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fix(cli): honor env precedence for LLM and run config

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Interactive selections and flag defaults overrode TRADINGAGENTS_* env vars.
Rule: an explicit env value or CLI flag wins; otherwise the env-applied
default is kept.

- Research depth: skip the prompt when both round-count env vars are set, and
  stop overwriting them (#977).
- Checkpoint: --checkpoint/--no-checkpoint is tri-state; omitting it keeps
  TRADINGAGENTS_CHECKPOINT_ENABLED (#976).
- Docker ollama: use TRADINGAGENTS_LLM_PROVIDER + OLLAMA_BASE_URL, not a bare
  LLM_PROVIDER the overlay never reads (#975).
- Reasoning/thinking knobs: settable via env; the prompt is skipped when set.
- Effort gating: forward effort only to models that accept it (Anthropic
  Opus 4.5+/Sonnet 4.6+, OpenAI reasoning models); drop it elsewhere.
- Boolean env values: raise a named error on invalid input instead of
  silently becoming False.
This commit is contained in:
Yijia-Xiao
2026-06-21 21:03:05 +00:00
parent c15200dc28
commit a420ad0f3b
11 changed files with 363 additions and 59 deletions
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119
cli/main.py
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@@ -517,6 +517,20 @@ def get_user_selections():
box_content += f"\n[dim]Default: {default}[/dim]"
return Panel(box_content, border_style="blue", padding=(1, 2))
def thinking_value_or_prompt(env_var, config_key, label, box_title, box_body, prompt_fn):
"""Return the env-configured reasoning/thinking value, or prompt for it.
When ``env_var`` is set the interactive choice is skipped and the value
the env overlay placed on DEFAULT_CONFIG is used — mirroring the
env-precedence rule applied to the other selection steps.
"""
if os.environ.get(env_var):
value = DEFAULT_CONFIG[config_key]
console.print(f"[green]✓ {label} from environment:[/green] {value}")
return value
console.print(create_question_box(box_title, box_body))
return prompt_fn()
# Step 1: Ticker symbol
console.print(
create_question_box(
@@ -571,13 +585,27 @@ def get_user_selections():
f"[green]Selected analysts:[/green] {', '.join(analyst.value for analyst in selected_analysts)}"
)
# Step 5: Research depth
console.print(
create_question_box(
"Step 5: Research Depth", "Select your research depth level"
)
# Step 5: Research depth (skipped when both round counts are set via env).
# Research depth maps to the debate + risk round counts; when both are
# supplied through TRADINGAGENTS_MAX_DEBATE_ROUNDS / _MAX_RISK_ROUNDS we keep
# the run non-interactive and honor the env values (#977).
depth_from_env = bool(os.environ.get("TRADINGAGENTS_MAX_DEBATE_ROUNDS")) and bool(
os.environ.get("TRADINGAGENTS_MAX_RISK_ROUNDS")
)
selected_research_depth = select_research_depth()
if depth_from_env:
selected_research_depth = DEFAULT_CONFIG["max_debate_rounds"]
console.print(
f"[green]✓ Research depth from environment:[/green] "
f"{DEFAULT_CONFIG['max_debate_rounds']} debate / "
f"{DEFAULT_CONFIG['max_risk_discuss_rounds']} risk rounds"
)
else:
console.print(
create_question_box(
"Step 5: Research Depth", "Select your research depth level"
)
)
selected_research_depth = select_research_depth()
# Step 6: LLM Provider (skipped when set via TRADINGAGENTS_LLM_PROVIDER).
# The backend URL comes from TRADINGAGENTS_LLM_BACKEND_URL when set,
@@ -649,43 +677,38 @@ def get_user_selections():
selected_shallow_thinker = select_shallow_thinking_agent(selected_llm_provider)
selected_deep_thinker = select_deep_thinking_agent(selected_llm_provider)
# Step 8: Provider-specific thinking configuration
# Step 8: Provider-specific reasoning/thinking configuration. Each knob is
# settable via its TRADINGAGENTS_* env var; when that var is set (or the
# provider itself came from env) the prompt is skipped and the configured
# value is used — same env-precedence rule as the steps above. None = each
# provider's own default.
thinking_level = None
reasoning_effort = None
anthropic_effort = None
provider_lower = selected_llm_provider.lower()
