Add explicit PyTorch dependency with platform-specific constraints

- Add torch as explicit dependency with environment markers
- Constrain macOS Intel to PyTorch <2.7.0 due to wheel availability issues
- Allow broader ranges for other platforms with better wheel support
- Fixes 'Unable to find installation candidates for torch (2.8.0)' on macOS Intel
- Ensures PyTorch compatibility across Windows, macOS (Intel/ARM), and Linux

Author: orlandocloss

pyproject.toml

@@ -23,6 +23,17 @@ pillow = [
     # Linux - most flexible
     {version = ">=10.0.0,<12.0.0", markers = "sys_platform == 'linux'"}
 ]
+# PyTorch with platform-specific compatibility to avoid wheel availability issues
+torch = [
+    # Windows - stable version range
+    {version = ">=2.0.0,<2.8.0", markers = "sys_platform == 'win32'"},
+    # macOS Intel - more conservative range due to wheel availability
+    {version = ">=2.0.0,<2.7.0", markers = "sys_platform == 'darwin' and platform_machine == 'x86_64'"},
+    # macOS ARM64 - broader range, better wheel support
+    {version = ">=2.0.0,<2.8.0", markers = "sys_platform == 'darwin' and platform_machine == 'arm64'"},
+    # Linux - most flexible, best wheel support
+    {version = ">=2.0.0,<2.8.0", markers = "sys_platform == 'linux'"}
+]
 # Comprehensive environment markers for numpy compatibility across all platforms and architectures
 # Note: pandas 2.1.4 requires numpy >=1.26.0, so we must respect that constraint
 numpy = [