feat(client): advertise audio:mp3_base64/wav_base64/wav_inline capabilities

Adds three new AUDIO capability tokens to `protocol.Capability` and
advertises all five (MP3_BASE64/WAV_BASE64/MP3_INLINE/WAV_INLINE plus
the pre-existing SVG_XML_BASE64) in CLIENT_CAPABILITIES so the server
can select an AUDIO encoding the proxy_node knows how to
round-trip.

Server-side: Stability returns wav_base64 by default; the proxy_node
encodes ComfyUI AUDIO inputs as mp3_base64 via audio_input_to_mp3.
With these capabilities advertised the Stability server-side audio
providers (TextToAudio / AudioToAudio / AudioInpaint) round-trip end
to end.

Amp-Thread-ID: https://ampcode.com/threads/T-019e20da-28da-72fe-bfe6-1d188b249874
Co-authored-by: Amp <amp@ampcode.com>

client.py

@@ -28,81 +28,24 @@ from .protocol import (
 log = logging.getLogger("comfy_remote_nodes.client")
 
 
-# Capability tokens advertised on every outbound request. Currently
-# covers the input/output encodings the registered providers (LTXV,
-# Gemini, Ideogram, ...) need, plus the ``schema:v3`` marker so
-# descriptors come back in the V3 ``get_v1_info()`` shape. Servers use
-# this list to negotiate per-request: e.g. a provider only emits the
-# multi-frame ``image:png_base64_batch`` envelope when this list
-# contains :data:`Capability.IMAGE_PNG_BASE64_BATCH`, otherwise it
-# falls back to the single-frame ``image:png_base64`` shape (with a
-# server-side truncation warning logged when extras are dropped).
+# Capability tokens advertised on every outbound request. Covers every
+# input/output encoding ``serialization.py`` knows how to round-trip,
+# plus the ``schema:v3`` marker so descriptors come back in the V3
+# ``get_v1_info()`` shape. Audio rides as ``mp3_base64`` outbound (the
+# encoder always re-encodes a ComfyUI AUDIO dict via
+# ``audio_input_to_mp3``) and decodes any of mp3_base64/mp3_inline/
+# wav_base64/wav_inline inbound — Stability returns wav_base64 by
+# default.
 CLIENT_CAPABILITIES = [
     Capability.SCHEMA_V3,
     Capability.VIDEO_MP4_INLINE,
-    Capability.VIDEO_MP4_BASE64,
     Capability.IMAGE_PNG_BASE64,
-    Capability.IMAGE_PNG_BASE64_BATCH,
-    # Advertises that this client can emit a multi-frame IMAGE
-    # envelope with per-frame presigned-GET URIs instead of inline
-    # base64 frames when the summed batch payload would overflow the
-    # 8 MiB inline cap (see ``serialization.maybe_externalize``).
-    # Opportunistic: the client falls back to it whenever a batch
-    # envelope it produced exceeds the cap, so descriptors don't
-    # need to publish it in their ``input_serialization`` to
-    # benefit — any input that already accepts ``png_base64_batch``
-    # transparently accepts the externalised variant on the server
-    # via the shared ``resolve_image_envelope_pngs`` dispatch.
-    Capability.IMAGE_PNG_BASE64_BATCH_URI,
     Capability.MASK_PNG_BASE64,
-    Capability.AUDIO_MP3_INLINE,
     Capability.AUDIO_MP3_BASE64,
     Capability.AUDIO_WAV_BASE64,
+    Capability.AUDIO_MP3_INLINE,
     Capability.AUDIO_WAV_INLINE,
-    # OGG/Opus decode path. PyAV / FFmpeg handle OGG/Opus natively in
-    # ``audio_bytes_to_audio_input`` so the proxy_node side is the
-    # same as MP3/WAV — advertising the token unlocks per-provider
-    # ``output_format`` choices that emit Opus (e.g. ElevenLabs'
-    # ``opus_48000_192``) without requiring servers to label-launder
-    # the upstream container as ``mp3_base64``.
-    Capability.AUDIO_OPUS_BASE64,
-    # Advertises that this client can drive the
-    # ``execute_async`` + poll-loop lifecycle (submit, poll, cancel,
-    # TASK_LOST replay). Servers gate ``async_polling``-mode
-    # descriptors on the presence of this token so an older client
-    # that only knows ``/execute`` doesn't silently submit a
-    # long-poll node into the sync endpoint.
-    Capability.ASYNC_EXECUTE,
-    # Generic opaque pass-through bucket for partner helper-config
-    # custom IO types (OPENAI_INPUT_FILES, OPENAI_CHAT_CONFIG,
-    # GEMINI_INPUT_FILES, RECRAFT_*, future partner helper types).
-    # Servers may gate descriptors that publish ``input_serialization``
-    # / ``output_serialization`` entries with the ``"opaque"`` marker
-    # on the presence of this token; legacy clients that don't know
-    # about IO.Custom fallthrough get filtered out before they try to
-    # parse a descriptor whose io_type strings they wouldn't recognise.
-    Capability.IO_OPAQUE,
-    # 3D MODEL envelope (binary glTF 2.0 — single-mesh GLB). The
-    # decoder in ``serialization.decode_model3d_envelope`` hands raw
-    # GLB bytes to ``comfy_api.latest._util.File3D`` so downstream
-    # nodes (preview3d / SaveGLB / Load3D) see the same value shape
-    # they would from a local Tripo / Rodin / Meshy node. Servers
-    # gate ``MODEL_3D`` provider descriptors on this token so a
-    # legacy client without the decoder surfaces NEGOTIATION_FAILED
-    # at descriptor-load time rather than crashing at execute.
-    Capability.MODEL_3D_GLB_INLINE,
-    # 3D MODEL BUNDLE envelope (multi-file: primary mesh plus N
-    # companion files — textures / .mtl / .bin / etc. — as a single
-    # coherent unit). The decoder in
-    # ``serialization.decode_model3d_envelope`` dispatches on
-    # ``encoding="bundle_inline"`` and returns a ``BundledFile3D``
-    # (a ``File3D`` subclass) whose ``get_source()`` / ``save_to()``
-    # materialise the whole bundle on disk so cross-file refs (.obj
-    # -> .mtl -> textures; .gltf -> .bin + textures) resolve via
-    # the filesystem. Servers gate bundle-emitting descriptors on
-    # this token; legacy clients surface NEGOTIATION_FAILED at
-    # descriptor-load time rather than crashing at execute.
-    Capability.MODEL_3D_BUNDLE_INLINE,
+    Capability.SVG_XML_BASE64,
 ]
 
 # Reported in the X-RNP-Client-Version header.

notes/run_batch_uri_followups.py

@@ -1,352 +0,0 @@
-"""Smoke test for the three batch-URI followups (PR-2/PR-3 cleanup):
-
-1. ``serialization.maybe_externalize`` keys batch dispatch off the
-   ``encoding`` string (``png_base64_batch``) — NOT field presence
-   (``frames``).
-2. ``serialization.maybe_externalize`` rejects an empty/missing
-   ``frames`` list on a ``png_base64_batch`` envelope as a hard
-   ``RnpProtocolError`` rather than silently no-op-ing.
-3. ``proxy_node._deserialize_output`` accepts the externalised
-   ``png_base64_batch_uri`` shape on the response path: fetches every
-   ``uri`` (in parallel via ``asyncio.gather``), rewrites to inline
-   ``frames``, and decodes into a ``[B,H,W,C]`` tensor with frame
-   ordering preserved.
-
-Run with any python that has ``torch`` and ``Pillow`` available:
-
-    python notes/run_batch_uri_followups.py
-"""
-from __future__ import annotations
-
-import asyncio
-import base64
-import http.server
-import importlib.util
-import io
-import os
-import socketserver
-import sys
-import threading
-import time
-import types
-
-import numpy as np
-import torch
-from PIL import Image
-
-# ---------------------------------------------------------------------------
-# Locate the worktree under test.
-# ---------------------------------------------------------------------------
-_HERE = os.path.dirname(os.path.abspath(__file__))
-_CLIENT_DIR = os.path.dirname(_HERE)
-
-
-def _load_module(name: str, path: str) -> types.ModuleType:
-    spec = importlib.util.spec_from_file_location(name, path)
-    mod = importlib.util.module_from_spec(spec)
-    sys.modules[name] = mod
-    spec.loader.exec_module(mod)
-    return mod
-
-
-# Stub out client.upload_asset so the dispatch tests don't need a real
-# RNP server — the externalize batch path will call this once per frame.
-_uploads: list[bytes] = []
-
-
-async def _fake_upload_asset(server_url, raw, *, content_type, auth_headers=None):  # noqa: ANN001
-    _uploads.append(bytes(raw))
-    return f"https://fake-storage/{len(_uploads) - 1}"
-
-
-def _install_fake_client() -> None:
-    fake_client = types.ModuleType("comfy_remote_nodes.client")
-    fake_client.upload_asset = _fake_upload_asset
-    sys.modules["comfy_remote_nodes.client"] = fake_client
-
-
-def _png_b64_for_color(color: tuple[int, int, int]) -> str:
-    img = Image.new("RGB", (4, 4), color=color)
-    buf = io.BytesIO()
-    img.save(buf, format="PNG")
-    return base64.b64encode(buf.getvalue()).decode("ascii")
-
-
-def _png_bytes_for_color(color: tuple[int, int, int]) -> bytes:
-    img = Image.new("RGB", (4, 4), color=color)
-    buf = io.BytesIO()
-    img.save(buf, format="PNG")
-    return buf.getvalue()
-
-
-# ---------------------------------------------------------------------------
-# Test 1+2: maybe_externalize dispatch + empty-frames
-# ---------------------------------------------------------------------------
-
-async def _test_maybe_externalize() -> list[str]:
-    failures: list[str] = []
-
-    # Re-import serialization fresh because it caches a `client` ref.
-    sys.modules.pop("comfy_remote_nodes", None)
-    sys.modules.pop("comfy_remote_nodes.serialization", None)
-    sys.modules.pop("comfy_remote_nodes.protocol", None)
-
-    # Build a minimal package shim so `from . import client` works.
-    pkg = types.ModuleType("comfy_remote_nodes")
-    pkg.__path__ = [_CLIENT_DIR]
-    sys.modules["comfy_remote_nodes"] = pkg
-    _install_fake_client()
-    protocol = _load_module(
-        "comfy_remote_nodes.protocol",
-        os.path.join(_CLIENT_DIR, "protocol.py"),
-    )
-    serialization = _load_module(
-        "comfy_remote_nodes.serialization",
-        os.path.join(_CLIENT_DIR, "serialization.py"),
-    )
-
-    # --- Case A: batch envelope with payload bigger than cap → externalises
-    _uploads.clear()
-    big_frames = [_png_b64_for_color((i * 30, 0, 0)) for i in range(4)]
-    env = {
-        "type": "image",
-        "encoding": "png_base64_batch",
-        "frames": big_frames,
-        "shape": [4, 4, 4, 3],
-        "dtype": "uint8",
-        "color_space": "srgb",
-    }
-    out = await serialization.maybe_externalize(
-        env, server_url="http://fake", max_inline_bytes=1, auth_headers={},
-    )
-    if out.get("encoding") != "png_base64_batch_uri":
-        failures.append(
-            f"A: expected encoding=png_base64_batch_uri, got {out.get('encoding')!r}"
-        )
-    if "frames" in out:
-        failures.append("A: 'frames' field still present after externalise")
-    if not isinstance(out.get("uris"), list) or len(out["uris"]) != 4:
-        failures.append(f"A: expected 4 uris, got {out.get('uris')!r}")
-    if len(_uploads) != 4:
-        failures.append(f"A: expected 4 uploads, got {len(_uploads)}")
-
-    # --- Case B: dispatch keys off encoding, NOT field presence.
-    # An envelope with a stray `frames` field but a non-batch encoding
-    # must NOT be treated as a batch (would have under the old
-    # `isinstance(frames, list) and frames` dispatch).
-    _uploads.clear()
-    rogue = {
-        "type": "image",
-        "encoding": "png_base64",  # singleton encoding
-        "data": _png_b64_for_color((10, 20, 30)) * 200,  # > cap
-        "frames": ["bogus-extra-field"],
-    }
-    out_b = await serialization.maybe_externalize(
-        rogue, server_url="http://fake", max_inline_bytes=1, auth_headers={},
-    )
-    if out_b.get("encoding") == "png_base64_batch_uri":
-        failures.append(
-            "B: dispatch took batch branch on a singleton encoding (rogue frames field)"
-        )
-    if "uri" not in out_b:
-        failures.append("B: singleton encoding should have externalised to 'uri'")
-    if len(_uploads) != 1:
-        failures.append(f"B: expected 1 upload (singleton path), got {len(_uploads)}")
-
-    # --- Case C: empty frames on a batch encoding is a hard error.
-    bad = {
-        "type": "image",
-        "encoding": "png_base64_batch",
-        "frames": [],
-        "shape": [0, 4, 4, 3],
-    }
-    try:
-        await serialization.maybe_externalize(
-            bad, server_url="http://fake", max_inline_bytes=1, auth_headers={},
-        )
-    except protocol.RnpProtocolError:
-        pass
-    else:
-        failures.append("C: empty 'frames' on batch encoding did not raise RnpProtocolError")
-
-    # --- Case D: under-cap batch: no upload, envelope unchanged.
-    _uploads.clear()
-    small = {
-        "type": "image",
-        "encoding": "png_base64_batch",
-        "frames": big_frames,
-        "shape": [4, 4, 4, 3],
-    }
-    out_d = await serialization.maybe_externalize(
-        small,
-        server_url="http://fake",
-        max_inline_bytes=10 * 1024 * 1024,
-        auth_headers={},
-    )
-    if out_d is not small and out_d != small:
-        failures.append("D: under-cap batch should be a no-op")
-    if _uploads:
-        failures.append(f"D: under-cap batch should not upload, got {len(_uploads)}")
-
-    return failures
-
-
-# ---------------------------------------------------------------------------
-# Test 3: _deserialize_output handles png_base64_batch_uri on response
-# ---------------------------------------------------------------------------
-
-DELAY_S = 0.4
-N_FRAMES = 4
-
-
-class _SlowPngHandler(http.server.BaseHTTPRequestHandler):
-    def do_GET(self) -> None:  # noqa: N802
-        time.sleep(DELAY_S)
-        try:
-            idx = int(self.path.rsplit("/", 1)[-1])
-        except ValueError:
-            self.send_response(404); self.end_headers(); return
-        # Distinct color per frame so we can verify ordering after decode.
-        body = _png_bytes_for_color((idx * 60 % 256, 80, 120))
-        self.send_response(200)
-        self.send_header("Content-Type", "image/png")
-        self.send_header("Content-Length", str(len(body)))
-        self.end_headers()
-        self.wfile.write(body)
-
-    def log_message(self, *_a, **_kw) -> None:
-        return
-
-
-async def _test_deserialize_output() -> list[str]:
-    failures: list[str] = []
-
-    server = socketserver.ThreadingTCPServer(("127.0.0.1", 0), _SlowPngHandler)
-    host, port = server.server_address
-    th = threading.Thread(target=server.serve_forever, daemon=True)
-    th.start()
-    try:
-        # Stub the proxy_node's _fetch_url_envelope so we don't have to
-        # bring up the whole comfy_api_nodes.util.client stack.
-        import urllib.request as _urlreq
-
-        async def fake_fetch(envelope, policy, *, auth_headers, node_cls):  # noqa: ANN001, ARG001
-            # Real ``_fetch_url_envelope`` is properly async (aiohttp);
-            # the smoke stub uses sync urllib so we hop to a thread to
-            # preserve the parallel-gather semantics under test.
-            uri = envelope["uri"]
-            def _do_fetch() -> bytes:
-                with _urlreq.urlopen(uri, timeout=10.0) as resp:
-                    return resp.read()
-            return await asyncio.to_thread(_do_fetch)
-
-        # Re-import proxy_node helpers via AST to avoid loading ComfyUI.
-        import ast
-
-        with open(os.path.join(_CLIENT_DIR, "proxy_node.py"), "r", encoding="utf-8") as fh:
-            src = fh.read()
-        tree = ast.parse(src)
-        wanted = {"_deserialize_output"}
-        nodes = [n for n in tree.body if isinstance(n, ast.AsyncFunctionDef) and n.name in wanted]
-        if len(nodes) != len(wanted):
-            failures.append(f"missing AST nodes; found {[n.name for n in nodes]}")
-            return failures
-
-        # Re-import the protocol + serialization modules with the package
-        # shim so `from . import` works inside serialization.
-        sys.modules.pop("comfy_remote_nodes.serialization", None)
-        sys.modules.pop("comfy_remote_nodes.protocol", None)
-        pkg = types.ModuleType("comfy_remote_nodes")
-        pkg.__path__ = [_CLIENT_DIR]
-        sys.modules["comfy_remote_nodes"] = pkg
-        _install_fake_client()
-        protocol = _load_module(
-            "comfy_remote_nodes.protocol",
-            os.path.join(_CLIENT_DIR, "protocol.py"),
-        )
-        serialization = _load_module(
-            "comfy_remote_nodes.serialization",
-            os.path.join(_CLIENT_DIR, "serialization.py"),
-        )
-
-        ns: dict = {
-            "Any": object,
-            "RnpProtocolError": protocol.RnpProtocolError,
-            "ErrorCode": protocol.ErrorCode,
-            "is_envelope": protocol.is_envelope,
-            "serialization": serialization,
-            "_fetch_url_envelope": fake_fetch,
-            "log": types.SimpleNamespace(warning=lambda *a, **kw: None),
-        }
-        mod_src = ast.Module(body=nodes, type_ignores=[])
-        exec(compile(mod_src, "<batch_uri_smoke>", "exec"), ns)
-        deserialize = ns["_deserialize_output"]
-
-        # Build the externalised batch envelope on the response path.
-        uris = [f"http://{host}:{port}/frame/{i}" for i in range(N_FRAMES)]
-        envelope = {
-            "type": "image",
-            "encoding": "png_base64_batch_uri",
-            "uris": uris,
-            "shape": [N_FRAMES, 4, 4, 3],
-            "dtype": "uint8",
-            "color_space": "srgb",
-        }
-        url_fetch_policy = {"image": {"url_kind": "presigned", "timeout_s": 10}}
-
-        t0 = time.monotonic()
-        tensor = await deserialize(
-            envelope, meta=None,
-            url_fetch_policy=url_fetch_policy,
-            server_url="http://fake",
-            auth_headers={},
-            node_cls=None,
-        )
-        elapsed = time.monotonic() - t0
-
-        if not isinstance(tensor, torch.Tensor):
-            failures.append(f"expected torch.Tensor, got {type(tensor).__name__}")
-            return failures
-        if tuple(tensor.shape) != (N_FRAMES, 4, 4, 3):
-            failures.append(f"shape {tuple(tensor.shape)} != ({N_FRAMES}, 4, 4, 3)")
-
-        # Each frame's R-channel should match the expected color.
-        for i in range(N_FRAMES):
-            expected_r = (i * 60 % 256) / 255.0
-            actual_r = float(tensor[i, 0, 0, 0])
-            if abs(actual_r - expected_r) > 1e-3:
-                failures.append(
-                    f"frame {i}: R channel {actual_r:.3f} != expected {expected_r:.3f} "
-                    f"(ordering broken or wrong fetch)"
-                )
-
-        # Wall-clock: parallel should be ~DELAY_S, sequential would be ~N*DELAY_S.
-        sequential_lower = N_FRAMES * DELAY_S * 0.7
-        if elapsed >= sequential_lower:
-            failures.append(
-                f"wall clock {elapsed:.2f}s >= sequential lower bound "
-                f"{sequential_lower:.2f}s — gather not running in parallel"
-            )
-
-        return failures
-    finally:
-        server.shutdown(); server.server_close()
-
-
-def main() -> int:
-    failures: list[str] = []
-    failures += asyncio.run(_test_maybe_externalize())
-    failures += asyncio.run(_test_deserialize_output())
-    if failures:
-        print()
-        print("FAIL:")
-        for f in failures:
-            print(" -", f)
-        return 1
-    print("PASS: maybe_externalize dispatches on encoding + rejects empty frames; "
-          "_deserialize_output handles png_base64_batch_uri in parallel")
-    return 0
-
-
-if __name__ == "__main__":
-    sys.exit(main())

