# ── Imports ──────────────────────────────────────────────────────────
import os, json, asyncio, re, shutil, sqlite3, urllib.parse, random, logging, tempfile
from datetime import datetime, timedelta
from fastapi import FastAPI, Query, Body
from fastapi.middleware.cors import CORSMiddleware
import uvicorn
from playwright.async_api import async_playwright


# ── Lazy Imports for browser-use (not always available) ──────────────
def _make_ollama(model: str | None = None, **kwargs):
    from langchain_ollama import ChatOllama
    llm = ChatOllama(model=model or CLASSIFY_MODEL, **kwargs)
    object.__setattr__(llm, 'provider', 'ollama')
    object.__setattr__(llm, 'name', 'ChatOllama')
    object.__setattr__(llm, 'model_name', llm.model)
    return llm


def _make_browser(**kwargs):
    from browser_use import Browser
    return Browser(**kwargs)


def _make_agent(task: str, llm, browser, **kwargs):
    from browser_use import Agent
    return Agent(task=task, llm=llm, browser=browser, **kwargs)


# ── Logging & App Setup ──────────────────────────────────────────────
logging.basicConfig(level=logging.INFO, format='%(asctime)s [%(levelname)s] %(message)s')
logger = logging.getLogger(__name__)

app = FastAPI()
app.add_middleware(
    CORSMiddleware,
    allow_origins=["http://localhost:3006", "http://127.0.0.1:3006"],
    allow_methods=["POST"],
    allow_headers=["*"],
)
PORT = int(os.getenv("PORT", "3008"))

# ── AI / Ollama Config ───────────────────────────────────────────────
OLLAMA_URL = os.getenv("OLLAMA_URL", "http://localhost:11434")
CLASSIFY_MODEL = os.getenv("CLASSIFY_MODEL", "dolphin-llama3:8b")


# ── Env Vars (set via .env.local) ──────────────────────────────────────
# These store detected browser profile paths from the setup wizard.
FX_PROFILE = os.getenv('FX_PROFILE', '')
CHROME_PROFILE = os.getenv('CHROME_PROFILE', '')
OPERA_PROFILE = os.getenv('OPERA_PROFILE', '')
EDGE_PROFILE = os.getenv('EDGE_PROFILE', '')
# SELECTED_BROWSER determines which browser the scrape dispatcher tries first.
# Values: "firefox", "chrome", "opera", "edge", or "" (auto-detect all).
SELECTED_BROWSER = os.getenv('SELECTED_BROWSER', '')

# ── Chromium Launch Args ──────────────────────────────────────────────
# These flags reduce detectable automation signals in Chrome/Edge/Opera.
# They disable background services, sync, updates, throttling, popups, etc.
CHROME_LAUNCH_ARGS = [
    '--headless=new',
    '--disable-blink-features=AutomationControlled',
    '--disable-background-networking',
    '--no-first-run',
    '--disable-sync',
    '--disable-field-trial-config',
    '--disable-background-timer-throttling',
    '--disable-backgrounding-occluded-windows',
    '--disable-breakpad',
    '--disable-component-update',
    '--disable-default-apps',
    '--disable-dev-shm-usage',
    '--disable-popup-blocking',
    '--disable-prompt-on-repost',
    '--disable-renderer-backgrounding',
    '--metrics-recording-only',
    '--no-default-browser-check',
    '--disable-extensions-http-throttling',
    '--disable-hang-monitor',
    '--disable-ipc-flooding-protection',
]


# ── Profile Detection ────────────────────────────────────────────────
# All find_*_profile() functions return the parent directory (User Data or equivalent),
# NOT the "Default" subdirectory. This is important because copy_chrome_profile()
# appends "Default" internally, so returning the full Default path would cause
# duplicated path segments (e.g. ".../User Data/Default/Default").

def detect_browser_from_profile(profile_path: str) -> str | None:
    """
    Infer browser type from the profile path string.
    Checks for keywords like "firefox", "opera", "edge", "chrome" in the path.
    Returns "firefox", "chrome", "opera", "edge", or None.
    """
    if not profile_path:
        return None
    p = profile_path.lower().replace('\\', '/')
    if 'firefox' in p or '.default' in p or '.dev-edition' in p:
        return 'firefox'
    if 'opera' in p:
        return 'opera'
    if 'edge' in p:
        return 'edge'
    if 'chrome' in p or 'chromium' in p:
        return 'chrome'
    return None


def find_firefox_profile() -> str | None:
    """Auto-detect Firefox profile directory cross-platform.
    Scans the Profiles dir and returns the first .default or .dev-edition folder found,
    preferring "default-release" profiles."""
    import sys
    home = os.path.expanduser("~")
    candidates = []

    if sys.platform == "win32":
        appdata = os.environ.get("APPDATA", "")
        if appdata:
            profiles_dir = os.path.join(appdata, "Mozilla", "Firefox", "Profiles")
        else:
            profiles_dir = os.path.join(home, "AppData", "Roaming", "Mozilla", "Firefox", "Profiles")
    elif sys.platform == "darwin":
        profiles_dir = os.path.join(home, "Library", "Application Support", "Firefox", "Profiles")
    else:
        profiles_dir = os.path.join(home, ".mozilla", "firefox")

    if os.path.isdir(profiles_dir):
        for entry in os.listdir(profiles_dir):
            full = os.path.join(profiles_dir, entry)
            if os.path.isdir(full) and (".default" in entry.lower() or ".dev-edition" in entry.lower()):
                candidates.append(full)
        candidates.sort(key=lambda p: "default-release" in p.lower(), reverse=True)
        if candidates:
            logger.info("Auto-detected Firefox profile: %s", candidates[0])
            return candidates[0]
    return None


def find_chrome_profile() -> str | None:
    """Auto-detect Chrome profile (User Data dir) cross-platform.
    Returns the User Data parent dir (NOT the Default subdirectory)."""
    import sys
    home = os.path.expanduser("~")

    if sys.platform == "win32":
        base = os.path.join(os.environ.get("LOCALAPPDATA", ""), "Google", "Chrome", "User Data")
    elif sys.platform == "darwin":
        base = os.path.join(home, "Library", "Application Support", "Google", "Chrome")
    else:
        base = os.path.join(home, ".config", "google-chrome")

    if os.path.isdir(os.path.join(base, "Default")):
        logger.info("Auto-detected Chrome profile: %s", base)
        return base
    return None


def find_opera_profile() -> str | None:
    """Auto-detect Opera profile directory cross-platform.
    Opera stores its profile at the "Opera Stable" level (no "User Data/Default"
    nesting like Chrome/Edge), so this returns the profile root directly."""
    import sys
    home = os.path.expanduser("~")

    if sys.platform == "win32":
        base = os.path.join(os.environ.get("APPDATA", ""), "Opera Software", "Opera Stable")
    elif sys.platform == "darwin":
        base = os.path.join(home, "Library", "Application Support", "com.operasoftware.Opera")
    else:
        base = os.path.join(home, ".config", "opera")

    if os.path.isdir(base) and os.listdir(base):
        logger.info("Auto-detected Opera profile: %s", base)
        return base
    return None


def find_edge_profile() -> str | None:
    """Auto-detect Edge profile (User Data dir) cross-platform.
    Returns the User Data parent dir (NOT the Default subdirectory)."""
    import sys
    home = os.path.expanduser("~")

    if sys.platform == "win32":
        base = os.path.join(os.environ.get("LOCALAPPDATA", ""), "Microsoft", "Edge", "User Data")
    elif sys.platform == "darwin":
        base = os.path.join(home, "Library", "Application Support", "Microsoft Edge")
    else:
        base = os.path.join(home, ".config", "microsoft-edge")

    if os.path.isdir(os.path.join(base, "Default")):
        logger.info("Auto-detected Edge profile: %s", base)
        return base
    return None


# ── Profile Copying ─────────────────────────────────────────────────
# Both functions copy essential cookies/login/storage files from the user's
# real browser profile to a temp directory. Playwright then uses these temp
# profiles via launch_persistent_context(), preserving Facebook login state
# without modifying the user's actual profile.

