🦀 Rust TUI Coder

A powerful terminal-based coding assistant that brings AI intelligence directly to your command line

📖 Documentation • 🚀 Quick Start • 🛠️ Features • 🤝 Contributing

🌟 What is Rust TUI Coder?

Rust TUI Coder is a revolutionary terminal-based AI assistant that seamlessly blends the power of modern large language models with an intuitive, keyboard-driven interface. Designed for developers who live in the terminal, it provides an interactive environment where you can:

🚀 Core Capabilities

💬 Chat naturally with AI about your code and projects
🔧 Execute tools to manipulate files, run commands, and manage your workspace
📊 Monitor progress with real-time tool execution logs
🎨 Enjoy a beautiful TUI built with modern Rust technologies

🎯 Why Choose Rust TUI Coder?

For Terminal Power Users

If you spend most of your development time in the terminal, Rust TUI Coder eliminates the constant context switching between your terminal workflow and web-based AI assistants. Keep your hands on the keyboard and your mind in the flow.

For AI-Assisted Development

Experience true AI-assisted development with real-time tool execution. Instead of copy-pasting code snippets, let the AI directly manipulate your files, run commands, and manage your project structure while you watch the progress in real-time.

For Privacy-Conscious Developers

Run local models for complete privacy and security. Your code and conversations never leave your machine, giving you full control over your development environment and intellectual property.

🔄 Workflow Transformation

Before: Traditional AI-Assisted Development

1. Write code in editor
2. Switch to web browser
3. Copy code to AI assistant
4. Get suggestions
5. Copy suggestions back
6. Switch back to editor
7. Apply changes manually

After: Integrated AI Development

1. Type request in Rust TUI Coder
2. AI understands context automatically
3. Tools execute in real-time
4. See results instantly
5. Continue conversation seamlessly

🌟 Key Differentiators

Feature	Rust TUI Coder	Web AI Assistants	IDE Extensions
Terminal Integration	✅ Native	❌ Browser-based	🟡 Partial
Direct File Access	✅ Full filesystem	❌ Copy/paste only	🟡 IDE scope only
Real-time Tool Execution	✅ Live monitoring	❌ None	🟡 Limited
Context Preservation	✅ Persistent sessions	🟡 Per conversation	🟡 Per file
Offline Capability	✅ Local models	❌ Requires internet	❌ Requires internet
Keyboard Workflow	✅ Full keyboard	🟡 Mouse required	🟡 Mixed
Customization	✅ Extensive	🟡 Limited	🟡 Extension scope
Privacy	✅ Full control	❌ Cloud storage	🟡 Vendor dependent

💡 Perfect For

🚀 Rapid Prototyping: Turn ideas into working code instantly
🐛 Debugging: Get AI assistance without leaving your terminal
📚 Learning: Interactive coding tutorials with immediate feedback
🛠️ DevOps Automation: System administration and deployment scripts
📝 Documentation: Auto-generate comprehensive project documentation
🔄 Code Refactoring: Bulk operations across entire codebases
🏗️ Project Setup: Automated scaffolding and configuration
🔍 Code Analysis: Deep insights into large codebases

🎨 Built for Performance

Powered by Rust's legendary performance characteristics:

⚡ Lightning-fast startup (<2 seconds)
🧠 Minimal memory footprint (50-200MB)
🔄 Real-time responsiveness (<100ms UI updates)
🛡️ Memory safe (no garbage collection pauses)
📦 Single binary deployment (no runtime dependencies)

🌍 Ecosystem Integration

Seamlessly integrates with your existing development ecosystem:

🔧 Version Control: Git-aware file operations
📦 Package Managers: Cargo, npm, pip, apt integration
🛠️ Build Systems: Support for all major build tools
☁️ Cloud Platforms: AWS, GCP, Azure CLI integration
🐳 Containerization: Docker and Kubernetes support
📊 Databases: SQL and NoSQL database operations

🚀 Getting Started in 60 Seconds

# Install Rust (if not already installed)
curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh

# Clone and build
git clone https://github.com/ammar-alnagar/rust-tui-coder.git
cd rust-tui-coder
cargo build --release

# Configure your API key
cp config_example.toml config.toml
# Edit config.toml with your API key

# Launch the application
./target/release/rust_tui_coder

That's it! You're now ready to experience AI-assisted development like never before.

📸 Screenshots

Interactive Conversation & File Operations

The main interface showing a conversation where the agent creates a file and executes tools. Notice the organized layout with conversation history, tool logs, input area, and status display.

Tool System Overview

The agent demonstrating all available tools including file operations, code execution, and directory management. The tool logs panel shows real-time execution feedback.

✨ Key Features

🖥️ Terminal User Interface

Experience a modern, keyboard-driven interface designed for power users:

Feature	Description
🎨 Modern TUI Design	Built with `ratatui` - responsive, beautiful, and lightning-fast
📱 Multi-Panel Layout	4 dedicated panels: conversation, tool logs, input area, and status
📜 Smart Scrolling	Auto-scrolls to latest messages with manual control available
📝 Intelligent Text Wrapping	Preserves formatting and readability across different terminal sizes
🎭 Syntax Highlighting	Color-coded messages for users, agents, and system outputs
⌨️ Keyboard-First	Full keyboard navigation with intuitive shortcuts

🤖 AI Integration

Seamlessly integrate with leading AI providers:

Provider	Models Supported	Key Features
OpenAI	GPT-4, GPT-3.5-Turbo	Industry-leading reasoning and code generation
Anthropic	Claude 3 (Opus, Sonnet, Haiku)	Exceptional safety and long-context understanding
Local/Custom	Any OpenAI-compatible API	Self-hosted models, custom deployments

🔄 Persistent Conversations: Maintains full context throughout your session
⚡ Real-time Streaming: Watch responses appear as they're generated
🛡️ Robust Error Handling: Graceful fallbacks and informative error messages
🎯 Model Auto-Detection: Automatically selects optimal models when available
📊 Usage Tracking: Monitor token usage, request counts, and tool executions

