🤖 GenAI for CI/CD: Prompt Engineering Playground

This repository contains hands-on experiments that apply Generative AI to DevOps, CI/CD, and DevSecOps workflows using the OpenAI API. It's part of a larger AI upskilling journey focused on becoming an AI-integrated Engineering Leader.

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📂 Folder Structure

genai-ci-cd/
├── notebooks/        # Jupyter notebooks with hands-on GenAI tasks
│   └── genai_ci_cd_tasks.ipynb
├── scripts/          # (Optional) Python scripts version of tasks
├── docs/             # Markdown notes or writeups
└── README.md         # This file

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🚀 Tasks Included

✅ Task 1: Release Note Summarization (Notebook)

Use GPT to convert raw git logs or changelogs into concise 3-line release notes for product managers.

✅ Task 2: Legacy Script Explanation (Notebook)

Use GPT to translate a legacy shell script into plain English for documentation or handover.

✅ Task 3: Risk Detection from Change Requests (Notebook)

Use GPT to detect missing rollback plans, testing gaps, and PROD deployment risks in change tickets.

✅ Task 4: FastAPI Backend with LLM Chains (Code)

Build real-world backend endpoints powered by structured LangChain-like logic:

• /ask: Simple prompt template with string output
• /structured: Chat prompt with structured JSON output (summary, tone)
• /reason: Chain of Thought reasoning endpoint with step-by-step logic (reasoning, conclusion)

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🛠️ How to Run Locally

1. Clone this repo

git clone https://github.com/<your-username>/genai-ci-cd.git
cd genai-ci-cd


### 3. Install dependencies
```bash
pip install openai

4. Launch notebook

cd notebooks
jupyter notebook

📌 Make sure your OpenAI key is valid and has billing enabled. Use GPT-3.5 to minimize cost.

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📈 Why This Repo Exists

This is part of a long-term, real-world transformation journey focused on:

• AI for engineering platforms
• Automating DevSecOps with GenAI
• Secure, explainable GenAI integration in BFSI

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📬 License

MIT — reuse with credit, contributions welcome.

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📒 Full Task History

For a complete week-by-week breakdown of tasks, goals, and concepts learned, see:
➡️ docs/TASKS.md

📘 Modules Included

• GenAI for CI/CD – Prompting experiments and automation flows
• RAG System (LangChain + FastAPI + CLI) – Modular RAG pipeline with evaluation logging