← AWS + OpenAI (ChatGPT) integrations

Chat with OpenAI (ChatGPT) API on New DynamoDB Stream Event from AWS API

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New DynamoDB Stream Event from the AWS API
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Chat with the OpenAI (ChatGPT) API
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Getting Started

This integration creates a workflow with a AWS 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 DynamoDB Stream Event trigger
    1. Connect your AWS account
    2. Configure timer
    3. Select a AWS Region
    4. Select a Stream
  3. Configure the Chat action
    1. Connect your OpenAI (ChatGPT) account
    2. Select a Model
    3. Configure User Message
    4. Optional- Configure System Instructions
    5. Optional- Configure Prior Message History
    6. Optional- Configure Images
    7. Optional- Select a Response Format
    8. Optional- Configure Max Tokens
    9. Optional- Configure Temperature
    10. Optional- Configure Top P
    11. Optional- Configure N
    12. Optional- Configure Stop
    13. Optional- Configure Presence Penalty
    14. Optional- Configure Frequency Penalty
    15. Optional- Configure User
  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 DynamoDB stream receives new events. [See the docs here](https://docs.aws.amazon.com/amazondynamodb/latest/APIReference/API_streams_GetRecords.html)
Version:0.0.2
Key:aws-new-dynamodb-stream-event

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 common from "../../common/common-dynamodb-streams.mjs";

export default {
  ...common,
  key: "aws-new-dynamodb-stream-event",
  name: "New DynamoDB Stream Event",
  description: "Emit new event when a DynamoDB stream receives new events. [See the docs here](https://docs.aws.amazon.com/amazondynamodb/latest/APIReference/API_streams_GetRecords.html)",
  type: "source",
  version: "0.0.2",
  dedupe: "unique",
  props: {
    ...common.props,
    stream: {
      type: "string",
      label: "Stream",
      description: "ARN of the Stream to watch for new events",
      async options({ prevContext }) {
        const {
          streams,
          lastEvaluatedStreamArn,
        } = await this.listEnabledStreams({
          ExclusiveStartStreamArn: prevContext.lastEvaluatedStreamArn,
        });
        const options = streams.map((stream) => ({
          label: `${stream.TableName} - Created ${stream.StreamLabel}`,
          value: stream.StreamArn,
        }));
        return {
          options,
          context: {
            lastEvaluatedStreamArn,
          },
        };
      },
    },
  },
  hooks: {
    async deploy() {
      const { StreamDescription: streamDescription } = await this.listShards({
        StreamArn: this.stream,
      });
      const shardId = streamDescription.Shards[streamDescription.Shards.length - 1].ShardId;
      const { ShardIterator: shardIterator } = await this.getShardIterator({
        ShardId: shardId,
        StreamArn: this.stream,
        ShardIteratorType: "LATEST",
      });
      this._setShardIterator(shardIterator);
    },
  },
  methods: {
    ...common.methods,
    _getShardIterator() {
      return this.db.get("shardIterator");
    },
    _setShardIterator(shardIterator) {
      this.db.set("shardIterator", shardIterator);
    },
    generateMeta({
      eventID, eventName, dynamodb,
    }) {
      return {
        id: eventID,
        summary: `New ${eventName} event`,
        ts: Date.parse(dynamodb.ApproximateCreationDateTime),
      };
    },
  },
  async run() {
    if (!(await this.isStreamEnabled(this.stream))) {
      throw new Error("Stream is no longer enabled.");
    }

    const shardIterator = this._getShardIterator();

    const {
      Records: records, NextShardIterator: nextShardIterator,
    } = await this.getRecords({
      ShardIterator: shardIterator,
    });

    for (const record of records) {
      const meta = this.generateMeta(record);
      this.$emit(record, meta);
    }

    this._setShardIterator(nextShardIterator);
  },
};

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
AWSawsappThis component uses the AWS app.
N/Adb$.service.dbThis component uses $.service.db to maintain state between executions.
timer$.interface.timer
AWS RegionregionstringSelect a value from the drop down menu.
StreamstreamstringSelect a value from the drop down menu.

