ComfyUI-H3-Continuous

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ComfyUI-H3-Continuous

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Chain MiniMax H3 renders into one unbroken take: each segment opens on an exact replay of the last, pinned with AddGuide. Resumable, with a both-ends-pinned repair node.

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ZIP 다운로드

- chain-workflow.png
- how-it-works.md
- kate.png
- stage.png
- __init__.py
- common.py
- engine.py
- nodes.py
- session.py
- video_io.py
- - README.md
  - seg-01.txt
  - seg-02.txt
  - seg-03.txt
  - seg-04.txt
  - seg-05.txt
  - seg-06.txt
- - README.md
- - README.md
  - seg-01.txt
  - seg-02.txt
  - seg-03.txt
  - seg-04.txt
- - README.md
  - seg-01.txt
  - seg-02.txt
  - seg-03.txt
- README.md
- adopt_workflow.py
- append_repair.py
- bench_chain.py
- build_workflows.py
- check_joins.py
- face_drift.py
- kate_drift6_prompts.py
- kate_rant6_prompts.py
- kate_stage_prompts.py
- latent_drift.py
- test_latent_handoff.py
- h3_continuous.json
.gitattributes
.gitignore
__init__.py
LICENSE
pyproject.toml
README.md

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// repository documentation

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Chain any number of MiniMax H3 renders into **one unbroken take**.

Each segment opens on an exact replay of the last ~1.6 seconds of the segment before
it, so the joins are invisible — not "similar framing", the same frames. Write a prompt
per shot, wire the references, hit Run once.

![the chain workflow](https://raw.githubusercontent.com/loopforge0/ComfyUI-H3-Continuous/main/docs/chain-workflow.png)

---

## Setup

Three steps, about 35 GB of downloads, and one `git clone`. There is nothing to
`pip install` — this pack has no dependencies of its own.

You need **ComfyUI 0.34.0 or newer**. *Settings → About* shows your version. Older
builds have no MiniMax H3 nodes at all, so nothing here will load.

### 1. Get the nodes

Clone into `ComfyUI/custom_nodes`:

```bash
cd ComfyUI/custom_nodes
git clone https://github.com/loopforge0/ComfyUI-H3-Continuous
```

Restart ComfyUI. To check it worked, double-click the empty canvas and type
`H3 Chain` — if **H3 Chain Settings** comes up, the nodes are installed.

### 2. Get the models

Five files, all from [Comfy-Org/MiniMax-H3](https://huggingface.co/Comfy-Org/MiniMax-H3):

| Download | Put it in |
| --- | --- |
| [`minimax_h3_ref2va_pruned_int8_convrot.safetensors`](https://huggingface.co/Comfy-Org/MiniMax-H3/blob/main/diffusion_models/minimax_h3_ref2va_pruned_int8_convrot.safetensors) (20 GB) | `ComfyUI/models/diffusion_models/` |
| [`qwen3vl_32b_minimax_h3_nvfp4_awq.safetensors`](https://huggingface.co/Comfy-Org/MiniMax-H3/blob/main/text_encoders/qwen3vl_32b_minimax_h3_nvfp4_awq.safetensors) (15 GB) | `ComfyUI/models/text_encoders/` |
| [`minimax_h3_video_vae_fp16.safetensors`](https://huggingface.co/Comfy-Org/MiniMax-H3/blob/main/vae/minimax_h3_video_vae_fp16.safetensors) | `ComfyUI/models/vae/` |
| [`minimax_h3_audio_vae_fp32.safetensors`](https://huggingface.co/Comfy-Org/MiniMax-H3/blob/main/vae/minimax_h3_audio_vae_fp32.safetensors) | `ComfyUI/models/vae/` |
| [`minimax_h3_ref2v_turbo_4step_v0.1_comfyui_bf16.safetensors`](https://huggingface.co/Comfy-Org/MiniMax-H3/blob/main/loras/minimax_h3_ref2v_turbo_4step_v0.1_comfyui_bf16.safetensors) | `ComfyUI/models/loras/` |

It must be the **ref2va** model, not `fl2va`. This pack chains *reference*-conditioned
renders; the fl2va model does not take reference images and the workflow will not run
on it.

