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refactor: one name per decision in the state and its log

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- the Research Manager's plan and the Portfolio Manager's decision live only in investment_plan and final_trade_decision; the debate states no longer copy them as judge_decision
- the saved state log writes the Trader's plan as trader_investment_plan, its state key
- the report tree, the final display and the live CLI read the decisions from those fields
This commit is contained in:
Yijia-Xiao
2026-09-24 19:38:41 +00:00
parent 1d20780095
commit cf960d6382
16 changed files with 46 additions and 43 deletions
Download Patch File Download Diff File Expand all files Collapse all files
cli/display.py
+6 -6
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@@ -404,8 +404,8 @@ def display_complete_report(final_state):
research.append(("Bull Researcher", debate["bull_history"]))
if debate.get("bear_history"):
research.append(("Bear Researcher", debate["bear_history"]))
if debate.get("judge_decision"):
research.append(("Research Manager", debate["judge_decision"]))
if final_state.get("investment_plan"):
research.append(("Research Manager", final_state["investment_plan"]))
if research:
console.print(Panel("[bold]II. Research Team Decision[/bold]", border_style="magenta"))
for title, content in research:
@@ -431,10 +431,10 @@ def display_complete_report(final_state):
for title, content in risk_reports:
console.print(Panel(Markdown(content), title=title, border_style="blue", padding=(1, 2)))
# V. Portfolio Manager Decision
if risk.get("judge_decision"):
console.print(Panel("[bold]V. Portfolio Manager Decision[/bold]", border_style="green"))
console.print(Panel(Markdown(risk["judge_decision"]), title="Portfolio Manager", border_style="blue", padding=(1, 2)))
# V. Portfolio Manager Decision
if final_state.get("final_trade_decision"):
console.print(Panel("[bold]V. Portfolio Manager Decision[/bold]", border_style="green"))
console.print(Panel(Markdown(final_state["final_trade_decision"]), title="Portfolio Manager", border_style="blue", padding=(1, 2)))
def update_research_team_status(status):
cli/run.py
+2 -2
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@@ -253,7 +253,7 @@ def run_analysis(checkpoint: bool | None = None, portfolio=None):
debate_state = chunk["investment_debate_state"]
bull_hist = debate_state.get("bull_history", "").strip()
bear_hist = debate_state.get("bear_history", "").strip()
judge = debate_state.get("judge_decision", "").strip()
judge = (chunk.get("investment_plan") or "").strip()
# Only update status when there's actual content
if bull_hist or bear_hist:
@@ -288,7 +288,7 @@ def run_analysis(checkpoint: bool | None = None, portfolio=None):
agg_hist = risk_state.get("aggressive_history", "").strip()
con_hist = risk_state.get("conservative_history", "").strip()
neu_hist = risk_state.get("neutral_history", "").strip()
judge = risk_state.get("judge_decision", "").strip()
judge = (chunk.get("final_trade_decision") or "").strip()
if agg_hist:
if message_buffer.agent_status.get("Aggressive Analyst") != "completed":
tests/test_cli_display.py
+15 -2
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@@ -48,9 +48,9 @@ def _state(ticker, final="评级: 买入"):
"fundamentals_report": "基本面", "investment_plan": "计划",
"trader_investment_plan": "交易计划", "final_trade_decision": final, "final_rating": "REVIEW",
"investment_debate_state": {"bull_history": "", "bear_history": "", "history": "",
"current_response": "", "judge_decision": "", "count": 0},
"current_response": "", "count": 0},
"risk_debate_state": {"aggressive_history": "", "conservative_history": "",
"neutral_history": "", "history": "", "judge_decision": "",
"neutral_history": "", "history": "",
"latest_speaker": "", "current_aggressive_response": "",
"current_conservative_response": "", "current_neutral_response": "",
"count": 0},
@@ -76,6 +76,19 @@ def test_the_state_log_keeps_non_ascii_readable(tmp_path):
assert json.loads(written) # still valid JSON
@pytest.mark.unit
def test_the_state_log_names_each_field_as_the_state_does(tmp_path):
"""One name per field: the Trader's plan under its state key, and no second
copy of the managers' decisions under the debate states."""
