Lingoport Wiki - User contributions [en]

Azure DevOps Server (TFS) Data Source Credential

2024-06-05T17:16:50Z

Rdaly: /* Creating a project using an Azure data source credential */

= Creating a Azure Repos Data Source Credential =
[Administrator]

The Administrator can create the data source credentials by selecting the [[File:CreateIcon.jpg|30px]] ('''Create new credential''') button on the Manage Data Source Credentials page.

'''Select the Azure Repos card'''

[[File:AzureCard.jpg|100px]]

[[File:AzureUsername.jpg|600px]]

'''Enter a Username the the Personal access token.'''
* Also enter the Server URL
* '''Next'''

[[File:AzureName.jpg|600px]]

'''Give the new credential a name'''
* Assign it to applicable managers
* '''Create'''

The system should return to the '''Manage Data Source Credentials''' page with "Credential created" note and the new credential should be listed.

= Creating a project using an Azure data source credential =
Select the [[File:LingoportIcon.jpg|50px]] to get to the '''Projects''' page and select the [[File:CreateIcon.jpg|30px]] to '''Create new project'''. The first step in the process will come up.

Step 1: Select the Azure Repos data source

[[File:SelectAzureRepos.jpg|600px]]

'''Next'''

Step 2: Choose an Azure repository

[[File:CreateAzureProject.jpg|600px]]

*'''Repository URL:''' In Azure, in the project, when the project is cloned, the resulting URL looks like: '''<nowiki>https://username@dev.azure.com/user/ACME.project/_git/proj</nowiki>'''. In Command Center, for the URL, remove the username: '''<nowiki>https://dev.azure.com/user/ACME.project/_git/proj</nowiki>'''.
*'''Project Branch:''' As with Git repositories, this value is required. It might be master or another created branch.

'''Next'''

Now continue with the Step-by-Step instructions.

[[Name The Project and Type |Step 3: Name the Project and select the run type]]

AWS S3 Data Source Credential

2024-06-05T17:16:06Z

Rdaly: /* Creating a project using the AWS S3 credential */

= Git to AWS S3 buckets =

AWS S3 may be used when the actual repository (Git, etc.) may not be reachable by Command Center directly. In that case, AWS S3 may be used as a bridge between the repository and Command Center.
For more information on how to set up the process between a Git repository and AWS S3, see:
* [[ Git to AWS S3 System ]]

In order to use this system from Command Center, a project needs to be created with an AWS S3 Data Source Credential.

= Creating an AWS S3 Data Source Credential =
[Administrator]

The Administrator can create the data source credentials by selecting the [[File:CreateIcon.jpg|30px]] ('''Create new credential''') button on the Manage Data Source Credentials page.

'''Select the AWS S3 card'''

[[File:AWS S3 Card.png|100px]]

This will start the configuration process

[[File:AWS S3 Step2.png|600px]]

*Enter a Region, an Access Key, and a Secret Key
These elements should be provided by an AWS administrator who has configured the AWS S3 bucket.

* '''Next'''

[[File:AWS S3 Step3.png|600px]]

'''Give the new credential a name'''
* Assign it to applicable managers
* '''Create'''

The system should return to the '''Manage Data Source Credentials''' page with "Credential created" note and the new credential should be listed.

= Creating a project using the AWS S3 credential =

Select the [[File:LingoportIcon.jpg|50px]] to get to the '''Projects''' page and select the [[File:CreateIcon.jpg|30px]] to '''Create new project'''. The first step in the process will come up.

Before creating the project, the AWS S3 bucket must be configured correctly. The bucket might contain '''to_localyzer''' and '''from_localyzer''' folders that contain resource files to be translated. These are the default names and can be anything as long as they are indicated in the project configuration.

Step 1: Select the AWS S3 data source credential

[[File:SelectAWSs3.jpg|600px]]

'''Next'''

Step 2: Specify the bucket and the optional directories

[[File:SpecifyBucket.jpg|600px]]

*'''Bucket name:''' This is the name of the bucket as shown in AWS S3
*'''Bucket directory''' and '''Additional upload directory:''' These are optional. But if there are values in the fields, they must exist as folders in the AWS S3 bucket.

'''Next'''

Now continue with the Step-by-step instructions.

[[Name The Project and Type |Step 3: Name the Project and select the run type]]

GitHub Data Source Credential

2024-06-05T17:14:54Z

Rdaly:

= Creating a GitHub Data Source Credential =
[Administrator]

The Administrator can create the data source credentials by selecting the [[File:CreateIcon.jpg|30px]] ('''Create new credential''') button on the Manage Data Source Credentials page.

'''Select the Github card'''

[[File:GithubCard.jpg|100px]]

[[File:GithubUsername.jpg|600px]]

'''Enter a Username the the Personal access token.'''
* The Personal access token is not the password.
** To create a personal access token, log in to https://github.com
** At the username icon, select the pulldown and select '''Settings'''
** At the left side of the screen, select '''Developer Settings''' at the bottom of the list
** Then select '''Personal access tokens''' at the left and generate a new token.
* If not using https://github.com/, select the '''Connect to GitHub Enterprise Server''' and fill in the information
* '''Next'''

[[File:GithubName.jpg|600px]]

'''Give the new credential a name'''
* Assign it to applicable managers
* '''Create'''

The system should return to the '''Manage Data Source Credentials''' page with "Credential created" note and the new credential should be listed.

= Creating a project using the GitHub credential =

Follow the Step-by-Step instructions to create a project using your GitHub credential.

[[Step_by_Step_Project_Creation | Step by Step Project Creation ]]

Azure DevOps Server (TFS) Data Source Credential

2024-06-05T17:09:06Z

Rdaly: /* Creating a project using an Azure data source credential */

= Creating a Azure Repos Data Source Credential =
[Administrator]

The Administrator can create the data source credentials by selecting the [[File:CreateIcon.jpg|30px]] ('''Create new credential''') button on the Manage Data Source Credentials page.

'''Select the Azure Repos card'''

[[File:AzureCard.jpg|100px]]

[[File:AzureUsername.jpg|600px]]

'''Enter a Username the the Personal access token.'''
* Also enter the Server URL
* '''Next'''

[[File:AzureName.jpg|600px]]

'''Give the new credential a name'''
* Assign it to applicable managers
* '''Create'''

The system should return to the '''Manage Data Source Credentials''' page with "Credential created" note and the new credential should be listed.

= Creating a project using an Azure data source credential =

When creating a project with an Azure data source credential, the second step asks about the Repository URL:

Step 1: Select the Azure Repos data source

[[File:SelectAzureRepos.jpg|600px]]

'''Next'''

Step 2: Choose an Azure repository

[[File:CreateAzureProject.jpg|600px]]

*'''Repository URL:''' In Azure, in the project, when the project is cloned, the resulting URL looks like: '''<nowiki>https://username@dev.azure.com/user/ACME.project/_git/proj</nowiki>'''. In Command Center, for the URL, remove the username: '''<nowiki>https://dev.azure.com/user/ACME.project/_git/proj</nowiki>'''.
*'''Project Branch:''' As with Git repositories, this value is required. It might be master or another created branch.

'''Next'''

Now continue with the Step-by-Step instructions.

[[Name The Project and Type |Step 3: Name the Project and select the run type]]

Azure DevOps Server (TFS) Data Source Credential

2024-06-05T17:08:37Z

Rdaly: /* Creating a project using an Azure data source credential */

= Creating a Azure Repos Data Source Credential =
[Administrator]

The Administrator can create the data source credentials by selecting the [[File:CreateIcon.jpg|30px]] ('''Create new credential''') button on the Manage Data Source Credentials page.

'''Select the Azure Repos card'''

[[File:AzureCard.jpg|100px]]

[[File:AzureUsername.jpg|600px]]

'''Enter a Username the the Personal access token.'''
* Also enter the Server URL
* '''Next'''

[[File:AzureName.jpg|600px]]

'''Give the new credential a name'''
* Assign it to applicable managers
* '''Create'''

The system should return to the '''Manage Data Source Credentials''' page with "Credential created" note and the new credential should be listed.

= Creating a project using an Azure data source credential =

When creating a project with an Azure data source credential, the second step asks about the Repository URL:

Step 1: Select the Azure Repost data source

[[File:SelectAzureRepos.jpg|600px]]

'''Next'''

Step 2: Choose an Azure repository

[[File:CreateAzureProject.jpg|600px]]

*'''Repository URL:''' In Azure, in the project, when the project is cloned, the resulting URL looks like: '''<nowiki>https://username@dev.azure.com/user/ACME.project/_git/proj</nowiki>'''. In Command Center, for the URL, remove the username: '''<nowiki>https://dev.azure.com/user/ACME.project/_git/proj</nowiki>'''.
*'''Project Branch:''' As with Git repositories, this value is required. It might be master or another created branch.

'''Next'''

Now continue with the Step-by-Step instructions.

[[Name The Project and Type |Step 3: Name the Project and select the run type]]

Azure DevOps Server (TFS) Data Source Credential

2024-06-05T17:08:10Z

Rdaly: /* Creating a project using an Azure data source credential */

= Creating a Azure Repos Data Source Credential =
[Administrator]

The Administrator can create the data source credentials by selecting the [[File:CreateIcon.jpg|30px]] ('''Create new credential''') button on the Manage Data Source Credentials page.

'''Select the Azure Repos card'''

[[File:AzureCard.jpg|100px]]

[[File:AzureUsername.jpg|600px]]

'''Enter a Username the the Personal access token.'''
* Also enter the Server URL
* '''Next'''

[[File:AzureName.jpg|600px]]

'''Give the new credential a name'''
* Assign it to applicable managers
* '''Create'''

The system should return to the '''Manage Data Source Credentials''' page with "Credential created" note and the new credential should be listed.

= Creating a project using an Azure data source credential =

When creating a project with an Azure data source credential, the second step asks about the Repository URL:

Step 1: Select the Azure Repost data source

[[File:SelectAzureRepos.jpg|600px]]

'''Next'''

Step 2: Choose an Azure repository

[[File:CreateAzureProject.jpg|600px]]

*'''Repository URL:''' In Azure, in the project, when the project is cloned, the resulting URL looks like: '''<nowiki>https://username@dev.azure.com/user/ACME.project/_git/proj</nowiki>'''. In Command Center, for the URL, remove the username: '''<nowiki>https://dev.azure.com/user/ACME.project/_git/proj</nowiki>'''.
*'''Project Branch:''' As with Git repositories, this value is required. It might be master or another created branch.

'''Next'''

Now continue with the Step-by-step instructions.

[[Name The Project and Type |Step 3: Name the Project and select the run type]]

Azure DevOps Server (TFS) Data Source Credential

2024-06-05T17:07:56Z

Rdaly: /* Creating a project using an Azure data source credential */

= Creating a Azure Repos Data Source Credential =
[Administrator]

The Administrator can create the data source credentials by selecting the [[File:CreateIcon.jpg|30px]] ('''Create new credential''') button on the Manage Data Source Credentials page.

'''Select the Azure Repos card'''

[[File:AzureCard.jpg|100px]]

[[File:AzureUsername.jpg|600px]]

'''Enter a Username the the Personal access token.'''
* Also enter the Server URL
* '''Next'''

[[File:AzureName.jpg|600px]]

'''Give the new credential a name'''
* Assign it to applicable managers
* '''Create'''

The system should return to the '''Manage Data Source Credentials''' page with "Credential created" note and the new credential should be listed.

= Creating a project using an Azure data source credential =

When creating a project with an Azure data source credential, the second step asks about the Repository URL:

Step 1: Select the Azure Repost data source

[[File:SelectAzureRepos.jpg|600px]]

Next

Step 2: Choose an Azure repository

[[File:CreateAzureProject.jpg|600px]]

*'''Repository URL:''' In Azure, in the project, when the project is cloned, the resulting URL looks like: '''<nowiki>https://username@dev.azure.com/user/ACME.project/_git/proj</nowiki>'''. In Command Center, for the URL, remove the username: '''<nowiki>https://dev.azure.com/user/ACME.project/_git/proj</nowiki>'''.
*'''Project Branch:''' As with Git repositories, this value is required. It might be master or another created branch.

'''Next'''

Now continue with the Step-by-step instructions.

[[Name The Project and Type |Step 3: Name the Project and select the run type]]

Azure DevOps Server (TFS) Data Source Credential

2024-06-05T17:04:25Z

Rdaly: /* Creating a project using an Azure data source credential */

= Creating a Azure Repos Data Source Credential =
[Administrator]

The Administrator can create the data source credentials by selecting the [[File:CreateIcon.jpg|30px]] ('''Create new credential''') button on the Manage Data Source Credentials page.

'''Select the Azure Repos card'''

[[File:AzureCard.jpg|100px]]

[[File:AzureUsername.jpg|600px]]

'''Enter a Username the the Personal access token.'''
* Also enter the Server URL
* '''Next'''

[[File:AzureName.jpg|600px]]

'''Give the new credential a name'''
* Assign it to applicable managers
* '''Create'''

The system should return to the '''Manage Data Source Credentials''' page with "Credential created" note and the new credential should be listed.

= Creating a project using an Azure data source credential =

When creating a project with an Azure data source credential, the second step asks about the Repository URL:

Step 1: Select the Azure Repost data source

[[File:SelectAzureRepos.jpg|600px]]

Next

Step 2: Choose an Azure repository

[[File:CreateAzureProject.jpg|600px]]

In Azure, in the project, when the project is cloned, the resulting URL looks like: '''<nowiki>https://username@dev.azure.com/user/ACME.project/_git/proj</nowiki>'''. In Command Center, for the URL, remove the username: '''<nowiki>https://dev.azure.com/user/ACME.project/_git/proj</nowiki>'''.

'''Next'''

Now continue with the Step-by-step instructions.

[[Name The Project and Type |Step 3: Name the Project and select the run type]]

Azure DevOps Server (TFS) Data Source Credential

2024-06-05T17:04:07Z

Rdaly: /* Creating a project using an Azure data source credential */

= Creating a Azure Repos Data Source Credential =
[Administrator]

The Administrator can create the data source credentials by selecting the [[File:CreateIcon.jpg|30px]] ('''Create new credential''') button on the Manage Data Source Credentials page.

'''Select the Azure Repos card'''

[[File:AzureCard.jpg|100px]]

[[File:AzureUsername.jpg|600px]]

'''Enter a Username the the Personal access token.'''
* Also enter the Server URL
* '''Next'''

[[File:AzureName.jpg|600px]]

'''Give the new credential a name'''
* Assign it to applicable managers
* '''Create'''

The system should return to the '''Manage Data Source Credentials''' page with "Credential created" note and the new credential should be listed.

== Creating a project using an Azure data source credential ==

When creating a project with an Azure data source credential, the second step asks about the Repository URL:

Step 1: Select the Azure Repost data source

[[File:SelectAzureRepos.jpg|600px]]

Next

Step2: Choose an Azure repository

[[File:CreateAzureProject.jpg|600px]]

In Azure, in the project, when the project is cloned, the resulting URL looks like: '''<nowiki>https://username@dev.azure.com/user/ACME.project/_git/proj</nowiki>'''. In Command Center, for the URL, remove the username: '''<nowiki>https://dev.azure.com/user/ACME.project/_git/proj</nowiki>'''.

'''Next'''

Now continue with the Step-by-step instructions.

[[Name The Project and Type |Step 3: Name the Project and select the run type]]

Azure DevOps Server (TFS) Data Source Credential

2024-06-05T17:02:08Z

Rdaly: /* Creating a project using an Azure data source credential */

= Creating a Azure Repos Data Source Credential =
[Administrator]

The Administrator can create the data source credentials by selecting the [[File:CreateIcon.jpg|30px]] ('''Create new credential''') button on the Manage Data Source Credentials page.

'''Select the Azure Repos card'''

[[File:AzureCard.jpg|100px]]

[[File:AzureUsername.jpg|600px]]

'''Enter a Username the the Personal access token.'''
* Also enter the Server URL
* '''Next'''

[[File:AzureName.jpg|600px]]

'''Give the new credential a name'''
* Assign it to applicable managers
* '''Create'''

The system should return to the '''Manage Data Source Credentials''' page with "Credential created" note and the new credential should be listed.

== Creating a project using an Azure data source credential ==

When creating a project with an Azure data source credential, the second step asks about the Repository URL:

Step1: Select the Data Source

[[File:SelectAzureRepos.jpg|600px]]

[[File:CreateAzureProject.jpg|600px]]

In Azure, in the project, when the project is cloned, the resulting URL looks like: '''<nowiki>https://username@dev.azure.com/user/ACME.project/_git/proj</nowiki>'''. In Command Center, for the URL, remove the username: '''<nowiki>https://dev.azure.com/user/ACME.project/_git/proj</nowiki>'''.

