chore(lint): make the repository ruff-clean under the strict select

Clear the deferred full-repo lint backlog so the whole tree passes the strict
ruff select (E,W,F,I,B,UP,C4,SIM). Mechanical fixes dominate: import sorting,
pep585/604 annotations, dropped dead imports, and whitespace. The few semantic
changes are behavior-preserving: declare __all__ on the agent_utils and
alpha_vantage re-export hubs; expand 'from x import *' to explicit names; use
immutable tuple defaults instead of mutable list defaults; contextlib.suppress
for try/except/pass; and narrow an over-broad assertRaises.

cli/announcements.py

@@ -1,4 +1,5 @@
 import getpass
+
 import requests
 from rich.console import Console
 from rich.panel import Panel

cli/main.py

@@ -1,38 +1,53 @@
-from typing import Optional
-import os
 import datetime
-import typer
+import os
-import questionary
-from pathlib import Path
-from functools import wraps
-from rich.console import Console
-from rich.panel import Panel
-from rich.spinner import Spinner
-from rich.live import Live
-from rich.columns import Columns
-from rich.markdown import Markdown
-from rich.layout import Layout
-from rich.text import Text
-from rich.table import Table
-from collections import deque
 import time
-from rich.tree import Tree
+from collections import deque
+from functools import wraps
+from pathlib import Path
+
+import typer
 from rich import box
 from rich.align import Align
+from rich.console import Console
+from rich.layout import Layout
+from rich.live import Live
+from rich.markdown import Markdown
+from rich.panel import Panel
 from rich.rule import Rule
+from rich.spinner import Spinner
+from rich.table import Table
+from rich.text import Text
 
-from tradingagents.graph.trading_graph import TradingAgentsGraph
+from cli.announcements import display_announcements, fetch_announcements
+from cli.stats_handler import StatsCallbackHandler
+from cli.utils import (
+    ask_anthropic_effort,
+    ask_gemini_thinking_config,
+    ask_glm_region,
+    ask_minimax_region,
+    ask_openai_reasoning_effort,
+    ask_output_language,
+    ask_qwen_region,
+    confirm_ollama_endpoint,
+    detect_asset_type,
+    ensure_api_key,
+    get_ticker,
+    prompt_openai_compatible_url,
+    resolve_backend_url,
+    select_analysts,
+    select_deep_thinking_agent,
+    select_llm_provider,
+    select_research_depth,
+    select_shallow_thinking_agent,
+)
+from tradingagents.default_config import DEFAULT_CONFIG
 from tradingagents.graph.analyst_execution import (
     AnalystWallTimeTracker,
     build_analyst_execution_plan,
     get_initial_analyst_node,
     sync_analyst_tracker_from_chunk,
 )
-from tradingagents.default_config import DEFAULT_CONFIG
+from tradingagents.graph.trading_graph import TradingAgentsGraph
-from cli.models import AnalystType
-from cli.utils import *
-from cli.announcements import fetch_announcements, display_announcements
-from cli.stats_handler import StatsCallbackHandler
 
 console = Console()
 
@@ -466,7 +481,7 @@ def update_display(layout, spinner_text=None, stats_handler=None, start_time=Non
 def get_user_selections():
     """Get all user selections before starting the analysis display."""
     # Display ASCII art welcome message
-    with open(Path(__file__).parent / "static" / "welcome.txt", "r", encoding="utf-8") as f:
+    with open(Path(__file__).parent / "static" / "welcome.txt", encoding="utf-8") as f:
         welcome_ascii = f.read()
 
     # Create welcome box content
@@ -922,8 +937,11 @@ def update_analyst_statuses(message_buffer, chunk, wall_time_tracker=None):
             message_buffer.update_agent_status(agent_name, "pending")
 
     # When all analysts complete, transition research team to in_progress
-    if not found_active and selected:
+    if (
-        if message_buffer.agent_status.get("Bull Researcher") == "pending":
+        not found_active
+        and selected
+        and message_buffer.agent_status.get("Bull Researcher") == "pending"
+    ):
         message_buffer.update_agent_status("Bull Researcher", "in_progress")
 
 def extract_content_string(content):
@@ -1097,7 +1115,7 @@ def run_analysis(checkpoint: bool = False):
     # Now start the display layout
     layout = create_layout()
 
-    with Live(layout, refresh_per_second=4) as live:
+    with Live(layout, refresh_per_second=4):
         # Initial display
         update_display(layout, stats_handler=stats_handler, start_time=start_time)
 
@@ -1232,8 +1250,7 @@ def run_analysis(checkpoint: bool = False):
                     message_buffer.update_report_section(
                         "final_trade_decision", f"### Neutral Analyst Analysis\n{neu_hist}"
                     )
-                if judge:
+                if judge and message_buffer.agent_status.get("Portfolio Manager") != "completed":
-                    if message_buffer.agent_status.get("Portfolio Manager") != "completed":
                     message_buffer.update_agent_status("Portfolio Manager", "in_progress")
                     message_buffer.update_report_section(
                         "final_trade_decision", f"### Portfolio Manager Decision\n{judge}"
@@ -1253,7 +1270,6 @@ def run_analysis(checkpoint: bool = False):
         final_state = {}
         for chunk in trace:
             final_state.update(chunk)
-        decision = graph.process_signal(final_state["final_trade_decision"])
 
         # Update all agent statuses to completed
         for agent in message_buffer.agent_status:
@@ -1265,7 +1281,7 @@ def run_analysis(checkpoint: bool = False):
         message_buffer.add_message("System", analyst_wall_time_tracker.format_summary())
 
         # Update final report sections
-        for section in message_buffer.report_sections.keys():
+        for section in message_buffer.report_sections:
             if section in final_state:
                 message_buffer.update_report_section(section, final_state[section])
 

cli/models.py

@@ -1,6 +1,4 @@
 from enum import Enum
-from typing import List, Optional, Dict
-from pydantic import BaseModel
 
 
 class AnalystType(str, Enum):

cli/stats_handler.py

@@ -1,9 +1,9 @@
 import threading
-from typing import Any, Dict, List, Union
+from typing import Any
 
 from langchain_core.callbacks import BaseCallbackHandler
-from langchain_core.outputs import LLMResult
 from langchain_core.messages import AIMessage
+from langchain_core.outputs import LLMResult
 
 
 class StatsCallbackHandler(BaseCallbackHandler):
@@ -19,8 +19,8 @@ class StatsCallbackHandler(BaseCallbackHandler):
 
     def on_llm_start(
         self,
-        serialized: Dict[str, Any],
+        serialized: dict[str, Any],
-        prompts: List[str],
+        prompts: list[str],
         **kwargs: Any,
     ) -> None:
         """Increment LLM call counter when an LLM starts."""
@@ -29,8 +29,8 @@ class StatsCallbackHandler(BaseCallbackHandler):
 
     def on_chat_model_start(
         self,
-        serialized: Dict[str, Any],
+        serialized: dict[str, Any],
-        messages: List[List[Any]],
+        messages: list[list[Any]],
         **kwargs: Any,
     ) -> None:
         """Increment LLM call counter when a chat model starts."""
@@ -57,7 +57,7 @@ class StatsCallbackHandler(BaseCallbackHandler):
 
     def on_tool_start(
         self,
-        serialized: Dict[str, Any],
+        serialized: dict[str, Any],
         input_str: str,
         **kwargs: Any,
     ) -> None:
@@ -65,7 +65,7 @@ class StatsCallbackHandler(BaseCallbackHandler):
         with self._lock:
             self.tool_calls += 1
 
