SieveAi

Advanced AI-Powered Code Review Tool with hybrid static + Active AI analysis

📦 Available on npm: npm install -g sieveai | View on NPM

SieveAi is an intelligent code review tool that combines static analysis with AI-powered insights to help maintain code quality, security, and performance. It supports 15+ programming languages and provides deep analysis including const correctness, security vulnerabilities, logic errors, and architectural improvements.

Showcase

Features

AI-Powered Analysis

Logic & Bug Detection: Identifies complex logic errors, race conditions, memory leaks
Security Analysis: Detects injection vulnerabilities, authentication issues, unsafe patterns
Performance Optimization: Suggests const correctness, inline functions, algorithmic improvements
Architecture Review: SOLID principles, encapsulation, design patterns

Multi-Language Support

Systems Languages: C++, C, Rust, Go
JVM Languages: Java, Kotlin, Scala
Web Technologies: JavaScript, TypeScript, HTML, CSS
Scripting: Python, Ruby, Shell, PHP
Data Formats: JSON, YAML, Markdown
And more: Automatic language detection

Comprehensive Analysis

Static Analysis: Syntax checking, secret scanning, dependency analysis
Whitespace Analysis: Formatting consistency, unnecessary diff noise detection
Security Scanning: Built-in secret detection, vulnerability patterns
Performance Insights: Optimization opportunities, algorithmic improvements

Professional Output

Clean TUI Interface: Professional bordered output with severity indicators
Multiple Formats: TUI, JSON, plain text
Detailed Reports: Confidence scores, rationale, fix suggestions
Git Integration: Works with diffs, staged changes, commits

Quick Start

Installation

Option 1: NPM Package (Recommended)

# Install globally for CLI usage
npm install -g sieveai

# Or install locally in your project
npm install --save-dev sieveai

Option 2: From Source

# Clone the repository
git clone https://github.com/Jayesh-Dev21/SieveAi.git
cd SieveAi

# Install dependencies
npm install

# Build the project
npm run build

# Make globally available (optional)
npm link

Setup LLM Backend

SieveAi requires an LLM for AI-powered analysis. Currently supports Ollama:

# Install Ollama (https://ollama.ai)
curl -fsSL https://ollama.ai/install.sh | sh

# Pull a supported model
ollama pull gemma3:latest
# or
ollama pull llama3.2:latest
# or
ollama pull deepseek-coder:latest

Basic Usage

# Run code review on current git changes
sieveai check

# Run with verbose output
sieveai check --verbose

# Run with specific format
sieveai check --format json

# Run with custom model
sieveai check --model ollama:deepseek-coder:latest

# If installed locally in project:
npx sieveai check

Configuration

Create a .sieveai.config.json file in your project root:

{
  "model": "ollama:gemma3:latest",
  "temperature": 0.7,
  "maxTokens": 2048,
  "minConfidence": 78,
  "enableCache": true,
  "parallel": true,
  "maxConcurrency": 3,
  "enableSecretScanning": true,
  "format": "tui",
  "verbose": false,
  "showRationale": true
}

Configuration Options

Option	Type	Default	Description
`model`	string	`"ollama:gemma3:latest"`	LLM model (provider:model:tag)
`temperature`	number	`0.7`	AI creativity (0.0-1.0)
`maxTokens`	number	`2048`	Maximum response length
`minConfidence`	number	`78`	Minimum confidence for findings (0-100)
`enableCache`	boolean	`true`	Enable result caching
`parallel`	boolean	`true`	Run agents in parallel
`maxConcurrency`	number	`3`	Max parallel agent execution
`enableSecretScanning`	boolean	`true`	Scan for leaked secrets
`format`	string	`"tui"`	Output format: `"tui"`, `"json"`, `"text"`
`verbose`	boolean	`false`	Enable detailed logging
`showRationale`	boolean	`true`	Show reasoning for findings

Usage Examples

Example 1: C++ Code Review

// ProcessingUnit.cpp
class ProcessingUnit {
public:
    void execute(std::vector<int> data) {  // ❌ Missing const, pass by value
        if (data.size() > 0) {             // ❌ Use !data.empty()
            process(data[0]);
        }
    }
private:
    std::string secret_key = "hardcoded_key"; // ❌ Security issue
};

SieveAi Analysis:

● HIGH | PERFORMANCE | ProcessingUnit.cpp:3
  Function parameter should be const reference
  Fix: Change to `const std::vector<int>& data` for better performance

● MEDIUM | STYLE | ProcessingUnit.cpp:4  
  Use container.empty() instead of size() comparison
  Fix: Replace `data.size() > 0` with `!data.empty()`

● CRITICAL | SECURITY | ProcessingUnit.cpp:8
  Hardcoded secret detected in source code
  Fix: Move sensitive data to environment variables or config files

