← AWS + OpenAI (ChatGPT) integrations

Chat with OpenAI (ChatGPT) API on New Records Returned by CloudWatch Logs Insights Query from AWS API

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New Records Returned by CloudWatch Logs Insights Query from the AWS 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 Records Returned by CloudWatch Logs Insights Query trigger
    1. Connect your AWS account
    2. Select a AWS Region
    3. Select one or more CloudWatch Log Groups
    4. Configure Logs Insights Query
    5. Optional- Configure Emit query results as a single event
    6. Configure Polling schedule
  3. Configure the Chat action
    1. Connect your OpenAI (ChatGPT) account
    2. Select a Model
    3. Configure User Message
    4. Optional- Configure Max Tokens
    5. Optional- Configure Temperature
    6. Optional- Configure Top P
    7. Optional- Configure N
    8. Optional- Configure Stop
    9. Optional- Configure Presence Penalty
    10. Optional- Configure Frequency Penalty
    11. Optional- Configure User
    12. Optional- Configure System Instructions
    13. Optional- Configure Prior Message History
    14. Optional- Configure Images
    15. Optional- Select a Response Format
  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:Executes a CloudWatch Logs Insights query on a schedule, and emits the records as invidual events (default) or in batch
Version:0.2.2
Key:aws-new-records-returned-by-cloudwatch-logs-insights-query

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-cloudwatch-logs.mjs";
import { DEFAULT_POLLING_SOURCE_TIMER_INTERVAL } from "@pipedream/platform";

export default {
  ...common,
  key: "aws-new-records-returned-by-cloudwatch-logs-insights-query",
  name: "New Records Returned by CloudWatch Logs Insights Query",
  // eslint-disable-next-line pipedream/source-description
  description: "Executes a CloudWatch Logs Insights query on a schedule, and emits the records as invidual events (default) or in batch",
  version: "0.2.2",
  type: "source",
  props: {
    aws: common.props.aws,
    region: common.props.region,
    db: "$.service.db",
    // eslint-disable-next-line pipedream/props-label
    logGroupNames: {
      ...common.props.logGroupName,
      type: "string[]",
      description: "The log groups you'd like to query",
    },
    queryString: {
      label: "Logs Insights Query",
      description: "The query you'd like to run. See [this AWS doc](https://docs.aws.amazon.com/AmazonCloudWatch/latest/logs/CWL_QuerySyntax.html) for help with query syntax",
      type: "string",
    },
    emitResultsInBatch: {
      type: "boolean",
      label: "Emit query results as a single event",
      description: "If `true`, all events are emitted as an array, within a single Pipedream event. If `false`, each row of results is emitted as its own event. Defaults to `true`",
      optional: true,
      default: true,
    },
    timer: {
      label: "Polling schedule",
      description: "How often you want to query CloudWatch Logs Insights for results",
      type: "$.interface.timer",
      default: {
        intervalSeconds: DEFAULT_POLLING_SOURCE_TIMER_INTERVAL,
      },
    },
  },
  async run() {
    const now = +new Date();
    const startTime = this.db.get("startTime") || now - 1000 * 60 * 60;

    // First, start the query
    const params = {
      queryString: this.queryString,
      startTime,
      endTime: now,
      logGroupNames: this.logGroupNames,
    };

    const { queryId } = await this.startQuery(params);

    // Then poll for its status, emitting each record as its own event when completed
    async function sleep(ms) {
      return new Promise((r) => setTimeout(r, ms));
    }

    let result, res;
    do {
      await sleep(1000);
      res = await this.getQueryResults({
        queryId,
      });
      result = res.status;
    } while (result === "Running" || result === "Scheduled");

    if (result !== "Complete") {
      throw new Error(`Query ${queryId} failed with status ${result}`);
    }

    console.log(JSON.stringify(res, null, 2));
    const { results } = res;

    if (!results || !results.length) {
      console.log("No results, exiting");
      this.db.set("startTime", now);
      return;
    }

    if (this.emitResultsInBatch === true) {
      this.$emit(results, {
        summary: JSON.stringify(results),
      });
    } else {
      for (const item of results) {
        this.$emit(item, {
          summary: JSON.stringify(item),
        });
      }
    }

    // The next time this source runs, query for data starting now
    this.db.set("startTime", 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.
LabelPropTypeDescription
AWSawsappThis component uses the AWS app.
AWS RegionregionstringSelect a value from the drop down menu.
N/Adb$.service.dbThis component uses $.service.db to maintain state between executions.
CloudWatch Log GroupslogGroupNamesstring[]Select a value from the drop down menu.
Logs Insights QueryqueryStringstring

The query you'd like to run. See this AWS doc for help with query syntax

Emit query results as a single eventemitResultsInBatchboolean

If true, all events are emitted as an array, within a single Pipedream event. If false, each row of results is emitted as its own event. Defaults to true

Polling scheduletimer$.interface.timer

How often you want to query CloudWatch Logs Insights for results

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:0.2.0
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: "0.2.0",
  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.",
    },
    ...common.props,
    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. \n- **Text** (default): Returns unstructured text output.\n- **JSON Object**: Ensures the model's output is a valid JSON object.\n- **JSON Schema** (GPT-4o and later): Enables you to define a specific structure for the model's output using a JSON schema. Supported with models `gpt-4o-2024-08-06` and later, and `gpt-4o-mini-2024-07-18` and later.",
      options: Object.values(constants.CHAT_RESPONSE_FORMAT),
      default: constants.CHAT_RESPONSE_FORMAT.TEXT.value,
      optional: true,
      reloadProps: true,
    },
  },
  additionalProps() {
    const { responseFormat } = this;
    if (responseFormat !== constants.CHAT_RESPONSE_FORMAT.JSON_SCHEMA.value) {
      return {};
    }
    return {
      jsonSchema: {
        type: "string",
        label: "JSON Schema",
        description: "Define the schema that the model's output must adhere to. [See the documentation here](https://platform.openai.com/docs/guides/structured-outputs/supported-schemas).",
      },
    };
  },
  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.

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.

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:{ "label": "Text", "value": "text" }{ "label": "JSON Object", "value": "json_object" }{ "label": "JSON Schema", "value": "json_schema" }

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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