Апстрим master-987-a77d362

README.md

@@ -48,6 +48,7 @@ API and command-line option may change frequently.***
     - [FLUX.2-dev/FLUX.2-klein](./docs/flux2.md)
     - [FLUX.3 Image Klein / Klein Base](./docs/flux3.md)
     - [MOSS-Image-Base / MOSS-Image-SFT](./docs/moss_image.md)
+    - [Fibo 2.0 Dev](./docs/fibo2.md)
     - [Lens](./docs/lens.md)
     - [Chroma](./docs/chroma.md)
     - [Chroma1-Radiance](./docs/chroma_radiance.md)
@@ -79,6 +80,7 @@ API and command-line option may change frequently.***
     - [Boogu Image Edit](./docs/boogu_image.md)
     - [Mage-Flow-Edit](./docs/mage_flow.md#image-editing)
     - [LLaDA-Image Edit](./docs/llada_image.md#image-editing)
+    - [Fibo 2.0 Dev / Edit Turbo](./docs/fibo2.md#editing-and-turbo)
   - Video Models
     - [Wan2.1/Wan2.2](./docs/wan.md)
     - [MiniMax-H3](./docs/minimax_h3.md)

docs/adetailer.md

@@ -1,9 +1,10 @@
 # ADetailer
 
 `sd-cli` can run a YOLOv8 object detector on an existing or newly generated
-image and perform a cropped inpaint pass for every detected object. The first
-implementation supports YOLOv8 detection checkpoints. YOLOv8 segmentation and
-MediaPipe models are not supported yet.
+image, and `sd-server` can run it after image generation. Both perform a cropped
+inpaint pass for every detected object. The implementation supports YOLOv8
+detection checkpoints. YOLOv8 segmentation and MediaPipe models are not
+supported yet.
 
