Brand mention monitoring

# brand_mentions.py
# Daily brand-mention sweep with dedupe. Keep `seen` somewhere durable between runs.
# Run with: INSIGHTSOCIAL_API_KEY=isk_live_... python brand_mentions.py
import json
import os
from concurrent.futures import ThreadPoolExecutor
from datetime import date, timedelta
from pathlib import Path

import requests

KEY = os.environ["INSIGHTSOCIAL_API_KEY"]
BASE = "https://api.insightsocial.app/v1"
BRAND = "notion"
MEANING = "Notion, the note-taking and workspace app"  # disambiguates a common word
SEEN_FILE = Path("seen-mentions.json")
YESTERDAY = (date.today() - timedelta(days=1)).isoformat()

SEARCHES = {
    "reddit":    ("reddit/search",          {"max_age_days": 1}),
    "tiktok":    ("tiktok/search",          {"max_age_days": 1}),
    "youtube":   ("youtube/search",         {"max_age_days": 1}),
    "twitter":   ("twitter/search/tweets",  {"max_age_days": 1}),
    "threads":   ("threads/search",         {"start_date": YESTERDAY}),
    "instagram": ("instagram/search/reels", {"max_age_days": 1}),
}

def get(path, **params):
    res = requests.get(f"{BASE}/{path}", params=params,
                       headers={"x-api-key": KEY}, timeout=120)
    return res.json()

def search(platform):
    path, extra = SEARCHES[platform]
    return platform, get(path, query=BRAND, relevance="filter",
                         relevant_to=MEANING, **extra)

# Step 1: six searches in parallel.
with ThreadPoolExecutor(max_workers=6) as pool:
    results = dict(pool.map(search, SEARCHES))

# Step 2: dedupe against earlier runs by post URL.
seen = set(json.loads(SEEN_FILE.read_text())) if SEEN_FILE.exists() else set()
fresh, spent = [], 0
for platform, body in results.items():
    spent += body.get("credits_used", 0)
    if not body["success"]:
        print(f"{platform}: {body['error']['type']}")
        continue
    for item in body["data"].get("items", []):
        post = item.get("post") or {}
        url = post.get("url")
        if url and url not in seen:
            seen.add(url)
            fresh.append((platform, post))
SEEN_FILE.write_text(json.dumps(sorted(seen)))

# Step 3: alert on what is new.
print(f"{len(fresh)} new mentions of {BRAND!r} ({spent} credits)")
for platform, post in fresh:
    print(f"[{platform}] {(post.get('text') or post.get('title') or '')[:120]}")
    print(f"  {post['url']}")
    # Replace print with a Slack webhook, an email or a database insert.