Release/v0.1.4 (#266)

* feat(middleware): reposition code interpreter middleware in the stack * feat(models): add qwen3.7-plus model entry and update context window comment * feat(models): add qwen3.7-max and qwen3.7-plus model entries for DashScope * feat(auxiliary): implement auxiliary model support for background tasks and tool selection - Added auxiliary model configuration to EvoScientistConfig. - Introduced _ensure_auxiliary_chat_model function to manage auxiliary model instances. - Updated onboarding steps to include auxiliary model selection. - Modified middleware to route tool selection to the auxiliary model when applicable. - Enhanced tests to cover auxiliary model functionality and configuration. * feat(steps): update UI backend selection options and descriptions * Refactor code structure for improved readability and maintainability * feat(patches): implement OpenRouter response reasoning item stripping to prevent multi-turn errors * feat: update version to v0.1.4 in badges, README, and pyproject.toml; adjust skill counts in steps.py * feat(config): add auxiliary model and provider environment variables to test setup
2026-06-07 00:52:59 +01:00
parent 3563c1d94f
commit 63969b596d
24 changed files with 888 additions and 113 deletions
@@ -5,5 +5,5 @@
  <rect x="54" y="5" width="62" height="24" rx="6" fill="#1565c0"/>
  <text x="85" y="22" text-anchor="middle"
        font-family="Inter, -apple-system, system-ui, sans-serif"
-        font-size="13" font-weight="700" fill="#ffffff">v0.1.3</text>
+        font-size="13" font-weight="700" fill="#ffffff">v0.1.4</text>
 </svg>
@@ -5,5 +5,5 @@
  <rect x="54" y="5" width="62" height="24" rx="6" fill="#2563eb"/>
  <text x="85" y="22" text-anchor="middle"
        font-family="Inter, -apple-system, system-ui, sans-serif"
-        font-size="13" font-weight="700" fill="#ffffff">v0.1.3</text>
+        font-size="13" font-weight="700" fill="#ffffff">v0.1.4</text>
 </svg>
@@ -59,6 +59,13 @@ _chat_model = None
 # /model switch to lag one step (see issue #179).
 _chat_model_key: tuple[str | None, str | None] | None = None

+# Auxiliary model for background/helper LLM calls (memory workers + main-agent
+# tool selector). Cached separately from the main model; falls back to the main
+# instance when the auxiliary_* config fields are empty (see
+# _ensure_auxiliary_chat_model).
+_auxiliary_chat_model = None
+_auxiliary_chat_model_key: tuple[str | None, str | None] | None = None
+
 # Cache MCP tools by the effective config signature to avoid reconnecting
 # to MCP servers on every `/new` when config is unchanged.
 _MCP_TOOLS_CACHE_KEY: str | None = None
@@ -124,6 +131,32 @@ def _ensure_chat_model():
    return _chat_model


+def _ensure_auxiliary_chat_model():
+    """Return the auxiliary chat model for background/helper LLM calls.
+
+    Resolves ``(cfg.auxiliary_model or cfg.model, cfg.auxiliary_provider or
+    cfg.provider)``. When the auxiliary fields are empty — or resolve to the same
+    ``(model, provider)`` pair as the main model — returns the main
+    ``_ensure_chat_model()`` instance directly, so no second client is built.
+    Otherwise it is cached separately under its own key. Onboard sets the
+    provider alongside the model, so the ``or cfg.provider`` fallback only
+    matters for a model set without an explicit auxiliary provider.
+    """
+    global _auxiliary_chat_model, _auxiliary_chat_model_key
+    from .llm import get_chat_model
+
+    cfg = _ensure_config()
+    aux_model = cfg.auxiliary_model or cfg.model
+    aux_provider = cfg.auxiliary_provider or cfg.provider
+    if (aux_model, aux_provider) == (cfg.model, cfg.provider):
+        return _ensure_chat_model()
+    key = (aux_model, aux_provider)
+    if _auxiliary_chat_model is None or _auxiliary_chat_model_key != key:
+        _auxiliary_chat_model = get_chat_model(model=aux_model, provider=aux_provider)
+        _auxiliary_chat_model_key = key
+    return _auxiliary_chat_model
+
+
 def set_chat_model(model: str, provider: str | None = None):
    """Replace the cached chat model with a new one.

@@ -136,6 +169,12 @@ def set_chat_model(model: str, provider: str | None = None):
    """
    from .llm import get_chat_model

+    # Invalidate the auxiliary cache too: when auxiliary_* is empty it mirrors
+    # the main model, so a /model switch must let it re-resolve to the new main.
+    global _auxiliary_chat_model, _auxiliary_chat_model_key
+    _auxiliary_chat_model = None
+    _auxiliary_chat_model_key = None
+
    key = (model, provider)
    if _chat_model is None or _chat_model_key != key:
        _replace_chat_model(get_chat_model(model=model, provider=provider), key)
@@ -585,13 +624,26 @@ def _get_default_middleware(
            MemoryObservationTarget.AGENT
        ),
    )
+    # Main-agent tool selection may use the auxiliary model; async sub-agents
+    # keep the main model (they do real work, not a one-off helper call).
+    # context_editing stays on the main model — its model only sizes the
+    # context-window trigger for the main agent's own history.
+    tool_selector_model = (
+        model if for_async_subagent else _ensure_auxiliary_chat_model()
+    )
    mw = [
        ConfigurableModelMiddleware(),
        create_context_editing_middleware(model),
        ModelFallbackMiddleware(),
        ContextOverflowMapperMiddleware(),
        ToolErrorHandlerMiddleware(),
-        *create_tool_selector_middleware(model=model),
+        *create_tool_selector_middleware(model=tool_selector_model),
+        # Interpreter prompt must land before runtime/memory context, so this
+        # middleware sits ahead of runtime_context in the stack.
+        create_code_interpreter_middleware(
+            timeout=cfg.code_interpreter_timeout,
+            max_result_chars=cfg.code_interpreter_max_result_chars,
+        ),
        create_runtime_context_middleware(),
    ]
    if memory_controls.memory_enabled:
@@ -624,12 +676,6 @@ def _get_default_middleware(

        mw.append(BackgroundExecutionMiddleware())

-    mw.append(
-        create_code_interpreter_middleware(
-            timeout=cfg.code_interpreter_timeout,
-            max_result_chars=cfg.code_interpreter_max_result_chars,
-        )
-    )
    return mw


@@ -43,7 +43,7 @@ from .validators import validate_tavily_key


 def _step_ui_backend(config: EvoScientistConfig) -> str:
-    """Step 0: Select UI backend (Textual TUI, Rich CLI, or browser WebUI).
+    """Step 0: Select UI backend (desktop WebUI, Textual TUI, or Rich CLI).

    Args:
        config: Current configuration.
@@ -52,9 +52,9 @@ def _step_ui_backend(config: EvoScientistConfig) -> str:
        Selected backend name ("tui", "cli", or "webui").
    """
    choices = [
+        Choice(title="WebUI (desktop interface, beta)", value="webui"),
        Choice(title="TUI (full-screen interface, recommended)", value="tui"),
        Choice(title="CLI (classic terminal, lightweight)", value="cli"),
-        Choice(title="WebUI (browser interface, beta)", value="webui"),
    ]

    # Map legacy values to current ones
@@ -228,11 +228,20 @@ def _step_webui_port(config: EvoScientistConfig) -> int:
    return port


-def _step_provider(config: EvoScientistConfig) -> str:
+def _step_provider(
+    config: EvoScientistConfig,
+    *,
+    label: str | None = None,
+    default_value: str | None = None,
+) -> str:
    """Step 1: Select LLM provider.

    Args:
        config: Current configuration.
+        label: Optional role label (e.g. "co-pilot") to clarify which model this
+            provider is for. When omitted, the generic main-model prompt is used.
+        default_value: Preselect this provider instead of ``config.provider``
+            (e.g. the auxiliary provider when configuring the co-pilot).

    Returns:
        Selected provider name.
@@ -297,12 +306,13 @@ def _step_provider(config: EvoScientistConfig) -> str:
        ),
    ]

-    # Set default based on current config
+    # Set default based on current config (or an explicit override).
    valid_providers = {c.value for c in choices}
-    default = config.provider if config.provider in valid_providers else "anthropic"
+    preferred = default_value or config.provider
+    default = preferred if preferred in valid_providers else "anthropic"

    provider = questionary.select(
-        "Select your LLM provider:",
+        f"Select {label} provider:" if label else "Select your LLM provider:",
        choices=choices,
        default=default,
        style=WIZARD_STYLE,
@@ -671,6 +681,8 @@ def _step_model(
    provider: str,
    *,
    ollama_detected_models: list[str] | None = None,
+    label: str | None = None,
+    default_value: str | None = None,
 ) -> str:
    """Step 3: Select model for the provider.

@@ -678,10 +690,16 @@ def _step_model(
        config: Current configuration.
        provider: Selected provider name.
        ollama_detected_models: Model names detected from a live Ollama server.
+        label: Optional role label (e.g. "co-pilot") for the prompt. When omitted,
+            the generic main-model prompt is used.
+        default_value: Preselect this model instead of ``config.model`` (e.g. the
+            auxiliary model when configuring the co-pilot).

