Update src/streamlit_app.py

src/streamlit_app.py

@@ -13,10 +13,11 @@ import os
 # ==============================
 HF_TOKEN = os.environ.get("HF_TOKEN")
 
-client = InferenceClient(
-    model="facebook/nllb-200-distilled-600M",
-    token=HF_TOKEN
-)
+if HF_TOKEN is None:
+    st.error("❌ HF_TOKEN not found. Add it in Hugging Face Secrets.")
+    st.stop()
+
+client = InferenceClient(token=HF_TOKEN)
 
 embed_model = SentenceTransformer("all-MiniLM-L6-v2")
 
@@ -25,7 +26,6 @@ embed_model = SentenceTransformer("all-MiniLM-L6-v2")
 # ==============================
 dimension = 384
 index = faiss.IndexFlatL2(dimension)
-
 memory_texts = []
 
 def embed(text):
@@ -57,6 +57,17 @@ lang_map = {
     "German": "deu_Latn"
 }
 
+# langdetect → NLLB mapping
+lang_detect_map = {
+    "en": "eng_Latn",
+    "ta": "tam_Taml",
+    "hi": "hin_Deva",
+    "fr": "fra_Latn",
+    "ar": "arb_Arab",
+    "es": "spa_Latn",
+    "de": "deu_Latn"
+}
+
 # ==============================
 # SPEECH TO TEXT
 # ==============================
@@ -78,30 +89,35 @@ def speech_to_text(audio_file):
     return text
 
 # ==============================
-# TRANSLATION FUNCTION
+# TRANSLATION FUNCTION (FIXED)
 # ==============================
 def translate(text, target_lang):
+
+    # Detect language
     try:
-        src_lang = detect(text)
+        detected = detect(text)
+        src_lang = lang_detect_map.get(detected, "eng_Latn")
     except:
-        src_lang = "unknown"
+        src_lang = "eng_Latn"
 
-    memory = retrieve_memory(text)
+    tgt_lang = lang_map[target_lang]
 
-    prompt = f"""
-    Translate the following text into {target_lang}.
-    Only return translated text.
+    # RAG memory
+    memory = retrieve_memory(text)
 
-    Text: {text}
-    """
+    try:
+        # ✅ Correct API usage
+        response = client.translation(
+            text=text,
+            src_lang=src_lang,
+            tgt_lang=tgt_lang,
+            model="facebook/nllb-200-distilled-600M"
+        )
 
-    response = client.text_generation(
-        prompt,
-        max_new_tokens=300,
-        temperature=0.2
-    )
+        translated = response["translation_text"]
 
-    translated = response.strip()
+    except Exception as e:
+        translated = f"❌ Translation failed: {str(e)}"
 
     store_memory(text, translated)
 
@@ -110,24 +126,25 @@ def translate(text, target_lang):
 # ==============================
 # UI
 # ==============================
+st.set_page_config(page_title="AI Translator", layout="wide")
+
 st.title("🌍 AI Translator with Voice")
 
 tab1, tab2 = st.tabs(["📝 Text Input", "🎤 Voice Input"])
 
+input_text = ""
+
 # ------------------------------
-# TEXT INPUT TAB
+# TEXT INPUT
 # ------------------------------
 with tab1:
     input_text = st.text_area("Enter text")
 
 # ------------------------------
-# VOICE INPUT TAB
+# VOICE INPUT
 # ------------------------------
 with tab2:
-    audio_file = st.file_uploader(
-        "Upload audio file (wav/mp3)",
-        type=["wav", "mp3"]
-    )
+    audio_file = st.file_uploader("Upload audio (wav/mp3)", type=["wav", "mp3"])
 
     if audio_file:
         st.audio(audio_file)
@@ -144,7 +161,7 @@ with tab2:
 target_lang = st.selectbox("Target Language", list(lang_map.keys()))
 
 if st.button("Translate"):
-    if 'input_text' not in locals() or input_text.strip() == "":
+    if not input_text.strip():
         st.warning("Please provide input text or audio")
     else:
         with st.spinner("Translating..."):