whet 0.1.0

What is Whet?

Whet is an open-source terminal coding agent in the same category as Claude Code and similar tools. It lives in your terminal, understands your codebase, and writes code for you using any LLM.

What makes it different:

• Open source (MIT) — you own the code, the data, and the workflow
• Provider-agnostic — Ollama, llama.cpp, Anthropic Claude, Google Gemini, or any OpenAI-compatible API
• Single binary — cargo install and you're done, no Node.js, no Python, no Docker
• Offline-capable — pair with a local LLM and nothing ever leaves your machine

Quick Start

# 1. Install (from source)
git clone https://github.com/kuroko1t/whet.git
cd whet && cargo install --path .

# 2. Pull a local model (or configure a cloud provider)
ollama pull qwen3:8b

# 3. Start coding
whet

Or use with a cloud provider:

export ANTHROPIC_API_KEY="sk-ant-..."
whet -m claude-sonnet-4-5-20250929

Demo

$ whet

whet v0.1.0
Model: qwen3:8b
Permission: default
Type Ctrl+D to exit.

you> Find all deprecation warnings and fix them

  [tool: grep] {"pattern": "deprecated", "path": "."}

I found 3 deprecation warnings. Let me fix them one by one.

  [tool: read_file] {"path": "src/main.rs"}
  [tool: edit_file] {"path": "src/main.rs", ...}

  Tool 'edit_file' wants to execute:
    path: src/main.rs
    old_text: use old_module::deprecated_fn;
    new_text: use new_module::updated_fn;
  Allow? [y/N/a(lways)] y

Done! Fixed all 3 deprecation warnings.
(2.3s)

Key Features

Project Instructions (WHET.md)

Like CLAUDE.md for Claude Code — place a WHET.md (or .whet.md) in your project root to give Whet project-specific context. It is automatically loaded and injected into the system prompt.

whet   # in a project with WHET.md → instructions are loaded automatically

Use /init to generate a starter template.

11 Built-in Tools

Web tools are disabled by default. Enable with web_enabled = true in config.

Git Safety Tiers

MCP Extension

Extend Whet with external tools via MCP (Model Context Protocol) servers:

[[mcp.servers]]
name = "filesystem"
command = "npx"
args = ["-y", "@modelcontextprotocol/server-filesystem", "/tmp"]

Permission System

Session Management

Conversations are saved per working directory and can be resumed later.

When resuming, previous user/assistant messages are displayed so you can see the conversation context at a glance.

Context Compression

Automatic conversation summarization prevents unbounded memory growth. Use /compact for manual compression.

Commands

LLM Providers

Configuration

Config file: ~/.whet/config.toml

[llm]
provider = "ollama"
model = "qwen3:8b"
base_url = "http://localhost:11434"
# api_key = "sk-..."
# streaming = true

[agent]
max_iterations = 10
# permission_mode = "default"
# web_enabled = false
# context_compression = true
# skills_dir = "~/.whet/skills"

[memory]
database_path = "~/.whet/memory.db"

[llm]
provider = "anthropic"
model = "claude-sonnet-4-5-20250929"
# api_key = "sk-ant-..."   # or set ANTHROPIC_API_KEY env var

[llm]
provider = "gemini"
model = "gemini-2.0-flash"
# api_key = "..."           # or set GEMINI_API_KEY env var

[llm]
provider = "openai_compat"
model = "your-model-name"
base_url = "http://localhost:8080"
api_key = "sk-..."

Skills

Custom prompt templates loaded from ~/.whet/skills/:

mkdir -p ~/.whet/skills
echo "Always write tests for new code." > ~/.whet/skills/testing.md

Skills are injected into the system prompt automatically. Use /skills to list them.

CLI

whet                             # start interactive chat
whet "fix the bug"               # single-shot mode
whet -m llama3.2:3b              # use a specific model
whet --resume                    # pick a session to resume (current directory)
whet --resume <id>               # resume a specific session by ID
whet --continue                  # resume the most recent session
whet -p "explain main.rs"        # single-shot via -p flag
whet -y                          # skip all permission prompts
whet tools                       # list available tools
whet config                      # show current configuration

vs Claude Code

Architecture

whet (single binary)

  Terminal (REPL) <--> Agent Loop
                        |
                        +-- LLM Provider
                        |     Ollama / OpenAI / Anthropic / Gemini
                        |
                        +-- Tool Executor
                        |     11 built-in + MCP + Skills
                        |
                        +-- Security Layer
                        |     Path safety, Permissions, Git safety tiers
                        |
                        +-- SQLite Memory
                              Chat history, Resume, Compression

Development

cargo test                     # run tests
cargo fmt -- --check           # check formatting
cargo clippy --all-targets     # lint

All pull requests are checked by GitHub Actions: format, clippy, test, and build.

Contributing

Contributions are welcome!

• Issues — Use GitHub Issues for bug reports and feature requests
• Pull Requests — Fork, create a feature branch, ensure all checks pass, and submit a clear PR
• Commits — Use imperative mood with prefix: feat:, fix:, docs:, refactor:, test:, chore:

License

MIT