feat(#1001): AI agent harness — state machine, capability registry, constrained tool protocol (Copilot v2 slice 1) - #1052
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…ity registry, constrained tool protocol The orchestration layer above AIChatManager/LLMManager (#1000, epic #818 Track C6): User -> AIAgentManager -> Planner -> Capability router -> Executor -> Observer -> Replan/Finish. - AIAgentTypes: Plan/Step/Observation/Limits — ALL task state lives here, never in the prompt; deterministic summarize() is the final message - AICapabilityRegistry (#1002): ~170 MCP tools grouped into 20 capabilities; the planner sees a 20-line index + full docs only for the routed capabilities and can ask for more ({"need_capabilities"}); docs are generated from the live buildToolsList() schema - constrained protocol (#1003): validateArguments checks/coerces every planned call against the schema before it reaches the server; unknown tools and bad enums never execute - AIAgentManager (#1001): Planning/Executing/Observing/Replanning/ AwaitingConfirmation/Completed/Failed/Cancelled; retry once, then bounded replans; identical failing action twice = stop; cancel in any state; one undo group per task (#1021b); destructive steps pause for Allow / Always allow / Skip unless trusted mode (#1021d); scene summary injected per turn (#1021c); planner + executor are injected interfaces - AIChatManager facade: agentMode (default on) delegates sendMessage to the agent; v1 loop kept behind the toggle; McpToolExecutor wired in setMcpServer; LlmPlannerBackend forwards LLM signals only while pending - QML: agent/ask-trusted toggles, live plan card, confirmation bar, model tip (Qwen 2.5 7B recommended for tool calling, #1021e) - tests: AIAgentManager_test (14 fixture cases: 5 dependent steps + one undo group, retry, replan, repeated failure, cancel, invalid args, unknown tool, confirmations, capability expansion, Q&A, malformed planner, no-model, context injection) + AICapabilityRegistry_test — headless, no LLM; four guards mutation-verified Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
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Included review availability: Your plan provides up to 1 included review per hour; 0 remain after this review. 📝 WalkthroughWalkthroughThe pull request adds an AI agent pipeline with capability routing, structured plans and observations, bounded execution and replanning, destructive-action confirmation, agent-mode chat integration, QML controls, MCP selection support, tests, model updates, and documentation. ChangesAI agent
Priority: ➖ Normal Estimated code review effort: 4 (Complex) | ~75 minutes Change: Feature Sequence Diagram(s)sequenceDiagram
participant User
participant AIChatPanel
participant AIChatManager
participant AIAgentManager
participant LlmPlannerBackend
participant MCPServer
User->>AIChatPanel: Enter task
AIChatPanel->>AIChatManager: sendMessage(task)
AIChatManager->>AIAgentManager: startTask(task)
AIAgentManager->>LlmPlannerBackend: request(plan prompt)
LlmPlannerBackend-->>AIAgentManager: completed(plan)
AIAgentManager->>MCPServer: Validate and execute tool step
MCPServer-->>AIAgentManager: Tool result and observation
AIAgentManager->>LlmPlannerBackend: request(replan prompt)
AIAgentManager-->>AIChatPanel: Plan, state, and confirmation updates
AIAgentManager-->>AIChatManager: taskFinished(summary)
AIChatManager-->>AIChatPanel: Chat message
Merge Risk: ⚪ Minimal · up to The reviewed incremental changes include validation and focused test coverage without an identified unresolved behavior regression. The change is ready to merge. 🚥 Pre-merge checks | ✅ 3 | ❌ 2❌ Failed checks (2 warnings)
✅ Passed checks (3 passed)
Full details: Linked Issues checkExplanation The PR meets the coding requirements in [ Resolution Add grammar or JSON-schema constrained generation for supported models. Keep balanced-brace extraction only for unsupported models or templates. Add headless tests that verify the supported path and confirm that it does not require balanced-brace extraction. Full details: Docstring CoverageExplanation Docstring coverage is 25.60% which is insufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 207 functions across 17 files. (1 skipped: 1 too large.)
✨ Finishing Touches 💡 1📝 Generate docstrings 💡
🧪 Generate unit tests (beta)
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Inline comments:
In `@qml/AIChatPanel.qml`:
- Line 213: Update the pin-condition binding near root.agentBusy to read
planCardPinned from its owning planCard object rather than root, preserving the
existing agentBusy condition and surrounding logic.
