---
title: LingBot World 2.0
metatags:
    description: "Serve LingBot World 2.0 realtime camera-controlled video world models with SGLang-diffusion."
tag: REALTIME
---

import { DiffusionModelTags } from '/src/snippets/diffusion/model-tags.jsx';

<DiffusionModelTags tags={["realtime", "world model", "14B causal DiT", "camera control", "interactive KV window"]} />

## 1. Model Introduction

[LingBot World 2.0](https://huggingface.co/robbyant/lingbot-world-v2-14b-causal-fast-diffusers) is the 14B realtime camera-controlled world model in the LingBot family. It generates continuously from a live causal session, accepts control updates between chunks, and reuses DiT and VAE state for incremental frame delivery.

Choose 2.0 when the larger model and interactive KV-window path justify an 8-GPU deployment. Like the earlier LingBot release, it prioritizes responsive control and bounded causal state over the full-clip global context of offline video diffusion.

## 2. Deployment

```bash Command
export SGLANG_LINGBOT_LAZY_VAE_ENCODE_BLACK_FRAMES=60
export SGLANG_LINGBOT_ENABLE_INTERACTIVE_KV_WINDOW=true
sglang serve \
  --model-path robbyant/lingbot-world-v2-14b-causal-fast-diffusers \
  --pipeline-class-name LingBotWorldCausalDMDPipeline \
  --num-gpus 8 \
  --ulysses-degree 8 \
  --dit-cpu-offload false \
  --text-encoder-cpu-offload false \
  --vae-config.use-parallel-decode true \
  --vae-config.parallel-decode-mode spatial \
  --enable-torch-compile false
```

### Optional KV-Cache Compression

Long-running sessions can enable lossy int4 PRQ compression for completed
causal KV-cache chunks by installing `quant-videogen` as described in the
quantization guide and adding `--kv-cache-quant int4` to the server command.
The current and most recent completed chunks remain in BF16. See
[Causal KV-Cache Quantization](/docs/sglang-diffusion/quantization#causal-kv-cache-quantization)
for the algorithm, tuning options, measured memory-latency tradeoff, and
support limits.

## 3. Realtime WebUI

The lightweight local WebUI is useful for validating latency, frame transport, and camera control behavior.

```bash Command
python -m http.server 18080 -d python/sglang/multimodal_gen/apps/realtime_webui
```

Open `http://127.0.0.1:18080` and use:

```text Example
ws://127.0.0.1:30000/v1/realtime_video/generate
```

## 4. HTTP and WebSocket API

LingBot World 2.0 uses the realtime video WebSocket endpoint. The server keeps one live session, generates one chunk at a time, and accepts runtime control events while generation is running.

### Endpoints

| API | Method | Purpose | Notes |
| --- | --- | --- | --- |
| `/v1/models` | `GET` | Query the served model id before opening a session. | The WebUI uses this to fill the model field when the server exposes model metadata. |
| `/v1/realtime_video/generate` | `WebSocket` | Create one realtime LingBot session and stream generated video chunks. | The first client message must be an `init` message encoded with MessagePack. |

### `init` message

Send this MessagePack map immediately after the WebSocket opens.

| Parameter | Type | Required | Meaning |
| --- | --- | --- | --- |
| `type` | string | Yes | Must be `"init"`. |
| `model` | string | No | Model id. Leave empty to use the served model. |
| `prompt` | string | Yes | Text prompt for the initial scene and motion style. |
| `first_frame` | bytes or string | Yes | Initial reference image. Send bytes from the WebUI/client, or a server-readable image path/string. |
| `size` | string | Yes | Generation size as `WIDTHxHEIGHT`, for example `832x480`. |
| `fps` | number | Yes | Target playback FPS for the generated stream. |
| `num_frames` | integer | Yes | Frames per generated chunk. LingBot uses chunked causal generation, so this controls per-chunk latency and queue size. |
| `seed` | integer | No | Random seed for deterministic sampling. |
| `num_inference_steps` | integer | No | Denoising steps per chunk. LingBot defaults to `4` when omitted. |
| `guidance_scale` | number | No | Classifier-free guidance scale. Realtime LingBot commonly uses `1`. |
| `negative_prompt` | string | No | Negative prompt passed to the diffusion pipeline. |
| `quality` | `"lossless"`, `"extra-high"`, `"high"` | No | `lossless` keeps FP32 VAE decode. `extra-high` keeps FP32 decode and enables only any eligible request-gated kernel fusions. `high` includes those fusions and uses the validated BF16 decode path for lower per-chunk latency. |
| `max_chunks` | integer | No | Stop after this many chunks. Omit for a continuous session. |
| `realtime_causal_sink_size` | integer | No | Number of sink frames/tokens retained in the causal attention window. |
| `realtime_causal_kv_cache_num_frames` | integer | No | Number of recent frames retained in the causal KV cache window. |
| `realtime_output_format` | `"webp"`, `"jpeg"`, `"raw"` | No | Preview/output transport. `webp` and `jpeg` send encoded preview frames; `raw` sends raw RGB; omit for lossless delta-gzip RGB. |
| `output_compression` | integer | No | Preview quality for `webp` or `jpeg`, from `1` to `100`. |
| `enable_upscaling` | boolean | No | Enable server-side super resolution after frame decode. |
| `upscaling_scale` | integer | No | Super-resolution scale. Current default is `4` when upscaling is enabled. |
| `upscaling_model_path` | string | No | Optional Real-ESRGAN model path. |
| `enable_frame_interpolation` | boolean | No | Enable frame interpolation. Keep this disabled when measuring true generated FPS. |
| `frame_interpolation_exp` | integer | No | Interpolation multiplier exponent. `1` means 2x frames. |
| `frame_interpolation_scale` | number | No | RIFE internal scale for interpolation. |
| `frame_interpolation_model_path` | string | No | Optional RIFE model path. |
| `condition_inputs.camera_actions` | `list[list[string]]` | No | Initial scripted camera actions, one action list per frame. |