def copy_firefox_profile(src_path: str) -> str:
    """Copy essential Firefox profile files (cookies, localStorage, permissions) to a temp dir for Playwright.
    Also creates a minimal profiles.ini so Firefox treats it as a valid profile."""
    essential = ['cookies.sqlite', 'webappsstore.sqlite', 'permissions.sqlite']
    dst = tempfile.mkdtemp(prefix='fb_fx_profile_')
    for f_name in essential:
        s = os.path.join(src_path, f_name)
        if os.path.exists(s):
            shutil.copy2(s, os.path.join(dst, f_name))
    with open(os.path.join(dst, 'profiles.ini'), 'w') as fh:
        fh.write("[Profile0]\nName=default\nIsRelative=0\nPath=.\nDefault=yes\n")
    logger.info("Copied Firefox profile to %s", dst)
    return dst


def copy_chrome_profile(user_data_dir: str, profile_dir: str = 'Default') -> str:
    """Copy Chromium-based profile (Chrome/Edge/Opera) to a temp dir.
    Copies Cookies, Login Data, Bookmarks, Web Data, Local Storage, Session Storage, and Local State.
    Args:
        user_data_dir: Parent directory (e.g. ".../Chrome/User Data")
        profile_dir:  Subdirectory name, typically "Default" (default)
    """
    essential = ['Cookies', 'Login Data', 'Bookmarks', 'Web Data']
    dst = tempfile.mkdtemp(prefix='fb_chrome_udir_')
    src_profile = os.path.join(user_data_dir, profile_dir)
    os.makedirs(dst, exist_ok=True)
    os.makedirs(os.path.join(dst, profile_dir), exist_ok=True)
    dst_profile = os.path.join(dst, profile_dir)
    for f_name in essential:
        s = os.path.join(src_profile, f_name)
        if os.path.exists(s):
            shutil.copy2(s, os.path.join(dst_profile, f_name))
    for sub in ['Local Storage', 'Session Storage']:
        s = os.path.join(src_profile, sub)
        if os.path.isdir(s):
            shutil.copytree(s, os.path.join(dst_profile, sub), dirs_exist_ok=True)
    local_state_src = os.path.join(user_data_dir, 'Local State')
    local_state_dst = os.path.join(dst, 'Local State')
    if os.path.exists(local_state_src):
        shutil.copy2(local_state_src, local_state_dst)
    logger.info("Copied Chrome profile from %s to %s", src_profile, dst)
    return dst


def ensure_ublock_extension() -> str | None:
    """Download and extract uBlock Origin extension for ad blocking via Chromium.
    Cached after first download to avoid re-downloading on every scrape."""
    ext_dir = os.path.join(tempfile.gettempdir(), 'fb_ublock_origin')
    manifest = os.path.join(ext_dir, 'manifest.json')
    if os.path.exists(manifest):
        return ext_dir
    import urllib.request, zipfile
    crx_url = ('https://clients2.google.com/service/update2/crx'
               '?response=redirect&prodversion=133&acceptformat=crx3'
               '&x=id%3Dddkjiahejlhfcafbddmgiahcphecmpfh%26uc')
    crx_path = os.path.join(tempfile.gettempdir(), 'ublock_origin.crx')
    try:
        if not os.path.exists(crx_path):
            logger.info("Downloading uBlock Origin extension...")
            urllib.request.urlretrieve(crx_url, crx_path)
        with zipfile.ZipFile(crx_path, 'r') as z:
            z.extractall(ext_dir)
        logger.info("uBlock Origin extension ready at %s", ext_dir)
        return ext_dir
    except Exception as e:
        logger.warning("Failed to load uBlock Origin extension: %s", e)
        return None


# ── Agent Output Parsing ──────────────────────────────────────────────
# When the browser-use Agent fallback is used, it returns natural language
# output containing post listings. This function tries to extract structured
# data from that output, first attempting JSON parsing, then falling back to
# a line-by-line heuristic (numbered or bulleted items).

def extract_agent_posts(agent_result: str, page_text: str) -> list[dict]:
    """Parse posts from agent output or page text fallback."""
    posts = []
    json_match = re.search(r'\[.*?\]', agent_result, re.DOTALL)
    if json_match:
        try:
            parsed = json.loads(json_match.group())
            if isinstance(parsed, list):
                for item in parsed:
                    if isinstance(item, dict) and item.get('content'):
                        posts.append({
                            'content': item.get('content', ''),
                            'author': item.get('author', '') or item.get('publisher', '') or '',
                            'url': item.get('url', ''),
                            'date': item.get('date', ''),
                        })
        except json.JSONDecodeError:
            pass

    if not posts:
        lines = [l.strip() for l in agent_result.split('\n') if l.strip()]
        cur = []
        for l in lines:
            if l.startswith(('1.', '2.', '3.', '4.', '5.', '6.', '7.', '8.', '9.', '- ', '* ')):
                if cur:
                    combined = ' '.join(cur)
                    if len(combined) > 30:
                        posts.append({'content': combined[:500], 'author': '', 'url': '', 'date': ''})
                    cur = []
            cur.append(l)
        if cur:
            combined = ' '.join(cur)
            if len(combined) > 30:
                posts.append({'content': combined[:500], 'author': '', 'url': '', 'date': ''})

    return posts


# ── Keyword Filters for Lead Detection ──────────────────────────────
# BROAD_KEYWORDS — catch any post that might relate to web development needs.
# OFFER_PATTERNS — regex patterns matching service offers (which we ignore).
# REQUEST_PATTERNS — regex patterns matching people asking for help/services.
# Together these form a two-pass filter + AI classification pipeline.

BROAD_KEYWORDS = [
    "website", "web design", "web develop", "web dev",
    "build my website", "build a website", "create a website",
    "need web", "looking for web", "new website",
    "landing page", "wordpress",
    "need a website", "my website", "business website",
    "need a designer", "help with my website",
    "redesign", "update my website",
    "looking for", "need a", "need an", "looking to",
    "help me build", "create my", "build me",
    "design my", "make me a", "would like",
    "need someone", "hire a", "looking to hire",
    "want someone", "need help with",
]

OFFER_PATTERNS = [
    r"\bfree\s+domain\b",
    r"\bweb\s+hosting\b",
    r"\bfree\s+website\b",
    r"\bprofessional\s+website",
    r"\baffordable\s+web\b",
    r"\bget\s+a\s+free\b",
    r"\bsee\s+more\b",
    r"\bbook\s+your\b",
    r"\bhire\s+a\s+freelancer\b",
    r"\bcontent\s+strategy\b",
    r"\bdigital\s+marketing\b",
    r"\bseo\s+service",
    r"\bsocial\s+media\b",
    r"\blimited\s+time\s+offer\b",
    r"\bspecial\s+offer\b",
    r"\bsign\s+up\s+now\b",
    r"\br\d[\d,.]",
    r"\bstarting\s+at\b",
    r"\bper\s+month\b",
    r"\bmonthly\b",
    r"\bfreelancer\s+marketplace\b",
    r"\bfirst\s+order\b",
    r"\bdomain\s+name\b",
    r"\bregister\s+your\s+domain\b",
    r"\bsponsored\b",
    r"\bpromoted\b",
    r"\badvertisement\b",
]

REQUEST_PATTERNS = [
    r"\bi\s+need\b",
    r"\bi\s+need\s+someone\b",
    r"\bi\s+need\s+a\b",
    r"\bi\s+need\s+an\b",
    r"\bi\s+want\b",
    r"\bi\s+would\s+like\b",
    r"\bi'm\s+looking\b",
    r"\bi\s+am\s+looking\b",
    r"\blooking\s+for\b",
    r"\blooking\s+to\b",
    r"\bwho\s+can\b",
    r"\bcan\s+someone\b",
    r"\bhelp\s+me\b",
    r"\bneed\s+help\b",
    r"\bwould\s+like\s+to\b",
    r"\bwant\s+to\b",
    r"\banyone\s+know\b",
    r"\bdoes\s+anyone\b",
    r"\brecommend\b",
    r"\bsuggestion\b",
    r"\bquote\s+(please|for|to)\b",
]

