• Stars
    star
    250
  • Rank 156,530 (Top 4 %)
  • Language
    JavaScript
  • License
    Apache License 2.0
  • Created almost 7 years ago
  • Updated over 1 year ago

Reviews

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

Repository Details

A chatbot for banking that uses the Watson Assistant, Discovery, Natural Language Understanding and Tone Analyzer services.

WARNING: This repository is no longer maintained ⚠️

This repository will not be updated. The repository will be kept available in read-only mode.

Create a banking chatbot with FAQ discovery, anger detection and natural language understanding

In this code pattern, we will create a chatbot using Node.js and Watson Assistant. The Assistant flow will detect customer emotions and be enhanced by using Natural Language Understanding to identify location entities. For FAQs, a call to the Discovery service will use passage retrieval to pull answers from a collection of documents.

When the reader has completed this pattern, they will understand how to:

  • Create a chatbot that converses via a web UI using Watson Assistant and Node.js
  • Use Watson Discovery with passage retrieval to find answers in FAQ documents
  • Identify location entities with Watson Natural Language Understanding

NOTE: This code pattern has been updated to include instructions for accessing Watson services running on IBM Cloud Pak for Data. These updates can be found in the specific instructions for deploying your app locally, or deploying your app to OpenShift on IBM Cloud. The main change required is that your application will need additional credentials to access the IBM Cloud Pak for Data cluster that is hosting the Watson services.

Click here for more information about IBM Cloud Pak for Data.

architecture

Flow

  1. The FAQ documents are added to the Discovery collection.
  2. The user interacts with a chatbot via the app UI.
  3. User input is processed with Natural Language Understanding (NLU). The context is enriched with NLU-detected entities and keywords (e.g., a location).
  4. The input and enriched context is sent to Assistant. Assistant recognizes intent, entities and dialog paths. It responds with a reply and/or action.
  5. Optionally, a requested action is performed by the app. This may include one of the following:
    • Lookup additional information from bank services to append to the reply
    • Use Discovery to reply with an answer from the FAQ documents

Included components

  • IBM Watson Assistant: Build, test and deploy a bot or virtual agent across mobile devices, messaging platforms, or even on a physical robot.
  • IBM Watson Discovery: A cognitive search and content analytics engine for applications to identify patterns, trends, and actionable insights.
  • IBM Watson Natural Language Understanding: Analyze text to extract meta-data from content such as concepts, entities, keywords, categories, sentiment, emotion, relations, semantic roles, using natural language understanding.
  • Node.js: An asynchronous event driven JavaScript runtime, designed to build scalable applications.

Steps

  1. Clone the repo
  2. Create Watson services
  3. Customize the Watson Assistant skill
  4. Load Discovery documents
  5. Deploy the application
  6. Use the web app

1. Clone the repo

Clone the watson-banking-chatbot locally. In a terminal, run:

git clone https://github.com/IBM/watson-banking-chatbot

2. Create Watson services

Provision the following services:

  • Watson Assistant
  • Watson Discovery
  • Watson Natural Language Understanding

NOTE: If you will be using the Deploy to Cloud Foundry on IBM Cloud deployment option, then you can skip these next steps and jump right to the Deploy the Application section. That deployment option automatically creates the services and links them to your application.

The instructions will depend on whether you are provisioning services using IBM Cloud Pak for Data or on IBM Cloud.

Click to expand one:

IBM Cloud Pak for Data

Use the following instructions for each of the three services.

Install and provision service instances

The services are not available by default. An administrator must install them on the IBM Cloud Pak for Data platform, and you must be given access to the service. To determine whether the service is installed, Click the Services icon (services_icon) and check whether the service is enabled.

IBM Cloud

Create the service instances
  • If you do not have an IBM Cloud account, register for a free trial account here.
  • Click here to create a Watson Assistant instance.
  • Click here to create a Discovery instance.
  • Click here to create a Natural Language Understanding instance.

