TradingAgents/tradingagents/dataflows/google.py

48 lines
1.6 KiB
Python

from typing import Annotated
from datetime import datetime
from dateutil.relativedelta import relativedelta
from .googlenews_utils import getNewsData
def get_google_news(
query: Annotated[str, "Query to search with"],
start_date: Annotated[str, "Start date in yyyy-mm-dd format"],
end_date: Annotated[str, "End date in yyyy-mm-dd format"],
) -> str:
query = query.replace(" ", "+")
# Direct pass-through since getNewsData handles the dates
news_results = getNewsData(query, start_date, end_date)
news_str = ""
for news in news_results:
title = str(news.get('title', ''))
source = str(news.get('source', ''))
snippet = str(news.get('snippet', ''))
news_str += f"### {title} (source: {source}) \n\n{snippet}\n\n"
if len(news_results) == 0:
return ""
return f"## {query} Google News, from {start_date} to {end_date}:\n\n{news_str}"
def get_google_global_news(
curr_date: Annotated[str, "Current date in yyyy-mm-dd format"],
look_back_days: Annotated[int, "Number of days to look back"] = 7,
limit: Annotated[int, "Maximum number of articles to return"] = 5
) -> str:
"""
Retrieve global news data using Google News scraper.
Adapts the signature (curr_date, look_back_days) to (start_date, end_date).
"""
# Calculate start date
end_date_dt = datetime.strptime(curr_date, "%Y-%m-%d")
start_date_dt = end_date_dt - relativedelta(days=look_back_days)
start_date = start_date_dt.strftime("%Y-%m-%d")
# Use a generic global market query
query = "Global Financial Markets"
return get_google_news(query, start_date, curr_date)