🛠️ Tool System

A comprehensive toolkit that turns natural language into executable actions:

📁 File & Directory Operations

Tool	Purpose	Use Case
`READ_FILE`	Display file contents with line numbers	Code review, debugging, documentation
`WRITE_FILE`	Create/modify files with auto directory creation	Code generation, configuration files
`APPEND_FILE`	Add content to existing files	Log files, documentation updates
`REPLACE_IN_FILE`	Search and replace text with regex support	Refactoring, bulk edits
`DELETE_FILE`	Safe file/directory removal	Cleanup, project maintenance
`LIST_FILES`	Browse directory contents	Project exploration, file discovery
`LIST_FILES_RECURSIVE`	Deep directory traversal	Finding files across large projects
`CREATE_DIRECTORY`	Create directory structures	Project setup, organization
`COPY_PATH`	Duplicate files/directories	Backup, template creation
`MOVE_PATH`	Relocate files/directories	Project restructuring

⚡ Code Execution & System Integration

Tool	Purpose	Capabilities
`EXECUTE_CODE`	Run code in multiple languages	Python, JavaScript, Rust, Go, and more
`RUN_COMMAND`	Execute shell commands	Build processes, testing, deployment
`SEARCH_TEXT`	Find text patterns with regex	Code search, debugging, analysis

🔧 Advanced Features

🔄 Retry Logic: Automatic retries with configurable limits
✅ Post-Write Verification: Ensures file changes are applied correctly
📁 Workspace Awareness: Context-aware file operations
🛡️ Safe Execution: Sandboxed command execution with output capture
📊 Real-time Monitoring: Live tool execution feedback

⚙️ Configuration

Flexible configuration system designed for different environments:

Feature	Benefit
📄 TOML Configuration	Human-readable, version-controllable settings
🔐 Secure Credentials	Multiple ways to manage API keys safely
🌍 Environment Variables	Easy deployment across different systems
🔧 Runtime Configuration	Change settings without restarting
📋 Validation	Automatic validation with helpful error messages

🚀 Getting Started

📋 Prerequisites

Before installing Rust TUI Coder, ensure your system meets these requirements:

System Requirements

Component	Minimum	Recommended	Notes
Operating System	Linux, macOS, Windows	Linux/macOS	Full TUI support on Unix-like systems
CPU	1 GHz dual-core	2+ GHz quad-core	For responsive UI interactions
RAM	2 GB	4 GB+	LLM responses require memory
Storage	100 MB	500 MB	For dependencies and cached data
Terminal	Modern Unicode terminal	Alacritty, iTerm2, Windows Terminal	Full color and Unicode support required

Software Dependencies

Dependency	Version	Installation	Purpose
Rust	1.70+	`curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs \| sh`	Core language and toolchain
Cargo	Latest	Included with Rust	Package manager and build tool
Git	2.0+	`apt/yum/brew install git`	Repository cloning

LLM Provider Access

Choose one of the supported AI providers:

Provider	Setup Required	Cost	Best For
OpenAI	API key + credits	Paid	Production use, reliability
Anthropic	API key + credits	Paid	Safety, long contexts
Local Models	Ollama/Local server	Free	Privacy, offline use

⚡ Quick Installation

Option 1: Direct Download (Recommended)

# Download and extract the latest release
curl -L https://github.com/ammar-alnagar/rust-tui-coder/releases/latest/download/rust-tui-coder.tar.gz | tar xz
cd rust-tui-coder

# Make executable and run setup
chmod +x rust-tui-coder
./rust-tui-coder --setup

Option 2: Build from Source

# Clone the repository
git clone https://github.com/ammar-alnagar/rust-tui-coder.git
cd rust-tui-coder

# Build optimized release version
cargo build --release

# Optional: Install globally
cargo install --path .

Option 3: Development Setup

# Clone with submodules (if any)
git clone --recursive https://github.com/ammar-alnagar/rust-tui-coder.git
cd rust-tui-coder

# Run in development mode
cargo run

🔧 Configuration Setup

1. Initial Configuration

# Copy the example configuration
cp config_example.toml config.toml

# Edit with your preferred editor
nano config.toml  # or vim, code, etc.

2. LLM Provider Configuration

For OpenAI:

[llm]
api_key = "sk-your-openai-api-key-here"
api_base_url = "https://api.openai.com/v1"
model_name = "gpt-4-turbo-preview"  # or gpt-3.5-turbo

For Anthropic:

[llm]
api_key = "sk-ant-your-anthropic-key-here"
api_base_url = "https://api.anthropic.com/v1"
model_name = "claude-3-sonnet-20240229"

For Local/Ollama:

[llm]
api_key = "not-needed"
api_base_url = "http://localhost:11434/v1"
model_name = "codellama:34b"  # or any local model

3. Advanced Configuration

[llm]
# Basic settings
api_key = "your-api-key"
api_base_url = "https://api.openai.com/v1"
model_name = "gpt-4"

# Performance tuning
max_tokens = 4000
temperature = 0.7
timeout_seconds = 30

# Tool system settings
max_attempts = 12
workspace_root = "/path/to/your/projects"
shell = "zsh"  # or bash, fish
post_write_verify = true

# UI preferences
theme = "dark"
font_size = 12

4. Environment Variables (Alternative)

# Set environment variables instead of config file
export LLM_API_KEY="sk-your-api-key"
export LLM_API_BASE_URL="https://api.openai.com/v1"
export LLM_MODEL_NAME="gpt-4"
export LLM_MAX_TOKENS="4000"

🧪 Verification

# Test your installation
cargo run -- --version

# Test LLM connection
cargo run -- --test-connection

# Launch the application
cargo run --release

🎯 First Run Experience

Launch: cargo run --release
Welcome Screen: Review the welcome message
First Command: Try /help to see available commands
Sample Interaction: Type "Hello! Can you help me with Rust development?"
Tool Discovery: Ask "What tools do you have available?"

