51 lines
1.7 KiB
Python
51 lines
1.7 KiB
Python
"""LangGraph state definition for the Portfolio Manager workflow."""
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from __future__ import annotations
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from typing import Annotated
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from langgraph.graph import MessagesState
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def _last_value(existing: str, new: str) -> str:
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"""Reducer that keeps the last written value."""
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return new
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class PortfolioManagerState(MessagesState):
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"""State for the Portfolio Manager workflow.
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Sequential workflow — no parallel nodes — but all string JSON fields use
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the ``_last_value`` reducer for defensive consistency (prevents any future
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INVALID_CONCURRENT_GRAPH_UPDATE if parallelism is added later).
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``prices`` and ``scan_summary`` are plain dicts — written only by the
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caller (initial state) and never mutated by nodes, so no reducer needed.
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"""
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# Inputs (set once by the caller, never written by nodes)
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portfolio_id: str
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analysis_date: str
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prices: dict # ticker → price
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scan_summary: dict # macro scan output from ScannerGraph
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ticker_analyses: dict # per-ticker analysis results keyed by ticker symbol
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# Processing fields (string-serialised JSON — written by individual nodes)
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portfolio_data: Annotated[str, _last_value]
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risk_metrics: Annotated[str, _last_value]
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holding_reviews: Annotated[str, _last_value]
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prioritized_candidates: Annotated[str, _last_value]
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# Summary briefs (written by parallel summary agents)
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macro_brief: Annotated[str, _last_value]
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micro_brief: Annotated[str, _last_value]
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# Pre-fetched memory context strings
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macro_memory_context: Annotated[str, _last_value]
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micro_memory_context: Annotated[str, _last_value]
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pm_decision: Annotated[str, _last_value]
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execution_result: Annotated[str, _last_value]
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sender: Annotated[str, _last_value]
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