TradingAgents/tradingagents/agents/analysts/seeking_alpha_analyst.py

72 lines
3.3 KiB
Python

from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
import time
import json
from tradingagents.agents.utils.seeking_alpha_tools import get_seeking_alpha_pdfs
from tradingagents.dataflows.config import get_config
def create_seeking_alpha_analyst(llm):
def seeking_alpha_analyst_node(state):
current_date = state["trade_date"]
ticker = state["company_of_interest"]
company_name = state["company_of_interest"]
tools = [
get_seeking_alpha_pdfs,
]
system_message = (
"You are a research analyst specializing in analyzing Seeking Alpha reports and research documents. "
"Your role is to extract and analyze key insights from PDF research documents about companies. "
"These documents typically contain detailed analysis, financial projections, investment theses, and expert opinions. "
"Please read through the PDF documents carefully and write a comprehensive report that includes:\n"
"- Key investment theses and arguments presented\n"
"- Financial analysis and projections mentioned\n"
"- Risk factors and concerns highlighted\n"
"- Expert opinions and recommendations\n"
"- Any quantitative metrics or data points\n"
"- Overall sentiment and outlook\n\n"
"Make sure to provide detailed and nuanced analysis. Do not simply state that the information is mixed - "
"provide specific insights, numbers, and detailed analysis that may help traders make 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."
)
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}. The company we want to look at is {ticker}",
),
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(ticker=ticker)
chain = prompt | llm.bind_tools(tools)
result = chain.invoke(state["messages"])
report = ""
if len(result.tool_calls) == 0:
report = result.content
return {
"messages": [result],
"seeking_alpha_report": report,
}
return seeking_alpha_analyst_node