← Moxie + OpenAI (ChatGPT) integrations

Classify Items into Categories with OpenAI (ChatGPT) API on New Client Added from Moxie API

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New Client Added from the Moxie 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 Moxie trigger and OpenAI (ChatGPT) 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 Client Added trigger
    1. Connect your Moxie account
    2. Configure timer
  3. Configure the Classify Items into Categories action
    1. Connect your OpenAI (ChatGPT) account
    2. Select a Model
    3. Optional- Configure Max Tokens
    4. Optional- Configure Temperature
    5. Optional- Configure Top P
    6. Optional- Configure N
    7. Optional- Configure Stop
    8. Optional- Configure Presence Penalty
    9. Optional- Configure Frequency Penalty
    10. Optional- Configure User
    11. Configure info
    12. Configure Items
    13. Configure Categories
  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 new client is created.
Version:0.0.1
Key:moxie-new-client-added

Moxie Overview

The Moxie API provides tools to facilitate customer engagement through chat and messaging services. With this API, you can integrate real-time chat capabilities, manage conversations, and leverage customer data to provide personalized support. On Pipedream, you can use the Moxie API to create automated workflows that respond to events in Moxie, such as new messages or chat engagements, and connect them with other services to enhance customer support, automate responses, and streamline communication processes.

Trigger Code

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

export default {
  ...common,
  key: "moxie-new-client-added",
  name: "New Client Added",
  version: "0.0.1",
  description: "Emit new event when a new client is created.",
  type: "source",
  dedupe: "unique",
  methods: {
    ...common.methods,
    getResources() {
      return this.moxie.listClients();
    },
    getTsKey() {
      return "created";
    },
    generateMeta(client) {
      return {
        id: client.id,
        summary: client.name,
        ts: Date.parse(client[this.getTsKey()]),
      };
    },
  },
  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
MoxiemoxieappThis component uses the Moxie app.
N/Adb$.service.dbThis component uses $.service.db to maintain state between executions.
timer$.interface.timer

Trigger Authentication

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

To retrieve your API Key and Base URL,

  • Navigate to your Moxie account and sign in
  • Pull up the “Workspace settings” menu on the bottom left
  • Go to “Connected Apps” > “Integrations” > "Enable custom integrations"

About Moxie

Moxie is a set of stupid-good tools work for you. Features Client management Invoices Project management Time tracking Accounting Collaborators Proposals & more.

Action

Description:Classify items into specific categories using the Chat API. [See the documentation](https://platform.openai.com/docs/api-reference/chat)
Version:0.1.2
Key:openai-classify-items-into-categories

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:

Action Code

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

export default {
  ...common,
  name: "Classify Items into Categories",
  version: "0.1.2",
  key: "openai-classify-items-into-categories",
  description: "Classify items into specific categories using the Chat API. [See the documentation](https://platform.openai.com/docs/api-reference/chat)",
  type: "action",
  props: {
    ...common.props,
    info: {
      type: "alert",
      alertType: "info",
      content: `Provide a list of **items** and a list of **categories**. The output will contain an array of objects, each with properties \`item\` and \`category\`
        \nExample:
        \nIf **Categories** is \`["people", "pets"]\`, and **Items** is \`["dog", "George Washington"]\`
        \n The output will contain the following categorizations:
        \n \`[{"item":"dog","category":"pets"},{"item":"George Washington","category":"people"}]\`
      `,
    },
    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 responses = response.choices?.map(({ message }) => message.content);
      const categorizations = [];
      for (const response of responses) {
        try {
          categorizations.push(JSON.parse(response));
        } catch (err) {
          console.log("Failed to parse output, assistant returned malformed JSON");
        }
      }
      const output = {
        messages,
      };
      if (this.n > 1) {
        output.categorizations = categorizations;
      } else {
        output.categorizations = categorizations[0];
      }
      return output;
    },
  },
};

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
OpenAI (ChatGPT)openaiappThis component uses the OpenAI (ChatGPT) app.
ModelmodelIdstringSelect a value from the drop down menu.
Max TokensmaxTokensinteger

The maximum number of tokens to generate in the completion.

Temperaturetemperaturestring

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 PtopPstring

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.

Nninteger

How many completions to generate for each prompt

Stopstopstring[]

Up to 4 sequences where the API will stop generating further tokens. The returned text will not contain the stop sequence.

Presence PenaltypresencePenaltystring

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 PenaltyfrequencyPenaltystring

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.

Useruserstring

A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. Learn more here.

Itemsitemsstring[]

Items to categorize

Categoriescategoriesstring[]

Categories to classify items into

Action 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.

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