Merge pull request #488 from aws-solutions/develop

Update to version v5.2.0.
aws-solutions · Jul 14, 2022 · 771b4b4 · 771b4b4
2 parents 46c3421 + 0d11064
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diff --git a/.gitignore b/.gitignore
@@ -80,5 +80,27 @@ temp/
 **/deployment/global-s3-assets
 **/deployment/regional-s3-assets
 **/deployment/open-source
+
+
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+
 docs/excel_import/~$sample.xlsx
 
+
diff --git a/CHANGELOG.md b/CHANGELOG.md
diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md
@@ -1,8 +1,8 @@
 # Contributing to the QnABot
 
 Contributions to the QnABot should be made via GitHub [pull
-requests](https://github.com/awslabs/aws-ai-qna-bot/pulls) and discussed using
-GitHub [issues](https://github.com/awslabs/aws-ai-qna-bot/issues).
+requests](https://github.com/aws-solutions/qnabot-on-aws/pulls) and discussed using
+GitHub [issues](https://github.com/aws-solutions/qnabot-on-aws/issues).
 
 ## Before you start
 

diff --git a/NOTICE.txt b/NOTICE.txt
@@ -1,4 +1,4 @@
-aws-qnabot
+qnabot-on-aws
 Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
 
 Licensed under the Apache License Version 2.0 (the 'License'). You may not use this file except in compliance
@@ -36,9 +36,11 @@ babel-polyfill the Massachusetts Institute of Technology (MIT) license
 babel-preset-env under the Massachusetts Institute of Technology (MIT) license
 babel-preset-es2015 under the Massachusetts Institute of Technology (MIT) license
 babel-preset-es2015-ie the Massachusetts Institute of Technology (MIT) license
+beautifulsoup under Massachusetts Institute of Technology (MIT) License
 bluebird under the Massachusetts Institute of Technology (MIT) license
 body-parser under the Massachusetts Institute of Technology (MIT) license
 bowser under the Massachusetts Institute of Technology (MIT) license
+canvasapi under Massachusetts Institute of Technology (MIT) License
 cfn-response under the Amazon Software License
 chalk under the Massachusetts Institute of Technology (MIT) license
 chrome-aws-lambda under the Massachusetts Institute of Technology (MIT) license

diff --git a/README.md b/README.md
@@ -6,57 +6,59 @@
 
 This repository contains code for the QnABot, described in the AWS AI blog post [“Creating a Question and Answer Bot with Amazon Lex and Amazon Alexa”](https://aws.amazon.com/blogs/ai/creating-a-question-and-answer-bot-with-amazon-lex-and-amazon-alexa/).
 
-Refer to [Getting Started](#getting-started) to launch your own QnABot, or [Automated Deployment](https://docs.aws.amazon.com/solutions/latest/aws-qnabot/automated-deployment.html) for detailed implementation instructions.
+Refer to [Getting Started](#getting-started) to launch your own QnABot, or [Automated Deployment](https://docs.aws.amazon.com/solutions/latest/qnabot-on-aws/automated-deployment.html) for detailed implementation instructions.
 
-The 5.1.0 release of QnABot provides support for a new mechanism where a Question can set a Lex session attribute. 
+The 5.1.0 release of QnABot provides support for a new mechanism where a Question can set a Lex session attribute.
 
 In prior versions, the use of handlebars in an answer could set a session attribute. For example, the following
 
 "{{setSessionAttr ‘attributeName' ‘attributeValue’}}""
- 
-will set the an attribute called “attributeName” to the value “attributeValue”. The drawback in this approach is that the attribute value could not itself contain nested handle bars. 
+
+will set the an attribute called “attributeName” to the value “attributeValue”. The drawback in this approach is that the attribute value could not itself contain nested handle bars.
 
 In 5.1.0, a Question can now define a set of name/value pairs to set as session attributes when the answer is returned. You’ll see a new field to set a name/value pair plus an “Add” button to define additional name/value pairs and a button to delete a name/value pair. The Value field can contain handlebar statements as well.
 
-The attribute name can be a simple name like “myAttribute” or a complex name like “myAttribute.subAttribute”. Using the dot notation an attribute several levels deep can be set. Note that one can overwrite reserved session attribute names. Avoid using “appContext” or “qnabotcontext” as attribute names. Setting these may have adverse effects on the system.  
+The attribute name can be a simple name like “myAttribute” or a complex name like “myAttribute.subAttribute”. Using the dot notation an attribute several levels deep can be set. Note that one can overwrite reserved session attribute names. Avoid using “appContext” or “qnabotcontext” as attribute names. Setting these may have adverse effects on the system.
 
