Update app.py

app.py

@@ -1,4 +1,36 @@
 import streamlit as st
+from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
+import torch
 
-x = st.slider('Select a value')
-st.write(x, 'squared is', x * x)
+# Display the torch version (optional, for verification)
+st.sidebar.write(f'PyTorch Version: {torch.__version__}')
+
+# Load models and tokenizers for both directions
+models = {
+    "ka-en": {
+        "model": AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-ka-en"),
+        "tokenizer": AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-ka-en")
+    },
+    "en-ka": {
+        # Assuming this model is correctly specified
+        "model": AutoModelForSeq2SeqLM.from_pretrained("SoyGema/english-georgian", use_auth_token=True if st.secrets["HF_TOKEN"] else None),
+        "tokenizer": AutoTokenizer.from_pretrained("SoyGema/english-georgian", use_auth_token=True if st.secrets["HF_TOKEN"] else None)
+    }
+}
+
+# UI for selecting translation direction
+direction = st.selectbox("Select translation direction:", options=["ka-en", "en-ka"], index=0)
+
+# UI for input text
+text = st.text_area("Text to translate:", height=150)
+
+if st.button('Translate'):
+    if text:
+        tokenizer = models[direction]['tokenizer']
+        model = models[direction]['model']
+        inputs = tokenizer(text, return_tensors="pt", padding=True, truncation=True, max_length=512)
+        translated = model.generate(**inputs)
+        translation = tokenizer.decode(translated[0], skip_special_tokens=True)
+        st.write(translation)
+    else:
+        st.write("Please enter some text to translate.")