bolade
864 lines
30 KiB
Python
864 lines
30 KiB
Python
import csv
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import io
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import logging
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import uuid
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from datetime import datetime
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from typing import List
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from database import (
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DBReceipt,
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DBTransaction,
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DBUploadedFile,
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create_db_tables,
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db_dependency,
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)
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from fastapi import FastAPI, File, Form, HTTPException, UploadFile
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from fastapi.middleware.cors import CORSMiddleware
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from schemas import (
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DocumentProcessRequest,
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DocumentProcessResponse,
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DocumentUploadResponse,
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MatchingResponse,
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MatchResponse,
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MatchSpecificRequest,
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Receipt,
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RuleRequest,
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Transaction,
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)
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from services.ai_rules import AIRule
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from services.document_processor import DocumentProcessor
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from services.matching_engine import MatchingEngine
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from sqlalchemy.orm import Session
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create_db_tables()
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logging.basicConfig(
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level=logging.INFO,
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format="%(asctime)s - %(name)s - %(levelname)s - %(message)s",
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handlers=[logging.StreamHandler()],
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)
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logger = logging.getLogger(__name__)
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app = FastAPI(
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title="AI Bookkeeper - Data Science Engine",
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description="AI-powered receipt-to-transaction matching engine. Receives transaction data and provides intelligent matching capabilities.",
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version="1.0.0",
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)
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# CORS middleware
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app.add_middleware(
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CORSMiddleware,
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allow_origins=["*"],
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allow_credentials=True,
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allow_methods=["*"],
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allow_headers=["*"],
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)
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# Initialize DS Engine components
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matching_engine = MatchingEngine()
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document_processor = DocumentProcessor()
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# Helper functions for database operations
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def get_transactions_from_db(
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db: Session, user_id: str = None, categorization_id: str = None
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):
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"""Retrieve transactions from database"""
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query = db.query(DBTransaction)
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if user_id:
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query = query.filter(DBTransaction.user_id == user_id)
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if categorization_id:
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query = query.filter(DBTransaction.categorisation_id == categorization_id)
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return query.all()
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def get_receipt_from_db(db: Session, file_id: str):
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"""Retrieve receipt from database by file_id"""
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return db.query(DBReceipt).filter(DBReceipt.file_id == file_id).first()
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def get_receipts_from_db(db: Session, file_ids: List[str]):
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"""Retrieve multiple receipts from database by file_ids"""
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return db.query(DBReceipt).filter(DBReceipt.file_id.in_(file_ids)).all()
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def get_uploaded_file_from_db(db: Session, file_id: str):
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"""Retrieve uploaded file from database by file_id"""
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return db.query(DBUploadedFile).filter(DBUploadedFile.file_id == file_id).first()
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def get_uploaded_files_from_db(db: Session, file_ids: List[str]):
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"""Retrieve multiple uploaded files from database by file_ids"""
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return db.query(DBUploadedFile).filter(DBUploadedFile.file_id.in_(file_ids)).all()
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@app.get("/", tags=["Health"])
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async def root():
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"""Health check endpoint"""
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return {
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"message": "AI Bookkeeper Data Science Engine is running",
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"version": "1.0.0",
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"status": "healthy",
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}
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# ============================================================================
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# TRANSACTION IMPORT ENDPOINTS
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# ============================================================================
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@app.post("/transactions/import/csv", tags=["Transaction Import"])
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async def import_transactions_csv(
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db: db_dependency,
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file: UploadFile = File(...),
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categorization_id: str = Form(...),
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user_id: str = Form(...),
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):
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"""
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Import transactions from a CSV file (custom bank export format).