💡 Pro Tip: Start with simple requests like file reading or basic questions to get familiar with the interface.

📖 Usage Guide

🎯 Basic Operation

Interface Overview

┌─────────────────────────────────────────────────┐
│ Conversation Panel                              │
│ User: Hello!                                    │
│ Agent: Hi there! How can I help you today?      │
├─────────────────────────────────────────────────┤
│ Tool Logs Panel                                 │
│ ✓ Executing LIST_FILES                          │
│ ✓ Success: Found 15 files                       │
├─────────────────────────────────────────────────┤
│ Input Panel                                     │
│ > Type your message here...                     │
├─────────────────────────────────────────────────┤
│ Status Panel                                    │
│ Ready | Tokens: 1,247 | Tools: 3                │
└─────────────────────────────────────────────────┘

Core Commands

Command	Description	Example
Regular Message	Chat naturally with AI	"Help me debug this Rust code"
`/quit`	Exit gracefully with summary	`/quit`
`/stats`	Show usage statistics	`/stats`
`/help`	Display available commands	`/help`
`/clear`	Clear conversation history	`/clear`

💡 Example Workflows

🌟 Getting Started Examples

1. Simple File Operations

You: Can you create a simple Rust "Hello World" program?

Agent: I'd be happy to create a Rust Hello World program for you! I'll create a new file called `hello.rs` with a basic Rust program.

[Tool Logs: ✓ WRITE_FILE executed successfully]
       ✓ File created: hello.rs (23 bytes)

Agent: Perfect! I've created `hello.rs` with a simple Hello World program. Would you like me to:
1. Show you the contents of the file?
2. Compile and run it for you?
3. Explain what each part of the code does?

2. Code Analysis & Debugging

You: I have a bug in my Rust code. Can you help me find it?

Agent: I'd be happy to help you debug your Rust code! Could you please:
1. Share the file path to your Rust code
2. Describe what the code is supposed to do
3. Tell me what error or unexpected behavior you're seeing

You: The file is src/main.rs and I'm getting a compilation error

Agent: Let me read your main.rs file to see what's causing the compilation error.

[Tool Logs: ✓ READ_FILE executed successfully]
       ✓ Reading: src/main.rs (156 lines)

Agent: I can see the issue! You're trying to use `unwrap()` on a `Result` that might be an error. This is on line 23. Here's what I recommend...

🚀 Advanced Workflows

3. Project Setup Automation

You: Set up a new Rust web project with Axum and SQLx

Agent: I'll help you set up a complete Rust web project with Axum and SQLx. This will involve:

1. Creating the project structure
2. Setting up Cargo.toml with dependencies
3. Creating basic application files
4. Setting up database configuration

Let me start by creating the project structure...

[Tool Logs: ✓ CREATE_DIRECTORY executed successfully]
       ✓ Created: src/, migrations/, templates/
       ✓ WRITE_FILE executed successfully]
       ✓ Created: Cargo.toml with Axum, SQLx, Tokio
       ✓ Created: src/main.rs with basic web server
       ✓ Created: src/database.rs for DB connections

Agent: Great! I've set up your Rust web project structure. Here's what I've created:

📁 Project Structure:
├── Cargo.toml (Axum, SQLx, Tokio dependencies)
├── src/
│   ├── main.rs (Basic Axum server setup)
│   └── database.rs (SQLx connection handling)
└── migrations/ (For database schema changes)

Would you like me to:
1. Add more routes to your web server?
2. Set up authentication?
3. Create database models?

4. Code Refactoring

You: Help me refactor this Python script to use classes instead of functions

Agent: I'll help you refactor your Python script to use object-oriented principles. First, let me read the current file to understand its structure.

[Tool Logs: ✓ READ_FILE executed successfully]
       ✓ Reading: script.py (89 lines)

Agent: I can see your script has several functions that would benefit from being organized into classes. Here's my refactoring plan:

1. Create a `DataProcessor` class for data operations
2. Create a `FileHandler` class for file I/O
3. Create a `ReportGenerator` class for output formatting

Let me implement this refactoring...

[Tool Logs: ✓ REPLACE_IN_FILE executed successfully]
       ✓ Refactored: script.py (112 lines)
       ✓ Added classes: DataProcessor, FileHandler, ReportGenerator

Agent: Perfect! I've successfully refactored your Python script into a well-organized object-oriented structure. The new code is:

- More maintainable and extensible
- Better separation of concerns
- Easier to test individual components
- Follows Python best practices

Would you like me to explain the changes or help you write unit tests for the new classes?

5. System Administration

You: Set up a development environment on this Linux server

Agent: I'll help you set up a comprehensive development environment. Let me check what's already installed and then install the necessary tools.

[Tool Logs: ✓ RUN_COMMAND executed successfully]
       ✓ Checked: Current system (Ubuntu 22.04)
       ✓ RUN_COMMAND executed successfully]
       ✓ Installed: curl, wget, git, vim, htop

Agent: Good! I've installed the basic development tools. Now let me set up:

1. Node.js and npm for JavaScript development
2. Python development environment
3. Docker for containerization
4. Rust toolchain
5. Development directories and configurations

[Tool Logs: ✓ RUN_COMMAND executed successfully]
       ✓ Installed: Node.js 18.x, Python 3.10, Docker
       ✓ Installed: Rust 1.70+ stable toolchain

Agent: Excellent! Your development environment is now set up with:

✅ Node.js 18.x + npm
✅ Python 3.10 + pip
✅ Docker + docker-compose
✅ Rust 1.70+ toolchain
✅ Essential development tools (git, vim, htop, curl)

Would you like me to:
1. Set up a sample project to test everything?
2. Configure your shell environment?
3. Install additional development tools?