_bare_graph(tmp_path)._log_state("2026-09-01", _state("NVDA"))
logged = json.loads(next(tmp_path.rglob("full_states_log*.json")).read_text(encoding="utf-8"))
assert logged["trader_investment_plan"] == "交易计划"
assert logged["investment_plan"] == "计划"
assert "trader_investment_decision" not in logged
assert "judge_decision" not in json.dumps(logged)
@pytest.mark.unit
def test_the_live_display_does_not_scroll_the_terminal():
"""A layout taller than the window makes rich redraw by scrolling, which
tests/test_memory_log.py
+2 -3
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@@ -74,7 +74,6 @@ def _make_pm_state(past_context=""):
"aggressive_history": "",
"conservative_history": "",
"neutral_history": "",
"judge_decision": "",
"current_aggressive_response": "",
"current_conservative_response": "",
"current_neutral_response": "",
@@ -906,13 +905,13 @@ class TestLegacyRemoval:
"fundamentals_report": "",
"investment_debate_state": {
"bull_history": "", "bear_history": "", "history": "",
"current_response": "", "judge_decision": "",
"current_response": "",
},
"investment_plan": "",
"trader_investment_plan": "",
"risk_debate_state": {
"aggressive_history": "", "conservative_history": "",
"neutral_history": "", "history": "", "judge_decision": "",
"neutral_history": "", "history": "",
"current_aggressive_response": "", "current_conservative_response": "",
"current_neutral_response": "", "count": 1, "latest_speaker": "",
},
tests/test_portfolio_context.py
+2 -2
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@@ -139,11 +139,11 @@ def test_decision_agents_see_the_portfolio(module, factory, monkeypatch):
"news_report": "N", "fundamentals_report": "F", "investment_plan": "P",
"trader_investment_plan": "T", "past_context": "",
"portfolio_context": "PORTFOLIO_BLOCK_MARKER",
"investment_debate_state": {"history": "", "judge_decision": "", "count": 0},
"investment_debate_state": {"history": "", "count": 0},
"risk_debate_state": {"history": "", "latest_speaker": "", "count": 0,
"aggressive_history": "", "conservative_history": "", "neutral_history": "",
"current_aggressive_response": "", "current_conservative_response": "",
"current_neutral_response": "", "judge_decision": ""},
"current_neutral_response": ""},
}
node = getattr(mod, factory)(_LLM())
node(state)
tests/test_prompt_integrity.py
+2 -2
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@@ -74,11 +74,11 @@ def test_a_report_that_was_never_produced_says_so(module, factory):
"market_report": "RSI 61, price 178.", "sentiment_report": "", "news_report": "",
"fundamentals_report": "", "investment_plan": "P", "trader_investment_plan": "T",
"investment_debate_state": {"bull_history": "", "bear_history": "", "history": "",
"current_response": "", "judge_decision": "", "count": 0},
"current_response": "", "count": 0},
"risk_debate_state": {"history": "", "latest_speaker": "", "count": 0,
"aggressive_history": "", "conservative_history": "", "neutral_history": "",
"current_aggressive_response": "", "current_conservative_response": "",
"current_neutral_response": "", "judge_decision": ""},
"current_neutral_response": ""},
}
getattr(mod, factory)(_LLM())(state)
tests/test_rating_integrity.py
+2 -2
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@@ -194,11 +194,11 @@ def test_a_decision_prompt_states_the_shape_of_its_answer(module, factory, must_
"news_report": "N", "fundamentals_report": "F", "investment_plan": "P",
"trader_investment_plan": "T", "past_context": "", "portfolio_context": "",
"investment_debate_state": {"bull_history": "b", "bear_history": "r", "history": "h",
"current_response": "", "judge_decision": "", "count": 2},
"current_response": "", "count": 2},
"risk_debate_state": {"history": "h", "latest_speaker": "", "count": 3,
"aggressive_history": "", "conservative_history": "", "neutral_history": "",
"current_aggressive_response": "", "current_conservative_response": "",
"current_neutral_response": "", "judge_decision": ""},
"current_neutral_response": ""},
}
getattr(mod, factory)(_LLM())(state)
tests/test_reporting.py
+4 -2
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@@ -13,9 +13,11 @@ def _state():
return {
"market_report": "MKT",
"news_report": "NEWS",
"investment_debate_state": {"judge_decision": "RM PLAN"},
"investment_debate_state": {"bull_history": "BULL"},
"investment_plan": "RM PLAN",
"trader_investment_plan": "TRADE",
"risk_debate_state": {"judge_decision": "PM DECISION"},
"risk_debate_state": {"neutral_history": "NEUTRAL"},
"final_trade_decision": "PM DECISION",
}
tests/test_structured_agent_prompts.py
+1 -1
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@@ -72,7 +72,7 @@ def test_research_manager_prompt_states_constraint():
"company_of_interest": "NVDA",
"investment_debate_state": {
"history": "h", "bull_history": "b", "bear_history": "r",
"current_response": "", "judge_decision": "", "count": 1,
"current_response": "", "count": 1,
},
})
assert NO_EXTERNAL_TOOLS in _prompt_text(captured["prompt"])
tests/test_structured_agents.py
-1
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@@ -292,7 +292,6 @@ def _make_rm_state():
