Agentic AI Mastery: From Zero to Pro — A Complete Guide (Module-2)

📌 Module 2: Your AI Workbench — Setting Up on Windows

1. Theory

A well-configured environment is the foundation for building and running Agentic AI applications efficiently.
On Windows, this means:

• Installing the right tools (Python, Git, IDEs)
• Managing virtual environments
• Installing dependencies
• Setting up local or cloud-based LLMs

A proper setup ensures reproducibility — you and others can run the same code with minimal issues.

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Why Windows Setup Matters for AI Development

• Many developers in enterprises use Windows by default.
• With WSL2 or native Python, you can still run modern AI frameworks.
• Windows allows both local LLM execution and cloud API integration.

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2. Step-by-Step Windows Setup (For This Module)

1. Install Python 3.10+
• Download: https://www.python.org/downloads/
• During installation → Check "Add Python to PATH"
2. Install Git
• Download: https://git-scm.com/download/win
3. Install VS Code
• Download: https://code.visualstudio.com/
• Add Python and Git extensions
4. Install Ollama for Local LLMs
• Download: https://ollama.com/download
• Verify with:

o   ollama run llama2

5. Create Virtual Environment

6.  python -m venv agentic_env

7.  .\agentic_env\Scripts\activate

8. Install Libraries

9.  pip install langchain openai requests wikipedia python-dotenv

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3. Examples

Example 1 — Running a Local LLM

• Run:

·       ollama run llama2

• Type:

·       What is Agentic AI?

Example 2 — Testing LangChain Installation

from langchain.prompts import PromptTemplate

template = PromptTemplate(input_variables=["name"], template="Hello {name}, welcome to Agentic AI!")

print(template.format(name="Ajay"))

Example 3 — Using Hugging Face Transformers Locally

from transformers import pipeline

qa = pipeline("question-answering", model="distilbert-base-uncased-distilled-squad")

print(qa(question="What is AI?", context="AI stands for Artificial Intelligence."))

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4. Exercises

1. Install a different local model in Ollama.
2. Create a Python script that checks if all dependencies are installed.
3. Set up a VS Code workspace for an Agentic AI project.

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5. Best Practices

• Keep your virtual environment per project.
• Use requirements.txt to track dependencies.

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6. Common Mistakes

• Forgetting to activate the venv before installing packages.
• Using system Python instead of project-specific venv.

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7. Quiz

1. Which command activates a virtual environment in PowerShell?
2. Name two benefits of using Ollama locally.
3. Why should you keep a requirements.txt file?

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