-    def get_stats(self) -> Dict[str, Any]:
+    def get_stats(self) -> dict[str, Any]:
         """Return current statistics."""
         with self._lock:
             return {

cli/utils.py

@@ -1,6 +1,5 @@
 import os
 from pathlib import Path
-from typing import List, Optional, Tuple, Dict
 
 import questionary
 from dotenv import find_dotenv, set_key
@@ -89,8 +88,8 @@ def detect_asset_type(ticker: str) -> AssetType:
 
 
 def filter_analysts_for_asset_type(
-    analysts: List[AnalystType], asset_type: AssetType
+    analysts: list[AnalystType], asset_type: AssetType
-) -> List[AnalystType]:
+) -> list[AnalystType]:
     if asset_type != AssetType.CRYPTO:
         return analysts
     return [
@@ -133,7 +132,7 @@ def get_analysis_date() -> str:
     return date.strip()
 
 
-def select_analysts(asset_type: AssetType = AssetType.STOCK) -> List[AnalystType]:
+def select_analysts(asset_type: AssetType = AssetType.STOCK) -> list[AnalystType]:
     """Select analysts using an interactive checkbox."""
     available_analysts = filter_analysts_for_asset_type(
         [value for _, value in ANALYST_ORDER],
@@ -197,7 +196,7 @@ def select_research_depth() -> int:
     return choice
 
 
-def _fetch_openrouter_models() -> List[Tuple[str, str]]:
+def _fetch_openrouter_models() -> list[tuple[str, str]]:
     """Fetch available models from the OpenRouter API."""
     import requests
     try:
@@ -556,7 +555,7 @@ def confirm_ollama_endpoint(url: str) -> None:
         )
 
 
-def ensure_api_key(provider: str) -> Optional[str]:
+def ensure_api_key(provider: str) -> str | None:
     """Make sure the API key for `provider` is available in the environment.
 
     If the env var is already set, returns its value untouched. Otherwise

main.py

@@ -1,5 +1,5 @@
-from tradingagents.graph.trading_graph import TradingAgentsGraph
 from tradingagents.default_config import DEFAULT_CONFIG
+from tradingagents.graph.trading_graph import TradingAgentsGraph
 
 # DEFAULT_CONFIG already applies TRADINGAGENTS_* env-var overrides
 # (llm_provider, deep_think_llm, quick_think_llm, backend_url, etc.),

scripts/smoke_structured_output.py

@@ -21,7 +21,6 @@ added, plus the heuristic SignalProcessor.
 from __future__ import annotations
 
 import argparse
-import os
 import sys
 
 from tradingagents.agents.managers.portfolio_manager import create_portfolio_manager
@@ -30,7 +29,6 @@ from tradingagents.agents.trader.trader import create_trader
 from tradingagents.graph.signal_processing import SignalProcessor
 from tradingagents.llm_clients import create_llm_client
 
-
 PROVIDER_DEFAULTS = {
     "openai": ("gpt-5.4-mini", None),
     "google": ("gemini-2.5-flash", None),

test.py

@@ -1,5 +1,8 @@
 import time
-from tradingagents.dataflows.y_finance import get_YFin_data_online, get_stock_stats_indicators_window, get_balance_sheet as get_yfinance_balance_sheet, get_cashflow as get_yfinance_cashflow, get_income_statement as get_yfinance_income_statement, get_insider_transactions as get_yfinance_insider_transactions
+
+from tradingagents.dataflows.y_finance import (
+    get_stock_stats_indicators_window,
+)
 
 print("Testing optimized implementation with 30-day lookback:")
 start_time = time.time()

tests/test_api_key_env.py

@@ -3,14 +3,12 @@
 from __future__ import annotations
 
 import os
-from pathlib import Path
 from unittest.mock import patch
 
 import pytest
 
 from tradingagents.llm_clients.api_key_env import PROVIDER_API_KEY_ENV, get_api_key_env
 
-
 # ---- Mapping coverage -----------------------------------------------------
 
 
@@ -71,6 +69,7 @@ def test_case_insensitive_lookup():
 def cli_utils(monkeypatch):
     """Import cli.utils with a fresh environment so module-level state is consistent."""
     import importlib
+
     import cli.utils as cli_utils_module
     return importlib.reload(cli_utils_module)
 

tests/test_capabilities.py

@@ -1,9 +1,10 @@
 """Unit tests for the LLM capability table."""
 
+from dataclasses import FrozenInstanceError
+
 import pytest
 
 from tradingagents.llm_clients.capabilities import (
-    ModelCapabilities,
     get_capabilities,
 )
 
@@ -119,5 +120,5 @@ class TestDefault:
 def test_capabilities_dataclass_is_frozen():
     """Capability rows are immutable so they can be safely shared."""
     caps = get_capabilities("deepseek-chat")
-    with pytest.raises(Exception):
+    with pytest.raises(FrozenInstanceError):
         caps.supports_tool_choice = False  # type: ignore[misc]

tests/test_checkpoint_resume.py

@@ -1,12 +1,9 @@
 """Test checkpoint resume: crash mid-analysis, re-run resumes from last node."""
 
-import sqlite3
 import tempfile
 import unittest
-from pathlib import Path
 from typing import TypedDict
 
-from langgraph.checkpoint.sqlite import SqliteSaver
 from langgraph.graph import END, StateGraph
 
 from tradingagents.graph.checkpointer import (

tests/test_deepseek_reasoning.py

@@ -24,7 +24,6 @@ from tradingagents.llm_clients.openai_client import (
     _input_to_messages,
 )
 
-
 # ---------------------------------------------------------------------------
 # _input_to_messages — the helper that handles list / ChatPromptValue / other
 # (Gemini bot review note: non-list inputs must also work)

tests/test_memory_log.py

@@ -1,15 +1,16 @@
 """Tests for TradingMemoryLog — storage, deferred reflection, PM injection, legacy removal."""
 
-import pytest
-import pandas as pd
 from unittest.mock import MagicMock, patch
 
-from tradingagents.agents.utils.memory import TradingMemoryLog
+import pandas as pd
+import pytest
+
+from tradingagents.agents.managers.portfolio_manager import create_portfolio_manager
 from tradingagents.agents.schemas import PortfolioDecision, PortfolioRating
+from tradingagents.agents.utils.memory import TradingMemoryLog
+from tradingagents.graph.propagation import Propagator
 from tradingagents.graph.reflection import Reflector
 from tradingagents.graph.trading_graph import TradingAgentsGraph
-from tradingagents.graph.propagation import Propagator
-from tradingagents.agents.managers.portfolio_manager import create_portfolio_manager
 
 _SEP = TradingMemoryLog._SEPARATOR
 

tests/test_news_lookahead.py

@@ -6,7 +6,6 @@ news injected future articles), #993 (empty-after-filter returned a blank body).
 """
 import time
 from datetime import datetime
-from unittest import mock
 
 import pytest
 

tests/test_no_data_handling.py

@@ -14,7 +14,7 @@ from unittest import mock
 import pandas as pd
 import pytest
 
-from tradingagents.dataflows import stockstats_utils, interface
+from tradingagents.dataflows import interface, stockstats_utils
 from tradingagents.dataflows.config import set_config
 from tradingagents.dataflows.symbol_utils import NoMarketDataError
 
