Create a bot that reacts to user inputs
Prerequisites: Up and Running instance of EDDI (see: Getting started)
Let's get started
Follow these steps to create the configuration files you will need:
1. Creating a Regular Dictionary inside Parser
See also Semantic Parser
Create regular dictionaries in order to store custom words and phrases. A dictionary is there to map user input to expressions, which are later used in Behavior Rules
. A POST
to /regulardictionarystore/regulardictionaries
with a JSON in the body like this:
Example using CURL
:
Dictionary parameters
Name
Description
Required
words
Array
of Word
phrases
Array
of Phrase
Word.word
String
, single word, no spaces.
True
Word.expressions
String
, "greeting(hello)": "greeting" is the category of this expression and "hello" is an entity.
Word.frequency
int
, Used for a randomizer
Phrase.phrase
String
, Spaces allowed
True
Phrase.expressions
String
, "greeting(hello)": "greeting" is the category of this expression and "hello" is an entity.
The returned URI is a reference for this specific resource. This resource will be referenced in the bot definition.
2. Creating Behavior Rules
See also Behavior Rules
Next, create a behaviorRule
resource to configure the decision making a. Make a POST
to /behaviorstore/behaviorsets
with a JSON in the body like this:
Behavior Rules parameters
Name
Description
BehaviorRule.name
String
, e.g. "Smalltalk"
BehaviourGroup.behaviorRules
Array
of BehaviorRule
BehaviorRule.name
String
, e.g. "Greeting"
BehaviorRule.actions
Array
of String
, e.g. "greet" or "CONVERSATION_END"
BehaviorRule.conditions
Array
of RuleChild
RuleChild.type
String
, allowed values:
—>"inputmatcher
" (has params: "expressions
" (Array
of String
( and "occurrence
")
—>"negation
" (BehaviorExtension
object, has params: "conditions
" and "occurrence
")
RuleChild.values
HashMap
, allowed values:
—>"expressions
": String
, mandatory. Expression e.g. "greeting(*)" or "how_are_you"
—>"occurrence
": String
, optional. Allowed values "currentStep
"
Negation.conditons
Array
of NegationChild
NegationChild.type
String
e.g. "occurrence
"
NegationChild.values
HashMap, allowed values:
—>"maxTimesOccurred
": String
, e.g. 1
—>"minTimesOccurred
": String
, e.g. 1
—>"behaviorRuleName
": String
You should again get a return code of 201
with a URI
in the location
header referencing the newly created Behavior Rules
:
eddi://ai.labs.behavior/behaviorstore/behaviorsets/
<UNIQUE_BEHAVIOR_ID>
?version=
<BEHAVIOR_VERSION>
Example:
eddi://ai.labs.behavior/behaviorstore/behaviorsets/5a26d8fd17312628b46119fb?version=1
3. Creating Output
You have guessed it correctly, another POST
to /outputstore/outputsets
creates the bot's Output
with a JSON in the body like this:
You should again get a return code of 201
with a URI
in the location
header referencing the newly created output :
eddi://ai.labs.output/outputstore/outputsets/
<UNIQUE_OUTPUTSET_ID>
?version=
<OUTPUTSET_VERSION>
Example :
eddi://ai.labs.output/outputstore/outputsets/5a26d97417312628b46119fc?version=1
4. Creating the Package
Now we will align the just created LifecycleTasks
in the Package
. Make a POST
to /packagestore/packages
with a JSON in the body like this:
Package parameters
Name
Description
Required
packageextensions
Array
of PackageExtension
PackageExtension.type
possible values, see table below "Extension Types
"
PackageExtension.extensions
Array
of Object
False
PackageExtension.config
Config
object, but can be empty.
True
Extension Types
Extension
Config
eddi://ai.labs.parser
Dictionaries
and/or corrections
Object "extensions
" can contain "dictionaries
" (Array
of Dictionary
) and/or "corrections
" (Array
of Correction
)
Object "Dictionary
" has params "type
" and "config
" (optional)
Dictionary.type
can reference Regular-Dictionaries
"eddi://ai.labs.parser.dictionaries.regular
" (needs param "config.uri
") or be one of the EDDI out of the box types:
—>"eddi://ai.labs.parser.dictionaries.integer
"
—>"eddi://ai.labs.parser.dictionaries.decimal
"
—>"eddi://ai.labs.parser.dictionaries.punctuation
"
—>"eddi://ai.labs.parser.dictionaries.email
"
—>"eddi://ai.labs.parser.dictionaries.time
"
—>"eddi://ai.labs.parser.dictionaries.ordinalNumber
"
Object "Correction
" has params "type
" and "config
" (optional)
Correction.type
can reference one of the EDDI out of the box types:
—>"eddi://ai.labs.parser.corrections.stemming
": Object "config
" has params "language
" (String
e.g. "english") and "lookupIfKnown
" (Boolean
)
—>"eddi://ai.labs.parser.corrections.levenshtein
": Object "config
" has param "distance
" (Integer, e.g. 2)
—>"eddi://ai.labs.parser.corrections.mergedTerms
"
eddi://ai.labs.behavior
Object Config
contains param uri
with Link to a behavior set, e.g. eddi://ai.labs.behavior/behaviorstore/behaviorsets/5a26d8fd17312628b46119fb?version=1
eddi://ai.labs.output
Object Config contains param uri
with Link to output set, e.g. eddi://ai.labs.output/outputstore/outputsets/5a26d97417312628b46119fc?version=1
New
Now you can use the new feature of defining properties in the package definition : This can be used by introducing an extension with type
eddi://ai.labs.property
which has the config
model as follows:
Description of eddi://ai.labs.property model
Name
Description
setOnActions.actions
(string
) defines which for which actions (triggered by BehaviorRules) these Properties should be set
setOnActions.setProperties
(Array
<Property
>: ) must respect the Property
model: name
, fromObjectPath
and scope
.
