Add Quick Start endpoint choices for subscription plan providers, require explicit WebSocket confirmation, and require a WebUI password when enabling the WebSocket channel. Update docs to route Quick Start users through the WebUI instead of agent -m.
Drive Quick Start provider choices from the provider registry instead of a short allowlist. Clean up parenthetical wizard labels and keep the beginner docs in sync.
Remove automatic Quick Start model discovery. Users now explicitly enter the model ID after choosing the provider and API key, and incomplete Quick Start input does not leave partial provider config behind.
Cleanup-only simplification: remove a one-entry dispatch table, avoid unused provider tuple unpacking, and strip the selected model once before storing it.
Remove the PR changes that made nanobot onboard default to the wizard, added --defaults, added non-TTY fallback behavior, and changed the Docker smoke command. Keep Quick Start available through nanobot onboard --wizard.
Maintainer edit: replace Quick Start key/base detection with an explicit provider-first flow. Users choose the provider that issued the API key, paste the key, and only custom OpenAI-compatible setups ask for a base URL.
Maintainer edit: restart the Quick Start flow around an API-key-first path without recommending OpenRouter or DeepSeek. Detect unique key prefixes locally, fall back to a user-provided base URL, and only fetch models from that approved URL.
Maintainer edit: restart the Quick Start default around a mainland-friendly provider instead of making OpenRouter the first-run dependency. Update wizard copy, default preset, focused tests, and beginner docs to use DeepSeek with the current deepseek-v4-flash model.
Maintainer edit: continue the wizard simplification pass by making Quick Start save after the API key path, hiding save/summary actions until they are needed, removing failed-key side effects, and aligning beginner docs with the local WebUI path.
Maintainer edit: collapse the first-run wizard to an API-key-only Quick Start and move lower-frequency provider, model, channel, gateway, and tool settings behind Advanced Settings.
Maintainer edit: reduce the default onboarding path to a recommended local WebUI setup that only asks for an OpenRouter key, while keeping the detailed provider/channel flow available for advanced setup.
Maintainer edit: make explicit --defaults refresh existing configs without prompting when no TTY is available, preserving user values for CI and Docker runs.
maintainer edit: remove the Feishu-specific config-file guard from the shared CLI login command. Feishu now follows the Weixin pattern where channel.login owns its setup and persistence.
maintainer edit: make gateway execution, WebUI automation listing, and delete protection agree on the new bound cron shape. Legacy delivery payloads that carry sessionKey are excluded from the WebUI-bound automation surface.
maintainer edit: keep existing cron jobs with legacy delivery fields on the legacy execution path, even when they already carry a sessionKey. This preserves deliver=false behavior and channel-specific routing metadata for upgraded jobs.
* refactor(dream): replace two-phase Dream class with simple cron + process_direct
- Remove the heavyweight Dream class (AgentRunner-based two-phase system)
from nanobot/agent/memory.py
- Delete dream_phase1.md and dream_phase2.md templates
- New dream.md template serves as the consolidation prompt
- Cron callback uses agent.process_direct(prompt, session_key=\"dream\")
instead of agent.dream.run()
- Always performs git auto_commit after execution
- /dream command updated to use process_direct + git commit
- DreamConfig kept for backward compatibility; deprecated fields
(model_override, max_batch_size, max_iterations, annotate_line_ages)
are ignored but accepted in config
- interval_h remains configurable via agents.defaults.dream.interval_h
- Update tests and webui settings to match new architecture
* feat(loop): add ephemeral mode to process_direct, skip history writes for Dream
When ephemeral=True, _state_save skips enforce_file_cap (which calls
raw_archive -> append_history) and consolidator.maybe_consolidate_by_tokens.
This prevents Dream sessions from creating a positive feedback loop where
they process their own output. The session IS still saved to disk.
* fix(loop): skip extra hooks for ephemeral sessions (Dream)
* feat(dream): per-run timestamped sessions with rotation for WebUI
* test(config): restore DreamConfig schedule and alias tests
* fix(dream): include LLM response summary in git auto-commit message
The old two-phase Dream class included the Phase 1 analysis in the git
commit message body. The new single-phase version lost this. Restore it
by extracting resp.content from the process_direct return value and
appending it to the commit message in both the cron handler and the
/dream command.
* fix(test): accept ephemeral kwarg in test_openai_api fake_process
* refactor(dream): merge dream_session.py into MemoryStore
The standalone dream_session.py module only contained three small helpers
that all revolve around MemoryStore concerns (session keys, commit messages,
file pruning). Fold them into MemoryStore as @staticmethod to reduce
indirection and avoid a 35-line module with no independent reason to exist.
* fix(test): address code review — patch correct instance, use actual function
- Fix test_ephemeral_skips_raw_archive to patch loop.context.memory
instead of the fixture's separate MemoryStore instance
- Fix TestDreamCommitMessage to call MemoryStore.build_dream_commit_message
instead of reimplementing the logic inline
- Move Dream helpers in memory.py above the Consolidator section comment
to avoid misleading visual boundary
* fix(dream): gate cursor advancement and restrict tools
maintainer edit: Dream now processes backlog from the oldest unprocessed entries, only advances the cursor after a completed ephemeral run, and uses a restricted file-only tool registry for background consolidation.
* fix(dream): skip idle compact for dream sessions
Dream runs use internal dream:* sessions that are pruned by Dream retention. Exclude them from AutoCompact scheduling, archive execution, and summary injection so idle-session compaction cannot truncate Dream transcripts.
* fix(dream): keep batched history isolated
* feat(dream): tag archived memory for single-phase Dream
---------
Co-authored-by: Xubin Ren <52506698+Re-bin@users.noreply.github.com>
- Remove ## Completed section from HEARTBEAT.md template; completed
tasks should be deleted, not accumulated
- Change in_active_section from tri-state (None/True/False) to bool
(True/False) so stray text before any ## heading no longer triggers
heartbeat
- Add test cases for stray pre-heading text and ## Notes section
- Update docs/chat-commands.md to reference ## Active Tasks
Remove standalone nanobot/heartbeat/ service and replace it with an
auto-registered system cron job on gateway startup. Key behaviors preserved:
- HeartbeatConfig (enabled, interval_s, keep_recent_messages) remains in
GatewayConfig for backward compatibility.
- On startup, if enabled, a system cron job "heartbeat" is registered with
schedule derived from interval_s.
- HEARTBEAT.md is checked on each tick; empty/template-identical files skip
to avoid wasting LLM calls.
- Post-run evaluate_response and session history truncation
(keep_recent_messages) are retained.
- Delivery target selection, deliverable filtering, and preamble guidance
are preserved.
Files removed:
- nanobot/heartbeat/__init__.py
- nanobot/heartbeat/service.py
- tests/heartbeat/*
- tests/agent/test_heartbeat_service.py
Templates and docs updated to reflect cron-based usage.