🤖 AI Developer Agent

🚀 Local AI-powered code completion and development assistant - A free, privacy-focused alternative to GitHub Copilot

Transform your coding experience with AI-powered assistance that runs entirely on your machine. No cloud dependencies, no data sharing, no subscription fees - just powerful AI helping you code faster and smarter.

✨ Features

🤖 GitHub Copilot-Style Code Completion

Real-time inline suggestions - Gray text appears as you type
Context-aware completions - Understands your entire codebase
Press Tab to accept - Familiar workflow
Multi-language support - JavaScript, Python, TypeScript, Java, C#, Go, Rust, and more

💬 Interactive AI Chat

Full conversation interface for coding questions
Code generation with clickable "Insert" buttons
Debug assistance and error explanations
Architecture discussions and best practices

🧪 Smart Code Actions

🧪 Generate Unit Tests - Comprehensive test suites with edge cases
📝 Auto Documentation - JSDoc, docstrings, and inline comments
💡 Code Explanations - Understand complex algorithms instantly
🔧 Code Refactoring - Improve performance and readability
🩹 Bug Detection & Fixes - Identify and resolve issues automatically

🔒 Privacy & Performance

100% Local - Your code never leaves your machine
No API keys required - No cloud dependencies
GPU acceleration - Lightning-fast responses with NVIDIA GPUs
Offline capable - Works without internet connection
Multiple model sizes - From ultra-fast (300MB) to high-quality (3.8GB)

🚀 Quick Start

1. Install Ollama (AI Runtime)

Option A: Docker (Recommended)

# CPU only
docker run -d -v ollama:/root/.ollama -p 11434:11434 --name ollama ollama/ollama

# With GPU acceleration (NVIDIA)
docker run -d --gpus all -v ollama:/root/.ollama -p 11434:11434 --name ollama ollama/ollama

Option B: Direct Installation

Windows/Mac: Download from ollama.ai
Linux: curl https://ollama.ai/install.sh | sh

2. Pull AI Models

# Ultra-fast model for code completion (300MB)
docker exec -it ollama ollama pull qwen2:0.5b

# Balanced model for code completion (637MB) 
docker exec -it ollama ollama pull tinyllama:1.1b

# High-quality model for chat and explanations (3.8GB)
docker exec -it ollama ollama pull codellama:7b-instruct

3. Install Extension

From VS Code Marketplace:

Open VS Code
Go to Extensions (Ctrl+Shift+X)
Search for "AI Developer Agent"
Click "Install"

From GitHub Releases:

Download latest .vsix from Releases
Ctrl+Shift+P → "Extensions: Install from VSIX"
Select the downloaded file

4. Configure Settings

Open VS Code Settings (Ctrl+,) and search for "AI Dev Agent", or add to settings.json:

{
    "aiDevAgent.ollamaUrl": "http://localhost:11434",
    "aiDevAgent.model": "tinyllama:1.1b",
    "aiDevAgent.chat.model": "codellama:7b-instruct",
    "aiDevAgent.codeCompletion.enabled": true
}

5. Start Coding!

Type code → Gray suggestions appear → Press Tab to accept
Select code → Right-click → Choose AI action
Open AI Chat → Ctrl+Shift+P → "AI Agent: Open Chat"

⚙️ Configuration

🔧 Essential Settings

Setting	Default	Description
`aiDevAgent.ollamaUrl`	`http://localhost:11434`	Ollama server URL
`aiDevAgent.model`	`tinyllama:1.1b`	Model for code completion
`aiDevAgent.chat.model`	`codellama:7b-instruct`	Model for chat interface
`aiDevAgent.codeCompletion.enabled`	`true`	Enable/disable code completion

⚡ Performance Settings

Setting	Default	Description
`aiDevAgent.keepAlive`	`-1`	Keep model loaded (-1 = indefinite)
`aiDevAgent.maxTokens`	`2000`	Maximum response length
`aiDevAgent.temperature`	`0.1`	Creativity (0 = consistent, 1 = creative)
`aiDevAgent.codeCompletion.timeoutMs`	`6000`	Completion timeout (milliseconds)
`aiDevAgent.codeCompletion.debounceMs`	`800`	Delay before triggering completion
`aiDevAgent.codeCompletion.maxLines`	`2`	Max lines in completion

