Adds ImageGenerationProvider ABC with shared __init__, _http_post(), and
_require_images(). Introduces _IMAGE_GEN_PROVIDERS registry with
register/get/image_gen_provider_configs() helpers.
Four existing providers (OpenRouter, AIHubMix, Gemini, MiniMax) now inherit
from the base class and self-register. Adding a new provider only requires
writing one class + one registration line.
Eliminates if/else chains in the tool dispatch and hardcoded provider config
dicts in commands.py (3 sites) and nanobot.py (1 site). Fixes the agent CLI
command missing image_generation_provider_configs entirely.
Also simplifies test monkeypatch targets to patch the registry lookup.
Adds GeminiImageGenerationClient covering both Imagen 4 (:predict) and
Gemini Flash (:generateContent), wires the gemini ProviderConfig through
the SDK, API server, and gateway entry points, and updates the
image-generation docs and skill. Errors from the Gemini endpoints are
logged and surface with the HTTP status and parsed message instead of an
empty string.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Add MiniMaxImageGenerationClient with support for:
- Text-to-image generation via MiniMax image-01 model
- Reference image support (subject_reference)
- Aspect ratio selection
- Proper error handling aligned with existing providers
Wire up MiniMax provider config in ImageGenerationTool, gateway,
serve, and Nanobot class.
Extract the [M] Model Presets interactive CRUD screen from PR #3696
and adapt it to the current main branch schema (fallback_models
instead of fallback_presets). Adds preset cache, field handlers for
model_preset/provider/fallback_models, and 9 new tests.
* feat(long-task): add LongTaskTool for multi-step agent tasks
Implements a meta-ReAct loop where long-running tasks are broken into
sequential subagent steps, each starting fresh with the original goal
and progress from the previous step. This prevents context drift when
agents work on complex, multi-step tasks.
- Extract build_tool_registry() from SubagentManager for reuse
- Add run_step() for synchronous subagent execution (no bus announcement)
- Add HandoffTool and CompleteTool as signal mechanisms via shared dict
- Add LongTaskTool orchestrator with simplified prompt (8 iterations/step)
- Register LongTaskTool in main agent loop
- Add _extract_handoff_from_messages fallback for robustness
* fix(long-task): add debug logging for step-level observability
* feat(long-task): major overhaul with structured handoffs, validation, and observability
- Structured HandoffState: HandoffTool now accepts files_created,
files_modified, next_step_hint, and verification fields instead of
a plain string. Progress is passed between steps as structured data.
- Completion validation round: After complete() is called, a dedicated
validator step runs to verify the claim against the original goal.
If validation fails, the task continues rather than returning
a false completion.
- Dynamic prompt system: 3 Jinja2 templates (step_start, step_middle,
step_final) selected based on step number. Final steps get tighter
budget and stronger "wrap up" guidance.
- Automatic file change tracking: Extracts write_file/edit_file events
from tool_events and injects them into the next step's context if
the subagent forgot to report them explicitly.
- Budget tracking & adaptive strategy: Cumulative token usage is tracked
across steps. Per-step tool budget drops from 8 to 4 in the last
two steps to force handoff/completion.
- Crash retry with graceful degradation: A step that crashes is retried
once. Persistent crashes terminate the task and return partial progress.
- Full observability hooks for future WebUI integration:
- set_hooks() with on_step_start, on_step_complete, on_handoff,
on_validation_started, on_validation_passed, on_validation_failed,
on_task_complete, on_task_error, and catch-all on_event.
- Readable state properties: current_step, total_steps, status,
last_handoff, cumulative_usage, goal.
- inject_correction() allows external code to send user corrections
that are injected into the next step's prompt.
- run_step() accepts optional max_iterations for dynamic budget control.
All 27 long-task tests and 11 subagent tests pass.
