Create app.py

app.py

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+import streamlit as st
+import pdfplumber
+import pandas as pd
+from io import BytesIO
+
+def is_header(text):
+    """Identify headers using common keywords."""
+    keywords = ['Purchase Order', 'Supplier Order', 'GSTIN', 'Annexure', 'Terms', 'Currency']
+    return any(keyword in text for keyword in keywords)
+
+def extract_cleaned_tables(pdf_file):
+    """Extract tables while skipping headers and arranging them by pages."""
+    tables = []
+    
+    with pdfplumber.open(pdf_file) as pdf:
+        for page_num, page in enumerate(pdf.pages):
+            text = page.extract_text()
+            
+            # Skip pages with header-heavy content
+            if is_header(text):
+                continue
+            
+            page_tables = page.extract_tables()
+            for table in page_tables:
+                if table:
+                    df = pd.DataFrame(table[1:], columns=table[0])
+                    # Fix misalignment issues (if 'Unit' in wrong columns, move it)
+                    if 'Delivery Date' in df.columns and 'Unit' in df.columns:
+                        mask = df['Delivery Date'].str.contains(r'NOS|PCS', na=False)
+                        df.loc[mask, 'Unit'] = df.loc[mask, 'Delivery Date']
+                        df.loc[mask, 'Delivery Date'] = None
+                    
+                    tables.append((f"Page_{page_num+1}", df))
+    
+    return tables
+
+# Streamlit App
+st.title("Enhanced PO Extraction Tool")
+
+uploaded_file = st.file_uploader("Upload PO PDF", type=["pdf"])
+
+if uploaded_file:
+    try:
+        # Extract and clean tables from the uploaded PDF
+        extracted_tables = extract_cleaned_tables(uploaded_file)
+
+        if extracted_tables:
+            st.success("Tables extracted successfully!")
+            
+            # Create an Excel file with multiple sheets
+            excel_buffer = BytesIO()
+            with pd.ExcelWriter(excel_buffer, engine='openpyxl') as writer:
+                for sheet_name, df in extracted_tables:
+                    df.to_excel(writer, index=False, sheet_name=sheet_name)
+            excel_buffer.seek(0)
+
+            # Provide download options
+            st.download_button(
+                label="Download as Excel",
+                data=excel_buffer,
+                file_name="po_data.xlsx",
+                mime="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
+            )
+        else:
+            st.warning("No valid tables found.")
+    except Exception as e:
+        st.error(f"An error occurred: {e}")