🚀 Optimized Configurations

Ultra-Fast Setup (GPU recommended):

{
    "aiDevAgent.model": "qwen2:0.5b",
    "aiDevAgent.codeCompletion.timeoutMs": 3000,
    "aiDevAgent.codeCompletion.maxLines": 1,
    "aiDevAgent.keepAlive": "-1"
}

Balanced Quality & Speed:

{
    "aiDevAgent.model": "tinyllama:1.1b",
    "aiDevAgent.chat.model": "codellama:7b-instruct",
    "aiDevAgent.codeCompletion.timeoutMs": 6000,
    "aiDevAgent.codeCompletion.maxLines": 2,
    "aiDevAgent.keepAlive": "-1"
}

Maximum Quality (Powerful hardware):

{
    "aiDevAgent.model": "codellama:7b-code",
    "aiDevAgent.chat.model": "deepseek-r1:7b",
    "aiDevAgent.codeCompletion.timeoutMs": 10000,
    "aiDevAgent.codeCompletion.maxLines": 3,
    "aiDevAgent.maxTokens": 4000
}

🎮 Usage

Code Completion

def fibonacci(n):
    if n <= 1:
        return n
    # Type here - AI suggests: return fibonacci(n-1) + fibonacci(n-2)

Gray text appears as you type
Press Tab to accept suggestion
Press Escape to dismiss
Context-aware - understands your entire file

AI Chat Interface

Open Chat: Ctrl+Shift+P → "AI Agent: Open Chat"
Ask questions: "How do I implement binary search in Python?"
Generate code: "Create a React login component with validation"
Debug help: "Why is my async function not working?"
Insert code: Click "Insert" button to add code to editor

Code Actions (Right-click menu)

🧪 Generate Unit Tests - Select function → Right-click → "Generate Unit Tests"
📝 Generate Documentation - Select code → Right-click → "Generate Documentation"
💡 Explain Code - Select complex code → Right-click → "Explain Code"
🔧 Refactor Code - Select code → Right-click → "Refactor Code"
🩹 Fix Code Issues - Select buggy code → Right-click → "Fix Code Issues"

🤖 Supported Models

Code Completion Models

Model	Size	Speed (CPU)	Speed (GPU)	Quality	Use Case
`qwen2:0.5b`	300MB	3-5s	0.5-1s	⭐⭐⭐	Ultra-fast completion
`tinyllama:1.1b`	637MB	4-7s	1-2s	⭐⭐⭐⭐	Recommended balance
`qwen2.5-coder:1.5b`	900MB	6-10s	2-3s	⭐⭐⭐⭐⭐	High-quality completion
`codellama:7b-code`	3.8GB	15-30s	3-5s	⭐⭐⭐⭐⭐	Best quality (slow)

Chat & Explanation Models

Model	Size	Speed	Quality	Use Case
`codellama:7b-instruct`	3.8GB	5-15s	⭐⭐⭐⭐⭐	Recommended for chat
`deepseek-r1:7b`	7GB	30-60s	⭐⭐⭐⭐⭐	Complex reasoning
`llama3.1:8b`	4.7GB	10-20s	⭐⭐⭐⭐	General purpose

🔧 Troubleshooting

Common Issues

❌ "Cannot connect to Ollama"

# Check if Ollama is running
docker ps | grep ollama

# Start Ollama if not running
docker start ollama

# Test connection
curl http://localhost:11434/api/tags

❌ "Model not found"

# List available models
docker exec -it ollama ollama list

# Pull missing model
docker exec -it ollama ollama pull tinyllama:1.1b

❌ "Completion timeout"

Increase timeout: Set aiDevAgent.codeCompletion.timeoutMs to 10000
Use faster model: Switch to qwen2:0.5b
Check Docker resources: Allocate 4GB+ memory to Docker

❌ "Code completion not working"

