Classify Items with 302.AI API on New Column from MySQL API

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Trigger workflow on

New Column from the MySQL API

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Classify Items with the 302.AI API

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Getting Started#

This integration creates a workflow with a MySQL trigger and 302.AI action. When you configure and deploy the workflow, it will run on Pipedream's servers 24x7 for free.

Select this integration
Configure the New Column trigger
1. Connect your MySQL account
2. Configure timer
3. Select a Table
Configure the Classify Items action
1. Connect your 302.AI 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
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 Column on MySQL

Description:Emit new event when you add a new column to a table. [See the docs here](https://dev.mysql.com/doc/refman/8.0/en/show-columns.html)

Version:2.0.6

Key:mysql-new-column

View on GitHub

MySQL Overview#

The MySQL application on Pipedream enables direct interaction with your MySQL databases, allowing you to perform CRUD operations—create, read, update, delete—on your data with ease. You can leverage these capabilities to automate data synchronization, report generation, and event-based triggers that kick off workflows in other apps. With Pipedream's serverless platform, you can connect MySQL to hundreds of other services without managing infrastructure, crafting complex code, or handling authentication.

Trigger Code#

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

export default {
  ...common,
  key: "mysql-new-column",
  name: "New Column",
  description:
    "Emit new event when you add a new column to a table. [See the docs here](https://dev.mysql.com/doc/refman/8.0/en/show-columns.html)",
  type: "source",
  version: "2.0.6",
  dedupe: "unique",
  props: {
    ...common.props,
    db: "$.service.db",
  },
  methods: {
    ...common.methods,
    _getPreviousColumns() {
      return this.db.get("previousColumns");
    },
    _setPreviousColumns(previousColumns) {
      this.db.set("previousColumns", previousColumns);
    },
    async listResults() {
      const { table } = this;
      let previousColumns = this._getPreviousColumns() || [];
      const columns = await this.mysql.listNewColumns({
        table,
        previousColumns,
      });
      this.iterateAndEmitEvents(columns);

      const newColumnNames = columns
        .map((column) => column.Field)
        .filter((c) => !previousColumns.includes(c));

      previousColumns = previousColumns.concat(newColumnNames);
      this._setPreviousColumns(previousColumns);
    },
    generateMeta(column) {
      const columnName = column.Field;
      return {
        id: `${columnName}${this.table}`,
        summary: columnName,
        ts: Date.now(),
      };
    },
  },
};

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
MySQL	`mysql`	`app`	This component uses the MySQL app.
	`timer`	`$.interface.timer`
Table	`table`	`string`	Select a value from the drop down menu.
N/A	`db`	`$.service.db`	This component uses `$.service.db` to maintain state between executions.

Trigger Authentication#

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

Connecting to Restricted Databases

Either enable the shared static IP for this account below, or configure a VPC to deploy any workflow in your workspace to a private network with a dedicated static IP. Learn more in our docs

SSL Setup

Configure SSL on your MySQL database by providing the CA (Certificate Authority), and choosing between Full Verification, Verify Certificate Authority (CA), or Skip Verification. Skipping verification is not recommended as this has serious security implications

About MySQL#

MySQL is an open-source relational database management system.

Action#

Classify Items on 302.AI

Description:Classify input items into predefined categories using 302.AI models. Perfect for tagging, segmentation, and automated organization. [See documentation](https://doc.302.ai/147522039e0)

Version:0.0.1

Key:_302_ai-classify-items

View on GitHub

Action Code#

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

export default {
  ...common,
  name: "Classify Items",
  version: "0.0.1",
  annotations: {
    destructiveHint: false,
    openWorldHint: true,
    readOnlyHint: true,
  },
  key: "_302_ai-classify-items",
  description: "Classify input items into predefined categories using 302.AI models. Perfect for tagging, segmentation, and automated organization. [See documentation](https://doc.302.ai/147522039e0)",
  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,
      };
      const n = this.n
        ? parseInt(this.n)
        : 1;
      if (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.

Label	Prop	Type	Description
302.AI	`_302_ai`	`app`	This component uses the 302.AI app.
Model	`modelId`	`string`	Select a value from the drop down menu.
Max Tokens	`maxTokens`	`string`	The maximum number of tokens to generate in the completion.
Temperature	`temperature`	`string`	What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic.
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.
N	`n`	`string`	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 monitor and detect abuse.
Items	`items`	`string[]`	Items to categorize
Categories	`categories`	`string[]`	Categories to classify items into