Classify Items into Categories with OpenAI (ChatGPT) API on New Company Created Event from Aero Workflow API

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New Company Created Event from the Aero Workflow API

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Classify Items into Categories with the OpenAI (ChatGPT) API

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Getting Started#

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

Select this integration
Configure the New Company Created Event trigger
1. Connect your Aero Workflow account
2. Configure timer
Configure the Classify Items into Categories action
1. Connect your OpenAI (ChatGPT) account
2. Optional- Configure Max Tokens
3. Optional- Configure Temperature
4. Optional- Configure Top P
5. Optional- Configure N
6. Optional- Configure Stop
7. Optional- Configure Presence Penalty
8. Optional- Configure Frequency Penalty
9. Optional- Configure User
10. Configure Items
11. Configure Categories
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 Company Created Event on Aero Workflow

Description:Emit new events when a new company is created. [See the docs](https://api.aeroworkflow.com/swagger/index.html)

Version:0.0.1

Key:aero_workflow-new-company-created

View on GitHub

Aero Workflow Overview#

You can use the Aero Workflow API to build from simpleETL processes to
multi-step workflows that encompass a variety of microservices. The following
are examples of what you can build using the Aero Workflow API:

A process that ingests data from a remote data source, transforms it, and
then stores it in a database.
A workflow that aggregates data from multiple data sources, runs some
analysis on it, and then produces a report.
A process that monitors a data source for new data, ingests it, and then
sends it to a message queue for processing by other elements of your system.

Trigger Code#

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

export default {
  ...common,
  key: "aero_workflow-new-company-created",
  name: "New Company Created Event",
  description: "Emit new events when a new company is created. [See the docs](https://api.aeroworkflow.com/swagger/index.html)",
  version: "0.0.1",
  type: "source",
  dedupe: "unique",
  methods: {
    ...common.methods,
    getResourceFnConfig() {
      return {
        resourceFn: this.app.getCompanies,
        resourceKey: "companies",
      };
    },
    getComparable(item) {
      return item.id;
    },
    getMeta(item) {
      return {
        id: item.id,
        summary: `New company was created: ${item.name}(ID: ${item.id})`,
        ts: new Date().getTime(),
      };
    },
    async getItem(item) {
      return this.app.getCompany({
        companyId: item.id,
      });
    },
  },
};

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
Aero Workflow	`app`	`app`	This component uses the Aero Workflow app.
	`timer`	`$.interface.timer`
N/A	`db`	`$.service.db`	This component uses `$.service.db` to maintain state between executions.

Trigger Authentication#

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

To get your API Key and Account Number, navigate to Account Settings > Account Profile.

If you've already created an API Key it will be listed on this screen.
If there is no API Key listed, click the Generate new API Key button.
The Account Number (also sometimes called "Account ID") is listed below the API Key

About Aero Workflow#

Aero is workflow & practice management built specifically with the modern cloud-based accounting firm in mind.

Action#

Classify Items into Categories on OpenAI (ChatGPT)

Description:Classify items into specific categories using the Chat API

Version:0.0.4

Key:openai-classify-items-into-categories

View on GitHub

OpenAI (ChatGPT) Overview#

The OpenAI API is a powerful tool that provides access to a range of
high-powered machine learning models. With the OpenAI API, developers can
create products, services, and tools that enable humanizing AI experiences, and
build applications that extend the power of human language.

Using the OpenAI API, developers can create language-driven applications such
as:

Natural language understanding and sentiment analysis
Text-based search
Question answering
Dialogue systems and conversation agents
Intelligent text completion
Text summarization
Text classification
Machine translation
Language generation
Multi-factor authentication
Anomaly detection
Text analysis

Action Code#

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

export default {
  ...common,
  name: "Classify Items into Categories",
  version: "0.0.4",
  key: "openai-classify-items-into-categories",
  description: "Classify items into specific categories using the Chat API",
  type: "action",
  props: {
    ...common.props,
    items: {
      label: "Items",
      description: "Items to categorize",
      type: "string[]",
    },
    categories: {
      label: "Categories",
      description: "Categories to classify items into",
      type: "string[]",
    },
  },
  methods: {
    ...common.methods,
    systemInstructions() {
      return "Your goal is to categorize items into specific categories and produce ONLY JSON. The user will provide both the items and categories. Please only categorize items into the specific categories, and no others, and output ONLY JSON.";
    },
    outputFormat() {
      return "Please only categorize items into the specific categories, and no others. Output a valid JSON string — an array of objects, where each object has the following properties: item, category. Do not return any English text other than the JSON, either before or after the JSON. I need to parse the response as JSON, and parsing will fail if you return any English before or after the JSON";
    },
    userMessage() {
      return `Categorize each of the following items:\n\n${this.items.join("\n")}\n\ninto one of the following categories:\n\n${this.categories.join("\n")}\n\n${this.outputFormat()}}`;
    },
    summary() {
      return `Categorized ${this.items.length} items into ${this.categories.length} categories`;
    },
    formatOutput({
      messages, response,
    }) {
      if (!messages || !response) {
        throw new Error("Invalid API output, please reach out to https://pipedream.com/support");
      }
      const assistantResponse = response.choices?.[0]?.message?.content;
      let categorizations = assistantResponse;
      try {
        categorizations = JSON.parse(assistantResponse);
      } catch (err) {
        console.log("Failed to parse output, assistant returned malformed JSON");
      }
      return {
        categorizations,
        messages,
      };
    },
  },
};

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
OpenAI (ChatGPT)	`openai`	`app`	This component uses the OpenAI (ChatGPT) app.
Max Tokens	`maxTokens`	`integer`	The maximum number of tokens to generate in the completion.
Temperature	`temperature`	`string`	Optional. What sampling temperature to use. Higher values means the model will take more risks. Try 0.9 for more creative applications, and 0 (argmax sampling) for ones with a well-defined answer.
Top P	`topP`	`string`	An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered. We generally recommend altering this or `temperature` but not both.
N	`n`	`integer`	How many completions to generate for each prompt
Stop	`stop`	`string[]`	Up to 4 sequences where the API will stop generating further tokens. The returned text will not contain the stop sequence.
Presence Penalty	`presencePenalty`	`string`	Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics.
Frequency Penalty	`frequencyPenalty`	`string`	Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim.
User	`user`	`string`	A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. Learn more here.
Items	`items`	`string[]`	Items to categorize
Categories	`categories`	`string[]`	Categories to classify items into