Check model is loaded: docker exec -it ollama ollama ps
Verify settings: Ensure aiDevAgent.codeCompletion.enabled is true
Restart extension: Ctrl+Shift+P → "Developer: Reload Window"

Performance Optimization

🚀 GPU Acceleration (NVIDIA)

# Stop current container
docker stop ollama && docker rm ollama

# Start with GPU support
docker run -d --gpus all -v ollama:/root/.ollama -p 11434:11434 --name ollama ollama/ollama

# Verify GPU usage
nvidia-smi  # Should show GPU activity during completion

💾 Memory Optimization

Docker Desktop: Settings → Resources → Memory (6GB+)
Keep models loaded: Set aiDevAgent.keepAlive to "-1"
Use smaller models: qwen2:0.5b for resource-constrained systems

🌍 Language Support

Fully Supported Languages:

JavaScript/TypeScript
Python
Java
C#
Go
Rust
C/C++
PHP
Ruby
Swift
Kotlin

Partial Support:

HTML/CSS
SQL
Shell/Bash
Markdown
JSON/YAML

🤝 Contributing

We welcome contributions! Please see our Contributing Guide.

Development Setup

# Clone repository
git clone https://github.com/hariprasathys22/AI-Agent.git
cd AI-Agent

# Install dependencies
npm install

# Build extension
npm run compile

# Test extension
# Press F5 in VS Code to open Extension Development Host

Submitting Issues

🐛 Bug reports: Create issue
💡 Feature requests: Create issue
❓ Questions: GitHub Discussions

📈 Roadmap

Multi-file context - Understand project structure
Jupyter Notebook support - AI assistance in notebooks
Git integration - Smart commit messages and PR descriptions
Custom model training - Fine-tune on your codebase
Collaborative features - Team model sharing
More languages - Expand language support

📊 Comparison

Feature	AI Dev Agent	GitHub Copilot	TabNine	CodeWhisperer
Privacy	✅ 100% Local	❌ Cloud-based	❌ Cloud-based	❌ Cloud-based
Cost	✅ Free	❌ $10/month	❌ $12/month	✅ Free tier
Offline	✅ Yes	❌ No	❌ No	❌ No
GPU Support	✅ Yes	N/A	N/A	N/A
Custom Models	✅ Yes	❌ No	❌ No	❌ No
Chat Interface	✅ Yes	✅ Yes	❌ No	❌ No
Code Actions	✅ Yes	❌ Limited	❌ No	❌ Limited

📄 License

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

🙏 Acknowledgments

Ollama - For providing the local AI runtime
VS Code team - For the excellent extension API
Hugging Face - For open-source model hosting
Contributors - Thank you to all who have contributed!

📞 Support

📚 Documentation: GitHub Wiki
💬 Community: GitHub Discussions
🐛 Issues: GitHub Issues
🔄 Updates: Release Notes

⭐ If this extension helps you code faster, please star the repository!

Made with ❤️ for developers who value privacy and performance

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src		src
.gitignore		.gitignore
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CONTRIBUTING.md		CONTRIBUTING.md
LICENSE.md		LICENSE.md
README.md		README.md
package-lock.json		package-lock.json
package.json		package.json
tsconfig.json		tsconfig.json
webpack.config.js		webpack.config.js

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hariprasathys22/AI-Agent

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🤖 AI Developer Agent

✨ Features

🤖 GitHub Copilot-Style Code Completion

💬 Interactive AI Chat

🧪 Smart Code Actions

🔒 Privacy & Performance

🚀 Quick Start

1. Install Ollama (AI Runtime)

2. Pull AI Models

3. Install Extension

4. Configure Settings

5. Start Coding!

⚙️ Configuration

🔧 Essential Settings

⚡ Performance Settings

🚀 Optimized Configurations

🎮 Usage

Code Completion

AI Chat Interface

Code Actions (Right-click menu)

🤖 Supported Models

Code Completion Models

Chat & Explanation Models

🔧 Troubleshooting

Common Issues

Performance Optimization

🌍 Language Support

🤝 Contributing

Development Setup

Submitting Issues

📈 Roadmap

📊 Comparison

📄 License

🙏 Acknowledgments

📞 Support

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