Summarization API for 2022-10-01-preview

dev/cognitiveservices/data-plane/Language/analyzeconversations.json

@@ -3,7 +3,7 @@
   "info": {
     "title": "Microsoft Cognitive Language Service - Analyze Conversations",
     "description": "The language service conversations API is a suite of natural language processing (NLP) skills that can be used to analyze structured conversations (textual or spoken). The synchronous API in this suite accepts a request and mediates among multiple language projects, such as LUIS Generally Available, Question Answering, Conversational Language Understanding, and then calls the best candidate service to handle the request. At last, it returns a response with the candidate service's response as a payload.\n\n In some cases, this API needs to forward requests and responses between the caller and an upstream service. The asynchronous APIs in this suite enable tasks like Conversation Summarization and Conversational PII detection.",
-    "version": "2022-07-01-preview"
+    "version": "2022-10-01-preview"
   },
   "securityDefinitions": {
     "apim_key": {
@@ -132,6 +132,9 @@
           },
           "Successful Conversation Summarization Analysis Job Request": {
             "$ref": "./examples/conversations/SuccessfulConversationSummarySubmit.json"
+          },
+          "Successful Conversation Summarization Task Submit": {
+            "$ref": "./examples/conversations/SuccessfulConversationSummarizationTaskSubmit.json"
           }
         },
         "x-ms-long-running-operation": true
@@ -176,6 +179,9 @@
           },
           "Successful Get Text Conversation Analysis Job Status Request": {
             "$ref": "./examples/conversations/SuccessfulConversationSummarizationTaskStatusRequest.json"
+          },
+          "Successful Get Conversation Summarization Result": {
+            "$ref": "./examples/conversations/SuccessfulConversationSummarizationTaskResult.json"
           }
         }
       }
@@ -1732,7 +1738,7 @@
       "properties": {
         "itn": {
           "type": "string",
-          "description": "Inverse Text Normalization representation of input. The inverse-text-normalized form is the recognized text from Microsoft’s Speech to Text API, with phone numbers, numbers, abbreviations, and other transformations applied."
+          "description": "Inverse Text Normalization representation of input. The inverse-text-normalized form is the recognized text from Microsoft's Speech to Text API, with phone numbers, numbers, abbreviations, and other transformations applied."
         },
         "maskedItn": {
           "type": "string",
@@ -1752,6 +1758,10 @@
           "items": {
             "$ref": "#/definitions/WordLevelTiming"
           }
+        },
+        "audioTiming": {
+          "description": "Conversation item level audio timing. This still can help on AI quality if word level audio timings are not available.",
+          "$ref": "#/definitions/AudioTiming"
         }
       }
     },
@@ -2004,18 +2014,41 @@
             "type": "string",
             "enum": [
               "issue",
-              "resolution"
+              "resolution",
+              "chapterTitle",
+              "generic"
             ],
             "x-ms-enum": {
               "name": "SummaryAspect",
-              "modelAsString": true
+              "modelAsString": true,
+              "values": [
+                {
+                  "value": "issue",
+                  "description": "A summary of issues in transcripts of web chats and service call transcripts between customer-service agents, and your customers."
+                },
+                {
+                  "value": "resolution",
+                  "description": "A summary of resolutions in transcripts of web chats and service call transcripts between customer-service agents, and your customers."
+                },
+                {
+                  "value": "chapterTitle",
+                  "description": "A chapter title of any conversation. It is usually one phrase or several phrases naturally combined together. Long conversation tends to have more chapters. The chapter boundary can be found from the summary context."
+                },
+                {
+                  "value": "generic",
+                  "description": "A generic summary of any conversation."
