Student GitHub Reviewer

An AI-powered tool that analyzes a student's GitHub portfolio and delivers personalized mentorship feedback.

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Overview

This project uses a multi-step AI agent pipeline to fetch a user's GitHub profile and repositories, then generates a professional code review with actionable suggestions — powered by Groq's Llama 3.1 model.

Live Application: https://github-reviewer-ui-p5e6.onrender.com

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Features

• AI Code Mentor Review: Generates a professional code review using Groq's Llama 3.1 based on a user's repositories, languages, and READMEs.
• Gamification (Grades and Badges): The AI automatically awards an overall letter grade and custom achievement badges based on the user's GitHub activity.
• AI Cover Letter Generator: Instantly generate a highly professional, 3-paragraph cover letter tailored to a Software Engineering role using the user's specific GitHub portfolio data.
• In-Memory Caching: Subsequent requests for the same GitHub user within 24 hours load instantly, heavily reducing API rate limits.
• Robust Rate Limit Handling: Implements exponential backoff retries and elegant fallback feedback for handling 429 Rate Limit errors gracefully.

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Architecture

User Request
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    v
FastAPI Server  (POST /review?username=...)
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    v
LangGraph Pipeline
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    +-- Step 1: extract_github_data  -->  GitHub API
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    +-- Step 2: code_mentor_review   -->  Groq / Llama 3.1
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    v
JSON Response  (extracted data + mentor feedback)
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    v
Streamlit UI  (renders feedback to the user)

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Tech Stack

Layer	Technology
Frontend	Streamlit
Backend	FastAPI
Agent	LangGraph
LLM	Groq (Llama 3.1 8B)
Deployment	Render

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Getting Started

Prerequisites

• Python 3.10 or higher
• A Groq API key — get one free at https://console.groq.com/keys
• A GitHub Personal Access Token — generate one at https://github.com/settings/tokens (scope: public_repo)

Installation

# Clone the repository
git clone https://github.com/14-himanshu/student-github-reviewer.git
cd student-github-reviewer

# Create and activate a virtual environment
python -m venv venv
source venv/bin/activate

# Install dependencies
pip install -r requirements.txt

# Set up environment variables
cp .env.example .env
# Open .env and add your API keys

Running Locally

Start the backend (which also serves the frontend):

uvicorn main:app --reload

Then open your browser and navigate to http://localhost:8000 to view the application!

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API Reference

GET /

Health check endpoint.

Response:

{ "message": "GitHub Reviewer backend is running perfectly!" }

POST /review

Analyzes a GitHub user's portfolio and returns AI mentor feedback.

Query Parameter:

Parameter	Type	Description
username	string	GitHub username to review

Example:

curl -X POST "https://student-github-reviewer-yraz.onrender.com/review?username=torvalds"

Response:

{
  "username": "torvalds",
  "extracted_data": {
    "avatar_url": "https://avatars.githubusercontent.com/u/1024025?v=4",
    "followers": 200000,
    "recent_repos": ["linux", "subsurface-for-dirk"],
    "primary_languages": ["C", "C++"],
    "public_repos_count": 7,
    "repo_readmes": {
       "linux": "Linux kernel..."
    }
  },
  "mentor_feedback": "[GRADE: A+]\n[BADGES: C Master, Open Source Legend]\n\nYour expertise in C is evident..."
}

POST /cover-letter

Generates a professional cover letter based on cached GitHub data. Must be called after /review.

Query Parameter:

Parameter	Type	Description
username	string	GitHub username to review

Example:

curl -X POST "https://student-github-reviewer-yraz.onrender.com/cover-letter?username=torvalds"

Response:

{
  "cover_letter": "Dear Hiring Manager, ..."
}

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Project Structure

student-github-reviewer/
├── agent/
│   ├── __init__.py        # Package initializer
│   ├── graph.py           # LangGraph workflow
│   ├── nodes.py           # Agent node functions
│   └── state.py           # State schema
├── ui/
│   └── app.py             # Streamlit frontend
├── main.py                # FastAPI entry point
├── requirements.txt       # Dependencies
├── .env.example           # Environment variable template
├── render.yaml            # Render deployment config
├── .gitignore
├── LICENSE
└── README.md

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Deployment

This project is deployed as two separate services on Render:

Service	Name	URL
Backend	github-reviewer-api	https://student-github-reviewer-yraz.onrender.com
Frontend	github-reviewer-ui	https://github-reviewer-ui-p5e6.onrender.com

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Contributing

1. Fork the repository
2. Create a feature branch: git checkout -b feature/your-feature
3. Commit your changes: git commit -m 'feat: add your feature'
4. Push to the branch: git push origin feature/your-feature
5. Open a Pull Request

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License

This project is licensed under the MIT License. See the LICENSE file for details.

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Built by Himanshu Pandey