import os import re import psycopg2 from psycopg2 import pool import requests import pandas as pd from datetime import datetime from bs4 import BeautifulSoup from googlesearch import search import gradio as gr import boto3 from botocore.exceptions import NoCredentialsError, PartialCredentialsError import openai from requests.adapters import HTTPAdapter from urllib3.util.retry import Retry import logging # Configuration aws_access_key_id = os.getenv("AWS_ACCESS_KEY_ID", "your-aws-access-key") aws_secret_access_key = os.getenv("AWS_SECRET_ACCESS_KEY", "your-aws-secret-key") region_name = "us-east-1" openai.api_key = os.getenv("OPENAI_API_KEY", "your-openai-api-key") openai.api_base = os.getenv("OPENAI_API_BASE", "https://api.openai.com/v1/") openai_model = "text-davinci-003" db_params = { "user": "your-postgres-user", "password": "your-postgres-password", "host": "your-postgres-host", "port": "your-postgres-port", "dbname": "your-postgres-dbname", "sslmode": "require" } # Initialize AWS SES client ses_client = boto3.client('ses', aws_access_key_id=aws_access_key_id, aws_secret_access_key=aws_secret_access_key, region_name=region_name) # Connection pool for PostgreSQL db_pool = pool.SimpleConnectionPool(1, 10, **db_params) # HTTP session with retry strategy session = requests.Session() retries = Retry(total=5, backoff_factor=1, status_forcelist=[502, 503, 504]) session.mount('https://', HTTPAdapter(max_retries=retries)) # Setup logging logging.basicConfig(level=logging.INFO, filename='app.log', filemode='a', format='%(asctime)s - %(levelname)s - %(message)s') # Initialize database def init_db(): conn = None try: conn = db_pool.getconn() conn.close() logging.info("Successfully connected to the database!") except Exception as e: logging.error(f"Failed to connect to the database: {e}") finally: if conn: db_pool.putconn(conn) init_db() # Fetch the most recent or frequently used template ID def fetch_recent_template_id(): conn = None try: conn = db_pool.getconn() with conn.cursor() as cursor: cursor.execute('SELECT id FROM email_templates ORDER BY last_used DESC LIMIT 1') recent_template_id = cursor.fetchone()[0] return recent_template_id except Exception as e: logging.error(f"Failed to fetch the most recent template: {e}") return None finally: if conn: db_pool.putconn(conn) # Auto-save drafts every few seconds def auto_save_drafts(draft_content): conn = None try: conn = db_pool.getconn() with conn.cursor() as cursor: cursor.execute('INSERT INTO drafts (content, saved_at) VALUES (%s, %s) RETURNING id', (draft_content, datetime.now())) conn.commit() logging.info("Draft saved successfully.") except Exception as e: logging.error(f"Failed to save draft: {e}") finally: if conn: db_pool.putconn(conn) # Auto-restore drafts when user returns def auto_restore_drafts(): conn = None try: conn = db_pool.getconn() with conn.cursor() as cursor: cursor.execute('SELECT content FROM drafts ORDER BY saved_at DESC LIMIT 1') draft_content = cursor.fetchone()[0] logging.info("Draft restored successfully.") return draft_content except Exception as e: logging.error(f"Failed to restore draft: {e}") return "" finally: if conn: db_pool.putconn(conn) # Save each search query automatically def save_search_query(query): conn = None try: conn = db_pool.getconn() with conn.cursor() as cursor: cursor.execute('INSERT INTO search_terms (status, fetched_emails, last_processed_at) VALUES (%s, %s, %s) RETURNING id', ('pending', 0, None)) search_term_id = cursor.fetchone()[0] conn.commit() return search_term_id except Exception as e: logging.error(f"Failed to save search query: {e}") return None finally: if conn: db_pool.putconn(conn) # Fetch unsent emails and auto-sort them by priority or date def fetch_unsent_emails(): conn = None try: conn = db_pool.getconn() with conn.cursor() as cursor: cursor.execute('SELECT * FROM generated_emails WHERE email_sent=0 ORDER BY email_id') unsent_emails = cursor.fetchall() return unsent_emails except Exception as e: logging.error(f"Failed to fetch unsent emails: {e}") return [] finally: if conn: db_pool.putconn(conn) # Enhanced function for tracking progress and sending emails def track_progress_and_send(from_address, reply_to): progress = 0 total_emails = len(fetch_unsent_emails()) for email in fetch_unsent_emails(): send_email_via_aws(email[2], email[3], email[4], from_address, reply_to) progress += 1 update_progress_bar(progress / total_emails) notify_user(f"Sent {progress}/{total_emails} emails.") return "All emails sent successfully." # Function to send emails via AWS SES def send_email_via_aws(to_address, subject, body_html, from_address, reply_to): try: response = ses_client.send_email( Source=from_address, Destination={'ToAddresses': [to_address]}, Message={ 'Subject': {'Data': subject}, 'Body': { 'Html': {'Data': body_html} } }, ReplyToAddresses=[reply_to] ) return response['MessageId'] except (NoCredentialsError, PartialCredentialsError) as e: logging.error(f"AWS credentials error: {e}") return None except Exception as e: logging.error(f"Failed to send email via AWS SES: {e}") return None # Function to update the progress bar def update_progress_bar(progress): # Implement your code to update the progress bar here pass # Function to notify the user with a message def notify_user(message): # Implement your code to notify the user here pass # Function to scrape emails from Google search results def scrape_emails(search_query, num_results): results = [] search_urls = list(search(search_query, num_results=num_results)) for url in search_urls: try: response = session.get(url, timeout=10) response.encoding = 'utf-8' soup = BeautifulSoup(response.text, 'html.parser') emails = find_emails(response.text) for email in emails: results.append((search_query, email, url)) save_lead(search_query, email, url) except Exception as e: logging.error(f"Failed to scrape {url}: {e}") return pd.DataFrame(results, columns=["Search Query", "Email", "URL"]) # ... rest of code ... # Gradio interface with gr.Blocks() as gradio_app: gr.Markdown("# Email Campaign Management System") with gr.Tab("Search Emails"): search_query = gr.Textbox(label="Search Query", placeholder="e.g., 'Potential Customers in Madrid'") num_results = gr.Slider(1, 100, value=10, step=1, label="Number of Results") search_button = gr.Button("Search") results = gr.Dataframe(headers=["Search Query", "Email", "URL"]) search_button.click(lambda query, num_results: scrape_emails(query, num_results), inputs=[search_query, num_results], outputs=[results]) with gr.Tab("Create Email Template"): # ... rest of code ... with gr.Tab("Generate and Send Emails"): # ... rest of code ... with gr.Tab("Bulk Process and Send"): # ... rest of code ... with gr.Tab("Manage Search Queries"): # ... rest of code ... gradio_app.launch()