Adding reprovision integration tests

src/main/java/org/opensearch/flowframework/model/Template.java

@@ -8,12 +8,12 @@
  */
 package org.opensearch.flowframework.model;
 
-import org.apache.logging.log4j.util.Strings;
 import org.opensearch.Version;
 import org.opensearch.common.xcontent.LoggingDeprecationHandler;
 import org.opensearch.common.xcontent.json.JsonXContent;
 import org.opensearch.common.xcontent.yaml.YamlXContent;
 import org.opensearch.commons.authuser.User;
+import org.opensearch.core.common.Strings;
 import org.opensearch.core.rest.RestStatus;
 import org.opensearch.core.xcontent.NamedXContentRegistry;
 import org.opensearch.core.xcontent.ToXContentObject;
@@ -372,10 +372,10 @@ public static Template updateExistingTemplate(Template existingTemplate, Templat
         if (templateWithNewFields.name() != null) {
             builder.name(templateWithNewFields.name());
         }
-        if (!Strings.isBlank(templateWithNewFields.description())) {
+        if (Strings.hasText(templateWithNewFields.description())) {
             builder.description(templateWithNewFields.description());
         }
-        if (!Strings.isBlank(templateWithNewFields.useCase())) {
+        if (Strings.hasText(templateWithNewFields.useCase())) {
             builder.useCase(templateWithNewFields.useCase());
         }
         if (templateWithNewFields.templateVersion() != null) {

src/test/java/org/opensearch/flowframework/FlowFrameworkRestTestCase.java

@@ -415,6 +415,25 @@ protected Response createWorkflowValidation(RestClient client, Template template
         return TestHelpers.makeRequest(client, "POST", WORKFLOW_URI, Collections.emptyMap(), template.toJson(), null);
     }
 
+    /**
+     * Helper method to invoke the Reprovision Workflow API
+     * @param client the rest client
+     * @param workflowId the document id
+     * @param templateFields the template to reprovision
+     * @throws Exception if the request fails
+     * @return a rest response
+     */
+    protected Response reprovisionWorkflow(RestClient client, String workflowId, Template template) throws Exception {
+        return TestHelpers.makeRequest(
+            client,
+            "PUT",
+            String.format(Locale.ROOT, "%s/%s?reprovision=true", WORKFLOW_URI, workflowId),
+            Collections.emptyMap(),
+            template.toJson(),
+            null
+        );
+    }
+
     /**
      * Helper method to invoke the Update Workflow API
      * @param client the rest client

src/test/java/org/opensearch/flowframework/TestHelpers.java

@@ -11,7 +11,6 @@
 import org.apache.hc.core5.http.Header;
 import org.apache.hc.core5.http.HttpEntity;
 import org.apache.hc.core5.http.io.entity.StringEntity;
-import org.apache.logging.log4j.util.Strings;
 import org.opensearch.client.Request;
 import org.opensearch.client.RequestOptions;
 import org.opensearch.client.Response;
@@ -24,6 +23,7 @@
 import org.opensearch.common.xcontent.XContentHelper;
 import org.opensearch.common.xcontent.XContentType;
 import org.opensearch.commons.authuser.User;
+import org.opensearch.core.common.Strings;
 import org.opensearch.core.common.bytes.BytesReference;
 import org.opensearch.core.rest.RestStatus;
 import org.opensearch.core.xcontent.ToXContent;
@@ -74,7 +74,7 @@ public static Response makeRequest(
         String jsonEntity,
         List<Header> headers
     ) throws IOException {
-        HttpEntity httpEntity = Strings.isBlank(jsonEntity) ? null : new StringEntity(jsonEntity, APPLICATION_JSON);
+        HttpEntity httpEntity = !Strings.hasText(jsonEntity) ? null : new StringEntity(jsonEntity, APPLICATION_JSON);
         return makeRequest(client, method, endpoint, params, httpEntity, headers);
     }
 

