Analyze Image/Video with Google Vertex AI API on Random item from multiple RSS feeds from RSS API

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Random item from multiple RSS feeds from the RSS API

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Analyze Image/Video with the Google Vertex AI API

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Getting Started#

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

Select this integration
Configure the Random item from multiple RSS feeds trigger
1. Connect your RSS account
2. Configure timer
3. Configure Feed URLs
Configure the Analyze Image/Video action
1. Connect your Google Vertex AI account
2. Select a Project ID
3. Configure Instructions
4. Configure URL
5. Optional- Configure Mime Type
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#

Random item from multiple RSS feeds on RSS

Description:Emit a random item from multiple RSS feeds

Version:0.2.7

Key:rss-random-item-in-multiple-feeds

View on GitHub

RSS Overview#

The RSS app allows users to automatically fetch and parse updates from web feeds. This functionality is pivotal for staying abreast of content changes or updates from websites, blogs, and news outlets that offer RSS feeds. With Pipedream, you can harness the RSS API to trigger workflows that enable a broad range of automations, like content aggregation, monitoring for specific keywords, notifications, and data synchronization across platforms.

Trigger Code#

import rss from "../../app/rss.app.mjs";
import { defineSource } from "@pipedream/types";
import rssCommon from "../common/common.mjs";
export default defineSource({
    ...rssCommon,
    key: "rss-random-item-in-multiple-feeds",
    name: "Random item from multiple RSS feeds",
    type: "source",
    description: "Emit a random item from multiple RSS feeds",
    version: "0.2.7",
    props: {
        ...rssCommon.props,
        urls: {
            propDefinition: [
                rss,
                "urls",
            ],
        },
    },
    dedupe: "unique",
    hooks: {
        async activate() {
            // Try to parse the feed one time to confirm we can fetch and parse.
            // The code will throw any errors to the user.
            for (const url of this.urls) {
                await this.rss.fetchAndParseFeed(url);
            }
        },
    },
    async run() {
        const items = [];
        for (const url of this.urls) {
            const feedItems = await this.rss.fetchAndParseFeed(url);
            items.push(...feedItems);
        }
        const item = items[Math.floor(Math.random() * items.length)];
        const meta = this.generateMeta(item);
        this.$emit(item, meta);
    },
});

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
RSS	`rss`	`app`	This component uses the RSS app.
	`timer`	`$.interface.timer`	How often you want to poll the feed for new items
Feed URLs	`urls`	`string[]`	Enter either one or multiple URLs from any public RSS feed

Trigger Authentication#

The RSS API does not require authentication.

About RSS#

Real Simple Syndication

Action#

Analyze Image/Video on Google Vertex AI

Description:Examines an image or video following given instructions. Results will contain the analysis findings. [See the documentation](https://cloud.google.com/vertex-ai/docs/reference/rest/v1/projects.locations.publishers.models/generateContent)

Version:0.0.1

Key:google_vertex_ai-analyze-image-video

View on GitHub

Google Vertex AI Overview#

With the Google Vertex AI API, you can tap into a robust suite of AI tools offered by Google Cloud to build, deploy, and scale machine learning models. Whether you're processing data, training custom models, or using pre-trained ones, Vertex AI provides a unified platform for AI development. In Pipedream, you can create serverless workflows that interact with Vertex AI, allowing you to automate tasks like model training, prediction, and resource management without provisioning your own infrastructure.

Action Code#

import vertexAi from "../../google_vertex_ai.app.mjs";

export default {
  key: "google_vertex_ai-analyze-image-video",
  name: "Analyze Image/Video",
  description: "Examines an image or video following given instructions. Results will contain the analysis findings. [See the documentation](https://cloud.google.com/vertex-ai/docs/reference/rest/v1/projects.locations.publishers.models/generateContent)",
  version: "0.0.1",
  type: "action",
  props: {
    vertexAi,
    projectId: {
      propDefinition: [
        vertexAi,
        "projectId",
      ],
    },
    instructions: {
      type: "string",
      label: "Instructions",
      description: "The rules for analysis of the input image/video",
    },
    url: {
      type: "string",
      label: "URL",
      description: "The URL of the file or video to analyze. Only GCS URIs are supported. Please make sure that the path is a valid GCS path. Example: `gs://cloud-samples-data/generative-ai/image/mount_fuji.jpg`",
    },
    mimeType: {
      type: "string",
      label: "Mime Type",
      description: "The mimeType of the image or video to analyze",
      optional: true,
      default: "image/jpeg",
    },
  },
  async run({ $ }) {
    const response = await this.vertexAi.generateContent({
      $,
      projectId: this.projectId,
      model: "gemini-1.0-pro-vision",
      data: {
        contents: [
          {
            role: "user",
            parts: [
              {
                fileData: {
                  mimeType: this.mimeType,
                  fileUri: this.url,
                },
              },
              {
                text: this.instructions,
              },
            ],
          },
        ],
      },
    });
    $.export("$summary", "Successfully analyzed resource");
    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 Vertex AI	`vertexAi`	`app`	This component uses the Google Vertex AI app.
Project ID	`projectId`	`string`	Select a value from the drop down menu.
Instructions	`instructions`	`string`	The rules for analysis of the input image/video
URL	`url`	`string`	The URL of the file or video to analyze. Only GCS URIs are supported. Please make sure that the path is a valid GCS path. Example: `gs://cloud-samples-data/generative-ai/image/mount_fuji.jpg`
Mime Type	`mimeType`	`string`	The mimeType of the image or video to analyze

Action Authentication#

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

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

emailprofilehttps://www.googleapis.com/auth/cloud-platform

About Google Vertex AI#

Vertex AI offers everything you need to build and use generative AI—from AI solutions, to Search and Conversation, to 130+ foundation models, to a unified AI platform.