@@ -33,8 +33,8 @@ class TestLoadOhlcvNoPoison(unittest.TestCase):
 
     def test_empty_download_raises_and_does_not_cache(self):
         empty = pd.DataFrame()
-        with mock.patch.object(stockstats_utils.yf, "download", return_value=empty) as dl:
+        with mock.patch.object(stockstats_utils.yf, "download", return_value=empty), \
-            with self.assertRaises(NoMarketDataError):
+                self.assertRaises(NoMarketDataError):
             stockstats_utils.load_ohlcv("FAKE", "2026-01-01")
         # Nothing should have been written to the cache.
         self.assertEqual(os.listdir(self._tmp), [])

tests/test_ollama_base_url.py

@@ -18,8 +18,8 @@ def _resync_reloaded_modules():
     doesn't leak across test modules.
     """
     yield
-    import cli.utils
     import cli.main
+    import cli.utils
     importlib.reload(cli.utils)
     importlib.reload(cli.main)
 

tests/test_openai_compatible_provider.py

@@ -4,7 +4,6 @@ Verifies the user-supplied base_url is required and honored, the key is optional
 (keyless local default), Chat Completions (not the Responses API) is used, any
 model name is accepted, and the env backend URL precedence (#978).
 """
-import os
 
 import pytest
 

tests/test_signal_processing.py

@@ -13,7 +13,6 @@ import pytest
 from tradingagents.agents.utils.rating import RATINGS_5_TIER, parse_rating
 from tradingagents.graph.signal_processing import SignalProcessor
 
-
 # ---------------------------------------------------------------------------
 # Heuristic parser
 # ---------------------------------------------------------------------------

tests/test_structured_agents.py

@@ -27,7 +27,6 @@ from tradingagents.agents.schemas import (
 )
 from tradingagents.agents.trader.trader import create_trader
 
-
 # ---------------------------------------------------------------------------
 # Render functions
 # ---------------------------------------------------------------------------

tests/test_symbol_utils.py

@@ -6,8 +6,8 @@ import pytest
 
 from tradingagents.dataflows.symbol_utils import (
     NoMarketDataError,
-    normalize_symbol,
     is_yahoo_safe,
+    normalize_symbol,
 )
 
 

tests/test_vendor_routing.py

@@ -6,7 +6,6 @@ Regressions for #988 (explicit single-vendor config still fell back to others),
 were swallowed without a trace).
 """
 import copy
-import logging
 import unittest
 from unittest import mock
 
@@ -76,8 +75,8 @@ class VendorRoutingTests(unittest.TestCase):
         # #989: primary errors + fallback no-data -> NO_DATA, but the failure
         # must be visible in logs (broken primary not hidden).
         set_config({"data_vendors": {"core_stock_apis": "yfinance,alpha_vantage"}})
-        with self._route({"yfinance": _raises(ValueError("boom")), "alpha_vantage": _no_data}):
+        with self._route({"yfinance": _raises(ValueError("boom")), "alpha_vantage": _no_data}), \
-            with self.assertLogs("tradingagents.dataflows.interface", level="WARNING") as cm:
+                self.assertLogs("tradingagents.dataflows.interface", level="WARNING") as cm:
             result = interface.route_to_vendor("get_stock_data", "AAPL", "2026-01-01", "2026-01-10")
         self.assertIn("NO_DATA_AVAILABLE", result)
         joined = "\n".join(cm.output)

tradingagents/__init__.py

@@ -1,3 +1,4 @@
+import contextlib
 import warnings
 
 # Load .env files at package import so DEFAULT_CONFIG's env-var overlay
@@ -20,10 +21,8 @@ except ImportError:
 # subclassed warning categories. To suppress a specific warning we must
 # install our filter AFTER langchain-core has installed its own, so import
 # it first. The package is a guaranteed transitive dep via langgraph.
-try:
+with contextlib.suppress(ImportError):
     import langchain_core  # noqa: F401
-except ImportError:
-    pass
 
 # langgraph-checkpoint 4.0.3 calls Reviver() at module load without an
 # explicit allowed_objects, which triggers a noisy pending-deprecation

tradingagents/agents/__init__.py

@@ -1,6 +1,3 @@
-from .utils.agent_utils import create_msg_delete
-from .utils.agent_states import AgentState, InvestDebateState, RiskDebateState
-
 from .analysts.fundamentals_analyst import create_fundamentals_analyst
 from .analysts.market_analyst import create_market_analyst
 from .analysts.news_analyst import create_news_analyst
@@ -8,18 +5,16 @@ from .analysts.sentiment_analyst import (
     create_sentiment_analyst,
     create_social_media_analyst,  # deprecated alias kept for back-compat
 )
-
+from .managers.portfolio_manager import create_portfolio_manager
+from .managers.research_manager import create_research_manager
 from .researchers.bear_researcher import create_bear_researcher
 from .researchers.bull_researcher import create_bull_researcher
-
 from .risk_mgmt.aggressive_debator import create_aggressive_debator
 from .risk_mgmt.conservative_debator import create_conservative_debator
 from .risk_mgmt.neutral_debator import create_neutral_debator
-
-from .managers.research_manager import create_research_manager
-from .managers.portfolio_manager import create_portfolio_manager
-
 from .trader.trader import create_trader
+from .utils.agent_states import AgentState, InvestDebateState, RiskDebateState
+from .utils.agent_utils import create_msg_delete
 
 __all__ = [
     "AgentState",

tradingagents/agents/analysts/fundamentals_analyst.py

@@ -1,14 +1,13 @@
 from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
+
 from tradingagents.agents.utils.agent_utils import (
-    get_instrument_context_from_state,
     get_balance_sheet,
     get_cashflow,
     get_fundamentals,
     get_income_statement,
-    get_insider_transactions,
+    get_instrument_context_from_state,
     get_language_instruction,
 )
-from tradingagents.dataflows.config import get_config
 
 
 def create_fundamentals_analyst(llm):

tradingagents/agents/analysts/market_analyst.py

@@ -1,12 +1,12 @@
 from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
+
 from tradingagents.agents.utils.agent_utils import (
-    get_instrument_context_from_state,
     get_indicators,
+    get_instrument_context_from_state,
     get_language_instruction,
     get_stock_data,
     get_verified_market_snapshot,
 )
-from tradingagents.dataflows.config import get_config
 
 
 def create_market_analyst(llm):

tradingagents/agents/analysts/news_analyst.py

@@ -1,13 +1,13 @@
 from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
+
 from tradingagents.agents.utils.agent_utils import (
-    get_instrument_context_from_state,
     get_global_news,
+    get_instrument_context_from_state,
     get_language_instruction,
     get_macro_indicators,
     get_news,
     get_prediction_markets,
 )
-from tradingagents.dataflows.config import get_config
 
 
 def create_news_analyst(llm):

tradingagents/agents/schemas.py

@@ -19,11 +19,10 @@ so that:
 from __future__ import annotations
 
 from enum import Enum
-from typing import Literal, Optional
+from typing import Literal
 
