Delete app.py

app.py

@@ -1,87 +0,0 @@
-import streamlit as st
-from typing import List, IO
-
-# Import utilities you finalised
-from utils import (
-    get_pdf_text,
-    get_docx_text,
-    get_text_chunks,
-    get_vector_store,
-    user_input,
-)
-
-# ---------------------------------------------------------------------------#
-#  Main Streamlit application
-# ---------------------------------------------------------------------------#
-def main() -> None:
-    # ----- Page configuration ------------------------------------------------
-    st.set_page_config(
-        page_title="Docosphere",
-        page_icon="📄",
-        layout="wide"
-    )
-
-    st.title("📄 Docosphere")
-    st.markdown("*Where Documents Come Alive …*")
-
-    # Two-column layout: Q&A on left, file upload on right
-    col_left, col_right = st.columns([2, 1])
-
-    # --------------------- Right column – document upload -------------------
-    with col_right:
-        st.markdown("### 📁 Document Upload")
-        uploaded_files: List[IO[bytes]] = st.file_uploader(
-            "Upload PDF or Word files",
-            accept_multiple_files=True,
-            type=["pdf", "docx"],
-            help="You can select multiple files at once."
-        )
-
-        if st.button("🚀 Process Documents"):
-            if not uploaded_files:
-                st.warning("📋 Please upload at least one file first.")
-                return
-
-            with st.spinner("🔄 Extracting text & creating vector index…"):
-                combined_text = ""
-
-                pdfs  = [f for f in uploaded_files if f.name.lower().endswith(".pdf")]
-                docs  = [f for f in uploaded_files if f.name.lower().endswith(".docx")]
-
-                if pdfs:
-                    combined_text += get_pdf_text(pdfs)
-                if docs:
-                    combined_text += get_docx_text(docs)
-
-                if combined_text.strip():
-                    chunks = get_text_chunks(combined_text)
-                    get_vector_store(chunks)
-                    st.success("✅ Documents processed! Ask away in the left panel.")
-                else:
-                    st.warning("⚠️ No readable text found in the uploaded files.")
-
-        with st.expander("ℹ️ How to use"):
-            st.markdown(
-                """
-                1. Upload one or more **PDF** or **Word** documents.\n
-                2. Click **Process Documents** to build the knowledge index.\n
-                3. Ask natural-language questions in the input box (left column).\n
-                4. The assistant will either answer from its own model knowledge or
-                   retrieve context from your documents when needed.
-                """
-            )
-
-    # ---------------------- Left column – chat interface --------------------
-    with col_left:
-        st.markdown("### 💬 Ask Your Question")
-        question: str = st.text_input(
-            "",
-            placeholder="Type a question about your documents or general topics…"
-        )
-
-        if question:
-            user_input(question)
-
-# Entry-point guard
-if __name__ == "__main__":
-    main()