    Returns:
        Selected model name.
    """
+    model_prompt = f"Select {label} model:" if label else "Select model:"
+    model_default = default_value or config.model
    # Ollama: show only what's actually pulled on the server
    if provider == "ollama":
        if ollama_detected_models:
@@ -692,11 +710,11 @@ def _step_model(
            choices.append(Choice(title="Type a model name...", value=_CUSTOM_SENTINEL))

            default = ollama_detected_models[0]
-            if config.model in ollama_detected_models:
-                default = config.model
+            if model_default in ollama_detected_models:
+                default = model_default

            selected = questionary.select(
-                "Select model:",
+                model_prompt,
                choices=choices,
                default=default,
                style=WIZARD_STYLE,
@@ -742,7 +760,7 @@ def _step_model(
                style=WIZARD_STYLE,
                qmark=QMARK,
                placeholder=FormattedText([("fg:#858585", " e.g. owner/model-name")]),
-                default=config.model or "",
+                default=model_default or "",
            ).ask()
            if model is None:
                raise KeyboardInterrupt()
@@ -763,14 +781,23 @@ def _step_model(
        choices.append(Choice(title=f"{name} ({model_id})", value=name))
    choices.append(Choice(title="Type a model name...", value=_CUSTOM_SENTINEL))

-    # Determine default
-    if config.model in provider_models:
-        default = config.model
+    # Determine default. An explicit ``default_value`` override (e.g. a saved
+    # co-pilot model on a re-run) that isn't a registry model is a custom name:
+    # preselect "Type a model name..." and prefill it. A plain ``config.model``
+    # that just isn't in the current provider's list (e.g. the provider was
+    # changed) falls back to the first model, NOT the custom entry.
+    custom_default = (
+        default_value if default_value and default_value not in provider_models else ""
+    )
+    if model_default in provider_models:
+        default = model_default
+    elif custom_default:
+        default = _CUSTOM_SENTINEL
    else:
        default = provider_models[0]

    selected = questionary.select(
-        "Select model:",
+        model_prompt,
        choices=choices,
        default=default,
        style=WIZARD_STYLE,
@@ -786,6 +813,7 @@ def _step_model(

    model = questionary.text(
        "Model name:",
+        default=custom_default,
        style=WIZARD_STYLE,
        qmark=QMARK,
        placeholder=FormattedText([("fg:#858585", " e.g. owner/model-name")]),
@@ -799,6 +827,40 @@ def _step_model(
    return model


+def _step_auxiliary_enable(config: EvoScientistConfig) -> bool:
+    """Step 3.25: Choose whether to assemble a co-pilot (auxiliary) model.
+
+    The co-pilot runs background/helper LLM calls — EvoMemory (memory workers)
+    and the main agent's tool selector — so it can be a cheaper/faster model.
+    Returns True when the user picks "Assemble"; the caller then runs the
+    provider/key/model pickers. Returns False to keep the pilot (main model)
+    everywhere.
+    """
+    console.print(
+        "  [dim]A cheaper/faster co-pilot for EvoMemory (memory workers).[/dim]"
+    )
+    choice = questionary.select(
+        "Co-pilot (auxiliary model):",
+        choices=[
+            Choice(
+                title="Skip — single pilot (main model handles everything)",
+                value="skip",
+            ),
+            Choice(
+                title="Assemble a co-pilot — separate cheaper/faster model",
+                value="assemble",
+            ),
+        ],
+        default="assemble" if config.auxiliary_model else "skip",
+        style=WIZARD_STYLE,
+        qmark=QMARK,
+        use_indicator=True,
+    ).ask()
+    if choice is None:
+        raise KeyboardInterrupt()
+    return choice == "assemble"
+
+
 def _step_reasoning_effort(config: EvoScientistConfig) -> str:
    """Step 3.5: Configure OpenRouter reasoning effort level.

@@ -935,18 +997,23 @@ _RECOMMENDED_SKILLS = [
    },
    # ── Third-party (K-Dense) ──
    {
-        "label": "Scientific Skills  (147 research & experiment skills, third party by K-Dense)",
+        "label": "Scientific Skills  (143 research & experiment skills, third party by K-Dense)",
        "source": "K-Dense-AI/scientific-agent-skills@skills",
    },
    {
-        "label": "Scientific Writer  (23 writing, review & presentation skills, third party by K-Dense)",
+        "label": "Scientific Writer  (27 writing, review & presentation skills, third party by K-Dense)",
        "source": "K-Dense-AI/claude-scientific-writer@skills",
    },
    # ── Third-party (Orchestra Research) ──
    {
-        "label": "AI Research Skills  (85 skills for training, evaluation, deployment, etc., third party by Orchestra Research)",
+        "label": "AI Research Skills  (98 skills for training, evaluation, deployment, etc., third party by Orchestra Research)",
        "source": "Orchestra-Research/AI-Research-SKILLs",
    },
+    # ── Third-party (Google DeepMind) ──
+    {
+        "label": "Science Skills  (37 genomics, structural-biology & literature skills, third party by Google DeepMind)",
+        "source": "google-deepmind/science-skills@skills",
+    },
    # ── Third-party (Anthropic) ──
    {
        "label": "Anthropic Skills  (co-authoring, design, etc., third party by Anthropic)",
@@ -104,6 +104,21 @@ def _print_header() -> None:
    console.print()


+_SECTION_WIDTH = 53  # ~ the Setup Wizard panel width (not the full terminal)
+
+
+def _print_section(title: str) -> None:
+    """Print a compact bold-cyan section divider, e.g. ──── Pilot ────.
+
+    Sized to roughly the Setup Wizard panel width and styled like the section
+    markers used elsewhere in the CLI, rather than a full-width rule.
+    """
+    label = f" {title} "
+    pad = max(2, _SECTION_WIDTH - len(label))
+    left = pad // 2
+    console.print(f"[bold cyan]{'─' * left}{label}{'─' * (pad - left)}[/bold cyan]")
+
+
 def _print_step_result(step_name: str, value: str, success: bool = True) -> None:
    """Print a completed step result inline.

@@ -18,6 +18,7 @@ from ..settings import (
 from .channels import _step_channels
 from .steps import (
    _step_anthropic_auth_mode,
+    _step_auxiliary_enable,
    _step_base_url,
    _step_langgraph_dev_port,
    _step_mcp_servers,
@@ -40,6 +41,7 @@ from .style import (
    CONFIRM_STYLE,
    QMARK,
    _print_header,
+    _print_section,
    _print_step_skipped,
    console,
 )
@@ -50,6 +52,7 @@ STEPS = [
    "Provider",
    "API Key",
    "Model",
+    "Auxiliary Model",
    "Tavily Key",
    "Workspace",
    "Thinking",
@@ -145,6 +148,7 @@ _SECTION_LABELS: list[tuple[str, str]] = [
    ("port", "LangGraph server port"),
    ("provider", "LLM provider + auth + API key"),
    ("model", "Model + reasoning effort"),
+    ("auxiliary_model", "Auxiliary model (optional)"),
    ("tavily", "Tavily search key"),
    ("workspace", "Workspace mode"),
    ("thinking", "Thinking panel"),
@@ -453,6 +457,7 @@ def run_onboard(
            if "provider" in sections_to_run:
                from .prompter import GoBack

+                _print_section("EvoScientist · Pilot (Main model)")
                _require("provider", "LLM provider")
                # Provider sub-loop: auth_mode can raise GoBack to re-pick provider.
                # We snapshot config at the top of each iteration so a GoBack can
@@ -665,6 +670,63 @@ def run_onboard(
                    config.reasoning_effort = _step_reasoning_effort(config)
                _autosave(config)

