← Cradl AI + OpenAI (ChatGPT) integrations

Classify Items into Categories with OpenAI (ChatGPT) API on New Document Parsing Completed (Instant) from Cradl AI API

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Trigger workflow on
New Document Parsing Completed (Instant) from the Cradl AI 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 Cradl AI 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 Document Parsing Completed (Instant) trigger
    1. Connect your Cradl AI account
    2. Configure timer
    3. Select a Workflow ID
  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 document processing flow has completed.
Version:0.0.1
Key:cradl_ai-new-document-parsing-completed-instant

Cradl AI Overview

Cradl AI is a powerful tool for creating customized machine learning models without extensive coding knowledge. It specializes in processing and understanding various forms of data, including text and images. Utilizing the Cradl AI API on Pipedream, developers can automate workflows involving data analysis, enhance data-driven decision-making, and integrate AI capabilities into applications seamlessly. This opens up opportunities for dynamic interactions with other services, streamlining operations and enhancing user experiences.

Trigger Code

import cradlAi from "../../cradl_ai.app.mjs";
import { DEFAULT_POLLING_SOURCE_TIMER_INTERVAL } from "@pipedream/platform";

export default {
  key: "cradl_ai-new-document-parsing-completed-instant",
  name: "New Document Parsing Completed (Instant)",
  description: "Emit new event when a document processing flow has completed.",
  version: "0.0.1",
  type: "source",
  dedupe: "unique",
  props: {
    cradlAi,
    db: "$.service.db",
    timer: {
      type: "$.interface.timer",
      default: {
        intervalSeconds: DEFAULT_POLLING_SOURCE_TIMER_INTERVAL,
      },
    },
    workflowId: {
      propDefinition: [
        cradlAi,
        "workflowId",
      ],
    },
  },
  hooks: {
    async deploy() {
      await this.processEvent(25);
    },
  },
  methods: {
    _getLastTs() {
      return this.db.get("lastTs") || 0;
    },
    _setLastTs(lastTs) {
      this.db.set("lastTs", lastTs);
    },
    emitEvent(item) {
      const meta = this.generateMeta(item);
      this.$emit(item, meta);
    },
    generateMeta(item) {
      return {
        id: item.executionId,
        summary: `Execution completed with ID ${item.executionId}`,
        ts: Date.parse(item.endTime),
      };
    },
    async processEvent(max) {
      const lastTs = this._getLastTs();
      const results = this.cradlAi.paginate({
        resourceFn: this.cradlAi.listExecutions,
        args: {
          workflowId: this.workflowId,
          params: {
            order: "descending",
            sortBy: "endTime",
            status: [
              "completed",
            ],
          },
        },
        resourceType: "executions",
        max,
      });
      const executions = [];
      for await (const item of results) {
        const ts = Date.parse(item.endTime);
        if (ts >= lastTs) {
          executions.push(item);
        } else {
          break;
        }
      }
      if (!executions.length) {
        return;
      }
      this._setLastTs(Date.parse(executions[0].endTime));
      executions.reverse().forEach((item) => this.emitEvent(item));
    },
  },
  async run() {
    await this.processEvent();
  },
};

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
Cradl AIcradlAiappThis component uses the Cradl AI app.
N/Adb$.service.dbThis component uses $.service.db to maintain state between executions.
timer$.interface.timer
Workflow IDworkflowIdstringSelect a value from the drop down menu.

Trigger Authentication

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

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

api.lucidtech.ai/users:read

About Cradl AI

Automate internal document processes with AI.

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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