Upload 2 files

app.py

@@ -2,7 +2,7 @@ import streamlit as st
 import trafilatura
 import numpy as np
 import pandas as pd
-from ai_edge_litert.interpreter import Interpreter
+from tflite_runtime.interpreter import Interpreter
 import requests
 
 # File paths
@@ -26,12 +26,16 @@ def load_labels():
 
 @st.cache_resource
 def load_model():
-    # Load the LiteRT model
-    interpreter = Interpreter(model_path=MODEL_PATH)
-    interpreter.allocate_tensors()
-    input_details = interpreter.get_input_details()
-    output_details = interpreter.get_output_details()
-    return interpreter, input_details, output_details
+    try:
+        # Use TensorFlow Lite Interpreter
+        interpreter = Interpreter(model_path=MODEL_PATH)
+        interpreter.allocate_tensors()
+        input_details = interpreter.get_input_details()
+        output_details = interpreter.get_output_details()
+        return interpreter, input_details, output_details
+    except Exception as e:
+        st.error(f"Failed to load the model: {e}")
+        raise
 
 def preprocess_text(text, vocab, max_length=128):
     # Tokenize the text using the provided vocabulary

requirements.txt

@@ -3,7 +3,4 @@ trafilatura
 numpy
 pandas
 requests
-ai-edge-litert
-lxml
-lxml_html_clean
-
+tflite-runtime