fix: recover from stale model context when configured models change (#898)

* fix: recover from stale model context after config model changes

* fix: fail fast on missing model config and expand model resolution tests

* fix: remove duplicate get_app_config imports

* fix: align model resolution tests with runtime imports

* Apply suggestions from code review

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

* fix: remove duplicate model resolution test case

---------

Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

backend/src/agents/lead_agent/agent.py

@@ -1,3 +1,5 @@
+import logging
+
 from langchain.agents import create_agent
 from langchain.agents.middleware import SummarizationMiddleware, TodoListMiddleware
 from langchain_core.runnables import RunnableConfig
@@ -17,6 +19,25 @@ from src.config.summarization_config import get_summarization_config
 from src.models import create_chat_model
 from src.sandbox.middleware import SandboxMiddleware
 
+logger = logging.getLogger(__name__)
+
+
+def _resolve_model_name(requested_model_name: str | None) -> str:
+    """Resolve a runtime model name safely, falling back to default if invalid. Returns None if no models are configured."""
+    app_config = get_app_config()
+    default_model_name = app_config.models[0].name if app_config.models else None
+    if default_model_name is None:
+        raise ValueError(
+            "No chat models are configured. Please configure at least one model in config.yaml."
+        )
+
+    if requested_model_name and app_config.get_model_config(requested_model_name):
+        return requested_model_name
+
+    if requested_model_name and requested_model_name != default_model_name:
+        logger.warning(f"Model '{requested_model_name}' not found in config; fallback to default model '{default_model_name}'.")
+    return default_model_name
+
 
 def _create_summarization_middleware() -> SummarizationMiddleware | None:
     """Create and configure the summarization middleware from config."""
@@ -184,7 +205,7 @@ Being proactive with task management demonstrates thoroughness and ensures all r
 # MemoryMiddleware queues conversation for memory update (after TitleMiddleware)
 # ViewImageMiddleware should be before ClarificationMiddleware to inject image details before LLM
 # ClarificationMiddleware should be last to intercept clarification requests after model calls
-def _build_middlewares(config: RunnableConfig):
+def _build_middlewares(config: RunnableConfig, model_name: str | None):
     """Build middleware chain based on runtime configuration.
 
     Args:
@@ -212,14 +233,9 @@ def _build_middlewares(config: RunnableConfig):
     # Add MemoryMiddleware (after TitleMiddleware)
     middlewares.append(MemoryMiddleware())
 
-    # Add ViewImageMiddleware only if the current model supports vision
-    model_name = config.get("configurable", {}).get("model_name") or config.get("configurable", {}).get("model")
-
+    # Add ViewImageMiddleware only if the current model supports vision.
+    # Use the resolved runtime model_name from make_lead_agent to avoid stale config values.
     app_config = get_app_config()
-    # If no model_name specified, use the first model (default)
-    if model_name is None and app_config.models:
-        model_name = app_config.models[0].name
-
     model_config = app_config.get_model_config(model_name) if model_name else None
     if model_config is not None and model_config.supports_vision:
         middlewares.append(ViewImageMiddleware())
@@ -240,11 +256,31 @@ def make_lead_agent(config: RunnableConfig):
     from src.tools import get_available_tools
 
     thinking_enabled = config.get("configurable", {}).get("thinking_enabled", True)
-    model_name = config.get("configurable", {}).get("model_name") or config.get("configurable", {}).get("model")
+    requested_model_name = config.get("configurable", {}).get("model_name") or config.get("configurable", {}).get("model")
+    model_name = _resolve_model_name(requested_model_name)
+    if model_name is None:
+        raise ValueError(
+            "No chat model could be resolved. Please configure at least one model in "
+            "config.yaml or provide a valid 'model_name'/'model' in the request."
+        )
     is_plan_mode = config.get("configurable", {}).get("is_plan_mode", False)
     subagent_enabled = config.get("configurable", {}).get("subagent_enabled", False)
     max_concurrent_subagents = config.get("configurable", {}).get("max_concurrent_subagents", 3)
-    print(f"thinking_enabled: {thinking_enabled}, model_name: {model_name}, is_plan_mode: {is_plan_mode}, subagent_enabled: {subagent_enabled}, max_concurrent_subagents: {max_concurrent_subagents}")
+
+    app_config = get_app_config()
+    model_config = app_config.get_model_config(model_name) if model_name else None
+    if thinking_enabled and model_config is not None and not model_config.supports_thinking:
+        logger.warning(f"Thinking mode is enabled but model '{model_name}' does not support it; fallback to non-thinking mode.")
+        thinking_enabled = False
+
+    logger.info(
+        "thinking_enabled: %s, model_name: %s, is_plan_mode: %s, subagent_enabled: %s, max_concurrent_subagents: %s",
+        thinking_enabled,
+        model_name,
+        is_plan_mode,
+        subagent_enabled,
+        max_concurrent_subagents,
+    )
 