 from pydantic import BaseModel, Field
 
-
 # ---------------------------------------------------------------------------
 # Shared rating types
 # ---------------------------------------------------------------------------
@@ -124,15 +123,15 @@ class TraderProposal(BaseModel):
             "the research plan. Two to four sentences."
         ),
     )
-    entry_price: Optional[float] = Field(
+    entry_price: float | None = Field(
         default=None,
         description="Optional entry price target in the instrument's quote currency.",
     )
-    stop_loss: Optional[float] = Field(
+    stop_loss: float | None = Field(
         default=None,
         description="Optional stop-loss price in the instrument's quote currency.",
     )
-    position_sizing: Optional[str] = Field(
+    position_sizing: str | None = Field(
         default=None,
         description="Optional sizing guidance, e.g. '5% of portfolio'.",
     )
@@ -196,11 +195,11 @@ class PortfolioDecision(BaseModel):
             "incorporate them; otherwise rely solely on the current analysis."
         ),
     )
-    price_target: Optional[float] = Field(
+    price_target: float | None = Field(
         default=None,
         description="Optional target price in the instrument's quote currency.",
     )
-    time_horizon: Optional[str] = Field(
+    time_horizon: str | None = Field(
         default=None,
         description="Optional recommended holding period, e.g. '3-6 months'.",
     )

tradingagents/agents/utils/agent_states.py

@@ -1,6 +1,7 @@
 from typing import Annotated
-from typing_extensions import TypedDict
+
 from langgraph.graph import MessagesState
+from typing_extensions import TypedDict
 
 
 # Researcher team state

tradingagents/agents/utils/agent_utils.py

@@ -1,37 +1,50 @@
 import functools
 import logging
-from typing import Any, Mapping, Optional
+from collections.abc import Mapping
+from typing import Any
 
 import yfinance as yf
 from langchain_core.messages import HumanMessage, RemoveMessage
 
 # Import tools from separate utility files
-from tradingagents.agents.utils.core_stock_tools import (
+from tradingagents.agents.utils.core_stock_tools import get_stock_data
-    get_stock_data
-)
-from tradingagents.agents.utils.technical_indicators_tools import (
-    get_indicators
-)
 from tradingagents.agents.utils.fundamental_data_tools import (
-    get_fundamentals,
     get_balance_sheet,
     get_cashflow,
-    get_income_statement
+    get_fundamentals,
+    get_income_statement,
 )
+from tradingagents.agents.utils.macro_data_tools import get_macro_indicators
+from tradingagents.agents.utils.market_data_validation_tools import get_verified_market_snapshot
 from tradingagents.agents.utils.news_data_tools import (
-    get_news,
+    get_global_news,
     get_insider_transactions,
-    get_global_news
+    get_news,
-)
-from tradingagents.agents.utils.macro_data_tools import (
-    get_macro_indicators
-)
-from tradingagents.agents.utils.prediction_markets_tools import (
-    get_prediction_markets
-)
-from tradingagents.agents.utils.market_data_validation_tools import (
-    get_verified_market_snapshot
 )
+from tradingagents.agents.utils.prediction_markets_tools import get_prediction_markets
+from tradingagents.agents.utils.technical_indicators_tools import get_indicators
+
+# Public surface: the data tools are imported here so agents and the graph
+# import them from one place, plus the instrument/language helpers defined below.
+__all__ = [
+    "get_stock_data",
+    "get_indicators",
+    "get_fundamentals",
+    "get_balance_sheet",
+    "get_cashflow",
+    "get_income_statement",
+    "get_news",
+    "get_global_news",
+    "get_insider_transactions",
+    "get_macro_indicators",
+    "get_prediction_markets",
+    "get_verified_market_snapshot",
+    "build_instrument_context",
+    "resolve_instrument_identity",
+    "get_instrument_context_from_state",
+    "get_language_instruction",
+    "create_msg_delete",
+]
 
 logger = logging.getLogger(__name__)
 
@@ -52,7 +65,7 @@ def get_language_instruction() -> str:
     return f" Write your entire response in {lang}."
 
 
-def _clean_identity_value(value: Any) -> Optional[str]:
+def _clean_identity_value(value: Any) -> str | None:
     """Return a trimmed string, or None for empty / placeholder-ish values."""
     if not isinstance(value, str):
         return None
@@ -109,7 +122,7 @@ def resolve_instrument_identity(ticker: str) -> dict:
 def build_instrument_context(
     ticker: str,
     asset_type: str = "stock",
-    identity: Optional[Mapping[str, str]] = None,
+    identity: Mapping[str, str] | None = None,
 ) -> str:
     """Describe the exact instrument so agents preserve identity and ticker.
 

tradingagents/agents/utils/core_stock_tools.py

@@ -1,5 +1,7 @@
-from langchain_core.tools import tool
 from typing import Annotated
+
+from langchain_core.tools import tool
+
 from tradingagents.dataflows.interface import route_to_vendor
 
 

tradingagents/agents/utils/fundamental_data_tools.py

@@ -1,5 +1,7 @@
-from langchain_core.tools import tool
 from typing import Annotated
+
+from langchain_core.tools import tool
+
 from tradingagents.dataflows.interface import route_to_vendor
 
 

tradingagents/agents/utils/memory.py

@@ -1,8 +1,7 @@
 """Append-only markdown decision log for TradingAgents."""
 
-from typing import List, Optional
-from pathlib import Path
 import re
+from pathlib import Path
 
 from tradingagents.agents.utils.rating import parse_rating
 
@@ -51,7 +50,7 @@ class TradingMemoryLog:
 
     # --- Read path (Phase A) ---
 
-    def load_entries(self) -> List[dict]:
+    def load_entries(self) -> list[dict]:
         """Parse all entries from log. Returns list of dicts."""
         if not self._log_path or not self._log_path.exists():
             return []
@@ -64,7 +63,7 @@ class TradingMemoryLog:
                 entries.append(parsed)
         return entries
 
-    def get_pending_entries(self) -> List[dict]:
+    def get_pending_entries(self) -> list[dict]:
         """Return entries with outcome:pending (for Phase B)."""
         return [e for e in self.load_entries() if e.get("pending")]
 
@@ -162,7 +161,7 @@ class TradingMemoryLog:
         tmp_path.write_text(new_text, encoding="utf-8")
         tmp_path.replace(self._log_path)
 
-    def batch_update_with_outcomes(self, updates: List[dict]) -> None:
+    def batch_update_with_outcomes(self, updates: list[dict]) -> None:
         """Apply multiple outcome updates in a single read + atomic write.
 
         Each element of updates must have keys: ticker, trade_date,
@@ -218,7 +217,7 @@ class TradingMemoryLog:
 
     # --- Helpers ---
 
-    def _apply_rotation(self, blocks: List[str]) -> List[str]:
+    def _apply_rotation(self, blocks: list[str]) -> list[str]:
         """Drop oldest resolved blocks when their count exceeds max_entries.
 