File:SelectAzureRepos.jpg

2024-06-05T17:00:58Z

Rdaly:

Team Foundation Server Data Source Credential

2024-06-05T16:41:07Z

Rdaly:

= Creating an Azure DevOps Server Team Foundation Server (TFS) Data Source Credential =
[Administrator]

The Administrator can create the data source credentials by selecting the [[File:CreateIcon.jpg|30px]] ('''Create new credential''') button on the Manage Data Source Credentials page.

'''Select the Azure DevOps Server (TFS) card'''

[[File:Azure devops tfs card.png|100px]]

[[File:TFS azure info page.png|800px]]
'''Enter a Username, Token and the TFS Callback URL '''
* '''Select Next'''

[[File:TFS azure info pg2.png|800px]]
'''Give the new credential a name'''

* '''Assign it to applicable managers'''
* '''Select Create'''

The system should return to the '''Manage Data Source Credentials''' page with "Credential created" note and the new credential should be listed.

If during a project initial setup there is an error returned indicating the Clone script FAILED, copy the contents shown under Clone errors and follow the instructions under "Additional EULA Acceptance Step":

'''Additional EULA Acceptance Step:'''

When TFS connects for the first time there is a EULA that is passed from Microsoft which must be accepted before any files can be pulled from the repository. Failure to perform this step will result in an error code 100 being returned from the TFS when a project attempts to leverage it to access a file repository. If this occurs capture the error log as there are a number of paramaters that are displayed which will be required to accept the EULA manually.

Note that this step requires logging into the container from the command line.

The following steps must be performed manually to accept the EULA

'''Log into the VM containing Docker and the application at the command line:'''

ssh into the VM that contains Docker and the Command Center application.

'''Log into the Docker container:'''

Here is the command string for logging into Docker

<code>sudo docker exec -it `sudo docker ps | grep command-center | awk '{print $1}' ` bash </code>

Once inside the container refer to the Clone errors: section in the log output for the variable values

cd to the ${workspacesDir}

Run the below command filling in the variables with the values from the Clone errors output as well. The "token" is not shown in the error output for security reasons.

<code>${TF} workspace -new -comment:"New CC Workspace" -collection:${url} -location:local ${tfsWorkspace} "-login:${username},${token}"</code>

When this runs there should be a return back indicating that the End User License Agreement must be accepted and you need to run tf eula to accept it.

Run this command

<code>${TF} eula</code>

The EULA will be displayed. Go to the end of the document and accept the EULA

At this point you can exit out of the container by typing exit and then exit the VM.

'''Confirmation and Validation of EULA acceptance:'''

The TFS connection should now function as expected in the projects so go back into the Project setup and continue with the configuration. Everything should now be functional

AWS S3 Data Source Credential

2024-06-05T16:33:51Z

Rdaly: /* Creating a project using the AWS S3 credential */

= Git to AWS S3 buckets =

AWS S3 may be used when the actual repository (Git, etc.) may not be reachable by Command Center directly. In that case, AWS S3 may be used as a bridge between the repository and Command Center.
For more information on how to set up the process between a Git repository and AWS S3, see:
* [[ Git to AWS S3 System ]]

In order to use this system from Command Center, a project needs to be created with an AWS S3 Data Source Credential.

= Creating an AWS S3 Data Source Credential =
[Administrator]

The Administrator can create the data source credentials by selecting the [[File:CreateIcon.jpg|30px]] ('''Create new credential''') button on the Manage Data Source Credentials page.

'''Select the AWS S3 card'''

[[File:AWS S3 Card.png|100px]]

This will start the configuration process

[[File:AWS S3 Step2.png|600px]]

*Enter a Region, an Access Key, and a Secret Key
These elements should be provided by an AWS administrator who has configured the AWS S3 bucket.

* '''Next'''

[[File:AWS S3 Step3.png|600px]]

'''Give the new credential a name'''
* Assign it to applicable managers
* '''Create'''

The system should return to the '''Manage Data Source Credentials''' page with "Credential created" note and the new credential should be listed.

= Creating a project using the AWS S3 credential =

Before creating the project, the AWS S3 bucket must be configured correctly. The bucket might contain '''to_localyzer''' and '''from_localyzer''' folders that contain resource files to be translated. These are the default names and can be anything as long as they are indicated in the project configuration.

Step 1: Select the AWS S3 data source credential

[[File:SelectAWSs3.jpg|600px]]

'''Next'''

Step 2: Specify the bucket and the optional directories

[[File:SpecifyBucket.jpg|600px]]

*'''Bucket name:''' This is the name of the bucket as shown in AWS S3
*'''Bucket directory''' and '''Additional upload directory:''' These are optional. But if there are values in the fields, they must exist as folders in the AWS S3 bucket.

'''Next'''

Now continue with the Step-by-step instructions.

[[Name The Project and Type |Step 3: Name the Project and select the run type]]

AWS S3 Data Source Credential

2024-06-05T16:32:22Z

Rdaly: /* Creating a project using the AWS S3 credential */

= Git to AWS S3 buckets =

AWS S3 may be used when the actual repository (Git, etc.) may not be reachable by Command Center directly. In that case, AWS S3 may be used as a bridge between the repository and Command Center.
For more information on how to set up the process between a Git repository and AWS S3, see:
* [[ Git to AWS S3 System ]]

In order to use this system from Command Center, a project needs to be created with an AWS S3 Data Source Credential.

= Creating an AWS S3 Data Source Credential =
[Administrator]

The Administrator can create the data source credentials by selecting the [[File:CreateIcon.jpg|30px]] ('''Create new credential''') button on the Manage Data Source Credentials page.

'''Select the AWS S3 card'''

[[File:AWS S3 Card.png|100px]]

This will start the configuration process

[[File:AWS S3 Step2.png|600px]]

*Enter a Region, an Access Key, and a Secret Key
These elements should be provided by an AWS administrator who has configured the AWS S3 bucket.

* '''Next'''

[[File:AWS S3 Step3.png|600px]]

'''Give the new credential a name'''
* Assign it to applicable managers
* '''Create'''

The system should return to the '''Manage Data Source Credentials''' page with "Credential created" note and the new credential should be listed.

= Creating a project using the AWS S3 credential =

Before creating the project, the AWS S3 bucket must be configured correctly. The bucket might contain '''to_localyzer''' and '''from_localyzer''' folders that contain resource files to be translated. These are the default names and can be anything as long as they are indicated in the project configuration.

Step 1: Select the AWS S3 data source credential

[[File:SelectAWSs3.jpg|600px]]

Step 2: Specify the bucket and the optional directories

[[File:SpecifyBucket.jpg|600px]]

*'''Bucket name:''' This is the name of the bucket as shown in AWS S3
*'''Bucket directory''' and '''Additional upload directory:''' These are optional. But if there are values in the fields, they must exist as folders in the AWS S3 bucket.

Step3: Name the project and set the run type

[[Name The Project and Type |Step 3: Name the Project]]

AWS S3 Data Source Credential

2024-06-05T16:29:06Z

Rdaly: /* Creating a project using the AWS S3 credential */

= Git to AWS S3 buckets =

AWS S3 may be used when the actual repository (Git, etc.) may not be reachable by Command Center directly. In that case, AWS S3 may be used as a bridge between the repository and Command Center.
For more information on how to set up the process between a Git repository and AWS S3, see:
* [[ Git to AWS S3 System ]]

In order to use this system from Command Center, a project needs to be created with an AWS S3 Data Source Credential.

= Creating an AWS S3 Data Source Credential =
[Administrator]

The Administrator can create the data source credentials by selecting the [[File:CreateIcon.jpg|30px]] ('''Create new credential''') button on the Manage Data Source Credentials page.

'''Select the AWS S3 card'''

[[File:AWS S3 Card.png|100px]]

This will start the configuration process

[[File:AWS S3 Step2.png|600px]]

*Enter a Region, an Access Key, and a Secret Key
These elements should be provided by an AWS administrator who has configured the AWS S3 bucket.

* '''Next'''

[[File:AWS S3 Step3.png|600px]]

'''Give the new credential a name'''
* Assign it to applicable managers
* '''Create'''

The system should return to the '''Manage Data Source Credentials''' page with "Credential created" note and the new credential should be listed.

= Creating a project using the AWS S3 credential =

Before creating the project, the AWS S3 bucket must be configured correctly. The bucket might contain '''to_localyzer''' and '''from_localyzer''' folders that contain resource files to be translated. These are the default names and can be anything as long as they are indicated in the project configuration.

Step 1: Select the AWS S3 data source credential

[[File:SelectAWSs3.jpg|600px]]

Step 2: Specify the bucket and the optional directories

[[File:SpecifyBucket.jpg|600px]]

*'''Bucket name:''' This is the name of the bucket as shown in AWS S3
*'''Bucket directory''' and '''Additional upload directory:''' These are optional. But if there are values in the fields, they must exist as folders in the AWS S3 bucket.

File:SpecifyBucket.jpg

2024-06-05T16:25:01Z

Rdaly:

AWS S3 Data Source Credential

2024-06-05T16:24:25Z

Rdaly:

= Git to AWS S3 buckets =

AWS S3 may be used when the actual repository (Git, etc.) may not be reachable by Command Center directly. In that case, AWS S3 may be used as a bridge between the repository and Command Center.
For more information on how to set up the process between a Git repository and AWS S3, see:
* [[ Git to AWS S3 System ]]

In order to use this system from Command Center, a project needs to be created with an AWS S3 Data Source Credential.

= Creating an AWS S3 Data Source Credential =
[Administrator]

The Administrator can create the data source credentials by selecting the [[File:CreateIcon.jpg|30px]] ('''Create new credential''') button on the Manage Data Source Credentials page.

'''Select the AWS S3 card'''

[[File:AWS S3 Card.png|100px]]

This will start the configuration process

[[File:AWS S3 Step2.png|600px]]

*Enter a Region, an Access Key, and a Secret Key
These elements should be provided by an AWS administrator who has configured the AWS S3 bucket.

* '''Next'''

[[File:AWS S3 Step3.png|600px]]

'''Give the new credential a name'''
* Assign it to applicable managers
* '''Create'''

The system should return to the '''Manage Data Source Credentials''' page with "Credential created" note and the new credential should be listed.

= Creating a project using the AWS S3 credential =

Before creating the project, the AWS S3 bucket must be configured correctly. The bucket might contain '''to_localyzer''' and '''from_localyzer''' folders that contain resource files to be translated. These are the default names and can be anything as long as they are indicated in the project configuration.

Step 1: Select the AWS S3 data source credential

[[File:SelectAWSs3.jpg|600px]]

Step 2: Specify the bucket and the optional directories

[[File:SpecifyBucket.jpg|600px]]

AWS S3 Data Source Credential

2024-06-05T16:12:24Z

Rdaly: /* Creating a project using the AWS S3 credential */

= Git to AWS S3 buckets =

AWS S3 may be used when the actual repository (Git, etc.) may not be reachable by Command Center directly. In that case, AWS S3 may be used as a bridge between the repository and Command Center.
For more information on how to set up the process between a Git repository and AWS S3, see:
* [[ Git to AWS S3 System ]]

In order to use this system from Command Center, a project needs to be created with an AWS S3 Data Source Credential.

= Creating an AWS S3 Data Source Credential =
[Administrator]

The Administrator can create the data source credentials by selecting the [[File:CreateIcon.jpg|30px]] ('''Create new credential''') button on the Manage Data Source Credentials page.

'''Select the AWS S3 card'''

[[File:AWS S3 Card.png|100px]]

This will start the configuration process

[[File:AWS S3 Step2.png|600px]]

*Enter a Region, an Access Key, and a Secret Key
These elements should be provided by an AWS administrator who has configured the AWS S3 bucket.

* '''Next'''

[[File:AWS S3 Step3.png|600px]]

'''Give the new credential a name'''
* Assign it to applicable managers
* '''Create'''

The system should return to the '''Manage Data Source Credentials''' page with "Credential created" note and the new credential should be listed.

= Creating a project using the AWS S3 credential =

Before creating the project, the AWS S3 bucket must be configured correctly. The bucket must contain '''to_localyzer''' and '''from_localyzer''' folders that contain resource files to be translated. These are the default names and can be anything as long as they are indicated in the project configuration.

Step 1: Select the AWS S3 data source credential

File:SelectAWSs3.jpg

File:SelectAWSs3.jpg

2024-06-05T16:11:30Z

Rdaly:

AWS S3 Data Source Credential

2024-06-05T16:10:49Z

Rdaly:

Data Source Credentials

2024-06-05T16:00:47Z

Rdaly: /* Create and Configure Data Source Credentials */

= Introduction =

The Data Source Credentials are the permissions that are used to connect to the repository where code is stored. One of the most common Data Source Credentials is GitHub.

Command Center supports the following data source credentials:
* AWS S3
* Azure Repos
* Custom Git
* Gerrit
* GitHub
* Gitlab
* Subversion

[[File:CCDataSourceCredentials.jpg|600px|center]]

= View Data Source Credentials =
[Administrator, Manager]

[[File:ManageDataSourceCredentials.jpg|600px|center]]

Only the Administrator user can see the list of all the data source credentials. A Manager can see only the credentials that they are defined as an accessor.

= Create and Configure Data Source Credentials =
[Administrator]

[[File:Data-sourcesv2.jpg|700px|center]]

In order to work with data source credentials. the system must be in Maintenance mode. The Administrator can create the data source credentials by selecting the [[File:CreateIcon.jpg|30px]] (Create new credential) button on the Manage Data Source Credentials page. The first step is to indicate the data source type.

For more details on configuring the specific data source credential:

* [[ AWS_S3_Data_Source_Credential | AWS S3]]
* [[ Team_Foundation_Server_Data_Source_Credential | Azure DevOps Server (TFS)]]
* [[ Azure_DevOps_Server_(TFS)_Data_Source_Credential | Azure Repos ]]
* [[ Custom_Git_Data_Source_Credential | Custom Git]]
* [[ Gerrit_Data_Source_Credential | Gerrit ]]
* [[ GitHub_Data_Source_Credential | GitHub]]
* [[ Gitlab_Data_Source_Credential | GitLab]]
* [[ Subversion_Data_Source_Credential | Subversion]]

== Edit Credentials ==

Credentials can only be edited when the system is in Maintenance mode which will be indicated at the top of the screen. The Administrator user can hover over the credential to change and the Edit button will appear.

[[File:ViewDataSourceCredential.jpg|700px|center]]

Alternatively, if the Administrator selects the name of the Data Source Credential, an '''Edit credentia'''l button will come up.

[[File:EditDataCredentials.jpg|700px|center]]

The Administrator can change:
* Name of the credential
* Type of credential and the username and personal access token
* Which manager users can access the credential
** The Search box allows the administrator to search in the Unassigned accessors

== Delete Credentials ==

Check the box next to the credentials from the list to be deleted and the delete icon will appear at the top of the screen. Select the icon. If the credential is being used by a project or a system file, it will not be able to be deleted.

Alternatively, select the credential name, in Maintenance mode, and the Edit Credential button. Or, select the Edit button from the list of credentials. Select the Delete button. If the credential is being used by a project or a system file, it will not be able to be deleted.

== Assign Credentials ==

Credentials can only be assigned to Manager users. Credentials can be assigned to managers two ways:
# When creating or editing the credential in Data Source Credentials
# When creating or editing the Manager user in Users & Teams

= Search and Sort Data Source Credentials =

[[File:SearchDataSourceCredentials.jpg|700px|center]]

A search can be done of all the data source credentials. In this example, all credentials with 'github' in the name was searched for.

[[File:SortDataSourceCredentials.jpg|700px|center]]

Teams can be sorted in ascending or descending order by the credential name, type, number of accessors and the number of projects.

[[Machine_Translation_and_Translation_Management_System| Next: Translation Management Systems and Machine Translation]]

Data Source Credentials

2024-06-05T15:59:45Z

Rdaly: /* Create and Configure Data Source Credentials */

= Introduction =

The Data Source Credentials are the permissions that are used to connect to the repository where code is stored. One of the most common Data Source Credentials is GitHub.

Command Center supports the following data source credentials:
* AWS S3
* Azure Repos
* Custom Git
* Gerrit
* GitHub
* Gitlab
* Subversion

[[File:CCDataSourceCredentials.jpg|600px|center]]

= View Data Source Credentials =
[Administrator, Manager]

[[File:ManageDataSourceCredentials.jpg|600px|center]]

Only the Administrator user can see the list of all the data source credentials. A Manager can see only the credentials that they are defined as an accessor.

= Create and Configure Data Source Credentials =
[Administrator]

[[File:Data-sourcesv2.jpg|700px|center]]

In order to work with data source credentials. the system must be in Maintenance mode. The Administrator can create the data source credentials by selecting the [[File:CreateIcon.jpg|30px]] (Create new credential) button on the Manage Data Source Credentials page. The first step is to indicate the data source type.