The last one is the turbo LoRA. It is optional but you almost certainly want it: it
cuts sampling from 20 steps to 4. On a 12 GB card that is the difference between
**5 minutes a shot and 31 minutes a shot**.

Once the files are in place, hit **R** on the ComfyUI canvas (or restart it) so the
loader dropdowns pick them up.

The workflow carries this same list in a blue **Models** note on its canvas, and each
loader node carries its download URL in `properties.models` the way ComfyUI's own
templates do — so a missing file is something ComfyUI can offer to fetch on open,
rather than an unexplained empty dropdown.

### 3. Open the workflow

Drag **`workflows/h3_continuous.json`** onto the ComfyUI canvas.
That is the only workflow file in this repo, and it holds everything:

| On the canvas | What it is |
| --- | --- |
| **A — the chain** (purple) | A finished worked example that runs as-is: a singer alone in a spotlight, one continuous ~21-second take in three shots. |
| **B — repair** (bypassed) | Re-render one bad shot without disturbing the rest. Ships switched off, below the chain, sharing the same models and settings. |
| **Models** / **Start here** / **Repair** notes | Download links, the storage tree, and how to drive each half. |

**It runs as it opens.** Copy the two files in `example_inputs/` into `ComfyUI/input/`
and hit Run — nothing else needs setting. About 27 minutes on a 12 GB card with the
turbo LoRA on. Read its three prompts side by side afterwards; that is where the method
is.

To make it yours, edit in place: rewrite the prompts, swap the `Load Image` nodes, and
add or delete **H3 Render Segment** nodes to change the shot count. There is no separate
blank template — a worked example you edit beats an empty one you have to fill.

---

## Your first run

Open the workflow and work left to right through group **A**.

**1 — Models (the blue group).** Point the five loaders at the files you just
downloaded. Most of them will already be right if you only have one of each.

Then decide your quality/speed trade-off:

* **Fast (recommended to start):** click the **Turbo LoRA** node once and press
  **Ctrl+B** to un-bypass it, then set **BasicScheduler** `steps` to **4**.
* **Best quality:** leave the LoRA bypassed (it ships that way) and `steps` at 20.

Set the canvas size on **ResolutionSelector** — pick an aspect ratio and a megapixel
budget. `0.41` MP (480×864 in 9:16) is a good, safe starting point on 12 GB.

**2 — Shots (the purple group).** One **H3 Render Segment** node per shot, wired in a
line: each node's `chain_state` output goes into the next node's `chain_state` input.
The first node's `chain_state` input stays empty.

On each node:

* **`prompt`** — the example's real prompts are in here. Rewrite them, but keep the
  section headings (`subject_definitions:`, `summary:`, and so on); H3 expects them.
* **`seconds`** — how long this shot runs.
* **reference images** — every shot is wired to the same two `Load Image` nodes,
  `kate.png` on `image_0` and `stage.png` on `image_1`. Click a filename to pick your
  own (anything in `ComfyUI/input/`, or the node's **choose file to upload** button).
  `image_0` becomes `<Picture 1>` in your prompt, `image_1` is `<Picture 2>`, and so on.
  **Feed the same image into every shot** — that is what keeps a character looking like
  the same person.

Two rules that will bite you if you skip them:

* **Repeat your camera, lighting and character descriptions word for word in every
  shot.** Not paraphrased. That verbatim repetition is what holds the look together
  across the joins.
* **Nothing new can happen in the first ~1.6 seconds of any shot after the first.**
  Those frames are a fixed replay of the previous shot. Schedule your first new action
  after the 1.7-second mark.

**3 — Name the session.** Set `session_name` on **H3 Chain Settings** to anything you
like. Everything lands in `ComfyUI/output/h3_continuous/<session_name>/`.

**4 — Hit Run.** Once. That is the whole thing.

Shots render one at a time and each is written to disk the moment it finishes, so you
can watch the take build up in the session folder. When the last one is done,
**H3 Chain to Video** stitches them into `<session_name>.mp4`.

If you stop it, change your mind, or crash: **just hit Run again.** Only the shots
whose settings actually changed get re-rendered. See
[It resumes](#it-resumes-and-that-changes-how-you-work).

