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

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.

.env.example

@@ -22,6 +22,9 @@ OPENROUTER_API_KEY=
 # Any TRADINGAGENTS_* variable below, when set, replaces the matching key
 # in tradingagents/default_config.py. Values are coerced to the type of
 # the existing default (bool / int / str), so "true"/"3" work as expected.
+# In the CLI, setting the LLM provider / models / backend URL / language
+# also skips the matching interactive selection step (useful for
+# OpenAI-compatible endpoints like opencode or LM Studio, and unattended runs).
 #TRADINGAGENTS_LLM_PROVIDER=openai
 #TRADINGAGENTS_DEEP_THINK_LLM=gpt-5.4
 #TRADINGAGENTS_QUICK_THINK_LLM=gpt-5.4-mini

cli/main.py

@@ -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",

cli/utils.py

@@ -268,14 +268,17 @@ def select_deep_thinking_agent(provider) -> str:
     """Select deep thinking llm engine using an interactive selection."""
     return _select_model(provider, "deep")
 
-def select_llm_provider() -> tuple[str, str | None]:
-    """Select the LLM provider and its API endpoint."""
-    # Ollama users can point at a remote ollama-serve via OLLAMA_BASE_URL
-    # (convention from the broader Ollama ecosystem); falls back to the
-    # localhost default when unset.
+def _llm_provider_table() -> list[tuple[str, str, str | None]]:
+    """(display_name, provider_key, base_url) for every supported provider.
+
+    Shared by the interactive picker and by env-driven configuration so an
+    env-set provider resolves to the same default endpoint the menu uses.
+    Ollama users can point at a remote ollama-serve via OLLAMA_BASE_URL
+    (convention from the broader Ollama ecosystem); falls back to the
+    localhost default when unset.
+    """
     ollama_url = os.environ.get("OLLAMA_BASE_URL") or "http://localhost:11434/v1"
-    # (display_name, provider_key, base_url)
-    PROVIDERS = [
+    return [
         ("OpenAI", "openai", "https://api.openai.com/v1"),
         ("Google", "google", None),
         ("Anthropic", "anthropic", "https://api.anthropic.com/"),
@@ -289,6 +292,20 @@ def select_llm_provider() -> tuple[str, str | None]:
         ("Ollama", "ollama", ollama_url),
     ]
 
+
+def provider_default_url(provider_key: str) -> str | None:
+    """Return the default backend URL for a provider key, or None if unknown."""
+    key = provider_key.lower()
+    for _, pk, url in _llm_provider_table():
+        if pk == key:
+            return url
+    return None
+
+
+def select_llm_provider() -> tuple[str, str | None]:
+    """Select the LLM provider and its API endpoint."""
+    PROVIDERS = _llm_provider_table()
+
     choice = questionary.select(
         "Select your LLM Provider:",
         choices=[

