Automated PDF Invoice Sorter – Folder Vendor

Task: Create a complete, production‑ready Python automation script that scans a directory of PDF invoices, extracts key information, and sorts each invoice into a vendor‑specific folder. The solution must be robust, well‑documented, and ready to run on a typical Windows/macOS/Linux environment.

Exact Requirements:

1. Core Functionality

   • Recursively scan a user‑specified input folder for PDF files.
   • For each PDF, extract the following fields:
     • Vendor/Company Name
     • Invoice Number
     • Invoice Date (ISO YYYY‑MM‑DD)
     • Total Amount (numeric, with currency symbol if present)
   • If the PDF is image‑based, fall back to OCR using pytesseract (assume Tesseract is installed).
   • Use pdfplumber (or PyPDF2 if you prefer) for text extraction; prefer the method that yields the highest confidence.

2. Sorting Logic

   • Create an output folder structure: //.
   • Rename each invoice file to the format YYYYMMDD_InvoiceNumber_VendorName.pdf.
   • Move the renamed file into the corresponding vendor folder.

3. Logging & Reporting

   • Generate a detailed log file (invoice_sorter.log) with timestamps, processed file names, extracted fields, and any errors or warnings.
   • Produce a CSV summary (invoice_summary.csv) containing one row per processed invoice with columns: OriginalFilePath, NewFilePath, Vendor, InvoiceNumber, InvoiceDate, TotalAmount, ExtractionMethod, Status.

4. Configuration

   • Accept all parameters via a single YAML configuration file (config.yaml) with sections for:
     • input_folder
     • output_folder
     • log_level (e.g., INFO, DEBUG)
     • ocr_language (default “eng”)
     • field_patterns (regular expressions for vendor, invoice number, date, amount)
   • Provide a command‑line interface (python invoice_sorter.py --config config.yaml) that validates the config and prints a helpful usage message if required fields are missing.

5. Error Handling

   • Gracefully handle corrupted PDFs, missing fields, or OCR failures.
   • For any invoice where required fields cannot be extracted, move the file to an unprocessed subfolder and log the reason.

6. Code Quality

   • Use type hints throughout.
   • Include a module‑level docstring describing purpose, usage, and dependencies.
   • Follow PEP 8 style; include # noqa: E501 where necessary.
   • Implement logging with the standard logging library, respecting the log_level from the config.

7. Packaging

   • Provide a requirements.txt listing exact versions of all third‑party libraries.
   • Include a concise README.md with:
     • Installation steps (virtual environment creation, pip install -r requirements.txt).
     • Tesseract installation guidance for each OS.
     • Example config.yaml.
     • How to run the script and interpret the output.

Expected Output Format:

When you respond, deliver the following files in plain text, each clearly labeled with a markdown code fence and the appropriate filename extension:

1. invoice_sorter.py – the full Python script.
2. config.yaml – a sample configuration file with placeholder values and comments.
3. requirements.txt – list of dependencies.
4. README.md – installation and usage guide.

Each file should be presented as:

# invoice_sorter.py

# config.yaml

# requirements.txt

# README.md

Make sure the script runs without modification after installing the listed requirements and setting up Tesseract. Do not include any explanatory text outside of the file sections.