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feat/user-
| Author | SHA1 | Date | |
|---|---|---|---|
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c95800e65d |
@@ -22,6 +22,7 @@ from .logic import (
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get_conversation_by_id,
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rename_conversation,
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)
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from .memory import get_memories_for_user
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from .models import (
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Conversation,
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PydConversation,
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@@ -36,15 +37,27 @@ conversation_blueprint = Blueprint(
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_SYSTEM_PROMPT = SIMBA_SYSTEM_PROMPT
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async def _build_system_prompt_with_memories(user_id: str) -> str:
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"""Append user memories to the base system prompt."""
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memories = await get_memories_for_user(user_id)
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if not memories:
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return _SYSTEM_PROMPT
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memory_block = "\n".join(f"- {m}" for m in memories)
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return f"{_SYSTEM_PROMPT}\n\nUSER MEMORIES (facts the user has asked you to remember):\n{memory_block}"
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def _build_messages_payload(
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conversation, query_text: str, image_description: str | None = None
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conversation,
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query_text: str,
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image_description: str | None = None,
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system_prompt: str | None = None,
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) -> list:
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recent_messages = (
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conversation.messages[-10:]
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if len(conversation.messages) > 10
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else conversation.messages
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)
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messages_payload = [{"role": "system", "content": _SYSTEM_PROMPT}]
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messages_payload = [{"role": "system", "content": system_prompt or _SYSTEM_PROMPT}]
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for msg in recent_messages[:-1]: # Exclude the message we just added
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role = "user" if msg.speaker == "user" else "assistant"
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text = msg.text
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@@ -80,10 +93,14 @@ async def query():
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user=user,
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)
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messages_payload = _build_messages_payload(conversation, query)
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system_prompt = await _build_system_prompt_with_memories(str(user.id))
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messages_payload = _build_messages_payload(
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conversation, query, system_prompt=system_prompt
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)
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payload = {"messages": messages_payload}
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agent_config = {"configurable": {"user_id": str(user.id)}}
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response = await main_agent.ainvoke(payload)
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response = await main_agent.ainvoke(payload, config=agent_config)
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message = response.get("messages", [])[-1].content
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await add_message_to_conversation(
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conversation=conversation,
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@@ -163,15 +180,19 @@ async def stream_query():
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logging.error(f"Failed to analyze image: {e}")
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image_description = "[Image could not be analyzed]"
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system_prompt = await _build_system_prompt_with_memories(str(user.id))
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messages_payload = _build_messages_payload(
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conversation, query_text or "", image_description
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conversation, query_text or "", image_description, system_prompt=system_prompt
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)
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payload = {"messages": messages_payload}
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agent_config = {"configurable": {"user_id": str(user.id)}}
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async def event_generator():
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final_message = None
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try:
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async for event in main_agent.astream_events(payload, version="v2"):
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async for event in main_agent.astream_events(
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payload, version="v2", config=agent_config
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):
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event_type = event.get("event")
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if event_type == "on_tool_start":
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@@ -5,9 +5,11 @@ from dotenv import load_dotenv
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from langchain.agents import create_agent
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from langchain.chat_models import BaseChatModel
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from langchain.tools import tool
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from langchain_core.runnables import RunnableConfig
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from langchain_openai import ChatOpenAI
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from tavily import AsyncTavilyClient
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from blueprints.conversation.memory import save_memory
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from blueprints.rag.logic import query_vector_store
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from utils.obsidian_service import ObsidianService
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from utils.ynab_service import YNABService
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@@ -589,8 +591,35 @@ async def obsidian_create_task(
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return f"Error creating task: {str(e)}"
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@tool
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async def save_user_memory(content: str, config: RunnableConfig) -> str:
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"""Save a fact or preference about the user for future conversations.
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Use this tool when the user:
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- Explicitly asks you to remember something ("remember that...", "keep in mind...")
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- Shares a personal preference that would be useful in future conversations
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(e.g., "I prefer metric units", "my cat's name is Luna")
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- Tells you a meaningful personal fact (e.g., "I'm allergic to peanuts")
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Do NOT save:
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- Trivial or ephemeral info (e.g., "I'm tired today")
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- Information already in the system prompt or documents
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- Conversation-specific context that won't matter later
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Args:
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content: A concise statement of the fact or preference to remember.
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Write it as a standalone sentence (e.g., "User prefers dark mode"
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rather than "likes dark mode").
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Returns:
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Confirmation that the memory was saved.