tests/test_cli_env_skip.py

@@ -0,0 +1,86 @@
+"""Tests for env-driven CLI behavior (#897, #873).
+
+The config-layer override (TRADINGAGENTS_* -> DEFAULT_CONFIG) is covered by
+test_env_overrides.py. These tests cover the CLI layer: an env-configured
+provider/model/language must skip its interactive prompt and use the value.
+"""
+
+import os
+import unittest
+from unittest import mock
+
+import pytest
+
+
+@pytest.mark.unit
+class TestProviderDefaultUrl(unittest.TestCase):
+    def test_known_providers_resolve(self):
+        from cli.utils import provider_default_url
+        self.assertEqual(provider_default_url("openai"), "https://api.openai.com/v1")
+        self.assertEqual(provider_default_url("DeepSeek"), "https://api.deepseek.com")
+        self.assertIsNone(provider_default_url("google"))  # uses SDK default
+
+    def test_unknown_provider_returns_none(self):
+        from cli.utils import provider_default_url
+        self.assertIsNone(provider_default_url("not-a-provider"))
+
+    def test_ollama_honors_base_url_env(self):
+        from cli.utils import provider_default_url
+        with mock.patch.dict(os.environ, {"OLLAMA_BASE_URL": "http://host:1234/v1"}):
+            self.assertEqual(provider_default_url("ollama"), "http://host:1234/v1")
+
+
+@pytest.mark.unit
+class TestCliSkipsPromptsFromEnv(unittest.TestCase):
+    def test_env_config_skips_llm_prompts(self):
+        import cli.main as m
+
+        env = {
+            "TRADINGAGENTS_LLM_PROVIDER": "openai",
+            "TRADINGAGENTS_DEEP_THINK_LLM": "kimi-k2.5",
+            "TRADINGAGENTS_QUICK_THINK_LLM": "deepseek-v4-pro",
+            "TRADINGAGENTS_LLM_BACKEND_URL": "https://opencode.ai/zen/go/v1",
+            "TRADINGAGENTS_OUTPUT_LANGUAGE": "Japanese",
+        }
+        fake_cfg = dict(m.DEFAULT_CONFIG)
+        fake_cfg.update({
+            "llm_provider": "openai",
+            "backend_url": "https://opencode.ai/zen/go/v1",
+            "quick_think_llm": "deepseek-v4-pro",
+            "deep_think_llm": "kimi-k2.5",
+            "output_language": "Japanese",
+        })
+
+        with mock.patch.dict(os.environ, env, clear=False), \
+             mock.patch.object(m, "DEFAULT_CONFIG", fake_cfg), \
+             mock.patch.object(m, "fetch_announcements", return_value=None), \
+             mock.patch.object(m, "display_announcements"), \
+             mock.patch.object(m, "get_ticker", return_value="AAPL"), \
+             mock.patch.object(m, "get_analysis_date", return_value="2026-05-29"), \
+             mock.patch.object(m, "select_analysts", return_value=[]), \
+             mock.patch.object(m, "select_research_depth", return_value=1), \
+             mock.patch.object(m, "ensure_api_key") as ensure_key, \
+             mock.patch.object(m, "select_llm_provider") as prompt_provider, \
+             mock.patch.object(m, "ask_output_language") as prompt_lang, \
+             mock.patch.object(m, "select_shallow_thinking_agent") as prompt_quick, \
+             mock.patch.object(m, "select_deep_thinking_agent") as prompt_deep:
+            sel = m.get_user_selections()
+
+        # None of the LLM selection prompts should have been shown.
+        prompt_provider.assert_not_called()
+        prompt_lang.assert_not_called()
+        prompt_quick.assert_not_called()
+        prompt_deep.assert_not_called()
+        # API key is still verified for the env-configured provider.
+        ensure_key.assert_called_once()
+
+        # The env values flow into the returned selections.
+        self.assertEqual(sel["llm_provider"], "openai")
+        self.assertEqual(sel["backend_url"], "https://opencode.ai/zen/go/v1")
+        self.assertEqual(sel["shallow_thinker"], "deepseek-v4-pro")
+        self.assertEqual(sel["deep_thinker"], "kimi-k2.5")
+        self.assertEqual(sel["output_language"], "Japanese")
+
+
+if __name__ == "__main__":
+    unittest.main()

tests/test_ollama_base_url.py

@@ -7,6 +7,23 @@ import importlib
 import pytest
 
 
+@pytest.fixture(scope="module", autouse=True)
+def _resync_reloaded_modules():
+    """Restore module state after this file's importlib.reload() calls.
+
+    Several tests below reload ``cli.utils`` to re-evaluate OLLAMA_BASE_URL.
+    That leaves ``cli.main``'s star-imported names (e.g. get_ticker) bound to
+    the pre-reload module objects, which breaks identity checks in unrelated
+    tests that happen to run afterward. Re-sync once on teardown so the reload
+    doesn't leak across test modules.
+    """
+    yield
+    import cli.utils
+    import cli.main
+    importlib.reload(cli.utils)
+    importlib.reload(cli.main)
+
+
 # ---- openai_client side: _resolve_provider_base_url -----------------------