chore(graph): remove SignalProcessor

- process_signal reads the rating with parse_rating; the adapter ignored the model it was given
This commit is contained in:
Yijia-Xiao
2026-09-24 04:31:05 +00:00
parent a6e92a6b5e
commit 4e1faf6465
7 changed files with 15 additions and 98 deletions
+2 -2
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@@ -76,8 +76,8 @@ class _FakeGraph:
return {"messages": [], "company_of_interest": ticker}
def process_signal(self, text):
from tradingagents.graph.signal_processing import SignalProcessor
return SignalProcessor.process_signal(None, text)
from tradingagents.agents.utils.rating import parse_rating
return parse_rating(text)
def record_decision(self, ticker, trade_date, final_state):
self.calls.append(("record_decision", ticker, trade_date, final_state.get("final_trade_decision")))
+1 -1
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@@ -937,7 +937,7 @@ class TestLegacyRemoval:
mock_graph.graph.invoke.return_value = fake_state
mock_graph.propagator.create_initial_state.return_value = fake_state
mock_graph.propagator.get_graph_args.return_value = {}
mock_graph.signal_processor.process_signal.return_value = "Buy"
mock_graph.process_signal.return_value = "Buy"
# Bind the real _run_graph so propagate's call to self._run_graph executes
# the actual write path instead of the auto-MagicMock.
mock_graph._run_graph = functools.partial(
+4 -4
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@@ -75,13 +75,13 @@ def test_the_memory_log_records_review_rather_than_a_tradeable_hold(tmp_path):
@pytest.mark.unit
def test_the_signal_and_the_log_agree_on_the_same_decision(tmp_path):
from tradingagents.agents.utils.memory import TradingMemoryLog
from tradingagents.graph.signal_processing import SignalProcessor
from tradingagents.agents.utils.rating import parse_rating
log = TradingMemoryLog({"memory_log_path": str(tmp_path / "m.md")})
for text in (INVERTED, REFUSAL, "**Rating**: Buy\n\nAccumulate."):
log.store_decision("NVDA", f"2026-01-0{len(log.load_entries()) + 1}", text)
signals = [SignalProcessor.process_signal(None, text)
signals = [parse_rating(text)
for text in (INVERTED, REFUSAL, "**Rating**: Buy\n\nAccumulate.")]
assert [e["rating"] for e in log.load_entries()] == signals
@@ -121,8 +121,8 @@ def test_the_cli_says_when_a_run_produced_no_usable_rating(monkeypatch, tmp_path
pass
def process_signal(self, text):
from tradingagents.graph.signal_processing import SignalProcessor
return SignalProcessor.process_signal(None, text)
from tradingagents.agents.utils.rating import parse_rating
return parse_rating(text)
def get_graph_args(self, callbacks=None):
return {}
+5 -47
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@@ -1,11 +1,7 @@
"""Tests for the shared rating heuristic and the SignalProcessor adapter.
"""The rating heuristic that reads the decision's 5-tier rating.
The Portfolio Manager produces a typed PortfolioDecision via structured
output and renders it to markdown that always contains a ``**Rating**: X``
header. The deterministic heuristic in ``tradingagents.agents.utils.rating``
is therefore sufficient to extract the rating downstream — no second LLM
call is needed — and SignalProcessor is now a thin adapter that delegates
to it.
The Portfolio Manager's rendered decision always carries a ``**Rating**: X``
header, so the rating is read deterministically; no second model call is made.
"""
import pytest
@@ -14,10 +10,8 @@ from tradingagents.agents.utils.rating import (
RATING_REVIEW,
RATINGS_5_TIER,
extract_rating,
is_review,
parse_rating,
)
from tradingagents.graph.signal_processing import SignalProcessor
# ---------------------------------------------------------------------------
# Heuristic parser
@@ -67,44 +61,9 @@ class TestParseRating:
for r in RATINGS_5_TIER:
assert parse_rating(f"Rating: {r}") == r
# ---------------------------------------------------------------------------
# SignalProcessor: thin adapter over the heuristic
# ---------------------------------------------------------------------------
@pytest.mark.unit
class TestSignalProcessor:
def test_returns_rating_from_pm_markdown(self):
sp = SignalProcessor()
md = "**Rating**: Overweight\n\n**Executive Summary**: Build gradually."
assert sp.process_signal(md) == "Overweight"
def test_makes_no_llm_calls(self):
"""SignalProcessor must not invoke the LLM it was constructed with —
the rating is parseable from the rendered PM markdown directly."""
from unittest.mock import MagicMock
llm = MagicMock()
sp = SignalProcessor(llm)
sp.process_signal("Rating: Buy\nDetails.")
