""" + preview + """
| ID | Sender | Typ | 📍 Halle | 🎯 Spiel | Inhalt | Status | Zeit |
|---|
#!/usr/bin/env python3 """ BSN Chatbot — Multi-Channel Intake System ========================================== WhatsApp webhook receiver + admin dashboard + knowledge query API. Architecture: WhatsApp → Meta Cloud API → POST /whatsapp/webhook → SQLite Admin: GET /admin → filterable table of all submissions Query: POST /query → RAG-style answer from knowledge table Usage: source .env && python3 app.py """ import json import os import re import sqlite3 import sys from datetime import datetime from pathlib import Path import requests # type: ignore from flask import Flask, request, jsonify, g # type: ignore # ── Config ────────────────────────────────────────────────────────── BASE_DIR = Path(__file__).parent # Load .env file if it exists (for tokens that can't be passed via env) _ENV_FILE = BASE_DIR / ".env" if _ENV_FILE.exists(): with open(_ENV_FILE) as _f: for _line in _f: _line = _line.strip() if _line and not _line.startswith("#") and "=" in _line: _key, _, _val = _line.partition("=") _key = _key.strip() _val = _val.strip().strip('"').strip("'") if _key not in os.environ or not os.environ[_key]: os.environ[_key] = _val DB_PATH = os.environ.get("DATABASE_PATH", str(BASE_DIR / "bsn_intake.db")) VERIFY_TOKEN = os.environ.get("VERIFY_TOKEN", "bsn_verify_2026") META_TOKEN = os.environ.get("META_TOKEN", "") PHONE_NUMBER_ID = os.environ.get("META_PHONE_NUMBER_ID", "1152708791258718") PORT = int(os.environ.get("PORT", "5002")) MEDIA_DIR = BASE_DIR / "media" MEDIA_DIR.mkdir(exist_ok=True) # Brettspiel News logo (base64-encoded JPEG, 993x217) LOGO_B64 = 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""" app = Flask(__name__) # ── Hall extraction ────────────────────────────────────────────────── def extract_halle(text: str) -> str | None: """Extract SPIEL Essen hall+stand from text. Returns e.g. 'H3 B123' or None.""" import re if not text: return None # Pattern: H[1-7] optionally followed by stand letter+number # Matches: "H3", "Halle 3", "H 3", "H3 B123", "Halle 6 Stand A42" patterns = [ # Halle with stand: H3 B123, Halle 6 A42, H 4 C7 r'(?:H|Halle)\s*([1-7])\s*[,\-]?\s*(?:Stand\s*)?([A-Z]\d{1,4})', # Just hall: H3, Halle 6, H 7 r'(?:H|Halle)\s*([1-7])\b', # Stand alone: B123 (only if preceded by "Stand" or after hall context) r'Stand\s*([A-Z]\d{1,4})', ] for pat in patterns: m = re.search(pat, text, re.IGNORECASE) if m: groups = m.groups() if len(groups) == 2 and groups[1]: return f"H{groups[0]} {groups[1]}" elif groups[0]: return f"H{groups[0]}" return None # ── Game title extraction from cover images ────────────────────────── def extract_game_title_from_image(image_path: str) -> str | None: """Use Gemini Flash vision to read the board game title from a cover image.""" import base64 import openai if not os.path.exists(image_path): return None try: with open(image_path, "rb") as f: img_b64 = base64.b64encode(f.read()).decode() except Exception: return None # Read API config config_path = os.path.expanduser("~/.hermes/config.yaml") try: with open(config_path) as f: import yaml cfg = yaml.safe_load(f) api_key = cfg["providers"]["datenhimmel"]["api_key"] base_url = cfg["providers"]["datenhimmel"]["base_url"] except Exception: return None client = openai.OpenAI(base_url=base_url, api_key=api_key) try: r = client.chat.completions.create( model="gemini-3-flash-preview:cloud", messages=[{ "role": "user", "content": [ {"type": "text", "text": ( "This is a board game cover. What is the EXACT game title?\n" "Reply with ONLY the title, nothing else. " "If it's a known game, use the official German title if it exists.