+            if "auxiliary_model" in sections_to_run:
+                _print_section("Co-pilot (Auxiliary model)")
+                if strict:
+                    # Optional; never prompt under --non-interactive. Keep
+                    # current (default empty = use main model).
+                    _print_step_skipped(
+                        "Auxiliary Model",
+                        "kept current" if config.auxiliary_model else "not set",
+                    )
+                elif _step_auxiliary_enable(config):
+                    # Assemble: pick provider -> base URL (custom) -> key -> model,
+                    # mirroring the main flow's order. Keys/base URLs are stored
+                    # per provider, so when the auxiliary provider matches the main
+                    # one they're already set and the user just keeps them (Enter).
+                    # Ollama needs no key. Re-runs default to the saved auxiliary
+                    # provider/model rather than the main ones.
+                    aux_provider = _step_provider(
+                        config,
+                        label="co-pilot",
+                        default_value=config.auxiliary_provider,
+                    )
+                    config.auxiliary_provider = aux_provider
+                    if aux_provider == "custom-openai":
+                        config.custom_openai_base_url = _step_base_url(
+                            config,
+                            current_value=config.custom_openai_base_url
+                            or os.environ.get("CUSTOM_OPENAI_BASE_URL", ""),
+                        )
+                    elif aux_provider == "custom-anthropic":
+                        config.custom_anthropic_base_url = _step_base_url(
+                            config,
+                            current_value=config.custom_anthropic_base_url
+                            or os.environ.get("CUSTOM_ANTHROPIC_BASE_URL", ""),
+                        )
+                    elif aux_provider == "minimax":
+                        config.minimax_base_url = _step_minimax_region(config)
+                    if aux_provider != "ollama":
+                        aux_key_attr = _PROVIDER_KEY_ATTR.get(
+                            aux_provider, "openai_api_key"
+                        )
+                        new_aux_key = _step_provider_api_key(
+                            config, aux_provider, skip_validation
+                        )
+                        if new_aux_key is not None:
+                            setattr(config, aux_key_attr, new_aux_key)
+                    config.auxiliary_model = _step_model(
+                        config,
+                        aux_provider,
+                        label="co-pilot",
+                        default_value=config.auxiliary_model,
+                    )
+                else:
+                    # Skip: single driver — clear any prior auxiliary config.
+                    config.auxiliary_provider = ""
+                    config.auxiliary_model = ""
+                _autosave(config)
+
            if "tavily" in sections_to_run:
                preset_tavily = _preset("tavily_key")
                if preset_tavily is not None:
@@ -95,6 +95,8 @@ class EvoScientistConfig:
        tavily_api_key: Tavily API key for web search.
        provider: Default LLM provider ('anthropic', 'openai', 'google-genai', or 'nvidia').
        model: Default model name (short name or full ID).
+        auxiliary_provider: Provider for auxiliary_model (empty = use main provider).
+        auxiliary_model: Model for memory workers + tool selector (empty = use main model).
        default_mode: Default workspace mode ('daemon' or 'run').
        default_workdir: Default workspace directory (empty = use current working directory).
        show_thinking: Whether to show thinking panels in CLI.
@@ -129,6 +131,10 @@ class EvoScientistConfig:
    provider: str = "anthropic"
    model: str = "claude-sonnet-4-6"
    model_fallbacks: str = ""  # "model:provider,model:provider" fallback chain
+    # Optional auxiliary model for background/helper LLM calls (memory workers +
+    # tool selector). Empty = fall back to the main model/provider.
+    auxiliary_provider: str = ""  # empty = use main provider
+    auxiliary_model: str = ""  # empty = use main model

    # Async Sub-agent Settings
    # When True (default), the EvoSci CLI auto-starts a langgraph dev subprocess
@@ -622,6 +628,8 @@ _ENV_MAPPINGS = {
    "ui_backend": "EVOSCIENTIST_UI_BACKEND",
    "log_level": "EVOSCIENTIST_LOG_LEVEL",
    "model_fallbacks": "EVOSCIENTIST_MODEL_FALLBACKS",
+    "auxiliary_provider": "EVOSCIENTIST_AUXILIARY_PROVIDER",
+    "auxiliary_model": "EVOSCIENTIST_AUXILIARY_MODEL",
    "reasoning_effort": "EVOSCIENTIST_REASONING_EFFORT",
    "channel_debug_tracing": "EVOSCIENTIST_CHANNEL_DEBUG_TRACING",
    "ccproxy_port": "EVOSCIENTIST_CCPROXY_PORT",
@@ -17,8 +17,9 @@ _KNOWN_MODEL_CONTEXT_WINDOWS: dict[str, int] = {
    # Qwen 3.6 open-source variants — exceptions to the ``qwen3.6`` family.
    "qwen3.6-27b": 262_000,
    "qwen3.6-35b-a3b": 262_000,
-    # Qwen 3.7 Max — closed-source flagship (1M).
+    # Qwen 3.7 closed-source tiers — Max flagship and Plus (1M).
    "qwen3.7-max": 1_000_000,
+    "qwen3.7-plus": 1_000_000,
    # xAI Grok — per-model windows (build-0.1: 256K, 4.3: 1M).
    "grok-build-0.1": 256_000,
    "grok-4.3": 1_000_000,
@@ -20,6 +20,7 @@ from .patches import (
    _patch_ccproxy_system_to_developer,
    _patch_deepseek_reasoning_passback,
    _patch_openai_compat_content,
+    _patch_openrouter_strip_responses_reasoning,
 )

 _MINIMAX_ANTHROPIC_BASE_URL = "https://api.minimaxi.com/anthropic"
@@ -149,6 +150,7 @@ _MODEL_ENTRIES: list[tuple[str, str, str]] = [
    ("grok-build-0.1", "x-ai/grok-build-0.1", "openrouter"),
    ("grok-4.3", "x-ai/grok-4.3", "openrouter"),
    ("qwen3.7-max", "qwen/qwen3.7-max", "openrouter"),
+    ("qwen3.7-plus", "qwen/qwen3.7-plus", "openrouter"),
    ("qwen3.6-flash", "qwen/qwen3.6-flash", "openrouter"),
    ("qwen3.5-122b", "qwen/qwen3.5-122b-a10b", "openrouter"),
    ("deepseek-v4-pro", "deepseek/deepseek-v4-pro", "openrouter"),
@@ -174,11 +176,21 @@ _MODEL_ENTRIES: list[tuple[str, str, str]] = [
    ("doubao-1.5-pro", "doubao-1.5-pro-256k", "volcengine"),
    ("doubao-1.5-thinking-pro", "doubao-1.5-thinking-pro", "volcengine"),
    # DashScope Coding Plan (阿里云代码计划 — subscription sk-sp-* endpoint)
+    ("qwen3.7-max", "qwen3.7-max", "dashscope-code"),
+    ("qwen3.7-plus", "qwen3.7-plus", "dashscope-code"),
+    ("qwen3.6-max", "qwen3.6-max-preview", "dashscope-code"),
+    ("qwen3.6-plus", "qwen3.6-plus", "dashscope-code"),
+    ("qwen3.6-flash", "qwen3.6-flash", "dashscope-code"),
    ("qwen3-coder", "qwen3-coder-plus", "dashscope-code"),
    ("qwen3-coder-next", "qwen3-coder-next", "dashscope-code"),
    ("qwen3-max", "qwen3-max", "dashscope-code"),
    ("qwen3.5-plus", "qwen3.5-plus", "dashscope-code"),
    # DashScope (阿里云 — Qwen models, default for simple lookups)
+    ("qwen3.7-max", "qwen3.7-max", "dashscope"),
+    ("qwen3.7-plus", "qwen3.7-plus", "dashscope"),
+    ("qwen3.6-max", "qwen3.6-max-preview", "dashscope"),
+    ("qwen3.6-plus", "qwen3.6-plus", "dashscope"),
+    ("qwen3.6-flash", "qwen3.6-flash", "dashscope"),
    ("qwen3-coder", "qwen3-coder-plus", "dashscope"),
    ("qwen3-235b", "qwen3-235b-a22b", "dashscope"),
    ("qwen-max", "qwen-max", "dashscope"),
@@ -403,9 +415,15 @@ def get_chat_model(
        api_key = os.environ.get("OPENROUTER_API_KEY", "")
        if api_key:
            kwargs["api_key"] = api_key
-        # Enable reasoning; disable summary to avoid multi-turn schema errors.
+        # Reasoning via `effort` + `summary: "auto"` so a readable reasoning
+        # summary is returned for display. OpenAI-Responses also emits encrypted
+        # reasoning items (`rs_*` id) that can't be replayed on multi-turn
+        # passback (OpenRouter's `/responses` beta is stateless, store=false —
+        # "Item with id 'rs_...' not found"); the patch strips them on passback,
+        # so enabling `summary` is safe. See langchain-ai/langchain#37777.
        effort = os.environ.get("EVOSCIENTIST_REASONING_EFFORT", "").strip() or "high"
-        kwargs.setdefault("reasoning", {"effort": effort, "summary": "disabled"})
+        kwargs.setdefault("reasoning", {"effort": effort, "summary": "auto"})
+        _patch_openrouter_strip_responses_reasoning()

    # Anthropic-routed providers → route through Anthropic provider with base_url
    elif provider in _ANTHROPIC_ROUTED_PROVIDERS:
@@ -14,6 +14,9 @@ Patches:
    - _patch_deepseek_reasoning_passback: re-inject reasoning_content into
      outgoing DeepSeek assistant messages for thinking-mode multi-turn /
      tool_use scenarios
+    - _patch_openrouter_strip_responses_reasoning: drop OpenAI-Responses
+      encrypted reasoning items (rs_* id) from outgoing OpenRouter messages
+      (store=false → "Item with id rs_... not found")

 Utilities:
    - _is_ccproxy_codex: detect ccproxy Codex OAuth adapter
@@ -726,6 +729,60 @@ def _patch_openai_capture_reasoning_content() -> None:
 _patch_openai_capture_reasoning_content()


