RASA Chatbot (VolgAI, Personal FAQs)


project-image

An AI powered Information Retrieval chatbot developed using the RASA stack.(Python, JavaScript, JQuery, HTML/CSS, YAML, Docker, docker-compose, supervisord, Nginx, RabbitMQ, Redis, PostgreSQL etc.)

Tasks/Achievements:

Overall Result:

  • Chatbot Development from scratch with RASA Stack(NLP).
  • Model Optimization, pipeline configurations, rasa-x integration.
  • STT intgration with rasa chatbot.
  • chatbot frontend development.
  • Docker/docker-compose deployment, supervisord, nginx, postgres, rabbitmq, etc. for deployment.

Designing and concepts:

  • Define chatbot personality
  • User intent, Chatbot action (interaction) design
  • User testing with GUI
  • Concepts of RASA core, RASA NLU, Domain, Stories, NLU Data, etc.

Building and working:

  • Understanding of user input, NLP
  • Natural Language Understanding(NLU)
  • Different approaches for the response that the chatbot will generate
  • Intent and Entity extraction, slots using, LSTM-RNN, GRU cell
  • Contextual dialogue handling with deep learning







Project details...


Links to personal FAQ chatbot:
personal_bot: https://sbmagar.github.io ....
Enterprise level chatbot on VolgAI website(https://volgai.com)

Bot is developed using Python RASA-Stack(Docker, docker-compose, supervisord, Nginx, RabbitMQ, Redis, PostgreSQL etc.)
Project screenshot

For demo project: https://sbmagar.github.io (Due to server limit, might not work at the time)

Please do visit, https://volgai.com for official chatbot.