Create an AI custom rule revision

"""
Create an AI custom rule revision returns "Successfully created" response
"""

from os import environ
from datadog_api_client import ApiClient, Configuration
from datadog_api_client.v2.api.static_analysis_api import StaticAnalysisApi
from datadog_api_client.v2.model.ai_custom_rule_revision_data_type import AiCustomRuleRevisionDataType
from datadog_api_client.v2.model.ai_custom_rule_revision_execution_mode import AiCustomRuleRevisionExecutionMode
from datadog_api_client.v2.model.ai_custom_rule_revision_request import AiCustomRuleRevisionRequest
from datadog_api_client.v2.model.ai_custom_rule_revision_request_attributes import AiCustomRuleRevisionRequestAttributes
from datadog_api_client.v2.model.ai_custom_rule_revision_request_data import AiCustomRuleRevisionRequestData
from datadog_api_client.v2.model.custom_rule_revision_attributes_category import CustomRuleRevisionAttributesCategory
from datadog_api_client.v2.model.custom_rule_revision_attributes_severity import CustomRuleRevisionAttributesSeverity

body = AiCustomRuleRevisionRequest(
    data=AiCustomRuleRevisionRequestData(
        attributes=AiCustomRuleRevisionRequestAttributes(
            category=CustomRuleRevisionAttributesCategory.SECURITY,
            content="Content",
            cwe="79",
            description="Ruleset description",
            directories=[],
            execution_mode=AiCustomRuleRevisionExecutionMode.AUTO,
            globs=[
                "**/*.py",
            ],
            is_published=False,
            is_testing=False,
            severity=CustomRuleRevisionAttributesSeverity.ERROR,
            short_description="Ruleset short description",
            version_id=1,
        ),
        id="revision-abc-123",
        type=AiCustomRuleRevisionDataType.AI_RULE_REVISION,
    ),
)

configuration = Configuration()
configuration.access_token = environ["DD_BEARER_TOKEN"]
configuration.unstable_operations["create_ai_custom_rule_revision"] = True
with ApiClient(configuration) as api_client:
    api_instance = StaticAnalysisApi(api_client)
    api_instance.create_ai_custom_rule_revision(ruleset_name="my-ai-ruleset", rule_name="my-ai-rule", body=body)

# Create an AI custom rule revision returns "Successfully created" response

require "datadog_api_client"
DatadogAPIClient.configure do |config|
  config.access_token = ENV["DD_BEARER_TOKEN"]
  config.unstable_operations["v2.create_ai_custom_rule_revision".to_sym] = true
end
api_instance = DatadogAPIClient::V2::StaticAnalysisAPI.new

body = DatadogAPIClient::V2::AiCustomRuleRevisionRequest.new({
  data: DatadogAPIClient::V2::AiCustomRuleRevisionRequestData.new({
    attributes: DatadogAPIClient::V2::AiCustomRuleRevisionRequestAttributes.new({
      category: DatadogAPIClient::V2::CustomRuleRevisionAttributesCategory::SECURITY,
      content: "Content",
      cwe: "79",
      description: "Ruleset description",
      directories: [],
      execution_mode: DatadogAPIClient::V2::AiCustomRuleRevisionExecutionMode::AUTO,
      globs: [
        "**/*.py",
      ],
      is_published: false,
      is_testing: false,
      severity: DatadogAPIClient::V2::CustomRuleRevisionAttributesSeverity::ERROR,
      short_description: "Ruleset short description",
      version_id: 1,
    }),
    id: "revision-abc-123",
    type: DatadogAPIClient::V2::AiCustomRuleRevisionDataType::AI_RULE_REVISION,
  }),
})
p api_instance.create_ai_custom_rule_revision("my-ai-ruleset", "my-ai-rule", body)

// Create an AI custom rule revision returns "Successfully created" response

package main

import (
	"context"
	"fmt"
	"os"

