← Figma + Google Gemini integrations

Generate Content from Text and Image with Google Gemini API on New Comment (Instant) from Figma API

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New Comment (Instant) from the Figma API
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Generate Content from Text and Image with the Google Gemini API
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Getting Started

This integration creates a workflow with a Figma trigger and Google Gemini 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 Comment (Instant) trigger
    1. Configure alert
    2. Connect your Figma account
  3. Configure the Generate Content from Text and Image action
    1. Connect your Google Gemini account
    2. Select a Model
    3. Configure Prompt Text
    4. Select a MIME Type
    5. Configure Image File Paths
    6. Optional- Configure JSON Output
  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 event when someone comments on a file
Version:0.0.3
Key:figma-new-comment

Figma Overview

The Figma API unlocks the power to automate and integrate design workflows, enabling both designers and developers to extract assets, update designs, and manage files programmatically. By leveraging the Figma API on Pipedream, you can create automated processes that sync design updates with other tools, notify team members of changes, or feed design information into other parts of your digital ecosystem.

Trigger Code

import { ConfigurationError } from "@pipedream/platform";
import { v4 as uuid } from "uuid";
import common from "../../common/common.mjs";

export default {
  ...common,
  key: "figma-new-comment",
  name: "New Comment (Instant)",
  description: "Emit new event when someone comments on a file",
  version: "0.0.3",
  type: "source",
  dedupe: "unique",
  props: {
    alert: {
      type: "alert",
      alertType: "info",
      content: "A Figma Organization Plan or higher is required to use webhooks. See Figma's [pricing page](https://www.figma.com/pricing) for more details.",
    },
    ...common.props,
    http: "$.interface.http",
    db: "$.service.db",
  },
  hooks: {
    async activate() {
      try {
        const passcode = uuid();
        this.setPasscode(passcode);

        const hookId = await this.figmaApp.createHook(
          "FILE_COMMENT",
          this.getTeamId(),
          this.http.endpoint,
          passcode,
        );

        this.setHookId(hookId);
      } catch (error) {
        if (error.response.status === 400) {
          throw new ConfigurationError("A Figma Organization Plan or higher is required to use webhooks. See Figma's [pricing page](https://www.figma.com/pricing) for more details.");
        }
        throw error;
      }
    },
    async deactivate() {
      await this.figmaApp.deleteHook(this.getHookId());
    },
  },
  methods: {
    ...common.methods,
    getHookId() {
      return this.db.get("hookId");
    },
    setHookId(hookId) {
      this.db.set("hookId", hookId);
    },
    getPasscode() {
      return this.db.get("passcode");
    },
    setPasscode(passcode) {
      this.db.set("passcode", passcode);
    },
  },
  async run(event) {
    this.http.respond({
      status: 200,
    });

    if (event.body.passcode === this.getPasscode()) {
      this.$emit(event.body, {
        summary: `New comment on a file (${event.body.comment_id})`,
        id: event.body.comment_id,
        ts: event.body.timestamp,
      });
    }
  },
};

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
FigmafigmaAppappThis component uses the Figma 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.

Trigger Authentication

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

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

file_read

About Figma

Figma is the leading collaborative design tool for building meaningful products.

Action

Description:Generates content from both text and image input using the Gemini API. [See the documentation](https://ai.google.dev/tutorials/rest_quickstart#text-and-image_input)
Version:0.1.1
Key:google_gemini-generate-content-from-text-and-image

Google Gemini Overview

The Google Gemini API is a cutting-edge tool from Google that enables developers to leverage AI models like Imagen and MusicLM to create and manipulate images and music based on textual descriptions. With Pipedream, you can harness this API to automate workflows that integrate AI-generated content into a variety of applications, from generating visuals for social media posts to composing background music for videos. Pipedream's serverless platform allows you to connect Google Gemini API with other apps to create complex, event-driven workflows without managing infrastructure.

Action Code

import fs from "fs";
import { ConfigurationError } from "@pipedream/platform";
import common from "../common/generate-content.mjs";
import utils from "../../common/utils.mjs";

export default {
  ...common,
  key: "google_gemini-generate-content-from-text-and-image",
  name: "Generate Content from Text and Image",
  description: "Generates content from both text and image input using the Gemini API. [See the documentation](https://ai.google.dev/tutorials/rest_quickstart#text-and-image_input)",
  version: "0.1.1",
  type: "action",
  props: {
    ...common.props,
    text: {
      propDefinition: [
        common.props.app,
        "text",
      ],
    },
    mimeType: {
      propDefinition: [
        common.props.app,
        "mimeType",
      ],
    },
    imagePaths: {
      propDefinition: [
        common.props.app,
        "imagePaths",
      ],
    },
    responseFormat: {
      propDefinition: [
        common.props.app,
        "responseFormat",
      ],
    },
  },
  methods: {
    fileToGenerativePart(path, mimeType) {
      if (!path) {
        return;
      }
      return {
        inline_data: {
          mime_type: mimeType,
          data: Buffer.from(fs.readFileSync(path)).toString("base64"),
        },
      };
    },
  },
  async run({ $ }) {
    const {
      app,
      model,
      text,
      imagePaths,
      mimeType,
      responseFormat,
      responseSchema,
      maxOutputTokens,
      temperature,
      topP,
      topK,
      stopSequences,
    } = this;

    if (!Array.isArray(imagePaths)) {
      throw new ConfigurationError("Image paths must be an array.");
    }

    if (!imagePaths.length) {
      throw new ConfigurationError("At least one image path must be provided.");
    }

    const response = await app.generateContent({
      $,
      model,
      data: {
        contents: [
          {
            parts: [
              {
                text,
              },
              ...imagePaths.map((path) => this.fileToGenerativePart(path, mimeType)),
            ],
          },
        ],
        ...(
          responseFormat || maxOutputTokens || temperature || topP || topK || stopSequences?.length
            ? {
              generationConfig: {
                responseMimeType: "application/json",
                responseSchema: utils.parse(responseSchema),
                maxOutputTokens,
                temperature,
                topP,
                topK,
                stopSequences,
              },
            }
            : {}
        ),
      },
    });

    $.export("$summary", "Successfully generated content from text and 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
Google GeminiappappThis component uses the Google Gemini app.
ModelmodelstringSelect a value from the drop down menu.
Prompt Texttextstring

The text to use as the prompt for content generation

MIME TypemimeTypestringSelect a value from the drop down menu:{ "label": "PNG", "value": "image/png" }{ "label": "JPEG", "value": "image/jpeg" }
Image File PathsimagePathsstring[]

The local file paths of the images to use in the content generation. The path to the image file saved to the /tmp directory (e.g. /tmp/example.pdf). See the documentation.

JSON OutputresponseFormatboolean

Enable to receive responses in structured JSON format instead of plain text. Useful for automated processing, data extraction, or when you need to parse the response programmatically. You can optionally define a specific schema for the response structure.

Action Authentication

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

About Google Gemini

Google Gemini is a multimodal AI by DeepMind that processes text, audio, images, and more.

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