From 1d14a2f69b29855ec25b488babfbceb0609a519c Mon Sep 17 00:00:00 2001 From: Yoshi Automation Date: Tue, 6 Dec 2022 07:07:41 +0000 Subject: [PATCH] feat(dialogflow): update the api #### dialogflow:v2 The following keys were added: - schemas.GoogleCloudDialogflowV2ConversationModelEvaluation.properties.rawHumanEvalTemplateCsv (Total Keys: 2) --- ...logflow_v2.projects.conversationModels.evaluations.html | 2 ++ ....projects.locations.conversationModels.evaluations.html | 3 +++ .../discovery_cache/documents/dialogflow.v2.json | 7 ++++++- .../discovery_cache/documents/dialogflow.v2beta1.json | 2 +- .../discovery_cache/documents/dialogflow.v3.json | 2 +- .../discovery_cache/documents/dialogflow.v3beta1.json | 2 +- 6 files changed, 14 insertions(+), 4 deletions(-) diff --git a/docs/dyn/dialogflow_v2.projects.conversationModels.evaluations.html b/docs/dyn/dialogflow_v2.projects.conversationModels.evaluations.html index 8d3b83f9365..93af74e314e 100644 --- a/docs/dyn/dialogflow_v2.projects.conversationModels.evaluations.html +++ b/docs/dyn/dialogflow_v2.projects.conversationModels.evaluations.html @@ -125,6 +125,7 @@

Method Details

}, }, "name": "A String", # The resource name of the evaluation. Format: `projects//conversationModels//evaluations/` + "rawHumanEvalTemplateCsv": "A String", # Output only. Human eval template in csv format. It tooks real-world conversations provided through input dataset, generates example suggestions for customer to verify quality of the model. For Smart Reply, the generated csv file contains columns of Context, (Suggestions,Q1,Q2)*3, Actual reply. Context contains at most 10 latest messages in the conversation prior to the current suggestion. Q1: "Would you send it as the next message of agent?" Evaluated based on whether the suggest is appropriate to be sent by agent in current context. Q2: "Does the suggestion move the conversation closer to resolution?" Evaluated based on whether the suggestion provide solutions, or answers customer's question or collect information from customer to resolve the customer's issue. Actual reply column contains the actual agent reply sent in the context. "smartReplyMetrics": { # The evaluation metrics for smart reply model. # Output only. Only available when model is for smart reply. "allowlistCoverage": 3.14, # Percentage of target participant messages in the evaluation dataset for which similar messages have appeared at least once in the allowlist. Should be [0, 1]. "conversationCount": "A String", # Total number of conversations used to generate this metric. @@ -175,6 +176,7 @@

Method Details

}, }, "name": "A String", # The resource name of the evaluation. Format: `projects//conversationModels//evaluations/` + "rawHumanEvalTemplateCsv": "A String", # Output only. Human eval template in csv format. It tooks real-world conversations provided through input dataset, generates example suggestions for customer to verify quality of the model. For Smart Reply, the generated csv file contains columns of Context, (Suggestions,Q1,Q2)*3, Actual reply. Context contains at most 10 latest messages in the conversation prior to the current suggestion. Q1: "Would you send it as the next message of agent?" Evaluated based on whether the suggest is appropriate to be sent by agent in current context. Q2: "Does the suggestion move the conversation closer to resolution?" Evaluated based on whether the suggestion provide solutions, or answers customer's question or collect information from customer to resolve the customer's issue. Actual reply column contains the actual agent reply sent in the context. "smartReplyMetrics": { # The evaluation metrics for smart reply model. # Output only. Only available when model is for smart reply. "allowlistCoverage": 3.14, # Percentage of target participant messages in the evaluation dataset for which similar messages have appeared at least once in the allowlist. Should be [0, 1]. "conversationCount": "A String", # Total number of conversations used to generate this metric. diff --git a/docs/dyn/dialogflow_v2.projects.locations.conversationModels.evaluations.html b/docs/dyn/dialogflow_v2.projects.locations.conversationModels.evaluations.html index 298a037732c..16173f58214 100644 --- a/docs/dyn/dialogflow_v2.projects.locations.conversationModels.evaluations.html +++ b/docs/dyn/dialogflow_v2.projects.locations.conversationModels.evaluations.html @@ -124,6 +124,7 @@

Method Details

}, }, "name": "A String", # The resource name of the evaluation. Format: `projects//conversationModels//evaluations/` + "rawHumanEvalTemplateCsv": "A String", # Output only. Human eval template in csv format. It tooks real-world conversations provided through input dataset, generates example suggestions for customer to verify quality of the model. For Smart Reply, the generated csv file contains columns of Context, (Suggestions,Q1,Q2)*3, Actual reply. Context contains at most 10 latest messages in the conversation prior to the current suggestion. Q1: "Would you send it as the next message of agent?" Evaluated based on whether the suggest is appropriate to be sent by agent in current context. Q2: "Does the suggestion move the conversation closer to resolution?" Evaluated based on whether the suggestion provide solutions, or answers customer's question or collect information from customer to resolve the customer's issue. Actual reply column contains the actual agent reply sent in the context. "smartReplyMetrics": { # The evaluation metrics for smart reply model. # Output only. Only available when model is for smart reply. "allowlistCoverage": 3.14, # Percentage of target participant messages in the evaluation dataset for which similar messages have appeared at least once in the allowlist. Should be [0, 1]. "conversationCount": "A String", # Total number of conversations used to generate this metric. @@ -199,6 +200,7 @@