# ── Anti-Detection Scripts ────────────────────────────────────────────
# These JS scripts are injected into every page via add_init_script().
# They override navigator properties (webdriver, userAgent, plugins, etc.)
# and WebGL/canvas/audio fingerprints to make Playwright harder to detect.
# Firefox and Chromium variants differ slightly (e.g. Chrome needs the
# "window.chrome" object; Firefox must NOT have it).

def firefox_init_script() -> str:
    return r"""// Firefox Anti-Detection
Object.defineProperty(navigator, 'webdriver', { get: () => undefined });
Object.defineProperty(navigator, 'languages', { get: () => ['en-US', 'en'] });
Object.defineProperty(navigator, 'platform', { get: () => 'Win32' });
Object.defineProperty(navigator, 'hardwareConcurrency', { get: () => 8 });
Object.defineProperty(navigator, 'maxTouchPoints', { get: () => 0 });
Object.defineProperty(navigator, 'oscpu', { get: () => 'Windows NT 10.0; Win64; x64' });
Object.defineProperty(navigator, 'vendor', { get: () => '' });
Object.defineProperty(navigator, 'vendorSub', { get: () => '' });
Object.defineProperty(navigator, 'productSub', { get: () => '20100101' });
Object.defineProperty(navigator, 'product', { get: () => 'Gecko' });
Object.defineProperty(navigator, 'appCodeName', { get: () => 'Mozilla' });
Object.defineProperty(navigator, 'appName', { get: () => 'Netscape' });
Object.defineProperty(navigator, 'appVersion', { get: () => '5.0 (Windows NT 10.0; Win64; x64; rv:130.0) Gecko/20100101 Firefox/130.0' });
Object.defineProperty(navigator, 'userAgent', { get: () => 'Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:130.0) Gecko/20100101 Firefox/130.0' });
Object.defineProperty(navigator, 'buildID', { get: () => '20250101000000' });
if (window.chrome !== undefined) { window.chrome = undefined; }
if (navigator.permissions) {
    const origQ = navigator.permissions.query.bind(navigator.permissions);
    navigator.permissions.query = (p) => origQ(p).then(r => (['camera','microphone','geolocation','notifications'].includes(p.name) ? Object.assign(r, { state: 'prompt' }) : r));
}
const _gEC = HTMLCanvasElement.prototype.getContext;
HTMLCanvasElement.prototype.getContext = function(t, ...a) {
    const ctx = _gEC.call(this, t, ...a);
    if (ctx && (t === 'webgl' || t === 'webgl2')) {
        const _gP = ctx.getParameter.bind(ctx);
        ctx.getParameter = function(p) { if (p===37445) return 'Intel Inc.'; if (p===37446) return 'Intel Iris OpenGL Engine'; if (p===7936||p===7937||p===35724) return ''; return _gP(p); };
        const _gE = ctx.getExtension.bind(ctx);
        ctx.getExtension = function(n) { if (n==='WEBGL_debug_renderer_info') return null; return _gE(n); };
    }
    return ctx;
};
const _tDU = HTMLCanvasElement.prototype.toDataURL;
HTMLCanvasElement.prototype.toDataURL = function(...a) {
    const img = _tDU.apply(this, a);
    if (img.includes('image/png') && img.length > 5000) { const n = btoa(String.fromCharCode(Math.floor(Math.random()*256))); return img.slice(0,-100)+n+img.slice(-100); }
    return img;
};
const _gFD = AnalyserNode.prototype.getFloatFrequencyData;
if (_gFD) { AnalyserNode.prototype.getFloatFrequencyData = function(a) { _gFD.call(this,a); for(let i=0;i<a.length;i++) a[i]+=(Math.random()-0.5)*0.02; }; }
Object.defineProperty(screen, 'colorDepth', { get: () => 24 });
Object.defineProperty(screen, 'pixelDepth', { get: () => 24 });
Object.defineProperty(navigator, 'plugins', { get: () => [{name:'Widevine Content Decryption Module',filename:'widevinecdm.dll',length:1,description:'Enables Widevine licenses'},{name:'OpenH264 Video Codec',filename:'openh264.dll',length:1,description:'H.264 video codec'}] });
Object.defineProperty(navigator, 'mimeTypes', { get: () => [{type:'application/pdf',suffixes:'pdf',description:'Portable Document Format',enabledPlugin:navigator.plugins[0]}] });"""


def chromium_init_script() -> str:
    return r"""// Enhanced Chromium Anti-Detection
Object.defineProperty(navigator, 'webdriver', { get: () => false });
Object.defineProperty(navigator, 'languages', { get: () => ['en-US', 'en'] });
Object.defineProperty(navigator, 'platform', { get: () => 'Win32' });
Object.defineProperty(navigator, 'hardwareConcurrency', { get: () => 8 });
Object.defineProperty(navigator, 'deviceMemory', { get: () => 8 });
Object.defineProperty(navigator, 'maxTouchPoints', { get: () => 0 });
Object.defineProperty(navigator, 'oscpu', { get: () => 'Windows NT 10.0; Win64; x64' });
Object.defineProperty(navigator, 'vendor', { get: () => 'Google Inc.' });
Object.defineProperty(navigator, 'vendorSub', { get: () => '' });
Object.defineProperty(navigator, 'productSub', { get: () => '20030107' });
Object.defineProperty(navigator, 'product', { get: () => 'Gecko' });
Object.defineProperty(navigator, 'appCodeName', { get: () => 'Mozilla' });
Object.defineProperty(navigator, 'appName', { get: () => 'Netscape' });
Object.defineProperty(navigator, 'appVersion', { get: () => '5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/125.0.0.0 Safari/537.36' });
Object.defineProperty(navigator, 'userAgent', { get: () => 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/125.0.0.0 Safari/537.36' });
window.chrome = { runtime: { onConnect: { addListener: () => {} }, onMessage: { addListener: () => {} }, sendMessage: () => {} }, app: { isInstalled: false, InstallState: { DISABLED: 'disabled', INSTALLED: 'installed', NOT_INSTALLED: 'not_installed' }, getDetails: () => null, getIsInstalled: () => false }, csi: () => {}, loadTimes: () => {} };
if (navigator.permissions) {
    const origQ = navigator.permissions.query.bind(navigator.permissions);
    navigator.permissions.query = (p) => origQ(p).then(r => (['camera','microphone','geolocation','notifications'].includes(p.name) ? Object.assign(r, { state: 'prompt' }) : r));
}
const _gEC = HTMLCanvasElement.prototype.getContext;
HTMLCanvasElement.prototype.getContext = function(t, ...a) {
    const ctx = _gEC.call(this, t, ...a);
    if (ctx && (t === 'webgl' || t === 'webgl2')) {
        const _gP = ctx.getParameter.bind(ctx);
        ctx.getParameter = function(p) { if (p===37445) return 'Intel Inc.'; if (p===37446) return 'Intel Iris OpenGL Engine'; if (p===7936||p===7937||p===35724) return ''; return _gP(p); };
        const _gE = ctx.getExtension.bind(ctx);
        ctx.getExtension = function(n) { if (n==='WEBGL_debug_renderer_info') return null; return _gE(n); };
    }
    return ctx;
};
const _tDU = HTMLCanvasElement.prototype.toDataURL;
HTMLCanvasElement.prototype.toDataURL = function(...a) {
    const img = _tDU.apply(this, a);
    if (img.includes('image/png') && img.length > 5000) { const n = btoa(String.fromCharCode(Math.floor(Math.random()*256))); return img.slice(0,-100)+n+img.slice(-100); }
    return img;
};
const _gFD = AnalyserNode.prototype.getFloatFrequencyData;
if (_gFD) { AnalyserNode.prototype.getFloatFrequencyData = function(a) { _gFD.call(this,a); for(let i=0;i<a.length;i++) a[i]+=(Math.random()-0.5)*0.02; }; }
Object.defineProperty(screen, 'colorDepth', { get: () => 24 });
Object.defineProperty(screen, 'pixelDepth', { get: () => 24 });
Object.defineProperty(navigator, 'plugins', { get: () => [1,2,3,4,5].map(i => ({name:['Chrome PDF Plugin','Chrome PDF Viewer','Native Client','Widevine Content Decryption Module','Chromium PDF Viewer'][i-1],filename:'internal-pdf-viewer',length:1,description:['Portable Document Format','','Native Client Executable','Enables Widevine licenses',''][i-1]})) });
Object.defineProperty(navigator, 'mimeTypes', { get: () => [{type:'application/pdf',suffixes:'pdf',description:'Portable Document Format',enabledPlugin:navigator.plugins[0]},{type:'text/pdf',suffixes:'pdf',description:'Portable Document Format',enabledPlugin:navigator.plugins[0]}] });"""


