fix: tiny fix cli (#12744)

python/sglang/cli/generate.py

@@ -1,6 +1,6 @@
 import argparse
 
-from sglang.cli.main import get_is_diffusion_model, get_model_path
+from sglang.cli.utils import get_is_diffusion_model, get_model_path
 from sglang.multimodal_gen.runtime.entrypoints.cli.generate import (
     add_multimodal_gen_generate_args,
     generate_cmd,
@@ -8,6 +8,13 @@ from sglang.multimodal_gen.runtime.entrypoints.cli.generate import (
 
 
 def generate(args, extra_argv):
+    # If help is requested, show generate subcommand help without requiring --model-path
+    if any(h in extra_argv for h in ("-h", "--help")):
+        parser = argparse.ArgumentParser(description="SGLang Multimodal Generation")
+        add_multimodal_gen_generate_args(parser)
+        parser.parse_args(extra_argv)
+        return
+
     model_path = get_model_path(extra_argv)
     is_diffusion_model = get_is_diffusion_model(model_path)
     if is_diffusion_model:

python/sglang/cli/main.py

@@ -1,160 +1,8 @@
 import argparse
-import hashlib
-import json
-import logging
-import os
-import tempfile
-from typing import Optional
-
-import filelock
-from huggingface_hub import hf_hub_download
 
 from sglang.cli.generate import generate
 from sglang.cli.serve import serve
 
-logger = logging.getLogger(__name__)
-
-temp_dir = tempfile.gettempdir()
-
-
-def _get_lock(model_name_or_path: str, cache_dir: Optional[str] = None):
-    lock_dir = cache_dir or temp_dir
-    os.makedirs(os.path.dirname(lock_dir), exist_ok=True)
-    model_name = model_name_or_path.replace("/", "-")
-    hash_name = hashlib.sha256(model_name.encode()).hexdigest()
-    lock_file_name = hash_name + model_name + ".lock"
-    lock = filelock.FileLock(os.path.join(lock_dir, lock_file_name), mode=0o666)
-    return lock
-
-
-# Copied and adapted from hf_diffusers_utils.py
-def _maybe_download_model(
-    model_name_or_path: str, local_dir: str | None = None, download: bool = True
-) -> str:
-    """
-    Resolve a model path. If it's a local directory, return it.
-    If it's a Hugging Face Hub ID, download only the config file
-    (`model_index.json` or `config.json`) and return its directory.
-
-    Args:
-        model_name_or_path: Local path or Hugging Face Hub model ID
-        local_dir: Local directory to save the downloaded file (if any)
-        download: Whether to download from Hugging Face Hub when needed
-
-    Returns:
-        Local directory path that contains the downloaded config file, or the original local directory.
-    """
-
-    if os.path.exists(model_name_or_path):
-        logger.info("Model already exists locally")
-        return model_name_or_path
-
-    if not download:
-        return model_name_or_path
-
-    with _get_lock(model_name_or_path):
-        # Try `model_index.json` first (diffusers models)
-        try:
-            logger.info(
-                "Downloading model_index.json from HF Hub for %s...",
-                model_name_or_path,
-            )
-            file_path = hf_hub_download(
-                repo_id=model_name_or_path,
-                filename="model_index.json",
-                local_dir=local_dir,
-            )
-            logger.info("Downloaded to %s", file_path)
-            return os.path.dirname(file_path)
-        except Exception as e_index:
-            logger.debug("model_index.json not found or failed: %s", e_index)
-
-        # Fallback to `config.json`
-        try:
-            logger.info(
-                "Downloading config.json from HF Hub for %s...", model_name_or_path
-            )
-            file_path = hf_hub_download(
-                repo_id=model_name_or_path,
-                filename="config.json",
-                local_dir=local_dir,
-            )
-            logger.info("Downloaded to %s", file_path)
-            return os.path.dirname(file_path)
-        except Exception as e_config:
-            raise ValueError(
-                (
-                    "Could not find model locally at %s and failed to download "
-                    "model_index.json/config.json from HF Hub: %s"
-                )
-                % (model_name_or_path, e_config)
-            ) from e_config
-
-
-# Copied and adapted from hf_diffusers_utils.py
-def is_diffusers_model_path(model_path: str) -> True:
-    """
-    Verify if the model directory contains a valid diffusers configuration.
-
-    Args:
-        model_path: Path to the model directory
-
-    Returns:
-        The loaded model configuration as a dictionary if the model is a diffusers model
-        None if the model is not a diffusers model
-    """
-
-    # Prefer model_index.json which indicates a diffusers pipeline
-    config_path = os.path.join(model_path, "model_index.json")
-    if not os.path.exists(config_path):
-        return False
-
-    # Load the config
-    with open(config_path) as f:
-        config = json.load(f)
-
-    # Verify diffusers version exists
-    if "_diffusers_version" not in config:
-        return False
-    return True
-
-
-def get_is_diffusion_model(model_path: str):
-    model_path = _maybe_download_model(model_path)
-    is_diffusion_model = is_diffusers_model_path(model_path)
-    if is_diffusion_model:
-        logger.info("Diffusion model detected")
-    return is_diffusion_model
-
-
-def get_model_path(extra_argv):
-    # Find the model_path argument
-    model_path = None
-    for i, arg in enumerate(extra_argv):
-        if arg == "--model-path":
-            if i + 1 < len(extra_argv):
-                model_path = extra_argv[i + 1]
-                break
-        elif arg.startswith("--model-path="):
-            model_path = arg.split("=", 1)[1]
-            break
-
-    if model_path is None:
-        # Fallback for --help or other cases where model-path is not provided
-        if any(h in extra_argv for h in ["-h", "--help"]):
-            raise Exception(
-                "Usage: sglang serve --model-path <model-name-or-path> [additional-arguments]\n\n"
-                "This command can launch either a standard language model server or a diffusion model server.\n"
-                "The server type is determined by the model path.\n"
-                "For specific arguments, please provide a model_path."
-            )
-        else:
-            raise Exception(
-                "Error: --model-path is required. "
-                "Please provide the path to the model."
-            )
-    return model_path
-
 