\n" "Examples: 'Cascadia', 'Flügelschlag', 'Die Siedler von Catan', 'Azul'" )}, {"type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{img_b64}"}}, ] }], max_tokens=50, temperature=0.1, ) title = r.choices[0].message.content.strip() # Clean up: remove quotes, extra text, limit length title = title.strip('"').strip("'").strip() if len(title) > 120: title = title[:120] return title if title else None except Exception as e: print(f"[vision error] {e}", file=sys.stderr) return None # ── Database helpers ──────────────────────────────────────────────── def get_db() -> sqlite3.Connection: if "db" not in g: g.db = sqlite3.connect(DB_PATH) g.db.row_factory = sqlite3.Row g.db.execute("PRAGMA journal_mode=WAL") return g.db @app.teardown_appcontext def close_db(_exception=None): db = g.pop("db", None) if db: db.close() # ── WhatsApp API helpers ──────────────────────────────────────────── def _gdpr_delete_sender(db: sqlite3.Connection, sender_id: str): """GDPR: Delete all submissions from a sender, leave a placeholder.""" # Delete media files (supports ||-separated paths) rows = db.execute( "SELECT media_path FROM submissions WHERE sender_id = ? AND channel = 'whatsapp'", (sender_id,), ).fetchall() for r in rows: if r["media_path"]: for p in r["media_path"].split("||"): if os.path.exists(p): os.remove(p) # Delete all submissions from this sender db.execute( "DELETE FROM submissions WHERE sender_id = ? AND channel = 'whatsapp'", (sender_id,), ) # Insert GDPR placeholder db.execute( """INSERT INTO submissions (channel, sender_id, type, content, status, category) VALUES ('whatsapp', ?, 'text', ?, 'gdpr_deleted', 'dsgvo')""", (sender_id, "Nutzer hat die Löschung verlangt"), ) def send_whatsapp_message(to: str, text: str) -> dict: """Send a text message back via WhatsApp Cloud API.""" url = f"https://graph.facebook.com/v25.0/{PHONE_NUMBER_ID}/messages" headers = { "Authorization": f"Bearer {META_TOKEN}", "Content-Type": "application/json", } payload = { "messaging_product": "whatsapp", "to": to, "type": "text", "text": {"body": text}, } r = requests.post(url, headers=headers, json=payload, timeout=15) return r.json() def generate_thorsten_tts(text: str) -> str | None: """Generate German TTS using Piper Thorsten voice. Returns path to OGG file or None.""" import subprocess import tempfile PIPER = "/home/hermes/.local/bin/piper" MODEL = "/home/hermes/.hermes/cache/piper-voices/de_DE-thorsten-medium.onnx" FFMPEG = "/home/hermes/.local/bin/ffmpeg" LD_PATH = "/home/hermes/.local/lib" ESPEAK_PATH = "/home/hermes/.local/share/espeak-ng-data" ogg_path = str(MEDIA_DIR / f"onboarding_{datetime.now().strftime('%Y%m%d%H%M%S')}.ogg") try: p1 = subprocess.Popen( [PIPER, "--model", MODEL, "--output-raw", "-"], stdin=subprocess.PIPE, stdout=subprocess.PIPE, stderr=subprocess.PIPE, env={"LD_LIBRARY_PATH": LD_PATH, "ESPEAK_DATA_PATH": ESPEAK_PATH, "PATH": os.environ.get("PATH", "")}, ) p2 = subprocess.Popen( [FFMPEG, "-f", "s16le", "-ar", "22050", "-ac", "1", "-i", "-", "-c:a", "libopus", "-b:a", "16k", "-f", "ogg", ogg_path, "-y"], stdin=p1.stdout, stdout=subprocess.PIPE, stderr=subprocess.PIPE, ) p1.stdin.write(text.encode("utf-8")) p1.stdin.close() p1.stdout.close() p2.communicate(timeout=30) p1.wait(timeout=10) if os.path.exists(ogg_path) and os.path.getsize(ogg_path) > 100: return ogg_path except Exception as e: print(f"[tts error] {e}", file=sys.stderr) return None def upload_whatsapp_media(file_path: str, mime_type: str = "audio/ogg") -> str | None: """Upload media to WhatsApp Cloud API. Returns media_id or None.""" url = f"https://graph.facebook.com/v25.0/{PHONE_NUMBER_ID}/media" headers = {"Authorization": f"Bearer {META_TOKEN}"} try: with open(file_path, "rb") as f: files = { "file": (os.path.basename(file_path), f, mime_type), } data = {"messaging_product": "whatsapp"} r = requests.post(url, headers=headers, files=files, data=data, timeout=20) result = r.json() return result.get("id") except Exception as e: print(f"[upload error] {e}", file=sys.stderr) return None def send_whatsapp_audio(to: str, media_id: str) -> dict: """Send an audio voice message via WhatsApp Cloud API.""" url = f"https://graph.facebook.com/v25.0/{PHONE_NUMBER_ID}/messages" headers = { "Authorization": f"Bearer {META_TOKEN}", "Content-Type": "application/json", } payload = { "messaging_product": "whatsapp", "to": to, "type": "audio", "audio": {"id": media_id}, } r = requests.post(url, headers=headers, json=payload, timeout=15) return r.json() def _send_email(to: str, subject: str, body: str) -> None: """Send an email notification using sendmail.""" import subprocess from email.message import EmailMessage msg = EmailMessage() msg["From"] = "noreply@brettspiel-news.de" msg["To"] = to