3. Customize the Watson Assistant skill

The following instructions will depend on if you are provisioning Assistant from IBM Cloud or from an IBM Cloud Pak for Data cluster. Choose one:

Provision on IBM Cloud Pak for Data

  • Find the Assistant service in your list of Provisioned Instances in your IBM Cloud Pak for Data Dashboard.
  • Click on View Details from the options menu associated with your Assistant service.
  • Click on Open Watson Assistant.
  • Go to the Skills tab.
  • Click Create skill
  • Select the Dialog skill option and then click Next.
  • Click the Import skill tab.
  • Click Choose JSON file, go to your cloned repo dir, and Open the JSON file in data/conversation/workspaces/banking_US.json (or use the old full version in full_banking.json). banking_IN.json is used for content for banking in India and banking_US.json is used for content for banking in United States.
  • Select Everything and click Import.

Provision on IBM Cloud

  • Find the Assistant service in your IBM Cloud Dashboard.
  • Click on the service and then click on Launch tool.
  • Go to the Skills tab.
  • Click Create skill.
  • Select the Dialog skill option and then click Next.
  • Click the Import skill tab.
  • Click Choose JSON file, go to your cloned repo dir, and Open the JSON file in data/conversation/workspaces/banking_US.json (or use the old full version in full_banking.json). banking_IN.json is used for content for banking in India and banking_US.json is used for content for banking in United States.
  • Select Everything and click Import.

To find the Skill ID for Watson Assistant:

  • Go back to the Skills tab.

  • Click on the three dots in the upper right-hand corner of a card and select View API Details.

  • Copy the Skill ID GUID. Use this value when setting up your run-time environment.

  • By default the application will import and use the skill named watson-banking-chatbot, but you can configure it to use another skill by setting the run-time environment variable SKILL_ID.

    view_api_details

To view the Assistant dialog, click on the skill and choose the Dialog tab. Here's a snippet of the dialog:

dialog

4. Load Discovery documents

By default, the application will create a collection named watson-banking-chatbot, but you can configure it to use another collection by setting the run-time environment variables DISCOVERY_COLLECTION_ID and DISCOVERY_ENVIRONMENT_ID.

The following instructions will depend on if you are provisioning Discovery from IBM Cloud or from an IBM Cloud Pak for Data cluster. Choose one:

Provision on IBM Cloud Pak for Data

  • Find the Discovery service in your list of Provisioned Instances in your IBM Cloud Pak for Data Dashboard.
  • Click on View Details from the options menu associated with your Discovery service.
  • Click on Open Watson Discovery.
  • Click on an existing Discovery Project, or create a new one.
  • From your Project panel, click the Collections tab.
  • Click on New Collection +.
  • Select the Upload data option and click Next.
  • Provide a collection name.
  • Select English language.
  • Click Finish to create the collection.
  • Use Drag and drop your documents here or select documents to seed the content with the five documents in data/discovery/docs of your cloned repo.
  • Click on the Integrate and deploy option from the left-side menu of the Discovery panel. Then select the View API Details tab to view the Project Id. Use this as the Collection ID value when setting up your run-time environment.

NOTE: The Environment Id for Cloud Pak for Data collections is always set to default.

disco_cpd_projectid

Provision on IBM Cloud

  • Find the Discovery service in your IBM Cloud Dashboard.

  • Click on the service and then click on Launch tool.

  • Create a new data collection by hitting the Upload your own data button.

    new_collection

    • Provide a collection name
    • Select English language
    • Click Create
  • Use Drag and drop your documents here or select documents to seed the content with the five documents in data/discovery/docs of your cloned repo.

  • Click on the upper-right api icon and save the Environment ID and Collection ID as they will be required when setting up your run-time environment.

    disco_guids

5. Deploy the application

Click on one of the options below for instructions on deploying the Node.js server.

local openshift public

6. Use the web app

The web app presents a customer service chatbot. Interact with the chatbot by pressing the buttons when prompted or use the Type something box. The chatbot is powered by Watson Assistant with additional information coming from Discovery and Natural Language Understanding.

demo

Troubleshooting

  • Error: Unable to list workspaces for Watson Assistant: Forbidden: Access is denied due to invalid credentials.

