diff --git a/.github/assets/badge-pypi-dark.svg b/.github/assets/badge-pypi-dark.svg index dce4c53..8e2b2a6 100644 --- a/.github/assets/badge-pypi-dark.svg +++ b/.github/assets/badge-pypi-dark.svg @@ -5,5 +5,5 @@ v0.1.3 + font-size="13" font-weight="700" fill="#ffffff">v0.1.4 \ No newline at end of file diff --git a/.github/assets/badge-pypi-light.svg b/.github/assets/badge-pypi-light.svg index a2523be..90962be 100644 --- a/.github/assets/badge-pypi-light.svg +++ b/.github/assets/badge-pypi-light.svg @@ -5,5 +5,5 @@ v0.1.3 + font-size="13" font-weight="700" fill="#ffffff">v0.1.4 \ No newline at end of file diff --git a/EvoScientist/EvoScientist.py b/EvoScientist/EvoScientist.py index c20520a..fe5f84a 100644 --- a/EvoScientist/EvoScientist.py +++ b/EvoScientist/EvoScientist.py @@ -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 diff --git a/EvoScientist/config/onboard/steps.py b/EvoScientist/config/onboard/steps.py index 14d4940..c77cadd 100644 --- a/EvoScientist/config/onboard/steps.py +++ b/EvoScientist/config/onboard/steps.py @@ -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)", diff --git a/EvoScientist/config/onboard/style.py b/EvoScientist/config/onboard/style.py index 0fb0f33..4b322b6 100644 --- a/EvoScientist/config/onboard/style.py +++ b/EvoScientist/config/onboard/style.py @@ -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. diff --git a/EvoScientist/config/onboard/wizard.py b/EvoScientist/config/onboard/wizard.py index 8e74efe..21008dc 100644 --- a/EvoScientist/config/onboard/wizard.py +++ b/EvoScientist/config/onboard/wizard.py @@ -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: diff --git a/EvoScientist/config/settings.py b/EvoScientist/config/settings.py index f897021..a14f7a3 100644 --- a/EvoScientist/config/settings.py +++ b/EvoScientist/config/settings.py @@ -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", diff --git a/EvoScientist/llm/context_window.py b/EvoScientist/llm/context_window.py index a1d62b9..2e4005f 100644 --- a/EvoScientist/llm/context_window.py +++ b/EvoScientist/llm/context_window.py @@ -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, diff --git a/EvoScientist/llm/models.py b/EvoScientist/llm/models.py index 87c8164..d0b021b 100644 --- a/EvoScientist/llm/models.py +++ b/EvoScientist/llm/models.py @@ -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: diff --git a/EvoScientist/llm/patches.py b/EvoScientist/llm/patches.py index 07e1c72..db786d3 100644 --- a/EvoScientist/llm/patches.py +++ b/EvoScientist/llm/patches.py @@ -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. diff --git a/EvoScientist/middleware/memory_lifecycle.py b/EvoScientist/middleware/memory_lifecycle.py index c574025..b715a7a 100644 --- a/EvoScientist/middleware/memory_lifecycle.py +++ b/EvoScientist/middleware/memory_lifecycle.py @@ -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( diff --git a/README.md b/README.md index e91ca6c..1e0d587 100644 --- a/README.md +++ b/README.md @@ -10,7 +10,7 @@ - PyPI v0.1.3 + PyPI v0.1.4 @@ -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
📦 Release Highlights — version changelog +- **[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. diff --git a/README.zh-CN.md b/README.zh-CN.md index 3f29cdb..653d24d 100644 --- a/README.zh-CN.md +++ b/README.zh-CN.md @@ -15,7 +15,7 @@ - PyPI v0.1.3 + PyPI v0.1.4 @@ -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
📦 版本更新摘要（changelog） +- **[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。 diff --git a/pyproject.toml b/pyproject.toml index 2acabb2..b3bf063 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -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", diff --git a/tests/test_ask_user.py b/tests/test_ask_user.py index 1725fb3..cc21f71 100644 --- a/tests/test_ask_user.py +++ b/tests/test_ask_user.py @@ -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}) diff --git a/tests/test_async_subagent_factory.py b/tests/test_async_subagent_factory.py index ba2b741..60758ef 100644 --- a/tests/test_async_subagent_factory.py +++ b/tests/test_async_subagent_factory.py @@ -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}) diff --git a/tests/test_auxiliary_model.py b/tests/test_auxiliary_model.py new file mode 100644 index 0000000..37de4fd --- /dev/null +++ b/tests/test_auxiliary_model.py @@ -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 diff --git a/tests/test_config.py b/tests/test_config.py index c955dfe..da8a55d 100644 --- a/tests/test_config.py +++ b/tests/test_config.py @@ -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" diff --git a/tests/test_context_editing_middleware.py b/tests/test_context_editing_middleware.py index 929b4ed..c7db267 100644 --- a/tests/test_context_editing_middleware.py +++ b/tests/test_context_editing_middleware.py @@ -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 diff --git a/tests/test_llm.py b/tests/test_llm.py index 9d797a3..63f7a4a 100644 --- a/tests/test_llm.py +++ b/tests/test_llm.py @@ -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 # ============================================================================= diff --git a/tests/test_onboard.py b/tests/test_onboard.py index 0e99a15..b62ca38 100644 --- a/tests/test_onboard.py +++ b/tests/test_onboard.py @@ -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 = [] diff --git a/tests/test_runtime_context_middleware.py b/tests/test_runtime_context_middleware.py index 7cb560d..a3f7465 100644 --- a/tests/test_runtime_context_middleware.py +++ b/tests/test_runtime_context_middleware.py @@ -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 diff --git a/tests/test_tool_selector_middleware.py b/tests/test_tool_selector_middleware.py index 007616e..2759614 100644 --- a/tests/test_tool_selector_middleware.py +++ b/tests/test_tool_selector_middleware.py @@ -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 diff --git a/uv.lock b/uv.lock index 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