In `@src/AIAgentManager.cpp`:
- Around line 473-476: Update the replan loop around m_plan.steps and the
following say call to count only steps actually appended, report that count, and
indicate the configured step budget when the repaired tail is truncated because
room is exhausted. Preserve the existing planChanged emission and avoid claiming
all input steps were added.
- Around line 589-593: Update the post-call flow around
setState(State::Observing) and observationFromToolResult to check
m_cancelRequested before transitioning or scheduling further execution,
preserving the Cancelled terminal state when cancel() runs during callTool. Make
finish() idempotent so repeated calls do not emit duplicate taskFinished signals
or summary messages, and ensure cancelled execution does not invoke executeNext.
- Around line 518-523: Update the no-pending-step branch in executeNext so it
checks m_plan.steps for any Step::Failed outcome before calling finish. Complete
successfully when remaining steps are only completed or intentionally skipped,
but finish with the failure state when an unrepaired failed step remains,
including when maxSteps prevents a replacement.
In `@src/AIAgentTypes.cpp`:
- Line 129: Update the JSON isError handling in the tool-output parsing logic so
that when it sets ob.status to "error", it also assigns the payload’s error
detail to ob.error. Preserve the existing behavior for non-error payloads and
ensure toPromptLine(), summarize(), and replanning receive the failure reason.
In `@src/AIChatManager.cpp`:
- Line 45: Change the default value used to initialize m_agentMode in
AIChatManager so fresh installations set it to false, preserving agent mode only
when explicitly enabled in settings and allowing sendMessage() to use the
existing non-agent generation path.
- Around line 68-74: Update AIChatManager’s agent task-finished handling to
retain a cancellation guard until the matching LLM terminal signal arrives.
Track the cancelled request identity, ignore late callbacks from that
request—including onGenerationCompleted—and clear the guard only after its
terminal completion signal, while preserving normal callbacks for subsequent
requests.
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…hinking Qwen3 entries
The Qwen 2.5 7B/14B/32B entries pointed at the official Qwen repos, which
split those quants into -00001-of-00002 parts; the single-file URL 404s
("Failed to download Qwen 2.5 7B"). Every URL now answers HTTP 200 as one
file (bartowski/unsloth mirrors), verified 2026-09-17.
- adds Qwen3 4B Instruct 2507 (non-thinking; the agent's recommended
model — fits 8 GB) and Qwen3 30B-A3B Instruct 2507 (MoE, strongest local
tool caller). Hybrid "thinking" Qwen3 variants are deliberately left out:
the worker feeds a generic chat template that cannot switch thinking off
- list kept in size order; Gemma 3 27B re-verified
- AIAgentManager::modelIsRecommended() drives the panel tip instead of a
hard-coded "7b" substring check
- LLMManager_test: every entry is a single-file https GGUF with unique
name/file, sorted by size, and the agent's recommendation is in the list
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
…, generic overwrite rail, planner drain guard - Linux CI link: the standalone test library (tests/CMakeLists.txt) now lists AIAgentManager/AIAgentTypes/AICapabilityRegistry next to AIChatManager.cpp (MaterialEditorQML_test failed to link) - Codex P1: MainWindow creates the MCPServer object on every launch as the in-process tool dispatcher (HTTP transport stays opt-in), so the agent has an executor on a fresh install; MCPServer's Windows _setmode moved from the constructor into start() — a GUI process has no console - Codex P1: replan capacity counts only steps that ran (skipped rows are transcript), and a repair that does not fit FAILS instead of reading as "completed"; executeNext uses the same retained-count rule - Codex P1: overwrite confirmation is derived from argument SHAPE (output*/out/dest*/export_path/save_path/*_output on any non-read-only tool; path/file only on exporter-named tools) instead of a per-tool allowlist — generate_mesh_from_image's `output` was missed - Codex P2: AgentPlannerBackend::pending() + AIAgentManager::plannerPending(); the chat facade keeps ignoring LLMManager callbacks while a cancelled planner request drains, so a late completion cannot restart the v1 loop - CodeRabbit: plan card pin reads planCard.planCardPinned - tests: repair-at-cap (fail vs fits), planner drain after cancel, output- shape overwrite cases incl. an existing INPUT path that must not count Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
…nish, unrepaired failures fail, JSON error reasons
- cancel() can run INSIDE the synchronous tool call (a long tool pumps GUI
events); the late result no longer resurrects the task, and finish() is
idempotent — one taskFinished, one summary (pinned with a QSignalSpy)
- a task with an unrepaired Failed step ends Failed, never Completed. A
failed step whose replacement was appended by a replan gets the new
Step::Repaired status so it is neither an unrepaired failure nor an
intentional skip (plan card shows ↻)
- a JSON `{"isError":true,"error":...}` payload carries its reason into
Observation::error, so the replan prompt and the summary see it
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
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Inline comments:
In `@src/AICapabilityRegistry.cpp`:
- Around line 400-402: Update destructiveReason() so cloud_upload requires
confirmation when trusted mode is disabled, using the actual file argument and
including the QtMesh Cloud destination, source file, and packaged dependencies
in the confirmation details. Ensure AIAgentManager::executeNext() receives a
non-empty destructive reason and does not dispatch the upload without
confirmation.