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"""
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try:
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content = await file.read()
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decoded = content.decode("utf-8")
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reader = csv.DictReader(io.StringIO(decoded))
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transactions = []
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errors = []
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for idx, row in enumerate(reader):
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try:
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# Use correct headers and strip whitespace
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account_number = row.get("Account Number") or row.get(
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"Account Number ".strip()
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)
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txn_date_raw = row.get("Transaction Date") or row.get(
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"Transaction Date ".strip() or row.get("Date")
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)
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amount_raw = row.get("Amount") or row.get("Amount ".strip())
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payee_name = row.get("Description 2") or row.get(
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"Description 2 ".strip()
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)
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memo = f"{row.get('Account Type', '').strip()} {row.get('Cheque Number', '').strip()} {row.get('Description 1', '').strip()}".strip()
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# Compose ID
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txn_id = f"{account_number}_{idx + 1}"
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# Parse date (try multiple formats)
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txn_date_str = txn_date_raw.strip()
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txn_date = None
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for fmt in ("%m/%d/%y", "%m/%d/%Y"):
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try:
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txn_date = datetime.strptime(txn_date_str, fmt).strftime(
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"%Y-%m-%d"
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)
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break
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except Exception:
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continue
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if not txn_date:
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raise ValueError(f"Could not parse date: {txn_date_str}")
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# Parse amount
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amount = float(amount_raw.replace(",", "").strip())
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# Create database transaction object
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txn_date_obj = datetime.strptime(txn_date, "%Y-%m-%d")
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db_transaction = DBTransaction(
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transaction_id=txn_id,
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amount=amount,
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date=txn_date_obj,
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vendor=payee_name.strip(),
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description=memo,
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categorisation_id=categorization_id,
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user_id=user_id,
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)
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# Add to database
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db.add(db_transaction)
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transactions.append(
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{
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"id": txn_id,
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"txn_date": txn_date,
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"amount": amount,
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"payee_name": payee_name.strip(),
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"memo": memo,
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"categorization_id": categorization_id,
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"user_id": user_id,
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}
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)
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except Exception as e:
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errors.append(f"Row {idx + 1}: {str(e)}")
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# Commit all transactions to database
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db.commit()
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return {
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"imported_count": len(transactions),
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"converted_transactions": transactions,
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"errors": errors,
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"categorization_id": categorization_id,
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"user_id": user_id,
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}
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except Exception as e:
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raise HTTPException(status_code=500, detail=str(e))
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@app.post("/transactions/import/image", tags=["Transaction Import"])
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async def import_transactions_from_image(
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db: db_dependency,
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file: UploadFile = File(...),
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categorization_id: str = Form("image_import"),
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user_id: str = Form("default"),
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):
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"""
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Import transactions from an image (bank statement, credit card statement, etc.) using AI extraction.
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"""
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try:
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# Validate file type
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allowed_types = ["jpg", "jpeg", "png", "gif", "bmp", "pdf"]
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file_extension = file.filename.split(".")[-1].lower()
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if file_extension not in allowed_types:
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raise HTTPException(
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status_code=400,
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detail=f"Unsupported file type. Allowed: {allowed_types}",
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)
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# Read file content
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content = await file.read()
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# Save file to disk
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image_path = await document_processor.save_uploaded_file(content, file.filename)
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# Extract transactions from image (pass file path)
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extraction_result = await document_processor.extract_transactions_from_image(
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image_path
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)
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if not extraction_result.get("extraction_success", False):
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raise HTTPException(
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status_code=500,
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detail=extraction_result.get("error", "Extraction failed"),
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)
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extracted_transactions = extraction_result.get("transactions", [])
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# Store transactions in database
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transactions = []
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for idx, txn in enumerate(extracted_transactions):
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try:
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txn_id = f"img_{file.filename}_{idx + 1}"
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txn_date_raw = txn.get("date")
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amount = txn.get("amount")
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vendor = txn.get("vendor")
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memo = txn.get("memo", "")
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# Parse date to YYYY-MM-DD format
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txn_date = document_processor._parse_date_to_iso(txn_date_raw)
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if not txn_date:
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# Fallback: use current year if parsing fails
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txn_date = f"2024-{txn_date_raw}"
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# Parse date for database
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txn_date_obj = datetime.strptime(txn_date, "%Y-%m-%d")
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# Create database transaction object
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db_transaction = DBTransaction(
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transaction_id=txn_id,
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amount=float(amount),
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date=txn_date_obj,
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vendor=vendor,
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description=memo,
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categorisation_id=categorization_id,
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user_id=user_id,
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)
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# Add to database
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db.add(db_transaction)
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transactions.append(
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{
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"id": txn_id,
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"txn_date": txn_date,
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"amount": amount,
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"payee_name": vendor,
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"memo": memo,
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}
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)
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except Exception as e:
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logger.warning(f"Error processing transaction {idx}: {str(e)}")
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continue
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# Commit all transactions to database
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db.commit()
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return {
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"imported_count": len(transactions),
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"converted_transactions": transactions,
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"errors": [],
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}
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except Exception as e:
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logger.error(f"Error importing transactions from image: {str(e)}")
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raise HTTPException(status_code=500, detail=str(e))
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# ============================================================================
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# DOCUMENT PROCESSING ENDPOINTS
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# ============================================================================
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@app.post(
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"/upload-multiple",
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response_model=List[DocumentUploadResponse],
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tags=["Document Processing"],
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)
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async def upload_multiple_documents(
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files: List[UploadFile] = File(...), db: db_dependency = None
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):
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"""
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Upload multiple receipt images for processing.
