diff --git a/cpp/CMakeLists.txt b/cpp/CMakeLists.txt
index a4725c7..ba282d7 100644
--- a/cpp/CMakeLists.txt
+++ b/cpp/CMakeLists.txt
@@ -33,8 +33,8 @@ add_executable(tflite_cpu
 
 target_link_libraries(tflite_cpu
   PRIVATE Threads::Threads
-  PRIVATE "$<LINK_LIBRARY:WHOLE_ARCHIVE,viam-cpp-sdk::viamsdk>"
-  PRIVATE "$<LINK_LIBRARY:WHOLE_ARCHIVE,tensorflow::tensorflowlite>"
+  PRIVATE viam-cpp-sdk::viamsdk
+  PRIVATE tensorflow::tensorflowlite
 )
 
 install(
diff --git a/cpp/conanfile.py b/cpp/conanfile.py
index c82de3d..6773f60 100644
--- a/cpp/conanfile.py
+++ b/cpp/conanfile.py
@@ -41,7 +41,7 @@ def configure(self):
             self.options["*"].shared = False
 
     def requirements(self):
-        self.requires("viam-cpp-sdk/0.0.11")
+        self.requires("viam-cpp-sdk/0.0.12")
         self.requires("tensorflow-lite/2.15.0")
         self.requires("abseil/20240116.2", override=True)
 
@@ -57,11 +57,3 @@ def build(self):
 
     def layout(self):
         cmake_layout(self, src_folder=".")
-
-    def test(self):
-        if can_run(self):
-            cmd = os.path.join(self.cpp.build.bindir, "tflite_module")
-            stderr = StringIO()
-            self.run(cmd, env='conanrun', stderr=stderr, ignore_errors=True)
-            if "main failed with exception:" not in stderr.getvalue():
-                raise ConanException("Unexpected error output from test")
diff --git a/cpp/src/tflite_cpu.cpp b/cpp/src/tflite_cpu.cpp
index 24d0dd8..4113722 100644
--- a/cpp/src/tflite_cpu.cpp
+++ b/cpp/src/tflite_cpu.cpp
@@ -28,7 +28,7 @@
 
 #include <viam/sdk/components/component.hpp>
 #include <viam/sdk/config/resource.hpp>
-#include <viam/sdk/common/proto_type.hpp>
+#include <viam/sdk/common/proto_value.hpp>
 #include <viam/sdk/module/service.hpp>
 #include <viam/sdk/registry/registry.hpp>
 #include <viam/sdk/resource/reconfigurable.hpp>
@@ -70,7 +70,7 @@ class MLModelServiceTFLite : public vsdk::MLModelService,
         // drain.
     }
 
-    void stop(const vsdk::AttributeMap& extra) noexcept final {
+    void stop(const vsdk::ProtoStruct& extra) noexcept final {
         return stop();
     }
 
@@ -135,7 +135,7 @@ class MLModelServiceTFLite : public vsdk::MLModelService,
     }
 
     std::shared_ptr<named_tensor_views> infer(const named_tensor_views& inputs,
-                                              const vsdk::AttributeMap& extra) final {
+                                              const vsdk::ProtoStruct& extra) final {
         auto state = lease_state_();
 
         // We serialize access to the interpreter. We use a
@@ -244,7 +244,7 @@ class MLModelServiceTFLite : public vsdk::MLModelService,
         return {std::move(inference_result), views};
     }
 
-    struct metadata metadata(const vsdk::AttributeMap& extra) final {
+    struct metadata metadata(const vsdk::ProtoStruct& extra) final {
         // Just return a copy of our metadata from leased state.
         return lease_state_()->metadata;
     }
@@ -284,14 +284,14 @@ class MLModelServiceTFLite : public vsdk::MLModelService,
         // Now we can begin parsing and validating the provided `configuration`.
         // Pull the model path out of the configuration.
         const auto& attributes = state->configuration.attributes();
-        auto model_path = attributes->find("model_path");
-        if (model_path == attributes->end()) {
+        auto model_path = attributes.find("model_path");
+        if (model_path == attributes.end()) {
             std::ostringstream buffer;
             buffer << service_name
                    << ": Required parameter `model_path` not found in configuration";
             throw std::invalid_argument(buffer.str());
         }
-        const auto* const model_path_string = model_path->second->get<std::string>();
+        const auto* const model_path_string = model_path->second.get<std::string>();
         if (!model_path_string || model_path_string->empty()) {
             std::ostringstream buffer;
             buffer << service_name
@@ -300,9 +300,9 @@ class MLModelServiceTFLite : public vsdk::MLModelService,
             throw std::invalid_argument(buffer.str());
         }
         std::string label_path_string = ""; // default value for label_path 
-        auto label_path = attributes->find("label_path");
-        if (label_path != attributes->end()) {
-            const auto* const lp_string = label_path->second->get<std::string>();
+        auto label_path = attributes.find("label_path");
+        if (label_path != attributes.end()) {
+            const auto* const lp_string = label_path->second.get<std::string>();
             if (!lp_string) {
                 std::ostringstream buffer;
                 buffer << service_name
@@ -360,9 +360,9 @@ class MLModelServiceTFLite : public vsdk::MLModelService,
         // If present, extract and validate the number of threads to
         // use in the interpreter and create an interpreter options
         // object to carry that information.
-        auto num_threads = attributes->find("num_threads");
-        if (num_threads != attributes->end()) {
-            const auto* num_threads_double = num_threads->second->get<double>();
+        auto num_threads = attributes.find("num_threads");
+        if (num_threads != attributes.end()) {
+            const auto* num_threads_double = num_threads->second.get<double>();
             if (!num_threads_double || !std::isnormal(*num_threads_double) ||
                 (*num_threads_double < 0) ||
                 (*num_threads_double >= std::numeric_limits<std::int32_t>::max()) ||
@@ -459,11 +459,7 @@ class MLModelServiceTFLite : public vsdk::MLModelService,
                 output_info.shape.push_back(TfLiteTensorDim(tensor, j));
             }
             if (state->label_path != "") {
-		if (!output_info.extra) {
-			output_info.extra = std::make_shared<std::unordered_map<std::string, std::shared_ptr<vsdk::ProtoType>>>();
-		}
-                auto protoValue = std::make_shared<vsdk::ProtoType>(std::string(state->label_path));
-                output_info.extra->insert({"labels", protoValue});
+                output_info.extra.insert({"labels", state->label_path});
             }
             state->output_tensor_indices_by_name[output_info.name] = i;
             state->metadata.outputs.emplace_back(std::move(output_info));