feat(modelfile): support TF SavedModel, ONNX external_data, and online-learning trees

go.mod

@@ -34,6 +34,7 @@ require (
 	golang.org/x/sync v0.19.0
 	golang.org/x/sys v0.41.0
 	google.golang.org/grpc v1.80.0
+	google.golang.org/protobuf v1.36.11
 	oras.land/oras-go/v2 v2.6.0
 )
 
@@ -164,7 +165,6 @@ require (
 	google.golang.org/api v0.214.0 // indirect
 	google.golang.org/genproto/googleapis/api v0.0.0-20260226221140-a57be14db171 // indirect
 	google.golang.org/genproto/googleapis/rpc v0.0.0-20260226221140-a57be14db171 // indirect
-	google.golang.org/protobuf v1.36.11 // indirect
 	gopkg.in/ini.v1 v1.67.0 // indirect
 	gopkg.in/warnings.v0 v0.1.2 // indirect
 	gopkg.in/yaml.v3 v3.0.1 // indirect

pkg/modelfile/constants.go

@@ -140,6 +140,10 @@ var (
 		"*.ftz",     // FastText compressed model
 		"*.ark",     // Kaldi ark format (speech/audio models)
 		"*.db",      // Database files (LMDB, etc.)
+
+		// TensorFlow SavedModel literal-name files (no extension).
+		"feature_map", // TF SavedModel feature map definition
+		"checkpoint",  // TF checkpoint pointer file (literal name)
 	}
 
 	// Code file patterns - supported script and notebook files.

pkg/modelfile/constants_test.go

@@ -121,6 +121,15 @@ func TestInferFileType(t *testing.T) {
 		{"at threshold", "borderline", WeightFileSizeThreshold, FileTypeCode},
 		// Just above threshold should be model
 		{"above threshold", "borderline", WeightFileSizeThreshold + 1, FileTypeModel},
+
+		// TF SavedModel literal-name files: must be MODEL even when 0 bytes,
+		// independent of the size heuristic that would otherwise classify them as CODE.
+		{"feature_map literal", "feature_map", 0, FileTypeModel},
+		{"feature_map small", "feature_map", 1024, FileTypeModel},
+		{"checkpoint literal small", "checkpoint", 32, FileTypeModel},
+		// Negative: the literal patterns must not match same-stem-different-extension files.
+		{"feature_map.json is config", "feature_map.json", 1024, FileTypeConfig},
+		{"checkpoint.bin is model via *.bin", "checkpoint.bin", 1024, FileTypeModel},
 	}
 
 	assert := assert.New(t)

pkg/modelfile/modelfile.go

@@ -346,13 +346,45 @@ func (mf *modelfile) generateByWorkspace(config *configmodelfile.GenerateConfig)
 		return err
 	}
 
+	// ONNX external_data post-processing: any tensor file referenced by an .onnx
+	// file via external_data.location is unconditionally a model weight file,
+	// regardless of its name or size. Walker may have classified small external
+	// tensor files as code/config/doc by extension/size heuristic; reclassify them.
+	mf.reclassifyONNXExternalData()
+
 	if mf.model.Size() == 0 && mf.code.Size() == 0 && mf.dataset.Size() == 0 {
 		return fmt.Errorf("no model/code/dataset found - you have to create the Modelfile by yourself")
 	}
 
 	return nil
 }
 
+// reclassifyONNXExternalData scans every .onnx file already in mf.model,
+// extracts external_data.location paths, and moves those paths into mf.model
+// from whichever bucket the walker placed them in.
+func (mf *modelfile) reclassifyONNXExternalData() {
+	for _, raw := range mf.model.Values() {
+		modelRel, ok := raw.(string)
+		if !ok || !strings.HasSuffix(strings.ToLower(modelRel), ".onnx") {
+			continue
+		}
+		onnxAbs := filepath.Join(mf.workspace, modelRel)
+		extPaths, err := ExtractONNXExternalDataPaths(onnxAbs)
+		if err != nil {
+			fmt.Fprintf(os.Stderr, "modelfile: parse ONNX external_data from %s failed: %v\n", modelRel, err)
+			continue
+		}
+		onnxDir := filepath.Dir(modelRel)
+		for _, ext := range extPaths {
+			relExt := filepath.Join(onnxDir, ext)
+			mf.code.Remove(relExt)
+			mf.config.Remove(relExt)
+			mf.doc.Remove(relExt)
+			mf.model.Add(relExt)
+		}
+	}
+}
+
 // generateByModelConfig generates the modelfile by the model config, such as config.json and generation_config.json.
 func (mf *modelfile) generateByModelConfig() error {
 	// Get config map from json files. Collect all the keys and values from the config files