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… the blocker Behaviour-neutral (99 tests unchanged): - BLOCKER S912: the `added.isEmpty() || ++m_plannerRetries > ...` side effect is a plain increment now (expandCapabilities + handlePlanReply) - onPlannerCompleted (CC 48) → dispatcher + handlePlanReply / handleReplanReply / appendRepairedTail / expandCapabilities - validateArguments (CC 105) → per-type coercers + matchEnum - destructiveReason (CC 33) → deleteReason + overwriteReason - observationFromToolResult (CC 53) → resultText / parseErrorStatus / parseLabelledNumbers / parseJsonFacts / parseArtifacts / parseWarnings - summarize (CC 41) → summaryHeadline / successObservationFor / factsFragment - extractJsonObject's lambda → firstBalancedObject free function - C-style tables → std::vector; qsizetype narrowing casts; one-statement- per-line in the planner backend lambdas; nested ternaries unrolled; a header comment Sonar read as commented-out code reworded Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
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Inline comments:
In `@src/AICapabilityRegistry.cpp`:
- Line 392: Update validateArguments around coerceToType and matchEnum to
validate every element of an array against its schema’s items definition before
dispatch. Preserve the existing top-level array type and enum checks, and reject
or report any element that fails the declared item constraints using the
existing warnings/why validation flow.
- Line 304: Update the integer handling in coerceNumber() so it validates that
the QJsonValue double is finite, integral, and within the qint64 range before
converting it to qint64; reject invalid values through the existing “expected an
integer” path and preserve normal conversion for valid integers.
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…onar blocker/majors - coerceNumber: an integer must be finite, integral and inside qint64 BEFORE the conversion (1e100 used to hit UB in qint64(double)) - checkArrayItems: elements are checked against the schema's items.type (join_mesh_parts.entity_names, cloud_upload.include/exclude are string arrays); arrays without an items schema pass as before - Sonar: the `--depth` side effect in `&&` (blocker) is a plain statement; parsePlanReply/parseReplanReply share parseReplyObject + stepFromJson; C-style tables → std::array; one statement per line; flattened toolsFor Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
…rcion, per-task trace log
Field findings from the first real sessions (Qwen3 4B): rigging never
worked because auto_rig and ~25 other tools act on the CURRENT SELECTION
and the agent could not set it; each prompt was treated as the first
because no earlier turn reached the planner.
- MCP `select_entity {name}` (node or entity name; empty clears) +
`get_scene_info` ends with "Selected: …"; auto_rig's error now names
the fix; planner rule 6 tells the model to select first
- AIAgentManager keeps the last 12 turns (request → outcome [objects])
and injects the last 6 + an "objects from earlier turns" list into every
planner prompt; AIChatManager::clearHistory clears it
- colour names where [R,G,B] is expected ("diffuse": "red") are coerced
with a warning; rule 7 spells out create_material → apply_material
- every task writes <AppData>/ai_agent/last_task.log with the planner
prompts, raw replies and raw tool results (AIAgentManager::traceLogPath)
- tests: history injection + clearHistory, trace log contents, colour
coercion, select_entity end-to-end (GL-gated MCP test)
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
…g call; chat dock regains focus on click Transcript from a real session (Qwen3 4B): apply_material was rejected twice for a missing 'material' — the model wrote material_name, which the MCP handler itself accepts. The validator must never be stricter than the tool: - normaliseAliases maps camelCase + a synonym table (material_name→material, entity/entity_name/node→mesh, output/path→output_path, skeleton→template, …) onto the schema names BEFORE the required check; an explicit schema key always wins over an alias - a rejection lists the keys that were passed; the replan prompt includes the failing call's arguments and asks for a changed call Chat dock: once another QQuickWidget dock held focus, clicking the QML input re-focused the item but not the hosting widget (keys went elsewhere until a detour via the viewport). ClickFocusFilter on the chat QQuickWidget turns every press into setFocus. Unit-tested with an offscreen QWidget. Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
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Actionable comments posted: 4
- 🪄 Fix CodeRabbit comments on this PR
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only still-valid issues, skip the rest with a brief reason, keep changes
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Inline comments:
In `@src/AIAgentManager.cpp`:
- Around line 181-183: Update the recent-object collection loop in the history
prompt-building logic to enforce the limit inside the inner iteration: stop
processing objects once recent reaches eight, while preserving deduplication and
newest-first traversal.
