Coder Social home page Coder Social logo

brijeshlakkad / smart-banking-chatbot Goto Github PK

View Code? Open in Web Editor NEW
5.0 1.0 1.0 152.18 MB

Smart Banking Chat Bot- AI based project uses several ML algorithms for Natural Language Understanding to identify intent and entities from user issues (text representation) and generates dialogue using Deep Learning.

PHP 48.23% Python 37.67% CSS 4.93% JavaScript 0.44% Hack 8.73%
python angularjs html css php jquery mysql nlp-machine-learning machine-learning artificial-intelligence

smart-banking-chatbot's Introduction

Minor-Project

Smart Banking Chat Bot- This is an AI based project which uses several ML algorithms for Natural Language Understanding which identifies intent and entities from user issues and generates dialogue.

This project can help Banks to add chatbot in their web-application, so that customer can ask question to chatbot to Banks without visiting to Bank.

Requirements

  • Python (v3.6.3) and Libraries required for AI and Natural Language Processing(NLP)
  • Rasa Core (v0.11.12)
  • Rasa NLU (v0.13.7)
  • Bootstrap (v3.3.7)
  • AngularJS (v1.6.4)
  • jQuery (v1.10.2)
  • SQL Server 2014
  • PHP (v5.6.32)

To install database with data, we have added sql file in repostory. To train model,

  1. go to train directory - cd train
  2. run command to train nlu which actually understands natural langauge examples given in training_data.json which have classfied - python Bank-bot.py train-nlu
  3. run command to train core which predicts actions using training data given in stories.md file - python Bank-bot.py train-nlu
  4. to train model online, run (using this we can have more data of predicting action which makes model more accurate :) ) - $ python -m rasa_core_sdk.endpoint --actions actions & python -m rasa_core.train --online -o models/dialogue -u models/nlu/default/bank_nlu -d bank_domain.yml -s data/stories.md --endpoints endpoints.yml --batch_size 500 --epochs 200 --history 15 --validation_split 0.2 --nlu_threshold 0.2 --core_threshold 0.2 --fallback_action_name action_fallback
  5. And to finally run bot, use - $ python -m rasa_core.run --enable_api -d models/dialogue -u models/nlu/default/bank_nlu --endpoints endpoints.yml - $ python -m rasa_core_sdk.endpoint --actions actions - which have to run both in different terminals

smart-banking-chatbot's People

Contributors

brijeshlakkad avatar

Stargazers

 avatar  avatar  avatar  avatar

Watchers

 avatar

smart-banking-chatbot's Issues

Could not find rasa_core: No module named converters

Operating System:
MacOS High Sierra -version 10.13.6
rasa_core
version - rasa-core-0.10.4
rasa_nlu
version - rasa-nlu-0.13.1

Traceback (most recent call last):
  File "nlu_model.py", line 12, in <module>
    from rasa_nlu.converters import load_data
ImportError: No module named converters

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.