Classify Text with MonkeyLearn API on New Run State Changed from OpenAI (ChatGPT) API

Pipedream makes it easy to connect APIs for MonkeyLearn, OpenAI (ChatGPT) and 2,400+ other apps remarkably fast.

Trigger workflow on

New Run State Changed from the OpenAI (ChatGPT) API

Next, do this

Classify Text with the MonkeyLearn API

No credit card required

▶

Watch us build a workflow

8 min

Watch now ➜

Trusted by 1,000,000+ developers from startups to Fortune 500 companies

Developers ♥ Pipedream

Getting Started#

This integration creates a workflow with a OpenAI (ChatGPT) trigger and MonkeyLearn action. When you configure and deploy the workflow, it will run on Pipedream's servers 24x7 for free.

Select this integration
Configure the New Run State Changed trigger
1. Connect your OpenAI (ChatGPT) account
2. Configure timer
3. Configure Thread ID
Configure the Classify Text action
1. Connect your MonkeyLearn account
2. Select a Classifier Id
3. Configure Data
4. Optional- Configure Production Model
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 Run State Changed on OpenAI (ChatGPT)

Description:Emit new event every time a run changes its status. [See the documentation](https://platform.openai.com/docs/api-reference/runs/listRuns)

Version:0.0.6

Key:openai-new-run-state-changed

View on GitHub

OpenAI (ChatGPT) Overview#

OpenAI provides a suite of powerful AI models through its API, enabling developers to integrate advanced natural language processing and generative capabilities into their applications. Here’s an overview of the services offered by OpenAI's API:

Use Python or Node.js code to make fully authenticated API requests with your OpenAI account:

Trigger Code#

import common from "../common/common.mjs";
import sampleEmit from "./test-event.mjs";

export default {
  ...common,
  key: "openai-new-run-state-changed",
  name: "New Run State Changed",
  description: "Emit new event every time a run changes its status. [See the documentation](https://platform.openai.com/docs/api-reference/runs/listRuns)",
  version: "0.0.6",
  type: "source",
  dedupe: "unique",
  props: {
    ...common.props,
    threadId: {
      propDefinition: [
        common.props.openai,
        "threadId",
      ],
    },
  },
  methods: {
    ...common.methods,
    getStatusItems() {
      return this.db.get("statusItems");
    },
    setStatusItems(value) {
      this.db.set("statusItems", value);
    },
    async getData() {
      const {
        openai,
        threadId,
      } = this;

      const { data } = await openai.listRuns({
        threadId,
      });

      return data;
    },
    getMeta(item) {
      const ts = Date.now();
      return {
        id: `${item.id}-${ts}`,
        summary: `Run State Changed: ${item.id}`,
        ts,
      };
    },
    statusByItemId(itemId, statusItems) {
      const { [itemId]: status } = statusItems || {};
      return status;
    },
    buildStatusItems(data) {
      return data?.reduce((acc, item) => ({
        ...acc,
        [item.id]: item.status,
      }), {});
    },
    async getAndProcessItems(maxEvents) {
      const {
        getData,
        getStatusItems,
        setStatusItems,
        statusByItemId,
        buildStatusItems,
        getMeta,
        $emit: emit,
      } = this;

      const data = await getData();
      const statusItems = getStatusItems();

      Array.from(data)
        .reverse()
        .forEach((item, index) => {
          const statusChanged = statusByItemId(item.id, statusItems) !== item.status;
          if ((!maxEvents || index < maxEvents) && statusChanged) {
            emit(item, getMeta(item));
          }
        });

      setStatusItems(buildStatusItems(data));
    },
  },
  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.

Label	Prop	Type	Description
OpenAI (ChatGPT)	`openai`	`app`	This component uses the OpenAI (ChatGPT) app.
N/A	`db`	`$.service.db`	This component uses `$.service.db` to maintain state between executions.
	`timer`	`$.interface.timer`
Thread ID	`threadId`	`string`	The unique identifier for the thread. Example: `thread_abc123`. To locate the thread ID, make sure your OpenAI Threads setting (Settings -> Organization/Personal -> General -> Features and capabilities -> Threads) is set to "Visible to organization owners" or "Visible to everyone". You can then access the list of threads and click on individual threads to reveal their IDs

Trigger Authentication#

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

About OpenAI (ChatGPT)#

OpenAI is an AI research and deployment company with the mission to ensure that artificial general intelligence benefits all of humanity. They are the makers of popular models like ChatGPT, DALL-E, and Whisper.

Action#

Classify Text on MonkeyLearn

Description:Classifies texts with a given classifier. [See the docs here](https://monkeylearn.com/api/v3/#classify)

Version:0.0.1

Key:monkeylearn-classify-text

View on GitHub

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-classify-text",
  name: "Classify Text",
  description: "Classifies texts with a given classifier. [See the docs here](https://monkeylearn.com/api/v3/#classify)",
  version: "0.0.1",
  type: "action",
  props: {
    app,
    classifierId: {
      propDefinition: [
        app,
        "classifierId",
      ],
    },
    data: {
      propDefinition: [
        app,
        "data",
      ],
    },
    productionModel: {
      propDefinition: [
        app,
        "productionModel",
      ],
    },
  },
  async run({ $ }) {
    const {
      classifierId,
      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.classifyText($, classifierId, data, productionModel);
    $.export("$summary", "Successfully classified 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.

Label	Prop	Type	Description
MonkeyLearn	`app`	`app`	This component uses the MonkeyLearn app.
Classifier Id	`classifierId`	`string`	Select a value from the drop down menu.
Data	`data`	`string[]`	A list of up to 500 data elements. Each element must be a string with the text.
Production Model	`productionModel`	`boolean`	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.