🔧 Specialized Use Cases

6. Documentation Generation

You: Generate comprehensive documentation for my Rust project

Agent: I'll create thorough documentation for your Rust project by:
1. Reading the source code structure
2. Generating API documentation
3. Creating usage examples
4. Writing a README with setup instructions

Let me start by exploring your project structure...

[Tool Logs: ✓ LIST_FILES_RECURSIVE executed successfully]
       ✓ Found: 23 Rust files, 5 config files
       ✓ READ_FILE executed successfully]
       ✓ Analyzed: src/lib.rs, src/main.rs

Agent: Based on my analysis, I'll create:
1. Comprehensive README.md
2. API documentation comments
3. Usage examples
4. Contributing guidelines

[Tool Logs: ✓ WRITE_FILE executed successfully]
       ✓ Created: README.md (450 lines)
       ✓ WRITE_FILE executed successfully]
       ✓ Created: docs/API.md (320 lines)
       ✓ WRITE_FILE executed successfully]
       ✓ Created: examples/ (with 5 example files)

Agent: Documentation generation complete! I've created:
- 📖 Detailed README with setup and usage
- 📚 API documentation for all public functions
- 💡 5 practical examples with explanations
- 🤝 Contributing guidelines for the project

⌨️ Keyboard Controls

Basic Navigation

Key	Action	Context
Enter	Send message	Input panel
Backspace	Delete character	Input panel
Tab	Auto-complete	Input panel
↑/↓	Navigate history	Input panel

Advanced Controls

Key Combination	Action	Description
Ctrl+C	Emergency exit	Force quit application
Ctrl+L	Clear screen	Refresh display
Ctrl+R	Search history	Find previous messages
Ctrl+Z	Suspend	Background process (Unix only)

Special Commands

Command	Purpose	Example
`/quit`	Graceful exit with summary	`/quit`
`/stats`	Show usage statistics	`/stats`
`/clear`	Clear conversation	`/clear`
`/help`	Show available commands	`/help`
`/save`	Save conversation to file	`/save discussion.txt`
`/load`	Load conversation from file	`/load previous_session.txt`

🎨 Interface Customization

Color Themes

# Set theme via environment variable
export RUST_TUI_CODER_THEME="dark"  # or "light", "auto"

# Or via config file
[ui]
theme = "dark"
syntax_highlighting = true

Layout Options

[ui]
# Panel proportions (must sum to 100)
conversation_panel = 60
tool_logs_panel = 20
input_panel = 10
status_panel = 10

# Text display options
word_wrap = true
show_line_numbers = true
max_display_width = 120

🏗️ Architecture

Rust TUI Coder follows a clean, modular architecture designed for maintainability and extensibility:

┌─────────────────┐    ┌─────────────────┐    ┌─────────────────┐
│    main.rs      │───▶│     app.rs      │◀───│     ui.rs       │
│                 │    │                 │    │                 │
│ • Entry point   │    │ • State mgmt    │    │ • UI rendering  │
│ • TUI setup     │    │ • Event loop    │    │ • Layout mgmt   │
│ • Config load   │    │ • User input    │    │ • Styling       │
└─────────────────┘    └─────────────────┘    └─────────────────┘
         │                       ▲
         │                       │
         ▼                       │
┌─────────────────┐    ┌─────────────────┐
│   config.rs     │    │    agent.rs     │
│                 │    │                 │
│ • TOML parsing  │    │ • Tool system   │
│ • Settings mgmt │    │ • LLM interface │
│ • Validation    │    │ • Task exec     │
└─────────────────┘    └─────────────────┘
                                │
                                │
                                ▼
                       ┌─────────────────┐
                       │     llm.rs      │
                       │                 │
                       │ • HTTP client   │
                       │ • API requests  │
                       │ • Response parse│
                       │ • Error handling│
                       └─────────────────┘

Module Responsibilities

Module	Purpose	Key Features
main.rs	Application entry point	Terminal setup, event loop, graceful shutdown
app.rs	State management	Conversation history, user input, tool logs
ui.rs	User interface	Multi-panel layout, scrolling, text formatting
config.rs	Configuration handling	TOML parsing, validation, defaults
agent.rs	AI agent logic	Tool definitions, execution, LLM communication
llm.rs	LLM communication	HTTP requests, response parsing, error handling

🔧 Configuration Reference

Complete Configuration Example

[llm]
# Your API key for the LLM provider
api_key = "sk-..."

# Base URL for the API endpoint
api_base_url = "https://api.openai.com/v1"

# Model name to use for completions
model_name = "gpt-4"

# Optional: Additional settings (future expansion)
# max_tokens = 4000
# temperature = 0.7
# timeout_seconds = 30

Environment Variables (Alternative)

You can also use environment variables instead of the config file:

export LLM_API_KEY="your-api-key"
export LLM_API_BASE_URL="https://api.openai.com/v1"
export LLM_MODEL_NAME="gpt-4"

🛠️ Development

🚀 Getting Started with Development

Development Environment Setup

Clone the repository:

git clone https://github.com/ammar-alnagar/rust-tui-coder.git
cd rust-tui-coder

Set up development tools:

# Install development dependencies
cargo install cargo-watch cargo-expand cargo-udeps cargo-audit

# Optional: Install additional tools
cargo install cargo-tarpaulin cargo-nextest

Verify your setup:

# Check Rust version
rustc --version
cargo --version

# Run initial build
cargo check

# Run tests to ensure everything works
cargo test

🏗️ Build System

Build Profiles

Profile	Command	Use Case	Optimizations
Debug	`cargo build`	Development	None, fast compilation
Release	`cargo build --release`	Production	Full optimizations
Dev Optimized	`cargo build --profile dev-optimized`	Fast development	Some optimizations