src/test/resources/template/registerremotemodel-createindex.json

@@ -0,0 +1,84 @@
+{
+    "name": "semantic search with local pretrained model",
+    "description": "Setting up semantic search, with a local pretrained embedding model",
+    "use_case": "SEMANTIC_SEARCH",
+    "version": {
+      "template": "1.0.0",
+      "compatibility": [
+        "2.12.0",
+        "3.0.0"
+      ]
+    },
+    "workflows": {
+      "provision": {
+        "nodes": [
+          {
+            "id": "create_openai_connector",
+            "type": "create_connector",
+            "user_inputs": {
+              "name": "OpenAI Chat Connector",
+              "description": "The connector to public OpenAI model service for text embedding model",
+              "version": "1",
+              "protocol": "http",
+              "parameters": {
+                "endpoint": "api.openai.com",
+                "model": "gpt-3.5-turbo",
+                "response_filter": "$.choices[0].message.content"
+              },
+              "credential": {
+                "openAI_key": "12345"
+              },
+              "actions": [
+                {
+                  "action_type": "predict",
+                  "method": "POST",
+                  "url": "https://${parameters.endpoint}/v1/chat/completions"
+                }
+              ]
+            }
+          },
+          {
+            "id": "register_openai_model",
+            "type": "register_remote_model",
+            "previous_node_inputs": {
+              "create_openai_connector": "connector_id"
+            },
+            "user_inputs": {
+              "name": "openAI-gpt-3.5-turbo",
+              "deploy": true
+            }
+          },
+          {
+            "id": "create_index",
+            "type": "create_index",
+            "user_inputs": {
+              "index_name": "my-nlp-index",
+              "configurations": {
+                "settings": {
+                  "index.knn": true,
+                  "index.number_of_shards": "2"
+                },
+                "mappings": {
+                  "properties": {
+                    "passage_embedding": {
+                      "type": "knn_vector",
+                      "dimension": "768",
+                      "method": {
+                        "engine": "lucene",
+                        "space_type": "l2",
+                        "name": "hnsw",
+                        "parameters": {}
+                      }
+                    },
+                    "passage_text": {
+                      "type": "text"
+                    }
+                  }
+                }
+              }
+            }
+          }
+        ]
+      }
+    }
+  }

src/test/resources/template/registerremotemodel-ingestpipeline-createindex.json

@@ -0,0 +1,111 @@
+{
+  "name": "semantic search with local pretrained model",
+  "description": "Setting up semantic search, with a local pretrained embedding model",
+  "use_case": "SEMANTIC_SEARCH",
+  "version": {
+    "template": "1.0.0",
+    "compatibility": [
+      "2.12.0",
+      "3.0.0"
+    ]
+  },
+  "workflows": {
+    "provision": {
+      "nodes": [
+        {
+          "id": "create_openai_connector",
+          "type": "create_connector",
+          "user_inputs": {
+            "name": "OpenAI Chat Connector",
+            "description": "The connector to public OpenAI model service for text embedding model",
+            "version": "1",
+            "protocol": "http",
+            "parameters": {
+              "endpoint": "api.openai.com",
+              "model": "gpt-3.5-turbo",
+              "response_filter": "$.choices[0].message.content"
+            },
+            "credential": {
+              "openAI_key": "12345"
+            },
+            "actions": [
+              {
+                "action_type": "predict",
+                "method": "POST",
+                "url": "https://${parameters.endpoint}/v1/chat/completions"
+              }
+            ]
+          }
+        },
+        {
+          "id": "register_openai_model",
+          "type": "register_remote_model",
+          "previous_node_inputs": {
+            "create_openai_connector": "connector_id"
+          },
+          "user_inputs": {
+            "name": "openAI-gpt-3.5-turbo",
+            "deploy": true
+          }
+        },
+        {
+          "id": "create_ingest_pipeline",
+          "type": "create_ingest_pipeline",
+          "previous_node_inputs": {
+            "register_openai_model": "model_id"
+          },
+          "user_inputs": {
+            "pipeline_id": "nlp-ingest-pipeline",
+            "configurations": {
+              "description": "A text embedding pipeline",
+              "processors": [
+                {
+                  "text_embedding": {
+                    "model_id": "${{register_openai_model.model_id}}",
+                    "field_map": {
+                      "passage_text": "passage_embedding"
+                    }
+                  }
+                }
+              ]
+            }
+          }
+        },
+        {
+          "id": "create_index",
+          "type": "create_index",
+          "previous_node_inputs": {
+            "create_ingest_pipeline": "pipeline_id"
+          },
+          "user_inputs": {
+            "index_name": "my-nlp-index",
+            "configurations": {
+              "settings": {
+                "index.knn": true,
+                "default_pipeline": "${{create_ingest_pipeline.pipeline_id}}",
+                "index.number_of_shards": "2"
+              },
+              "mappings": {
+                "properties": {
+                  "passage_embedding": {
+                    "type": "knn_vector",
+                    "dimension": "768",
+                    "method": {
+                      "engine": "lucene",
+                      "space_type": "l2",
+                      "name": "hnsw",
+                      "parameters": {}
+                    }
+                  },
+                  "passage_text": {
+                    "type": "text"
+                  }
+                }
+              }
+            }
+          }
+        }
+      ]
+    }
+  }
+}