### Runtime `event` messages

After `init`, send MessagePack event maps to update the live session.

| Parameter | Type | Required | Meaning |
| --- | --- | --- | --- |
| `type` | string | Yes | Must be `"event"`. |
| `kind` | `"prompt"`, `"camera_actions"`, or `"composite_input"` | Yes | Runtime event kind. |
| `payload` | string, object, or list | Yes | For `prompt`, a non-empty string. For `camera_actions`, either scripted `list[list[string]]` or state-mode payload. For `composite_input`, a map containing `input_types` plus each named input. |
| `event_id` | integer | No | Client sequence id. The server echoes it in chunk/frame metadata after the event is sampled. |

`camera_actions` supports two payload modes:

| Mode | Payload shape | Meaning |
| --- | --- | --- |
| Script | `list[list[string]]` | A fixed sequence of per-frame actions consumed by upcoming chunks. |
| State | `{ "mode": "state", "transitions": [{"actions": [...], "client_ts_ms": ...}] }` | Live control state transitions from keyboard or UI controls. |

Supported LingBot action tokens include `w`, `a`, `s`, `d` for camera movement and `i`, `j`, `k`, `l` for look controls.

Use `composite_input` when multiple runtime inputs should be sampled together, such as updating the prompt and camera controls in one event.

### Server messages

| Message | Payload | Meaning |
| --- | --- | --- |
| `frame_batch` | MessagePack map with `payload` bytes | One batch of frames. The map includes `chunk_index`, `num_frames`, `content_type`, `encoding`, `width`, `height`, and frame-batch metadata. |
| `chunk_stats` | MessagePack map | Per-chunk timing and transport metrics, including `scheduler_forward_ms`, `raw_payload_build_ms`, `chunk_total_ms`, `num_frames`, and `ws_payload_bytes`. |
| `error` | MessagePack map | Server-side validation or generation error. |

### Minimal client sketch

```python Python
import msgspec.msgpack
import websocket

ws = websocket.create_connection("ws://127.0.0.1:30000/v1/realtime_video/generate")
ws.send_binary(msgspec.msgpack.encode({
    "type": "init",
    "prompt": "A quiet rainy London alley, stable camera motion.",
    "first_frame": open("reference.jpg", "rb").read(),
    "size": "832x480",
    "fps": 25,
    "num_frames": 9,
    "num_inference_steps": 4,
    "guidance_scale": 1,
    "realtime_output_format": "webp",
    "output_compression": 95,
}))

ws.send_binary(msgspec.msgpack.encode({
    "type": "event",
    "kind": "camera_actions",
    "event_id": 1,
    "payload": {"mode": "state", "transitions": [{"actions": ["w"], "client_ts_ms": 0}]},
}))

ws.send_binary(msgspec.msgpack.encode({
    "type": "event",
    "kind": "prompt",
    "event_id": 2,
    "payload": "A quiet snowy Tokyo alley, stable camera motion.",
}))

ws.send_binary(msgspec.msgpack.encode({
    "type": "event",
    "kind": "composite_input",
    "event_id": 3,
    "payload": {
        "input_types": ["prompt", "camera_actions"],
        "prompt": "A quiet neon Shanghai alley, stable forward camera motion.",
        "camera_actions": [["w"], ["w"], []],
    },
}))
```

## 5. Consistency

LingBot World 2.0 uses raw-frame websocket GT plus per-chunk latency guards for consistency checks.

## 6. Notes

- Use the realtime endpoint for interactive sessions: `/v1/realtime_video/generate`.
- Prefer WebP preview transport for interactive testing; use raw-frame transport for consistency checks.
- Long-running sessions should be validated with raw-frame consistency before changing causal cache, condition sampling, or VAE decode behavior.

## 7. Run in ComfyUI

import { ComfyUISupport } from '/src/snippets/diffusion/comfyui-support.jsx';

<ComfyUISupport model="video" />