Advanced Build Options

# Build with specific features
cargo build --features "additional-tools"

# Build for different targets
cargo build --target x86_64-unknown-linux-gnu
cargo build --target aarch64-apple-darwin

# Cross-compilation (requires cross)
cross build --target armv7-unknown-linux-gnueabihf --release

Development Workflow

# Watch mode for continuous rebuilding
cargo watch -x check

# Run tests on file changes
cargo watch -x test

# Format and lint on save
cargo watch -x 'fmt && clippy'

# Full development cycle
cargo watch -x 'check && test && fmt && clippy'

🧪 Testing

Test Categories

Test Type	Command	Coverage	Speed
Unit Tests	`cargo test`	Individual functions	⚡ Fast
Integration Tests	`cargo test --test integration`	Module interactions	🟡 Medium
End-to-End Tests	`cargo test --test e2e`	Full workflows	🟡 Medium
Benchmark Tests	`cargo bench`	Performance	🐌 Slow

Testing Commands

# Run all tests
cargo test

# Run specific test
cargo test test_name

# Run tests with output
cargo test -- --nocapture

# Run only integration tests
cargo test --test integration

# Run tests for specific module
cargo test --package rust_tui_coder --lib agent

# Generate coverage report (requires tarpaulin)
cargo tarpaulin --out Html --output-dir coverage/

# Run benchmarks
cargo bench

🔧 Code Quality

Linting & Formatting

# Format code
cargo fmt

# Run clippy lints
cargo clippy

# Fix auto-fixable issues
cargo clippy --fix

# Check for unused dependencies
cargo udeps

# Security audit
cargo audit

📚 Architecture & Code Organization

Module Structure

src/
├── main.rs          # Application entry point
├── app.rs           # State management
├── ui.rs            # Terminal user interface
├── agent.rs         # AI agent and tool system
├── llm.rs           # LLM API communication
└── config.rs        # Configuration handling

Key Design Patterns

State Management
- Central App struct for application state
- Immutable updates with builder pattern
- Event-driven architecture
Error Handling
- Custom error types with thiserror
- Proper error propagation with anyhow
- User-friendly error messages
Async Programming
- tokio for async runtime
- Structured concurrency patterns
- Proper cancellation handling
Configuration Management
- TOML-based configuration
- Environment variable support
- Runtime configuration reloading

🛠️ Tool Development

Adding New Tools

Define the tool function:

async fn my_custom_tool(args: HashMap<String, Value>) -> Result<String, Box<dyn Error>> {
    // Tool implementation
    let path = args.get("path").ok_or("Missing 'path' argument")?;
    // ... tool logic ...
    Ok(format!("Tool executed successfully on {}", path))
}

Register the tool:

impl Agent {
    pub fn register_tools(&mut self) {
        self.tools.insert("my_custom_tool".to_string(), my_custom_tool);
    }
}

Tool Best Practices

Input Validation: Always validate input parameters
Error Handling: Provide clear, actionable error messages
Idempotency: Tools should be safe to run multiple times
Logging: Use appropriate log levels for different operations
Performance: Consider async operations for I/O-bound tasks
Security: Validate file paths and command arguments

🤝 Contributing Guidelines

Development Workflow

Choose an issue from the issue tracker

Create a feature branch:

git checkout -b feature/amazing-feature
# or
git checkout -b fix/bug-description

Make your changes following the established patterns
Write tests for new functionality
Update documentation if needed
Run quality checks:
```
cargo fmt && cargo clippy && cargo test
```

Commit your changes:

git commit -m "feat: add amazing new feature

- What was changed
- Why it was changed
- How it was implemented"

Code Standards

Rust Idioms:

Use snake_case for variables and functions
Use PascalCase for types and traits
Prefer &str over &String for function parameters
Use Result<T, E> for error handling
Implement Debug and Clone where appropriate

Documentation:

Add doc comments to all public APIs
Include examples in documentation
Document error conditions and edge cases
Keep README and docs up to date

Testing:

Write tests for all new functionality
Include both positive and negative test cases
Test error conditions and edge cases
Aim for >80% code coverage

📦 Dependencies

Core Dependencies

Crate	Version	Purpose	License
`ratatui`	0.26.0	Terminal UI framework	MIT
`crossterm`	0.27.0	Terminal manipulation	MIT
`tokio`	1.35.1	Async runtime	MIT
`reqwest`	0.11.23	HTTP client	MIT/Apache-2.0
`serde`	1.0.195	Serialization	MIT/Apache-2.0
`serde_json`	1.0.111	JSON handling	MIT/Apache-2.0
`toml`	0.8.8	TOML parsing	MIT/Apache-2.0
`anyhow`	1.0.75	Error handling	MIT/Apache-2.0
`thiserror`	1.0.50	Error types	MIT/Apache-2.0

🔍 Troubleshooting

Common Issues & Solutions

🚫 Build & Compilation Issues

Issue: "error[E0658]: use of unstable library feature"

error[E0658]: use of unstable library feature `async_fn_in_trait`

Solution:

# Update Rust toolchain to latest stable
rustup update stable
rustup default stable

# Or use a specific nightly version that supports the features
rustup install nightly-2024-01-01
rustup override set nightly-2024-01-01

Issue: "failed to select a version for the requirement ratatui = "^0.26.0""

error: failed to select a version for the requirement `ratatui = "^0.26.0"`

Solution:

# Update Cargo index
cargo update

# Or clear Cargo cache and rebuild
rm -rf ~/.cargo/registry/cache/
rm -rf ~/.cargo/git/checkouts/
cargo clean
cargo build

🔧 Runtime Issues

Issue: "Permission denied" when running tools

Error: Permission denied (os error 13)

Solution:

# Check file permissions
ls -la target/release/rust_tui_coder

# Make executable if needed
chmod +x target/release/rust_tui_coder

# Or run with explicit permissions
sudo target/release/rust_tui_coder

Issue: Terminal displays garbled text or escape sequences

35;102;43M35;103;43M35;103;42M...