* test(long-task): add boundary tests and fix race conditions
- Add 7 edge-case tests: validation crash resilience, hook exception safety, mid-run correction injection, FIFO correction ordering, explicit file changes overriding auto-detection, final budget for max_steps=1, and dynamic budget switching boundaries
- Fix assertion in test_long_task_completes_after_multiple_handoffs to match exact prompt format
- Remove asyncio timing hack from test_state_exposure
- Add asyncio.sleep(0) yield in test_inject_correction_during_execution to prevent race between signal injection and step continuation
- All 34 tests passing
* fix(long-task): address code review findings
- Declare _scopes = {"core"} explicitly to prevent recursive nesting in subagent scope
- Document fragile coupling in _extract_file_changes: path extraction depends on
write_file/edit_file detail format; add debug log for unexpected formats
- Align final-template threshold (max_steps - 2) with budget switch threshold
- Eliminate hasattr(self, "_state") in _reset_state by initializing in __init__
* fix(long-task): honor final signal and file tracking
Co-authored-by: Cursor <cursoragent@cursor.com>
* feat(long-task): improve prompt structure and agent contract
- Expand LongTaskTool.description to instruct parent agent on goal
construction, return value semantics, and how to handle results.
- Expand CompleteTool.description to emphasize that the summary IS the
final answer returned to the parent agent.
- Prefix validated return value with an explicit "final answer" directive
to stop parent agent from re-running work.
- Redesign step_start.md: Step 1 is now explicitly for exploration,
planning, and skeleton-building. complete() is discouraged.
- Remove bulky payload debug logging from _emit(); add targeted
info/warning/error logs at key state transitions instead.
- Add signal_type to HandoffState for cleaner signal detection.
* test(long-task): expect wrapped completion message after validation
Align assertions with LongTaskTool final return shape on main.
Co-authored-by: Cursor <cursoragent@cursor.com>
* feat(webui): turn timing strip, latency, and session-switch restore
- Agent loop: publish goal_status run/idle for WebSocket turns; attach
wall-clock latency_ms on turn_end and persisted assistant metadata.
- WebSocket channel: forward goal_status and latency fields to clients.
- NanobotClient: track goal_status started_at per chat without requiring
onChat; useNanobotStream restores run strip when returning to a chat.
- Thread UI: composer/shell viewport hooks for run duration and latency;
format helpers and i18n strings.
- MessageBubble: drop trailing StreamCursor (layout artifact vs block markdown).
- Builtin / tests: model command coverage, websocket and loop tests.
Covers multi-session UX and round-trip timing visibility for the WebUI.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix: keep message-tool file attachments after canonical history hydrate
- MessageTool records per-turn media paths delivered to the active chat.
- nanobot.utils.session_attachments stages out-of-media-root files and
merges into the last assistant message before save (loop stays a thin call).
- WebUI MediaCell: use a signed URL as a real download link when present.
Fixes attachments flashing then vanishing on turn_end when paths lived
outside get_media_dir (e.g. workspace files).
Co-authored-by: Cursor <cursoragent@cursor.com>
* feat(webui): agent activity cluster, stable keys, LTR sheen labels
- Group reasoning and tool traces in AgentActivityCluster with i18n summaries
- Stabilize React list keys for activity clusters (first message id anchor)
- Replace background-clip shimmer with overlay sheen for streaming labels
- ThreadMessages/MessageList integration and locale strings
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(webui): render assistant reasoning with Markdown + deferred stream
- Use MarkdownText for ReasoningBubble body (same GFM/KaTeX path as replies)
- Apply muted/italic prose tokens so thinking stays visually subordinate
- useDeferredValue while reasoningStreaming to ease parser work during deltas
- Preload markdown chunk when trace opens; add regression test with preloaded renderer
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(webui): default-collapse agent activity cluster while Working
Outer fold no longer auto-expands during isTurnStreaming; user opens to see traces.
Header sheen and live summary unchanged.