# ── Text Classification Utilities ────────────────────────────────────
def kw_match(text: str) -> bool:
    t = text.lower()
    return any(kw in t for kw in BROAD_KEYWORDS)

def is_request(text: str) -> bool:
    """Detect if text contains a request for services (e.g. "I need", "looking for")."""
    t = text.lower()
    return any(re.search(p, t) for p in REQUEST_PATTERNS)

def is_offer(text: str) -> bool:
    """Detect if text is an offer/advertisement (we skip these, not leads)."""
    t = text.lower()
    return any(re.search(p, t) for p in OFFER_PATTERNS)

# ── Facebook Search Queries ───────────────────────────────────────────
# These are the search terms the scraper will use on Facebook.
# They target people looking for web development / website services.
# Each run picks 2-4 random queries to vary behavior and reduce detection.
FB_SEARCHES = [
    "looking for web developer",
    "need a website designed",
    "need website built South Africa",
    "need someone to build my website",
    "need web designer",
    "looking for someone to create website",
    "need ecommerce website built",
    "want to hire web developer",
    "need wordpress website",
    "I need a website for my business",
    "need a site for my business",
    "looking for website designer South Africa",
    "need website for my small business",
    "who can build me a website",
    "want to create a website for my business",
    "looking for affordable web design",
    "need a web developer South Africa",
    "help me build a website",
    "need someone to design my website",
    "looking for web designer near me",
    "need a website for my startup",
]

VIEWPORTS = [
    {'width': 1280, 'height': 800},
    {'width': 1366, 'height': 768},
    {'width': 1440, 'height': 900},
    {'width': 1536, 'height': 864},
    {'width': 1920, 'height': 1080},
]

# ── Cookie Extraction ────────────────────────────────────────────────
# Reads Facebook cookies from the browser profile's SQLite database.
# Firefox stores cookies in cookies.sqlite; Chromium stores them in Cookies
# (a SQLite DB as well). This function handles Firefox's format.
# The cookies are copied to a temp file first to avoid locking issues.

async def get_fb_cookies(profile_path: str | None = None):
    cookie_db_path = profile_path or FX_PROFILE
    if not cookie_db_path:
        logger.warning("No profile path provided")
        return []
    cookie_db = os.path.join(cookie_db_path, 'cookies.sqlite')
    if not os.path.exists(cookie_db):
        logger.warning("Cookie DB not found at %s", cookie_db)
        return []
    tmp = os.path.join(os.path.dirname(cookie_db), f'cookies_tmp_{os.getpid()}.sqlite')
    for attempt in range(3):
        try:
            shutil.copy2(cookie_db, tmp)
            break
        except PermissionError:
            if attempt < 2:
                await asyncio.sleep(0.5)
            else:
                logger.error("Failed to copy cookie DB after 3 attempts")
                return []
    try:
        conn = sqlite3.connect(tmp)
        c = conn.cursor()
        c.execute("SELECT name, value, host, path FROM moz_cookies WHERE host LIKE '%facebook.com'")
        rows = c.fetchall()
        conn.close()
        try:
            os.remove(tmp)
        except Exception:
            pass
        return [{
            "name": name, "value": value,
            "domain": host if host.startswith('.') else f'.{host}',
            "path": path,
            "httpOnly": True, "secure": True, "sameSite": "Lax",
        } for name, value, host, path in rows]
    except Exception as e:
        logger.error("Cookie DB read error: %s", e)
        try:
            os.remove(tmp)
        except Exception:
            pass
        return []

# ── Date Parsing ─────────────────────────────────────────────────────
# Facebook displays dates in relative format ("2h ago", "Yesterday", "Monday")
# or various absolute formats. These functions normalize them to YYYY-MM-DD.
WEEKDAY_ORDER = ['monday', 'tuesday', 'wednesday', 'thursday', 'friday', 'saturday', 'sunday']

def _parse_fb_date(block: list[str]) -> str:
    for l in block:
        l = l.strip()
        m = re.match(r'(\d+)\s*(h|hr|hrs|hour|hours)\s*ago', l)
        if m:
            hours = int(m.group(1))
            d = datetime.now() - timedelta(hours=hours)
            return d.strftime('%Y-%m-%d')
        if l.lower() == 'yesterday':
            d = datetime.now() - timedelta(days=1)
            return d.strftime('%Y-%m-%d')
        low = l.lower()
        if low in WEEKDAY_ORDER:
            day_idx = WEEKDAY_ORDER.index(low)
            today_idx = datetime.now().weekday()
            days_ago = (today_idx - day_idx) % 7
            d = datetime.now() - timedelta(days=days_ago)
            return d.strftime('%Y-%m-%d')
        for fmt in ['%Y-%m-%d', '%d %B %Y', '%B %d %Y', '%d %b %Y', '%b %d %Y', '%d %b', '%b %d']:
            try:
                dt = datetime.strptime(l, fmt)
                return dt.strftime('%Y-%m-%d')
            except ValueError:
                pass
    return datetime.now().strftime('%Y-%m-%d')


def _is_within_days(date_str: str, max_days: int = 3) -> bool:
    """Check if date is within max_days from now. Empty/unparseable = keep."""
    if not date_str:
        return True
    try:
        dt = datetime.strptime(date_str.strip(), '%Y-%m-%d')
        return (datetime.now() - dt).days <= max_days
    except ValueError:
        return True


def _clean_fb_text(text: str) -> str:
    cleaned_lines = []
    for l in text.split('\n'):
        stripped = l.strip()
        if not stripped:
            continue
        if len(stripped) < 3:
            continue
        if all(not c.isalpha() for c in stripped):
            continue
        cleaned_lines.append(stripped)
    return '\n'.join(cleaned_lines)

# ── Post Extraction ──────────────────────────────────────────────────
# Two strategies for extracting posts from page content:
#   1. _extract_posts_from_elements — uses structured DOM data from _get_article_elements()
#   2. _extract_posts_from_text     — fallback that parses raw page text line by line
# Both apply dedup (seen_texts), offer filtering, and request scoring.

def _extract_posts_from_elements(elements: list[dict], base_url: str) -> list[dict]:
    posts = []
    seen_texts = set()
    for el in elements:
        raw_text = el.get('text', '')
        if len(raw_text) < 40:
            continue
        text = _clean_fb_text(raw_text)
        if len(text) < 40:
            continue
        if is_offer(text):
            continue
        lines = text.split('\n')
        dekey = text[:80]
        if dekey in seen_texts:
            continue
        seen_texts.add(dekey)
        request_score = 2 if is_request(text) else 0
        post_url = el.get('url') or base_url

