The Rich console.status() spinner ('nanobot is thinking...') was not
cleared when tool call progress lines were printed during processing,
causing overlapping/garbled terminal output.
Replace the context-manager approach with explicit start/stop lifecycle:
- _pause_spinner() stops the spinner before any progress line is printed
- _resume_spinner() restarts it after printing
- Applied to both single-message mode (_cli_progress) and interactive
mode (_consume_outbound)
Closes#1956
Replace fire-and-forget consolidation with archive_messages(), which
retries until the raw-dump fallback triggers — making it effectively
infallible. /new now clears the session immediately and archives in
the background. Pending archive tasks are drained on shutdown via
close_mcp() so no data is lost on process exit.
PR #881 (commit 755e424) fixed the race condition between normal consolidation
and /new consolidation, but did so by making /new wait for consolidation to
complete before returning. This hurts user experience - /new should be instant.
This PR restores the original immediate-return behavior while keeping safety:
1. **Immediate return**: Session clears and user sees "New session started" right away
2. **Background archival**: Consolidation runs in background via asyncio.create_task
3. **Serialized consolidation**: Uses the same lock as normal consolidation via
`memory_consolidator.get_lock()` to prevent concurrent writes
If consolidation fails after session clear, archived messages may be lost.
This is acceptable because:
- User already sees the new session and can continue working
- Failure is logged for debugging
- The alternative (blocking /new on every call) hurts UX for all users
- Add CONTRIBUTING.md with detailed contribution guidelines
- Add branching strategy section to README.md explaining main/nightly branches
- Include maintainer information and development setup instructions
Phase 1 _decide() now includes "Current date/time: YYYY-MM-DD HH:MM UTC"
in the user prompt and instructs the LLM to use it for time-aware scheduling.
Without this, the LLM defaults to 'run' for any task description regardless
of whether it is actually due, defeating Phase 1's pre-screening purpose.
Closes#1929
Instead of adding a separate load_skill tool to bypass workspace restrictions,
extend ReadFileTool with extra_allowed_dirs so it can read builtin skill paths
while keeping write/edit tools locked to the workspace. Fixes the original issue
for both main agent and subagents.
Made-with: Cursor
When restrictToWorkspace is enabled, the agent cannot read builtin skill
files via read_file since they live outside the workspace. This adds a
dedicated load_skill tool that reads skills by name through the SkillsLoader,
which accesses files directly via Python without the workspace restriction.
- Add LoadSkillTool to filesystem tools
- Register it in the agent loop
- Update system prompt to instruct agent to use load_skill instead of read_file
- Remove raw filesystem paths from skills summary
Replace the static provider-level supports_vision check with a
reactive fallback: when a model returns an image-unsupported error,
strip image_url blocks from messages and retry once. This avoids
maintaining an inaccurate vision capability table and correctly
handles gateway/unknown model scenarios.
Also extract _safe_chat() to deduplicate try/except boilerplate
in chat_with_retry().
- Add field to ProviderSpec (default True)
- Add and methods in LiteLLMProvider
- Filter image_url content blocks in before sending to non-vision models
- Reverts session-layer filtering from original PR (wrong layer)
This fixes the issue where switching from Claude (vision-capable) to
non-vision models (e.g., Baidu Qianfan) causes API errors due to
unsupported image_url content blocks.
The provider layer is the correct place for this filtering because:
1. It has access to model/provider capabilities
2. It only affects non-vision models
3. It preserves session layer purity (storage should not know about model capabilities)
With custom_llm_provider kwarg handling routing, the openrouter/ prefix
caused model names like anthropic/claude-sonnet-4-6 to become
openrouter/anthropic/claude-sonnet-4-6, which OpenRouter API rejects.
- Add nanobot/utils/evaluator.py: lightweight LLM tool-call to decide notify/silent after background task execution
- Remove magic token injection from heartbeat and cron prompts
- Clean session history (no more <SILENT_OK> pollution)
- Add tests for evaluator and updated heartbeat three-phase flow
Appends a strict instruction to background task prompts (cron and heartbeat)
directing the agent to return a `<SILENT_OK>` token if there is nothing
material to report. Adds conditional logic to intercept this token and
suppress the outbound message to the user, preventing notification spam
from autonomous background checks.
Appends a strict instruction to background task prompts (cron and heartbeat)
directing the agent to return a `<SILENT_OK>` token if there is nothing
material to report. Adds conditional logic to intercept this token and
suppress the outbound message to the user, preventing notification spam
from autonomous background checks.
Replace platform-specific shell=True logic with shutil.which('npm') to
resolve the full path to the npm executable. This is cleaner because:
- No shell=True needed (safer, no shell injection risk)
- No platform-specific branching (sys.platform checks removed)
- Works identically on Windows, macOS, and Linux
- shutil.which() resolves npm.cmd on Windows automatically
The npm path check that already existed in _get_bridge_dir() is now
reused as the resolved path for subprocess calls. The same pattern is
applied to channels_login().
On Windows, npm is installed as npm.cmd (a batch script), not a direct
executable. When subprocess.run() is called with a list like
['npm', 'install'] without shell=True, Python's CreateProcess cannot
locate npm.cmd, resulting in:
FileNotFoundError: [WinError 2] The system cannot find the file specified
This fix adds a sys.platform == 'win32' check before each npm subprocess
call. On Windows, it uses shell=True with a string command so the shell
can resolve npm.cmd. On other platforms, the original list-based call is
preserved unchanged.
Affected locations:
- _get_bridge_dir(): npm install, npm run build
- channels_login(): npm start
No behavioral change on Linux/macOS.
Merge the latest main branch into the Telegram media filename fix and keep the file_unique_id-based download path on top of the refactored media handling and newer Telegram tests.
Made-with: Cursor
- test_channel_plugins: fix assertion logic for discoverable channels
- test_filesystem_tools: normalize path separators for Windows
- test_tool_validation: use python to generate output, avoid cmd line limits
