Got facebook to work test tomorrow with new accounts please
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import os, json, asyncio, re, shutil, sqlite3, traceback, urllib.parse
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from datetime import datetime, timedelta
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from bs4 import BeautifulSoup
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import httpx
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from fastapi import FastAPI
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from pydantic import BaseModel
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import uvicorn
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from playwright.async_api import async_playwright
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app = FastAPI()
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PORT = int(os.getenv("PORT", "3008"))
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OLLAMA_URL = os.getenv("OLLAMA_URL", "http://localhost:11434")
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CLASSIFY_MODEL = os.getenv("CLASSIFY_MODEL", "dolphin-llama3:8b")
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FX_PROFILE = os.getenv('FX_PROFILE', r'C:\Users\USER-PC\AppData\Roaming\Mozilla\Firefox\Profiles\h8p11vlj.default-release')
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FX_COOKIE_DB = os.path.join(FX_PROFILE, 'cookies.sqlite')
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HEADERS = {
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'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36',
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'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
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}
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last_scrape_time: datetime | None = None
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_pw_browser = None
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STRICT_KEYWORDS = [
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"website", "web design", "web develop", "web dev",
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"build my website", "build a website", "create a website",
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"need web", "looking for web", "new website",
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"landing page", "wordpress",
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"need a website", "my website", "business website",
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"need a designer", "help with my website",
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"redesign", "update my website",
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]
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BROAD_KEYWORDS = STRICT_KEYWORDS + [
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"looking for", "need a", "need an", "looking to",
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"help me build", "create my", "build me",
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"design my", "make me a", "would like",
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"need someone", "hire a", "looking to hire",
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"want someone", "need help with",
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]
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def kw_match_strict(text: str) -> bool:
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t = text.lower()
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return any(kw in t for kw in STRICT_KEYWORDS)
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def kw_match(text: str) -> bool:
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t = text.lower()
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return any(kw in t for kw in BROAD_KEYWORDS)
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FB_SEARCHES = [
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"looking for web developer",
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"need a website designed",
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"need website built South Africa",
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"need someone to build my website",
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"need web designer",
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"looking for someone to create website",
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"need ecommerce website built",
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"want to hire web developer",
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"website quote please",
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"need wordpress website",
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"I need a website for my business",
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"need a site for my business",
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]
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def get_fb_cookies():
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"""Copy Firefox cookie DB and extract Facebook cookies for Chromium injection."""
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tmp = os.path.join(os.path.dirname(FX_COOKIE_DB), 'cookies_tmp.sqlite')
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try:
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if not os.path.exists(FX_COOKIE_DB):
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return []
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shutil.copy2(FX_COOKIE_DB, tmp)
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conn = sqlite3.connect(tmp)
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c = conn.cursor()
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c.execute("SELECT name, value, host, path FROM moz_cookies WHERE host LIKE '%facebook.com'")
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rows = c.fetchall()
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conn.close()
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os.remove(tmp)
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return [{
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"name": name, "value": value,
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"domain": host if host.startswith('.') else f'.{host}',
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"path": path,
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"httpOnly": False, "secure": False, "sameSite": "Lax",
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} for name, value, host, path in rows]
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except Exception as e:
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return []
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def _is_real_text(line: str) -> bool:
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if not line:
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return False
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# Count words (sequences of letters)
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words = re.findall(r'[A-Za-z]{2,}', line)
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return len(words) >= 2
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def _extract_posts_from_text(raw: str, url: str) -> list[dict]:
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"""Parse Facebook search results page text into structured posts."""