+                }
+              ]
             }
           }
         }
       },
       "allOf": [
         {
           "$ref": "common.json#/definitions/PreBuiltTaskParameters"
+        },
+        {
+          "$ref": "common.json#/definitions/AbstractiveSummarizationTaskParametersBase"
         }
       ]
     },
@@ -2089,6 +2122,13 @@
         },
         "text": {
           "type": "string"
+        },
+        "contexts": {
+          "type": "array",
+          "description": "The context list of the summary.",
+          "items": {
+            "$ref": "#/definitions/ItemizedSummaryContext"
+          }
         }
       },
       "required": [
@@ -2251,6 +2291,24 @@
           "$ref": "common.json#/definitions/RequestStatistics"
         }
       ]
+    },
+    "ItemizedSummaryContext": {
+      "type": "object",
+      "description": "The context of the summary with conversation item id.",
+      "required": [
+        "conversationItemId"
+      ],
+      "properties": {
+        "conversationItemId": {
+          "type": "string",
+          "description": "Reference to the id of ConversationItem."
+        }
+      },
+      "allOf": [
+        {
+          "$ref": "common.json#/definitions/SummaryContext"
+        }
+      ]
     }
   },
   "parameters": {

dev/cognitiveservices/data-plane/Language/analyzetext.json

@@ -3,7 +3,7 @@
   "info": {
     "title": "Microsoft Cognitive Language Service - Text Analysis",
     "description": "The language service API is a suite of natural language processing (NLP) skills built with best-in-class Microsoft machine learning algorithms.  The API can be used to analyze unstructured text for tasks such as sentiment analysis, key phrase extraction, language detection and question answering. Further documentation can be found in <a href=\"https://docs.microsoft.com/en-us/azure/cognitive-services/language-service/overview\">https://docs.microsoft.com/en-us/azure/cognitive-services/language-service/overview</a>.0",
-    "version": "2022-07-01-preview"
+    "version": "2022-10-01-preview"
   },
   "securityDefinitions": {
     "apim_key": {
@@ -88,9 +88,6 @@
           },
           "Successful Sentiment Analysis Request": {
             "$ref": "./examples/text/SuccessfulSentimentAnalysisRequest.json"
-          },
-          "Succesful Healthcare Request": {
-            "$ref": "./examples/text/SuccessfulHealthcareRequest.json"
           }
         }
       }
@@ -139,6 +136,9 @@
         "x-ms-examples": {
           "Successful Submit Analysis Job Request": {
             "$ref": "./examples/text/SuccessfulAnalyzeTextJobsMultipleTaskSubmitRequest.json"
+          },
+          "Successful Submit Abstractive Summarization Task": {
+            "$ref": "./examples/text/SuccessfulAbstractiveSummarizationTaskSubmit.json"
           }
         },
         "x-ms-long-running-operation": true
@@ -186,6 +186,9 @@
         "x-ms-examples": {
           "Successful Get Text Analysis Job Status Request": {
             "$ref": "./examples/text/SuccessfulAnalyzeTextJobsMultipleTaskStatusRequest.json"
+          },
+          "Successful Get Abstractive Summarization Result": {
+            "$ref": "./examples/text/SuccessfulAbstractiveSummarizationTaskResult.json"
           }
         }
       }
@@ -261,7 +264,8 @@
         "ExtractiveSummarization",
         "CustomEntityRecognition",
         "CustomSingleLabelClassification",
-        "CustomMultiLabelClassification"
+        "CustomMultiLabelClassification",
+        "AbstractiveSummarization"
       ],
       "x-ms-enum": {
         "name": "AnalyzeTextLROTaskKind",
@@ -297,7 +301,8 @@
         "ExtractiveSummarizationLROResults",
         "CustomEntityRecognitionLROResults",
         "CustomSingleLabelClassificationLROResults",
-        "CustomMultiLabelClassificationLROResults"
+        "CustomMultiLabelClassificationLROResults",
+        "AbstractiveSummarizationLROResults"
       ],
       "x-ms-enum": {
         "name": "AnalyzeTextLROResultsKind",
@@ -1960,20 +1965,16 @@
       "type": "object",
       "description": "Supported parameters for an Extractive Summarization task.",
       "properties": {
-        "sentenceCount": {
-          "type": "integer",
-          "default": 3
