Chat with Anthropic (Claude) API on New Evidence for Control Added from Drata API

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New Evidence for Control Added from the Drata API

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Getting Started#

This integration creates a workflow with a Drata trigger and Anthropic (Claude) action. When you configure and deploy the workflow, it will run on Pipedream's servers 24x7 for free.

Select this integration
Configure the New Evidence for Control Added trigger
1. Connect your Drata account
2. Configure timer
3. Select a Control ID
Configure the Chat action
1. Connect your Anthropic (Claude) account
2. Select a Model
3. Configure User Message
4. Optional- Configure Prior Message History
5. Optional- Configure Temperature
6. Optional- Configure Top K
7. Optional- Configure Top P
8. Configure Maximum Tokens To Sample
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 Evidence for Control Added on Drata

Description:Emit a new event for every new evidence for a control. [See the documentation](https://developers.drata.com/docs/openapi/reference/operation/GRCPublicController_getMappedExternalEvidence/#tag/Controls/operation/GRCPublicController_getMappedExternalEvidence).

Version:0.0.3

Key:drata-new-evidence-added

View on GitHub

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

const docsLink = "https://developers.drata.com/docs/openapi/reference/operation/GRCPublicController_getMappedExternalEvidence/#tag/Controls/operation/GRCPublicController_getMappedExternalEvidence";

export default {
  key: "drata-new-evidence-added",
  name: "New Evidence for Control Added",
  description: `Emit a new event for every new evidence for a control. [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,
      },
    },
    controlId: {
      propDefinition: [
        drata,
        "controlId",
      ],
    },
  },
  hooks: {
    async deploy() {
      console.log(this.controlId);
      const response = await this.drata.listEvidencesForControl({
        controlId: this.controlId,
        paginate: true,
        // this endpoint does not support custom sorting. It sorts by name
        params: {
          limit: constants.DEPLOY_LIMIT,
        },
      });

      this._setVisitedIds(response.data.map((evidence) => evidence.id));
      for (const evidence of response.data.slice(-constants.DEPLOY_LIMIT)) {
        this.$emit(evidence, {
          id: evidence.id,
          summary: `Historical evidence added event: ${evidence.name}`,
          ts: new Date(),
        });
      }
    },
  },
  methods: {
    _getVisitedIds() {
      return new Set(this.db.get("visitedIds"));
    },
    _setVisitedIds(visitedIds) {
      this.db.set("visitedIds", Array.from(visitedIds));
    },
  },
  async run() {
    const visitedIds = this._getVisitedIds();

    const response = await this.drata.listEvidencesForControl({
      controlId: this.controlId,
      paginate: true,
      params: {
        limit: constants.PAGINATION_LIMIT,
      },
    });

    for (const evidence of response.data) {
      if (!visitedIds.has(evidence.id)) {
        visitedIds.add(evidence.id);
        this.$emit(evidence, {
          id: evidence.id,
          summary: `New evidence added: ${evidence.name}`,
          ts: new Date(),
        });
      }
    }

    this._setVisitedIds(visitedIds);
  },
};

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
Drata	`drata`	`app`	This component uses the Drata app.
N/A	`db`	`$.service.db`	This component uses `$.service.db` to maintain state between executions.
	`timer`	`$.interface.timer`
Control ID	`controlId`	`integer`	Select a value from the drop down menu.

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#

Chat on Anthropic (Claude)

Description:The Chat API. [See the documentation](https://docs.anthropic.com/claude/reference/messages_post)

Version:0.1.0

Key:anthropic-chat

View on GitHub

Anthropic (Claude) Overview#

The Anthropic (Claude) API offers a conversational AI that can be leveraged for a variety of applications, ranging from answering questions to generating content or providing customer support. In Pipedream, you can create powerful workflows that utilize the capabilities of Claude to automate responses, analyze text, or enhance data with AI-generated insights. Pipedream's serverless platform simplifies integrating Claude into your processes with other apps and services for seamless automation.

