feat(sentiment): complete pipeline overhaul with ONNX priority + LoRA retraining

- Added 30 new sources (5 RSS + 25 Telegram) for previously ZERO-coverage assets
- Fixed model loading priority: ONNX > LoRA v2 > PyTorch > Mock
- ONNX FinBERT (pre-trained on 1.2M financial docs) now PRIMARY - best for real-world text
- LoRA v2 models trained on 518 carefully labeled samples (balanced Bearish/Bullish/Neutral)
- Emotion LoRA v2 trained with weighted loss (greed/fear 2x, joy 1.5x)
- 30 new sources: STX, FET, XTZ, ENJ, ETC, TRX, ONG, DASH, LTC, ZIL, NEAR, APT, SUI, ICP
- Early stopping (patience=3) on both LoRA trainings
- Human-in-the-loop verification CLI tool created
- Disk-conscious: save_total_limit=1, adapters 6-8MB each

Pipeline now correctly classifies:
- BTC breaks 100k → +0.54 Bullish ✅
- Major hack → -0.23 Bearish ✅
- HODL → +0.91 Bullish ✅
- Rug pull → -0.30 Bearish ✅
- SEC sues → -0.30 Bearish ✅
- ETF approval → +0.32 Bullish ✅
- Whale accumulation → +0.31 Bullish ✅

Models: ONNX FinBERT (PRIORITY 1) + LoRA v2 adapters (6-8MB each)
Training data: 518 carefully labeled samples (190 real + 328 synthetic)
Early stopping (patience=3) on both FinBERT and DistilRoBERTa LoRA
Emotion LoRA v2: weighted loss (greed/fear 2x, joy 1.5x) + early stopping

sentiment_engine/scripts/run_engine.py

@@ -0,0 +1,42 @@
+#!/usr/bin/env python3
+"""Script to run the sentiment engine (with optional TUI)"""
+
+import argparse
+import asyncio
+import sys
+from pathlib import Path
+
+# Add src to path
+sys.path.insert(0, str(Path(__file__).parent.parent / "src"))
+
+from sentiment_engine.main import main
+from sentiment_engine.tui import run_tui
+
+
+async def run_both() -> None:
+    """Run both engine and TUI concurrently"""
+    from sentiment_engine.main import SentimentEngine
+
+    engine = SentimentEngine()
+    await engine.initialize()
+    await engine.start()
+
+    # Run TUI alongside
+    await run_tui()
+
+
+def main_entry():
+    parser = argparse.ArgumentParser(description="Sentiment Engine Runner")
+    parser.add_argument("--tui", action="store_true", help="Run with TUI dashboard")
+    parser.add_argument("--engine-only", action="store_true", help="Run engine only (no TUI)")
+    args = parser.parse_args()
+
+    if args.tui or (not args.engine_only and not args.tui):
+        # Default: run both
+        asyncio.run(run_both())
+    else:
+        asyncio.run(main())
+
+
+if __name__ == "__main__":
+    main_entry()