        # Prefer JS-extracted date, fall back to text parsing
        js_date = (el.get('date') or '').strip()
        if js_date:
            # Try ISO datetime from <time datetime>
            try:
                dt = datetime.fromisoformat(js_date.replace('Z', '+00:00'))
                date_str = dt.strftime('%Y-%m-%d')
            except (ValueError, TypeError):
                date_str = _parse_fb_date([js_date])
        else:
            date_str = _parse_fb_date(lines)

        posts.append({
            "title": text[:300],
            "content": text[:1000],
            "author": el.get('author', ''),
            "url": post_url,
            "source": "facebook",
            "date": date_str,
            "_score": request_score,
        })
    posts.sort(key=lambda p: p.get('_score', 0), reverse=True)
    for p in posts:
        p.pop('_score', None)
    return posts

def _extract_posts_from_text(raw: str, url: str) -> list[dict]:
    lines = [l.strip() for l in raw.split('\n') if l.strip() and len(l.strip()) >= 15]
    posts = []
    seen_texts = set()
    cur = []
    for l in lines:
        words = re.findall(r'[A-Za-z]{2,}', l)
        if len(words) < 2:
            continue
        lower = l.lower()
        if any(kw in lower for kw in BROAD_KEYWORDS) and not is_offer(l):
            if cur:
                snippet = ' '.join(cur[-3:] + [l])
                if len(snippet) >= 40 and not is_offer(snippet):
                    dekey = snippet[:80]
                    if dekey not in seen_texts:
                        seen_texts.add(dekey)
                        posts.append({
                            "title": snippet[:300],
                            "content": snippet[:1000],
                            "author": '',
                            "url": url,
                            "source": "facebook",
                            "date": _parse_fb_date(cur + [l]),
                        })
                cur = []
            else:
                if not is_offer(l):
                    snippet = l
                    if len(snippet) >= 40:
                        dekey = snippet[:80]
                        if dekey not in seen_texts:
                            seen_texts.add(dekey)
                            posts.append({
                                "title": snippet[:300],
                                "content": snippet[:1000],
                                "author": '',
                                "url": url,
                                "source": "facebook",
                                "date": _parse_fb_date([l]),
                            })
        cur.append(l)
        if len(cur) > 10:
            cur.pop(0)
    return posts

# ── Human-like Behavior Simulation ──────────────────────────────────
# These functions add random delays, mouse movements, and scroll patterns
# to make automated browsing look more like a real human user.
# This is critical for avoiding Facebook's bot detection.

async def human_scroll(page, steps: int = None, total_delay: float = None):
    steps = steps or random.randint(2, 5)
    total_delay = total_delay or random.uniform(6, 18)
    step_delay = total_delay / steps
    for i in range(steps):
        scroll_dist = random.randint(200, 600)
        await page.evaluate(f"window.scrollBy(0, {scroll_dist})")
        try:
            vp = await page.evaluate('({w: window.innerWidth, h: window.innerHeight})')
            x = random.randint(100, vp['w'] - 100)
            y = random.randint(100, vp['h'] - 100)
            await page.mouse.move(x, y, steps=random.randint(15, 35))
        except Exception:
            pass
        await page.wait_for_timeout(int(step_delay * 1000))
    if random.random() < 0.3:
        await page.evaluate(f"window.scrollBy(0, -{random.randint(100, 300)})")
        await page.wait_for_timeout(random.randint(1000, 3000))

async def random_idle(page):
    action = random.random()
    if action < 0.15:
        try:
            elems = await page.query_selector_all('a, span, div[role="button"]')
            if elems:
                el = random.choice(elems[:20])
                box = await el.bounding_box()
                if box:
                    x = box['x'] + box['width'] / 2 + random.randint(-20, 20)
                    y = box['y'] + box['height'] / 2 + random.randint(-10, 10)
                    await page.mouse.move(x, y, steps=random.randint(20, 40))
                    await page.wait_for_timeout(random.randint(500, 2000))
        except Exception:
            pass

# ── Facebook DOM Parsing ─────────────────────────────────────────────
# This JS function runs inside the page context to extract structured post
# data (text, author, URL, date) from Facebook's complex DOM structure.
# It tries multiple selectors (article, feed, etc.) and uses the first
# one that returns results, since Facebook's DOM changes frequently.

async def _get_article_elements(page) -> list[dict]:
    return await page.evaluate('''() => {
        const results = [];
        const seenTexts = new Set();
        const selectors = [
            'div[role="article"]',
            'div[role="feed"] > div',
            'div.x1yztbdb',
            'div[data-pagelet]',
        ];
        for (const sel of selectors) {
            const els = document.querySelectorAll(sel);
            for (const el of els) {
                const text = (el.innerText || '').trim();
                if (text.length < 40) continue;
                const key = text.substring(0, 80);
                if (seenTexts.has(key)) continue;
                seenTexts.add(key);

                // --- Publisher name ---
                let author = '';
                const nameEl = el.querySelector('h4, strong, a[role="link"]');
                if (nameEl) {
                    author = (nameEl.innerText || '').trim();
                }
                if (!author) {
                    const links = el.querySelectorAll('a');
                    for (const a of links) {
                        const t = (a.innerText || '').trim();
                        if (t && t.length > 1 && t.length < 60 && /^[A-Za-zÀ-ÿ]/.test(t) && !t.includes('facebook') && !t.includes('/')) {
                            author = t;
                            break;
                        }
                    }
                }

                // --- Post URL ---
                let postUrl = '';
                for (const a of el.querySelectorAll('a')) {
                    const h = (a.getAttribute('href') || '');
                    if (h.includes('/posts/') || h.includes('/photo/') || h.includes('/video/') || h.includes('/groups/') || h.includes('/permalink/')) {
                        postUrl = h.startsWith('http') ? h : 'https://www.facebook.com' + h;
                        break;
                    }
                }

                // --- Date from <time datetime> ---
                let date = '';
                const timeEl = el.querySelector('time');
                if (timeEl) {
                    date = timeEl.getAttribute('datetime') || timeEl.getAttribute('aria-label') || '';
                }

                results.push({ text, author, url: postUrl, date });
            }
            if (results.length > 0) break;
        }
        return results;
    }''')

async def _ensure_page(page, context):
    """Check if the current page is still alive. If closed (e.g. by a popup),
    create a fresh page and navigate to Facebook."""
    try:
        await page.evaluate('1')
        return page
    except Exception:
        logger.warning("Page was closed mid-scrape, creating a fresh page")
        page = await context.new_page()
        try:
            await page.goto('https://www.google.com/', wait_until='domcontentloaded', timeout=15000)
            await page.wait_for_timeout(random.randint(1000, 3000))
        except Exception:
            logger.warning("Google navigation failed during page recreation")
        await page.goto('https://www.facebook.com/', wait_until='domcontentloaded', timeout=30000)
        await page.wait_for_timeout(random.randint(3000, 8000))
        return page


# ── Facebook Search & Scrape ─────────────────────────────────────────
# Performs a Facebook search for a given query, scrolls through results,
# extracts posts, and returns them. Includes randomization of scroll behavior,
# mouse movements, and idle actions to mimic human browsing patterns.

async def search_facebook(page, context, query: str):
    page = await _ensure_page(page, context)
    url = f'https://www.facebook.com/search/posts/?q={urllib.parse.quote(query)}'
    try:
        await page.goto(url, wait_until='domcontentloaded', timeout=30000)
        try:
            await page.wait_for_selector('div[role="article"], div[role="feed"]', timeout=15000)
        except Exception:
            pass
        await page.wait_for_timeout(random.randint(3000, 8000))

        await human_scroll(page, steps=random.randint(2, 4), total_delay=random.uniform(6, 15))

        if random.random() < 0.1:
            await page.evaluate("window.scrollTo(0, document.body.scrollHeight)")
            await page.wait_for_timeout(random.randint(1000, 3000))
            await page.evaluate("window.scrollBy(0, -300)")
            await page.wait_for_timeout(random.randint(1000, 3000))

        if random.random() < 0.2:
            await page.evaluate("window.scrollTo(0, 0)")
            await page.wait_for_timeout(random.randint(2000, 5000))

        if random.random() < 0.3:
            await random_idle(page)

        raw_articles = await _get_article_elements(page)
        posts = _extract_posts_from_elements(raw_articles, url) if raw_articles else []
        if not posts:
            raw = await page.evaluate('document.body.innerText')
            posts = _extract_posts_from_text(raw, url)
    except Exception as e:
        logger.warning("Facebook search '%s' failed: %s", query, e)
        return page, []
    return page, posts

# ── Detection Signals ────────────────────────────────────────────────
# Keywords/phrases in page URL or body text that indicate Facebook's
# security/bot detection systems have flagged the session.

