ipyclaude is an IPython extension that turns any input starting with . into an AI prompt.
It is aimed at terminal IPython, not notebook frontends.
pip install ipyclaudeipyclaude provides a standalone command that launches IPython with ipyclaude and ipythonng extensions pre-loaded and output history enabled:
ipyclaudeResume a previous session:
ipyclaude -r # interactive session picker
ipyclaude -r 43 # resume session 43 directlyOn exit, ipyclaude prints the session ID so you can resume later.
%load_ext ipyclaudeIf you change the package in a running shell:
%reload_ext ipyclaudeAdd this to an ipython_config.py file used by terminal ipython:
c.TerminalIPythonApp.extensions = ["ipyclaude.core"]Good places for that file include:
- env-local:
{sys.prefix}/etc/ipython/ipython_config.py - user-local:
~/.ipython/profile_default/ipython_config.py
In a virtualenv, the env-local path is usually .venv/etc/ipython/ipython_config.py.
To see which config paths your current ipython is searching, run:
ipython --debug -c 'exit()' 2>&1 | grep SearchingOnly the leading period is special. There is no closing delimiter.
Single line:
.write a haiku about sqliteMultiline paste:
.summarize this module:
focus on state management
and persistence behaviorBackslash-Enter continuation in the terminal:
.draft a migration plan \
with risks and rollback stepsipyclaude also provides a line and cell magic named %ipyclaude / %%ipyclaude.
Note: .01 * 3 and similar expressions starting with . followed by a digit will be interpreted as prompts. Write 0.01 * 3 instead.
Any IPython cell containing only a string literal is treated as a "note". Notes provide context to the AI without being executable code:
"This is a note explaining what I'm about to do"Notes appear in the AI context as <note> blocks rather than <code> blocks. When saving a session, notes are stored as markdown cells in the startup notebook.
%ipyclaude
%ipyclaude model claude-sonnet-4-6
%ipyclaude completion_model claude-haiku-4-5-20251001
%ipyclaude think m
%ipyclaude search h
%ipyclaude code_theme monokai
%ipyclaude log_exact true
%ipyclaude save
%ipyclaude reset%ipyclaude— show current settings and config file paths%ipyclaude model .../completion_model .../think .../search .../code_theme .../log_exact ...— change settings for the current session%ipyclaude save— save the current session (code, notes, and AI history) tostartup.ipynb%ipyclaude reset— clear AI prompt history for the current session%ipyclaude sessions— list resumable sessions for the current directory (falls back to git repo root)
Expose a function from the active IPython namespace as a tool by referencing it with &name`` in the prompt:
def weather(city): return f"Sunny in {city}"
.use &`weather` to answer the question about BrisbaneCallable objects and async callables are also supported.
Tools are discovered from multiple sources beyond direct &name`` mentions in prompts:
- Skills: tools listed in
allowed-toolsfrontmatter or referenced with&name`` in the skill body - Notes: string-literal cells can contain
&name`` references or YAML frontmatter withallowed-tools - Tool responses: when a tool result starts with YAML frontmatter containing
allowed-toolsoreval: true, any&name`` references andallowed-toolsentries in that result are also added
All discovered tools that exist as callables in the IPython namespace are included in the AI's tool schema.
ipyclaude supports Agent Skills — reusable instruction sets that the AI can load on demand. Skills are discovered at extension load time from:
.agents/skills/in the current directory and every parent directory~/.config/agents/skills/
Each skill is a directory containing a SKILL.md file with YAML frontmatter (name, description) and markdown instructions. Skills can also declare allowed-tools in their frontmatter (space-delimited list of tool names) to pre-approve tools without requiring explicit &name`` mentions in prompts.
At the start of each conversation, the AI sees a list of available skill names and descriptions. When a request matches a skill, the AI calls the load_skill tool to read its full instructions before responding.
Python code blocks in skills that start with #| eval: true (nbdev/quarto syntax) are executed in the IPython namespace when the skill is loaded, allowing skills to define tool functions:
```python
#| eval: true
def my_tool(x):
"A skill-provided tool"
return x * 2
```See the Agent Skills specification for the full format.
ipyclaude registers prompt_toolkit keybindings:
| Shortcut | Action |
|---|---|
| Alt-. | AI inline completion (calls Haiku, shows as greyed suggestion — accept with right arrow, or Alt-f to accept one word at a time) |
| Alt-Up/Down | Jump through complete history entries (skips line-by-line in multiline inputs) |
| Alt-Shift-W | Insert all Python code blocks from the last AI response |
| Alt-Shift-1 through Alt-Shift-9 | Insert the Nth code block |
| Alt-Shift-Up/Down | Cycle through code blocks one at a time |
Code blocks are extracted from fenced markdown blocks tagged as python or py. Blocks tagged with other languages (bash, json, etc.) or untagged blocks are skipped.
Syntax highlighting is disabled while typing . prompts and %%ipyclaude cells so natural language isn't coloured as Python.
%ipyclaude save snapshots the current session to ~/.config/ipyclaude/startup.ipynb:
- code cells are saved as code cells (notes become markdown cells)
- AI prompts are saved with the response as markdown and the prompt in cell metadata
When ipyclaude loads into a fresh session, saved code is replayed and saved prompts are restored into the conversation history. This primes new sessions with imports, helpers, tools, and prior AI context without re-running the prompts.
Responses are streamed and rendered as markdown in the terminal via Rich. Thinking indicators (🧠) are displayed during model reasoning and removed once the response begins. Tool calls are compacted to a short form like 🔧 f(x=1) => 2.
Config files live under ~/.config/ipyclaude/ and are created on demand:
| File | Purpose |
|---|---|
config.json |
Model, think/search level, code theme, log flag |
sysp.txt |
System prompt |
startup.ipynb |
Saved session snapshot |
exact-log.jsonl |
Raw prompt/response log (when log_exact is enabled) |
config.json supports:
{
"model": "claude-sonnet-4-6",
"completion_model": "claude-haiku-4-5-20251001",
"think": "l",
"search": "l",
"code_theme": "monokai",
"log_exact": false
}modeldefaults from theIPYAI_MODELenvironment variable if set when the config is first createdcompletion_modelis the model used for Alt-. inline completionsthinkandsearchmust be one ofl,m, orh
ipycodex is a sister project with the same interface but backed by the Codex app-server instead of litellm/Anthropic.
See DEV.md for project layout, architecture, persistence details, and development workflow.