937 lines
28 KiB
Python
937 lines
28 KiB
Python
"""
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FastAPI Application Factory
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Creates and configures the FastAPI application.
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"""
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from __future__ import annotations
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import logging
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from contextlib import asynccontextmanager
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from pathlib import Path
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from typing import TYPE_CHECKING
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from fastapi import FastAPI
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from fastapi.middleware.cors import CORSMiddleware
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from fastapi.staticfiles import StaticFiles
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from fastapi.responses import HTMLResponse
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from .config import AppConfig, default_config
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from inference.web.services import InferenceService
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# Public API imports
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from inference.web.api.v1.public import (
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create_inference_router,
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create_async_router,
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set_async_service,
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create_labeling_router,
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)
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# Async processing imports
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from inference.data.async_request_db import AsyncRequestDB
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from inference.web.workers.async_queue import AsyncTaskQueue
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from inference.web.services.async_processing import AsyncProcessingService
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from inference.web.dependencies import init_dependencies
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from inference.web.core.rate_limiter import RateLimiter
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# Admin API imports
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from inference.web.api.v1.admin import (
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create_annotation_router,
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create_augmentation_router,
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create_auth_router,
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create_documents_router,
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create_locks_router,
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create_training_router,
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)
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from inference.web.core.scheduler import start_scheduler, stop_scheduler
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from inference.web.core.autolabel_scheduler import start_autolabel_scheduler, stop_autolabel_scheduler
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# Batch upload imports
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from inference.web.api.v1.batch.routes import router as batch_upload_router
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from inference.web.workers.batch_queue import init_batch_queue, shutdown_batch_queue
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from inference.web.services.batch_upload import BatchUploadService
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from inference.data.admin_db import AdminDB
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if TYPE_CHECKING:
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from collections.abc import AsyncGenerator
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logger = logging.getLogger(__name__)
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def create_app(config: AppConfig | None = None) -> FastAPI:
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"""
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Create and configure FastAPI application.
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Args:
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config: Application configuration. Uses default if not provided.
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Returns:
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Configured FastAPI application
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"""
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config = config or default_config
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# Create model path resolver that reads from database
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def get_active_model_path():
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"""Resolve active model path from database."""
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try:
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db = AdminDB()
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active_model = db.get_active_model_version()
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if active_model and active_model.model_path:
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return active_model.model_path
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except Exception as e:
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logger.warning(f"Failed to get active model from database: {e}")
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return None
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# Create inference service with database model resolver
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inference_service = InferenceService(
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model_config=config.model,
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storage_config=config.storage,
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model_path_resolver=get_active_model_path,
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)
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# Create async processing components
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async_db = AsyncRequestDB()
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rate_limiter = RateLimiter(async_db)
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task_queue = AsyncTaskQueue(
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max_size=config.async_processing.queue_max_size,
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worker_count=config.async_processing.worker_count,
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)
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async_service = AsyncProcessingService(
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inference_service=inference_service,
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db=async_db,
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queue=task_queue,
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rate_limiter=rate_limiter,
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async_config=config.async_processing,
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storage_config=config.storage,
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)
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# Initialize dependencies for FastAPI
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init_dependencies(async_db, rate_limiter)
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set_async_service(async_service)
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@asynccontextmanager
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async def lifespan(app: FastAPI) -> AsyncGenerator[None, None]:
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"""Application lifespan manager."""
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logger.info("Starting Invoice Inference API...")