pkg/modelfile/modelfile_test.go

@@ -811,6 +811,111 @@ func TestNewModelfileByWorkspace(t *testing.T) {
 			expectCodes:   []string{},
 			expectName:    "selective-include",
 		},
+		{
+			// Mirrors screenshot 1 (TF SavedModel directory) plus the screenshots 4/5
+			// /home/admin/<ts>/{checkpoint,variables,...} layout: variables/ shards
+			// and a sibling checkpoint/ directory with model.ckpt-NNN.{data-*,index,meta}.
+			// Pre-fix, feature_map and the literal `checkpoint` files would have been
+			// classified as CODE because they have no extension and are small.
+			name: "tensorflow saved_model directory",
+			setupFiles: map[string]string{
+				"saved_model.pb":                          "",
+				"feature_map":                             "",
+				"tf_signature.txt":                        "",
+				"alps.meta":                               "",
+				"ais-sync.done":                           "",
+				"variables/checkpoint":                    "",
+				"variables/variables.index":               "",
+				"variables/variables.data-00000-of-00002": "",
+				"variables/variables.data-00001-of-00002": "",
+				"checkpoint/checkpoint":                   "",
+				"checkpoint/model.ckpt-756921.index":      "",
+				"checkpoint/model.ckpt-756921.meta":       "",
+				"checkpoint/model.ckpt-756921.data-00000-of-00002": "",
+				"checkpoint/model.ckpt-756921.data-00001-of-00002": "",
+			},
+			config: &configmodelfile.GenerateConfig{
+				Name: "tf-savedmodel",
+			},
+			expectError: false,
+			// *.meta hits ConfigFilePatterns first (alps.meta, model.ckpt-*.meta).
+			expectConfigs: []string{
+				"alps.meta",
+				"checkpoint/model.ckpt-756921.meta",
+			},
+			expectModels: []string{
+				"saved_model.pb",
+				"feature_map",
+				"variables/checkpoint",
+				"variables/variables.index",
+				"variables/variables.data-00000-of-00002",
+				"variables/variables.data-00001-of-00002",
+				"checkpoint/checkpoint",
+				"checkpoint/model.ckpt-756921.index",
+				"checkpoint/model.ckpt-756921.data-00000-of-00002",
+				"checkpoint/model.ckpt-756921.data-00001-of-00002",
+			},
+			// ais-sync.done has no extension and is empty -> falls back to CODE by
+			// the size heuristic. Documented intentional behavior (user accepted).
+			expectCodes: []string{"ais-sync.done"},
+			expectDocs:  []string{"tf_signature.txt"},
+			expectName:  "tf-savedmodel",
+		},
+		{
+			// Mirrors screenshot 3/4/5: a parent directory containing base/<ts>/
+			// and delta/<ts>/ subdirs, each holding a complete TF SavedModel +
+			// checkpoint layout. Verifies the walker recurses correctly and that
+			// relative paths in the resulting Modelfile preserve the timestamp
+			// directory prefix so pull-side reconstruction restores the full tree.
+			name: "online-learning base plus delta tree",
+			setupFiles: map[string]string{
+				"base/20251202030708/saved_model.pb":                          "",
+				"base/20251202030708/feature_map":                             "",
+				"base/20251202030708/tf_signature.txt":                        "",
+				"base/20251202030708/alps.meta":                               "",
+				"base/20251202030708/ais-sync.done":                           "",
+				"base/20251202030708/variables/checkpoint":                    "",
+				"base/20251202030708/variables/variables.index":               "",
+				"base/20251202030708/variables/variables.data-00000-of-00002": "",
+				"delta/20251202060205/saved_model.pb":                         "",
+				"delta/20251202060205/feature_map":                            "",
+				"delta/20251202060205/tf_signature.txt":                       "",
+				"delta/20251202060205/alps.meta":                              "",
+				"delta/20251202060205/ais-sync.done":                          "",
+				"delta/20251202060205/variables/checkpoint":                   "",
+				"delta/20251202060205/variables/variables.index":              "",
+				"delta/20251202060205/variables/variables.data-00000-of-00002": "",
+			},
+			config: &configmodelfile.GenerateConfig{
+				Name: "online-learning",
+			},
+			expectError: false,
+			expectConfigs: []string{
+				"base/20251202030708/alps.meta",
+				"delta/20251202060205/alps.meta",
+			},
+			expectModels: []string{
+				"base/20251202030708/saved_model.pb",
+				"base/20251202030708/feature_map",
+				"base/20251202030708/variables/checkpoint",
+				"base/20251202030708/variables/variables.index",
+				"base/20251202030708/variables/variables.data-00000-of-00002",
+				"delta/20251202060205/saved_model.pb",
+				"delta/20251202060205/feature_map",
+				"delta/20251202060205/variables/checkpoint",
+				"delta/20251202060205/variables/variables.index",
+				"delta/20251202060205/variables/variables.data-00000-of-00002",
+			},
+			expectCodes: []string{
+				"base/20251202030708/ais-sync.done",
+				"delta/20251202060205/ais-sync.done",
+			},
+			expectDocs: []string{
+				"base/20251202030708/tf_signature.txt",
+				"delta/20251202060205/tf_signature.txt",
+			},
+			expectName: "online-learning",
+		},
 	}
 
