drjones/alpaca-llm-bot-v1
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Fix forced-paper execution semantics and add minimum forced notional control

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drjones
2026-02-27 02:35:22 -08:00
parent 1da0c04242
commit 4dcfc79635
3 changed files with 18 additions and 14 deletions
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1
.env.example
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@@ -14,6 +14,7 @@ TRADE_INTERVAL_HOURS=2
CURATE_INTERVAL_MINUTES=30
TIMEZONE=America/Los_Angeles
FORCE_PAPER_TRADES=true
FORCE_PAPER_MIN_USD=10
OLLAMA_URL=http://10.30.20.110:11434
OLLAMA_CURATOR_MODEL=gemma3:latest

30
bot.py
View File

@@ -69,6 +69,12 @@ def run_cycle():
memory_hits = qdrant_similar(symbol, json.dumps(news)[:2000], limit=5)
decision = llm_final_decision(symbol, news, strat, memory_hits)
if settings.paper_mode and settings.force_paper_trades and decision["action"] == "hold":
decision["action"] = "buy"
decision["confidence"] = max(decision.get("confidence", 0.0), settings.min_confidence)
decision["order_usd"] = max(decision.get("order_usd", 0.0), settings.force_paper_min_usd)
decision["reason"] = f"{decision.get('reason','')} | force_paper_trades"
drow = BotDecision(
symbol=symbol,
action=decision["action"],
@@ -82,11 +88,6 @@ def run_cycle():
db.commit()
db.refresh(drow)
if settings.paper_mode and settings.force_paper_trades and decision["action"] == "hold":
decision["action"] = "buy"
decision["confidence"] = max(decision.get("confidence", 0.0), settings.min_confidence)
decision["reason"] = f"{decision.get('reason','')} | force_paper_trades"
should_trade = decision["action"] in {"buy", "sell"} and decision["confidence"] >= settings.min_confidence
if should_trade:
@@ -103,15 +104,16 @@ def run_cycle():
drow.status = "executed" if ok else "failed"
db.add(drow)
trade = TradeExecution(
symbol=symbol,
side=decision["action"],
qty=float((res or {}).get("json", {}).get("qty", 0) or 0),
notional=notional,
alpaca_order_id=(res or {}).get("json", {}).get("id", ""),
raw=json.dumps({"decision": decision, "strategy": strat, "memory": memory_hits, "broker": res})[:60000],
)
db.add(trade)
if ok:
trade = TradeExecution(
symbol=symbol,
side=decision["action"],
qty=float((res or {}).get("json", {}).get("qty", 0) or 0),
notional=notional,
alpaca_order_id=(res or {}).get("json", {}).get("id", ""),
raw=json.dumps({"decision": decision, "strategy": strat, "memory": memory_hits, "broker": res})[:60000],
)
db.add(trade)
db.commit()
# learning memory + notes + orchestration signal

1
config.py
View File

@@ -21,6 +21,7 @@ class Settings:
curate_interval_minutes = int(os.getenv("CURATE_INTERVAL_MINUTES", "30"))
timezone = os.getenv("TIMEZONE", "America/Los_Angeles")
force_paper_trades = os.getenv("FORCE_PAPER_TRADES", "true").lower() == "true"
force_paper_min_usd = float(os.getenv("FORCE_PAPER_MIN_USD", "10"))
ollama_url = os.getenv("OLLAMA_URL", "http://10.30.20.110:11434")
ollama_curator_model = os.getenv("OLLAMA_CURATOR_MODEL", "gemma3:latest")