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# Initialize database tables
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try:
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async_db.create_tables()
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logger.info("Async database tables ready")
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except Exception as e:
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logger.error(f"Failed to initialize async database: {e}")
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# Initialize inference service on startup
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try:
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inference_service.initialize()
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logger.info("Inference service ready")
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except Exception as e:
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logger.error(f"Failed to initialize inference service: {e}")
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# Continue anyway - service will retry on first request
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# Start async processing service
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try:
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async_service.start()
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logger.info("Async processing service started")
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except Exception as e:
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logger.error(f"Failed to start async processing: {e}")
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# Start batch upload queue
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try:
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admin_db = AdminDB()
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batch_service = BatchUploadService(admin_db)
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init_batch_queue(batch_service)
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logger.info("Batch upload queue started")
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except Exception as e:
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logger.error(f"Failed to start batch upload queue: {e}")
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# Start training scheduler
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try:
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start_scheduler()
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logger.info("Training scheduler started")
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except Exception as e:
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logger.error(f"Failed to start training scheduler: {e}")
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# Start auto-label scheduler
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try:
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start_autolabel_scheduler()
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logger.info("AutoLabel scheduler started")
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except Exception as e:
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logger.error(f"Failed to start autolabel scheduler: {e}")
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yield
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logger.info("Shutting down Invoice Inference API...")
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# Stop auto-label scheduler
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try:
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stop_autolabel_scheduler()
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logger.info("AutoLabel scheduler stopped")
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except Exception as e:
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logger.error(f"Error stopping autolabel scheduler: {e}")
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# Stop training scheduler
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try:
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stop_scheduler()
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logger.info("Training scheduler stopped")
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except Exception as e:
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logger.error(f"Error stopping training scheduler: {e}")
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# Stop batch upload queue
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try:
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shutdown_batch_queue()
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logger.info("Batch upload queue stopped")
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except Exception as e:
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logger.error(f"Error stopping batch upload queue: {e}")
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# Stop async processing service
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try:
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async_service.stop(timeout=30.0)
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logger.info("Async processing service stopped")
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except Exception as e:
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logger.error(f"Error stopping async service: {e}")
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# Close database connection
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try:
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async_db.close()
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logger.info("Database connection closed")
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except Exception as e:
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logger.error(f"Error closing database: {e}")
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# Create FastAPI app
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# Store inference service for access by routes (e.g., model reload)
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# This will be set after app creation
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app = FastAPI(
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title="Invoice Field Extraction API",
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description="""
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REST API for extracting fields from Swedish invoices.
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## Features
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- YOLO-based field detection
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- OCR text extraction
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- Field normalization and validation
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- Visualization of detections
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## Supported Fields
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- InvoiceNumber
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- InvoiceDate
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- InvoiceDueDate
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- OCR (reference number)
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- Bankgiro
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- Plusgiro
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- Amount
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- supplier_org_number (Swedish organization number)
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- customer_number
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- payment_line (machine-readable payment code)
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""",
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version="1.0.0",
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lifespan=lifespan,
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)
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# Add 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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# Mount static files for results
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config.storage.result_dir.mkdir(parents=True, exist_ok=True)
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app.mount(
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"/static/results",
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StaticFiles(directory=str(config.storage.result_dir)),
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name="results",
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)
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# Include public API routes
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inference_router = create_inference_router(inference_service, config.storage)
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app.include_router(inference_router)
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async_router = create_async_router(config.storage.allowed_extensions)
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app.include_router(async_router, prefix="/api/v1")
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labeling_router = create_labeling_router(inference_service, config.storage)
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app.include_router(labeling_router)
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# Include admin API routes
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auth_router = create_auth_router()
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app.include_router(auth_router, prefix="/api/v1")
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documents_router = create_documents_router(config.storage)
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app.include_router(documents_router, prefix="/api/v1")
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locks_router = create_locks_router()
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app.include_router(locks_router, prefix="/api/v1")
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annotation_router = create_annotation_router()
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app.include_router(annotation_router, prefix="/api/v1")
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training_router = create_training_router()
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app.include_router(training_router, prefix="/api/v1")
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augmentation_router = create_augmentation_router()
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app.include_router(augmentation_router, prefix="/api/v1/admin")
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# Include batch upload routes
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app.include_router(batch_upload_router)
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# Store inference service in app state for access by routes
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app.state.inference_service = inference_service
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# Root endpoint - serve HTML UI
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@app.get("/", response_class=HTMLResponse)
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async def root() -> str:
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"""Serve the web UI."""
