merge upstream main into crypto-analysis-mvp

tradingagents/agents/analysts/news_analyst.py

@@ -1,16 +1,21 @@
 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.agents.utils.agent_utils import (
+    build_instrument_context,
+    get_global_news,
+    get_language_instruction,
+    get_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"]
         asset_type = state.get("asset_type", "stock")
         asset_label = "company" if asset_type == "stock" else "asset"
+        instrument_context = build_instrument_context(
+            state["company_of_interest"], asset_type
+        )
 
         tools = [
             get_news,
@@ -18,8 +23,9 @@ def create_news_analyst(llm):
         ]
 
         system_message = (
-            f"You are a news researcher tasked with analyzing recent news and trends over the past week. Please write a comprehensive report of the current state of the world that is relevant for trading and macroeconomics. Use the available tools: get_news(query, start_date, end_date) for {asset_label}-specific or targeted news searches, and get_global_news(curr_date, look_back_days, limit) for broader macroeconomic news. Do not simply state the trends are mixed, provide detailed and finegrained analysis and insights that may help traders make decisions."
+            f"You are a news researcher tasked with analyzing recent news and trends over the past week. Please write a comprehensive report of the current state of the world that is relevant for trading and macroeconomics. Use the available tools: get_news(query, start_date, end_date) for {asset_label}-specific or targeted news searches, and get_global_news(curr_date, look_back_days, limit) for broader macroeconomic news. Provide specific, actionable insights with supporting evidence to help traders make informed decisions."
             + """ 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."""
+            + get_language_instruction()
         )
 
         prompt = ChatPromptTemplate.from_messages(
@@ -33,7 +39,7 @@ def create_news_analyst(llm):
                     " If you or any other assistant has the FINAL TRANSACTION PROPOSAL: **BUY/HOLD/SELL** or deliverable,"
                     " prefix your response with FINAL TRANSACTION PROPOSAL: **BUY/HOLD/SELL** 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 {asset_label} {ticker}",
+                    "For your reference, the current date is {current_date}. {instrument_context}",
                 ),
                 MessagesPlaceholder(variable_name="messages"),
             ]
@@ -42,8 +48,7 @@ def create_news_analyst(llm):
         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)
-        prompt = prompt.partial(asset_label=asset_label)
+        prompt = prompt.partial(instrument_context=instrument_context)
 
         chain = prompt | llm.bind_tools(tools)
         result = chain.invoke(state["messages"])