90 lines
5.5 KiB
Python
90 lines
5.5 KiB
Python
from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
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import time
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import json
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from tradingagents.agents.utils.agent_utils import (
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get_asset_news,
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get_global_news_unified as get_global_news,
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)
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from tradingagents.dataflows.config import get_config
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def create_news_analyst(llm):
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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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asset_class = state.get("asset_class", "equity")
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# Use unified tools for all asset classes
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tools = [get_asset_news, get_global_news]
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# Asset-specific messaging
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if asset_class == "commodity":
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system_message = (
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f"You are a news researcher tasked with analyzing recent news and trends for the commodity {ticker}. "
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"Please write a comprehensive report of relevant news over the past week that impacts this commodity's price. "
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f"Use the available tools: get_asset_news(symbol, start_date, end_date, asset_class=\"{asset_class}\") for commodity-specific news, "
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"and get_global_news(curr_date, look_back_days) for broader macroeconomic context (do NOT specify limit). "
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f"IMPORTANT: Always pass asset_class=\"{asset_class}\" when calling get_asset_news. If get_asset_news returns limited results, make sure to use get_global_news to provide additional market context. "
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"Focus on supply/demand factors, geopolitical events, weather impacts (for agriculture), and macroeconomic trends. "
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"Do not simply state the trends are mixed, provide detailed and fine-grained analysis."
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+ """ Make sure to append a Markdown table at the end of the report to organize key points."""
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)
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elif asset_class == "crypto":
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system_message = (
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f"You are a news researcher tasked with analyzing recent news and trends for the cryptocurrency {ticker}. "
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"Please write a comprehensive report of relevant news over the past week that impacts this cryptocurrency's price. "
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f"Use the available tools: get_asset_news(symbol, start_date, end_date, asset_class=\"{asset_class}\") for crypto-specific blockchain news, "
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"and get_global_news(curr_date, look_back_days) for broader macroeconomic context (do NOT specify limit). "
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f"IMPORTANT: Always pass asset_class=\"{asset_class}\" when calling get_asset_news. If get_asset_news returns limited results, make sure to use get_global_news to provide additional market context. "
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"Focus on regulatory developments, adoption trends, technological updates, market sentiment, and macroeconomic factors affecting crypto. "
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"Do not simply state the trends are mixed, provide detailed and fine-grained analysis."
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+ """ Make sure to append a Markdown table at the end of the report to organize key points."""
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)
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else: # equity
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system_message = (
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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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f"Use the available tools: get_asset_news(symbol, start_date, end_date, asset_class=\"{asset_class}\") for company-specific or targeted news searches, "
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"and get_global_news(curr_date, look_back_days) for broader macroeconomic news (omit limit parameter). "
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f"IMPORTANT: Always pass asset_class=\"{asset_class}\" when calling get_asset_news. "
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"Do not simply state the trends are mixed, provide detailed and fine-grained 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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prompt = ChatPromptTemplate.from_messages(
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[
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(
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"system",
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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"
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" 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,"
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" 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: {tool_names}.\n{system_message}"
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"For your reference, the current date is {current_date}. We are looking at the company {ticker}",
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),
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MessagesPlaceholder(variable_name="messages"),
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]
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)
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prompt = prompt.partial(system_message=system_message)
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prompt = prompt.partial(tool_names=", ".join([tool.name for tool in tools]))
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prompt = prompt.partial(current_date=current_date)
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prompt = prompt.partial(ticker=ticker)
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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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