Auto detect handler for sklearn (#2917)

Author: xyang16

engines/python/setup/djl_python/ts_service_loader.py

@@ -76,8 +76,9 @@ def invoke_handler(self, function_name, inputs):
         if content_type is not None:
             outputs.add_property("content-type", content_type)
 
-        if ts_out is None:
+        if not ts_out:
             outputs.message = "No content"
+            output.add("No content")
         else:
             val = ts_out[0]
             if isinstance(val, torch.Tensor):

engines/python/src/main/java/ai/djl/python/engine/PyModel.java

@@ -179,7 +179,10 @@ public void load(Path modelPath, String prefix, Map<String, ?> options) throws I
                     entryPoint = modelFile.toFile().getName();
                 }
                 // find recommendedEntryPoint
-                if ("nc".equals(manager.getDevice().getDeviceType())
+                if (hasModelFile(
+                        modelDir, prefix, ".skops", ".joblib", ".pkl", ".pickle", ".cloudpkl")) {
+                    recommendedEntryPoint = "djl_python.sklearn_handler";
+                } else if ("nc".equals(manager.getDevice().getDeviceType())
                         && pyEnv.getTensorParallelDegree() > 0) {
                     recommendedEntryPoint = "djl_python.transformers_neuronx";
                 } else if ("trtllm".equals(features)) {
@@ -327,6 +330,18 @@ private Path findModelFile(String prefix) {
         return modelFile;
     }
 
+    private boolean hasModelFile(Path modelDir, String prefix, String... extensions) {
+        for (String extension : extensions) {
+            if (Files.isRegularFile(modelDir.resolve(prefix + extension))) {
+                return true;
+            }
+            if (Files.isRegularFile(modelDir.resolve("model" + extension))) {
+                return true;
+            }
+        }
+        return false;
+    }
+
     private void createAllPyProcesses(int mpiWorkers, int worldSize) {
         long begin = System.currentTimeMillis();
         ExecutorService pool = null;

wlm/src/main/java/ai/djl/serving/wlm/ModelInfo.java

@@ -742,6 +742,18 @@ public Device withDefaultDevice(String deviceName) {
         return Device.fromName(deviceName, Engine.getEngine(engineName));
     }
 
+    private boolean hasModelFile(Path modelDir, String prefix, String... extensions) {
+        for (String extension : extensions) {
+            if (Files.isRegularFile(modelDir.resolve(prefix + extension))) {
+                return true;
+            }
+            if (Files.isRegularFile(modelDir.resolve("model" + extension))) {
+                return true;
+            }
+        }
+        return false;
+    }
+
     private String inferEngine() throws ModelException {
         String eng = prop.getProperty("engine");
         if (eng != null) {
@@ -768,23 +780,19 @@ private String inferEngine() throws ModelException {
             return zoo.getSupportedEngines().iterator().next();
         } else if (isTorchServeModel()) {
             return "Python";
-        } else if (Files.isRegularFile(modelDir.resolve(prefix + ".pt"))
-                || Files.isRegularFile(modelDir.resolve("model.pt"))) {
+        } else if (hasModelFile(modelDir, prefix, ".pt")) {
             return "PyTorch";
         } else if (Files.isRegularFile(modelDir.resolve("config.pbtxt"))) {
             return "TritonServer";
         } else if (Files.isRegularFile(modelDir.resolve("saved_model.pb"))) {
             return "TensorFlow";
-        } else if (Files.isRegularFile(modelDir.resolve(prefix + ".onnx"))
-                || Files.isRegularFile(modelDir.resolve("model.onnx"))) {
+        } else if (hasModelFile(modelDir, prefix, ".onnx")) {
             return "OnnxRuntime";
-        } else if (Files.isRegularFile(modelDir.resolve(prefix + ".json"))
-                || Files.isRegularFile(modelDir.resolve(prefix + ".xgb"))
-                || Files.isRegularFile(modelDir.resolve(prefix + ".bst"))
-                || Files.isRegularFile(modelDir.resolve("model.json"))
-                || Files.isRegularFile(modelDir.resolve("model.bst"))
-                || Files.isRegularFile(modelDir.resolve("model.xgb"))) {
+        } else if (hasModelFile(modelDir, prefix, ".json", ".xgb", ".bst")) {
             return "XGBoost";
+        } else if (hasModelFile(
+                modelDir, prefix, ".skops", ".joblib", ".pkl", ".pickle", ".cloudpkl")) {
+            return "Python";
         } else if (isPythonModel(prefix)) {
             // TODO: How to differentiate Rust model from Python
             return "Python";