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return get_html_ui()
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return app
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def get_html_ui() -> str:
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"""Generate HTML UI for the web application."""
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return """
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<!DOCTYPE html>
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<html lang="en">
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<head>
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<meta charset="UTF-8">
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<meta name="viewport" content="width=device-width, initial-scale=1.0">
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<title>Invoice Field Extraction</title>
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<style>
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* {
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box-sizing: border-box;
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margin: 0;
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padding: 0;
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}
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body {
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font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, sans-serif;
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background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
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min-height: 100vh;
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padding: 20px;
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}
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.container {
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max-width: 1200px;
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margin: 0 auto;
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}
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header {
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text-align: center;
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color: white;
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margin-bottom: 30px;
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}
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header h1 {
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font-size: 2.5rem;
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margin-bottom: 10px;
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}
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header p {
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opacity: 0.9;
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font-size: 1.1rem;
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}
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.main-content {
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display: flex;
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flex-direction: column;
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gap: 20px;
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}
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.card {
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background: white;
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border-radius: 16px;
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padding: 24px;
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box-shadow: 0 10px 40px rgba(0,0,0,0.2);
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}
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.card h2 {
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color: #333;
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margin-bottom: 20px;
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font-size: 1.3rem;
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display: flex;
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align-items: center;
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gap: 10px;
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}
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.upload-card {
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display: flex;
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align-items: center;
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gap: 20px;
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flex-wrap: wrap;
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}
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.upload-card h2 {
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margin-bottom: 0;
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white-space: nowrap;
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}
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.upload-area {
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border: 2px dashed #ddd;
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border-radius: 10px;
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padding: 15px 25px;
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text-align: center;
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cursor: pointer;
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transition: all 0.3s;
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background: #fafafa;
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flex: 1;
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min-width: 200px;
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}
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.upload-area:hover, .upload-area.dragover {
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border-color: #667eea;
