Update app.py

app.py

@@ -1,28 +1,39 @@
-import gradio as gr
 from huggingface_hub import from_pretrained_keras
-from transformers import AutoTokenizer
+import gradio as gr
+import json
 
-# Load the model from Hugging Face
-model = from_pretrained_keras("Bajiyo/Malayalam_transliteration")
+# Set the path to the directory containing the model files
+model_directory = "Bajiyo/Malayalam_transliteration"
 
-# Load the tokenizer
-tokenizer = AutoTokenizer.from_pretrained("Bajiyo/Malayalam_transliteration")
+# Set the paths to the tokenizer configuration files
+source_tokenizer_config_path = f"{model_directory}/source_tokenizer_config.json"
+target_tokenizer_config_path = f"{model_directory}/target_tokenizer_config.json"
 
-# Define a function to make predictions
-def predict(text):
-    # Tokenize the input text
-    inputs = tokenizer(text, return_tensors="tf", padding=True, truncation=True)
+# Load tokenizer configurations
+with open(source_tokenizer_config_path, "r") as source_config_file:
+    source_tokenizer_config = json.load(source_config_file)
 
-    # Make predictions using the model
-    outputs = model.predict(inputs)
+with open(target_tokenizer_config_path, "r") as target_config_file:
+    target_tokenizer_config = json.load(target_config_file)
 
-    # Decode the predicted tokens
-    predicted_text = tokenizer.decode(outputs.logits[0], skip_special_tokens=True)
+# Load the model from Hugging Face
+model = from_pretrained_keras("Bajiyo/Malayalam_transliteration")
 
-    return predicted_text
+def transliterate(input_text):
+    # Tokenize the input text using the loaded tokenizer configurations
+    # (Assuming you have functions to tokenize input_text using source_tokenizer_config and target_tokenizer_config)
+    inputs = tokenize_input(input_text, source_tokenizer_config)
+    
+    # Make predictions using the model
+    predictions = model.predict(inputs)
+    
+    # Post-process the predictions if needed
+    output_text = post_process_predictions(predictions, target_tokenizer_config)
+    
+    return output_text
 
-# Create a Gradio interface
+# Define Gradio interface
 inputs = gr.inputs.Textbox(label="Enter Malayalam Text")
 outputs = gr.outputs.Textbox(label="Transliteration to English")
-interface = gr.Interface(predict, inputs, outputs, title="Malayalam to English Transliteration")
+interface = gr.Interface(transliterate, inputs, outputs, title="Malayalam to English Transliteration")
 interface.launch()