+# ---------------------------------------------------------------------------
+# Patch (lazy, OpenRouter only): strip OpenAI-Responses encrypted reasoning
+# items from outgoing assistant messages.
+#
+# OpenRouter's `/responses` beta is stateless — it does not propagate
+# `store=true` / `previous_response_id` upstream. So when a prior turn's
+# assistant message carries a reasoning item with an `rs_*` id (the encrypted
+# Responses reasoning block), replaying it on the next turn fails with HTTP 400:
+#   "Item with id 'rs_...' not found. Items are not persisted when `store` is
+#    set to false. ... remove this item from your input."
+# (observed against both Azure and OpenAI upstreams — so deepagents'
+# azure-ignore is not sufficient). The only robust fix is to drop these items
+# on passback, exactly as the upstream error instructs. Reasoning DISPLAY is
+# unaffected: it happens when the item is generated, not on passback.
+# Related: langchain-ai/langchain#37777.
+# ---------------------------------------------------------------------------
+_openrouter_reasoning_strip_patched = False
+
+
+def _is_responses_reasoning_item(entry: Any) -> bool:
+    """True for an OpenAI-Responses encrypted reasoning item (`rs_` id / data)."""
+    if not isinstance(entry, dict):
+        return False
+    return str(entry.get("id") or "").startswith("rs_") or bool(entry.get("data"))
+
+
+def _patch_openrouter_strip_responses_reasoning() -> None:
+    global _openrouter_reasoning_strip_patched
+    if _openrouter_reasoning_strip_patched:
+        return
+    try:
+        import langchain_openrouter.chat_models as _mod
+
+        _orig = _mod._convert_message_to_dict
+
+        def _patched(message: Any) -> Any:
+            result = _orig(message)
+            details = (
+                result.get("reasoning_details") if isinstance(result, dict) else None
+            )
+            if isinstance(details, list):
+                kept = [e for e in details if not _is_responses_reasoning_item(e)]
+                if kept:
+                    result["reasoning_details"] = kept
+                else:
+                    result.pop("reasoning_details", None)
+            return result
+
+        _mod._convert_message_to_dict = _patched
+        _openrouter_reasoning_strip_patched = True
+    except Exception:
+        pass
+
+
 # ---------------------------------------------------------------------------
 # Patch: DeepSeek thinking mode requires reasoning_content to be passed back
 # in all assistant messages for multi-turn + tool_use scenarios.
@@ -706,11 +706,13 @@ def _build_memory_worker_agent(
    """Create a background memory worker agent for one lifecycle hook."""
    from deepagents import create_deep_agent

-    from ..EvoScientist import _ensure_chat_model
+    from ..EvoScientist import _ensure_auxiliary_chat_model

    agent = create_deep_agent(
        name=role.worker_agent_name,
-        model=_ensure_chat_model(),
+        # Memory workers are background helper agents — use the auxiliary model
+        # (falls back to the main model when auxiliary_* is unset).
+        model=_ensure_auxiliary_chat_model(),
        system_prompt=system_prompt,
        tools=[],
        backend=_build_memory_worker_backend(
@@ -10,7 +10,7 @@
 <a href="https://pypi.org/project/EvoScientist/"><picture>
  <source media="(prefers-color-scheme: light)" srcset="https://raw.githubusercontent.com/EvoScientist/EvoScientist/main/.github/assets/badge-pypi-light.svg">
  <source media="(prefers-color-scheme: dark)" srcset="https://raw.githubusercontent.com/EvoScientist/EvoScientist/main/.github/assets/badge-pypi-dark.svg">
-  <img alt="PyPI v0.1.3" src="https://raw.githubusercontent.com/EvoScientist/EvoScientist/main/.github/assets/badge-pypi-light.svg" height="28">
+  <img alt="PyPI v0.1.4" src="https://raw.githubusercontent.com/EvoScientist/EvoScientist/main/.github/assets/badge-pypi-light.svg" height="28">
 </picture></a><a href="https://EvoScientist.github.io/"><picture>
  <source media="(prefers-color-scheme: light)" srcset="https://raw.githubusercontent.com/EvoScientist/EvoScientist/main/.github/assets/badge-website-light.svg">
  <source media="(prefers-color-scheme: dark)" srcset="https://raw.githubusercontent.com/EvoScientist/EvoScientist/main/.github/assets/badge-website-dark.svg">
@@ -109,7 +109,7 @@ Moving beyond traditional human-in-the-loop systems, EvoScientist adopts a human

 ## ✨ Features
 - **🤖 Multi-Agent Team** — 6 sub-agents (plan, research, code, debug, analyze, write) working in concert.
- **🧠 Persistent Memory** — Context, preferences, and findings survive across sessions.
+- **🧠 Self-Evolving Memory** — User profile and observations auto-distilled each turn, growing across sessions.
 - **🌐 Multi-Provider** — Anthropic, OpenAI, Google, MiniMax, NVIDIA — one config to switch.
 - **📱 Multi-Channel** — CLI as the hub; Telegram, Slack, Feishu, WeChat, and more — one agent session.
 - **🖥️ Browser WebUI (beta)** — Workspace-panel web app, one terminal via `--ui webui`.
@@ -136,6 +136,7 @@ Moving beyond traditional human-in-the-loop systems, EvoScientist adopts a human
 <details>
 <summary>📦 Release Highlights — version changelog</summary>

+- **[07 Jun 2026]** **[v0.1.4](https://github.com/EvoScientist/EvoScientist/releases/tag/v0.1.4)** — Auxiliary model for background tasks & tool selection, observation-memory lifecycle, Qwen3.7-Max/Plus (DashScope), UI-backend selection, plus an OpenRouter multi-turn reasoning fix.
 - **[03 Jun 2026]** **[v0.1.3](https://github.com/EvoScientist/EvoScientist/releases/tag/v0.1.3)** — Multimodal handling (image + PDF/doc flatten/hoisting, text-only model fallback), runtime-context middleware, memory middleware → profile files with stream timeline narration, textual CJK-input fix.
 - **[02 Jun 2026]** **[v0.1.2](https://github.com/EvoScientist/EvoScientist/releases/tag/v0.1.2)** — Browser WebUI mode (beta), `EvoSci deploy` standalone LangGraph server, default model → claude-sonnet-4-6, MiniMax M3, plus sandbox-timeout and async-notifier channel-routing fixes.
 - **[19 May 2026]** **[v0.1.1](https://github.com/EvoScientist/EvoScientist/releases/tag/v0.1.1)** — deepagents 0.6.2 DeltaChannel upgrade, tier-aware skill mounts, status & elapsed-time bar, QQ inline buttons.
@@ -15,7 +15,7 @@
 <a href="https://pypi.org/project/EvoScientist/"><picture>
  <source media="(prefers-color-scheme: light)" srcset="https://raw.githubusercontent.com/EvoScientist/EvoScientist/main/.github/assets/badge-pypi-light.svg">
  <source media="(prefers-color-scheme: dark)" srcset="https://raw.githubusercontent.com/EvoScientist/EvoScientist/main/.github/assets/badge-pypi-dark.svg">
-  <img alt="PyPI v0.1.3" src="https://raw.githubusercontent.com/EvoScientist/EvoScientist/main/.github/assets/badge-pypi-light.svg" height="28">
+  <img alt="PyPI v0.1.4" src="https://raw.githubusercontent.com/EvoScientist/EvoScientist/main/.github/assets/badge-pypi-light.svg" height="28">
 </picture></a><a href="https://EvoScientist.github.io/"><picture>
  <source media="(prefers-color-scheme: light)" srcset="https://raw.githubusercontent.com/EvoScientist/EvoScientist/main/.github/assets/badge-website-light.svg">
  <source media="(prefers-color-scheme: dark)" srcset="https://raw.githubusercontent.com/EvoScientist/EvoScientist/main/.github/assets/badge-website-dark.svg">
@@ -117,7 +117,7 @@ EvoScientist 超越了传统的人在回路（Human-in-the-Loop）模式，采
 ## ✨ 特性

 - **🤖 多智能体协作** — 6 个子智能体（规划、调研、编码、调试、分析、写作）协同工作。
- **🧠 持久化记忆** — 上下文、偏好和研究发现跨会话保持。
+- **🧠 自进化记忆** — 用户画像与观察记录每轮自动提炼，跨会话持续进化。
 - **🌐 多模型供应商** — Anthropic、OpenAI、Google、MiniMax、NVIDIA——一处配置，随时切换。
 - **📱 多渠道接入** — CLI 为中心；Telegram、Slack、飞书、微信等——共享同一智能体会话。
 - **🖥️ 浏览器 WebUI（beta）** — 单终端 `--ui webui` 启动带工作区面板的 Web 应用。
@@ -145,6 +145,7 @@ EvoScientist 超越了传统的人在回路（Human-in-the-Loop）模式，采
 <details>
 <summary>📦 版本更新摘要（changelog）</summary>

