Initial import
This commit is contained in:
root
259
app.py
Normal file
259
app.py
Normal file
@@ -0,0 +1,259 @@
|
||||
from fastapi import FastAPI, UploadFile, HTTPException, Body
|
||||
from PIL import Image
|
||||
import pytesseract
|
||||
from doctr.models import ocr_predictor
|
||||
from doctr.io import DocumentFile
|
||||
from PyPDF2 import PdfReader
|
||||
import camelot
|
||||
import spacy
|
||||
import logging
|
||||
import io
|
||||
from logging.handlers import RotatingFileHandler
|
||||
import re
|
||||
|
||||
LOG_PATH = "/var/log/automation-service.log"
|
||||
|
||||
file_handler = RotatingFileHandler(
|
||||
LOG_PATH,
|
||||
maxBytes=10*1024*1024,
|
||||
backupCount=5,
|
||||
encoding="utf-8"
|
||||
)
|
||||
file_handler.setFormatter(logging.Formatter(
|
||||
"%(asctime)s - %(levelname)s - %(name)s - %(message)s"
|
||||
))
|
||||
|
||||
# Configure root logger explicitly
|
||||
root = logging.getLogger()
|
||||
root.setLevel(logging.INFO)
|
||||
root.addHandler(file_handler)
|
||||
root.addHandler(logging.StreamHandler())
|
||||
|
||||
# Use root logger for your app
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
app = FastAPI()
|
||||
logger.info("Loading models...")
|
||||
|
||||
nlp = spacy.load("en_core_web_sm")
|
||||
predictor = ocr_predictor(pretrained=True)
|
||||
|
||||
logger.info("Models loaded successfully.")
|
||||
|
||||
# =============================
|
||||
# 🧠 Smart OCR
|
||||
# =============================
|
||||
@app.post("/ocr")
|
||||
async def ocr(file: UploadFile):
|
||||
logger.info(f"Received OCR request: {file.filename}")
|
||||
try:
|
||||
file_data = await file.read()
|
||||
ext = file.filename.lower()
|
||||
|
||||
# --------- PDF with native text ---------
|
||||
if ext.endswith(".pdf"):
|
||||
logger.info("PDF detected → Extracting native text first")
|
||||
reader = PdfReader(io.BytesIO(file_data))
|
||||
direct_text = "".join(
|
||||
page.extract_text() or "" for page in reader.pages
|
||||
)
|
||||
|
||||
if direct_text.strip():
|
||||
logger.info("Native PDF text found → No OCR needed")
|
||||
return {"ocr_text": direct_text}
|
||||
|
||||
# -------- Fallback: scanned PDF OCR --------
|
||||
logger.info("No native text → PDF treated as scanned → OCR")
|
||||
from pdf2image import convert_from_bytes
|
||||
images = convert_from_bytes(file_data)
|
||||
text = ""
|
||||
for i, img in enumerate(images):
|
||||
logger.info(f"OCR page {i+1}/{len(images)}")
|
||||
text += pytesseract.image_to_string(img) + "\n"
|
||||
|
||||
return {"ocr_text": text}
|
||||
|
||||
# --------- Image file OCR ---------
|
||||
logger.info("Image detected → Running OCR")
|
||||
img = Image.open(io.BytesIO(file_data))
|
||||
text = pytesseract.image_to_string(img)
|
||||
return {"ocr_text": text}
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"OCR failed: {e}", exc_info=True)
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
# =============================
|
||||
# 🧱 Structure / Layout
|
||||
# =============================
|
||||
@app.post("/structure")
|
||||
async def structure(file: UploadFile):
|
||||
logger.info(f"Received structure request: {file.filename}")
|
||||
try:
|
||||
file_data = await file.read()
|
||||
ext = file.filename.lower()
|
||||
|
||||
if ext.endswith(".pdf"):
|
||||
doc = DocumentFile.from_pdf(file_data)
|
||||
logger.info(f"Structure prediction on PDF ({len(doc)} pages)")
|
||||
else:
|
||||
img = Image.open(io.BytesIO(file_data)).convert("RGB")
|
||||
doc = DocumentFile.from_images([img])
|
||||
logger.info("Structure prediction on image")
|
||||
|
||||
res = predictor(doc)
|
||||
return {"structure": str(res)}
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Structure extraction failed: {e}", exc_info=True)
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
# =============================
|
||||
# 📊 Tables extraction (PDF only)
|
||||
# =============================
|
||||
@app.post("/tables")
|
||||
async def tables(file: UploadFile):
|
||||
logger.info(f"Received table extraction request: {file.filename}")
|
||||
try:
|
||||
file_data = await file.read()
|
||||
buffer = io.BytesIO(file_data)
|
||||
|
||||
tables = camelot.read_pdf(buffer)
|
||||
logger.info(f"Found {len(tables)} tables")
|
||||
return {"tables": [t.df.to_dict() for t in tables]}
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Table extraction failed: {e}", exc_info=True)
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
def safe_search(pattern, text, default=None, group_index=1, context=""):
|
||||
"""Recherche sécurisée avec logging en cas d'absence de correspondance."""
|
||||
m = re.search(pattern, text, re.I | re.S)
|
||||
if not m:
|
||||
logger.warning("Pattern not found for %s: %s", context, pattern)
|
||||
return default
|
||||
try:
|
||||
return m.group(group_index).strip()
|
||||
except IndexError:
|
||||
logger.warning("Group index %d not found for %s: %s", group_index, context, pattern)
|
||||
return default
|
||||
|
||||
def section(text, start, end=None):
|
||||
"""Extract a block of text between two headings, safely."""
