AI Code Assistant (Offline) 2026 🧠 💻

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📋 Table of Contents

• 📖 About
• ⚙️ Requirements
• ✨ Features
• 🔧 Configuration
• 💻 CLI Usage
• 📦 Installation
• 📊 Compatibility
• ❓ FAQ
• 💬 Community & Support
• 📜 License
• ⚠️ Disclaimer

📖 About

AI Code Assistant (Offline) is a local-first, privacy-focused code completion and refactoring tool for developers. Powered by a quantized 7B LLM running entirely on your machine, it provides intelligent suggestions without cloud dependency. Ideal for air-gapped environments, sensitive codebases, or latency-sensitive workflows.

⚙️ Requirements

• Windows 10/11 (64-bit)
• 16GB RAM (32GB recommended for optimal performance)
• 8GB free disk space (SSD preferred)
• NVIDIA GPU with CUDA 12.2+ (optional but highly recommended)
• No internet required after initial download

✨ Features

1. Local LLM Inference 🔧 — Runs a quantized 7B parameter model entirely offline with 4-bit precision. No API calls, no telemetry.
2. Multi-Language Support 🔧 — Native support for Python, JavaScript, TypeScript, Java, C++, Go, Rust, and C# with language-aware completions.
3. Context-Aware Suggestions 🔧 — Understands project structure, imports, and recent edits to provide relevant completions (up to 128k context window).
4. Privacy-Preserving 🔧 — All data stays on your machine. No cloud processing, no data logging.
5. Custom Model Support 🔧 — Import GGUF/GGML models or fine-tune with your own dataset (via CLI).
6. IDE Integration 🔧 — Plugins for VS Code, JetBrains (IntelliJ, PyCharm), and Neovim with real-time suggestions.
7. Static Analysis 🔧 — Detects anti-patterns, security vulnerabilities, and performance bottlenecks in real-time.
8. Offline Documentation 🔧 — Bundled docs for Python, JavaScript, and C++ with instant lookup (no internet required).

🔧 Configuration

Configure via config.json (auto-generated on first launch):

{
  "model": {
    "path": "models/codellama-7b.Q4_K_M.gguf",
    "gpu_layers": 40,
    "context_length": 128000
  },
  "completion": {
    "max_tokens": 128,
    "temperature": 0.2,
    "top_p": 0.95
  },
  "ide": {
    "vscode": {
      "enabled": true,
      "hotkey": "Ctrl+Alt+C"
    },
    "jetbrains": {
      "enabled": false
    }
  }
}

💻 CLI Usage

# Start the local inference server (default port: 8080)
aica-server --model models/codellama-7b.Q4_K_M.gguf --gpu-layers 40

# Generate completions (REST API)
curl -X POST http://localhost:8080/v1/completions \
  -H "Content-Type: application/json" \
  -d '{"prompt": "def fibonacci(n):", "max_tokens": 50}'

📦 Installation

1. Go to the Releases page and download the latest version.
2. Extract the archive using 7-Zip or WinRAR.
3. Run the executable as Administrator.
4. Follow the on-screen setup steps (model download may take 5-10 minutes).
5. Launch your IDE and enable the plugin.

📊 Compatibility

OS	Version	Status	Notes
Windows 11	22H2+	✅	Best performance
Windows 10	1909+	✅	Requires latest updates
Windows 7	SP1	⚠️	Limited GPU support
Linux	WSL2	⚠️	Experimental (no GPU passthrough)
macOS	-	❌	Not supported

❓ FAQ

Q: Is this detectable by IDEs or anti-virus? A: The tool runs as a local process with no network calls after setup. Detection risk is minimal if used responsibly (avoid automated mass refactoring in sensitive environments).

Q: How often are models updated? A: New model versions are released quarterly. Check Releases for updates.

Q: I get "CUDA out of memory" errors. What should I do? A: Reduce gpu_layers in config.json or use a smaller model (e.g., 3B parameter variant).

💬 Community & Support

• Report a Bug
• Request a Feature

📜 License

MIT License. Copyright (c) 2026 AI Code Assistant (Offline) Contributors.

⚠️ Disclaimer

This tool is for educational and development purposes only. The developers are not responsible for any misuse or damage caused by this software. Use at your own risk.