I Built a Local AI Code Reviewer That Reads Your Entire Codebase (and PRs!) for Free

As developers, we all want AI to review our code. But sending proprietary, unreleased code to third-party cloud APIs (like OpenAI or Anthropic) isn't always an option-especially if you're working on client projects or under strict NDAs. I wanted an AI code reviewer that was 100% private, free, and actually understood the context of my entire project. So, I built one using Python and Ollama. Here’s a look at what it does and how you can use it!

What it does

It’s a CLI tool that uses local LLMs (like qwen2.5-coder or llama3) to review your code. No API keys, no subscriptions, and zero data leaves your machine. But I didn't want to just paste code snippets into a terminal. I wanted a tool that actually fits into a developer's workflow. Here is what it supports:

1. Review an Entire Codebase
   Just point it at your project folder. The app will recursively gather your files, automatically ignoring bulky folders like node_modules, .git, vendor, and .next, and give you a full architectural review.

   python3 app.py ./my-project/
   

2. Review Pull Requests Automatically
   Want to review a PR? Just pass the GitHub PR URL. The tool auto-detects that it's a diff, fetches the changes, and switches into "PR Review Mode." Instead of looking at architecture, it zeroes in on the + lines to find bugs, edge cases, and missing tests introduced by the PR.

   python3 app.py https://github.com/facebook/react/pull/30000
   

   (Working on a private repo? Just pipe it: gh pr diff 123 | python3 app.py)

3. Pipe Anything Into It
   You can pipe individual files, diffs, or snippets straight from your terminal.

   cat src/main.py | python3 app.py
   

🛠️ How to run it yourself

• Install Ollama and pull a solid coding model:

  ollama pull qwen2.5-coder
  

• Clone the repo and install the requirements:

  pip install -r requirements.txt
  

• Run it!

  python3 app.py ./your-code
  

💡 The Magic Under the Hood

The script dynamically switches its prompt based on what you feed it. If you give it a directory, it looks for separation of concerns and system design. If you feed it a Git Diff, it laser-focuses on unintended side effects and edge cases in the modified lines.

Give it a try and let me know what you think! What features would you like to see added next?

bimashazaman / AI-Code-Reviewer-Ollama-LLM

Imagine you're coding, and before committing your code, your own local AI reviews it. No OpenAI. No internet. No API costs. Runs entirely on Ollama.

AI Code Reviewer

Review code locally with Ollama. No API keys, no cloud - your code stays on your machine.

Setup

• Install Ollama and pull a model:

  ollama pull qwen2.5-coder
  

• Install dependencies:

  pip install -r requirements.txt
  

Usage

You can use the AI Code Reviewer to analyze an entire codebase, a single file, or a quick snippet.

Review an Entire Codebase
Simply provide the path to your project folder. The tool will automatically gather your code while ignoring massive folders (like node_modules, .git, vendor) and large data files to keep the review efficient.

python3 app.py ./my-project/

Review a Single File
Pass the exact file you want to review.

python3 app.py src/main.py

Review a Snippet (Interactive)
Run the script without any arguments. You can paste your code directly into the terminal. Type END on a new line when you're finished.

python3 app.py

Pipe Code In
You can also...

View on GitHub