feat: productionize local service — fix signal pipeline, lower thresholds, add company-name ticker extraction

- Point Ollama to local instance via host.docker.internal, use gemma3 model
- Remove Docker Ollama service (using host's Ollama instead)
- Add company-name-to-ticker mapping (Apple→AAPL, Tesla→TSLA, etc.) for RSS articles
- Lower signal thresholds for faster feedback with paper trading:
  - FinBERT confidence: 0.6→0.4, signal strength: 0.3→0.15
  - News strategy: article_count 2→1, confidence 0.5→0.3, score ±0.3→±0.15
- Fix market data BarSet access bug (BarSet.__contains__ returns False incorrectly)
- Fix market data SIP feed error by switching to IEX feed for free Alpaca accounts
- Fix nginx proxy routing for /api/auth/* to api-gateway /auth/*
- Add seed_sample_data script
- Update tests for new thresholds and alpaca mock modules

services/sentiment_analyzer/analyzers/finbert.py

@@ -34,7 +34,7 @@ class FinBERTAnalyzer:
             self._pipeline = pipeline(
                 "sentiment-analysis",
                 model=self.model_name,
-                return_all_scores=True,
+                top_k=None,
             )
             logger.info("FinBERT model loaded successfully")
         return self._pipeline
@@ -84,8 +84,9 @@ class FinBERTAnalyzer:
     def _parse_scores(results: list[list[dict[str, Any]]]) -> tuple[float, float]:
         """Map pipeline output to ``(score, confidence)``.
 
-        The ``return_all_scores=True`` pipeline returns a list of lists of dicts:
-        ``[[{"label": "positive", "score": 0.85}, ...]]``.
+        With ``top_k=None`` the pipeline returns either:
+          - ``[[{"label": "positive", "score": 0.85}, ...]]``  (older transformers)
+          - ``[{"label": "positive", "score": 0.85}, ...]``    (newer transformers)
 
         Mapping:
           - ``"positive"`` -> +1
@@ -98,8 +99,8 @@ class FinBERTAnalyzer:
         """
         label_map = {"positive": 1.0, "negative": -1.0, "neutral": 0.0}
 
-        # results is [[{label, score}, ...]]
-        scores = results[0]
+        # Handle both [[{label, score}, ...]] and [{label, score}, ...]
+        scores = results[0] if isinstance(results[0], list) else results
 
         sentiment_score = 0.0
         confidence = 0.0