- Introduced a helper method `_for_each_hook_safe` to reduce code duplication in hook method implementations.
- Updated error logging to include the method name for better traceability.
- Improved the `SkillsLoader` class by adding a new method `_skill_entries_from_dir` to simplify skill listing logic.
- Enhanced skill loading and filtering logic, ensuring workspace skills take precedence over built-in ones.
- Added comprehensive tests for `SkillsLoader` to validate functionality and edge cases.
DDGS's internal `timeout=10` relies on `requests` read-timeout semantics,
which only measure the gap between bytes — not total wall-clock time.
When the underlying HTTP connection enters CLOSE-WAIT or the server
dribbles data slowly, this timeout never fires, causing `ddgs.text` to
hang indefinitely via `asyncio.to_thread`.
Since `asyncio.to_thread` cannot cancel the underlying OS thread, the
agent's session lock is never released, blocking all subsequent messages
on the same session (observed: 8+ hours of unresponsiveness).
Fix:
- Add `timeout` field to `WebSearchConfig` (default: 30s, configurable
via config.json or NANOBOT_TOOLS__WEB__SEARCH__TIMEOUT env var)
- Wrap `asyncio.to_thread` with `asyncio.wait_for` to enforce a hard
wall-clock deadline
Closes#2804
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The same test function name appeared twice; Python silently shadows the
first definition so it never ran. Keep the version that also asserts
the request URL contains "s.jina.ai".
Made-with: Cursor
Dream Phase 2 uses fail_on_tool_error=True, which terminates the entire
run on the first tool error (e.g. old_text not found in edit_file).
Normal agent runs default to False so the LLM can self-correct and retry.
Dream should behave the same way.
The streaming path in OpenAICompatProvider.chat_stream() was passing
reasoning_content deltas through on_content_delta(), causing model
internal reasoning to be displayed to the user alongside the actual
response content.
reasoning_content is already collected separately in _parse_chunks()
and stored in LLMResponse.reasoning_content for session history.
It should never be forwarded to the user-facing stream.
Feishu's GetMessageResource API only accepts 'image' or 'file' as the
type parameter. Video messages have msg_type='media', which was passed
through unchanged, causing error 234001 (Invalid request param). Now
both 'audio' and 'media' are converted to 'file' for download.
- _add_reaction now returns reaction_id on success
- Add _remove_reaction_sync and _remove_reaction methods
- Remove reaction when stream ends to clear processing indicator
- Store reaction_id in metadata for later removal
Fixes#2591
The "nanobot is thinking..." spinner was printing ANSI escape codes
literally in some terminals, causing garbled output like:
?[2K?[32m⠧?[0m ?[2mnanobot is thinking...?[0m
Root causes:
1. Console created without force_terminal=True, so Rich couldn't
reliably detect terminal capabilities
2. Spinner continued running during user input prompt, conflicting
with prompt_toolkit
Changes:
- Set force_terminal=True in _make_console() for proper ANSI handling
- Add stop_for_input() method to StreamRenderer
- Call stop_for_input() before reading user input in interactive mode
- Add tests for the new functionality
Enable GPT-5 models (gpt-5, gpt-5.4, gpt-5.4-mini, etc.) to work
correctly with the OpenAI-compatible provider by:
- Setting `supports_max_completion_tokens=True` on the OpenAI provider
spec so `max_completion_tokens` is sent instead of the deprecated
`max_tokens` parameter that GPT-5 rejects.
- Adding `_supports_temperature()` to conditionally omit the
`temperature` parameter for reasoning models (o1/o3/o4) and when
`reasoning_effort` is active, matching the existing Azure provider
behaviour.
Both changes are backward-compatible: older GPT-4 models continue to
work as before since `max_completion_tokens` is accepted by all recent
OpenAI models and temperature is only omitted when reasoning is active.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
The test test_openai_compat_strips_message_level_reasoning_fields was
added in fbedf7a and incorrectly asserted that reasoning_content and
extra_content should be stripped from messages. This contradicts the
intent of b5302b6 which explicitly added these fields to _ALLOWED_MSG_KEYS
to preserve them through sanitization.
Rename the test and fix assertions to match the original design intent:
reasoning_content and extra_content at message level should be preserved,
and extra_content inside tool_calls should also be preserved.
Signed-off-by: Lingao Meng <menglingao@xiaomi.com>
reasoning_content and extra_content were accidentally dropped from
_ALLOWED_MSG_KEYS.
Also fix session/manager.py to include reasoning_content when building
LLM messages from session history, so the field is not lost across
turns.
Without this fix, providers such as Kimi, emit reasoning_content in
assistant messages will have it stripped on the next request, breaking
multi-turn thinking mode.
Fixes: https://github.com/HKUDS/nanobot/issues/2777
Signed-off-by: Lingao Meng <menglingao@xiaomi.com>
Use dream_log and dream_restore in Telegram's bot command menu so command registration succeeds, while still accepting the original dream-log and dream-restore forms in chat. Keep the internal command routing unchanged and add coverage for the alias normalization path.
- Added Jinja2 template support for various agent responses, including identity, skills, and memory consolidation.
- Introduced new templates for evaluating notifications, handling subagent announcements, and managing platform policies.
- Updated the agent context and memory modules to utilize the new templating system for improved readability and maintainability.
- Added a new dependency on Jinja2 in pyproject.toml.
