Update app.py

app.py

@@ -1,39 +1,52 @@
 import streamlit as st
-import requests
-import os
 from PIL import Image
+import os
+import argostranslate.package
+import argostranslate.translate
+
+# Load Argos Translate Urdu to English model (first time only)
+def load_argos_translate_model():
+    available_packages = argostranslate.package.get_available_packages()
+    for pkg in available_packages:
+        if pkg.from_code == "ur" and pkg.to_code == "en":
+            argostranslate.package.install_from_path(pkg.download())
+            break
+
+# Check if translation model is installed
+installed_languages = argostranslate.translate.get_installed_languages()
+urdu_to_english = None
+for lang in installed_languages:
+    if lang.code == "ur":
+        for to_lang in lang.translations:
+            if to_lang.to_lang.code == "en":
+                urdu_to_english = to_lang
+                break
 
+# If not installed, download and install
+if urdu_to_english is None:
+    with st.spinner("Downloading translation model..."):
+        load_argos_translate_model()
+        installed_languages = argostranslate.translate.get_installed_languages()
+        for lang in installed_languages:
+            if lang.code == "ur":
+                for to_lang in lang.translations:
+                    if to_lang.to_lang.code == "en":
+                        urdu_to_english = to_lang
+                        break
 
-# Streamlit config
+# Streamlit UI
 st.set_page_config(page_title="DeafTranslator", layout="centered")
 st.title("🤟 DeafTranslator")
 st.markdown("Translate **Urdu** text to **English** and view it in **Sign Language** (ASL).")
 
-# Hugging Face translation model (no token required for public models, but safer with token)
-TRANSLATE_API_URL = "https://api-inference.huggingface.co/models/Helsinki-NLP/opus-mt-ur-en"
-HF_API_TOKEN = st.secrets.get("HF_API_TOKEN", None)
-HEADERS = {"Authorization": f"Bearer {HF_API_TOKEN}"} if HF_API_TOKEN else {}
-
-# Sign language images folder (alphabet or word-based)
-SIGN_IMAGE_FOLDER = "sign_images"  # Place a.jpg, b.jpg, etc. here
+SIGN_IMAGE_FOLDER = "sign_images"  # Ensure images like a.jpg, b.jpg etc. are in this folder
 
 def translate_urdu_to_english(urdu_text):
-    payload = {"inputs": urdu_text}
     try:
-        response = requests.post(TRANSLATE_API_URL, headers=HEADERS, json=payload)
-        # Check for 404 or any other status code
-        response.raise_for_status()  # Will raise HTTPError for bad responses
-        result = response.json()
-        if response.status_code == 200:
-            return result[0]['translation_text']
-        else:
-            st.error(f"Error: Unable to get translation. Status Code: {response.status_code}")
-    except requests.exceptions.HTTPError as err:
-        st.error(f"Translation failed: {response.status_code} - {response.text}")
+        return urdu_to_english.translate(urdu_text)
     except Exception as e:
-        st.error(f"Unexpected error: {str(e)}")
-    return ""
-
+        st.error(f"Translation failed: {str(e)}")
+        return ""
 
 def display_sign_language(english_text):
     words = english_text.lower().split()
@@ -49,7 +62,6 @@ def display_sign_language(english_text):
                     if os.path.exists(char_image_path):
                         st.image(char_image_path, caption=char.upper(), width=80)
 
-# --- Streamlit App UI ---
 urdu_text = st.text_area("📝 Enter Urdu Text", height=150)
 
 if st.button("🔄 Translate & Show Signs"):
@@ -58,7 +70,6 @@ if st.button("🔄 Translate & Show Signs"):
     else:
         with st.spinner("Translating..."):
             english_translation = translate_urdu_to_english(urdu_text)
-
         if english_translation:
             st.markdown("### ✅ Translated English")
             st.success(english_translation)