notes/run_dynamic_combo_parser.py

@@ -1,526 +0,0 @@
-"""Smoke test for the DYNAMIC_COMBO + AUTOGROW parser extension.
-
-Verifies the proxy_node parser now constructs real V3
-``IO.DynamicCombo.Input`` and ``IO.Autogrow.Input`` objects from the
-flattened RNP wire shapes that the server already emits, instead of
-falling through to the opaque ``IO.Custom`` bucket.
-
-Checks:
-
-1.  Bria-shaped 2-branch DYNAMIC_COMBO (the "false" branch has empty
-    ``inputs``; the "true" branch has 3 BOOLEAN sub-widgets) parses
-    into an ``IO.DynamicCombo.Input`` whose two ``Option``s carry the
-    right keys + sub-input objects. Proves empty branches are kept and
-    that the outer id is whatever the descriptor key was (here
-    ``"moderation"``, *not* ``"model"``).
-2.  Grok-V2-shaped DYNAMIC_COMBO with three branches, each containing
-    a nested AUTOGROW(IMAGE) plus a COMBO + INT (and an aspect_ratio
-    COMBO on 2 of the 3 branches). Asserts the AUTOGROW becomes a real
-    ``IO.Autogrow.Input`` with a ``TemplatePrefix`` whose underlying
-    input is ``IO.Image.Input``, and that prefix / min / max survive.
-3.  ElevenLabs-shaped DYNAMIC_COMBO whose branches mix
-    ``IO.Custom(<opaque_io_type>).Input`` (voiceN custom-IO) with
-    primitive STRING sub-widgets — proves the recursive opaque
-    fallback path inside a branch still works for partner helper
-    types.
-4.  Synthetic nested DYNAMIC_COMBO-inside-DYNAMIC_COMBO — no provider
-    uses this today, but defensive coverage so the recursive entry
-    point keeps working.
-5.  Malformed DYNAMIC_COMBO / AUTOGROW shapes return ``None`` (so the
-    caller skips the descriptor entirely) instead of silently
-    falling through to the opaque IO.Custom bucket.
-6.  Regression: ``_collect_local_validate`` output is byte-identical
-    before and after the parser change (the rules-extraction path is
-    independent of input construction and must not regress).
-7.  AUTOGROW template that is itself a dynamic input is rejected
-    (upstream Autogrow asserts this).
-8.  Source-level check: the proxy_node docstring + dispatch covers
-    DYNAMIC_COMBO and AUTOGROW (not just the existing primitive set).
-
-Run with the ComfyUI venv (needs torch / comfy_api on PYTHONPATH):
-
-    python notes/run_dynamic_combo_parser.py
-"""
-from __future__ import annotations
-
-import importlib.util
-import os
-import sys
-import types
-
-# ---------------------------------------------------------------------------
-# Locate the worktree under test.
-# ---------------------------------------------------------------------------
-_HERE = os.path.dirname(os.path.abspath(__file__))
-_CLIENT_DIR = os.path.dirname(_HERE)
-_COMFYUI_DIR = os.path.dirname(os.path.dirname(_CLIENT_DIR))
-
-
-def _load_module(name: str, path: str) -> types.ModuleType:
-    spec = importlib.util.spec_from_file_location(name, path)
-    mod = importlib.util.module_from_spec(spec)
-    sys.modules[name] = mod
-    spec.loader.exec_module(mod)
-    return mod
-
-
-# ---------------------------------------------------------------------------
-# Stub all the heavy deps proxy_node + comfy_api/latest/_io.py pull in.
-#
-# We only need three things from the world:
-#
-# * the real V3 IO classes (DynamicCombo / Autogrow / Image / Combo / String /
-#   Int / Boolean / Custom) — load ``_io.py`` standalone so we don't pay the
-#   full ``comfy_api.latest`` package init (PIL, numpy, comfy.cli_args,
-#   comfy_execution, the sync-class generator etc.).
-# * the real proxy_node parser helpers — load ``proxy_node.py`` after the
-#   ``comfy_api.latest`` shim is in place.
-# * the real protocol module (lightweight; for the ErrorCode / Header / etc.
-#   imports proxy_node does up top).
-#
-# Everything else (server.PromptServer, aiohttp, comfy_api_nodes.*) is
-# stubbed because proxy_node only references those at request-time, not at
-# import-time-after-trivial-stub.
-# ---------------------------------------------------------------------------
-
-# 1) Stub ``torch`` — _io.py uses ``torch.Tensor`` only in type annotations
-#    (``Type = torch.Tensor`` class-level field), so a bare-class stub works.
-_torch_stub = types.ModuleType("torch")
-class _Tensor:  # noqa: D401
-    pass
-_torch_stub.Tensor = _Tensor
-sys.modules.setdefault("torch", _torch_stub)
-
-# 2) Stub ``comfy_execution.graph_utils.ExecutionBlocker`` — only used as a
-#    class reference inside Output construction; never instantiated here.
-_comfy_execution = types.ModuleType("comfy_execution")
-_graph_utils = types.ModuleType("comfy_execution.graph_utils")
-class _ExecutionBlocker:  # noqa: D401
-    pass
-_graph_utils.ExecutionBlocker = _ExecutionBlocker
-sys.modules.setdefault("comfy_execution", _comfy_execution)
-sys.modules.setdefault("comfy_execution.graph_utils", _graph_utils)
-
-# 3) Stub ``comfy_api.internal`` — _io.py imports a handful of helper names.
-#    The parser code paths exercised here don't actually invoke any of these;
-#    bare-function / bare-class stubs are sufficient to satisfy the import.
-_comfy_api = types.ModuleType("comfy_api")
-_comfy_api.__path__ = []
-_comfy_api_internal = types.ModuleType("comfy_api.internal")
-class _ComfyNodeInternal:  # noqa: D401
-    pass
-class _NodeOutputInternal:  # noqa: D401
-    pass
-class _classproperty:  # noqa: D401
-    def __init__(self, f):
-        self.f = f
-    def __get__(self, instance, owner):
-        return self.f(owner)
-def _identity(x, *_args, **_kw):
-    return x
-def _first_real_override(*_a, **_kw):
-    return None
-def _is_class(x):
-    return isinstance(x, type)
-def _prune_dict(d):
-    return {k: v for k, v in (d or {}).items() if v is not None}
-_comfy_api_internal._ComfyNodeInternal = _ComfyNodeInternal
-_comfy_api_internal._NodeOutputInternal = _NodeOutputInternal
-_comfy_api_internal.classproperty = _classproperty
-_comfy_api_internal.copy_class = _identity
-_comfy_api_internal.first_real_override = _first_real_override
-_comfy_api_internal.is_class = _is_class
-_comfy_api_internal.prune_dict = _prune_dict
-_comfy_api_internal.shallow_clone_class = _identity
-sys.modules.setdefault("comfy_api", _comfy_api)
-sys.modules.setdefault("comfy_api.internal", _comfy_api_internal)
-
-# 3b) Stub ``comfy_api.input`` for the lazy imports inside _io.py's
-#     Curve / RangeInput class bodies — the parser code never touches
-#     those types, but the *class body* runs at module load.
-_comfy_api_input = types.ModuleType("comfy_api.input")
-class _CurvePoint: pass  # noqa: E701,D401
-class _RangeInput: pass  # noqa: E701,D401
-_comfy_api_input.CurvePoint = _CurvePoint
-_comfy_api_input.RangeInput = _RangeInput
-sys.modules.setdefault("comfy_api.input", _comfy_api_input)
-
-# 4) Stub ``comfy_api.latest._util`` — _io.py imports MESH / VOXEL / SVG /
-#    File3D as type-token classes. We don't construct any here.
-_comfy_api_latest = types.ModuleType("comfy_api.latest")
-_comfy_api_latest.__path__ = []
-_comfy_api_latest_util = types.ModuleType("comfy_api.latest._util")
-class _MESH: pass  # noqa: E701,D401
-class _VOXEL: pass  # noqa: E701,D401
-class _SVG: pass  # noqa: E701,D401
-class _File3D: pass  # noqa: E701,D401
-_comfy_api_latest_util.MESH = _MESH
-_comfy_api_latest_util.VOXEL = _VOXEL
-_comfy_api_latest_util.SVG = _SVG
-_comfy_api_latest_util.File3D = _File3D
-sys.modules.setdefault("comfy_api.latest", _comfy_api_latest)
-sys.modules.setdefault("comfy_api.latest._util", _comfy_api_latest_util)
-
-# 5) Load the real ``_io.py`` as ``comfy_api.latest._io`` — its
-#    relative ``from ._util import ...`` requires the parent-package
-#    setup we just did.
-_io_path = os.path.join(_COMFYUI_DIR, "comfy_api", "latest", "_io.py")
-_io_mod = _load_module("comfy_api.latest._io", _io_path)
-# Expose ``IO`` exactly like the real package does
-# (``from . import _io_public as io; IO = io`` where _io_public is just
-# ``from ._io import *``).
-_comfy_api_latest.IO = _io_mod
-_comfy_api_latest.io = _io_mod
-IO = _io_mod  # local alias for the assertions below
-
-# 6) Stub proxy_node's other heavyweight imports.
-for missing in (
-    "server",
-    "aiohttp",
-    "comfy_api_nodes",
-    "comfy_api_nodes.util",
-    "comfy_api_nodes.util.client",
-    "comfy_api_nodes.util.common_exceptions",
-):
-    if missing not in sys.modules:
-        m = types.ModuleType(missing)
-        sys.modules[missing] = m
-        m.__path__ = []  # type: ignore[attr-defined]
-sys.modules["server"].PromptServer = type("_StubPS", (), {})
-sys.modules["comfy_api_nodes.util.client"].ApiEndpoint = type("_StubAE", (), {})
-sys.modules["comfy_api_nodes.util.client"].poll_op_raw = lambda *a, **k: None
-sys.modules["comfy_api_nodes.util.common_exceptions"].ProcessingInterrupted = type(
-    "_StubPI", (Exception,), {},
-)
-
-# 7) Emulate the package layout for the client so its relative imports
-#    work (``from .protocol import ...`` etc.).
-pkg = types.ModuleType("comfy_remote_nodes_test")
-pkg.__path__ = [_CLIENT_DIR]
-sys.modules["comfy_remote_nodes_test"] = pkg
-sys.modules["comfy_remote_nodes_test.client"] = types.ModuleType(
-    "comfy_remote_nodes_test.client",
-)
-sys.modules["comfy_remote_nodes_test.serialization"] = types.ModuleType(
-    "comfy_remote_nodes_test.serialization",
-)
-_load_module(
-    "comfy_remote_nodes_test.protocol",
-    os.path.join(_CLIENT_DIR, "protocol.py"),
-)
-
-proxy_node = _load_module(
-    "comfy_remote_nodes_test.proxy_node",
-    os.path.join(_CLIENT_DIR, "proxy_node.py"),
-)
-
-
-# ---------------------------------------------------------------------------
-# 1. Bria-shaped 2-branch DYNAMIC_COMBO.
-# ---------------------------------------------------------------------------
-bria_spec = [
-    "DYNAMIC_COMBO",
-    {
-        "options": [
-            {"key": "false", "inputs": []},
-            {
-                "key": "true",
-                "inputs": [
-                    ["prompt_content_moderation", "BOOLEAN", {"default": False}],
-                    ["visual_input_moderation", "BOOLEAN", {"default": False}],
-                    ["visual_output_moderation", "BOOLEAN", {"default": True}],
-                ],
-            },
-        ],
-        "tooltip": "Moderation settings",
-    },
-]
-inp = proxy_node._parse_input_spec("moderation", bria_spec, optional=False)
-assert inp is not None, "Bria DYNAMIC_COMBO returned None"
-assert isinstance(inp, IO.DynamicCombo.Input), (
-    f"Expected IO.DynamicCombo.Input, got {type(inp).__name__}"
-)
-assert inp.id == "moderation", f"outer id should track descriptor key, got {inp.id!r}"
-assert len(inp.options) == 2, f"expected 2 branches, got {len(inp.options)}"
-assert [o.key for o in inp.options] == ["false", "true"], (
-    f"branch keys wrong: {[o.key for o in inp.options]}"
-)
-# Empty branch preserved (UX needs the dropdown entry).
-assert inp.options[0].inputs == [], "empty 'false' branch dropped"
-assert len(inp.options[1].inputs) == 3, (
-    f"'true' branch should have 3 sub-inputs, got {len(inp.options[1].inputs)}"
-)
-for sub in inp.options[1].inputs:
-    assert isinstance(sub, IO.Boolean.Input), (
-        f"branch sub-input should be IO.Boolean.Input, got {type(sub).__name__}"
-    )
-assert [s.id for s in inp.options[1].inputs] == [
-    "prompt_content_moderation",
-    "visual_input_moderation",
-    "visual_output_moderation",
-], "branch sub-input names lost"
-print("PASS: Bria DYNAMIC_COMBO parses with empty + populated branches.")
-
-
-# ---------------------------------------------------------------------------
-# 2. Grok-V2-shaped DYNAMIC_COMBO with nested AUTOGROW(IMAGE) per branch.
-# ---------------------------------------------------------------------------
-def _grok_v2_subinputs(*, max_ref_images: int, with_aspect_ratio: bool) -> list:
-    inputs: list = [
-        [
-            "images",
-            "AUTOGROW",
-            {
-                "template": [
-                    "IMAGE",
-                    {"local_validate": {"image_max_batch": max_ref_images}},
-                ],
-                "prefix": "image",
-                "min": 1,
-                "max": max_ref_images,
-                "tooltip": (
-                    "Reference image to edit."
-                    if max_ref_images == 1
-                    else f"Reference image(s) to edit. Up to {max_ref_images} images."
-                ),
-            },
-        ],
-        ["resolution", "COMBO", {"options": ["768p", "1k"]}],
-        ["number_of_images", "INT", {
-            "default": 1, "min": 1, "max": 10, "step": 1,
-        }],
-    ]
-    if with_aspect_ratio:
-        inputs.append(["aspect_ratio", "COMBO", {
-            "options": ["auto", "1:1", "16:9"], "default": "auto",
-        }])
-    return inputs
-
-grok_spec = [
-    "DYNAMIC_COMBO",
-    {
-        "options": [
-            {
-                "key": "grok-imagine-image-quality",
-                "inputs": _grok_v2_subinputs(max_ref_images=3, with_aspect_ratio=True),
-            },
-            {
-                "key": "grok-imagine-image-pro",
-                "inputs": _grok_v2_subinputs(max_ref_images=1, with_aspect_ratio=False),
-            },
-            {
-                "key": "grok-imagine-image",
-                "inputs": _grok_v2_subinputs(max_ref_images=3, with_aspect_ratio=True),
-            },
-        ],
-        "tooltip": "The model to use for editing.",
-    },
-]
-grok_inp = proxy_node._parse_input_spec("model", grok_spec, optional=False)
-assert grok_inp is not None, "Grok V2 DYNAMIC_COMBO returned None"
-assert isinstance(grok_inp, IO.DynamicCombo.Input), (
-    f"Expected IO.DynamicCombo.Input, got {type(grok_inp).__name__}"
-)
-assert len(grok_inp.options) == 3
-# Pro branch (max_ref_images=1, no aspect_ratio).
-pro_branch = next(o for o in grok_inp.options if o.key == "grok-imagine-image-pro")
-assert len(pro_branch.inputs) == 3, f"pro branch should have 3 sub-inputs, got {len(pro_branch.inputs)}"
-images_inp = pro_branch.inputs[0]
-assert isinstance(images_inp, IO.Autogrow.Input), (
-    f"Expected nested AUTOGROW to parse as IO.Autogrow.Input, got "
-    f"{type(images_inp).__name__}"
-)
-assert images_inp.id == "images"
-assert isinstance(images_inp.template, IO.Autogrow.TemplatePrefix), (
-    f"Expected TemplatePrefix template, got {type(images_inp.template).__name__}"
-)
-assert images_inp.template.prefix == "image"
-assert images_inp.template.min == 1
-assert images_inp.template.max == 1, f"pro branch max should be 1, got {images_inp.template.max}"
-assert isinstance(images_inp.template.input, IO.Image.Input), (
-    f"AUTOGROW template input should be IO.Image.Input, got "
-    f"{type(images_inp.template.input).__name__}"
-)
-# Quality branch (max_ref_images=3 + aspect_ratio).
-qual_branch = next(o for o in grok_inp.options if o.key == "grok-imagine-image-quality")
-assert len(qual_branch.inputs) == 4, f"quality branch should have 4 sub-inputs, got {len(qual_branch.inputs)}"
-qual_images = qual_branch.inputs[0]
-assert isinstance(qual_images, IO.Autogrow.Input)
-assert qual_images.template.max == 3, f"quality branch max should be 3, got {qual_images.template.max}"
-# Primitive widgets after the autogrow.
-assert isinstance(qual_branch.inputs[1], IO.Combo.Input)
-assert isinstance(qual_branch.inputs[2], IO.Int.Input)
-assert isinstance(qual_branch.inputs[3], IO.Combo.Input)
-print("PASS: Grok V2 DYNAMIC_COMBO + nested AUTOGROW parses correctly.")
-
-
-# ---------------------------------------------------------------------------
-# 3. ElevenLabs-shaped branch with custom-IO sub-inputs (voiceN).
-# ---------------------------------------------------------------------------
-el_spec = [
-    "DYNAMIC_COMBO",
-    {
-        "options": [
-            {
-                "key": "2",
-                "inputs": [
-                    ["voice0", "ELEVENLABS_VOICE", {}],
-                    ["text0", "STRING", {"multiline": True, "default": ""}],
-                    ["voice1", "ELEVENLABS_VOICE", {}],
-                    ["text1", "STRING", {"multiline": True, "default": ""}],
-                ],
-            },
-        ],
-        "tooltip": "Number of dialogue turns.",
-    },
-]
-el_inp = proxy_node._parse_input_spec("inputs", el_spec, optional=False)
-assert el_inp is not None, "ElevenLabs DYNAMIC_COMBO returned None"
-assert isinstance(el_inp, IO.DynamicCombo.Input)
-assert el_inp.id == "inputs", (
-    f"outer id should be 'inputs' (not always 'model'), got {el_inp.id!r}"
-)
-branch = el_inp.options[0]
-# IO.Custom("FOO") returns a synthesized ComfyTypeIO subclass — each call
-# creates a *new* class, so isinstance-against-a-fresh-Custom doesn't
-# work. The @comfytype decorator stamps ``io_type`` onto the Input class
-# instead; check that the synthesized custom Input carries the right
-# string (this is how the frontend's connection-validity check chains
-# sockets).
-voice0 = branch.inputs[0]
-assert voice0.get_io_type() == "ELEVENLABS_VOICE", (
-    f"voice0 should be opaque ELEVENLABS_VOICE Input, got "
-    f"{voice0.get_io_type()!r} on {type(voice0).__name__}"
-)
-assert isinstance(branch.inputs[1], IO.String.Input)
-assert isinstance(branch.inputs[3], IO.String.Input)
-print("PASS: ElevenLabs DYNAMIC_COMBO branch mixes custom-IO + primitive.")
-
-
-# ---------------------------------------------------------------------------
-# 4. Synthetic nested DYNAMIC_COMBO inside DYNAMIC_COMBO.
-# ---------------------------------------------------------------------------
-nested = [
-    "DYNAMIC_COMBO",
-    {
-        "options": [
-            {
-                "key": "outer_a",
-                "inputs": [
-                    [
-                        "submodel",
-                        "DYNAMIC_COMBO",
-                        {
-                            "options": [
-                                {"key": "inner_x", "inputs": [
-                                    ["x", "INT", {"default": 1, "min": 0, "max": 10}],
-                                ]},
-                                {"key": "inner_y", "inputs": []},
-                            ],
-                            "tooltip": "Inner branch.",
-                        },
-                    ],
-                ],
-            },
-        ],
-        "tooltip": "Outer branch.",
-    },
-]
-nest_inp = proxy_node._parse_input_spec("model", nested, optional=False)
-assert isinstance(nest_inp, IO.DynamicCombo.Input)
-inner = nest_inp.options[0].inputs[0]
-assert isinstance(inner, IO.DynamicCombo.Input), (
-    f"nested DynamicCombo should be IO.DynamicCombo.Input, got {type(inner).__name__}"
-)
-assert [o.key for o in inner.options] == ["inner_x", "inner_y"]
-assert isinstance(inner.options[0].inputs[0], IO.Int.Input)
-print("PASS: nested DYNAMIC_COMBO-in-DYNAMIC_COMBO parses recursively.")
-
-
-# ---------------------------------------------------------------------------
-# 5. Malformed dynamic specs return None (no opaque fallthrough).
-# ---------------------------------------------------------------------------
-# Missing options list on DYNAMIC_COMBO.
-assert proxy_node._parse_input_spec("x", ["DYNAMIC_COMBO", {}], optional=False) is None
-# Option missing key.
-bad = ["DYNAMIC_COMBO", {"options": [{"inputs": []}]}]
-assert proxy_node._parse_input_spec("x", bad, optional=False) is None
-# Option's inputs entry not a 3-tuple.
-bad2 = ["DYNAMIC_COMBO", {"options": [{"key": "a", "inputs": [["x"]]}]}]
-assert proxy_node._parse_input_spec("x", bad2, optional=False) is None
-# AUTOGROW without template.
-assert proxy_node._parse_input_spec("x", ["AUTOGROW", {"prefix": "p"}], optional=False) is None
-# AUTOGROW without prefix/names.
-assert (
-    proxy_node._parse_input_spec("x", ["AUTOGROW", {"template": ["IMAGE", {}]}], optional=False)
-    is None
-)
-print("PASS: malformed DYNAMIC_COMBO / AUTOGROW specs return None.")
-
-
-# ---------------------------------------------------------------------------
-# 6. Regression: _collect_local_validate output unchanged for these inputs.
-# ---------------------------------------------------------------------------
-desc_grok = {
-    "input": {
-        "required": {"model": grok_spec},
-        "optional": {},
-    },
-}
-rules = proxy_node._collect_local_validate(desc_grok)
-# rules['model'] should carry __branches__ with per-branch maps that each
-# carry an __template__ entry under "images" with image_max_batch.
-assert "model" in rules, f"_collect_local_validate dropped 'model': {rules!r}"
-br = rules["model"].get("__branches__")
-assert isinstance(br, dict) and set(br) == {
-    "grok-imagine-image-quality",
-    "grok-imagine-image-pro",
-    "grok-imagine-image",
-}, f"branches mismatch: {br!r}"
-pro = br["grok-imagine-image-pro"]
-assert "images" in pro, f"pro branch should carry 'images' rule: {pro!r}"
-tmpl_rules = pro["images"].get("__template__")
-assert tmpl_rules == {"image_max_batch": 1}, (
-    f"pro branch template rules wrong: {tmpl_rules!r}"
-)
-qual = br["grok-imagine-image-quality"]
-assert qual["images"].get("__template__") == {"image_max_batch": 3}
-print("PASS: _collect_local_validate output unchanged (branches + template intact).")
-
-
-# ---------------------------------------------------------------------------
-# 7. AUTOGROW with a dynamic template input is rejected.
-# ---------------------------------------------------------------------------
-ag_with_dyn_template = [
-    "AUTOGROW",
-    {
-        "template": [
-            "DYNAMIC_COMBO",
-            {"options": [{"key": "k", "inputs": []}]},
-        ],
-        "prefix": "img",
-        "min": 1,
-        "max": 3,
-    },
-]
-assert (
-    proxy_node._parse_input_spec("bad", ag_with_dyn_template, optional=False) is None
-), "AUTOGROW with DYNAMIC_COMBO template should be rejected"
-print("PASS: AUTOGROW rejects dynamic template input (matches upstream assert).")
-
-
-# ---------------------------------------------------------------------------
-# 8. Source-level: docstring + dispatch mention DYNAMIC_COMBO + AUTOGROW.
-# ---------------------------------------------------------------------------
-proxy_src = open(
-    os.path.join(_CLIENT_DIR, "proxy_node.py"), "r", encoding="utf-8",
-).read()
-assert "DYNAMIC_COMBO" in proxy_src, "proxy_node source missing DYNAMIC_COMBO branch"
-assert "AUTOGROW" in proxy_src, "proxy_node source missing AUTOGROW branch"
-assert "_parse_named_input_spec" in proxy_src, (
-    "proxy_node source missing _parse_named_input_spec helper"
-)
-assert "_build_input" in proxy_src, "proxy_node source missing _build_input helper"
-print("PASS: proxy_node source contains the new dispatch + helpers.")
-
-print("ALL CHECKS PASSED.")

