- Add toggle, update and delete APIs for scheduled tasks
- Add task edit modal with schedule/action updates in web console (PS: In edit box, now I Prevent channel type changes during editing (weixin token bound to session) )
- Add enable/disable switch with visual feedback in task cards
- Sort task list by enabled status first, then by next_run_at
Closes#2882
- Merge the separate custom-providers section into the unified provider
grid; "Custom" in the add-provider picker now acts as an add-new action
(trailing + mark) and opens the dedicated modal, supporting multiple
OpenAI-compatible endpoints
- Simplify the custom provider modal: drop the default-model field, add
an inline delete button, align colors with the theme
- Keep the legacy single "custom" card visible (models page, chat
dropdown and legacy config page) while custom_api_key/custom_api_base
is still in use, so existing single-provider setups don't disappear
- Unify user-facing wording from "vendor" to "provider" in UI and docs
- Restructure custom provider docs (zh/en/ja) around Web console and
config file usage
1. Creating a provider no longer auto-switches bot_type. Only an
explicit make_active=true changes the active model — prevents
silently hijacking users on Claude/OpenAI/etc.
2. When a provider IS activated, its 'model' is now written into the
global 'model' field. This ensures all three paths (regular chat,
agent_bridge, vision) use the correct model without per-path patches.
3. Removed unused i18n key 'models_custom_name_exists' (no longer
referenced after the id-based rework removed name-collision checks).
4. Updated tests: 39 passing (added model-sync tests, fixed tests that
relied on the removed auto-activation behavior).
Rework the multi custom-provider design per maintainer review:
1. Data model: use server-generated uuid4 short id as primary key;
'name' is now a pure display label that can be freely renamed.
2. Routing: drop 'custom_active_provider'; activate a provider by
setting bot_type to 'custom:<id>'. Single source of truth — no
pointer drift between bot_type and a separate active selector.
3. Security: drag_sensitive() now recursively masks api_key/secret in
nested structures (custom_providers list); previously only top-level
string fields were masked.
4. Per-provider model: the provider's 'model' field now takes effect on
the main chat path and agent path (was silently ignored before).
5. XSS fix: replace all inline onclick handlers in custom-provider UI
with data-* attributes + event delegation. Provider names never
appear in executable HTML contexts.
Legacy compatibility: bot_type='custom' (no colon) still reads the flat
custom_api_key/custom_api_base fields byte-for-byte identically.
Closes: consolidates #2876 into this PR as requested.
Ref: #2838
Adds first-class support for configuring more than one custom
OpenAI-compatible provider (e.g. SiliconFlow, DeepSeek, local vLLM)
and switching the active one from the web console, addressing #2838.
Backend:
- config: new `custom_providers` (list) and `custom_active_provider`
fields, fully backward compatible with the legacy single
`open_ai_api_base`/`model` fields (used as fallback).
- models/custom_provider.py: centralized resolver
`resolve_custom_credentials()` returning (api_key, api_base, model),
with active-provider selection and graceful fallback.
- chat_gpt_bot.py wired to use the resolver.
- web_channel.py: `_provider_overview` expands `custom_providers` into
one card per provider (id `custom:<name>`, active flag, masked key);
new POST actions `set_custom_provider`, `delete_custom_provider`,
`set_active_custom_provider` with hermetic persistence + bridge reset.
Frontend:
- console.js: dedicated "Custom providers" section with add / edit /
delete / set-active actions, masked-key keep-existing handling, and
~20 new zh/en i18n strings.
- chat.html: custom provider modal.
Tests:
- tests/test_custom_provider.py (11) - resolver/config behavior.
- tests/test_custom_provider_handlers.py (18) - write-side handlers and
overview expansion, including duplicate-name rejection.
All 29 unit tests pass.
Add a self-evolution subsystem that reviews idle conversations in an
isolated agent and durably learns from them — patching/creating skills,
finishing unfinished tasks, and backfilling missed memory.
- Trigger: background idle scan, fires when a session is idle >= N min AND
(>= N turns OR context usage > 80%). In-memory cursor reviews only new
messages so a session never re-learns old content.
- Isolated review agent: same model, restricted toolset, hard write-guard
confining edits to the workspace (built-in skills are protected).
- Safety: file-level backup before edits + evolution_undo tool; notify the
user ONLY when a workspace file actually changed (no-nag rule); capped
concurrency.
- Records to memory/evolution/<date>.md, surfaced in the memory UI's
renamed "Self-Evolution" tab (merged with dream diaries).
- Hide internal [SCHEDULED]/[EVOLUTION]/backup_id markers from chat history
display (also fixes scheduler marker leakage) while keeping them in stored
content for undo.
- Flat config: self_evolution_enabled (default off until release),
self_evolution_idle_minutes (15), self_evolution_min_turns (6).
- Tests: tests/test_evolution.py (stub + real model modes, 7 scenarios).
- Add language labels and copy buttons to code blocks
- Enhance drag-and-drop to full chat view
- Fix data consistency bugs in message operations
- Use RLock to prevent deadlock in conversation store"
Search tool now supports 4 backends with unified output (bocha,
qianfan, zhipu, linkai) and a routing layer:
- strategy 'auto' (default): pick first configured in canonical order
bocha > qianfan > zhipu > linkai
- strategy 'fixed': pin a specific provider
- agent may pass `provider` to override per-call (only exposed when
≥2 providers configured + auto strategy)
When reloading a conversation, failed tool calls incorrectly showed checkmark instead of X because the is_error field was lost in the history rendering pipeline. Propagate is_error from DB extraction through to the frontend rendering to match the live SSE behavior.
Boot MCP servers (npx/uvx) on a background thread instead of blocking
agent init. Built-in tools serve traffic immediately while MCP comes
online; each new agent reads whatever is ready at creation time.
Idempotent via _mcp_loaded flag — concurrent sessions never re-fork
subprocesses. Per-server failures are isolated and warmup is triggered
in app.py so loading overlaps with channel startup.
