Vibecomfy

VibeComfy

VibeComfy is this package: a Python-first way to drive ComfyUI without hand-editing JSON. The center of gravity is VibeWorkflow: load a workflow, edit it in Python, validate it, then compile to ComfyUI API JSON and run it.

Use this umbrella skill for orientation and package rules. For real work, route to the smallest focused skill:

The operating path is:

discover -> load_bundle -> edit/compose -> validate -> compile("api") -> run -> collect outputs

Custom Python functions use @python_node and lower to visible, executable vibecomfy.exec nodes. Complete modules/projects use python_node.from_source with a bounded source capsule; worker-installed packages use python_node.from_installed. Route authoring and source edits to edit-comfy-workflow, execution and queue evidence to run-comfy-workflow, and dependency/import failures to vibecomfy-setup or debug-comfy-workflow. Read custom Python workflow nodes for the canonical syntax and validation boundaries.

For a reusable source-to-Python onboarding path, including provenance and honest import/runtime blockers, see workflow onboarding.

First Moves

Work from the user's project directory so relative import destinations and recipe paths are predictable. Repository maintenance commands may require the VibeComfy repo root. Prefer the vibecomfy ... console entrypoint; if an editable checkout has no console script, use python -m vibecomfy.cli ....

For a runnable starting point:

vibecomfy workflows list --ready
vibecomfy inspect image/z_image
vibecomfy copy-to-recipe image/z_image --out recipes/my_run.py
vibecomfy validate recipes/my_run.py
vibecomfy run recipes/my_run.py --runtime server --server-url http://127.0.0.1:8188

For raw JSON:

vibecomfy import workflow.json
vibecomfy inspect workflows/workflow --json
vibecomfy edit workflows/workflow set sampler.steps 30
vibecomfy validate workflows/workflow --json
vibecomfy doctor workflows/workflow --json

For a community workflow, obtain workflow.json by searching Hivemind through the deployed Astrid pack and fetching the selected accepted revision. Pull it only when needed, then import it into workflows/. Do not bulk-download or maintain a second local copy of Hivemind's workflow catalogue.

import creates an editable folder with workflow.py, workflow.vibe.json, and a byte-identical source.json; provenance stays in the bundle metadata. Use --out <directory>, --dry-run, or --json as needed. This prepares authoring files but does not install dependencies or run the workflow. Use validate and doctor for checks, and templates create for intentional ready-template promotion. A ready_templates/ entry is a curated executable adapter, not a replacement for the Hivemind source or the local workflows/ ingestion bundle. This standalone route is local and untracked by default. Add --project <name> to import and edit to opt those transitions into an existing Astrid project. If the workflow is already being handled by Astrid, use its native astrid media import plus astrid tasks create --capability vibecomfy.import route instead; it inherits the admitted project/task context and does not use VibeComfy's --project flag. The workflow onboarding guide explains the three routes, atomic batch edits, direct Python capture, validation, and Astrid history.

For node details, use vibecomfy node <ClassType>. Its default view includes inputs, outputs, schema provenance, and locally available implementation class source. Use --inputs, --outputs, or --source to focus the result, combine filters when useful, and add --json for machine-readable output. Treat source unavailability separately from a missing schema; never substitute a generated wrapper for the underlying node implementation.

For setup trouble:

vibecomfy config show --json
vibecomfy runtime doctor

Automatic Local Preparation

Local canonical Python workflows are statically reconciled after load. Missing model URLs, node repositories, destinations, and class accounting gaps are reported together; the run stops before compilation, session changes, package or node installation, model transfer, or queueing. Common unresolved entries are written back to the same workflow source for the user to complete.

Once the dependency report is resolved, vibecomfy run uses the existing model fetch, node-pack, lockfile, session, and bounded download plumbing automatically. --deps reuse is the default: it only compares the declared runtime target and emits one actionable drift warning; missing or demonstrably incompatible fields block before queueing. --deps sync is explicit and managed-target-only, and uses the existing preparation/install seams. Set VIBECOMFY_OFFLINE=1 to make sync fail closed instead of attempting network access. Managed sync requires an existing VibeComfy-owned runtime_root/.venv or runtime_root/venv plus the .vibecomfy-managed marker written by the managed setup path; it never installs into an unrelated caller interpreter. --runtime-root, --session, --keep-warm, --restart-session, --download-workers, and --json remain available on the normal run command. Explicit --server-url runs are remote and non-mutating; unverifiable target fields are reported as such.

The typed requirements.runtime declaration records the tested ComfyUI commit/version, Python version, package constraints, launch flags, model identities, and custom-node versions/commits. Legacy metadata.python_env and metadata.comfy_commit are normalized for compatibility; contradictory values fail at ingest rather than silently choosing one.

The local repair loop is canonical and same-file: authored ModelAsset rows and requirements.custom_node_refs are the only dependency declarations. URL-only models use the current URL bytes and leave an observed SHA-256/size/ effective-URL receipt; optional hf_revision, sha256, and node version/tag/branch/commit pins remain explicit. Matching model receipts and custom_nodes.lock entries are reused exactly. Before any setup or queueing, root and nested graph classes are checked against core classes, declared classes/class_set, and an unambiguous local pack catalog. Gaps are reported with source locations and actionable same-file placeholders; dynamic forms remain manual-edit diagnostics. Warm sessions and bounded concurrency are preserved after reconciliation. Live RunPod/GPU acceptance remains an explicitly separate validation and is not claimed from local structural tests.

Authoring Model

Use one loader by default:

from vibecomfy.cli_loader import load_bundle

def build():
    wf = load_bundle("image/z_image").workflow
    wf.set_prompt("a glass teapot on basalt")
    wf.set_seed(42)
    wf.set_steps(20)
    return wf.finalize_metadata()

Choose the lightest edit shape:

Keep ComfyUI's terms precise: a workflow is any graph; a template is a curated starting-point workflow under ready_templates/.