Yijia-Xiao
d7b40a2a5c
Agents had no ground-truth ticker→company mapping, so the market analyst could pattern-match a price chart to the wrong company (e.g. TOTDY read as "TotalEnergies"), and every downstream agent inherited the bad framing. Resolve identity once at run start via a cached, fail-open yfinance lookup and inject company/sector/exchange into the shared instrument context that all twelve agents consume, with an explicit do-not-substitute instruction. Resolution runs on both the propagate() and CLI entry points. Also replaces the bare "Continue" message-clear placeholder, which some OpenAI-compatible providers interpreted as the user task, with a context-anchored placeholder carrying the resolved identity and date. #814 #888
76 lines
3.2 KiB
Python
76 lines
3.2 KiB
Python
from typing import Annotated
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from typing_extensions import TypedDict
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from langgraph.graph import MessagesState
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# Researcher team state
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class InvestDebateState(TypedDict):
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bull_history: Annotated[
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str, "Bullish Conversation history"
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] # Bullish Conversation history
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bear_history: Annotated[
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str, "Bearish Conversation history"
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] # Bullish Conversation history
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history: Annotated[str, "Conversation history"] # Conversation history
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current_response: Annotated[str, "Latest response"] # Last response
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judge_decision: Annotated[str, "Final judge decision"] # Last response
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count: Annotated[int, "Length of the current conversation"] # Conversation length
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# Risk management team state
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class RiskDebateState(TypedDict):
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aggressive_history: Annotated[
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str, "Aggressive Agent's Conversation history"
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] # Conversation history
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conservative_history: Annotated[
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str, "Conservative Agent's Conversation history"
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] # Conversation history
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neutral_history: Annotated[
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str, "Neutral Agent's Conversation history"
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] # Conversation history
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history: Annotated[str, "Conversation history"] # Conversation history
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latest_speaker: Annotated[str, "Analyst that spoke last"]
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current_aggressive_response: Annotated[
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str, "Latest response by the aggressive analyst"
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] # Last response
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current_conservative_response: Annotated[
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str, "Latest response by the conservative analyst"
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] # Last response
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current_neutral_response: Annotated[
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str, "Latest response by the neutral analyst"
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] # Last response
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judge_decision: Annotated[str, "Judge's decision"]
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count: Annotated[int, "Length of the current conversation"] # Conversation length
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class AgentState(MessagesState):
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company_of_interest: Annotated[str, "Company that we are interested in trading"]
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asset_type: Annotated[str, "Asset type under analysis such as stock or crypto"]
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instrument_context: Annotated[str, "Deterministic ticker identity resolved at run start"]
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trade_date: Annotated[str, "What date we are trading at"]
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sender: Annotated[str, "Agent that sent this message"]
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# research step
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market_report: Annotated[str, "Report from the Market Analyst"]
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sentiment_report: Annotated[str, "Report from the Sentiment Analyst"]
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news_report: Annotated[
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str, "Report from the News Researcher of current world affairs"
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]
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fundamentals_report: Annotated[str, "Report from the Fundamentals Researcher"]
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# researcher team discussion step
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investment_debate_state: Annotated[
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InvestDebateState, "Current state of the debate on if to invest or not"
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]
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investment_plan: Annotated[str, "Plan generated by the Analyst"]
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trader_investment_plan: Annotated[str, "Plan generated by the Trader"]
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# risk management team discussion step
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risk_debate_state: Annotated[
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RiskDebateState, "Current state of the debate on evaluating risk"
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]
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final_trade_decision: Annotated[str, "Final decision made by the Risk Analysts"]
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past_context: Annotated[str, "Memory log context injected at run start (same-ticker decisions + cross-ticker lessons)"]
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