msg["Subject"] = subject msg.set_content(body) try: subprocess.run( ["/usr/sbin/sendmail", "-t", "-oi"], input=msg.as_bytes(), timeout=10, check=True, ) except Exception: pass # silently ignore email failures def download_media(media_id: str) -> tuple[str | None, str | None]: """Download media from WhatsApp. Returns (local_path, mime_type) or (None, None).""" url = f"https://graph.facebook.com/v25.0/{media_id}" headers = {"Authorization": f"Bearer {META_TOKEN}"} r = requests.get(url, headers=headers, timeout=10) if r.status_code != 200: print(f"[download_media] Meta API returned {r.status_code}: {r.text[:200]}", file=sys.stderr) return None, None data = r.json() media_url = data.get("url") mime_type = data.get("mime_type", "unknown") if not media_url: print(f"[download_media] No URL in Meta response for media {media_id}", file=sys.stderr) return None, None r2 = requests.get(media_url, headers=headers, timeout=30) if r2.status_code != 200: print(f"[download_media] Media download returned {r2.status_code} for {media_id}", file=sys.stderr) return None, None ext = mime_type.split("/")[-1] if "/" in mime_type else "bin" filename = f"{media_id}.{ext}" local_path = MEDIA_DIR / filename local_path.write_bytes(r2.content) return str(local_path), mime_type def auto_process_bg(db_path: str, submission_id: int): """Background: after transcription, run LLM to summarize + extract halle/stand.""" import yaml as _yaml try: conn = sqlite3.connect(db_path) conn.row_factory = sqlite3.Row row = conn.execute("SELECT content, halle FROM submissions WHERE id=?", (submission_id,)).fetchone() if not row or not row["content"]: conn.close() return text = (row["content"] or "").strip() # Skip if text is too short or placeholder if len(text) < 20: conn.close() return # Read API key config_path = os.path.expanduser("~/.hermes/config.yaml") api_key = "" try: with open(config_path) as f: cfg = _yaml.safe_load(f) api_key = cfg.get("providers", {}).get("datenhimmel", {}).get("api_key", "") except Exception: pass if not api_key: conn.close() return prompt = ( "Du bist Redaktionsassistent für brettspiel-news.de. Analysiere folgende Community-Nachricht " "und antworte NUR mit diesem JSON-Format, kein weiterer Text:\n" '{"summary": "Kurze Zusammenfassung in 1-2 Sätzen, max 250 Zeichen, journalistisch, Präsens", ' '"halle": "Halle und Stand im Format z.B. H3 B123, oder null wenn nichts erkannt", ' '"spiel_titel": "Name des Brettspiels falls genannt, sonst null"}\n\n' f"Nachricht:\n{text[:2000]}" ) import requests as _req r = _req.post( "https://ui.datenhimmel.work/api/chat/completions", headers={"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"}, json={"model": "deepseek-v4-flash:cloud", "messages": [{"role": "user", "content": prompt}], "max_tokens": 300, "temperature": 0.2}, timeout=20, ) if r.status_code != 200: conn.close() return import json as _json data = r.json() result_text = data["choices"][0]["message"]["content"].strip() # Parse JSON from response (may have markdown wrapping) if "```" in result_text: result_text = result_text.split("```")[1] if result_text.startswith("json"): result_text = result_text[4:] result_text = result_text.strip() parsed = _json.loads(result_text) summary = parsed.get("summary", "").strip() llm_halle = parsed.get("halle", "").strip() if parsed.get("halle") and parsed["halle"] != "null" else None spiel_titel = parsed.get("spiel_titel", "").strip() if parsed.get("spiel_titel") and parsed["spiel_titel"] != "null" else None # Build update fields existing = conn.execute("SELECT halle, spiel_titel, summary FROM submissions WHERE id=?", (submission_id,)).fetchone() updates = [] params = [] if summary: updates.append("summary=?") params.append(summary[:500]) if llm_halle and not existing["halle"]: updates.append("halle=?") params.append(llm_halle) if spiel_titel and not existing["spiel_titel"]: updates.append("spiel_titel=?") params.append(spiel_titel) if updates: params.append(submission_id) conn.execute(f"UPDATE submissions SET {', '.join(updates)} WHERE id=?", params) conn.commit() conn.close() except Exception as e: print(f"[auto_process error] {e}", file=sys.stderr) def transcribe_audio(audio_path: str) -> str | None: """Transcribe an audio file using faster-whisper (local). Returns transcription text or None.""" import subprocess import json WHISPER_PYTHON = "/home/hermes/.hermes/venvs/speech/bin/python" script = ( "from faster_whisper import WhisperModel\n" "import sys, json\n" "model = WhisperModel('base', device='cpu', compute_type='int8')\n" "segments, info = model.transcribe(sys.argv[1])\n" "text = ' '.join(seg.text.strip() for seg in segments)\n" "print(json.dumps({'text': text, 'lang': info.language}))\n" ) try: result = subprocess.run( [WHISPER_PYTHON, "-c", script, audio_path], capture_output=True, text=True, timeout=120, ) if result.returncode == 0 and result.stdout.strip(): data = json.loads(result.stdout.strip()) return data.get("text", "") else: print(f"[transcribe error] {result.stderr[:200]}", file=sys.stderr) return None except Exception as e: print(f"[transcribe exception] {e}", file=sys.stderr) return None def _transcribe_bg(db_path: str, submission_id: int, audio_path: str): """Background thread: transcribe audio and update the DB record.""" text = transcribe_audio(audio_path) if text: try: conn = sqlite3.connect(db_path) conn.row_factory = sqlite3.Row row = conn.execute( "SELECT content FROM submissions WHERE id=?", (submission_id,) ).fetchone() if row: old = row["content"] or "" new_content = old.replace( "[🎤 Sprachnachricht — Transkription läuft...]", f"🎤 {text}", ) if new_content == old: # fallback if placeholder not found (e.g. old records) new_content = old + f"\n🎤 Transkription: {text}" conn.execute( "UPDATE submissions SET content=? WHERE id=?", (new_content, submission_id), ) conn.commit() conn.close() except Exception as e: print(f"[transcribe bg error] {e}", file=sys.stderr) # Auto-summarize + hall extraction after transcription auto_process_bg(db_path, submission_id) def transcribe_video(video_path: str) -> str | None: """Extract audio from video, then transcribe. Returns text or None.""" import subprocess import tempfile import json WHISPER_PYTHON = "/home/hermes/.hermes/venvs/speech/bin/python" FFMPEG = "/home/hermes/.local/bin/ffmpeg" LD_PATH = "/home/hermes/.local/lib" wav_path = None try: # Extract audio to temp WAV file fd, wav_path = tempfile.mkstemp(suffix=".wav") os.close(fd) result = subprocess.run( [FFMPEG, "-i", video_path, "-vn", "-acodec", "pcm_s16le", "-ar", "16000", "-ac", "1", wav_path, "-y"], capture_output=True, text=True, timeout=60, env={"LD_LIBRARY_PATH": LD_PATH, "PATH": os.environ.get("PATH", "")}, ) if not os.path.exists(wav_path) or os.path.getsize(wav_path) < 100: return None # Now transcribe the extracted audio return transcribe_audio(wav_path) except Exception as e: print(f"[video transcribe error] {e}", file=sys.stderr) return None finally: if wav_path and os.path.exists(wav_path): os.unlink(wav_path) def generate_video_thumbnail(video_path: str) -> str | None: """Extract a thumbnail frame from a video at 1 second. Returns path to .jpg or None.""" import subprocess FFMPEG = "/home/hermes/.local/bin/ffmpeg" thumb_path = video_path + ".thumb.jpg" # Don't regenerate if exists and is not empty if os.path.exists(thumb_path) and os.path.getsize(thumb_path) > 100: return thumb_path try: subprocess.run( [FFMPEG, "-i", video_path, "-ss", "00:00:01", "-vframes", "1", "-q:v", "5", thumb_path, "-y"], capture_output=True, timeout=30, check=True ) if os.path.exists(thumb_path) and os.path.getsize(thumb_path) > 100: return thumb_path except Exception: pass return None def _transcribe_video_bg(db_path: str, submission_id: int, video_path: str): """Background thread: extract audio from video, transcribe, update DB.""" text = transcribe_video(video_path) if text: try: conn = sqlite3.connect(db_path) conn.row_factory = sqlite3.Row row = conn.execute( "SELECT content FROM submissions WHERE id=?", (submission_id,) ).fetchone() if row: old = row["content"] or "" new_content = old.replace( "[🎬 Video — Transkription läuft...]", f"🎬 {text}", ) if new_content == old: new_content = old + f"\n🎬 Transkription: {text}" conn.execute( "UPDATE submissions SET content=? WHERE id=?", (new_content, submission_id), ) conn.commit() conn.close() except Exception as e: print(f"[video transcribe bg