feat: add on-demand memory storage and recall tools#193
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Signed-off-by: kyteinsky <kyteinsky@gmail.com> Assisted-by: Github Copilot:qwen-3-6-35b-a3b Assisted-by: Github Copilot:claude-sonnet-4-6
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do we want specific tests for this feature in the integration tests? |
marcelklehr
reviewed
Jun 18, 2026
marcelklehr
reviewed
Jun 18, 2026
marcelklehr
reviewed
Jun 18, 2026
marcelklehr
reviewed
Jun 18, 2026
marcelklehr
reviewed
Jun 18, 2026
marcelklehr
reviewed
Jun 18, 2026
Signed-off-by: kyteinsky <kyteinsky@gmail.com>
Signed-off-by: kyteinsky <kyteinsky@gmail.com>
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Member
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Nice! We can now make the memory tools dependent on the assistant app being installed and it should be ok |
kyteinsky
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Jun 18, 2026
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Pull request overview
This PR introduces a new “Memories” toolset that lets the agent persist, browse, load, delete, and (optionally) semantically search user-scoped memory files stored under the Assistant folder in Nextcloud. It also updates TaskProcessing output validation to support the new Context Chat search output shape.
Changes:
- Added
ex_app/lib/all_tools/memory.pyimplementing memory storage/recall tools (list/load/store/delete/delete-folder/search). - Added DAV folder-creation logic to ensure the Memories base folder and subfolders exist when storing memories.
- Updated TaskProcessing output-key validation to accept
sourcesoutputs.
Reviewed changes
Copilot reviewed 2 out of 2 changed files in this pull request and generated 7 comments.
| File | Description |
|---|---|
| ex_app/lib/all_tools/memory.py | Adds new memory management tools + path validation + DAV folder creation + Context Chat-backed semantic search. |
| ex_app/lib/all_tools/lib/task_processing.py | Extends accepted TaskProcessing output keys to include sources for Context Chat search results. |
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| path_parts = [p for p in decoded.strip('/').split('/') if p] | ||
| if len(path_parts) > MAX_MEMORY_FOLDER_DEPTH + 1: # +1 for the filename itself | ||
| raise AgentFacingError(f'Memory path exceeds maximum depth of {MAX_MEMORY_FOLDER_DEPTH}') |
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| base_parts = [p for p in base_memories_path.split('/') if p] | ||
| all_parts = base_parts + scoped_folder_parts | ||
| for i in range(len(base_parts) + 1, len(all_parts) + 1): | ||
| folder_path = '/'.join(all_parts[:i]) |
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| fsnode = await files_handle.by_id(file_id) | ||
| filepath = '/' + fsnode.user_path.removeprefix(prefix).rstrip('/') | ||
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| if fsnode is None: | ||
| await log(nc, logging.WARNING, f'Could not fetch file by id: {file_id}') | ||
| return {'path': filepath, 'content': ''} |
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| try: | ||
| full_path, _ = __validate_memory_path(path, memories_folder_path, allow_folder_path=True) |
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| if not isinstance(task.output, dict) or all(x not in ["file", "output", "images", "slide_deck"] for x in task.output): | ||
| if not isinstance(task.output, dict) or all(x not in ["file", "output", "images", "slide_deck", "sources"] for x in task.output): | ||
| raise Exception('"output" key not found in Nextcloud TaskProcessing task result') |
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| async def __is_context_chat_available(nc: AsyncNextcloudApp, memories_folder_path: str): | ||
| tasktypes = (await nc.ocs('GET', '/ocs/v2.php/taskprocessing/tasktypes'))['types'].keys() | ||
| return CONTEXT_CHAT_SEARCH_TASK_TYPE in tasktypes |
Member
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Works nicely. I didn't test the context_chat integration though, because I don't want to set it up 😇 |
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needs nextcloud/context_chat#247
🤖 AI (if applicable)