72 lines
3.2 KiB
Python
72 lines
3.2 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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def create_fundamentals_analyst(llm, toolkit):
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def fundamentals_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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if toolkit.config["online_tools"]:
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tools = [toolkit.get_fundamentals_from_llm]
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else:
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tools = [
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toolkit.get_finnhub_company_insider_sentiment,
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toolkit.get_finnhub_company_insider_transactions,
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toolkit.get_simfin_balance_sheet,
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toolkit.get_simfin_cashflow,
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toolkit.get_simfin_income_stmt,
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]
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system_message = (
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"You are a researcher tasked with analyzing fundamental information over the past week about a company. "
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"Please write a comprehensive report of the company's fundamental information such as "
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"financial documents, company profile, basic company financials, company financial history, "
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"insider sentiment and insider transactions to gain a full view of the company's fundamental information to inform traders. "
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"Make sure to include as much detail as possible. "
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"Do not simply state the trends are mixed. "
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"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, "
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"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}. 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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"fundamentals_report": report,
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}
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return fundamentals_analyst_node
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