Chatbot Framework. Overview. Installation. Getting Started

Transcription

1 Chatbot Framework Overview Chatbot framework is available as a gadget in Business Console. It is a new framework for building a user interface that is conversational, and which uses the machine learning technology. It involves creating Agents and configuring each Agent with a set of Entities and Intents. Intents are mapped to Actions and Actions are configured using RESTful APIs. Agents trigger Actions based on the Intent of a user query and produce Responses based on the invoked RESTful APIs. Installation The chatbot framework is available as a sample gadget in Business Console. To install, do one of the following: Copy the wm_bc_gadgets_bot_framework.war file from <SAG_INSTALL>\MWS\components\samples \businessconsole\gadgets\ to <SAG_INSTALL>\ MWS\server\default\deploy. In MWS, go to "Install Administration" and install war file from <SAG_INSTALL>\MWS\components\samples \businessconsole\gadgets\ wm_bc_gadgets_bot_framework.war. By default, the 'chatbot' folder is created in the <SAG_INSTALL>\ path after the first Agent is created, and all agent data is saved inside the folder. If you want to change the path of the 'chatbot' folder, then set the target location using the system property "chatbot.data.path" in the custom_wrapper.conf file. Getting Started After installing the chatbot framework, the "AI Agent" gadgets are available and you can add them to AppSpaces as shown in Figure 1. Following gadgets are for creating Agents and testing Agents: 1. Agent Configuration - Used to create Agent and configure Entities, Intents, Actions, and Server configuration. 2. Chatbot UI - Used to test Agents that are created by the "Agent Configuration" gadget. 3. Export Import Agent - Used to export all chatbot data (Entities, Intents, and Actions) from one Agent o another Agent. These gadgets are explained in the following sections. Figure 1 Chatbot Framework Page 1

2 Agent Configuration Gadget Agent Configuration gadget, as shown in figure 2, is used to create Agent and configure Entities, Intents, Actions, and server configuration for an Agent. Agent Configuration gadget has multiple tabs. Figure 2 Create Agent - Used to create an Agent. You must enter the name of the Agent, its description, and the language that it supports. Currently, the Chatbot framework supports the English language only. For example, figure 3 shows how the "LoanApplicationChatbot" is created. Figure 3 Entity - Entity is a set of words that Agents use to understand the user query and extract parameter values from the natural language. For example, as shown in figure 4, LOANSTATUS is an Entity defined for the "LoanApplicationChatbot" agent. Agent is made aware that the words Rejected, Reject, declined, and decline mean the same as the word "Declined" which is added as Referenced Value. These words are added as Synonym so that if these words are present in a query, the Agent understands it as Referenced Value "Declined". Similarly, you can define the Referenced Value "Approved". Chatbot Framework Page 2

3 If a user query is "Get me loan applications which got rejected", then Agent can identify the word 'rejected' as the Entity LOANSTATUS in the query with Referenced Value "Declined". Figure 4 Two types of Entity are supported: 1. System Entities - The chatbot framework comes with predefined Entities called System Entities. These are built in Entities and can be used by all Agents. You cannot create or edit System Entities. Click "System Entities" to view System Entities. Currently, three System Entities are supported as shown in Figure Figure 5 User Defined Entities - These Entities are domain specific Entities related to an Agent. You can create, update, and view these Entities as described below. You must not create duplicate Entities or same Referenced Value or synonyms in two different Entities as it will confuse an Agent while processing the natural language. While creating Chatbot Framework Page 3

4 the Entities, consider the domain for which you are building the Agent and the user queries for which the Agent needs to respond. 1. Select the Agent or ChatBot name from the drop down depending on your requirement or context. 2. Click "Entities", All Entities created for the Agent appears as shown in figure 6. You can delete the particular Entity or click the Entity name to get all the data for a particular Entity as shown in figure 7. In Figure 7, 'PRODUCT' Entity data is shown. 3. You can change the values presented in figure 7 and click Save to update the entity. 4.On clicking the "+" button, a new window appears with empty values to create a new Entity. You can fill the data and click Save to create new Entity as shown in figure 8. Figure 6 Chatbot Framework Page 4

5 Figure 7 Figure 8 Intents - An Intent means the intention of users. An Agent should respond to a user query and there must be an intention behind the user query. You must configure an Agent with a set of Intents for which it must respond. For Intents that are Chatbot Framework Page 5