llm.invoke.assert_not_called()
llm.with_structured_output.assert_not_called()
def test_unparseable_signal_is_review_not_silent_hold(self):
# #1170: an unrecognizable decision must surface REVIEW, not a fabricated
# tradeable Hold.
sp = SignalProcessor()
signal = sp.process_signal("Plain prose without a recommendation.")
assert signal == RATING_REVIEW
assert is_review(signal)
assert signal not in RATINGS_5_TIER
def test_fullwidth_colon_is_parsed_not_reviewed(self):
# #1170: `Rating:Overweight` (fullwidth colon) used to defeat the regex
# and silently become Hold; NFKC normalization now parses it.
sp = SignalProcessor()
assert sp.process_signal("Rating:Overweight\n理由はこちら。") == "Overweight"
# `Rating:Overweight` (fullwidth colon) is read, not sent to review (#1170).
assert parse_rating("Rating:Overweight\n理由はこちら。") == "Overweight"
@pytest.mark.unit
@@ -131,7 +90,6 @@ class TestGraphSignalContract:
def _bare_graph(self):
from tradingagents.graph.trading_graph import TradingAgentsGraph
g = object.__new__(TradingAgentsGraph)
g.signal_processor = SignalProcessor()
return g
def test_graph_surfaces_review(self):
-2
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@@ -4,7 +4,6 @@ from .conditional_logic import ConditionalLogic
from .propagation import Propagator
from .reflection import Reflector
from .setup import GraphSetup
from .signal_processing import SignalProcessor
from .trading_graph import TradingAgentsGraph
__all__ = [
@@ -13,5 +12,4 @@ __all__ = [
"GraphSetup",
"Propagator",
"Reflector",
"SignalProcessor",
]
-38
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@@ -1,38 +0,0 @@
"""Extract the 5-tier portfolio rating from the Portfolio Manager's decision.
The Portfolio Manager produces a typed ``PortfolioDecision`` via structured
output and renders it to markdown that always carries a ``**Rating**: X``
header (see :func:`tradingagents.agents.schemas.render_pm_decision`). The
deterministic heuristic in :mod:`tradingagents.agents.utils.rating` is more
than sufficient to extract that rating; no extra LLM call is needed.
This module exists for backwards compatibility with callers that expect a
``SignalProcessor.process_signal(text)`` interface.
"""
from __future__ import annotations
from typing import Any
from tradingagents.agents.utils.rating import RATING_REVIEW, extract_rating
class SignalProcessor:
"""Read the 5-tier rating out of a Portfolio Manager decision."""
def __init__(self, quick_thinking_llm: Any = None):
# The LLM argument is accepted for backwards compatibility but ignored:
# the PM's structured output guarantees the rating is parseable from the
# rendered markdown without a second LLM call, so it is not stored.
pass
def process_signal(self, full_signal: str) -> str:
"""Return one of Buy / Overweight / Hold / Underweight / Sell, or REVIEW.
An unrecognizable decision yields ``REVIEW`` rather than a fabricated
``Hold``, so a parsing failure is visible instead of masquerading as a
tradeable neutral signal (#1170). Consumers that map the result onto the
5-tier enum should guard with :func:`~tradingagents.agents.utils.rating.is_review`.
"""
rating = extract_rating(full_signal)
return rating if rating is not None else RATING_REVIEW
+3 -4
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@@ -28,6 +28,7 @@ from tradingagents.agents.utils.agent_utils import (
resolve_instrument_identity,
)
from tradingagents.agents.utils.memory import TradingMemoryLog
from tradingagents.agents.utils.rating import parse_rating
from tradingagents.dataflows.config import run_config, set_config
from tradingagents.dataflows.utils import get_current_date, safe_ticker_component
from tradingagents.dataflows.y_finance import get_closes
@@ -40,7 +41,6 @@ from .conditional_logic import ConditionalLogic
from .propagation import Propagator
from .reflection import Reflector
from .setup import GraphSetup
from .signal_processing import SignalProcessor
logger = logging.getLogger(__name__)
@@ -163,7 +163,6 @@ class TradingAgentsGraph:
max_recur_limit=self.config.get("max_recur_limit", 100),
)
self.reflector = Reflector(self.quick_thinking_llm)
self.signal_processor = SignalProcessor(self.quick_thinking_llm)
# State tracking
self.curr_state = None
@@ -655,5 +654,5 @@ class TradingAgentsGraph:
json.dump(entry, f, indent=4, ensure_ascii=False)
def process_signal(self, full_signal):
"""Process a signal to extract the core decision."""
return self.signal_processor.process_signal(full_signal)
"""The decision's 5-tier rating, or REVIEW when it has none."""
return parse_rating(full_signal)