60 lines
1.8 KiB
Python
60 lines
1.8 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.default_config import DEFAULT_CONFIG
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from tradingagents.i18n import get_prompts
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def create_market_analyst(llm, toolkit):
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def market_analyst_node(state):
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current_date = state["trade_date"]
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ticker = state["asset_of_interest"]
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asset_name = state["asset_of_interest"]
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investment_preferences = state.get("investment_preferences", "")
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tools = [
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toolkit.get_binance_data,
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toolkit.get_taapi_bulk_indicators
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]
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system_message = (
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get_prompts("analysts", "market_analyst", "system_message")
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.replace("{max_tokens}", str(DEFAULT_CONFIG["max_tokens"]))
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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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get_prompts("analysts", "template")
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),
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(
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"system",
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get_prompts("user_preferences", "system_message")
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.replace("{investment_preferences}", investment_preferences)
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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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"market_report": report,
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}
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return market_analyst_node
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