TradingAgents/tradingagents/agents/risk_mgmt/neutral_debator.py

54 lines
2.3 KiB
Python

import time
import json
from tradingagents.default_config import DEFAULT_CONFIG
from tradingagents.i18n import get_prompts
def create_neutral_debator(llm):
def neutral_node(state) -> dict:
risk_debate_state = state["risk_debate_state"]
history = risk_debate_state.get("history", "")
neutral_history = risk_debate_state.get("neutral_history", "")
current_risky_response = risk_debate_state.get("current_risky_response", "")
current_safe_response = risk_debate_state.get("current_safe_response", "")
market_research_report = state["market_report"]
sentiment_report = state["sentiment_report"]
news_report = state["news_report"]
fundamentals_report = state["fundamentals_report"]
trader_decision = state["trader_investment_plan"]
prompt = get_prompts("risk_mgmt", "neutral_debator") \
.replace("{max_tokens}", str(DEFAULT_CONFIG["max_tokens"])) \
.replace("{trader_decision}", trader_decision) \
.replace("{market_research_report}", market_research_report) \
.replace("{sentiment_report}", sentiment_report) \
.replace("{news_report}", news_report) \
.replace("{fundamentals_report}", fundamentals_report) \
.replace("{history}", history) \
.replace("{current_risky_response}", current_risky_response) \
.replace("{current_safe_response}", current_safe_response)
response = llm.invoke(prompt)
argument = f"Neutral Analyst: {response.content}"
new_risk_debate_state = {
"history": history + "\n" + argument,
"risky_history": risk_debate_state.get("risky_history", ""),
"safe_history": risk_debate_state.get("safe_history", ""),
"neutral_history": neutral_history + "\n" + argument,
"latest_speaker": "Neutral",
"current_risky_response": risk_debate_state.get(
"current_risky_response", ""
),
"current_safe_response": risk_debate_state.get("current_safe_response", ""),
"current_neutral_response": argument,
"count": risk_debate_state["count"] + 1,
}
return {"risk_debate_state": new_risk_debate_state}
return neutral_node