refactor: switch trtllm config modifier to --trtllm.* dynamic CLI flags (#7884)

components/src/dynamo/profiler/utils/config_modifiers/trtllm.py

 # SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
-import json
 import logging
 import re
 from typing import Tuple
@@ -15,7 +14,6 @@ from dynamo.profiler.utils.config import (
     break_arguments,
     get_service_name_by_type,
     get_worker_service_from_config,
-    parse_override_engine_args,
     remove_valued_arguments,
     setup_worker_service_resources,
     update_image,
@@ -46,6 +44,20 @@ DEFAULT_TRTLLM_AGG_CONFIG_PATH = resolve_deploy_path(
 )
 
 
+def _trtllm_flags(overrides: dict) -> list[str]:
+    """Build a flat ``--trtllm.<dotted.key> <value>`` flag list."""
+    flags: list[str] = []
+    for key, value in overrides.items():
+        flags.append(f"--trtllm.{key}")
+        if value is None:
+            flags.append("none")
+        elif isinstance(value, bool):
+            flags.append(str(value).lower())
+        else:
+            flags.append(str(value))
+    return flags
+
+
 class TrtllmConfigModifier(BaseConfigModifier):
     BACKEND = "trtllm"
 
@@ -116,28 +128,16 @@ class TrtllmConfigModifier(BaseConfigModifier):
             args = remove_valued_arguments(args, "--disaggregation-mode")
             args = remove_valued_arguments(args, "--disaggregation-strategy")
 
-            # Keep the original extra-engine-args (prefill.yaml) which may contain user settings
-            # Check if user already has override-engine-args and merge with our changes
-            override_dict, args = parse_override_engine_args(args)
-
-            # Merge our overrides for converting prefill-only disagg to aggregated:
-            # - Disable enable_block_reuse (no KV reuse for prefill-only)
-            # - Enable overlap scheduler (disabled in prefill.yaml but needed for agg)
-            # - Remove cache_transceiver_config (not needed in agg mode)
-            if "kv_cache_config" not in override_dict or not isinstance(
-                override_dict["kv_cache_config"], dict
-            ):
-                override_dict["kv_cache_config"] = {}
-            override_dict["kv_cache_config"]["enable_block_reuse"] = False
-            override_dict[
-                "disable_overlap_scheduler"
-            ] = False  # Enable overlap scheduler for agg
-            override_dict[
-                "cache_transceiver_config"
-            ] = None  # Remove cache transceiver for agg
-
-            override_str = json.dumps(override_dict)
-            args = append_argument(args, ["--override-engine-args", override_str])
+            args = append_argument(
+                args,
+                _trtllm_flags(
+                    {
+                        "kv_cache_config.enable_block_reuse": False,
+                        "disable_overlap_scheduler": False,
+                        "cache_transceiver_config": None,
+                    }
+                ),
+            )
 
             worker_service.extraPodSpec.mainContainer.args = args
 
@@ -170,24 +170,15 @@ class TrtllmConfigModifier(BaseConfigModifier):
             args = remove_valued_arguments(args, "--disaggregation-mode")
             args = remove_valued_arguments(args, "--disaggregation-strategy")
 
-            # Keep the original extra-engine-args (decode.yaml) which may contain user settings
-            # Check if user already has override-engine-args and merge with our changes
-            override_dict, args = parse_override_engine_args(args)
-
-            # Merge our overrides for converting decode-only disagg to aggregated:
-            # - Enable enable_block_reuse (to skip prefill in decode-only)
-            # - Remove cache_transceiver_config (not needed in agg mode)
-            if "kv_cache_config" not in override_dict or not isinstance(
-                override_dict["kv_cache_config"], dict
-            ):
-                override_dict["kv_cache_config"] = {}
-            override_dict["kv_cache_config"]["enable_block_reuse"] = True
-            override_dict[
-                "cache_transceiver_config"
-            ] = None  # Remove cache transceiver for agg
-
-            override_str = json.dumps(override_dict)
-            args = append_argument(args, ["--override-engine-args", override_str])
+            args = append_argument(
+                args,
+                _trtllm_flags(
+                    {
+                        "kv_cache_config.enable_block_reuse": True,
+                        "cache_transceiver_config": None,
+                    }
+                ),
+            )
 
             worker_service.extraPodSpec.mainContainer.args = args
 
@@ -225,14 +216,7 @@ class TrtllmConfigModifier(BaseConfigModifier):
         # Break arguments to handle both joined strings and lists
         args = break_arguments(args)
 
-        # For TRT-LLM, we need to update the override-engine-args
-        # to set the tensor_parallel_size
-        override_dict, args = parse_override_engine_args(args)
-
-        # Add/update tensor_parallel_size in the override
-        override_dict["tensor_parallel_size"] = tp_size
-        override_str = json.dumps(override_dict)
-        args = append_argument(args, ["--override-engine-args", override_str])
+        args = append_argument(args, _trtllm_flags({"tensor_parallel_size": tp_size}))
 
         worker_service.extraPodSpec.mainContainer.args = args
 
@@ -328,7 +312,7 @@ class TrtllmConfigModifier(BaseConfigModifier):
     ) -> dict:
         """
         Configure prefill-related limits for aggregated prefill runs.
-        For TRT-LLM we set these via --override-engine-args JSON:
+        For TRT-LLM we set these via ``--trtllm.*`` dynamic CLI flags:
         - max_batch_size
         - max_num_tokens
         """
@@ -339,12 +323,15 @@ class TrtllmConfigModifier(BaseConfigModifier):
         args = validate_and_get_worker_args(worker_service, backend="trtllm")
         args = break_arguments(args)
 
-        # Parse existing override-engine-args (if any) and update
-        override_dict, args = parse_override_engine_args(args)
-        override_dict["max_batch_size"] = int(max_batch_size)
-        override_dict["max_num_tokens"] = int(max_num_tokens)
-        override_str = json.dumps(override_dict)
-        args = append_argument(args, ["--override-engine-args", override_str])
+        args = append_argument(
+            args,
+            _trtllm_flags(
+                {
+                    "max_batch_size": int(max_batch_size),
+                    "max_num_tokens": int(max_num_tokens),
+                }
+            ),
+        )
 
         worker_service.extraPodSpec.mainContainer.args = args
         return cfg.model_dump()

components/src/dynamo/trtllm/dynamic_flags.py

@@ -13,8 +13,11 @@ DYNAMIC_FLAG_PREFIX = "--trtllm."
 def infer_type(value: str) -> Any:
     """Infer the Python type of a CLI value string.
 
-    Tries int, float, bool, then falls back to string.
+    Tries None, int, float, bool, then falls back to string.
     """
+    # none / null
+    if value.lower() in ("none", "null"):
+        return None
     # int
     try:
         return int(value)