         Pending blocks are always kept (they represent unprocessed work).
@@ -247,7 +246,7 @@ class TradingMemoryLog:
             return blocks
 
         to_drop = resolved_count - self._max_entries
-        kept: List[str] = []
+        kept: list[str] = []
         for block, is_resolved in decisions:
             if is_resolved and to_drop > 0:
                 to_drop -= 1
@@ -255,7 +254,7 @@ class TradingMemoryLog:
             kept.append(block)
         return kept
 
-    def _parse_entry(self, raw: str) -> Optional[dict]:
+    def _parse_entry(self, raw: str) -> dict | None:
         lines = raw.strip().splitlines()
         if not lines:
             return None

tradingagents/agents/utils/news_data_tools.py

@@ -1,7 +1,10 @@
+from typing import Annotated
+
 from langchain_core.tools import tool
-from typing import Annotated, Optional
+
 from tradingagents.dataflows.interface import route_to_vendor
 
+
 @tool
 def get_news(
     ticker: Annotated[str, "Ticker symbol"],
@@ -23,8 +26,8 @@ def get_news(
 @tool
 def get_global_news(
     curr_date: Annotated[str, "Current date in yyyy-mm-dd format"],
-    look_back_days: Annotated[Optional[int], "Days to look back; omit to use the configured default"] = None,
+    look_back_days: Annotated[int | None, "Days to look back; omit to use the configured default"] = None,
-    limit: Annotated[Optional[int], "Max articles to return; omit to use the configured default"] = None,
+    limit: Annotated[int | None, "Max articles to return; omit to use the configured default"] = None,
 ) -> str:
     """
     Retrieve global news data.

tradingagents/agents/utils/rating.py

@@ -12,11 +12,9 @@ Centralising it here avoids drift between those call sites.
 from __future__ import annotations
 
 import re
-from typing import Tuple
-
 
 # Canonical, ordered 5-tier scale (most bullish to most bearish).
-RATINGS_5_TIER: Tuple[str, ...] = (
+RATINGS_5_TIER: tuple[str, ...] = (
     "Buy", "Overweight", "Hold", "Underweight", "Sell",
 )
 

tradingagents/agents/utils/structured.py

@@ -19,7 +19,8 @@ all three agents log the same warnings when fallback fires.
 from __future__ import annotations
 
 import logging
-from typing import Any, Callable, Optional, TypeVar
+from collections.abc import Callable
+from typing import Any, TypeVar
 
 from pydantic import BaseModel
 
@@ -28,7 +29,7 @@ logger = logging.getLogger(__name__)
 T = TypeVar("T", bound=BaseModel)
 
 
-def bind_structured(llm: Any, schema: type[T], agent_name: str) -> Optional[Any]:
+def bind_structured(llm: Any, schema: type[T], agent_name: str) -> Any | None:
     """Return ``llm.with_structured_output(schema)`` or ``None`` if unsupported.
 
     Logs a warning when the binding fails so the user understands the agent
@@ -46,7 +47,7 @@ def bind_structured(llm: Any, schema: type[T], agent_name: str) -> Optional[Any]
 
 
 def invoke_structured_or_freetext(
-    structured_llm: Optional[Any],
+    structured_llm: Any | None,
     plain_llm: Any,
     prompt: Any,
     render: Callable[[T], str],

tradingagents/agents/utils/technical_indicators_tools.py

@@ -1,7 +1,10 @@
-from langchain_core.tools import tool
 from typing import Annotated
+
+from langchain_core.tools import tool
+
 from tradingagents.dataflows.interface import route_to_vendor
 
+
 @tool
 def get_indicators(
     symbol: Annotated[str, "ticker symbol of the company"],

tradingagents/dataflows/alpha_vantage.py

@@ -1,5 +1,23 @@
-# Import functions from specialized modules
+# Aggregates the per-category Alpha Vantage implementations into one module the
-from .alpha_vantage_stock import get_stock
+# vendor router imports from; the imports below are the public surface.
+from .alpha_vantage_fundamentals import (
+    get_balance_sheet,
+    get_cashflow,
+    get_fundamentals,
+    get_income_statement,
+)
 from .alpha_vantage_indicator import get_indicator
-from .alpha_vantage_fundamentals import get_fundamentals, get_balance_sheet, get_cashflow, get_income_statement
+from .alpha_vantage_news import get_global_news, get_insider_transactions, get_news
-from .alpha_vantage_news import get_news, get_global_news, get_insider_transactions
+from .alpha_vantage_stock import get_stock
+
+__all__ = [
+    "get_balance_sheet",
+    "get_cashflow",
+    "get_fundamentals",
+    "get_income_statement",
+    "get_indicator",
+    "get_global_news",
+    "get_insider_transactions",
+    "get_news",
+    "get_stock",
+]

tradingagents/dataflows/alpha_vantage_indicator.py

@@ -1,4 +1,5 @@
-from .alpha_vantage_common import _make_api_request, AlphaVantageNotConfiguredError
+from .alpha_vantage_common import AlphaVantageNotConfiguredError, _make_api_request
+
 
 def get_indicator(
     symbol: str,
@@ -25,6 +26,7 @@ def get_indicator(
         String containing indicator values and description
     """
     from datetime import datetime
+
     from dateutil.relativedelta import relativedelta
 
     supported_indicators = {
@@ -98,21 +100,7 @@ def get_indicator(
                 "series_type": series_type,
                 "datatype": "csv"
             })
-        elif indicator == "macd":
+        elif indicator == "macd" or indicator == "macds" or indicator == "macdh":
-            data = _make_api_request("MACD", {
-                "symbol": symbol,
-                "interval": interval,
-                "series_type": series_type,
-                "datatype": "csv"
-            })
-        elif indicator == "macds":
-            data = _make_api_request("MACD", {
-                "symbol": symbol,
-                "interval": interval,
-                "series_type": series_type,
-                "datatype": "csv"
-            })
-        elif indicator == "macdh":
             data = _make_api_request("MACD", {
                 "symbol": symbol,
                 "interval": interval,

tradingagents/dataflows/alpha_vantage_news.py

@@ -1,5 +1,6 @@
 from .alpha_vantage_common import _make_api_request, format_datetime_for_api
 
+
 def get_news(ticker, start_date, end_date) -> dict[str, str] | str:
     """Returns live and historical market news & sentiment data from premier news outlets worldwide.
 

tradingagents/dataflows/alpha_vantage_stock.py

@@ -1,5 +1,7 @@
 from datetime import datetime
-from .alpha_vantage_common import _make_api_request, _filter_csv_by_date_range
+
+from .alpha_vantage_common import _filter_csv_by_date_range, _make_api_request
+
 
 def get_stock(
     symbol: str,

tradingagents/dataflows/config.py

@@ -1,10 +1,9 @@
 from copy import deepcopy
-from typing import Dict, Optional
 
 import tradingagents.default_config as default_config
 
 # Use default config but allow it to be overridden
-_config: Optional[Dict] = None
+_config: dict | None = None
 
 
 def initialize_config():
@@ -14,7 +13,7 @@ def initialize_config():
         _config = deepcopy(default_config.DEFAULT_CONFIG)
 
 
-def set_config(config: Dict):
+def set_config(config: dict):
     """Update the configuration with custom values.
 