	"github.com/DataDog/datadog-api-client-go/v2/api/datadog"
	"github.com/DataDog/datadog-api-client-go/v2/api/datadogV2"
)

func main() {
	body := datadogV2.AiCustomRuleRevisionRequest{
		Data: &datadogV2.AiCustomRuleRevisionRequestData{
			Attributes: &datadogV2.AiCustomRuleRevisionRequestAttributes{
				Category:      datadogV2.CUSTOMRULEREVISIONATTRIBUTESCATEGORY_SECURITY,
				Content:       "Content",
				Cwe:           *datadog.NewNullableString(datadog.PtrString("79")),
				Description:   "Ruleset description",
				Directories:   []string{},
				ExecutionMode: datadogV2.AICUSTOMRULEREVISIONEXECUTIONMODE_AUTO,
				Globs: []string{
					"**/*.py",
				},
				IsPublished:      false,
				IsTesting:        false,
				Severity:         datadogV2.CUSTOMRULEREVISIONATTRIBUTESSEVERITY_ERROR,
				ShortDescription: "Ruleset short description",
				VersionId:        datadog.PtrInt64(1),
			},
			Id:   datadog.PtrString("revision-abc-123"),
			Type: datadogV2.AICUSTOMRULEREVISIONDATATYPE_AI_RULE_REVISION.Ptr(),
		},
	}
	ctx := datadog.NewDefaultContext(context.Background())
	ctx = context.WithValue(ctx, datadog.ContextAccessToken, os.Getenv("DD_BEARER_TOKEN"))
	configuration := datadog.NewConfiguration()
	configuration.SetUnstableOperationEnabled("v2.CreateAiCustomRuleRevision", true)
	apiClient := datadog.NewAPIClient(configuration)
	api := datadogV2.NewStaticAnalysisApi(apiClient)
	r, err := api.CreateAiCustomRuleRevision(ctx, "my-ai-ruleset", "my-ai-rule", body)

	if err != nil {
		fmt.Fprintf(os.Stderr, "Error when calling `StaticAnalysisApi.CreateAiCustomRuleRevision`: %v\n", err)
		fmt.Fprintf(os.Stderr, "Full HTTP response: %v\n", r)
	}
}

// Create an AI custom rule revision returns "Successfully created" response

import com.datadog.api.client.ApiClient;
import com.datadog.api.client.ApiException;
import com.datadog.api.client.v2.api.StaticAnalysisApi;
import com.datadog.api.client.v2.model.AiCustomRuleRevisionDataType;
import com.datadog.api.client.v2.model.AiCustomRuleRevisionExecutionMode;
import com.datadog.api.client.v2.model.AiCustomRuleRevisionRequest;
import com.datadog.api.client.v2.model.AiCustomRuleRevisionRequestAttributes;
import com.datadog.api.client.v2.model.AiCustomRuleRevisionRequestData;
import com.datadog.api.client.v2.model.CustomRuleRevisionAttributesCategory;
import com.datadog.api.client.v2.model.CustomRuleRevisionAttributesSeverity;
import java.util.Collections;

public class Example {
  public static void main(String[] args) {
    ApiClient defaultClient = ApiClient.getDefaultApiClient();
    defaultClient.setAccessToken(System.getenv("DD_BEARER_TOKEN"));
    defaultClient.setUnstableOperationEnabled("v2.createAiCustomRuleRevision", true);
    StaticAnalysisApi apiInstance = new StaticAnalysisApi(defaultClient);

    AiCustomRuleRevisionRequest body =
        new AiCustomRuleRevisionRequest()
            .data(
                new AiCustomRuleRevisionRequestData()
                    .attributes(
                        new AiCustomRuleRevisionRequestAttributes()
                            .category(CustomRuleRevisionAttributesCategory.SECURITY)
                            .content("Content")
                            .cwe("79")
                            .description("Ruleset description")
                            .executionMode(AiCustomRuleRevisionExecutionMode.AUTO)
                            .globs(Collections.singletonList("**/*.py"))
                            .isPublished(false)
                            .isTesting(false)
                            .severity(CustomRuleRevisionAttributesSeverity.ERROR)
                            .shortDescription("Ruleset short description")
                            .versionId(1L))
                    .id("revision-abc-123")
                    .type(AiCustomRuleRevisionDataType.AI_RULE_REVISION));

    try {
      apiInstance.createAiCustomRuleRevision("my-ai-ruleset", "my-ai-rule", body);
    } catch (ApiException e) {
      System.err.println("Exception when calling StaticAnalysisApi#createAiCustomRuleRevision");
      System.err.println("Status code: " + e.getCode());
      System.err.println("Reason: " + e.getResponseBody());
      System.err.println("Response headers: " + e.getResponseHeaders());
      e.printStackTrace();
    }
  }
}