Co-authored-by: Cursor <cursoragent@cursor.com>
* feat(long_task): cumulative run history, file union, and prompt tuning
Inject cross-step summaries and merged file paths into middle/final step
templates so chains do not lose early context. Strip the last run-history
block when it duplicates Previous Progress to save tokens. Add optional
cumulative_prompt_max_chars and cumulative_step_body_max_chars parameters
with clamped defaults.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(webui): session switch keeps in-flight thread and replays buffered WS
Save the prior chat message list to the per-chat cache in a layout effect
when chatId changes (before stale writes could corrupt another chat).
Skip one post-switch layout cache tick so we do not snapshot the wrong tab.
Buffer inbound events per chat_id when no onChat subscriber is registered
(e.g. user focused another session) and drain on resubscribe up to a cap,
so streaming deltas are not lost while off-tab.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(webui): snap thread scroll to bottom on session open (no smooth glide)
Use scroll-behavior auto on the viewport, instant programmatic scroll when
following new messages and on scrollToBottomSignal. Keep smooth only for
the explicit scroll-to-bottom button.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(webui): respect manual scroll-up after opening a session
Track when the user leaves the bottom with a ref and skip ResizeObserver
and deferred bottom snaps until they return or the conversation is reset.
Remove the time-based force-bottom window that overrode atBottom.
Multi-frame scrollToBottom honours the same guard unless force (scroll button).
Co-authored-by: Cursor <cursoragent@cursor.com>
* Publish long_task UI snapshots on outbound metadata
- Add OUTBOUND_META_AGENT_UI (_agent_ui) for channel-agnostic structured state
- LongTaskTool publishes {kind: long_task, data: snapshot} on the bus with _progress
- WebSocket send forwards metadata as agent_ui for WebUI clients
- Tests for bus payload, WS frame, and progress assertions
- Fix loop progress tests: ignore _goal_status in streaming final filter and
avoid brittle outbound[-1] ordering after goal status idle messages
Co-authored-by: Cursor <cursoragent@cursor.com>
* feat: WebUI long_task activity card and resilient history merge
Add optional ui_summary to the long_task tool for one-line UI labels. Stream
long_task agent_ui into a dedicated message row with timeline, markdown peek,
and a right sheet for details. Merge canonical history after turn_end while
re-inserting long_task rows before the final assistant reply. Collapse
duplicate task_start/step_start steps in the timeline and extend i18n.
Co-authored-by: Cursor <cursoragent@cursor.com>
* refactor: align long_task with thread_goal and drop orchestrator UI
- Persist sustained objectives via session metadata (long_task / complete_goal); no subagent wiring or tool-driven agent_ui payloads.\n- Remove WebUI long-task activity UI, types, and translations; history merge preserves trace replay only, with legacy long_task rows normalized to traces.\n- Drop long_task prompt templates and get_long_task_run_dir; add webui thread disk helper for gateway persistence tests.
Co-authored-by: Cursor <cursoragent@cursor.com>
* feat(agent): thread goal runtime context, tools, and skill
- Add thread_goal_state helper and mirror active objectives into Runtime Context
- Wire loop/context/memory/events as needed for goal metadata in turns
- Expand long_task / complete_goal semantics (pivot/cancel/honest recap)
- Add always-on thread-goal SKILL.md; align /goal command prompt
- Tests for context builder and thread goal state
- Remove unused webui ChatPane component
Co-authored-by: Cursor <cursoragent@cursor.com>
* feat(thread-goal): add websocket snapshot helper and publish goal updates from long_task
Introduce thread_goal_ws_blob for bounded JSON snapshots, attach snapshots to
websocket turn_end metadata in AgentLoop, and let long_task fan-out dedicated
thread_goal frames on the websocket channel after persisting session metadata.
Co-authored-by: Cursor <cursoragent@cursor.com>
* feat(channels): websocket thread_goal frames, turn_end replay, and session API scrub for subagent inject
Emit thread_goal events and optional thread_goal on turn_end; scrub persisted
subagent announce blobs on GET /api/sessions/.../messages and shorten session
list previews so WebUI does not surface full Task/Summarize scaffolding.