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This endpoint accepts multiple image files and returns file IDs
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that can be used with the /process/{file_id} endpoint.
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"""
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try:
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responses = []
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for file in files:
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# Validate file type
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allowed_types = ["jpg", "jpeg", "png", "gif", "bmp", "pdf"]
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file_extension = file.filename.split(".")[-1].lower()
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if file_extension not in allowed_types:
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raise HTTPException(
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status_code=400,
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detail=f"Unsupported file type for {file.filename}. Allowed: {allowed_types}",
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)
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# Generate unique file ID
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file_id = str(uuid.uuid4())
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# Read file content and save to disk
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content = await file.read()
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file_path = await document_processor.save_uploaded_file(
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content, file.filename
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)
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# Create database record for uploaded file
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db_uploaded_file = DBUploadedFile(
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file_id=file_id,
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filename=file.filename,
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file_path=file_path,
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file_type=file_extension,
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upload_date=datetime.now(),
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status="uploaded",
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)
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# Add to database
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db.add(db_uploaded_file)
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responses.append(
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DocumentUploadResponse(
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file_id=file_id,
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filename=file.filename,
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file_type=file_extension,
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upload_date=datetime.now(),
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status="uploaded",
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)
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)
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# Commit all uploaded files to database
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db.commit()
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return responses
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except Exception as e:
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logger.error(f"Error uploading documents: {str(e)}")
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raise HTTPException(status_code=500, detail=str(e))
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@app.post(
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"/process/{file_id}",
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response_model=DocumentProcessResponse,
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tags=["Document Processing"],
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)
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async def process_document(
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file_id: str, request: DocumentProcessRequest, db: db_dependency
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):
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"""
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Process a previously uploaded document to extract receipt information.
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This endpoint uses AI to extract structured data from receipt images,
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including vendor, amount, date, and category information.
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Optionally accepts user_location to guide tax calculations and depreciation
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based on the user's location (format: "State/Province, Country" e.g., "Ontario, Canada").