Method Details

}, }, "name": "A String", # The resource name of the evaluation. Format: `projects//conversationModels//evaluations/` + "rawHumanEvalTemplateCsv": "A String", # Output only. Human eval template in csv format. It tooks real-world conversations provided through input dataset, generates example suggestions for customer to verify quality of the model. For Smart Reply, the generated csv file contains columns of Context, (Suggestions,Q1,Q2)*3, Actual reply. Context contains at most 10 latest messages in the conversation prior to the current suggestion. Q1: "Would you send it as the next message of agent?" Evaluated based on whether the suggest is appropriate to be sent by agent in current context. Q2: "Does the suggestion move the conversation closer to resolution?" Evaluated based on whether the suggestion provide solutions, or answers customer's question or collect information from customer to resolve the customer's issue. Actual reply column contains the actual agent reply sent in the context. "smartReplyMetrics": { # The evaluation metrics for smart reply model. # Output only. Only available when model is for smart reply. "allowlistCoverage": 3.14, # Percentage of target participant messages in the evaluation dataset for which similar messages have appeared at least once in the allowlist. Should be [0, 1]. "conversationCount": "A String", # Total number of conversations used to generate this metric. @@ -249,6 +251,7 @@

Method Details

}, }, "name": "A String", # The resource name of the evaluation. Format: `projects//conversationModels//evaluations/` + "rawHumanEvalTemplateCsv": "A String", # Output only. Human eval template in csv format. It tooks real-world conversations provided through input dataset, generates example suggestions for customer to verify quality of the model. For Smart Reply, the generated csv file contains columns of Context, (Suggestions,Q1,Q2)*3, Actual reply. Context contains at most 10 latest messages in the conversation prior to the current suggestion. Q1: "Would you send it as the next message of agent?" Evaluated based on whether the suggest is appropriate to be sent by agent in current context. Q2: "Does the suggestion move the conversation closer to resolution?" Evaluated based on whether the suggestion provide solutions, or answers customer's question or collect information from customer to resolve the customer's issue. Actual reply column contains the actual agent reply sent in the context. "smartReplyMetrics": { # The evaluation metrics for smart reply model. # Output only. Only available when model is for smart reply. "allowlistCoverage": 3.14, # Percentage of target participant messages in the evaluation dataset for which similar messages have appeared at least once in the allowlist. Should be [0, 1]. "conversationCount": "A String", # Total number of conversations used to generate this metric. diff --git a/googleapiclient/discovery_cache/documents/dialogflow.v2.json b/googleapiclient/discovery_cache/documents/dialogflow.v2.json index 30b4e624ced..ea2577c4d12 100644 --- a/googleapiclient/discovery_cache/documents/dialogflow.v2.json +++ b/googleapiclient/discovery_cache/documents/dialogflow.v2.json @@ -8077,7 +8077,7 @@ } } }, - "revision": "20221118", + "revision": "20221202", "rootUrl": "https://dialogflow.googleapis.com/", "schemas": { "GoogleCloudDialogflowCxV3AudioInput": { @@ -12636,6 +12636,11 @@ "description": "The resource name of the evaluation. Format: `projects//conversationModels//evaluations/`", "type": "string" }, + "rawHumanEvalTemplateCsv": { + "description": "Output only. Human eval template in csv format. It tooks real-world conversations provided through input dataset, generates example suggestions for customer to verify quality of the model. For Smart Reply, the generated csv file contains columns of Context, (Suggestions,Q1,Q2)*3, Actual reply. Context contains at most 10 latest messages in the conversation prior to the current suggestion. Q1: \"Would you send it as the next message of agent?\" Evaluated based on whether the suggest is appropriate to be sent by agent in current context. Q2: \"Does the suggestion move the conversation closer to resolution?\" Evaluated based on whether the suggestion provide solutions, or answers customer's question or collect information from customer to resolve the customer's issue. Actual reply column contains the actual agent reply sent in the context.", + "readOnly": true, + "type": "string" + }, "smartReplyMetrics": { "$ref": "GoogleCloudDialogflowV2SmartReplyMetrics", "description": "Output only. Only available when model is for smart reply.", diff --git a/googleapiclient/discovery_cache/documents/dialogflow.v2beta1.json b/googleapiclient/discovery_cache/documents/dialogflow.v2beta1.json index 6ec673dd4db..93c140f2545 100644 --- a/googleapiclient/discovery_cache/documents/dialogflow.v2beta1.json +++ b/googleapiclient/discovery_cache/documents/dialogflow.v2beta1.json @@ -7507,7 +7507,7 @@ } } }, - "revision": "20221118", + "revision": "20221202", "rootUrl": "https://dialogflow.googleapis.com/", "schemas": { "GoogleCloudDialogflowCxV3AudioInput": { diff --git a/googleapiclient/discovery_cache/documents/dialogflow.v3.json b/googleapiclient/discovery_cache/documents/dialogflow.v3.json index a3a0dde2608..232723b2b2f 100644 --- a/googleapiclient/discovery_cache/documents/dialogflow.v3.json +++ b/googleapiclient/discovery_cache/documents/dialogflow.v3.json @@ -3820,7 +3820,7 @@ } } }, - "revision": "20221118", + "revision": "20221202", "rootUrl": "https://dialogflow.googleapis.com/", "schemas": { "GoogleCloudDialogflowCxV3AdvancedSettings": { diff --git a/googleapiclient/discovery_cache/documents/dialogflow.v3beta1.json b/googleapiclient/discovery_cache/documents/dialogflow.v3beta1.json index 4e77028e9bd..c44e8fc8eb8 100644 --- a/googleapiclient/discovery_cache/documents/dialogflow.v3beta1.json +++ b/googleapiclient/discovery_cache/documents/dialogflow.v3beta1.json @@ -3820,7 +3820,7 @@ } } }, - "revision": "20221118", + "revision": "20221202", "rootUrl": "https://dialogflow.googleapis.com/", "schemas": { "GoogleCloudDialogflowCxV3AudioInput": {