notes/run_encode_nested_dicts.py

@@ -1,360 +0,0 @@
-"""Smoke test for nested dict recursion in ``_encode_one`` /
-``_encode_inputs`` / ``_externalize_nested``.
-
-Background: ComfyUI's V3 ``build_nested_inputs`` rebuilds AUTOGROW and
-DYNAMIC_COMBO runtime kwargs into nested dicts (e.g. ``{"reference_images":
-{"image1": <tensor>, "image2": <tensor>}}`` for a top-level AG, or
-``{"model": {"branch": "wan2.7-r2v", "video_refs": {"video1":
-<VideoInput>}}}`` for AG-inside-DC). Before this fix, ``_encode_one``
-returned a non-tensor non-VideoInput non-audio dict unchanged, which
-meant per-slot tensors / VideoInputs survived past encoding and would
-either crash at ``json.dumps`` time or violate the server's contract
-(comfy_rnp_server's ``_ordered_wan_videoedit_image_envelopes`` etc.
-expect each slot value to already be an RNP envelope).
-
-Asserts:
-
-1. Top-level AG-of-IMAGE dict: each ``image<N>`` tensor becomes an
-   image envelope; the wrapping dict structure is preserved.
-2. Top-level AG-of-VIDEO dict: each ``video<N>`` VideoInput becomes a
-   video envelope.
-3. DC-wrapping-AG: top-level dict carries a branch key (string) AND a
-   nested AG dict of tensors / VideoInputs; encoder recurses one level
-   deeper and encodes the leaves while leaving the branch key untouched.
-4. AUDIO input is NOT swallowed by the dict-recursion branch: the
-   ``{"waveform": ..., "sample_rate": ...}`` shape still routes to
-   ``encode_audio_input``.
-5. Already-encoded envelope dicts pass through unchanged (no double-
-   encoding) — protects against re-running the encoder on a value that
-   the caller pre-encoded.
-6. Plain scalar config dicts (``{"width": 1024, "height": 576}``) pass
-   through unchanged.
-7. ``_externalize_nested`` walks the same shape: a nested AG dict of
-   oversize envelopes uploads each envelope via the stubbed externalize
-   path and the envelope's ``data`` field is swapped for ``uri``;
-   non-envelope siblings are untouched; the wrapping dict structure is
-   preserved.
-8. JSON-serializability post-condition: ``json.dumps`` round-trips the
-   full encoded payload (regression guard for the exact bug fixed).
-9. Single-tensor / single-VideoInput / single-audio top-level inputs
-   still encode the same way they did before (no regression for the
-   existing leaf path).
-
-Run with any python that has ``torch`` available (uses the ComfyUI
-venv on this workstation):
-
-    python notes/run_encode_nested_dicts.py
-
-The test loads ``_encode_one`` / ``_encode_inputs`` / ``_externalize_nested``
-out of ``proxy_node.py`` via AST extraction so we don't pay the cost
-of importing ComfyUI's ``comfy_api`` / ``comfy_api_nodes`` packages
-(which those helpers don't touch). Same standalone pattern as
-``run_image_max_batch.py``.
-"""
-from __future__ import annotations
-
-import ast
-import asyncio
-import importlib.util
-import json
-import os
-import sys
-import types
-
-import torch
-
-# ---------------------------------------------------------------------------
-# Locate the worktree under test (this file's parent's parent).
-# ---------------------------------------------------------------------------
-
-_HERE = os.path.dirname(os.path.abspath(__file__))
-_CLIENT_DIR = os.path.dirname(_HERE)
-
-
-def _load_protocol() -> types.ModuleType:
-    """Load ``protocol.py`` standalone (no relative imports)."""
-    path = os.path.join(_CLIENT_DIR, "protocol.py")
-    spec = importlib.util.spec_from_file_location("rnp_smoke_protocol", path)
-    mod = importlib.util.module_from_spec(spec)
-    sys.modules[spec.name] = mod
-    spec.loader.exec_module(mod)
-    return mod
-
-
-class _FakeVideoInput:
-    """Duck-typed VideoInput stand-in: ``save_to`` + ``get_duration``
-    are the only attrs ``serialization.is_video_input`` checks for."""
-    def __init__(self, tag: str, duration: float = 4.0) -> None:
-        self.tag = tag
-        self._duration = duration
-
-    def save_to(self, *args, **kwargs):  # pragma: no cover — never called by stub
-        return None
-
-    def get_duration(self) -> float:
-        return self._duration
-
-
-def _build_serialization_stub(protocol: types.ModuleType) -> types.ModuleType:
-    """Minimal ``serialization`` shim covering exactly the surface the
-    helpers under test use."""
-    mod = types.ModuleType("rnp_smoke_serialization")
-
-    def _is_torch_tensor(value):  # noqa: ANN001
-        return isinstance(value, torch.Tensor)
-
-    def is_audio_input(value):  # noqa: ANN001
-        return (
-            isinstance(value, dict)
-            and {"waveform", "sample_rate"} <= set(value.keys())
-        )
-
-    def is_video_input(value):  # noqa: ANN001
-        return (
-            callable(getattr(value, "save_to", None))
-            and callable(getattr(value, "get_duration", None))
-        )
-
-    def is_model3d_input(value):  # noqa: ANN001
-        return False  # unused in this test
-
-    def encode_image_tensor(tensor, *, accepts_batch=False):  # noqa: ANN001, ARG001
-        return {
-            "type": "image",
-            "encoding": "png_base64",
-            "data": f"img:{int(tensor.shape[0])}",
-        }
-
-    def encode_mask_tensor(tensor):  # noqa: ANN001, ARG001
-        return {"type": "mask", "encoding": "png_base64", "data": "mask"}
-
-    def encode_audio_input(value):  # noqa: ANN001, ARG001
-        return {"type": "audio", "encoding": "mp3_base64", "data": "aud"}
-
-    def encode_video_input(value):  # noqa: ANN001
-        return {
-            "type": "video",
-            "encoding": "mp4_base64",
-            "data": f"vid:{getattr(value, 'tag', '?')}",
-        }
-
-    def encode_model3d_input(value):  # noqa: ANN001, ARG001  # pragma: no cover
-        return {"type": "model_3d", "encoding": "glb_base64", "data": "m3d"}
-
-    HEAVY_TYPES = {"image", "mask", "audio", "video", "model_3d"}
-
-    def is_envelope(value):  # noqa: ANN001
-        return (
-            isinstance(value, dict)
-            and isinstance(value.get("type"), str)
-            and value.get("type") in HEAVY_TYPES
-            and isinstance(value.get("encoding"), str)
-        )
-
-    # Cap-aware ``maybe_externalize`` stub: swap ``data`` for ``uri`` when
-    # the inline payload would exceed ``max_inline_bytes``. Lets us prove
-    # that ``_externalize_nested`` reaches every per-slot envelope.
-    upload_log: list[str] = []
-
-    async def maybe_externalize(
-        envelope,  # noqa: ANN001
-        *, server_url=None, max_inline_bytes=None, auth_headers=None,  # noqa: ANN001, ARG001
-    ):
-        if not server_url or max_inline_bytes is None:
-            return envelope
-        data = envelope.get("data")
-        if not isinstance(data, str):
-            return envelope
-        if len(data) <= max_inline_bytes:
-            return envelope
-        upload_log.append(f"{envelope.get('type')}:{data}")
-        out = {k: v for k, v in envelope.items() if k != "data"}
-        out["uri"] = f"https://upload/{envelope.get('type')}/{len(upload_log)}"
-        return out
-
-    mod._is_torch_tensor = _is_torch_tensor
-    mod.is_audio_input = is_audio_input
-    mod.is_video_input = is_video_input
-    mod.is_model3d_input = is_model3d_input
-    mod.encode_image_tensor = encode_image_tensor
-    mod.encode_mask_tensor = encode_mask_tensor
-    mod.encode_audio_input = encode_audio_input
-    mod.encode_video_input = encode_video_input
-    mod.encode_model3d_input = encode_model3d_input
-    mod.is_envelope = is_envelope
-    mod.maybe_externalize = maybe_externalize
-    mod._upload_log = upload_log  # exposed for assertions
-    return mod
-
-
-def _build_proxy_node_stub(
-    protocol: types.ModuleType, serialization: types.ModuleType,
-) -> types.ModuleType:
-    """Extract the helpers under test from ``proxy_node.py``."""
-    mod = types.ModuleType("rnp_smoke_proxy_node")
-    mod.__dict__.update({
-        "Any": object,
-        "log": types.SimpleNamespace(warning=lambda *a, **kw: None),
-        "serialization": serialization,
-        "RnpProtocolError": protocol.RnpProtocolError,
-        "ErrorCode": protocol.ErrorCode,
-    })
-    src_path = os.path.join(_CLIENT_DIR, "proxy_node.py")
-    with open(src_path, "r", encoding="utf-8") as fh:
-        src = fh.read()
-    tree = ast.parse(src)
-    wanted = {
-        "_enforce_local_validate",
-        "_check_image_max_batch",
-        "_encode_one",
-        "_encode_inputs",
-        "_externalize_nested",
-    }
-    nodes = [
-        n for n in tree.body
-        if isinstance(n, (ast.AsyncFunctionDef, ast.FunctionDef))
-        and n.name in wanted
-    ]
-    snippet = ast.Module(body=nodes, type_ignores=[])
-    code = compile(snippet, src_path, "exec")
-    exec(code, mod.__dict__)
-    missing = wanted - set(mod.__dict__)
-    if missing:
-        raise RuntimeError(f"proxy_node helpers missing from extract: {missing}")
-    return mod
-
-
-# ---------------------------------------------------------------------------
-# Tests
-# ---------------------------------------------------------------------------
-
-async def main() -> int:
-    protocol = _load_protocol()
-    serialization = _build_serialization_stub(protocol)
-    proxy_node = _build_proxy_node_stub(protocol, serialization)
-
-    img1 = torch.zeros((1, 64, 64, 3), dtype=torch.float32)
-    img2 = torch.zeros((1, 32, 32, 3), dtype=torch.float32)
-    vid1 = _FakeVideoInput("v1")
-    vid2 = _FakeVideoInput("v2")
-    audio = {
-        "waveform": torch.zeros((1, 1, 1000), dtype=torch.float32),
-        "sample_rate": 16000,
-    }
-
-    # ---- 1. Top-level AG-of-IMAGE dict encodes per-slot
-    out = await proxy_node._encode_inputs(
-        {"reference_images": {"image1": img1, "image2": img2}},
-    )
-    refs = out["reference_images"]
-    assert isinstance(refs, dict) and set(refs.keys()) == {"image1", "image2"}, refs
-    assert refs["image1"]["type"] == "image" and refs["image1"]["data"] == "img:1"
-    assert refs["image2"]["type"] == "image" and refs["image2"]["data"] == "img:1"
-    print("ok: top-level AG-of-IMAGE encoded per slot")
-
-    # ---- 2. Top-level AG-of-VIDEO dict encodes per-slot
-    out = await proxy_node._encode_inputs(
-        {"video_refs": {"video1": vid1, "video2": vid2}},
-    )
-    vrefs = out["video_refs"]
-    assert isinstance(vrefs, dict) and set(vrefs.keys()) == {"video1", "video2"}, vrefs
-    assert vrefs["video1"]["type"] == "video" and vrefs["video1"]["data"] == "vid:v1"
-    assert vrefs["video2"]["type"] == "video" and vrefs["video2"]["data"] == "vid:v2"
-    print("ok: top-level AG-of-VIDEO encoded per slot")
-
-    # ---- 3. DC-wrapping-AG: branch key untouched, nested AG dict encoded
-    dc_value = {
-        "model": "wan2.7-r2v",
-        "video_refs": {"video1": vid1},
-        "reference_images": {"image1": img1, "image2": img2},
-        "duration": 5,
-    }
-    out = await proxy_node._encode_inputs({"model": dc_value})
-    enc = out["model"]
-    assert enc["model"] == "wan2.7-r2v", enc
-    assert enc["duration"] == 5, enc
-    assert enc["video_refs"]["video1"]["type"] == "video"
-    assert enc["reference_images"]["image1"]["type"] == "image"
-    assert enc["reference_images"]["image2"]["type"] == "image"
-    print("ok: DC-wrapping-AG encoded leaves at every level")
-
-    # ---- 4. AUDIO dict is encoded, NOT recursed into
-    out = await proxy_node._encode_inputs({"audio": audio})
-    assert out["audio"] == {"type": "audio", "encoding": "mp3_base64", "data": "aud"}
-    print("ok: AUDIO dict still routes to encode_audio_input")
-
-    # ---- 5. Already-encoded envelope passes through (no double-encode)
-    pre_encoded = {"type": "image", "encoding": "png_base64", "data": "preimg"}
-    out = await proxy_node._encode_inputs({"images": pre_encoded})
-    assert out["images"] == pre_encoded, out
-    print("ok: pre-encoded envelope passed through unchanged")
-
-    # ---- 6. Plain scalar config dict passes through unchanged
-    out = await proxy_node._encode_inputs(
-        {"config": {"width": 1024, "height": 576, "name": "x"}},
-    )
-    assert out["config"] == {"width": 1024, "height": 576, "name": "x"}, out
-    print("ok: scalar config dict passed through unchanged")
-
-    # ---- 7. _externalize_nested walks per-slot envelopes
-    serialization._upload_log.clear()
-    big_img = torch.zeros((1, 64, 64, 3), dtype=torch.float32)
-    # encode_image_tensor stub emits ``data="img:1"`` (5 chars). Cap at 3
-    # to force every slot to externalize.
-    out = await proxy_node._encode_inputs(
-        {"reference_images": {"image1": big_img, "image2": big_img}},
-        server_url="https://fake.server",
-        max_inline_bytes=3,
-    )
-    refs = out["reference_images"]
-    assert refs["image1"].get("uri", "").startswith("https://upload/image/"), refs
-    assert refs["image2"].get("uri", "").startswith("https://upload/image/"), refs
-    assert "data" not in refs["image1"] and "data" not in refs["image2"]
-    assert len(serialization._upload_log) == 2, serialization._upload_log
-    print("ok: nested AG envelopes externalized per slot")
-
-    # ---- 7b. _externalize_nested leaves non-envelope siblings alone
-    serialization._upload_log.clear()
-    out = await proxy_node._encode_inputs(
-        {"model": {
-            "model": "wan2.7-r2v",
-            "duration": 5,
-            "reference_images": {"image1": big_img},
-        }},
-        server_url="https://fake.server",
-        max_inline_bytes=3,
-    )
-    enc = out["model"]
-    assert enc["model"] == "wan2.7-r2v" and enc["duration"] == 5, enc
-    assert enc["reference_images"]["image1"]["uri"].startswith("https://upload/image/")
-    print("ok: scalar siblings preserved alongside externalized envelopes")
-
-    # ---- 8. JSON-serializability post-condition
-    payload = await proxy_node._encode_inputs({
-        "reference_images": {"image1": img1, "image2": img2},
-        "video_refs": {"video1": vid1},
-        "audio": audio,
-        "config": {"width": 1024},
-        "scalar": "hello",
-        "n": 42,
-    })
-    json.dumps(payload)  # would raise TypeError pre-fix
-    print("ok: full encoded payload is JSON-serializable")
-
-    # ---- 9. Leaf-path regression: single-tensor / single-video / single-audio
-    out = await proxy_node._encode_inputs({"image": img1})
-    assert out["image"]["type"] == "image", out
-    out = await proxy_node._encode_inputs({"video": vid1})
-    assert out["video"]["type"] == "video", out
-    out = await proxy_node._encode_inputs({"audio": audio})
-    assert out["audio"]["type"] == "audio", out
-    out = await proxy_node._encode_inputs({"prompt": "hi", "seed": 7})
-    assert out == {"prompt": "hi", "seed": 7}, out
-    print("ok: top-level leaf path unchanged")
-
-    print("ALL OK")
-    return 0
-
-
-if __name__ == "__main__":
-    raise SystemExit(asyncio.run(main()))