error] {e}", file=sys.stderr) # Auto-summarize + hall extraction after transcription auto_process_bg(db_path, submission_id) # ── Routes ────────────────────────────────────────────────────────── @app.route("/whatsapp/webhook", methods=["GET", "POST"]) def whatsapp_webhook(): """Meta WhatsApp Webhook. GET=verification, POST=incoming messages.""" if request.method == "GET": mode = request.args.get("hub.mode") token = request.args.get("hub.verify_token") challenge = request.args.get("hub.challenge") if mode == "subscribe" and token == VERIFY_TOKEN: return challenge, 200 return "Forbidden", 403 # POST: Incoming message body = request.get_json(force=True, silent=True) if not body: return "OK", 200 try: entries = body.get("entry", []) db = get_db() for entry in entries: changes = entry.get("changes", []) for change in changes: value = change.get("value", {}) contacts = value.get("contacts", [{}]) messages = value.get("messages", []) for msg in messages: sender_id = msg.get("from", "unknown") sender_name = contacts[0].get("profile", {}).get("name", "unknown") msg_type = msg.get("type", "text") content = "" media_path = None spiel_titel = None category_override = None # set to "ausverkauft" for #out if msg_type == "text": content = msg.get("text", {}).get("body", "") elif msg_type == "image": content = msg.get("image", {}).get("caption", "[Bild ohne Text]") media_id = msg.get("image", {}).get("id") if media_id: media_path, _ = download_media(media_id) elif msg_type == "audio": content = "[🎤 Sprachnachricht — Transkription läuft...]" media_id = msg.get("audio", {}).get("id") if media_id: media_path, _ = download_media(media_id) elif msg_type == "video": content = msg.get("video", {}).get( "caption", "[🎬 Video — Transkription läuft...]" ) media_id = msg.get("video", {}).get("id") if media_id: media_path, _ = download_media(media_id) elif msg_type == "document": content = msg.get("document", {}).get( "caption", "[Dokument]" ) media_id = msg.get("document", {}).get("id") if media_id: media_path, _ = download_media(media_id) else: content = f"[{msg_type}]" # #out detection: set category to "ausverkauft" and extract game title if "#out" in content.lower(): category_override = "ausverkauft" idx = content.lower().find("#out") after = content[idx + 4:].strip() if after: spiel_titel = re.split(r'[.!?\n]| - | – | — | ist | war | in ', after, maxsplit=1)[0].strip()[:200] # GDPR: "Meine Daten löschen" trigger if msg_type == "text" and content.strip().lower() == "meine daten löschen": _gdpr_delete_sender(db, sender_id) if META_TOKEN: try: send_whatsapp_message( sender_id, "✅ Alle deine Daten wurden vollständig und endgültig vom Server gelöscht. " "Es befinden sich keinerlei personenbezogene Daten mehr von dir bei uns. " "Lediglich ein anonymer Vermerk über die erfolgte Löschung bleibt für " "unsere Dokumentationspflicht.", ) except Exception: pass continue # Check for existing thread from this sender (5-min window) recent = db.execute( """SELECT id, content, media_path, halle FROM submissions WHERE channel='whatsapp' AND sender_id=? AND status != 'gdpr_deleted' ORDER BY created_at DESC LIMIT 1""", (sender_id,), ).fetchone() is_new_user = db.execute( "SELECT COUNT(*) FROM submissions WHERE channel='whatsapp' AND sender_id=? AND status != 'gdpr_deleted'", (sender_id,), ).fetchone()[0] == 0 THREAD_WINDOW_MINUTES = 5 thread_found = False if recent: age_check = db.execute( "SELECT (strftime('%s','now') - strftime('%s',created_at)) < ? FROM submissions WHERE id=?", (THREAD_WINDOW_MINUTES * 60, recent["id"]), ).fetchone() if age_check and age_check[0]: thread_found = True if thread_found: # Append to existing thread prefix = { "text": "", "image": "\n[🖼️ Bild] ", "audio": "\n[🎤 Sprachnachricht]", "video": "\n[🎬 Video] ", "document": "\n[📎 Dokument] ", }.get(msg_type, f"\n[{msg_type}] ") new_content = (recent["content"] or "") + prefix + content # Re-extract halle from combined content new_halle = extract_halle(new_content) or recent["halle"] db.execute( "UPDATE submissions SET content=?, halle=?, created_at=CURRENT_TIMESTAMP WHERE id=?", (new_content, new_halle, recent["id"]), ) # Check for #out in appended content — update category + spiel_titel if "#out" in content.lower(): out_title = None idx = content.lower().find("#out") after = content[idx + 4:].strip() if after: out_title = re.split(r'[.!?