Co-authored-by: Cursor <cursoragent@cursor.com>
* feat(webui): merge ephemeral traces per user turn when reconciling canonical history
Preserve disk/live trace rows inside the matching user–assistant segment instead
of stacking every trace before the final assistant reply (fixes inflated tool
counts after refresh or session switch).
Co-authored-by: Cursor <cursoragent@cursor.com>
* feat(webui): show assistant reply copy only on the last slice before the next user turn
Avoid duplicate copy affordances on intermediate assistant bubbles that precede
more agent activity in the same turn (tools or further assistant text).
Co-authored-by: Cursor <cursoragent@cursor.com>
* feat(webui): thread_goal stream plumbing, composer goal strip, sky glow, and client-side subagent scrub projection
Track thread_goal and turn_goal snapshots in NanobotClient, hydrate React state
from thread_goal frames and turn_end, surface objective/elapsed in the composer,
add breathing sky halo CSS while goals are active, mirror server scrub logic on
history hydration and webui_thread snapshots, and extend tests/client mocks.
Co-authored-by: Cursor <cursoragent@cursor.com>
* feat(channels): add Slack Socket Mode connect timeout with actionable timeout errors
Abort hung websockets.connect handshakes after a bounded wait, log REST-vs-WSS
guidance, surface RuntimeError to channel startup, and log successful WSS setup.
Co-authored-by: Cursor <cursoragent@cursor.com>
* webui: expand thread goal in composer bottom sheet
Add ChevronUp control on the run/goal strip that opens a bottom Sheet
with full ui_summary and objective. Inline preview logic in RunElapsedStrip,
add i18n strings across locales, and a composer unit test.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(webui): widen dedupeToolCallsForUi input for session API typing
fetchSessionMessages types tool_calls as unknown; accept unknown so tsc
build passes when passing message.tool_calls through.
Co-authored-by: Cursor <cursoragent@cursor.com>
* refactor(agent): extract WebSocket turn run status to webui_turn_helpers
* refactor(skills): rename thread-goal to long-task and document idempotent goals
* feat(skills): rename sustained-goal skill to long-goal and tighten long_task guidance
* chore: remove unused subagent/context/router helpers
* feat(session): rename sustained goal to goal_state and align WS/WebUI
- Move helpers from agent/thread_goal_state to session/goal_state:
GOAL_STATE_KEY, goal_state_runtime_lines, goal_state_ws_blob, parse_goal_state.
- Session metadata now uses "goal_state"; still read legacy "thread_goal";
long_task writes drop the legacy key after save.
- WebSocket: event/field goal_state, _goal_state_sync; turn_end carries goal_state;
accept legacy _thread_goal_sync/thread_goal inbound metadata for dispatch.
- WebUI: GoalStateWsPayload, goalState hook/client props, i18n keys goalState*.
- Runtime Context copy uses "Goal (active):" instead of "Thread goal".
* feat(agent): stream Anthropic thinking deltas and fix stream idle timeout
* refactor(webui): transcript jsonl as sole timeline source
* fix(agent): reject mismatched WS message chat_id and stream reasoning deltas
* feat(webui): hydrate sustained goal and run timer after websocket subscribe
* chore(webui,websocket): remove unused fetch helpers and legacy thread_goal WS paths
* Raise default max_tokens and context window in agent schema.
Align AgentDefaults and ModelPresetConfig with typical Claude-scale usage
(32k completion budget, 256k context window) and update migration tests.
