ryan
5809ad3adb
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>
75 lines
2.4 KiB
Python
75 lines
2.4 KiB
Python
import enum
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from tortoise import fields
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from tortoise.contrib.pydantic import (
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pydantic_model_creator,
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pydantic_queryset_creator,
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)
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from tortoise.models import Model
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class Speaker(enum.Enum):
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USER = "user"
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SIMBA = "simba"
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TOOL = "tool"
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class Conversation(Model):
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id = fields.UUIDField(primary_key=True)
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name = fields.CharField(max_length=255)
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created_at = fields.DatetimeField(auto_now_add=True)
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updated_at = fields.DatetimeField(auto_now=True)
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user: fields.ForeignKeyRelation = fields.ForeignKeyField(
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"models.User", related_name="conversations", null=True
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)
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channel = fields.CharField(max_length=20, default="web", null=True)
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pinned = fields.BooleanField(default=False)
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class Meta:
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table = "conversations"
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# Conversation list: a user's conversations, most recent first.
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indexes = (("user_id", "updated_at"),)
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class ConversationMessage(Model):
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id = fields.UUIDField(primary_key=True)
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text = fields.TextField()
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conversation = fields.ForeignKeyField(
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"models.Conversation", related_name="messages"
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)
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created_at = fields.DatetimeField(auto_now_add=True)
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speaker = fields.CharEnumField(enum_type=Speaker, max_length=10)
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image_key = fields.CharField(max_length=512, null=True, default=None)
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message_handle = fields.CharField(max_length=255, null=True, default=None)
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class Meta:
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table = "conversation_messages"
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# Loading a conversation's history in order.
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indexes = (("conversation_id", "created_at"),)
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class UserMemory(Model):
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id = fields.UUIDField(primary_key=True)
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user = fields.ForeignKeyField("models.User", related_name="memories", db_index=True)
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content = fields.TextField()
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created_at = fields.DatetimeField(auto_now_add=True)
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updated_at = fields.DatetimeField(auto_now=True)
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class Meta:
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table = "user_memories"
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PydConversationMessage = pydantic_model_creator(ConversationMessage)
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PydConversation = pydantic_model_creator(
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Conversation, name="Conversation", allow_cycles=True, exclude=("user",)
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)
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PydConversationWithMessages = pydantic_model_creator(
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Conversation,
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name="ConversationWithMessages",
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allow_cycles=True,
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exclude=("user",),
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include=("messages",),
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)
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PydListConversation = pydantic_queryset_creator(Conversation)
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PydListConversationMessage = pydantic_queryset_creator(ConversationMessage)
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