Solution:

# In config.toml, ensure mouse capture is disabled
[ui]
mouse_capture = false
raw_mode = true

Issue: "Connection refused" to LLM API

Error: Connection refused (os error 111)

Solution:

# Check network connectivity
curl -I https://api.openai.com/v1/models

# Verify API key and endpoint in config
cat config.toml | grep -E "(api_key|api_base_url)"

# Test with a simple curl command
curl -H "Authorization: Bearer YOUR_API_KEY" \
     -H "Content-Type: application/json" \
     https://api.openai.com/v1/models

🎨 Display & UI Issues

Issue: Interface appears broken or misaligned

Symptoms: Panels overlap, text wraps incorrectly, colors don't display

Solution:

# Check terminal capabilities
echo $TERM

# Force a compatible terminal type
export TERM=xterm-256color

# Test with a simpler terminal
# Or resize terminal window to at least 80x24 characters

Issue: Colors don't display correctly

Expected: Colored text and UI elements
Actual: Plain text only

Solution:

# Enable 256-color support
export TERM=xterm-256color

# Or force color output
export CLICOLOR_FORCE=1

# Check if terminal supports colors
tput colors

🔑 Configuration Issues

Issue: "No such file or directory" for config.toml

Error: No such file or directory (os error 2)

Solution:

# Copy the example configuration
cp config_example.toml config.toml

# Or create minimal config manually
cat > config.toml << EOF
[llm]
api_key = "your-api-key-here"
api_base_url = "https://api.openai.com/v1"
model_name = "gpt-4"
EOF

Issue: API key not recognized

Error: Invalid API key or unauthorized access

Solution:

# Check API key format
echo $LLM_API_KEY | head -c 10  # Should start with sk-

# Verify key in config file
grep api_key config.toml

# Test key with direct API call
curl -H "Authorization: Bearer YOUR_API_KEY" \
     https://api.openai.com/v1/models | jq .error

🔧 Tool Execution Issues

Issue: Tools fail with "command not found"

Error: bash: cargo: command not found

Solution:

# Check if command exists in PATH
which cargo

# Install missing tool
# For Rust: curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh
# For Node.js: curl -fsSL https://deb.nodesource.com/setup_18.x | sudo -E bash -
# For Python: sudo apt install python3 python3-pip

# Update PATH in shell profile
echo 'export PATH="$HOME/.cargo/bin:$PATH"' >> ~/.bashrc
source ~/.bashrc

Issue: File operations fail due to permissions

Error: Permission denied when writing to file

Solution:

# Check current directory permissions
pwd && ls -la

# Change to a directory with write permissions
cd ~/projects/

# Or fix permissions on current directory
chmod 755 .
chmod 644 *.rs  # for Rust files

🐛 Debugging Commands

Test LLM Connection

# Test basic connectivity
curl -H "Authorization: Bearer $LLM_API_KEY" \
     -H "Content-Type: application/json" \
     "$LLM_API_BASE_URL/models"

# Test with the application
cargo run -- --test-connection

Check System Resources

# Memory usage
free -h

# Disk space
df -h

# Network connectivity
ping -c 3 api.openai.com

Generate Debug Logs

# Run with debug logging
RUST_LOG=debug cargo run

# Or save logs to file
RUST_LOG=debug cargo run 2>&1 | tee debug.log

Reset Application State

# Clear all caches and temporary files
cargo clean
rm -rf target/
rm -f *.log

# Reset configuration
cp config_example.toml config.toml

📞 Getting Help

If you can't resolve an issue:

Check the Issues page for similar problems
Enable debug logging and share relevant logs

Provide system information:

uname -a
rustc --version
cargo --version
echo $TERM

Create a new issue with:
- Your operating system and version
- Rust version (rustc --version)
- Full error message and stack trace
- Steps to reproduce the issue
- Your config.toml (with API keys removed)

❓ FAQ

🤖 General Questions

Q: What is Rust TUI Coder? A: Rust TUI Coder is a terminal-based AI assistant that combines the power of modern language models with an intuitive keyboard-driven interface. It allows you to chat with AI while executing tools to manipulate files, run commands, and manage your development environment—all without leaving your terminal.

Q: How is this different from ChatGPT or GitHub Copilot? A: Unlike web-based AI assistants, Rust TUI Coder:

Keeps you in your terminal workflow
Provides real-time tool execution with visual feedback
Offers persistent conversations and project context
Enables direct file and system manipulation
Works offline with local models

Q: Is it free to use? A: The application itself is free and open-source. You only pay for the underlying LLM API usage (OpenAI, Anthropic, etc.) based on their pricing models.

Q: Can I use it offline? A: Yes! You can use local models via Ollama or other local LLM servers. Simply configure the api_base_url to point to your local instance.

🛠️ Technical Questions

Q: Which operating systems are supported? A: Linux (primary), macOS, and Windows (via WSL). Full TUI support requires a modern Unicode terminal.

Q: Which LLM providers are supported? A: OpenAI (GPT-4, GPT-3.5), Anthropic (Claude), and any OpenAI-compatible API (local models, custom deployments).

Q: Can I use my own API keys? A: Yes, the application supports API keys for all major providers and can read them from configuration files or environment variables.

Q: How much RAM do I need? A: Minimum 2GB, recommended 4GB+. Memory usage depends on the LLM model and conversation length.

Q: Can I customize the interface? A: Yes! You can customize colors, panel layouts, keyboard shortcuts, and more through the configuration file.

🔧 Usage Questions

Q: How do I exit the application? A: Type /quit and press Enter for a graceful exit with usage summary, or use Ctrl+C for emergency exit.

Q: Can I save my conversations? A: Yes, use /save filename.txt to save your conversation history to a file.

Q: What commands are available? A: Type /help in the application to see all available commands and tools.

