2025-12-05 14:42:18 +01:00
|
|
|
fastapi==0.115.0
|
|
|
|
|
uvicorn[standard]==0.32.1
|
|
|
|
|
psycopg2-binary==2.9.10
|
|
|
|
|
pydantic==2.10.3
|
|
|
|
|
pydantic-settings==2.6.1
|
|
|
|
|
python-dotenv==1.0.1
|
|
|
|
|
python-multipart==0.0.17
|
2025-12-06 02:22:01 +01:00
|
|
|
jinja2==3.1.4
|
|
|
|
|
pyjwt==2.9.0
|
|
|
|
|
aiohttp==3.10.10
|
2025-12-07 03:29:54 +01:00
|
|
|
|
|
|
|
|
# AI & Document Processing
|
|
|
|
|
httpx==0.27.2
|
|
|
|
|
PyPDF2==3.0.1
|
2025-12-08 09:15:52 +01:00
|
|
|
pdfplumber==0.11.4
|
2025-12-07 03:29:54 +01:00
|
|
|
pytesseract==0.3.13
|
|
|
|
|
Pillow==11.0.0
|
feat: Implement quick analysis on PDF upload for CVR, document type, and number extraction
- Added `check_invoice_number_exists` method in `EconomicService` to verify invoice numbers in e-conomic journals.
- Introduced `quick_analysis_on_upload` method in `OllamaService` for extracting critical fields from uploaded PDFs, including CVR, document type, and document number.
- Created migration script to add new fields for storing detected CVR, vendor ID, document type, and document number in the `incoming_files` table.
- Developed comprehensive tests for the quick analysis functionality, validating CVR detection, document type identification, and invoice number extraction.
2025-12-09 14:54:33 +01:00
|
|
|
invoice2data==0.4.4
|
|
|
|
|
pyyaml==6.0.2
|