    This error occurs with Deploy to IBM Cloud button. Configure a runtime environment variable for ASSISTANT_APIKEY to allow automatic configuration of the default skill or configure SKILL_ID to use another skill.

  • Fail: An operation for service instance wbc-discovery-service is in progress.

    This error occurs when starting the app before the service is ready. It is currently common behavior with the Deploy to IBM Cloud button. In this case, click the Run button to restart the application. It will succeed when the service is ready.

  • Error: Environment {GUID} is still not active, retry once status is active

    This is common during the first run. The app tries to start before the Discovery environment is fully created. Wait a few minutes and click the Run button to restart the application.

  • Error: Only one free environment is allowed per organization

    To work with a free trial, a small free Discovery environment is created. If you already have a Discovery environment, this will fail. If you are not using Discovery, check for an old service thay you may want to delete. Otherwise use the .env DISCOVERY_ENVIRONMENT_ID to tell the app which environment you want it to use. A collection will be created in this environment using the default configuration.

License

This code pattern is licensed under the Apache License, Version 2. Separate third-party code objects invoked within this code pattern are licensed by their respective providers pursuant to their own separate licenses. Contributions are subject to the Developer Certificate of Origin, Version 1.1 and the Apache License, Version 2.

Apache License FAQ

More Repositories

1

sarama

Sarama is a Go library for Apache Kafka.
Go
10,858
star
2

plex

The package of IBM’s typeface, IBM Plex.
CSS
9,297
star
3

css-gridish

Automatically build your grid design’s CSS Grid code, CSS Flexbox fallback code, Sketch artboards, and Chrome extension.
CSS
2,253
star
4

openapi-to-graphql

Translate APIs described by OpenAPI Specifications (OAS) into GraphQL
TypeScript
1,594
star
5

Project_CodeNet

This repository is to support contributions for tools for the Project CodeNet dataset hosted in DAX
Python
1,485
star
6

fp-go

functional programming library for golang
Go
1,480
star
7

pytorch-seq2seq

An open source framework for seq2seq models in PyTorch.
Python
1,431
star
8

fhe-toolkit-linux

IBM Fully Homomorphic Encryption Toolkit For Linux. This toolkit is a Linux based Docker container that demonstrates computing on encrypted data without decrypting it! The toolkit ships with two demos including a fully encrypted Machine Learning inference with a Neural Network and a Privacy-Preserving key-value search.
C++
1,427
star
9

ibm.github.io

IBM Open Source at GitHub
JavaScript
1,106
star
10

MicroscoPy

An open-source, motorized, and modular microscope built using LEGO bricks, Arduino, Raspberry Pi and 3D printing.
Python
1,102
star
11

Dromedary

Dromedary: towards helpful, ethical and reliable LLMs.
Python
1,059
star
12

MAX-Image-Resolution-Enhancer

Upscale an image by a factor of 4, while generating photo-realistic details.
Python
863
star
13

elasticsearch-spark-recommender

Use Jupyter Notebooks to demonstrate how to build a Recommender with Apache Spark & Elasticsearch
Jupyter Notebook
806
star
14

differential-privacy-library

Diffprivlib: The IBM Differential Privacy Library
Python
774
star
15

build-blockchain-insurance-app

Sample insurance application using Hyperledger Fabric
JavaScript
719
star
16

FfDL

Fabric for Deep Learning (FfDL, pronounced fiddle) is a Deep Learning Platform offering TensorFlow, Caffe, PyTorch etc. as a Service on Kubernetes
Go
676
star
17

spring-boot-microservices-on-kubernetes

In this code we demonstrate how a simple Spring Boot application can be deployed on top of Kubernetes. This application, Office Space, mimicks the fictitious app idea from Michael Bolton in the movie "Office Space".
JavaScript
548
star
18