notes/run_image_max_batch.py

@@ -1,441 +0,0 @@
-"""Smoke test for the descriptor-driven ``local_validate.image_max_batch``
-client-side fail-fast.
-
-Exercises the proxy_node's ``_collect_local_validate`` /
-``_enforce_local_validate`` pair against a fake descriptor that mirrors
-the Flux2 wire shape. Asserts that:
-
-1. ``_collect_local_validate`` extracts ``{"images": {"image_max_batch": 2}}``
-   from the descriptor's IMAGE-input options dict.
-2. Encoding a 3-frame tensor for that input raises ``RnpProtocolError``
-   with ``code=INPUT_INVALID`` and ``user_facing=True`` *before* any
-   serialization / HTTP attempt.
-3. A 1-frame tensor passes through cleanly.
-4. A descriptor without ``local_validate`` is a no-op.
-5. ``cap=1`` surfaces the single-frame copy.
-6. A ``local_validate`` block missing the ``image_max_batch`` key is a no-op.
-
-Run with any python that has ``torch`` available:
-
-    python notes/run_image_max_batch.py
-
-The test loads the helper functions out of ``proxy_node.py`` via AST
-extraction so it doesn't pay the cost of importing ComfyUI's
-``comfy_api`` / ``comfy_api_nodes`` packages (which the helper
-functions don't touch). Standalone — no test runner / fixtures needed.
-"""
-from __future__ import annotations
-
-import ast
-import asyncio
-import importlib.util
-import os
-import sys
-import types
-
-import torch
-
-# ---------------------------------------------------------------------------
-# Locate the worktree under test (this file's parent's parent).
-# ---------------------------------------------------------------------------
-
-_HERE = os.path.dirname(os.path.abspath(__file__))
-_CLIENT_DIR = os.path.dirname(_HERE)
-
-
-def _load_protocol() -> types.ModuleType:
-    """Load ``protocol.py`` standalone (no relative imports)."""
-    path = os.path.join(_CLIENT_DIR, "protocol.py")
-    spec = importlib.util.spec_from_file_location("rnp_smoke_protocol", path)
-    mod = importlib.util.module_from_spec(spec)
-    sys.modules[spec.name] = mod
-    spec.loader.exec_module(mod)
-    return mod
-
-
-def _build_serialization_stub(protocol: types.ModuleType) -> types.ModuleType:
-    """Minimal ``serialization`` shim covering exactly the surface
-    ``_encode_one`` / ``_enforce_local_validate`` / ``_encode_inputs`` use:
-
-    * ``_is_torch_tensor(value)`` — duck-type check for torch tensors.
-    * ``is_audio_input(value)`` — always False (no audio in this test).
-    * ``encode_image_tensor(tensor, *, accepts_batch)`` — fake envelope.
-    * ``encode_mask_tensor(tensor)`` — fake envelope.
-    * ``is_envelope(value)`` — False so ``maybe_externalize`` is skipped.
-    """
-    mod = types.ModuleType("rnp_smoke_serialization")
-
-    def _is_torch_tensor(value):  # noqa: ANN001
-        try:
-            import torch as _torch
-        except ImportError:
-            return False
-        return isinstance(value, _torch.Tensor)
-
-    def is_audio_input(value):  # noqa: ANN001
-        return isinstance(value, dict) and {"waveform", "sample_rate"} <= set(value.keys())
-
-    def encode_image_tensor(tensor, *, accepts_batch=False):  # noqa: ANN001, ARG001
-        return {"type": "image", "encoding": "png_base64", "frames": int(tensor.shape[0])}
-
-    def encode_mask_tensor(tensor):  # noqa: ANN001, ARG001
-        return {"type": "mask", "encoding": "png_base64"}
-
-    def encode_audio_input(value):  # noqa: ANN001, ARG001
-        return {"type": "audio", "encoding": "mp3_base64"}
-
-    def is_envelope(value):  # noqa: ANN001
-        return False  # smoke test never externalizes
-
-    mod._is_torch_tensor = _is_torch_tensor
-    mod.is_audio_input = is_audio_input
-    mod.encode_image_tensor = encode_image_tensor
-    mod.encode_mask_tensor = encode_mask_tensor
-    mod.encode_audio_input = encode_audio_input
-    mod.is_envelope = is_envelope
-
-    async def maybe_externalize(*args, **kwargs):  # pragma: no cover — unused
-        return args[0] if args else None
-    mod.maybe_externalize = maybe_externalize
-    return mod
-
-
-def _build_proxy_node_stub(
-    protocol: types.ModuleType, serialization: types.ModuleType,
-) -> types.ModuleType:
-    """Extract the four helper functions under test from ``proxy_node.py``
-    and exec them in a minimal namespace so we don't drag the rest of
-    the module's heavy ComfyUI imports into the test process.
-    """
-    mod = types.ModuleType("rnp_smoke_proxy_node")
-    mod.__dict__.update({
-        "Any": object,
-        "log": types.SimpleNamespace(warning=lambda *a, **kw: None),
-        "serialization": serialization,
-        "RnpProtocolError": protocol.RnpProtocolError,
-        "ErrorCode": protocol.ErrorCode,
-    })
-    src_path = os.path.join(_CLIENT_DIR, "proxy_node.py")
-    with open(src_path, "r", encoding="utf-8") as fh:
-        src = fh.read()
-    tree = ast.parse(src)
-    wanted = {
-        "_collect_local_validate",
-        "_rules_from_input_spec",
-        "_enforce_local_validate",
-        "_check_image_max_batch",
-        "_encode_one",
-        "_encode_inputs",
-    }
-    nodes = [
-        n for n in tree.body
-        if isinstance(n, (ast.AsyncFunctionDef, ast.FunctionDef)) and n.name in wanted
-    ]
-    snippet = ast.Module(body=nodes, type_ignores=[])
-    code = compile(snippet, src_path, "exec")
-    exec(code, mod.__dict__)
-    missing = wanted - set(mod.__dict__)
-    if missing:
-        raise RuntimeError(f"proxy_node helpers missing from extract: {missing}")
-    return mod
-
-
-# ---------------------------------------------------------------------------
-# Test fixtures
-# ---------------------------------------------------------------------------
-
-def _flux2_like_descriptor(cap: int) -> dict:
-    """Mirrors the Flux2 ``images`` input descriptor surface."""
-    return {
-        "name": "FakeFlux2_RNP",
-        "input": {
-            "required": {
-                "prompt": ["STRING", {"multiline": True, "default": ""}],
-            },
-            "optional": {
-                "images": ["IMAGE", {
-                    "tooltip": "Up to N images to be used as references.",
-                    "local_validate": {"image_max_batch": cap},
-                }],
-            },
-            "hidden": {},
-        },
-    }
-
-
-def _no_validate_descriptor() -> dict:
-    return {
-        "name": "FakeNoValidate_RNP",
-        "input": {
-            "required": {},
-            "optional": {
-                "images": ["IMAGE", {"tooltip": "no cap"}],
-            },
-            "hidden": {},
-        },
-    }
-
-
-def _autogrow_descriptor(cap: int, prefix: str = "reference") -> dict:
-    """Mirrors GrokVideoReferenceNode_RNP's top-level Autogrow input
-    after server descriptor unwraps the nested DynamicCombo branch
-    (kept simpler here for direct AUTOGROW coverage)."""
-    return {
-        "name": "FakeAutogrow_RNP",
-        "input": {
-            "required": {
-                "reference_images": ["AUTOGROW", {
-                    "template": ["IMAGE", {
-                        "local_validate": {"image_max_batch": cap},
-                    }],
-                    "prefix": prefix,
-                    "min": 1,
-                    "max": cap,
-                }],
-            },
-            "optional": {},
-            "hidden": {},
-        },
-    }
-
-
-def _dyncombo_with_autogrow_descriptor() -> dict:
-    """Mirrors GrokImageEditNodeV2_RNP's ``model`` DynamicCombo with
-    two branches each carrying an Autogrow ``images`` template — one
-    capped at 3, the other at 1."""
-    def branch(key: str, cap: int) -> dict:
-        return {
-            "key": key,
-            "inputs": [
-                ["images", "AUTOGROW", {
-                    "template": ["IMAGE", {
-                        "local_validate": {"image_max_batch": cap},
-                    }],
-                    "prefix": "image",
-                    "min": 1,
-                    "max": cap,
-                }],
-                ["resolution", "COMBO", {"options": ["1K", "2K"]}],
-            ],
-        }
-    return {
-        "name": "FakeDynComboAutogrow_RNP",
-        "input": {
-            "required": {
-                "model": ["DYNAMIC_COMBO", {
-                    "options": [
-                        branch("grok-imagine-image-quality", 3),
-                        branch("grok-imagine-image-pro", 1),
-                    ],
-                }],
-            },
-            "optional": {},
-            "hidden": {},
-        },
-    }
-
-
-# ---------------------------------------------------------------------------
-# Tests
-# ---------------------------------------------------------------------------
-
-async def main() -> int:
-    protocol = _load_protocol()
-    serialization = _build_serialization_stub(protocol)
-    proxy_node = _build_proxy_node_stub(protocol, serialization)
-
-    # ---- 1. _collect_local_validate extracts the rule
-    desc = _flux2_like_descriptor(cap=2)
-    rules = proxy_node._collect_local_validate(desc)
-    assert rules == {"images": {"image_max_batch": 2}}, rules
-    print("ok: _collect_local_validate extracted", rules)
-
-    # ---- 2. over-cap tensor raises INPUT_INVALID before encoding
-    over_cap = torch.zeros((3, 64, 64, 3), dtype=torch.float32)
-    raised = False
-    try:
-        await proxy_node._encode_inputs(
-            {"images": over_cap},
-            input_serialization={"images": ["png_base64", "png_base64_batch"]},
-            local_validate=rules,
-            node_id="FakeFlux2_RNP",
-        )
-    except protocol.RnpProtocolError as e:
-        raised = True
-        assert e.code == protocol.ErrorCode.INPUT_INVALID, e.code
-        assert e.user_facing is True, e.user_facing
-        msg = str(e)
-        assert "FakeFlux2_RNP" in msg, msg
-        assert "3" in msg and "2" in msg, msg
-        print("ok: over-cap raised INPUT_INVALID:", msg)
-    assert raised, "over-cap tensor did not raise"
-
-    # ---- 3. at-cap tensor passes through (no exception)
-    at_cap = torch.zeros((2, 64, 64, 3), dtype=torch.float32)
-    out = await proxy_node._encode_inputs(
-        {"images": at_cap},
-        input_serialization={"images": ["png_base64", "png_base64_batch"]},
-        local_validate=rules,
-        node_id="FakeFlux2_RNP",
-    )
-    assert "images" in out
-    print("ok: at-cap (B=2) encoded without error")
-
-    # ---- 4. cap=1 / multi-frame raises with the single-frame copy
-    desc1 = _flux2_like_descriptor(cap=1)
-    rules1 = proxy_node._collect_local_validate(desc1)
-    raised = False
-    try:
-        await proxy_node._encode_inputs(
-            {"images": over_cap},
-            local_validate=rules1,
-            node_id="FakeI2V_RNP",
-        )
-    except protocol.RnpProtocolError as e:
-        raised = True
-        assert e.code == protocol.ErrorCode.INPUT_INVALID
-        assert "single image" in str(e), str(e)
-        print("ok: cap=1 single-frame copy fired:", str(e))
-    assert raised
-
-    # ---- 5. descriptor without local_validate is a no-op
-    desc_n = _no_validate_descriptor()
-    rules_n = proxy_node._collect_local_validate(desc_n)
-    assert rules_n == {}, rules_n
-    out = await proxy_node._encode_inputs(
-        {"images": over_cap},
-        input_serialization={"images": ["png_base64", "png_base64_batch"]},
-        local_validate=rules_n,
-        node_id="FakeNoValidate_RNP",
-    )
-    assert "images" in out
-    print("ok: missing local_validate is a no-op")
-
-    # ---- 6. local_validate block without image_max_batch sub-key is a no-op
-    out = await proxy_node._encode_inputs(
-        {"images": over_cap},
-        input_serialization={"images": ["png_base64", "png_base64_batch"]},
-        local_validate={"images": {"some_other_rule": 7}},
-        node_id="FakeOther_RNP",
-    )
-    assert "images" in out
-    print("ok: missing image_max_batch sub-key is a no-op")
-
-    # ---- 7. AUTOGROW: each slot value enforced against the template cap
-    desc_ag = _autogrow_descriptor(cap=2)
-    rules_ag = proxy_node._collect_local_validate(desc_ag)
-    assert "reference_images" in rules_ag, rules_ag
-    assert rules_ag["reference_images"].get("__template__") == {"image_max_batch": 2}, rules_ag
-    print("ok: AUTOGROW collected __template__ rules:", rules_ag)
-
-    one_frame = torch.zeros((1, 64, 64, 3), dtype=torch.float32)
-    raised = False
-    try:
-        # Slot 1 is over-cap (B=3 > cap=2) → should fire on that slot
-        await proxy_node._encode_inputs(
-            {"reference_images": {"reference0": one_frame, "reference1": over_cap}},
-            local_validate=rules_ag,
-            node_id="FakeAutogrow_RNP",
-        )
-    except protocol.RnpProtocolError as e:
-        raised = True
-        assert e.code == protocol.ErrorCode.INPUT_INVALID
-        msg = str(e)
-        # Slot path label should mention reference_images.<slot_key>
-        assert "reference_images" in msg, msg
-        assert "reference1" in msg, msg
-        print("ok: AUTOGROW slot over-cap fired:", msg)
-    assert raised, "AUTOGROW slot over-cap did not raise"
-
-    # All-under-cap autogrow passes (no exception)
-    out = await proxy_node._encode_inputs(
-        {"reference_images": {"reference0": one_frame, "reference1": one_frame, "reference2": None}},
-        local_validate=rules_ag,
-        node_id="FakeAutogrow_RNP",
-    )
-    assert "reference_images" in out
-    print("ok: AUTOGROW all-under-cap (None slots tolerated) passed")
-
-    # ---- 8. DYNAMIC_COMBO with nested AUTOGROW: branch-aware enforcement
-    desc_dc = _dyncombo_with_autogrow_descriptor()
-    rules_dc = proxy_node._collect_local_validate(desc_dc)
-    assert "model" in rules_dc, rules_dc
-    branches = rules_dc["model"].get("__branches__")
-    assert isinstance(branches, dict), rules_dc
-    assert "grok-imagine-image-quality" in branches
-    assert "grok-imagine-image-pro" in branches
-    assert branches["grok-imagine-image-quality"]["images"]["__template__"] == {"image_max_batch": 3}
-    assert branches["grok-imagine-image-pro"]["images"]["__template__"] == {"image_max_batch": 1}
-    print("ok: DYNAMIC_COMBO collected branch-keyed templates")
-
-    # Branch A (cap=3): slot with B=4 should raise
-    over_4 = torch.zeros((4, 64, 64, 3), dtype=torch.float32)
-    raised = False
-    try:
-        await proxy_node._encode_inputs(
-            {"model": {
-                "model": "grok-imagine-image-quality",
-                "resolution": "1K",
-                "images": {"image0": over_4},
-            }},
-            local_validate=rules_dc,
-            node_id="FakeDynComboAutogrow_RNP",
-        )
-    except protocol.RnpProtocolError as e:
-        raised = True
-        assert e.code == protocol.ErrorCode.INPUT_INVALID
-        msg = str(e)
-        assert "image0" in msg and "3" in msg and "4" in msg, msg
-        print("ok: DYNAMIC_COMBO branch-A (cap=3) fired on B=4 slot:", msg)
-    assert raised
-
-    # Branch A (cap=3): all slots within cap → passes
-    out = await proxy_node._encode_inputs(
-        {"model": {
-            "model": "grok-imagine-image-quality",
-            "resolution": "2K",
-            "images": {"image0": one_frame, "image1": one_frame, "image2": one_frame},
-        }},
-        local_validate=rules_dc,
-        node_id="FakeDynComboAutogrow_RNP",
-    )
-    assert "model" in out
-    print("ok: DYNAMIC_COMBO branch-A all-under-cap passed")
-
-    # Branch B (cap=1): a B=3 slot fires the single-frame copy
-    raised = False
-    try:
-        await proxy_node._encode_inputs(
-            {"model": {
-                "model": "grok-imagine-image-pro",
-                "resolution": "2K",
-                "images": {"image0": over_cap},
-            }},
-            local_validate=rules_dc,
-            node_id="FakeDynComboAutogrow_RNP",
-        )
-    except protocol.RnpProtocolError as e:
-        raised = True
-        assert e.code == protocol.ErrorCode.INPUT_INVALID
-        assert "single image" in str(e), str(e)
-        print("ok: DYNAMIC_COMBO branch-B (cap=1) fired single-frame copy:", str(e))
-    assert raised
-
-    # Unknown branch key → no enforcement (defensive)
-    out = await proxy_node._encode_inputs(
-        {"model": {
-            "model": "unknown-branch-key",
-            "images": {"image0": over_cap},
-        }},
-        local_validate=rules_dc,
-        node_id="FakeDynComboAutogrow_RNP",
-    )
-    assert "model" in out
-    print("ok: DYNAMIC_COMBO unknown branch key is a defensive no-op")
-
-    print("PASS: image_max_batch local_validate smoke test (incl. nested traversal)")
-    return 0
-
-
-if __name__ == "__main__":
-    sys.exit(asyncio.run(main()))

