feat(x): X (Twitter) als Bezugsquelle pro Lage

X-Accounts werden analog zu Telegram als Quelle (source_type=x_account)
konfiguriert und pro Lage ueber include_x zugeschaltet. Der Scraper
(feeds/x_parser.py, twscrape) liest Account-Timelines, optional ueber
einen HTTP-Proxy mit Fallback auf direkten Abruf ueber die Server-IP.

- DB-Migration include_x, Pydantic-Modelle, incidents-Router
- Orchestrator-X-Pipeline plus Haiku-Account-Vorselektion
- sources-Router /x/validate, x_account-Typ in Stats und Frontend
- Lage-Einstellungen: X-Toggle neben international und Telegram
- twscrape als Abhaengigkeit

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

src/agents/orchestrator.py

@@ -34,6 +34,7 @@ CATEGORY_REPUTATION = {
     "international":         0.75,  # CNN, Guardian, NYT, Al Jazeera, France24
     "regional":              0.65,  # regionale Tageszeitungen
     "telegram":              0.5,   # OSINT-Kanaele — gemischte Qualitaet
+    "x":                     0.4,   # X/Twitter-Accounts, hohes Rauschen
     "sonstige":              0.4,   # unkategorisiert
     "boulevard":             0.3,   # Bild, Sun etc.
 }
@@ -750,6 +751,7 @@ class AgentOrchestrator:
             # Einschraenkung passiert in get_feeds_with_metadata.
             # Hinweis: source_lang_whitelist wird weiter unten geladen.
             include_telegram = bool(incident["include_telegram"]) if "include_telegram" in incident.keys() else False
+            include_x = bool(incident["include_x"]) if "include_x" in incident.keys() else False
             visibility = incident["visibility"] if "visibility" in incident.keys() else "public"
             created_by = incident["created_by"] if "created_by" in incident.keys() else None
             tenant_id = incident["tenant_id"] if "tenant_id" in incident.keys() else None
@@ -1078,20 +1080,67 @@ class AgentOrchestrator:
                 logger.info(f"Telegram-Pipeline: {len(articles)} Nachrichten")
                 return articles, None
 
+            async def _x_pipeline():
+                """X-Account-Suche (Twitter) mit KI-basierter Account-Selektion."""
+                from feeds.x_parser import XParser
+                x_parser = XParser()
+
+                # Alle X-Accounts laden
+                all_accounts = await x_parser._get_x_accounts(tenant_id=tenant_id)
+                if not all_accounts:
+                    logger.info("Keine X-Accounts konfiguriert")
+                    return [], None
+
+                # KI waehlt relevante Accounts aus
+                x_researcher = ResearcherAgent()
+                selected_accounts, x_sel_usage = await x_researcher.select_relevant_x_accounts(
+                    title, description, all_accounts
+                )
+                if x_sel_usage:
+                    usage_acc.add(x_sel_usage)
+
+                selected_ids = [acc["id"] for acc in selected_accounts]
+                logger.info(f"X-Selektion: {len(selected_ids)} von {len(all_accounts)} Accounts")
+
+                # Dynamische Keywords fuer X (eigener Aufruf, da parallel zu RSS)
+                cursor_x_hl = await db.execute(
+                    """SELECT COALESCE(headline_de, headline) as hl
+                       FROM articles WHERE incident_id = ?
+                       AND COALESCE(headline_de, headline) IS NOT NULL
+                       ORDER BY collected_at DESC LIMIT 30""",
+                    (incident_id,),
+                )
+                x_headlines = [row["hl"] for row in await cursor_x_hl.fetchall() if row["hl"]]
+                x_keywords, x_kw_usage = await x_researcher.extract_dynamic_keywords(title, x_headlines)
+                if x_kw_usage:
+                    usage_acc.add(x_kw_usage)
+
+                articles = await x_parser.search_accounts(
+                    title, tenant_id=tenant_id, keywords=x_keywords, account_ids=selected_ids
+                )
+                logger.info(f"X-Pipeline: {len(articles)} Posts")
+                return articles, None
+
             # Pipeline-Schritt 2: Nachrichten sammeln (Start)
             await _pipe_start("collect")
 
-            # Pipelines parallel starten (RSS + WebSearch + Podcasts + optional Telegram)
+            # Pipelines parallel starten (RSS + WebSearch + Podcasts + optional Telegram/X)
             pipelines = [_rss_pipeline(), _web_search_pipeline(), _podcast_pipeline()]
+            telegram_idx = x_idx = None
             if include_telegram:
+                telegram_idx = len(pipelines)
                 pipelines.append(_telegram_pipeline())
+            if include_x:
+                x_idx = len(pipelines)
+                pipelines.append(_x_pipeline())
 
             pipeline_results = await asyncio.gather(*pipelines)
 
             (rss_articles, rss_feed_usage) = pipeline_results[0]
             (search_results, search_usage, search_parse_failed) = pipeline_results[1]
             (podcast_articles, _podcast_usage) = pipeline_results[2]
-            telegram_articles = pipeline_results[3][0] if include_telegram else []
+            telegram_articles = pipeline_results[telegram_idx][0] if telegram_idx is not None else []
+            x_articles = pipeline_results[x_idx][0] if x_idx is not None else []
 
             # Podcast-Artikel in die RSS-Liste einfuegen (gleicher Downstream-Pfad)
             if podcast_articles:
@@ -1110,7 +1159,7 @@ class AgentOrchestrator:
             self._check_cancelled(incident_id)
 
             # Alle Ergebnisse zusammenführen
-            all_results = rss_articles + search_results + telegram_articles
+            all_results = rss_articles + search_results + telegram_articles + x_articles
             # Pipeline-Schritt 2: Nachrichten sammeln (fertig)
             try:
                 _delivering_sources = len({a.get("source", "") for a in all_results if a.get("source")})