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background: #f0f4ff;
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}
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.upload-area.has-file {
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border-color: #10b981;
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background: #ecfdf5;
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}
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.upload-icon {
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font-size: 24px;
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display: inline;
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margin-right: 8px;
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}
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.upload-area p {
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color: #666;
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margin: 0;
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display: inline;
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}
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.upload-area small {
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color: #999;
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display: block;
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margin-top: 5px;
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}
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#file-input {
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display: none;
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}
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.file-name {
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margin-top: 15px;
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padding: 10px 15px;
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background: #e0f2fe;
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border-radius: 8px;
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color: #0369a1;
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font-weight: 500;
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}
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.btn {
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display: inline-block;
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padding: 12px 24px;
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border: none;
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border-radius: 10px;
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font-size: 0.9rem;
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font-weight: 600;
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cursor: pointer;
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transition: all 0.3s;
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text-transform: uppercase;
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letter-spacing: 0.5px;
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}
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.btn-primary {
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background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
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color: white;
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}
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.btn-primary:hover:not(:disabled) {
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transform: translateY(-2px);
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box-shadow: 0 5px 20px rgba(102, 126, 234, 0.4);
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}
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.btn-primary:disabled {
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opacity: 0.6;
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cursor: not-allowed;
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}
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.loading {
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display: none;
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align-items: center;
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gap: 10px;
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}
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.loading.active {
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display: flex;
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}
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.spinner {
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width: 24px;
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height: 24px;
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border: 3px solid #f3f3f3;
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border-top: 3px solid #667eea;
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border-radius: 50%;
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animation: spin 1s linear infinite;
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}
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@keyframes spin {
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0% { transform: rotate(0deg); }
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100% { transform: rotate(360deg); }
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}
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.results {
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display: none;
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}
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.results.active {
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display: block;
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}
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.result-header {
