mirror of
https://github.com/TauricResearch/TradingAgents.git
synced 2026-09-25 22:12:27 +03:00
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:
@@ -76,8 +76,8 @@ class _FakeGraph:
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return {"messages": [], "company_of_interest": ticker}
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def process_signal(self, text):
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from tradingagents.graph.signal_processing import SignalProcessor
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return SignalProcessor.process_signal(None, text)
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from tradingagents.agents.utils.rating import parse_rating
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return parse_rating(text)
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def record_decision(self, ticker, trade_date, final_state):
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self.calls.append(("record_decision", ticker, trade_date, final_state.get("final_trade_decision")))
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@@ -937,7 +937,7 @@ class TestLegacyRemoval:
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mock_graph.graph.invoke.return_value = fake_state
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mock_graph.propagator.create_initial_state.return_value = fake_state
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mock_graph.propagator.get_graph_args.return_value = {}
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mock_graph.signal_processor.process_signal.return_value = "Buy"
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mock_graph.process_signal.return_value = "Buy"
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# Bind the real _run_graph so propagate's call to self._run_graph executes
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# the actual write path instead of the auto-MagicMock.
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mock_graph._run_graph = functools.partial(
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@@ -75,13 +75,13 @@ def test_the_memory_log_records_review_rather_than_a_tradeable_hold(tmp_path):
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@pytest.mark.unit
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def test_the_signal_and_the_log_agree_on_the_same_decision(tmp_path):
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from tradingagents.agents.utils.memory import TradingMemoryLog
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from tradingagents.graph.signal_processing import SignalProcessor
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from tradingagents.agents.utils.rating import parse_rating
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log = TradingMemoryLog({"memory_log_path": str(tmp_path / "m.md")})
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for text in (INVERTED, REFUSAL, "**Rating**: Buy\n\nAccumulate."):
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log.store_decision("NVDA", f"2026-01-0{len(log.load_entries()) + 1}", text)
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signals = [SignalProcessor.process_signal(None, text)
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signals = [parse_rating(text)
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for text in (INVERTED, REFUSAL, "**Rating**: Buy\n\nAccumulate.")]
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assert [e["rating"] for e in log.load_entries()] == signals
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@@ -121,8 +121,8 @@ def test_the_cli_says_when_a_run_produced_no_usable_rating(monkeypatch, tmp_path
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pass
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def process_signal(self, text):
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from tradingagents.graph.signal_processing import SignalProcessor
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return SignalProcessor.process_signal(None, text)
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from tradingagents.agents.utils.rating import parse_rating
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return parse_rating(text)
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def get_graph_args(self, callbacks=None):
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return {}
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@@ -1,11 +1,7 @@
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"""Tests for the shared rating heuristic and the SignalProcessor adapter.
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"""The rating heuristic that reads the decision's 5-tier rating.
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The Portfolio Manager produces a typed PortfolioDecision via structured
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output and renders it to markdown that always contains a ``**Rating**: X``
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header. The deterministic heuristic in ``tradingagents.agents.utils.rating``
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is therefore sufficient to extract the rating downstream — no second LLM
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call is needed — and SignalProcessor is now a thin adapter that delegates
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to it.
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The Portfolio Manager's rendered decision always carries a ``**Rating**: X``
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header, so the rating is read deterministically; no second model call is made.
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"""
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import pytest
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@@ -14,10 +10,8 @@ from tradingagents.agents.utils.rating import (
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RATING_REVIEW,
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RATINGS_5_TIER,
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extract_rating,
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is_review,
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parse_rating,
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)
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from tradingagents.graph.signal_processing import SignalProcessor
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# ---------------------------------------------------------------------------
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# Heuristic parser
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@@ -67,44 +61,9 @@ class TestParseRating:
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for r in RATINGS_5_TIER:
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assert parse_rating(f"Rating: {r}") == r
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# ---------------------------------------------------------------------------
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# SignalProcessor: thin adapter over the heuristic
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# ---------------------------------------------------------------------------
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@pytest.mark.unit
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class TestSignalProcessor:
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def test_returns_rating_from_pm_markdown(self):
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sp = SignalProcessor()
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md = "**Rating**: Overweight\n\n**Executive Summary**: Build gradually."
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assert sp.process_signal(md) == "Overweight"
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def test_makes_no_llm_calls(self):
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"""SignalProcessor must not invoke the LLM it was constructed with —
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the rating is parseable from the rendered PM markdown directly."""
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from unittest.mock import MagicMock
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llm = MagicMock()
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sp = SignalProcessor(llm)
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sp.process_signal("Rating: Buy\nDetails.")
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llm.invoke.assert_not_called()
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llm.with_structured_output.assert_not_called()
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def test_unparseable_signal_is_review_not_silent_hold(self):
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# #1170: an unrecognizable decision must surface REVIEW, not a fabricated
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# tradeable Hold.