 ## Convert a detector
 
@@ -68,6 +69,36 @@ ADetailer can also run automatically after normal image generation:
   --extra-ad-args "confidence=0.3,denoising_strength=0.4,inpaint_width=512,inpaint_height=512"
 ```
 
+The same options can be supplied when starting `sd-server`. When `--ad-model` is set, its detector runs after OpenAI-compatible and native asynchronous image generation. SDAPI requests enable ADetailer through `alwayson_scripts`, as described below. If no object is detected, the original image is returned unchanged. RGBA output keeps its original alpha channel, including when detected regions are repaired. Detector initialization or detail-pass failures are reported as request failures.
+
+Server image-generation requests limit base, hires, and detail-pass dimensions to 4096 pixels per side. ADetailer step overrides are limited to 1–100; `steps=0` in `extra_ad_args` keeps inheriting the main generation steps. These limits also apply to inherited dimensions and `extra_ad_args` overrides. Requests exceeding the limits return a parameter error before generation. CLI limits are unchanged.
+
+### SDAPI requests
+
+`/sdapi/v1/txt2img` and `/sdapi/v1/img2img` accept the WebUI ADetailer argument format:
+
+```json
+{
+  "prompt": "portrait photo",
+  "alwayson_scripts": {
+    "ADetailer": {
+      "args": [true, false, {
+        "ad_model": "face_yolov8n.pt",
+        "ad_prompt": "[PROMPT], detailed face",
+        "ad_use_steps": true,
+        "ad_steps": 20
+      }]
+    }
+  }
+}
+```
+
+The detector must be configured at server startup with `--ad-model`. `ad_model` must match that file's basename; the original `.pt` basename is also accepted for a converted detector. Requests cannot load arbitrary detector paths. Omitting the script, setting its first argument to `false`, selecting `"None"`, or setting `ad_tab_enable` to `false` disables detailing. Dictionary-only argument arrays are also accepted. Multiple enabled dictionaries run in order using the configured detector.
+
+Supported settings include prompts, confidence, mask filtering by area or confidence, mask count and area ratios, dilation/erosion, offsets, mask merging/inversion, blur, denoising strength, masked or full-image inpainting, padding, and optional overrides for inpaint dimensions, steps, CFG, sampler/scheduler, and CLIP skip. The corresponding `ad_use_*` flags control whether overrides apply. Otherwise dimensions, steps, CFG, sampler, scheduler, and CLIP skip inherit the main request. Denoising strength defaults to `0.4`. Pixel mask settings are limited to the larger output dimension, with a minimum limit of 32 and a maximum of 16384 pixels.
+
+Model/VAE switching, non-default noise multipliers, face restoration, ControlNet, and skipping the initial img2img pass are not supported; active requests for these features return an error. Unknown settings and invalid active values also return errors. During detailing, `/sdapi/v1/progress` remains active with an `adetailer` job; its percentage and preview stay fixed until detailing finishes.
+
 An empty ADetailer prompt inherits the main prompt. `[PROMPT]` inserts the main
 prompt, `[SEP]` assigns different prompts to consecutive masks, and `[SKIP]`
 skips the corresponding mask.
@@ -82,6 +113,7 @@ All settings other than the detector path and prompts are passed through
 | `nms` | `0.45` | NMS IoU threshold |
 | `max_detections` | `100` | Maximum detections retained after NMS |
 | `mask_k_largest` | `0` | Keep only the largest K masks; zero keeps all |
+| `mask_filter_method` | `area` | Rank retained masks by `area` or `confidence` |
 | `mask_min_ratio` | `0` | Minimum bbox area relative to the image |
 | `mask_max_ratio` | `1` | Maximum bbox area relative to the image |
 | `dilate_erode` | `4` | Positive values dilate; negative values erode |
@@ -90,6 +122,7 @@ All settings other than the detector path and prompts are passed through
 | `merge_masks`, `invert_mask` | `false` | Boolean alternatives to `mask_mode` |
 | `mask_blur` | `4` | Final composite feather radius |
 | `inpaint_padding` | `32` | Padding around the detected region |
+| `inpaint_only_masked` | `true` | Crop to the detected region; `false` uses the full image with the detection mask |
 | `inpaint_width`, `inpaint_height` | mode-specific | `512x512` after generation; input/output size in `adetailer` mode |
 | `denoising_strength` | mode-specific | `0.4` after generation; inherits `--strength` in `adetailer` mode |
 | `steps` | `0` | Detail steps; zero inherits the main generation |

docs/edit.md

@@ -19,6 +19,7 @@ Depending on the architecture, different models handle reference images differen
 | **Krea2 (Community Edit LoRAs)** | `krea2_ostris_edit` |
