feat(server): trigger next action once all slots have been filled

server/src/core/brain.js

@@ -160,7 +160,10 @@ class Brain {
           executionTime
         })
       } else {
-        const { actionType } = obj
+        const { nluDataFilePath, classification: { action: actionName } } = obj
+        const { actions } = JSON.parse(fs.readFileSync(nluDataFilePath, 'utf8'))
+        const { type: actionType } = actions[actionName]
+
         if (!actionType || !supportedActionTypes.includes(actionType)) {
           log.error(`This action type isn't supported: ${actionType}`)
         }

server/src/core/conversation.js

@@ -7,6 +7,7 @@ const defaultActiveContext = {
   domain: null,
   intent: null,
   slots: { },
+  nextAction: null,
   activatedAt: 0
 }
 
@@ -57,9 +58,12 @@ class Conversation {
 
     // If slots are required to trigger next actions, then go through the context activation
     if (slotKeys.length > 0) {
-      // Grab output context from the NLU data file
       const { actions } = JSON.parse(fs.readFileSync(nluDataFilePath, 'utf8'))
+      const actionsKeys = Object.keys(actions)
+      // Grab output context from the NLU data file
       const { output_context: outputContext } = actions[actionName]
+      // Define next action
+      const [nextAction] = actionsKeys.filter((key) => actions[key].input_context === outputContext)
 
       /**
        * If there is an active context and a new one is triggered
@@ -74,6 +78,7 @@ class Conversation {
           domain,
           intent,
           slots: { },
+          nextAction,
           activatedAt: Date.now()
         }
       }

server/src/core/nlu.js

@@ -120,9 +120,11 @@ class Nlu {
         const { domain, intent } = this.conv.activeContext
         const [skillName, actionName] = intent.split('.')
         const nluDataFilePath = join(process.cwd(), 'skills', domain, skillName, `nlu/${this.brain.lang}.json`)
-        const nluResultObj = {
+        // TODO: create specific method to build this important object
+        let nluResultObj = {
           utterance,
           entities: [],
+          nluDataFilePath,
           classification: {
             domain,
             skill: skillName,
@@ -165,16 +167,29 @@ class Nlu {
            * 2. [OK] If none of them match any slot in the active context, then continue
            * 3. [OK] If an entity match slot in active context, then fill it
            * 4. [OK] Move skill type to action type
-           * 5.1 In Conversation, need to chain output/input contexts to each other
+           * 5.1 [OK] In Conversation, need to chain output/input contexts to each other
            * to understand what action should be next
-           * 5.2 Execute next action (based on input_context?)
+           * 5.2 [OK] Execute next action (based on input_context?)
            * 5.3 Need to handle the case if a context is filled in one shot
            * e.g. I wanna play with 2 players and louis.grenard@gmail.com
-           * 6. Split this process() method into several ones
+           * 6. What's next once the next action has been executed?
-           * 7. Add logs in terminal about context switching, active context, etc.
+           * 7. Handle a "loop" feature from action (guess the number)
+           * 8. Split this process() method into several ones + clean nlu.js and brain.js
+           * 9. Add logs in terminal about context switching, active context, etc.
            */
 
-            // TODO: recreate nluResultObj for the NEXT action (actionType, etc.)
+          nluResultObj = {
+            utterance: '',
+            entities: [],
+            // TODO: the brain needs to forward slots to the skill execution
+            slots: this.conv.activeContext.slots,
+            nluDataFilePath,
+            classification: {
+              domain,
+              skill: skillName,
+              action: this.conv.activeContext.nextAction
+            }
+          }
 
           const data = await this.brain.execute(nluResultObj, { mute: opts.mute })
           return resolve({
@@ -280,10 +295,7 @@ class Nlu {
       log.success(`Intent found: ${nluResultObj.classification.skill}.${nluResultObj.classification.action} (domain: ${nluResultObj.classification.domain})`)
 
       const nluDataFilePath = join(process.cwd(), 'skills', nluResultObj.classification.domain, nluResultObj.classification.skill, `nlu/${this.brain.lang}.json`)
-      const { actions } = JSON.parse(fs.readFileSync(nluDataFilePath, 'utf8'))
+      nluResultObj.nluDataFilePath = nluDataFilePath
-      const { type: actionType } = actions[actionName]
-
-      nluResultObj.actionType = actionType
 
       try {
         nluResultObj.entities = await this.ner.extractEntities(

server/src/intent-object.sample.json

@@ -1,7 +1,7 @@
 {
   "lang": "en",
-  "domain": "checker",
+  "domain": "utilities",
-  "skill": "isitdown",
+  "skill": "is_it_down",
   "action": "run",
   "utterance": "Check if github.com, mozilla.org and twitter.com are up",
   "entities": [

skills/games/guess_the_number/src/actions/pick_up.py

@@ -0,0 +1,9 @@
+#!/usr/bin/env python
+# -*- coding:utf-8 -*-
+
+import utils
+
+def pick_up(string, entities):
+	"""This is a test"""
+
+	return utils.output('end', 'ready', utils.translate('ready'))

skills/games/guess_the_number/src/actions/run.py

@@ -1,10 +0,0 @@
-#!/usr/bin/env python
-# -*- coding:utf-8 -*-
-
-import utils
-from random import randint
-
-def run(string, entities):
-	"""TODO..."""
-
-	return utils.output('end', 'ready', utils.translate('ready')