Merge remote-tracking branch 'origin/main' into openshift-ai-integration

Author: Jan-Kazlouski-elastic

compiler/src/steps/validate-model.ts

@@ -45,14 +45,10 @@ const privateNamespaces = ['_internal', 'profiling']
  * Any inconsistency is logged as an error.
  *
  * Missing validations:
- * - verify uniqueness of property names in the inheritance chain
  * - verify that request parents don't define properties (would they be path/request/body properties?)
  * - verify that unions can be distinguished in a JSON stream (otherwise they should be inheritance trees)
  */
 export default async function validateModel (apiModel: model.Model, restSpec: Map<string, JsonSpec>, errors: ValidationErrors): Promise<model.Model> {
-  // Fail hard if the FAIL_HARD env var is defined
-  const failHard = process.env.FAIL_HARD != null
-
   const initialTypeCount = apiModel.types.length
 
   // Returns the fully-qualified name of a type name
@@ -87,13 +83,20 @@ export default async function validateModel (apiModel: model.Model, restSpec: Ma
   function modelError (msg: string): void {
     const fullMsg = (context.length === 0) ? msg : context.join(' / ') + ' - ' + msg
 
+    let ignored = false
     if (currentEndpoint != null) {
-      errors.addEndpointError(currentEndpoint, currentPart, fullMsg)
+      ignored = errors.addEndpointError(currentEndpoint, currentPart, fullMsg)
+      if (!ignored) {
+        console.error(currentEndpoint, currentPart, fullMsg)
+      }
     } else {
       errors.addGeneralError(fullMsg)
+      console.error(fullMsg)
     }
 
-    errorCount++
+    if (!ignored) {
+      errorCount++
+    }
   }
 
   // ----- Type definition management
@@ -206,8 +209,8 @@ export default async function validateModel (apiModel: model.Model, restSpec: Ma
   const danglingTypesCount = initialTypeCount - apiModel.types.length
   console.info(`Model validation: ${typesSeen.size} types visited, ${danglingTypesCount} dangling types.`)
 
-  if (errorCount > 0 && failHard) {
-    throw new Error('Model is inconsistent. Check logs for details')
+  if (errorCount > 0) {
+    throw new Error('Model is inconsistent.')
   }
 
   return apiModel

compiler/src/validation-errors.ts

@@ -38,9 +38,9 @@ export class ValidationErrors {
   }
 
   /** Add some error information relative to an endpoint's request or response */
-  addEndpointError (endpoint: string, part: 'request' | 'response', message: string): void {
+  addEndpointError (endpoint: string, part: 'request' | 'response', message: string): boolean {
     if (IGNORED_ERRORS.includes(message)) {
-      return
+      return true
     }
 
     let error = this.endpointErrors[endpoint]
@@ -50,6 +50,7 @@ export class ValidationErrors {
     }
 
     error[part].push(message)
+    return false
   }
 
   /** Add a general error, unrelated to an endpoint */

output/openapi/elasticsearch-openapi.json

@@ -1,7 +1,6 @@
 {
   "endpointErrors": {},
   "generalErrors": [
-    "ResponseBody is present in multiple namespaces: _global.search and ml.evaluate_data_frame",
     "Dangling type '_global.scripts_painless_execute:PainlessExecutionPosition'",
     "Dangling type '_global.scripts_painless_execute:PainlessScript'",
     "Dangling type '_global.search._types:HitMetadata'",

output/openapi/elasticsearch-serverless-openapi.json

@@ -24,24 +24,20 @@ import {
 } from './types'
 
 export class Response {
-  /** @codegen_name result */
-  body: ResponseBody
-}
-
-/** @variants container */
-export class ResponseBody {
-  /**
-   * Evaluation results for a classification analysis.
-   * It outputs a prediction that identifies to which of the classes each document belongs.
-   */
-  classification?: DataframeClassificationSummary
-  /**
-   * Evaluation results for an outlier detection analysis.
-   * It outputs the probability that each document is an outlier.
-   */
-  outlier_detection?: DataframeOutlierDetectionSummary
-  /**
-   * Evaluation results for a regression analysis which outputs a prediction of values.
-   */
-  regression?: DataframeRegressionSummary
+  body: {
+    /**
+     * Evaluation results for a classification analysis.
+     * It outputs a prediction that identifies to which of the classes each document belongs.
+     */
+    classification?: DataframeClassificationSummary
+    /**
+     * Evaluation results for an outlier detection analysis.
+     * It outputs the probability that each document is an outlier.
+     */
+    outlier_detection?: DataframeOutlierDetectionSummary
+    /**
+     * Evaluation results for a regression analysis which outputs a prediction of values.
+     */
+    regression?: DataframeRegressionSummary
+  }
 }