# When the provider is configured via environment we keep the run fully
# non-interactive and use the config defaults (None = each provider's own
# default reasoning/thinking behavior) instead of prompting.
if provider_from_env:
thinking_level = DEFAULT_CONFIG["google_thinking_level"]
reasoning_effort = DEFAULT_CONFIG["openai_reasoning_effort"]
anthropic_effort = DEFAULT_CONFIG["anthropic_effort"]
elif provider_lower == "google":
console.print(
create_question_box(
"Step 8: Thinking Mode",
"Configure Gemini thinking mode"
)
thinking_level = thinking_value_or_prompt(
"TRADINGAGENTS_GOOGLE_THINKING_LEVEL", "google_thinking_level",
"Gemini thinking mode", "Step 8: Thinking Mode",
"Configure Gemini thinking mode", ask_gemini_thinking_config,
)
thinking_level = ask_gemini_thinking_config()
elif provider_lower == "openai":
console.print(
create_question_box(
"Step 8: Reasoning Effort",
"Configure OpenAI reasoning effort level"
)
reasoning_effort = thinking_value_or_prompt(
"TRADINGAGENTS_OPENAI_REASONING_EFFORT", "openai_reasoning_effort",
"Reasoning effort", "Step 8: Reasoning Effort",
"Configure OpenAI reasoning effort level", ask_openai_reasoning_effort,
)
reasoning_effort = ask_openai_reasoning_effort()
elif provider_lower == "anthropic":
console.print(
create_question_box(
"Step 8: Effort Level",
"Configure Claude effort level"
)
anthropic_effort = thinking_value_or_prompt(
"TRADINGAGENTS_ANTHROPIC_EFFORT", "anthropic_effort",
"Claude effort", "Step 8: Effort Level",
"Configure Claude effort level", ask_anthropic_effort,
)
anthropic_effort = ask_anthropic_effort()
return {
"ticker": selected_ticker,
@@ -1019,14 +1042,20 @@ def format_tool_args(args, max_length=80) -> str:
return result[:max_length - 3] + "..."
return result
def run_analysis(checkpoint: bool = False):
# First get all user selections
selections = get_user_selections()
def _build_run_config(selections: dict, checkpoint: bool | None) -> dict:
"""Assemble the run config from interactive selections, honoring env precedence.
# Create config with selected research depth
Round counts and checkpoint follow "explicit env/flag wins": an env-applied
value on DEFAULT_CONFIG is preserved unless the user overrode it on the CLI.
"""
config = DEFAULT_CONFIG.copy()
config["max_debate_rounds"] = selections["research_depth"]
config["max_risk_discuss_rounds"] = selections["research_depth"]
# Research depth sets both round counts, but an explicit env override
# (TRADINGAGENTS_MAX_DEBATE_ROUNDS / _MAX_RISK_ROUNDS) wins over the
# interactive selection — leave the env-applied value in place (#977).
if not os.environ.get("TRADINGAGENTS_MAX_DEBATE_ROUNDS"):
config["max_debate_rounds"] = selections["research_depth"]
if not os.environ.get("TRADINGAGENTS_MAX_RISK_ROUNDS"):
config["max_risk_discuss_rounds"] = selections["research_depth"]
config["quick_think_llm"] = selections["shallow_thinker"]
config["deep_think_llm"] = selections["deep_thinker"]
config["backend_url"] = selections["backend_url"]
@@ -1036,7 +1065,18 @@ def run_analysis(checkpoint: bool = False):
config["openai_reasoning_effort"] = selections.get("openai_reasoning_effort")
config["anthropic_effort"] = selections.get("anthropic_effort")
config["output_language"] = selections.get("output_language", "English")
config["checkpoint_enabled"] = checkpoint
# --checkpoint/--no-checkpoint overrides only when explicitly given; omitting
# the flag preserves TRADINGAGENTS_CHECKPOINT_ENABLED / the default (#976).
if checkpoint is not None:
config["checkpoint_enabled"] = checkpoint
return config
def run_analysis(checkpoint: bool | None = None):
# First get all user selections
selections = get_user_selections()
config = _build_run_config(selections, checkpoint)
# Create stats callback handler for tracking LLM/tool calls
stats_handler = StatsCallbackHandler()
@@ -1316,10 +1356,11 @@ def run_analysis(checkpoint: bool = False):
@app.command()
def analyze(
checkpoint: bool = typer.Option(
False,
"--checkpoint",
help="Enable checkpoint/resume: save state after each node so a crashed run can resume.",
checkpoint: bool | None = typer.Option(
None,
"--checkpoint/--no-checkpoint",
help="Enable/disable checkpoint-resume (save state after each node so a "
"crashed run can resume). Omit to honor TRADINGAGENTS_CHECKPOINT_ENABLED.",
),
clear_checkpoints: bool = typer.Option(
False,