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display: flex;
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justify-content: space-between;
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align-items: center;
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margin-bottom: 20px;
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padding-bottom: 15px;
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border-bottom: 2px solid #eee;
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}
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.result-status {
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padding: 6px 12px;
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border-radius: 20px;
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font-size: 0.85rem;
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font-weight: 600;
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}
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.result-status.success {
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background: #dcfce7;
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color: #166534;
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}
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.result-status.partial {
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background: #fef3c7;
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color: #92400e;
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}
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.result-status.error {
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background: #fee2e2;
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color: #991b1b;
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}
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.fields-grid {
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display: grid;
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grid-template-columns: repeat(auto-fit, minmax(200px, 1fr));
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gap: 12px;
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}
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.field-item {
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padding: 12px;
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background: #f8fafc;
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border-radius: 10px;
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border-left: 4px solid #667eea;
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}
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.field-item label {
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display: block;
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font-size: 0.75rem;
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color: #64748b;
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text-transform: uppercase;
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letter-spacing: 0.5px;
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margin-bottom: 4px;
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}
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.field-item .value {
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font-size: 1.1rem;
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font-weight: 600;
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color: #1e293b;
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}
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.field-item .confidence {
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font-size: 0.75rem;
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color: #10b981;
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margin-top: 2px;
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}
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.visualization {
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margin-top: 20px;
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}
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.visualization img {
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width: 100%;
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border-radius: 12px;
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box-shadow: 0 4px 20px rgba(0,0,0,0.1);
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}
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.processing-time {
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text-align: center;
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color: #64748b;
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font-size: 0.9rem;
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margin-top: 15px;
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}
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.cross-validation {
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background: #f8fafc;
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border: 1px solid #e2e8f0;
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border-radius: 10px;
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padding: 15px;
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margin-top: 20px;
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}
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.cross-validation h3 {
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margin: 0 0 10px 0;
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color: #334155;
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font-size: 1rem;
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}
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|
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.cv-status {