### How long it takes

Measured on a 12 GB RTX 3060 at 480×864, per shot:

| | 4-second shot | 8-second shot |
| --- | --- | --- |
| turbo LoRA, 4 steps | ~5 min | ~9 min |
| no LoRA, 20 steps | ~18 min | ~31 min |

The model is 20 GB and does not fit in 12 GB, so it streams weights every step. More
VRAM is a very large speed-up here. If you hit out-of-memory partway through a long
chain, turn on `unload_models_after` on the single shot where it happens.

---

## The knobs that matter

| Setting | Where | What it does |
| --- | --- | --- |
| `seconds` | Render Segment | Length of this shot. Snapped up to H3's 17k+5 grid (8 s → 192 frames). Trained range ≈ 5–15 s. |
| `handoff_seconds` | Render Segment, advanced | How much of **this** shot's ending the **next** one opens on. Snapped down to 5 / 22 / 39 / 56 frames. Set to 0 on the last shot of a take. |
| `seed_override` | Render Segment, advanced | 0 derives from the chain seed. Set it to re-roll one shot. |
| `model` | Render Segment | Optional. A MODEL for this shot only, overriding the Settings one — this is where a per-shot LoRA goes. |
| `chain_seed` | Settings | Changing it re-renders everything. |
| `resume` | Render Segment | Reuse this segment if unchanged (see below). |
| `handoff_mode` | Settings, advanced | `latent` (default) slices the handoff out of the sampled latent — no VAE, exact anchor, faster. `pixel` is the old decode/re-encode route; use it only to change resolution mid-session. |
| `stabilize` | Chain to Video, advanced | 1.0 flattens the take's slow colour drift away from its own opening. Costs no GPU. **Leave it on.** |
| `drift_arrest` | Settings, advanced | Experimental, ships at 0. Steers the latent but overshoots the picture; no measured benefit. [Why](docs/how-it-works.md#drift_arrest). |
| `unload_models_after` | Render Segment, advanced | Unload models after this segment. OOM-only — turn it on for just the segment where you actually OOM. |

**Set `handoff_seconds` to about a fifth of `seconds`.** That is the one rule. The
1.625 s default is right for 8-second shots and wrong for short ones — on a 4-second
shot it is 36 % of the whole thing, past the point where the model has too little free
footage left and the seam starts to show.

| shot length | use |
| --- | --- |
| 8 s | **1.625 s** (the default) |
| 5-6 s | 0.917 s |
| 4 s | **0.917 s** |
| under 4 s | 0.917 s, and consider longer shots instead |

Longer handoffs also cost you finished footage: at 8 s shots with a 1.625 s handoff,
every shot after the first contributes 6.375 s to the cut. The reasons behind the exact
numbers — why 39 frames in particular, and what the audio grid has to do with it — are
in [how it works](docs/how-it-works.md#1-anchor-the-tail-dont-reference-it).

### A LoRA on one shot

**H3 Render Segment** has an optional `model` input. Wire one in and that segment
renders on it instead of the model on **H3 Chain Settings**; leave it unconnected and
nothing changes. There is no LoRA widget on the node, because ComfyUI already has good
LoRA nodes and this way you get all of them:

```
Load Diffusion Model ─┬─ LoraLoaderModelOnly (turbo) ─┬─ H3 Chain Settings . model
                      │                               ├─ H3 Render Segment 2 . model
                      │                               └─ LoraLoaderModelOnly (dance) ─ H3 Render Segment 3 . model
```

Two things to hold on to:

**Chain the turbo LoRA through, don't replace it.** The input swaps the model out
rather than adding to it, so a segment handed a bare checkpoint samples on 4-step
sigmas without the LoRA those sigmas exist for — 4 steps of a 20-step model, which
looks like a render that gave up half way.

**MODEL only.** H3 LoRAs are diffusion-side; there is no CLIP input here, and routing
one through Qwen3-VL is not what they are trained for.

Changing a LoRA or its strength re-renders that segment and every segment after it even
with `resume` on — the cache key reads the model's patch list, so it sees the swap. That
is also the cost: a style LoRA dropped onto shot 2 of a six-shot take re-renders five
shots. Settle the take first, then decorate.

