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https://github.com/seatedro/glimpse

Copy code from your codebase to clipboard instantly for LLM context!
https://github.com/seatedro/glimpse

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Copy code from your codebase to clipboard instantly for LLM context!

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README 

        
# Glimpse



A blazingly fast tool for peeking at codebases. Perfect for loading your codebase into an LLM's context, with built-in token counting support.



## Features



- 🚀 Fast parallel file processing

- 🌳 Tree-view of codebase structure

- 📝 Source code content viewing

- 🔢 Token counting with multiple backends

- ⚙️ Configurable defaults

- 📋 Clipboard support

- 🎨 Customizable file type detection

- 🥷 Respects .gitignore automatically



## Installation



Using cargo:

```bash

cargo install glimpse

```



Using homebrew:

```bash

brew tap seatedro/glimpse

brew install glimpse

```



Using Nix:

```bash

# Install directly

nix profile install github:seatedro/glimpse



# Or use in your flake

{

  inputs.glimpse.url = "github:seatedro/glimpse";

}

```



## Usage



Basic usage:

```bash

glimpse /path/to/project



glimpse file1 file2 file3



glimpse /path/to/project -e "*.h"

```



Common options:

```bash

# Show hidden files

glimpse -H /path/to/project



# Only show tree structure

glimpse -o tree /path/to/project



# Copy output to clipboard

glimpse -c /path/to/project



# Save output to file

glimpse -f output.txt /path/to/project



# Include specific file types

glimpse -i "*.rs,*.go" /path/to/project



# Exclude patterns

glimpse -e "target/*,dist/*" /path/to/project



# Count tokens using tiktoken (OpenAI's tokenizer)

glimpse /path/to/project



# Use HuggingFace tokenizer with specific model

glimpse --tokenizer huggingface --model gpt2 /path/to/project



# Use custom local tokenizer file

glimpse --tokenizer huggingface --tokenizer-file /path/to/tokenizer.json /path/to/project

```



## CLI Options



```

Usage: glimpse [OPTIONS] [PATH]



Arguments:

  [PATH]  Directory/Files to analyze [default: .]



Options:

      --interactive              Opens interactive file picker (? for help)

  -i, --include        Additional patterns to include (e.g. "*.rs,*.go")

  -e, --exclude        Additional patterns to exclude

  -s, --max-size          Maximum file size in bytes

      --max-depth         Maximum directory depth to traverse

  -o, --output           Output format: tree, files, or both

  -f, --file               Save output to specified file

  -p, --print                    Print to stdout instead of clipboard

  -t, --threads           Number of threads for parallel processing

  -H, --hidden                   Show hidden files and directories

      --no-ignore                Don't respect .gitignore files

      --no-tokens                Disable token counting

      --tokenizer          Tokenizer to use: tiktoken or huggingface

      --model              Model name for HuggingFace tokenizer

      --tokenizer-file     Path to local tokenizer file

  -h, --help                     Print help

  -V, --version                  Print version

```



## Configuration



Glimpse uses a config file located at:

- Linux/macOS: `~/.config/glimpse/config.toml`

- Windows: `%APPDATA%\glimpse\config.toml`



Example configuration:

```toml

# General settings

max_size = 10485760  # 10MB

max_depth = 20

default_output_format = "both"



# Token counting settings

default_tokenizer = "tiktoken"       # Can be "tiktoken" or "huggingface"

default_tokenizer_model = "gpt2"     # Default model for HuggingFace tokenizer



# Default exclude patterns

default_excludes = [

    "**/.git/**",

    "**/target/**",

    "**/node_modules/**"

]

```



## Token Counting



Glimpse supports two tokenizer backends:



1. Tiktoken (Default): OpenAI's tokenizer implementation, perfect for accurately estimating tokens for GPT models.



2. HuggingFace Tokenizers: Supports any model from the HuggingFace hub or local tokenizer files, great for custom models or other ML frameworks.



The token count appears in both file content views and the final summary, helping you estimate context window usage for large language models.



Example token count output:

```

File: src/main.rs

Tokens: 245

==================================================

// File contents here...



Summary:

Total files: 10

Total size: 15360 bytes

Total tokens: 2456

```



## Troubleshooting



1. **File too large**: Adjust `max_size` in config

2. **Missing files**: Check `hidden` flag and exclude patterns

3. **Performance issues**: Try adjusting thread count with `-t`

4. **Tokenizer errors**: 

   - For HuggingFace models, ensure you have internet connection for downloading

   - For local tokenizer files, verify the file path and format

   - Try using the default tiktoken backend if issues persist



## License



MIT