79 lines
3.7 KiB
Python
79 lines
3.7 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 get_economic_indicators, get_yield_curve, get_fed_calendar
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from tradingagents.dataflows.config import get_config
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def create_macro_analyst(llm):
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def macro_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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company_name = state["company_of_interest"]
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tools = [
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get_economic_indicators,
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get_yield_curve,
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get_fed_calendar,
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]
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system_message = (
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"You are a macro economic analyst tasked with analyzing Federal Reserve data, economic indicators, and macroeconomic trends. "
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"Your objective is to write a comprehensive report detailing current economic conditions, monetary policy implications, and their impact on financial markets. "
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"Analyze key indicators such as:\n"
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"- Federal Funds Rate and monetary policy trajectory\n"
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"- Inflation indicators (CPI, PPI)\n"
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"- Employment data (unemployment rate, payrolls)\n"
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"- Treasury yield curve and inversion signals\n"
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"- Economic growth indicators (GDP, PMI)\n"
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"- Market volatility (VIX)\n\n"
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"Provide detailed analysis of:\n"
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"1. Current economic cycle positioning\n"
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"2. Federal Reserve policy stance and likely direction\n"
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"3. Inflation and employment trends\n"
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"4. Yield curve implications for recession risk\n"
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"5. Market implications and trading considerations\n\n"
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"Use the available tools: `get_economic_indicators` for comprehensive economic data, "
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"`get_yield_curve` for Treasury yields and inversion analysis, and `get_fed_calendar` for FOMC schedule and policy trajectory. "
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"Make sure to provide detailed, actionable insights rather than generic summaries. "
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"Append a Markdown table at the end summarizing key macro indicators and their implications."
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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}. The company we want to look at is {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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"macro_report": report,
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}
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return macro_analyst_node
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