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.

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, Optional[str]] = {
+PROVIDER_API_KEY_ENV: dict[str, str | None] = {
     "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.