-        },
         "sortBy": {
           "$ref": "#/definitions/ExtractiveSummarizationSortingCriteria"
-        },
-        "stringIndexType": {
-          "$ref": "common.json#/definitions/StringIndexType"
         }
       },
       "allOf": [
         {
           "$ref": "common.json#/definitions/PreBuiltTaskParameters"
+        },
+        {
+          "$ref": "common.json#/definitions/SummarizationTaskParametersBase"
         }
       ]
     },
@@ -2699,6 +2700,133 @@
           "type": "string"
         }
       }
+    },
+    "AbstractiveSummarizationLROTask": {
+      "type": "object",
+      "description": "An object representing the task definition for an Abstractive Summarization task.",
+      "required": [
+        "parameters"
+      ],
+      "properties": {
+        "parameters": {
+          "$ref": "#/definitions/AbstractiveSummarizationTaskParameters"
+        }
+      },
+      "allOf": [
+        {
+          "$ref": "#/definitions/AnalyzeTextLROTask"
+        }
+      ],
+      "x-ms-discriminator-value": "AbstractiveSummarization"
+    },
+    "AbstractiveSummarizationTaskParameters": {
+      "type": "object",
+      "description": "Supported parameters for the pre-build Abstractive Summarization task.",
+      "allOf": [
+        {
+          "$ref": "common.json#/definitions/AbstractiveSummarizationTaskParametersBase"
+        },
+        {
+          "$ref": "common.json#/definitions/PreBuiltTaskParameters"
+        }
+      ]
+    },
+    "AbstractiveSummarizationLROResults": {
+      "type": "object",
+      "description": "An object representing the results for an Abstractive Summarization task.",
+      "properties": {
+        "results": {
+          "$ref": "#/definitions/AbstractiveSummarizationResult"
+        }
+      },
+      "allOf": [
+        {
+          "$ref": "#/definitions/AnalyzeTextLROResult"
+        }
+      ],
+      "required": [
+        "results"
+      ],
+      "x-ms-discriminator-value": "AbstractiveSummarizationLROResults"
+    },
+    "AbstractiveSummarizationResultBase": {
+      "type": "object",
+      "description": "An object representing the summarization results of each document.",
+      "properties": {
+        "documents": {
+          "type": "array",
+          "description": "Response by document",
+          "items": {
+            "allOf": [
+              {
+                "$ref": "#/definitions/AbstractiveSummaryDocumentResult"
+              },
+              {
+                "$ref": "#/definitions/DocumentDetectedLanguage"
+              }
+            ]
+          }
+        }
+      },
+      "required": [
+        "documents"
+      ]
+    },
+    "AbstractiveSummarizationResult": {
+      "type": "object",
+      "description": "An object representing the pre-build summarization results of each document.",
+      "allOf": [
+        {
+          "$ref": "#/definitions/AbstractiveSummarizationResultBase"
+        },
+        {
+          "$ref": "common.json#/definitions/PreBuiltResult"
+        }
+      ],
+      "required": [
+        "documents"
+      ]
+    },
+    "AbstractiveSummaryDocumentResult": {
+      "type": "object",
+      "description": "An object representing the summarization result of a single document.",
+      "properties": {
+        "summaries": {
+          "type": "array",
+          "description": "A list of abstractive summaries.",
+          "items": {
+            "$ref": "#/definitions/AbstractiveSummary"
+          }
+        }
+      },
+      "allOf": [
+        {
+          "$ref": "#/definitions/DocumentResult"
+        }
+      ],
+      "required": [
+        "summaries"
+      ]
+    },
+    "AbstractiveSummary": {
+      "type": "object",
+      "description": "An object representing a single summary with context for given document.",
+      "properties": {
+        "text": {
+          "type": "string",
+          "description": "The text of the summary."
+        },
+        "contexts": {
+          "type": "array",
+          "description": "The context list of the summary.",
+          "items": {
+            "$ref": "common.json#/definitions/SummaryContext"
+          }
+        }
+      },
+      "required": [
+        "text"
+      ]
     }
   },
   "parameters": {}