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font-weight: 600;
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padding: 8px 12px;
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border-radius: 6px;
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margin-bottom: 10px;
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display: inline-block;
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}
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.cv-status.valid {
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background: #dcfce7;
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color: #166534;
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}
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.cv-status.invalid {
|
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background: #fef3c7;
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color: #92400e;
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}
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.cv-details {
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display: flex;
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flex-wrap: wrap;
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|
gap: 8px;
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margin-top: 10px;
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}
|
|
|
|
.cv-item {
|
|
background: white;
|
|
border: 1px solid #e2e8f0;
|
|
border-radius: 6px;
|
|
padding: 6px 12px;
|
|
font-size: 0.85rem;
|
|
display: flex;
|
|
align-items: center;
|
|
gap: 6px;
|
|
}
|
|
|
|
.cv-item.match {
|
|
border-color: #86efac;
|
|
background: #f0fdf4;
|
|
}
|
|
|
|
.cv-item.mismatch {
|
|
border-color: #fca5a5;
|
|
background: #fef2f2;
|
|
}
|
|
|
|
.cv-icon {
|
|
font-weight: bold;
|
|
}
|
|
|
|
.cv-item.match .cv-icon {
|
|
color: #16a34a;
|
|
}
|
|
|
|
.cv-item.mismatch .cv-icon {
|
|
color: #dc2626;
|
|
}
|
|
|
|
.cv-summary {
|
|
margin-top: 10px;
|
|
font-size: 0.8rem;
|
|
color: #64748b;
|
|
}
|
|
|
|
.error-message {
|
|
background: #fee2e2;
|
|
color: #991b1b;
|
|
padding: 15px;
|
|
border-radius: 10px;
|
|
margin-top: 15px;
|
|
}
|
|
|
|
footer {
|
|
text-align: center;
|
|
color: white;
|
|
opacity: 0.8;
|
|
margin-top: 30px;
|
|
font-size: 0.9rem;
|
|
}
|
|
</style>
|
|
</head>
|
|
<body>
|
|
<div class="container">
|
|
<header>
|
|
<h1>📄 Invoice Field Extraction</h1>
|
|
<p>Upload a Swedish invoice (PDF or image) to extract fields automatically</p>
|
|
</header>
|
|
|
|
<div class="main-content">
|
|
<!-- Upload Section - Compact -->
|
|
<div class="card upload-card">
|
|
<h2>📤 Upload</h2>
|
|
|
|
<div class="upload-area" id="upload-area">
|
|
<span class="upload-icon">📁</span>
|
|
<p>Drag & drop or <strong>click to browse</strong></p>
|
|
<small>PDF, PNG, JPG (max 50MB)</small>
|
|
<input type="file" id="file-input" accept=".pdf,.png,.jpg,.jpeg">
|
|
</div>
|
|
|
|
<div class="file-name" id="file-name" style="display: none;"></div>
|
|
|
|
<button class="btn btn-primary" id="submit-btn" disabled>
|
|
🚀 Extract
|
|
</button>
|
|
|
|
<div class="loading" id="loading">
|
|
<div class="spinner"></div>
|
|
<p>Processing...</p>
|
|
</div>
|
|
</div>
|
|
|
|
<!-- Results Section - Full Width -->
|
|
<div class="card">
|
|
<h2>📊 Extraction Results</h2>
|
|
|
|
<div id="placeholder" style="text-align: center; padding: 30px; color: #999;">
|
|
<div style="font-size: 48px; margin-bottom: 10px;">🔍</div>
|
|
<p>Upload a document to see extraction results</p>
|
|
</div>
|
|
|
|
<div class="results" id="results">
|
|
<div class="result-header">
|
|
<span>Document: <strong id="doc-id"></strong></span>
|
|
<span class="result-status" id="result-status"></span>
|
|
</div>
|
|
|
|
<div class="fields-grid" id="fields-grid"></div>
|
|
|
|
<div class="processing-time" id="processing-time"></div>
|
|
|
|
<div class="cross-validation" id="cross-validation" style="display: none;"></div>
|
|
|
|
<div class="error-message" id="error-message" style="display: none;"></div>
|
|
|
|
<div class="visualization" id="visualization" style="display: none;">
|
|
<h3 style="margin-bottom: 10px; color: #333;">🎯 Detection Visualization</h3>
|
|
<img id="viz-image" src="" alt="Detection visualization">
|
|
</div>
|
|
</div>
|
|
</div>
|
|
</div>
|
|
|
|
<footer>
|
|
<p>Powered by ColaCoder</p>
|
|
</footer>
|
|
</div>
|
|
|
|
<script>
|
|
const uploadArea = document.getElementById('upload-area');
|
|
const fileInput = document.getElementById('file-input');
|
|
const fileName = document.getElementById('file-name');
|
|
const submitBtn = document.getElementById('submit-btn');
|
|
const loading = document.getElementById('loading');
|
|
const placeholder = document.getElementById('placeholder');
|
|
const results = document.getElementById('results');
|
|
|
|
let selectedFile = null;
|
|
|
|
// Drag and drop handlers
|
|
uploadArea.addEventListener('click', () => fileInput.click());
|
|
|
|
uploadArea.addEventListener('dragover', (e) => {
|
|
e.preventDefault();
|
|
uploadArea.classList.add('dragover');
|
|
});
|
|
|
|
uploadArea.addEventListener('dragleave', () => {
|
|
uploadArea.classList.remove('dragover');
|
|
});
|
|
|
|
uploadArea.addEventListener('drop', (e) => {
|
|
e.preventDefault();
|
|
uploadArea.classList.remove('dragover');
|
|
const files = e.dataTransfer.files;
|
|
if (files.length > 0) {
|
|
handleFile(files[0]);
|
|
}
|
|
});
|
|
|
|
fileInput.addEventListener('change', (e) => {
|
|
if (e.target.files.length > 0) {
|
|
handleFile(e.target.files[0]);
|
|
}
|
|
});
|
|
|
|
function handleFile(file) {
|
|
const validTypes = ['.pdf', '.png', '.jpg', '.jpeg'];
|
|
const ext = '.' + file.name.split('.').pop().toLowerCase();
|
|
|
|
if (!validTypes.includes(ext)) {
|
|
alert('Please upload a PDF, PNG, or JPG file.');