In `@src/AICapabilityRegistry.cpp`:
- Line 329: Update checkArrayItems() so integer array items are accepted only
when their QJsonValue double is finite, integral, and within the supported
integer range; keep number items using the existing isDouble() validation.
Ensure this validation occurs before AIAgentManager::validateArguments() sends
values to MCPServer, matching mcpJsonIntValue() behavior.
- Around line 375-377: Update validateArguments() and coerceArray() so
colourNameToRgb() runs only for properties explicitly marked with colour
metadata. Add that metadata to schemas whose array values accept colour names,
while leaving transform_mesh.scale and other numeric arrays such as position and
rotation unmarked so values like "red" are rejected rather than coerced.
In `@src/ClickFocusFilter_test.cpp`:
- Line 31: Replace the tautological assertion in the ClickFocusFilter test with
a watched widget that records receipt of QEvent::MouseButtonPress, then assert
that the widget received the press after applying the filter.
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…integer array items, recent-object cap, real focus-filter assertion - colourNameToRgb applies only to colour properties (key diffuse/ambient/ specular/emissive/colour/tint/rgb/albedo, or a description that says colour) — "scale": "red" is an error again instead of a [1,0,0] scale - integer array items get the same finite/integral/range check as scalars - the "objects from earlier turns" list is capped inside the inner loop - ClickFocusFilter test asserts the widget actually received the press (was a tautology) Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
…o helpers (Sonar nesting/complexity) Behaviour-neutral: snakeCaseKeys + fillFromAliases; sceneEntityLine / sceneEntityLines / selectedSceneNodeNames for get_scene_info. Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
…complexity) Behaviour-neutral. Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
…del's real context window Switching the agent to another model produced "Failed to decode prompt": LLMWorker's prompt-too-long pre-check compared against the CONFIGURED context size, but the context actually created is clamped to the model's training limit, so an oversized prompt slipped through to llama_decode. - LLMWorker checks against llama_n_ctx (+32 headroom) with a message naming the prompt size and the window, and emits contextReady(nCtx) - LLMManager::effectiveContextSize (0 when unloaded) - AIAgentManager::systemPromptWithinBudget trims the planner prompt to the window: drop history → keep the most relevant capabilities → truncate the scene listing → hard cut; each step traced + breadcrumbed - default contextSize 4096 → 8192 (the agent's tool docs need it); the Sonar-era default test updated Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
…achable from QML); actionable llama_decode failure - AIAgentManager::modelIsRecommended was a STATIC Q_INVOKABLE — QML cannot call that on the singleton, the binding evaluated to undefined and the "small model" tip showed for every model, the 30B included. Instance invokable now (isRecommendedModelName keeps the pure static); a test pins the meta-method kind. The tip names the model that is actually loaded. - "Failed to decode prompt" now says what it is: llama_decode failing to allocate compute/KV buffers — the model does not fit in memory — with the token position, window and model name, and the three things to change. - the Qwen3 30B-A3B entry states 32 GB: on a 24 GB Mac the 17 GB weights load but the GPU working-set budget cannot hold the KV cache. Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
…es from AI Model Settings; model chip opens the dialog - generate_mesh_from_image: schema says 2D IMAGE, not a mesh → load_mesh; the handler refuses mesh extensions (and unsupported ones) by name; the agent's validator (rejectMeshAsImage) stops any image-typed parameter carrying a .obj/.glb/… before the tool runs; capability index reworded - LLMManager::deleteModelFile / deleteAllModelFiles (models dir only, no path traversal, unload-first, .part removed) + per-row Delete, Remove All and Open Folder in the LLM tab, with confirmation dialogs like the QtMeshEditor Models tab - the chat header's model name/status is a clickable chip that opens AI Model Settings (AIChatManager::openModelSettings → showAIModelSettings) - tests: mesh-as-image rejection (case-insensitive, other params untouched), model file deletion incl. traversal refusal and .part cleanup Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