// Create an AI custom rule revision returns "Successfully created" response
use datadog_api_client::datadog;
use datadog_api_client::datadogV2::api_static_analysis::StaticAnalysisAPI;
use datadog_api_client::datadogV2::model::AiCustomRuleRevisionDataType;
use datadog_api_client::datadogV2::model::AiCustomRuleRevisionExecutionMode;
use datadog_api_client::datadogV2::model::AiCustomRuleRevisionRequest;
use datadog_api_client::datadogV2::model::AiCustomRuleRevisionRequestAttributes;
use datadog_api_client::datadogV2::model::AiCustomRuleRevisionRequestData;
use datadog_api_client::datadogV2::model::CustomRuleRevisionAttributesCategory;
use datadog_api_client::datadogV2::model::CustomRuleRevisionAttributesSeverity;

#[tokio::main]
async fn main() {
    let body = AiCustomRuleRevisionRequest::new().data(
        AiCustomRuleRevisionRequestData::new()
            .attributes(
                AiCustomRuleRevisionRequestAttributes::new(
                    CustomRuleRevisionAttributesCategory::SECURITY,
                    "Content".to_string(),
                    "Ruleset description".to_string(),
                    vec![],
                    AiCustomRuleRevisionExecutionMode::AUTO,
                    vec!["**/*.py".to_string()],
                    false,
                    false,
                    CustomRuleRevisionAttributesSeverity::ERROR,
                    "Ruleset short description".to_string(),
                )
                .cwe(Some("79".to_string()))
                .version_id(1),
            )
            .id("revision-abc-123".to_string())
            .type_(AiCustomRuleRevisionDataType::AI_RULE_REVISION),
    );
    let mut configuration = datadog::Configuration::new();
    configuration.set_unstable_operation_enabled("v2.CreateAiCustomRuleRevision", true);
    let api = StaticAnalysisAPI::with_config(configuration);
    let resp = api
        .create_ai_custom_rule_revision("my-ai-ruleset".to_string(), "my-ai-rule".to_string(), body)
        .await;
    if let Ok(value) = resp {
        println!("{:#?}", value);
    } else {
        println!("{:#?}", resp.unwrap_err());
    }
}

/**
 * Create an AI custom rule revision returns "Successfully created" response
 */

import { client, v2 } from "@datadog/datadog-api-client";

const configuration = client.createConfiguration({
  authMethods: {
    AuthZ: {
      accessToken: process.env.DD_BEARER_TOKEN as string,
    },
  },
});
configuration.unstableOperations["v2.createAiCustomRuleRevision"] = true;
const apiInstance = new v2.StaticAnalysisApi(configuration);

const params: v2.StaticAnalysisApiCreateAiCustomRuleRevisionRequest = {
  body: {
    data: {
      attributes: {
        category: "SECURITY",
        content: "Content",
        cwe: "79",
        description: "Ruleset description",
        directories: [],
        executionMode: "auto",
        globs: ["**/*.py"],
        isPublished: false,
        isTesting: false,
        severity: "ERROR",
        shortDescription: "Ruleset short description",
        versionId: 1,
      },
      id: "revision-abc-123",
      type: "ai_rule_revision",
    },
  },
  rulesetName: "my-ai-ruleset",
  ruleName: "my-ai-rule",
};

apiInstance
  .createAiCustomRuleRevision(params)
  .then((data: any) => {
    console.log(
      "API called successfully. Returned data: " + JSON.stringify(data)
    );
  })
  .catch((error: any) => console.error(error));