Update app.py

app.py

@@ -13,7 +13,7 @@ load_dotenv()
 
 icons = {"assistant": "robot.png", "user": "man-kddi.png"}
 
-# Configure the Llama index settings for Google/Gemma-7B-IT model and English embedding
+# Configure the Llama index settings for the Google/Gemma-7B-IT model and English embedding
 Settings.llm = HuggingFaceInferenceAPI(
     model_name="google/gemma-7b-it",
     tokenizer_name="google/gemma-7b-it",
@@ -24,7 +24,7 @@ Settings.llm = HuggingFaceInferenceAPI(
 )
 
 Settings.embed_model = HuggingFaceEmbedding(
-    model_name="BAAI/bge-small-en-v1.5"  # English embedding model; adjust if Italian model is available
+    model_name="BAAI/bge-small-en-v1.5"  # English embedding model; adjust if an Italian model is available
 )
 
 # Define the directory for persistent storage and data
@@ -43,12 +43,12 @@ def displayPDF(file):
 
 def displayDOCX(file):
     text = docx2txt.process(file)
-    st.text_area("Contenuto del documento", text, height=400)
+    st.text_area("Document Content", text, height=400)
 
 def displayTXT(file):
     with open(file, "r") as f:
         text = f.read()
-    st.text_area("Contenuto del documento", text, height=400)
+    st.text_area("Document Content", text, height=400)
 
 def data_ingestion():
     documents = SimpleDirectoryReader(DATA_DIR).load_data()
@@ -62,10 +62,10 @@ def handle_query(query):
     chat_text_qa_msgs = [
         (
             "user",
-            """Sei un assistente Q&A chiamato CHAT-DOC. Il tuo obiettivo principale è fornire risposte il più accuratamente possibile, basate sulle istruzioni e il contesto che ti sono stati dati. Se una domanda non corrisponde al contesto fornito o è al di fuori dello scopo del documento, cortesemente consiglia all'utente di fare domande all'interno del contesto del documento.
-            Contesto:
+            """You are a Q&A assistant named CHAT-DOC. Your main goal is to provide answers as accurately as possible, based on the instructions and context given to you. If a question does not match the provided context or is outside the scope of the document, kindly advise the user to ask questions within the context of the document.
+            Context:
             {context_str}
-            Domanda:
+            Question:
             {query_str}
             """
         )
@@ -79,14 +79,14 @@ def handle_query(query):
     elif isinstance(answer, dict) and 'response' in answer:
         return answer['response']
     else:
-        return "Mi dispiace, non ho trovato una risposta."
+        return "Sorry, I couldn't find an answer."
 
 # Streamlit app initialization
-st.title("Chatta con il Tuo Documento 📄")
-st.markdown("Chatta qui👇")
+st.title("Chat with Your Document 📄")
+st.markdown("Chat here👇")
 
 if 'messages' not in st.session_state:
-    st.session_state.messages = [{'role': 'assistant', "content": 'Ciao! Carica un file PDF, DOCX o TXT e chiedimi qualcosa riguardo al contenuto.'}]
+    st.session_state.messages = [{'role': 'assistant', "content": 'Hello! Upload a PDF, DOCX, or TXT file and ask me anything about its content.'}]
 
 for message in st.session_state.messages:
     with st.chat_message(message['role'], avatar=icons[message['role']]):
@@ -94,9 +94,9 @@ for message in st.session_state.messages:
 
 with st.sidebar:
     st.title("Menu:")
-    uploaded_file = st.file_uploader("Carica il documento (PDF, DOCX, TXT)", type=["pdf", "docx", "txt"])
-    if st.button("Invia & Processa") and uploaded_file:
-        with st.spinner("Elaborazione..."):
+    uploaded_file = st.file_uploader("Upload your document (PDF, DOCX, TXT)", type=["pdf", "docx", "txt"])
+    if st.button("Submit & Process") and uploaded_file:
+        with st.spinner("Processing..."):
             file_extension = os.path.splitext(uploaded_file.name)[1].lower()
             filepath = os.path.join(DATA_DIR, "uploaded_file" + file_extension)
             with open(filepath, "wb") as f:
@@ -110,9 +110,9 @@ with st.sidebar:
                 displayTXT(filepath)
             
             data_ingestion()  # Process file every time a new file is uploaded
-            st.success("Fatto")
+            st.success("Done")
 
-user_prompt = st.text_input("Chiedimi qualcosa riguardo al contenuto del documento:")
+user_prompt = st.text_input("Ask me anything about the content of the document:")
 
 if user_prompt and uploaded_file:
     st.session_state.messages.append({'role': 'user', "content": user_prompt})
@@ -120,7 +120,7 @@ if user_prompt and uploaded_file:
         st.write(user_prompt)
 
     # Trigger assistant's response retrieval and update UI
-    with st.spinner("Pensando..."):
+    with st.spinner("Thinking..."):
         response = handle_query(user_prompt)
         with st.chat_message("assistant", avatar=icons["assistant"]):
             st.write(response)