|
||||
pattern_start = re.escape(start)
|
||||
if end:
|
||||
pattern_end = re.escape(end)
|
||||
reg = re.compile(pattern_start + r"(.*?)" + pattern_end, re.S | re.I)
|
||||
else:
|
||||
reg = re.compile(pattern_start + r"(.*)", re.S | re.I)
|
||||
m = reg.search(text)
|
||||
if not m:
|
||||
logger.warning("Section not found: start='%s', end='%s'", start, end)
|
||||
return ""
|
||||
return m.group(1).strip()
|
||||
|
||||
def extract_field(text, label, default=None):
|
||||
"""Extract a line of the form 'Label: value', safely."""
|
||||
pattern = rf"{re.escape(label)}\s*:?[\s]+([^\n]+)"
|
||||
return safe_search(pattern, text, default=default, context=f"field '{label}'")
|
||||
|
||||
def extract_report_metadata(text):
|
||||
logger.info("Starting metadata extraction, text length=%d", len(text))
|
||||
|
||||
try:
|
||||
# ----------- SECTIONS -----------
|
||||
order_details = section(text, "Order details", "Weights")
|
||||
invoice_section = section(text, "INVOICE WEIGHTS", "Bales Weighed")
|
||||
landed_section = section(text, "Bales Weighed", "Outturn")
|
||||
loss_section = section(text, "LOSS", "Invoice average")
|
||||
avg_section = section(text, "Invoice average", "Comments")
|
||||
signature_block = section(text, "Signed on")
|
||||
|
||||
# ----------- TOP INFO -----------
|
||||
top_info = {
|
||||
"produced_on": extract_field(text, "Produced On"),
|
||||
"printed_date": extract_field(text, "Printed Date"),
|
||||
"client_reference": extract_field(text, "Client Reference"),
|
||||
"report_number": safe_search(r"(AHK\S+)", text, default="", context="report_number", group_index=1),
|
||||
}
|
||||
|
||||
# ----------- ORDER DETAILS -----------
|
||||
parties = {
|
||||
"client": extract_field(order_details, "Client"),
|
||||
"client_ref_no": extract_field(order_details, "Client Ref No"),
|
||||
"buyer": extract_field(order_details, "Buyer"),
|
||||
"destination": extract_field(order_details, "Destination"),
|
||||
}
|
||||
|
||||
shipment = {
|
||||
"total_bales": extract_field(order_details, "Total Bales"),
|
||||
"vessel": extract_field(order_details, "Vessel"),
|
||||
"voyage_no": extract_field(order_details, "Voy. No"),
|
||||
"bl_no": extract_field(order_details, "B/L No"),
|
||||
"bl_date": extract_field(order_details, "B/L Date"),
|
||||
"growth": extract_field(order_details, "Growth"),
|
||||
"arrival_date": extract_field(order_details, "Arrival Date"),
|
||||
"first_weighing_date": extract_field(order_details, "First date of weighing"),
|
||||
"last_weighing_date": extract_field(order_details, "Last Date of Weighing"),
|
||||
"weighing_method": extract_field(order_details, "Weighing method"),
|
||||
"tare_basis": extract_field(order_details, "Tare"),
|
||||
}
|
||||
|
||||
# ----------- INVOICE SECTION -----------
|
||||
invoice = {
|
||||
"bales": extract_field(invoice_section, "Bales"),
|
||||
"gross": extract_field(invoice_section, "Gross"),
|
||||
"tare": extract_field(invoice_section, "Tare"),
|
||||
"net": extract_field(invoice_section, "Net"),
|
||||
}
|
||||
|
||||
# ----------- LANDED SECTION -----------
|
||||
landed = {
|
||||
"bales": extract_field(landed_section, "Bales"),
|
||||
"gross": extract_field(landed_section, "Gross"),
|
||||
"tare": extract_field(landed_section, "Tare"),
|
||||
"net": extract_field(landed_section, "Net"),
|
||||
}
|
||||
|
||||
# ----------- LOSS SECTION -----------
|
||||
loss = {
|
||||
"kg": extract_field(loss_section, "kg"),
|
||||
"lb": extract_field(loss_section, "lb"),
|
||||
"percent": extract_field(loss_section, "Percentage"),
|
||||
}
|
||||
|
||||
# ----------- AVERAGES SECTION -----------
|
||||
averages = {
|
||||
"invoice_gross_per_bale": extract_field(avg_section, "Invoice average"),
|
||||
"landed_gross_per_bale": extract_field(avg_section, "Landed average"),
|
||||
}
|
||||
|
||||
# ----------- SIGNATURE -----------
|
||||
signature = {
|
||||
"signed_on": extract_field(signature_block, "Signed on"),
|
||||
"signed_by": safe_search(r"\n([A-Za-z ]+)\nClient Services", signature_block, default="", context="signed_by"),
|
||||
"role": "Client Services Coordinator",
|
||||
"company": "Alfred H. Knight International Limited"
|
||||
}
|
||||
|
||||
logger.info("Metadata extraction completed successfully")
|
||||
return {
|
||||
"report": top_info,
|
||||
"parties": parties,
|
||||
"shipment": shipment,
|
||||
"weights": {
|
||||
"invoice": invoice,
|
||||
"landed": landed,
|
||||
"loss": loss,
|
||||
"averages": averages
|
||||
},
|
||||
"signature": signature
|
||||
}
|
||||
|
||||
except Exception as e:
|
||||
logger.exception("Unexpected error during metadata extraction")
|
||||
raise HTTPException(status_code=500, detail=f"Metadata extraction failed: {e}")
|
||||
|
||||
@app.post("/metadata")
|
||||
async def metadata(text: str = Body(..., embed=True)):
|
||||
return extract_report_metadata(text)
|
||||
Reference in New Issue
Block a user