 def main():
     parser = argparse.ArgumentParser()

python/sglang/cli/serve.py

@@ -4,16 +4,49 @@ import argparse
 import logging
 import os
 
-from sglang.cli.main import get_is_diffusion_model, get_model_path
+from sglang.cli.utils import get_is_diffusion_model, get_model_path
 from sglang.srt.utils import kill_process_tree
 
 logger = logging.getLogger(__name__)
 
 
 def serve(args, extra_argv):
+    if any(h in extra_argv for h in ("-h", "--help")):
+        # Since the server type is determined by the model, and we don't have a model path,
+        # we can't show the exact help. Instead, we show a general help message and then
+        # the help for both possible server types.
+        print(
+            "Usage: sglang serve --model-path <model-name-or-path> [additional-arguments]\n"
+        )
+        print(
+            "This command can launch either a standard language model server or a diffusion model server."
+        )
+        print("The server type is determined by the model path.\n")
+        print("For specific arguments, please provide a model_path.")
+        print("\n--- Help for Standard Language Model Server ---")
+        from sglang.srt.server_args import prepare_server_args
+
+        try:
+            prepare_server_args(["--help"])
+        except SystemExit:
+            pass  # argparse --help calls sys.exit
+
+        print("\n--- Help for Diffusion Model Server ---")
+        from sglang.multimodal_gen.runtime.entrypoints.cli.serve import (
+            add_multimodal_gen_serve_args,
+        )
+
+        parser = argparse.ArgumentParser(description="SGLang Diffusion Model Serving")
+        add_multimodal_gen_serve_args(parser)
+        parser.print_help()
+        return
+
     model_path = get_model_path(extra_argv)
     try:
         is_diffusion_model = get_is_diffusion_model(model_path)
+        if is_diffusion_model:
+            logger.info("Diffusion model detected")
+
         if is_diffusion_model:
             # Logic for Diffusion Models
             from sglang.multimodal_gen.runtime.entrypoints.cli.serve import (