\n]| - | – | — | ist | war | in ', after, maxsplit=1)[0].strip()[:200] db.execute( "UPDATE submissions SET category=?, spiel_titel=? WHERE id=?", ("ausverkauft", out_title, recent["id"]), ) # Merge media paths (keep all, separated by ||) if media_path: merged_media = media_path if recent["media_path"]: merged_media = recent["media_path"] + "||" + media_path db.execute( "UPDATE submissions SET media_path=? WHERE id=?", (merged_media, recent["id"]), ) else: # New thread halle = extract_halle(content) cat = category_override or None db.execute( """INSERT INTO submissions (channel, sender_id, sender_name, type, content, media_path, status, halle, category, spiel_titel) VALUES (?, ?, ?, ?, ?, ?, 'new', ?, ?, ?)""", ("whatsapp", sender_id, sender_name, msg_type, content, media_path, halle, cat, spiel_titel), ) # Auto-reply: only on NEW threads, not appends if not thread_found and META_TOKEN: try: if is_new_user: reply = ( f"🎲 Hey {sender_name}! Cool, dass du da bist — willkommen in der " f"brettspiel-news.de Community!\n\n" f"Schick uns einfach, was dich bewegt: 💬 Text, 🎤 Sprachnachrichten, " f"🖼️ Fotos oder 🎬 Videos — alles rund um Brettspiele. Wir schauen uns alles an!\n\n" f"✍️ Nenn uns deinen Vornamen, wenn du magst — das ist deine Einwilligung, " f"dass wir dich als Quelle nennen, falls wir deinen Beitrag verwenden. " f"Ohne Namen schreiben wir „anonyme Quelle\".\n\n" f"🔒 „Meine Daten löschen\" genügt — und alles ist sofort und vollständig weg." ) send_whatsapp_message(sender_id, reply) # Thorsten voice: same text but without emojis import re tts_text = re.sub(r'[^\x00-\x7F\u00C0-\u00FF\u0100-\u017F\u0180-\u024F\u1E00-\u1EFF\u2018-\u201F\u2013\u2014\u2026\u00A0\u00AB\u00BB\u20AC]', '', reply) tts_text = re.sub(r' +', ' ', tts_text).strip() audio_path = generate_thorsten_tts(tts_text) if audio_path: media_id = upload_whatsapp_media(audio_path) if media_id: send_whatsapp_audio(sender_id, media_id) else: reply = ( f"📨 Danke {sender_name}! Ist angekommen — " f"wir kümmern uns drum." ) send_whatsapp_message(sender_id, reply) except Exception: pass # Transcribe audio in background (non-blocking) if msg_type == "audio" and media_path: import threading sub_id = recent["id"] if thread_found else db.execute( "SELECT last_insert_rowid()" ).fetchone()[0] threading.Thread( target=_transcribe_bg, args=(DB_PATH, sub_id, media_path), daemon=True, ).start() # Transcribe video in background if msg_type == "video" and media_path: import threading sub_id = recent["id"] if thread_found else db.execute( "SELECT last_insert_rowid()" ).fetchone()[0] threading.Thread( target=_transcribe_video_bg, args=(DB_PATH, sub_id, media_path), daemon=True, ).start() # Auto-summarize text/image submissions (LLM hall + summary) if msg_type in ("text", "image") and not thread_found and content and len(content.strip()) > 20: import threading sub_id = db.execute("SELECT last_insert_rowid()").fetchone()[0] # Only if regex didn't already find a halle if not halle: threading.Thread( target=auto_process_bg, args=(DB_PATH, sub_id), daemon=True, ).start() db.commit() except Exception as e: print(f"[webhook error] {e}", file=sys.stderr) return "OK", 200 return "OK", 200 @app.route("/admin") def admin_dashboard(): """Internal admin dashboard — filterable table of all submissions.""" db = get_db() channel_filter = request.args.get("channel", "") status_filter = request.args.get("status", "") category_filter = request.args.get("category", "") search = request.args.get("q", "") halle_filter = request.args.get("halle", "") query = "SELECT * FROM submissions WHERE deleted_at IS NULL" params: list = [] if channel_filter: query += " AND channel = ?" params.append(channel_filter) if status_filter: query += " AND status = ?" params.append(status_filter) if category_filter: query += " AND category = ?" params.append(category_filter) if halle_filter: query += " AND halle = ?" params.append(halle_filter) if search: query += " AND (content LIKE ? OR sender_id LIKE ?)" params.extend([f"%{search}%", f"%{search}%"]) query += " ORDER BY created_at DESC LIMIT 200" rows = db.execute(query, params).fetchall() channels = [ r[0] for r in db.execute("SELECT DISTINCT channel FROM submissions").fetchall() ] statuses = [ r[0] for r in db.execute("SELECT DISTINCT status FROM submissions").fetchall() ] categories = [ r[0] for r in db.execute( "SELECT DISTINCT category FROM submissions WHERE category IS NOT NULL" ).fetchall() ] # Channel totals totals_html = "".join( f'
