refactor: align multimodal example port allocation with vLLM components (#4163)

Co-authored-by: Claude <noreply@anthropic.com>

examples/multimodal/components/worker.py

@@ -418,7 +418,7 @@ async def worker(runtime: DistributedRuntime):
     args, config = VllmBaseWorker.parse_args()
 
     # vLLM config overwrites
-    await configure_ports(runtime, config)
+    configure_ports(config)
     overwrite_args(config)
     await init(runtime, args, config)
 

examples/multimodal/launch/disagg.sh

@@ -60,9 +60,9 @@ python -m dynamo.frontend --http-port=8000 &
 python3 components/processor.py --model $MODEL_NAME --prompt-template "$PROMPT_TEMPLATE" &
 
 # run E/P/D workers
-CUDA_VISIBLE_DEVICES=0 python3 components/encode_worker.py --model $MODEL_NAME &
-CUDA_VISIBLE_DEVICES=1 python3 components/worker.py --model $MODEL_NAME --worker-type prefill --enable-disagg &
-CUDA_VISIBLE_DEVICES=2 python3 components/worker.py --model $MODEL_NAME --worker-type decode --enable-disagg &
+VLLM_NIXL_SIDE_CHANNEL_PORT=20097 CUDA_VISIBLE_DEVICES=0 python3 components/encode_worker.py --model $MODEL_NAME &
+VLLM_NIXL_SIDE_CHANNEL_PORT=20098 CUDA_VISIBLE_DEVICES=1 python3 components/worker.py --model $MODEL_NAME --worker-type prefill --enable-disagg &
+VLLM_NIXL_SIDE_CHANNEL_PORT=20099 CUDA_VISIBLE_DEVICES=2 python3 components/worker.py --model $MODEL_NAME --worker-type decode --enable-disagg &
 
 # Wait for all background processes to complete
 wait

examples/multimodal/launch/disagg_llama.sh

@@ -41,10 +41,10 @@ if [[ $HEAD_NODE -eq 1 ]]; then
     # LLama 4 doesn't support image embedding input, so the prefill worker will also
     # handle image encoding.
     # run EP/D workers
-    python3 components/worker.py --model $MODEL_NAME --worker-type encode_prefill --enable-disagg --tensor-parallel-size=8 --max-model-len=208960 &
+    VLLM_NIXL_SIDE_CHANNEL_PORT=20097 python3 components/worker.py --model $MODEL_NAME --worker-type encode_prefill --enable-disagg --tensor-parallel-size=8 --max-model-len=208960 &
 else
     # run decode worker on non-head node
-    python3 components/worker.py --model $MODEL_NAME --worker-type decode --enable-disagg --tensor-parallel-size=8 --max-model-len=208960 &
+    VLLM_NIXL_SIDE_CHANNEL_PORT=20098 python3 components/worker.py --model $MODEL_NAME --worker-type decode --enable-disagg --tensor-parallel-size=8 --max-model-len=208960 &
 fi
 
 # Wait for all background processes to complete

examples/multimodal/launch/video_agg.sh

@@ -16,8 +16,8 @@ python -m dynamo.frontend --http-port=8000 &
 python3 components/processor.py --model $MODEL_NAME --prompt-template "$PROMPT_TEMPLATE" &
 
 # run E/P/D workers
-CUDA_VISIBLE_DEVICES=0 python3 components/video_encode_worker.py --model $MODEL_NAME --num-frames-to-sample $NUM_FRAMES_TO_SAMPLE &
-CUDA_VISIBLE_DEVICES=1 python3 components/worker.py --model $MODEL_NAME --worker-type prefill &
+VLLM_NIXL_SIDE_CHANNEL_PORT=20097 CUDA_VISIBLE_DEVICES=0 python3 components/video_encode_worker.py --model $MODEL_NAME --num-frames-to-sample $NUM_FRAMES_TO_SAMPLE &
+VLLM_NIXL_SIDE_CHANNEL_PORT=20098 CUDA_VISIBLE_DEVICES=1 python3 components/worker.py --model $MODEL_NAME --worker-type prefill &
 