python/sglang/cli/utils.py

@@ -0,0 +1,152 @@
+import hashlib
+import json
+import logging
+import os
+import tempfile
+from typing import Optional
+
+import filelock
+from huggingface_hub import hf_hub_download
+
+logger = logging.getLogger(__name__)
+
+temp_dir = tempfile.gettempdir()
+
+
+def _get_lock(model_name_or_path: str, cache_dir: Optional[str] = None):
+    lock_dir = cache_dir or temp_dir
+    os.makedirs(os.path.dirname(lock_dir), exist_ok=True)
+    model_name = model_name_or_path.replace("/", "-")
+    hash_name = hashlib.sha256(model_name.encode()).hexdigest()
+    lock_file_name = hash_name + model_name + ".lock"
+    lock = filelock.FileLock(os.path.join(lock_dir, lock_file_name), mode=0o666)
+    return lock
+
+
+# Copied and adapted from hf_diffusers_utils.py
+def _maybe_download_model(
+    model_name_or_path: str, local_dir: str | None = None, download: bool = True
+) -> str:
+    """
+    Resolve a model path. If it's a local directory, return it.
+    If it's a Hugging Face Hub ID, download only the config file
+    (`model_index.json` or `config.json`) and return its directory.
+
+    Args:
+        model_name_or_path: Local path or Hugging Face Hub model ID
+        local_dir: Local directory to save the downloaded file (if any)
+        download: Whether to download from Hugging Face Hub when needed
+
+    Returns:
+        Local directory path that contains the downloaded config file, or the original local directory.
+    """
+
+    if os.path.exists(model_name_or_path):
+        logger.info("Model already exists locally")
+        return model_name_or_path
+
+    if not download:
+        return model_name_or_path
+
+    with _get_lock(model_name_or_path):
+        # Try `model_index.json` first (diffusers models)
+        try:
+            logger.info(
+                "Downloading model_index.json from HF Hub for %s...",
+                model_name_or_path,
+            )
+            file_path = hf_hub_download(
+                repo_id=model_name_or_path,
+                filename="model_index.json",
+                local_dir=local_dir,
+            )
+            logger.info("Downloaded to %s", file_path)
+            return os.path.dirname(file_path)
+        except Exception as e_index:
+            logger.debug("model_index.json not found or failed: %s", e_index)
+
+        # Fallback to `config.json`
+        try:
+            logger.info(
+                "Downloading config.json from HF Hub for %s...", model_name_or_path
+            )
+            file_path = hf_hub_download(
+                repo_id=model_name_or_path,
+                filename="config.json",
+                local_dir=local_dir,
+            )
+            logger.info("Downloaded to %s", file_path)
+            return os.path.dirname(file_path)
+        except Exception as e_config:
+            raise ValueError(
+                (
+                    "Could not find model locally at %s and failed to download "
+                    "model_index.json/config.json from HF Hub: %s"
+                )
+                % (model_name_or_path, e_config)
+            ) from e_config
+
+
+# Copied and adapted from hf_diffusers_utils.py
+def is_diffusers_model_path(model_path: str) -> True:
+    """
+    Verify if the model directory contains a valid diffusers configuration.
+
+    Args:
+        model_path: Path to the model directory
+
+    Returns:
+        The loaded model configuration as a dictionary if the model is a diffusers model
+        None if the model is not a diffusers model
+    """
+
+    # Prefer model_index.json which indicates a diffusers pipeline
+    config_path = os.path.join(model_path, "model_index.json")
+    if not os.path.exists(config_path):
+        return False
+
+    # Load the config
+    with open(config_path) as f:
+        config = json.load(f)
+
+    # Verify diffusers version exists
+    if "_diffusers_version" not in config:
+        return False
+    return True
+
+
+def get_is_diffusion_model(model_path: str):
+    model_path = _maybe_download_model(model_path)
+    is_diffusion_model = is_diffusers_model_path(model_path)
+    if is_diffusion_model:
+        logger.info("Diffusion model detected")
+    return is_diffusion_model
+
+
+def get_model_path(extra_argv):
+    # Find the model_path argument
+    model_path = None
+    for i, arg in enumerate(extra_argv):
+        if arg == "--model-path":
+            if i + 1 < len(extra_argv):
+                model_path = extra_argv[i + 1]
+                break
+        elif arg.startswith("--model-path="):
+            model_path = arg.split("=", 1)[1]
+            break
+
+    if model_path is None:
+        # Fallback for --help or other cases where model-path is not provided
+        if any(h in extra_argv for h in ["-h", "--help"]):
+            raise Exception(
+                "Usage: sglang serve --model-path <model-name-or-path> [additional-arguments]\n\n"
+                "This command can launch either a standard language model server or a diffusion model server.\n"
+                "The server type is determined by the model path.\n"
+                "For specific arguments, please provide a model_path."
+            )
+        else:
+            raise Exception(
+                "Error: --model-path is required. "
+                "Please provide the path to the model."
+            )
+    return model_path