…wnload tab (the dialog the menu actually opens) The previous commit put the delete buttons in the QML AISettingsDialog, but AI → AI Model Settings opens the Qt Widgets LLMSettingsWidget; its "LLM Download" tab now has the same affordances as its QtMeshEditor Models tab: Delete Selected (enabled only for a downloaded model; unloads the active model first), Remove All, Open Folder — each behind a QMessageBox confirmation, backed by LLMManager::deleteModelFile/deleteAllModelFiles. Widget test pins the buttons and the disabled-without-selection state. Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
…r setter uses a non-default value) Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Clicking outside QtMeshEditor and back into the chat input left the caret dead until a detour via the viewport: the chat QQuickWidget was still the window's focus widget, so the click-to-focus filter's "only if not focused" guard did nothing and the QML scene never received a fresh FocusIn. The filter now clears and re-sets focus on every press, which forces the FocusOut/FocusIn pair QQuickWidget forwards to its scene. The test asserts a FocusIn is delivered even when the widget is already focused. Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
…as is a nudge, not a failure "create a f22 raptor scene" ended with "I could not find tools for: generation_3d": the second prompt DID carry generate_mesh_from_image's docs, the 14B model asked for the capability again anyway, and expandCapabilities returned false → the "unknown capability" failure. - expandCapabilities reports alreadyHad/unknown separately; an already- provided capability re-asks the planner with "ALREADY listed — plan with those tools now", a truly missing one says "this build has no tools for", and a model that never stops asking is cut off with an honest message - creation phrasing (create/make/build/scene/character/creature/vehicle, "a 3d") routes the single-tool generation_3d capability up front Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
…ation in untrusted mode Review finding (CodeRabbit): destructiveReason() only knew deletes and overwrites of an existing file, so an untrusted agent dispatched cloud_upload without the promised confirmation — nothing local is destroyed, but the mesh and its packaged dependencies leave the machine and that cannot be undone. outboundReason() now names the upload (source file, project name) and the account changes (login stores a credential, logout revokes the session); read-only cloud tools stay silent. Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
…delete, download-state buttons, generation cap, budget copy, colour-name warning CodeRabbit on the stacked router PR (#1054), all on harness code: - LLMManager: unloadModel() is queued to the worker thread, so deleting the ACTIVE model's file right after it raced the still-mapped file (fails on Windows). The active file now waits in m_pendingDeletions and is removed from onWorkerModelUnloaded; other files delete immediately. - deleteAllModelFiles() covers .bin (+ .bin.part) too, so the Remove All confirmation count and the deletion are the same set scanForModels lists. - LLMSettingsWidget: Delete Selected / Remove All follow ModelDownloader::isDownloadingChanged (a delete also removes the .part an active download is writing) and refresh after a deferred rescan. - LLMWorker: the reply is capped to the context positions left after the prompt; a prompt is rejected only when none remain, instead of a fixed 32-token headroom that still let the loop run into "context full". - AIAgentManager: systemPromptWithinBudget trims a LOCAL copy of the capability list — one oversized prompt no longer shrinks the task's capabilities for every later round. QRegularExpression include added. - AICapabilityRegistry: the colour-name coercion warning names the colour (it read the already-replaced RGB array). - LLMSettingsWidget_test: the #1052 test moved inside ENABLE_LOCAL_LLM. Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
