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community_contributions/chrys/orchestrator.py

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+"""ARIA orchestrator: run all agents in sequence and pass state."""
+from typing import List, Tuple
+
+from config import get_watchlist, ALERT_SCORE_THRESHOLD, PUSHOVER_USER, PUSHOVER_TOKEN
+from models import AssetData, TechResult, SentimentResult, DecisionRecord
+from agents import DataFetcherAgent, TechAnalystAgent, SentimentAgent, DecisionAgent, NotifierAgent
+from db import log_decisions
+
+from config import (
+    ALPHA_VANTAGE_API_KEY,
+    COMMODITY_PRICE_API_KEY,
+    NEWSAPI_KEY,
+    OPENROUTER_API_KEY,
+    SENTIMENT_MODEL,
+)
+
+
+def run_pipeline() -> Tuple[List[DecisionRecord], List[AssetData]]:
+    watchlist = get_watchlist()
+    # 1. Data Fetcher
+    fetcher = DataFetcherAgent(alpha_key=ALPHA_VANTAGE_API_KEY, metals_key=COMMODITY_PRICE_API_KEY)
+    asset_data = fetcher.run(watchlist)
+    if not asset_data:
+        return [], []
+
+    # 2. Tech Analyst
+    tech_agent = TechAnalystAgent()
+    tech_results = tech_agent.run(asset_data)
+
+    # 3. Sentiment (only for non-neutral)
+    assets_for_sentiment = [tr.asset for tr in tech_results if tr.bias != "NEUTRAL"]
+    sentiment_agent = SentimentAgent(
+        newsapi_key=NEWSAPI_KEY,
+        model=SENTIMENT_MODEL,
+        openrouter_key=OPENROUTER_API_KEY,
+    )
+    sentiment_results = sentiment_agent.run(tech_results, assets_for_sentiment)
+    sentiment_by_asset = {s.asset: s for s in sentiment_results}
+    asset_by_asset = {a.asset: a for a in asset_data}
+
+    # 4. Decision Agent
+    decision_agent = DecisionAgent()
+    records = decision_agent.run(tech_results, sentiment_results, asset_data)
+
+    # 5. Notifier: only ALERT, top 1-2 by score, up to MAX per hour (handled in decision)
+    alert_records = [r for r in records if r.decision == "ALERT"]
+    alert_records.sort(key=lambda x: x.final_score, reverse=True)
+    to_send = alert_records[:2]  # Top 2
+    notifier = NotifierAgent(user=PUSHOVER_USER, token=PUSHOVER_TOKEN)
+    to_send_tuples: List[Tuple[DecisionRecord, TechResult, SentimentResult | None, AssetData | None]] = []
+    tech_by_asset = {t.asset: t for t in tech_results}
+    for rec in to_send:
+        tech = tech_by_asset[rec.asset]
+        sent = sentiment_by_asset.get(rec.asset)
+        ad = asset_by_asset.get(rec.asset)
+        to_send_tuples.append((rec, tech, sent, ad))
+    notifier.run(to_send_tuples)
+
+    # Audit log
+    log_decisions(records)
+    return records, asset_data