Reklamator/app/routes/submission.py

"""Submission routes - anonymous feedback submission"""
import threading
import os
from flask import Blueprint, render_template, request, redirect, url_for, flash, abort, current_app
from app.models.product import Product
from app.services.feedback_storage import FeedbackStorageService
from app.services.ai_analyzer import ClaudeAnalyzer
from app.utils.file_validator import validate_file, scan_file_for_viruses


bp = Blueprint('submission', __name__, url_prefix='/submit')


@bp.route('/<product_slug>', methods=['GET'])
def form(product_slug):
    """Display feedback submission form

    Args:
        product_slug: Product submission URL slug

    Returns:
        Rendered submission form template or 404
    """
    # Load product by slug
    product = Product.get_by_slug(product_slug)

    if not product:
        abort(404, description="Product not found")

    # Check if product is archived
    if product.is_archived():
        abort(404, description="This product is no longer accepting feedback")

    return render_template('submission/form.html', product=product)


@bp.route('/<product_slug>', methods=['POST'])
def submit(product_slug):
    """Process feedback submission

    Args:
        product_slug: Product submission URL slug

    Returns:
        Redirect to success page or error page
    """
    # Load product by slug
    product = Product.get_by_slug(product_slug)

    if not product:
        abort(404, description="Product not found")

    # Check if product is archived
    if product.is_archived():
        abort(404, description="This product is no longer accepting feedback")

    # Get form data
    feedback_text = request.form.get('feedback_text', '').strip()

    # Get uploaded files
    uploaded_files = request.files.getlist('files')
    # Filter out empty file inputs
    files = [f for f in uploaded_files if f and f.filename != '']

    # Validation: Must provide either text or files
    if not feedback_text and not files:
        abort(400, description="Please provide either feedback text or attachments")

    # Validation: Maximum 3 files
    if len(files) > 3:
        abort(400, description="Maximum 3 attachments allowed")

    # Validate each file
    for file in files:
        is_valid, error_message = validate_file(file)
        if not is_valid:
            abort(400, description=error_message)

        # Scan for viruses
        is_clean, virus_message = scan_file_for_viruses(file)
        if not is_clean:
            abort(400, description=f"File rejected: {virus_message}")

    # Save feedback
    try:
        feedback = FeedbackStorageService.save_complete_feedback(
            product_id=product.product_id,
            content_text=feedback_text if feedback_text else None,
            files=files if files else None
        )

        # Trigger background analysis (T084, T085)
        if feedback_text:  # Only analyze if there's text content
            _trigger_background_analysis(feedback, feedback_text, product)

        return render_template('submission/success.html',
                             product=product,
                             feedback_id=feedback.feedback_id)

    except Exception as e:
        # Log error
        current_app.logger.error(f"Error saving feedback: {e}")

        return render_template('submission/error.html',
                             product=product,
                             error_message="An error occurred while saving your feedback. Please try again."), 500


def _trigger_background_analysis(feedback, feedback_text, product):
    """Trigger background AI analysis task (T084)

    Args:
        feedback: Feedback instance
        feedback_text: Feedback text content
        product: Product instance
    """
    # Get the current app instance to pass to background thread
    app = current_app._get_current_object()

    # Run analysis in background thread
    thread = threading.Thread(
        target=_analyze_feedback_background,
        args=(app, feedback.product_id, feedback.feedback_id, feedback_text, product.owner_language)
    )
    thread.daemon = True
    thread.start()


def _analyze_feedback_background(app, product_id, feedback_id, feedback_text, target_language):
    """Background task for AI analysis (T086-T088)

    This runs in a separate thread to avoid blocking the submission response.

    Args:
        app: Flask app instance for application context
        product_id: Product ID
        feedback_id: Feedback ID
        feedback_text: Feedback text to analyze
        target_language: Target language for translation
    """
    # Run within Flask application context
    with app.app_context():
        try:
            # Update status to "analyzing" (T086)
            FeedbackStorageService.update_feedback_status_by_id(
                product_id, feedback_id, 'analyzing'
            )

            # Get API key from environment
            api_key = os.getenv('ANTHROPIC_API_KEY')

            if not api_key:
                raise Exception("ANTHROPIC_API_KEY not configured")

            # Initialize analyzer
            analyzer = ClaudeAnalyzer(api_key=api_key)

            # Analyze feedback
            result = analyzer.analyze_feedback(
                feedback_text=feedback_text,
                target_language=target_language,
                product_id=product_id
            )

            # Save analysis results
            FeedbackStorageService.save_analysis(product_id, feedback_id, result)

            # Update status to "analyzed" (T087)
            FeedbackStorageService.update_feedback_status_by_id(
                product_id, feedback_id, 'analyzed'
            )

        except Exception as e:
            # Update status to "analysis_failed" on error (T088)
            FeedbackStorageService.update_feedback_status_by_id(
                product_id, feedback_id, 'analysis_failed'
            )
            # Log error
            print(f"Analysis failed for feedback {feedback_id}: {e}")