… six "image not found" failures Field finding: "create a f22 raptor scene" planned generate_mesh_from_image with ~/Downloads/f22_raptor.png — a file that never existed — and every repair round guessed another path (.jpg, .png again) until the stuck detector stopped the task with nothing made. - executeNext: repairMissingImageInput drops a non-existent image_path before the call and, when no prompt was given, turns the request's subject into the tool's text prompt (subjectFromGoal: "create a f22 raptor scene" → "f22 raptor"); the transcript and trace say so. - Planner rule 8: never invent file paths; image_path is the user's real image, prompt is for things that do not exist yet. - Replan prompt: a "not found / does not exist / no such file" failure adds an explicit "do NOT guess another path — use prompt" hint. - Tool schema: image_path says "only a file that really exists". Tests: AIAgentSubject.* (subject extraction, the repair's four cases) and AgentFixture.InventedImagePathIsRepairedBeforeTheToolRunsAndTheTaskSucceeds (one call, no image_path, prompt "f22 raptor", task Completed). Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
…ead of freezing it Generating a mesh froze the whole window for minutes: the agent drives tools synchronously on the main thread and generate_mesh_from_image is a long ONNX pipeline. The work cannot just move to a worker — MeshGenBuilder is Ogre and main-thread-only — so the fix is to report and pump from inside it. - MCPServer::toolProgress(tool, stage, done, total), driven from the predictor's existing ProgressFn (already called many times per stage). The same callback pumps processEvents(ExcludeUserInputEvents) at ~20 Hz, so the window keeps painting and no click can re-enter a tool mid-run. - The image phase already spun nested event loops; its SDManager sampling ticks are relayed to the same signal so the bar moves there too. - McpToolExecutor relays it to AIAgentManager::reportToolProgress → stepProgressLabel / stepProgress (ignored when idle, cleared around every tool call); the chat panel's plan card draws a labelled bar, indeterminate when the total is unknown. Test: AgentFixture.HeavyToolProgressIsExposedWhileBusyAndClearedBetweenSteps covers the idle-report guard, the fraction, the indeterminate case and the clear between steps. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
…writes confirm; deferred deletes report their real outcome CodeRabbit review round on the progress fix: - The pump excluded user input, so the Stop button could not be clicked during the very operation it exists to abort — and the panel had no Stop button at all. The pump now delivers all events (re-entry is prevented by the agent running one step at a time), MCPServer::requestToolCancel sets a flag the predictor's progress callback returns as false, and AIAgentManager::cancel() forwards to the executor while Executing. The image phase checks the same flag before the longer 3D phase starts. - qml: a Stop button beside the thinking dots; the plan card no longer requires planCardPinned (nothing ever set it, so the finished plan and any failure reason disappeared the moment the run ended). - take_screenshot is read-only for the SCENE but writes its `path`: the overwrite check now runs before the read-only gate, so it asks before clobbering an existing file. - A deferred deletion (the active model's file, removed only once the worker released it) reported "Deleted" before the removal happened and ignored a failure. LLMManager::deferredDeletionFinished(removed, failed) carries the real outcome; the widget reports from it and says "unloading…" meanwhile. Tests: AgentFixture.CancelDuringAToolCallAsksTheRunningToolToStop and take_screenshot overwrite cases in the registry suite. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
…ctive window unit-tests-linux failed: ClickFocusFilter expected a fresh FocusIn after the filter re-asserts focus on an already-focused widget. Qt dispatches QFocusEvent only inside an ACTIVE window, and the CI display (Xvfb, no window manager) never activates one — the focus widget still changes but no focus event is delivered, so the assertion passed locally and failed on Linux. The "5954/5955 discovered tests executed" guard then failed too, so one root cause was counted as two suite failures. The test now asserts the clearFocus()+setFocus() pair through the focus-OUT count (only clearFocus can produce it) plus the resulting focus state, and gates the event-count assertion on window.isActiveWindow(). Verified both ways: native macOS (window activates → the guarded branch runs) and QT_QPA_PLATFORM=offscreen (no activation, as on CI). Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
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Slice 1 of #1000 (AI agent harness v3) / #818 Track C6. Closes #1001, closes #1002, closes #1003. Delivers #1021 items (a) tool coverage from the live schema, (b) plans + one undo group + abort on failure, (c) per-turn scene context, (d) safety rails, and the recommendation half of (e).