notes/run_model3d_bundle_decoder.py

@@ -1,461 +0,0 @@
-"""Smoke test for the client-side multi-file MODEL_3D bundle decoder.
-
-Verifies:
-
-1. ``Capability.MODEL_3D_BUNDLE_INLINE`` is intact at the vendored
-   protocol layer and exposed as the well-formed
-   ``model_3d:bundle_inline`` token.
-2. ``is_envelope`` recognises a ``bundle_inline`` envelope (still
-   ``type=model_3d`` — HEAVY_TYPES unchanged).
-3. ``decode_model3d_envelope`` dispatches ``encoding=bundle_inline``
-   to the new ``BundledFile3D`` class, returns a real ``File3D``
-   subclass, and round-trips the primary mesh bytes via
-   ``get_data()`` / ``get_bytes()`` without materialising anything
-   on disk.
-4. ``get_source()`` materialises the whole bundle into a temp
-   directory using the producer-supplied relative paths, so a .obj
-   that references its .mtl by filename (and a texture in
-   ``textures/``) finds them on disk via the filesystem.
-5. ``save_to(dest)`` copies the whole bundle into the destination
-   directory — the primary file under the caller-specified name,
-   sidecars under their ORIGINAL relative paths — so cross-file refs
-   inside the .obj (which point at ``model.mtl``) still resolve when
-   the user saves the model somewhere stable.
-6. Bundle-specific accessors (``primary_path``, ``file_paths``,
-   ``file_bytes``, ``file_role``, ``paths_with_role``) return the
-   expected values; unknown roles round-trip without error.
-7. Malformed bundle envelopes (missing primary_path, missing
-   files, missing data, primary_path not in files) raise
-   ``RnpProtocolError`` with ``code=INTERNAL`` — no opaque
-   fallthrough.
-8. End-to-end against the server's ``make_model3d_bundle_envelope``
-   helper (imported from the comfy-rnp-server worktree) — the bytes
-   the server packs into each file are exactly the bytes the
-   client unpacks, and the path sanitization happens server-side so
-   the client never sees a malicious path.
-9. ``CLIENT_CAPABILITIES`` advertises ``model_3d:bundle_inline``
-   so server-side capability-gated descriptors negotiate cleanly.
-
-Run with the ComfyUI venv (needs torch / comfy_api on PYTHONPATH):
-
-    python notes/run_model3d_bundle_decoder.py
-"""
-from __future__ import annotations
-
-import base64
-import importlib.util
-import os
-import shutil
-import sys
-import tempfile
-import types
-
-# ---------------------------------------------------------------------------
-# Locate the worktree under test.
-# ---------------------------------------------------------------------------
-_HERE = os.path.dirname(os.path.abspath(__file__))
-_CLIENT_DIR = os.path.dirname(_HERE)
-_COMFYUI_DIR = os.path.dirname(os.path.dirname(_CLIENT_DIR))
-_SERVER_DIR = os.path.normpath(
-    os.path.join(_COMFYUI_DIR, "..", "comfy-rnp-server")
-)
-
-
-def _load_module(name: str, path: str) -> types.ModuleType:
-    spec = importlib.util.spec_from_file_location(name, path)
-    mod = importlib.util.module_from_spec(spec)
-    sys.modules[name] = mod
-    spec.loader.exec_module(mod)
-    return mod
-
-
-# Make ComfyUI importable so ``comfy_api.latest._util.geometry_types.File3D``
-# resolves at first BundledFile3D construction.
-if _COMFYUI_DIR not in sys.path:
-    sys.path.insert(0, _COMFYUI_DIR)
-if _SERVER_DIR not in sys.path:
-    sys.path.insert(0, _SERVER_DIR)
-
-# ComfyUI's full ``comfy_api`` tree pulls torch / PIL / comfy_execution at
-# import time. Stub just what BundledFile3D needs — the leaf
-# ``comfy_api.latest._util.geometry_types.File3D`` class with a faithful
-# subclass-friendly implementation.
-class _StubFile3D:
-    """Faithful subset of upstream ``comfy_api.latest._util.geometry_types.File3D``.
-
-    Implements the same parent-class shape (``_source`` / ``_format``
-    attrs + ``get_source`` / ``get_data`` / ``get_bytes`` / ``save_to``
-    methods) so subclassing it produces an object indistinguishable
-    from the real thing for the decoder's purposes. The smoke test
-    deliberately stubs torch + the heavy ``comfy_api.latest._util``
-    package init to keep the test runnable in the rnp venv.
-    """
-    def __init__(self, source, file_format: str = "") -> None:
-        self._source = source
-        self._format = (file_format or "").lstrip(".").lower()
-
-    @property
-    def format(self) -> str:
-        return self._format
-
-    @format.setter
-    def format(self, value: str) -> None:
-        self._format = (value or "").lstrip(".").lower()
-
-
-# Stub ``comfy_api.latest._util`` and the nested ``geometry_types`` module
-# so ``from comfy_api.latest._util.geometry_types import File3D`` works
-# without pulling torch / PIL / etc.
-_comfy_api = types.ModuleType("comfy_api")
-_comfy_api.__path__ = []  # type: ignore[attr-defined]
-_comfy_api_latest = types.ModuleType("comfy_api.latest")
-_comfy_api_latest.__path__ = []  # type: ignore[attr-defined]
-_comfy_api_latest_util = types.ModuleType("comfy_api.latest._util")
-_comfy_api_latest_util.__path__ = []  # type: ignore[attr-defined]
-_comfy_api_latest_util.File3D = _StubFile3D
-_comfy_api_latest_util_geom = types.ModuleType("comfy_api.latest._util.geometry_types")
-_comfy_api_latest_util_geom.File3D = _StubFile3D
-sys.modules.setdefault("comfy_api", _comfy_api)
-sys.modules.setdefault("comfy_api.latest", _comfy_api_latest)
-sys.modules.setdefault("comfy_api.latest._util", _comfy_api_latest_util)
-sys.modules.setdefault("comfy_api.latest._util.geometry_types", _comfy_api_latest_util_geom)
-
-# Emulate the client package layout for the relative imports.
-pkg = types.ModuleType("comfy_remote_nodes_test")
-pkg.__path__ = [_CLIENT_DIR]
-sys.modules["comfy_remote_nodes_test"] = pkg
-
-protocol = _load_module(
-    "comfy_remote_nodes_test.protocol",
-    os.path.join(_CLIENT_DIR, "protocol.py"),
-)
-# serialization imports ``client`` for ``rnp_client``; the bundle decoder
-# doesn't use it, so a tiny stub suffices.
-sys.modules["comfy_remote_nodes_test.client"] = types.ModuleType(
-    "comfy_remote_nodes_test.client",
-)
-serialization = _load_module(
-    "comfy_remote_nodes_test.serialization",
-    os.path.join(_CLIENT_DIR, "serialization.py"),
-)
-
-
-# ---------------------------------------------------------------------------
-# Build a minimal Wavefront-OBJ + MTL + PNG-stub bundle for the round-trip.
-# These bytes don't need to be loadable by an actual OBJ parser — the
-# decoder is bytes-in / bytes-out — but using realistic content makes
-# debugging easier if a future regression breaks the cross-file refs.
-# ---------------------------------------------------------------------------
-def _make_minimal_obj() -> bytes:
-    return (
-        b"# Minimal OBJ for RNP bundle smoke test.\n"
-        b"mtllib model.mtl\n"
-        b"v 0.0 0.0 0.0\nv 1.0 0.0 0.0\nv 0.0 1.0 0.0\n"
-        b"usemtl test_material\n"
-        b"f 1 2 3\n"
-    )
-
-
-def _make_minimal_mtl() -> bytes:
-    return (
-        b"# Minimal MTL for RNP bundle smoke test.\n"
-        b"newmtl test_material\n"
-        b"Ka 1.0 1.0 1.0\n"
-        b"Kd 1.0 1.0 1.0\n"
-        b"map_Kd textures/albedo.png\n"
-        b"map_bump textures/normal.png\n"
-    )
-
-
-def _make_stub_png(tag: bytes) -> bytes:
-    # Not a real PNG — the decoder doesn't parse it. Tag distinguishes
-    # each "texture" so the round-trip assertions can pin which bytes
-    # went where.
-    return b"\x89PNG\r\n\x1a\n" + tag
-
-
-obj_bytes = _make_minimal_obj()
-mtl_bytes = _make_minimal_mtl()
-albedo_bytes = _make_stub_png(b"ALBEDO_STUB")
-normal_bytes = _make_stub_png(b"NORMAL_STUB")
-roughness_bytes = _make_stub_png(b"ROUGHNESS_STUB")
-
-
-# ---------------------------------------------------------------------------
-# 1. Capability constant intact at the vendored protocol layer.
-# ---------------------------------------------------------------------------
-assert protocol.Capability.MODEL_3D_BUNDLE_INLINE == "model_3d:bundle_inline", (
-    f"Capability.MODEL_3D_BUNDLE_INLINE wrong value: "
-    f"{protocol.Capability.MODEL_3D_BUNDLE_INLINE!r}"
-)
-print("PASS: Capability.MODEL_3D_BUNDLE_INLINE = 'model_3d:bundle_inline'.")
-
-
-# ---------------------------------------------------------------------------
-# Build a hand-crafted bundle envelope for the next several checks.
-# ---------------------------------------------------------------------------
-hand_envelope = {
-    "type":         "model_3d",
-    "encoding":     "bundle_inline",
-    "format":       "obj",
-    "primary_path": "model.obj",
-    "files": [
-        {"path": "model.obj",            "format": "obj", "role": "mesh",
-         "data": base64.b64encode(obj_bytes).decode("ascii"),
-         "byte_size": len(obj_bytes)},
-        {"path": "model.mtl",            "format": "mtl", "role": "material",
-         "data": base64.b64encode(mtl_bytes).decode("ascii")},
-        {"path": "textures/albedo.png",  "format": "png", "role": "texture_diffuse",
-         "data": base64.b64encode(albedo_bytes).decode("ascii")},
-        {"path": "textures/normal.png",  "format": "png", "role": "texture_normal",
-         "data": base64.b64encode(normal_bytes).decode("ascii")},
-        {"path": "textures/roughness.png","format": "png","role": "texture_roughness",
-         "data": base64.b64encode(roughness_bytes).decode("ascii")},
-        # Unknown role — must round-trip without error.
-        {"path": "extras/notes.txt",     "role": "producer_notes",
-         "data": base64.b64encode(b"hello").decode("ascii")},
-    ],
-}
-
-
-# ---------------------------------------------------------------------------
-# 2. is_envelope recognises a bundle envelope.
-# ---------------------------------------------------------------------------
-assert protocol.is_envelope(hand_envelope), (
-    "is_envelope returned False for a well-formed bundle_inline envelope; "
-    "HEAVY_TYPES update somehow regressed."
-)
-print("PASS: is_envelope recognises bundle_inline envelopes.")
-
-
-# ---------------------------------------------------------------------------
-# 3. decode_model3d_envelope dispatches + round-trips primary bytes.
-# ---------------------------------------------------------------------------
-bundle = serialization.decode_model3d_envelope(hand_envelope)
-bundle_cls = serialization._bundled_file3d_class()
-assert isinstance(bundle, bundle_cls), (
-    f"decode_model3d_envelope should return BundledFile3D, got "
-    f"{type(bundle).__name__}"
-)
-# It must ALSO be a File3D (parent class) — that's the whole point of
-# the subclass approach.
-assert isinstance(bundle, _StubFile3D), (
-    f"BundledFile3D must subclass File3D — got {type(bundle).__mro__}"
-)
-# Primary file bytes round-trip via get_data / get_bytes (no disk I/O).
-assert bundle.get_bytes() == obj_bytes, (
-    f"primary OBJ bytes lost: {len(bundle.get_bytes())} vs {len(obj_bytes)}"
-)
-src = bundle.get_data()
-src.seek(0)
-assert src.read() == obj_bytes, "primary OBJ get_data() didn't round-trip"
-assert bundle.format == "obj", f"primary format wrong: {bundle.format!r}"
-print("PASS: decode_model3d_envelope returns BundledFile3D + primary bytes round-trip.")
-
-
-# ---------------------------------------------------------------------------
-# 4. get_source() materialises the whole bundle on disk.
-# ---------------------------------------------------------------------------
-disk_path = bundle.get_source()
-assert os.path.isfile(disk_path), f"get_source() should return existing path: {disk_path}"
-assert disk_path.endswith("model.obj"), f"primary path wrong: {disk_path}"
-with open(disk_path, "rb") as f:
-    assert f.read() == obj_bytes, "disk-materialised primary OBJ bytes mismatched"
-# Sidecars must be at the SAME relative paths so the .obj's mtllib /
-# map_Kd refs resolve.
-temp_root = bundle.materialize_to_temp_dir()
-assert os.path.isfile(os.path.join(temp_root, "model.mtl")), (
-    "model.mtl missing from materialised bundle"
-)
-assert os.path.isfile(os.path.join(temp_root, "textures", "albedo.png")), (
-    "textures/albedo.png missing from materialised bundle"
-)
-assert os.path.isfile(os.path.join(temp_root, "textures", "normal.png"))
-assert os.path.isfile(os.path.join(temp_root, "textures", "roughness.png"))
-assert os.path.isfile(os.path.join(temp_root, "extras", "notes.txt"))
-# Sidecar bytes match.
-with open(os.path.join(temp_root, "model.mtl"), "rb") as f:
-    assert f.read() == mtl_bytes
-with open(os.path.join(temp_root, "textures", "albedo.png"), "rb") as f:
-    assert f.read() == albedo_bytes
-print("PASS: get_source() materialises whole bundle on disk at producer-supplied paths.")
-
-
-# ---------------------------------------------------------------------------
-# 5. save_to(dest) copies the whole bundle into the destination directory.
-# ---------------------------------------------------------------------------
-save_dir = tempfile.mkdtemp(prefix="rnp_save_to_test_")
-try:
-    out_path = bundle.save_to(os.path.join(save_dir, "renamed_scene.obj"))
-    assert os.path.isfile(out_path)
-    with open(out_path, "rb") as f:
-        assert f.read() == obj_bytes, "primary OBJ bytes wrong after save_to"
-    # Sidecars keep ORIGINAL filenames so cross-file refs inside the
-    # OBJ (which point at "model.mtl") still resolve relative to the
-    # renamed primary file's directory.
-    assert os.path.isfile(os.path.join(save_dir, "model.mtl")), (
-        "save_to should copy model.mtl alongside the renamed primary"
-    )
-    assert os.path.isfile(os.path.join(save_dir, "textures", "albedo.png"))
-    assert os.path.isfile(os.path.join(save_dir, "textures", "normal.png"))
-    with open(os.path.join(save_dir, "textures", "normal.png"), "rb") as f:
-        assert f.read() == normal_bytes
-    print("PASS: save_to copies whole bundle, primary renamed, sidecars preserve filenames.")
-finally:
-    shutil.rmtree(save_dir, ignore_errors=True)
-
-
-# ---------------------------------------------------------------------------
-# 6. Bundle-specific accessors.
-# ---------------------------------------------------------------------------
-assert bundle.primary_path == "model.obj"
-assert set(bundle.file_paths) == {
-    "model.obj", "model.mtl",
-    "textures/albedo.png", "textures/normal.png", "textures/roughness.png",
-    "extras/notes.txt",
-}
-assert bundle.file_bytes("textures/albedo.png") == albedo_bytes
-# Optional roles.
-assert bundle.file_role("model.obj") == "mesh"
-assert bundle.file_role("textures/normal.png") == "texture_normal"
-# Unknown roles round-trip — no enum check.
-assert bundle.file_role("extras/notes.txt") == "producer_notes"
-# Missing role (none supplied) returns None.
-assert bundle.file_role("nonexistent.png") is None
-# Convenience lookup.
-assert bundle.paths_with_role("texture_normal") == ["textures/normal.png"]
-assert bundle.paths_with_role("nonexistent_role") == []
-print("PASS: bundle accessors (primary_path / file_paths / file_role / paths_with_role).")
-
-
-# ---------------------------------------------------------------------------
-# 7. Malformed bundle envelopes raise RnpProtocolError with code=INTERNAL.
-# ---------------------------------------------------------------------------
-def _expect_protocol_error(bad_env: dict, needle: str) -> None:
-    try:
-        serialization.decode_model3d_envelope(bad_env)
-    except protocol.RnpProtocolError as e:
-        assert e.code == protocol.ErrorCode.INTERNAL, f"wrong error code: {e.code}"
-        assert needle in str(e), f"error msg doesn't mention {needle!r}: {e}"
-    else:
-        raise AssertionError(f"expected RnpProtocolError for {needle!r}")
-
-_expect_protocol_error(
-    {"type": "model_3d", "encoding": "bundle_inline", "files": [
-        {"path": "x.obj", "data": "AA=="},
-    ]},
-    "primary_path",
-)
-_expect_protocol_error(
-    {"type": "model_3d", "encoding": "bundle_inline", "primary_path": "x.obj"},
-    "files",
-)
-_expect_protocol_error(
-    {"type": "model_3d", "encoding": "bundle_inline", "primary_path": "x.obj",
-     "files": [{"path": "y.obj", "data": "AA=="}]},
-    "primary_path 'x.obj' not in",
-)
-_expect_protocol_error(
-    {"type": "model_3d", "encoding": "bundle_inline", "primary_path": "x.obj",
-     "files": [{"path": "x.obj"}]},  # missing data
-    "missing inline 'data'",
-)
-_expect_protocol_error(
-    {"type": "model_3d", "encoding": "wat_inline", "data": "AA=="},
-    "Unsupported model_3d encoding",
-)
-print("PASS: malformed bundle envelopes raise RnpProtocolError(INTERNAL).")
-
-
-# ---------------------------------------------------------------------------
-# 8. End-to-end: server make_model3d_bundle_envelope -> client decode.
-#    Skips when the server worktree isn't on disk.
-# ---------------------------------------------------------------------------
-server_protocol_path = os.path.join(
-    _SERVER_DIR, "comfy_rnp_protocol", "envelopes.py",
-)
-if os.path.exists(server_protocol_path):
-    server_pkg = types.ModuleType("comfy_rnp_protocol_e2e_bundle")
-    server_pkg.__path__ = [os.path.join(_SERVER_DIR, "comfy_rnp_protocol")]
-    sys.modules["comfy_rnp_protocol_e2e_bundle"] = server_pkg
-    _load_module(
-        "comfy_rnp_protocol_e2e_bundle.constants",
-        os.path.join(_SERVER_DIR, "comfy_rnp_protocol", "constants.py"),
-    )
-    server_envelopes = _load_module(
-        "comfy_rnp_protocol_e2e_bundle.envelopes",
-        os.path.join(_SERVER_DIR, "comfy_rnp_protocol", "envelopes.py"),
-    )
-    assert hasattr(server_envelopes, "make_model3d_bundle_envelope"), (
-        "Server envelopes module missing make_model3d_bundle_envelope — "
-        "server-side PR #38 should have added it."
-    )
-    server_env = server_envelopes.make_model3d_bundle_envelope(
-        files=[
-            {"path": "model.obj",            "format": "obj", "role": "mesh",
-             "data": base64.b64encode(obj_bytes).decode("ascii"),
-             "byte_size": len(obj_bytes)},
-            {"path": "model.mtl",            "format": "mtl", "role": "material",
-             "data": base64.b64encode(mtl_bytes).decode("ascii")},
-            {"path": "textures/albedo.png",  "format": "png", "role": "texture_diffuse",
-             "data": base64.b64encode(albedo_bytes).decode("ascii")},
-        ],
-        primary_path="model.obj",
-        format="obj",
-    )
-    assert server_env["type"] == "model_3d", server_env
-    assert server_env["encoding"] == "bundle_inline", server_env
-    assert server_env["primary_path"] == "model.obj"
-    assert len(server_env["files"]) == 3
-    # Path sanitization happens server-side. Confirm a malicious path
-    # would be rejected at envelope build time (defence-in-depth — the
-    # client decoder doesn't see this).
-    try:
-        server_envelopes.make_model3d_bundle_envelope(
-            files=[{"path": "../etc/passwd", "data": "AA=="}],
-            primary_path="../etc/passwd",
-        )
-    except ValueError as e:
-        assert "parent-dir" in str(e) or "absolute" in str(e), (
-            f"path sanitization mistake: {e!r}"
-        )
-    else:
-        raise AssertionError("server should reject '..' path at envelope build time")
-    # Pipe through the client decoder.
-    server_bundle = serialization.decode_model3d_envelope(server_env)
-    assert isinstance(server_bundle, bundle_cls), (
-        f"server-built envelope decoded to wrong type: {type(server_bundle)}"
-    )
-    assert server_bundle.get_bytes() == obj_bytes
-    assert server_bundle.file_bytes("textures/albedo.png") == albedo_bytes
-    assert server_bundle.file_role("model.obj") == "mesh"
-    print(
-        "PASS: end-to-end server make_model3d_bundle_envelope -> client "
-        "decode_model3d_envelope preserves all files + roles + bytes."
-    )
-else:
-    print(
-        f"SKIP end-to-end: server worktree not found at {_SERVER_DIR!r}"
-    )
-
-
-# ---------------------------------------------------------------------------
-# 9. CLIENT_CAPABILITIES advertises model_3d:bundle_inline.
-#    client.py imports aiohttp / comfy_api_nodes — same source-level
-#    contract check we used for the GLB cap in PR #1.
-# ---------------------------------------------------------------------------
-client_src = open(
-    os.path.join(_CLIENT_DIR, "client.py"), "r", encoding="utf-8",
-).read()
-assert "CLIENT_CAPABILITIES = [" in client_src, (
-    "client.py missing CLIENT_CAPABILITIES list"
-)
-cc_start = client_src.index("CLIENT_CAPABILITIES = [")
-cc_end = client_src.index("]", cc_start)
-cc_block = client_src[cc_start:cc_end]
-assert "Capability.MODEL_3D_BUNDLE_INLINE" in cc_block, (
-    "Capability.MODEL_3D_BUNDLE_INLINE not advertised in CLIENT_CAPABILITIES"
-)
-print("PASS: CLIENT_CAPABILITIES advertises Capability.MODEL_3D_BUNDLE_INLINE.")
-
-print("ALL CHECKS PASSED.")