Co-authored-by: Cursor <cursoragent@cursor.com>
* feat(gateway): bootstrap prefers in-memory model; clarify websocket naming
* fix(websocket): websocket _handle_message passes is_dm; refresh /status test expectations
---------
Co-authored-by: chengyongru <2755839590@qq.com>
Co-authored-by: chengyongru <chengyongru.ai@gmail.com>
Co-authored-by: Cursor <cursoragent@cursor.com>
CLI pairing commands (list/approve/deny/revoke) are fully replaceable by
`nanobot agent -m "/pairing ..."`, which routes through the same
CommandRouter and handle_pairing_command() backend. Removing them
cuts 86 lines of duplicate surface area without losing any functionality.
- Remove pairing_app and its 4 subcommands from cli/commands.py
- Update format_pairing_reply() to drop the "Via CLI" line
- Clear pending_user_turn after shortcut command persistence
- Guard is_allowed against None allow_from values
- Update pairing help text for two-arg revoke
- Reuse format_expiry in CLI pairing list
Replace the file-editing onboarding workflow with a chat-native pairing flow:
- New pairing store (nanobot/pairing/store.py) persists approved senders
and pending codes in ~/.nanobot/pairing.json.
- DM messages from unknown senders receive a short pairing code instead of
silent denial. Group chats remain silently ignored.
- Existing allowFrom semantics are fully preserved; approved pairing users
are merged at runtime so no config migration is needed.
- nanobot pairing list/approve/deny/revoke CLI commands for bootstrap and
emergency management.
- /pairing slash commands intercepted in-channel so owners can approve
senders without leaving the chat.
- is_dm flag added to BaseChannel._handle_message; Telegram, Discord and
WebSocket updated to pass it.
Closes#3768
Resolves conflicts after main landed the state-machine turn refactor
and the test_runner.py 9-file split:
- nanobot/agent/loop.py: take main's `_state_build`/`_persist_user_message_early`
flow; restore the `reasoning: bool` parameter on `_build_bus_progress_callback`
so the loop hook can mark progress as reasoning-channel without coupling to
the answer stream.
- nanobot/cli/stream.py: keep main's configurable `bot_name`/`bot_icon` header
while preserving the PR's `transient=True` Live + `self._console` routing
+ `_renderable()` final-render path that fixed TUI duplication.
- tests/agent/test_runner.py was deleted on main and split into 9 focused
files; relocated all 6 reasoning tests into a new `test_runner_reasoning.py`
matching the new layout, deduplicated the per-test `ReasoningHook` boilerplate
through a shared `_RecordingHook` helper.
Co-authored-by: Cursor <cursoragent@cursor.com>
Reasoning surfacing was split across three branches in runner.py plus
two separate streaming buffers (loop hook and runner progress stream),
with three independent display-side gates in the CLI. This collapsed
the policy into one source of truth and fixed two real bugs:
- Structured `reasoning_content` was suppressed whenever the answer was
streamed, because the runner gated emission on `streamed_content`.
Providers don't stream `reasoning_content`; it only arrives on the
final response, so the answer stream and the reasoning channel are
independent. Added `streamed_reasoning` to `AgentHookContext` to track
the right bit.
- `channels.showReasoning` was subordinated to `sendProgress`. They are
orthogonal — turning off progress streaming shouldn't silence
reasoning. Reworked the CLI gates accordingly.
Single-helper consolidation:
- `extract_reasoning(reasoning_content, thinking_blocks, content)`
returns `(reasoning_text, cleaned_content)` with a defined fallback
order: dedicated field → Anthropic thinking_blocks → inline
`<think>`/`<thought>` tags. Models that expose none of these
short-circuit to `(None, content)` — zero overhead.
- `IncrementalThinkExtractor` replaces the ad-hoc `emit_incremental_think`
function and its hand-rolled "emitted cursor" state in both the loop
hook and the runner progress stream.
Also documented the new `showReasoning` channel option in
docs/configuration.md and noted its independence from sendProgress.
