TradingAgents/tradingagents/agents/utils/agent_utils.py

62 lines
1.9 KiB
Python

from langchain_core.messages import HumanMessage, RemoveMessage
# Import tools from separate utility files
from tradingagents.agents.utils.core_stock_tools import (
get_stock_data
)
from tradingagents.agents.utils.technical_indicators_tools import (
get_indicators
)
from tradingagents.agents.utils.fundamental_data_tools import (
get_fundamentals,
get_balance_sheet,
get_cashflow,
get_income_statement
)
from tradingagents.agents.utils.news_data_tools import (
get_news,
get_insider_transactions,
get_global_news
)
def get_language_instruction() -> str:
"""Return a prompt instruction for the configured output language.
Returns empty string when English (default), so no extra tokens are used.
Only applied to user-facing agents (analysts, portfolio manager).
Internal debate agents stay in English for reasoning quality.
"""
from tradingagents.dataflows.config import get_config
lang = get_config().get("output_language", "English")
if lang.strip().lower() == "english":
return ""
return f" Write your entire response in {lang}."
def build_instrument_context(ticker: str) -> str:
"""Describe the exact instrument so agents preserve exchange-qualified tickers."""
return (
f"The instrument to analyze is `{ticker}`. "
"Use this exact ticker in every tool call, report, and recommendation, "
"preserving any exchange suffix (e.g. `.TO`, `.L`, `.HK`, `.T`)."
)
def create_msg_delete():
def delete_messages(state):
"""Clear messages and add placeholder for Anthropic compatibility"""
messages = state["messages"]
# Remove all messages
removal_operations = [RemoveMessage(id=m.id) for m in messages]
# Add a minimal placeholder message
placeholder = HumanMessage(content="Continue")
return {"messages": removal_operations + [placeholder]}
return delete_messages