---

## It resumes, and that changes how you work

Every finished segment is written to `output/h3_continuous/<session>/`:

```
seg_01.mp4          the segment
seg_01.tail.mp4     the clip segment 2 opens on
seg_01.tail.wav     that clip's soundtrack, sample-exact
manifest.json       what was rendered, and the fingerprint of each segment
stage_song.mp4      the joined cut
```

**Each shot is its own node execution**, not one loop hidden inside a container node, so
`seg_03.mp4` and `manifest.json` are both written to disk the moment segment 3 finishes —
not when the whole chain finally does. Wire a Preview Video node (or anything else) to
any segment's `video` output and it plays as soon as that one segment is done, while
later segments are still rendering. The manifest is rewritten after *every* segment, so
even a hard kill — not just a clean interrupt — leaves it exactly matching what is on
disk: the next queue never re-renders something that actually finished.

Reused segments still post a thumbnail on their node, so a resumed run visibly walks
through what it is keeping.

Re-running reuses everything that has not changed. A segment's fingerprint includes the
fingerprint of the one before it, so:

* Edit **segment 3's prompt** → 3, 4, 5… re-render. 1 and 2 are reused untouched.
* **Interrupt** mid-chain → the next run picks up at the segment that was in flight.
* Change `chain_seed`, the resolution, the sampler or the LoRA → everything re-renders.

Swapping the checkpoint file for a *different file of the same architecture* is the one
change the fingerprint cannot see. Rename the session or turn `resume` off when you do
that.

Need to add more shots to a session that already finished? **H3 Load Session**'s `chain`
output wires straight into another **H3 Render Segment**'s `chain_state` input, same as
chaining live segments — it renders on, without touching what is already there.

---

## Repairing one bad shot

It is already on the canvas, in the **B - REPAIR** groups below the chain, shipped
**bypassed** so it costs nothing until you want it. To switch over: select the repair
nodes and press **Ctrl+B** to un-bypass them, then select the shots in group **A** and
**Ctrl+B** those off. Run with both halves live and you render — and pay GPU time for —
both.

It shares the **H3 Chain Settings** node with the chain, so the models, sampler, canvas
size and `chain_seed` are already the ones your session used. They have to be.

One segment came out wrong — a fluffed line, a hand through a lamppost. Normally
re-rendering segment N changes its ending, so every segment after it stops joining and
has to be re-rendered too. On a seven-shot chain, fixing shot 2 costs you six renders.

**H3 Repair Segment pins both ends.** The opening is pinned to the previous segment's
handoff clip; the ending is pinned to *the very clip the next segment already opens on*.
The replacement lands between two fixed points and nothing downstream moves.

1. Type the `session_name` into **H3 Load Session**. It prints what is in that session.
2. Set `segment_number` (1-based, matching `seg_NN.mp4`).
3. Rebuild that shot on the **H3 Repair Segment** node — same references, same length,
   fixed prompt.
4. Run. The old file is kept as `seg_NN.replaced.mp4`, the node's own `video` output
   plays the replacement immediately, and the whole cut is re-joined.

Two details worth knowing:

* The pinned ending is anchored as **picture only**. Its audio comes from the render you
  are throwing away, and re-anchoring that would drag back exactly what you are
  removing. (This is not hypothetical: it is how a shot with no dialogue of its own ends
  up replaying the previous shot's lines.)
* `seg_NN.tail.mp4` is deliberately **not** rewritten. It is what segment N+1 actually
  opens on, and the repair was pinned to it.

Leave `pin_ending` on. Turn it off only for the last segment, or when you mean to
re-render everything after this one — the node will tell you what that invalidated.

---

## Writing the prompts

H3's reference format wants six sections: `subject_definitions`, `summary`,
`retention_analysis`, `detailed_description`, `overall_soundscape`,
`non_diegetic_music`. Every segment in the shipped workflow carries a real one.

What matters for *chaining*, beyond the two rules at the top:

* **Repeat the camera and lighting rules verbatim** in every segment. Not paraphrased —
  word for word. That repetition is what keeps the look identical across the joins.
* **Restate the subject definitions in full** every time. A segment is generated on its
  own; it knows nothing about the last one except the frames you pinned.
* Add a line telling the shot to *continue* the pose it inherits: "holds the exact body
  pose, head angle, gaze direction and facial expression carried in by the replayed
  opening, continuing them without any reset."
* Set `non_diegetic_music` to `N/A` and score the finished cut in post. Independently
  generated music beds will not match across a join.