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lines = [l.strip() for l in raw.split('\n')]
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# Split into blocks separated by "Facebook" boilerplate lines (2+ consecutive)
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blocks = []
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cur = []
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fb_run = 0
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for l in lines:
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if 'facebook' in l.lower():
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fb_run += 1
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if cur and fb_run >= 2:
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blocks.append(cur)
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cur = []
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else:
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fb_run = 0
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if l and len(l) >= 15:
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# Check for real words (not scattered reaction chars)
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words = re.findall(r'[A-Za-z]{2,}', l)
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if len(words) >= 2:
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cur.append(l)
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if cur:
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blocks.append(cur)
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posts = []
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seen_texts = set()
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for block in blocks:
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if not block:
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continue
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# Find keyword-matched content in this block
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kw_indices = [i for i, l in enumerate(block) if kw_match(l)]
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if not kw_indices:
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continue
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# Use first keyword match as anchor, grab context
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i = kw_indices[0]
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start = max(0, i - 2)
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end = min(len(block), i + 5)
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snippet = ' '.join(block[start:end])
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if len(snippet) < 40:
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continue
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dekey = snippet[:80]
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if dekey in seen_texts:
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continue
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seen_texts.add(dekey)
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posts.append({
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"title": snippet[:300],
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"content": snippet[:1000],
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"author": block[start] if start < i else '',
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"url": url,
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"source": "facebook",
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"date": datetime.now().strftime('%Y-%m-%d'),
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})
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return posts
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async def search_facebook(page, query: str) -> list[dict]:
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"""Search Facebook and extract post leads from raw page text."""
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url = f'https://www.facebook.com/search/posts/?q={urllib.parse.quote(query)}'
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try:
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await page.goto(url, wait_until='domcontentloaded', timeout=30000)
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# Wait for the page content to fully render (React/XHR loads)
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await page.wait_for_timeout(6000)
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except:
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return []
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raw = await page.evaluate('document.body.innerText')
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return _extract_posts_from_text(raw, url)
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async def scrape_facebook() -> list[dict]:
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"""Launch headless Chromium, inject Firefox Facebook cookies, search for leads."""
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all_posts = []
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fb_cookies = get_fb_cookies()
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if not fb_cookies:
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return []
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try:
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async with async_playwright() as pw:
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browser = await pw.chromium.launch(headless=True)
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context = await browser.new_context(
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user_agent='Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:150.0) Gecko/20100101 Firefox/150.0',
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viewport={'width': 1280, 'height': 800},
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)
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for c in fb_cookies:
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try:
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await context.add_cookies([c])
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except:
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pass
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page = await context.new_page()
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await page.goto('https://www.facebook.com/', wait_until='domcontentloaded', timeout=30000)
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await page.wait_for_timeout(5000)
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url = page.url
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if '/login' in url.lower():
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return []
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for query in FB_SEARCHES[:6]:
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try:
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posts = await search_facebook(page, query)
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all_posts.extend(posts)
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await page.wait_for_timeout(2000)
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except:
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continue
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except Exception:
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return []
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seen = set()
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deduped = []
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for p in all_posts:
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key = p['content'][:100]
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if key not in seen:
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seen.add(key)
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deduped.append(p)
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return deduped[:20]
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async def ask_ollama(prompt: str) -> str:
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async with httpx.AsyncClient(timeout=120) as c:
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r = await c.post(f"{OLLAMA_URL}/api/chat", json={
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"model": CLASSIFY_MODEL,
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"messages": [
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{"role": "system", "content": "You classify forum posts. Return only valid JSON."},
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{"role": "user", "content": prompt}
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],
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"stream": False,
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"options": {"temperature": 0.05, "num_predict": 1024},
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})
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r.raise_for_status()
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return r.json()["message"]["content"]
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async def scrape_warriorforum() -> list[dict]:
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results = []
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try:
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async with httpx.AsyncClient(headers=HEADERS, timeout=15, follow_redirects=True) as c:
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r = await c.get('https://www.warriorforum.com/wanted-members-looking-hire-you/')
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soup = BeautifulSoup(r.text, 'lxml')
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for row in soup.find_all('td', class_='FlexTable-item--title'):
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a = row.find('a', href=True)
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if not a:
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continue
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href = a['href']
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title = a.text.strip()
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if not title or len(title) < 15 or not kw_match_strict(title):
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continue
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author_div = row.find('div', class_='FlexTable-item-author')
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author = author_div.get_text(strip=True).lstrip('by') if author_div else ''
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date_str = ''
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date_div = row.find('div', class_=lambda c: c and 'media--available' in c)
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if date_div:
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txt = date_div.get_text(strip=True)
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m = re.search(r'(\d{10})', txt)
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if m:
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from datetime import datetime as dtdt
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date_str = dtdt.utcfromtimestamp(int(m.group(1))).strftime('%Y-%m-%d')
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results.append({
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"title": title, "url": href,
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"author": author,
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"content": title[:300],
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"source": "warriorforum",
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"date": date_str
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})
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except Exception:
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traceback.print_exc()
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return results
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async def classify_leads(results: list[dict]) -> list[dict]:
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if not results:
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return []
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filtered = []
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briefs = [r["title"][:200] for r in results]
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prompt = f"""Classify each post as LEAD or NOT.
