Development Environment Setup

🛠️ Setting Up Your AI Development Environment

Setting up your development environment for AI projects

🐍 Python Environment

Installing Python

# Install Python 3.8+ (recommended: 3.9 or 3.10)
# Download from python.org or use package manager

# macOS with Homebrew
brew install python@3.10

# Ubuntu/Debian
sudo apt update
sudo apt install python3.10 python3.10-pip python3.10-venv

# Windows
# Download from python.org and run installer

Setting Up Virtual Environment

# Create virtual environment
python -m venv ai-env

# Activate (macOS/Linux)
source ai-env/bin/activate

# Activate (Windows)
ai-env\Scripts\activate

# Install essential packages
pip install jupyter pandas numpy matplotlib seaborn

📦 Essential Python Packages

Core AI/ML Libraries

# Install essential AI libraries
pip install openai langchain chromadb sentence-transformers
pip install transformers torch torchvision torchaudio
pip install scikit-learn pandas numpy matplotlib

For LangChain Development

pip install langchain langchain-openai langchain-community
pip install langchain-chroma langchain-pinecone
pip install streamlit gradio  # For building UIs

For Vector Database Work

pip install chromadb pinecone-client qdrant-client
pip install sentence-transformers faiss-cpu

🔧 Development Tools

Code Editor Setup

• VS Code: Install Python extension, Jupyter extension
• PyCharm: Professional IDE for Python development
• Jupyter Lab: Web-based interactive development

Essential VS Code Extensions

• Python
• Jupyter
• GitHub Copilot
• Markdown All in One
• Git Lens

Git Configuration

git config --global user.name "Your Name"
git config --global user.email "your.email@example.com"

🚀 Quick Start Template

Basic AI Project Structure

my-ai-project/
├── .env                 # API keys and secrets
├── requirements.txt     # Python dependencies
├── main.py             # Main application
├── notebooks/          # Jupyter notebooks
├── data/               # Data files
├── models/             # Saved models
└── docs/               # Documentation

Sample requirements.txt

openai>=1.0.0
langchain>=0.1.0
chromadb>=0.4.0
sentence-transformers>=2.2.0
streamlit>=1.28.0
python-dotenv>=1.0.0

Environment Variables (.env)

OPENAI_API_KEY=your_openai_api_key_here
PINECONE_API_KEY=your_pinecone_api_key_here
ANTHROPIC_API_KEY=your_anthropic_api_key_here

🐳 Docker Setup (Optional)

Dockerfile for AI Projects

FROM python:3.10-slim

WORKDIR /app

COPY requirements.txt .
RUN pip install -r requirements.txt

COPY . .

EXPOSE 8501

CMD ["streamlit", "run", "app.py"]

Docker Compose for Development

version: '3.8'
services:
  ai-app:
    build: .
    ports:
      - "8501:8501"
    environment:
      - OPENAI_API_KEY=${OPENAI_API_KEY}
    volumes:
      - ./data:/app/data

☁️ Cloud Development Options

GitHub Codespaces

• Full VS Code environment in the browser
• Pre-configured with Python and common tools
• Good for experimentation and learning

Google Colab

• Free Jupyter notebooks with GPU access
• Great for experimentation and learning
• Limited session time and storage

Replit

• Browser-based IDE
• Good for quick prototypes
• Easy sharing and collaboration

🔑 API Key Management

Getting API Keys

1. OpenAI: Sign up at platform.openai.com
2. Anthropic: Apply for access at anthropic.com
3. Pinecone: Create account at pinecone.io
4. Cohere: Sign up at cohere.com

Secure Key Storage

# Use python-dotenv for local development
from dotenv import load_dotenv
import os

load_dotenv()
api_key = os.getenv('OPENAI_API_KEY')

Environment Variables in Production

• Use cloud provider's secret management
• AWS Secrets Manager, Azure Key Vault, etc.
• Never commit API keys to git repositories

🧪 Testing Your Setup

Quick Test Script

# test_setup.py
import openai
import langchain
import chromadb
from sentence_transformers import SentenceTransformer

print("Testing AI development environment...")

# Test OpenAI (if you have API key)
# client = openai.OpenAI()
# print("✅ OpenAI client created")

# Test sentence transformers
model = SentenceTransformer('all-MiniLM-L6-v2')
print("✅ Sentence transformer loaded")

# Test ChromaDB
client = chromadb.Client()
print("✅ ChromaDB client created")

print("🎉 Environment setup complete!")

📚 Next Steps

Once your environment is set up:

1. Run the test script to verify everything works
2. Try the basic examples in each technology section
3. Build your first simple project (e.g., document Q&A)
4. Explore the frameworks and experiment with different models

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Your development environment is now ready for AI application development!