feat: Load saved models

app.py

@@ -1,5 +1,7 @@
 import gradio as gr
 
+from predictor import predict
+
 # 📌 CUSTOM CSS
 css_code = """
 #footer-container {
@@ -20,44 +22,6 @@ css_code = """
 """
 
 
-# 📌 FUNCTIONS
-def predict(mode, text, image_path):
-    """
-    This placeholder function now returns a dictionary
-    in the format expected by the gr.Label component.
-    """
-    multimodal_output = {
-        "abcat0100000": 0.05,
-        "abcat0200000": 0.10,
-        "abcat0300000": 0.20,
-        "abcat0400000": 0.45,
-        "abcat0500000": 0.20,
-    }
-    text_only_output = {
-        "abcat0100000": 0.08,
-        "abcat0200000": 0.15,
-        "abcat0300000": 0.25,
-        "abcat0400000": 0.35,
-        "abcat0500000": 0.17,
-    }
-    image_only_output = {
-        "abcat0100000": 0.10,
-        "abcat0200000": 0.20,
-        "abcat0300000": 0.30,
-        "abcat0400000": 0.25,
-        "abcat0500000": 0.15,
-    }
-
-    if mode == "Multimodal":
-        return multimodal_output
-    elif mode == "Text Only":
-        return text_only_output
-    elif mode == "Image Only":
-        return image_only_output
-    else:
-        return {}
-
-
 def update_inputs(mode: str):
     if mode == "Multimodal":
         return gr.Textbox(visible=True), gr.Image(visible=True)

predictor.py

@@ -0,0 +1,60 @@
+from tensorflow.keras.models import load_model
+
+# TODO: Review Code
+# Load the models once at the start of the script
+print("💬 Loading models...")
+try:
+    text_model = load_model("./models/text_model")
+    image_model = load_model("./models/image_model")
+    multimodal_model = load_model("./models/multimodal_model")
+    print("✅ Models loaded successfully!")
+except Exception as e:
+    print(f"❌ Error loading models: {e}")
+    text_model = None
+    image_model = None
+    multimodal_model = None
+
+# A placeholder for your class labels
+CLASS_LABELS = [
+    "abcat0100000",
+    "abcat0200000",
+    "abcat0207000",
+]  # Add your actual labels
+
+
+# 📌 FUNCTIONS
+def predict(mode, text, image_path):
+    """
+    This placeholder function now returns a dictionary
+    in the format expected by the gr.Label component.
+    """
+    multimodal_output = {
+        "abcat0100000": 0.05,
+        "abcat0200000": 0.10,
+        "abcat0300000": 0.20,
+        "abcat0400000": 0.45,
+        "abcat0500000": 0.20,
+    }
+    text_only_output = {
+        "abcat0100000": 0.08,
+        "abcat0200000": 0.15,
+        "abcat0300000": 0.25,
+        "abcat0400000": 0.35,
+        "abcat0500000": 0.17,
+    }
+    image_only_output = {
+        "abcat0100000": 0.10,
+        "abcat0200000": 0.20,
+        "abcat0300000": 0.30,
+        "abcat0400000": 0.25,
+        "abcat0500000": 0.15,
+    }
+
+    if mode == "Multimodal":
+        return multimodal_output
+    elif mode == "Text Only":
+        return text_only_output
+    elif mode == "Image Only":
+        return image_only_output
+    else:
+        return {}

requirements.txt

@@ -1 +1,5 @@
 gradio==5.44.0
+tensorflow==2.15.0
+transformers==4.44.2
+numpy==1.26.4
+sentence-transformers==5.1.0