Q: How do I clear the conversation? A: Use /clear to reset the conversation history while keeping the application running.

Q: Can I load previous conversations? A: Yes, use /load filename.txt to load a previously saved conversation.

🐛 Troubleshooting Questions

Q: Why do I see strange escape sequences? A: This usually happens when mouse capture is enabled but your terminal doesn't support it properly. Disable mouse capture in your config or use a different terminal.

Q: The interface looks broken in my terminal A: Try resizing your terminal to at least 80x24 characters, or set TERM=xterm-256color in your environment.

Q: Tools are failing with permission errors A: Check file permissions and ensure you're running the application with appropriate access to the directories you want to modify.

Q: API connection is failing A: Verify your API key, check your internet connection, and ensure your firewall isn't blocking the API endpoints.

Q: The application is slow A: Try using a smaller model, check your internet connection, or use a local model for better performance.

🛠️ Development Questions

Q: Can I contribute to the project? A: Absolutely! See the Contributing section below for guidelines on how to help improve Rust TUI Coder.

Q: How do I add new tools? A: Tools are defined in the agent module. Create a new tool function and add it to the tool registry following the existing patterns.

Q: Can I modify the UI layout? A: Yes, the UI is built with ratatui and can be customized in the ui.rs module.

Q: How do I add support for new LLM providers? A: Add a new case to the LLM client in llm.rs following the existing OpenAI/Anthropic patterns.

🤝 Contributing

We welcome contributions! Here's how you can help:

Fork the repository
Create a feature branch: git checkout -b feature/amazing-feature
Make your changes: Follow Rust best practices and add tests
Commit your changes: git commit -m 'Add amazing feature'
Push to the branch: git push origin feature/amazing-feature
Open a Pull Request

Development Guidelines

Follow Rust naming conventions and idioms
Add tests for new functionality
Update documentation for API changes
Ensure cargo clippy passes without warnings
Format code with cargo fmt

📈 Performance & Comparisons

🚀 Performance Benchmarks

System Requirements & Performance

Component	Minimum	Recommended	Performance Impact
CPU	1 GHz dual-core	2+ GHz quad-core	UI responsiveness, tool execution speed
RAM	2 GB	4 GB+	LLM response caching, concurrent operations
Network	10 Mbps	50+ Mbps	API response times, real-time streaming
Storage	100 MB	500 MB+	Dependencies, cached responses

Benchmark Results (Approximate)

Operation	Local Model	OpenAI GPT-4	Anthropic Claude
Simple Query	0.5-2s	2-5s	2-4s
Code Generation	1-3s	3-8s	3-7s
File Analysis	0.2-1s	1-3s	1-3s
Tool Execution	0.1-0.5s	0.1-0.5s	0.1-0.5s
UI Rendering	<0.1s	<0.1s	<0.1s

Benchmarks performed on Ubuntu 22.04 with 8GB RAM, 100Mbps internet

🔍 Feature Comparison

vs. ChatGPT Web Interface

Feature	Rust TUI Coder	ChatGPT Web
Terminal Integration	✅ Native	❌ Limited
File System Access	✅ Direct	❌ Manual copy/paste
Tool Execution	✅ Real-time	❌ None
Offline Capability	✅ Local models	❌ Requires internet
Keyboard Navigation	✅ Full keyboard	🟡 Mouse required
Customization	✅ Extensive	🟡 Limited
Privacy	✅ Local storage	❌ Cloud storage
Cost	🟡 API usage only	🟡 Subscription

vs. GitHub Copilot

Feature	Rust TUI Coder	GitHub Copilot
Interface	Terminal TUI	IDE integration
Language Support	All languages	IDE-supported languages
Context Awareness	Full project	Current file + tabs
Tool Integration	File system, commands	IDE features only
Conversation Memory	Persistent sessions	Per-file context
Offline Usage	✅ Local models	❌ Requires internet
Cost	API usage	Subscription

vs. Cursor/VS Code AI Extensions

Feature	Rust TUI Coder	Cursor/VS Code AI
Terminal Focus	✅ Dedicated	❌ IDE-centric
File Operations	✅ Direct manipulation	🟡 Through IDE
System Commands	✅ Full shell access	❌ Limited
Multi-file Editing	✅ Bulk operations	🟡 Sequential
Project Automation	✅ Script generation	🟡 Manual workflows
Resource Usage	🟡 Lightweight	🟡 IDE overhead

💰 Cost Analysis

API Usage Costs (Approximate monthly)

Usage Pattern	OpenAI GPT-4	Anthropic Claude	Local Models
Light (10 queries/day)	$5-15	$3-10	$0 (one-time setup)
Moderate (50 queries/day)	$25-75	$15-50	$0
Heavy (200+ queries/day)	$100-300	$60-200	$0

Total Cost of Ownership

Hardware Investment: $0-500 (if upgrading)
Software: $0 (free and open-source)
API Usage: $10-100/month (depending on usage)
Local Models: $0-50 one-time (optional GPU upgrade)

🏆 Strengths & Advantages

✅ Key Advantages

🏃‍♂️ Speed & Efficiency
- Lightning-fast TUI rendering (<100ms)
- Direct file system access (no copy/paste)
- Keyboard-driven workflow (no mouse required)
- Real-time tool execution feedback
🔒 Privacy & Security
- Local conversation storage
- No cloud dependency for basic features
- API keys stored locally
- Full control over data
🔧 Developer Experience
- Terminal-native workflow
- Seamless integration with existing tools
- Extensible architecture for custom tools
- Rust performance and reliability
💰 Cost Effectiveness
- Free application (open-source)
- Pay only for API usage
- Local models eliminate API costs entirely
- No subscription fees

🎯 Use Cases & Scenarios

Perfect For:

🚀 Rapid Prototyping: Quick project setup and file generation
🐛 Debugging: Code analysis with immediate file access
📚 Learning: Interactive coding tutorials and explanations
🛠️ DevOps: System administration and automation
📝 Documentation: Auto-generating project docs and READMEs
🔄 Refactoring: Bulk code changes across multiple files

Ideal Users:

💻 Terminal Power Users: Developers who live in the command line
🏢 DevOps Engineers: System administrators and automation specialists
🎓 Students: Learning programming with interactive AI assistance
🚀 Startup Developers: Rapid prototyping and MVP development
🔧 Open Source Contributors: Working across multiple projects

🔬 Technical Specifications

System Architecture

┌─────────────────────────────────────┐
│         Rust TUI Coder              │
├─────────────────────────────────────┤
│ 🖥️  TUI Layer (ratatui + crossterm) │
│ 🤖 Agent Layer (tool execution)     │
│ 🌐 LLM Layer (API communication)    │
│ ⚙️  Config Layer (TOML + env vars)   │
└─────────────────────────────────────┘

Dependencies & Ecosystem

Core Framework: ratatui for terminal UI, crossterm for input handling
Async Runtime: tokio for concurrent operations
HTTP Client: reqwest for API communication
Serialization: serde for configuration and data handling
Error Handling: Comprehensive error propagation and user feedback

Performance Characteristics

Memory Usage: 50-200MB (depending on conversation size)
CPU Usage: Minimal (<5%) during idle, spikes during LLM calls
Network Usage: 10-100KB per API call (excluding streaming)
Disk Usage: 100MB base + conversation logs
Startup Time: <2 seconds (optimized release build)

📄 License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

Happy Coding! 🦀✨

Updates (2025-08-18)

New Features

Expanded Toolset: Added AppendFile, ReplaceInFile, SearchText, CopyPath, MovePath, and ListFilesRecursive for more powerful automation.
JSON Tool Calls: Supports structured JSON format for tool calls (backward-compatible with legacy format).
Configurable Automation:
- max_attempts: Limit retries per task (default: 12).
- workspace_root: Set a fixed working directory (default: current dir).
- shell: Default shell for commands (default: bash).
- post_write_verify: Auto-verify file changes (default: true).
Improved Prompt: Now includes workspace context, OS info, and stricter guidance for autonomous task completion.
Model Auto-Detection: When model_name = "AUTODETECT", the system automatically selects the first available model from your LLM provider's API.

Architecture

System Overview

graph TD
    A[User Input] --> B(Agent)
    B --> C{Tool Call?}
    C -->|Yes| D[Execute Tool]
    D --> E[Verify Results]
    E --> B
    C -->|No| F[Final Output]

Tool Execution Flow

sequenceDiagram
    participant User
    participant Agent
    participant Tools
    User->>Agent: Task Request
    Agent->>Tools: TOOL: {"name":"WRITE_FILE", ...}
    Tools-->>Agent: Success/Failure
    Agent->>User: Tool Logs + Next Step

Task Completion Logic

flowchart LR
    Start --> Plan
    Plan --> Execute
    Execute --> Verify
    Verify -->|Success| Done
    Verify -->|Failure| Adjust
    Adjust --> Execute
    Done --> End

Example: Adding a CLI Command

graph LR
    A[Task: 'Add version flag'] --> B[List Files]
    B --> C[Find main.rs]
    C --> D[Edit main.rs]
    D --> E[Compile]
    E --> F[Test]
    F --> G[Done]

These diagrams visualize:

The end-to-end flow from input to output
Tool call mechanics (JSON/legacy)
The autonomous loop (plan → execute → verify)
A concrete example of adding a CLI command

Name		Name	Last commit message	Last commit date
Latest commit History 39 Commits
rust_tui_coder		rust_tui_coder
LICENSE		LICENSE
README.md		README.md
img1.png		img1.png
img2.png		img2.png
rust-coder-cli-logo.png		rust-coder-cli-logo.png

License

Ammar-Alnagar/Rust-Coder-CLI

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🦀 Rust TUI Coder

🌟 What is Rust TUI Coder?

🚀 Core Capabilities

🎯 Why Choose Rust TUI Coder?

For Terminal Power Users

For AI-Assisted Development

For Privacy-Conscious Developers

🔄 Workflow Transformation

🌟 Key Differentiators

💡 Perfect For

🎨 Built for Performance

🌍 Ecosystem Integration

🚀 Getting Started in 60 Seconds

📋 Table of Contents

📸 Screenshots

Interactive Conversation & File Operations

Tool System Overview

✨ Key Features

🖥️ Terminal User Interface

🤖 AI Integration

🛠️ Tool System

📁 File & Directory Operations

⚡ Code Execution & System Integration

🔧 Advanced Features

⚙️ Configuration

🚀 Getting Started

📋 Prerequisites

System Requirements

Software Dependencies

LLM Provider Access

⚡ Quick Installation

Option 1: Direct Download (Recommended)

Option 2: Build from Source

Option 3: Development Setup

🔧 Configuration Setup

1. Initial Configuration

2. LLM Provider Configuration

3. Advanced Configuration

4. Environment Variables (Alternative)

🧪 Verification

🎯 First Run Experience

📖 Usage Guide

🎯 Basic Operation

Interface Overview

Core Commands

💡 Example Workflows

🌟 Getting Started Examples

🚀 Advanced Workflows

🔧 Specialized Use Cases

⌨️ Keyboard Controls

Basic Navigation

Advanced Controls

Special Commands

🎨 Interface Customization

Color Themes

Layout Options

🏗️ Architecture

Module Responsibilities

🔧 Configuration Reference

Complete Configuration Example

Environment Variables (Alternative)

🛠️ Development

🚀 Getting Started with Development

Development Environment Setup

🏗️ Build System

Build Profiles

Advanced Build Options

Development Workflow

🧪 Testing

Test Categories

Testing Commands

🔧 Code Quality

Linting & Formatting

📚 Architecture & Code Organization