 Note, the handlebar syntax still works just as it did before. The question configuration just has a new option.
 
 ## Architecture Overview
+
 ![Architecture](docs/architecture.png)
- 
+
 The AWS CloudFormation template deploys the following workflows and services:
 
 1. The admin deploys the solution into their AWS account, opens the Content Designer UI, and uses Amazon Cognito to authenticate.
 
 2. After authentication, Amazon CloudFront
-and Amazon S3 deliver the contents of the Content Designer UI.
+   and Amazon S3 deliver the contents of the Content Designer UI.
 
 3. The admin configures questions and answers in the Content Designer and the UI sends requests to Amazon API Gateway to save the questions and answers.
 
 4. The Content Designer AWS Lambda
-function saves the input in Amazon OpenSearch Service (successor to Amazon ElasticSearch Service) in a questions bank index.
+   function saves the input in Amazon OpenSearch Service (successor to Amazon ElasticSearch Service) in a questions bank index.
 
 5. Users of the chatbot interact with Amazon Lex via the web client UI or Amazon Connect.
 
 6. Amazon Lex forwards requests to the AWS Lambda (Bot Fulfillment) function. (Users can also send requests to this Lambda function via Amazon Alexa devices).
 
 7. The Bot Fulfillment function takes the users input and uses Amazon Comprehend
-and Amazon Translate (if necessary) to translate non-English requests to English and then looks up the answer in in Amazon OpenSearch Service. If Amazon Kendra index is configured and provided at the time of deployment, the Bot Fulfillment function also sends a request to the Amazon Kendra index.
+   and Amazon Translate (if necessary) to translate non-English requests to English and then looks up the answer in in Amazon OpenSearch Service. If Amazon Kendra index is configured and provided at the time of deployment, the Bot Fulfillment function also sends a request to the Amazon Kendra index.
+
+8. User interactions with Bot Fulfillment functions generate logs and metrics data, which is sent to Amazon Kinesis Data Firehose then to Amazon S3 for later data analysis.
 
-8. User interactions with Bot Fulfillment functions generate logs and metrics data, which is sent to Amazon Kinesis Data Firehose then to Amazon S3 for later data analysis. 
 ## Upgrade Notes
 
 During an upgrade, we recommend that existing QnABot content first be exported and downloaded from the Content Designer prior to
 the upgrade. In this release we expect upgrade to be smooth but just in case you should always have your QnABot content preserved.
 
 ## Prerequisites
 
-- Run Linux. (tested on Amazon Linux)
-- Install npm >7.10.0 and node >12.15.1. ([instructions](https://nodejs.org/en/download/))
-- Clone this repo.
-- Set up an AWS account. ([instructions](https://AWS.amazon.com/free/?sc_channel=PS&sc_campaign=acquisition_US&sc_publisher=google&sc_medium=cloud_computing_b&sc_content=AWS_account_bmm_control_q32016&sc_detail=%2BAWS%20%2Baccount&sc_category=cloud_computing&sc_segment=102882724242&sc_matchtype=b&sc_country=US&s_kwcid=AL!4422!3!102882724242!b!!g!!%2BAWS%20%2Baccount&ef_id=WS3s1AAAAJur-Oj2:20170825145941:s))
-- Configure AWS CLI and a local credentials file. ([instructions](https://docs.AWS.amazon.com/cli/latest/userguide/cli-chap-welcome.html))
+-   Run Linux. (tested on Amazon Linux)
+-   Install npm >7.10.0 and node >12.15.1. ([instructions](https://nodejs.org/en/download/))
+-   Clone this repo.
+-   Set up an AWS account. ([instructions](https://AWS.amazon.com/free/?sc_channel=PS&sc_campaign=acquisition_US&sc_publisher=google&sc_medium=cloud_computing_b&sc_content=AWS_account_bmm_control_q32016&sc_detail=%2BAWS%20%2Baccount&sc_category=cloud_computing&sc_segment=102882724242&sc_matchtype=b&sc_country=US&s_kwcid=AL!4422!3!102882724242!b!!g!!%2BAWS%20%2Baccount&ef_id=WS3s1AAAAJur-Oj2:20170825145941:s))
+-   Configure AWS CLI and a local credentials file. ([instructions](https://docs.AWS.amazon.com/cli/latest/userguide/cli-chap-welcome.html))
 
 ## Getting Started
 
@@ -65,26 +67,26 @@ Two approaches can be used to get started. Deploy from pre-created repositories
 ### Pre-created deployment
 
 Sign in to the AWS Management Console and select the button to launch
-the `aws-qnabot.template` AWS CloudFormation template.
+the `qnabot-onaws-main.template` AWS CloudFormation template.
 Alternatively, you can download the template as a starting point for your
 own implementation. The template launches in the US East (N. Virginia) Region by default. To launch the solution in a
 different AWS Region, use the Region selector in the console navigation bar.
 
