Create Videos with Gan.AI API on New Row Custom Query from PostgreSQL API

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New Row Custom Query from the PostgreSQL API

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Create Videos with the Gan.AI API

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Getting Started#

This integration creates a workflow with a PostgreSQL trigger and Gan.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 Row Custom Query trigger
1. Connect your PostgreSQL account
2. Configure Polling Interval
3. Select a Schema
4. Select a Table
5. Select a Column
6. Configure SQL Query
7. Optional- Configure Values
Configure the Create Videos action
1. Connect your Gan.AI account
2. Select a Project ID
3. Configure Data
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 Row Custom Query on PostgreSQL

Description:Emit new event when new rows are returned from a custom query that you provide. [See the documentation](https://node-postgres.com/features/queries)

Version:2.0.6

Key:postgresql-new-row-custom-query

View on GitHub

PostgreSQL Overview#

On Pipedream, you can leverage the PostgreSQL app to create workflows that automate database operations, synchronize data across platforms, and react to database events in real-time. Think handling new row entries, updating records from webhooks, or even compiling reports on a set schedule. Pipedream's serverless platform provides a powerful way to connect PostgreSQL with a variety of apps, enabling you to create tailored automation that fits your specific needs.

Trigger Code#

import common from "../common.mjs";

export default {
  ...common,
  name: "New Row Custom Query",
  key: "postgresql-new-row-custom-query",
  description: "Emit new event when new rows are returned from a custom query that you provide. [See the documentation](https://node-postgres.com/features/queries)",
  version: "2.0.6",
  type: "source",
  dedupe: "unique",
  props: {
    ...common.props,
    schema: {
      propDefinition: [
        common.props.postgresql,
        "schema",
      ],
    },
    table: {
      propDefinition: [
        common.props.postgresql,
        "table",
        (c) => ({
          schema: c.schema,
        }),
      ],
    },
    column: {
      propDefinition: [
        common.props.postgresql,
        "column",
        (c) => ({
          table: c.table,
          schema: c.schema,
        }),
      ],
    },
    query: {
      propDefinition: [
        common.props.postgresql,
        "query",
      ],
    },
    values: {
      propDefinition: [
        common.props.postgresql,
        "values",
      ],
    },
  },
  methods: {
    ...common.methods,
    generateMeta(row, column) {
      return {
        id: row[column],
        summary: "New Row",
        ts: Date.now(),
      };
    },
  },
  async run() {
    const {
      schema,
      table,
      column,
      query,
      values = [],
    } = this;

    if (!Array.isArray(values)) {
      throw new Error("No valid values provided. The values property must be an array.");
    }

    const numberOfValues = query?.match(/\$/g)?.length || 0;
    if (values.length !== numberOfValues) {
      throw new Error("The number of values provided does not match the number of values in the query.");
    }

    const isColumnUnique = await this.isColumnUnique(schema, table, column);
    if (!isColumnUnique) {
      throw new Error("The column selected contains duplicate values. Column must be unique");
    }

    const rows = await this.postgresql.executeQuery({
      text: query,
      values,
    });
    for (const row of rows) {
      const meta = this.generateMeta(row, column);
      this.$emit(row, 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
PostgreSQL	`postgresql`	`app`	This component uses the PostgreSQL app.
N/A	`db`	`$.service.db`	This component uses `$.service.db` to maintain state between executions.
Polling Interval	`timer`	`$.interface.timer`	Pipedream will poll the API on this schedule
Schema	`schema`	`string`	Select a value from the drop down menu.
Table	`table`	`string`	Select a value from the drop down menu.
Column	`column`	`string`	Select a value from the drop down menu.
SQL Query	`query`	`string`	Your custom SQL Query using `$1`, `$2`... to represent values (eg. `INSERT INTO users(name, email) VALUES($1, $2)`
Values	`values`	`string[]`	List of values represented in your SQL Query above

Trigger Authentication#

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

Before you connect to your PostgreSQL database from Pipedream, please make sure your database is either:

Accessible from the public internet (You may need to add a firewall rule on 0.0.0.0/0 on port 5432), or
Accessible from a static IP that you've configured from a VPC in Pipedream, and enabled the workflow to connect through that VPC

SSL Setup

Configure SSL on your PostgreSQL database by providing the CA (Certificate Authority), and choosing between Full Verification (default), or Skip Verification. Skipping verification is not recommended as this has serious security implications.

About PostgreSQL#

PostgreSQL is a free and open-source relational database management system emphasizing extensibility and SQL compliance.

Action#

Create Videos on Gan.AI

Description:Creates videos in bulk by passing tags and values. Requires a project ID. [See the documentation](https://docs.gan.ai/create-video/create-videos)

Version:0.0.1

Key:gan_ai-create-videos

View on GitHub

Gan.AI Overview#

Gan.AI is a dynamic API that leverages the power of generative adversarial networks (GANs) to create synthetic datasets, simulate user behaviors, and generate realistic images or text. With Gan.AI, developers can enhance their applications by integrating AI-generated content that improves user engagement and simulates various scenarios for testing or training models. Using Pipedream, you can automate workflows involving Gan.AI to process data, trigger AI-based actions, and connect outputs to other apps for extended functionality.

Action Code#

import utils from "../../common/utils.mjs";
import app from "../../gan_ai.app.mjs";

export default {
  key: "gan_ai-create-videos",
  name: "Create Videos",
  description: "Creates videos in bulk by passing tags and values. Requires a project ID. [See the documentation](https://docs.gan.ai/create-video/create-videos)",
  version: "0.0.1",
  type: "action",
  props: {
    app,
    projectId: {
      propDefinition: [
        app,
        "projectId",
      ],
    },
    data: {
      type: "string[]",
      label: "Data",
      description: "The payload is a list of dictionaries, where all the parameters required for video generation have to provide a `unique_id` along with the rest of the values you want to set. Eg. `[{ \"names\": \"Manash\", \"unique_id\": \"abc123\" }, { \"names\": \"Manash2\", \"unique_id\": \"cba321\" } ]`",
    },
  },
  methods: {
    createVideos(args = {}) {
      return this.app.post({
        path: "/create_video/bulk",
        ...args,
      });
    },
  },
  async run({ $ }) {
    const {
      createVideos,
      projectId,
      data,
    } = this;

    const response = await createVideos({
      $,
      params: {
        project_id: projectId,
      },
      data: utils.parseArray(data),
    });

    if (!response.length) {
      $.export("$summary", "No videos were created");
      return response;
    }

    $.export("$summary", `Successfully created \`${response.length}\` video(s)`);
    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
Gan.AI	`app`	`app`	This component uses the Gan.AI app.
Project ID	`projectId`	`string`	Select a value from the drop down menu.
Data	`data`	`string[]`	The payload is a list of dictionaries, where all the parameters required for video generation have to provide a `unique_id` along with the rest of the values you want to set. Eg. `[{ "names": "Manash", "unique_id": "abc123" }, { "names": "Manash2", "unique_id": "cba321" } ]`

Action Authentication#

Gan.AI uses OAuth authentication. When you connect your Gan.AI account, Pipedream will open a popup window where you can sign into Gan.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 Gan.AI API.

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