DETECTION_SIGNALS = [
    '/checkpoint/', '/login.php?', 'action=security_check',
    'unusual activity', 'suspicious login', 'suspicious activity',
    'temporarily blocked', 'temporarily restricted',
    'confirm your identity', 'enter the code we sent',
    'we noticed unusual', 'help us confirm',
    'security check', 'challenge', 'please verify',
]


def check_detection_signals(page_url: str, page_text: str = '') -> str | None:
    """Check page for Facebook detection signals. Returns signal text or None."""
    combined = (page_url + ' ' + page_text).lower()
    for signal in DETECTION_SIGNALS:
        if signal in combined:
            return signal
    return None


def cleanup_chrome():
    """Kill orphaned Chrome headless shell processes. These sometimes linger
    after failed scrapes and interfere with subsequent runs."""
    import subprocess, signal
    try:
        subprocess.run(["taskkill", "/F", "/IM", "chrome-headless-shell.exe"], capture_output=True, timeout=5)
    except Exception:
        pass


# ── Main Scrape Dispatcher ────────────────────────────────────────────
# scrape_facebook() is the main entry point. It:
#   1. Resolves the browser profile path (from SELECTED_BROWSER env var or auto-detect)
#   2. Dispatches to the correct browser-specific scraper
#   3. If the browser scrape is flagged by Facebook, falls through to the Agent fallback
#
# Priority order for browser selection:
#   - SELECTED_BROWSER env var (set by setup wizard) → that browser's scraper
#   - Auto-detect: Firefox → Opera → Chrome → Edge (first found wins)
#   - If no profile found → Agent (browser-use + ChatOllama) fallback

async def scrape_facebook(profile_path: str | None = None, force: bool = False) -> dict:
    """Dispatcher — respect SELECTED_BROWSER, fall through on flag, then Agent."""
    effective_path = profile_path or ""
    browser_type = ""

    # Resolve profile and browser type
    if effective_path:
        browser_type = detect_browser_from_profile(effective_path) or ""
    elif SELECTED_BROWSER == "firefox":
        effective_path = FX_PROFILE or find_firefox_profile() or ""
        browser_type = "firefox"
    elif SELECTED_BROWSER == "opera":
        effective_path = OPERA_PROFILE or find_opera_profile() or ""
        browser_type = "opera"
    elif SELECTED_BROWSER == "edge":
        effective_path = EDGE_PROFILE or find_edge_profile() or ""
        browser_type = "edge"
    elif SELECTED_BROWSER == "chrome":
        effective_path = CHROME_PROFILE or find_chrome_profile() or ""
        browser_type = "chrome"
    else:
        # Auto-detect — try all in priority order
        for name, env_var, find_fn in [
            ("firefox", "FX_PROFILE", find_firefox_profile),
            ("opera", "OPERA_PROFILE", find_opera_profile),
            ("chrome", "CHROME_PROFILE", find_chrome_profile),
            ("edge", "EDGE_PROFILE", find_edge_profile),
        ]:
            p = os.getenv(env_var, "") or find_fn() or ""
            if p:
                effective_path = p
                browser_type = name
                break

    if not browser_type or not effective_path:
        logger.info("No profile found — falling back to Agent")
        return await _scrape_with_agent(force)

    logger.info("Selected browser: %s (profile: %s)", browser_type, effective_path)

    # Firefox path
    if browser_type == "firefox":
        result = await _scrape_with_firefox(effective_path, force)
        if result.get("success") or not result.get("flagged"):
            return result
        logger.warning("Firefox flagged (%s), trying Agent", result.get("flag_reason", "unknown"))
        return await _scrape_with_agent(force)

    # Chromium-based (chrome / opera / edge)
    result = await _scrape_with_chromium(effective_path, browser_type, force)
    if result.get("success") or not result.get("flagged"):
        return result
    logger.warning("%s flagged (%s), trying Agent", browser_type, result.get("flag_reason", "unknown"))
    return await _scrape_with_agent(force)


# ── Firefox Scraper ──────────────────────────────────────────────────
# Launches a headless Firefox with the user's real profile cookies (copied
# to a temp dir). Uses firefox_user_prefs to disable automation flags and
# tracking protection. Injects anti-detection script via add_init_script().
# If force=False, randomly skips 30% of runs as a decoy (looks like random
# human browsing). If flagged by Facebook, returns flagged=True for the
# dispatcher to fall through to the Agent.

async def _scrape_with_firefox(profile_path: str, force: bool) -> dict:
    """Scrape Facebook using Firefox + persistent real profile (no cookie injection)."""
    if not profile_path:
        return {"success": False, "leads": [], "flagged": False, "flag_reason": None, "error": "No profile path"}

    profile_dir = None
    try:
        profile_dir = copy_firefox_profile(profile_path)
        async with async_playwright() as pw:
            context = await pw.firefox.launch_persistent_context(
                user_data_dir=profile_dir,
                headless=True,
                firefox_user_prefs={
                    "dom.webdriver.enabled": False,
                    "dom.webdriver.timeout": 0,
                    "useAutomationExtension": False,
                    "privacy.trackingprotection.enabled": False,
                    "privacy.trackingprotection.fingerprinting.enabled": False,
                    "privacy.trackingprotection.cryptomining.enabled": False,
                },
            )
            pages = context.pages
            page = pages[0] if pages else await context.new_page()
            await context.add_init_script(firefox_init_script())

            try:
                await page.goto('https://www.google.com/', wait_until='domcontentloaded', timeout=15000)
                await page.wait_for_timeout(random.randint(1000, 3000))
            except Exception:
                logger.warning("Google navigation failed, trying Facebook directly")

            await page.goto('https://www.facebook.com/', wait_until='domcontentloaded', timeout=30000)
            await page.wait_for_timeout(random.randint(3000, 8000))

            url = page.url
            page_text = await page.evaluate('document.body.innerText') if '/login' in url.lower() else ''
            det = check_detection_signals(url, page_text)
            if det or '/login' in url.lower():
                logger.warning("Facebook login page detected — flag: %s", det or "login_page")
                await context.close()
                return {"success": False, "leads": [], "flagged": True, "flag_reason": det or "login_page", "error": "Facebook login page detected"}

            await human_scroll(page, steps=random.randint(2, 4), total_delay=random.uniform(8, 20))
            if random.random() < 0.25:
                await page.evaluate("window.scrollTo(0, 0)")
                await page.wait_for_timeout(random.randint(2000, 5000))
                await human_scroll(page, steps=random.randint(1, 2))

            if not force and random.random() < 0.3:
                await page.wait_for_timeout(random.randint(8000, 20000))
                await context.close()
                return {"success": True, "leads": [], "flagged": False, "flag_reason": None, "error": None}

            all_posts = []
            searches = random.sample(FB_SEARCHES, k=random.randint(2, 4))
            for i, query in enumerate(searches):
                page, posts = await search_facebook(page, context, query)
                all_posts.extend(posts)
                if not posts:
                    continue
                if random.random() < 0.4:
                    await page.evaluate(f"window.scrollBy(0, {random.randint(-300, 300)})")
                delay = random.uniform(8, 25)
                await page.wait_for_timeout(int(delay * 1000))
                if i == random.randint(0, 1) and random.random() < 0.15:
                    new_page = await context.new_page()
                    try:
                        await new_page.goto('https://www.facebook.com/groups/', wait_until='domcontentloaded', timeout=15000)
                        await new_page.wait_for_timeout(random.randint(3000, 8000))
                    except Exception:
                        pass
                    await new_page.close()
                    page = await _ensure_page(page, context)

            if random.random() < 0.5:
                await page.wait_for_timeout(random.randint(3000, 10000))

            await context.close()

            seen = set()
            deduped = []
            for p in all_posts:
                key = p.get('content', '')[:100]
                if key not in seen:
                    seen.add(key)
                    deduped.append(p)

            # Filter to last 3 days only
            deduped = [p for p in deduped if _is_within_days(p.get('date', ''), 3)]

            leads = deduped[:20]
            if leads:
                leads = await classify_leads(leads)

            return {"success": True, "leads": leads[:15], "flagged": False, "flag_reason": None, "error": None}

    except Exception as e:
        logger.error("Firefox scrape failed: %s", e)
        return {"success": False, "leads": [], "flagged": False, "flag_reason": None, "error": str(e)}
    finally:
        if profile_dir and os.path.exists(profile_dir):
            try:
                shutil.rmtree(profile_dir, ignore_errors=True)
            except Exception:
                pass