For dialogue: speakers must face the lens, delight belongs in the eyes and brows (a held
smile is an open mouth that overrides articulation), and gestures go *after* the line —
under it, the motion budget goes to the gesture and the mouth freezes.

The three shipped prompts show all of the above in one place — the repeated blocks, the
replayed openings, and the sing-then-move alternation that keeps the mouth and the body
from competing. The reasoning behind each choice is written up in
[`tools/kate_stage_prompts.py`](tools/kate_stage_prompts.py).

### Twenty seven worked examples

[`prompts/`](prompts) holds every prompt behind the takes in the video walkthrough, one file
per render, copied byte for byte from what was sent rather than tidied up afterwards: a
seven-render walk down Market Street built twice at two resolutions, a four-render piece to
camera, a six-render one, and the three-render stage song that ships as the example workflow.

Each folder carries a README with the thing a prompt cannot carry itself — **which reference
image was wired into which `<Picture N>` slot**. Those numbers are positional, taken from the
order the images enter the node, so a prompt read without that table has unresolvable
references. Seeds, frame counts and handoff lengths are in the same tables, and the reference
images are in each folder's `refs/`.

---

## The nodes

| Node | Does |
| --- | --- |
| **H3 Chain Settings** | Models, sampler, canvas, seed and session name in one bundle. Every other node here takes it. |
| **H3 Render Segment** | One shot, in and out: prompt, images → `<Picture n>`, videos → `<Video n>`, audio → `<Audio n>`, length, handoff — and it renders right there. Optional `model` input takes this shot on a LoRA of its own. Outputs its own `video` the moment it finishes, plus a `chain_state` that wires into the next H3 Render Segment to continue the take. |
| **H3 Chain to Video** | Joins a chain's segments into one cut, dropping each replayed opening. `stabilize` also flattens the chain's slow colour drift, on the CPU. |
| **H3 Repair Segment** | Re-renders one segment pinned at both ends. |
| **H3 Load Session** | Picks up a session already on disk, to re-join, repair, or extend with more H3 Render Segment nodes, without re-rendering what is done. |

There is no separate "chain" node: the chain is however many **H3 Render Segment**
nodes you wire in a row. Each one is its own execution, so its `video` output — and
anything hanging off it, like a Preview Video node — is available the instant that
segment is done, independent of how many more are still to render.

The chain calls ComfyUI's own `MiniMaxH3ReferenceToVideo`, `MiniMaxH3AddGuide` and
`SamplerCustomAdvanced` rather than reimplementing them, so a ComfyUI update carries
straight through.

---

## Troubleshooting

**Segment 1 renders, segment 2 dies with `shape mismatch: value tensor of shape
[A, 96] cannot be broadcast to indexing result of shape [B, 96]`.** Your ComfyUI is
half updated. Segment 1 pins nothing, so it never touches the code that is wrong;
segment 2 opens on a 39-frame handoff, and a core from before `MiniMaxH3AddGuide`
(ComfyUI 0.34.0) reserves room for **one** latent frame of guide however long the guide
actually is — so twelve frames' worth of rows go into a slot sized for one, and torch
says so.

The odd part is that such a core cannot have `MiniMaxH3AddGuide` at all, and this pack
refuses to load without it. Both arrived in the same commit. So if you are seeing this,
`comfy_extras/nodes_minimax_h3.py` updated and `comfy/ldm/minimax/model.py` did not.
Update ComfyUI, restart it fully — not just "reload the frontend" — and check:

```bash
grep "vt = video_latent.shape\[2\]" ComfyUI/comfy/ldm/minimax/model.py
```

One line back means you are fixed. Nothing back means the file is still the old one; if
it prints the line and the error persists, delete `ComfyUI/comfy/ldm/minimax/__pycache__`
and restart. From this version on the pack checks for this before it starts sampling, so
you get this explanation instead of a tensor shape, in the first second rather than the
fifth minute.

