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feat(cli): skip interactive LLM selection when configured via environment (#873)

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Setting the LLM env vars now skips the matching CLI selection step and uses
the value, so OpenAI-compatible endpoints (opencode, LM Studio, etc.) and
unattended runs work without prompting. Unset vars are chosen interactively
as before.

  TRADINGAGENTS_LLM_PROVIDER -> skips provider step (still verifies API key)
  TRADINGAGENTS_LLM_BACKEND_URL -> custom endpoint (else provider default)
  TRADINGAGENTS_DEEP_THINK_LLM / _QUICK_THINK_LLM -> skips model step
  TRADINGAGENTS_OUTPUT_LANGUAGE -> skips language step

Builds on the existing TRADINGAGENTS_* config overrides (which already feed
DEFAULT_CONFIG); this wires the CLI to honor them instead of re-prompting.
This commit is contained in:
Yijia-Xiao
2026-05-31 22:38:48 +00:00
parent 1ff3f07a73
commit 2e67782f20
5 changed files with 202 additions and 45 deletions
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110
cli/main.py
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@@ -1,4 +1,5 @@
from typing import Optional
import os
import datetime
import typer
import questionary
@@ -529,14 +530,20 @@ def get_user_selections():
)
analysis_date = get_analysis_date()
# Step 3: Output language
console.print(
create_question_box(
"Step 3: Output Language",
"Select the language for analyst reports and final decision"
# Step 3: Output language (skipped when set via TRADINGAGENTS_OUTPUT_LANGUAGE)
if os.environ.get("TRADINGAGENTS_OUTPUT_LANGUAGE"):
output_language = DEFAULT_CONFIG["output_language"]
console.print(
f"[green]✓ Output language from environment:[/green] {output_language}"
)
)
output_language = ask_output_language()
else:
console.print(
create_question_box(
"Step 3: Output Language",
"Select the language for analyst reports and final decision"
)
)
output_language = ask_output_language()
# Step 4: Select analysts
console.print(
@@ -557,42 +564,62 @@ def get_user_selections():
)
selected_research_depth = select_research_depth()
# Step 6: LLM Provider
console.print(
create_question_box(
"Step 6: LLM Provider", "Select your LLM provider"
# Step 6: LLM Provider (skipped when set via TRADINGAGENTS_LLM_PROVIDER).
# The backend URL comes from TRADINGAGENTS_LLM_BACKEND_URL when set,
# otherwise the provider's default endpoint — the same value the menu
# would have picked.
provider_from_env = bool(os.environ.get("TRADINGAGENTS_LLM_PROVIDER"))
if provider_from_env:
selected_llm_provider = DEFAULT_CONFIG["llm_provider"].lower()
backend_url = DEFAULT_CONFIG["backend_url"] or provider_default_url(selected_llm_provider)
console.print(f"[green]✓ LLM provider from environment:[/green] {selected_llm_provider}")
console.print(f"[green]✓ Backend URL:[/green] {backend_url}")
# Still confirm/persist the API key so the run doesn't fail later.
ensure_api_key(selected_llm_provider)
else:
console.print(
create_question_box(
"Step 6: LLM Provider", "Select your LLM provider"
)
)
)
selected_llm_provider, backend_url = select_llm_provider()
selected_llm_provider, backend_url = select_llm_provider()
# Providers with regional endpoints prompt for the region as a secondary
# step so the main dropdown stays clean (mainland China and international
# accounts cannot share API keys).
if selected_llm_provider == "qwen":
selected_llm_provider, backend_url = ask_qwen_region()
elif selected_llm_provider == "minimax":
selected_llm_provider, backend_url = ask_minimax_region()
elif selected_llm_provider == "glm":
selected_llm_provider, backend_url = ask_glm_region()
# Providers with regional endpoints prompt for the region as a secondary
# step so the main dropdown stays clean (mainland China and international
# accounts cannot share API keys).
if selected_llm_provider == "qwen":
selected_llm_provider, backend_url = ask_qwen_region()
elif selected_llm_provider == "minimax":
selected_llm_provider, backend_url = ask_minimax_region()
elif selected_llm_provider == "glm":
selected_llm_provider, backend_url = ask_glm_region()
# For Ollama, surface the resolved endpoint (OLLAMA_BASE_URL vs default)
# before model selection so it's obvious where we're connecting.
if selected_llm_provider == "ollama":
confirm_ollama_endpoint(backend_url)
# For Ollama, surface the resolved endpoint (OLLAMA_BASE_URL vs default)
# before model selection so it's obvious where we're connecting.
if selected_llm_provider == "ollama":
confirm_ollama_endpoint(backend_url)
# Confirm the provider's API key is present; prompt the user to paste
# one and persist it to .env if it's missing, so the analysis run
# doesn't fail later at the first API call.
ensure_api_key(selected_llm_provider)
# Confirm the provider's API key is present; prompt the user to paste
# one and persist it to .env if it's missing, so the analysis run
# doesn't fail later at the first API call.
ensure_api_key(selected_llm_provider)
# Step 7: Thinking agents
console.print(
create_question_box(
"Step 7: Thinking Agents", "Select your thinking agents for analysis"
# Step 7: Thinking agents (skipped when either model is set via environment)
if os.environ.get("TRADINGAGENTS_QUICK_THINK_LLM") or os.environ.get("TRADINGAGENTS_DEEP_THINK_LLM"):
selected_shallow_thinker = DEFAULT_CONFIG["quick_think_llm"]
selected_deep_thinker = DEFAULT_CONFIG["deep_think_llm"]
console.print(
f"[green]✓ Thinking agents from environment:[/green] "
f"quick={selected_shallow_thinker}, deep={selected_deep_thinker}"
)
)
selected_shallow_thinker = select_shallow_thinking_agent(selected_llm_provider)
selected_deep_thinker = select_deep_thinking_agent(selected_llm_provider)
else:
console.print(
create_question_box(
"Step 7: Thinking Agents", "Select your thinking agents for analysis"
)
)
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
thinking_level = None
@@ -600,7 +627,14 @@ def get_user_selections():
anthropic_effort = None
provider_lower = selected_llm_provider.lower()
if provider_lower == "google":
# 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",