain state between executions.
FormformIdstringSelect a value from the drop down menu.

Trigger Authentication

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

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

offlineaccounts:readforms:writeforms:readimages:writeimages:readthemes:writethemes:readresponses:readresponses:writewebhooks:readwebhooks:writeworkspaces:readworkspaces:write

About Typeform

Typeform lets you build no-code forms, quizzes, and surveys - and get more responses.

Action

Description:This task reads some image input and outputs the likelihood of classes. This action allows you to classify images into categories. [See the docs](https://huggingface.co/docs/huggingface.js/inference/classes/HfInference#imageclassification).
Version:0.0.1
Key:hugging_face-image-classification

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-image-classification",
  name: "Image Classification",
  description: "This task reads some image input and outputs the likelihood of classes. This action allows you to classify images into categories. [See the docs](https://huggingface.co/docs/huggingface.js/inference/classes/HfInference#imageclassification).",
  type: "action",
  version: "0.0.1",
  props: {
    app,
    modelId: {
      propDefinition: [
        app,
        "modelId",
        () => ({
          tagFilter: tag.IMAGE_CLASSIFICATION,
        }),
      ],
    },
    imageUrl: {
      description: "The image url to use for classification.",
      propDefinition: [
        app,
        "imageUrl",
      ],
    },
  },
  async run({ $: step }) {
    const {
      modelId,
      imageUrl,
    } = this;

    const image = await this.app.getBinaryFromUrl(imageUrl);

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

    step.export("$summary", "Successfully classified image");

    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
Hugging FaceappappThis component uses the Hugging Face app.
Model IDmodelIdstringSelect a value from the drop down menu.
Image URLimageUrlstring

The image url to use for classification.

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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