AI Context Generator

[![Crates.i```toml

Cargo.toml

[dependencies] ai-context-gen = "0.1.2"

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A context generator for Rust repositories that creates a structured markdown file with relevant information for LLMs and AI agents.

## 🎯 Quick Start

**Choose your preferred way to use AI Context Generator:**

| Usage Mode | When to Use | Quick Start |
|------------|-------------|-------------|
| 🔧 **CLI Tool** | Interactive use, one-time analysis, scripts | `ai-context-gen --path ./my-project` |
| 📚 **Rust Library** | Integrate into Rust apps, custom workflows | `cargo add ai-context-gen` |

---

### 🚀 CLI Quick Start

```bash
# Install globally
git clone https://github.com/brbtavares/ai-context-gen
cd ai-context-gen && make install

# Use anywhere
ai-context-gen --path /path/to/project

📦 Library Quick Start

# Cargo.toml
[dependencies]
ai-context-gen = "0.1.1"

use ai_context_gen::generate_context;
use std::path::PathBuf;

#[tokio::main]
async fn main() -> anyhow::Result<()> {
    generate_context(PathBuf::from("."), "context.md".to_string()).await?;
    Ok(())
}

Features

• 🔍 Complete Scanning: Analyzes all .rs and .md files in the repository
• 🌳 Abstract Syntax Tree: Extracts and documents structures, functions, enums and implementations
• 📊 Token Control: Respects token limits and prioritizes important content
• 📁 Project Structure: Generates file tree visualization
• 📖 Documentation: Includes markdown files like README, documentation, etc.
• ⚡ Performance: Asynchronous and optimized processing

---

🔧 CLI Tool Usage

The AI Context Generator CLI is perfect for interactive use, one-time analysis, and shell scripts.

Installation

Prerequisites

• Rust 1.76 or higher
• Linux system (tested on Ubuntu/Debian)

Build and Install

# Clone the repository
git clone https://github.com/brbtavares/ai-context-gen
cd ai-context-gen

# Build and install globally (recommended)
make install

# Alternative: step by step
make build
sudo cp target/release/ai-context-gen /usr/local/bin/

Verify Installation

# Check if installed correctly
ai-context-gen --version
ai-context-gen --help

# Should work from any directory
cd /tmp && ai-context-gen --path ~/my-project

Developer Commands (Make)

# Development & Testing
make dev          # Build and run in development mode
make demo         # Run demo with current directory
make test         # Run tests
make check        # Run format, lint and tests

# Build & Installation
make build        # Build using script (recommended)
make install      # Install on system
make uninstall    # Remove from system

# Utilities
make clean        # Clean build artifacts
make help-make    # Show all make commands

CLI Commands

Basic Usage

# Analyze current directory (interactive mode)
ai-context-gen

# Analyze specific directory
ai-context-gen --path /path/to/project

# Custom output file
ai-context-gen --output my_context.md

# High token limit for large projects
ai-context-gen --max-tokens 100000

All CLI Options

ai-context-gen [OPTIONS]

Options:
    -p, --path <PATH>              Path to repository (default: current directory)
    -m, --max-tokens <MAX_TOKENS>  Maximum number of tokens (default: 50000)
    -o, --output <OUTPUT>          Output file name (default: repo_context.md)
        --include-hidden           Include hidden files and directories
        --include-deps             Include external dependencies analysis
    -h, --help                     Print help
    -V, --version                  Print version

CLI Examples

# Complete analysis with all options
ai-context-gen --path ~/my-rust-project --max-tokens 200000 --output complete_analysis.md --include-hidden

# Quick summary
ai-context-gen --max-tokens 10000 --output summary.md

# Analyze remote/different project
ai-context-gen --path /opt/some-project --output /tmp/analysis.md

---

📚 Rust Library Usage

The AI Context Generator library is perfect for integrating context generation into your Rust applications.

Installation

Add to your Cargo.toml:

[dependencies]
ai-context-gen = "0.1.2"

Library Examples

Simple Usage

use ai_context_gen::generate_context;
use std::path::PathBuf;

#[tokio::main]
async fn main() -> anyhow::Result<()> {
    // Generate context for current directory
    generate_context(PathBuf::from("."), "context.md".to_string()).await?;
    println!("Context generated in context.md");
    Ok(())
}

Advanced Usage with Custom Configuration

use ai_context_gen::{Config, ContextGenerator, RepositoryScanner};
use std::path::PathBuf;

#[tokio::main]
async fn main() -> anyhow::Result<()> {
    // Custom configuration
    let config = Config {
        repo_path: PathBuf::from("./my-project"),
        max_tokens: 100000,
        output_file: "detailed_context.md".to_string(),
        include_hidden: true,
        include_deps: true,
    };

    // Two-step process for more control
    let scanner = RepositoryScanner::new(config.clone());
    let scan_result = scanner.scan().await?;
    
    println!("Files found: {}", scan_result.files.len());
    
    let generator = ContextGenerator::new(config);
    generator.generate_context(scan_result).await?;
    
    println!("Context generated successfully!");
    Ok(())
}

Using with Custom Configuration Function

use ai_context_gen::{Config, generate_context_with_config};
use std::path::PathBuf;

#[tokio::main]
async fn main() -> anyhow::Result<()> {
    let config = Config {
        repo_path: PathBuf::from("/path/to/analyze"),
        max_tokens: 75000,
        output_file: "custom_context.md".to_string(),
        include_hidden: false,
        include_deps: true,
    };

    generate_context_with_config(config).await?;
    Ok(())
}

Available Library API

• generate_context(path, output): Simple function for basic cases
• generate_context_with_config(config): Function with custom configuration
• Config: Configuration structure
