Bug 1: _drain_pending did not call extract_documents on follow-up
messages arriving mid-turn. Documents attached to queued messages were
silently dropped because _build_user_content only handles images.
Fix: call extract_documents before _build_user_content in _drain_pending.
Bug 2: extract_documents read the entire file into memory (up to 50 MB)
just to check 16 bytes of magic header for MIME detection.
Fix: read only the first 16 bytes via open()+read(16) instead of
Path.read_bytes().
Added regression tests for both bugs.
Made-with: Cursor
Move extract_documents() to nanobot.utils.document as a reusable helper
and call it once in AgentLoop._process_message, the single entry point
for all message processing (API + all channels).
This replaces the previous API-only _extract_documents() in server.py,
ensuring Telegram, Feishu, Slack, WeChat, and all other channels also
benefit from automatic document text extraction.
Adds a configurable max_file_size guard (default 50 MB) to skip
oversized files gracefully, preventing unbounded memory/CPU usage
from channel-downloaded attachments.
- server.py: removed _extract_documents and related imports
- document.py: added extract_documents() with size limit
- loop.py: calls extract_documents() at the top of _process_message
- Tests updated: 70 related tests pass
Made-with: Cursor
ContextBuilder._build_user_content now only handles images (its original
responsibility). Document text extraction (PDF, DOCX, XLSX, PPTX) is
performed by the new _extract_documents() helper in server.py, called
before process_direct(). This keeps the core context builder free of
format-specific dependencies and makes the API boundary the single place
where uploaded files are pre-processed.
Tests updated to reflect the new responsibility boundary.
Made-with: Cursor
Keep the API file upload branch current with main, enforce the documented JSON base64 per-file limit, and avoid leaking document extraction error strings into user prompts.
Made-with: Cursor