6 not associated with the Agent, it can respond with a standard text, for example, "Sorry! Not understood your requirement. Please reframe the question in proper English.". Each intent configuration has the following: Set of prospective user queries and each query will be marked with defined Entity. The Action name that should be invoked by the Agent. Action name will be mapped to a REST API, which needs to be invoked and that configuration can be done in the "Configure Actions" tab. The mapping between parameter name and Entity. User query will be extracted with Entity and reference value of the Entity is assigned to a parameter that is used during configuring Actions, and actual invocation of Action (RESTful API). Users can create, update and view Intents as described below. 1. Select Agent or ChatBot name from the drop down based on your requirement or context. 2. Click "Intents" and all intents created for the Agent appears as shown in figure 9. Users can delete the particular Intent or click the Intent name to get all the data for a particular intent as shown in figure 10. Figure 10 shows the Intent name as 'getloanapplications' mapped to the Action 'getloanapplicationsapi', and user queries, parameter name and mapped Entity. Action 'getloanapplicationsapi' configuration will be described in the next section "Configure Actions". 3. Users can change the values presented in figure 10 and click save to update the Intent. 4. On clicking "+" button, a new window appears with empty values to create new Intent as shown in figure 11. Users can fill the data and click save to create a new Intent. Users can add the query and after adding it, click the query to get the window as shown in figure 12. Users should mark the query words with already defined Entity. User should not mark same word with different Entity. Figure 12 shows the following: 'House' word is tagged as Entity 'MortgageType' 'Purchase' is tagged as Entity 'Product' 'applications' is tagged as Entity 'LOANAPPLICATION' On clicking save, Agent will use these queries and already defined Entity to train itself. After training, the Agent will have the capability to identify Intent even when a similar new query is presented to the Agent and then it invokes proper mapped Action. Action configuration will be dealt in the "Configure Actions" tab. Figure 9 Chatbot Framework Page 6

7 Chatbot Framework Page 7 Figure 10

8 Chatbot Framework Page 8 Figure 11

9 Figure 12 Configure Actions - Multiple Intent can be configured for a Agent and each Intent is mapped to an Action as described in the previous section. This section deals with mapping of Actions to REST APIs and the configuration will have the following as shown in Figure 13. The figure shows the Action name 'getloanapplicationsapi' mapped to REST API with URI '/rest/bc/tasklist'. Chatbot Framework Page 9

10 Figure Select the Action from the drop down for which you want to add the configuration. 2. REST URI - REST API URI which needs to be invoked as per this action. For example, in figure 13 '/rest/bc/tasklist' API is configured. Server on which the REST API is available should be configured in the "Configure Server" tab. In this example, MWS will be configured as described in the next section. 3. HTTP Method - It can be GET, POST, PUT, or DELETE. 4. Consumes - It can be 'application/json' or 'text/plain'. 5. Produces - It can be 'application/json'. 6. Query Parameters - Any query parameter can be configured. Query Parameter name can be defined by user as any text. Either any fixed value or $"Parameter Name" ($ should be in prefix to "Parameter Name" ) as described in the "Intents" tab and can be configured in the Value field. 7. Post Payload - Proper input JSON should be added. JSON Variable value which is dependent on parameter value extracted from the natural language can be added in JSON using $"Parameter Name" ($ should be in prefix to "Parameter Chatbot Framework Page 10

11 Name" ) as described in the "Intents" tab. Refer JSON screenshot of tasklist API given below which is also shown in Figure 13 As UI does not have the capability to check JSON syntax, so it is recommended to create sample JSON and test REST API call from a REST Client like POST Client, then copy the JSON in POST Payload field, and add the $"Parameter Name" where required. This will ensure that configured JSON is syntactically correct. Below given JSON is what is configured and shown in Figure Remove Intent Parameter - If $"Parameter Name" (described in point 6 above) value extracted from the natural language is empty, then empty value will be sent in POST Payload JSON to REST API. If you want to remove the JSON variable when parameter value is empty, then you can configure the "Parameter Name" as comma separated in the field. For example - As in figure 13, LOANTYPE,PRODUCT is configured in "Remove Intent Parameter" and say user query is "which loan applications are House Mortage type". Let's say the Agent identifies the LOANTYPE as "House Mortgage" and PRODUCT as empty, then the input JSON to REST API will be as below. As immediate parent is JSON Array, so complete particular index will be removed from the JSON Array. If it would not have been JSON Array, then only the particular JSON element will be removed. But if "Remove Intent Parameter" would not have been configured, then the input JSON to REST API will be as below. Chatbot Framework Page 11