Boardgame Social
| ID | Sender | Typ | 📍 Halle | 🎯 Spiel | Inhalt | Status | Zeit |
|---|

Dieser curl-Befehl sendet eine Fake-WhatsApp-Nachricht an den lokalen Webhook:
curl -X POST http://127.0.0.1:5002/whatsapp/webhook \\
-H "Content-Type: application/json" \\
-d '{
"object": "whatsapp_business_account",
"entry": [{
"id": "TEST",
"changes": [{
"value": {
"messaging_product": "whatsapp",
"metadata": {
"display_phone_number": "TEST",
"phone_number_id": "TEST"
},
"contacts": [{
"profile": {"name": "Max Mustermann"}
}],
"messages": [{
"from": "+491234567890",
"id": "wamid.test123",
"timestamp": "1718550000",
"type": "text",
"text": {"body": "Hallo! Gibt es Catan noch in Halle 5?"}
}]
}
}]
}]
}'
""".replace("{LOGO_B64}", LOGO_B64)
@app.route("/health")
def health():
return jsonify(
{
"status": "ok",
"db": str(DB_PATH),
"whatsapp_configured": bool(META_TOKEN),
"phone_number_id": PHONE_NUMBER_ID,
}
)
@app.route("/submission/📁 Datei nicht gefunden: {os.path.basename(path)}
' continue _, ext = os.path.splitext(path) mime = mime_map.get(ext.lower(), "application/octet-stream") try: basename = os.path.basename(path) src = f"/media/{basename}" media_html += f'' except Exception as e: media_html += f'Fehler: {e}
' # SVG type icons (16x16, BSN blue) _svg_icons = { "text": '', "image": '', "audio": '', "video": '', "document": '', } type_emoji = _svg_icons.get(row["type"], _svg_icons["document"]) return f"""{row['content'] or '(leer)'}Nur Medien mit Haken erscheinen im Frontend.
Löscht den Eintrag und alle Mediendateien unwiderruflich.
Noch keine ver\u00f6ffentlichten Beitr\u00e4ge. Komm bald wieder — die Community f\u00fcllt diesen Ort mit spannenden Geschichten.
""" + preview + """
""" + preview + """
Boardgame Social
Angaben gemäß § 5 DDG (Digitale-Dienste-Gesetz)
Daniel Krause
Brettspiel-News.de
Teichweg 13a
50374 Erftstadt
Deutschland
Telefon: +49 152 27909535
E-Mail: kontakt@brettspiel-news.de
USt-IdNr. gemäß § 27 a UStG: DE238244230
Daniel Krause
Teichweg 13a
50374 Erftstadt
Die Europäische Kommission stellt eine Plattform zur Online-Streitbeilegung (OS) bereit: https://ec.europa.eu/consumers/odr/
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Unser Angebot enthält Links zu externen Websites Dritter, auf deren Inhalte wir keinen Einfluss haben. Deshalb können wir für diese fremden Inhalte auch keine Gewähr übernehmen. Für die Inhalte der verlinkten Seiten ist stets der jeweilige Anbieter oder Betreiber der Seiten verantwortlich.
Die durch die Seitenbetreiber erstellten Inhalte und Werke auf diesen Seiten unterliegen dem deutschen Urheberrecht. Die Vervielfältigung, Bearbeitung, Verbreitung und jede Art der Verwertung außerhalb der Grenzen des Urheberrechtes bedürfen der schriftlichen Zustimmung des jeweiligen Autors bzw. Erstellers.
Soweit die Inhalte auf dieser Seite nicht vom Betreiber erstellt wurden, werden die Urheberrechte Dritter beachtet. Bei Bekanntwerden von Rechtsverletzungen werden wir derartige Inhalte umgehend entfernen.
BSN-Chatsystem (chat.datenhimmel.work) ist ein Angebot von Brettspiel-News.de, betrieben durch Daniel Krause.
""") @app.route("/datenschutz") def legal_datenschutz(): return _legal_page("Datenschutzerklärung", """Stand: 17. Juni 2026 — Geltungsbereich: BSN-Chatsystem (chat.datenhimmel.work)
Daniel Krause
Teichweg 13a
50374 Erftstadt
Deutschland
E-Mail: kontakt@brettspiel-news.de
Telefon: +49 152 27909535
Wir verarbeiten personenbezogene Daten nur, soweit dies zur Bereitstellung des BSN-Chatsystems erforderlich ist.
Daten werden gelöscht, sobald der Zweck entfällt, es sei denn gesetzliche Aufbewahrungspflichten bestehen.
Verarbeitet werden: WhatsApp-Telefonnummer, Profilname, Nachrichteninhalte, Medien (Bilder, Videos, Audio), Transkriptionen, KI-Zusammenfassungen.
