Update app.py

app.py

@@ -1,52 +1,32 @@
 from multilingual_translation import text_to_text_generation
-from utils import lang_ids, data_scraping
+from utils import data_scraping
 import gradio as gr
 
-lang_list = list(lang_ids.keys())
 model_list = data_scraping()
 
-def multilingual_translate(
-    prompt: str, 
-    model_id: str, 
-    target_lang: str
-    ):
-    
+def multilingual_translate(prompt: str, model_id: str):
+    target_lang = "en" # English language code
     return text_to_text_generation(
         prompt=prompt, 
         model_id=model_id, 
         device='cpu',
-        target_lang=lang_ids[target_lang]
-        )
-
+        target_lang=target_lang
+    )
 
 inputs = [
     gr.Textbox(lines=4, value="Hello world!", label="Input Text"),
     gr.Dropdown(model_list, value="facebook/m2m100_418M", label="Model"),
-    gr.Dropdown(lang_list, value="Turkish", label="Target Language"),
 ]
 
 output = gr.outputs.Textbox(label="Output Text")
 
 examples = [
-    [
-        "Hello world!",
-        "facebook/m2m100_418M",
-        "Turkish",
-    ],
-    [
-        "Omar ve Merve çok iyi arkadaşlar.",
-        "facebook/m2m100_418M",
-        "Spanish",
-    ],
-    [
-        "Hugging Face is a great company.",
-        "facebook/m2m100_418M",
-        "French",
-    ]
+    ["Hello world!", "facebook/m2m100_418M"],
+    ["Omar ve Merve çok iyi arkadaşlar.", "facebook/m2m100_418M"],
+    ["Hugging Face is a great company.", "facebook/m2m100_418M"]
 ]
 
 title = "Beyond English-Centric Multilingual Machine Translation"
-
 description = "M2M100 is a multilingual encoder-decoder (seq-to-seq) model trained for Many-to-Many multilingual translation. It was introduced in this [paper](https://arxiv.org/abs/2010.11125) and first released in [this](https://github.com/pytorch/fairseq/tree/master/examples/m2m_100) repository."
 
 app = gr.Interface(