+- **[2026 年 6 月 7 日]** **[v0.1.4](https://github.com/EvoScientist/EvoScientist/releases/tag/v0.1.4)** — 辅助模型（后台任务与工具选择）、observation 记忆生命周期、Qwen3.7-Max/Plus（DashScope）、UI 后端选择，以及 OpenRouter 多轮推理修复。
 - **[2026 年 6 月 3 日]** **[v0.1.3](https://github.com/EvoScientist/EvoScientist/releases/tag/v0.1.3)** — 多模态处理（图片 + PDF/文档 flatten/hoisting、纯文本模型回退）、runtime-context 中间件、memory 中间件迁移至 profile 文件 + stream 时间线叙述、textual 中文输入修复。
 - **[2026 年 6 月 2 日]** **[v0.1.2](https://github.com/EvoScientist/EvoScientist/releases/tag/v0.1.2)** — 浏览器 WebUI 模式（beta）、`EvoSci deploy` 独立 LangGraph 服务器、默认模型 → claude-sonnet-4-6、MiniMax M3，以及 sandbox 超时与 async-notifier 渠道路由修复。
 - **[2026 年 5 月 19 日]** **[v0.1.1](https://github.com/EvoScientist/EvoScientist/releases/tag/v0.1.1)** — deepagents 0.6.2 DeltaChannel 升级、tier-aware skill mounts、状态/耗时栏、QQ 内联按钮。
@@ -1,6 +1,6 @@
 [project]
 name = "EvoScientist"
-version = "0.1.3"
+version = "0.1.4"
 description = "EvoScientist: Towards Self-Evolving AI Scientists for End-to-End Scientific Discovery"
 readme = "README.md"
 requires-python = ">=3.11"
@@ -16,7 +16,7 @@ classifiers = [
    "Programming Language :: Python :: 3",
 ]
 dependencies = [
-    "deepagents[quickjs]~=0.6.7",
+    "deepagents[quickjs]~=0.6.8",
    "langchain>=1.3",
    "langchain-anthropic>=1.4",
    "langchain-openai>=1.2",
@@ -411,6 +411,8 @@ def test_auto_approve_still_includes_ask_user_middleware(
    cfg.enable_ask_user = True
    cfg.auto_approve = True
    cfg.auto_mode = False
+    cfg.auxiliary_model = ""
+    cfg.auxiliary_provider = ""
    mock_config.return_value = cfg
    mock_model.return_value = MagicMock(profile={"max_input_tokens": 200_000})

@@ -430,6 +432,8 @@ def test_auto_mode_disables_ask_user_middleware(
    cfg.enable_ask_user = True
    cfg.auto_approve = True
    cfg.auto_mode = True
+    cfg.auxiliary_model = ""
+    cfg.auxiliary_provider = ""
    mock_config.return_value = cfg
    mock_model.return_value = MagicMock(profile={"max_input_tokens": 200_000})

@@ -458,6 +462,8 @@ def test_for_async_subagent_omits_ask_user_middleware(
    cfg.enable_ask_user = True
    cfg.auto_approve = False
    cfg.auto_mode = False
+    cfg.auxiliary_model = ""
+    cfg.auxiliary_provider = ""
    mock_config.return_value = cfg
    mock_model.return_value = MagicMock(profile={"max_input_tokens": 200_000})

@@ -125,6 +125,8 @@ def test_inject_subagent_omits_memory_middleware_when_memory_disabled(
    cfg.memory_observations_enabled = False
    cfg.memory_observation_writer = MemoryObservationWriter.ALL
    cfg.memory_workers_enabled = True
+    cfg.auxiliary_model = ""
+    cfg.auxiliary_provider = ""
    mock_config.return_value = cfg

    from EvoScientist.EvoScientist import _inject_subagent_middleware
@@ -153,6 +155,8 @@ def test_inject_subagent_worker_only_observation_writer_keeps_live_tool_off(
    cfg.memory_observations_enabled = True
    cfg.memory_observation_writer = MemoryObservationWriter.WORKER
    cfg.memory_workers_enabled = True
+    cfg.auxiliary_model = ""
+    cfg.auxiliary_provider = ""
    mock_config.return_value = cfg

    from EvoScientist.EvoScientist import _inject_subagent_middleware
@@ -191,6 +195,8 @@ def test_all_observation_writer_skips_turn_worker_without_profile_memory(
    cfg.memory_observations_enabled = True
    cfg.memory_observation_writer = MemoryObservationWriter.ALL
    cfg.memory_workers_enabled = True
+    cfg.auxiliary_model = ""
+    cfg.auxiliary_provider = ""
    mock_config.return_value = cfg
    mock_chat.return_value = MagicMock(profile={"max_input_tokens": 200_000})

@@ -259,6 +265,8 @@ def test_async_subagent_mode_filters_ask_user(
    cfg.memory_observations_enabled = True
    cfg.memory_observation_writer = MemoryObservationWriter.ALL
    cfg.memory_workers_enabled = True
+    cfg.auxiliary_model = ""
+    cfg.auxiliary_provider = ""
    mock_config.return_value = cfg
    mock_chat.return_value = MagicMock(profile={"max_input_tokens": 200_000})

@@ -0,0 +1,159 @@
+"""Tests for the auxiliary-model resolver and its middleware scoping.
+
+Covers ``EvoScientist.EvoScientist._ensure_auxiliary_chat_model`` (fallback to
+the main model when unset) and the wiring in ``_get_default_middleware`` that
+routes the main agent's tool selector to the auxiliary model while keeping
+context editing — and async sub-agents — on the main model.
+"""
+
+from types import SimpleNamespace
+from unittest.mock import MagicMock, patch
+
+import pytest
+
+import EvoScientist.EvoScientist as E
+
+
+@pytest.fixture(autouse=True)
+def _reset_model_caches(monkeypatch):
+    """Isolate the module-level model caches per test."""
+    monkeypatch.setattr(E, "_chat_model", None, raising=False)
+    monkeypatch.setattr(E, "_chat_model_key", None, raising=False)
+    monkeypatch.setattr(E, "_auxiliary_chat_model", None, raising=False)
+    monkeypatch.setattr(E, "_auxiliary_chat_model_key", None, raising=False)
+
+
+def _cfg(**over):
+    base = {
+        "model": "main-m",
+        "provider": "main-p",
+        "auxiliary_model": "",
+        "auxiliary_provider": "",
+    }
+    base.update(over)
+    return SimpleNamespace(**base)
+
+
+class TestAuxiliaryResolver:
+    def test_empty_returns_main_instance(self, monkeypatch):
+        main = object()
+        monkeypatch.setattr(E, "_ensure_config", lambda config=None: _cfg())
+        monkeypatch.setattr(E, "_ensure_chat_model", lambda: main)
+        assert E._ensure_auxiliary_chat_model() is main
+
+    def test_aux_equal_to_main_reuses_main_instance(self, monkeypatch):
+        main = object()
+        monkeypatch.setattr(
+            E,
+            "_ensure_config",
+            lambda config=None: _cfg(
+                auxiliary_model="main-m", auxiliary_provider="main-p"
+            ),
+        )
+        monkeypatch.setattr(E, "_ensure_chat_model", lambda: main)
+        assert E._ensure_auxiliary_chat_model() is main
+
+    def test_set_builds_auxiliary(self, monkeypatch):
+        fake = object()
+        get_chat_model = MagicMock(return_value=fake)
+        monkeypatch.setattr(
+            E,
+            "_ensure_config",
+            lambda config=None: _cfg(
+                auxiliary_model="aux-m", auxiliary_provider="aux-p"
+            ),
+        )
+        monkeypatch.setattr("EvoScientist.llm.get_chat_model", get_chat_model)
+        assert E._ensure_auxiliary_chat_model() is fake
+        get_chat_model.assert_called_once_with(model="aux-m", provider="aux-p")
+
+    def test_empty_provider_falls_back_to_main_provider(self, monkeypatch):
+        get_chat_model = MagicMock(return_value=object())
+        monkeypatch.setattr(
+            E,
+            "_ensure_config",
+            lambda config=None: _cfg(auxiliary_model="aux-m", auxiliary_provider=""),
+        )
+        monkeypatch.setattr("EvoScientist.llm.get_chat_model", get_chat_model)
+        E._ensure_auxiliary_chat_model()
+        get_chat_model.assert_called_once_with(model="aux-m", provider="main-p")
+
+    def test_set_chat_model_resets_aux_cache(self, monkeypatch):
+        monkeypatch.setattr(E, "_auxiliary_chat_model", object(), raising=False)
+        monkeypatch.setattr(E, "_auxiliary_chat_model_key", ("x", "y"), raising=False)
+        monkeypatch.setattr(
+            "EvoScientist.llm.get_chat_model", MagicMock(return_value=object())
+        )
+        E.set_chat_model("new-m", "new-p")
+        assert E._auxiliary_chat_model is None
+        assert E._auxiliary_chat_model_key is None
+
+
+def _mock_cfg():
+    cfg = MagicMock()
+    cfg.enable_ask_user = False
+    cfg.auto_mode = False
+    cfg.auto_approve = False
+    cfg.model_fallbacks = None
+    cfg.auxiliary_model = ""
+    cfg.auxiliary_provider = ""
+    return cfg
+
+
+class TestAuxiliaryMiddlewareScope:
+    """``_get_default_middleware`` routes only the right components to aux."""
+
+    def _capture(self):
+        cap: dict[str, object] = {}
+
+        def fake_tool_selector(*args, model=None, **kwargs):
+            cap["tool_selector"] = model
+            return [MagicMock()]
+
+        def fake_context_editing(model=None, *args, **kwargs):
+            cap["context_editing"] = model
+            return MagicMock()
+
+        return cap, fake_tool_selector, fake_context_editing
+
+    def test_main_agent_tool_selector_aux_context_editing_main(self):
+        cap, fake_ts, fake_ce = self._capture()
+        main_model, aux_model = object(), object()
+        with (
+            patch.object(E, "_ensure_config", return_value=_mock_cfg()),
+            patch.object(E, "_ensure_chat_model", return_value=main_model),
+            patch.object(E, "_ensure_auxiliary_chat_model", return_value=aux_model),
+            patch(
+                "EvoScientist.middleware.create_tool_selector_middleware",
+                side_effect=fake_ts,
+            ),
+            patch(
+                "EvoScientist.middleware.create_context_editing_middleware",
+                side_effect=fake_ce,
+            ),
+        ):
+            E._get_default_middleware()
+
+        assert cap["tool_selector"] is aux_model
+        assert cap["context_editing"] is main_model
+
+    def test_async_subagent_tool_selector_stays_main(self):
+        cap, fake_ts, fake_ce = self._capture()
+        main_model, aux_model = object(), object()
+        with (
+            patch.object(E, "_ensure_config", return_value=_mock_cfg()),
+            patch.object(E, "_ensure_chat_model", return_value=main_model),
+            patch.object(E, "_ensure_auxiliary_chat_model", return_value=aux_model),
+            patch(
+                "EvoScientist.middleware.create_tool_selector_middleware",
+                side_effect=fake_ts,
+            ),
+            patch(
+                "EvoScientist.middleware.create_context_editing_middleware",
+                side_effect=fake_ce,
+            ),
+        ):
+            E._get_default_middleware(for_async_subagent=True)
+
+        assert cap["tool_selector"] is main_model
+        assert cap["context_editing"] is main_model
@@ -50,6 +50,8 @@ def temp_config_dir(tmp_path, monkeypatch):
        "EVOSCIENTIST_MEMORY_OBSERVATIONS_ENABLED",
        "EVOSCIENTIST_MEMORY_OBSERVATION_WRITER",
        "EVOSCIENTIST_MEMORY_WORKERS_ENABLED",
+        "EVOSCIENTIST_AUXILIARY_MODEL",
+        "EVOSCIENTIST_AUXILIARY_PROVIDER",
    ]:
        monkeypatch.delenv(key, raising=False)
    return config_dir
@@ -69,6 +71,8 @@ def clean_env(monkeypatch):
        "EVOSCIENTIST_MEMORY_OBSERVATIONS_ENABLED",
        "EVOSCIENTIST_MEMORY_OBSERVATION_WRITER",
        "EVOSCIENTIST_MEMORY_WORKERS_ENABLED",
+        "EVOSCIENTIST_AUXILIARY_MODEL",
+        "EVOSCIENTIST_AUXILIARY_PROVIDER",
    ]:
        monkeypatch.delenv(key, raising=False)

