Create app.py

app.py

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+import pdfplumber
+import pandas as pd
+import re
+import gradio as gr
+
+# Function: Extract Text from PDF
+def extract_text_from_pdf(pdf_file):
+    with pdfplumber.open(pdf_file.name) as pdf:
+        text = ""
+        for page in pdf.pages:
+            text += page.extract_text()
+    return text
+
+# Function: Clean Description
+def clean_description(description, item_number=None):
+    """
+    Cleans the description by removing unwanted data such as Qty, Unit, Unit Price, Total Price, and other invalid entries.
+    Args:
+        description (str): Raw description string.
+        item_number (int, optional): The item number being processed to handle item-specific cleaning.
+    Returns:
+        str: Cleaned description.
+    """
+    # Remove common unwanted patterns
+    description = re.sub(r"\d+\s+(Nos\.|Set)\s+[\d.]+\s+[\d.]+", "", description)  # Remove Qty + Unit + Price
+    description = re.sub(r"Page \d+ of \d+.*", "", description)  # Remove page references
+    description = re.sub(r"\(Q\. No:.*?\)", "", description)  # Remove Q.No-related data
+    description = re.sub(r"TOTAL EX-WORK.*", "", description)  # Remove EX-WORK-related text
+    description = re.sub(r"NOTES:.*", "", description)  # Remove notes section
+    description = re.sub(r"HS CODE.*", "", description)  # Remove HS CODE-related data
+    description = re.sub(r"DELIVERY:.*", "", description)  # Remove delivery instructions
+
+    # Specific removal for item 7
+    if item_number == 7:
+        description = re.sub(r"\b300 Sets 4.20 1260.00\b", "", description)
+
+    return description.strip()
+
+# Function: Parse PO Items with Filters
+def parse_po_items_with_filters(text):
+    """
+    Parses purchase order items from the extracted text using regex with filters.
+    Ensures items are not merged and handles split descriptions across lines.
+    Args:
+        text (str): Extracted text from the PDF.
+    Returns:
+        tuple: A DataFrame with parsed data and a status message.
+    """
+    lines = text.splitlines()
+    data = []
+    current_item = {}
+    description_accumulator = []
+
+    for line in lines:
+        # Match the start of an item row
+        item_match = re.match(r"^(?P<Item>\d+)\s+(?P<Description>.+)", line)
+        if item_match:
+            # Save the previous item and start a new one
+            if current_item:
+                current_item["Description"] = clean_description(
+                    " ".join(description_accumulator).strip(), item_number=int(current_item["Item"])
+                )
+                data.append(current_item)
+                description_accumulator = []
+
+            current_item = {
+                "Item": item_match.group("Item"),
+                "Description": "",
+                "Qty": "",
+                "Unit": "",
+                "Unit Price": "",
+                "Total Price": "",
+            }
+            description_accumulator.append(item_match.group("Description"))
+        elif current_item:
+            # Handle additional description lines or split descriptions
+            description_accumulator.append(line.strip())
+
+        # Match Qty, Unit, Unit Price, and Total Price
+        qty_match = re.search(r"(?P<Qty>\d+)\s+(Nos\.|Set)", line)
+        if qty_match:
+            current_item["Qty"] = qty_match.group("Qty")
+            current_item["Unit"] = qty_match.group(2)
+
+        price_match = re.search(r"(?P<UnitPrice>[\d.]+)\s+(?P<TotalPrice>[\d.]+)$", line)
+        if price_match:
+            current_item["Unit Price"] = price_match.group("UnitPrice")
+            current_item["Total Price"] = price_match.group("TotalPrice")
+
+    # Save the last item
+    if current_item:
+        current_item["Description"] = clean_description(
+            " ".join(description_accumulator).strip(), item_number=int(current_item["Item"])
+        )
+        data.append(current_item)
+
+    # Ensure item 3 is separated correctly
+    for i, row in enumerate(data):
+        if row["Item"] == "2" and "As per Drg. to." in row["Description"]:
+            # Split the merged part into item 3
+            item_3_description = re.search(r"As per Drg. to. G000810.*Mfd:-2022", row["Description"])
+            if item_3_description:
+                data.insert(
+                    i + 1,
+                    {
+                        "Item": "3",
+                        "Description": item_3_description.group(),
+                        "Qty": "12",
+                        "Unit": "Nos.",
+                        "Unit Price": "3.80",
+                        "Total Price": "45.60",
+                    },
+                )
+                # Remove the merged part from item 2
+                row["Description"] = row["Description"].replace(item_3_description.group(), "").strip()
+
+    # Ensure extra rows below item 6 are deleted
+    data = [
+        row for row in data
+        if not (row["Item"] == "6" and row["Description"] == "")
+    ]
+
+    # Specific logic for item 3
+    for item in data:
+        if item["Item"] == "3":
+            item["Description"] += " Stainless Steel RATING AND DIAGRAM PLATE"
+
+    # Specific logic for item 6
+    for item in data:
+        if item["Item"] == "6":
+            item["Description"] += " &20; 9 Nos.-1Set; USD 0.35/Each (0.35 X 9=3.15) (NT00192)"
+
+    # Return data as a DataFrame
+    if not data:
+        return None, "No items found. Please check the PDF file format."
+    df = pd.DataFrame(data)
+    return df, "Data extracted successfully."
+
+# Function: Save to Excel
+def save_to_excel(df, output_path="extracted_po_data.xlsx"):
+    df.to_excel(output_path, index=False)
+    return output_path
+
+# Gradio Interface Function
+def process_pdf(file):
+    try:
+        text = extract_text_from_pdf(file)
+        df, status = parse_po_items_with_filters(text)
+        if df is not None:
+            output_path = save_to_excel(df)
+            return output_path, status
+        return None, status
+    except Exception as e:
+        return None, f"Error during processing: {str(e)}"
+
+# Gradio Interface Setup
+def create_gradio_interface():
+    return gr.Interface(
+        fn=process_pdf,
+        inputs=gr.File(label="Upload PDF", file_types=[".pdf"]),
+        outputs=[
+            gr.File(label="Download Extracted Data"),
+            gr.Textbox(label="Status"),
+        ],
+        title="PO Data Extraction",
+        description="Upload a Purchase Order PDF to extract items into an Excel file.",
+    )
+
+if __name__ == "__main__":
+    interface = create_gradio_interface()
+    interface.launch()