fix: address model spec crash

services/core/models/src/nmp/core/models/tasks/model_spec/run.py

@@ -261,7 +261,7 @@ def analyze_checkpoint(self, config: ModelSpecTaskConfig) -> ModelEntity:
 
         logger.info(os.listdir(dest_dir))
         is_trusted = me.trust_remote_code if me.trust_remote_code is not None else False
-        model_spec = infer_model_cfg_from_hf(dest_dir, is_trusted=is_trusted, file_listing=all_file_paths)
+        model_spec = infer_model_cfg_from_hf(str(dest_dir), is_trusted=is_trusted, file_listing=all_file_paths)
         # Embedding if model name or storage path contains "embed"; use or to avoid
         # overwriting a correct True from model name when storage path lacks "embed"
         model_spec.is_embedding_model = is_embedding_model(me.name)
@@ -302,7 +302,7 @@ def analyze_checkpoint(self, config: ModelSpecTaskConfig) -> ModelEntity:
             me: ModelEntity = self._models.update_model(
                 name=config.name,
                 workspace=config.workspace,
-                body=UpdateModelEntityRequest(spec=PluginModelSpec.model_validate(model_spec)),
+                body=UpdateModelEntityRequest(spec=PluginModelSpec.model_validate(model_spec.model_dump())),
             ).data()
         except NotFoundError as err:
             raise ModelSpecCreationError(
@@ -338,6 +338,8 @@ def run(*, sdk: NeMoPlatform | None = None, job_ctx: NMPJobContext | None = None
         ).with_options(workspace=job_ctx.workspace)
         runner = ModelSpecRunner(sdk=sdk, job_ctx=job_ctx)
 
+        if job_ctx.config_path is None:
+            raise ModelSpecCreationError("Failed to create model spec: job step config path is not configured")
         config = get_config(job_ctx.config_path)
 
         logger.info(f"Starting model spec task with job context: {job_ctx}")

services/core/models/src/nmp/core/models/tasks/model_spec/schemas.py

@@ -44,8 +44,8 @@ class NMPJobContext:
     files_url: str | None
     models_url: str | None
 
-    storage_path: str | None
-    config_path: str | None
+    storage_path: Path
+    config_path: Path | None
 
     @classmethod
     def from_env(cls) -> Self:

services/core/models/tests/unit/tasks/model_spec/test_run.py

@@ -0,0 +1,227 @@
+# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+
+import sys
+import types
+from dataclasses import dataclass
+from datetime import datetime
+from pathlib import Path
+from types import SimpleNamespace
+from typing import Any, cast
+from unittest.mock import MagicMock, patch
+
+from nemo_platform import NeMoPlatform
+from nemo_platform_plugin.files.client import FilesClient
+from nemo_platform_plugin.files.metadata import FilesetMetadata
+from nemo_platform_plugin.files.storage_config import LocalStorageConfig
+from nemo_platform_plugin.files.types import FilesetOutput, FilesetPurpose
+from nemo_platform_plugin.models.client import ModelsClient
+from nemo_platform_plugin.models.types import (
+    ModelEntity,
+    UpdateModelEntityRequest,
+)
+from nemo_platform_plugin.models.types import (
+    ModelSpec as PluginModelSpec,
+)
+from nmp.core.models.schemas import (
+    LinearLayerSpec,
+    MambaConfig,
+    ModelSpec,
+    MoEConfig,
+    SlidingWindowConfig,
+    ToolCallConfig,
+)
+from nmp.core.models.tasks.model_spec.run import ModelSpecRunner
+from nmp.core.models.tasks.model_spec.schemas import ModelSpecTaskConfig, NMPJobContext
+
+
+@dataclass(frozen=True)
+class _Response:
+    body: Any
+
+    def data(self) -> Any:
+        return self.body
+
+
+def _core_model_spec() -> ModelSpec:
+    return ModelSpec(
+        context_size=32_768,
+        num_virtual_tokens=16,
+        is_chat=True,
+        checkpoint_model_name="Qwen/Qwen3-0.6B",
+        family="qwen3",
+        num_layers=28,
+        hidden_size=1024,
+        num_attention_heads=16,
+        num_kv_heads=8,
+        ffn_hidden_size=3072,
+        vocab_size=151_936,
+        tied_embeddings=True,
+        gated_mlp=True,
+        base_num_parameters=600_000_000,
+        precision="bfloat16",
+        moe_config=MoEConfig(
+            num_experts=8,
+            num_experts_per_tok=2,
+            num_expert_layers=12,
+            expert_ffn_size=1536,
+            num_shared_experts=1,
+        ),
+        mamba_config=MambaConfig(
+            is_hybrid=True,
+            num_mamba_layers=4,
+            num_attention_layers=24,
+            num_mlp_layers=28,
+            state_size=128,
+            conv_kernel=4,
+        ),
+        sliding_window_config=SlidingWindowConfig(window_size=4096),
+        linear_layers=[
+            LinearLayerSpec(name="model.layers.0.self_attn.q_proj", in_features=1024, out_features=1024),
+            LinearLayerSpec(name="model.layers.0.mlp.gate_proj", in_features=1024, out_features=3072),
+        ],
+        chat_template="{% for message in messages %}{{ message['content'] }}{% endfor %}",
+        tool_call_config=ToolCallConfig(
+            tool_call_parser="llama3_json",
+            tool_call_plugin="default/qwen-tools",
+            auto_tool_choice=True,
+        ),
+    )
+
+
+def _model_entity(name: str) -> ModelEntity:
+    now = datetime(2026, 1, 1)
+    return ModelEntity(
+        id="model-123",
+        name=name,
+        workspace="default",
+        created_at=now,
+        updated_at=now,
+        fileset="fileset://default/qwen3-fileset",
+        trust_remote_code=False,
+    )
+
+
+def _fileset(tmp_path: Path) -> FilesetOutput:
+    return FilesetOutput(
+        id="fileset-123",
+        name="qwen3-fileset",
+        workspace="default",
+        description="Qwen3 checkpoint",
+        purpose=FilesetPurpose.MODEL,
+        storage=LocalStorageConfig(path=str(tmp_path / "checkpoint")),
+        metadata=FilesetMetadata(),
+        custom_fields={},
+        project="default",
+        created_at="2026-01-01T00:00:00Z",
+        updated_at="2026-01-01T00:00:00Z",
+    )
+
+
+def test_analyze_checkpoint_updates_model_with_plugin_model_spec(tmp_path: Path) -> None:
+    files_sdk = MagicMock()
+    files_sdk.list.return_value = SimpleNamespace(
+        data=[
+            SimpleNamespace(path="config.json"),
+            SimpleNamespace(path="model.safetensors"),
+        ]
+    )
+    files_sdk.download.side_effect = lambda **kwargs: kwargs["local_path"].mkdir(parents=True, exist_ok=True)
+    sdk = cast(NeMoPlatform, SimpleNamespace(files=files_sdk))
+
+    model_name = "qwen3-0-6b-automodel"
+    model_entity = _model_entity(model_name)
+    fileset = _fileset(tmp_path)
+
+    models_client = MagicMock()
+    models_client.get_model.return_value = _Response(model_entity)
+
+    def update_model(**kwargs: Any) -> _Response:
+        body = cast(UpdateModelEntityRequest, kwargs["body"])
+        return _Response(model_entity.model_copy(update={"spec": body.spec}))
+
+    models_client.update_model.side_effect = update_model
+
+    files_client = MagicMock()
+    files_client.get_fileset.return_value = _Response(fileset)
+
+    def client_factory(_sdk: NeMoPlatform, client_cls: type[Any]) -> Any:
+        if client_cls is ModelsClient:
+            return models_client
+        if client_cls is FilesClient:
+            return files_client
+        raise AssertionError(f"Unexpected client class: {client_cls}")
+
+    inferred_spec = _core_model_spec()
+    parallelism_api = types.ModuleType("nmp.core.models.parallelism.api")
+    infer_model_cfg_from_hf = MagicMock(return_value=inferred_spec)
+    find_minimum_gpus_from_metadata = MagicMock(side_effect=[(4, {}), (2, {})])
+    setattr(parallelism_api, "infer_model_cfg_from_hf", infer_model_cfg_from_hf)
+    setattr(parallelism_api, "find_minimum_gpus_from_metadata", find_minimum_gpus_from_metadata)
+    parallelism_pkg = types.ModuleType("nmp.core.models.parallelism")
+    parallelism_pkg.__path__ = []
+
+    job_ctx = NMPJobContext(
+        workspace="default",
+        job_id="job-123",
+        attempt_id="attempt-0",
+        step="model-spec",
+        task="model-spec",
+        jobs_url=None,
+        files_url=None,
+        models_url=None,
+        storage_path=tmp_path,
+        config_path=None,
+    )
+
+    with (
+        patch.dict(
+            sys.modules,
+            {
+                "nmp.core.models.parallelism": parallelism_pkg,
+                "nmp.core.models.parallelism.api": parallelism_api,
+            },
+        ),
+        patch("nmp.core.models.tasks.model_spec.run.client_from_platform", side_effect=client_factory),
+    ):
+        runner = ModelSpecRunner(sdk=sdk, job_ctx=job_ctx)
+        result = runner.analyze_checkpoint(ModelSpecTaskConfig(workspace="default", name=model_name))
+
+    models_client.update_model.assert_called_once()
+    update_kwargs = models_client.update_model.call_args.kwargs
+    assert update_kwargs["name"] == model_name
+    assert update_kwargs["workspace"] == "default"
+
+    body = update_kwargs["body"]
+    assert isinstance(body, UpdateModelEntityRequest)
+    assert isinstance(body.spec, PluginModelSpec)
+    assert body.spec.model_dump() == inferred_spec.model_dump()
+    assert result.spec == body.spec
+
+    assert body.spec.minimum_gpus_all_weights == 4
+    assert body.spec.minimum_gpus_lora == 2
+    assert body.spec.moe_config is not None
+    assert body.spec.moe_config.num_experts == 8
+    assert body.spec.mamba_config is not None
+    assert body.spec.mamba_config.num_mamba_layers == 4
+    assert body.spec.sliding_window_config is not None
+    assert body.spec.sliding_window_config.window_size == 4096
+    assert body.spec.linear_layers is not None
+    assert body.spec.linear_layers[0].name == "model.layers.0.self_attn.q_proj"
+    assert body.spec.tool_call_config is not None
+    assert body.spec.tool_call_config.tool_call_parser == "llama3_json"
+
+    infer_model_cfg_from_hf.assert_called_once()
+    assert infer_model_cfg_from_hf.call_args.args == (str(tmp_path / "model"),)
+    assert type(infer_model_cfg_from_hf.call_args.args[0]) is str
+    assert infer_model_cfg_from_hf.call_args.kwargs == {
+        "is_trusted": False,
+        "file_listing": ["config.json", "model.safetensors"],
+    }
+
+    files_sdk.download.assert_called_once_with(
+        remote_path=["config.json"],
+        local_path=tmp_path / "model",
+        fileset="qwen3-fileset",
+        workspace="default",
+    )