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"""
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try:
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# Get file info from database
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db_uploaded_file = get_uploaded_file_from_db(db, file_id)
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if not db_uploaded_file:
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raise HTTPException(status_code=404, detail=f"File {file_id} not found")
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# Process the file using the stored file path
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receipt_data = await document_processor.process_file(
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db_uploaded_file.file_path,
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db_uploaded_file.file_type,
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user_location=request.user_location,
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)
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# Parse date for database storage
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receipt_date = None
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if receipt_data.get("date"):
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try:
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receipt_date = datetime.strptime(receipt_data["date"], "%Y-%m-%d")
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except ValueError:
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receipt_date = datetime.now()
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else:
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receipt_date = datetime.now()
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# Create database receipt object
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db_receipt = DBReceipt(
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receipt_id=f"receipt_{file_id}",
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file_id=file_id,
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amount=receipt_data.get("total_amount", 0.0),
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date=receipt_date,
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vendor=receipt_data.get("vendor", ""),
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description=receipt_data.get("description", ""),
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category=receipt_data.get("category", ""),
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tax_amount=receipt_data.get("tax_amount", 0.0),
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confidence=receipt_data.get("confidence", 0.0),
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extraction_success=str(receipt_data.get("extraction_success", False)),
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error_message=receipt_data.get("error"),
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receipt_currency=receipt_data.get("currency"),
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receipt_location=receipt_data.get("location"),
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calculated_tax=receipt_data.get("calculated_tax"),
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is_depreciable=str(receipt_data.get("is_depreciable"))
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if receipt_data.get("is_depreciable") is not None
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else None,
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name_of_asset=receipt_data.get("name_of_asset"),
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cca_rate=receipt_data.get("cca_rate"),
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useful_life=receipt_data.get("useful_life"),
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residual_value=receipt_data.get("residual_value"),
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)
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# Add to database
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db.add(db_receipt)
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db.commit()
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return DocumentProcessResponse(
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file_id=file_id,
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receipt_id=db_receipt.receipt_id,
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extraction_success=receipt_data.get("extraction_success", False),
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vendor=receipt_data.get("vendor", ""),
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description=receipt_data.get("description", ""),
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total_amount=receipt_data.get("total_amount", 0.0),
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tax_amount=receipt_data.get("tax_amount", 0.0),
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date=receipt_data.get("date", ""),
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category=receipt_data.get("category", ""),
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confidence=receipt_data.get("confidence", 0.0),
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error=receipt_data.get("error", None),
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receipt_currency=receipt_data.get("currency"),
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receipt_location=receipt_data.get("location"),
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calculated_tax=receipt_data.get("calculated_tax"),
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is_depreciable=receipt_data.get("is_depreciable"),
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name_of_asset=receipt_data.get("name_of_asset"),
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cca_rate=receipt_data.get("cca_rate"),
