E2E-AI-Chatbot 🤖

Pipeline

Current:

Next stage:

• FastAPI & Gradio backend
• Dockerize packages
• Add UI ingest upload file
• Add login page
• Add docs
• Nginx for http and https
• K8s
• CI/CD cloud (AWS/Azure)

Installation Requirements

• Minimum CPU 8GiB RAM
• Uncomment line 8 packages = [{include = “**”}] to use all internal packages (Passing Flake8)
• Install packages and download GPT4All model by
  1. Run locally

     chmod u+x ./setup.sh
     bash ./setup.sh
     

• Build MongoDB, Mongo Express, Logstash, Elasticsearch and Kibana

  docker compose -f docker-compose-service.yml up
  poetry run python app.py --host 0.0.0.0 --port 8071
  

  1. Run docker

     docker compose up
     

     User Interface App

     poetry run python app.py --host 0.0.0.0 --port 8071
     

     Run on: http://localhost:8071

1. Chatbot:

2. Ingest PDF:

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Model

1. GPT4ALL: Current best commercially licensable model based on GPT-J and trained by Nomic AI on the latest curated GPT4All dataset.

Database

1. MongoDB Run on: http://localhost:27017

   poetry run python src/ingest_database.py --mongodb-host "mongodb://localhost:27017/" --data-path "static/pdf/"
   

   Mongo Compass (Windows)

   

Mongo Express

Run on: http://localhost:8081

Data Migration

Run on: http://localhost:9600

Search

1. Elasticsearch & Kibana

   poetry run python src/ingest_search.py --mongodb-host "mongodb://localhost:27017/" --es-host "http://localhost:9200/" --index_name "document"
   

   Elasticsearch run on: http://localhost:9200

Kibana run on: http://localhost:5601

Contact

• KhoiVN - @linkedin-khoivn8071 - nguyenkhoi8071@gmail.com
• Project Link: Github-E2E-AI-Chatbot
• Website: khoispace.io.vn

  Impressive

• From Langchain Framework: https://github.com/hwchase17/langchain
• From GPT4All: https://github.com/nomic-ai/gpt4all

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