Githubify - Codebase Comprehension Platform and Onboarding SAAS

👥 Team

Ethereum Bots Team

This project was developed by:

• Manav Pandya - Core Architecture & Backend Development
• Tushar Jain - AI Integration & Query Engine
• Prayag Bhatt - API Development & Infrastructure

📋 Table of Contents

• Overview
• Architecture
• Problem Statement
• Solution
• Features
• Getting Started
• API Documentation
• Technology Stack

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🎯 Overview

Githubify is an intelligent codebase comprehension platform designed to accelerate developer onboarding and reduce the learning curve for new team members, interns, and open-source contributors. By leveraging AI-powered analysis, Githubify transforms complex repositories into understandable, queryable knowledge bases.

Chat with your Codebase

Visualise your Codebase:

Codebase as a Tree

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🏗 Architecture

🚨 Problem Statement

Organizations face significant challenges when onboarding new developers:

• Time-Intensive Onboarding: New developers spend weeks understanding codebases, consuming valuable senior developer time
• Knowledge Bottleneck: Limited availability of senior developers to guide newcomers through complex architectures
• Context Loss: Documentation often becomes outdated, making it difficult to understand design decisions and code relationships
• Steep Learning Curve: Large repositories with multiple modules and dependencies are overwhelming for newcomers
• Reduced Productivity: Delayed understanding leads to slower contribution cycles and increased frustration
• The Cost: Companies lose an average of 30-50 hours of senior developer time per new hire during onboarding, while new developers take 3-6 months to become fully productive.

✨ Features

Core Capabilities

• Intelligent Repository Analysis: Automatically ingests and analyzes GitHub repositories to build a comprehensive knowledge graph
• Natural Language Queries: Ask questions in plain English about code functionality, architecture, and implementation
• Fast Onboarding: Reduce onboarding time from weeks to days
• Repository Insights: Understand codebase structure, patterns, and best practices

Benefits

• For Senior Developers: Reduced time spent on repetitive onboarding explanations
• For Teams & New Developers: Faster time-to-productivity and more consistent knowledge sharing
• For Open Source Projects: Lower barrier to entry for new contributors

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Key Components

1. Ingestion Service: Clones and analyzes repositories, extracting code structure and relationships
2. Knowledge Base: Stores processed repository information in a queryable format
3. Query Engine: Processes natural language queries and retrieves relevant information
4. API Layer: FastAPI-based REST interface for client interactions

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🚀 Getting Started

Prerequisites

Ensure you have the following installed:

• Python: Version 3.7 or higher
• UV Package Manager: For dependency management

Installation

Step 1: Install UV Package Manager

If you don't have UV installed, install it first:

# On macOS/Linux
curl -LsSf https://astral.sh/uv/install.sh | sh

# On Windows
powershell -c "irm https://astral.sh/uv/install.ps1 | iex"

Step 2: Clone the Repository

git clone https://github.com/Prayag2003/githubify-ethereum-bots-futurestack-hack
cd githubify-ethereum-bots-futurestack-hack/server

Step 3: Create Virtual Environment and Install Dependencies

# Create virtual environment
uv venv

# Activate virtual environment
# On macOS/Linux:
source .venv/bin/activate

# On Windows:
.venv\Scripts\activate

# Install dependencies
uv pip install -r requirements.txt

Step 4: Configure Environment Variables

Create a .env file in the server directory:

CEREBRAS_API_KEY=""
PINECONE_API_KEY=""

Step 5: Start the Development Server

uvicorn app.main:app --reload

The server will start on http://localhost:8000. You can access the interactive API documentation at http://localhost:8000/docs.

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📚 API Documentation

Base URL

http://localhost:8000

Endpoints

1. Repository Ingestion

Analyze and ingest a GitHub repository into the knowledge base.

Endpoint: POST /repos/ingest

Request Body:

{
	"github_url": "https://github.com/username/repository-name"
}

Response:

{
	"repo_id": "ab4de4a4-6262-4dfa-8f68-9863d5a7082d",
	"status": "success",
	"message": "Repository ingested successfully",
	"files_processed": 42,
	"analysis_time": "15.3s"
}

Status Codes:

• 200 OK: Repository ingested successfully
• 400 Bad Request: Invalid GitHub URL
• 404 Not Found: Repository not found
• 500 Internal Server Error: Processing error

2. Query Repository

Ask questions about an ingested repository.

Endpoint: POST /query

Request Body:

{
	"repo_id": "ab4de4a4-6262-4dfa-8f68-9863d5a7082d",
	"query": "What does this codebase do?"
}

Response:

{
	"answer": "This codebase implements a Discord bot for the Across Protocol...",
	"relevant_files": [
		"src/bot/main.py",
		"src/handlers/message_handler.py"
	],
	"confidence": 0.95,
	"timestamp": "2025-10-04T10:30:00Z"
}

Status Codes:

• 200 OK: Query processed successfully
• 400 Bad Request: Invalid request format
• 404 Not Found: Repository ID not found
• 500 Internal Server Error: Query processing error

3. List Repositories

Get all ingested repositories.

Endpoint: GET /repos

Response:

{
	"repositories": [
		{
			"repo_id": "ab4de4a4-6262-4dfa-8f68-9863d5a7082d",
			"name": "across-protocol-discord-bot",
			"url": "https://github.com/Prayag2003/across-protocol-discord-bot",
			"ingested_at": "2025-10-04T09:15:00Z",
			"files_count": 42
		}
	]
}

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💻 Usage Examples

Example 1: Ingesting a Repository

curl -X POST \
  http://localhost:8000/repos/ingest \
  -H 'Content-Type: application/json' \
  -d '{
    "github_url": "https://github.com/Prayag2003/across-protocol-discord-bot"
  }'

Example 2: Querying About Architecture

curl -X POST \
  http://localhost:8000/query \
  -H 'Content-Type: application/json' \
  -d '{
    "repo_id": "ab4de4a4-6262-4dfa-8f68-9863d5a7082d",
    "query": "Explain the main architecture of this application"
  }'

Example 3: Finding Specific Functionality

curl -X POST \
  http://localhost:8000/query \
  -H 'Content-Type: application/json' \
  -d '{
    "repo_id": "ab4de4a4-6262-4dfa-8f68-9863d5a7082d",
    "query": "Where is the authentication logic implemented?"
  }'

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🛠 Technology Stack

Backend

• FastAPI: Modern, fast web framework for building APIs
• Python 3.7+: Core programming language
• UV: Fast Python package installer and resolver
• Uvicorn: ASGI server for running FastAPI applications

AI/ML

• OpenAI GPT: Natural language understanding and response generation
• LangChain: Framework for developing LLM-powered applications
• Vector Embeddings: For semantic code search

Storage

• SQLite: Lightweight database for metadata
• Vector Database: For code embeddings (Pinecone Vector DB)

Tools

• Git/GitHub API: Repository access and management
• AST Parsers: Code structure analysis

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Made with ❤️ by Team Ethereum Bots