Dockerized Chatbot using Kafka:

To run the project make sure you have a docker and docker-compose installed.

You can clone the project and run :

docker-compose up

The project architecture is structured as follow :

• A frontend view connected to the Flask API via Websocket will send the message written by the user in the chat
• Flask API : The Flask API will send via a Kafka-Producer the message received via websocket to the Kafka topic
• Model : Kafka-Consumer will connecty to the Kafka topic and consumes the message. It will make the inference using Dialo-GPT model provided by Huggingface.
• Kafka zookeeper and broker : A dockerized version of zookeeper and a kafka broker instance will run simultaneously when running docker-compose.
• You can access the chatbot app via browser on : localhost:80

Notes :

• You will need to check firewall setting to allow Websocket connections.
• Make sure the port 9092 is available for the kafka broker.
• On the first start the app will take some time to download the pretrained model (~1.7 go), the webapp will be accessible as soon as the model is loaded.