← Notion + MonkeyLearn integrations

Extract Text with MonkeyLearn API on New Page in Database from Notion API

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New Page in Database from the Notion API
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Extract Text with the MonkeyLearn API
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Getting Started

This integration creates a workflow with a Notion trigger and MonkeyLearn 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 Page in Database trigger
    1. Connect your Notion account
    2. Configure timer
    3. Select a Database ID
  3. Configure the Extract Text action
    1. Connect your MonkeyLearn account
    2. Select a Extractor Id
    3. Configure Data
    4. Optional- Configure Production Model
  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 a page in a database is created
Version:0.0.10
Key:notion-new-page

Notion Overview

Notion's API allows for the creation, reading, updating, and deleting of pages, databases, and their contents within Notion. Using Pipedream's platform, you can build workflows that connect Notion with various other services to automate tasks such as content management, task tracking, and data synchronization. With Pipedream's serverless execution, you can trigger these workflows on a schedule, or by external events from other services, without managing any infrastructure.

Trigger Code

import notion from "../../notion.app.mjs";
import sampleEmit from "./test-event.mjs";
import base from "../common/base.mjs";
import constants from "../common/constants.mjs";

export default {
  ...base,
  key: "notion-new-page",
  name: "New Page in Database",
  description: "Emit new event when a page in a database is created",
  version: "0.0.10",
  type: "source",
  props: {
    ...base.props,
    databaseId: {
      propDefinition: [
        notion,
        "databaseId",
      ],
    },
  },
  hooks: {
    ...base.hooks,
    async deploy() {
      await this.processEvents(25);
    },
  },
  methods: {
    ...base.methods,
    async processEvents(max) {
      const pages = [];
      const lastCreatedTimestamp = this.getLastCreatedTimestamp();
      const lastCreatedTimestampDate = new Date(lastCreatedTimestamp);
      const lastCreatedTimestampISO = lastCreatedTimestampDate.toISOString();

      // Add a filter so that we only receive pages that have been created since the saved time.
      const params = {
        ...this.lastCreatedSortParam(),
        filter: {
          timestamp: "created_time",
          created_time: {
            after: lastCreatedTimestampISO,
          },
        },
      };

      // Get pages in created order descending until the first page edited after
      // lastCreatedTimestamp, then reverse list of pages and emit
      const pagesStream = this.notion.getPages(this.databaseId, params);

      for await (const page of pagesStream) {
        if (!this.isResultNew(page.created_time, lastCreatedTimestamp)
          || (max && pages.length >= max)) {
          break;
        }
        pages.push(page);
      }

      pages.reverse().forEach((page) => {
        const meta = this.generateMeta(
          page,
          constants.types.PAGE,
          constants.timestamps.CREATED_TIME,
          constants.summaries.PAGE_ADDED,
        );
        this.$emit(page, meta);
      });

      const lastCreatedTime = pages[pages.length - 1]?.created_time;
      if (lastCreatedTime) {
        this.setLastCreatedTimestamp(Date.parse(lastCreatedTime));
      }
    },
  },
  async run() {
    await this.processEvents(100);
  },
  sampleEmit,
};

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
NotionnotionappThis component uses the Notion app.
N/Adb$.service.dbThis component uses $.service.db to maintain state between executions.
timer$.interface.timer
Database IDdatabaseIdstringSelect a value from the drop down menu.

Trigger Authentication

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

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

About Notion

Notion is a new tool that blends your everyday work apps into one. It's the all-in-one workspace for you and your team.

Action

Description:Extracts information from texts with a given extractor. [See the docs here](https://monkeylearn.com/api/v3/#extract)
Version:0.0.1
Key:monkeylearn-extract-text

MonkeyLearn Overview

MonkeyLearn is a text analysis platform that employs machine learning to extract and process data from chunks of text. By leveraging the MonkeyLearn API on Pipedream, you can automate the categorization of text, extract specific data, analyze sentiment, and more, all in real-time. This enables the development of powerful custom workflows that can analyze customer feedback, automate email processing, or provide insightful analytics on textual data from various sources.

Action Code

import app from "../../monkeylearn.app.mjs";
import { ConfigurationError } from "@pipedream/platform";

export default {
  key: "monkeylearn-extract-text",
  name: "Extract Text",
  description: "Extracts information from texts with a given extractor. [See the docs here](https://monkeylearn.com/api/v3/#extract)",
  version: "0.0.1",
  type: "action",
  props: {
    app,
    extractorId: {
      propDefinition: [
        app,
        "extractorId",
      ],
    },
    data: {
      propDefinition: [
        app,
        "data",
      ],
    },
    productionModel: {
      propDefinition: [
        app,
        "productionModel",
      ],
    },
  },
  async run({ $ }) {
    const {
      extractorId,
      data,
      productionModel,
    } = this;
    if (!data || !Array.isArray(data) || data.length === 0) {
      throw new ConfigurationError("Data array is required and must have at least one string to be classified.");
    }
    const response = await this.app.extractText($, extractorId, data, productionModel);
    $.export("$summary", "Successfully extracted from all elements");
    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
MonkeyLearnappappThis component uses the MonkeyLearn app.
Extractor IdextractorIdstringSelect a value from the drop down menu.
Datadatastring[]

A list of up to 500 data elements. Each element must be a string with the text.

Production ModelproductionModelboolean

Indicates if the extractions are performed by the production model. Only use this parameter on custom models. Note that you first need to deploy your model to production.

Action Authentication

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

MonkeyLearn requires that you authenticate by sending an API Key with each request to grant you access to the API. See docs.

About MonkeyLearn

Text Analysis

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