diff --git a/custom-words.txt b/custom-words.txt
index 5fb936a9899f..54e939afb4f3 100644
--- a/custom-words.txt
+++ b/custom-words.txt
@@ -9,6 +9,7 @@ aapl
AATP
abcxyz
ABFS
+Abstractive
ABGRABGR
Accel
ACCELCONTAINER
diff --git a/dev/cognitiveservices/data-plane/Language/analyzeconversations.json b/dev/cognitiveservices/data-plane/Language/analyzeconversations.json
index 45ecd6709457..49bd6e6abbc4 100644
--- a/dev/cognitiveservices/data-plane/Language/analyzeconversations.json
+++ b/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"
}
}
}
@@ -1772,7 +1778,7 @@
"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",
@@ -1786,12 +1792,16 @@
"type": "string",
"description": "The lexical form of the recognized text from speech to text API with the actual words recognized."
},
- "audioTimings": {
+ "wordLevelTimings": {
"type": "array",
"description": "The list of word level audio timing information",
"items": {
"$ref": "#/definitions/WordLevelTiming"
}
+ },
+ "conversationItemLevelTiming": {
+ "description": "Conversation item level audio timing. This still can help on AI quality if word level audio timings are not available.",
+ "$ref": "#/definitions/ConversationItemLevelTiming"
}
}
},
@@ -2044,11 +2054,31 @@
"type": "string",
"enum": [
"issue",
- "resolution"
+ "resolution",
+ "chapterTitle",
+ "narrative"
],
"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": "narrative",
+ "description": "A generic narrative summary of any conversation. It generally converts the conversational language into formal written language, compresses the text length and keeps the salient information."
+ }
+ ]
}
}
}
@@ -2056,6 +2086,9 @@
"allOf": [
{
"$ref": "common.json#/definitions/PreBuiltTaskParameters"
+ },
+ {
+ "$ref": "common.json#/definitions/AbstractiveSummarizationTaskParametersBase"
}
]
},
@@ -2129,6 +2162,13 @@
},
"text": {
"type": "string"
+ },
+ "contexts": {
+ "type": "array",
+ "description": "The context list of the summary.",
+ "items": {
+ "$ref": "#/definitions/ItemizedSummaryContext"
+ }
}
},
"required": [
@@ -2291,6 +2331,33 @@
"$ref": "common.json#/definitions/RequestStatistics"
}
]
+ },
+ "ConversationItemLevelTiming": {
+ "type": "object",
+ "description": "The conversation item level audio timing.",
+ "allOf": [
+ {
+ "$ref": "#/definitions/AudioTiming"
+ }
+ ]
+ },
+ "ItemizedSummaryContext": {
+ "type": "object",
+ "description": "The context of the summary with conversation item id.",
+ "required": [
+ "conversationItemId"
+ ],
+ "properties": {
+ "conversationItemId": {
+ "type": "string",
+ "description": "Reference to the id of ConversationItem."
