🤖 SARKAAR-AI

JARVIS-Inspired Modular AI System

Automation · Vision · Voice · Safety Agents

A sophisticated, production-ready modular AI system with automation, vision, voice, and safety agents — orchestrated through a central CORE system. Built as the evolution of AstraOps.

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📋 Table of Contents

• Features
• Architecture
• Installation
• Quick Start
• Usage Examples
• API Reference
• VS Code Integration
• Agent Details
• Contributing

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✨ Features

🔍 Code Analysis

• AST-based code parsing
• Complexity metrics (cyclomatic, cognitive)
• Code quality scoring
• Security vulnerability detection
• Performance issue identification
• Best practices checking

🐛 Intelligent Debugging

• Syntax error detection
• Runtime error prediction
• Logic error identification
• Automatic fix suggestions
• Context-aware explanations

💡 Code Generation

• Natural language to code
• Template-based generation
• Algorithm implementations
• API client scaffolding
• Data processing pipelines

⚡ Performance Optimization

• Loop optimization
• Data structure recommendations
• String operation improvements
• Function call optimization
• Memory usage analysis

📖 Code Explanation

• Line-by-line breakdown
• Concept identification
• Complexity analysis
• Purpose inference
• Step-by-step walkthrough

🎯 DSA Problem Solver

• Common algorithm patterns
• Data structure implementations
• Complexity analysis
• Test case generation
• Multiple solution approaches

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🏗️ Architecture

                    CORE SYSTEM
            Request Router & Orchestrator
                         |
        ┌────────────────┼────────────────┐
        │                │                │
  Memory &         Intent Router    Agent Coordinator
  Context                │
                         │
        ┌────────────────┼────────────────┐
        │                │                │
  Code Analysis    Debug Agent    Code Generation
     Agent                              Agent
        │                │                │
  Optimization    Explanation        DSA Solver
     Agent           Agent

Key Components

1. CORE System — Central orchestrator managing all operations
2. Memory Store — Maintains context and conversation history
3. Intent Router — Routes requests to appropriate agents
4. Agent Coordinator — Manages multi-agent workflows
5. Specialized Agents — Domain-specific processing units

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🚀 Installation

Prerequisites

• Python 3.10+
• Windows 11 (or any OS with Python support)
• pip package manager

Step 1: Clone the Repository

git clone https://github.com/saikumar1626/SARKAAR-AI.git
cd SARKAAR-AI

Step 2: Install Dependencies

# No external dependencies required!
# The system uses only Python standard library

All agents use only Python's standard library (ast, re, logging, etc.), making it lightweight and portable.

Step 3: Verify Installation

python main.py

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⚡ Quick Start

Basic Usage

import asyncio
from main import CodingAssistant

async def main():
    # Initialize assistant
    assistant = CodingAssistant()

    # Analyze code
    code = """
def factorial(n):
    if n <= 1:
        return 1
    return n * factorial(n-1)
    """

    result = await assistant.analyze_code(code, language="python")
    print(result['data']['insights'])

asyncio.run(main())

Command Line Interface

python cli.py analyze my_code.py
python cli.py debug buggy_code.py
python cli.py explain algorithm.py

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💡 Usage Examples

Example 1: Comprehensive Code Review

async def code_review_example():
    assistant = CodingAssistant()
    code = """
def process_data(items):
    result = []
    for item in items:
        if item > 0:
            result.append(item * 2)
    return result
    """
    review = await assistant.comprehensive_review(code)
    print("Analysis:", review['data']['code_analysis'])
    print("Debug Report:", review['data']['debug'])
    print("Optimizations:", review['data']['optimize'])

Example 2: Generate and Test Code

async def generate_and_test():
    assistant = CodingAssistant()
    result = await assistant.generate_code(
        "Create a function to calculate the nth Fibonacci number"
    )
    generated_code = result['data']['generated_code']
    analysis = await assistant.analyze_code(generated_code)
    print("\nCode Quality:", analysis['data']['analysis']['code_quality'])

Example 3: Solve DSA Problem

async def solve_problem():
    assistant = CodingAssistant()
    problem = "Implement a function to reverse a linked list"
    solution = await assistant.solve_dsa_problem(problem)
    print("Approach:", solution['data']['solution']['approach'])
    print("Time Complexity:", solution['data']['solution']['time_complexity'])

Example 4: Debug with Error Message

async def debug_with_error():
    assistant = CodingAssistant()
    code = """
def divide(a, b):
    return a / b
result = divide(10, 0)
    """
    error = "ZeroDivisionError: division by zero at line 5"
    result = await assistant.debug_code(code, error_message=error)
    print("Debug Report:")
    print(result['data']['report'])
    if result['data'].get('fixed_code'):
        print("\nFixed Code:")
        print(result['data']['fixed_code'])

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📚 API Reference

CodingAssistant Class

async analyze_code(code: str, language: str = "python") -> Dict

Analyze code quality, complexity, and issues.

async debug_code(code: str, language: str = "python", error_message: Optional[str] = None) -> Dict

Debug code and suggest fixes.

async generate_code(description: str, language: str = "python") -> Dict

Generate code from description.

async optimize_code(code: str, language: str = "python") -> Dict

Optimize code for performance.

async explain_code(code: str, language: str = "python", detail_level: str = "medium") -> Dict

Explain what code does. detail_level: "low", "medium", or "high"

async solve_dsa_problem(problem: str, language: str = "python") -> Dict

Solve DSA problem with complexity analysis.

async comprehensive_review(code: str, language: str = "python") -> Dict

Complete code review (analysis + debug + optimization).

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🔌 VS Code Integration

Creating a VS Code Extension

const vscode = require('vscode');
const { spawn } = require('child_process');

function activate(context) {
    let analyzeCmd = vscode.commands.registerCommand(
        'coding-assistant.analyze',
        async () => {
            const editor = vscode.window.activeTextEditor;
            if (!editor) return;
            const code = editor.document.getText();
            const result = await runPythonScript('analyze', code);
            vscode.window.showInformationMessage(
                `Code Quality: ${result.score}`
            );
        }
    );
    context.subscriptions.push(analyzeCmd);
}
module.exports = { activate };

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🤖 Agent Details

Agent	Purpose	Output
Code Analysis Agent	Comprehensive code quality analysis	Quality score, metrics, recommendations
Debug Agent	Error detection and fix suggestions	Bug reports, fix suggestions, corrected code
Code Generation Agent	Generate code from descriptions	Generated code with documentation
Optimization Agent	Performance improvement suggestions	Optimization suggestions with impact analysis
Explanation Agent	Explain code in simple terms	Multi-level explanations
DSA Solver Agent	Solve algorithm and data structure problems	Complete solutions with complexity analysis

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🗺️ Roadmap

• Web API with FastAPI
• Real-time VS Code extension
• Support for more languages (C++, JavaScript, Go)
• AI model integration for enhanced analysis
• Collaborative features
• Cloud deployment options

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🤝 Contributing

Contributions welcome! Please:

1. Fork the repository
2. Create a feature branch
3. Submit 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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🤖 SARKAAR-AI — Built with ❤️ for developers

The evolution of intelligent development assistance.