"bull_history": "Bull says...",
"bear_history": "Bear says...",
"current_response": "",
"judge_decision": "",
"count": 1,
},
}
tradingagents/agents/managers/portfolio_manager.py
-1
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@@ -86,7 +86,6 @@ Write these sections, in this order, starting with the rating on its own line:
final_rating = parse_rating(final_trade_decision)
new_risk_debate_state = {
"judge_decision": final_trade_decision,
"history": risk_debate_state["history"],
"aggressive_history": risk_debate_state["aggressive_history"],
"conservative_history": risk_debate_state["conservative_history"],
tradingagents/agents/managers/research_manager.py
-1
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@@ -59,7 +59,6 @@ Write these sections, in this order, starting with the recommendation on its own
)
new_investment_debate_state = {
"judge_decision": investment_plan,
"history": investment_debate_state.get("history", ""),
"bear_history": investment_debate_state.get("bear_history", ""),
"bull_history": investment_debate_state.get("bull_history", ""),
tradingagents/agents/state.py
-2
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@@ -14,7 +14,6 @@ class InvestDebateState(TypedDict):
]
history: Annotated[str, "Conversation history"]
current_response: Annotated[str, "Latest response"]
judge_decision: Annotated[str, "Final judge decision"]
count: Annotated[int, "Length of the current conversation"]
@@ -40,7 +39,6 @@ class RiskDebateState(TypedDict):
current_neutral_response: Annotated[
str, "Latest response by the neutral analyst"
]
judge_decision: Annotated[str, "Judge's decision"]
count: Annotated[int, "Length of the current conversation"]
tradingagents/graph/propagation.py
-2
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@@ -41,7 +41,6 @@ class Propagator:
"bear_history": "",
"history": "",
"current_response": "",
"judge_decision": "",
"count": 0,
}
),
@@ -55,7 +54,6 @@ class Propagator:
"current_aggressive_response": "",
"current_conservative_response": "",
"current_neutral_response": "",
"judge_decision": "",
"count": 0,
}
),
tradingagents/graph/trading_graph.py
+1 -5
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@@ -359,17 +359,13 @@ class TradingAgentsGraph:
"current_response": final_state["investment_debate_state"][
"current_response"
],
"judge_decision": final_state["investment_debate_state"][
"judge_decision"
],
},
"trader_investment_decision": final_state["trader_investment_plan"],
"trader_investment_plan": final_state["trader_investment_plan"],
"risk_debate_state": {
"aggressive_history": final_state["risk_debate_state"]["aggressive_history"],
"conservative_history": final_state["risk_debate_state"]["conservative_history"],
"neutral_history": final_state["risk_debate_state"]["neutral_history"],
"history": final_state["risk_debate_state"]["history"],
"judge_decision": final_state["risk_debate_state"]["judge_decision"],
},
"investment_plan": final_state["investment_plan"],
"final_trade_decision": final_state["final_trade_decision"],
tradingagents/reporting.py
+9 -9
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@@ -52,10 +52,10 @@ def write_report_tree(final_state: dict, ticker: str, save_path) -> Path:
research_dir.mkdir(exist_ok=True)
(research_dir / "bear.md").write_text(debate["bear_history"], encoding="utf-8")
research_parts.append(("Bear Researcher", debate["bear_history"]))
if debate.get("judge_decision"):
if final_state.get("investment_plan"):
research_dir.mkdir(exist_ok=True)
(research_dir / "manager.md").write_text(debate["judge_decision"], encoding="utf-8")
research_parts.append(("Research Manager", debate["judge_decision"]))
(research_dir / "manager.md").write_text(final_state["investment_plan"], encoding="utf-8")
research_parts.append(("Research Manager", final_state["investment_plan"]))
if research_parts:
content = "\n\n".join(f"### {name}\n{text}" for name, text in research_parts)
sections.append(f"## II. Research Team Decision\n\n{content}")
@@ -88,12 +88,12 @@ def write_report_tree(final_state: dict, ticker: str, save_path) -> Path:
content = "\n\n".join(f"### {name}\n{text}" for name, text in risk_parts)
sections.append(f"## IV. Risk Management Team Decision\n\n{content}")
# 5. Portfolio Manager
if risk.get("judge_decision"):
portfolio_dir = save_path / "5_portfolio"
portfolio_dir.mkdir(exist_ok=True)
(portfolio_dir / "decision.md").write_text(risk["judge_decision"], encoding="utf-8")
sections.append(f"## V. Portfolio Manager Decision\n\n### Portfolio Manager\n{risk['judge_decision']}")
# 5. Portfolio Manager
if final_state.get("final_trade_decision"):
portfolio_dir = save_path / "5_portfolio"
portfolio_dir.mkdir(exist_ok=True)
(portfolio_dir / "decision.md").write_text(final_state["final_trade_decision"], encoding="utf-8")
sections.append(f"## V. Portfolio Manager Decision\n\n### Portfolio Manager\n{final_state['final_trade_decision']}")
# Write consolidated report
header = f"# Trading Analysis Report: {ticker}\n\nGenerated: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}\n\n"