-<a target="_blank" href="https://us-east-1.console.aws.amazon.com/cloudformation/home?region=us-east-1#/stacks/new?stackName=QnABot&templateURL=https://solutions-reference.s3.amazonaws.com/aws-qnabot/latest/aws-qnabot-main.template"><span><img height="24px" src="https://s3.amazonaws.com/cloudformation-examples/cloudformation-launch-stack.png"/></span></a> 
+<a target="_blank" href="https://us-east-1.console.aws.amazon.com/cloudformation/home?region=us-east-1#/stacks/new?stackName=QnABot&templateURL=https://solutions-reference.s3.amazonaws.com/qnabot-on-aws/latest/qnabot-on-aws-main.template"><span><img height="24px" src="https://s3.amazonaws.com/cloudformation-examples/cloudformation-launch-stack.png"/></span></a>
 
 The solution is supported in the following Regions:
 
-| Region   |
-|----------|
+| Region            |
+| ----------------- |
 | Northern Virginia |
-| Oregon |
-| Ireland |
-| Sydney |
-| London |
-| Frankfurt |
-| Singapore |
-| Tokyo |
-| Canada Central |
+| Oregon            |
+| Ireland           |
+| Sydney            |
+| London            |
+| Frankfurt         |
+| Singapore         |
+| Tokyo             |
+| Canada Central    |
 
 ### Clone the git repo and build a version
 
@@ -102,20 +104,20 @@ npm run config
 
 now edit config.json with you information.
 
-| param | description |
-|-------|-------------|
-|region | the AWS region to launch stacks in |
-|profile| the AWS credential profile to use |
-|namespace| a logical name space to run your templates in such as dev, test and/or prod |
-|devEmail(required) | the email to use when creating admin users in automated stack launches |
+| param              | description                                                                 |
+| ------------------ | --------------------------------------------------------------------------- |
+| region             | the AWS region to launch stacks in                                          |
+| profile            | the AWS credential profile to use                                           |
+| namespace          | a logical name space to run your templates in such as dev, test and/or prod |
+| devEmail(required) | the email to use when creating admin users in automated stack launches      |
 
 Next, use the following command to launch a CloudFormation template to create the S3 bucket to be used for lambda code and CloudFormation templates. Wait for this template to complete (you can watch progress from the command line or [AWS CloudFormation console](https://console.AWS.amazon.com/cloudformation/home))
 
 ```shell
 npm run bootstrap
 ```
 
-Finally, use the following command to launch template to deploy the QnA bot in your AWS account. When the stack has completed you will be able to log into the Designer UI (The URL is an output of the template). A temporary password to the email in your config.json:
+Finally, use the following command to launch template to deploy the QnAbot in your AWS account. When the stack has completed you will be able to log into the Designer UI (The URL is an output of the template). A temporary password to the email in your config.json:
 
 ```shell
 npm run up
@@ -131,26 +133,28 @@ npm run update
 
 Currently the only browsers supported are:
 
-- Chrome
-- FireFox
-We are currently working on adding Microsoft Edge support.
+-   Chrome
+-   FireFox
+    We are currently working on adding Microsoft Edge support.
 
 ## Built With
 
-- [Vue](https://vuejs.org/)
-- [Webpack](https://webpack.github.io/)
+-   [Vue](https://vuejs.org/)
+-   [Webpack](https://webpack.github.io/)
 
 ## License
 
 Refer to [LICENSE.md](LICENSE.md) file for details.
 
 ## New features
+
 Refer to [CHANGELOG.md](CHANGELOG.md) file for details of new features in each version.
 
 A [workshop](https://qnabot.workshop.aws) is available
 that will walk you through QnABot features.
 
 ## Known Behavior
+
 When deploying the Cloudformation stack rarely, the custom resource creating Amazon OpenSearch Service resources timesout and causes the deployment fail. Deleting the failed deployment and re-deploying the Cloudformation stack fixes this issue.
 
 ---
@@ -167,4 +171,4 @@ Unless required by applicable law or agreed to in writing, software
 distributed under the License is distributed on an "AS IS" BASIS,
 WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 See the License for the specific language governing permissions and
-limitations under the License.
+limitations under the License.