# Dynamic image-list queue

Process a list of images across **the master and direct local or remote ComfyUI workers** without assigning fixed chunks to each participant.

The master evaluates the input list once. By default, the master and each selected idle worker receive one image job at a time; when a participant finishes, it gets the next unassigned image. Faster participants can therefore process more images. The master restores input order before running downstream nodes.

The existing **Orchestrator Only** setting (`settings.master_delegate_only`) excludes the master from per-image processing. It still creates the input list and runs downstream nodes. API callers can override the setting for a run with `delegate_master`. There is no second image-list-specific toggle.

## Wiring

```text
Image list or IMAGE batch
          |
Distributed Image List Start -------- context ---------+
          | image                                     |
          v                                           |
    Per-image processing                              |
          | IMAGE                                     |
          v                                           v
                 Distributed Image List End
                            | image_list
                            v
                     Preview / Save / next stage
```

1. Install the same feature-capable version of Distributed on the master and every selected worker. Workers on an older image-list protocol fail preflight before any work is sent. Restart those instances and refresh the frontend after installation.
2. Enable Distributed and select the **direct** workers to use. The master also participates unless **Orchestrator Only** is enabled. With the master participating, an empty worker selection runs locally through the same image-list scheduler; orchestrator-only mode requires at least one reachable, idle direct worker. The master must be reachable from remote workers at its configured callback address.
3. Feed your image list or tensor batch into **Distributed Image List Start → images**.
4. Connect its `image` output through the per-image processing nodes to **Distributed Image List End → images**.
5. Connect Start's **context** directly to End's **context**. This is a dedicated `DISTRIBUTED_IMAGE_LIST_CONTEXT` socket, not editable text.
6. Put preview/save nodes **after End**, then queue normally. API callers should submit through `/distributed/queue`, not directly through `/prompt`.

ComfyUI represents these as ordinary `IMAGE` sockets with list semantics, not a separate `IMAGE_LIST` socket type. Outside the region there is a list; for each assigned item, Start provides one frame and its aligned values. End returns ordered lists, not a concatenated tensor batch, so differently sized images can be preserved.

## Inputs and outputs

Start accepts:

- `images`: one image, an IMAGE batch, or a ComfyUI image list. A batch is split into individual frames; each frame becomes one job.
- Optional `mask`.
- Optional `value_1`, `value_2`, … inputs. Only `value_1` is shown at first; connecting it adds `value_2`, and so on, up to `value_10`. Each accepts an IMAGE, MASK, STRING, INT, FLOAT or BOOLEAN.

`mask` and every value follow one rule:

- **1 value** is shared by every image.
- **One value per image** pairs them in order.
- **Any other count** is an error. Values are never padded or repeated silently.

Only `images` is split into frames. A batch connected to a value input stays a single value, so a 2-image batch can travel with each item (for example, two reference images per job). To pass a different batch to each image, connect a list with one batch per image.

Start outputs, in order: `image`, `mask`, `item_index` (zero-based), `context`, then one `value_N` output per connected `value_N` input, with the same type. Unused value outputs are hidden. Seeds and strengths are ordinary values: connect a single number to share it, a list for one per image, or derive it from `item_index`.

Values that cannot be transported exactly (models, latents, conditioning and other objects) are rejected. Load models inside the region from a loader connected directly to the processing nodes, as described below.

End accepts `images`, optional `masks` / `texts`, and `context`. It returns `image_list`, `masks`, and `texts` in original item order. Each job must produce exactly one image, at most one mask, and at most one text value. Unconnected optional outputs contain `None` entries.

Models are **loaded and cached on each processing participant**, not serialized between machines. Connect loader outputs directly to the processing nodes. The master needs the region's model files when participating, as does each selected worker. **The master still validates the prompt:** it needs the relevant node definitions and any model-name/file availability required by their validation (including combo lists). This is not a model-free-master guarantee.

Per-image data must pass through Start; do not bypass it with upstream images, latents or generated batches connected directly into the processing region. Shared dependencies across Start are restricted to registered model outputs or scalar constants, not arbitrary image-producing leaf nodes.

End's optional `texts` is a connection-only socket. For workflows saved before this fix, recreate End and reconnect its wires if an old text widget or literal `texts: ""` remains in the compiled prompt. Arbitrary text literals are not accepted at End.

File-based dependencies keep ComfyUI's `[output]` / `[temp]` root annotations while being read on the master. Their worker copies use separate content-addressed paths under `input/distributed-media/`; each worker's rewritten prompt is reused across items without reusing item tokens.

