AI News HubLIVE
站内改写3 min read

Show HN: Nanocode-CLI – A lightweight terminal-based AI coding assistant

Nanocode-CLI is a lightweight terminal-based AI coding assistant written in Python. It features live turn control, file-state brain, stale-edit protection, project-aware navigation, recoverable context, cache-aware context, focused working memory, and a terminal-first workflow. Install with uv.

SourceHacker News AIAuthor: hit9

Notifications You must be signed in to change notification settings

Fork 0

Star 8

BranchesTags

Open more actions menu

Folders and files

NameName

Last commit message

Last commit date

Latest commit

History

689 Commits

689 Commits

.github/workflows

.github/workflows

snapshots

snapshots

tests

tests

.gitignore

.gitignore

CHANGELOG.md

CHANGELOG.md

LICENSE

LICENSE

MANIFEST.in

MANIFEST.in

Makefile

Makefile

README.md

README.md

README.zh-CN.md

README.zh-CN.md

nanocode.py

nanocode.py

pyproject.toml

pyproject.toml

Repository files navigation

A small terminal coding agent written in Python.

简体中文

nanocode is pre-1.0 software. Commands, configuration, and tool behavior may change before a stable release.

Features

Live turn control: Add follow-up input while the agent is still working, without losing the current tool flow.

File-state brain: Reads and edits build a current, line-numbered view of the files that matter now.

Stale-edit protection: line:hash anchors reject edits when the target code has drifted.

Project-aware navigation: Use the symbol index to jump through outlines, references, and changed files quickly.

Recoverable context: Tool output stays bounded in the prompt, while raw tr.N results remain recallable.

Cache-aware context: Stable sections stay early and noisy working state stays late to improve prompt-cache reuse.

Focused working memory: Note separates goal, plan, and known facts from noisy execution logs.

Terminal-first workflow: Model selection, history search, confirmations, live command output, appended input, and status all stay in one CLI.

Install

uv tool install nanocode-cli

Upgrade:

uv tool upgrade nanocode-cli

For local development:

uv sync --extra dev uv run nanocode

Usage

Start the CLI:

nanocode

Useful arguments:

--config : use a TOML config file.

--init-config: create a default config file.

--yolo: skip confirmations for mutating tools.

-v, --version: show the version.

During a running turn, the +> prompt accepts follow-up input for the next model request.

Commands

/help: show commands and tools.

/status: show runtime status.

/config: show active config.

/api [auto|chat|anthropic]: show or set provider API format.

/debug [on|off]: toggle model I/O debug traces.

/compact: compact context now.

/index [force]: sync or rebuild the code symbol index.

/provider [NAME]: show or set provider.

/model [MODEL]: show or set model.

/reason: choose reasoning effort.

/set KEY VALUE: set provider/runtime values.

/yolo: toggle tool confirmations.

/exit, /quit: exit.

Interactive selectors support j/k, arrows, / search, Enter, and Esc. Input supports history, completion, and Ctrl-R history search.

Tools

File: Read, LineCount, List, Find, Search.

Code index: InspectCode.

Edit: Edit creates or patches file content.

Shell: Bash, Git.

Tool results: Recall.

Working notes: Note.

Read, Search, and InspectCode return line anchors where useful. Edit uses current line:hash anchors to reject stale edits.

Configuration

Run:

nanocode --init-config

Default config location is ~/.nanocode/config.toml.

Main fields:

[provider] active = "name"

[provider.]: url, key, model, api, prompt_cache_key, available_models, reasoning, chat_reasoning, temperature, timeout

[paths] data_dir

[runtime] shell_timeout, max_agent_steps, max_context_tokens, yolo

api = "auto" chooses between Chat Completions and Anthropic Messages using provider/model profiles. prompt_cache_key = "auto" derives a stable key from provider, model, workspace, and tool schema names.

Tested Providers

The following providers have been tested with nanocode:

deepseek: DeepSeek API

opencode: OpenCode API

aliyun: Alibaba Cloud (Tongyi Qianwen) API via Chat Completions

llama.cpp: Local inference via llama.cpp server

Context Design

Each model request is built manually from explicit messages. Stable context comes first, conversation stays as messages, working memory follows, and the latest file state is appended at the end.

model request +--------------------------------------------------+ | system | | concise agent contract and tool rules | +--------------------------------------------------+ | user | | Environment | +--------------------------------------------------+ | user/assistant | | conversation, compacted summaries, tools | +--------------------------------------------------+ | user | | Memory: goal, plan, known, date | +--------------------------------------------------+ | user | | FILE STATE: latest Read/Edit file view | +--------------------------------------------------+

Core rules:

Mid-turn assistant text and appended user input are kept as conversation.

Earlier conversation is compacted into an explicit summary when the context grows too large.

FILE STATE is updated by successful Read and Edit tools and shows current listed file ranges, with recent files first.

Newer file lines overwrite older lines; edit invalidations clear stale ranges.

File lines are checked against current file stat or line hash before being shown.

Successful Read and Edit tool messages point to FILE STATE instead of repeating file bodies.

Other tool outputs are bounded in conversation messages and can be recalled by tr.N.

Safety

nanocode can edit files and run shell commands in the environment where it is started. It does not provide sandbox protection. Run it inside your own sandbox, container, VM, or other isolated environment when needed.

About

A lightweight terminal-based AI coding assistant

Resources

Readme

License

BSD-3-Clause license

Uh oh!

There was an error while loading. Please reload this page.

Activity

Stars

8 stars

Watchers

0 watching

Forks

0 forks

Report repository

Releases

35 tags

Contributors

Uh oh!

There was an error while loading. Please reload this page.

Languages

Python 99.9%

Makefile 0.1%

Show HN: Nanocode-CLI – A lightweight terminal-based AI coding assistant | AI News Hub