Update app.py

app.py

@@ -1,5 +1,6 @@
 import os
 import docx
+import pandas as pd
 import numpy as np
 import streamlit as st
 from sentence_transformers import SentenceTransformer
@@ -19,12 +20,12 @@ st.set_page_config(page_title="Word RAG App", layout="wide")
 st.title("📄 Word Document RAG")
 
 uploaded_file = st.file_uploader(
-    "Upload a Word document",
+    "Upload a Word document (.docx)",
     type=["docx"]
 )
 
 # ==========================================================
-# WORD TEXT EXTRACTION (UNCHANGED LOGIC)
+# WORD TEXT EXTRACTION (UNCHANGED)
 # ==========================================================
 def read_word(doc_path):
     doc = docx.Document(doc_path)
@@ -95,7 +96,7 @@ def generate_answer(query, context):
     You are a document-based assistant.
     Use the context to answer the question clearly.
     If the answer is partially available, summarize it.
-    If the answer is not present, you may say 'Not found in the document'.
+    If the answer is not present, say 'Not found in the document'.
 
     Context:
     {context}
@@ -114,12 +115,12 @@ def generate_answer(query, context):
 # APP LOGIC
 # ==========================================================
 if uploaded_file:
-    with st.spinner("📄 Reading Word document..."):
-        file_name = uploaded_file.name
-        with open(file_name, "wb") as f:
+    with st.spinner("📄 Reading document..."):
+        temp_path = "/tmp/uploaded.docx"
+        with open(temp_path, "wb") as f:
             f.write(uploaded_file.getbuffer())
 
-        pages = read_word(file_name)
+        pages = read_word(temp_path)
 
     with st.spinner("✂️ Chunking & embedding document..."):
         chunks = chunk_text(pages)
@@ -139,3 +140,4 @@ if uploaded_file:
 
         st.markdown("### ✅ Answer")
         st.write(answer)
+