12 9. Output Text : You should put text that should be responded by the Agent when a particular Action is invoked. It can be simple English text or English text along with simple rules that will process JSON response of REST API, and prepare the response accordingly. For example, the content of field "Output Text" (which is shown in Figure 13) is given in Figure 14, and it has few simple rules which helps the Agent to understand that which value from JSON Response should be used to prepare final response. In Figure 14, it has also been shown which rule tag to which JSON value, and after first iteration how the variable reference changes. Details about these rules is described below. Chatbot Framework Page 12

13 Figure 14 There are #totalrecords loan application. See details for <strong>loan applications</strong>. </br> <ul> (row=#tasks) {{ <li> Loan is created By: #row.createdby and created on: #row.createddate.loan details are (row1=#row.taskdata.entry) {{ #row1.key.$ = #row1.value.$, }} </li> }} </ul> As JSON can have simple JSON element (that is without JSON array) as well as array type of JSON element (JSON Array), so rules should be such that it can process both simple and array type of JSON element. JSON data is written as key/value pairs. A key/value pair consists of a field name (in double quotes), followed by a colon, followed by a value. In JSON, values must be one of the following: a primitive JSON in the form of a string an object (JSON object) an array (JSON Array) Rules support Direct binding of JSON value from primitive JSON type - In this case rule starts with '#' followed by the key name. In Figure 14, yellow highlighted text '#totalrecords' is direct binding. Agent is made to understand it needs to process JSON from start and fetch the value of key with name 'totalrecords'. Variable definition to process JSON Array in loop - Variable definition should be done in () and followed by "space key+{{". Variable will be in scope till matching end brackets "spaced key+}}" is reached in text. Variable definition starts from variable name followed by '=#', and then JSON key. Agent will internally create the variable and point it to the given JSON key. In above example, the Grey highlighted text is variable definition and their end brackets (end Chatbot Framework Page 13

14 brackets marks the end of a loop construct). Two variables are defined, one is 'row' and second is 'row1', and both of them together form a nested loop. The 'row' variable will iterate (outer loop) on 'tasks' JSON Array and 'row1' will iterate (inner loop) on 'entry' JSON array that is inside 'row.taskdata' object ('row' variable points to JSON value which changes on each iteration of outer loop). Figure 14 shows the value to which the variable points in the first iteration. HTML tags - The green color text in Figure 14 in Output text shows some HTML tags which are also supported. Currently, no provision in UI has been given to validate the rule added in 'Output Text'. It is recommended to first add the 'Output Text' in English having simple rules and test the complete flow, and then add the 'Output Text' with rules having loop. Configure Server - This tab deals with configuration of server where all REST API configured with Action is deployed. Figure 15 shows the server configuration for the Agent 'LoanApplicationChatbot': MWS 'daehglobal21302.daedmz.loc:8585' is configured as Server having all the REST API. Only Basic Authentication is supported and user needs to enter the User name and Password as shown in the figure below. Say REST URI configured in Action is '/rest/bc/tasklist' and server is configured as shown in the figure below, then Agent internally will form complete REST URI as "daehglobal21302.daedmz.loc:8585/rest/bc/tasklist" Figure 15 Chatbot UI Gadget - The framework comes with a UI through which users can communicate and test any Agent. Chatbot UI looks as shown in Figure 16. Users can edit the gadget setting, which is available when AppSpace is edited, and select the Agent name to communicate with. Figure 17 shows the response from 'LoanApplicationChatbot' Agent when the query "get House Mortgage and Purchase application" is entered in the UI. Internally the Agent identifies the Entity and Intents using rules and training data and finds user intent is same as what is configured in the Intent 'getloanapplications'. Then, the Agent takes action as mapped to Intent which is 'getloanapplicationsapi' and formulates the input JSON using entity, and invoke the REST API '/rest/bc/tasklist' (API input JSON has fixed task ID which relates to loan application in MWS ). It then processes the JSON response using 'Output Text' (as explained in 'Configure Actions' section ) and prepares the final response which is Chatbot Framework Page 14

15 presented in Chatbot UI gadget as shown in Figure 17. Figure 16 Figure 17 Export Import Agent Gadget - This gadget has been provided to export configuration (Entity, Intent, Action) from a source Agent in a zip file and then import the zip file in to another target Agent which will create the same Entity, Intent, and Action in the target Agent. Figure 18 shows the screenshot of the gadget. Select the Agent from drop down and click 'Export'. The exported zip file will be created in 'chatbot\inbound' Chatbot Framework Page 15

16 folder(check Installation section to find location of the 'chatbot' folder). Once exported, you can select the zip file in Import section from the 'Import File' drop down, then select the target Agent from the drop down and click 'Import'. Entity, Intent, and Action will be imported in the target Agent. Figure 18 Chatbot Framework Page 16