For more details on configuring the specific data source credential:

* [[ AWS_S3_Data_Source_Credential | AWS S3]]
* [[ Team_Foundation_Server_Data_Source_Credential | Azure DevOps Server (TFS)]]
* [[ Azure_DevOps_Server_(TFS)_Data_Source_Credential | Azure Repos ]]
* [[ Custom_Git_Data_Source_Credential | Custom Git]]
* [[ Gerrit_Data_Source_Credential | Gerrit ]]
* [[ GitHub_Data_Source_Credential | GitHub]]
* [[ Gitlab_Data_Source_Credential | GitLab]]
* [[ Team_Foundation_Server_Data_Source_Credential | Team Foundation Server]]
* [[ Subversion_Data_Source_Credential | Subversion]]

== Edit Credentials ==

Credentials can only be edited when the system is in Maintenance mode which will be indicated at the top of the screen. The Administrator user can hover over the credential to change and the Edit button will appear.

[[File:ViewDataSourceCredential.jpg|700px|center]]

Alternatively, if the Administrator selects the name of the Data Source Credential, an '''Edit credentia'''l button will come up.

[[File:EditDataCredentials.jpg|700px|center]]

The Administrator can change:
* Name of the credential
* Type of credential and the username and personal access token
* Which manager users can access the credential
** The Search box allows the administrator to search in the Unassigned accessors

== Delete Credentials ==

Check the box next to the credentials from the list to be deleted and the delete icon will appear at the top of the screen. Select the icon. If the credential is being used by a project or a system file, it will not be able to be deleted.

Alternatively, select the credential name, in Maintenance mode, and the Edit Credential button. Or, select the Edit button from the list of credentials. Select the Delete button. If the credential is being used by a project or a system file, it will not be able to be deleted.

== Assign Credentials ==

Credentials can only be assigned to Manager users. Credentials can be assigned to managers two ways:
# When creating or editing the credential in Data Source Credentials
# When creating or editing the Manager user in Users & Teams

= Search and Sort Data Source Credentials =

[[File:SearchDataSourceCredentials.jpg|700px|center]]

A search can be done of all the data source credentials. In this example, all credentials with 'github' in the name was searched for.

[[File:SortDataSourceCredentials.jpg|700px|center]]

Teams can be sorted in ascending or descending order by the credential name, type, number of accessors and the number of projects.

[[Machine_Translation_and_Translation_Management_System| Next: Translation Management Systems and Machine Translation]]

Data Source Credentials

2024-06-05T15:56:33Z

Rdaly: /* Create and Configure Data Source Credentials */

= Introduction =

The Data Source Credentials are the permissions that are used to connect to the repository where code is stored. One of the most common Data Source Credentials is GitHub.

Command Center supports the following data source credentials:
* AWS S3
* Azure Repos
* Custom Git
* Gerrit
* GitHub
* Gitlab
* Subversion

[[File:CCDataSourceCredentials.jpg|600px|center]]

= View Data Source Credentials =
[Administrator, Manager]

[[File:ManageDataSourceCredentials.jpg|600px|center]]

Only the Administrator user can see the list of all the data source credentials. A Manager can see only the credentials that they are defined as an accessor.

= Create and Configure Data Source Credentials =
[Administrator]

[[File:Data-sourcesv2.jpg|700px|center]]

In order to work with data source credentials. the system must be in Maintenance mode. The Administrator can create the data source credentials by selecting the [[File:CreateIcon.jpg|30px]] (Create new credential) button on the Manage Data Source Credentials page. The first step is to indicate the data source type.

For more details on configuring the specific data source credential:

* [[ AWS_S3_Data_Source_Credential | AWS S3]]
* [[ Team_Foundation_Server_Data_Source_Credential | Azure DevOps Server (TFS)]]
* [[ Azure Repos | Azure Repos ]]
* [[ Custom_Git_Data_Source_Credential | Custom Git]]
* [[ Gerrit_Data_Source_Credential | Gerrit ]]
* [[ GitHub_Data_Source_Credential | GitHub]]
* [[ Gitlab_Data_Source_Credential | GitLab]]
* [[ Team_Foundation_Server_Data_Source_Credential | Team Foundation Server]]
* [[ Subversion_Data_Source_Credential | Subversion]]

== Edit Credentials ==

Credentials can only be edited when the system is in Maintenance mode which will be indicated at the top of the screen. The Administrator user can hover over the credential to change and the Edit button will appear.

[[File:ViewDataSourceCredential.jpg|700px|center]]

Alternatively, if the Administrator selects the name of the Data Source Credential, an '''Edit credentia'''l button will come up.

[[File:EditDataCredentials.jpg|700px|center]]

The Administrator can change:
* Name of the credential
* Type of credential and the username and personal access token
* Which manager users can access the credential
** The Search box allows the administrator to search in the Unassigned accessors

== Delete Credentials ==

Check the box next to the credentials from the list to be deleted and the delete icon will appear at the top of the screen. Select the icon. If the credential is being used by a project or a system file, it will not be able to be deleted.

Alternatively, select the credential name, in Maintenance mode, and the Edit Credential button. Or, select the Edit button from the list of credentials. Select the Delete button. If the credential is being used by a project or a system file, it will not be able to be deleted.

== Assign Credentials ==

Credentials can only be assigned to Manager users. Credentials can be assigned to managers two ways:
# When creating or editing the credential in Data Source Credentials
# When creating or editing the Manager user in Users & Teams

= Search and Sort Data Source Credentials =

[[File:SearchDataSourceCredentials.jpg|700px|center]]

A search can be done of all the data source credentials. In this example, all credentials with 'github' in the name was searched for.

[[File:SortDataSourceCredentials.jpg|700px|center]]

Teams can be sorted in ascending or descending order by the credential name, type, number of accessors and the number of projects.

[[Machine_Translation_and_Translation_Management_System| Next: Translation Management Systems and Machine Translation]]

Data Source Credentials

2024-06-05T15:40:59Z

Rdaly: /* Create and Configure Data Source Credentials */

= Introduction =

The Data Source Credentials are the permissions that are used to connect to the repository where code is stored. One of the most common Data Source Credentials is GitHub.

Command Center supports the following data source credentials:
* AWS S3
* Azure Repos
* Custom Git
* Gerrit
* GitHub
* Gitlab
* Subversion

[[File:CCDataSourceCredentials.jpg|600px|center]]

= View Data Source Credentials =
[Administrator, Manager]

[[File:ManageDataSourceCredentials.jpg|600px|center]]

Only the Administrator user can see the list of all the data source credentials. A Manager can see only the credentials that they are defined as an accessor.

= Create and Configure Data Source Credentials =
[Administrator]

[[File:Data-sourcesv2.jpg|700px|center]]

In order to work with data source credentials. the system must be in Maintenance mode. The Administrator can create the data source credentials by selecting the [[File:CreateIcon.jpg|30px]] (Create new credential) button on the Manage Data Source Credentials page. The first step is to indicate the data source type.

For more details on configuring the specific data source credential:

* [[ AWS_S3_Data_Source_Credential | AWS S3]]
* [[ Azure_DevOps_Server_(TFS)_Data_Source_Credential | Azure Repos]]
* [[ Azure Repos | Azure Repos ]]
* [[ Custom_Git_Data_Source_Credential | Custom Git]]
* [[ Gerrit_Data_Source_Credential | Gerrit ]]
* [[ GitHub_Data_Source_Credential | GitHub]]
* [[ Gitlab_Data_Source_Credential | GitLab]]
* [[ Team_Foundation_Server_Data_Source_Credential | Team Foundation Server]]
* [[ Subversion_Data_Source_Credential | Subversion]]

== Edit Credentials ==

Credentials can only be edited when the system is in Maintenance mode which will be indicated at the top of the screen. The Administrator user can hover over the credential to change and the Edit button will appear.

[[File:ViewDataSourceCredential.jpg|700px|center]]

Alternatively, if the Administrator selects the name of the Data Source Credential, an '''Edit credentia'''l button will come up.

[[File:EditDataCredentials.jpg|700px|center]]

The Administrator can change:
* Name of the credential
* Type of credential and the username and personal access token
* Which manager users can access the credential
** The Search box allows the administrator to search in the Unassigned accessors

== Delete Credentials ==

Check the box next to the credentials from the list to be deleted and the delete icon will appear at the top of the screen. Select the icon. If the credential is being used by a project or a system file, it will not be able to be deleted.

Alternatively, select the credential name, in Maintenance mode, and the Edit Credential button. Or, select the Edit button from the list of credentials. Select the Delete button. If the credential is being used by a project or a system file, it will not be able to be deleted.

== Assign Credentials ==

Credentials can only be assigned to Manager users. Credentials can be assigned to managers two ways:
# When creating or editing the credential in Data Source Credentials
# When creating or editing the Manager user in Users & Teams

= Search and Sort Data Source Credentials =

[[File:SearchDataSourceCredentials.jpg|700px|center]]

A search can be done of all the data source credentials. In this example, all credentials with 'github' in the name was searched for.

[[File:SortDataSourceCredentials.jpg|700px|center]]

Teams can be sorted in ascending or descending order by the credential name, type, number of accessors and the number of projects.

[[Machine_Translation_and_Translation_Management_System| Next: Translation Management Systems and Machine Translation]]

File:Data-sourcesv2.jpg

2024-06-05T15:38:26Z

Rdaly: Rdaly uploaded a new version of File:Data-sourcesv2.jpg

Data Source Credential for the project

2024-06-05T15:34:14Z

Rdaly:

Select the [[File:LingoportIcon.jpg|50px]] to get to the '''Projects''' page and select the [[File:CreateIcon.jpg|30px]] to '''Create new project'''. The first step in the process will come up.

[[File:Step1DataSource.jpg|700px|center]]

When Manager users are created, Data Source Credentials are assigned. If the Manager does not have any Data Source Credentials assigned, the process will fail with the error: '''Must have access to at least one credential before creating a project'''. Contact an Administrator to get credential access. Administrator users have access to all Data Source Credentials in the system.

This example uses the GitHub data source credential. Other credentials will have different pages.

Select '''Next'''

[[Choose a Repository|Step 2:Choose a Repository]]

[[Step_by_Step_Project_Creation|<== Back to Introduction]]

Step by Step Project Creation

2024-06-05T15:31:03Z

Rdaly: /* Prerequisites */

= Table of Contents =

[[Data Source Credential for the project |Step 1:Data Source Credential for the project]]

[[Choose a Repository|Step 2:Choose a Repository]]

[[Name The Project and Type |Step 3: Name the Project]]

[[Creating a Globalyzer Project |Creating a Globalyzer Project - Step 4: Globayzer Lite Definition File]]

[[Creating a Localyzer Project| Creating a Localyzer Project - Step 5: Which MT or TMS will Localyzer use ]]

[[What are the Localyzer locales| Step 6: What are the locales Localyzer is acting on? ]]

[[Resource File(s) Format| Step 7: Resource file formats]]

[[Include and Exclude Patterns|Step 8: Set up optional include or exclude patterns]]

[[Optional Localyzer Settings|Step 9: Optional Advanced Localyzer Settings]]

[[Grant Users and Teams Access | Step 10: Grant Users and Teams Access]]

= Prerequisites =
Only users that with Manager or Administrator roles can create projects. Other users can view created projects if they have been granted access.

Before creating a new project, there are a few items that are needed.
# The licensing needs to be valid for Globalyzer and/or Localyzer depending on the type of projects to be created.
# The System Email Sender needs to be set up.
# The Data Source that the project will be using, such as GitHub, Subversion or Azure. Command Center will not allow projects to be created if there are no Data Sources available. A Manager creating the project must have access to the data source credential. Additionally, the specific branch being used in the repository is needed.
# For Globalyzer projects, the Project Definition File must be available in the repository or on the Command Center System.
# For Localyzer projects:
## the Translation Management System or Machine Translation engine must be defined
## The locales to be translated to
## The resource file types such as .properties or .json and the naming format for the source files.
## Include and Exclude folders for locating the resource files.
## Any other configuration such as custom scripts that should be in the Command Center System.

This example uses a GitHub repository for the data source. If using a different data source, refer to the sections that describe how to configure and create projects using those data sources.

[[Data Source Credential for the project |Step 1:Data Source Credential for the project]]

[[Command_Center_User%27s_Guide#Projects_Overview| <== Back to Projects Overview]]

Command Center FAQ

2024-03-25T23:02:54Z

Rdaly: /* How to use a separate branch for translation which developers can later merge into the master branch using a pull request? */

= Why am I not seeing all the projects? =
(Manager, Developer, Translator, chips, search, favorites, tags...]

= What are the settings for MySQL 8 JDBC connection? =
Deploying Command Center entails installing two Docker containers, one for the Web application, one for the MySQL 8 database. Both are on the same system and communicate via a Docker network. Command Center is reachable via its URL behind HTTPS. One cannot reach the database from outside the VM on which it is installed. Based on the above, the JDBC URL going from the Web application container to the MySQL container is configured as follows:

app.database.url=jdbc:mysql://mysqlservercommand:3306/LRM?characterEncoding=utf8&permitMysqlScheme&restrictedAuth=mysql_native_password,client_ed25519,auth_gssapi_client,caching_sha2_password,dialog,mysql_clear_password&allowPublicKeyRetrieval=true

If LRM, the Localyzer engine, requires another configuration, that will be up to the customer IT to make that determination. For reference, the following parameters can be set on the JDBC connection:
* https://mysqlconnector.net/connection-options/

In particular, if the MySQL 8 is installed in a non-default way and the VM on which the database is setup is not the same as the VM from which the connection is made or is exposed to a public network, the values for the following attributes may be of particular interest:
* ServerRSAPublicKeyFile
* allowPublicKeyRetrieval

= Open Source Libraries and Licenses =

See: [[Command Center Open Source Libraries ]]

= How to use a separate branch for translation which developers can later merge into the master branch using a pull request? =

# In your repository, create a new branch off of the master branch for the translations. In this example, it is called '''Lingoport'''.
# Edit the configuration for your project, or create it, to do the following:
##For every analysis or other actions in Command Center, first merge the commits from '''master''' into '''Lingoport'''.
##The translations will come back to the '''Lingoport''' branch.
##At some point, a team member will have to do a pull request and merge of the '''Lingoport''' branch back into the '''master''' branch at the repository. When prompted, keep the '''Lingoport''' branch. Otherwise, the translations will not make it back to the '''master''' branch.

[[File:MergeBranch.jpg|700px|center]]

Watch out for the following:
* Translated files cannot be modified outside the "Lingoport" branch or merge conflict will happen.
* In an automated system, that means blocking the process
* Make sure to relay this part clearly to the team in charge of the repository.

= Why am I not getting any resource files? =

= Why can't I find my project in the list? =

= Where do I find the description of the errors? =

= Why am I not receiving notification for my project? =

Command Center FAQ

2024-03-25T23:02:18Z

Rdaly: /* How to use a separate branch for translation which developers can later merge into the master branch using a pull request? */

= Why am I not seeing all the projects? =
(Manager, Developer, Translator, chips, search, favorites, tags...]

= What are the settings for MySQL 8 JDBC connection? =
Deploying Command Center entails installing two Docker containers, one for the Web application, one for the MySQL 8 database. Both are on the same system and communicate via a Docker network. Command Center is reachable via its URL behind HTTPS. One cannot reach the database from outside the VM on which it is installed. Based on the above, the JDBC URL going from the Web application container to the MySQL container is configured as follows:

app.database.url=jdbc:mysql://mysqlservercommand:3306/LRM?characterEncoding=utf8&permitMysqlScheme&restrictedAuth=mysql_native_password,client_ed25519,auth_gssapi_client,caching_sha2_password,dialog,mysql_clear_password&allowPublicKeyRetrieval=true

If LRM, the Localyzer engine, requires another configuration, that will be up to the customer IT to make that determination. For reference, the following parameters can be set on the JDBC connection:
* https://mysqlconnector.net/connection-options/

In particular, if the MySQL 8 is installed in a non-default way and the VM on which the database is setup is not the same as the VM from which the connection is made or is exposed to a public network, the values for the following attributes may be of particular interest:
* ServerRSAPublicKeyFile
* allowPublicKeyRetrieval

= Open Source Libraries and Licenses =

See: [[Command Center Open Source Libraries ]]

= How to use a separate branch for translation which developers can later merge into the master branch using a pull request? =

# In your repository, create a new branch off of the master branch for the translations. In this example, it is called '''Lingoport'''.
# Edit the configuration for your project, or create it, to do the following:
##For every analysis or other actions in Command Center, first merge the commits from '''master''' into '''Lingoport'''.
##The translations will come back to the '''Lingoport''' branch.
##At some point, a team member will have to do a pull request and merge of the '''Lingoport''' branch back into the '''master''' branch at the repository. When prompted, keep the '''Lingoport''' branch. Otherwise, the translations will not make it back to the '''master''' branch.

[[File:MergeBranch.jpg|700px|center]]

Watch out for the following:
* Translated files cannot be modified outside the "Lingoport" branch or merge conflict will happen.
* In an automated system, that means blocking the process
* Please make sure to relay this part very clearly to the team in charge of the repository.

