🧠 AI Code Reviewer

A web-based AI-powered tool that reviews Python code, detects bugs, suggests improvements, and generates human-friendly documentation using language models.

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Documentation : https://medium.com/@abhayemani8/ai-code-reviewer-documentation-0a17280adcfd

📌 Overview

This project demonstrates the evolution of a code reviewer app through two versions:

• Version 1: Built with guidance from ChatGPT and tutorials. It uses Google's Gemini API and Streamlit for quick prototyping.
• Version 2: Fully self-written using Flask and a local Ollama LLM (llama3.2) for offline, more customizable AI processing.

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🧾 Table of Contents

• Project Structure
• Version Highlights
• Tech Stack
• Setup & Installation
• How to Run
• Learnings & Evolution
• Screenshots (optional)
• License

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📁 File Structure

.
├── version_1/                   # Streamlit + Gemini API version
│   ├── app.py
│   └── .env (Google API key)
│
├── version_2/                   # Flask + Ollama + Llama3.2 version
│   ├── app.py
│   ├── templates/
│   │   └── index.html
│   └── utils/
│       └── functions.py
│
├── README.md
└── requirements.txt             # Optional, depending on environment

✨ Version Highlights

🔹 Version 1 (Assisted Build)

• Built using Streamlit for fast UI.

• Uses Google Gemini API via google.generativeai.

• Offers simple input/output layout for quick feedback.

🔸 Version 2 (Self-Built)

• Built using Flask from scratch.

• Implements Ollama with a locally running llama3.2 model.

• Enhanced prompt engineering for better review quality.

• Beautiful custom HTML/CSS UI for better user experience.

• Contains robust instructions for context filtering (code-only reviews).

Area	Tools Used
Frontend	Streamlit (v1), HTML/CSS (v2)
Backend	Python, Flask
LLM	Google Gemini API (v1), Ollama LLM (llama3.2) (v2)
Environment	dotenv (.env), virtualenv

⚙️ Setup & Installation

🧪 Version 1

cd version_1
python -m venv venv
source venv/bin/activate       # Windows: venv\Scripts\activate
pip install streamlit google.generativeai 

Set your Google API Key in .env

echo GOOGLE_API_KEY=your_key_here > .env

streamlit run app.py

🛠️ Version 2

cd version_2
python -m venv venv
source venv/bin/activate
pip install flask ollama

# Make sure Ollama is installed and running
ollama run llama3.2

python app.py

🧠 Learnings & Evolution

Version 1

• taught me the basics of API calls, prompt structuring, and how to quickly prototype with Streamlit.

Version 2

• was my full-stack build using Flask, local LLMs, and custom UI — improving my understanding of backend routing, HTML templating, and deploying AI models locally.

• Implemented stricter prompt rules and better error handling in v2.