## Scope and failure behavior

- This version supports the master and direct workers, not Runpod serverless pools. Unsupported pools are excluded without contacting the provider for this job.
- Worker eligibility is determined before execution and checked again before dispatch. Busy or transiently unreachable workers are excluded; healthy candidates can continue. Malformed capability/queue responses and incompatible versions fail explicitly. Workers joining later are not added to an already-running region.
- Omitted worker IDs select enabled direct workers. Explicit IDs select the named configured direct workers, including disabled ones; an empty list stays empty, unknown IDs fail, and serverless workers are excluded. Local workers use the master's loopback callback; remote workers use its configured public address.
- Only the enclosed processing is distributed. List creation and downstream saving run on the master in both modes. With participation enabled, the master is a normal scheduler participant and can run alone when no direct workers are available. **Orchestrator-only mode never silently falls back to master processing.** Failed items are not reassigned automatically.
- Local items execute while the enclosing master prompt waits; they are not queued behind that prompt on the master's `/prompt` queue. The enclosed branch is not also evaluated as a full list by the outer prompt.
- Start/End regions may be chained sequentially and share model-loader dependencies. Nested/overlapping per-image regions and data escaping a region without End are rejected. Collector and distributed-upscaler nodes cannot be mixed into the same prompt in this first version.
- Output nodes inside a region are rejected because ComfyUI would execute them independently on the master. Avoid other side-effecting processing nodes as well; save after End.
- The entire input list is materialized before scheduling; this is not streaming input. The limit is 4,096 frames. Remote transport preserves floating-point tensor dtype and values rather than encoding to lossy images. Each transported tensor is limited to 50 MiB, and the complete JSON/base64 HTTP request to 101 MiB; image/mask/value combinations can hit the aggregate request limit first. In-process master items use tensors directly and do not incur those HTTP limits.
- Results are accepted once per item using assignment tokens. Missing, duplicate, malformed and wrong-index results fail rather than silently returning a partial list. No failed or ambiguous submission is retried automatically.
- Worker errors fail the region. The worker timeout measures loss of evidence for the **owned prompt ID**, not maximum render duration. Pending/running evidence refreshes liveness; unrelated busy jobs and failed polls do not. Healthy cold loads and long renders can continue.
- User interruption is checked during submission and result waiting. Cleanup targets only this region's acknowledged prompt IDs and staged input tokens. Submission may wait briefly for an acknowledgement before cancellation; remote transport and cleanup have finite time limits. Local cleanup stops at node/progress boundaries and waits for its execution thread to finish before the parent prompt can resume. A synchronous node that does not cooperate with cancellation can delay this beyond the configured deadline. Lost acknowledgements are **ambiguous**, never retried automatically. Unreachable cleanup is logged as unconfirmed and may require checking the worker manually; cancellation does not guarantee remote termination through a broken network.
- State is in memory. Restarting the master does not resume an interrupted region. Abandoned master contexts and expired worker staging are actively swept on the server loop; active/queued master work is protected from age-only expiry. End also removes its context on success, failure or interruption. This releases feature-owned references, not ComfyUI's separate execution cache.

### Time and size limits

`settings.image_list_job_timeout_seconds` defaults to `0` (no arbitrary total-run cap). A positive finite number opts into an overall deadline with owned-work cleanup; negative, non-finite or malformed settings fail explicitly. There is no fixed one-hour region deadline. The setting is separate from the existing worker liveness timeout.

Uploads, media preparation and submission acknowledgements are independently bounded. WebSocket acknowledgement waiting includes connect/send/receive and is not extended by heartbeats or unrelated messages. A user interrupt allows up to one second for a late acknowledgement; cleanup requests use five-second bounds each.

**4K float32 RGB outputs cannot be returned by direct workers under these transport limits.** A 3840×2160 RGB float32 tensor exceeds 50 MiB before base64 encoding. Mixed master/worker 1080p-to-4K upscaling therefore cannot use this configuration; master-only execution does not use the HTTP transport. Dtypes/values are never silently reduced to fit. Complete encoded input requests are checked before upload, including image/mask/value combinations; output limits are checked when the worker has computed the result. Reverse proxies may impose lower HTTP limits.

Use trusted workers and trusted workflows, as with the existing ComfyUI API. Capability tokens protect assignment/result matching; they are not a replacement for network access control.

## Verification

The generic acceptance helper starts two isolated loopback worker test servers and uses actual CPU ComfyUI `PromptExecutor` instances. Production queue preparation, list nodes, graph extraction, HTTP item/result routes, dynamic scheduling, float transport, ordering and cancellation are exercised. The harness checks orchestrator-only, mixed master/worker and master-only execution, including exact-once item assignment, source-once materialization and cached local model-loader dependencies. The lightweight queue/history facade is test code; no managed ComfyUI service or model is started.

```bash
COMFYUI_SOURCE_ROOT=/path/to/ComfyUI /path/to/ComfyUI/.venv/bin/python -m pytest tests -q
bash scripts/test-web.sh
```

Without `COMFYUI_SOURCE_ROOT`, real-framework tests are explicitly skipped. This coverage is not a substitute for checking your model workflow and connectivity on the actual GPU worker machines.