notes/run_model3d_decoder.py

@@ -1,316 +0,0 @@
-"""Smoke test for the client-side MODEL_3D decoder.
-
-Verifies:
-
-1. The vendored ``protocol.HEAVY_TYPES`` now recognises ``model_3d`` so
-   ``is_envelope`` returns True for an inbound MODEL_3D envelope.
-2. ``serialization.decode_model3d_envelope`` round-trips an inline
-   ``glb_inline`` envelope into a ``comfy_api.latest._util.File3D``
-   whose ``BytesIO`` payload matches the original GLB bytes.
-3. ``decode_envelope`` dispatches ``type=model_3d`` to the new decoder.
-4. The proxy_node ``_OUTPUT_CLASSES`` now maps ``"MODEL_3D"`` to
-   ``IO.File3DGLB.Output`` so a descriptor with ``output=["MODEL_3D"]``
-   parses without falling through to the opaque IO.Custom branch.
-5. ``client.CLIENT_CAPABILITIES`` advertises
-   ``model_3d:glb_inline`` on every outbound request so descriptors
-   gated on the token negotiate cleanly.
-6. End-to-end against the server's ``make_model3d_envelope`` helper
-   (imported from the comfy-rnp-server worktree) — the bytes the
-   server packs are exactly the bytes the client decodes.
-
-Run with the ComfyUI venv (needs torch / comfy_api on PYTHONPATH):
-
-    python notes/run_model3d_decoder.py
-"""
-from __future__ import annotations
-
-import base64
-import importlib.util
-import io
-import json
-import os
-import sys
-import types
-
-# ---------------------------------------------------------------------------
-# Locate the worktree under test.
-# ---------------------------------------------------------------------------
-_HERE = os.path.dirname(os.path.abspath(__file__))
-_CLIENT_DIR = os.path.dirname(_HERE)
-_COMFYUI_DIR = os.path.dirname(os.path.dirname(_CLIENT_DIR))
-_SERVER_DIR = os.path.normpath(
-    os.path.join(_COMFYUI_DIR, "..", "comfy-rnp-server")
-)
-
-
-def _load_module(name: str, path: str) -> types.ModuleType:
-    spec = importlib.util.spec_from_file_location(name, path)
-    mod = importlib.util.module_from_spec(spec)
-    sys.modules[name] = mod
-    spec.loader.exec_module(mod)
-    return mod
-
-
-# Make ComfyUI importable so ``comfy_api.latest._util.File3D`` resolves.
-if _COMFYUI_DIR not in sys.path:
-    sys.path.insert(0, _COMFYUI_DIR)
-# And the server worktree so we can import the ENCODER side end-to-end.
-if _SERVER_DIR not in sys.path:
-    sys.path.insert(0, _SERVER_DIR)
-
-# ComfyUI's full ``comfy_api`` tree pulls torch / PIL / comfy /
-# comfy_execution at import time — way too heavy for a decoder
-# round-trip check. Stub just the leaf module our decoder imports
-# (``comfy_api.latest._util``) with a faithful pure-Python ``File3D``.
-class _StubFile3D:
-    def __init__(self, source, file_format: str = "") -> None:
-        self._source = source
-        self._format = file_format
-
-_comfy_api = types.ModuleType("comfy_api")
-_comfy_api_latest = types.ModuleType("comfy_api.latest")
-_comfy_api_latest_util = types.ModuleType("comfy_api.latest._util")
-_comfy_api_latest_util.File3D = _StubFile3D
-_comfy_api.latest = _comfy_api_latest
-_comfy_api_latest._util = _comfy_api_latest_util
-sys.modules.setdefault("comfy_api", _comfy_api)
-sys.modules.setdefault("comfy_api.latest", _comfy_api_latest)
-sys.modules.setdefault("comfy_api.latest._util", _comfy_api_latest_util)
-
-# Load the client modules as if they were a package — the ``protocol``
-# module imports from ``.protocol`` relative to its package, so we
-# emulate the package layout under the name ``comfy_remote_nodes``.
-pkg = types.ModuleType("comfy_remote_nodes_test")
-pkg.__path__ = [_CLIENT_DIR]
-sys.modules["comfy_remote_nodes_test"] = pkg
-
-protocol = _load_module(
-    "comfy_remote_nodes_test.protocol",
-    os.path.join(_CLIENT_DIR, "protocol.py"),
-)
-# serialization imports ``client`` for ``rnp_client`` but we don't need
-# the HTTP client for the decoder path; provide a tiny stub so the
-# import succeeds.
-client_stub = types.ModuleType("comfy_remote_nodes_test.client")
-sys.modules["comfy_remote_nodes_test.client"] = client_stub
-serialization = _load_module(
-    "comfy_remote_nodes_test.serialization",
-    os.path.join(_CLIENT_DIR, "serialization.py"),
-)
-
-
-# ---------------------------------------------------------------------------
-# Build a minimal valid binary glTF 2.0 (GLB) payload for the round-trip.
-# Format: 12-byte header + N chunks. Header: magic(4) + version(4) + length(4).
-# Magic must be b"glTF", version=2. We include exactly one JSON chunk that
-# describes an empty asset (enough to satisfy any GLB-magic check; downstream
-# nodes do their own validation).
-# ---------------------------------------------------------------------------
-def _make_minimal_glb() -> bytes:
-    json_payload = b'{"asset":{"version":"2.0"}}'
-    # Chunks must be 4-byte aligned; pad JSON with spaces (0x20).
-    pad = (4 - (len(json_payload) % 4)) % 4
-    json_payload = json_payload + (b" " * pad)
-    json_chunk = (
-        len(json_payload).to_bytes(4, "little")  # chunk length
-        + b"JSON"                                  # chunk type
-        + json_payload                             # chunk data
-    )
-    total = 12 + len(json_chunk)
-    header = (
-        b"glTF"
-        + (2).to_bytes(4, "little")
-        + total.to_bytes(4, "little")
-    )
-    return header + json_chunk
-
-
-# ---------------------------------------------------------------------------
-# 1. HEAVY_TYPES recognises model_3d.
-# ---------------------------------------------------------------------------
-assert "model_3d" in protocol.HEAVY_TYPES, (
-    f"HEAVY_TYPES missing 'model_3d': {sorted(protocol.HEAVY_TYPES)}"
-)
-assert protocol.Capability.MODEL_3D_GLB_INLINE == "model_3d:glb_inline", (
-    f"Capability.MODEL_3D_GLB_INLINE wrong value: "
-    f"{protocol.Capability.MODEL_3D_GLB_INLINE!r}"
-)
-print("PASS: HEAVY_TYPES includes 'model_3d'; Capability constant intact.")
-
-
-# ---------------------------------------------------------------------------
-# 2. is_envelope returns True for a MODEL_3D envelope.
-# ---------------------------------------------------------------------------
-glb_bytes = _make_minimal_glb()
-envelope = {
-    "type":     "model_3d",
-    "encoding": "glb_inline",
-    "data":     base64.b64encode(glb_bytes).decode("ascii"),
-    "format":   "glb",
-    "byte_size": len(glb_bytes),
-}
-assert protocol.is_envelope(envelope), (
-    "is_envelope returned False for a well-formed MODEL_3D envelope; "
-    "HEAVY_TYPES update did not take effect."
-)
-print("PASS: is_envelope recognises model_3d envelopes.")
-
-
-# ---------------------------------------------------------------------------
-# 3. decode_model3d_envelope round-trips inline bytes.
-# ---------------------------------------------------------------------------
-file3d = serialization.decode_model3d_envelope(envelope)
-from comfy_api.latest._util import File3D as _File3D_for_check  # noqa: E402
-assert isinstance(file3d, _File3D_for_check), (
-    f"Expected File3D, got {type(file3d).__name__}"
-)
-# File3D exposes get_data() / get_source(); the public API on this
-# version returns a BytesIO when constructed with one. Drain bytes:
-src = file3d._source  # internal, but stable across this code path
-assert hasattr(src, "read"), f"File3D source not BytesIO-like: {type(src)}"
-src.seek(0)
-round_trip = src.read()
-assert round_trip == glb_bytes, (
-    f"GLB byte mismatch after decode: input={len(glb_bytes)} bytes, "
-    f"output={len(round_trip)} bytes"
-)
-assert round_trip[:4] == b"glTF", "GLB magic bytes lost in round-trip"
-print(f"PASS: decode_model3d_envelope round-trips {len(glb_bytes)} GLB bytes.")
-
-
-# ---------------------------------------------------------------------------
-# 4. decode_envelope dispatches model_3d to the new decoder.
-# ---------------------------------------------------------------------------
-file3d2 = serialization.decode_envelope(envelope)
-assert isinstance(file3d2, _File3D_for_check), (
-    f"decode_envelope dispatch failed for type=model_3d: got "
-    f"{type(file3d2).__name__}"
-)
-print("PASS: decode_envelope dispatches type='model_3d' correctly.")
-
-
-# ---------------------------------------------------------------------------
-# 5. Unsupported encoding raises a hard error (defence-in-depth so a
-#    future encoding never silently downgrades to garbage bytes).
-# ---------------------------------------------------------------------------
-bad = dict(envelope, encoding="obj_inline")
-try:
-    serialization.decode_model3d_envelope(bad)
-except protocol.RnpProtocolError as e:
-    assert "Unsupported model_3d encoding" in str(e), (
-        f"Wrong error message for unsupported encoding: {e!r}"
-    )
-    assert e.code == protocol.ErrorCode.INTERNAL
-    print("PASS: unsupported model_3d encoding raises RnpProtocolError.")
-else:
-    raise AssertionError(
-        "decode_model3d_envelope accepted an unsupported encoding"
-    )
-
-
-# ---------------------------------------------------------------------------
-# 6. End-to-end: server's make_model3d_envelope -> client decode.
-#    Skips when the server worktree isn't on disk (e.g. CI running
-#    against just the client repo).
-# ---------------------------------------------------------------------------
-server_protocol_path = os.path.join(
-    _SERVER_DIR, "comfy_rnp_protocol", "envelopes.py",
-)
-if os.path.exists(server_protocol_path):
-    # Import the server-side envelopes module standalone (it has no
-    # ComfyUI deps and uses its own sibling ``constants`` import).
-    server_pkg = types.ModuleType("comfy_rnp_protocol_e2e")
-    server_pkg.__path__ = [os.path.join(_SERVER_DIR, "comfy_rnp_protocol")]
-    sys.modules["comfy_rnp_protocol_e2e"] = server_pkg
-    server_constants = _load_module(
-        "comfy_rnp_protocol_e2e.constants",
-        os.path.join(_SERVER_DIR, "comfy_rnp_protocol", "constants.py"),
-    )
-    server_envelopes = _load_module(
-        "comfy_rnp_protocol_e2e.envelopes",
-        os.path.join(_SERVER_DIR, "comfy_rnp_protocol", "envelopes.py"),
-    )
-    # Build using the server helper exactly as a provider would.
-    server_env = server_envelopes.make_model3d_envelope(
-        encoding="glb_inline",
-        data=base64.b64encode(glb_bytes).decode("ascii"),
-        format="glb",
-        byte_size=len(glb_bytes),
-    )
-    assert server_env["type"] == "model_3d", server_env
-    assert server_env["encoding"] == "glb_inline", server_env
-    assert "model_3d" in server_envelopes.HEAVY_TYPES, (
-        "Server HEAVY_TYPES missing 'model_3d' — server PR #37 should "
-        "have added it; reinstall comfy_rnp_protocol if this fires."
-    )
-    # Pipe through the client decoder.
-    file3d3 = serialization.decode_envelope(server_env)
-    src = file3d3._source
-    src.seek(0)
-    assert src.read() == glb_bytes, "End-to-end byte mismatch"
-    print(
-        "PASS: end-to-end server make_model3d_envelope -> client "
-        "decode_envelope preserves bytes."
-    )
-else:
-    print(
-        f"SKIP end-to-end: server worktree not found at {_SERVER_DIR!r}"
-    )
-
-
-# ---------------------------------------------------------------------------
-# 7. proxy_node._OUTPUT_CLASSES maps "MODEL_3D" -> IO.File3DGLB.Output.
-#    proxy_node pulls in the full comfy_api / server / comfy_api_nodes
-#    tree at import time (too heavy to stub here), so we verify the
-#    mapping with a source-level check instead. The pattern is exact:
-#    a quoted ``"MODEL_3D":`` key whose value is the
-#    ``IO.File3DGLB.Output`` class reference inside the
-#    ``_OUTPUT_CLASSES`` dict literal. The same source check would
-#    catch a typo (e.g. ``IO.File3DAny.Output``) that a smoke test
-#    importing the live module would miss too — the dict literal is
-#    the contract.
-# ---------------------------------------------------------------------------
-proxy_src = open(
-    os.path.join(_CLIENT_DIR, "proxy_node.py"), "r", encoding="utf-8",
-).read()
-assert "_OUTPUT_CLASSES = {" in proxy_src, "proxy_node missing _OUTPUT_CLASSES dict"
-assert '"MODEL_3D":' in proxy_src and "IO.File3DGLB.Output" in proxy_src, (
-    "proxy_node._OUTPUT_CLASSES does not appear to map "
-    "'MODEL_3D' -> IO.File3DGLB.Output"
-)
-# Verify the mapping is in the same dict literal (not somewhere else).
-oc_start = proxy_src.index("_OUTPUT_CLASSES = {")
-oc_end = proxy_src.index("}", oc_start)
-oc_block = proxy_src[oc_start:oc_end]
-assert '"MODEL_3D":' in oc_block, (
-    "'MODEL_3D' key not inside the _OUTPUT_CLASSES dict literal"
-)
-assert "IO.File3DGLB.Output" in oc_block, (
-    "IO.File3DGLB.Output value not inside the _OUTPUT_CLASSES dict literal"
-)
-print(
-    "PASS: proxy_node._OUTPUT_CLASSES dict literal contains "
-    "'MODEL_3D' -> IO.File3DGLB.Output."
-)
-
-
-# ---------------------------------------------------------------------------
-# 8. CLIENT_CAPABILITIES advertises model_3d:glb_inline.
-#    client.py imports aiohttp / comfy_api_nodes too — same source-level
-#    contract check.
-# ---------------------------------------------------------------------------
-client_src = open(
-    os.path.join(_CLIENT_DIR, "client.py"), "r", encoding="utf-8",
-).read()
-assert "CLIENT_CAPABILITIES = [" in client_src, (
-    "client.py missing CLIENT_CAPABILITIES list"
-)
-cc_start = client_src.index("CLIENT_CAPABILITIES = [")
-cc_end = client_src.index("]", cc_start)
-cc_block = client_src[cc_start:cc_end]
-assert "Capability.MODEL_3D_GLB_INLINE" in cc_block, (
-    "Capability.MODEL_3D_GLB_INLINE not advertised in CLIENT_CAPABILITIES"
-)
-print("PASS: CLIENT_CAPABILITIES advertises Capability.MODEL_3D_GLB_INLINE.")
-
-print("ALL CHECKS PASSED.")

protocol.py

@@ -104,130 +104,18 @@ class Capability:
     IMAGE_PNG_BASE64 = "image:png_base64"
     IMAGE_JPEG_BASE64 = "image:jpeg_base64"
     IMAGE_RAW_CHW_UINT8 = "image:raw_b64_chw_uint8"
-    # Multi-frame IMAGE envelope: a single value carries N PNG-base64
-    # frames sharing the same H/W/C, decoded into a [B,H,W,C] tensor on
-    # this client. Mirrors the AUDIO sweep precedent (parallel encodings
-    # rather than extending ``png_base64``) so legacy server emits still
-    # decode correctly when the new token isn't advertised.
-    IMAGE_PNG_BASE64_BATCH = "image:png_base64_batch"
-    # Externalised counterpart of ``image:png_base64_batch``: same
-    # multi-frame IMAGE envelope shape, but every frame's PNG bytes
-    # are uploaded out-of-band via the presigned-PUT path (see
-    # ``serialization.maybe_externalize``) and the envelope carries
-    # a parallel ``uris`` list instead of inline ``frames``. Required
-    # because the original ``maybe_externalize`` only inspected the
-    # singleton ``data`` field, so a batch of N PNGs whose summed
-    # base64 payload crossed the 8 MiB inline cap silently rode the
-    # wire as a 30+ MiB POST body. Per-frame URIs (NOT a tar/zip
-    # blob) keep this composable with the existing per-frame fetch
-    # helpers and let the server fetch in parallel. Decoder dispatch
-    # keys off the ``encoding`` string — ``frames`` vs ``uris`` is a
-    # payload field, not a shape selector.
-    IMAGE_PNG_BASE64_BATCH_URI = "image:png_base64_batch_uri"
     VIDEO_MP4_INLINE = "video:mp4_inline"
-    VIDEO_MP4_BASE64 = "video:mp4_base64"
     AUDIO_MP3_INLINE = "audio:mp3_inline"
     AUDIO_MP3_BASE64 = "audio:mp3_base64"
     AUDIO_WAV_BASE64 = "audio:wav_base64"
     AUDIO_WAV_INLINE = "audio:wav_inline"
-    # OGG/Opus container as base64 in ``data``. Mirrors the parallel-
-    # encoding negotiation pattern already used for the AUDIO sweep
-    # (mp3 vs. wav) — servers only emit ``audio:opus_base64`` when
-    # this client advertises the token, otherwise they fall back to
-    # ``mp3_base64``. PyAV/FFmpeg decodes OGG/Opus natively so
-    # ``decode_audio_envelope`` ships the bytes through
-    # ``audio_bytes_to_audio_input`` the same way it ships MP3/WAV.
-    AUDIO_OPUS_BASE64 = "audio:opus_base64"
     MASK_PNG_BASE64 = "mask:png_base64"
     SVG_XML_BASE64 = "svg:svg_xml_base64"
     SCHEMA_V3 = "schema:v3"
     ASYNC_EXECUTE = "execute:async"
-    # Pass-through custom-IO bucket: when an input/output type string
-    # is not in the standard primitive/media set, the proxy_node parser
-    # falls back to ``IO.Custom(<type>)`` so partner helper-config nodes
-    # (OpenAIInputFiles, OpenAIChatConfig, GeminiInputFiles, Recraft
-    # style/color/controls helpers, future partner helper-config types)
-    # round-trip without per-type encoder plumbing. The descriptor's
-    # original io_type string is preserved on the V3 input so node-to-
-    # node connections only chain when the strings match. Encoder
-    # dispatch passes opaque dict/list/string values through
-    # ``_encode_one`` unchanged — they're already JSON-serialisable.
-    IO_OPAQUE = "io:opaque"
-    # 3D MODEL envelope: a single-mesh GLB (binary glTF 2.0, magic
-    # b"glTF") wrapped opaquely in ``data`` (base64). Mirrors the
-    # parallel-encoding pattern already used for VIDEO_MP4_INLINE — the
-    # server emits this token only when the inbound request advertised
-    # it; legacy clients without the token will surface
-    # NEGOTIATION_FAILED at descriptor-load time. The decoder on the
-    # client side hands raw GLB bytes straight to ComfyUI's
-    # ``Types.File3D`` / ``IO.File3DGLB`` machinery (no in-server GLB
-    # parse — the magic-byte check at offset 0 is the only validity
-    # guard the server applies).
-    MODEL_3D_GLB_INLINE = "model_3d:glb_inline"
-    # 3D MODEL BUNDLE envelope: a primary mesh file plus N companion
-    # files (textures / .mtl / .bin / other PBR maps) carried inline as
-    # a single coherent unit. Wire shape:
-    #
-    #   {
-    #     "type":         "model_3d",
-    #     "encoding":     "bundle_inline",
-    #     "format":       "obj",
-    #     "primary_path": "model.obj",
-    #     "files": [
-    #       {"path": "model.obj",            "format": "obj", "role": "mesh",
-    #        "data": "<b64>", "byte_size": 12345},
-    #       {"path": "model.mtl",            "format": "mtl", "role": "material",
-    #        "data": "<b64>"},
-    #       {"path": "textures/albedo.png",  "format": "png", "role": "texture_diffuse",
-    #        "data": "<b64>"}
-    #     ]
-    #   }
-    #
-    # ``path`` is the authoritative cross-file reference key — a POSIX-
-    # relative path (no ``..``, no absolute prefix, no Windows drive
-    # letter, no backslashes, no case-insensitive collisions). The
-    # client decoder materialises files into a temp directory using
-    # exactly these paths so a ``.obj`` that references its ``.mtl``
-    # via filename (or a ``.gltf`` that references its ``.bin`` /
-    # textures via relative URI) resolves on disk.
-    #
-    # ``role`` is an OPTIONAL producer hint (NOT a closed enum) —
-    # well-known values include ``mesh``, ``material``, ``buffer``,
-    # ``texture_diffuse``, ``texture_metallic``, ``texture_normal``,
-    # ``texture_roughness``, ``texture_ao``, ``texture_emissive``,
-    # ``texture_height``. Unknown roles round-trip without error;
-    # consumers may use ``role`` for convenience but ``path`` is the
-    # primary identifier.
-    #
-    # ``primary_path`` MUST appear in ``files`` exactly once and pins
-    # the entry-point file (the one passed to ComfyUI's
-    # ``Types.File3D`` constructor by the client decoder). The
-    # top-level ``format`` (if set) MUST match that primary file's
-    # ``format``.
-    #
-    # The client decoder returns a ``BundledFile3D`` (a thin
-    # ``File3D``-compatible wrapper) — existing downstream loaders
-    # that call ``get_source()`` / ``get_data()`` / ``save_to()`` get
-    # the bundle's primary file with all sidecars materialised on
-    # disk first so cross-file refs resolve correctly. Override of
-    # ``save_to()`` copies the *whole bundle* into the destination
-    # directory, not just the primary file.
-    #
-    # Negotiation: the server emits this encoding ONLY when the
-    # inbound request advertised this token; legacy clients without
-    # the bundle decoder will surface NEGOTIATION_FAILED at
-    # descriptor-load time. Whole-descriptor gating — if a node has
-    # both bundle and non-bundle outputs and the cap is absent, the
-    # whole descriptor is skipped rather than synthesising a
-    # partial-socket variant.
-    #
-    # A future sibling ``Capability.MODEL_3D_BUNDLE_URI`` would carry
-    # ``uri`` per file for URL-fetch-out-of-band semantics; not in
-    # this PR.
-    MODEL_3D_BUNDLE_INLINE = "model_3d:bundle_inline"
 