**A later segment replays the previous segment's dialogue.** The handoff clip's audio is
longer than its video. A guide's audio is cropped against the *target's* remaining
duration, never against the picture beside it, so an over-long soundtrack gets anchored
whole. On the pixel path the pack writes handoff audio as a sample-exact sidecar WAV
precisely to stop this — check that `seg_NN.tail.wav` exists next to `seg_NN.tail.mp4`.
On the latent path the audio tail is cut on the 40 Hz latent grid and cannot run long
in the first place.

**The join stutters.** The replayed opening is not being dropped. Only **H3 Chain to
Video** knows how many frames to cut off each segment; joining the `seg_NN.mp4` files by
hand in an editor will repeat 1.6 s at every cut.

**File → Open does nothing and the canvas stays blank.** A **ComfyUI-Manager** bug, not
this pack. Manager patches `app.handleFile` — the code behind File → Open *and*
drag-and-drop — and reads `.datetime` off the first value in the file; when that value
is `null` it throws inside an async callback, so the open silently never happens, with no
error toast. It hits any workflow whose `id` is `null`, which is every workflow ComfyUI
itself saves. The workflow here ships with a real `id` and is unaffected. For any other
file that will not open: load it from the **Workflows sidebar** instead (that path skips
Manager's hook), or set its `"id"` to any string.

**The workflow opens but the canvas looks empty, or the nodes are unreadable grey
boxes.** The graph is off-screen or zoomed out. Press **`.`** (period) with nothing
selected — that fits the whole workflow to the window. A workflow stores its own saved
viewport, so this is about where you are looking, not whether it loaded; the node count
bottom-left tells you what is actually there.

**The model dropdowns are empty, or say `null`.** ComfyUI has not seen the files yet.
Confirm each one is in the exact folder from the table above — not a subfolder — then
press **R** on the canvas to refresh, or restart ComfyUI.

**The nodes show up red, saying "missing node types".** The pack is not loaded. Check
that the folder you cloned sits directly in `ComfyUI/custom_nodes/`, and look at
ComfyUI's startup console for an import error from `ComfyUI-H3-Continuous`.

**Everything re-renders every run.** Something in the fingerprint moved — most often a
seed widget set to randomize somewhere upstream, or a resolution change.

**Out of memory partway through a long chain.** Turn on `unload_models_after` (advanced)
on the segment where it happens. It costs a full model reload before the next segment
starts, so use it only there, not on every segment.

**A segment errors and the run stops.** Everything already finished is on disk and in
the manifest — written after every segment, not just at the end — so fixing the problem
and re-queueing resumes from the segment that failed.

---

## Under the hood

[**docs/how-it-works.md**](docs/how-it-works.md) is the background: why a keyframe
anchor beats `ref_videos`, where the 39-frame handoff number comes from, what colour
drift does over a long chain and what `stabilize` does about it. Every number in it was
measured, and the scripts that measured it are in `tools/` — `check_joins.py`,
`face_drift.py`, `latent_drift.py` and `bench_chain.py`.

The handoff itself is frame arithmetic on a latent, which is the kind of thing that is
silently three frames wrong for a month. `tools/test_latent_handoff.py` asserts the
slice lands where it should across every legal shape, and needs no GPU and no models:

```bash
python tools/test_latent_handoff.py --comfy /path/to/ComfyUI
```

`tools/build_workflows.py` regenerates the shipped workflow from a running ComfyUI's
`/object_info`, so widget order and socket names cannot drift away from the nodes.
`adopt_workflow.py` pulls a hand-rearranged workflow back into the repo, and
`append_repair.py` adds the repair half to it.

---

## Credits

Built out of the Market Street walk project — a 46-second continuous H3 shot assembled
from seven chained renders. The measurements behind the defaults here (17 dB vs 30 dB,
the 0/17/34 fidelity peaks, the audio-anchor failure) came out of building it, and are
written up in [how it works](docs/how-it-works.md).

The drift work came later, out of asking why a chain that joins perfectly can still
end up somewhere else. Everything in that section was measured on a 12 GB RTX 3060 at
480×864 — five six-shot chains rendered for the comparison, plus three earlier ones
re-measured. `tools/bench_chain.py` reproduces it.

---

## License

MIT. See [LICENSE](LICENSE).

ComfyUI-H3-Continuous

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