# ── Chromium Scraper ─────────────────────────────────────────────────
# Generic scraper for Chrome/Edge/Opera. Uses the same structure as the
# Firefox scraper but with Chromium-specific launch config:
#   - Chrome: channel="chrome"
#   - Edge:   channel="msedge"
#   - Opera:  executable_path from shutil.which("opera")
# Cookies come from copy_chrome_profile (temp copy of user's profile data).
# Anti-detection script differs slightly from Firefox variant.
# Same decoy-skip and flagged-fallback behavior as Firefox.

async def _scrape_with_chromium(profile_path: str, browser: str, force: bool = False) -> dict:
    """Scrape Facebook using a Chromium-based browser profile (Chrome/Edge/Opera)."""
    if not profile_path:
        return {"success": False, "leads": [], "flagged": False, "flag_reason": None, "error": "No profile path"}

    channel = None
    executable_path = None
    if browser == "chrome":
        channel = "chrome"
    elif browser == "edge":
        channel = "msedge"
    elif browser == "opera":
        executable_path = shutil.which("opera") or shutil.which("Opera")

    profile_dir = None
    try:
        profile_dir = copy_chrome_profile(profile_path)
        async with async_playwright() as pw:
            launch_kwargs = dict(
                user_data_dir=profile_dir,
                headless=True,
                args=CHROME_LAUNCH_ARGS,
            )
            if channel:
                launch_kwargs["channel"] = channel
            if executable_path:
                launch_kwargs["executable_path"] = executable_path

            context = await pw.chromium.launch_persistent_context(**launch_kwargs)
            pages = context.pages
            page = pages[0] if pages else await context.new_page()
            await context.add_init_script(chromium_init_script())

            try:
                await page.goto('https://www.google.com/', wait_until='domcontentloaded', timeout=15000)
                await page.wait_for_timeout(random.randint(1000, 3000))
            except Exception:
                logger.warning("Google navigation failed, trying Facebook directly")

            await page.goto('https://www.facebook.com/', wait_until='domcontentloaded', timeout=30000)
            await page.wait_for_timeout(random.randint(3000, 8000))

            url = page.url
            page_text = await page.evaluate('document.body.innerText') if '/login' in url.lower() else ''
            det = check_detection_signals(url, page_text)
            if det or '/login' in url.lower():
                logger.warning("Facebook login page detected — flag: %s", det or "login_page")
                await context.close()
                return {"success": False, "leads": [], "flagged": True, "flag_reason": det or "login_page", "error": "Facebook login page detected"}

            await human_scroll(page, steps=random.randint(2, 4), total_delay=random.uniform(8, 20))
            if random.random() < 0.25:
                await page.evaluate("window.scrollTo(0, 0)")
                await page.wait_for_timeout(random.randint(2000, 5000))
                await human_scroll(page, steps=random.randint(1, 2))

            if not force and random.random() < 0.3:
                await page.wait_for_timeout(random.randint(8000, 20000))
                await context.close()
                return {"success": True, "leads": [], "flagged": False, "flag_reason": None, "error": None}

            all_posts = []
            searches = random.sample(FB_SEARCHES, k=random.randint(2, 4))
            for i, query in enumerate(searches):
                page, posts = await search_facebook(page, context, query)
                all_posts.extend(posts)
                if not posts:
                    continue
                if random.random() < 0.4:
                    await page.evaluate(f"window.scrollBy(0, {random.randint(-300, 300)})")
                delay = random.uniform(8, 25)
                await page.wait_for_timeout(int(delay * 1000))
                if i == random.randint(0, 1) and random.random() < 0.15:
                    new_page = await context.new_page()
                    try:
                        await new_page.goto('https://www.facebook.com/groups/', wait_until='domcontentloaded', timeout=15000)
                        await new_page.wait_for_timeout(random.randint(3000, 8000))
                    except Exception:
                        pass
                    await new_page.close()
                    page = await _ensure_page(page, context)

            if random.random() < 0.5:
                await page.wait_for_timeout(random.randint(3000, 10000))

            await context.close()

            seen = set()
            deduped = []
            for p in all_posts:
                key = p.get('content', '')[:100]
                if key not in seen:
                    seen.add(key)
                    deduped.append(p)

            deduped = [p for p in deduped if _is_within_days(p.get('date', ''), 3)]
            leads = deduped[:20]
            if leads:
                leads = await classify_leads(leads)

            return {"success": True, "leads": leads[:15], "flagged": False, "flag_reason": None, "error": None}

    except Exception as e:
        logger.error("%s scrape failed: %s", browser, e)
        return {"success": False, "leads": [], "flagged": False, "flag_reason": None, "error": str(e)}
    finally:
        if profile_dir and os.path.exists(profile_dir):
            try:
                shutil.rmtree(profile_dir, ignore_errors=True)
            except Exception:
                pass


# ── Agent Fallback ──────────────────────────────────────────────────
# When all browser-based scrapers fail/are flagged, this fallback uses
# browser-use Agent with ChatOllama (local, free) to navigate Facebook
# autonomously via GPT-style prompting. No API keys needed.
# Uses Chromium headless with the same launch args as _scrape_with_chromium.
# The Agent is prompted to extract structured post data and return JSON.

async def _scrape_with_agent(force: bool = False) -> dict:
    """Fallback scraper — browser-use Agent + ChatOllama (free/local, Chromium)."""
    cleanup_chrome()
    profile_dir = None
    try:
        user_data_dir = None
        if CHROME_PROFILE:
            profile_dir = copy_chrome_profile(CHROME_PROFILE)
            user_data_dir = profile_dir

        browser = _make_browser(
            headless=True,
            args=CHROME_LAUNCH_ARGS,
            user_data_dir=user_data_dir,
            allowed_domains=["*.facebook.com", "*.messenger.com", "www.google.com"],
        )
        await browser.start()

        all_posts = []
        for query in random.sample(FB_SEARCHES, k=random.randint(2, 4)):
            agent = _make_agent(
                task=f"""You are logged into Facebook. Do the following:
1. Navigate to facebook.com and make sure you are on the homepage
2. Use the Facebook search to find: {query}
3. Scroll through the results
4. For each relevant post, extract and list:
   - The publisher/author name (who posted it)
   - The post text content
   - The post URL (if visible)
   - The post date
5. ONLY include posts from the last 3 days
6. Collect as many posts as you can (aim for 5-10 per search)

When done, return the data as a JSON list with keys: content, author, url, date.""",
                llm=_make_ollama(num_ctx=32000, temperature=0.3),
                browser=browser,
                max_actions_per_step=3,
                use_vision=False,
                max_failures=6,
                step_timeout=180,
            )
            history = await agent.run()
            result = history.final_result() or ""
            posts = extract_agent_posts(result, "")
            all_posts.extend(posts)

            if random.random() < 0.3:
                await asyncio.sleep(random.randint(5, 15))

        await browser.close()

        seen = set()
        deduped = []
        for p in all_posts:
            key = p.get('content', '')[:100]
            if key not in seen:
                seen.add(key)
                deduped.append(p)

        # Filter to last 3 days only
        deduped = [p for p in deduped if _is_within_days(p.get('date', ''), 3)]

        leads = deduped[:20]
        if leads:
            leads = await classify_leads(leads)

        return {"success": True, "leads": leads[:15], "flagged": False, "flag_reason": None, "error": None}
    except Exception as e:
        logger.error("Agent scrape failed: %s", e)
        return {"success": False, "leads": [], "flagged": False, "flag_reason": None, "error": str(e)}
    finally:
        if profile_dir and os.path.isdir(profile_dir):
            try:
                shutil.rmtree(profile_dir, ignore_errors=True)
            except Exception as e:
                logger.warning("Failed to clean up Chrome profile %s: %s", profile_dir, e)