     # Inject run metadata for LangSmith trace tagging
     if "metadata" not in config:
@@ -261,7 +297,7 @@ def make_lead_agent(config: RunnableConfig):
     return create_agent(
         model=create_chat_model(name=model_name, thinking_enabled=thinking_enabled),
         tools=get_available_tools(model_name=model_name, subagent_enabled=subagent_enabled),
-        middleware=_build_middlewares(config),
+        middleware=_build_middlewares(config, model_name=model_name),
         system_prompt=apply_prompt_template(subagent_enabled=subagent_enabled, max_concurrent_subagents=max_concurrent_subagents),
         state_schema=ThreadState,
     )

backend/tests/test_lead_agent_model_resolution.py

@@ -0,0 +1,136 @@
+"""Tests for lead agent runtime model resolution behavior."""
+
+from __future__ import annotations
+
+import pytest
+
+from src.agents.lead_agent import agent as lead_agent_module
+from src.config.app_config import AppConfig
+from src.config.model_config import ModelConfig
+from src.config.sandbox_config import SandboxConfig
+
+
+def _make_app_config(models: list[ModelConfig]) -> AppConfig:
+    return AppConfig(
+        models=models,
+        sandbox=SandboxConfig(use="src.sandbox.local:LocalSandboxProvider"),
+    )
+
+
+def _make_model(name: str, *, supports_thinking: bool) -> ModelConfig:
+    return ModelConfig(
+        name=name,
+        display_name=name,
+        description=None,
+        use="langchain_openai:ChatOpenAI",
+        model=name,
+        supports_thinking=supports_thinking,
+        supports_vision=False,
+    )
+
+
+def test_resolve_model_name_falls_back_to_default(monkeypatch, caplog):
+    app_config = _make_app_config(
+        [
+            _make_model("default-model", supports_thinking=False),
+            _make_model("other-model", supports_thinking=True),
+        ]
+    )
+
+    monkeypatch.setattr(lead_agent_module, "get_app_config", lambda: app_config)
+
+    with caplog.at_level("WARNING"):
+        resolved = lead_agent_module._resolve_model_name("missing-model")
+
+    assert resolved == "default-model"
+    assert "fallback to default model 'default-model'" in caplog.text
+
+
+def test_resolve_model_name_uses_default_when_none(monkeypatch):
+    app_config = _make_app_config(
+        [
+            _make_model("default-model", supports_thinking=False),
+            _make_model("other-model", supports_thinking=True),
+        ]
+    )
+
+    monkeypatch.setattr(lead_agent_module, "get_app_config", lambda: app_config)
+
+    resolved = lead_agent_module._resolve_model_name(None)
+
+    assert resolved == "default-model"
+
+
+def test_resolve_model_name_raises_when_no_models_configured(monkeypatch):
+    app_config = _make_app_config([])
+
+    monkeypatch.setattr(lead_agent_module, "get_app_config", lambda: app_config)
+
+    with pytest.raises(
+        ValueError,
+        match="No chat models are configured",
+    ):
+        lead_agent_module._resolve_model_name("missing-model")
+
+
+def test_make_lead_agent_disables_thinking_when_model_does_not_support_it(monkeypatch):
+    app_config = _make_app_config([_make_model("safe-model", supports_thinking=False)])
+
+    import src.tools as tools_module
+
+    monkeypatch.setattr(lead_agent_module, "get_app_config", lambda: app_config)
+    monkeypatch.setattr(tools_module, "get_available_tools", lambda **kwargs: [])
+    monkeypatch.setattr(lead_agent_module, "_build_middlewares", lambda config, model_name: [])
+
+    captured: dict[str, object] = {}
+
+    def _fake_create_chat_model(*, name, thinking_enabled):
+        captured["name"] = name
+        captured["thinking_enabled"] = thinking_enabled
+        return object()
+
+    monkeypatch.setattr(lead_agent_module, "create_chat_model", _fake_create_chat_model)
+    monkeypatch.setattr(lead_agent_module, "create_agent", lambda **kwargs: kwargs)
+
+    result = lead_agent_module.make_lead_agent(
+        {
+            "configurable": {
+                "model_name": "safe-model",
+                "thinking_enabled": True,
+                "is_plan_mode": False,
+                "subagent_enabled": False,
+            }
+        }
+    )
+
+    assert captured["name"] == "safe-model"
+    assert captured["thinking_enabled"] is False
+    assert result["model"] is not None
+
+
+def test_build_middlewares_uses_resolved_model_name_for_vision(monkeypatch):
+    app_config = _make_app_config(
+        [
+            _make_model("stale-model", supports_thinking=False),
+            ModelConfig(
+                name="vision-model",
+                display_name="vision-model",
+                description=None,
+                use="langchain_openai:ChatOpenAI",
+                model="vision-model",
+                supports_thinking=False,
+                supports_vision=True,
+            ),
+        ]
+    )
+
+    monkeypatch.setattr(lead_agent_module, "get_app_config", lambda: app_config)
+    monkeypatch.setattr(lead_agent_module, "_create_summarization_middleware", lambda: None)
+    monkeypatch.setattr(lead_agent_module, "_create_todo_list_middleware", lambda is_plan_mode: None)
+
+    middlewares = lead_agent_module._build_middlewares(
+        {"configurable": {"model_name": "stale-model", "is_plan_mode": False, "subagent_enabled": False}},
+        model_name="vision-model",
+    )
+
+    assert any(isinstance(m, lead_agent_module.ViewImageMiddleware) for m in middlewares)

