Classify Items Into Categories with Azure OpenAI Service API on New SNS Messages from AWS API

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New SNS Messages from the AWS API

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Classify Items Into Categories with the Azure OpenAI Service API

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Getting Started#

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

Select this integration
Configure the New SNS Messages trigger
1. Connect your AWS account
2. Select a AWS Region
3. Optional- Select a SNS Topic
4. Optional- Configure SNS Topic Name
Configure the Classify Items Into Categories action
1. Connect your Azure OpenAI Service account
2. Configure Items
3. Configure Categories
4. Optional- Configure Temperature
5. Optional- Configure N
6. Optional- Configure Stream
7. Optional- Configure Stop
8. Optional- Configure Max Tokens
9. Optional- Configure Presence Penalty
10. Optional- Configure Frequency Penalty
11. Optional- Configure User
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 SNS Messages on AWS

Description:Creates an SNS topic in your AWS account. Messages published to this topic are emitted from the Pipedream source.

Version:0.4.2

Key:aws-new-sns-messages

View on GitHub

AWS Overview#

The AWS API unlocks endless possibilities for automation with Pipedream. With this powerful combo, you can manage your AWS services and resources, automate deployment workflows, process data, and react to events across your AWS infrastructure. Pipedream offers a serverless platform for creating workflows triggered by various events that can execute AWS SDK functions, making it an efficient tool to integrate, automate, and orchestrate tasks across AWS services and other apps.

Trigger Code#

import base from "../common/sns.mjs";
import { toSingleLineString } from "../../common/utils.mjs";
import commonSNS from "../../common/common-sns.mjs";
import { ConfigurationError } from "@pipedream/platform";

export default {
  ...base,
  key: "aws-new-sns-messages",
  name: "New SNS Messages",
  description: toSingleLineString(`
    Creates an SNS topic in your AWS account.
    Messages published to this topic are emitted from the Pipedream source.
  `),
  version: "0.4.2",
  type: "source",
  dedupe: "unique", // Dedupe on SNS message ID
  props: {
    ...base.props,
    topicArn: {
      ...commonSNS.props.topic,
      optional: true,
    },
    topic: {
      label: "SNS Topic Name",
      description: toSingleLineString(`
        **Pipedream will create an SNS topic with this name in your account**,
        converting it to a [valid SNS topic
        name](https://docs.aws.amazon.com/sns/latest/api/API_CreateTopic.html).
      `),
      type: "string",
      optional: true,
    },
  },
  methods: {
    ...base.methods,
    getTopicName() {
      return this.convertNameToValidSNSTopicName(this.topic);
    },
  },
  async run(event) {
    if (!this.topicArn && !this.topic) {
      throw new ConfigurationError("Must specify either an existing topic or a new topic name");
    }

    if (this._isSubscriptionConfirmationEvent(event)) {
      const { body } = event;
      const subscriptionArn = await this._confirmSubscription(body);
      this._setSubscriptionArn(subscriptionArn);
      return;
    }

    await this.processEvent(event);
  },
};

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
AWS	`aws`	`app`	This component uses the AWS app.
N/A	`db`	`$.service.db`	This component uses `$.service.db` to maintain state between executions.
N/A	`http`	`$.interface.http`	This component uses `$.interface.http` to generate a unique URL when the component is first instantiated. Each request to the URL will trigger the `run()` method of the component.
AWS Region	`region`	`string`	Select a value from the drop down menu.
SNS Topic	`topicArn`	`string`	Select a value from the drop down menu.
SNS Topic Name	`topic`	`string`	Pipedream will create an SNS topic with this name in your account, converting it to a valid SNS topic name.

Trigger Authentication#

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

Follow the AWS Instructions for creating an IAM user with an associated access and secret key.

As a best practice, attach the minimum set of IAM permissions necessary to perform the specific task in Pipedream. If your workflow only needs to perform a single API call, you should create a user and associate an IAM group / policy with permission to do only that task. You can create as many linked AWS accounts in Pipedream as you'd like.

Enter your access and secret key below.

About AWS#

Amazon Web Services (AWS) offers reliable, scalable, and inexpensive cloud computing services.

Action#

Classify Items Into Categories on Azure OpenAI Service

Description:Classify items into specific categories. [See the documentation](https://learn.microsoft.com/en-us/azure/ai-services/openai/reference#chat-completions)

Version:0.0.1

Key:azure_openai_service-classify-items-into-categories

View on GitHub

Azure OpenAI Service Overview#

The Azure OpenAI Service API provides access to powerful AI models that can understand and generate human-like text. With Pipedream, you can harness this capability to create a variety of serverless workflows, automating tasks like content creation, code generation, and language translation. By integrating the API with other apps on Pipedream, you can streamline processes, analyze sentiment, and even automate customer support.

Action Code#

import azureOpenAI from "../../azure_openai_service.app.mjs";
import common from "../common/common-helper.mjs";

export default {
  ...common,
  key: "azure_openai_service-classify-items-into-categories",
  name: "Classify Items Into Categories",
  description: "Classify items into specific categories. [See the documentation](https://learn.microsoft.com/en-us/azure/ai-services/openai/reference#chat-completions)",
  version: "0.0.1",
  type: "action",
  props: {
    azureOpenAI,
    items: {
      label: "Items",
      description: "Items to categorize",
      type: "string[]",
    },
    categories: {
      label: "Categories",
      description: "Categories to classify items into",
      type: "string[]",
    },
    ...common.props,
  },
  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 {
        const categorizationJSON = assistantResponse.substring(
          assistantResponse.indexOf("```json") + 7,
          assistantResponse.lastIndexOf("```"),
        ).trim();
        categorizations = JSON.parse(categorizationJSON);
      } 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
Azure OpenAI Service	`azureOpenAI`	`app`	This component uses the Azure OpenAI Service app.
Items	`items`	`string[]`	Items to categorize
Categories	`categories`	`string[]`	Categories to classify items into
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.
N	`n`	`integer`	How many completions to generate
Stream	`stream`	`boolean`	If set, partial message deltas will be sent, like in ChatGPT. Tokens will be sent as data-only server-sent events as they become available, with the stream terminated by a data: [DONE] message.
Stop	`stop`	`string`	Up to 4 sequences where the API will stop generating further tokens.
Max Tokens	`maxTokens`	`integer`	The maximum number of tokens allowed for the generated answer. By default, the number of tokens the model can return will be (4096 - prompt tokens).
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 Azure OpenAI to monitor and detect abuse.

Action Authentication#

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

Before you start, you'll need to deploy a model in the Azure OpenAI Service.

Once that's done, enter the name of your Azure OpenAI resource, the deployment name you chose when you deployed the model, and your Azure OpenAI key below.

About Azure OpenAI Service#

Apply large language models and generative AI to a variety of use cases

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Classify Items Into Categories with Azure OpenAI Service API on New SNS Messages from AWS API

Pipedream makes it easy to connect APIs for Azure OpenAI Service, AWS and 2,000+ other apps remarkably fast.

Trusted by 800,000+ developers from startups to Fortune 500 companies

Developers ♥ Pipedream

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