Create app.py

app.py

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+import gradio as gr
+import yaml
+import torch
+from mmtafrica import load_params, translate
+from huggingface_hub import hf_hub_download
+
+language_map = {'English':'en','Swahili':'sw','Fon':'fon','Igbo':'ig',
+                'Kinyarwanda':'rw','Xhosa':'xh','Yoruba':'yo','French':'fr'}  
+  
+available_languages = list(language_map.keys())
+
+# Load parameters and model from checkpoint
+checkpoint = hf_hub_download(repo_id="chrisjay/mmtafrica", filename="mmt_translation.pt")
+device = 'gpu' if torch.cuda.is_available() else 'cpu'
+params = load_params({'checkpoint':checkpoint,'device':device})
+
+
+def get_translation(source_language,target_language,source_sentence=None):
+    '''
+    This takes a sentence and gets the translation.
+    '''
+    
+    source_language_ = language_map[source_language]
+    target_language_ = language_map[target_language]
+   
+  
+    try:
+        pred = translate(params,source_sentence,source_lang=source_language_,target_lang=target_language_)
+        if pred=='':
+            return f"Could not find translation"
+        else:
+            return pred
+    except Exception as error:
+        return f"Issue with translation: \n {error}"
+ 
+title = "MMTAfrica: Multilingual Machine Translation"
+description = "Enjoy our MMT model that allows you to translate among 6 African languages, English and French!"
+
+iface = gr.Interface(fn=get_translation, 
+  inputs=[gr.inputs.Dropdown(choices = available_languages,default='Igbo'),
+  gr.inputs.Dropdown(choices = available_languages,default='Fon'),
+  gr.inputs.Textbox(label="Input")],
+  outputs=gr.outputs.Textbox(type="auto", label='Translation'),
+  title=title,
+  description=description,
+  enable_queue=True,
+  theme='huggingface')
+iface.launch()