# ── AI Classification ────────────────────────────────────────────────
# Uses the local Ollama model to classify scraped posts as LEAD or NOT LEAD.
# Falls back to keyword-based filtering if the AI is unavailable.
# ask_ollama() sends a raw prompt to Ollama's /api/chat endpoint.
# classify_leads() builds a classification prompt and parses the JSON response.

async def ask_ollama(prompt: str) -> str:
    import httpx
    async with httpx.AsyncClient(timeout=120) as c:
        r = await c.post(f"{OLLAMA_URL}/api/chat", json={
            "model": CLASSIFY_MODEL,
            "messages": [
                {"role": "system", "content": "You classify forum posts. Return only valid JSON."},
                {"role": "user", "content": prompt}
            ],
            "stream": False,
            "options": {"temperature": 0.05, "num_predict": 1024},
        })
        r.raise_for_status()
        data = r.json()
        return data["message"]["content"]

async def classify_leads(results: list[dict]) -> list[dict]:
    if not results:
        return []
    briefs = [r["title"][:200] for r in results]
    prompt = f"""Classify each post as LEAD or NOT.
LEAD = someone REQUESTING/POSTING/WANTING a website built, designed, or created for them.
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"

NOT LEAD:
- Offering web design services: "I build websites", "I offer web design", "Affordable web design packages"
- Already have a website and need marketing, SEO, content, video, link building, email marketing, affiliates
- Recruiting employees, hiring staff, looking for business partners
- Selling products, promoting services, affiliate offers
- "Need web hosting", "Looking for a partner", "Looking for content writer", "Video spokesperson"

For each numbered post, answer ONLY "yes" (LEAD) or "no" (NOT LEAD):
{chr(10).join(f'{i+1}. {t}' for i, t in enumerate(briefs))}
Return a JSON array like ["yes","no","yes"] matching the order above."""
    ai_succeeded = False
    try:
        raw = await ask_ollama(prompt)
        raw = raw.strip()
        if raw.startswith("```"):
            first_nl = raw.find('\n')
            if first_nl != -1:
                raw = raw[first_nl + 1:]
            if raw.endswith("```"):
                raw = raw[:-3]
            raw = raw.strip()
        answers = json.loads(raw)
        if isinstance(answers, list) and len(answers) == len(results):
            ai_succeeded = True
            filtered = []
            for i, ans in enumerate(answers):
                if isinstance(ans, str) and ans.lower() == 'yes':
                    filtered.append(results[i])
            if filtered:
                return filtered[:10]
            logger.info("AI classified all %d items as NOT LEAD — returning empty", len(results))
            return []
    except Exception as e:
        logger.warning("AI classification failed, falling back to keyword filter: %s", e)

    if not ai_succeeded:
        strict_keywords = [
            "website", "web design", "web develop", "web dev",
            "build my website", "build a website", "create a website",
            "need web", "looking for web", "new website",
            "landing page", "wordpress",
            "need a website", "my website", "business website",
            "need a designer", "help with my website",
            "redesign", "update my website",
            "looking for", "need a", "need an", "looking to",
            "need someone", "hire a", "want someone",
            "need help with", "would like", "build me",
            "design my", "make me a", "create my",
        ]
        filtered = []
        for r in results:
            t = r['title'].lower()
            if not any(kw in t for kw in strict_keywords):
                continue
            if any(kw in t for kw in ['i build website', 'i offer web', 'i am a web developer',
                                       'affordable web design package', 'web hosting']):
                continue
            filtered.append(r)
        return filtered[:10]
    return []

# ══════════════════════════════════════════════════════════════════════
# FastAPI Endpoints
# ══════════════════════════════════════════════════════════════════════

@app.get("/health")
async def health():
    """Simple health check for the splash page status polling."""
    return {"status": "ok"}

def _detect_all_profiles() -> dict:
    """Return all detected browser profiles."""
    return {
        "firefox": FX_PROFILE or find_firefox_profile() or "",
        "opera": OPERA_PROFILE or find_opera_profile() or "",
        "chrome": CHROME_PROFILE or find_chrome_profile() or "",
        "edge": EDGE_PROFILE or find_edge_profile() or "",
    }

@app.get("/setup/profile")
async def setup_profile():
    """Auto-detect all browser profiles."""
    return _detect_all_profiles()

async def _check_browser_login(profile_path: str, browser: str) -> dict:
    """Check Facebook login for a specific browser type."""
    profile_dir = None
    try:
        if browser == "firefox":
            profile_dir = copy_firefox_profile(profile_path)
            async with async_playwright() as pw:
                context = await pw.firefox.launch_persistent_context(
                    user_data_dir=profile_dir, headless=True,
                    firefox_user_prefs={"dom.webdriver.enabled": False},
                )
                page = context.pages[0] if context.pages else await context.new_page()
                await page.goto("https://www.facebook.com/", wait_until="domcontentloaded", timeout=30000)
                await page.wait_for_timeout(3000)
                logged_in = "/login" not in page.url.lower()
                await context.close()
            shutil.rmtree(profile_dir, ignore_errors=True)
            return {"logged_in": logged_in, "browser": browser, "path": profile_path}
        else:
            channel = None
            exe = None
            if browser == "chrome":
                channel = "chrome"
            elif browser == "edge":
                channel = "msedge"
            elif browser == "opera":
                exe = shutil.which("opera") or shutil.which("Opera")
            profile_dir = copy_chrome_profile(profile_path)
            async with async_playwright() as pw:
                kw = dict(user_data_dir=profile_dir, headless=True, args=CHROME_LAUNCH_ARGS)
                if channel:
                    kw["channel"] = channel
                if exe:
                    kw["executable_path"] = exe
                context = await pw.chromium.launch_persistent_context(**kw)
                page = context.pages[0] if context.pages else await context.new_page()
                await page.goto("https://www.facebook.com/", wait_until="domcontentloaded", timeout=30000)
                await page.wait_for_timeout(3000)
                logged_in = "/login" not in page.url.lower()
                await context.close()
            shutil.rmtree(profile_dir, ignore_errors=True)
            return {"logged_in": logged_in, "browser": browser, "path": profile_path}
    except Exception as e:
        if profile_dir:
            try: shutil.rmtree(profile_dir, ignore_errors=True)
            except: pass
        return {"logged_in": False, "browser": browser, "path": profile_path, "error": str(e)}

@app.post("/setup/check-login")
async def setup_check_login(body: dict):
    """Check if Facebook is logged in. Accepts optional 'browser' param, tries all if not given."""
    browser = (body.get("browser") or "").strip().lower()
    profile_path = (body.get("profile_path") or "").strip()

    if browser and profile_path:
        return await _check_browser_login(profile_path, browser)

    # No specific browser — try all detected
    profiles = _detect_all_profiles()
    priority = ["firefox", "opera", "chrome", "edge"]
    for b in priority:
        p = profiles.get(b, "")
        if p:
            result = await _check_browser_login(p, b)
            if result.get("logged_in"):
                return result
            logger.info("%s not logged in, trying next", b)
    return {"logged_in": False, "reason": "none_logged_in", "message": "No browser with Facebook login found"}

@app.post("/agent/run")
async def agent_run(task: str = Body(..., embed=True)):
    """Run a browser-use Agent with ChatOllama (free/local)."""
    try:
        browser = _make_browser(headless=True, args=CHROME_LAUNCH_ARGS)
        await browser.start()
        agent = _make_agent(
            task=task,
            llm=_make_ollama(num_ctx=32000, temperature=0.3),
            browser=browser,
            use_vision=False,
            max_actions_per_step=5,
            max_failures=8,
            step_timeout=180,
        )
        history = await agent.run()
        await browser.close()
        return {"success": True, "result": history.final_result()}
    except Exception as e:
        logger.error("Agent run failed: %s", e)
        return {"success": False, "error": str(e)}

@app.post("/scrape/facebook")
async def scrape_facebook_endpoint(profile_path: str | None = Query(None), force: bool = Query(False)):
    result = await scrape_facebook(profile_path, force)
    return result

if __name__ == "__main__":
    uvicorn.run(app, host="0.0.0.0", port=PORT)
