Describe Image with astica.ai API on New Events (Instant) from Twilio SendGrid API

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New Events (Instant) from the Twilio SendGrid API

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Describe Image with the astica.ai API

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Getting Started#

This integration creates a workflow with a Twilio SendGrid trigger and astica.ai action. When you configure and deploy the workflow, it will run on Pipedream's servers 24x7 for free.

Select this integration
Configure the New Events (Instant) trigger
1. Connect your Twilio SendGrid account
2. Select one or more Event Types
Configure the Describe Image action
1. Connect your astica.ai account
2. Configure Image
3. Optional- Configure Describe
4. Optional- Configure GPT
5. Optional- Configure GPT Detailed
6. Optional- Configure Faces
7. Optional- Configure Moderate
8. Optional- Configure Tags
9. Optional- Configure Brands
10. Optional- Configure Celebrities
11. Optional- Configure Landmarks
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 Events (Instant) on Twilio SendGrid

Description:Emit new event when any of the specified SendGrid events is received

Version:0.0.5

Key:sendgrid-events

View on GitHub

Twilio SendGrid Overview#

The Twilio SendGrid API opens up a world of possibilities for email automation, enabling you to send emails efficiently and track their performance. With this API, you can programmatically create and send personalized email campaigns, manage contacts, and parse inbound emails for data extraction. When you harness the power of Pipedream, you can connect SendGrid to hundreds of other apps to automate workflows, such as triggering email notifications based on specific actions, syncing email stats with your analytics, or handling incoming emails to create tasks or tickets.

Trigger Code#

import common from "../common/http-based.mjs";
import deliveryEventTypes from "./delivery-event-types.mjs";
import engagementEventTypes from "./engagement-event-types.mjs";

export default {
  ...common,
  key: "sendgrid-events",
  name: "New Events (Instant)",
  description: "Emit new event when any of the specified SendGrid events is received",
  version: "0.0.5",
  type: "source",
  dedupe: "unique",
  props: {
    ...common.props,
    eventTypes: {
      type: "string[]",
      label: "Event Types",
      description: "The type of events to listen to",
      options(context) {
        const { page } = context;
        if (page !== 0) {
          return {
            options: [],
          };
        }

        const options = [
          ...deliveryEventTypes,
          ...engagementEventTypes,
        ];
        return {
          options,
        };
      },
    },
  },
  methods: {
    ...common.methods,
    baseWebhookSettings() {
      // The list of events that a webhook can listen to. This method returns an
      // exhaustive list of all such flags disabled, and each event source can
      // then override the flags that are relevant to the event they handle.
      //
      // See the docs for more information:
      // https://sendgrid.com/docs/api-reference/
      const eventTypesData = [
        ...deliveryEventTypes,
        ...engagementEventTypes,
      ];
      return eventTypesData.reduce((accum, eventTypeData) => ({
        ...accum,
        [eventTypeData.value]: false,
      }), {});
    },
    webhookEventFlags() {
      return this.eventTypes.reduce((accum, eventType) => ({
        ...accum,
        [eventType]: true,
      }), {});
    },
    generateMeta(data) {
      const {
        event: eventType,
        sg_event_id: id,
        timestamp: ts,
      } = data;
      const summary = `New event: ${eventType}`;
      return {
        id,
        summary,
        ts,
      };
    },
  },
};

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
N/A	`db`	`$.service.db`	This component uses `$.service.db` to maintain state between executions.
Twilio SendGrid	`sendgrid`	`app`	This component uses the Twilio SendGrid 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.
Event Types	`eventTypes`	`string[]`	Select a value from the drop down menu.

Trigger Authentication#

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

About Twilio SendGrid#

Send marketing and transactional email through the Twilio SendGrid platform with the Email API, proprietary mail transfer agent, and infrastructure for scalable delivery.

Action#

Describe Image on astica.ai

Description:Analyze an image with Astica AI [See the documentation](https://astica.ai/vision/documentation/)

Version:0.0.1

Key:astica_ai-describe-image

View on GitHub

astica.ai Overview#

The Astica.ai API affords developers the ability to tap into advanced natural language processing (NLP) capabilities. By integrating this API into Pipedream workflows, you can automate text analysis, summarization, sentiment analysis, and more, leveraging the AI-powered insights to enrich applications or streamline processes. Pipedream’s serverless platform makes it painless to set up event-driven workflows that respond to various triggers and manipulate or move data between apps with no need for infrastructure management.