What
AIAgentTypes—Plan/Step/Observation/Limits. All task state lives here, never in the prompt; the prompt is rebuilt from it on every planner call. The final chat message is the deterministicsummarize()(steps, statuses, parsed facts, artifacts, warnings), so a flaky model cannot misreport what happened.AICapabilityRegistry(AI Agent: capability registry and dynamic MCP/tool routing #1002) — the ~170 MCP tools grouped into 20 capabilities (scene, scene_io, view, materials, lighting, textures_ai, mesh_optimize, uv, rigging, segmentation, generation_3d, animation, motion_ai, morph_pose, node_animation, paint, mocap, cloud, ps1, other). The planner sees a 20-line capability index plus the full per-tool docs only for the keyword-routed capabilities, and may reply{"need_capabilities": [...]}to get more before planning. Docs are generated frombuildToolsList(), so they cannot drift. The v1 loop hard-coded a 19-tool subset that silently excluded rigging, segmentation and generation.validateArgumentschecks every planned call against the JSON schema before it reaches the server (required, types, enums; chatty output like"2, 2, 2"/"yes"is coerced with a warning). An invalid call becomes aninvalid_argumentsobservation and a replan, never a tool call.AIAgentManager(AI Agent: introduce AIAgentManager task state machine and structured observations #1001) —Planning → Executing → Observing → (Replanning | AwaitingConfirmation) → Completed | Failed | Cancelled. A failing step is retried once, then the planner repairs the tail ({"steps":[...]}or{"done":true,"summary"}), bounded byLimits(12 steps, 2 replans, 2 planner retries). The same action failing twice stops the task. Cancel works in every state. OneQUndoStackmacro per task, opened on the first non-read-only step and closed on every terminal path. Destructive steps (deletes, geometry rewrites, overwriting an existing file) pause for Allow / Always allow / Skip step unless trusted mode is on.AIChatManager.agentMode(default on) routessendMessageto the agent; the v1 loop stays one click away.McpToolExecutorandLlmPlannerBackendare the production implementations of the injected interfaces.Tests (headless, no LLM, no Ogre)
AIAgentManager_test.cpp: 5 dependent steps with observable state and ONE undo group; retry then success; persistent failure → one replan → repaired tail succeeds; repeated identical failure detected; replan budget exhausted closes the undo group; cancel between steps and during planning; invalid arguments never reach the tool; unknown tool rejected; destructive step waits for confirmation (deny / approve / trusted); planner asks for more capabilities; question answered without tools; malformed planner output retried then fails; refuses without a model or while busy; scene context injected.AICapabilityRegistry_test.cpp: grouping, prompt fragments from the schema, keyword routing, validation and coercion, destructive reasons, read-only set, taxonomy sanity.Mutation-checked: removing the confirmation gate, the repeated-failure detection, the argument validation, or the undo
endMacroeach fails exactly the intended test(s).Fixes from live testing (after the first review)
Everything below came out of actually driving the agent with Qwen3 4B/14B, not from review:
select_entitytool, aSelected:line inget_scene_info, and a planner rule.apply_materialfor a missingmaterialalthough the handler acceptsmaterial_name. A validator must never be stricter than its tool: aliases and camelCase are normalised before the required check, and a rejection lists the keys that were passed.llama_n_ctx, publishes it, and the agent budgets every prompt against it (drop history → fewer capabilities → truncate scene → hard cut)..objasimage_path; the schema, the handler and the validator now all refuse it and nameload_mesh.~/Downloads/f22_raptor.png, which never existed, and the repair rounds guessed.jpgthen.pngagain until the stuck detector stopped the task with nothing made. A non-existentimage_pathis now dropped before the call and, when no prompt was given, the request's subject becomes the tool's text prompt ("f22 raptor"), so text → image → 3D runs in one call. Planner rule 8 and the replan hint say never to guess a path.MeshGenBuilderis Ogre, main-thread only), so the predictor's existing progress callback now reports its stage and pumps the event loop, and the chat panel draws a labelled progress bar across both the image and 3D phases.cancel()reaches the running tool through the executor, the predictor aborts at its next callback, and the panel has a Stop button. Re-entry is prevented structurally (one step at a time), not by dropping clicks.cloud_upload/cloud_login/cloud_logoutconfirm in untrusted mode (nothing local is destroyed, but the data leaves the machine);take_screenshotconfirms before overwriting a file; deleting the loaded model's file waits for the worker to release it and reports the real outcome; the reply is capped to the context left after the prompt;Remove Allcovers.bintoo.FocusIn, which Qt only delivers inside an active window — true on a desktop, false under Xvfb. It now asserts theclearFocus()+setFocus()pair and gates the event assertion on window activation.Not in this slice (children of #1000)
#1004 local VLM viewport inspection (mtmd is already linked for the captioner), #1005 model lifecycle / memory budget, #1006 verifier layer, #1007 e2e benchmark, #1008 batch factory. #1021 (e) one-click download of the recommended GGUF already exists in AI Model Settings → Recommended.
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Summary by CodeRabbit