Two independent leaf modules (no intra-new_chat deps, no frozen importer),
consumed only by flows/routes/tests. Flipped 8 importers across both the
dotted-path and module-style (from app.agents.new_chat import mention_resolver)
forms. No shims needed.
Relocate the mutually-dependent LLM config layer and the LiteLLM prompt-caching
helper to the shared kernel as one unit, rewiring their internal cross-reference
to the shared paths. Flip 21 non-frozen importers. Re-export shims remain at
new_chat/{llm_config,prompt_caching}.py for the frozen single-agent stack
(chat_deepagent); they will be removed when that stack is retired.
Continue promoting the shared agent toolkit out of `new_chat` into the
cross-agent `app/agents/shared` kernel.
- state_reducers.py: clean move (no single-agent importer); all 7 importers
flipped to app.agents.shared.state_reducers.
- context.py: moved to app.agents.shared.context; flipped the multi-agent,
app, automations, chat-flows and monolith importers. A thin re-export shim
remains at new_chat/context.py because the not-yet-retired single-agent
(chat_deepagent) and the new_chat package __init__ still import it; the shim
goes away with the single-agent deletion.
- Updated the stream parity test's annotation normalizer to strip the new
app.agents.shared.context. prefix (SurfSenseContextSchema.__module__ changed
with the move), keeping monolith<->flows signature parity intact.
Behavior-preserving: definitions unchanged; only import paths move. 1219 tests green.
- Enhanced lambda function formatting in `_after_commit` for better clarity.
- Simplified generator expression in `_match_condition` for improved readability.
- Streamlined function signature in `_eligible` for consistency.
- Updated imports and refactored anonymous chat routes to use a new agent creation method.
- Added a new function `_load_anon_document` to handle document loading from Redis.
- Improved UI components by replacing legacy structures with modern alternatives, including alerts and separators.
- Refactored quota-related components to utilize new alert structures for better user feedback.
- Cleaned up unused variables and optimized component states for performance.
- Removed the eligibility gate for model selection in the automation creation process, allowing users to choose models directly in the builder.
- Updated the `AutomationBuilderForm` to incorporate model selection logic, ensuring that selected models are validated and preserved during automation creation and editing.
- Simplified the `AutomationsContent` and `AutomationNewContent` components by eliminating unnecessary eligibility checks and alerts.
- Enhanced the user experience by integrating model selection directly into the automation approval process, ensuring that only billable models are used.
- Refactored related tests to cover new model selection behavior and ensure proper validation of user-selected models.
- Added model eligibility checks to ensure automations can only use billable models (premium or BYOK).
- Introduced new API endpoint to report model eligibility status for search spaces.
- Updated frontend components to display eligibility alerts and disable creation options when models are not billable.
- Enhanced automation creation forms to reflect model eligibility, preventing users from submitting invalid configurations.
- Implemented server-side logic to capture and preserve model preferences across automation edits, ensuring consistent behavior during execution.
- Added support for @-mentions in agent tasks, allowing users to reference documents, folders, and connectors directly in their queries.
- Updated `run_agent_task` to resolve mentions and include them in the context passed to the agent.
- Introduced new parameters in `AgentTaskActionParams` for handling mentioned document and connector IDs.
- Refactored the automation edit and new components to utilize the new `AutomationBuilderForm` for a more streamlined user experience.
- Removed deprecated JSON forms to simplify the automation creation process.
The shared AsyncPostgresSaver caches DB connections in a module-level
pool. Cached connections are bound to the asyncio loop that opened
them, but `run_async_celery_task` discards the loop on each task's
exit — so after the first task the pool holds connections pointing
to a dead loop, and the next automation hangs 30s before failing
with `PoolTimeout: couldn't get a connection after 30.00 sec`.
Swap agent_task to `InMemorySaver`; automation runs only need state
within one Celery task, so nothing is lost. Site-local TODO tracks
the proper future fix (dispose the checkpointer pool around each
Celery task, mirroring `_dispose_shared_db_engine`).
Manual-as-a-standalone-trigger conflates "user clicks Run now" with the
trigger model and forces ad-hoc input plumbing on the caller. Remove the
unreachable surface so the tree reflects reality (schedule is the only
v1 trigger).
- Unregister `manual`: drop import from triggers/__init__.py
- Delete `app/automations/triggers/manual/`
- Drop `RunService.dispatch_manual` (RunService is now read-only)
- Drop `POST /automations/{id}/run` and `RunDispatched` schema
- Keep `TriggerType.MANUAL` Python + PG enum value (reserved, documented)
to avoid an Alembic round-trip when Run-now is redesigned
