- Add DOCX MIME type to ALLOWED_DOCUMENT_TYPES in storage_service.py
- Add python-docx text extraction in _generate_ai_description
- Extract shared _store_document_content helper for PDF/DOCX
- Add python-docx>=1.1.0 to requirements.txt
- Add tests for docx upload acceptance and document fetch
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
PDF uploads were stored in S3 and had text extracted during upload, but
fetch_upload_images() filtered exclusively for image MIME types, so
document content never reached the AI.
- Add fetch_upload_documents() in storage_service.py to retrieve
extracted_content for PDFs and text files
- Update ai_sessions.py chat endpoint to call both fetch_upload_images
and fetch_upload_documents, injecting document text as context
- Add PDF text extraction in _generate_ai_description (pypdf)
- Add pypdf>=4.0.0 to requirements.txt
- Fix test_db teardown to avoid connection pool issues
- Add 5 tests for fetch_upload_documents
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
The old /assistant/chats/* CRUD endpoints and assistant_chat_service
chat functions were unused — the frontend exclusively uses
/ai-sessions/{id}/chat (unified_chat_service) for all chat operations.
Removed:
- Chat CRUD endpoints (create, list, get, send, delete, conclude)
- assistant_chat_service: create_chat, send_message,
generate_conclusion_summary, CONCLUSION_SYSTEM_PROMPT
- Frontend: assistantChatApi chat methods, dead types
(AssistantChat, AssistantChatMessage, ConcludeChatRequest, etc.)
Kept:
- /assistant/retention endpoints (used by ChatRetentionSettingsPage)
- Shared AI infrastructure (_call_ai, _call_anthropic_cached,
ASSISTANT_SYSTEM_PROMPT, _auto_title) — imported by unified_chat_service
Moved:
- fetch_upload_images + resize_image_for_vision → storage_service.py
(shared location, not tied to dead endpoint)
Also added "Image Analysis" section to system prompt so Claude knows
to describe attached screenshots.
-650 lines of dead code removed.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- Backend: ChatMessageRequest accepts upload_ids, endpoint fetches
images from S3, base64-encodes them, passes to Claude as multimodal
content blocks (vision API)
- Backend: add download_file() to storage_service for fetching from S3
- Frontend: handleSend collects completed upload IDs from pendingUploads
and includes them in the sendChatMessage API call
- Frontend: prefill handler passes upload IDs from dashboard nav state
- Enables paste-screenshot → AI-sees-it flow end-to-end
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