cloud-native-starter

Cloud Native Starter for Java/Jakarta EE based Microservices on Kubernetes and Istio
Shell
517
star
19

federated-learning-lib

A library for federated learning (a distributed machine learning process) in an enterprise environment.
Python
480
star
20

nicedoc.io

pretty README as service.
JavaScript
473
star
21

clai

Command Line Artificial Intelligence or CLAI is an open-sourced project from IBM Research aimed to bring the power of AI to the command line interface.
Python
466
star
22

import-tracker

Python utility for tracking third party dependencies within a library
Python
458
star
23

mac-ibm-enrollment-app

The Mac@IBM enrollment app makes setting up macOS with Jamf Pro more intuitive for users and easier for IT. The application offers IT admins the ability to gather additional information about their users during setup, allows users to customize their enrollment by selecting apps or bundles of apps to install during setup, and provides users with next steps when enrollment is complete.
Swift
454
star
24

mobx-react-router

Keep your MobX state in sync with react-router
JavaScript
437
star
25

openapi-validator

Configurable and extensible validator/linter for OpenAPI documents
JavaScript
429
star
26

EvolveGCN

Code for EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs
Python
384
star
27

fhe-toolkit-macos

IBM Homomorphic Encryption Toolkit For MacOS
C++
356
star
28

AutoMLPipeline.jl

A package that makes it trivial to create and evaluate machine learning pipeline architectures.
HTML
345
star
29

graphql-query-generator

Randomly generates GraphQL queries from a GraphQL schema
TypeScript
334
star
30

portieris

A Kubernetes Admission Controller for verifying image trust.
Go
329
star
31

BluePic

WARNING: This repository is no longer maintained ⚠️ This repository will not be updated. The repository will be kept available in read-only mode.
Swift
325
star
32

FedMA

Code for Federated Learning with Matched Averaging, ICLR 2020.
Python
320
star
33

lale

Library for Semi-Automated Data Science
Python
320
star
34

powerai-counting-cars

Run a Jupyter Notebook to detect, track, and count cars in a video using Maximo Visual Insights (formerly PowerAI Vision) and OpenCV
Jupyter Notebook
317
star
35

evote

A voting application that leverages Hyperledger Fabric and the IBM Blockchain Platform to record and tally ballots.
JavaScript
316
star
36

aihwkit

IBM Analog Hardware Acceleration Kit
Jupyter Notebook
314
star
37

zshot

Zero and Few shot named entity & relationships recognition
Python
308
star
38

blockchain-network-on-kubernetes

Demonstrates the steps involved in setting up your business network on Hyperledger Fabric using Kubernetes APIs on IBM Cloud Kubernetes Service.
Shell
305
star
39

IBM-Z-zOS

The helpful and handy location for finding and sharing z/OS files, which are not included in the product.
REXX
296
star
40

charts

The IBM/charts repository provides helm charts for IBM and Third Party middleware.
Smarty
295
star
41

TabFormer

Code & Data for "Tabular Transformers for Modeling Multivariate Time Series" (ICASSP, 2021)
Python
295
star
42

blockchain-application-using-fabric-java-sdk

Create and Deploy a Blockchain Network using Hyperledger Fabric SDK Java
Java
292
star
43

mac-ibm-notifications

macOS agent used to display custom notifications and alerts to the end user.
Swift
289
star
44

MAX-Object-Detector

Localize and identify multiple objects in a single image.
Python
286
star
45

design-kit

The IBM Design kit is a collection of tools aimed to help you design and prototype experiences faster, with confidence and thoughtfulness. This kit is based on the IBM Design System. Also, you may use this documentation to create add-on libraries to the IBM Design System or submit bugs to the current system.
272
star
46

AccDNN

A compiler from AI model to RTL (Verilog) accelerator in FPGA hardware with auto design space exploration.
Verilog
270
star
47

deploy-ibm-cloud-private

Instructions and Code required to install IBM Cloud Private
HCL
263
star
48

vue-a11y-calendar

Accessible, internationalized Vue calendar
JavaScript
253
star
49

audit-ci

Audit NPM, Yarn, and PNPM dependencies in continuous integration environments, preventing integration if vulnerabilities are found at or above a configurable threshold while ignoring allowlisted advisories
TypeScript
253
star
50

