Update app.py

app.py

@@ -16,9 +16,9 @@ import networkx as nx
 nltk.download('punkt')
 nltk.download('stopwords')
 
-def greet(name):
-    return "Hello " + name + "!!"
-
+model_checkpoint = "marefa-nlp/marefa-mt-en-ar"
+tokenizer = AutoTokenizer.from_pretrained(model_checkpoint)
+model = TFAutoModelForSeq2SeqLM.from_pretrained("tf_model.h5")
 
 # Load cleaned_word_embeddings
 with open("cleaned_word_embeddings.pkl", "rb") as f:
@@ -99,7 +99,12 @@ def summarize(text):
         summary += ranked_sentences[j][1] + " "
     return summary
 
+def translate(text):
+    summarized = summarize(text)
+    tokenized = tokenizer([summarized], return_tensors='np')
+    arabic = model.generate(**tokenized, max_length=128)
+    return arabic
     
-demo = gr.Interface(fn=summarize, inputs="text", outputs="text")
+demo = gr.Interface(fn=translate, inputs="text", outputs="text")
 demo.launch(share=True)