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330 lines
14 KiB
330 lines
14 KiB
import requests |
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import random |
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import time |
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import logging |
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import os |
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import json |
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from datetime import datetime, timedelta, timezone |
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from openai import OpenAI |
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from urllib.parse import quote |
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from requests.packages.urllib3.util.retry import Retry |
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from requests.adapters import HTTPAdapter |
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import praw |
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from foodie_config import ( |
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AUTHORS, RECIPE_KEYWORDS, PROMO_KEYWORDS, HOME_KEYWORDS, PRODUCT_KEYWORDS, |
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SUMMARY_PERSONA_PROMPTS, CATEGORIES, CTAS, get_clean_source_name, |
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REDDIT_CLIENT_ID, REDDIT_CLIENT_SECRET, REDDIT_USER_AGENT, LIGHT_TASK_MODEL |
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) |
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from foodie_utils import ( |
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load_json_file, save_json_file, get_image, generate_image_query, |
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upload_image_to_wp, determine_paragraph_count, insert_link_naturally, |
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summarize_with_gpt4o, generate_category_from_summary, post_to_wp, |
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prepare_post_data, select_best_author, smart_image_and_filter, get_flickr_image_via_ddg |
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) |
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from foodie_hooks import get_dynamic_hook, select_best_cta |
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LOG_FILE = "/home/shane/foodie_automator/foodie_automator_reddit.log" |
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LOG_PRUNE_DAYS = 30 |
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def setup_logging(): |
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if os.path.exists(LOG_FILE): |
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with open(LOG_FILE, 'r') as f: |
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lines = f.readlines() |
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cutoff = datetime.now(timezone.utc) - timedelta(days=LOG_PRUNE_DAYS) |
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pruned_lines = [] |
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for line in lines: |
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try: |
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timestamp = datetime.strptime(line[:19], '%Y-%m-%d %H:%M:%S').replace(tzinfo=timezone.utc) |
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if timestamp > cutoff: |
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pruned_lines.append(line) |
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except ValueError: |
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logging.warning(f"Skipping malformed log line: {line.strip()[:50]}...") |
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continue |
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with open(LOG_FILE, 'w') as f: |
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f.writelines(pruned_lines) |
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logging.basicConfig( |
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filename=LOG_FILE, |
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level=logging.INFO, |
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format="%(asctime)s - %(levelname)s - %(message)s" |
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) |
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logging.getLogger("requests").setLevel(logging.WARNING) |
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logging.getLogger("prawcore").setLevel(logging.WARNING) |
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console_handler = logging.StreamHandler() |
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console_handler.setFormatter(logging.Formatter('%(asctime)s - %(levelname)s - %(message)s')) |
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logging.getLogger().addHandler(console_handler) |
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logging.info("Logging initialized for foodie_automator_reddit.py") |
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setup_logging() |
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POSTED_TITLES_FILE = '/home/shane/foodie_automator/posted_reddit_titles.json' |
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USED_IMAGES_FILE = '/home/shane/foodie_automator/used_images.json' |
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EXPIRATION_HOURS = 24 |
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IMAGE_EXPIRATION_DAYS = 7 |
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posted_titles_data = load_json_file(POSTED_TITLES_FILE, EXPIRATION_HOURS) |
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posted_titles = set(entry["title"] for entry in posted_titles_data if "title" in entry) |
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used_images_data = load_json_file(USED_IMAGES_FILE, IMAGE_EXPIRATION_DAYS) |
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used_images = set(entry["title"] for entry in used_images_data if "title" in entry) |
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client = OpenAI(api_key="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") |
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def is_interesting_reddit(title, summary, upvotes, comment_count, top_comments): |
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try: |
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content = f"Title: {title}\n\nContent: {summary}" |
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if top_comments: |
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content += f"\n\nTop Comments:\n{'\n'.join(top_comments)}" |
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response = client.chat.completions.create( |
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model=LIGHT_TASK_MODEL, |
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messages=[ |
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{"role": "system", "content": ( |
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"Rate this Reddit post from 0-10 based on rarity, buzzworthiness, and engagement potential for food lovers, covering food topics (skip recipes). " |
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"Score 8-10 for rare, highly shareable ideas (e.g., unique dishes or restaurant trends). " |
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"Score 5-7 for fresh, engaging updates with broad appeal. Score below 5 for common or unremarkable content. " |
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"Consider comments for added context (e.g., specific locations or unique details). " |
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"Return only a number." |
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)}, |
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{"role": "user", "content": content} |
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], |
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max_tokens=5 |
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) |
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base_score = int(response.choices[0].message.content.strip()) if response.choices[0].message.content.strip().isdigit() else 0 |
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engagement_boost = 0 |
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if upvotes >= 500: |
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engagement_boost += 3 |
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elif upvotes >= 100: |
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engagement_boost += 2 |
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elif upvotes >= 50: |
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engagement_boost += 1 |
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if comment_count >= 100: |
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engagement_boost += 2 |
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elif comment_count >= 20: |
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engagement_boost += 1 |
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final_score = min(base_score + engagement_boost, 10) |