Action Code#

import asticaAi from "../../astica_ai.app.mjs";

export default {
  name: "Describe Image",
  description: "Analyze an image with Astica AI [See the documentation](https://astica.ai/vision/documentation/)",
  key: "astica_ai-describe-image",
  version: "0.0.1",
  type: "action",
  props: {
    asticaAi,
    image: {
      type: "string",
      label: "Image",
      description: "The URL of the image to analyze",
    },
    describe: {
      type: "boolean",
      label: "Describe",
      description: "Returns a caption which describes the image.",
      optional: true,
      default: false,
    },
    gpt: {
      type: "boolean",
      label: "GPT",
      description: "Uses the result of asticaVision to create a GPT description. Using this parameter increases the processing time of your API request. Be Patient.",
      optional: true,
      default: false,
    },
    gpt_detailed: {
      type: "boolean",
      label: "GPT Detailed",
      description: "Uses the result of asticaVision to create a GPT-4 description. Using this parameter greatly increases the processing time of your API request. Please be patient.",
      optional: true,
      default: false,
    },
    faces: {
      type: "boolean",
      label: "Faces",
      description: "Returns the age and gender of all faces detected in the image.",
      optional: true,
      default: false,
    },
    moderate: {
      type: "boolean",
      label: "Moderate",
      description: "Returns a calculated value for different types of sensitive materials found in the image.",
      optional: true,
      default: false,
    },
    tags: {
      type: "boolean",
      label: "Tags",
      description: "Returns a list of descriptive terms which describe the image.",
      optional: true,
      default: false,
    },
    brands: {
      type: "boolean",
      label: "Brands",
      description: "Returns a list of brands that have been identified. For example, a logo on a cup, or a t-shirt.",
      optional: true,
      default: false,
    },
    celebrities: {
      type: "boolean",
      label: "Celebrities",
      description: "Returns a list of celebrities and other known persons that have been detected in the photo.",
      optional: true,
      default: false,
    },
    landmarks: {
      type: "boolean",
      label: "Landmarks",
      description: "Returns a list of known locations and landmarks found in the photo. For example, the Eiffel Tower.",
      optional: true,
      default: false,
    },
  },
  async run({ $ }) {
    const {
      asticaAi,
      image,
      ...otherProps
    } = this;

    const visionParams = [];
    for (const [
      key,
      value,
    ] of Object.entries(otherProps)) {
      if (value) {
        visionParams.push(key);
      }
    }

    const response = await asticaAi.describeImage({
      data: {
        input: image,
        visionParams: visionParams.join(","),
        modelVersion: "2.1_full",
        gpt_prompt: "",
        gpt_length: "90",
      },
      $,
    });

    if (response?.status === "success") {
      $.export("$summary", "Successfully analyzed 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.

Label	Prop	Type	Description
astica.ai	`asticaAi`	`app`	This component uses the astica.ai app.
Image	`image`	`string`	The URL of the image to analyze
Describe	`describe`	`boolean`	Returns a caption which describes the image.
GPT	`gpt`	`boolean`	Uses the result of asticaVision to create a GPT description. Using this parameter increases the processing time of your API request. Be Patient.
GPT Detailed	`gpt_detailed`	`boolean`	Uses the result of asticaVision to create a GPT-4 description. Using this parameter greatly increases the processing time of your API request. Please be patient.
Faces	`faces`	`boolean`	Returns the age and gender of all faces detected in the image.
Moderate	`moderate`	`boolean`	Returns a calculated value for different types of sensitive materials found in the image.
Tags	`tags`	`boolean`	Returns a list of descriptive terms which describe the image.
Brands	`brands`	`boolean`	Returns a list of brands that have been identified. For example, a logo on a cup, or a t-shirt.
Celebrities	`celebrities`	`boolean`	Returns a list of celebrities and other known persons that have been detected in the photo.
Landmarks	`landmarks`	`boolean`	Returns a list of known locations and landmarks found in the photo. For example, the Eiffel Tower.