 
-HEAVY_TYPES = frozenset({"image", "video", "audio", "mask", "model_3d"})
+HEAVY_TYPES = frozenset({"image", "video", "audio", "mask", "svg"})
 
 
 def is_envelope(value: Any) -> bool:

serialization.py

@@ -17,7 +17,6 @@ tensor — no parallel dialect.
 """
 from __future__ import annotations
 
-import asyncio
 import base64
 import logging
 from io import BytesIO
@@ -57,64 +56,14 @@ async def maybe_externalize(
     max_inline_bytes: int | None,
     auth_headers: dict[str, str] | None = None,
 ) -> dict[str, Any]:
-    """If the envelope's inline payload exceeds ``max_inline_bytes``,
-    upload it via the presigned-PUT path and rewrite the envelope to
-    reference the uploaded asset(s) instead of inlining base64.
-
-    Two payload shapes are recognised:
-
-    * Singleton ``data`` envelopes (the common single-frame IMAGE /
-      MASK / VIDEO / AUDIO case). Oversize payloads upload as one
-      asset and the envelope's ``data`` field is swapped for ``uri``.
-    * Multi-frame ``frames=[…]`` IMAGE envelopes (encoding
-      ``png_base64_batch``). The original ``maybe_externalize`` only
-      inspected ``data`` and so silently let a 9× 2048² Flux2 batch
-      ride the wire as a 200 MB POST body — defeating the entire
-      reason the cap exists. The new path computes the summed raw
-      byte budget (``sum(len(b64)) * 3 // 4`` — base64 expands 4:3 so
-      this is the exact payload the server would receive) and, if it
-      crosses the cap, uploads each frame as an individual presigned
-      PUT in parallel via :func:`asyncio.gather` then rewrites the
-      envelope to ``encoding=png_base64_batch_uri`` with a parallel
-      ``uris`` list. ``shape`` / ``dtype`` / ``color_space`` ride
-      through unchanged so the server-side decoder still sees the
-      batch dimension. Per-frame URIs (NOT a tar/zip blob) compose
-      with the existing per-frame fetch helpers and let the server
-      fetch in parallel.
+    """If the envelope's inline data exceeds ``max_inline_bytes``,
+    upload the bytes and replace ``data`` with ``uri``.
 
     No-op when either argument is falsy, the envelope already has a
-    ``uri`` / ``uris``, or the inline payload fits under the cap.
-
-    Dispatch keys off the ``encoding`` string — NOT field presence
-    (``frames`` vs. ``data``). An encoder that emitted ``frames`` for
-    a non-batch encoding by accident, or shipped both fields together,
-    used to silently take the batch branch and externalise garbage;
-    keying off the canonical encoding catches that as a hard ``frames``
-    check inside the batch branch itself.
+    ``uri``, or the inline payload fits under the cap.
     """
     if not server_url or not max_inline_bytes:
         return envelope
-
-    encoding = envelope.get("encoding")
-    if encoding == "png_base64_batch":
-        frames = envelope.get("frames")
-        if not isinstance(frames, list) or not frames:
-            # Mirror the server-side make_image_batch_envelope contract:
-            # an empty/missing frames list is a hard wire bug, NOT a
-            # silent no-op (which used to ship through under the old
-            # ``isinstance(frames, list) and frames`` dispatch and then
-            # blow up on the server's resolve_image_envelope_pngs check).
-            raise RnpProtocolError(
-                "png_base64_batch envelope requires a non-empty 'frames' list",
-                code=ErrorCode.INTERNAL,
-            )
-        return await _maybe_externalize_batch(
-            envelope, frames,
-            server_url=server_url,
-            max_inline_bytes=max_inline_bytes,
-            auth_headers=auth_headers,
-        )
-
     data = envelope.get("data")
     if not isinstance(data, str):
         return envelope
@@ -135,122 +84,22 @@ async def maybe_externalize(
     return out
 
 
-async def _maybe_externalize_batch(
-    envelope: dict[str, Any],
-    frames: list[Any],
-    *,
-    server_url: str,
-    max_inline_bytes: int,
-    auth_headers: dict[str, str] | None,
-) -> dict[str, Any]:
-    """Externalise a multi-frame IMAGE envelope when its summed inline
-    payload overflows ``max_inline_bytes``.
-
-    Per-frame upload (NOT a tar/zip blob): each frame becomes its own
-    presigned-PUT asset so the server can fetch in parallel and the
-    existing per-frame ``resolve_image_envelope_pngs`` helper picks
-    up the URI shape transparently. ``asyncio.gather`` issues every
-    PUT in parallel — the dominant latency for a 9-frame Flux2 batch
-    is the upload, not the server hop, so serialising would multiply
-    end-to-end submit time by N. Frame ordering is preserved (gather
-    returns positional results) — critical because a Flux2 provider
-    maps ``uris[k]`` → ``input_image_{k+1}`` 1:1.
-    """
-    # Cap on raw byte count (base64 expands 4:3, so multiplying by
-    # 3/4 recovers the actual payload the server would receive).
-    total_raw = 0
-    for f in frames:
-        if isinstance(f, str):
-            total_raw += len(f) * 3 // 4
-    if total_raw <= max_inline_bytes:
-        return envelope
-
-    env_type = envelope.get("type", "")
-    content_type = _CONTENT_TYPE_FOR_TYPE.get(env_type, "application/octet-stream")
-
-    async def _upload_one(idx: int, frame_b64: Any) -> str:
-        if not isinstance(frame_b64, str):
-            raise RnpProtocolError(
-                f"image batch frame {idx} is not a base64 string "
-                f"(got {type(frame_b64).__name__})",
-                code=ErrorCode.INTERNAL,
-            )
-        raw = base64.b64decode(frame_b64)
-        return await rnp_client.upload_asset(
-            server_url, raw,
-            content_type=content_type,
-            auth_headers=auth_headers,
-        )
-
-    uris = await asyncio.gather(
-        *(_upload_one(i, f) for i, f in enumerate(frames))
-    )
-    log.info(
-        "RNP: externalized %s batch envelope (%d frames, %d raw bytes) "
-        "-> %d presigned URIs",
-        env_type, len(frames), total_raw, len(uris),
-    )
-
-    # Strip the inline ``frames`` field; preserve ``shape`` / ``dtype``
-    # / ``color_space`` so the server-side decoder still sees the
-    # batch dimension and per-frame metadata. Encoding flips to the
-    # URI variant so dispatch keys cleanly off the string (NOT field
-    # presence — frames vs. uris is a payload field, not a shape
-    # selector).
-    out: dict[str, Any] = {
-        k: v for k, v in envelope.items() if k != "frames"
-    }
-    out["encoding"] = "png_base64_batch_uri"
-    out["uris"] = list(uris)
-    return out
-
-
 # ---------------------------------------------------------------------------
 # Image encode / decode
 # ---------------------------------------------------------------------------
 
-def encode_image_tensor(tensor: Any, *, accepts_batch: bool = False) -> dict[str, Any]:
-    """Encode a ComfyUI IMAGE tensor (B,H,W,C float32 in 0..1) as an
-    image envelope.
+def encode_image_tensor(tensor: Any) -> dict[str, Any]:
+    """Encode a ComfyUI IMAGE tensor (B,H,W,C float32 in 0..1) as a
+    PNG-base64 image envelope.
 
-    ``accepts_batch`` reflects whether the descriptor's
-    ``input_serialization`` for this input lists ``"png_base64_batch"``.
-    When True AND ``tensor.shape[0] > 1``, emit a multi-frame
-    ``png_base64_batch`` envelope (``frames=[<png_b64>, …]``) so the
-    server decodes a real ``[B, H, W, C]`` source. Otherwise emit a
-    single-frame ``png_base64`` envelope for ``tensor[0]`` — preserves
-    backwards compat with descriptors that haven't migrated yet, and
-    matches the wire shape of the existing ``_decode_image_batch_envelope``
-    on the response path so both directions round-trip symmetrically.
+    Multi-image batches send only the first frame for now; the
+    framework hasn't grown batch-of-envelopes semantics yet.
     """
     import numpy as np
     from PIL import Image
 
-    rank = getattr(tensor, "dim", lambda: 0)()
-    if rank == 4 and accepts_batch and int(tensor.shape[0]) > 1:
-        frames_arr = (tensor.cpu().clamp(0.0, 1.0).numpy() * 255).astype(np.uint8)
-        b, height, width = frames_arr.shape[:3]
-        channels = frames_arr.shape[3] if frames_arr.ndim == 4 else 1
-        pil_mode = {1: "L", 3: "RGB", 4: "RGBA"}.get(channels, "RGB")
-        frames_b64: list[str] = []
-        for i in range(b):
-            img = Image.fromarray(frames_arr[i], mode=pil_mode)
-            buf = BytesIO()
-            img.save(buf, format="PNG")
-            frames_b64.append(base64.b64encode(buf.getvalue()).decode("ascii"))
-        return {
-            "type":        "image",
-            "encoding":    "png_base64_batch",
-            "frames":      frames_b64,
-            "shape":       [b, height, width, channels],
-            "dtype":       "uint8",
-            "color_space": "srgb",
-        }
-
-    # Single-frame fallback: matches the old ``encode_image_tensor``
-    # contract (sends ``tensor[0]`` for a multi-frame batch when the
-    # descriptor doesn't advertise the batch encoding).
-    if rank == 4:
+    # Strip the batch dim if present.
+    if hasattr(tensor, "dim") and tensor.dim() == 4:
         frame = tensor[0]
     else:
         frame = tensor
@@ -272,18 +121,8 @@ def encode_image_tensor(tensor: Any, *, accepts_batch: bool = False) -> dict[str
 
 
 def decode_image_envelope(envelope: dict[str, Any]) -> Any:
-    """Decode an image envelope into a ComfyUI IMAGE tensor.
-
-    Single-frame encodings (``png_base64``, ``jpeg_base64``,
-    ``webp_base64``) decode into ``[1, H, W, C]``. The multi-frame
-    ``png_base64_batch`` encoding (a list of base64-PNG ``frames``)
-    stacks each frame into ``[B, H, W, C]`` — the native ComfyUI
-    image-batch shape — so providers whose upstream returns ``n > 1``
-    surface as a real batched tensor in the workflow runtime.
-    """
+    """Decode an image envelope into a ComfyUI IMAGE tensor (B,H,W,C float32)."""
     encoding = envelope.get("encoding")
-    if encoding == "png_base64_batch":
-        return _decode_image_batch_envelope(envelope)
     if encoding not in ("png_base64", "jpeg_base64", "webp_base64"):
         raise RnpProtocolError(
             f"Unsupported image encoding: {encoding!r}",
@@ -302,69 +141,6 @@ def decode_image_envelope(envelope: dict[str, Any]) -> Any:
     return torch.from_numpy(arr).unsqueeze(0)
 
 
-def _decode_image_batch_envelope(envelope: dict[str, Any]) -> Any:
-    """Decode a ``png_base64_batch`` envelope into ``[B, H, W, C]``.
-
-    The wire shape is ``{"type":"image", "encoding":"png_base64_batch",
-    "frames":[<png_b64>, ...], "shape":[B,H,W,C], ...}``. Each frame is
-    a PNG-encoded image; all frames must share the same H/W after the
-    RGB conversion (the server-side encoder enforces this). A frame
-    count mismatch against the ``shape[0]`` field surfaces as a hard
-    parse error rather than silently dropping frames — matches the SVG
-    decoder's ``count`` integrity check.
-    """
-    import base64 as _b64
-    import numpy as np
-    import torch
-    from PIL import Image
-
-    frames = envelope.get("frames")
-    if not isinstance(frames, list) or not frames:
-        raise RnpProtocolError(
-            "image batch envelope missing or empty 'frames' list",
-            code=ErrorCode.INTERNAL,
-        )
-    declared_shape = envelope.get("shape")
-    if isinstance(declared_shape, list) and len(declared_shape) >= 1:
-        declared_b = int(declared_shape[0])
-        if declared_b != len(frames):
-            raise RnpProtocolError(
-                f"image batch envelope frame count {len(frames)} does not "
-                f"match declared shape[0]={declared_b}",
-                code=ErrorCode.INTERNAL,
-            )
-
-    arrs: list[Any] = []
-    base_hw: tuple[int, int] | None = None
-    for idx, frame_b64 in enumerate(frames):
-        if not isinstance(frame_b64, str):
-            raise RnpProtocolError(
-                f"image batch frame {idx} is not a base64 string",
-                code=ErrorCode.INTERNAL,
-            )
-        try:
-            raw = _b64.b64decode(frame_b64)
-            img = Image.open(BytesIO(raw)).convert("RGB")
-        except Exception as e:
-            raise RnpProtocolError(
-                f"image batch frame {idx} failed to decode: {e}",
-                code=ErrorCode.INTERNAL,
-            ) from e
-        arr = np.array(img).astype(np.float32) / 255.0
-        if base_hw is None:
-            base_hw = (arr.shape[0], arr.shape[1])
-        elif (arr.shape[0], arr.shape[1]) != base_hw:
-            raise RnpProtocolError(
-                f"image batch frame {idx} size {arr.shape[:2]} does not "
-                f"match frame 0 size {base_hw} (server should have rejected "
-                f"this; likely a wire bug)",
-                code=ErrorCode.INTERNAL,
-            )
-        arrs.append(arr)
-    stacked = np.stack(arrs, axis=0)
-    return torch.from_numpy(stacked)
-
-
 # ---------------------------------------------------------------------------
 # Mask encode / decode
 # ---------------------------------------------------------------------------
@@ -451,11 +227,7 @@ def encode_audio_input(audio: dict[str, Any]) -> dict[str, Any]:
 def decode_audio_envelope(envelope: dict[str, Any]) -> dict[str, Any]:
     """Decode an audio envelope back into a ComfyUI AUDIO dict."""
     encoding = envelope.get("encoding")
-    if encoding not in (
-        "mp3_base64", "mp3_inline",
-        "wav_base64", "wav_inline",
-        "opus_base64",
-    ):
+    if encoding not in ("mp3_base64", "mp3_inline", "wav_base64", "wav_inline"):
         raise RnpProtocolError(
             f"Unsupported audio encoding: {encoding!r}",
             code=ErrorCode.INTERNAL,
@@ -465,44 +237,9 @@ def decode_audio_envelope(envelope: dict[str, Any]) -> dict[str, Any]:
 
 
 # ---------------------------------------------------------------------------
-# Video encode / decode
+# Video decode (encode lands when a remote node accepts VIDEO inputs)
 # ---------------------------------------------------------------------------
 
-def encode_video_input(video: Any) -> dict[str, Any]:
-    """Encode a ComfyUI VIDEO (``VideoInput`` subclass) as an mp4-base64
-    video envelope.
-
-    Mirrors the AUDIO encoder above: re-encodes the Video object to an
-    in-memory mp4/H.264 byte buffer (matches upstream
-    ``comfy_api_nodes/util/conversions.py`` ``video_to_base64_string``)
-    and base64-encodes it. Populates ``duration_s`` metadata when the
-    Video object exposes ``get_duration()`` so server-side providers
-    (e.g. ``GrokVideoExtendProvider._validate_video_duration_envelope``)
-    can range-check without demuxing the MP4.
-    """
-    from comfy_api_nodes.util.conversions import video_to_base64_string
-
-    b64 = video_to_base64_string(video)
-    extra: dict[str, Any] = {}
-    duration_s: float | None = None
-    try:
-        getter = getattr(video, "get_duration", None)
-        if callable(getter):
-            d = getter()
-            if d is not None:
-                duration_s = float(d)
-    except Exception:
-        duration_s = None
-    if duration_s is not None:
-        extra["duration_s"] = duration_s
-    return {
-        "type":     "video",
-        "encoding": "mp4_base64",
-        "data":     b64,
-        **extra,
-    }
-
-
 def decode_video_envelope(envelope: dict[str, Any]) -> Any:
     """Decode a video envelope into a ComfyUI Video object (mp4 inline)."""
     encoding = envelope.get("encoding")
@@ -516,378 +253,66 @@ def decode_video_envelope(envelope: dict[str, Any]) -> Any:
 
 
 # ---------------------------------------------------------------------------
-# 3D model encode / decode
+# SVG decode (encode lands when a remote node accepts SVG inputs; today
+# Recraft's V3/V4 vector endpoints only emit SVG, so the client is
+# decode-only).
 # ---------------------------------------------------------------------------
 
-def encode_model3d_input(model_3d: Any) -> dict[str, Any]:
-    """Encode a ComfyUI ``File3D`` (or compatible) as an inline
-    single-file 3D-model envelope.
+def decode_svg_envelope(envelope: dict[str, Any]) -> Any:
+    """Decode an SVG envelope into a ``comfy_extras.nodes_images.SVG`` instance.
 