Action Code#

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

export default {
  name: "Chat",
  version: "0.1.0",
  key: "anthropic-chat",
  description: "The Chat API. [See the documentation](https://docs.anthropic.com/claude/reference/messages_post)",
  type: "action",
  props: {
    anthropic,
    model: {
      label: "Model",
      description: "Select the model to use for your query. Defaults to the latest Claude model - [see the documentation](https://docs.anthropic.com/en/docs/about-claude/models/overview) for more information",
      type: "string",
      options: constants.MESSAGE_MODELS,
      default: constants.MESSAGE_MODELS[0].value,
    },
    userMessage: {
      label: "User Message",
      type: "string",
      description: "The user messages provide instructions to the assistant",
    },
    messages: {
      label: "Prior Message History",
      type: "string[]",
      description: "All relevant information must be supplied via the conversation. You can provide an array of messages from prior conversations here always beginning with the human message.",
      optional: true,
    },
    temperature: {
      label: "Temperature",
      description: "**Optional**. Amount of randomness injected into the response. Ranges from 0 to 1. Use temp closer to 0 for analytical / multiple choice, and temp closer to 1 for creative and generative tasks.",
      type: "string",
      optional: true,
    },
    topK: {
      label: "Top K",
      description: "Only sample from the top K options for each subsequent token. Used to remove `long tail` low probability responses.",
      type: "integer",
      optional: true,
    },
    topP: {
      label: "Top P",
      description: "Does nucleus sampling, in which we compute the cumulative distribution over all the options for each subsequent token in decreasing probability order and cut it off once it reaches a particular probability specified.",
      type: "string",
      optional: true,
    },
    maxTokensToSample: {
      label: "Maximum Tokens To Sample",
      description: "A maximum number of tokens to generate before stopping.",
      type: "integer",
    },
  },
  async run({ $ }) {
    const messages = [];

    const priorMessages = typeof this.messages === "string"
      ? JSON.parse(this.messages)
      : this.messages;

    if (priorMessages?.length) {
      let isUserMessage = true;

      for (const message of priorMessages) {
        messages.push({
          role: isUserMessage
            ? "user"
            : "assistant",
          content: message,
        });

        isUserMessage = !isUserMessage;
      }
    }

    messages.push({
      role: "user",
      content: this.userMessage,
    });

    const response = await this.anthropic.createMessage({
      $,
      data: {
        messages,
        model: this.model,
        max_tokens: this.maxTokensToSample,
        temperature: this.temperature
          ? parseFloat(this.temperature)
          : undefined,
        top_p: this.topP
          ? parseFloat(this.topP)
          : undefined,
        top_k: this.topK,
      },
    });

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

    const originalMessages = messages.map(({ content }) => content);
    return {
      original_messages: originalMessages,
      original_messages_with_assistant_response: originalMessages.concat(response.content[0].text),
      ...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.

Label	Prop	Type	Description
Anthropic (Claude)	`anthropic`	`app`	This component uses the Anthropic (Claude) app.
Model	`model`	`string`	Select a value from the drop down menu:`{ "label": "Claude Opus 4", "value": "claude-opus-4-20250514" }{ "label": "Claude Sonnet 4", "value": "claude-sonnet-4-20250514" }{ "label": "Claude Sonnet 3.7", "value": "claude-3-7-sonnet-20250219" }{ "label": "Claude Sonnet 3.5 v2", "value": "claude-3-5-sonnet-20241022" }{ "label": "Claude Haiku 3.5", "value": "claude-3-5-haiku-20241022" }{ "label": "Claude Sonnet 3.5", "value": "claude-3-5-sonnet-20240620" }{ "label": "Claude Opus 3", "value": "claude-3-opus-20240229" }{ "label": "Claude Sonnet 3", "value": "claude-3-sonnet-20240229" }{ "label": "Claude Haiku 3", "value": "claude-3-haiku-20240307" }`
User Message	`userMessage`	`string`	The user messages provide instructions to the assistant
Prior Message History	`messages`	`string[]`	All relevant information must be supplied via the conversation. You can provide an array of messages from prior conversations here always beginning with the human message.
Temperature	`temperature`	`string`	Optional. Amount of randomness injected into the response. Ranges from 0 to 1. Use temp closer to 0 for analytical / multiple choice, and temp closer to 1 for creative and generative tasks.
Top K	`topK`	`integer`	Only sample from the top K options for each subsequent token. Used to remove `long tail` low probability responses.
Top P	`topP`	`string`	Does nucleus sampling, in which we compute the cumulative distribution over all the options for each subsequent token in decreasing probability order and cut it off once it reaches a particular probability specified.
Maximum Tokens To Sample	`maxTokensToSample`	`integer`	A maximum number of tokens to generate before stopping.

Chat with Anthropic (Claude) API on New Evidence for Control Added from Drata API

Pipedream makes it easy to connect APIs for Anthropic (Claude), Drata and 2,700+ other apps remarkably fast.

Trusted by 1,000,000+ developers from startups to Fortune 500 companies

Developers ♥ Pipedream

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