+ }
+ },
+ "allOf": [
+ {
+ "$ref": "common.json#/definitions/SummaryContext"
+ }
+ ]
}
},
"parameters": {
diff --git a/dev/cognitiveservices/data-plane/Language/analyzetext.json b/dev/cognitiveservices/data-plane/Language/analyzetext.json
index e797303e1fd7..f6bc4ba24384 100644
--- a/dev/cognitiveservices/data-plane/Language/analyzetext.json
+++ b/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 https://docs.microsoft.com/en-us/azure/cognitive-services/language-service/overview.0",
- "version": "2022-07-01-preview"
+ "version": "2022-10-01-preview"
},
"securityDefinitions": {
"apim_key": {
@@ -139,6 +139,9 @@
},
"Successful Healthcare Post Request": {
"$ref": "./examples/text/SuccessfulHealthcarePostRequest.json"
+ },
+ "Successful Submit Abstractive Summarization Task": {
+ "$ref": "./examples/text/SuccessfulAbstractiveSummarizationTaskSubmit.json"
}
},
"x-ms-long-running-operation": true
@@ -189,6 +192,9 @@
},
"Successful Get Text Analysis Health Request": {
"$ref": "./examples/text/SuccessfulHealthcareTaskStatusRequest.json"
+ },
+ "Successful Get Abstractive Summarization Result": {
+ "$ref": "./examples/text/SuccessfulAbstractiveSummarizationTaskResult.json"
}
}
}
@@ -264,7 +270,8 @@
"ExtractiveSummarization",
"CustomEntityRecognition",
"CustomSingleLabelClassification",
- "CustomMultiLabelClassification"
+ "CustomMultiLabelClassification",
+ "AbstractiveSummarization"
],
"x-ms-enum": {
"name": "AnalyzeTextLROTaskKind",
@@ -300,7 +307,8 @@
"ExtractiveSummarizationLROResults",
"CustomEntityRecognitionLROResults",
"CustomSingleLabelClassificationLROResults",
- "CustomMultiLabelClassificationLROResults"
+ "CustomMultiLabelClassificationLROResults",
+ "AbstractiveSummarizationLROResults"
],
"x-ms-enum": {
"name": "AnalyzeTextLROResultsKind",
@@ -2718,6 +2726,133 @@
"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": {
+ "$ref": "common.json#/definitions/SummaryContext"
+ }
+ }
+ },
+ "required": [
+ "text"
+ ]
}
},
"parameters": {}
diff --git a/dev/cognitiveservices/data-plane/Language/common.json b/dev/cognitiveservices/data-plane/Language/common.json
index 2f541f1f61ab..e93bb48519e0 100644
--- a/dev/cognitiveservices/data-plane/Language/common.json
+++ b/dev/cognitiveservices/data-plane/Language/common.json
@@ -3,7 +3,7 @@
"info": {
"title": "Microsoft Cognitive Language Service",
"description": "The language service API is a suite of natural language processing (NLP) skills built with best-in-class Microsoft machine learning algorithms. The API can be used to analyze unstructured text for tasks such as sentiment analysis, key phrase extraction, language detection and question answering. Further documentation can be found in https://docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/overview.",
- "version": "2022-07-01-preview"
+ "version": "2022-10-01-preview"
},
"paths": {},
"definitions": {
@@ -722,6 +722,90 @@
"minimum": 1
}
}
+ },
+ "AbstractiveSummarizationTaskParametersBase": {
+ "type": "object",
+ "description": "Supported parameters for an Abstractive Summarization task.",
+ "properties": {
+ "sentenceCount": {
+ "type": "integer",
+ "format": "int32"
+ },
+ "stringIndexType": {
+ "$ref": "#/definitions/StringIndexType"
+ },
+ "phraseControls": {
+ "type": "array",
+ "description": "Control the phrases to be used in the summary.",
+ "items": {
+ "$ref": "#/definitions/PhraseControl"
+ }
+ }
+ }
+ },
+ "PhraseControl": {
+ "type": "object",
+ "description": "Control the phrases to be used in the summary.",
+ "required": [
+ "targetPhrase",
+ "strategy"
+ ],
+ "properties": {
+ "targetPhrase": {
+ "type": "string",
+ "description": "The target phrase to control."
+ },
+ "strategy": {
+ "$ref": "#/definitions/PhraseControlStrategy"
+ }
+ }
+ },
+ "PhraseControlStrategy": {
+ "enum": [
+ "encourage",
+ "discourage",
+ "disallow"
+ ],
+ "type": "string",
+ "description": "The strategy to use in phrase control.",
+ "x-ms-enum": {
+ "modelAsString": false,
+ "name": "PhraseControlStrategy",
+ "values": [
+ {
+ "value": "encourage",
+ "description": "The model will have higher probability to select the target phrase in the summary if there are multiple alternates."
+ },
+ {
+ "value": "discourage",
+ "description": "The model will have lower probability to select the target phrase in the summary if there are multiple alternates."
+ },
+ {
+ "value": "disallow",
+ "description": "The model will avoid to select the target phrase in the summary."
+ }
+ ]
+ }
+ },
+ "SummaryContext": {
+ "type": "object",
+ "description": "The context of the summary.",
+ "required": [
+ "offset",
+ "length"
+ ],
+ "properties": {
+ "offset": {
+ "type": "integer",
+ "format": "int32",
+ "description": "Start position for the context. Use of different 'stringIndexType' values can affect the offset returned."
