update to latest watson sdk (#45)

* update to latest watson sdk

* make linting happy

* use predefined service name for key

* drop authenticator call

* Update .travis.yml

Author: stevemar

.travis.yml

@@ -1,6 +1,5 @@
 language: python
 python:
-  - "2.7"
   - "3.6"
 install:
   - "pip install -r requirements.txt"

README.md

@@ -131,7 +131,7 @@ Follow the steps below for deploying the application:
 
 * Once viewing the application, click the `Runtime` option on the menu and navigate to the `Environment Variables` section.
 
-* Update the `CLASSIFIER_ID`, and `NATURAL_LANGUAGE_CLASSIFIER_IAM_APIKEY` variables with your `Model ID` from [Step 4](#4-train-the-nlc-model)  and NLC API key from [Step 2](#2-create-ibm-cloud-services). Click `Save`.
+* Update the `CLASSIFIER_ID`, and `NATURAL_LANGUAGE_CLASSIFIER_APIKEY` variables with your `Model ID` from [Step 4](#4-train-the-nlc-model)  and NLC API key from [Step 2](#2-create-ibm-cloud-services). Click `Save`.
 
   ![env vars](doc/source/images/nlc-envvars.png)
 
@@ -172,10 +172,8 @@ The general recommendation for Python development is to use a virtual environmen
   # Comment out the unset environment variables
   # Rename this file to .env before running app.py.
 
-  # NATURAL_LANGUAGE_CLASSIFIER_USERNAME=<add_NLC_username>
-  # NATURAL_LANGUAGE_CLASSIFIER_PASSWORD=<add_NLC_password>
-
-  NATURAL_LANGUAGE_CLASSIFIER_IAM_APIKEY=<add_NLC_iam_apikey>
+  CLASSIFIER_ID=<add_nlc_classifier_id>
+  NATURAL_LANGUAGE_CLASSIFIER_APIKEY=<add_nlc_apikey>
   ```
 
 * Install the app dependencies by running:

app.py

@@ -16,37 +16,24 @@
 
 from dotenv import load_dotenv
 from flask import Flask, render_template, request
+
 from ibm_watson import NaturalLanguageClassifierV1
 
 DEBUG = True
 app = Flask(__name__)
 
 load_dotenv(os.path.join(os.path.dirname(__file__), ".env"))
-
-nlc_username = os.environ.get("NATURAL_LANGUAGE_CLASSIFIER_USERNAME")
-nlc_password = os.environ.get("NATURAL_LANGUAGE_CLASSIFIER_PASSWORD")
-nlc_iam_apikey = os.environ.get("NATURAL_LANGUAGE_CLASSIFIER_IAM_APIKEY")
 classifier_id = os.environ.get("CLASSIFIER_ID")
 
-# Use provided credentials from environment or pull from IBM Cloud VCAP
-if nlc_iam_apikey != "placeholder":
-    NLC_SERVICE = NaturalLanguageClassifierV1(
-      iam_apikey=nlc_iam_apikey
-    )
-elif nlc_username != "placeholder":
-    NLC_SERVICE = NaturalLanguageClassifierV1(
-      username=nlc_username,
-      password=nlc_password
-    )
-else:
-    NLC_SERVICE = NaturalLanguageClassifierV1()
+NLC_SERVICE = NaturalLanguageClassifierV1()
 
 
 @app.route('/')
 def default():
     classifier_info = "cannot detect classifier"
     if NLC_SERVICE:
-        classifier_info = "classifier detected, using API: " + NLC_SERVICE.url
+        classifier_info = ("classifier detected, using API: " +
+                           NLC_SERVICE.service_url)
     return render_template(
         'index.html',
         classifier_info=classifier_info,
@@ -58,12 +45,21 @@ def default():
 @app.route('/classifyhandler', methods=['GET', 'POST'])
 def classify_text():
     inputtext = request.form['classifierinput']
-    classifier_info = NLC_SERVICE.get_classifier(classifier_id)
-    classifier_output = NLC_SERVICE.classify(classifier_id,
-                                             inputtext).get_result()
-    icd_code, icd_output = _get_ICD_code_info(classifier_output)
-    classifier_output = json.dumps(classifier_output, indent=4)
-    icd_output = json.dumps(icd_output, indent=4)
+
+    try:
+        classifier_info = NLC_SERVICE.get_classifier(classifier_id)
+        classifier_output = NLC_SERVICE.classify(classifier_id,
+                                                 inputtext).get_result()
+        icd_code, icd_output = _get_ICD_code_info(classifier_output)
+        classifier_output = json.dumps(classifier_output, indent=4)
+        icd_output = json.dumps(icd_output, indent=4)
+    except Exception:
+        classifier_info = ("error from classifier service, "
+                           "check if credentials are set")
+        classifier_output = ""
+        icd_code = ""
+        icd_output = ""
+
     return render_template(
         'index.html',
         classifier_info=classifier_info,

doc/source/images/nlc-envvars.png

@@ -2,8 +2,5 @@
 # Comment out the unset environment variables
 # Rename this file to .env before running app.py.
 
-CLASSIFIER_ID=<add_NLC_classifier_id>
-NATURAL_LANGUAGE_CLASSIFIER_USERNAME=<add_NLC_username>
-NATURAL_LANGUAGE_CLASSIFIER_PASSWORD=<add_NLC_password>
-
-NATURAL_LANGUAGE_CLASSIFIER_IAM_APIKEY=<add_NLC_iam_apikey>
+CLASSIFIER_ID=<add_nlc_classifier_id>
+NATURAL_LANGUAGE_CLASSIFIER_APIKEY=<add_nlc_apikey>

env.example

@@ -8,6 +8,4 @@ applications:
   buildpack: python_buildpack
   env:
     CLASSIFIER_ID: placeholder
-    NATURAL_LANGUAGE_CLASSIFIER_USERNAME: placeholder
-    NATURAL_LANGUAGE_CLASSIFIER_PASSWORD: placeholder
-    NATURAL_LANGUAGE_CLASSIFIER_IAM_APIKEY: placeholder
+    NATURAL_LANGUAGE_CLASSIFIER_APIKEY: placeholder

manifest.yml

@@ -1,3 +1,3 @@
-python-dotenv
-Flask
-ibm-watson
+Flask==1.1.1
+ibm-watson==4.2.1
+python-dotenv==0.10.5