Co-authored-by: Cursor <cursoragent@cursor.com>
Remove unused code confirmed dead via vulture scan, grep verification,
and coverage analysis:
- _get_bridge_dir (cli/commands.py): 82-line function with zero callers
- add_assistant_message (agent/context.py): method body never executed,
also removed now-unused build_assistant_message import
- _tool_parameters_schema (agent/tools/base.py): redundant copy of schema
already exposed via the `parameters` property
- MSTEAMS_REF_TTL_S (channels/msteams.py): unused constant (production
uses config.ref_ttl_days directly); inlined in test
- MESSAGE_TYPE_USER (channels/weixin.py): unused constant
- Add `ModelPresetConfig` schema for named model presets
- Add `model_presets` dict to `Config` and `model_preset` field to `AgentDefaults`
- Add `resolve_preset()` to return effective model params from preset or defaults
- Add `@model_validator` to reject unknown preset names
- Update `_match_provider()` to use resolved preset model/provider
- Update `make_provider()` and `provider_signature()` to use `resolve_preset()`
- Add `model_preset` property to `AgentLoop` for atomic runtime switching
- Update `AgentLoop.from_config()` to inject a runtime `default` preset
- Wire self-tool to inspect/clear preset state
- Update CLI display strings to show active preset
Both StreamRenderer instantiations in the agent command (single-message
mode and interactive mode) now read bot_name and bot_icon from
config.agents.defaults and forward them to the renderer.
This is the wiring step that makes the schema fields actually take
effect at runtime. With safe defaults of "nanobot" and "🐈", existing
users see no change.
Threads bot_name/bot_icon through ThinkingSpinner and StreamRenderer
with safe defaults that preserve current behavior.
- ThinkingSpinner uses bot_name in its status text
- StreamRenderer header is "<icon> <name>" when icon is set,
or just "<name>" when icon is empty
- Removes the now-unused __logo__ import (the cat emoji is the
default value of bot_icon, not a hardcoded constant)
Add show_reasoning config (default: False) to display model
thinking/reasoning content in the TUI during streaming. Reasoning
is emitted via a new emit_reasoning hook on AgentHook, gated by the
channels config. Display uses ✻ prefix with dim italic styling.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Route progress output through the Live's render hook to fix cursor
misalignment that caused content duplication. The root cause was that
progress/reasoning output used a separate Console instance, bypassing
Rich Live's process_renderables hook. Also fixes pre-existing issue
where multiple headers printed per agent turn.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
- Pop model and context_window_tokens from extra kwargs before
forwarding to __init__, allowing callers like _run_gateway to
pass snapshot-derived values instead of config defaults
- _run_gateway now explicitly passes model/context_window_tokens
from provider_snapshot to preserve pre-refactor behavior
Extract duplicated bus/provider/loop initialization from CLI commands
(serve, _run_gateway, agent) and Nanobot facade into a single
AgentLoop.from_config() classmethod.
- Remove _make_provider() from cli/commands.py and nanobot.py
- Remove inline provider creation in all three CLI entry points
- AgentLoop.from_config() creates MessageBus, calls make_provider(),
and assembles AgentLoop with all standard config-derived parameters
- Supports **extra overrides for callers that need custom args
(e.g. cron_service, session_manager, provider_snapshot_loader)
- Update tests to mock make_provider at nanobot.providers.factory
and add from_config classmethod to _FakeAgentLoop fixtures
This is PR 1/4 of the model-preset feature decomposition.
On Windows, prompt_toolkit produces lone surrogate code points (e.g.
🐈) for emoji input. These propagate through the message bus
and crash at json.dumps() / file write time because surrogates cannot
be encoded as UTF-8.
Extract _sanitize_surrogates() that round-trips through UTF-16 to
reconstruct paired surrogates into real characters (e.g. 🐈
→ 🐈), replacing unpaired surrogates with U+FFFD. Apply it at the CLI
input path and reuse in SafeFileHistory.
Fixes two related input-handling bugs in the onboard wizard:
1. _input_text treated "" as None, preventing users from clearing
optional string fields or entering empty strings intentionally.
