Delete app.py

app.py

@@ -1,63 +0,0 @@
-import streamlit as st
-from deep_translator import GoogleTranslator
-from transformers import pipeline
-import os
-
-# Create a local cache directory
-os.environ["TRANSFORMERS_CACHE"] = "./models_cache"
-os.makedirs("./models_cache", exist_ok=True)
-
-@st.cache_resource
-def load_translator():
-    def translate_to_english(text, src_lang='auto'):
-        """Translate any input text to English."""
-        try:
-            translated = GoogleTranslator(source=src_lang, target='en').translate(text)
-            return translated
-        except Exception as e:
-            return f"Translation error: {e}"
-
-    def translate_from_english(text, target_lang):
-        """Translate English response back to user language."""
-        try:
-            translated = GoogleTranslator(source='en', target=target_lang).translate(text)
-            return translated
-        except Exception as e:
-            return f"Translation error: {e}"
-    return translate_to_english, translate_from_english
-
-@st.cache_resource
-def load_chatbot_model():
-    # Use a small multilingual model (or fine-tuned one from Hugging Face)
-    chatbot = pipeline("text-generation", model="facebook/blenderbot-400M-distill")
-    def get_chatbot_response(prompt):
-        """Generate chatbot reply using a transformer model."""
-        result = chatbot(prompt, max_length=120, num_return_sequences=1)
-        return result[0]['generated_text']
-    return get_chatbot_response
-
-translate_to_english, translate_from_english = load_translator()
-get_chatbot_response = load_chatbot_model()
-
-st.set_page_config(page_title="GUVI Multilingual Chatbot", layout="centered")
-st.title("🤖 GUVI Multilingual Chatbot")
-st.write("Chat with AI in your own language!")
-
-# User selects language
-language = st.selectbox("Select your language:",
-                        ["en", "ta", "hi", "ml", "te", "bn", "fr", "es"])
-
-user_input = st.text_input("You:", "")
-
-if st.button("Send"):
-    if user_input:
-        # Step 1: Translate to English
-        english_text = translate_to_english(user_input, src_lang=language)
-
-        # Step 2: Get GPT response
-        english_reply = get_chatbot_response(english_text)
-
-        # Step 3: Translate back
-        final_reply = translate_from_english(english_reply, target_lang=language)
-
-        st.markdown(f"**Bot:** {final_reply}")