setOnActions.setProperties.name
(string
) name of the Property
.
setOnActions.setProperties.fromObjectPath
(string
) path to the json object.
setOnActions.setProperties.scope
(string
) Possible values step
, conversation
and longTerm
.
Example of eddi://ai.labs.property
You should again get a return code of 201
with an URI
in the location header referencing the newly created package format
eddi://ai.labs.package/packagestore/packages/<UNIQUE_PACKAGE_ID>?version=<PACKAGE_VERSION>
Example
eddi://ai.labs.package/packagestore/packages/5a2ae60f17312624f8b8a445?version=1
See also the API documentation at http://localhost:7070/view#!/configurations/createPackage
5. Creating a Bot
Make a POST
to /botstore/bots
with a JSON like this:
Bot parameters
Name
Description
packages
Array
of String
, references to Packages
channels
Array
of Channel
,
Channel.type
String
, e.g. "eddi://ai.labs.channel.facebook"
Channel.config
Config
Object. For "Facebook" this object has the params "appSecret
" (String
), "verificationToken
" (String
), "pageAccessToken
" (String
)
b. You should again get a return code of 201
with a URI
in the location
header referencing the newly created bot :
eddi://ai.labs.bot/botstore/bots/
<UNIQUE_BOT_ID>
?version=
<BOT_VERSION>
Example:
eddi://ai.labs.bot/botstore/bots/5a2ae68a17312624f8b8a446?version=1
See also the API documentation at http://localhost:7070/view#!/configurations/createBot
6. Launching the Bot
Finally, we are ready to let the bot fly. From here on, you have the possibility to let an UI do it for you or you do it step by step.
The UI that automates these steps can be reached here: /chat/unrestricted/
<UNIQUE_BOT_ID>
Otherwise via REST:
Deploy the Bot:
Make a
POST
to/administration/unrestricted/deploy/
<UNIQUE_BOT_ID>
?version=
<BOT_VERSION>
You will receive a
202
http code.Since deployment could take a while it has been made asynchronous.
Make a
GET
to/administration/unrestricted/deploymentstatus/
<UNIQUE_BOT_ID>
?version=
<BOT_VERSION>
to find out the status of deployment.
NOT_FOUND
, IN_PROGRESS
, ERROR
and READY
is what you can expect to be returned in the body.
As soon as the Bot is deployed and has
READY
status, make aPOST
to/bots/unrestricted/
<UNIQUE_BOT_ID>
You will receive a
201
with theURI
for the newly created Conversation, like this:e.g.
eddi://ai.labs.conversation/conversationstore/conversations/
<UNIQUE_CONVERSATION_ID>
Now it's time to start talking to our Bot 1. Make a
POST
to/bots/unrestricted/
<UNIQUE_BOT_ID>
/
<UNIQUE_CONVERSATION_ID>
Option 1: is to hand over the input text as contentType text/plain
. Include the User Input in the body as text/plain
(e.g. Hello)
Option 2: is to hand over the input as contentType application/json
, which also allows you to handover context information that you can use with the eddi configurations 1. Include the User Input in the body as application/json (e.g. Hello)
You have two query params you can use to config the returned output 1.
returnDetailed
- default is false - will return all sub results of the entire conversation steps, otherwise only public ones such as input, action, output & quickreplies 2.returnCurrentStepOnly
- default is true - will return only the latest conversation step that has just been processed, otherwise returns all conversation steps since the beginning of this conversationThe output from the bot will be returned as JSON
If you are interested in fetching the
conversationmemory
at any given time, make aGET
to/bots/unrestricted/
<UNIQUE_BOT_ID>
/
<UNIQUE_CONVERSATION_ID>
?returnDetailed=true
(the query param is optional, default is false)
If you made it till here, CONGRATULATIONS, you have created your first Chatbot with EDDI !
By the way you can use the attached postman collection below to do all of the steps mentioned above by clicking send on each request in postman.
Create dictionary (greetings)
Create behaviourSet
Create outputSet
Creating package
Creating bot
Deploy the bot
Create conversation
Say Hello to the bot
External Links
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