2. _input_model_with_autocomplete used `if value else None`, which
discarded falsy values such as empty strings or 0.
To support clearing optional string fields, add _is_str_or_none() and
normalize empty strings to None inside _configure_pydantic_model only
when the field annotation is `str | None`. Required str fields keep
"" as a valid value.
Also included:
- Remember last selected item in provider/channel/model menus for
better UX when configuring multiple items.
- Rename _SIMPLE_TYPES and _MENU_DISPATCH to lowercase to follow
Python naming conventions (they are local variables, not constants).
- Remove unused imports in test file.
Extracted from PR #3358.
The config field was added but never passed from config to AgentLoop.
The value was always falling back to the default (40) regardless of
what was set in config.json.
Now passes tool_hint_max_length through all AgentLoop() call sites:
- nanobot/nanobot.py (main bot)
- nanobot/cli/commands.py (CLI agent, dev, webui commands)
Also adds documentation in docs/configuration.md.
Logout previously claimed to support github-copilot in --help text but had
no registered handler, so `provider logout github-copilot` failed with
"Logout not implemented". Add the handler, sharing token deletion with the
codex flow via `_delete_oauth_files`. Tighten handler-table types, fix the
codex test fixture filename, and cover github-copilot plus the unknown
provider path.
- Implement \
anobot provider logout <provider>\ to clear OAuth credentials.
- Add \_LOGOUT_HANDLERS\ registration mechanism mirroring login.
- Implement logout for \openai-codex\ by deleting local \oauth-cli-kit\ token and lock files.
- Fallback gracefully when attempting to logout from providers lacking local credentials or implementations.
- Fixes#2665
Keep provider retry wait messages on the interactive progress path so they do not fall through as assistant responses.
Co-authored-by: Cursor <cursoragent@cursor.com>
The max_messages config field in AgentDefaults was accepted by the
schema but never threaded through to the actual get_history() calls
in the agent loop. Both call sites in _process_message hardcoded the
default, so sessions with slow or local models accumulated unbounded
history that inflated prompt tokens and caused LLM timeouts.
Changes:
- Add max_messages field to AgentDefaults (default 0 = use built-in
constant, any positive value caps history replay)
- Store the value on AgentLoop and pass it to get_history() when
non-zero
- Wire the config through all three AgentLoop construction sites in
commands.py (gateway, API server, CLI chat)
- 14 focused tests covering schema validation, init storage, history
slicing, boundary alignment, integration wiring, and the
zero/default path
Three failure modes addressed:
1. Model reflects HEARTBEAT.md instructions back as output instead of
executing them ("HEARTBEAT.md has active tasks listed...")
2. Model narrates decision logic ("Best judgment call: stay quiet")
3. Model produces empty output for silence, runner treats it as failure,
finalization retry generates "couldn't produce a final answer" which
gets delivered to the user
Changes:
- Add _is_deliverable() pre-filter in HeartbeatService._tick() that catches
finalization fallback messages and leaked reasoning patterns before they
reach the evaluator
- Wrap Phase 2 task input with a delivery-awareness preamble telling the
model its output goes directly to the user's messaging app
- Add meta-reasoning suppression criterion to evaluator template
No changes to agent/loop.py, runner.py, providers, or config schema.
The old prompt framed cron firing as a "task triggered" status report,
which led the agent to reply with things like "Done ✅ 已提醒
U0AV8BJPV8D 喝水" — exposing the user id and reading like a system log
instead of a friendly reminder. Reword it to instruct the agent to
speak directly to the user and forbid status-style language.
Made-with: Cursor
Capture Slack thread metadata for cron and message-tool deliveries so replies stay in the originating thread, and hydrate first thread mentions with recent Slack context.
Made-with: Cursor
Only mark message-tool deliveries for channel-session recording while cron jobs are running, avoiding duplicate session writes during normal user turns.
Made-with: Cursor
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