Update bhel.py

bhel.py

@@ -1,110 +1,83 @@
 import pdfplumber
 import pandas as pd
 import re
-import gradio as gr
 
-def extract_data(pdf_file):
-    """
-    Extract data from the uploaded PDF for dynamic ranges (e.g., 10 to n).
-    """
-    data = []
-    columns = ["SI No", "Material Description", "Unit", "Quantity", "Dely Qty", "Dely Date", "Unit Rate", "Value"]
-
-    start_si = 10  # Start from SI No 10
-    end_si = None  # Dynamically detect the end SI No
-
-    with pdfplumber.open(pdf_file) as pdf:
+# 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:
-            full_text = page.extract_text()  # Get the text content for the page
-            lines = full_text.splitlines() if full_text else []
-
-            for line in lines:
-                try:
-                    # Parse the first column for SI No
-                    si_no_match = re.match(r"^\s*(\d+)\s", line)
-                    if not si_no_match:
-                        continue
-
-                    si_no = int(si_no_match.group(1))
-                    # Dynamically set the end SI No if higher SI Nos are found
-                    if end_si is None or si_no > end_si:
-                        end_si = si_no
-
-                    if si_no < start_si:
-                        continue  # Skip rows below the start SI No
-
-                    # Extract Material Description and details dynamically
-                    material_desc = extract_material_description(full_text, si_no)
-
-                    # Extract remaining fields
-                    parts = line.split()
-                    unit = parts[3]
-                    quantity = int(parts[4])
-                    dely_qty = int(parts[5])
-                    dely_date = parts[6]
-                    unit_rate = float(parts[7])
-                    value = float(parts[8])
-
-                    # Append row data
-                    data.append([si_no, material_desc, unit, quantity, dely_qty, dely_date, unit_rate, value])
-
-                except (ValueError, IndexError):
-                    # Skip invalid rows or rows with missing data
-                    continue
+            text += page.extract_text()
+    return text
 
-    # Convert data to DataFrame and save as Excel
-    df = pd.DataFrame(data, columns=columns)
-    excel_path = "/tmp/Extracted_PO_Data_Dynamic.xlsx"
-    df.to_excel(excel_path, index=False)
-    return excel_path
-
-def extract_material_description(full_text, si_no):
+# Function: Parse PO Items
+def parse_po_items(text):
     """
-    Extract Material Description, including Material Number, HSN Code, and IGST, using unique patterns.
+    Parses purchase order items from the extracted text.
+    Handles split descriptions across lines and filters unwanted text.
     """
-    material_desc = ""
-
-    # Match the specific SI No row to extract details
-    si_no_pattern = rf"{si_no}\s+(BPS\s+\d+).*?Material\s+Number:\s+(\d+)"
-    match = re.search(si_no_pattern, full_text, re.DOTALL)
-    if match:
-        bps_code = match.group(1)
-        material_number = match.group(2)
-        material_desc += f"{bps_code}\nMaterial Number: {material_number}\n"
-
-    # Extract HSN Code
-    hsn_code_match = re.search(r"HSN\s+Code:\s*(\d+)", full_text)
-    if hsn_code_match:
-        hsn_code = hsn_code_match.group(1)
-        material_desc += f"HSN Code: {hsn_code}\n"
-    else:
-        material_desc += "HSN Code: Not Found\n"
-
-    # Extract IGST
-    igst_match = re.search(r"IGST\s*:\s*(\d+)\s*%", full_text)
-    if igst_match:
-        igst = igst_match.group(1)
-        material_desc += f"IGST: {igst} %"
-    else:
-        material_desc += "IGST: Not Found"
-
-    return material_desc.strip()
-
-# Gradio Interface
-def gradio_interface(pdf_file):
-    """
-    Interface function for Gradio to process the PDF and return the Excel file.
-    """
-    return extract_data(pdf_file.name)
-
-# Define Gradio interface
-interface = gr.Interface(
-    fn=gradio_interface,
-    inputs=gr.File(label="Upload PDF"),
-    outputs=gr.File(label="Download Extracted Excel"),
-    title="Dynamic BHEL PO Data Extractor",
-    description="Upload a PDF to extract accurate Material Numbers and related data dynamically into an Excel file."
-)
-
-if __name__ == "__main__":
-    interface.launch()
+    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"] = " ".join(description_accumulator).strip()
+                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"] = " ".join(description_accumulator).strip()
+        data.append(current_item)
+
+    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="bhel_extracted_data.xlsx"):
+    df.to_excel(output_path, index=False)
+    return output_path
+
+# Main function to process PDF
+def process_pdf(file):
+    try:
+        text = extract_text_from_pdf(file)
+        df, status = parse_po_items(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)}"