TradingAgents/tradingagents/agents/analysts/news_analyst.py

68 lines
3.1 KiB
Python

from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
import time
import json
from tradingagents.agents.utils.agent_utils import get_news, get_global_news
from tradingagents.dataflows.config import get_config
def create_news_analyst(llm):
def news_analyst_node(state):
current_date = state["trade_date"]
ticker = state["company_of_interest"]
tools = [
get_news,
# get_global_news,
]
system_message = (
"You are a News Analyst focused on IMMEDIATE market impact (1-2 weeks). "
"Interpret breaking news and upcoming macro events (CPI, Fed, Geopolitics) to determine short-term direction. "
"Focus on the 'Narrative' — what story is the market telling itself right now? "
"Use the available tools: get_news(query, start_date, end_date) for company-specific news. "
"Filter out noise and old news. Prioritize news that changes the short-term outlook."
+ "\n\nDECISION LOGIC:"
+ "\n- LONG: Distinct positive news cycle, analyst upgrades, or strong macro tailwinds."
+ "\n- SHORT: Distinct negative news cycle, lawsuits, regulatory hits, or macro headwinds."
+ "\n- HOLD: Mixed news, stale news, or high uncertainty waiting for a major event."
+ """ Make sure to append a Markdown table at the end of the report to organize key points in the report, organized and easy to read."""
+ "\n\nYOU MUST CONCLUDE YOUR REPORT WITH: 'SIGNAL: [LONG/SHORT/HOLD]'"
)
prompt = ChatPromptTemplate.from_messages(
[
(
"system",
"You are a helpful AI assistant, collaborating with other assistants."
" Use the provided tools to progress towards answering the question."
" If you are unable to fully answer, that's OK; another assistant with different tools"
" will help where you left off. Execute what you can to make progress."
" If you or any other assistant has the FINAL TRANSACTION PROPOSAL: **LONG/HOLD/SHORT** or deliverable,"
" prefix your response with FINAL TRANSACTION PROPOSAL: **LONG/HOLD/SHORT** so the team knows to stop."
" You have access to the following tools: {tool_names}.\n{system_message}"
"For your reference, the current date is {current_date}. We are looking at the company {ticker}",
),
MessagesPlaceholder(variable_name="messages"),
]
)
prompt = prompt.partial(system_message=system_message)
prompt = prompt.partial(tool_names=", ".join([tool.name for tool in tools]))
prompt = prompt.partial(current_date=current_date)
prompt = prompt.partial(ticker=ticker)
chain = prompt | llm.bind_tools(tools)
result = chain.invoke(state["messages"])
report = ""
if len(result.tool_calls) == 0:
report = result.content
return {
"messages": [result],
"news_report": report,
}
return news_analyst_node