Update app.py

app.py

@@ -15,12 +15,18 @@ paraphrase_model = AutoModelForSeq2SeqLM.from_pretrained("csebuetnlp/banglat5_ba
 paraphrase_tokenizer = AutoTokenizer.from_pretrained("csebuetnlp/banglat5_banglaparaphrase")
 
 # Function to perform machine translation
-def translate_text(input_text):
+def translate_text_en_bn(input_text):
     inputs = translation_tokenizer_en_bn("translate: " + input_text, return_tensors="pt")
     outputs = translation_model_en_bn.generate(**inputs)
     translated_text = translation_tokenizer_en_bn.decode(outputs[0], skip_special_tokens=True)
     return translated_text
 
+def translate_text_bn_en(input_text):
+    inputs = translation_tokenizer_bn_en("translate: " + input_text, return_tensors="pt")
+    outputs = translation_model_bn_en.generate(**inputs)
+    translated_text = translation_tokenizer_bn_en.decode(outputs[0], skip_special_tokens=True)
+    return translated_text
+
 # Function to perform summarization
 def summarize_text(input_text):
     inputs = summarization_tokenizer("summarize: " + input_text, return_tensors="pt")
@@ -35,31 +41,24 @@ def paraphrase_text(input_text):
     paraphrased_text = paraphrase_tokenizer.decode(outputs[0], skip_special_tokens=True)
     return paraphrased_text
 
-# Gradio Interface
-iface = gr.Interface(
-    fn=translate_text,  # Placeholder function; will be updated dynamically based on task selection
-    inputs=gr.Textbox("textarea", label="Input Text"),
-    outputs=gr.Textbox("auto", label="Output Text"),
-    live=False
-)
-
-# Function to update the Gradio interface based on task selection
-def update_interface(change):
-    selected_task = task_selector.value
-
-    if selected_task == 'Translate':
-        iface.fn = translate_text
-    elif selected_task == 'Summarize':
-        iface.fn = summarize_text
-    elif selected_task == 'Paraphrase':
-        iface.fn = paraphrase_text
+def process_text(text, task):
+    if task == "Translate_English_to_Bengali":
+        return translate_text_en_bn(text)
+    elif task == "Translate_Bengali_to_English":
+        return translate_text_bn_en(text)
+    elif task == "Summarize":
+        return summarize_text(text)
+    elif task == "Paraphrase":
+        return paraphrase_text(text)
 
-# Dropdown widget to select the task
-task_selector = gr.Dropdown(
-    ["Translate", "Summarize", "Paraphrase"],
-    label="Select Task"
+# Define the Gradio interface
+iface = gr.Interface(
+    fn=process_text,
+    inputs=["text", gr.Dropdown(["Translate_English_to_Bengali", "Translate_Bengali_to_English", "Summarize", "Paraphrase"])],
+    outputs="text",
+    live=False,
+    title="Usage of BanglaT5 Model"
 )
 
-
 # Launch the Gradio app
 iface.launch(inline=False)