Merge branch 'develop'

# Conflicts:
#	CHANGELOG.md

.vscode/spellright.dict

@@ -35,3 +35,8 @@ gotanswer
 qnabotcontext
 nnn-nn-nnnn
 Conne
+ssml
+cardtitle
+cardimageurl
+buttonvalue
+py_lambda_hooks

CHANGELOG.md

@@ -17,6 +17,15 @@
 - QnABot's Elasticsearch cache is now automatically kept warm to improve query time consistency.
 - Negative feedback (thumbs down) messages can now generate notifications (text, email, etc.) using Amazon SNS.
 
+## [4.7.1]
+- Amazon Elasticsearch version 7.10 is now utilized.
+- Encrypted Elasticsearch (production) instance types now use m6g.large.elasticsearch for improved price/performance/memory.
+- The QnABot fulfillment Lambda function has been optimized to reduce query response times and variability,
+  especially after periods of inactivity.
+- LexV2 built-in Elicit Response bots have been added.
+- Custom settings can now be exported and imported from the Content Designer Settings page.
+- Bug fix when ES_SCORE_ANSWER_FIELD is set to true. Prior to this fix, answer fields were not
+  utilized fully in Elasticsearch queries.
 ## [4.5.2]
 - Fix for new Kendra resources deployed in VPC addressing issues in 4.5.0 and 4.5.1.
 ## [4.5.1]

README.md

@@ -8,13 +8,23 @@ This repository contains code for the QnABot, described in the AWS AI blog post
 
 See the "Getting Started" to launch your own QnABot.
 
+**See all the new features list for 4.7.1** [Lex V2 Elicit response bots, Config import/export](#new-features)
+
+4.7.1 provides performance improvements and component upgrades
+  - Amazon Elasticsearch version 7.10 is now utilized.
+  - Encrypted Elasticsearch (production) instance types now use m6g.large.elasticsearch for improved price/performance/memory. 
+  - The QnABot fulfillment Lambda function has been optimized to reduce query response times and variability, 
+    especially after periods of inactivity. 
+  - LexV2 built-in Elicit Response bots have been added. 
+  - Custom settings can now be exported and imported from the Content Designer Settings page.
+  - Bug fix when ES_SCORE_ANSWER_FIELD is set to true. Prior to this fix, answer fields were not
+    utilized fully in Elasticsearch queries.
+
 4.7.0 QnABot now supports LexV2 with voice interaction in multiple languages.
   - Two installation/update modes are now available:
     - (i) LexV1 + LexV2 (default, recommended for most AWS regions.
     - (ii) LexV2-only (currently recommended for AWS regions where LexV1 is not available).
-
-**See all the new features in 4.7.0** [LexV2 support, Excel Import, New Canada Central region](#new-features)
-
+
 4.6.0 provides a number of new features described below. Several to call attention to are the following:
 
 - Kendra custom no_hits item required in earlier releases is no longer required to enable Kendra Fallback and should be removed, configurable confidence thresholds now available for filtering Kendra results.
@@ -118,6 +128,10 @@ See the [LICENSE.md](LICENSE.md) file for details
 
 ## New features
 
+### Version 4.7.1
+- LexV2 built-in Elicit Response bots have been added.
+- Custom settings can now be exported and imported from the Content Designer Settings page.
+
 ### Version 4.7.0
 
 - QnABot now supports LexV2 with voice interaction in multiple languages. 

bin/config.js

@@ -20,6 +20,7 @@ module.exports={
     "devEncryption": "UNENCRYPTED",
     "devPublicOrPrivate": "PUBLIC",
     "namespace":"dev",
+    "LexBotVersion":"LexV1 and LexV2",
     "stackNamePrefix":"QNA"
 }
 

bin/launch.js

@@ -115,7 +115,7 @@ async function up(stack,options){
             if(Buffer.byteLength(template)<51200){
                 var create=await cf.createStack({
                     StackName,
-                    Capabilities:["CAPABILITY_NAMED_IAM"],
+                    Capabilities:["CAPABILITY_NAMED_IAM","CAPABILITY_AUTO_EXPAND"],
                     DisableRollback:true,
                     TemplateBody:template
                 }).promise()
@@ -131,7 +131,7 @@ async function up(stack,options){
                 }).promise()
                 var create=await cf.createStack({
                     StackName,
-                    Capabilities:["CAPABILITY_NAMED_IAM"],
+                    Capabilities:["CAPABILITY_NAMED_IAM","CAPABILITY_AUTO_EXPAND"],
                     DisableRollback:true,
                     TemplateURL:url
                 }).promise()
@@ -164,7 +164,7 @@ function update(stack,options){
             if(Buffer.byteLength(template)<51200){
                 var start=cf.updateStack({
                     StackName,
-                    Capabilities:["CAPABILITY_NAMED_IAM"],
+                    Capabilities:["CAPABILITY_NAMED_IAM","CAPABILITY_AUTO_EXPAND"],
                     TemplateBody:template
                 }).promise()
             }else{
@@ -180,7 +180,7 @@ function update(stack,options){
                     }).promise()
                     .then(()=>cf.updateStack({
                         StackName,
-                        Capabilities:["CAPABILITY_NAMED_IAM"],
+                        Capabilities:["CAPABILITY_NAMED_IAM","CAPABILITY_AUTO_EXPAND"],
                         TemplateURL:url
                     }).promise())
                 })