 | [**Mage-Flow-Edit**](./mage_flow.md#image-editing) | `mage_flow` |
 | [**LLaDA-Image**](./llada_image.md#image-editing) | `llada_image` |
+| [**Fibo 2.0 Dev / Edit Turbo**](./fibo2.md#examples) | `fibo2` |
 | **Anima (Community Edit LoRAs)** | `cosmos_reference` |
 
 Stable-diffusion.spp also supports basic Unet-based editing models like instruct-pix2pix or CosXL-Edit. This document is not about those.
@@ -50,6 +51,7 @@ The `--ref-image-args` argument accepts a comma-separated list of key-value pair
 | `flux_kontext` | FLUX.1 Kontext |
 | `longcat` | LongCat Image Edit |
 | `flux2` | FLUX.2 models |
+| `fibo2` | Fibo 2.0 Dev / Edit Turbo |
 | `qwen` | Qwen Image Edit |
 | `qwen_layered` | Qwen Image Layered |
 | `z_image_omni` | Boogu, Z-Image Omni |
@@ -73,7 +75,12 @@ If presets are insufficient, you can manually configure the following parameters
 | `ref_index_mode` | string | Behavior of the RoPE index. | `fixed`, `increase`, `decrease` |
 | `force_ref_timestep_zero` | bool | Forces timestep=0 for reference tokens. | `true`, `false` (Krea2 only) |
 | `resize_before_vae` | bool | Whether reference images are resized before VAE encoding. | `true`, `false` |
-| `vae_input_max_pixels` | int | Maximum pixel area for VAE reference inputs. | Integer |
+| `resize_vae_to_target` | bool | Use output dimensions for every reference, overriding area-based sizing. | `true`, `false` |
+| `resize_single_ref_to_target` | bool | Use output dimensions when exactly one reference is supplied. | `true`, `false` |
+| `vae_size_buckets` | bool | Choose aligned dimensions within ±10% of the requested area, minimizing aspect-ratio cropping. Ignored when using output dimensions. | `true`, `false` |
+| `vae_center_crop` | bool | Scale to cover the selected dimensions with Lanczos, then center-crop. Otherwise resize directly. | `true`, `false` |
+| `vae_input_max_pixels` | int | VAE area budget, also capped by output area in ordinary resizing. With size buckets, this is the target area and output area does not cap it. | Integer |
+| `vlm_use_vae_input` | bool | Reuse the resized/cropped VAE input for the VLM, before the VLM's own resize. Has no effect when `resize_before_vae=false`. | `true`, `false` |
 | `vlm_resize_mode` | string | How to resize VLM reference inputs. | `longest_side`, `area`, `none` |
 | `vlm_max_size` | int | Maximum VLM input size; interpreted according to `vlm_resize_mode`. | Integer |
 | `vlm_min_size` | int | Minimum VLM input size; interpreted according to `vlm_resize_mode`. | Integer |
@@ -88,6 +95,7 @@ For a technical overview of how each preset is configured, see the table below.
 | `flux_kontext` | No | `fixed` | `none` | |
 | `longcat` | Yes | `fixed` | `area` | |
 | `flux2` | No | `increase` | `none` | |
+| `fibo2` | Yes | `increase` | `longest` | Shared reference crops; clean reference timesteps; see [Fibo 2.0](./fibo2.md) |
 | `qwen` | Yes | `increase` | `area` | |
 | `qwen_layered` | Yes | `decrease` | `area` | |
 | `mage_flow` | Yes | `increase` | `longest` | `vlm_max_size = 384`, VAE input resized to target |
@@ -99,3 +107,5 @@ For a technical overview of how each preset is configured, see the table below.
 **Additional Default Notes:**
 - **VLM Input Sizes:** For most presets, `vlm_max_size` and `vlm_min_size` are set to `-1`, meaning the values are model-dependent and handled automatically. In `area` mode they represent pixel area; in `longest_side` mode they represent a side length in pixels.
 - **VAE Input Size:** `vae_input_max_pixels` defaults to $1024 \times 1024$ pixels (`1048576`).
+- **VAE Geometry:** `resize_vae_to_target` defaults to `true` for Mage-Flow and LLaDA-Image. Fibo enables `resize_single_ref_to_target`, `vae_size_buckets`, and `vae_center_crop`. These options are otherwise `false`. Bucket dimensions use the model's alignment (normally 16, Qwen Image 32), with a minimum side of four alignment units; if no bucket fits, output dimensions are used.
+- **Shared Encoder Input:** `vlm_use_vae_input` defaults to `true` for Fibo and Qwen Image 2.1, otherwise `false`. All these options can be overridden individually after selecting a preset.

docs/fibo2.md

@@ -0,0 +1,53 @@
+# How to Use
+
+Fibo 2.0 uses a Fibo diffusion transformer, the standard FLUX.2 VAE, and Qwen3-VL 4B as the LLM text encoder. The Qwen tokenizer is built in.
+
+## Download weights
+
+- Download Fibo 2.0 Dev
+    - safetensors: https://huggingface.co/Comfy-Org/Fibo-2.0/tree/main/diffusion_models
+- Download Fibo 2.0 Edit Turbo
+    - safetensors: https://huggingface.co/Comfy-Org/Fibo-2.0/tree/main/diffusion_models
+- Download vae
+    - safetensors: https://huggingface.co/black-forest-labs/FLUX.2-dev/tree/main
+- Download Qwen3-VL 4B