@@ -590,3 +594,39 @@ class TestApplyConfigToEnv:
        apply_config_to_env(config)

        assert os.environ.get("OLLAMA_BASE_URL") == "http://existing:11434"
+
+
+class TestAuxiliaryModelConfig:
+    """auxiliary_model / auxiliary_provider config fields (plain str, optional)."""
+
+    def test_defaults_empty(self):
+        cfg = EvoScientistConfig()
+        assert cfg.auxiliary_model == ""
+        assert cfg.auxiliary_provider == ""
+
+    def test_save_and_load_round_trip(self, temp_config_dir, clean_env):
+        save_config(
+            EvoScientistConfig(
+                auxiliary_model="claude-haiku-4-5",
+                auxiliary_provider="anthropic",
+            )
+        )
+        loaded = load_config()
+        assert loaded.auxiliary_model == "claude-haiku-4-5"
+        assert loaded.auxiliary_provider == "anthropic"
+
+    def test_get_set_value(self, temp_config_dir, clean_env):
+        save_config(EvoScientistConfig())
+        assert set_config_value("auxiliary_model", "qwen3.6-flash") is True
+        assert set_config_value("auxiliary_provider", "dashscope") is True
+        assert get_config_value("auxiliary_model") == "qwen3.6-flash"
+        assert get_config_value("auxiliary_provider") == "dashscope"
+
+    def test_env_overrides_file(self, temp_config_dir, monkeypatch):
+        save_config(EvoScientistConfig(auxiliary_model="claude-haiku-4-5"))
+        monkeypatch.setenv("EVOSCIENTIST_AUXILIARY_MODEL", "gpt-5.5")
+        monkeypatch.setenv("EVOSCIENTIST_AUXILIARY_PROVIDER", "openai")
+
+        config = get_effective_config()
+        assert config.auxiliary_model == "gpt-5.5"
+        assert config.auxiliary_provider == "openai"
@@ -114,6 +114,8 @@ def test_default_middleware_includes_context_editing(mock_config, mock_model, mo
    cfg = MagicMock()
    cfg.enable_ask_user = False
    cfg.auto_approve = False
+    cfg.auxiliary_model = ""
+    cfg.auxiliary_provider = ""
    mock_config.return_value = cfg

    from EvoScientist.EvoScientist import _get_default_middleware
@@ -148,6 +150,8 @@ def test_context_editing_before_overflow_mapper(mock_config, mock_model, mock_ts
    cfg = MagicMock()
    cfg.enable_ask_user = False
    cfg.auto_approve = False
+    cfg.auxiliary_model = ""
+    cfg.auxiliary_provider = ""
    mock_config.return_value = cfg

    from EvoScientist.EvoScientist import _get_default_middleware
@@ -402,13 +402,15 @@ class TestThirdPartyRouting:
        """OpenRouter should use native 'openrouter' provider via init_chat_model."""
        mock_init.return_value = "mock_model"
        monkeypatch.setenv("OPENROUTER_API_KEY", "or-key-456")
+        # Assert the DEFAULT effort, so isolate from any leaked env override.
+        monkeypatch.delenv("EVOSCIENTIST_REASONING_EFFORT", raising=False)

        get_chat_model("x-ai/grok-4.3", provider="openrouter")

        call_kwargs = mock_init.call_args[1]
        assert call_kwargs["model_provider"] == "openrouter"
        assert call_kwargs["api_key"] == "or-key-456"
-        assert call_kwargs["reasoning"] == {"effort": "high", "summary": "disabled"}
+        assert call_kwargs["reasoning"] == {"effort": "high", "summary": "auto"}

    @patch("EvoScientist.llm.models.init_chat_model")
    def test_openrouter_reasoning_user_override(self, mock_init, monkeypatch):
@@ -435,7 +437,7 @@ class TestThirdPartyRouting:
        get_chat_model("x-ai/grok-4.3", provider="openrouter")

        call_kwargs = mock_init.call_args[1]
-        assert call_kwargs["reasoning"] == {"effort": "medium", "summary": "disabled"}
+        assert call_kwargs["reasoning"] == {"effort": "medium", "summary": "auto"}

    @patch("EvoScientist.llm.models.init_chat_model")
    def test_custom_routes_through_openai(self, mock_init, monkeypatch):
@@ -1994,6 +1996,142 @@ class TestPatchOpenAICaptureReasoningContent:
        assert msg.additional_kwargs.get("reasoning_content") == "use the tool"


