Codebind

Codebind turns an ordinary IPython session into a durable model harness with one tool: an IPython cell executed in the active session. IPython owns execution, namespace, history, magics, tracebacks, and rich display; Codebind owns conversation state and model orchestration.

Installation

uvx codebind

Or install it with any Python package installer:

pip install codebind

Configuration

Codebind reads its private model choice from $XDG_CONFIG_HOME/codebind/configuration.json, or ~/.config/codebind/configuration.json when XDG_CONFIG_HOME is unset:

{
  "model": "openai/gpt-5.6-luna",
  "parameters": {
    "reasoning_effort": "medium"
  }
}

Provider credentials use the same XDG directory in models.json. Keep both files readable only by their owner. Loading Codebind does not add chat, model, models, Models, or any other variable to the IPython namespace.

Terminal IPython

Start a new conversation:

uvx codebind

Ask through ordinary IPython magic syntax:

%%question
Inspect this project and tell me what to implement first.

Terminal conversations remain live for the current IPython process. Durable automatic resumption belongs to notebooks, where the notebook file provides an unambiguous conversation identity. Model-executed cells appear with IPython's native input counter, syntax highlighting, output prompts, streams, and tracebacks. Assistant Markdown is rendered through IPython's terminal MIME renderer. A terminal is a stream rather than a notebook document, so these displays are not editable notebook cells.

JupyterLab

uvx --from jupyterlab --with codebind --with 'nbconvert[webpdf]' jupyter lab

When running an unpublished local checkout, expose both its editable Python source and its current prebuilt frontend:

JUPYTER_PATH=/path/to/codebind/data/share/jupyter \
uvx --refresh --from jupyterlab --with-editable /path/to/codebind \
  --with 'nbconvert[webpdf]' jupyter-lab

Load Codebind in a notebook:

%load_ext codebind

That is the complete setup. Question is a native toolbar toggle:

• Turning it on converts the selected cell into a Question and makes each newly created user cell a Question until the toggle is turned off.
• Codebind-generated instruction, tool, and answer cells are never converted.
• Write ordinary Markdown and press Shift+Enter.

Instructions and notebook context

• Loading the extension adds a locked Markdown cell containing Codebind's packaged instructions. Its exact text becomes the conversation's immutable system message and remains stable when the server or kernel restarts.
• The whole notebook is model context. Before each Question, Codebind snapshots ordinary Markdown, raw, and code cells—including visible text and image outputs, but never the live Python namespace.
• Images displayed by the model's IPython tool are included in that tool's result. PNG, JPEG, WebP, GIF, and SVG renditions are prepared as model-visible images; unsupported or oversized images are reported as omissions.
• The first turn records the snapshot. Later turns append only new, changed, removed, or reordered cells. Existing Questions, tool calls, tool results, and answers in the conversation ledger are not duplicated.
• Image bytes travel in the relevant message; notebook snapshots contain only stable image descriptors. This append-only representation keeps the prior model prefix unchanged for provider caching.

Persistence and notebook behavior

• Codebind stores the complete LangChain message, notebook-context, and turn ledger in notebook metadata. Reopening the notebook, restarting its kernel, and loading the extension restores the accumulated context automatically.
• Each assistant Markdown segment is buffered and inserted as one complete native cell as soon as it finishes, before a following tool call completes.
• Tool executions and assistant answers are appended to the notebook end without changing the user's selection or scroll position. Tool outputs are collapsed by default and expandable through JupyterLab's native output control.

Reliability and editing

• The conversation ledger validates its structure and each assistant tool call against its single matching result, without a version gate.
• Interrupted saves finish before a turn is cancelled, preventing a restart from turning a partial write into an orphan tool result. An interrupted tool call is closed with an explicit interrupted result.
• Temporary model transport failures retry the same Question with a fresh connection; repeated WebSocket failures use HTTP. Invalid requests and authentication failures remain visible errors.
• If a provider stream is cancelled or fails, Codebind discards that provider session before the next Question while retaining the notebook conversation and stable prompt-cache identity.
• The instruction cell, sent Question cells, model-authored tool cells, and assistant Markdown cells are non-editable and non-deletable. Draft Questions remain editable until sent. Jupyter's standard interrupt button cancels an active Codebind question.

Markdown and other frontends

• Question and assistant Markdown supports $...$, $$...$$, \(...\), and \[...\] through JupyterLab's native MathJax renderer.
• Other IPython frontends retain standard MIME display, syntax-highlighted code, Markdown, stdout, tracebacks, rich results, and native IPython history.

ChatGPT account access

• Models Provider owns OpenAI account authorization and token refresh.
• Save the resulting provider-values object in Codebind's XDG models.json; Codebind loads it privately when the extension starts.
• ChatGPT subscription access is separate from the public, pay-as-you-go OpenAI API and may require compatibility updates when the account protocol changes.