GENE.ai 🚀

Advanced AI assistant powered by Groq's lightning-fast LLMs with multi-domain knowledge and conversation analytics.

Features

• Multiple AI personas (Expert, Creative, Technical)
• 7 specialized knowledge domains
• Real-time conversation analytics
• Docker/Kubernetes ready
• CI/CD pipeline
• Responsive UI with dark/light mode

Repo Structure

nexusai-assistant/ ├── .github/ │ ├── workflows/ │ │ └── ci-cd.yml ├── app/ │ ├── core/ │ │ ├── init.py │ │ ├── chat.py │ │ ├── memory.py │ │ └── utils.py │ ├── ui/ │ │ ├── init.py │ │ ├── components.py │ │ └── layouts.py │ ├── init.py │ └── main.py ├── configs/ │ ├── init.py │ ├── default.yaml │ └── production.yaml ├── tests/ │ ├── init.py │ ├── test_chat.py │ └── test_ui.py ├── docker/ │ ├── nginx.conf │ └── Dockerfile.prod ├── docs/ │ ├── architecture.md │ └── setup.md ├── scripts/ │ ├── setup.sh │ └── deploy.sh ├── .env.example ├── .gitignore ├── .dockerignore ├── Dockerfile ├── docker-compose.yml ├── requirements.txt ├── pyproject.toml ├── README.md └── LICENSE

Quick Start

# Clone repo
git clone https://github.com/wahidpanda/Conversational-Chatbot-with-GROQ-with-Multi-Domain-Expertise-
cd GENE.ai

Setup environment

cp .env.example .env

Add your GROQ_API_KEY in .env

Run with Docker

docker-compose up -d

Access at: http://localhost:8501

Deployment Options Deploy on Railway Deploy on Render

Documentation Full documentation available in docs/ folder:

Architecture

API Reference

Development Guide

.github/workflows/ci-cd.yml:

name: CI/CD Pipeline

on:
  push:
    branches: [ main ]
  pull_request:
    branches: [ main ]

jobs:
  test:
    runs-on: ubuntu-latest
    steps:
    - uses: actions/checkout@v4
    - name: Set up Python
      uses: actions/setup-python@v4
      with:
        python-version: '3.9'
    - name: Install dependencies
      run: |
        python -m pip install --upgrade pip
        pip install -r requirements.txt
        pip install pytest pytest-cov
    - name: Run tests
      run: |
        pytest --cov=app --cov-report=xml
    - name: Upload coverage
      uses: codecov/codecov-action@v3

  deploy:
    needs: test
    runs-on: ubuntu-latest
    if: github.ref == 'refs/heads/main'
    steps:
    - uses: actions/checkout@v4
    - name: Build Docker image
      run: docker build -t nexusai-assistant .
    - name: Log in to Docker Hub
      uses: docker/login-action@v2
      with:
        username: ${{ secrets.DOCKER_HUB_USERNAME }}
        password: ${{ secrets.DOCKER_HUB_TOKEN }}
    - name: Push to Docker Hub
      run: |
        docker tag nexusai-assistant ${{ secrets.DOCKER_HUB_USERNAME }}/nexusai-assistant:latest
        docker push ${{ secrets.DOCKER_HUB_USERNAME }}/nexusai-assistant:latest

pyproject.toml (Modern Python config):

[project]
name = "nexusai-assistant"
version = "0.1.0"
description = "Advanced AI assistant powered by Groq"
authors = [
    {name = "Your Name", email = "your@email.com"}
]
readme = "README.md"
requires-python = ">=3.9"
license = {text = "MIT"}

[project.urls]
Homepage = "https://github.com/yourusername/nexusai-assistant"
Documentation = "https://github.com/yourusername/nexusai-assistant/docs"

[tool.setuptools.packages.find]
where = ["app"]

[tool.pytest.ini_options]
python_files = "test_*.py"
testpaths = ["tests"]

3. Initialize Git Repository bash

Initialize git

git init

Create main branch

git checkout -b main

Add files

git add .

Initial commit

git commit -m "Initial commit: NexusAI Assistant"

Create GitHub repo and push

gh repo create nexusai-assistant --public --source=. --remote=origin git push -u origin main 4. Recommended GitHub Repository Settings Branch Protection Rules:

• Require pull request reviews
• Require status checks to pass
• Require linear history

Secrets:

-DOCKER_HUB_USERNAME -DOCKER_HUB_TOKEN -GROQ_API_KEY (for CI tests)

Features:

• Enable Discussions
• Set up Project board
• Configure CODEOWNERS

Labels:

• enhancement
• bug
• documentation
• question

5. Documentation Files docs/architecture.md:

markdown

System Architecture

graph TD
    A[UI Layer] --> B[Business Logic]
    B --> C[Memory Management]
    B --> D[LLM Integration]
    C --> E[Conversation History]
    D --> F[Groq API]

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Components

UI Layer:

• Streamlit-based interface
• Responsive layouts
• Dark/light mode support

Business Logic:

• Conversation management
• Domain-specific processing
• Analytics generation

Memory:

• Short-term conversation memory
• Knowledge base persistence

docs/setup.md:

Development Setup

Local Development

python -m venv .venv
source .venv/bin/activate  # Linux/Mac
.\.venv\Scripts\activate   # Windows

pip install -e .
Environment Variables
Create .env file:

ini
GROQ_API_KEY=your_key_here
STREAMLIT_SERVER_PORT=8501

This complete GitHub repository setup includes:

• Proper Python project structure
• CI/CD pipeline
• Comprehensive documentation
• Modern packaging configuration
• Docker/Kubernetes support
• Testing infrastructure
• Issue templates (can be added in .github/ISSUE_TEMPLATE/)
• All necessary configuration files