+ },
+ "length": {
+ "type": "integer",
+ "format": "int32",
+ "description": "The length of the context. Use of different 'stringIndexType' values can affect the length returned."
+ }
+ }
}
},
"parameters": {
diff --git a/dev/cognitiveservices/data-plane/Language/examples/conversations/SuccessfulConversationPIISubmit.json b/dev/cognitiveservices/data-plane/Language/examples/conversations/SuccessfulConversationPIISubmit.json
index 11e7ae14947a..4663be8badce 100644
--- a/dev/cognitiveservices/data-plane/Language/examples/conversations/SuccessfulConversationPIISubmit.json
+++ b/dev/cognitiveservices/data-plane/Language/examples/conversations/SuccessfulConversationPIISubmit.json
@@ -21,7 +21,7 @@
"itn": "good morning john doe",
"maskedItn": "good morning john doe",
"lexical": "good morning john doe",
- "audioTimings": [
+ "wordLevelTimings": [
{
"word": "good",
"offset": 390000,
diff --git a/dev/cognitiveservices/data-plane/Language/examples/conversations/SuccessfulConversationSummarizationTaskResult.json b/dev/cognitiveservices/data-plane/Language/examples/conversations/SuccessfulConversationSummarizationTaskResult.json
new file mode 100644
index 000000000000..089ccbe23def
--- /dev/null
+++ b/dev/cognitiveservices/data-plane/Language/examples/conversations/SuccessfulConversationSummarizationTaskResult.json
@@ -0,0 +1,75 @@
+{
+ "parameters": {
+ "Ocp-Apim-Subscription-Key": "{API key}",
+ "api-version": "{api-version}",
+ "Endpoint": "{Endpoint}",
+ "jobId": "3e9e8518-492f-47f9-abd1-9a7468231086"
+ },
+ "responses": {
+ "200": {
+ "headers": {},
+ "body": {
+ "displayName": "Conversation Summarization Example",
+ "createdDateTime": "2022-04-01T15:00:45Z",
+ "expirationDateTime": "2022-04-02T15:00:45Z",
+ "jobId": "3e9e8518-492f-47f9-abd1-9a7468231086",
+ "lastUpdatedDateTime": "2022-04-01T15:00:49Z",
+ "status": "succeeded",
+ "tasks": {
+ "completed": 1,
+ "failed": 0,
+ "inProgress": 0,
+ "total": 1,
+ "items": [
+ {
+ "kind": "ConversationalSummarizationResults",
+ "lastUpdateDateTime": "2022-04-01T15:00:49Z",
+ "taskName": "Conversation Summarization Task 1",
+ "status": "succeeded",
+ "results": {
+ "conversations": [
+ {
+ "id": "1",
+ "summaries": [
+ {
+ "aspect": "chapterTitle",
+ "text": "Bug Triage",
+ "contexts": [
+ {
+ "conversationItemId": "2",
+ "offset": 4,
+ "length": 39
+ }
+ ]
+ },
+ {
+ "aspect": "generic",
+ "text": "Speaker 3 believes there are 3 remaining bugs.",
+ "contexts": [
+ {
+ "conversationItemId": "2",
+ "offset": 4,
+ "length": 39
+ },
+ {
+ "conversationItemId": "3",
+ "offset": 0,
+ "length": 7
+ }
+ ]
+ }
+ ],
+ "warnings": []
+ }
+ ],
+ "errors": [],
+ "modelVersion": "2022-10-01-preview"
+ }
+ }
+ ]
+ },
+ "nextLink": "/language/analyze-conversation/jobs/3e9e8518-492f-47f9-abd1-9a7468231086?$skip=10&$top=10"
+ }
+ }
+ }
+}
diff --git a/dev/cognitiveservices/data-plane/Language/examples/conversations/SuccessfulConversationSummarizationTaskSubmit.json b/dev/cognitiveservices/data-plane/Language/examples/conversations/SuccessfulConversationSummarizationTaskSubmit.json
new file mode 100644
index 000000000000..32d6690d1b44
--- /dev/null
+++ b/dev/cognitiveservices/data-plane/Language/examples/conversations/SuccessfulConversationSummarizationTaskSubmit.json
@@ -0,0 +1,77 @@
+{
+ "parameters": {
+ "Ocp-Apim-Subscription-Key": "{API key}",
+ "api-version": "{api-version}",
