* feat: add POST /api/v1/memory endpoint for realtime conversation memory
Add memory extraction API that accepts conversation messages and
stores them via Mem0. This enables realtime voice sessions to save
memories through the same pipeline as chat conversations.
Fixes: sparticleinc/mygpt-frontend#2126
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix: address code review findings for memory API
- Use Literal["user","assistant"] for role field validation
- Add Field constraints (min_length, max_length=200)
- Track and report pairs_failed in response
- Hide internal exception details from HTTP response
- Remove unused authorization parameter (internal API)
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
---------
Co-authored-by: zhuchao <zhuchaowe@163.com>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
* chore: add .worktrees/ to .gitignore
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* feat(memory): add memory management API endpoints
Add new /api/v1/memory endpoints for viewing and managing user memories:
- GET /api/v1/memory - list all memories for a bot
- DELETE /api/v1/memory/{memory_id} - delete single memory
- DELETE /api/v1/memory - delete all memories for a bot
Also add delete_memory and delete_all_memories methods to Mem0Manager.
Issue: #1844
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
---------
Co-authored-by: zhuchao <zhuchaowe@163.com>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
- Remove __debug__ conditional that exposed tracebacks in production
- Simplify error response structure to {"error": str(e)}
- Remove redundant exception handling in init_agent()
- Remove unnecessary traceback logging
- Reduce code from ~30 lines to ~10 lines
Fixes security vulnerability where __debug__ is always True
unless Python runs with -O flag, causing full tracebacks
to be sent to clients in production.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Create new skill_manager.py with list and upload endpoints
- Add GET /api/v1/skill/list to retrieve official and user skills
- Add POST /api/v1/skill/upload for skill file upload
- Parse SKILL.md frontmatter to extract name and description
- Move skill upload endpoint from files.py to skill_manager.py
- Add SKILLS_DIR configuration to settings.py
- Register skill_manager router in fastapi_app.py
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Enhance exception handling in agent_task() to capture and send structured error messages via SSE stream
- Add [DONE] marker to outer exception handler to ensure proper stream termination
- Improve MCP tool loading error handling in init_agent() to prevent cascading failures
- Add detailed error logging with traceback for debugging
Fixes RemoteProtocolError that occurred when MCP tool calls failed,
which previously caused incomplete chunked read errors and connection drops.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
Add new POST endpoint /api/v1/skills/upload for uploading skill zip files.
The endpoint:
- Accepts zip files with bot_id parameter
- Validates file format (must be .zip)
- Saves zip to projects/uploads/{bot_id}/skill_zip/
- Automatically extracts to projects/uploads/{bot_id}/skills/{skill_name}/
- Returns success response with file and extract paths
This enables programmatic skill deployment for specific bots.
The create_folder endpoint was incorrectly defined to accept query
parameters instead of JSON request body, causing 400 errors when
called from the frontend.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