• RepositoryScanner: File scanning and analysis
• ContextGenerator: Context generation with priorities
• RustParser: Rust code AST parser

---

📋 Generated File Structure

The generated file contains the following sections (in priority order):

1. Project Metadata (High Priority)

• Project name and description
• Rust version
• Main dependencies
• Project statistics

2. Project Structure (High Priority)

• File tree
• Directory organization

3. Markdown Documentation (High Priority)

• README.md
• Other .md files found
• Project documentation

4. Rust AST Analysis (Medium Priority)

• Structures (structs)
• Enumerations (enums)
• Functions
• Implementations (impls)
• Modules
• Code documentation

5. Source Code (Low Priority)

• Complete content of .rs files
• Syntax highlighting for markdown

🧠 Prioritization Algorithm

The system uses an intelligent prioritization algorithm:

1. High Priority (9): Metadata, structure and documentation
2. Medium Priority (5): AST analysis and code architecture
3. Low Priority (1): Complete source code

When the token limit is reached, the system:

• Includes high priority sections first
• Truncates low priority sections if necessary
• Reports which sections were truncated

🚫 Ignored Files

The system automatically ignores:

Directories:

• target/
• node_modules/
• .git/
• .vscode/
• .idea/

Files:

• Cargo.lock
• .gitignore
• .DS_Store

🔢 Token Counting

Uses the GPT-4 tokenizer for precise token counting, ensuring compatibility with:

• OpenAI GPT-4
• Claude
• Other models based on similar tokens

🎯 Use Cases

For Developers

• Automatic project documentation
• Onboarding new team members
• Code architecture analysis

For LLMs/AI

• Structured context for code assistants
• Analysis of existing projects
• Documentation generation
• Automated code review

For Documentation

• Project wiki generation
• Architecture reports
• Technical documentation

⚠️ Limitations

• Supports only Rust projects
• Analyzes only .rs and .md files
• Requires Linux system for execution
• Token limit may truncate content

🤝 Contributing

Contributions are welcome! Please:

1. Fork the project
2. Create a branch for your feature
3. Implement your changes
4. Add tests if necessary
5. Open a Pull Request

Development Setup

git clone https://github.com/brbtavares/ai-context-gen
cd ai-context-gen
cargo build
cargo test

Release Process

For maintainers, releases are automated. See RELEASE.md for details.

# Update version and changelog, then:
git tag v0.1.2
git push origin v0.1.2
# GitHub Actions handles the rest!

📄 License

This project is licensed under the MIT license. See the LICENSE file for details.

🛤️ Roadmap

• Web interface
• Git integration
• Commit history analysis
• Support for other output formats (JSON, YAML)
• Cache for better performance

📝 Changelog

v0.1.2

• 🔧 MSRV Compatibility: Updated MSRV to Rust 1.76 to support Cargo lock file version 4
• 🚀 Workflow Improvements: Modernized GitHub Actions workflows with updated actions
• 🛠️ CI Fixes: Fixed MSRV check to handle newer lock file formats correctly
• 📦 Release Automation: Enhanced release workflow with better asset handling
• 🔒 Better Error Handling: Improved release workflow with proper secret handling

v0.1.1

• ✨ Documentation Improvements: Completely restructured README.md and lib.rs documentation
• 🔧 Clear CLI/Library Separation: Added clear distinction between CLI and library usage
• 📚 Enhanced Library Examples: Added multiple usage patterns and integration examples
• 🎯 Quick Start Guide: Added comparison table and clear guidance on when to use each mode
• 🛠️ Better Error Handling: Improved CLI output messages and error reporting
• 📖 API Documentation: Enhanced rustdoc comments with comprehensive examples
• 🧹 Code Organization: Improved module structure and exports

v0.1.0

• Initial implementation
• Support for Rust AST analysis
• Content prioritization system
• Token counting with tiktoken
• Structured markdown file generation

🔧 Troubleshooting

CLI Installation Issues

Command not found after installation

# Check if /usr/local/bin is in your PATH
echo $PATH | grep -o '/usr/local/bin'

# If not found, add to your shell profile
echo 'export PATH="/usr/local/bin:$PATH"' >> ~/.bashrc
source ~/.bashrc

# Verify installation
which ai-context-gen
ai-context-gen --version

Permission denied during installation

# Make sure you have sudo privileges
sudo make install

# Or install manually
make build
sudo cp target/release/ai-context-gen /usr/local/bin/
sudo chmod +x /usr/local/bin/ai-context-gen

Old version conflicts

# Remove old installations
rm -f ~/.local/bin/ai-context-gen
sudo rm -f /usr/local/bin/ai-context-gen

# Reinstall fresh
make clean
make install

Library Usage Issues

Tokio runtime errors

Make sure you're using #[tokio::main] or initializing a runtime:

// Option 1: Use tokio::main
#[tokio::main]
async fn main() -> anyhow::Result<()> {
    // your code here
}

// Option 2: Manual runtime
fn main() -> anyhow::Result<()> {
    let rt = tokio::runtime::Runtime::new()?;
    rt.block_on(async {
        // your async code here
    })
}

File permission errors

use ai_context_gen::{Config, generate_context_with_config};
use std::path::PathBuf;

// Make sure output directory is writable
let config = Config {
    repo_path: PathBuf::from("./my-project"),
    output_file: "/tmp/context.md".to_string(), // Use temp dir if needed
    // ... other config
};

General Issues

Large projects hitting token limits

# Use higher token limits for large projects
ai-context-gen --path ./large-project --max-tokens 200000

# Or focus on specific parts
ai-context-gen --path ./large-project/src --max-tokens 50000

Including/excluding files

# Include hidden files
ai-context-gen --include-hidden

# For library usage, modify Config
let config = Config {
    include_hidden: true,
    include_deps: true,
    // ...
};

---

⚠️ Limitations