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useful_life=receipt_data.get("useful_life"),
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residual_value=receipt_data.get("residual_value"),
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)
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except Exception as e:
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logger.error(f"Error processing document {request.file_id}: {str(e)}")
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raise HTTPException(status_code=500, detail=str(e))
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@app.post("/match-specific", response_model=MatchingResponse, tags=["AI Matching"])
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async def match_specific_receipts(request: MatchSpecificRequest, db: db_dependency):
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"""
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Match specific receipts against imported transactions.
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This endpoint takes a request with receipt file IDs and categorization ID,
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and matches them against the currently imported transactions using AI-powered matching logic.
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"""
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try:
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file_ids = request.file_ids
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categorization_id = request.categorization_id
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logger.info(
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f"Starting match-specific for file IDs: {file_ids}, categorization_id: {categorization_id}"
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)
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# Get transactions from database
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db_transactions = get_transactions_from_db(
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db, categorization_id=categorization_id
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)
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if not db_transactions:
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logger.warning("No transactions found in database")
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raise HTTPException(
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status_code=400,
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detail="No transactions found. Please upload CSV first.",
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)
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logger.info(f"Found {len(db_transactions)} transactions in database")
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# Convert database transactions to Transaction objects
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transactions = []
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for db_txn in db_transactions:
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try:
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transaction = Transaction(
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id=db_txn.transaction_id,
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transaction_date=db_txn.date,
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amount=db_txn.amount,
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vendor=db_txn.vendor,
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notes=db_txn.description or "",
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)
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transactions.append(transaction)
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except Exception as e:
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logger.warning(
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f"Error converting transaction {db_txn.transaction_id}: {str(e)}"
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)
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continue
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logger.info(f"Converted {len(transactions)} transactions")
|
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|
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# Get receipts for the specified file IDs from database
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db_receipts = get_receipts_from_db(db, file_ids)
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receipts = []
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missing_files = []
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for file_id in file_ids:
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# Find the corresponding database receipt
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db_receipt = next((r for r in db_receipts if r.file_id == file_id), None)
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|
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if db_receipt:
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try:
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receipt = Receipt(
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id=db_receipt.receipt_id,
|
|
receipt_date=db_receipt.date,
|
|
amount=db_receipt.amount,
|
|
vendor=db_receipt.vendor,
|
|
category=db_receipt.category or "Other",
|
|
description=db_receipt.description or "",
|
|
tax=db_receipt.tax_amount or 0.0,
|
|
file_name=db_receipt.file_id,
|
|
upload_date=datetime.now(),
|
|
)
|
|
receipts.append(receipt)
|
|
logger.info(f"Successfully loaded receipt for file_id: {file_id}")
|
|
except Exception as e:
|
|
logger.error(
|
|
f"Error creating receipt object for {file_id}: {str(e)}"
|
|
)
|
|
missing_files.append(file_id)
|
|
else:
|
|
logger.warning(f"Receipt {file_id} not found in database")
|
|