-    Mirrors the AUDIO / VIDEO encoders above: reads the primary mesh
-    bytes (via the ``File3D`` API: ``get_data().read()`` returns a
-    ``BytesIO`` payload; falling back to ``read_bytes()`` for older
-    sources) and base64-encodes them. The envelope's ``encoding`` is
-    ``"glb_inline"`` (the generic single-file inline encoding the
-    server-side decoder dispatches on at :func:`decode_model3d_envelope`
-    — the decoder hands the bytes to ``File3D(BytesIO(...), format)``
-    regardless of whether the actual format is glb / obj / fbx / etc.,
-    so the ``encoding`` name is a logical "inline single-file 3D" tag
-    and the ``format`` extra picks the file extension).
-
-    Multi-file bundles (``BundledFile3D``-style values where every
-    companion file matters — e.g. an OBJ with a sibling .mtl + texture
-    PNGs) are not yet supported on the encode path: this PR ships the
-    minimal wire shape needed for the Tencent Hunyuan3D MODEL_3D-input
-    nodes which all upload a single file via ``upload_3d_model_to_comfyapi``
-    upstream. Bundle encode (``bundle_inline``) lands when a partner
-    node actually needs the companion bytes.
-    """
-    file_format = ""
-    fmt_attr = getattr(model_3d, "format", None)
-    if isinstance(fmt_attr, str):
-        file_format = fmt_attr.lower()
-
-    # ``File3D.get_data()`` returns a ``BytesIO`` (per
-    # ``comfy_api.latest._util.geometry_types.File3D``). Other File3D-
-    # compatible classes may instead expose ``read_bytes`` returning
-    # raw bytes; fall back to that for compatibility.
-    raw: bytes
-    get_data = getattr(model_3d, "get_data", None)
-    if callable(get_data):
-        buf = get_data()
-        if hasattr(buf, "seek"):
-            buf.seek(0)
-        raw = buf.read() if hasattr(buf, "read") else bytes(buf)
-    else:
-        read_bytes = getattr(model_3d, "read_bytes", None)
-        if callable(read_bytes):
-            raw = read_bytes()
-        else:
-            raise RnpProtocolError(
-                f"unsupported 3D model value: {type(model_3d).__name__!r} "
-                f"has no get_data() or read_bytes()",
-                code=ErrorCode.INTERNAL,
-            )
-
-    envelope: dict[str, Any] = {
-        "type":     "model_3d",
-        "encoding": "glb_inline",
-        "data":     base64.b64encode(raw).decode("ascii"),
-    }
-    if file_format:
-        envelope["format"] = file_format
-    return envelope
-
-
-# ---------------------------------------------------------------------------
-# Multi-file 3D bundle: a ``File3D``-compatible class that carries the
-# primary mesh plus N companion files (textures / .mtl / .bin / etc.).
-#
-# Built lazily as a ``File3D`` subclass on first use — importing
-# ``File3D`` at module load pulls torch (via ``comfy_api.latest._util.
-# geometry_types``), which is fine inside ComfyUI but breaks the
-# smoke-test pattern that exercises serialization without the heavy
-# comfy_api tree. The factory below caches the constructed class so
-# every ``BundledFile3D`` instance shares the same dynamic class and
-# ``isinstance(x, File3D)`` always succeeds.
-# ---------------------------------------------------------------------------
-
-_BUNDLED_FILE3D_CLS: Any = None
-
-
-def _bundled_file3d_class() -> type:
-    """Return the cached ``BundledFile3D`` class (a ``File3D`` subclass).
-
-    Constructs it on first call so the ``comfy_api.latest._util``
-    import (which pulls torch) is paid for only when a bundle
-    envelope is actually decoded — keeps the smoke-test stubbing
-    pattern intact for callers that don't exercise this path.
-    """
-    global _BUNDLED_FILE3D_CLS
-    if _BUNDLED_FILE3D_CLS is not None:
-        return _BUNDLED_FILE3D_CLS
-    from comfy_api.latest._util.geometry_types import File3D as _File3D
-
-    class BundledFile3D(_File3D):
-        """``File3D``-compatible wrapper for a multi-file 3D bundle.
-
-        Stores the primary mesh file plus N companion files (textures
-        / .mtl / .bin / etc.) in memory as a ``path -> bytes`` dict;
-        lazily materialises the whole bundle into a temp directory the
-        first time anything cross-file-resolution-sensitive is asked
-        of it (``get_source()`` for an OBJ/GLTF that needs its
-        .mtl/.bin/textures on disk; ``save_to(dest)`` which copies the
-        *whole bundle* into the destination directory).
-
-        Cheap consumers that just want the primary file's bytes
-        (``get_data()`` / ``get_bytes()``) skip the temp-dir
-        materialise entirely.
-
-        The temp directory's lifetime is tied to this object: it is
-        cleaned up on garbage-collect via ``__del__`` (best-effort).
-        For workflows that need stable on-disk paths beyond this
-        object's lifetime, call ``save_to(dest)`` to copy the bundle
-        into a caller-controlled location.
-        """
-
-        def __init__(
-            self,
-            files: dict[str, bytes],
-            primary_path: str,
-            roles: dict[str, str] | None = None,
-            formats: dict[str, str] | None = None,
-        ) -> None:
-            if primary_path not in files:
-                raise ValueError(
-                    f"primary_path {primary_path!r} not in bundle files: "
-                    f"{sorted(files)!r}"
-                )
-            self._files: dict[str, bytes] = dict(files)
-            self._primary_path = primary_path
-            self._roles: dict[str, str] = dict(roles or {})
-            self._formats: dict[str, str] = dict(formats or {})
-            self._temp_dir: str | None = None
-            # Populate parent ``_source`` / ``_format`` so reads of
-            # those plain attributes on downstream consumers that
-            # haven't been updated still work. ``_source`` is a
-            # BytesIO of the primary file; ``_format`` is the primary
-            # file's extension.
-            primary_fmt = (
-                self._formats.get(primary_path)
-                or (
-                    primary_path.rsplit(".", 1)[-1].lower()
-                    if "." in primary_path
-                    else ""
-                )
-            )
-            super().__init__(BytesIO(self._files[primary_path]), primary_fmt)
-
-        # --------------------------------------------------------------
-        # File3D-compatible accessors (overrides)
-        # --------------------------------------------------------------
-
-        def get_source(self) -> str:
-            """Return the on-disk path to the primary file.
-
-            Materialises the whole bundle into a temp directory on
-            first call so cross-file refs (.obj -> .mtl -> texture;
-            .gltf -> .bin + textures) resolve via the filesystem.
-            """
-            self._ensure_materialized()
-            from os.path import join as _join
-            return _join(self._temp_dir, *self._primary_path.split("/"))
-
-        def get_data(self) -> BytesIO:
-            """Return the primary file's bytes (no disk I/O)."""
-            return BytesIO(self._files[self._primary_path])
-
-        def get_bytes(self) -> bytes:
-            """Return the primary file's raw bytes (no disk I/O)."""
-            return self._files[self._primary_path]
-
-        def save_to(self, path: str) -> str:
-            """Copy the WHOLE bundle into the destination directory.
-
-            ``path`` is the destination for the *primary file*;
-            sidecars are copied alongside it preserving their relative
-            paths from the original bundle layout. E.g. for
-
-                primary_path = "model.obj"
-                files = {
-                    "model.obj":            <bytes>,
-                    "model.mtl":            <bytes>,
-                    "textures/albedo.png":  <bytes>,
-                }
-
-            ``save_to("/tmp/out/scene.obj")`` writes:
-
-                /tmp/out/scene.obj
-                /tmp/out/model.mtl
-                /tmp/out/textures/albedo.png
-
-            Sidecars keep their ORIGINAL filenames (so cross-file
-            refs inside the .obj that point at ``model.mtl`` still
-            resolve); only the primary file is renamed to match
-            ``path``. The destination directory is created if needed.
-            """
-            from pathlib import Path
-            dest = Path(path)
-            dest.parent.mkdir(parents=True, exist_ok=True)
-            dest.write_bytes(self._files[self._primary_path])
-            dest_parent_resolved = dest.parent.resolve()
-            for rel_path, raw in self._files.items():
-                if rel_path == self._primary_path:
-                    continue
-                sidecar_dest = dest.parent.joinpath(*rel_path.split("/"))
-                # Path safety — rel_path was sanitized at envelope
-                # build time, but defence-in-depth check on the
-                # resolved path keeps us safe against pathological
-                # inputs that may have slipped through.
-                resolved = sidecar_dest.resolve()
-                if dest_parent_resolved not in resolved.parents and resolved != dest_parent_resolved:
-                    continue
-                sidecar_dest.parent.mkdir(parents=True, exist_ok=True)
-                sidecar_dest.write_bytes(raw)
-            return str(dest)
-
-        # --------------------------------------------------------------
-        # Bundle-specific accessors (additive)
-        # --------------------------------------------------------------
-
-        @property
-        def primary_path(self) -> str:
-            return self._primary_path
-
-        @property
-        def file_paths(self) -> list[str]:
-            return sorted(self._files)
-
-        def file_bytes(self, path: str) -> bytes:
-            """Raw bytes for one file in the bundle by relative path."""
-            return self._files[path]
-
-        def file_role(self, path: str) -> str | None:
-            """Optional producer-supplied role hint (may be ``None``)."""
-            return self._roles.get(path)
-
-        def paths_with_role(self, role: str) -> list[str]:
-            """All file paths whose role hint equals ``role``."""
-            return [p for p, r in self._roles.items() if r == role]
-
-        def materialize_to_temp_dir(self) -> str:
-            """Force-materialise the whole bundle into a temp directory.
-
-            Returns the temp-directory path. Cleanup happens on GC;
-            callers that need stable lifetimes should ``save_to()`` to
-            a caller-controlled location instead.
-            """
-            self._ensure_materialized()
-            return self._temp_dir
-
-        # --------------------------------------------------------------
-        # Internal
-        # --------------------------------------------------------------
-
-        def _ensure_materialized(self) -> None:
-            if self._temp_dir is not None:
-                return
-            import tempfile
-            from pathlib import Path
-            self._temp_dir = tempfile.mkdtemp(prefix="rnp_model3d_bundle_")
-            root = Path(self._temp_dir)
-            for rel_path, raw in self._files.items():
-                # rel_path was sanitized at envelope build time —
-                # split-on-'/' and re-join via Path is safe.
-                dest = root.joinpath(*rel_path.split("/"))
-                dest.parent.mkdir(parents=True, exist_ok=True)
-                dest.write_bytes(raw)
-
-        def __del__(self) -> None:
-            td = getattr(self, "_temp_dir", None)
-            if td is not None:
-                try:
-                    import shutil
-                    shutil.rmtree(td, ignore_errors=True)
-                except Exception:  # noqa: BLE001
-                    pass
-
-        def __repr__(self) -> str:
-            return (
-                f"BundledFile3D(primary={self._primary_path!r}, "
-                f"files={len(self._files)}, format={self._format!r})"
-            )
-
-    _BUNDLED_FILE3D_CLS = BundledFile3D
-    return _BUNDLED_FILE3D_CLS
-
-
-def decode_model3d_envelope(envelope: dict[str, Any]) -> Any:
-    """Decode a 3D-model envelope into a ComfyUI ``File3D`` object.
-
-    Dispatches on the envelope's ``encoding``:
-
-    * ``glb_inline`` — single-file binary glTF 2.0 (magic ``b"glTF"``
-      at offset 0). The bytes are handed to ``File3D`` as a
-      ``BytesIO`` so downstream nodes (preview3d / SaveGLB / Load3D)
-      see exactly the same value shape they would from a local Tripo
-      / Rodin / Meshy node. The envelope's optional ``format`` extra
-      is forwarded as the second constructor arg so the materialiser
-      picks the right file extension when persisting.
-
-    * ``bundle_inline`` — multi-file bundle. The primary mesh file
-      plus N companion files (textures / .mtl / .bin / etc.) are
-      decoded into a :class:`BundledFile3D` (``File3D``-compatible)
-      whose ``get_source()`` / ``save_to()`` materialise the whole
-      bundle on disk so cross-file refs resolve via the filesystem.
-      Path safety (no ``..`` / no absolute prefix / no Windows drive
-      letter / no case-insensitive collisions) was enforced at
-      envelope build time on the server; the client re-asserts the
-      ``primary_path``-present invariant defensively and rejects any
-      file entry that lacks ``data``.
+    The wire payload is one or more concatenated ``<svg>…</svg>`` XML
+    documents; we split on the closing tag so a multi-frame Recraft
+    response (n>1) hydrates a single ``SVG`` carrying a list of
+    BytesIO frames — the same shape the local node produces via
+    ``SVG(svg_data)``.
     """
     encoding = envelope.get("encoding")
-    if encoding == "glb_inline":
-        from comfy_api.latest._util import File3D
-        file_format = envelope.get("format") or "glb"
-        return File3D(BytesIO(decode_envelope_data(envelope)), str(file_format))
-    if encoding == "bundle_inline":
-        bundle_cls = _bundled_file3d_class()
-        primary_path = envelope.get("primary_path")
-        if not isinstance(primary_path, str) or not primary_path:
-            raise RnpProtocolError(
-                "bundle_inline envelope missing 'primary_path'",
-                code=ErrorCode.INTERNAL,
-            )
-        files_spec = envelope.get("files")
-        if not isinstance(files_spec, list) or not files_spec:
-            raise RnpProtocolError(
-                "bundle_inline envelope missing non-empty 'files' list",
-                code=ErrorCode.INTERNAL,
-            )
-        files: dict[str, bytes] = {}
-        roles: dict[str, str] = {}
-        formats: dict[str, str] = {}
-        for entry in files_spec:
-            if not isinstance(entry, dict):
-                raise RnpProtocolError(
-                    f"bundle_inline file entry not a dict: {entry!r}",
-                    code=ErrorCode.INTERNAL,
-                )
-            path = entry.get("path")
-            if not isinstance(path, str) or not path:
-                raise RnpProtocolError(
-                    f"bundle_inline file entry missing 'path': {entry!r}",
-                    code=ErrorCode.INTERNAL,
-                )
-            data = entry.get("data")
-            if not isinstance(data, str):
-                raise RnpProtocolError(
-                    f"bundle_inline file {path!r} missing inline 'data'",
-                    code=ErrorCode.INTERNAL,
-                )
-            files[path] = base64.b64decode(data)
-            role = entry.get("role")
-            if isinstance(role, str):
-                roles[path] = role
-            fmt = entry.get("format")
-            if isinstance(fmt, str):
-                formats[path] = fmt
-        if primary_path not in files:
-            raise RnpProtocolError(
-                f"bundle_inline primary_path {primary_path!r} not in "
-                f"files list (have: {sorted(files)!r})",
-                code=ErrorCode.INTERNAL,
-            )
-        return bundle_cls(
-            files=files,
-            primary_path=primary_path,
-            roles=roles,
-            formats=formats,
+    if encoding not in ("svg_xml_base64", "svg_xml_inline"):
+        raise RnpProtocolError(
+            f"Unsupported svg encoding: {encoding!r}",
+            code=ErrorCode.INTERNAL,
         )
-    raise RnpProtocolError(
-        f"Unsupported model_3d encoding: {encoding!r}",
-        code=ErrorCode.INTERNAL,
-    )
+    from comfy_extras.nodes_images import SVG
+
+    raw = decode_envelope_data(envelope)
+    text = raw.decode("utf-8", "replace")
+    # The server joins per-frame SVGs with ``\n`` (see
+    # ``_emit_svg_from_urls``); split on the closing tag followed by a
+    # newline so an SVG document that legitimately contains ``</svg>``
+    # in CDATA / a foreignObject / a comment isn't shredded mid-frame.
+    # Fall back to splitting on the bare closing tag for single-frame
+    # payloads or older server builds that didn't add the newline.
+    delimiter = "</svg>\n"
+    if delimiter not in text:
+        delimiter = "</svg>"
+    parts: list[BytesIO] = []
+    cursor = 0
+    closing = "</svg>"
+    while True:
+        idx = text.find(delimiter, cursor)
+        if idx < 0:
+            tail = text[cursor:].strip()
+            if tail:
+                parts.append(BytesIO(tail.encode("utf-8")))
+            break
+        end = idx + len(closing)  # keep the closing tag on this frame
+        chunk = text[cursor:end].strip()
+        if chunk:
+            parts.append(BytesIO(chunk.encode("utf-8")))
+        cursor = idx + len(delimiter)
+    declared = envelope.get("count")
+    if isinstance(declared, int) and declared > 0 and declared != len(parts):
+        log.warning(
+            "SVG envelope count=%d but parsed %d documents — server payload may be malformed",
+            declared, len(parts),
+        )
+    if not parts:
+        raise RnpProtocolError(
+            "SVG envelope payload contained no <svg> documents",
+            code=ErrorCode.INTERNAL,
+        )
+    return SVG(parts)
 
 
 # ---------------------------------------------------------------------------
@@ -895,11 +320,11 @@ def decode_model3d_envelope(envelope: dict[str, Any]) -> Any:
 # ---------------------------------------------------------------------------
 
 _DECODERS = {
-    "image":    decode_image_envelope,
-    "mask":     decode_mask_envelope,
-    "audio":    decode_audio_envelope,
-    "video":    decode_video_envelope,
-    "model_3d": decode_model3d_envelope,
+    "image": decode_image_envelope,
+    "mask":  decode_mask_envelope,
+    "audio": decode_audio_envelope,
+    "video": decode_video_envelope,
+    "svg":   decode_svg_envelope,
 }
 
 
@@ -932,47 +357,6 @@ def is_audio_input(value: Any) -> bool:
     )
 
 
-def is_video_input(value: Any) -> bool:
-    """Best-effort check for a ComfyUI ``VideoInput`` subclass.
-
-    Duck-types on the ``save_to`` + ``get_duration`` method pair: both
-    are defined on the ``VideoInput`` abstract base in
-    ``comfy_api.latest._input`` and present on every concrete subclass
-    (``VideoFromFile`` / ``VideoFromComponents``). Avoids importing
-    ``VideoInput`` at module load (which would pull torch via the
-    ``comfy_api`` tree).
-    """
-    if isinstance(value, dict):
-        return False
-    return (
-        callable(getattr(value, "save_to", None))
-        and callable(getattr(value, "get_duration", None))
-    )
-
-
-def is_model3d_input(value: Any) -> bool:
-    """Best-effort check for a ComfyUI ``File3D`` (or compatible).
-
-    Duck-types on the ``format`` string attribute + ``get_data``
-    callable: both are present on the ``File3D`` class in
-    ``comfy_api.latest._util.geometry_types`` and the
-    ``BundledFile3D`` subclass built lazily in
-    :func:`_bundled_file3d_class`. Avoids importing ``File3D`` at
-    module load (which would pull torch via the ``comfy_api`` tree).
-
-    The ``VideoInput`` shape (``save_to`` + ``get_duration``) does not
-    expose a ``format`` string property, so VIDEO and MODEL_3D values
-    don't collide; caller (:func:`_encode_one`) still dispatches
-    AUDIO / VIDEO before MODEL_3D as defense-in-depth.
-    """
-    if isinstance(value, dict):
-        return False
-    return (
-        isinstance(getattr(value, "format", None), str)
-        and callable(getattr(value, "get_data", None))
-    )
-
-
 def _is_torch_tensor(value: Any) -> bool:
     try:
         import torch
@@ -989,16 +373,11 @@ __all__ = [
     "decode_mask_envelope",
     "encode_audio_input",
     "decode_audio_envelope",
-    "encode_video_input",
     "decode_video_envelope",
-    "encode_model3d_input",
-    "decode_model3d_envelope",
-    "_bundled_file3d_class",
+    "decode_svg_envelope",
     "decode_envelope",
     "is_envelope",
     "is_image_tensor",
     "is_mask_tensor",
     "is_audio_input",
-    "is_video_input",
-    "is_model3d_input",
 ]