+ "Endpoint": "{Endpoint}",
+ "jobId": "{Job ID}",
+ "body": {
+ "displayName": "Conversation Summarization Example",
+ "analysisInput": {
+ "conversations": [
+ {
+ "id": "1",
+ "language": "en",
+ "modality": "transcript",
+ "conversationItems": [
+ {
+ "participantId": "speaker 1",
+ "id": "1",
+ "text": "Let's get started.",
+ "lexical": "",
+ "itn": "",
+ "maskedItn": "",
+ "conversationItemLevelTiming": {
+ "offset": 0,
+ "duration": 20000000
+ }
+ },
+ {
+ "participantId": "speaker 2",
+ "id": "2",
+ "text": "OK. How many remaining bugs do we have now?",
+ "lexical": "",
+ "itn": "",
+ "maskedItn": "",
+ "conversationItemLevelTiming": {
+ "offset": 20000000,
+ "duration": 50000000
+ }
+ },
+ {
+ "participantId": "speaker 3",
+ "id": "3",
+ "text": "Only 3.",
+ "lexical": "",
+ "itn": "",
+ "maskedItn": "",
+ "conversationItemLevelTiming": {
+ "offset": 50000000,
+ "duration": 60000000
+ }
+ }
+ ]
+ }
+ ]
+ },
+ "tasks": [
+ {
+ "taskName": "Conversation Summarization Task 1",
+ "kind": "ConversationalSummarizationTask",
+ "parameters": {
+ "summaryAspects": [
+ "chapterTitle",
+ "narrative"
+ ]
+ }
+ }
+ ]
+ }
+ },
+ "responses": {
+ "202": {
+ "headers": {
+ "Operation-Location": "{Endpoint}/language/analyze-conversation/jobs/{jobId}?api-version={api-version}"
+ }
+ }
+ }
+}
diff --git a/dev/cognitiveservices/data-plane/Language/examples/text/SuccessfulAbstractiveSummarizationTaskResult.json b/dev/cognitiveservices/data-plane/Language/examples/text/SuccessfulAbstractiveSummarizationTaskResult.json
new file mode 100644
index 000000000000..39198c84b288
--- /dev/null
+++ b/dev/cognitiveservices/data-plane/Language/examples/text/SuccessfulAbstractiveSummarizationTaskResult.json
@@ -0,0 +1,56 @@
+{
+ "parameters": {
+ "Ocp-Apim-Subscription-Key": "{API key}",
+ "api-version": "{api-version}",
+ "Endpoint": "{Endpoint}",
+ "jobId": "c0f2a446-05d9-48fc-ba8f-3ef4af8d0b18"
+ },
+ "responses": {
+ "200": {
+ "headers": {},
+ "body": {
+ "createdDateTime": "2020-10-01T15:00:45Z",
+ "displayName": "Document Abstractive Summarization Task Example",
+ "expirationDateTime": "2020-10-03T15:01:03Z",
+ "jobId": "c0f2a446-05d9-48fc-ba8f-3ef4af8d0b18",
+ "lastUpdatedDateTime": "2020-10-01T15:01:03Z",
+ "status": "succeeded",
+ "tasks": {
+ "completed": 1,
+ "failed": 0,
+ "inProgress": 0,
+ "total": 1,
+ "items": [
+ {
+ "kind": "AbstractiveSummarizationLROResults",
+ "taskName": "Document Abstractive Summarization Task 1",
+ "lastUpdateDateTime": "2020-10-01T15:01:03Z",
+ "status": "succeeded",
+ "results": {
+ "documents": [
+ {
+ "summaries": [
+ {
+ "text": "Microsoft have been on a quest to advance AI beyond existing techniques.",
+ "contexts": [
+ {
+ "offset": 0,
+ "length": 1629
+ }
+ ]
+ }
+ ],
+ "id": "1",
+ "warnings": []
+ }
+ ],
+ "errors": [],
+ "modelVersion": "2022-10-01-preview"
+ }
+ }
+ ]
+ }
+ }
+ }
+ }
+}
diff --git a/dev/cognitiveservices/data-plane/Language/examples/text/SuccessfulAbstractiveSummarizationTaskSubmit.json b/dev/cognitiveservices/data-plane/Language/examples/text/SuccessfulAbstractiveSummarizationTaskSubmit.json
new file mode 100644
index 000000000000..6710db4d53a4
--- /dev/null
+++ b/dev/cognitiveservices/data-plane/Language/examples/text/SuccessfulAbstractiveSummarizationTaskSubmit.json
@@ -0,0 +1,36 @@
+{
+ "parameters": {
+ "Ocp-Apim-Subscription-Key": "{API key}",
