import os import json import time import queue import requests import logging from flask import Blueprint, request, Response from dotenv import load_dotenv from src.api_consumers.review_analysis import ReviewAnalyzer from src.helpers.processWords import NgramAnalysis from src.helpers.processImage import CreateDocumentPPT from src.api_consumers.openai_client import OpenAIClient from .sentenceFinder import search from .imageAnalyzer import analyzePattern from .asinSourcer import getAsinFromUrl from .images_url_sourcer import get_images_url from .proposal_ppt import ProposalPPT from .proposal_content import ProposalContent # Configurar logging logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s') logger = logging.getLogger(__name__) load_dotenv() event_queue = queue.Queue() def event_handler(message): event_queue.put(message) proposalController = Blueprint('proposalController', __name__) @proposalController.route('/form-notification', methods=['POST']) def formReadyNotification(): logger.info('Received form notification request') try: data = request.json logger.info(f'Request payload: Company Name: {data.get("companyName")}, Token: {data.get("formToken")}') # Procesar la notificación y agregarla a la cola de eventos event_handler({ "event": 'form', "companyName": data['companyName'], "token": data['formToken'] }) # Enviar la notificación a otro servicio response = requests.post( os.getenv('AGENCIA_URL') + 'api/v1/notifications/store', headers={'Content-Type': 'application/json'}, json={ "type": 'form', "companyName": data['companyName'], "token": data['formToken'] } ) logger.info(f'Sent notification to Agencia, response status: {response.status_code}') return "Notification Sent!" except Exception as e: logger.error(f"Error in form notification: {str(e)}") return "Error sending notification", 500 @proposalController.route('/proposal', methods=['POST']) def createProposal(): logger.info('Received proposal creation request') try: # Validación inicial de la solicitud if not request.json: logger.error("No JSON payload in request") return {"error": "Request payload must be JSON"}, 400 data = request.json required_fields = [ "competitorLink", "companyName", "titleKeywords", "formToken", "productTitle", "productDescription", "buyerDescription", "diffFactor", "competitorsFeatures", "listing_image", "aplus_content" ] # Validar que los campos obligatorios estén presentes missing_fields = [field for field in required_fields if field not in data] if missing_fields: logger.error(f"Missing required fields: {missing_fields}") return {"error": f"Missing required fields: {', '.join(missing_fields)}"}, 400 logger.info( f'Request payload: Competitor Link: {data.get("competitorLink")}, Company Name: {data.get("companyName")}' ) urls = data['competitorLink'].split(',') if not urls: logger.error("Competitor Link is invalid or empty") return {"error": "Competitor Link is invalid or empty"}, 400 keywords = data['titleKeywords'].split(',') proposal_file_name = f"{data['companyName']}_{data['formToken']}" logger.info(f"Processing ASIN from URL: {urls[0]}") asin = getAsinFromUrl(urls[0]) logger.info(f"Analyzing reviews for ASIN: {asin}") reviewAnalyzer = ReviewAnalyzer(asin) try: bestReviews, worstReviews = reviewAnalyzer.analyze_reviews() except KeyError as e: logger.error(f"KeyError during review analysis: {str(e)}") return {"error": f"Review data missing key: {str(e)}"}, 400 except Exception as e: logger.error(f"Error during review analysis: {str(e)}") return {"error": "Failed to analyze reviews"}, 500 logger.info(f"Best Reviews: {len(bestReviews)}, Worst Reviews: {len(worstReviews)}") # Procesar palabras clave try: processWords = NgramAnalysis(bestReviews) bestMonograms = processWords.extract_common_words_across_all_texts() bestBigrams = processWords.extract_common_bigrams_across_all_texts() bestTrigrams = processWords.extract_common_trigrams_across_all_texts() wordsArray = processWords.extract_words_from_dataFrames((bestBigrams, bestTrigrams), nro=5) if worstReviews: processWords = NgramAnalysis(worstReviews) worstMonograms = processWords.extract_common_words_across_all_texts() worstBigrams = processWords.extract_common_bigrams_across_all_texts() worstTrigrams = processWords.extract_common_trigrams_across_all_texts() logger.info("Worst reviews processed") except Exception as e: logger.error(f"Error processing