Floret Model Update and ML Inference working solution

contextual-classifier/Include/MLInference.h

@@ -11,6 +11,7 @@
 #include <floret/fasttext.h>
 #include <mutex>
 #include <string>
+#include <regex>
 
 class MLInference : public Inference {
   public:
@@ -19,17 +20,39 @@ class MLInference : public Inference {
     CC_TYPE Classify(int process_pid) override;
   private:
     // Derived implementation using fastText.
-    uint32_t predict(int pid,
+    uint32_t Predict(int pid,
                      const std::map<std::string, std::string> &raw_data,
                      std::string &cat);
+
     fasttext::FastText ft_model_;
     std::mutex predict_mutex_;
 
     std::vector<std::string> classes_;
     std::vector<std::string> text_cols_;
     int embedding_dim_;
 
-    std::string normalize_text(const std::string &text);
+    // initialize a set having string that we can ignore.
+    const std::set<std::string> REMOVE_KEYWORDS = {
+        "unconfined", "user.slice", "user-n.slice", "user@n.service",
+        "app.slice", "app-org.gnome.terminal.slice", "vte-spawn-n.scope",
+        "usr", "bin", "lib"
+    };
+
+    const std::set<std::string> BROWSER_TERMS = {
+        "httrack", "konqueror", "amfora", "luakit", "epiphany",
+        "firefox", "chrome", "chromium", "webkit", "gecko", "safari",
+        "opera", "brave", "vivaldi", "edge", "lynx", "w3m", "falkon"
+    };
+
+    std::regex user_slice_pattern_;
+    std::regex user_service_pattern_;
+    std::regex vte_spawn_pattern_;
+    std::regex decimal_pattern_;
+    std::regex hex_pattern_;
+    std::regex long_number_pattern_;
+
+    // Method to clean the text as same as we are doing in floret model building.
+    std::string CleanTextPython(const std::string &input);
 
 };