 # Wait for all background processes to complete
 wait

examples/multimodal/launch/video_disagg.sh

@@ -17,9 +17,9 @@ python -m dynamo.frontend --http-port=8000 &
 python3 components/processor.py --model $MODEL_NAME --prompt-template "$PROMPT_TEMPLATE" &
 
 # run E/P/D workers
-CUDA_VISIBLE_DEVICES=0 python3 components/video_encode_worker.py --model $MODEL_NAME --num-frames-to-sample $NUM_FRAMES_TO_SAMPLE &
-CUDA_VISIBLE_DEVICES=1 python3 components/worker.py --model $MODEL_NAME --worker-type prefill --enable-disagg &
-CUDA_VISIBLE_DEVICES=2 python3 components/worker.py --model $MODEL_NAME --worker-type decode --enable-disagg &
+VLLM_NIXL_SIDE_CHANNEL_PORT=20097 CUDA_VISIBLE_DEVICES=0 python3 components/video_encode_worker.py --model $MODEL_NAME --num-frames-to-sample $NUM_FRAMES_TO_SAMPLE &
+VLLM_NIXL_SIDE_CHANNEL_PORT=20098 CUDA_VISIBLE_DEVICES=1 python3 components/worker.py --model $MODEL_NAME --worker-type prefill --enable-disagg &
+VLLM_NIXL_SIDE_CHANNEL_PORT=20099 CUDA_VISIBLE_DEVICES=2 python3 components/worker.py --model $MODEL_NAME --worker-type decode --enable-disagg &
 
 # Wait for all background processes to complete
 wait

examples/multimodal/utils/args.py

@@ -2,20 +2,16 @@
 # SPDX-License-Identifier: Apache-2.0
 
 import argparse
-import json
 import logging
 import os
 import socket
 import sys
-import time
 from typing import Callable, List, Optional, Tuple
 
 from vllm.config import KVTransferConfig
 from vllm.distributed.kv_events import KVEventsConfig
 from vllm.engine.arg_utils import AsyncEngineArgs
 
-from dynamo.runtime import DistributedRuntime
-
 logger = logging.getLogger(__name__)
 
 DYN_NAMESPACE = os.environ.get("DYN_NAMESPACE", "dynamo")
@@ -30,7 +26,6 @@ class Config:
     component: str
     endpoint: str
     kv_port: Optional[int] = None
-    side_channel_port: Optional[int] = None
 
     # mirror vLLM
     model: str
@@ -115,76 +110,45 @@ def base_parse_args(
     return args, config
 
 
-async def allocate_and_reserve_port(
-    runtime: DistributedRuntime,
-    namespace: str,
-    worker_id: str,
-    reason: str,
-) -> int:
-    """
-    Get an OS-assigned port and atomically reserve it.
-    Retries until successful or internal max attempts reached.
-    """
+def get_kv_port() -> int:
+    """Get KV events port from environment or default."""
+    return int(os.getenv("DYN_VLLM_KV_EVENT_PORT", "20080"))
 
-    context_json = {
-        "worker_id": worker_id,
-        "reason": reason,
-        "reserved_at": time.time(),
-        "pid": os.getpid(),
-        "block_size": 1,
-    }
 
-    # Any ephemeral port, equivalent to binding port 0
-    port_range_min = 32_768
-    port_range_max = 60_999
-    allocated_ports = await runtime.allocate_port_block(
-        namespace,
-        port_range_min,
-        port_range_max,
-        1,  # how many ports to allocate
-        json.dumps(context_json),
+def ensure_side_channel_host():
+    """Ensure the NIXL side-channel host is available without overriding user settings."""
+    existing_host = os.getenv("VLLM_NIXL_SIDE_CHANNEL_HOST")
+    if existing_host:
+        logger.debug(
+            "Preserving existing VLLM_NIXL_SIDE_CHANNEL_HOST=%s", existing_host
         )
-    if not allocated_ports:
-        raise RuntimeError("allocate_port_block returned no ports")
-    port = allocated_ports[0]
-    logger.debug(f"Reserved OS-assigned port {port} for {worker_id}")
-    return port
+        return
 