+    - safetensors: https://huggingface.co/Comfy-Org/Fibo-2.0/tree/main/text_encoders
+    - gguf: https://huggingface.co/Qwen/Qwen3-VL-4B-Instruct-GGUF/tree/main
+
+The original Diffusers weights from [briaai/Fibo-2.0-dev](https://huggingface.co/briaai/Fibo-2.0-dev) and [briaai/Fibo-2.0-edit-turbo](https://huggingface.co/briaai/Fibo-2.0-edit-turbo) are also supported. Pass the transformer's `diffusion_pytorch_model.safetensors.index.json` to `--diffusion-model` and keep its shards alongside it.
+
+INT8 convrot weights load directly; see [INT8 convrot](./int8_convrot.md) for backend requirements.
+
+## Examples
+
+### Fibo 2.0 Dev
+
+Dev supports both text-to-image generation and reference-image editing.
+
+```
+.\bin\Release\sd-cli.exe --diffusion-model ..\models\diffusion_models\fibo2_dev_int8_convrot.safetensors --llm ..\models\text_encoders\Qwen3-VL-4B-Instruct-Q4_K_M.gguf --llm_vision ..\models\text_encoders\Qwen3-VL-4B-Instruct-mmproj-BF16.gguf --vae ..\models\vae\flux2_ae.safetensors -p "a lovely cat holding a sign says 'fibo2.cpp'" --cfg-scale 5.0 --sampling-method euler -v  --offload-to-cpu
+```
+
+<img src="../assets/fibo2/t2i.png" />
+
+```
+.\bin\Release\sd-cli.exe --diffusion-model ..\models\diffusion_models\fibo2_dev_int8_convrot.safetensors --llm ..\models\text_encoders\Qwen3-VL-4B-Instruct-Q4_K_M.gguf --llm_vision ..\models\text_encoders\Qwen3-VL-4B-Instruct-mmproj-BF16.gguf --vae ..\models\vae\flux2_ae.safetensors -r ..\assets\flux\flux1-dev-q8_0.png -p "change 'flux.cpp' to 'fibo2.cpp'" --cfg-scale 5.0 --sampling-method euler -v  --offload-to-cpu
+```
+
+<img src="../assets/fibo2/dev_edit.png" />
+
+### Fibo 2.0 Edit Turbo
+
+Edit Turbo is distilled for reference-image editing in 4 steps with CFG 1.
+
+```
+.\bin\Release\sd-cli.exe --diffusion-model ..\models\diffusion_models\fibo2_edit_turbo_int8_convrot.safetensors --llm ..\models\text_encoders\Qwen3-VL-4B-Instruct-Q4_K_M.gguf --llm_vision ..\models\text_encoders\Qwen3-VL-4B-Instruct-mmproj-BF16.gguf --vae ..\models\vae\flux2_ae.safetensors -r ..\assets\flux\flux1-dev-q8_0.png -p "change 'flux.cpp' to 'fibo2.cpp'" --cfg-scale 1 --steps 4 --sampling-method euler -v  --offload-to-cpu
+```
+
+The BF16 files accept the same options. Use dimensions divisible by 16. Repeat `-r` to use multiple reference images; instructions can refer to `<image_1>`, `<image_2>`, etc. See [Image Editing](./edit.md) for reference-image preprocessing options. Separate GGUF text encoders need their vision projector passed with `--llm_vision` for editing.
+
+The automatic `fibo2` reference preset combines `resize_single_ref_to_target=true`, `vae_size_buckets=true`, `vae_center_crop=true`, and `vlm_use_vae_input=true`. A single reference is scaled to cover the output dimensions and center-cropped. Multiple references use dimensions divisible by 16, chosen within ±10% of one megapixel to minimize cropping for each image's aspect ratio; `vae_input_max_pixels` overrides that target area. The VAE and vision encoder receive the same crops, with smaller copies used by the vision encoder. These are generic reference-image options and can be overridden individually: for example, `--ref-image-args vae_center_crop=false` uses direct resizing, while `resize_before_vae=false` skips this automatic crop and resize step entirely.
+
+The vision encoder defaults to `vlm_resize_mode=longest_side,vlm_max_size=768`. Override these with `--ref-image-args`, for example `vlm_max_size=512`, or use `vlm_resize_mode=none` to skip size-based scaling. Vision inputs are still aligned to the encoder's patch grid.
+
+Plain prompts and structured JSON captions are accepted. This integration uses the caption-only text-rendering path (`render_text_images=False`); it does not generate auxiliary glyph images or expand prompts with Bria VGL. Native Fibo mask preprocessing is not connected to `--mask`.

docs/rpc.md

@@ -131,7 +131,7 @@ If you want to allow connections from other machines on the network:
 
 > **Drivers & Hardware:** Ensure the Server machine has the necessary drivers installed and functional (e.g., Nvidia Drivers for CUDA, Vulkan SDK, or Metal). If no devices are found, the server will simply fallback to CPU usage.
 
-<!-- ### Step B: Check if the client is able to connect to the server and see the available devices
+### Step B: Check if the client is able to connect to the server and see the available devices
 
 We're assuming the server is running on your local machine, and listening on the default port `50052`. If it's running on a different machine, you can replace `localhost` with the IP address of the server.
 
@@ -147,15 +147,15 @@ Example output:
 (Client built without GPU acceleration, two GPUs available on the server)
 