Example 2: JavaScript Security Analysis

// server.js
app.get('/user/:id', (req, res) => {
    const query = `SELECT * FROM users WHERE id = ${req.params.id}`;  // ❌ SQL injection
    db.query(query, (err, results) => {
        res.json(results);  // ❌ No error handling
    });
});

SieveAi Analysis:

● CRITICAL | SECURITY | server.js:2
  SQL injection vulnerability detected
  Fix: Use parameterized queries: `SELECT * FROM users WHERE id = ?`

● HIGH | BUG | server.js:3
  Unhandled database error could crash application  
  Fix: Add proper error handling for database operations

Advanced Features

Custom Analysis Depth

# High confidence only (fewer, higher-quality findings)
sieveai check --min-confidence 90

# Lower confidence (more findings, some potential false positives)  
sieveai check --min-confidence 50

# Performance-focused analysis
sieveai check --model ollama:deepseek-coder:latest --temperature 0.3

Git Integration

# Review specific commit range
sieveai check --base main --target feature-branch

# Review staged changes only
git add . && sieveai check --staged

# Review specific files
git diff path/to/file.cpp | sieveai check

Output Formats

# Beautiful TUI output (default)
sieveai check --format tui

# JSON for automation
sieveai check --format json | jq '.findings[] | select(.severity == "critical")'

# Plain text for logging
sieveai check --format text >> code-review.log

Development

Building from Source

# Development setup
git clone https://github.com/Jayesh-Dev21/SieveAi.git
cd SieveAi
npm install

# Development build with watch
npm run dev

# Production build
npm run build

# Run tests
npm test

Available Scripts

# Core scripts
npm run build          # Build TypeScript to dist/
npm run dev           # Watch mode for development
npm test             # Run test suite
npm run lint         # Lint code with ESLint
npm run format       # Format code with Prettier

# Quick usage
npm run check         # Run code review
npm run check:verbose # Run with verbose output
npm run check:json    # Get JSON output
npm run setup         # One-command setup

Project Structure

src/
├── agents/          # AI analysis agents (bug, security, style)
├── cache/           # Result caching system
├── cli/             # Command-line interface
├── config/          # Configuration management
├── git/             # Git integration and diff parsing
├── llm/             # LLM client and prompts
├── orchestrator/    # Main review coordination
├── reporters/       # Output formatting (TUI, JSON, text)
├── static/          # Static analyzers (syntax, secrets, whitespace)
├── types/           # TypeScript type definitions
└── utils/           # Shared utilities

docs/               # Documentation
examples/           # Usage examples
web/                # Web interface (Vite + React)
dist/               # Compiled output

Troubleshooting

Common Issues

LLM Not Available

# Check if Ollama is running
ollama list

# Restart Ollama service
systemctl restart ollama  # Linux
brew services restart ollama  # macOS

Model Not Found

# Pull the model explicitly
ollama pull gemma3:latest

# Check available models
ollama list

Slow Analysis

# Reduce model size
sieveai check --model ollama:gemma3:2b  

# Disable caching temporarily
sieveai check --no-cache

# Reduce concurrency
sieveai check --max-concurrency 1

High Memory Usage

# Use smaller model
ollama pull gemma3:2b

# Reduce token limit
echo '{"maxTokens": 1024}' > .sieveai.config.json

🤝 Contributing

We welcome contributions! Please see CONTRIBUTING.md for guidelines.

Areas for Contribution

New Language Support: Add syntax checkers for additional languages
AI Agents: Enhance existing agents or create specialized ones
LLM Providers: Add support for OpenAI, Anthropic, etc.
Static Analyzers: Improve existing or add new static analysis tools
Documentation: Help improve documentation and examples

License

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

🙏 Acknowledgments

Ollama for local LLM inference
Google Gemma for the base AI model
All contributors and the open source community

Made with ❤️ for better code quality

Name		Name	Last commit message	Last commit date
Latest commit History 30 Commits
docs		docs
examples		examples
sieveAssets		sieveAssets
src		src
web		web
.gitignore		.gitignore
.sieveai.config.example.json		.sieveai.config.example.json
LICENSE		LICENSE
README.md		README.md
SETUP_COMPLETE.md		SETUP_COMPLETE.md
biome.json		biome.json
debug-cache-detailed.js		debug-cache-detailed.js
debug-cache.js		debug-cache.js
package.json		package.json
tsconfig.json		tsconfig.json
vitest.config.ts		vitest.config.ts

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SieveAi

Showcase

Features

AI-Powered Analysis

Multi-Language Support

Comprehensive Analysis

Professional Output

Quick Start

Installation

Option 1: NPM Package (Recommended)

Option 2: From Source

Setup LLM Backend

Basic Usage

Configuration

Configuration Options

Usage Examples

Example 1: C++ Code Review

Example 2: JavaScript Security Analysis

Advanced Features

Custom Analysis Depth

Git Integration

Output Formats

Development

Building from Source

Available Scripts

Project Structure

Troubleshooting

Common Issues

🤝 Contributing

Areas for Contribution

License

🙏 Acknowledgments

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