feat: dynamic OpenRouter model selection with search (#482, #337)

cli/utils.py

@@ -134,9 +134,52 @@ def select_research_depth() -> int:
     return choice
 
 
+def _fetch_openrouter_models() -> List[Tuple[str, str]]:
+    """Fetch available models from the OpenRouter API."""
+    import requests
+    try:
+        resp = requests.get("https://openrouter.ai/api/v1/models", timeout=10)
+        resp.raise_for_status()
+        models = resp.json().get("data", [])
+        return [(m.get("name") or m["id"], m["id"]) for m in models]
+    except Exception as e:
+        console.print(f"\n[yellow]Could not fetch OpenRouter models: {e}[/yellow]")
+        return []
+
+
+def select_openrouter_model() -> str:
+    """Select an OpenRouter model from the newest available, or enter a custom ID."""
+    models = _fetch_openrouter_models()
+
+    choices = [questionary.Choice(name, value=mid) for name, mid in models[:5]]
+    choices.append(questionary.Choice("Custom model ID", value="custom"))
+
+    choice = questionary.select(
+        "Select OpenRouter Model (latest available):",
+        choices=choices,
+        instruction="\n- Use arrow keys to navigate\n- Press Enter to select",
+        style=questionary.Style([
+            ("selected", "fg:magenta noinherit"),
+            ("highlighted", "fg:magenta noinherit"),
+            ("pointer", "fg:magenta noinherit"),
+        ]),
+    ).ask()
+
+    if choice is None or choice == "custom":
+        return questionary.text(
+            "Enter OpenRouter model ID (e.g. google/gemma-4-26b-a4b-it):",
+            validate=lambda x: len(x.strip()) > 0 or "Please enter a model ID.",
+        ).ask().strip()
+
+    return choice
+
+
 def select_shallow_thinking_agent(provider) -> str:
     """Select shallow thinking llm engine using an interactive selection."""
 
+    if provider.lower() == "openrouter":
+        return select_openrouter_model()
+
     choice = questionary.select(
         "Select Your [Quick-Thinking LLM Engine]:",
         choices=[
@@ -165,6 +208,9 @@ def select_shallow_thinking_agent(provider) -> str:
 def select_deep_thinking_agent(provider) -> str:
     """Select deep thinking llm engine using an interactive selection."""
 
+    if provider.lower() == "openrouter":
+        return select_openrouter_model()
+
     choice = questionary.select(
         "Select Your [Deep-Thinking LLM Engine]:",
         choices=[

tradingagents/llm_clients/model_catalog.py

@@ -63,16 +63,8 @@ MODEL_OPTIONS: ProviderModeOptions = {
             ("Grok 4.1 Fast (Non-Reasoning) - Speed optimized, 2M ctx", "grok-4-1-fast-non-reasoning"),
         ],
     },
-    "openrouter": {
+    # OpenRouter models are fetched dynamically at CLI runtime.
-        "quick": [
+    # No static entries needed; any model ID is accepted by the validator.
-            ("NVIDIA Nemotron 3 Nano 30B (free)", "nvidia/nemotron-3-nano-30b-a3b:free"),
-            ("Z.AI GLM 4.5 Air (free)", "z-ai/glm-4.5-air:free"),
-        ],
-        "deep": [
-            ("Z.AI GLM 4.5 Air (free)", "z-ai/glm-4.5-air:free"),
-            ("NVIDIA Nemotron 3 Nano 30B (free)", "nvidia/nemotron-3-nano-30b-a3b:free"),
-        ],
-    },
     "ollama": {
         "quick": [
             ("Qwen3:latest (8B, local)", "qwen3:latest"),