UQ360

Uncertainty Quantification 360 (UQ360) is an extensible open-source toolkit that can help you estimate, communicate and use uncertainty in machine learning model predictions.
Python
249
star
51

Kubernetes-container-service-GitLab-sample

This code shows how a common multi-component GitLab can be deployed on Kubernetes cluster. Each component (NGINX, Ruby on Rails, Redis, PostgreSQL, and more) runs in a separate container or group of containers.
Shell
243
star
52

tensorflow-hangul-recognition

Handwritten Korean Character Recognition with TensorFlow and Android
Python
232
star
53

transition-amr-parser

SoTA Abstract Meaning Representation (AMR) parsing with word-node alignments in Pytorch. Includes checkpoints and other tools such as statistical significance Smatch.
Python
229
star
54

BlockchainNetwork-CompositeJourney

Part 1 in a series of patterns showing the building blocks of a Blockchain application
Shell
227
star
55

pytorchpipe

PyTorchPipe (PTP) is a component-oriented framework for rapid prototyping and training of computational pipelines combining vision and language
Python
223
star
56

Graph2Seq

Graph2Seq is a simple code for building a graph-encoder and sequence-decoder for NLP and other AI/ML/DL tasks.
Python
219
star
57

LNN

A `Neural = Symbolic` framework for sound and complete weighted real-value logic
Python
214
star
58

Scalable-WordPress-deployment-on-Kubernetes

This code showcases the full power of Kubernetes clusters and shows how can we deploy the world's most popular website framework on top of world's most popular container orchestration platform.
Shell
214
star
59

janusgraph-utils

Develop a graph database app using JanusGraph
Java
204
star
60

ModuleFormer

ModuleFormer is a MoE-based architecture that includes two different types of experts: stick-breaking attention heads and feedforward experts. We released a collection of ModuleFormer-based Language Models (MoLM) ranging in scale from 4 billion to 8 billion parameters.
Python
203
star
61

ibm-generative-ai

IBM-Generative-AI is a Python library built on IBM's large language model REST interface to seamlessly integrate and extend this service in Python programs.
Python
202
star
62

tensorflow-large-model-support

Large Model Support in Tensorflow
199
star
63

Scalable-Cassandra-deployment-on-Kubernetes

In this code we provide a full roadmap the deployment of a multi-node scalable Cassandra cluster on Kubernetes. Cassandra understands that it is running within a cluster manager, and uses this cluster management infrastructure to help implement the application. Kubernetes concepts like Replication Controller, StatefulSets etc. are leveraged to deploy either non-persistent or persistent Cassandra clusters on Kubernetes cluster.
Shell
195
star
64

adaptive-federated-learning

Code for paper "Adaptive Federated Learning in Resource Constrained Edge Computing Systems"
Python
193
star
65

action-recognition-pytorch

This is the pytorch implementation of some representative action recognition approaches including I3D, S3D, TSN and TAM.
Python
193
star
66

gantt-chart

IBM Gantt Chart Component, integrable in Vanilla, jQuery, or React Framework.
JavaScript
193
star
67

api-samples

Samples code that uses QRadar API's
Python
192
star
68

cdfsl-benchmark

(ECCV 2020) Cross-Domain Few-Shot Learning Benchmarking System
Python
190
star
69

kube101

Kubernetes 101 workshop (https://ibm.github.io/kube101/)
Shell
184
star
70

CrossViT

Official implementation of CrossViT. https://arxiv.org/abs/2103.14899
Python
180
star
71

browser-functions

A lightweight serverless platform that uses Web Browsers as execution engines
JavaScript
180
star
72

pwa-lit-template

A template for building Progressive Web Applications using Lit and Vaadin Router.
TypeScript
176
star
73

rl-testbed-for-energyplus

Reinforcement Learning Testbed for Power Consumption Optimization using EnergyPlus
Python
170
star
74

