starforge-kernel 0.1.0

*Forge — pipeline canvas, checkpointing, and stale/hydrate execution for the repo you already have open

*Forge (starforge)

Forge's canvas — checkpointing, provenance, stale/hydrate execution — as a VS Code extension over the repo you already have open. Blocks are ordinary Python functions tagged with @block. See DESIGN.md for the full design.

Try it (M0)

# 1. Install the kernel + decorator into the venv your target repo uses
pip install -e <forge-repo>/starforge

# 2. Build the extension
cd <forge-repo>/starforge/vscode
npm install && npm run build

# 3. Open starforge/vscode in VS Code and press F5 (extension dev host).
#    In the dev-host window, open any Python repo.

In your repo:

# analysis/blocks.py
import matplotlib.pyplot as plt
from starforge import block

@block(category="IO")
def make_numbers(n: int = 5) -> dict:
    return {"values": list(range(1, n + 1))}

@block
def scale(data: dict, factor: float = 2.0) -> dict:
    return {"values": [v * factor for v in data["values"]]}

@block
def plot(data: dict) -> dict:
    plt.plot(data["values"])
    plt.show()  # rendered inline on the canvas node
    return data

Save, run “*Forge: New Pipeline”, drag the blocks from the palette, wire output → data, hit ▶ Run. Run again — instant, everything reused. Edit scale, watch it (and only it) go stale.

Layout

Path	What
src/starforge/__init__.py	the @block decorator — zero-dep, the only thing user code touches
src/starforge/index/	static AST indexer (discovery, import graph, incremental cache)
src/starforge/core/	doc schema, history hashing, serializers, checkpoint store, runner
src/starforge/kernel/	stdio JSON-RPC kernel + per-run worker subprocess
vscode/	the extension (TS host + React Flow webview)
tests/	headless M0 proof — python -m pytest starforge/tests

State lives in the target repo under .forge/ — pipelines/ is committable, checkpoints/ and cache/ are auto-gitignored.