Create app.py

app.py

@@ -1,7 +1,34 @@
 import gradio as gr
+from transformers import pipeline
 
-def greet(name):
-    return "Hello " + name + "!!"
+available_models = {
+    "mt5.baseline": pipeline("text2text-generation", model="samzirbo/mt5.baseline"),
+    "mt5.genered": pipeline("text2text-generation", model="samzirbo/mt5.gendered"),
+    "mt5.balanced": pipeline("text2text-generation", model="samzirbo/mt5.balanced"),
+    "mt5.gendered_balanced": pipeline("text2text-generation", model="samzirbo/mt5.gendered_balanced")
+}
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+def translate_text(model_name, lang_dir, gender, input_text):
+
+    model = available_models[model_name]
+
+    src, tgt = lang_dir.split(" -> ")
+
+    prompt = f"Translate {src} to {tgt} " + f"as a {gender} : " if gender and  "gendered" in model_name else f"Translate {src} to {tgt} : "
+    inputs = prompt + input_text
+    print(inputs)
+    output_text = model(inputs, max_length=128)
+    return output_text[0]['generated_text']
+
+
+model_dropdown = gr.Dropdown(choices=list(available_models.keys()), label="Select Model", value="mt5.baseline")
+lang_dropdown = gr.Dropdown(choices=["English -> Spanish", "Spanish -> English"], label="Language Direction", value="English -> Spanish")
+gender_dropdown = gr.Dropdown(choices=["female", "male"], label="Select Gender", value=None)
+
+iface = gr.Interface(fn=translate_text, 
+                     inputs=[model_dropdown, lang_dropdown, gender_dropdown, "text"], 
+                     outputs="text", 
+                     title="Translation Interface",
+                     description="Select a model, language direction, and input text to translate.")
+
+iface.launch()