 ```
-List of available GGML devices:
-Name    Description
--------------------
 CPU     AMD Ryzen 9 5900X 12-Core Processor
 RPC0    localhost:50052
 RPC1    localhost:50052
-``` -->
+```
+
+The options can be given in either order; no model is required. The client exits
+with an error if RPC support is unavailable or a server cannot provide devices.
 
-### Step B: Run with RPC device
+### Step C: Run with RPC device
 
 If everything is working correctly, you can now run the client while offloading some or all of the work to the RPC server.
 
@@ -217,4 +217,4 @@ The client will map these servers to sequential device IDs (e.g., RPC0 from the
 
 ## 6. Performance Considerations
 
-RPC performance is heavily dependent on network bandwidth, as large weights and activations must be transferred back and forth over the network, especially for large models, or when using high resolutions. For best results, ensure your network connection is stable and has sufficient bandwidth (>1Gbps recommended). This shoumd not be a concern if you are running the server and client on the same machine, as the data transfer will happen over the loopback interface.
+RPC performance is heavily dependent on network bandwidth, as large weights and activations must be transferred back and forth over the network, especially for large models, or when using high resolutions. For best results, ensure your network connection is stable and has sufficient bandwidth (>1Gbps recommended). This shoumd not be a concern if you are running the server and client on the same machine, as the data transfer will happen over the loopback interface.

examples/cli/main.cpp

@@ -301,6 +301,10 @@ void parse_args(int argc, const char** argv, SDCliParams& cli_params, SDContextP
     log_level = cli_params.log_level;
     log_color = cli_params.color;
 
+    if (ctx_params.list_devices) {
+        exit(ctx_params.print_devices() ? 0 : 1);
+    }
+
     bool valid = cli_params.resolve_and_validate();
     if (valid && cli_params.mode != METADATA) {
         valid = ctx_params.resolve_and_validate(cli_params.mode) &&

examples/common/common.cpp

@@ -596,6 +596,11 @@ ArgOptions SDContextParams::get_options() {
     };
 
     options.bool_options = {
+        {"",
+         "--list-devices",
+         "list available ggml backend devices, including --rpc-servers (one 'name<TAB>description' per line), and exit; "
+         "the names are the device names accepted by --backend and --params-backend",
+         true, &list_devices},
         {"",
          "--disable-prefetch",
          "disable asynchronous next-segment weight prefetch (defaults to false)",
@@ -819,23 +824,22 @@ ArgOptions SDContextParams::get_options() {
          "but it usually offers faster inference speed and, in some cases, lower memory usage. "
          "The at_runtime mode, on the other hand, is exactly the opposite.",
          on_lora_apply_mode_arg},
-        {"",
-         "--list-devices",
-         "list available ggml backend devices (one 'name<TAB>description' per line) and exit; "
-         "the names are the device names accepted by --backend and --params-backend",
-         [](int /*argc*/, const char** /*argv*/, int /*index*/) {
-             size_t device_list_size = sd_list_devices(nullptr, 0);
-             std::vector<char> devices(device_list_size + 1);
-             sd_list_devices(devices.data(), devices.size());
-             fputs(devices.data(), stdout);
-             std::exit(0);
-             return 0;
-         }},
     };
 
     return options;
 }
 
+bool SDContextParams::print_devices() const {
+    if (!sd_add_rpc_servers(rpc_servers.c_str())) {
+        return false;
+    }
+    size_t device_list_size = sd_list_devices(nullptr, 0);
+    std::vector<char> devices(device_list_size + 1);
+    sd_list_devices(devices.data(), devices.size());
+    fputs(devices.data(), stdout);
+    return true;
+}
+
 void SDContextParams::build_embedding_map() {
     static const std::vector<std::string> valid_ext = {".gguf", ".safetensors", ".pt", ".ckpt"};
 
@@ -2219,7 +2223,7 @@ bool SDGenerationParams::from_json_str(
         if (target_custom_sigmas != nullptr &&
             sample_json.contains("custom_sigmas") &&
             sample_json["custom_sigmas"].is_array() &&
-            !sample_json["custom_sigmas"].empty()) { // empty [] = "not specified", keep server/CLI default
+            !sample_json["custom_sigmas"].empty()) {  // empty [] = "not specified", keep server/CLI default
             *target_custom_sigmas = sample_json["custom_sigmas"].get<std::vector<float>>();
         }
         if (sample_json.contains("sample_method") && sample_json["sample_method"].is_string()) {