missing_files.append(file_id)
|
|
|
|
logger.info(f"Found {len(receipts)} receipts, {len(missing_files)} missing")
|
|
|
|
if missing_files:
|
|
logger.warning(f"Missing files: {missing_files}")
|
|
|
|
if not receipts:
|
|
logger.warning("No valid receipts found")
|
|
raise HTTPException(
|
|
status_code=400,
|
|
detail="No valid receipts found for matching.",
|
|
)
|
|
|
|
# Perform matching
|
|
logger.info(
|
|
f"Starting matching with {len(receipts)} receipts and {len(transactions)} transactions"
|
|
)
|
|
|
|
# Extract user location from user_tax_info if provided
|
|
user_location = request.user_location # Default/fallback
|
|
if request.user_tax_info:
|
|
# Use state_code from user_tax_info (e.g., "ON", "QC", "BC")
|
|
user_location = request.user_tax_info.state.state_code
|
|
logger.info(
|
|
f"Using location from user_tax_info: {user_location} ({request.user_tax_info.state.name}, {request.user_tax_info.country.name})"
|
|
)
|
|
else:
|
|
logger.info(f"Using default/provided user_location: {user_location}")
|
|
|
|
try:
|
|
matching_results = matching_engine.process_matching(
|
|
receipts, transactions, user_location=user_location
|
|
)
|
|
logger.info(f"Matching completed, got {len(matching_results)} results")
|
|
|
|
# Convert matching results to response format
|
|
match_responses = []
|
|
for result in matching_results:
|
|
# Get final tax amount from LLM analysis if available, otherwise use receipt's stated tax
|
|
final_tax = result.receipt.tax
|
|
# if result.tax_analysis and "final_tax_amount" in result.tax_analysis:
|
|
# final_tax = result.tax_analysis["final_tax_amount"]
|
|
|
|
match_response = MatchResponse(
|
|
receipt_id=result.receipt.id,
|
|
transaction_id=result.transaction.id
|
|
if result.transaction
|
|
else "no_match",
|
|
confidence_score=result.confidence_score * 100,
|
|
match_reason=result.match_reason,
|
|
receipt_vendor=result.receipt.vendor,
|
|
receipt_amount=result.receipt.amount,
|
|
receipt_description=result.receipt.description,
|
|
receipt_category=result.receipt.category,
|
|
receipt_tax_amount=final_tax,
|
|
transaction_vendor=result.transaction.vendor
|
|
if result.transaction
|
|
else "",
|
|
transaction_amount=result.transaction.amount
|
|
if result.transaction
|
|
else 0.0,
|
|
tax_analysis=result.tax_analysis,
|
|
)
|
|
match_responses.append(match_response)
|
|
|
|
# Calculate statistics
|
|
high_confidence = len(
|
|
[r for r in matching_results if r.confidence_score >= 0.8]
|
|
)
|
|
low_confidence = len(
|
|
[r for r in matching_results if r.confidence_score < 0.5]
|
|
)
|
|
avg_score = (
|
|
sum(r.confidence_score for r in matching_results)
|
|
/ len(matching_results)
|
|
if matching_results
|
|
else 0
|
|
)
|
|
|
|
stats = {
|
|
"total": len(match_responses),
|
|
"high_confidence": high_confidence,
|
|
"low_confidence": low_confidence,
|
|
"avg_score": round(avg_score, 2),
|
|
}
|
|
|
|
logger.info(f"Generated stats: {stats}")
|
|
logger.info(
|
|
f"Match-specific completed successfully with {len(match_responses)} matches"
|
|
)
|
|
|
|
return MatchingResponse(matches=match_responses, stats=stats)
|
|
|
|
except Exception as e:
|
|
logger.error(f"Exception in matching section: {str(e)}")
|
|
logger.error(f"Exception type: {type(e)}")
|
|
logger.error(f"Exception args: {e.args}")
|
|
raise HTTPException(
|
|
status_code=500, detail=f"Unexpected matching error: {str(e)}"
|
|
)
|
|
|
|
except HTTPException:
|
|
raise
|
|
except Exception as e:
|
|
logger.error(f"Unexpected error in match_specific_receipts: {str(e)}")
|
|
raise HTTPException(status_code=500, detail=str(e))
|
|
|
|
|
|
# ============================================================================
|
|
# DATABASE QUERY ENDPOINTS
|
|
# ============================================================================
|
|
|
|
|
|
@app.get("/transactions", tags=["Database Queries"])
|
|
async def get_transactions(
|
|
db: db_dependency,
|
|
user_id: str = None,
|
|
categorization_id: str = None,
|
|
limit: int = 100,
|
|
):
|
|
"""
|
|
Get transactions from the database.
|
|
"""
|
|
try:
|
|
transactions = get_transactions_from_db(db, user_id, categorization_id)
|
|
|
|
# Limit results
|
|
transactions = transactions[:limit]
|
|
|
|
# Convert to response format
|
|
result = []
|
|
for txn in transactions:
|
|
result.append(
|
|
{
|
|
"id": txn.transaction_id,
|
|
"amount": txn.amount,
|
|
"date": txn.date.strftime("%Y-%m-%d"),
|
|
"vendor": txn.vendor,
|
|
"description": txn.description,
|
|
"category": txn.category,
|
|
"tax_amount": txn.tax_amount,
|
|
"categorisation_id": txn.categorisation_id,
|
|
"user_id": txn.user_id,
|
|
}
|
|
)
|
|
|
|
return {
|
|
"transactions": result,
|
|
"count": len(result),
|
|
}
|
|
except Exception as e:
|
|
raise HTTPException(status_code=500, detail=str(e))
|
|
|
|
|
|
@app.get("/receipts", tags=["Database Queries"])
|
|
async def get_receipts(db: db_dependency, limit: int = 100):
|
|
"""
|
|
Get receipts from the database.
|
|
"""
|
|
try:
|
|
receipts = db.query(DBReceipt).limit(limit).all()
|
|
|
|
# Convert to response format
|
|
result = []
|
|
for receipt in receipts:
|
|
result.append(
|
|
{
|
|
"id": receipt.receipt_id,
|
|
"file_id": receipt.file_id,
|
|
"amount": receipt.amount,
|
|
"date": receipt.date.strftime("%Y-%m-%d"),
|
|
"vendor": receipt.vendor,
|
|
"description": receipt.description,
|
|
"category": receipt.category,
|
|
"tax_amount": receipt.tax_amount,
|
|
"confidence": receipt.confidence,
|
|
"extraction_success": receipt.extraction_success,
|
|
"error_message": receipt.error_message,
|
|
}
|
|
)
|
|
|
|
return {
|
|
"receipts": result,
|
|
"count": len(result),
|
|
}
|
|
except Exception as e:
|
|
raise HTTPException(status_code=500, detail=str(e))
|
|
|
|
|
|
@app.get("/uploaded-files", tags=["Database Queries"])
|
|
async def get_uploaded_files(db: db_dependency, limit: int = 100):
|
|
"""
|
|
Get uploaded files from the database.