= Why am I not getting any resource files? =

= Why can't I find my project in the list? =

= Where do I find the description of the errors? =

= Why am I not receiving notification for my project? =

Command Center FAQ

2024-03-25T23:00:31Z

Rdaly: /* How to use a separate branch for translation which developers can later merge into the master branch using a pull request? */

= Why am I not seeing all the projects? =
(Manager, Developer, Translator, chips, search, favorites, tags...]

= What are the settings for MySQL 8 JDBC connection? =
Deploying Command Center entails installing two Docker containers, one for the Web application, one for the MySQL 8 database. Both are on the same system and communicate via a Docker network. Command Center is reachable via its URL behind HTTPS. One cannot reach the database from outside the VM on which it is installed. Based on the above, the JDBC URL going from the Web application container to the MySQL container is configured as follows:

app.database.url=jdbc:mysql://mysqlservercommand:3306/LRM?characterEncoding=utf8&permitMysqlScheme&restrictedAuth=mysql_native_password,client_ed25519,auth_gssapi_client,caching_sha2_password,dialog,mysql_clear_password&allowPublicKeyRetrieval=true

If LRM, the Localyzer engine, requires another configuration, that will be up to the customer IT to make that determination. For reference, the following parameters can be set on the JDBC connection:
* https://mysqlconnector.net/connection-options/

In particular, if the MySQL 8 is installed in a non-default way and the VM on which the database is setup is not the same as the VM from which the connection is made or is exposed to a public network, the values for the following attributes may be of particular interest:
* ServerRSAPublicKeyFile
* allowPublicKeyRetrieval

= Open Source Libraries and Licenses =

See: [[Command Center Open Source Libraries ]]

= How to use a separate branch for translation which developers can later merge into the master branch using a pull request? =

# In your repository, create a new branch off of the master branch for the translations. In this example, it is called Lingoport.
# Edit the configuration for your project, or create it, to do the following:
##For every analysis or other actions in Command Center, first merge the commits from "master" into "Lingoport".
##The translations will come back to the "Lingoport" branch.
##At some point, a team member will have to do a pull request and merge of the "Lingoport" branch back into the "master" branch at the repository. When prompted, keep the "Lingoport" branch. Otherwise, the translations will not make it back to the "master" branch.

[[File:MergeBranch.jpg|700px|center]]

Watch out for the following:
* Translated files cannot be modified outside the "Lingoport" branch or merge conflict will happen.
* In an automated system, that means blocking the process
* Please make sure to relay this part very clearly to the team in charge of the repository.

= Why am I not getting any resource files? =

= Why can't I find my project in the list? =

= Where do I find the description of the errors? =

= Why am I not receiving notification for my project? =

Command Center FAQ

2024-03-25T23:00:14Z

Rdaly: /* How to use a separate branch for translation which developers can later merge into the master branch using a pull request? */

= Why am I not seeing all the projects? =
(Manager, Developer, Translator, chips, search, favorites, tags...]

= What are the settings for MySQL 8 JDBC connection? =
Deploying Command Center entails installing two Docker containers, one for the Web application, one for the MySQL 8 database. Both are on the same system and communicate via a Docker network. Command Center is reachable via its URL behind HTTPS. One cannot reach the database from outside the VM on which it is installed. Based on the above, the JDBC URL going from the Web application container to the MySQL container is configured as follows:

app.database.url=jdbc:mysql://mysqlservercommand:3306/LRM?characterEncoding=utf8&permitMysqlScheme&restrictedAuth=mysql_native_password,client_ed25519,auth_gssapi_client,caching_sha2_password,dialog,mysql_clear_password&allowPublicKeyRetrieval=true

If LRM, the Localyzer engine, requires another configuration, that will be up to the customer IT to make that determination. For reference, the following parameters can be set on the JDBC connection:
* https://mysqlconnector.net/connection-options/

In particular, if the MySQL 8 is installed in a non-default way and the VM on which the database is setup is not the same as the VM from which the connection is made or is exposed to a public network, the values for the following attributes may be of particular interest:
* ServerRSAPublicKeyFile
* allowPublicKeyRetrieval

= Open Source Libraries and Licenses =

See: [[Command Center Open Source Libraries ]]

= How to use a separate branch for translation which developers can later merge into the master branch using a pull request? =

# In your repository, create a new branch off of the master branch for the translations. In this example, it is called Lingoport.
# Edit the configuration for your project, or create it, to do the following:
##For every analysis or other actions in Command Center, first merge the commits from "master" into "Lingoport".
##The translations will come back to the "Lingoport" branch.
##At some point, a team member will have to do a pull request and merge of the "Lingoport" branch back into the "master" branch at the repository. When prompted, keep the "Lingoport" branch. Otherwise, the translations will not make it back to the "master" branch.

[[File:File:MergeBranch.jpg|700px|center]]

Watch out for the following:
* Translated files cannot be modified outside the "Lingoport" branch or merge conflict will happen.
* In an automated system, that means blocking the process
* Please make sure to relay this part very clearly to the team in charge of the repository.

= Why am I not getting any resource files? =

= Why can't I find my project in the list? =

= Where do I find the description of the errors? =

= Why am I not receiving notification for my project? =

File:MergeBranch.jpg

2024-03-25T22:58:42Z

Rdaly:

Command Center FAQ

2024-03-25T22:58:02Z

Rdaly: /* How to use a separate branch for translation which developers can later merge into the master branch using a pull request? */

= Why am I not seeing all the projects? =
(Manager, Developer, Translator, chips, search, favorites, tags...]

= What are the settings for MySQL 8 JDBC connection? =
Deploying Command Center entails installing two Docker containers, one for the Web application, one for the MySQL 8 database. Both are on the same system and communicate via a Docker network. Command Center is reachable via its URL behind HTTPS. One cannot reach the database from outside the VM on which it is installed. Based on the above, the JDBC URL going from the Web application container to the MySQL container is configured as follows:

app.database.url=jdbc:mysql://mysqlservercommand:3306/LRM?characterEncoding=utf8&permitMysqlScheme&restrictedAuth=mysql_native_password,client_ed25519,auth_gssapi_client,caching_sha2_password,dialog,mysql_clear_password&allowPublicKeyRetrieval=true

If LRM, the Localyzer engine, requires another configuration, that will be up to the customer IT to make that determination. For reference, the following parameters can be set on the JDBC connection:
* https://mysqlconnector.net/connection-options/

In particular, if the MySQL 8 is installed in a non-default way and the VM on which the database is setup is not the same as the VM from which the connection is made or is exposed to a public network, the values for the following attributes may be of particular interest:
* ServerRSAPublicKeyFile
* allowPublicKeyRetrieval

= Open Source Libraries and Licenses =

See: [[Command Center Open Source Libraries ]]

= How to use a separate branch for translation which developers can later merge into the master branch using a pull request? =

# In your repository, create a new branch off of the master branch for the translations. In this example, it is called Lingoport.
# Edit the configuration for your project, or create it, to do the following:
##For every analysis or other actions in Command Center, first merge the commits from "master" into "Lingoport".
##The translations will come back to the "Lingoport" branch.
##At some point, a team member will have to do a pull request and merge of the "Lingoport" branch back into the "master" branch at the repository. When prompted, keep the "Lingoport" branch. Otherwise, the translations will not make it back to the "master" branch.

Watch out for the following:
Translated files cannot be modified outside the "Lingoport" branch or merge conflict will happen. In an automated system, that means blocking the process Please make sure to relay this part very clearly to the team in charge of fs-labs.

= Why am I not getting any resource files? =

= Why can't I find my project in the list? =

= Where do I find the description of the errors? =

= Why am I not receiving notification for my project? =

Command Center FAQ

2024-03-25T22:56:39Z

Rdaly:

= Why am I not seeing all the projects? =
(Manager, Developer, Translator, chips, search, favorites, tags...]

= What are the settings for MySQL 8 JDBC connection? =
Deploying Command Center entails installing two Docker containers, one for the Web application, one for the MySQL 8 database. Both are on the same system and communicate via a Docker network. Command Center is reachable via its URL behind HTTPS. One cannot reach the database from outside the VM on which it is installed. Based on the above, the JDBC URL going from the Web application container to the MySQL container is configured as follows:

app.database.url=jdbc:mysql://mysqlservercommand:3306/LRM?characterEncoding=utf8&permitMysqlScheme&restrictedAuth=mysql_native_password,client_ed25519,auth_gssapi_client,caching_sha2_password,dialog,mysql_clear_password&allowPublicKeyRetrieval=true

If LRM, the Localyzer engine, requires another configuration, that will be up to the customer IT to make that determination. For reference, the following parameters can be set on the JDBC connection:
* https://mysqlconnector.net/connection-options/

In particular, if the MySQL 8 is installed in a non-default way and the VM on which the database is setup is not the same as the VM from which the connection is made or is exposed to a public network, the values for the following attributes may be of particular interest:
* ServerRSAPublicKeyFile
* allowPublicKeyRetrieval

= Open Source Libraries and Licenses =

See: [[Command Center Open Source Libraries ]]

= How to use a separate branch for translation which developers can later merge into the master branch using a pull request? =

# In your repository, create a new branch off of the master branch for the translations. In this example, it is called Lingoport.
# Edit the configuration for your project, or create it, to do the following:
a. For every analysis or other actions in Command Center, first merge the commits from "master" into "Lingoport".
b. The translations will come back to the "Lingoport" branch.
c. At some point, a team member will have to do a Pull request and merge of the "Lingoport" branch back into the "master" branch. When prompted, keep the "Lingoport" branch. Otherwise, the translations will not make it back to the "master" branch.

Watch out for the following:
Translated files cannot be modified outside the "Lingoport" branch or merge conflict will happen. In an automated system, that means blocking the process Please make sure to relay this part very clearly to the team in charge of fs-labs.

= Why am I not getting any resource files? =

= Why can't I find my project in the list? =

= Where do I find the description of the errors? =

= Why am I not receiving notification for my project? =

Installing the Lingobot Service

2024-03-19T22:06:34Z

Rdaly: /* Installation Verification */

===Set up install.conf ===

#
# Provide your home directory, lingobot folder will be created
#
home_directory=/home/centos
#
# Provide the Lingobot version
#
lingobot_image_version=
#
# Provide the Lingobot port
#
serverPort=8084
#
# Provide your Docker Hub username
#
docker_username=lingoportcustomer
#
# Provide your Docker Hub account token
#
docker_account_token=dckr_pat_cUuqyjSfv3JQRG0R5_cwmWsHceg
# Slack security config
BOT_TOKEN=xoxb-**********
APP_TOKEN=xapp-**********
COMMAND_CENTER_URL=https://your_server/command-center
COMMAND_CENTER_USER=
COMMAND_CENTER_TOKEN=
docker_image=lingoport/lingobot_dev

* Verify that the <code>/home/directory</code> is correct.
* The <code>lingobot_image_version=</code> value should be provided
* Make sure the <code>serverPort=8084</code> is not a port that is being used by anything else.
* Set the <code>docker_username=</code> and <code>docker_account_token=<token value></code> to the DockerHub login
* Set the <code>COMMAND_CENTER_URL</code> to the correct Command Center URL

==Run install.sh==

chmod +x *.sh
sudo ./install.sh

To check the running container status

sudo docker ps

If you need to re-run the install.sh, make sure to run uninstall.sh first to clean your environment.

Note: Docker image version is not the Lingobot version, check latest docker image version at https://hub.docker.com/repository/docker/lingoport/lingobot/general

Once this is done, your instance of LingoBot will be up and running!

== Installation Verification ==
A quick way to verify that the LingoBot service has successfully launched and can be accessed by your team, go to your collaboration environment (Slack, Flowdock, etc.) and try sending a message to LingoBot. To do this, you may have to invite LingoBot to the room you are currently in.

Example:
lingobot hello

if LingoBot responds with "hello", then you have successfully launched LingoBot. Have Fun!

Verify that you see the correct projects:
lingobot list projects

List of all active projects:
Name | Type
-----------------------------------------------------|---------------|----------
CET.IOS.testPush(testPush) | Localyzer | Parent
CET.National.testing(testing) | Globalyzer | Parent
CET.Android.test8665(test8665) | Globalyzer | Parent
CET.NOAAWeatherGithub.testing(testing) | Localyzer | Parent

Installing the Lingobot Service

2024-03-19T22:05:58Z

Rdaly: /* Installation Verification */

Installing the Lingobot Service

2024-03-19T22:04:03Z

Rdaly: /* Set up install.conf */

===Set up install.conf ===

#
# Provide your home directory, lingobot folder will be created
#
home_directory=/home/centos
#
# Provide the Lingobot version
#
lingobot_image_version=
#
# Provide the Lingobot port
#
serverPort=8084
#
# Provide your Docker Hub username
#
docker_username=lingoportcustomer
#
# Provide your Docker Hub account token
#
docker_account_token=dckr_pat_cUuqyjSfv3JQRG0R5_cwmWsHceg
# Slack security config
BOT_TOKEN=xoxb-**********
APP_TOKEN=xapp-**********
COMMAND_CENTER_URL=https://your_server/command-center
COMMAND_CENTER_USER=
COMMAND_CENTER_TOKEN=
docker_image=lingoport/lingobot_dev

* Verify that the <code>/home/directory</code> is correct.
* The <code>lingobot_image_version=</code> value should be provided
* Make sure the <code>serverPort=8084</code> is not a port that is being used by anything else.
* Set the <code>docker_username=</code> and <code>docker_account_token=<token value></code> to the DockerHub login
* Set the <code>COMMAND_CENTER_URL</code> to the correct Command Center URL

==Run install.sh==

chmod +x *.sh
sudo ./install.sh

To check the running container status

sudo docker ps

If you need to re-run the install.sh, make sure to run uninstall.sh first to clean your environment.

Note: Docker image version is not the Lingobot version, check latest docker image version at https://hub.docker.com/repository/docker/lingoport/lingobot/general

Once this is done, your instance of LingoBot will be up and running!

== Installation Verification ==
A quick way to verify that the LingoBot service has successfully launched and can be accessed by your team, go to your collaboration environment and try sending a message to LingoBot. To do this, you may have to invite LingoBot to the room you are currently in.

Example:
lingobot hello

if LingoBot responds with "hello", then you have successfully launched LingoBot. Have Fun!

Verify that you see the correct projects:
lingobot list projects

Installing the Lingobot Service

2024-03-19T22:03:43Z

Rdaly: /* Set up install.conf */

===Set up install.conf ===

#
# Provide your home directory, lingobot folder will be created
#
home_directory=/home/centos
#
# Provide the Lingobot version
#
lingobot_image_version=
#
# Provide the Lingobot port
#
serverPort=8084
#
# Provide your Docker Hub username
#
docker_username=lingoportcustomer
#
# Provide your Docker Hub account token
#
docker_account_token=dckr_pat_cUuqyjSfv3JQRG0R5_cwmWsHceg
# Slack security config
BOT_TOKEN=xoxb-**********
APP_TOKEN=xapp-**********
COMMAND_CENTER_URL=https://your_server/command-center
COMMAND_CENTER_USER=
COMMAND_CENTER_TOKEN=
docker_image=lingoport/lingobot_dev

* Verify that the <code>/home/directory</code> is correct.
* The <code>lingobot_image_version=</code> value should be provided
* Make sure the <code>serverPort=8084</code> is not a port that is being used by anything else.
* Set the <code>docker_username=</code> and <code>docker_account_token=<token value></code> to the DockerHub login
* Set the <code>COMMAND_CENTER_URL</code> is set the the correct Command Center URL

==Run install.sh==

chmod +x *.sh
sudo ./install.sh

To check the running container status

sudo docker ps

If you need to re-run the install.sh, make sure to run uninstall.sh first to clean your environment.

Note: Docker image version is not the Lingobot version, check latest docker image version at https://hub.docker.com/repository/docker/lingoport/lingobot/general

Once this is done, your instance of LingoBot will be up and running!

== Installation Verification ==
A quick way to verify that the LingoBot service has successfully launched and can be accessed by your team, go to your collaboration environment and try sending a message to LingoBot. To do this, you may have to invite LingoBot to the room you are currently in.

Example:
lingobot hello

if LingoBot responds with "hello", then you have successfully launched LingoBot. Have Fun!

Verify that you see the correct projects:
lingobot list projects

Installing the Lingobot Service

2024-03-19T22:03:10Z

Rdaly: /* Set up install.conf */

===Set up install.conf ===

#
# Provide your home directory, lingobot folder will be created
#
home_directory=/home/centos
#
# Provide the Lingobot version
#
lingobot_image_version=
#
# Provide the Lingobot port
#
serverPort=8084
#
# Provide your Docker Hub username
#
docker_username=lingoportcustomer
#
# Provide your Docker Hub account token
#
docker_account_token=dckr_pat_cUuqyjSfv3JQRG0R5_cwmWsHceg
# Slack security config
BOT_TOKEN=xoxb-**********
APP_TOKEN=xapp-**********
COMMAND_CENTER_URL=https://your_server/command-center
COMMAND_CENTER_USER=
COMMAND_CENTER_TOKEN=
docker_image=lingoport/lingobot_dev

* Verify that the <code>/home/directory</code> is correct.
* The <code>lingobot_image_version=</code> value should be provided
* Make sure the <code>serverPort=8084</code> is not a port that is being used by anything else.
* Set the <code>docker_username=</code> and <code>docker_account_token=<token value></code> is set to the DockerHub values
* Set the <code>COMMAND_CENTER_URL</code> is set the the correct Command Center URL

==Run install.sh==

chmod +x *.sh
sudo ./install.sh

To check the running container status

sudo docker ps

If you need to re-run the install.sh, make sure to run uninstall.sh first to clean your environment.