|
|
return;
|
|
}
|
|
|
|
selectedFile = file;
|
|
fileName.textContent = `📎 ${file.name}`;
|
|
fileName.style.display = 'block';
|
|
uploadArea.classList.add('has-file');
|
|
submitBtn.disabled = false;
|
|
}
|
|
|
|
submitBtn.addEventListener('click', async () => {
|
|
if (!selectedFile) return;
|
|
|
|
// Show loading
|
|
submitBtn.disabled = true;
|
|
loading.classList.add('active');
|
|
placeholder.style.display = 'none';
|
|
results.classList.remove('active');
|
|
|
|
try {
|
|
const formData = new FormData();
|
|
formData.append('file', selectedFile);
|
|
|
|
const response = await fetch('/api/v1/infer', {
|
|
method: 'POST',
|
|
body: formData,
|
|
});
|
|
|
|
const data = await response.json();
|
|
|
|
if (!response.ok) {
|
|
throw new Error(data.detail || 'Processing failed');
|
|
}
|
|
|
|
displayResults(data);
|
|
|
|
} catch (error) {
|
|
console.error('Error:', error);
|
|
document.getElementById('error-message').textContent = error.message;
|
|
document.getElementById('error-message').style.display = 'block';
|
|
results.classList.add('active');
|
|
} finally {
|
|
loading.classList.remove('active');
|
|
submitBtn.disabled = false;
|
|
}
|
|
});
|
|
|
|
function displayResults(data) {
|
|
const result = data.result;
|
|
|
|
// Document ID
|
|
document.getElementById('doc-id').textContent = result.document_id;
|
|
|
|
// Status
|
|
const statusEl = document.getElementById('result-status');
|
|
statusEl.textContent = result.success ? 'Success' : 'Partial';
|
|
statusEl.className = 'result-status ' + (result.success ? 'success' : 'partial');
|
|
|
|
// Fields
|
|
const fieldsGrid = document.getElementById('fields-grid');
|
|
fieldsGrid.innerHTML = '';
|
|
|
|
const fieldOrder = [
|
|
'InvoiceNumber', 'InvoiceDate', 'InvoiceDueDate', 'OCR',
|
|
'Amount', 'Bankgiro', 'Plusgiro',
|
|
'supplier_org_number', 'customer_number', 'payment_line'
|
|
];
|
|
|
|
fieldOrder.forEach(field => {
|
|
const value = result.fields[field];
|
|
const confidence = result.confidence[field];
|
|
|
|
if (value !== null && value !== undefined) {
|
|
const fieldDiv = document.createElement('div');
|
|
fieldDiv.className = 'field-item';
|
|
fieldDiv.innerHTML = `
|
|
<label>${formatFieldName(field)}</label>
|
|
<div class="value">${value}</div>
|
|
${confidence ? `<div class="confidence">✓ ${(confidence * 100).toFixed(1)}% confident</div>` : ''}
|
|
`;
|
|
fieldsGrid.appendChild(fieldDiv);
|
|
}
|
|
});
|
|
|
|
// Processing time
|
|
document.getElementById('processing-time').textContent =
|
|
`⏱️ Processed in ${result.processing_time_ms.toFixed(0)}ms`;
|
|
|
|
// Cross-validation results
|
|
const cvDiv = document.getElementById('cross-validation');
|
|
if (result.cross_validation) {
|
|
const cv = result.cross_validation;
|
|
let cvHtml = '<h3>🔍 Cross-Validation (Payment Line)</h3>';
|
|
cvHtml += `<div class="cv-status ${cv.is_valid ? 'valid' : 'invalid'}">`;
|
|
cvHtml += cv.is_valid ? '✅ Valid' : '⚠️ Mismatch Detected';
|
|
cvHtml += '</div>';
|
|
|
|
cvHtml += '<div class="cv-details">';
|
|
if (cv.payment_line_ocr) {
|
|
const matchIcon = cv.ocr_match === true ? '✓' : (cv.ocr_match === false ? '✗' : '—');
|
|
cvHtml += `<div class="cv-item ${cv.ocr_match === true ? 'match' : (cv.ocr_match === false ? 'mismatch' : '')}">`;
|
|
cvHtml += `<span class="cv-icon">${matchIcon}</span> OCR: ${cv.payment_line_ocr}</div>`;
|
|
}
|
|
if (cv.payment_line_amount) {
|
|
const matchIcon = cv.amount_match === true ? '✓' : (cv.amount_match === false ? '✗' : '—');
|
|
cvHtml += `<div class="cv-item ${cv.amount_match === true ? 'match' : (cv.amount_match === false ? 'mismatch' : '')}">`;
|
|
cvHtml += `<span class="cv-icon">${matchIcon}</span> Amount: ${cv.payment_line_amount}</div>`;
|
|
}
|
|
if (cv.payment_line_account) {
|
|
const accountType = cv.payment_line_account_type === 'bankgiro' ? 'Bankgiro' : 'Plusgiro';
|
|
const matchField = cv.payment_line_account_type === 'bankgiro' ? cv.bankgiro_match : cv.plusgiro_match;
|
|
const matchIcon = matchField === true ? '✓' : (matchField === false ? '✗' : '—');
|
|
cvHtml += `<div class="cv-item ${matchField === true ? 'match' : (matchField === false ? 'mismatch' : '')}">`;
|
|
cvHtml += `<span class="cv-icon">${matchIcon}</span> ${accountType}: ${cv.payment_line_account}</div>`;
|
|
}
|
|
cvHtml += '</div>';
|
|
|
|
if (cv.details && cv.details.length > 0) {
|
|
cvHtml += '<div class="cv-summary">' + cv.details[cv.details.length - 1] + '</div>';
|
|
}
|
|
|
|
cvDiv.innerHTML = cvHtml;
|
|
cvDiv.style.display = 'block';
|
|
} else {
|
|
cvDiv.style.display = 'none';
|
|
}
|
|
|
|
// Visualization
|
|
if (result.visualization_url) {
|
|
const vizDiv = document.getElementById('visualization');
|
|
const vizImg = document.getElementById('viz-image');
|
|
vizImg.src = result.visualization_url;
|
|
vizDiv.style.display = 'block';
|
|
}
|
|
|
|
// Errors
|
|
if (result.errors && result.errors.length > 0) {
|
|
document.getElementById('error-message').textContent = result.errors.join(', ');
|
|
document.getElementById('error-message').style.display = 'block';
|
|
} else {
|
|
document.getElementById('error-message').style.display = 'none';
|
|
}
|
|
|
|
results.classList.add('active');
|
|
}
|
|
|
|
function formatFieldName(name) {
|
|
const nameMap = {
|
|
'InvoiceNumber': 'Invoice Number',
|
|
'InvoiceDate': 'Invoice Date',
|
|
'InvoiceDueDate': 'Due Date',
|
|
'OCR': 'OCR Reference',
|
|
'Amount': 'Amount',
|
|
'Bankgiro': 'Bankgiro',
|
|
'Plusgiro': 'Plusgiro',
|
|
'supplier_org_number': 'Supplier Org Number',
|
|
'customer_number': 'Customer Number',
|
|
'payment_line': 'Payment Line'
|
|
};
|
|
return nameMap[name] || name.replace(/([A-Z])/g, ' $1').replace(/_/g, ' ').trim();
|
|
}
|
|
</script>
|
|
</body>
|
|
</html>
|
|
"""
|