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sp = SignalProcessor()
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signal = sp.process_signal("Plain prose without a recommendation.")
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assert signal == RATING_REVIEW
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assert is_review(signal)
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assert signal not in RATINGS_5_TIER
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def test_fullwidth_colon_is_parsed_not_reviewed(self):
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# #1170: `Rating:Overweight` (fullwidth colon) used to defeat the regex
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# and silently become Hold; NFKC normalization now parses it.
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sp = SignalProcessor()
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assert sp.process_signal("Rating:Overweight\n理由はこちら。") == "Overweight"
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# `Rating:Overweight` (fullwidth colon) is read, not sent to review (#1170).
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assert parse_rating("Rating:Overweight\n理由はこちら。") == "Overweight"
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@pytest.mark.unit
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@@ -131,7 +90,6 @@ class TestGraphSignalContract:
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def _bare_graph(self):
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from tradingagents.graph.trading_graph import TradingAgentsGraph
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g = object.__new__(TradingAgentsGraph)
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g.signal_processor = SignalProcessor()
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return g
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def test_graph_surfaces_review(self):
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@@ -4,7 +4,6 @@ from .conditional_logic import ConditionalLogic
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from .propagation import Propagator
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from .reflection import Reflector
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from .setup import GraphSetup
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from .signal_processing import SignalProcessor
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from .trading_graph import TradingAgentsGraph
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__all__ = [
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@@ -13,5 +12,4 @@ __all__ = [
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"GraphSetup",
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"Propagator",
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"Reflector",
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"SignalProcessor",
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]
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@@ -1,38 +0,0 @@
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"""Extract the 5-tier portfolio rating from the Portfolio Manager's decision.
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The Portfolio Manager produces a typed ``PortfolioDecision`` via structured
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output and renders it to markdown that always carries a ``**Rating**: X``
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header (see :func:`tradingagents.agents.schemas.render_pm_decision`). The
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deterministic heuristic in :mod:`tradingagents.agents.utils.rating` is more
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than sufficient to extract that rating; no extra LLM call is needed.
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This module exists for backwards compatibility with callers that expect a
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``SignalProcessor.process_signal(text)`` interface.
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"""
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from __future__ import annotations
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from typing import Any
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from tradingagents.agents.utils.rating import RATING_REVIEW, extract_rating
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class SignalProcessor:
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"""Read the 5-tier rating out of a Portfolio Manager decision."""
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def __init__(self, quick_thinking_llm: Any = None):
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# The LLM argument is accepted for backwards compatibility but ignored:
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# the PM's structured output guarantees the rating is parseable from the
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# rendered markdown without a second LLM call, so it is not stored.
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pass
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def process_signal(self, full_signal: str) -> str:
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"""Return one of Buy / Overweight / Hold / Underweight / Sell, or REVIEW.
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An unrecognizable decision yields ``REVIEW`` rather than a fabricated
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``Hold``, so a parsing failure is visible instead of masquerading as a
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tradeable neutral signal (#1170). Consumers that map the result onto the
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5-tier enum should guard with :func:`~tradingagents.agents.utils.rating.is_review`.
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"""
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rating = extract_rating(full_signal)
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return rating if rating is not None else RATING_REVIEW
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@@ -28,6 +28,7 @@ from tradingagents.agents.utils.agent_utils import (
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resolve_instrument_identity,
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)
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from tradingagents.agents.utils.memory import TradingMemoryLog
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from tradingagents.agents.utils.rating import parse_rating
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from tradingagents.dataflows.config import run_config, set_config
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from tradingagents.dataflows.utils import get_current_date, safe_ticker_component
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from tradingagents.dataflows.y_finance import get_closes
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@@ -40,7 +41,6 @@ from .conditional_logic import ConditionalLogic
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from .propagation import Propagator
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from .reflection import Reflector
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from .setup import GraphSetup
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from .signal_processing import SignalProcessor
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logger = logging.getLogger(__name__)
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@@ -163,7 +163,6 @@ class TradingAgentsGraph:
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max_recur_limit=self.config.get("max_recur_limit", 100),
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)
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self.reflector = Reflector(self.quick_thinking_llm)
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self.signal_processor = SignalProcessor(self.quick_thinking_llm)
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# State tracking
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self.curr_state = None
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@@ -655,5 +654,5 @@ class TradingAgentsGraph:
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json.dump(entry, f, indent=4, ensure_ascii=False)
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def process_signal(self, full_signal):
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"""Process a signal to extract the core decision."""
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return self.signal_processor.process_signal(full_signal)
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"""The decision's 5-tier rating, or REVIEW when it has none."""
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return parse_rating(full_signal)
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