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LEAD = someone REQUESTING/POSTING/WANTING a website built, designed, or created for them.
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LEAD examples: "Need a website for my business", "Looking for web developer to build my site", "I need someone to create my website", "Want a new website for my company", "Looking for someone to design my WordPress site"
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NOT LEAD:
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- Offering web design services: "I build websites", "I offer web design", "Affordable web design packages"
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- Already have a website and need marketing, SEO, content, video, link building, email marketing, affiliates
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- Recruiting employees, hiring staff, looking for business partners
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- Selling products, promoting services, affiliate offers
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- "Need web hosting", "Looking for a partner", "Looking for content writer", "Video spokesperson"
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For each numbered post, answer ONLY "yes" (LEAD) or "no" (NOT LEAD):
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{chr(10).join(f'{i+1}. {t}' for i, t in enumerate(briefs))}
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Return a JSON array like ["yes","no","yes"] matching the order above."""
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try:
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raw = await ask_ollama(prompt)
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raw = raw.strip()
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if raw.startswith("```json"): raw = raw[7:]
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if raw.startswith("```"): raw = raw.split("\n", 1)[-1].rsplit("```", 1)[0]
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answers = json.loads(raw)
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if isinstance(answers, list) and len(answers) == len(results):
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for i, ans in enumerate(answers):
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if isinstance(ans, str) and ans.lower() == 'yes':
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filtered.append(results[i])
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except:
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pass
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if not filtered:
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for r in results:
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t = r['title'].lower()
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# MUST match a web-dev keyword to be a lead
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if not kw_match_strict(t):
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continue
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# But NOT these (offerings, not requests)
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if any(kw in t for kw in ['i build', 'i offer', 'i create', 'i am a', 'web developer available',
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'affordable web', 'web hosting', 'free website',
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'limited time', 'special offer', 'sign up now',
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'offer']):
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continue
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filtered.append(r)
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return filtered[:10]
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@app.get("/health")
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async def health():
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return {"status": "ok"}
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class ScrapeRequest(BaseModel):
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query: str = ""
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@app.post("/scrape/requests")
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async def scrape_requests(req: ScrapeRequest):
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global last_scrape_time
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now = datetime.now()
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if last_scrape_time and (now - last_scrape_time) < timedelta(seconds=15):
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return {"error": "rate_limited", "retry_after": 15}
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last_scrape_time = now
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results = await scrape_warriorforum()
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if results:
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results = await classify_leads(results)
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return results[:10]
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@app.post("/scrape/facebook")
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async def scrape_facebook_endpoint():
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results = await scrape_facebook()
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if results:
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results = await classify_leads(results)
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return results[:15]
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@app.post("/scrape/all")
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async def scrape_all():
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results = []
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try:
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wf = await scrape_warriorforum()
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if wf:
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wf = await classify_leads(wf)
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results.extend(wf[:5])
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except:
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pass
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try:
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fb = await scrape_facebook()
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if fb:
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fb = await classify_leads(fb)
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results.extend(fb[:8])
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except:
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pass
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return results[:12]
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if __name__ == "__main__":
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uvicorn.run(app, host="0.0.0.0", port=PORT)
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