|
|
"""
|
|
try:
|
|
uploaded_files = db.query(DBUploadedFile).limit(limit).all()
|
|
|
|
# Convert to response format
|
|
result = []
|
|
for file in uploaded_files:
|
|
result.append(
|
|
{
|
|
"file_id": file.file_id,
|
|
"filename": file.filename,
|
|
"file_path": file.file_path,
|
|
"file_type": file.file_type,
|
|
"upload_date": file.upload_date.strftime("%Y-%m-%d %H:%M:%S"),
|
|
"status": file.status,
|
|
}
|
|
)
|
|
|
|
return {
|
|
"uploaded_files": result,
|
|
"count": len(result),
|
|
}
|
|
except Exception as e:
|
|
raise HTTPException(status_code=500, detail=str(e))
|
|
|
|
|
|
# ============================================================================
|
|
# RULES MANAGEMENT ENDPOINTS
|
|
# ============================================================================
|
|
|
|
|
|
@app.post("/rules", tags=["AI Rules Management"])
|
|
async def add_rule(request: RuleRequest):
|
|
"""
|
|
Add a new AI rule for transaction matching.
|
|
"""
|
|
try:
|
|
new_rule = AIRule(
|
|
name=request.name,
|
|
condition=request.condition,
|
|
action=request.action,
|
|
source=request.source,
|
|
)
|
|
|
|
matching_engine.rules_engine.rules.append(new_rule)
|
|
|
|
return {"message": f"Rule '{request.name}' added successfully"}
|
|
|
|
except Exception as e:
|
|
raise HTTPException(status_code=500, detail=str(e))
|
|
|
|
|
|
@app.get("/rules", tags=["AI Rules Management"])
|
|
async def get_rules():
|
|
"""
|
|
Get all current AI rules.
|
|
"""
|
|
try:
|
|
rules = []
|
|
for rule in matching_engine.rules_engine.rules:
|
|
rules.append(
|
|
{
|
|
"name": rule.name,
|
|
"condition": rule.condition,
|
|
"action": rule.action,
|
|
"source": rule.source,
|
|
"status": rule.status,
|
|
}
|
|
)
|
|
|
|
return {"rules": rules}
|
|
|
|
except Exception as e:
|
|
raise HTTPException(status_code=500, detail=str(e))
|
|
|
|
|
|
@app.delete("/rules/{rule_name}", tags=["AI Rules Management"])
|
|
async def delete_rule(rule_name: str):
|
|
"""
|
|
Delete an AI rule by name.
|
|
"""
|
|
try:
|
|
rules = matching_engine.rules_engine.rules
|
|
for i, rule in enumerate(rules):
|
|
if rule.name == rule_name:
|
|
del rules[i]
|
|
return {"message": f"Rule '{rule_name}' deleted successfully"}
|
|
|
|
raise HTTPException(status_code=404, detail=f"Rule '{rule_name}' not found")
|
|
|
|
except HTTPException:
|
|
raise
|
|
except Exception as e:
|
|
raise HTTPException(status_code=500, detail=str(e))
|
|
|
|
|
|
# ============================================================================
|
|
# STATISTICS ENDPOINT
|
|
# ============================================================================
|
|
|
|
|
|
@app.get("/stats", tags=["Statistics"])
|
|
async def get_stats(db: db_dependency):
|
|
"""
|
|
Get system statistics.
|
|
"""
|
|
try:
|
|
# Count transactions, receipts, and uploaded files from database
|
|
total_transactions = db.query(DBTransaction).count()
|
|
total_receipts = db.query(DBReceipt).count()
|
|
total_uploaded_files = db.query(DBUploadedFile).count()
|
|
|
|
return {
|
|
"total_transactions": total_transactions,
|
|
"total_receipts": total_receipts,
|
|
"total_uploaded_files": total_uploaded_files,
|
|
"rules_count": len(matching_engine.rules_engine.rules),
|
|
}
|
|
|
|
except Exception as e:
|
|
raise HTTPException(status_code=500, detail=str(e))
|
|
|
|
|
|
if __name__ == "__main__":
|
|
import uvicorn
|
|
|
|
uvicorn.run(app, host="0.0.0.0", port=8654)
|