feat(domain): add ModelSize value object

src/modeldock/cli/commands/info.py

@@ -25,9 +25,9 @@ def _echo_spec(spec: Any) -> None:
     if spec.variants:
         typer.echo("Variants:")
         for v in spec.variants:
-            size = f"{v.size_bytes} bytes" if v.size_bytes else "?"
+            size = str(v.size) if v.size else "?"
             ram = v.min_ram or "?"
-            typer.echo(f"  - {v.tag} ({v.params or '?'}), {size}, min RAM {ram}")
+            typer.echo(f"  - {v.tag} ({size}), min RAM {ram}")
 
 
 def info_cmd(

src/modeldock/domain/model.py

@@ -9,7 +9,7 @@
 from enum import Enum
 from typing import TYPE_CHECKING, List, Optional
 
-from pydantic import BaseModel, Field
+from pydantic import BaseModel, ConfigDict, Field
 
 if TYPE_CHECKING:
     from modeldock.ports.registry import RegistryPort
@@ -75,14 +75,46 @@ def from_value(cls, value: str) -> RuntimeBackend:
         raise ValueError(f"Unknown runtime backend: {value!r}")
 
 
+class ModelSize(BaseModel):
+    """Value object representing a model's size: parameter count and disk footprint.
+
+    Pure data — no I/O. Consolidates the loose ``params``/``size_bytes`` fields
+    previously carried directly on ``ModelVariant``. See issue #98.
+    """
+
+    model_config = ConfigDict(frozen=True)
+
+    params: int  # raw parameter count, e.g. 8_000_000_000
+    size_bytes: int  # size on disk in bytes, e.g. 4_700_000_000
+
+    def format_params(self) -> str:
+        """Return a compact parameter count, e.g. '8B' or '1.5B'."""
+        if self.params >= 1_000_000_000:
+            value = self.params / 1_000_000_000
+            suffix = "B"
+        else:
+            value = self.params / 1_000_000
+            suffix = "M"
+        text = f"{value:.1f}".rstrip("0").rstrip(".")
+        return f"{text}{suffix}"
+
+    def format_size(self) -> str:
+        """Return a human-readable disk size, e.g. '4.7GB'."""
+        gb = self.size_bytes / (1000**3)
+        text = f"{gb:.1f}".rstrip("0").rstrip(".")
+        return f"{text}GB"
+
+    def __str__(self) -> str:
+        return f"{self.format_params()} ({self.format_size()})"
+
+
 class ModelVariant(BaseModel):
     """A specific tag/variant of a model (e.g. llama3:8b)."""
 
     tag: str
     download_url: Optional[str] = None
     sha256: Optional[str] = None
-    params: Optional[str] = None
-    size_bytes: Optional[int] = None
+    size: Optional[ModelSize] = None
     min_ram: Optional[str] = None
 
 

tests/unit/test_cli_json_output.py

@@ -30,6 +30,7 @@
     Device,
     ModelInfo,
     ModelRef,
+    ModelSize,
     ModelSpec,
     ModelVariant,
     RuntimeBackend,
@@ -45,7 +46,9 @@
     category=Category.CHAT,
     capabilities=[Capability.CHAT, Capability.TOOL_USE],
     default_tag="8b",
-    variants=[ModelVariant(tag="8b", params="8B", size_bytes=4_700_000_000)],
+    variants=[
+        ModelVariant(tag="8b", size=ModelSize(params=8_000_000_000, size_bytes=4_700_000_000)),
+    ],
     description="Meta Llama 3",
     source=OLLAMA_OFFICIAL,
 )

tests/unit/test_model_size.py

@@ -0,0 +1,38 @@
+"""Tests for the ModelSize value object. See issue #98."""
+
+import pytest
+
+from modeldock.domain.model import ModelSize
+
+
+def test_format_params_billions():
+    size = ModelSize(params=8_000_000_000, size_bytes=4_700_000_000)
+    assert size.format_params() == "8B"
+
+
+def test_format_params_with_decimal():
+    size = ModelSize(params=1_500_000_000, size_bytes=1_000_000_000)
+    assert size.format_params() == "1.5B"
+
+
+def test_format_params_millions():
+    size = ModelSize(params=350_000_000, size_bytes=200_000_000)
+    assert size.format_params() == "350M"
+
+
+def test_format_size_gb():
+    size = ModelSize(params=8_000_000_000, size_bytes=4_700_000_000)
+    assert size.format_size() == "4.7GB"
+
+
+def test_str_combines_both():
+    size = ModelSize(params=8_000_000_000, size_bytes=4_700_000_000)
+    assert str(size) == "8B (4.7GB)"
+
+
+def test_immutable():
+    from pydantic import ValidationError
+
+    size = ModelSize(params=8_000_000_000, size_bytes=4_700_000_000)
+    with pytest.raises(ValidationError):
+        size.params = 1  # type: ignore[misc]