+class TestIsResponsesReasoningItem:
+    """_is_responses_reasoning_item flags encrypted OpenAI-Responses items."""
+
+    def test_rs_id_is_responses_item(self):
+        from EvoScientist.llm.patches import _is_responses_reasoning_item
+
+        assert _is_responses_reasoning_item({"id": "rs_09363d42", "type": "x"})
+
+    def test_encrypted_data_is_responses_item(self):
+        from EvoScientist.llm.patches import _is_responses_reasoning_item
+
+        assert _is_responses_reasoning_item({"data": "gAAAAAB...", "type": "x"})
+
+    def test_plain_text_reasoning_is_not_responses_item(self):
+        from EvoScientist.llm.patches import _is_responses_reasoning_item
+
+        assert not _is_responses_reasoning_item(
+            {"type": "reasoning.text", "text": "thinking", "index": 0}
+        )
+        assert not _is_responses_reasoning_item("not a dict")
+
+
+class TestPatchOpenrouterStripResponsesReasoning:
+    """OpenAI-Responses encrypted reasoning items (`rs_` id / encrypted data)
+    are stripped from outgoing OpenRouter assistant messages, preventing the
+    multi-turn "Item with id 'rs_...' not found" 400 (store=false; #37777).
+    """
+
+    def _apply(self):
+        import langchain_openrouter.chat_models as mod
+
+        import EvoScientist.llm.patches as patches
+
+        orig = mod._convert_message_to_dict
+        orig_flag = patches._openrouter_reasoning_strip_patched
+        patches._openrouter_reasoning_strip_patched = False
+        patches._patch_openrouter_strip_responses_reasoning()
+        return patches, mod, orig, orig_flag
+
+    @staticmethod
+    def _restore(patches, mod, orig, orig_flag):
+        mod._convert_message_to_dict = orig
+        patches._openrouter_reasoning_strip_patched = orig_flag
+
+    def test_strips_encrypted_item_drops_key_when_empty(self):
+        from langchain_core.messages import AIMessage
+
+        patches, mod, orig, orig_flag = self._apply()
+        try:
+            msg = AIMessage(
+                content="done",
+                additional_kwargs={
+                    "reasoning_details": [
+                        {
+                            "type": "reasoning.summary",
+                            "format": "openai-responses-v1",
+                            "id": "rs_09363d42b054",
+                            "data": "gAAAAAB...",
+                            "summary": "real reasoning text",
+                            "index": 0,
+                        }
+                    ],
+                },
+            )
+            result = mod._convert_message_to_dict(msg)
+            # sole entry was an rs_ item → reasoning_details removed entirely.
+            assert "reasoning_details" not in result
+        finally:
+            self._restore(patches, mod, orig, orig_flag)
+
+    def test_keeps_plain_text_reasoning(self):
+        from langchain_core.messages import AIMessage
+
+        patches, mod, orig, orig_flag = self._apply()
+        try:
+            msg = AIMessage(
+                content="done",
+                additional_kwargs={
+                    "reasoning_details": [
+                        {"type": "reasoning.text", "text": "thinking", "index": 0},
+                        {"id": "rs_abc", "data": "blob", "index": 1},
+                    ],
+                },
+            )
+            result = mod._convert_message_to_dict(msg)
+            kept = result["reasoning_details"]
+            assert len(kept) == 1
+            assert kept[0]["type"] == "reasoning.text"
+        finally:
+            self._restore(patches, mod, orig, orig_flag)
+
+    def test_does_not_mutate_original_message(self):
+        from langchain_core.messages import AIMessage
+
+        patches, mod, orig, orig_flag = self._apply()
+        try:
+            details = [{"id": "rs_abc", "data": "blob"}]
+            msg = AIMessage(
+                content="x", additional_kwargs={"reasoning_details": details}
+            )
+            mod._convert_message_to_dict(msg)
+            # stored history untouched — we filter a fresh list, not in place.
+            assert details == [{"id": "rs_abc", "data": "blob"}]
+        finally:
+            self._restore(patches, mod, orig, orig_flag)
+
+    def test_patch_is_idempotent(self):
+        patches, mod, orig, orig_flag = self._apply()
+        try:
+            wrapper = mod._convert_message_to_dict
+            # Second call is guarded by the flag → must not re-wrap.
+            patches._patch_openrouter_strip_responses_reasoning()
+            assert mod._convert_message_to_dict is wrapper
+        finally:
+            self._restore(patches, mod, orig, orig_flag)
+
+    def test_non_dict_entry_is_kept(self):
+        from langchain_core.messages import AIMessage
+
+        patches, mod, orig, orig_flag = self._apply()
+        try:
+            msg = AIMessage(
+                content="done",
+                additional_kwargs={
+                    "reasoning_details": [
+                        "opaque",  # non-dict slipped in → kept, not crashed on
+                        {"id": "rs_abc", "data": "blob", "index": 1},
+                    ],
+                },
+            )
+            result = mod._convert_message_to_dict(msg)
+            assert result["reasoning_details"] == ["opaque"]
+        finally:
+            self._restore(patches, mod, orig, orig_flag)
+
+
 # =============================================================================
 # Test _apply_auto_config
 # =============================================================================
@@ -46,15 +46,16 @@ def _patch_all_questionary(mock_q):


 class TestConstants:
-    def test_steps_has_twelve_items(self):
-        """Test that STEPS contains exactly 12 steps."""
-        assert len(STEPS) == 12
+    def test_steps_has_thirteen_items(self):
+        """Test that STEPS contains exactly 13 steps."""
+        assert len(STEPS) == 13
        assert STEPS == [
            "UI",
            "LangGraph Port",
            "Provider",
            "API Key",
            "Model",
+            "Auxiliary Model",
            "Tavily Key",
            "Workspace",
            "Thinking",
@@ -353,6 +354,20 @@ class TestStepProvider:
        assert result == "anthropic"
        mock_q.select.assert_called_once()

+    def test_default_value_and_label_override(self):
+        """default_value preselects a provider (re-run co-pilot default) and
+        label customizes the prompt text."""
+        from EvoScientist.config.onboard.steps import _step_provider
+
+        config = EvoScientistConfig(provider="anthropic")
+        with patch("EvoScientist.config.onboard.steps.questionary") as mock_q:
+            mock_q.select.return_value.ask.return_value = "openai"
+            _step_provider(config, label="co-pilot", default_value="openrouter")
+
+        call = mock_q.select.call_args
+        assert call.kwargs["default"] == "openrouter"  # override, not config.provider
+        assert "co-pilot" in call.args[0]
+
    def test_raises_keyboard_interrupt_on_cancel(self):
        """Test that _step_provider raises KeyboardInterrupt on cancel."""
        from EvoScientist.config.onboard.steps import _step_provider
@@ -378,6 +393,38 @@ class TestStepModel:

        assert result == "claude-sonnet-4-6"

+    def test_main_model_not_in_provider_list_defaults_to_first(self):
+        """Reset/main flow: a config.model that isn't in the chosen provider's
+        list (e.g. provider switched to google-genai) defaults to that
+        provider's first model, NOT the custom 'Type a model name...' entry."""
+        from EvoScientist.config.onboard.steps import _step_model
+        from EvoScientist.llm.models import get_models_for_provider
+
+        config = EvoScientistConfig(model="claude-sonnet-4-6")
+        entries = get_models_for_provider("google-genai")
+        with patch("EvoScientist.config.onboard.steps.questionary") as mock_q:
+            mock_q.select.return_value.ask.return_value = entries[0][0]
+            _step_model(config, "google-genai")
+
+        default = mock_q.select.call_args.kwargs["default"]
+        assert default == entries[0][0]
+        assert default != "__custom__"
+
+    def test_custom_default_value_preselects_and_prefills(self):
+        """Co-pilot re-run: a saved custom (non-registry) model preselects and
+        prefills the 'Type a model name...' entry."""
+        from EvoScientist.config.onboard.steps import _step_model
+
+        config = EvoScientistConfig()
+        with patch("EvoScientist.config.onboard.steps.questionary") as mock_q:
+            mock_q.select.return_value.ask.return_value = "__custom__"
+            mock_q.text.return_value.ask.return_value = "my-private/model"
+            result = _step_model(config, "openrouter", default_value="my-private/model")
+
+        assert mock_q.select.call_args.kwargs["default"] == "__custom__"
+        assert mock_q.text.call_args.kwargs["default"] == "my-private/model"
+        assert result == "my-private/model"
+
    def test_raises_keyboard_interrupt_on_cancel(self):
        """Test that _step_model raises KeyboardInterrupt on cancel."""
        from EvoScientist.config.onboard.steps import _step_model
@@ -1143,6 +1190,7 @@ class TestRunOnboard:
                "anthropic",  # Provider
                "api_key",  # Anthropic auth mode (API key, not OAuth)
                "claude-sonnet-4-6",  # Model
+                "skip",  # Auxiliary: Skip (single driver)
                "daemon",  # Workspace mode
                True,  # Show thinking
            ]
@@ -1173,6 +1221,101 @@ class TestRunOnboard:
        assert final_config.ui_backend == "tui"
        assert final_config.default_mode == "daemon"