Note: Docker image version is not the Lingobot version, check latest docker image version at https://hub.docker.com/repository/docker/lingoport/lingobot/general

Once this is done, your instance of LingoBot will be up and running!

== Installation Verification ==
A quick way to verify that the LingoBot service has successfully launched and can be accessed by your team, go to your collaboration environment and try sending a message to LingoBot. To do this, you may have to invite LingoBot to the room you are currently in.

Example:
lingobot hello

if LingoBot responds with "hello", then you have successfully launched LingoBot. Have Fun!

Verify that you see the correct projects:
lingobot list projects

Configure the Collaboration Environment

2024-03-19T21:56:18Z

Rdaly: /* LingoBot Cisco Spark Setup */

Lingobot supports several collaboration environments; Slack, Flowdock and Cisco Spark.

== LingoBot Slack Setup ==
This portion of the installation guide only applies if the collaboration environment you will be using is Slack.

1. Go to https://api.slack.com/apps

2. Click '''Create New App'''

3. Choose '''From an app manifest''' and choose a workspace. The workspace will probably be the company workspace

4. Choose the '''YAML''' tab
Enter App Manifest using contents of '''manifest.yaml'''
#manifest.yaml
display_information:
name: Lingobot App
features:
app_home:
home_tab_enabled: false
messages_tab_enabled: true
messages_tab_read_only_enabled: false
bot_user:
display_name: lingobot
always_online: true
oauth_config:
scopes:
bot:
- channels:history
- channels:join
- commands
- chat:write
- im:history
settings:
event_subscriptions:
bot_events:
- message.channels
- message.im
interactivity:
is_enabled: true
org_deploy_enabled: false
socket_mode_enabled: true
is_hosted: false
token_rotation_enabled: false

5. Click the '''Create''' button

6. Once the app is created, select '''Install to Workspace'''

7. Then select '''Basic Information''' on the left side, scroll down to '''App-Level Tokens''' and click "Generate Token and Scopes", and click "Add Scope" to add all scopes

8. Click "Generate" to get an APP_TOKEN, copy and paste it to '''install.conf'''

APP_TOKEN=<generated token>

9. At "OAuth & Permissions" page, copy and paste the "Bot User OAuth Token" to install.conf

BOT_TOKEN=<generated token>

Once this is complete, the bot is now configured and ready to be installed! Follow the instructions below on running the installation script to finish the installation process.

[[Installing_the_Lingobot_Service|Next: Install and Start the Lingobot Service]]

== LingoBot CA Flowdock Setup ==
This portion of the installation guide only applies if the collaboration environment you will be using is CA Flowdock. If you will be using either Slack or Cisco Spark, please follow the corresponding setup instructions.

Setting up LingoBot to run on CA Flowdock is as simple as creating a new user account through which LingoBot will communicate. If you would rather not deal with the hassle of creating a new Flowdock user account, feel free to ask us to make one for your LingoBot instance. We will send you the API token needed for LingoBot's configuration file and you can simply invite the account to join your Flow once it is ready.

If you don't mind creating the account yourself, then simply follow these instructions to do so.

* First, you will need an email account with which you can create a Flowdock account. You can make one for free on [https://accounts.google.com/SignUp?hl=en-US Gmail] if need be.
* Once this is completed, navigate to the [https://www.flowdock.com/signup Flowdock Sign Up page] and click "Sign Up Using Google"
* When prompted, sign in using the Google account you created for LingoBot (alternatively, you can sign up using a non-google account by filling out the details manually).
* Once the account has been created, navigate to the [https://www.flowdock.com/account/edit Profile Editing Page] and set the following information:
** Name: Lingoport Chatbot
** Display Name: By default, we recommend simply calling it "lingobot", however you're welcome to name it whatever you would like.
*** If you do choose to call it something other than "lingobot", make sure that you set the LINGOBOT_NAME variable in the configuration file to whatever name you chose.
*** Example: <code>export LINGOBOT_NAME=lingobot-123</code>
** Avatar: You can download the following icon [[File:Lingoport logo small.jpeg|30px]] and upload it, upload your own custom icon, or simply leave it blank.
* Once this is done, scroll down and click "Update Profile"
* The final step is to navigate to the [https://www.flowdock.com/account/tokens API Tokens page]. Here you will find an API token labeled "Personal Api Token".
* Copy the API token and paste it into the LingoBot configuration file next to the HUBOT_FLOWDOCK_API_TOKEN variable declaration.

Example:
export HUBOT_FLOWDOCK_API_TOKEN=0a1b2c3d4e5f6g7a8b9c0d

Furthermore, make sure the LINGOBOT_ADAPTER variable is set to "flowdock".

Example:
export LINGOBOT_ADAPTER=flowdock

Once this is complete, the bot is now configured and ready to be installed! Follow the instructions below on running the installation script to finish the installation process.

[[Installing_the_Lingobot_Service|Next: Install and Start the Lingobot Service]]

== LingoBot Cisco Spark Setup ==
This portion of the installation guide only applies if the collaboration environment you will be using is Cisco Spark. If you will be using either Slack or CA Flowdock, please follow the corresponding setup instructions.

Configuring LingoBot to communicate via Cisco Spark is a fairly straight forward process. All that is required is access to an account that has access to your organization's Cisco Spark.

=== Creating a Custom Bot ===
* The first step is to sign in to your Cisco Spark account on the [https://developer.ciscospark.com/# Developer Portal].
* Once signed in, navigate to the [https://developer.ciscospark.com/add-bot.html Custom Bot Creation page].
* On the bot creation page, fill in the form with the following information:
** Display Name: By default, we recommend simply calling it "lingobot", however you're welcome to name it whatever you would like.
*** If you do choose to call it something other than "lingobot", make sure that you set the LINGOBOT_NAME variable in the configuration file to whatever name you chose.
*** Example: <code>export LINGOBOT_NAME=lingobot-123</code>
** Bot Name: Ideally this should be the same as the display name, however due to the necessity that it be unique this can be just about anything. This will only be used to invite the bot to a chat room.
** Icon: Paste the following URL into the Icon field: '''http://i.imgur.com/3bzw0zp.jpg'''
* Once this is done, click "Add Bot". On the following page, you will find an API token. Click the "Copy" button next to it (or select and copy the token itself) then paste it into the LingoBot configuration file next to the CISCOSPARK_ACCESS_TOKEN variable declaration.

Example:
export CISCOSPARK_ACCESS_TOKEN=LDA5YjBiOTItMTAwOS00ODMxLTk4ZjEtYTQ4OGI4N2FjN2Y2MjVlM2QyNTUtYmM2

=== Creating a Webhook for LingoBot ===
* The final step is to create a webhook that LingoBot can receive message event notifications through. To do this, navigate to the [https://developer.ciscospark.com/endpoint-webhooks-post.html Spark Webhook Creation Page].
* Make sure that the "Test Mode" switch is turned ON. This will allow you to generate webhooks directly into your organization's account.
* Under the "Request Headers" section, fill in the following information:
** Authorization: "Bearer '''[YOUR BOT'S API TOKEN HERE]'''"
* In the "Request Parameters" section, fill in the the following information under the "Your values" column:
** name: This can be anything. i.e. "lingobot".
** targetURL: "'''[YOUR JENKINS INSTANCE URL HERE]''':5001/hubot/ciscospark/incoming"
** resource: "all"
** event: "all"
** secret: This can be just about anything, but ideally it is a random string of letters and numbers that it at least 32 characters long.
*** Whatever you chose for this must also be copied to the LingoBot configuration file, next to the CISCOSPARK_SECRET variable declaration.
Example:
export CISCOSPARK_SECRET=a1b2c3d4e5f6g7h8i9j0k1l2m3n4o5p6
* Once all of these values have been entered, click the "Run" button. You should see a response containing the webhook's information on the right.

Finally, make sure the LINGOBOT_ADAPTER variable is set to "sparkwebhook".

Example:
export LINGOBOT_ADAPTER=sparkwebhook

Once this is complete, the bot is now configured and ready to be installed! Follow the instructions on running the installation script to finish the installation process.

[[Installing_the_Lingobot_Service|Next: Install and Start the Lingobot Service]]

== LingoBot MS Teams Setup ==
This portion of the installation guide only applies if the collaboration environment you will be using is MS Teams. If you will be using either Flowdock or Cisco Spark or Slack, please skip to the corresponding setup instructions.

=== Setup ngrok===
* Navigate to the [https://ngrok.com/ ngrok] page and sign up a free account or login to an existing account. Click Auth from the left list, and copy your '''Tunnel Authtoken'''.

* Copy the Tunnel Authtoken and paste it into the LingoBot configuration file
('''/var/lib/jenkins/lingoport/lingobot-<x.y>/config/config.yml''') next to the '''authtoken''' variable declaration.

Example:
authtoken: 2nde8yqeH8wLiBkv848BW_2Mm39SdudjQJmJ7xxxxxx
tunnels:
default:
proto: http
addr: 5001

* As a root user (not jenkins), run the following commands to start the ngrok service
sudo systemctl enable ngrok.service
sudo systemctl start ngrok.service
sudo systemctl status ngrok.service
If the status does not show '''active (running)''', then there is a problem.

* Return to the [https://ngrok.com/ ngrok] page and click '''Status''' from the left list. If the page does not show any tunnels online, refresh the page. Store the HTTPS URL for later use.

=== Microsoft Bot Registration===

* Navigate to the [https://portal.azure.com/#create/Microsoft.AzureBot AzureBot Registration Page] page. Create a Botframework Registration by completing the Bot Registration Page. Or login to an existing account.

[[File:Azurebot.PNG|700px]]
[[File:Azurebot2.PNG|700px]]

* On this page, you can set a custom icon for the bot under the "'''Upload custom icon'''" section. You can download the following icon [[File:Lingoport logo small.jpeg|30px]] and upload it, upload your own custom icon, or simply leave it blank.

* In the '''Display name''' field, enter the name that you would like LingoBot to respond to.
** By default, we recommend simply calling it "'''lingobot'''", however you're welcome to name it whatever you would like.
** If you do choose to call it something other than "lingobot", make sure that you set the '''LINGOBOT_NAME''' variable in the configuration file to whatever name you chose.
*** Example: <code>export LINGOBOT_NAME=lingobot-123</code>

* Click '''Create Microsoft App ID and password'''. You may be prompted to login into your MS Teams account first. Store the created app id and app password for use later. See this page [https://docs.microsoft.com/en-us/azure/bot-service/bot-service-resources-bot-framework-faq?view=azure-bot-service-4.0#app-registration how to create a new app and generate password]

* Copy the created app id and paste it into the LingoBot configuration file
('''/var/lib/jenkins/lingoport/lingobot-<x.y>/config/lingobot_config.sh''') next to the '''BOTBUILDER_APP_ID''' variable declaration.

Example:
export BOTBUILDER_APP_ID=e8911192-eca4-4f37-8284-616f3339f0e6

Furthermore, make sure the '''LINGOBOT_ADAPTER''' variable is set to '''botframework'''.

Example:
export LINGOBOT_ADAPTER=botframework

* Copy the created app password and past it into the LingoBot configuration file
('''/var/lib/jenkins/lingoport/lingobot-<x.y>/config/lingobot_config.sh''') next to the '''BOTBUILDER_APP_PASSWORD''' variable declaration.

Example:
export BOTBUILDER_APP_PASSWORD='wdS50{cphgeDCTKZO073{]#'

* Copy and paste the URL generated by ngrok to '''Messaging endpoint''' field on the Botframework Registration page, and add /api/messages to the end.

Example:
https://87406e76.ngrok.io/api/messages

[[File:Endpoint.PNG|700px]]

* Fill in the '''Paste your app ID below to continue''' field using the App ID.

* Once this is done, scroll down to the bottom of the page, agree to the terms of service, and click "'''Register'''" to complete.

* On the new opened '''My bots''' page, you will find your just created bot, under '''Connect to channels''' field, the Web Chat has been added as default. Click MS Teams icon under "'''Add a featured channel'''" to add MS Teams channel. And '''Save''' your changes.

[[File:Channel.PNG|700px]]

=== Create a Microsoft Teams app package ===

* Installing App Studio for Microsoft Teams follow steps on [https://docs.microsoft.com/en-us/microsoftteams/platform/get-started/get-started-app-studio this] page.

* Once you are in App Studio, click on the '''Chat''' tab, '''App Studio''' and the '''Manifest editor''' tab. Click '''Create a new app'''.

* Complete the '''App details''' section. This includes things such as the app’s name, description, and visual branding. You can automatically generate a GUID for your app and provide URLs for your privacy statement and terms of use.

* Click '''Bots''' section, '''Set up''' a bot then click '''Existing bot''' tab, type in your bot name and '''Select from one of your existing bots''', then choose the bot you just created above. '''Save'''.

* Copy and paste the URL to Messaging endpoints and make sure it matches the value you just set at bot Register page.

Example:
https://87406e76.ngrok.io/api/messages

* Click "Add" button under Commands section to add new commands

Example:
Command text: list projects
Help text: Displays list of active projects
Scope: Team

* Create a Microsoft Teams app package (.zip) to upload in Teams. Click '''Test and distribute''' under the '''Finish''' section, and click '''Download''' button to download the package file.

* Click the '''Store''' button (left down at the Teams), click '''Upload a custom app''' (at bottom left). And upload the package file just created above.

Once this is complete, the bot is now configured and ready to be installed! Follow the instructions below on running the installation script to finish the installation process.

[[Installing_the_Lingobot_Service|Next: Install and Start the Lingobot Service]]

Configure the Collaboration Environment

2024-03-19T21:55:30Z

Rdaly:

Lingobot supports several collaboration environments; Slack, Flowdock and Cisco Spark.

== LingoBot Slack Setup ==
This portion of the installation guide only applies if the collaboration environment you will be using is Slack.

1. Go to https://api.slack.com/apps

2. Click '''Create New App'''

3. Choose '''From an app manifest''' and choose a workspace. The workspace will probably be the company workspace

4. Choose the '''YAML''' tab
Enter App Manifest using contents of '''manifest.yaml'''
#manifest.yaml
display_information:
name: Lingobot App
features:
app_home:
home_tab_enabled: false
messages_tab_enabled: true
messages_tab_read_only_enabled: false
bot_user:
display_name: lingobot
always_online: true
oauth_config:
scopes:
bot:
- channels:history
- channels:join
- commands
- chat:write
- im:history
settings:
event_subscriptions:
bot_events:
- message.channels
- message.im
interactivity:
is_enabled: true
org_deploy_enabled: false
socket_mode_enabled: true
is_hosted: false
token_rotation_enabled: false

5. Click the '''Create''' button

6. Once the app is created, select '''Install to Workspace'''

7. Then select '''Basic Information''' on the left side, scroll down to '''App-Level Tokens''' and click "Generate Token and Scopes", and click "Add Scope" to add all scopes

8. Click "Generate" to get an APP_TOKEN, copy and paste it to '''install.conf'''

APP_TOKEN=<generated token>

9. At "OAuth & Permissions" page, copy and paste the "Bot User OAuth Token" to install.conf

BOT_TOKEN=<generated token>

Once this is complete, the bot is now configured and ready to be installed! Follow the instructions below on running the installation script to finish the installation process.

[[Installing_the_Lingobot_Service|Next: Install and Start the Lingobot Service]]

== LingoBot CA Flowdock Setup ==
This portion of the installation guide only applies if the collaboration environment you will be using is CA Flowdock. If you will be using either Slack or Cisco Spark, please follow the corresponding setup instructions.

Setting up LingoBot to run on CA Flowdock is as simple as creating a new user account through which LingoBot will communicate. If you would rather not deal with the hassle of creating a new Flowdock user account, feel free to ask us to make one for your LingoBot instance. We will send you the API token needed for LingoBot's configuration file and you can simply invite the account to join your Flow once it is ready.

If you don't mind creating the account yourself, then simply follow these instructions to do so.