src/test/resources/template/registerremotemodel-ingestpipeline-updateindex.json

@@ -0,0 +1,111 @@
+{
+  "name": "semantic search with local pretrained model",
+  "description": "Setting up semantic search, with a local pretrained embedding model",
+  "use_case": "SEMANTIC_SEARCH",
+  "version": {
+    "template": "1.0.0",
+    "compatibility": [
+      "2.12.0",
+      "3.0.0"
+    ]
+  },
+  "workflows": {
+    "provision": {
+      "nodes": [
+        {
+          "id": "create_openai_connector",
+          "type": "create_connector",
+          "user_inputs": {
+            "name": "OpenAI Chat Connector",
+            "description": "The connector to public OpenAI model service for text embedding model",
+            "version": "1",
+            "protocol": "http",
+            "parameters": {
+              "endpoint": "api.openai.com",
+              "model": "gpt-3.5-turbo",
+              "response_filter": "$.choices[0].message.content"
+            },
+            "credential": {
+              "openAI_key": "12345"
+            },
+            "actions": [
+              {
+                "action_type": "predict",
+                "method": "POST",
+                "url": "https://${parameters.endpoint}/v1/chat/completions"
+              }
+            ]
+          }
+        },
+        {
+          "id": "register_openai_model",
+          "type": "register_remote_model",
+          "previous_node_inputs": {
+            "create_openai_connector": "connector_id"
+          },
+          "user_inputs": {
+            "name": "openAI-gpt-3.5-turbo",
+            "deploy": true
+          }
+        },
+        {
+          "id": "create_ingest_pipeline",
+          "type": "create_ingest_pipeline",
+          "previous_node_inputs": {
+            "register_openai_model": "model_id"
+          },
+          "user_inputs": {
+            "pipeline_id": "nlp-ingest-pipeline",
+            "configurations": {
+              "description": "A text embedding pipeline",
+              "processors": [
+                {
+                  "text_embedding": {
+                    "model_id": "${{register_openai_model.model_id}}",
+                    "field_map": {
+                      "passage_text": "passage_embedding"
+                    }
+                  }
+                }
+              ]
+            }
+          }
+        },
+        {
+          "id": "create_index",
+          "type": "create_index",
+          "previous_node_inputs": {
+            "create_ingest_pipeline": "pipeline_id"
+          },
+          "user_inputs": {
+            "index_name": "my-nlp-index",
+            "configurations": {
+              "settings": {
+                "index.knn": true,
+                "default_pipeline": "_none",
+                "index.number_of_shards": "2"
+              },
+              "mappings": {
+                "properties": {
+                  "passage_embedding": {
+                    "type": "knn_vector",
+                    "dimension": "768",
+                    "method": {
+                      "engine": "lucene",
+                      "space_type": "l2",
+                      "name": "hnsw",
+                      "parameters": {}
+                    }
+                  },
+                  "passage_text": {
+                    "type": "text"
+                  }
+                }
+              }
+            }
+          }
+        }
+      ]
+    }
+  }
+}