AMLSim

The AMLSim project is intended to provide a multi-agent based simulator that generates synthetic banking transaction data together with a set of known money laundering patterns - mainly for the purpose of testing machine learning models and graph algorithms. We welcome you to enhance this effort since the data set related to money laundering is critical to advance detection capabilities of money laundering activities.
Python
170
star
75

socket-io

A Socket.IO client for C#
C#
169
star
76

tfjs-web-app

A TensorFlow.js Progressive Web App for Offline Visual Recognition
JavaScript
164
star
77

molformer

Repository for MolFormer
Jupyter Notebook
163
star
78

spark-tpc-ds-performance-test

Use the TPC-DS benchmark to test Spark SQL performance
TSQL
160
star
79

watson-online-store

Learn how to use Watson Assistant and Watson Discovery. This application demonstrates a simple abstraction of a chatbot interacting with a Cloudant NoSQL database, using a Slack UI.
HTML
156
star
80

istio101

Istio 101 workshop (https://ibm.github.io/istio101/)
Shell
154
star
81

Medical-Blockchain

A healthcare data management platform built on blockchain that stores medical data off-chain
Vue
150
star
82

watson-assistant-slots-intro

A Chatbot for ordering a pizza that demonstrates how using the IBM Watson Assistant Slots feature, one can fill out an order, form, or profile.
JavaScript
143
star
83

tsfm

Foundation Models for Time Series
Jupyter Notebook
143
star
84

simulai

A toolkit with data-driven pipelines for physics-informed machine learning.
Python
142
star
85

etcd-java

Alternative etcd3 java client
Java
141
star
86

deploy-react-kubernetes

Built for developers who are interested in learning how to deploy a React application on Kubernetes, this pattern uses the React and Redux framework and calls the OMDb API to look up movie information based on user input. This pattern can be built and run on both Docker and Kubernetes.
JavaScript
139
star
87

innovate-digital-bank

This repository contains instructions to build a digital bank composed of a set of microservices that communicate with each other. Using Nodejs, Express, MongoDB and deployed to a Kubernetes cluster on IBM Cloud.
JavaScript
137
star
88

ipfs-social-proof

IPFS Social Proof: A decentralized identity and social proof system
JavaScript
135
star
89

KubeflowDojo

Repository to hold code, instructions, demos and pointers to presentation assets for Kubeflow Dojo
Jupyter Notebook
132
star
90

probabilistic-federated-neural-matching

Bayesian Nonparametric Federated Learning of Neural Networks
Python
132
star
91

fhe-toolkit-ios

IBM Fully Homomorphic Encryption Toolkit For iOS
C++
131
star
92

pytorch-large-model-support

Large Model Support in PyTorch
130
star
93

taxinomitis

Source code for Machine Learning for Kids site
JavaScript
127
star
94

Decentralized-Energy-Composer

WARNING: This repository is no longer maintained ⚠️ We are no longer showing the Hyperledger Composer Service.
TypeScript
127
star
95

quantum-careers

Learn about career opportunities with IBM Quantum.
126
star
96

cloud-pak

IBM Cloud Paks are enterprise-grade containerized software by combining container images with enterprise capabilities for deployment in production use cases with integrations for management and lifecycle operations. Features such as pre-configured deployments based on product expertise, rolling upgrades, and management of production workloads.
Shell
126
star
97

build-knowledge-base-with-domain-specific-documents

Create a knowledge base using domain specific documents and the mammoth python library
Jupyter Notebook
125
star
98

japan-technology

IBM Related Japanese technical documents - Code Patterns, Learning Path, Tutorials, etc.
Jupyter Notebook
125
star
99

DiffuseKronA

DiffuseKronA: A Parameter Efficient Fine-tuning Method for Personalized Diffusion Models
125
star
100

compliance-trestle

An opinionated tooling platform for managing compliance as code, using continuous integration and NIST's OSCAL standard.
Python
124
star