Zweck: Entgegennahme von Community-Beiträgen, redaktionelle Sichtung, Veröffentlichung.
Empfänger: Meta Platforms, Inc. (USA) — zertifiziert unter EU-US Data Privacy Framework. DeepSeek / datenhimmel.work — zur KI-Zusammenfassung.
Verarbeitet werden: Name (optional), Nachricht, hochgeladene Medien, Metadaten, KI-Zusammenfassung, Referenz-ID.
Zweck und Rechtsgrundlagen wie unter Ziffer 3.
Bei Veröffentlichung werden sichtbar: Ihr Name (oder "Anonyme Quelle"), Beitragsinhalt, Medien, KI-Zusammenfassung, Halle/Kategorie. Ohne Namensangabe erfolgt die Veröffentlichung als "Anonyme Quelle".
Kein Zugriff auf nicht-veröffentlichte Daten. Keine Speicherung von Chat-Verläufen. Keine Verarbeitung personenbezogener Daten der Fragesteller.
Keine Cookies, kein Tracking. Nur localStorage für Theme-Präferenz (Dark/Light).
HTTPS-Verschlüsselung, Zugriffskontrolle, Datenminimierung, Löschkonzept.
Meta (USA): EU-US DPF-zertifiziert. DeepSeek/datenhimmel.work: Serverstandort zu prüfen; ggf. Standardvertragsklauseln nach Art. 46 DSGVO.
Kein Profiling nach Art. 22 DSGVO.
Dieses Dokument wurde mit Sorgfalt erstellt, ersetzt jedoch keine individuelle Rechtsberatung durch einen Fachanwalt für Datenschutzrecht.""") @app.route("/agb") def legal_agb(): return _legal_page("AGB", """
Geltungsbereich: BSN-Chatsystem (chat.datenhimmel.work) — Stand: 17. Juni 2026
Diese AGB regeln die Nutzung des BSN-Chatsystems, betrieben von:
Daniel Krause, Teichweg 13a, 50374 Erftstadt
E-Mail: kontakt@brettspiel-news.de
Mit der Nutzung erkennen Sie diese Bedingungen an.
Die Nutzung ist kostenlos. Kein Anspruch auf Veröffentlichung. Mindestalter: 16 Jahre.
Sie können Texte (max. 5.000 Zeichen), Fotos, Videos und Sprachnachrichten einreichen. Sie versichern: Urheberschaft, keine Rechtsverletzungen, Einwilligung abgebildeter Personen, keine rechtswidrigen Inhalte.
Sie räumen ein einfaches, zeitlich und räumlich unbeschränktes, unentgeltliches Nutzungsrecht ein (Speicherung, Bearbeitung, öffentliche Wiedergabe, Vervielfältigung). Sie bleiben Urheber. Das Recht erlischt bei Löschung.
Keine automatische Veröffentlichung. Redaktionelle Prüfung vorbehalten. Kein Anspruch auf Veröffentlichung. Bei Veröffentlichung: Vorname/Spitzname oder "Anonyme Quelle". Beiträge sind öffentlich einsehbar.
Keine rechtswidrigen, Rechte-verletzenden Inhalte, kein Spam, keine Malware, keine Desinformation. Sie stellen den Betreiber von Ansprüchen Dritter frei.
Der Betreiber kann Beiträge jederzeit ändern, zurücknehmen oder löschen.
So löschen Sie Ihre Daten:
WhatsApp: "Meine Daten löschen" senden.
Web: Referenz-ID an kontakt@brettspiel-news.de
Unbeschränkt bei Vorsatz/grober Fahrlässigkeit. Bei leichter Fahrlässigkeit nur bei Kardinalpflichtverletzung, begrenzt auf vorhersehbaren Schaden. Keine Haftung für Nutzerinhalte. §§ 8–10 DDG: Keine Überwachungspflicht, aber Entfernung bei Kenntnis.
Beantwortet Fragen auf Basis veröffentlichter Beiträge (DeepSeek V4 Flash). Antworten unverbindlich, können Fehler enthalten. Keine Speicherung von Chat-Verläufen.
Änderungen mit Wirkung für die Zukunft vorbehalten. Aktuelle Version unter chat.datenhimmel.work/agb.
Es gilt deutsches Recht unter Ausschluss des CISG. Gerichtsstand: Erftstadt (für Kaufleute). Salvatorische Klausel.
Diese AGB regeln ausschließlich das BSN-Chatsystem. Für brettspiel-news.de gelten die dort hinterlegten Bedingungen.""") @app.route('/media/
Die Datenschutzerklärung ist unter chat.datenhimmel.work/datenschutz abrufbar.
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