+    try:
+        host_name = socket.gethostname()
+        host_ip = socket.gethostbyname(host_name)
+        with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as test_socket:
+            test_socket.bind((host_ip, 0))
+        os.environ["VLLM_NIXL_SIDE_CHANNEL_HOST"] = host_ip
+        logger.debug("Set VLLM_NIXL_SIDE_CHANNEL_HOST to %s", host_ip)
+    except (socket.error, socket.gaierror):
+        logger.warning("Failed to get hostname, falling back to 127.0.0.1")
+        os.environ["VLLM_NIXL_SIDE_CHANNEL_HOST"] = "127.0.0.1"
 
-async def configure_ports(runtime: DistributedRuntime, config: Config):
-    """Configure including port allocation and vLLM overrides."""
 
-    # First, allocate ports
-    dp_rank = config.engine_args.data_parallel_rank or 0
-    worker_id = f"vllm-{config.component}-dp{dp_rank}"
-
-    # Allocate KV events port
-    kv_port = await allocate_and_reserve_port(
-        runtime=runtime,
-        namespace=config.namespace,
-        worker_id=f"{worker_id}",
-        reason="zmq_kv_event_port",
-    )
+def configure_ports(config: Config):
+    """Configure port settings from dedicated environment overrides."""
 
-    # Allocate side channel port
-    side_channel_port = await allocate_and_reserve_port(
-        runtime=runtime,
-        namespace=config.namespace,
-        worker_id=f"{worker_id}",
-        reason="nixl_side_channel_port",
-    )
+    # Always set kv_port as it's used by overwrite_args regardless of prefix caching
+    config.kv_port = get_kv_port()
 
-    # Update config with allocated ports
-    config.kv_port = kv_port
-    config.side_channel_port = side_channel_port
+    ensure_side_channel_host()
 
 
 def overwrite_args(config):
     """Set vLLM defaults for Dynamo."""
+    if config.engine_args.enable_prefix_caching:
         assert config.kv_port is not None, "Must set the kv_port, use configure_ports"
-    assert (
-        config.side_channel_port is not None
-    ), "Must set the side_channel_port, use configure_ports"
 
     dp_rank = config.engine_args.data_parallel_rank or 0
 
@@ -206,8 +170,6 @@ def overwrite_args(config):
         ),
     }
 
-    set_side_channel_host_and_port(config)
-
     logger.debug("Setting Dynamo defaults for vLLM")
     for key, value in defaults.items():
         if hasattr(config.engine_args, key):
@@ -215,25 +177,3 @@ def overwrite_args(config):
             logger.debug(f" engine_args.{key} = {value}")
         else:
             raise ValueError(f"{key} not found in AsyncEngineArgs from vLLM.")
-
-
-def set_side_channel_host_and_port(config: Config, hostname: Optional[str] = None):
-    """vLLM V1 NixlConnector creates a side channel to exchange metadata with other NIXL connectors.
-    This sets the port number for the side channel.
-    """
-    if hostname is None:
-        hostname = socket.gethostname()
-        # Test if hostname is usable by attempting to bind to it
-        try:
-            with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as test_socket:
-                test_socket.bind((hostname, 0))
-        except (socket.error, socket.gaierror):
-            # If hostname is not usable, fall back to localhost
-            logger.warning(
-                f"Hostname '{hostname}' is not usable, falling back to '127.0.0.1'"
-            )
-            hostname = "127.0.0.1"
-
-    os.environ["VLLM_NIXL_SIDE_CHANNEL_HOST"] = hostname
-    os.environ["VLLM_NIXL_SIDE_CHANNEL_PORT"] = str(config.side_channel_port)
-    logger.debug(f"Set NIXL side channel to {hostname}:{config.side_channel_port}")