* First, you will need an email account with which you can create a Flowdock account. You can make one for free on [https://accounts.google.com/SignUp?hl=en-US Gmail] if need be.
* Once this is completed, navigate to the [https://www.flowdock.com/signup Flowdock Sign Up page] and click "Sign Up Using Google"
* When prompted, sign in using the Google account you created for LingoBot (alternatively, you can sign up using a non-google account by filling out the details manually).
* Once the account has been created, navigate to the [https://www.flowdock.com/account/edit Profile Editing Page] and set the following information:
** Name: Lingoport Chatbot
** Display Name: By default, we recommend simply calling it "lingobot", however you're welcome to name it whatever you would like.
*** If you do choose to call it something other than "lingobot", make sure that you set the LINGOBOT_NAME variable in the configuration file to whatever name you chose.
*** Example: <code>export LINGOBOT_NAME=lingobot-123</code>
** Avatar: You can download the following icon [[File:Lingoport logo small.jpeg|30px]] and upload it, upload your own custom icon, or simply leave it blank.
* Once this is done, scroll down and click "Update Profile"
* The final step is to navigate to the [https://www.flowdock.com/account/tokens API Tokens page]. Here you will find an API token labeled "Personal Api Token".
* Copy the API token and paste it into the LingoBot configuration file next to the HUBOT_FLOWDOCK_API_TOKEN variable declaration.

Example:
export HUBOT_FLOWDOCK_API_TOKEN=0a1b2c3d4e5f6g7a8b9c0d

Furthermore, make sure the LINGOBOT_ADAPTER variable is set to "flowdock".

Example:
export LINGOBOT_ADAPTER=flowdock

Once this is complete, the bot is now configured and ready to be installed! Follow the instructions below on running the installation script to finish the installation process.

[[Installing_the_Lingobot_Service|Next: Install and Start the Lingobot Service]]

== LingoBot Cisco Spark Setup ==
This portion of the installation guide only applies if the collaboration environment you will be using is Cisco Spark. If you will be using either Slack or CA Flowdock, please follow the corresponding setup instructions.

Configuring LingoBot to communicate via Cisco Spark is a fairly straight forward process. All that is required is access to an account that has access to your organization's Cisco Spark.

=== Creating a Custom Bot ===
* The first step is to sign in to your Cisco Spark account on the [https://developer.ciscospark.com/# Developer Portal].
* Once signed in, navigate to the [https://developer.ciscospark.com/add-bot.html Custom Bot Creation page].
* On the bot creation page, fill in the form with the following information:
** Display Name: By default, we recommend simply calling it "lingobot", however you're welcome to name it whatever you would like.
*** If you do choose to call it something other than "lingobot", make sure that you set the LINGOBOT_NAME variable in the configuration file to whatever name you chose.
*** Example: <code>export LINGOBOT_NAME=lingobot-123</code>
** Bot Name: Ideally this should be the same as the display name, however due to the necessity that it be unique this can be just about anything. This will only be used to invite the bot to a chat room.
** Icon: Paste the following URL into the Icon field: '''http://i.imgur.com/3bzw0zp.jpg'''
* Once this is done, click "Add Bot". On the following page, you will find an API token. Click the "Copy" button next to it (or select and copy the token itself) then paste it into the LingoBot configuration file next to the CISCOSPARK_ACCESS_TOKEN variable declaration.

Example:
export CISCOSPARK_ACCESS_TOKEN=LDA5YjBiOTItMTAwOS00ODMxLTk4ZjEtYTQ4OGI4N2FjN2Y2MjVlM2QyNTUtYmM2

=== Creating a Webhook for LingoBot ===
* The final step is to create a webhook that LingoBot can receive message event notifications through. To do this, navigate to the [https://developer.ciscospark.com/endpoint-webhooks-post.html Spark Webhook Creation Page].
* Make sure that the "Test Mode" switch is turned ON. This will allow you to generate webhooks directly into your organization's account.
* Under the "Request Headers" section, fill in the following information:
** Authorization: "Bearer '''[YOUR BOT'S API TOKEN HERE]'''"
* In the "Request Parameters" section, fill in the the following information under the "Your values" column:
** name: This can be anything. i.e. "lingobot".
** targetURL: "'''[YOUR JENKINS INSTANCE URL HERE]''':5001/hubot/ciscospark/incoming"
** resource: "all"
** event: "all"
** secret: This can be just about anything, but ideally it is a random string of letters and numbers that it at least 32 characters long.
*** Whatever you chose for this must also be copied to the LingoBot configuration file, next to the CISCOSPARK_SECRET variable declaration.
Example:
export CISCOSPARK_SECRET=a1b2c3d4e5f6g7h8i9j0k1l2m3n4o5p6
* Once all of these values have been entered, click the "Run" button. You should see a response containing the webhook's information on the right.

Finally, make sure the LINGOBOT_ADAPTER variable is set to "sparkwebhook".

Example:
export LINGOBOT_ADAPTER=sparkwebhook

Once this is complete, the bot is now configured and ready to be installed! Follow the instructions below on running the installation script to finish the installation process.

== LingoBot MS Teams Setup ==
This portion of the installation guide only applies if the collaboration environment you will be using is MS Teams. If you will be using either Flowdock or Cisco Spark or Slack, please skip to the corresponding setup instructions.

=== Setup ngrok===
* Navigate to the [https://ngrok.com/ ngrok] page and sign up a free account or login to an existing account. Click Auth from the left list, and copy your '''Tunnel Authtoken'''.

* Copy the Tunnel Authtoken and paste it into the LingoBot configuration file
('''/var/lib/jenkins/lingoport/lingobot-<x.y>/config/config.yml''') next to the '''authtoken''' variable declaration.

Example:
authtoken: 2nde8yqeH8wLiBkv848BW_2Mm39SdudjQJmJ7xxxxxx
tunnels:
default:
proto: http
addr: 5001

* As a root user (not jenkins), run the following commands to start the ngrok service
sudo systemctl enable ngrok.service
sudo systemctl start ngrok.service
sudo systemctl status ngrok.service
If the status does not show '''active (running)''', then there is a problem.

* Return to the [https://ngrok.com/ ngrok] page and click '''Status''' from the left list. If the page does not show any tunnels online, refresh the page. Store the HTTPS URL for later use.

=== Microsoft Bot Registration===

* Navigate to the [https://portal.azure.com/#create/Microsoft.AzureBot AzureBot Registration Page] page. Create a Botframework Registration by completing the Bot Registration Page. Or login to an existing account.

[[File:Azurebot.PNG|700px]]
[[File:Azurebot2.PNG|700px]]

* On this page, you can set a custom icon for the bot under the "'''Upload custom icon'''" section. You can download the following icon [[File:Lingoport logo small.jpeg|30px]] and upload it, upload your own custom icon, or simply leave it blank.

* In the '''Display name''' field, enter the name that you would like LingoBot to respond to.
** By default, we recommend simply calling it "'''lingobot'''", however you're welcome to name it whatever you would like.
** If you do choose to call it something other than "lingobot", make sure that you set the '''LINGOBOT_NAME''' variable in the configuration file to whatever name you chose.
*** Example: <code>export LINGOBOT_NAME=lingobot-123</code>

* Click '''Create Microsoft App ID and password'''. You may be prompted to login into your MS Teams account first. Store the created app id and app password for use later. See this page [https://docs.microsoft.com/en-us/azure/bot-service/bot-service-resources-bot-framework-faq?view=azure-bot-service-4.0#app-registration how to create a new app and generate password]

* Copy the created app id and paste it into the LingoBot configuration file
('''/var/lib/jenkins/lingoport/lingobot-<x.y>/config/lingobot_config.sh''') next to the '''BOTBUILDER_APP_ID''' variable declaration.

Example:
export BOTBUILDER_APP_ID=e8911192-eca4-4f37-8284-616f3339f0e6

Furthermore, make sure the '''LINGOBOT_ADAPTER''' variable is set to '''botframework'''.

Example:
export LINGOBOT_ADAPTER=botframework

* Copy the created app password and past it into the LingoBot configuration file
('''/var/lib/jenkins/lingoport/lingobot-<x.y>/config/lingobot_config.sh''') next to the '''BOTBUILDER_APP_PASSWORD''' variable declaration.

Example:
export BOTBUILDER_APP_PASSWORD='wdS50{cphgeDCTKZO073{]#'

* Copy and paste the URL generated by ngrok to '''Messaging endpoint''' field on the Botframework Registration page, and add /api/messages to the end.

Example:
https://87406e76.ngrok.io/api/messages

[[File:Endpoint.PNG|700px]]

* Fill in the '''Paste your app ID below to continue''' field using the App ID.

* Once this is done, scroll down to the bottom of the page, agree to the terms of service, and click "'''Register'''" to complete.

* On the new opened '''My bots''' page, you will find your just created bot, under '''Connect to channels''' field, the Web Chat has been added as default. Click MS Teams icon under "'''Add a featured channel'''" to add MS Teams channel. And '''Save''' your changes.

[[File:Channel.PNG|700px]]

=== Create a Microsoft Teams app package ===

* Installing App Studio for Microsoft Teams follow steps on [https://docs.microsoft.com/en-us/microsoftteams/platform/get-started/get-started-app-studio this] page.

* Once you are in App Studio, click on the '''Chat''' tab, '''App Studio''' and the '''Manifest editor''' tab. Click '''Create a new app'''.

* Complete the '''App details''' section. This includes things such as the app’s name, description, and visual branding. You can automatically generate a GUID for your app and provide URLs for your privacy statement and terms of use.

* Click '''Bots''' section, '''Set up''' a bot then click '''Existing bot''' tab, type in your bot name and '''Select from one of your existing bots''', then choose the bot you just created above. '''Save'''.

* Copy and paste the URL to Messaging endpoints and make sure it matches the value you just set at bot Register page.

Example:
https://87406e76.ngrok.io/api/messages

* Click "Add" button under Commands section to add new commands

Example:
Command text: list projects
Help text: Displays list of active projects
Scope: Team

* Create a Microsoft Teams app package (.zip) to upload in Teams. Click '''Test and distribute''' under the '''Finish''' section, and click '''Download''' button to download the package file.

* Click the '''Store''' button (left down at the Teams), click '''Upload a custom app''' (at bottom left). And upload the package file just created above.

Once this is complete, the bot is now configured and ready to be installed! Follow the instructions below on running the installation script to finish the installation process.

[[Installing_the_Lingobot_Service|Next: Install and Start the Lingobot Service]]

Configure the Collaboration Environment

2024-03-19T21:54:25Z

Rdaly: /* Create a Microsoft Teams app package */

Lingobot supports several collaboration environments; Slack, Flowdock and Cisco Spark.

== LingoBot Slack Setup ==
This portion of the installation guide only applies if the collaboration environment you will be using is Slack.

1. Go to https://api.slack.com/apps

2. Click '''Create New App'''

3. Choose '''From an app manifest''' and choose a workspace. The workspace will probably be the company workspace

4. Choose the '''YAML''' tab
Enter App Manifest using contents of '''manifest.yaml'''
#manifest.yaml
display_information:
name: Lingobot App
features:
app_home:
home_tab_enabled: false
messages_tab_enabled: true
messages_tab_read_only_enabled: false
bot_user:
display_name: lingobot
always_online: true
oauth_config:
scopes:
bot:
- channels:history
- channels:join
- commands
- chat:write
- im:history
settings:
event_subscriptions:
bot_events:
- message.channels
- message.im
interactivity:
is_enabled: true
org_deploy_enabled: false
socket_mode_enabled: true
is_hosted: false
token_rotation_enabled: false

5. Click the '''Create''' button

6. Once the app is created, select '''Install to Workspace'''

7. Then select '''Basic Information''' on the left side, scroll down to '''App-Level Tokens''' and click "Generate Token and Scopes", and click "Add Scope" to add all scopes

8. Click "Generate" to get an APP_TOKEN, copy and paste it to '''install.conf'''

APP_TOKEN=<generated token>

9. At "OAuth & Permissions" page, copy and paste the "Bot User OAuth Token" to install.conf

BOT_TOKEN=<generated token>

Once this is complete, the bot is now configured and ready to be installed! Follow the instructions below on running the installation script to finish the installation process.

Skip to the next step: [http://wiki.lingoport.com/LingoBot_Installation#Running_The_Installation_Script Running The Installation Script]

== LingoBot CA Flowdock Setup ==
This portion of the installation guide only applies if the collaboration environment you will be using is CA Flowdock. If you will be using either Slack or Cisco Spark, please follow the corresponding setup instructions.

Setting up LingoBot to run on CA Flowdock is as simple as creating a new user account through which LingoBot will communicate. If you would rather not deal with the hassle of creating a new Flowdock user account, feel free to ask us to make one for your LingoBot instance. We will send you the API token needed for LingoBot's configuration file and you can simply invite the account to join your Flow once it is ready.

If you don't mind creating the account yourself, then simply follow these instructions to do so.

* First, you will need an email account with which you can create a Flowdock account. You can make one for free on [https://accounts.google.com/SignUp?hl=en-US Gmail] if need be.
* Once this is completed, navigate to the [https://www.flowdock.com/signup Flowdock Sign Up page] and click "Sign Up Using Google"
* When prompted, sign in using the Google account you created for LingoBot (alternatively, you can sign up using a non-google account by filling out the details manually).
* Once the account has been created, navigate to the [https://www.flowdock.com/account/edit Profile Editing Page] and set the following information:
** Name: Lingoport Chatbot
** Display Name: By default, we recommend simply calling it "lingobot", however you're welcome to name it whatever you would like.
*** If you do choose to call it something other than "lingobot", make sure that you set the LINGOBOT_NAME variable in the configuration file to whatever name you chose.
*** Example: <code>export LINGOBOT_NAME=lingobot-123</code>
** Avatar: You can download the following icon [[File:Lingoport logo small.jpeg|30px]] and upload it, upload your own custom icon, or simply leave it blank.
* Once this is done, scroll down and click "Update Profile"
* The final step is to navigate to the [https://www.flowdock.com/account/tokens API Tokens page]. Here you will find an API token labeled "Personal Api Token".
* Copy the API token and paste it into the LingoBot configuration file next to the HUBOT_FLOWDOCK_API_TOKEN variable declaration.

Example:
export HUBOT_FLOWDOCK_API_TOKEN=0a1b2c3d4e5f6g7a8b9c0d

Furthermore, make sure the LINGOBOT_ADAPTER variable is set to "flowdock".

Example:
export LINGOBOT_ADAPTER=flowdock

Once this is complete, the bot is now configured and ready to be installed! Follow the instructions below on running the installation script to finish the installation process.

Skip to the next step: [http://wiki.lingoport.com/LingoBot_Installation#Running_The_Installation_Script Running The Installation Script]

== LingoBot Cisco Spark Setup ==
This portion of the installation guide only applies if the collaboration environment you will be using is Cisco Spark. If you will be using either Slack or CA Flowdock, please follow the corresponding setup instructions.

Configuring LingoBot to communicate via Cisco Spark is a fairly straight forward process. All that is required is access to an account that has access to your organization's Cisco Spark.

=== Creating a Custom Bot ===
* The first step is to sign in to your Cisco Spark account on the [https://developer.ciscospark.com/# Developer Portal].
* Once signed in, navigate to the [https://developer.ciscospark.com/add-bot.html Custom Bot Creation page].
* On the bot creation page, fill in the form with the following information:
** Display Name: By default, we recommend simply calling it "lingobot", however you're welcome to name it whatever you would like.
*** If you do choose to call it something other than "lingobot", make sure that you set the LINGOBOT_NAME variable in the configuration file to whatever name you chose.
*** Example: <code>export LINGOBOT_NAME=lingobot-123</code>
** Bot Name: Ideally this should be the same as the display name, however due to the necessity that it be unique this can be just about anything. This will only be used to invite the bot to a chat room.
** Icon: Paste the following URL into the Icon field: '''http://i.imgur.com/3bzw0zp.jpg'''
* Once this is done, click "Add Bot". On the following page, you will find an API token. Click the "Copy" button next to it (or select and copy the token itself) then paste it into the LingoBot configuration file next to the CISCOSPARK_ACCESS_TOKEN variable declaration.

Example:
export CISCOSPARK_ACCESS_TOKEN=LDA5YjBiOTItMTAwOS00ODMxLTk4ZjEtYTQ4OGI4N2FjN2Y2MjVlM2QyNTUtYmM2

=== Creating a Webhook for LingoBot ===
* The final step is to create a webhook that LingoBot can receive message event notifications through. To do this, navigate to the [https://developer.ciscospark.com/endpoint-webhooks-post.html Spark Webhook Creation Page].
* Make sure that the "Test Mode" switch is turned ON. This will allow you to generate webhooks directly into your organization's account.
* Under the "Request Headers" section, fill in the following information:
** Authorization: "Bearer '''[YOUR BOT'S API TOKEN HERE]'''"
* In the "Request Parameters" section, fill in the the following information under the "Your values" column:
** name: This can be anything. i.e. "lingobot".
** targetURL: "'''[YOUR JENKINS INSTANCE URL HERE]''':5001/hubot/ciscospark/incoming"
** resource: "all"
** event: "all"
** secret: This can be just about anything, but ideally it is a random string of letters and numbers that it at least 32 characters long.
*** Whatever you chose for this must also be copied to the LingoBot configuration file, next to the CISCOSPARK_SECRET variable declaration.
Example:
export CISCOSPARK_SECRET=a1b2c3d4e5f6g7h8i9j0k1l2m3n4o5p6
* Once all of these values have been entered, click the "Run" button. You should see a response containing the webhook's information on the right.

