Generate Content from Text 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 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.

Select this integration
Configure the New Comment (Instant) trigger
1. Configure alert
2. Connect your Figma account
Configure the Generate Content from Text action
1. Connect your Google Gemini account
2. Select a Model
3. Configure Prompt Text
4. Optional- Configure JSON Output
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 Comment (Instant) on Figma

Description:Emit new event when someone comments on a file

Version:0.0.3

Key:figma-new-comment

View on GitHub

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.

Label	Prop	Type	Description
Figma	`figmaApp`	`app`	This component uses the Figma app.
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.
N/A	`db`	`$.service.db`	This component uses `$.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#

Generate Content from Text on Google Gemini

Description:Generates content from text input using the Google Gemini API. [See the documentation](https://ai.google.dev/tutorials/rest_quickstart#text-only_input)

Version:0.1.1

Key:google_gemini-generate-content-from-text

View on GitHub

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 common from "../common/generate-content.mjs";
import utils from "../../common/utils.mjs";

export default {
  ...common,
  key: "google_gemini-generate-content-from-text",
  name: "Generate Content from Text",
  description: "Generates content from text input using the Google Gemini API. [See the documentation](https://ai.google.dev/tutorials/rest_quickstart#text-only_input)",
  version: "0.1.1",
  type: "action",
  props: {
    ...common.props,
    text: {
      propDefinition: [
        common.props.app,
        "text",
      ],
    },
    responseFormat: {
      propDefinition: [
        common.props.app,
        "responseFormat",
      ],
    },
  },
  async run({ $ }) {
    const {
      app,
      model,
      text,
      responseFormat,
      responseSchema,
      maxOutputTokens,
      temperature,
      topP,
      topK,
      stopSequences,
    } = this;

    const response = await app.generateContent({
      $,
      model,
      data: {
        contents: [
          {
            parts: [
              {
                text,
              },
            ],
          },
        ],
        ...(
          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 input.");

    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
Google Gemini	`app`	`app`	This component uses the Google Gemini app.
Model	`model`	`string`	Select a value from the drop down menu.
Prompt Text	`text`	`string`	The text to use as the prompt for content generation
JSON Output	`responseFormat`	`boolean`	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.