81 lines
3.7 KiB
Python
81 lines
3.7 KiB
Python
from datetime import datetime, timedelta, timezone
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from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
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from tradingagents.agents.utils.scanner_tools import (
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get_earnings_calendar,
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get_gap_candidates,
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get_topic_news,
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)
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from tradingagents.agents.utils.tool_runner import run_tool_loop
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def create_drift_scanner(llm):
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def drift_scanner_node(state):
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scan_date = state["scan_date"]
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tools = [get_gap_candidates, get_topic_news, get_earnings_calendar]
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gatekeeper_context = state.get("gatekeeper_universe_report", "")
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market_context = state.get("market_movers_report", "")
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sector_context = state.get("sector_performance_report", "")
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context_chunks = []
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if gatekeeper_context:
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context_chunks.append(f"Gatekeeper universe:\n{gatekeeper_context}")
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if market_context:
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context_chunks.append(f"Market regime context:\n{market_context}")
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if sector_context:
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context_chunks.append(f"Sector rotation context:\n{sector_context}")
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context_section = f"\n\n{'\n\n'.join(context_chunks)}" if context_chunks else ""
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try:
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start_date = datetime.strptime(scan_date, "%Y-%m-%d").date()
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except ValueError:
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start_date = datetime.now(timezone.utc).date()
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end_date = start_date + timedelta(days=14)
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system_message = (
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"You are a drift-window scanner focused on 1-3 month continuation setups. "
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"Stay global and bounded: the gatekeeper universe defines the only admissible stock set, and the Finviz "
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"gap scan provides the event subset within that universe.\n\n"
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"You MUST perform these bounded searches:\n"
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"1. Call get_gap_candidates to retrieve Finviz gap candidates from the gatekeeper universe.\n"
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"2. Call get_topic_news for earnings beats, raised guidance, and positive post-event follow-through.\n"
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f"3. Call get_earnings_calendar from {start_date.isoformat()} to {end_date.isoformat()}.\n\n"
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"Then write a concise report covering:\n"
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"(1) which gatekeeper names look most likely to sustain a 1-3 month drift,\n"
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"(2) which sectors show the cleanest drift setup rather than short-covering noise,\n"
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"(3) 5-8 candidate tickers surfaced from the gap subset plus catalyst confirmation,\n"
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"(4) the key evidence for continuation risk versus reversal risk."
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f"{context_section}"
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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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" 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}.",
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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=scan_date)
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chain = prompt | llm.bind_tools(tools)
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result = run_tool_loop(chain, state["messages"], tools)
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return {
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"messages": [result],
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"drift_opportunities_report": result.content or "",
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"sender": "drift_scanner",
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}
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return drift_scanner_node
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