+ "api-version": "{api-version}",
+ "Endpoint": "{Endpoint}",
+ "jobId": "{Job ID}",
+ "body": {
+ "displayName": "Document Abstractive Summarization Task Example",
+ "analysisInput": {
+ "documents": [
+ {
+ "id": "1",
+ "language": "en",
+ "text": "At Microsoft, we have been on a quest to advance AI beyond existing techniques, by taking a more holistic, human-centric approach to learning and understanding. As Chief Technology Officer of Azure AI Cognitive Services, I have been working with a team of amazing scientists and engineers to turn this quest into a reality. In my role, I enjoy a unique perspective in viewing the relationship among three attributes of human cognition: monolingual text (X), audio or visual sensory signals, (Y) and multilingual (Z). At the intersection of all three, there is magic—what we call XYZ-code as illustrated in Figure 1—a joint representation to create more powerful AI that can speak, hear, see, and understand humans better. We believe XYZ-code will enable us to fulfill our long-term vision: cross-domain transfer learning, spanning modalities and languages. The goal is to have pre-trained models that can jointly learn representations to support a broad range of downstream AI tasks, much in the way humans do today. Over the past five years, we have achieved human performance on benchmarks in conversational speech recognition, machine translation, conversational question answering, machine reading comprehension, and image captioning. These five breakthroughs provided us with strong signals toward our more ambitious aspiration to produce a leap in AI capabilities, achieving multi-sensory and multilingual learning that is closer in line with how humans learn and understand. I believe the joint XYZ-code is a foundational component of this aspiration, if grounded with external knowledge sources in the downstream AI tasks."
+ }
+ ]
+ },
+ "tasks": [
+ {
+ "kind": "AbstractiveSummarization",
+ "taskName": "Document Abstractive Summarization Task 1",
+ "parameters": {
+ "sentenceCount": 1
+ }
+ }
+ ]
+ }
+ },
+ "responses": {
+ "202": {
+ "headers": {
+ "Operation-Location": "{endpoint}/language/analyze-text/jobs/{jobId}?api-version={api-version}"
+ }
+ }
+ }
+}
diff --git a/dev/cognitiveservices/data-plane/Language/readme.md b/dev/cognitiveservices/data-plane/Language/readme.md
index 37c93e2c917e..81e4097dbf2d 100644
--- a/dev/cognitiveservices/data-plane/Language/readme.md
+++ b/dev/cognitiveservices/data-plane/Language/readme.md
@@ -6,12 +6,12 @@ This is the AutoRest configuration file the Cognitive Services Language SDK.
## Releases
-The current preview release of Language is 2022-07-01-preview.
+The current preview release of Language is 2022-10-01-preview.
```yaml
-tag: release_2022-07-01-preview
+tag: release_2022-10-01-preview
add-credentials: true
clear-output-folder: true
openapi-type: data-plane
@@ -22,6 +22,20 @@ directive:
### Release
+``` yaml $(tag) == 'release_2022-10-01-preview'
+input-file:
+ - analyzetext.json
+ - analyzetext-authoring.json
+ - analyzeconversations.json
+ - analyzeconversations-authoring.json
+ - questionanswering.json
+ - questionanswering-authoring.json
+title:
+ Microsoft Cognitive Language Service
+modelerfour:
+ lenient-model-deduplication: true
+```
+
``` yaml $(tag) == 'release_2022-07-01-preview'
input-file:
- analyzetext.json