docs/recent_topics_lambda_hook_example/README.md

@@ -0,0 +1,83 @@
+# Create Recent Topics Response Walkthrough
+
+The CreateRecentTopicsResponse Lambda hook demonstrates how you can extend QnABot with custom functionality.
+
+The Lambda hook allows you to add buttons to a question with the recent topics answered by QnABot.
+
+## Importing the sample question bank
+
+Choose *Import* from the Tools menu.
+
+![Import Tool](./Import.png)
+
+Load the *RecentTopicsDemo* question bank.
+
+![Import question bank](./Import_qnabank.png)
+
+The sample question bank is loaded with questions tagged with topics.
+
+![Question List](./question_list.png)
+
+QnABot stores the topics of questions answered in a DynamoDB table per user.
+
+## Importing custom settings
+
+QnABot needs three pieces of information to display the buttons - the topic, the text that should be displayed on the button and the question
+that should be asked based on the button selected.
+
+The configuration for the buttons is done by adding custom settings in the Setting window.
+
+- Download the [recent topics settings](./recent_topics_settings.json) json file from the QnABot repository.
+- Go to the Settings screen, choose "Import Settings" and import the recent_topics_settings.json file.
+![Import Dialog](./import_dialog.png)
+- You should now see the custom settings loaded.
+![Loaded Settings](./loaded_settings.png)
+
+Notice the format of a setting that maps a topic to a button is:
+
+- topic::\<topic\> -- the name of the topic for QnABot to remember.
+- \<display text\>::\<QID\> -- the display text of the button and the ID of the question to be asked when the button is selected separated by two colons (::)
+
+## Configuring the Lambda hook
+
+You can have a combination of static buttons and dynamic buttons generated by the CreateRecentTopicsResponse Lambda hook.
+
+Edit the *PreviousTopics* question and expand the *Advanced* section.
+
+![Response card settings](./response_card.png)
+
+- The *Card Title* is required. But is not displayed.
+- Under *Lex Buttons* a button with the text "Ask Another Question" will always be displayed.  If chosen, the answer for the question with an ID of General.001 will be returned to the user.
+- The Lambda hook (QNA:EXTCreateRecentTopicsResponse) will be called with the parameters specified under *Lambda Hook Arguments*. This tells the Lambda hook to return the most recent topic (*"start":"0"*) and return at most five (*"end":5*) buttons.
+
+## Adding a topic to be recalled
+
+Let's add another question.
+
+- In Content Designer, click "Add" to add a question.
+  - Item ID - Textract.001
+  - Question - "What is Amazon Textract
+  - Answer `Amazon Textract is a machine learning service that automatically extracts text, handwriting and data from scanned documents that goes beyond simple optical character recognition (OCR) to identify, understand, and extract data from forms and tables.`
+
+![Textract](./textract.png)
+
+- Expand the "Advanced" Section
+  - Markdown Answer `Amazon Textract is a machine learning service that automatically extracts text, handwriting and data from scanned documents that goes beyond simple optical character recognition (OCR) to identify, understand, and extract data from forms and tables.`
+  - Topic - "Textract"
+  - click on "Create"
+
+![Advanced configuration](./advanced.png)
+
+- Now edit the AI.001 question and expand the "Advanced" section to add another button.
+  - Click "ADD LEX BUTTON"
+  - Display Text - Amazon Textract
+  - Button Value - QID::Textract.001
+  - Click "Update"
+
+![Add Lex Button](./add_lex_button.png)
+
+- Finally, you will need to add a custom setting.
+  - Click "ADD NEW SETTING"
+  - Click "Save"
+
+![Add New Setting](./add_new_setting.png)

docs/recent_topics_lambda_hook_example/recent topic settings.json

@@ -0,0 +1 @@
+{"topic::Comprehend":"Amazon Comprehend::Comprehend","topic::Kendra":"Amazon Kendra::Kendra","topic::Lex":"Amazon Lex::Lex","topic::Polly":"Amazon Polly::Polly","topic::SageMaker":"Amazon SageMaker::SageMaker","topic::Translate":"Amazon Translate::Translate"}

docs/recent_topics_lambda_hook_example/recent_topics_settings.json

@@ -0,0 +1,8 @@
+{
+  "topic::Comprehend": "Amazon Comprehend::Comprehend",
+  "topic::Kendra": "Amazon Kendra::Kendra",
+  "topic::Lex": "Amazon Lex::Lex",
+  "topic::Polly": "Amazon Polly::Polly",
+  "topic::SageMaker": "Amazon SageMaker::SageMaker",
+  "topic::Translate": "Amazon Translate::Translate"
+}

lambda/aws-sdk-layer/Makefile

@@ -0,0 +1,12 @@
+NAME=$(shell basename $(shell pwd))
+DST=../../build/lambda/$(NAME).zip
+
+RESOURCES := $(shell  find . | grep -v node_modules | grep -v test )
+
+$(DST): $(RESOURCES) 
+	echo "Building $(NAME)"; 
+	npm install -production
+	rm -r ./nodejs || true
+	mkdir ./nodejs 
+	mv node_modules ./nodejs/node_modules 
+	zip -r $(DST) .