TradingAgents/tradingagents/agents/analysts/fundamentals_analyst.py

76 lines
3.2 KiB
Python

from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
from tradingagents.agents.utils.agent_utils import (
build_fundamentals_context,
build_instrument_context,
get_balance_sheet,
get_cashflow,
get_fundamentals,
get_income_statement,
get_insider_transactions,
get_language_instruction,
)
from tradingagents.dataflows.config import get_config
def create_fundamentals_analyst(llm):
def fundamentals_analyst_node(state):
current_date = state["trade_date"]
symbol = state["company_of_interest"]
instrument_context = build_instrument_context(symbol)
fundamentals_context = build_fundamentals_context(symbol)
tools = [
get_fundamentals,
get_balance_sheet,
get_cashflow,
get_income_statement,
]
system_message = (
"You are a researcher tasked with analyzing fundamental information about the target trading instrument. "
"Write a comprehensive report that helps traders understand intrinsic value drivers and key risks. "
"Use as much concrete evidence as possible."
+ " 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."
+ " Use the available tools: `get_fundamentals` for overview data, `get_balance_sheet`, `get_cashflow`, and `get_income_statement` for financial statement detail when available."
+ f" {fundamentals_context}"
+ get_language_instruction(),
)
prompt = ChatPromptTemplate.from_messages(
[
(
"system",
"You are a helpful AI assistant, collaborating with other assistants."
" Use the provided tools to progress towards answering the question."
" 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."
" 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}. {instrument_context}",
),
MessagesPlaceholder(variable_name="messages"),
]
)
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(instrument_context=instrument_context)
chain = prompt | llm.bind_tools(tools)
result = chain.invoke(state["messages"])
report = ""
if len(result.tool_calls) == 0:
report = result.content
return {
"messages": [result],
"fundamentals_report": report,
}
return fundamentals_analyst_node