reviews or generating word clouds: {str(e)}") return {"error": "Error processing reviews or generating word clouds"}, 500 # Generar WordClouds try: logger.info("Generating WordClouds") processImage = CreateDocumentPPT() positiveWordCloud = processImage.add_wordcloud_to_slide(bestMonograms) if worstReviews: negativeWordCloud = processImage.add_wordcloud_to_slide(worstMonograms) except Exception as e: logger.error(f"Error generating WordClouds: {str(e)}") return {"error": "Failed to generate WordClouds"}, 500 # Crear contenido de la propuesta try: logger.info("Generating proposal content") proposal_content = ProposalContent( OpenAIClient(), data['productTitle'], data['model'], data['set'], data['props'], data['brandVision'], data['brandCreationReason'], "Technical" if data['productApproach'] else "Benefit" ) proposal_content.build_general_context( data['productTitle'], data['productDescription'], data['buyerDescription'], data['diffFactor'], data['competitorsFeatures'], ) except Exception as e: logger.error(f"Error generating proposal content: {str(e)}") return {"error": "Failed to generate proposal content"}, 500 # Crear PPT try: logger.info("Creating Proposal PPT") proposal_ppt = ProposalPPT( proposal_file_name, positiveWordCloud, get_images_url(data['productTitle']), (bestMonograms, bestBigrams, bestTrigrams), negativeWordCloud if 'negativeWordCloud' in locals() else None, (worstMonograms, worstBigrams, worstTrigrams) if 'worstMonograms' in locals() else None, proposal_content.generate_main_image_text() if int(data['listing_image']) else None, proposal_content.generate_main_image() if int(data['listing_image']) else None, proposal_content.generate_lifestyle_image_text() if int(data['listing_image']) else None, proposal_content.generate_lifestyle_image() if int(data['listing_image']) else None, proposal_content.generate_infographic_image_text() if int(data['listing_image']) else None, proposal_content.generate_infographic_image() if int(data['listing_image']) else None, proposal_content.generate_a_plus_content_text() if data['aplus_content'] != '0' else None, proposal_content.generate_listing_video_text() if int(data['listing_video']) else None, proposal_content.generate_premium_a_plus_content_text() if data['aplus_content'] != '0' else None, proposal_content.generate_premium_a_plus_video_content_text() if data['selected_premium'].find( 'video') != -1 else None, proposal_content.generate_sponsored_ads_video_text() if int(data['sba_video']) else None, proposal_content.generate_brand_story_text() if int(data['brand_story']) else None ) proposal_ppt.generate_ppt() except Exception as e: logger.error(f"Error creating proposal PPT: {str(e)}") return {"error": "Failed to create proposal PPT"}, 500 # Enviar notificaciones try: logger.info("Sending proposal notifications to Agencia") response_notification = requests.post( os.getenv('AGENCIA_URL') + 'api/v1/notifications/store', headers={'Content-Type': 'application/json'}, json={ "type": 'proposal', "companyName": data['companyName'], "token": data['formToken'] } ) logger.info(f'Sent proposal notification, response status: {response_notification.status_code}') response_status = requests.post( os.getenv('AGENCIA_URL') + 'api/v1/update-proposal-status', headers={'Content-Type': 'application/json'}, json={'token': data['formToken']} ) logger.info(f'Updated proposal status, response status: {response_status.status_code}') except requests.RequestException as e: logger.error(f"Error sending notifications: {str(e)}") return {"error": "Failed to send notifications"}, 500 logger.info(f"Proposal created successfully for {data['companyName']} with token {data['formToken']}") return {"message": "Proposal created successfully"} except Exception as e: logger.error(f"Unexpected error: {str(e)}") return {"error": "An unexpected error occurred", "details": str(e)}, 500 def stream_events(): try: while True: # Wait for an event message message = event_queue.get(block=False) yield f"data: {json.dumps(message)}\n\n" except queue.Empty: # Send a comment as a heartbeat yield ':keepalive\n\n' except GeneratorExit: logger.info("Stream was closed by the client") @proposalController.route('/proposal-notification') def proposalNotification(): logger.info('Started streaming events') return Response( stream_events(), mimetype='text/event-stream', headers={'Cache-Control': 'no-cache'} )