     Dict-valued keys (e.g. ``data_vendors``) are merged one level deep so a
@@ -31,7 +30,7 @@ def set_config(config: Dict):
             _config[key] = value
 
 
-def get_config() -> Dict:
+def get_config() -> dict:
     """Get the current configuration."""
     if _config is None:
         initialize_config()

tradingagents/dataflows/market_data_validator.py

@@ -10,7 +10,7 @@ claim. Deterministic, no LLM involved.
 
 from __future__ import annotations
 
-from typing import Iterable, Optional
+from collections.abc import Iterable
 
 import pandas as pd
 from stockstats import wrap
@@ -63,7 +63,7 @@ def build_verified_market_snapshot(
     symbol: str,
     curr_date: str,
     look_back_days: int = 30,
-    indicators: Optional[Iterable[str]] = None,
+    indicators: Iterable[str] | None = None,
 ) -> str:
     """Render a ground-truth snapshot: latest OHLCV row, indicators, recent closes."""
     # `df` keeps the original capitalized OHLCV columns (Open/High/Low/Close/

tradingagents/dataflows/utils.py

@@ -1,10 +1,9 @@
-import os
 import re
-import json
+from datetime import date, datetime, timedelta
-import pandas as pd
-from datetime import date, timedelta, datetime
 from typing import Annotated
 
+import pandas as pd
+
 SavePathType = Annotated[str, "File path to save data. If None, data is not saved."]
 
 # Tickers can contain letters, digits, dot, dash, underscore, caret

tradingagents/dataflows/yfinance_news.py

@@ -1,9 +1,9 @@
 """yfinance-based news data fetching functions."""
 
-from typing import Optional
+import contextlib
+from datetime import datetime
 
 import yfinance as yf
-from datetime import datetime
 from dateutil.relativedelta import relativedelta
 
 from .config import get_config
@@ -28,10 +28,8 @@ def _extract_article_data(article: dict) -> dict:
         pub_date_str = content.get("pubDate", "")
         pub_date = None
         if pub_date_str:
-            try:
+            with contextlib.suppress(ValueError, AttributeError):
                 pub_date = datetime.fromisoformat(pub_date_str.replace("Z", "+00:00"))
-            except (ValueError, AttributeError):
-                pass
 
         return {
             "title": title,
@@ -47,10 +45,8 @@ def _extract_article_data(article: dict) -> dict:
         pub_date = None
         ts = article.get("providerPublishTime")
         if ts:
-            try:
+            with contextlib.suppress(ValueError, OSError, TypeError):
                 pub_date = datetime.fromtimestamp(ts)
-            except (ValueError, OSError, TypeError):
-                pass
         return {
             "title": article.get("title", "No title"),
             "summary": article.get("summary", ""),
@@ -131,8 +127,8 @@ def get_news_yfinance(
 
 def get_global_news_yfinance(
     curr_date: str,
-    look_back_days: Optional[int] = None,
+    look_back_days: int | None = None,
-    limit: Optional[int] = None,
+    limit: int | None = None,
 ) -> str:
     """
     Retrieve global/macro economic news using yfinance Search.

tradingagents/graph/__init__.py

@@ -1,11 +1,11 @@
 # TradingAgents/graph/__init__.py
 
-from .trading_graph import TradingAgentsGraph
 from .conditional_logic import ConditionalLogic
-from .setup import GraphSetup
 from .propagation import Propagator
 from .reflection import Reflector
+from .setup import GraphSetup
 from .signal_processing import SignalProcessor
+from .trading_graph import TradingAgentsGraph
 
 __all__ = [
     "TradingAgentsGraph",

tradingagents/graph/analyst_execution.py

@@ -1,6 +1,6 @@
+from collections.abc import Iterable
 from dataclasses import dataclass
 from time import monotonic
-from typing import Dict, Iterable, List, Optional
 
 
 @dataclass(frozen=True)
@@ -14,11 +14,11 @@ class AnalystNodeSpec:
 
 @dataclass(frozen=True)
 class AnalystExecutionPlan:
-    specs: List[AnalystNodeSpec]
+    specs: list[AnalystNodeSpec]
     concurrency_limit: int
 
 
-ANALYST_NODE_SPECS: Dict[str, AnalystNodeSpec] = {
+ANALYST_NODE_SPECS: dict[str, AnalystNodeSpec] = {
     "market": AnalystNodeSpec(
         key="market",
         agent_node="Market Analyst",
@@ -61,7 +61,7 @@ def build_analyst_execution_plan(
     if concurrency_limit < 1:
         raise ValueError("analyst concurrency limit must be >= 1")
 
-    specs: List[AnalystNodeSpec] = []
+    specs: list[AnalystNodeSpec] = []
     for analyst_key in selected_analysts:
         spec = ANALYST_NODE_SPECS.get(analyst_key)
         if spec is None:
@@ -81,10 +81,10 @@ def get_initial_analyst_node(plan: AnalystExecutionPlan) -> str:
 class AnalystWallTimeTracker:
     def __init__(self, plan: AnalystExecutionPlan):
         self.plan = plan
-        self._started_at: Dict[str, float] = {}
+        self._started_at: dict[str, float] = {}
-        self._wall_times: Dict[str, float] = {}
+        self._wall_times: dict[str, float] = {}
 
-    def mark_started(self, analyst_key: str, started_at: Optional[float] = None) -> None:
+    def mark_started(self, analyst_key: str, started_at: float | None = None) -> None:
         if analyst_key not in ANALYST_NODE_SPECS:
             raise ValueError(f"unknown analyst key: {analyst_key}")
         self._started_at.setdefault(analyst_key, monotonic() if started_at is None else started_at)
@@ -92,7 +92,7 @@ class AnalystWallTimeTracker:
     def mark_completed(
         self,
         analyst_key: str,
-        completed_at: Optional[float] = None,
+        completed_at: float | None = None,
     ) -> None:
         if analyst_key not in ANALYST_NODE_SPECS:
             raise ValueError(f"unknown analyst key: {analyst_key}")
@@ -104,7 +104,7 @@ class AnalystWallTimeTracker:
         finished_at = monotonic() if completed_at is None else completed_at
         self._wall_times[analyst_key] = max(0.0, finished_at - started_at)
 
-    def get_wall_times(self) -> Dict[str, float]:
+    def get_wall_times(self) -> dict[str, float]:
         return dict(self._wall_times)
 
     def format_summary(self) -> str:
@@ -121,8 +121,8 @@ class AnalystWallTimeTracker:
 
 def sync_analyst_tracker_from_chunk(
     tracker: AnalystWallTimeTracker,
-    chunk: Dict[str, str],
+    chunk: dict[str, str],
-    now: Optional[float] = None,
+    now: float | None = None,
 ) -> None:
     current_time = monotonic() if now is None else now
     active_found = False

tradingagents/graph/checkpointer.py

@@ -7,9 +7,9 @@ from __future__ import annotations
 
 import hashlib
 import sqlite3
+from collections.abc import Generator
 from contextlib import contextmanager
 from pathlib import Path
-from typing import Generator
 
 from langgraph.checkpoint.sqlite import SqliteSaver
 

tradingagents/graph/propagation.py

@@ -1,8 +1,8 @@
 # TradingAgents/graph/propagation.py
 
-from typing import Dict, Any, List, Optional
+from typing import Any
+
 from tradingagents.agents.utils.agent_states import (
-    AgentState,
     InvestDebateState,
     RiskDebateState,
 )
@@ -22,7 +22,7 @@ class Propagator:
         asset_type: str = "stock",
         past_context: str = "",
         instrument_context: str = "",
-    ) -> Dict[str, Any]:
+    ) -> dict[str, Any]:
         """Create the initial state for the agent graph.
 