+    def test_auxiliary_model_enabled_collects_provider_and_key(self):
+        """Enabling the auxiliary step stores its provider, model, and the
+        chosen provider's API key (a different company than the main agent)."""
+        from EvoScientist.config.onboard.wizard import run_onboard
+
+        mock_q = MagicMock()
+        with (
+            _patch_all_questionary(mock_q),
+            patch("EvoScientist.config.onboard.wizard.load_config") as mock_load,
+            patch("EvoScientist.config.onboard.wizard.save_config") as mock_save,
+            patch("EvoScientist.config.onboard.wizard.console"),
+            patch("EvoScientist.config.onboard.steps.console"),
+            patch("EvoScientist.config.onboard.channels.console"),
+            patch("EvoScientist.config.onboard.helpers.console"),
+            patch("EvoScientist.config.onboard.wizard._step_tinytex"),
+        ):
+            mock_load.return_value = EvoScientistConfig()
+
+            mock_q.select.return_value.ask.side_effect = [
+                "tui",  # UI backend
+                "anthropic",  # Provider
+                "api_key",  # Anthropic auth mode
+                "claude-sonnet-4-6",  # Model
+                "assemble",  # Auxiliary: Assemble
+                "openai",  # Auxiliary provider (a different company)
+                "gpt-5.5",  # Auxiliary model
+                "daemon",  # Workspace mode
+                True,  # Show thinking
+            ]
+            mock_q.password.return_value.ask.side_effect = [
+                "",  # Main provider API key (keep current)
+                "sk-aux-openai",  # Auxiliary provider API key
+                "",  # Tavily key (keep current)
+            ]
+            mock_q.confirm.return_value.ask.side_effect = [
+                True,  # Save config
+            ]
+            mock_q.text.return_value.ask.side_effect = [
+                "",  # Workspace directory
+            ]
+            mock_q.checkbox.return_value.ask.return_value = []  # Skills: skip
+
+            result = run_onboard(skip_validation=True)
+
+        assert result is True
+        final_config = mock_save.call_args_list[-1].args[0]
+        assert final_config.auxiliary_provider == "openai"
+        assert final_config.auxiliary_model == "gpt-5.5"
+        # The auxiliary provider's key is stored in its per-provider field.
+        assert final_config.openai_api_key == "sk-aux-openai"
+        # Main agent is untouched.
+        assert final_config.provider == "anthropic"
+        assert final_config.model == "claude-sonnet-4-6"
+
+    def test_auxiliary_custom_provider_collects_base_url(self):
+        """Regression for the custom-provider fix: a custom auxiliary provider
+        collects its base URL (provider -> base URL -> key -> model order)."""
+        from EvoScientist.config.onboard.wizard import run_onboard
+
+        mock_q = MagicMock()
+        with (
+            _patch_all_questionary(mock_q),
+            patch("EvoScientist.config.onboard.wizard.load_config") as mock_load,
+            patch("EvoScientist.config.onboard.wizard.save_config") as mock_save,
+            patch("EvoScientist.config.onboard.wizard.console"),
+            patch("EvoScientist.config.onboard.steps.console"),
+            patch("EvoScientist.config.onboard.channels.console"),
+            patch("EvoScientist.config.onboard.helpers.console"),
+        ):
+            mock_load.return_value = EvoScientistConfig()
+            mock_q.select.return_value.ask.side_effect = [
+                "assemble",  # Auxiliary: Assemble
+                "custom-openai",  # Auxiliary provider
+                "gpt-5.5",  # Auxiliary model (from the custom-openai registry)
+            ]
+            mock_q.text.return_value.ask.side_effect = [
+                "https://my-endpoint/v1",  # Auxiliary base URL (custom provider)
+            ]
+            mock_q.password.return_value.ask.side_effect = [
+                "sk-aux-custom",  # Auxiliary provider API key
+            ]
+            mock_q.confirm.return_value.ask.side_effect = [True]  # Save
+
+            result = run_onboard(
+                skip_validation=True, only_sections={"auxiliary_model"}
+            )
+
+        assert result is True
+        final_config = mock_save.call_args_list[-1].args[0]
+        assert final_config.auxiliary_provider == "custom-openai"
+        assert final_config.auxiliary_model == "gpt-5.5"
+        # Base URL must be collected for the custom auxiliary provider.
+        assert final_config.custom_openai_base_url == "https://my-endpoint/v1"
+        assert final_config.custom_openai_api_key == "sk-aux-custom"
+
    def test_returns_false_on_cancel(self):
        """Test that run_onboard returns False when cancelled."""
        from EvoScientist.config.onboard.wizard import run_onboard
@@ -1218,6 +1361,7 @@ class TestRunOnboard:
                "anthropic",  # Provider
                "api_key",  # Anthropic auth mode
                "claude-sonnet-4-6",  # Model
+                "skip",  # Auxiliary: Skip (single driver)
                "daemon",  # Workspace mode
                True,  # Show thinking
            ]
@@ -1288,11 +1432,14 @@ class TestRunOnboard:
                    "anthropic",
                    "api_key",
                    "claude-sonnet-4-6",
+                    "skip",  # Auxiliary: Skip (single driver)
                    "daemon",
                    True,
                ]
                mock_q.password.return_value.ask.side_effect = ["", ""]
-                mock_q.confirm.return_value.ask.side_effect = [False]  # Save? = No
+                mock_q.confirm.return_value.ask.side_effect = [
+                    False,  # Save? = No
+                ]
                mock_q.text.return_value.ask.side_effect = [""]
                mock_q.checkbox.return_value.ask.return_value = []

@@ -1335,11 +1482,14 @@ class TestRunOnboard:
                "anthropic",
                "api_key",
                "claude-sonnet-4-6",
+                "skip",  # Auxiliary: Skip (single driver)
                "daemon",
                True,
            ]
            mock_q.password.return_value.ask.side_effect = ["", ""]
-            mock_q.confirm.return_value.ask.side_effect = [False]  # Save? = No
+            mock_q.confirm.return_value.ask.side_effect = [
+                False,  # Save? = No
+            ]
            mock_q.text.return_value.ask.side_effect = [""]
            mock_q.checkbox.return_value.ask.return_value = []

@@ -40,6 +40,8 @@ def _mock_config():
    cfg.auto_mode = False
    cfg.auto_approve = False
    cfg.model_fallbacks = None
+    cfg.auxiliary_model = ""
+    cfg.auxiliary_provider = ""
    cfg.code_interpreter_timeout = 60
    cfg.code_interpreter_max_result_chars = 6000
    return cfg
@@ -161,6 +161,8 @@ def test_default_middleware_includes_tool_selector(mock_config, mock_model, mock
    cfg = MagicMock()
    cfg.enable_ask_user = False
    cfg.auto_approve = False
+    cfg.auxiliary_model = ""
+    cfg.auxiliary_provider = ""
    mock_config.return_value = cfg

    from EvoScientist.EvoScientist import _get_default_middleware
@@ -196,6 +198,8 @@ def test_tool_selector_ordering(mock_config, mock_model, mock_ts):
    cfg = MagicMock()
    cfg.enable_ask_user = False
    cfg.auto_approve = False
+    cfg.auxiliary_model = ""
+    cfg.auxiliary_provider = ""
    mock_config.return_value = cfg

    from EvoScientist.EvoScientist import _get_default_middleware
@@ -810,7 +810,7 @@ wheels = [

 [[package]]
 name = "deepagents"
-version = "0.6.7"
+version = "0.6.8"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "langchain" },
@@ -820,9 +820,9 @@ dependencies = [
    { name = "langsmith" },
    { name = "wcmatch" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/51/bb/bb837a2c51631fe9d7eedf6aca7629ddca6336831801e75efcd2f5fa9c27/deepagents-0.6.7.tar.gz", hash = "sha256:af7b5857b28e29a847a4ced4cc7aaa809d33d42107696b1ca5d978d17e96b831", size = 194236, upload-time = "2026-05-30T04:42:14.591Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/97/77/e3b7efd9bff9cd101c085a5a3bf74180c13ab6c41a96f725cd1cb1bf53e8/deepagents-0.6.8.tar.gz", hash = "sha256:70cdd4da920cc420a8a0f729792ec559688bbbff39f7ab1508110cce9f901c06", size = 196927, upload-time = "2026-06-03T17:08:36.724Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/97/25/3a7f23d04778ccb95542f1b1ed39826290916221cc8203d0fb8b26c3edc1/deepagents-0.6.7-py3-none-any.whl", hash = "sha256:3518c1e5f4b9f6588ba39912b668b42b5c864b99a638e94c166d1c7176c7388e", size = 218740, upload-time = "2026-05-30T04:42:13.225Z" },
+    { url = "https://files.pythonhosted.org/packages/8e/19/1b7b76e958ac7f4e40886edc70f67aff4d7188770ab68105c9c48cbeb769/deepagents-0.6.8-py3-none-any.whl", hash = "sha256:087bdc1458202a3436854cf180f7ec059d07d2114a6c232819e9ad6533a5174a", size = 221469, upload-time = "2026-06-03T17:08:35.133Z" },
 ]

 [package.optional-dependencies]
@@ -997,7 +997,7 @@ requires-dist = [
    { name = "certifi", marker = "extra == 'wechat'", specifier = ">=2024.0" },
    { name = "cryptography", marker = "extra == 'all-channels'", specifier = ">=41.0" },
    { name = "cryptography", marker = "extra == 'qq'", specifier = ">=41.0" },
-    { name = "deepagents", extras = ["quickjs"], specifier = "~=0.6.7" },
+    { name = "deepagents", extras = ["quickjs"], specifier = "~=0.6.8" },
    { name = "discord-py", marker = "extra == 'all-channels'", specifier = ">=2.3" },
    { name = "discord-py", marker = "extra == 'discord'", specifier = ">=2.3" },
    { name = "faster-whisper", marker = "extra == 'stt'", specifier = ">=1.0" },
@@ -1960,16 +1960,16 @@ wheels = [

 [[package]]
 name = "langchain"
-version = "1.3.2"
+version = "1.3.4"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "langchain-core" },
    { name = "langgraph" },
    { name = "pydantic" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/d5/d0/c7f9d3d26c0e3f8bb146c6d707ee0fc1d30d8da65a59626e8a580085e929/langchain-1.3.2.tar.gz", hash = "sha256:ffd5f204a46b5fa1a38bf89ba3b45ca0902c02d18fa7d2a2eaeaeb1f5bf19d0a", size = 600598, upload-time = "2026-05-26T18:17:57.715Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/36/3f/034eb6cbef90bfccc89b7f8ed0c1d853dc9cb0bea17c7a269534c647ba3a/langchain-1.3.4.tar.gz", hash = "sha256:d6e0654c22848925534f5c0a706f9be481bb09a619ec60a738fbd1e5502e457a", size = 606617, upload-time = "2026-06-02T20:04:49.411Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/f8/82/a54edcd1c48163de5642eb10fa2cb58b13a8889c659964f63f0306b58b1e/langchain-1.3.2-py3-none-any.whl", hash = "sha256:900f6b3f4ee08b9ba3cdbe667dbf42525bd6f66a4a07a7f1db26262673e41ed6", size = 121225, upload-time = "2026-05-26T18:17:56.075Z" },
+    { url = "https://files.pythonhosted.org/packages/a5/29/9ffe99c7dc4891a0215ec59c423bea320f943c08a231bc5bae392a438a83/langchain-1.3.4-py3-none-any.whl", hash = "sha256:e51b05ab23d056bc6bf2d97d8c694fb92d6d5765126fef74565d007c27581672", size = 125286, upload-time = "2026-06-02T20:04:48.13Z" },
 ]

 [[package]]
@@ -2092,14 +2092,14 @@ wheels = [

 [[package]]
 name = "langchain-protocol"
-version = "0.0.14"
+version = "0.0.16"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
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