Closes the create loop in chat: the agent describes user intent → the
drafter sub-LLM produces an AutomationCreate JSON → this card surfaces
a structured preview → approve persists; reject cancels. Edits flow
through chat refinement (re-call with a refined intent), not in-card,
so the card stays simple and the multi-turn checkpointer carries the
context.
Tool UI (components/tool-ui/automation/):
- create-automation.tsx — entry dispatcher + ApprovalCard chrome
(pending/processing/complete/rejected via useHitlPhase) + SavedCard
(links to the detail page) + InvalidCard (lists drafter validation
issues) + ErrorCard (verbatim message). Rejection result is hidden
because the approval card itself shows the rejected phase inline.
- automation-draft-preview.tsx — structured preview body: name +
description + goal, triggers (humanised cron + tz + static-input
keys), plan steps (step_id → action), and a collapsible raw JSON
for power users.
Wiring:
- components/tool-ui/index.ts — re-export.
- features/chat-messages/timeline/tool-registry/registry.ts —
register create_automation → CreateAutomationToolUI (dynamic import,
same pattern as other connector tools).
- contracts/enums/toolIcons.tsx — Workflow icon + "Create automation"
display name so fallback chrome (and timeline headers) are honest.
Shared util:
- lib/automations/describe-cron.ts — lifted from the route slice's
lib/ folder since both the dashboard slice and the new approval card
now render schedule descriptions. Slice imports updated; the now-
empty slice lib/ folder is gone.
Backend prompt fragments:
- main_agent/system_prompt/.../create_automation/description.md and
the tool's docstring no longer promise in-card edits. They make the
refinement path explicit: if the user wants changes after seeing the
draft, they reply in chat and the agent calls the tool again with a
refined intent.
v1 deliberately excludes:
- In-card edit form / right-side edit panel — defer until we see real
demand. The chat refinement loop covers the common case.
- approve_always / persistent allow rules — automations are a single
artifact, not a repeated mutation, so the "trust this kind of call"
affordance doesn't apply.
- Added `index_batch_parallel` method to enable concurrent indexing of documents with bounded concurrency, improving performance and efficiency.
- Refactored existing indexing logic to utilize `asyncio.to_thread` for non-blocking execution of embedding and chunking functions.
- Introduced unit tests to validate the functionality of the new parallel indexing method, ensuring robustness and error handling during document processing.
- Refactored token refresh logic in ConfluenceHistoryConnector and JiraHistoryConnector to use lazy imports, avoiding circular dependencies.
- Enhanced the ComposerAction component to manage tool availability based on connected types, adding support for Jira and Confluence tools.
- Updated tool icon management to include Jira and Confluence, improving the user interface for tool interactions.
- Added support for grouping tools with connector icons, improving organization and user interaction.
- Implemented logic to toggle tool groups based on their enabled/disabled state, enhancing user experience.
- Updated the display of enabled tools count to reflect the new grouping structure.
- Introduced a new constant for connector tool icon paths to streamline icon management across components.
- Added a new tool action for updating Gmail drafts in the backend agent, expanding functionality.
Add full MiniMax provider support across the entire stack:
Backend:
- Add MINIMAX to LiteLLMProvider enum in db.py
- Add MINIMAX mapping to all provider_map dicts in llm_service.py,
llm_router_service.py, and llm_config.py
- Add Alembic migration (rev 106) for PostgreSQL enum
- Add MiniMax M2.5 example in global_llm_config.example.yaml
Frontend:
- Add MiniMax to LLM_PROVIDERS enum with apiBase
- Add MiniMax-M2.5 and MiniMax-M2.5-highspeed to LLM_MODELS
- Add MINIMAX to Zod validation schema
- Add MiniMax SVG icon and wire up in provider-icons
Docs:
- Add MiniMax setup guide in chinese-llm-setup.md
MiniMax uses an OpenAI-compatible API (https://api.minimax.io/v1)
with models supporting up to 204K context window.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Introduced new enum values for Composio connectors: COMPOSIO_GOOGLE_DRIVE_CONNECTOR, COMPOSIO_GMAIL_CONNECTOR, and COMPOSIO_GOOGLE_CALENDAR_CONNECTOR.
- Updated database migration to add these new enum values to the relevant types.
- Refactored Composio integration logic to handle specific connector types, improving the management of connected accounts and indexing processes.
- Enhanced frontend components to support the new Composio connector types, including updated UI elements and connector configuration handling.
- Improved backend services to manage Composio connected accounts more effectively, including deletion and indexing tasks.