Cornell Course Projects

This repository contains coursework, exercises, and project implementations developed for Cornell and eCornell courses.

Repository contents

Cornell_git/
├── Agentic_AI/
│   └── CIS643_M2_3_Harness_Agent/
│       ├── CIS643_M2_3_Parallelization._using_deepagent.py
│       ├── input.txt
│       ├── README.md
│       └── skills/
└── README.md

Agentic AI

The current project demonstrates a multi-agent marketing workflow built with LangChain Deep Agents. It generates dietary-supplement marketing copy, runs parallel compliance checks, and returns an approval or rejection report.

See Agentic_AI/CIS643_M2_3_Harness_Agent/README.md for the workflow design, examples, and detailed usage instructions.

Setup

The current project requires:

• Python 3.10 or later
• An Anthropic API key

Install its dependencies:

pip install -U deepagents langchain-anthropic python-dotenv

Create a .env file in this repository root:

ANTHROPIC_API_KEY=your-api-key

The .env file contains credentials and must not be committed to source control.

Run the current project

From the repository root:

python ".\Agentic_AI\CIS643_M2_3_Harness_Agent\CIS643_M2_3_Parallelization._using_deepagent.py"

Follow the terminal prompt to enter a marketing request.

Notes

• Individual projects may provide their own README files and setup steps.
• Dependencies are currently installed directly with pip; this repository does not yet include a shared dependency manifest.
• Course projects are organized by subject and module as the repository grows.