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

Description:The Chat API, using the `gpt-3.5-turbo` or `gpt-4` model. [See the documentation](https://platform.openai.com/docs/api-reference/chat)
Version:0.1.10
Key:openai-chat

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 openai from "../../openai.app.mjs";
import common from "../common/common.mjs";
import constants from "../../common/constants.mjs";

export default {
  ...common,
  name: "Chat",
  version: "0.1.10",
  key: "openai-chat",
  description: "The Chat API, using the `gpt-3.5-turbo` or `gpt-4` model. [See the documentation](https://platform.openai.com/docs/api-reference/chat)",
  type: "action",
  props: {
    openai,
    modelId: {
      propDefinition: [
        openai,
        "chatCompletionModelId",
      ],
    },
    userMessage: {
      label: "User Message",
      type: "string",
      description: "The user messages provide instructions to the assistant. They can be generated by the end users of an application, or set by a developer as an instruction.",
    },
    systemInstructions: {
      label: "System Instructions",
      type: "string",
      description: "The system message helps set the behavior of the assistant. For example: \"You are a helpful assistant.\" [See these docs](https://platform.openai.com/docs/guides/chat/instructing-chat-models) for tips on writing good instructions.",
      optional: true,
    },
    messages: {
      label: "Prior Message History",
      type: "string[]",
      description: "_Advanced_. Because [the models have no memory of past chat requests](https://platform.openai.com/docs/guides/chat/introduction), all relevant information must be supplied via the conversation. You can provide [an array of messages](https://platform.openai.com/docs/guides/chat/introduction) from prior conversations here. If this param is set, the action ignores the values passed to **System Instructions** and **Assistant Response**, appends the new **User Message** to the end of this array, and sends it to the API.",
      optional: true,
    },
    images: {
      label: "Images",
      type: "string[]",
      description: "Provide one or more images to [OpenAI's vision model](https://platform.openai.com/docs/guides/vision). Accepts URLs or base64 encoded strings. Compatible with the `gpt4-vision-preview model`",
      optional: true,
    },
    responseFormat: {
      type: "string",
      label: "Response Format",
      description: "Specify the format that the model must output. [Setting to `json_object` guarantees the message the model generates is valid JSON](https://platform.openai.com/docs/api-reference/chat/create#chat-create-response_format). Defaults to `text`",
      options: constants.CHAT_RESPONSE_FORMATS,
      optional: true,
      default: "text",
    },
    ...common.props,
  },
  async run({ $ }) {
    const args = this._getChatArgs();

    const response = await this.openai.createChatCompletion({
      $,
      data: args,
    });

    if (response) {
      $.export("$summary", `Successfully sent chat with id ${response.id}`);
    }

    const { messages } = args;
    return {
      original_messages: messages,
      original_messages_with_assistant_response: messages.concat(response.choices[0]?.message),
      ...response,
    };
  },
};

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.
User MessageuserMessagestring

The user messages provide instructions to the assistant. They can be generated by the end users of an application, or set by a developer as an instruction.

System InstructionssystemInstructionsstring

The system message helps set the behavior of the assistant. For example: "You are a helpful assistant." See these docs for tips on writing good instructions.

Prior Message Historymessagesstring[]

Advanced. Because the models have no memory of past chat requests, all relevant information must be supplied via the conversation. You can provide an array of messages from prior conversations here. If this param is set, the action ignores the values passed to System Instructions and Assistant Response, appends the new User Message to the end of this array, and sends it to the API.

Imagesimagesstring[]

Provide one or more images to OpenAI's vision model. Accepts URLs or base64 encoded strings. Compatible with the gpt4-vision-preview model

Response FormatresponseFormatstringSelect a value from the drop down menu:textjson_object
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.

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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