python/sglang/multimodal_gen/docs/cli.md

@@ -143,7 +143,7 @@ SERVER_ARGS=(
   --ring-degree=2
 )
 
-sglang serve $SERVER_ARGS
+sglang serve"${SERVER_ARGS[@]}"
 ```
 
 - **--model-path**: Which model to load. The example uses `Wan-AI/Wan2.1-T2V-1.3B-Diffusers`.
@@ -265,7 +265,7 @@ SAMPLING_ARGS=(
   --output-file-name "A curious raccoon.mp4"
 )
 
-sglang generate $SERVER_ARGS $SAMPLING_ARGS
+sglang generate "${SERVER_ARGS[@]}" "${SAMPLING_ARGS[@]}"
 ```
 
 Once the generation task has finished, the server will shut down automatically.

python/sglang/multimodal_gen/runtime/entrypoints/diffusion_generator.py

@@ -258,10 +258,10 @@ class DiffGenerator:
         data_type = (
             DataType.IMAGE
             if self.server_args.pipeline_config.is_image_gen
-            or sampling_params.num_frames == 1
+            or pretrained_sampling_params.num_frames == 1
             else DataType.VIDEO
         )
-        sampling_params.data_type = data_type
+        pretrained_sampling_params.data_type = data_type
         pretrained_sampling_params.set_output_file_name()
 
         requests: list[Req] = []

python/sglang/multimodal_gen/runtime/platforms/cuda.py

@@ -217,6 +217,7 @@ class CudaPlatformBase(Platform):
         elif selected_backend == AttentionBackendEnum.FA3:
             if is_blackwell():
                 raise ValueError("The 'fa3' backend is not supported on Blackwell GPUs")
+            target_backend = AttentionBackendEnum.FA3
         elif selected_backend:
             raise ValueError(f"Invalid attention backend for {cls.device_name}")
         else:

python/sglang/multimodal_gen/runtime/server_args.py

@@ -777,6 +777,13 @@ class ServerArgs:
                 )
             self.sp_degree = self.ulysses_degree = self.ring_degree = 1
 
+        if (
+            self.ring_degree is not None
+            and self.ring_degree > 1
+            and self.attention_backend != "fa3"
+        ):
+            raise ValueError("Ring Attention is only supported for fa3 backend for now")
+
         if self.sp_degree == -1:
             # assume we leave all remaining gpus to sp
             num_gpus_per_group = self.dp_size * self.tp_size