         ``instrument_context`` is the deterministic ticker-identity string
@@ -68,7 +68,7 @@ class Propagator:
             "news_report": "",
         }
 
-    def get_graph_args(self, callbacks: Optional[List] = None) -> Dict[str, Any]:
+    def get_graph_args(self, callbacks: list | None = None) -> dict[str, Any]:
         """Get arguments for the graph invocation.
 
         Args:

tradingagents/graph/setup.py

@@ -1,10 +1,25 @@
 # TradingAgents/graph/setup.py
 
-from typing import Any, Dict
+from typing import Any
+
 from langgraph.graph import END, START, StateGraph
 from langgraph.prebuilt import ToolNode
 
-from tradingagents.agents import *
+from tradingagents.agents import (
+    create_aggressive_debator,
+    create_bear_researcher,
+    create_bull_researcher,
+    create_conservative_debator,
+    create_fundamentals_analyst,
+    create_market_analyst,
+    create_msg_delete,
+    create_neutral_debator,
+    create_news_analyst,
+    create_portfolio_manager,
+    create_research_manager,
+    create_sentiment_analyst,
+    create_trader,
+)
 from tradingagents.agents.utils.agent_states import AgentState
 
 from .analyst_execution import build_analyst_execution_plan
@@ -18,7 +33,7 @@ class GraphSetup:
         self,
         quick_thinking_llm: Any,
         deep_thinking_llm: Any,
-        tool_nodes: Dict[str, ToolNode],
+        tool_nodes: dict[str, ToolNode],
         conditional_logic: ConditionalLogic,
         analyst_concurrency_limit: int = 1,
     ):
@@ -30,7 +45,7 @@ class GraphSetup:
         self.analyst_concurrency_limit = analyst_concurrency_limit
 
     def setup_graph(
-        self, selected_analysts=["market", "social", "news", "fundamentals"]
+        self, selected_analysts=("market", "social", "news", "fundamentals")
     ):
         """Set up and compile the agent workflow graph.
 

tradingagents/graph/trading_graph.py

@@ -1,66 +1,57 @@
 # TradingAgents/graph/trading_graph.py
 
+import json
 import logging
 import os
-from pathlib import Path
-import json
 from datetime import datetime, timedelta
-from typing import Dict, Any, Tuple, List, Optional
+from pathlib import Path
+from typing import Any
 
 import yfinance as yf
-
-logger = logging.getLogger(__name__)
-
 from langgraph.prebuilt import ToolNode
 
-from tradingagents.llm_clients import create_llm_client
+# Import the abstract tool methods from agent_utils
-
-from tradingagents.agents import *
-from tradingagents.default_config import DEFAULT_CONFIG
-from tradingagents.agents.utils.memory import TradingMemoryLog
-from tradingagents.dataflows.utils import safe_ticker_component
-from tradingagents.agents.utils.agent_states import (
-    AgentState,
-    InvestDebateState,
-    RiskDebateState,
-)
-from tradingagents.dataflows.config import set_config
-
-# Import the new abstract tool methods from agent_utils
 from tradingagents.agents.utils.agent_utils import (
     build_instrument_context,
-    resolve_instrument_identity,
-    get_stock_data,
-    get_indicators,
-    get_verified_market_snapshot,
-    get_fundamentals,
     get_balance_sheet,
     get_cashflow,
-    get_income_statement,
+    get_fundamentals,
-    get_news,
-    get_insider_transactions,
     get_global_news,
+    get_income_statement,
+    get_indicators,
+    get_insider_transactions,
     get_macro_indicators,
-    get_prediction_markets
+    get_news,
+    get_prediction_markets,
+    get_stock_data,
+    get_verified_market_snapshot,
+    resolve_instrument_identity,
 )
+from tradingagents.agents.utils.memory import TradingMemoryLog
+from tradingagents.dataflows.config import set_config
+from tradingagents.dataflows.utils import safe_ticker_component
+from tradingagents.default_config import DEFAULT_CONFIG
+from tradingagents.llm_clients import create_llm_client
 
 from .checkpointer import checkpoint_step, clear_checkpoint, get_checkpointer, thread_id
 from .conditional_logic import ConditionalLogic
-from .setup import GraphSetup
 from .propagation import Propagator
 from .reflection import Reflector
+from .setup import GraphSetup
 from .signal_processing import SignalProcessor
 
+logger = logging.getLogger(__name__)
+
 
 class TradingAgentsGraph:
     """Main class that orchestrates the trading agents framework."""
 
     def __init__(
         self,
-        selected_analysts=["market", "social", "news", "fundamentals"],
+        selected_analysts=("market", "social", "news", "fundamentals"),
         debug=False,
-        config: Dict[str, Any] = None,
+        config: dict[str, Any] = None,
-        callbacks: Optional[List] = None,
+        callbacks: list | None = None,
     ):
         """Initialize the trading agents graph and components.
 
@@ -138,7 +129,7 @@ class TradingAgentsGraph:
         self.graph = self.workflow.compile()
         self._checkpointer_ctx = None
 
-    def _get_provider_kwargs(self) -> Dict[str, Any]:
+    def _get_provider_kwargs(self) -> dict[str, Any]:
         """Get provider-specific kwargs for LLM client creation."""
         kwargs = {}
         provider = self.config.get("llm_provider", "").lower()
@@ -167,7 +158,7 @@ class TradingAgentsGraph:
 
         return kwargs
 
-    def _create_tool_nodes(self) -> Dict[str, ToolNode]:
+    def _create_tool_nodes(self) -> dict[str, ToolNode]:
         """Create tool nodes for different data sources using abstract methods."""
         return {
             "market": ToolNode(
@@ -233,7 +224,7 @@ class TradingAgentsGraph:
     def _fetch_returns(
         self, ticker: str, trade_date: str, holding_days: int = 5,
         benchmark: str = "SPY",
-    ) -> Tuple[Optional[float], Optional[float], Optional[int]]:
+    ) -> tuple[float | None, float | None, int | None]:
         """Fetch raw and alpha return for ticker over holding_days from trade_date.
 
         ``benchmark`` is the index used as the alpha baseline (resolved by the

tradingagents/llm_clients/anthropic_client.py

@@ -1,5 +1,5 @@
 import re
-from typing import Any, Optional
+from typing import Any
 
 from langchain_anthropic import ChatAnthropic
 
@@ -43,7 +43,7 @@ class NormalizedChatAnthropic(ChatAnthropic):
 class AnthropicClient(BaseLLMClient):
     """Client for Anthropic Claude models."""
 
-    def __init__(self, model: str, base_url: Optional[str] = None, **kwargs):
+    def __init__(self, model: str, base_url: str | None = None, **kwargs):
         super().__init__(model, base_url, **kwargs)
 
     def get_llm(self) -> Any:

tradingagents/llm_clients/api_key_env.py

@@ -11,10 +11,7 @@ prompts for it automatically instead of failing on first API call.
 
 from __future__ import annotations
 
-from typing import Optional
+PROVIDER_API_KEY_ENV: dict[str, str | None] = {
-
-
-PROVIDER_API_KEY_ENV: dict[str, Optional[str]] = {
     "openai":     "OPENAI_API_KEY",
     "anthropic":  "ANTHROPIC_API_KEY",
     "google":     "GOOGLE_API_KEY",
@@ -47,7 +44,7 @@ PROVIDER_API_KEY_ENV: dict[str, Optional[str]] = {
 }
 
 
-def get_api_key_env(provider: str) -> Optional[str]:
+def get_api_key_env(provider: str) -> str | None:
     """Return the env var name for `provider`'s API key, or None if not applicable.
 