Finally, make sure the LINGOBOT_ADAPTER variable is set to "sparkwebhook".

Example:
export LINGOBOT_ADAPTER=sparkwebhook

Once this is complete, the bot is now configured and ready to be installed! Follow the instructions below on running the installation script to finish the installation process.

== LingoBot MS Teams Setup ==
This portion of the installation guide only applies if the collaboration environment you will be using is MS Teams. If you will be using either Flowdock or Cisco Spark or Slack, please skip to the corresponding setup instructions.

=== Setup ngrok===
* Navigate to the [https://ngrok.com/ ngrok] page and sign up a free account or login to an existing account. Click Auth from the left list, and copy your '''Tunnel Authtoken'''.

* Copy the Tunnel Authtoken and paste it into the LingoBot configuration file
('''/var/lib/jenkins/lingoport/lingobot-<x.y>/config/config.yml''') next to the '''authtoken''' variable declaration.

Example:
authtoken: 2nde8yqeH8wLiBkv848BW_2Mm39SdudjQJmJ7xxxxxx
tunnels:
default:
proto: http
addr: 5001

* As a root user (not jenkins), run the following commands to start the ngrok service
sudo systemctl enable ngrok.service
sudo systemctl start ngrok.service
sudo systemctl status ngrok.service
If the status does not show '''active (running)''', then there is a problem.

* Return to the [https://ngrok.com/ ngrok] page and click '''Status''' from the left list. If the page does not show any tunnels online, refresh the page. Store the HTTPS URL for later use.

=== Microsoft Bot Registration===

* Navigate to the [https://portal.azure.com/#create/Microsoft.AzureBot AzureBot Registration Page] page. Create a Botframework Registration by completing the Bot Registration Page. Or login to an existing account.

[[File:Azurebot.PNG|700px]]
[[File:Azurebot2.PNG|700px]]

* On this page, you can set a custom icon for the bot under the "'''Upload custom icon'''" section. You can download the following icon [[File:Lingoport logo small.jpeg|30px]] and upload it, upload your own custom icon, or simply leave it blank.

* In the '''Display name''' field, enter the name that you would like LingoBot to respond to.
** By default, we recommend simply calling it "'''lingobot'''", however you're welcome to name it whatever you would like.
** If you do choose to call it something other than "lingobot", make sure that you set the '''LINGOBOT_NAME''' variable in the configuration file to whatever name you chose.
*** Example: <code>export LINGOBOT_NAME=lingobot-123</code>

* Click '''Create Microsoft App ID and password'''. You may be prompted to login into your MS Teams account first. Store the created app id and app password for use later. See this page [https://docs.microsoft.com/en-us/azure/bot-service/bot-service-resources-bot-framework-faq?view=azure-bot-service-4.0#app-registration how to create a new app and generate password]

* Copy the created app id and paste it into the LingoBot configuration file
('''/var/lib/jenkins/lingoport/lingobot-<x.y>/config/lingobot_config.sh''') next to the '''BOTBUILDER_APP_ID''' variable declaration.

Example:
export BOTBUILDER_APP_ID=e8911192-eca4-4f37-8284-616f3339f0e6

Furthermore, make sure the '''LINGOBOT_ADAPTER''' variable is set to '''botframework'''.

Example:
export LINGOBOT_ADAPTER=botframework

* Copy the created app password and past it into the LingoBot configuration file
('''/var/lib/jenkins/lingoport/lingobot-<x.y>/config/lingobot_config.sh''') next to the '''BOTBUILDER_APP_PASSWORD''' variable declaration.

Example:
export BOTBUILDER_APP_PASSWORD='wdS50{cphgeDCTKZO073{]#'

* Copy and paste the URL generated by ngrok to '''Messaging endpoint''' field on the Botframework Registration page, and add /api/messages to the end.

Example:
https://87406e76.ngrok.io/api/messages

[[File:Endpoint.PNG|700px]]

* Fill in the '''Paste your app ID below to continue''' field using the App ID.

* Once this is done, scroll down to the bottom of the page, agree to the terms of service, and click "'''Register'''" to complete.

* On the new opened '''My bots''' page, you will find your just created bot, under '''Connect to channels''' field, the Web Chat has been added as default. Click MS Teams icon under "'''Add a featured channel'''" to add MS Teams channel. And '''Save''' your changes.

[[File:Channel.PNG|700px]]

=== Create a Microsoft Teams app package ===

* Installing App Studio for Microsoft Teams follow steps on [https://docs.microsoft.com/en-us/microsoftteams/platform/get-started/get-started-app-studio this] page.

* Once you are in App Studio, click on the '''Chat''' tab, '''App Studio''' and the '''Manifest editor''' tab. Click '''Create a new app'''.

* Complete the '''App details''' section. This includes things such as the app’s name, description, and visual branding. You can automatically generate a GUID for your app and provide URLs for your privacy statement and terms of use.

* Click '''Bots''' section, '''Set up''' a bot then click '''Existing bot''' tab, type in your bot name and '''Select from one of your existing bots''', then choose the bot you just created above. '''Save'''.

* Copy and paste the URL to Messaging endpoints and make sure it matches the value you just set at bot Register page.

Example:
https://87406e76.ngrok.io/api/messages

* Click "Add" button under Commands section to add new commands

Example:
Command text: list projects
Help text: Displays list of active projects
Scope: Team

* Create a Microsoft Teams app package (.zip) to upload in Teams. Click '''Test and distribute''' under the '''Finish''' section, and click '''Download''' button to download the package file.

* Click the '''Store''' button (left down at the Teams), click '''Upload a custom app''' (at bottom left). And upload the package file just created above.

Once this is complete, the bot is now configured and ready to be installed! Follow the instructions below on running the installation script to finish the installation process.

[[Installing_the_Lingobot_Service|Next: Install and Start the Lingobot Service]]

Configure the Collaboration Environment

2024-03-19T21:53:29Z

Rdaly:

Lingobot supports several collaboration environments; Slack, Flowdock and Cisco Spark.

== LingoBot Slack Setup ==
This portion of the installation guide only applies if the collaboration environment you will be using is Slack.

1. Go to https://api.slack.com/apps

2. Click '''Create New App'''

3. Choose '''From an app manifest''' and choose a workspace. The workspace will probably be the company workspace

4. Choose the '''YAML''' tab
Enter App Manifest using contents of '''manifest.yaml'''
#manifest.yaml
display_information:
name: Lingobot App
features:
app_home:
home_tab_enabled: false
messages_tab_enabled: true
messages_tab_read_only_enabled: false
bot_user:
display_name: lingobot
always_online: true
oauth_config:
scopes:
bot:
- channels:history
- channels:join
- commands
- chat:write
- im:history
settings:
event_subscriptions:
bot_events:
- message.channels
- message.im
interactivity:
is_enabled: true
org_deploy_enabled: false
socket_mode_enabled: true
is_hosted: false
token_rotation_enabled: false

5. Click the '''Create''' button

6. Once the app is created, select '''Install to Workspace'''

7. Then select '''Basic Information''' on the left side, scroll down to '''App-Level Tokens''' and click "Generate Token and Scopes", and click "Add Scope" to add all scopes

8. Click "Generate" to get an APP_TOKEN, copy and paste it to '''install.conf'''

APP_TOKEN=<generated token>

9. At "OAuth & Permissions" page, copy and paste the "Bot User OAuth Token" to install.conf

BOT_TOKEN=<generated token>

Once this is complete, the bot is now configured and ready to be installed! Follow the instructions below on running the installation script to finish the installation process.

Skip to the next step: [http://wiki.lingoport.com/LingoBot_Installation#Running_The_Installation_Script Running The Installation Script]

== LingoBot CA Flowdock Setup ==
This portion of the installation guide only applies if the collaboration environment you will be using is CA Flowdock. If you will be using either Slack or Cisco Spark, please follow the corresponding setup instructions.

Setting up LingoBot to run on CA Flowdock is as simple as creating a new user account through which LingoBot will communicate. If you would rather not deal with the hassle of creating a new Flowdock user account, feel free to ask us to make one for your LingoBot instance. We will send you the API token needed for LingoBot's configuration file and you can simply invite the account to join your Flow once it is ready.

If you don't mind creating the account yourself, then simply follow these instructions to do so.

* First, you will need an email account with which you can create a Flowdock account. You can make one for free on [https://accounts.google.com/SignUp?hl=en-US Gmail] if need be.
* Once this is completed, navigate to the [https://www.flowdock.com/signup Flowdock Sign Up page] and click "Sign Up Using Google"
* When prompted, sign in using the Google account you created for LingoBot (alternatively, you can sign up using a non-google account by filling out the details manually).
* Once the account has been created, navigate to the [https://www.flowdock.com/account/edit Profile Editing Page] and set the following information:
** Name: Lingoport Chatbot
** Display Name: By default, we recommend simply calling it "lingobot", however you're welcome to name it whatever you would like.
*** If you do choose to call it something other than "lingobot", make sure that you set the LINGOBOT_NAME variable in the configuration file to whatever name you chose.
*** Example: <code>export LINGOBOT_NAME=lingobot-123</code>
** Avatar: You can download the following icon [[File:Lingoport logo small.jpeg|30px]] and upload it, upload your own custom icon, or simply leave it blank.
* Once this is done, scroll down and click "Update Profile"
* The final step is to navigate to the [https://www.flowdock.com/account/tokens API Tokens page]. Here you will find an API token labeled "Personal Api Token".
* Copy the API token and paste it into the LingoBot configuration file next to the HUBOT_FLOWDOCK_API_TOKEN variable declaration.

Example:
export HUBOT_FLOWDOCK_API_TOKEN=0a1b2c3d4e5f6g7a8b9c0d

Furthermore, make sure the LINGOBOT_ADAPTER variable is set to "flowdock".

Example:
export LINGOBOT_ADAPTER=flowdock

Once this is complete, the bot is now configured and ready to be installed! Follow the instructions below on running the installation script to finish the installation process.

Skip to the next step: [http://wiki.lingoport.com/LingoBot_Installation#Running_The_Installation_Script Running The Installation Script]

== LingoBot Cisco Spark Setup ==
This portion of the installation guide only applies if the collaboration environment you will be using is Cisco Spark. If you will be using either Slack or CA Flowdock, please follow the corresponding setup instructions.

Configuring LingoBot to communicate via Cisco Spark is a fairly straight forward process. All that is required is access to an account that has access to your organization's Cisco Spark.

=== Creating a Custom Bot ===
* The first step is to sign in to your Cisco Spark account on the [https://developer.ciscospark.com/# Developer Portal].
* Once signed in, navigate to the [https://developer.ciscospark.com/add-bot.html Custom Bot Creation page].
* On the bot creation page, fill in the form with the following information:
** Display Name: By default, we recommend simply calling it "lingobot", however you're welcome to name it whatever you would like.
*** If you do choose to call it something other than "lingobot", make sure that you set the LINGOBOT_NAME variable in the configuration file to whatever name you chose.
*** Example: <code>export LINGOBOT_NAME=lingobot-123</code>
** Bot Name: Ideally this should be the same as the display name, however due to the necessity that it be unique this can be just about anything. This will only be used to invite the bot to a chat room.
** Icon: Paste the following URL into the Icon field: '''http://i.imgur.com/3bzw0zp.jpg'''
* Once this is done, click "Add Bot". On the following page, you will find an API token. Click the "Copy" button next to it (or select and copy the token itself) then paste it into the LingoBot configuration file next to the CISCOSPARK_ACCESS_TOKEN variable declaration.

Example:
export CISCOSPARK_ACCESS_TOKEN=LDA5YjBiOTItMTAwOS00ODMxLTk4ZjEtYTQ4OGI4N2FjN2Y2MjVlM2QyNTUtYmM2

=== Creating a Webhook for LingoBot ===
* The final step is to create a webhook that LingoBot can receive message event notifications through. To do this, navigate to the [https://developer.ciscospark.com/endpoint-webhooks-post.html Spark Webhook Creation Page].
* Make sure that the "Test Mode" switch is turned ON. This will allow you to generate webhooks directly into your organization's account.
* Under the "Request Headers" section, fill in the following information:
** Authorization: "Bearer '''[YOUR BOT'S API TOKEN HERE]'''"
* In the "Request Parameters" section, fill in the the following information under the "Your values" column:
** name: This can be anything. i.e. "lingobot".
** targetURL: "'''[YOUR JENKINS INSTANCE URL HERE]''':5001/hubot/ciscospark/incoming"
** resource: "all"
** event: "all"
** secret: This can be just about anything, but ideally it is a random string of letters and numbers that it at least 32 characters long.
*** Whatever you chose for this must also be copied to the LingoBot configuration file, next to the CISCOSPARK_SECRET variable declaration.
Example:
export CISCOSPARK_SECRET=a1b2c3d4e5f6g7h8i9j0k1l2m3n4o5p6
* Once all of these values have been entered, click the "Run" button. You should see a response containing the webhook's information on the right.

Finally, make sure the LINGOBOT_ADAPTER variable is set to "sparkwebhook".

Example:
export LINGOBOT_ADAPTER=sparkwebhook

Once this is complete, the bot is now configured and ready to be installed! Follow the instructions below on running the installation script to finish the installation process.

== LingoBot MS Teams Setup ==
This portion of the installation guide only applies if the collaboration environment you will be using is MS Teams. If you will be using either Flowdock or Cisco Spark or Slack, please skip to the corresponding setup instructions.

=== Setup ngrok===
* Navigate to the [https://ngrok.com/ ngrok] page and sign up a free account or login to an existing account. Click Auth from the left list, and copy your '''Tunnel Authtoken'''.

* Copy the Tunnel Authtoken and paste it into the LingoBot configuration file
('''/var/lib/jenkins/lingoport/lingobot-<x.y>/config/config.yml''') next to the '''authtoken''' variable declaration.

Example:
authtoken: 2nde8yqeH8wLiBkv848BW_2Mm39SdudjQJmJ7xxxxxx
tunnels:
default:
proto: http
addr: 5001

* As a root user (not jenkins), run the following commands to start the ngrok service
sudo systemctl enable ngrok.service
sudo systemctl start ngrok.service
sudo systemctl status ngrok.service
If the status does not show '''active (running)''', then there is a problem.

* Return to the [https://ngrok.com/ ngrok] page and click '''Status''' from the left list. If the page does not show any tunnels online, refresh the page. Store the HTTPS URL for later use.

=== Microsoft Bot Registration===

* Navigate to the [https://portal.azure.com/#create/Microsoft.AzureBot AzureBot Registration Page] page. Create a Botframework Registration by completing the Bot Registration Page. Or login to an existing account.

[[File:Azurebot.PNG|700px]]
[[File:Azurebot2.PNG|700px]]

* On this page, you can set a custom icon for the bot under the "'''Upload custom icon'''" section. You can download the following icon [[File:Lingoport logo small.jpeg|30px]] and upload it, upload your own custom icon, or simply leave it blank.

* In the '''Display name''' field, enter the name that you would like LingoBot to respond to.
** By default, we recommend simply calling it "'''lingobot'''", however you're welcome to name it whatever you would like.
** If you do choose to call it something other than "lingobot", make sure that you set the '''LINGOBOT_NAME''' variable in the configuration file to whatever name you chose.
*** Example: <code>export LINGOBOT_NAME=lingobot-123</code>

* Click '''Create Microsoft App ID and password'''. You may be prompted to login into your MS Teams account first. Store the created app id and app password for use later. See this page [https://docs.microsoft.com/en-us/azure/bot-service/bot-service-resources-bot-framework-faq?view=azure-bot-service-4.0#app-registration how to create a new app and generate password]

* Copy the created app id and paste it into the LingoBot configuration file
('''/var/lib/jenkins/lingoport/lingobot-<x.y>/config/lingobot_config.sh''') next to the '''BOTBUILDER_APP_ID''' variable declaration.

Example:
export BOTBUILDER_APP_ID=e8911192-eca4-4f37-8284-616f3339f0e6

Furthermore, make sure the '''LINGOBOT_ADAPTER''' variable is set to '''botframework'''.

Example:
export LINGOBOT_ADAPTER=botframework

* Copy the created app password and past it into the LingoBot configuration file
('''/var/lib/jenkins/lingoport/lingobot-<x.y>/config/lingobot_config.sh''') next to the '''BOTBUILDER_APP_PASSWORD''' variable declaration.

Example:
export BOTBUILDER_APP_PASSWORD='wdS50{cphgeDCTKZO073{]#'

* Copy and paste the URL generated by ngrok to '''Messaging endpoint''' field on the Botframework Registration page, and add /api/messages to the end.

Example:
https://87406e76.ngrok.io/api/messages

[[File:Endpoint.PNG|700px]]

* Fill in the '''Paste your app ID below to continue''' field using the App ID.