 	assert := assert.New(t)
@@ -2125,3 +2230,69 @@ func min(a, b int64) int64 {
 	}
 	return b
 }
+
+// TestNewModelfileByWorkspace_ONNXExternalData mirrors screenshot 2: an ONNX
+// directory where model.onnx references many extension-less tensor files via
+// external_data. Pre-fix, small external tensor files were classified as CODE
+// by the size heuristic; the ONNX post-processor must reclassify them all as
+// MODEL deterministically — regardless of the file's size.
+func TestNewModelfileByWorkspace_ONNXExternalData(t *testing.T) {
+	// Subset of the 36 extension-less files seen in screenshot 2. Names taken
+	// verbatim from the actual workflow_10062365 directory.
+	externalLocations := []string{
+		"tower_deep_layer_0_kernel_read__448_1",
+		"tower_shallow_layer_0_kernel_read__440_0",
+		"moe_layer_layer_0_kernel__399_15",
+		"moe_layer_layer_0_domain_bn_ExpandDims__400_16",
+		"moe_layer_search_layer_0_kernel__413_3",
+		"moe_layer_non_search_layer_0_kernel__427_9",
+		"feature_gate_main_kernel_read__352_27",
+		"feature_gate_main_domain_bn_ExpandDims__354_28",
+		"gated_dcn_layer_0_transform_kernel__385_21",
+		"conversion_layer_0_kernel_read__364_35",
+		"main_domain_embedding_Mark_output_user_main_domain_kernel_read__270_20",
+		"external_data_for_resource_handle",
+	}
+
+	tempDir, err := os.MkdirTemp("", "modelfile-onnx-*")
+	require.NoError(t, err)
+	defer os.RemoveAll(tempDir)
+
+	// Write the ONNX file with external_data references encoded into protobuf bytes.
+	require.NoError(t, os.WriteFile(
+		filepath.Join(tempDir, "model.onnx"),
+		buildMinimalONNXBytes(externalLocations),
+		0o644,
+	))
+
+	// Create each external tensor file as an empty placeholder.
+	for _, name := range externalLocations {
+		require.NoError(t, os.WriteFile(filepath.Join(tempDir, name), nil, 0o644))
+	}
+
+	// Sibling files from the screenshot.
+	require.NoError(t, os.WriteFile(filepath.Join(tempDir, "tf_signature.txt"), nil, 0o644))
+	require.NoError(t, os.WriteFile(filepath.Join(tempDir, "variable_sequence_def_0.onnx"), buildMinimalONNXBytes(nil), 0o644))
+
+	mf, err := NewModelfileByWorkspace(tempDir, &configmodelfile.GenerateConfig{
+		Name:      "onnx-external-data",
+		Workspace: tempDir,
+	})
+	require.NoError(t, err)
+
+	models := mf.GetModels()
+	codes := mf.GetCodes()
+	configs := mf.GetConfigs()
+
+	// Every external_data location must appear in MODEL, regardless of file size.
+	for _, name := range externalLocations {
+		assert.Contains(t, models, name, "external_data tensor %q must be reclassified as MODEL", name)
+		assert.NotContains(t, codes, name, "external_data tensor %q must NOT be in CODE", name)
+		assert.NotContains(t, configs, name, "external_data tensor %q must NOT be in CONFIG", name)
+	}
+	// Both .onnx files themselves are MODELs by extension.
+	assert.Contains(t, models, "model.onnx")
+	assert.Contains(t, models, "variable_sequence_def_0.onnx")
+	// tf_signature.txt is a doc per default DocFilePatterns (*.txt).
+	assert.Contains(t, mf.GetDocs(), "tf_signature.txt")
+}