Final updates for 0.0.2, updating API server functionality and info i…

…n README

README.md

@@ -1,8 +1,8 @@
 # GeniSys NLU Engine
 [![GeniSys NLU Engine](images/GeniSys.png)](https://github.com/GeniSysAI/NLU)
 
-[![CURRENT RELEASE](https://img.shields.io/badge/CURRENT%20RELEASE-0.0.1-blue.svg)](https://github.com/GeniSysAI/NLU/tree/0.0.1)
-[![UPCOMING RELEASE](https://img.shields.io/badge/UPCOMING%20RELEASE-0.0.2-blue.svg)](https://github.com/GeniSysAI/NLU/tree/0.0.2)
+[![CURRENT RELEASE](https://img.shields.io/badge/CURRENT%20RELEASE-0.0.2-blue.svg)](https://github.com/GeniSysAI/NLU/tree/0.0.2)
+[![UPCOMING RELEASE](https://img.shields.io/badge/UPCOMING%20RELEASE-0.0.3-blue.svg)](https://github.com/GeniSysAI/NLU/tree/0.0.3)
 
 # About GeniSys AI
 
@@ -21,7 +21,6 @@ This tutorial will help you setup the NLU Engine required for your GeniSys netwo
 - Installing and setting up required software
 - Creating your intent and entity training data
 - Training your intent and entity classifiers
-- Testing your classifier locally
 - Testing your classifier locally in real time
 - Testing your classifier API via a client
 
@@ -138,7 +137,7 @@ To begin training, make sure you are all set up, navigate to the root of the pro
 
 [![Training Your NLU Engine](images/train-results.jpg)](https://github.com/GeniSysAI/NLU/blob/master/Train.py)
 
-# Communicating with your AI
+# Communicating with your AI Locally
 
 Now you have trained your AI, it is time to test her out! In this tutorial I will base my explanation on the conversation block at the beginning of this tutorial. 
 
@@ -147,6 +146,7 @@ As your AI is now trained, all you need to do (assuming you are in the project r
 ```
  $ python3 run.py INPUT  1 0.5
 ```
+
 What this does is starts up a session using the user ID of 1 and a threshold of 0.5, sometimes if your model is misclassifying it can help to play with this threshold. 
 
 [![Communicating with your AI](images/talk.jpg)](https://github.com/GeniSysAI/NLU/blob/master/run.py)
@@ -211,6 +211,36 @@ Due to a rather good idea I had, ;) basic functionality exists for parsing AIML
 >Haha
 ```
 
+# Communicating with your AI Via The Internet
+
+In version 0.0.2, the functionality was added to enable accessing the NLU via a secure API endpoint. To start your NLU engine in server mode, you can enter the following commands into terminal:
+
+```
+ $ python3 run.py SERVER 0.5
+```
+
+This starts the server up and sets a threshold for classifications of 0.5. 
+
+If you used the provided [NGINX configuration](https://github.com/GeniSysAI/Server/blob/master/etc/nginx/sites-available/default "NGINX configuration") of the [GeniSys Server](https://github.com/GeniSysAI/Server/ "GeniSys Server") guide,
+
+```
+server_name Subdomain.Domain.TLD;
+
+location ~ ^/communicate/ {
+    proxy_pass http://###.###.#.###:5824/$uri$is_args$args;
+}
+```
+
+you will now be able to access your NLU by posting to http://www.YourDomain.com/communicate/infer/USERID, to do this, I provided an an API client programmed in Python which takes your input from console and sends it to the server for processing: [GeniSys API Client](https://github.com/GeniSysAI/NLU/blob/master/client.py "GeniSys API Client").
+
+Navigate to the project root and execute the following command to send a query to your NLU engine, you can use any question or statement, but bear in mind it must be within the boundaries of variations of the training date.
+
+```
+ $ python3 client.py CLASSIFY 1 "Do you know what I am saying?"
+```
+
+In other GeniSys AI tutorials, you will build applications and use the UI to train and manage the engine.
+
 # Stay Tuned!!
 
 There are more features from my original version that are still yet to be implemented plus some other cool features, pluse the combined system of all three GeniSys AI repos.

data/training.json

@@ -302,6 +302,30 @@
                   "contextClear": "",
                   "entities": []
             },
+            {
+                  "intent": "Entiendo",
+                  "text": [
+                        "Do you understand what I am saying",
+                        "Do you understand me",
+                        "Do you know what I am saying",
+                        "Do you get me",
+                        "Comprendo",
+                        "Know what I mean"
+                  ],
+                  "responses": [
+                        "Well I would not be a very clever AI if I did not would I?",
+                        "I read you loud and clear!",
+                        "I do in deed!"
+                  ],
+                  "action":  {
+                        "function": "",
+                        "responses": []
+                  },
+                  "contextIn": "",
+                  "contextOut": "",
+                  "contextClear": "",
+                  "entities": []
+            },
             {
                   "intent": "Gossip",
                   "text": [