* Once this is done, scroll down to the bottom of the page, agree to the terms of service, and click "'''Register'''" to complete.

* On the new opened '''My bots''' page, you will find your just created bot, under '''Connect to channels''' field, the Web Chat has been added as default. Click MS Teams icon under "'''Add a featured channel'''" to add MS Teams channel. And '''Save''' your changes.

[[File:Channel.PNG|700px]]

=== Create a Microsoft Teams app package ===

* Installing App Studio for Microsoft Teams follow steps on [https://docs.microsoft.com/en-us/microsoftteams/platform/get-started/get-started-app-studio this] page.

* Once you are in App Studio, click on the '''Chat''' tab, '''App Studio''' and the '''Manifest editor''' tab. Click '''Create a new app'''.

* Complete the '''App details''' section. This includes things such as the app’s name, description, and visual branding. You can automatically generate a GUID for your app and provide URLs for your privacy statement and terms of use.

* Click '''Bots''' section, '''Set up''' a bot then click '''Existing bot''' tab, type in your bot name and '''Select from one of your existing bots''', then choose the bot you just created above. '''Save'''.

* Copy and paste the URL to Messaging endpoints and make sure it matches the value you just set at bot Register page.

Example:
https://87406e76.ngrok.io/api/messages

* Click "Add" button under Commands section to add new commands

Example:
Command text: list projects
Help text: Displays list of active projects
Scope: Team

* Create a Microsoft Teams app package (.zip) to upload in Teams. Click '''Test and distribute''' under the '''Finish''' section, and click '''Download''' button to download the package file.

* Click the '''Store''' button (left down at the Teams), click '''Upload a custom app''' (at bottom left). And upload the package file just created above.

Once this is complete, the bot is now configured and ready to be installed! Follow the instructions below on running the installation script to finish the installation process.

Next Step: [http://wiki.lingoport.com/Installing_the_Lingobot_Service Install and Start the Lingobot Service]

[[Installing_the_Lingobot_Service|Next: Install and Start the Lingobot Service]]

Configure the Collaboration Environment

2024-03-19T21:51:18Z

Rdaly: /* LingoBot Slack Setup */

Lingobot supports several collaboration environments; Slack, Flowdock and Cisco Spark.

== LingoBot Slack Setup ==
This portion of the installation guide only applies if the collaboration environment you will be using is Slack.

1. Go to https://api.slack.com/apps

2. Click '''Create New App'''

3. Choose '''From an app manifest''' and choose a workspace. The workspace will probably be the company workspace

4. Choose the '''YAML''' tab
Enter App Manifest using contents of '''manifest.yaml'''
#manifest.yaml
display_information:
name: Lingobot App
features:
app_home:
home_tab_enabled: false
messages_tab_enabled: true
messages_tab_read_only_enabled: false
bot_user:
display_name: lingobot
always_online: true
oauth_config:
scopes:
bot:
- channels:history
- channels:join
- commands
- chat:write
- im:history
settings:
event_subscriptions:
bot_events:
- message.channels
- message.im
interactivity:
is_enabled: true
org_deploy_enabled: false
socket_mode_enabled: true
is_hosted: false
token_rotation_enabled: false

5. Click the '''Create''' button

6. Once the app is created, select '''Install to Workspace'''

7. Then select '''Basic Information''' on the left side, scroll down to '''App-Level Tokens''' and click "Generate Token and Scopes", and click "Add Scope" to add all scopes

8. Click "Generate" to get an APP_TOKEN, copy and paste it to '''install.conf'''

APP_TOKEN=<generated token>

9. At "OAuth & Permissions" page, copy and paste the "Bot User OAuth Token" to install.conf

BOT_TOKEN=<generated token>

Once this is complete, the bot is now configured and ready to be installed! Follow the instructions below on running the installation script to finish the installation process.

Skip to the next step: [http://wiki.lingoport.com/LingoBot_Installation#Running_The_Installation_Script Running The Installation Script]

== LingoBot CA Flowdock Setup ==
This portion of the installation guide only applies if the collaboration environment you will be using is CA Flowdock. If you will be using either Slack or Cisco Spark, please follow the corresponding setup instructions.

Setting up LingoBot to run on CA Flowdock is as simple as creating a new user account through which LingoBot will communicate. If you would rather not deal with the hassle of creating a new Flowdock user account, feel free to ask us to make one for your LingoBot instance. We will send you the API token needed for LingoBot's configuration file and you can simply invite the account to join your Flow once it is ready.

If you don't mind creating the account yourself, then simply follow these instructions to do so.

* First, you will need an email account with which you can create a Flowdock account. You can make one for free on [https://accounts.google.com/SignUp?hl=en-US Gmail] if need be.
* Once this is completed, navigate to the [https://www.flowdock.com/signup Flowdock Sign Up page] and click "Sign Up Using Google"
* When prompted, sign in using the Google account you created for LingoBot (alternatively, you can sign up using a non-google account by filling out the details manually).
* Once the account has been created, navigate to the [https://www.flowdock.com/account/edit Profile Editing Page] and set the following information:
** Name: Lingoport Chatbot
** Display Name: By default, we recommend simply calling it "lingobot", however you're welcome to name it whatever you would like.
*** If you do choose to call it something other than "lingobot", make sure that you set the LINGOBOT_NAME variable in the configuration file to whatever name you chose.
*** Example: <code>export LINGOBOT_NAME=lingobot-123</code>
** Avatar: You can download the following icon [[File:Lingoport logo small.jpeg|30px]] and upload it, upload your own custom icon, or simply leave it blank.
* Once this is done, scroll down and click "Update Profile"
* The final step is to navigate to the [https://www.flowdock.com/account/tokens API Tokens page]. Here you will find an API token labeled "Personal Api Token".
* Copy the API token and paste it into the LingoBot configuration file next to the HUBOT_FLOWDOCK_API_TOKEN variable declaration.

Example:
export HUBOT_FLOWDOCK_API_TOKEN=0a1b2c3d4e5f6g7a8b9c0d

Furthermore, make sure the LINGOBOT_ADAPTER variable is set to "flowdock".

Example:
export LINGOBOT_ADAPTER=flowdock

Once this is complete, the bot is now configured and ready to be installed! Follow the instructions below on running the installation script to finish the installation process.

Skip to the next step: [http://wiki.lingoport.com/LingoBot_Installation#Running_The_Installation_Script Running The Installation Script]

== LingoBot Cisco Spark Setup ==
This portion of the installation guide only applies if the collaboration environment you will be using is Cisco Spark. If you will be using either Slack or CA Flowdock, please follow the corresponding setup instructions.

Configuring LingoBot to communicate via Cisco Spark is a fairly straight forward process. All that is required is access to an account that has access to your organization's Cisco Spark.

=== Creating a Custom Bot ===
* The first step is to sign in to your Cisco Spark account on the [https://developer.ciscospark.com/# Developer Portal].
* Once signed in, navigate to the [https://developer.ciscospark.com/add-bot.html Custom Bot Creation page].
* On the bot creation page, fill in the form with the following information:
** Display Name: By default, we recommend simply calling it "lingobot", however you're welcome to name it whatever you would like.
*** If you do choose to call it something other than "lingobot", make sure that you set the LINGOBOT_NAME variable in the configuration file to whatever name you chose.
*** Example: <code>export LINGOBOT_NAME=lingobot-123</code>
** Bot Name: Ideally this should be the same as the display name, however due to the necessity that it be unique this can be just about anything. This will only be used to invite the bot to a chat room.
** Icon: Paste the following URL into the Icon field: '''http://i.imgur.com/3bzw0zp.jpg'''
* Once this is done, click "Add Bot". On the following page, you will find an API token. Click the "Copy" button next to it (or select and copy the token itself) then paste it into the LingoBot configuration file next to the CISCOSPARK_ACCESS_TOKEN variable declaration.

Example:
export CISCOSPARK_ACCESS_TOKEN=LDA5YjBiOTItMTAwOS00ODMxLTk4ZjEtYTQ4OGI4N2FjN2Y2MjVlM2QyNTUtYmM2

=== Creating a Webhook for LingoBot ===
* The final step is to create a webhook that LingoBot can receive message event notifications through. To do this, navigate to the [https://developer.ciscospark.com/endpoint-webhooks-post.html Spark Webhook Creation Page].
* Make sure that the "Test Mode" switch is turned ON. This will allow you to generate webhooks directly into your organization's account.
* Under the "Request Headers" section, fill in the following information:
** Authorization: "Bearer '''[YOUR BOT'S API TOKEN HERE]'''"
* In the "Request Parameters" section, fill in the the following information under the "Your values" column:
** name: This can be anything. i.e. "lingobot".
** targetURL: "'''[YOUR JENKINS INSTANCE URL HERE]''':5001/hubot/ciscospark/incoming"
** resource: "all"
** event: "all"
** secret: This can be just about anything, but ideally it is a random string of letters and numbers that it at least 32 characters long.
*** Whatever you chose for this must also be copied to the LingoBot configuration file, next to the CISCOSPARK_SECRET variable declaration.
Example:
export CISCOSPARK_SECRET=a1b2c3d4e5f6g7h8i9j0k1l2m3n4o5p6
* Once all of these values have been entered, click the "Run" button. You should see a response containing the webhook's information on the right.

Finally, make sure the LINGOBOT_ADAPTER variable is set to "sparkwebhook".

Example:
export LINGOBOT_ADAPTER=sparkwebhook

Once this is complete, the bot is now configured and ready to be installed! Follow the instructions below on running the installation script to finish the installation process.

== LingoBot MS Teams Setup ==
This portion of the installation guide only applies if the collaboration environment you will be using is MS Teams. If you will be using either Flowdock or Cisco Spark or Slack, please skip to the corresponding setup instructions.

=== Setup ngrok===
* Navigate to the [https://ngrok.com/ ngrok] page and sign up a free account or login to an existing account. Click Auth from the left list, and copy your '''Tunnel Authtoken'''.

* Copy the Tunnel Authtoken and paste it into the LingoBot configuration file
('''/var/lib/jenkins/lingoport/lingobot-<x.y>/config/config.yml''') next to the '''authtoken''' variable declaration.

Example:
authtoken: 2nde8yqeH8wLiBkv848BW_2Mm39SdudjQJmJ7xxxxxx
tunnels:
default:
proto: http
addr: 5001

* As a root user (not jenkins), run the following commands to start the ngrok service
sudo systemctl enable ngrok.service
sudo systemctl start ngrok.service
sudo systemctl status ngrok.service
If the status does not show '''active (running)''', then there is a problem.

* Return to the [https://ngrok.com/ ngrok] page and click '''Status''' from the left list. If the page does not show any tunnels online, refresh the page. Store the HTTPS URL for later use.

=== Microsoft Bot Registration===

* Navigate to the [https://portal.azure.com/#create/Microsoft.AzureBot AzureBot Registration Page] page. Create a Botframework Registration by completing the Bot Registration Page. Or login to an existing account.

[[File:Azurebot.PNG|700px]]
[[File:Azurebot2.PNG|700px]]

* On this page, you can set a custom icon for the bot under the "'''Upload custom icon'''" section. You can download the following icon [[File:Lingoport logo small.jpeg|30px]] and upload it, upload your own custom icon, or simply leave it blank.

* In the '''Display name''' field, enter the name that you would like LingoBot to respond to.
** By default, we recommend simply calling it "'''lingobot'''", however you're welcome to name it whatever you would like.
** If you do choose to call it something other than "lingobot", make sure that you set the '''LINGOBOT_NAME''' variable in the configuration file to whatever name you chose.
*** Example: <code>export LINGOBOT_NAME=lingobot-123</code>

* Click '''Create Microsoft App ID and password'''. You may be prompted to login into your MS Teams account first. Store the created app id and app password for use later. See this page [https://docs.microsoft.com/en-us/azure/bot-service/bot-service-resources-bot-framework-faq?view=azure-bot-service-4.0#app-registration how to create a new app and generate password]

* Copy the created app id and paste it into the LingoBot configuration file
('''/var/lib/jenkins/lingoport/lingobot-<x.y>/config/lingobot_config.sh''') next to the '''BOTBUILDER_APP_ID''' variable declaration.

Example:
export BOTBUILDER_APP_ID=e8911192-eca4-4f37-8284-616f3339f0e6

Furthermore, make sure the '''LINGOBOT_ADAPTER''' variable is set to '''botframework'''.

Example:
export LINGOBOT_ADAPTER=botframework

* Copy the created app password and past it into the LingoBot configuration file
('''/var/lib/jenkins/lingoport/lingobot-<x.y>/config/lingobot_config.sh''') next to the '''BOTBUILDER_APP_PASSWORD''' variable declaration.

Example:
export BOTBUILDER_APP_PASSWORD='wdS50{cphgeDCTKZO073{]#'

* Copy and paste the URL generated by ngrok to '''Messaging endpoint''' field on the Botframework Registration page, and add /api/messages to the end.

Example:
https://87406e76.ngrok.io/api/messages

[[File:Endpoint.PNG|700px]]

* Fill in the '''Paste your app ID below to continue''' field using the App ID.

* Once this is done, scroll down to the bottom of the page, agree to the terms of service, and click "'''Register'''" to complete.

* On the new opened '''My bots''' page, you will find your just created bot, under '''Connect to channels''' field, the Web Chat has been added as default. Click MS Teams icon under "'''Add a featured channel'''" to add MS Teams channel. And '''Save''' your changes.

[[File:Channel.PNG|700px]]

=== Create a Microsoft Teams app package ===

* Installing App Studio for Microsoft Teams follow steps on [https://docs.microsoft.com/en-us/microsoftteams/platform/get-started/get-started-app-studio this] page.

* Once you are in App Studio, click on the '''Chat''' tab, '''App Studio''' and the '''Manifest editor''' tab. Click '''Create a new app'''.

* Complete the '''App details''' section. This includes things such as the app’s name, description, and visual branding. You can automatically generate a GUID for your app and provide URLs for your privacy statement and terms of use.

* Click '''Bots''' section, '''Set up''' a bot then click '''Existing bot''' tab, type in your bot name and '''Select from one of your existing bots''', then choose the bot you just created above. '''Save'''.

* Copy and paste the URL to Messaging endpoints and make sure it matches the value you just set at bot Register page.

Example:
https://87406e76.ngrok.io/api/messages

* Click "Add" button under Commands section to add new commands

Example:
Command text: list projects
Help text: Displays list of active projects
Scope: Team

* Create a Microsoft Teams app package (.zip) to upload in Teams. Click '''Test and distribute''' under the '''Finish''' section, and click '''Download''' button to download the package file.

* Click the '''Store''' button (left down at the Teams), click '''Upload a custom app''' (at bottom left). And upload the package file just created above.

Once this is complete, the bot is now configured and ready to be installed! Follow the instructions below on running the installation script to finish the installation process.

Next Step: [http://wiki.lingoport.com/Installing_the_Lingobot_Service Install and Start the Lingobot Service]

LingoBot Command Center Setup

2024-03-19T21:42:46Z

Rdaly:

=== Create Command Center lingobot user===

[[File:ccbot.png|700px|center]]

In Command Center -> Settings -> Users & Teams:
*Add a new API user called '''lingobot'''.
*Assign teams and projects to the user
*Create
*Copy the token to the clipboard.

=== Update install.conf ===

In the console, update the LingoBot install.conf file:

COMMAND_CENTER_USER=lingobot
COMMAND_CENTER_TOKEN=<copied token>

[[Configure_the_Collaboration_Environment|Next: Configure the Collaboration Environment (Slack/ Flowdock/ Cisco Spark/ MS Teams)]]

LingoBot Command Center Setup

2024-03-19T21:42:28Z

Rdaly:

LingoBot Command Center Setup

2024-03-19T21:41:38Z

Rdaly:

LingoBot Command Center Setup

2024-03-19T21:39:35Z

Rdaly: /* Create Command Center lingobot user */

LingoBot Command Center Setup

2024-03-19T21:39:15Z

Rdaly: /* Update install.conf */

=== Create Command Center lingobot user===

[[File:ccbot.png|700px|center]]

In Command Center -> Settings -> Users & Teams:
*Add a new API user called '''lingobot'''.
*Assign teams and projects to the user
*Create
*Copy the token

=== Update install.conf ===

In the console, update the LingoBot install.conf file:

COMMAND_CENTER_USER=lingobot
COMMAND_CENTER_TOKEN=<copied token>

LingoBot Command Center Setup

2024-03-19T21:38:37Z

Rdaly:

=== Create Command Center lingobot user===

[[File:ccbot.png|700px|center]]

In Command Center -> Settings -> Users & Teams:
*Add a new API user called '''lingobot'''.
*Assign teams and projects to the user
*Create
*Copy the token

=== Update install.conf ===

In the console, update the LingoBot install.conf file:

COMMAND_CENTER_USER=lingobot
COMMAND_CENTER_TOKEN=bW4v1BzkFJtRkM619we1Uwu0