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logging.info(f"Reddit Interest Score: {final_score} (base: {base_score}, upvotes: {upvotes}, comments: {comment_count}, top_comments: {len(top_comments)}) for '{title}'") |
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print(f"Interest Score for '{title[:50]}...': {final_score} (base: {base_score}, upvotes: {upvotes}, comments: {comment_count})") |
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return final_score |
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except Exception as e: |
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logging.error(f"Reddit interestingness scoring failed: {e}") |
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print(f"Reddit Interest Error: {e}") |
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return 0 |
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def get_top_comments(post_url, reddit, limit=3): |
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try: |
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submission = reddit.submission(url=post_url) |
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submission.comments.replace_more(limit=0) |
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submission.comment_sort = 'top' |
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top_comments = [comment.body for comment in submission.comments[:limit] if not comment.body.startswith('[deleted]')] |
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logging.info(f"Fetched {len(top_comments)} top comments for {post_url}") |
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return top_comments |
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except Exception as e: |
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logging.error(f"Failed to fetch comments for {post_url}: {e}") |
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return [] |
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def fetch_reddit_posts(): |
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reddit = praw.Reddit( |
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client_id=REDDIT_CLIENT_ID, |
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client_secret=REDDIT_CLIENT_SECRET, |
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user_agent=REDDIT_USER_AGENT |
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) |
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feeds = ['FoodPorn', 'restaurant', 'FoodIndustry', 'food'] |
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articles = [] |
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cutoff_date = datetime.now(timezone.utc) - timedelta(hours=EXPIRATION_HOURS) |
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logging.info(f"Starting fetch with cutoff date: {cutoff_date}") |
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for subreddit_name in feeds: |
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try: |
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subreddit = reddit.subreddit(subreddit_name) |
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for submission in subreddit.top(time_filter='day', limit=100): |
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pub_date = datetime.fromtimestamp(submission.created_utc, tz=timezone.utc) |
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if pub_date < cutoff_date: |
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logging.info(f"Skipping old post: {submission.title} (Published: {pub_date})") |
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continue |
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articles.append({ |
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"title": submission.title, |
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"link": f"https://www.reddit.com{submission.permalink}", |
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"summary": submission.selftext, |
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"feed_title": get_clean_source_name(subreddit_name), |
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"pub_date": pub_date, |
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"upvotes": submission.score, |
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"comment_count": submission.num_comments |
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}) |
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logging.info(f"Fetched {len(articles)} posts from r/{subreddit_name}") |
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except Exception as e: |
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logging.error(f"Failed to fetch Reddit feed r/{subreddit_name}: {e}") |
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logging.info(f"Total Reddit posts fetched: {len(articles)}") |
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return articles |
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def curate_from_reddit(): |
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articles = fetch_reddit_posts() |
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if not articles: |
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print("No Reddit posts available") |
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logging.info("No Reddit posts available") |
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return None, None, None |
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# Sort by upvotes descending |
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articles.sort(key=lambda x: x["upvotes"], reverse=True) |
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reddit = praw.Reddit( |
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client_id=REDDIT_CLIENT_ID, |
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client_secret=REDDIT_CLIENT_SECRET, |
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user_agent=REDDIT_USER_AGENT |
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) |
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attempts = 0 |
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max_attempts = 10 |
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while attempts < max_attempts and articles: |
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article = articles.pop(0) # Take highest-upvote post |
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title = article["title"] |
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link = article["link"] |
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summary = article["summary"] |
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source_name = "Reddit" |
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original_source = '<a href="https://www.reddit.com/">Reddit</a>' |
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if title in posted_titles: |
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print(f"Skipping already posted post: {title}") |
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logging.info(f"Skipping already posted post: {title}") |
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attempts += 1 |
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continue |
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print(f"Trying Reddit Post: {title} from {source_name}") |
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logging.info(f"Trying Reddit Post: {title} from {source_name}") |
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image_query, relevance_keywords, skip = smart_image_and_filter(title, summary) |
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if skip or any(keyword in title.lower() or keyword in summary.lower() for keyword in RECIPE_KEYWORDS + ["homemade"]): |
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print(f"Skipping filtered Reddit post: {title}") |
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logging.info(f"Skipping filtered Reddit post: {title}") |
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attempts += 1 |
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continue |
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top_comments = get_top_comments(link, reddit, limit=3) |
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interest_score = is_interesting_reddit( |
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title, |
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summary, |
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article["upvotes"], |
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article["comment_count"], |
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top_comments |
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) |
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logging.info(f"Interest Score: {interest_score} for '{title}'") |
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if interest_score < 6: |
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print(f"Reddit Interest Too Low: {interest_score}") |
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logging.info(f"Reddit Interest Too Low: {interest_score}") |
