74 lines
2.7 KiB
Python
74 lines
2.7 KiB
Python
from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
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from tradingagents.agents.utils.agent_utils import get_news, get_global_news
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def create_news_analyst(llm, config):
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"""Create the news analyst node with language support."""
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def news_analyst_node(state):
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current_date = state["trade_date"]
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ticker = state["company_of_interest"]
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tools = [
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get_news,
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get_global_news,
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]
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language = config["output_language"]
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language_prompts = {
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"en": "",
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"zh-tw": "Use Traditional Chinese as the output.",
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"zh-cn": "Use Simplified Chinese as the output.",
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}
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language_prompt = language_prompts.get(language, "")
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system_message = (
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f"""
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You are a news researcher tasked with analyzing recent news and trends over the past week.
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Please write a comprehensive report of the current state of the world that is relevant for trading and macroeconomics.
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Use the available tools: get_news(query, start_date, end_date) for company-specific or targeted news searches, and get_global_news(curr_date, look_back_days, limit) for broader macroeconomic news.
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Do not simply state the trends are mixed, provide detailed and finegrained analysis and insights that may help traders make decisions.
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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.
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"""
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)
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prompt = ChatPromptTemplate.from_messages(
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[
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(
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"system",
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f"""
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You are a helpful AI assistant, collaborating with other assistants.
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Use the provided tools to progress towards answering the question.
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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.
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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.
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You have access to the following tools: {tools}.
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{system_message}
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For your reference, the current date is {current_date}.
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The company we want to look at is {ticker}
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Output language: ***{language_prompt}***
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""",
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),
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MessagesPlaceholder(variable_name="messages"),
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]
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)
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chain = prompt | llm.bind_tools(tools)
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result = chain.invoke(state["messages"])
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report = ""
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if len(result.tool_calls) == 0:
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report = result.content
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return {
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"messages": [result],
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"news_report": report,
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}
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return news_analyst_node
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