frontend/src/components/workspace/input-box.tsx

@@ -12,7 +12,13 @@ import {
   ZapIcon,
 } from "lucide-react";
 import { useSearchParams } from "next/navigation";
-import { useCallback, useMemo, useState, type ComponentProps } from "react";
+import {
+  useCallback,
+  useEffect,
+  useMemo,
+  useState,
+  type ComponentProps,
+} from "react";
 
 import {
   PromptInput,
@@ -63,6 +69,21 @@ import {
 import { ModeHoverGuide } from "./mode-hover-guide";
 import { Tooltip } from "./tooltip";
 
+type InputMode = "flash" | "thinking" | "pro" | "ultra";
+
+function getResolvedMode(
+  mode: InputMode | undefined,
+  supportsThinking: boolean,
+): InputMode {
+  if (!supportsThinking && mode !== "flash") {
+    return "flash";
+  }
+  if (mode) {
+    return mode;
+  }
+  return supportsThinking ? "pro" : "flash";
+}
+
 export function InputBox({
   className,
   disabled,
@@ -104,42 +125,64 @@ export function InputBox({
   const searchParams = useSearchParams();
   const [modelDialogOpen, setModelDialogOpen] = useState(false);
   const { models } = useModels();
-  const selectedModel = useMemo(() => {
-    if (!context.model_name && models.length > 0) {
-      const model = models[0]!;
-      setTimeout(() => {
-        onContextChange?.({
-          ...context,
-          model_name: model.name,
-          mode: model.supports_thinking ? "pro" : "flash",
-        });
-      }, 0);
-      return model;
+
+  useEffect(() => {
+    if (models.length === 0) {
+      return;
     }
-    return models.find((m) => m.name === context.model_name);
+    const currentModel = models.find((m) => m.name === context.model_name);
+    const fallbackModel = currentModel ?? models[0]!;
+    const supportsThinking = fallbackModel.supports_thinking ?? false;
+    const nextModelName = fallbackModel.name;
+    const nextMode = getResolvedMode(context.mode, supportsThinking);
+
+    if (context.model_name === nextModelName && context.mode === nextMode) {
+      return;
+    }
+
+    onContextChange?.({
+      ...context,
+      model_name: nextModelName,
+      mode: nextMode,
+    });
   }, [context, models, onContextChange]);
+
+  const selectedModel = useMemo(() => {
+    if (models.length === 0) {
+      return undefined;
+    }
+    return models.find((m) => m.name === context.model_name) ?? models[0];
+  }, [context.model_name, models]);
+
   const supportThinking = useMemo(
     () => selectedModel?.supports_thinking ?? false,
     [selectedModel],
   );
+
   const handleModelSelect = useCallback(
     (model_name: string) => {
+      const model = models.find((m) => m.name === model_name);
+      if (!model) {
+        return;
+      }
       onContextChange?.({
         ...context,
         model_name,
+        mode: getResolvedMode(context.mode, model.supports_thinking ?? false),
       });
       setModelDialogOpen(false);
     },
-    [onContextChange, context],
+    [onContextChange, context, models],
   );
+
   const handleModeSelect = useCallback(
-    (mode: "flash" | "thinking" | "pro" | "ultra") => {
+    (mode: InputMode) => {
       onContextChange?.({
         ...context,
-        mode,
+        mode: getResolvedMode(mode, supportThinking),
       });
     },
-    [onContextChange, context],
+    [onContextChange, context, supportThinking],
   );
   const handleSubmit = useCallback(
     async (message: PromptInputMessage) => {