     Unknown providers also return None — callers should treat that as

tradingagents/llm_clients/azure_client.py

@@ -1,10 +1,9 @@
 import os
-from typing import Any, Optional
+from typing import Any
 
 from langchain_openai import AzureChatOpenAI
 
 from .base_client import BaseLLMClient, normalize_content
-from .validators import validate_model
 
 _PASSTHROUGH_KWARGS = (
     "timeout", "max_retries", "api_key", "reasoning_effort", "temperature",
@@ -29,7 +28,7 @@ class AzureOpenAIClient(BaseLLMClient):
         OPENAI_API_VERSION: API version (e.g. 2025-03-01-preview)
     """
 
-    def __init__(self, model: str, base_url: Optional[str] = None, **kwargs):
+    def __init__(self, model: str, base_url: str | None = None, **kwargs):
         super().__init__(model, base_url, **kwargs)
 
     def get_llm(self) -> Any:

tradingagents/llm_clients/base_client.py

@@ -1,6 +1,6 @@
-from abc import ABC, abstractmethod
-from typing import Any, Optional
 import warnings
+from abc import ABC, abstractmethod
+from typing import Any
 
 
 def normalize_content(response):
@@ -25,7 +25,7 @@ def normalize_content(response):
 class BaseLLMClient(ABC):
     """Abstract base class for LLM clients."""
 
-    def __init__(self, model: str, base_url: Optional[str] = None, **kwargs):
+    def __init__(self, model: str, base_url: str | None = None, **kwargs):
         self.model = model
         self.base_url = base_url
         self.kwargs = kwargs

tradingagents/llm_clients/capabilities.py

@@ -18,7 +18,6 @@ import re
 from dataclasses import dataclass
 from typing import Literal
 
-
 StructuredMethod = Literal[
     "function_calling",  # uses tools; respects supports_tool_choice
     "json_mode",         # uses response_format={"type":"json_object"}

tradingagents/llm_clients/factory.py

@@ -1,11 +1,11 @@
-from typing import Optional
 
 from .base_client import BaseLLMClient
 
+
 def create_llm_client(
     provider: str,
     model: str,
-    base_url: Optional[str] = None,
+    base_url: str | None = None,
     **kwargs,
 ) -> BaseLLMClient:
     """Create an LLM client for the specified provider.

tradingagents/llm_clients/google_client.py

@@ -1,4 +1,4 @@
-from typing import Any, Optional
+from typing import Any
 
 from langchain_google_genai import ChatGoogleGenerativeAI
 
@@ -20,7 +20,7 @@ class NormalizedChatGoogleGenerativeAI(ChatGoogleGenerativeAI):
 class GoogleClient(BaseLLMClient):
     """Client for Google Gemini models."""
 
-    def __init__(self, model: str, base_url: Optional[str] = None, **kwargs):
+    def __init__(self, model: str, base_url: str | None = None, **kwargs):
         super().__init__(model, base_url, **kwargs)
 
     def get_llm(self) -> Any:

tradingagents/llm_clients/model_catalog.py

@@ -2,14 +2,12 @@
 
 from __future__ import annotations
 
-from typing import Dict, List, Tuple
+ModelOption = tuple[str, str]
-
+ProviderModeOptions = dict[str, dict[str, list[ModelOption]]]
-ModelOption = Tuple[str, str]
-ProviderModeOptions = Dict[str, Dict[str, List[ModelOption]]]
 
 # Providers that serve many / frequently-changing models: offer only "Custom
 # model ID" rather than a list that goes stale.
-_CUSTOM_ONLY: Dict[str, List[ModelOption]] = {
+_CUSTOM_ONLY: dict[str, list[ModelOption]] = {
     "quick": [("Custom model ID", "custom")],
     "deep": [("Custom model ID", "custom")],
 }
@@ -18,7 +16,7 @@ _CUSTOM_ONLY: Dict[str, List[ModelOption]] = {
 # Shared model list for GLM via Z.AI (international) and BigModel (China).
 # Source: docs.z.ai (GLM Coding Plan supported models + LLM guides).
 # All GLM 4.7+ entries support thinking mode via thinking={"type":"enabled"}.
-_GLM_MODELS: Dict[str, List[ModelOption]] = {
+_GLM_MODELS: dict[str, list[ModelOption]] = {
     "quick": [
         ("GLM-5-Turbo - Fast, switchable thinking modes", "glm-5-turbo"),
         ("GLM-4.7 - Previous-gen flagship", "glm-4.7"),
@@ -44,7 +42,7 @@ _GLM_MODELS: Dict[str, List[ModelOption]] = {
 # the backing model. Users who want a specific generation pick it
 # explicitly; users who really want auto-latest can enter the alias via
 # "Custom model ID".
-_QWEN_MODELS: Dict[str, List[ModelOption]] = {
+_QWEN_MODELS: dict[str, list[ModelOption]] = {
     "quick": [
         ("Qwen 3.6 Flash - Latest fast, agentic coding + vision-language", "qwen3.6-flash"),
         ("Qwen 3.5 Flash - Previous-gen fast", "qwen3.5-flash"),
@@ -62,7 +60,7 @@ _QWEN_MODELS: Dict[str, List[ModelOption]] = {
 # Shared model list for MiniMax's global and CN endpoints (same IDs).
 # Full official lineup per platform.minimax.io/docs/api-reference/text-openai-api.
 # All M2.x models share a 204,800-token context window.
-_MINIMAX_MODELS: Dict[str, List[ModelOption]] = {
+_MINIMAX_MODELS: dict[str, list[ModelOption]] = {
     "quick": [
         ("MiniMax-M2.7-highspeed - Faster M2.7, 204K ctx, ~100 TPS", "MiniMax-M2.7-highspeed"),
         ("MiniMax-M2.5-highspeed - Previous-gen highspeed, 204K ctx", "MiniMax-M2.5-highspeed"),
@@ -198,12 +196,12 @@ MODEL_OPTIONS: ProviderModeOptions = {
 }
 
 
-def get_model_options(provider: str, mode: str) -> List[ModelOption]:
+def get_model_options(provider: str, mode: str) -> list[ModelOption]:
     """Return shared model options for a provider and selection mode."""
     return MODEL_OPTIONS[provider.lower()][mode]
 
 
-def get_known_models() -> Dict[str, List[str]]:
+def get_known_models() -> dict[str, list[str]]:
     """Build known model names from the shared CLI catalog."""
     return {
         provider: sorted(

tradingagents/llm_clients/validators.py

@@ -2,7 +2,6 @@
 
 from .model_catalog import get_known_models
 
-
 # Providers whose model names are user-defined (local servers, relays, hosted
 # OpenAI-compatible endpoints serving many models), so any model string is
 # accepted without warning.