Shared runtime
- One agent entry point (runtime.invoke_agent_for_user / prepare_agent_turn) for
web, email, iMessage, WhatsApp, scheduled and cron, so identity, permissions,
memories, summaries and metrics match across channels.
- Serialize turns per checkpoint thread; /query validates input and returns 409
while a durable run owns the conversation.
Reconnectable chat (durable runs)
- POST /runs creates an idempotent, owner-scoped run; GET .../events replays an
ordered SSE log by cursor, so generation survives refresh and device switches.
Stop cancels; disconnect only detaches. /stream-query is a compatibility adapter.
- Coalesce streamed deltas (150 ms) and wake same-process subscribers instead of
polling; keep buffered text when a run is stopped.
- Drain runs on shutdown; serve via Hypercorn with a shutdown timeout covering
the drain (and no longer in debug mode). CHAT_RUN_* settings are forwarded.
Scheduled messages and cron
- Atomic delivery claims, attempt history and explicit retries; ambiguous sends
become "uncertain" and are never resent automatically.
- Cron triggers need a run_id/Idempotency-Key; legacy jobs need an explicit owner.
- Cancelling never rewrites a started delivery; series stop via tombstones.
Legacy sent rows are not forked into new series. Malformed bodies return 400.
History, integrations and retrieval
- Message-content search, pinned conversations, JSON/Markdown export and a
memory editor.
- Integration status panel and YNAB data-freshness provenance.
- Date-filtered document/note search with stable citations and a source viewer.
Migration 20 is generated by aerich.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Load an allowlisted subset of homebox-mcp tools (read + safe writes, no
deletes) over stdio and compile them into a separate admin agent, so
non-admins never see them. Each tool also re-checks is_admin per call.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Global module variable was unreliable across import boundaries. Storing
the compiled agent on app.main_agent and reading it via current_app is
the idiomatic Quart pattern and guaranteed to reflect the initialized value.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
from-import captures the None value set at module load; importing the module
and accessing .main_agent at call time gets the value set by build_agent().
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
state_modifier was removed in this version of LangGraph; use the prompt
parameter with a static system prompt string instead. Dynamic memory
injection via configurable is deferred — memories are still saved by the
save_user_memory tool, just not pre-loaded into the system prompt.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Replaces per-request history reconstruction with a persistent AsyncSqliteSaver
checkpointer keyed by conversation ID, so agent state (tool calls, intermediate
steps) carries forward between turns without manual message list building.
Also includes the missing migration for the CronJob model added in bb4619a.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Native reply threading: inbound replies continue their conversation via
SendBlue message_handle lookup; standalone messages create a new conversation
- Our responses are sent with reply_to so they thread visually in iMessage
- Typing indicator fires before agent invocation and stops in a finally block
- Add extract_agent_text() to handle list-type AIMessage content and strip
<think> tokens from Qwen3 — applied to iMessage, WhatsApp, and web chat
- ConversationMessage gains a nullable message_handle field (migration needed)
- /threads command lists recent iMessage conversations
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Two fixes for the agent losing track of conversation context:
- History replay compared msg.speaker (a Speaker enum) to the string
"user", which is always false, so every prior message — including the
user's — was sent to the LLM with role "assistant". Compare against
Speaker.USER instead. Affected web, iMessage, WhatsApp, and email.
- Tool outputs (web searches, RAG chunks) were discarded after each
turn, so follow-up questions about fetched content had nothing to
reference. Persist them as speaker="tool" messages (capped at 4000
chars) and replay them in history as assistant context. The
conversation GET endpoint serves only their header line so the UI
tool pill stays compact.
Also bumps the replayed history window from 10 to 20 messages since
tool messages now share it.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Revert get_conversation_for_user to use Conversation.get() with
MultipleObjectsReturned fallback. Add channel field to Conversation
model and get_conversation_for_channel helper so each messaging
channel gets its own isolated conversation per user.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Users can now receive a unique email address (ask+<token>@domain) and
interact with Simba by sending emails. Inbound emails hit a Mailgun
webhook, are authenticated via HMAC token lookup, processed through the
LangChain agent, and replied to via the Mailgun API.
- Extract shared SIMBA_SYSTEM_PROMPT to blueprints/conversation/prompts.py
- Add email_enabled and email_hmac_token fields to User model
- Create blueprints/email with webhook, signature validation, rate limiting
- Add admin endpoints to enable/disable email per user
- Update AdminPanel with Email column, toggle, and copy-address button
- Add Mailgun env vars to .env.example
- Include database migration for new fields
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Ryan Chen