← Drata + OpenAI (ChatGPT) integrations

Chat with OpenAI (ChatGPT) API on New Asset Added from Drata API

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New Asset Added from the Drata API
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Chat with the OpenAI (ChatGPT) API
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Getting Started

This integration creates a workflow with a Drata 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 Asset Added trigger
    1. Connect your Drata account
    2. Configure timer
  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:Emit a new event for every new asset. [See the documentation](https://developers.drata.com/docs/openapi/reference/operation/AssetsPublicController_listAssetss/).
Version:0.0.3
Key:drata-new-asset-added

Drata Overview

Drata is a compliance automation platform. Drata’s platform is built by compliance and security experts so you don’t have to be one. With 75+ native integrations, you can easily connect your tech stack and automate evidence collection and testing.

Pipedream customers get 25% off Drata, with implementation fees waived. Visit https://drata.com/partner/pipedream for more information.

Trigger Code

import drata from "../../drata.app.mjs";
import { DEFAULT_POLLING_SOURCE_TIMER_INTERVAL } from "@pipedream/platform";
import constants from "../../common/constants.mjs";

const docsLink = "https://developers.drata.com/docs/openapi/reference/operation/AssetsPublicController_listAssetss/";

export default {
  key: "drata-new-asset-added",
  name: "New Asset Added",
  description: `Emit a new event for every new asset. [See the documentation](${docsLink}).`,
  type: "source",
  version: "0.0.3",
  dedupe: "unique",
  props: {
    drata,
    db: "$.service.db",
    timer: {
      type: "$.interface.timer",
      default: {
        intervalSeconds: DEFAULT_POLLING_SOURCE_TIMER_INTERVAL,
      },
    },
  },
  hooks: {
    async deploy() {
      const response = await this.drata.listAssets({
        params: {
          limit: constants.DEPLOY_LIMIT,
          sort: constants.SORT_CRITERIA.CREATED,
          sortDir: "DESC",
        },
      });

      this._setLastId(response.data[0].id);
      for (const asset of response.data.reverse()) {
        this.$emit(asset, {
          id: asset.id,
          summary: `Historical asset: ${asset.name}`,
          ts: asset.createdAt,
        });
      }
    },
  },
  methods: {
    _getLastId() {
      return this.db.get("lastId");
    },
    _setLastId(lastId) {
      this.db.set("lastId", lastId);
    },
  },
  async run() {
    const lastId = this._getLastId();
    const assets = [];
    let page = 1;

    while (true) {
      const response = await this.drata.listAssets({
        params: {
          limit: constants.PAGINATION_LIMIT,
          sort: constants.SORT_CRITERIA.CREATED,
          sortDir: "DESC",
          page: page++,
        },
      });

      for (const asset of response.data) {
        if (asset.id <= lastId) {
          if (assets.length) {
            this._setLastId(assets[assets.length - 1].id);
            for (const asset of assets) {
              this.$emit(asset, {
                id: asset.id,
                summary: `New asset added: ${asset.name}`,
                ts: asset.createdAt,
              });
            }
          }
          return;
        }

        assets.unshift(asset);
      }
    }
  },
};

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
DratadrataappThis component uses the Drata app.
N/Adb$.service.dbThis component uses $.service.db to maintain state between executions.
timer$.interface.timer

Trigger Authentication

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

Make sure you're logged into the Drata UI, then see these docs to create a Drata API key. Enter it below.

About Drata

Drata automates your compliance journey from start to audit-ready and beyond and provides support from the security and compliance experts who built it.

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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