Default title and path recognition to skip image fetching, while keeping scrape entrypoints and transfer-to-scrape paths populated with image data. This preserves lightweight recognition behavior without breaking metadata scraping.
Route title and path lookups through the fallback-aware entrypoints so auxiliary matches can reuse pre-assist keywords without forcing image fetches in lightweight flows. Also reduce noisy agent shutdown logging during cleanup.
Return only a 10KB preview to the agent so large command results do not overwhelm conversations while keeping the full output available for follow-up reads. Add pytest to the project dependencies to make the regression tests runnable in the project venv.
- Add mechanism to always include core tools (e.g., file operations, command execution) in LLMToolSelectorMiddleware
- Update MoviePilotToolFactory to provide filtered always-include tool names based on loaded tools
- Set default LLM_MAX_TOOLS to 30 in config
- Refactor agent initialization to support always_include parameter
- Enhance tests to cover always_include logic and async agent creation
- Add tools for querying built-in and custom filter rules, and for adding, updating, and deleting custom rules and rule groups
- Refactor filter module to use shared builtin rule definitions
- Enhance rule group querying to include syntax guidance and usage references
- Add unittests for agent filter rule tools registration and parsing logic
- Implement batch AI re-organize endpoint for transfer history with progress tracking
- Add batch_manual_transfer_redo system task template and prompt generation
- Refactor agent_manager to support generic background prompt execution
- Add AIRecommendChain for search result recommendation using agent background prompt
- Update search endpoints to use new AIRecommendChain and remove legacy code
- Enhance test cases for batch manual transfer redo
- Minor code cleanup and style fixes
- Integrate voice message handling: detect and extract audio references from Telegram and WeChat messages, route to agent with voice reply preference.
- Add voice provider abstraction and OpenAI-based TTS/STT implementation.
- Implement agent tool `send_voice_message` for generating and sending voice replies, with fallback to text if voice is unavailable.
- Extend agent prompt and context to support voice reply instructions.
- Update notification and message schemas to support audio fields.
- Add Telegram and WeChat voice sending logic, including audio file conversion and temporary media upload for WeChat.
- Add tests for voice helper and agent voice routing.