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attempts += 1 |
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continue |
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num_paragraphs = determine_paragraph_count(interest_score) |
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extra_prompt = ( |
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f"Generate exactly {num_paragraphs} paragraphs. " |
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f"FOCUS: Summarize ONLY the provided content, explicitly mentioning '{title}' and sticking to its specific topic and details. " |
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"Incorporate relevant insights from these top comments if available: {', '.join(top_comments) if top_comments else 'None'}. " |
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"Do NOT introduce unrelated concepts unless in the content or comments. " |
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"If brief, expand on the core idea with relevant context about its appeal or significance." |
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) |
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content_to_summarize = f"{title}\n\n{summary}" |
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if top_comments: |
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content_to_summarize += f"\n\nTop Comments:\n{'\n'.join(top_comments)}" |
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final_summary = summarize_with_gpt4o( |
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content_to_summarize, |
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source_name, |
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link, |
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interest_score=interest_score, |
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extra_prompt=extra_prompt |
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) |
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if not final_summary: |
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logging.info(f"Summary failed for '{title}'") |
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attempts += 1 |
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continue |
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final_summary = insert_link_naturally(final_summary, source_name, link) |
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post_data, author, category, image_url, image_source, uploader, pixabay_url = prepare_post_data(final_summary, title) |
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if not post_data: |
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attempts += 1 |
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continue |
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image_url, image_source, uploader, page_url = get_flickr_image_via_ddg(image_query, relevance_keywords) |
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if not image_url: |
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image_url, image_source, uploader, page_url = get_image(image_query) |
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hook = get_dynamic_hook(post_data["title"]).strip() |
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cta = select_best_cta(post_data["title"], final_summary, post_url=None) |
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post_data["content"] = f"{final_summary}\n\n{cta}" |
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post_id, post_url = post_to_wp( |
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post_data=post_data, |
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category=category, |
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link=link, |
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author=author, |
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image_url=image_url, |
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original_source=original_source, |
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image_source=image_source, |
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uploader=uploader, |
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pixabay_url=pixabay_url, |
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interest_score=interest_score |
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) |
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if post_id: |
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cta = select_best_cta(post_data["title"], final_summary, post_url=post_url) |
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post_data["content"] = f"{final_summary}\n\n{cta}" |
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post_to_wp( |
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post_data=post_data, |
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category=category, |
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link=link, |
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author=author, |
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image_url=image_url, |
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original_source=original_source, |
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image_source=image_source, |
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uploader=uploader, |
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pixabay_url=pixabay_url, |
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interest_score=interest_score, |
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post_id=post_id |
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) |
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timestamp = datetime.now(timezone.utc).isoformat() |
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save_json_file(POSTED_TITLES_FILE, title, timestamp) |
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posted_titles.add(title) |
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logging.info(f"Successfully saved '{title}' to {POSTED_TITLES_FILE} with timestamp {timestamp}") |
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if image_url: |
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save_json_file(USED_IMAGES_FILE, image_url, timestamp) |
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used_images.add(image_url) |
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logging.info(f"Saved image '{image_url}' to {USED_IMAGES_FILE} with timestamp {timestamp}") |
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print(f"***** SUCCESS: Posted '{post_data['title']}' (ID: {post_id}) from Reddit *****") |
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print(f"Actual post URL: {post_url}") |
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logging.info(f"***** SUCCESS: Posted '{post_data['title']}' (ID: {post_id}) from Reddit *****") |
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logging.info(f"Actual post URL: {post_url}") |
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return post_data, category, random.randint(0, 1800) |
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attempts += 1 |
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logging.info(f"WP posting failed for '{post_data['title']}'") |
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print("No interesting Reddit post found after attempts") |
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logging.info("No interesting Reddit post found after attempts") |
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return None, None, random.randint(600, 1800) |
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def run_reddit_automator(): |
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print(f"{datetime.now(timezone.utc)} - INFO - ***** Reddit Automator Launched *****") |
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logging.info("***** Reddit Automator Launched *****") |
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post_data, category, sleep_time = curate_from_reddit() |
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if not post_data: |
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print(f"No postable Reddit article found - sleeping for {sleep_time} seconds") |
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logging.info(f"No postable Reddit article found - sleeping for {sleep_time} seconds") |
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else: |
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print(f"Completed Reddit run with sleep time: {sleep_time} seconds") |
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logging.info(f"Completed Reddit run with sleep time: {sleep_time} seconds") |
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print(f"Sleeping for {sleep_time}s") |
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time.sleep(sleep_time) |
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return post_data, category, sleep_time |
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if __name__ == "__main__": |
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run_reddit_automator() |