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"""
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user_id = config["configurable"]["user_id"]
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return await save_memory(user_id=user_id, content=content)
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# Create tools list based on what's available
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tools = [get_current_date, simba_search, web_search]
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tools = [get_current_date, simba_search, web_search, save_user_memory]
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if ynab_enabled:
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tools.extend(
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[
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19
blueprints/conversation/memory.py
Normal file
19
blueprints/conversation/memory.py
Normal file
@@ -0,0 +1,19 @@
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from .models import UserMemory
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async def get_memories_for_user(user_id: str) -> list[str]:
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"""Return all memory content strings for a user, ordered by most recently updated."""
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memories = await UserMemory.filter(user_id=user_id).order_by("-updated_at")
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return [m.content for m in memories]
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async def save_memory(user_id: str, content: str) -> str:
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"""Save a new memory or touch an existing one (exact-match dedup)."""
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existing = await UserMemory.filter(user_id=user_id, content=content).first()
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if existing:
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existing.updated_at = None # auto_now=True will refresh it on save
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await existing.save(update_fields=["updated_at"])
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return "Memory already exists (refreshed)."
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await UserMemory.create(user_id=user_id, content=content)
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return "Memory saved."
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@@ -47,6 +47,17 @@ class ConversationMessage(Model):
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table = "conversation_messages"
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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")
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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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@@ -54,4 +54,7 @@ You have access to Ryan's daily journal notes. Each note lives at journal/YYYY/Y
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- Use journal_get_tasks to list tasks (done/pending) for today or a specific date
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- Use journal_add_task to add a new task to today's (or a given date's) note
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- Use journal_complete_task to check off a task as done
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Use these tools when Ryan asks about today's tasks, wants to add something to his list, or wants to mark a task complete."""
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Use these tools when Ryan asks about today's tasks, wants to add something to his list, or wants to mark a task complete.
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USER MEMORY:
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You can remember facts about the user across conversations using the save_user_memory tool. When a user explicitly asks you to remember something, or shares a meaningful preference or personal fact, save it. Saved memories will automatically appear at the end of this prompt in future conversations under "USER MEMORIES"."""
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112
migrations/models/5_20260409215154_add_user_memories.py
Normal file
112
migrations/models/5_20260409215154_add_user_memories.py
Normal file
@@ -0,0 +1,112 @@
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from tortoise import BaseDBAsyncClient
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RUN_IN_TRANSACTION = True
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async def upgrade(db: BaseDBAsyncClient) -> str:
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return """
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CREATE TABLE IF NOT EXISTS "user_memories" (
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"id" UUID NOT NULL PRIMARY KEY,
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"content" TEXT NOT NULL,
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"created_at" TIMESTAMPTZ NOT NULL DEFAULT CURRENT_TIMESTAMP,
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"updated_at" TIMESTAMPTZ NOT NULL DEFAULT CURRENT_TIMESTAMP,
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"user_id" UUID NOT NULL REFERENCES "users" ("id") ON DELETE CASCADE
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);
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CREATE TABLE IF NOT EXISTS "email_accounts" (
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"id" UUID NOT NULL PRIMARY KEY,
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"email_address" VARCHAR(255) NOT NULL UNIQUE,
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"display_name" VARCHAR(255),
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"imap_host" VARCHAR(255) NOT NULL,
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"imap_port" INT NOT NULL DEFAULT 993,
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"imap_username" VARCHAR(255) NOT NULL,
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"imap_password" TEXT NOT NULL,
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"is_active" BOOL NOT NULL DEFAULT True,
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"last_error" TEXT,
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"created_at" TIMESTAMPTZ NOT NULL DEFAULT CURRENT_TIMESTAMP,
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"updated_at" TIMESTAMPTZ NOT NULL DEFAULT CURRENT_TIMESTAMP,
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"user_id" UUID NOT NULL REFERENCES "users" ("id") ON DELETE CASCADE
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);
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COMMENT ON TABLE "email_accounts" IS 'Email account configuration for IMAP connections.';
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CREATE TABLE IF NOT EXISTS "emails" (
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"id" UUID NOT NULL PRIMARY KEY,
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"message_id" VARCHAR(255) NOT NULL UNIQUE,
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"subject" VARCHAR(500) NOT NULL,
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"from_address" VARCHAR(255) NOT NULL,
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"to_address" TEXT NOT NULL,
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"date" TIMESTAMPTZ NOT NULL,
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"body_text" TEXT,
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"body_html" TEXT,
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"chromadb_doc_id" VARCHAR(255),
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"created_at" TIMESTAMPTZ NOT NULL DEFAULT CURRENT_TIMESTAMP,
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"expires_at" TIMESTAMPTZ NOT NULL,
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"account_id" UUID NOT NULL REFERENCES "email_accounts" ("id") ON DELETE CASCADE
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);
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CREATE INDEX IF NOT EXISTS "idx_emails_message_981ddd" ON "emails" ("message_id");
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COMMENT ON TABLE "emails" IS 'Email message metadata and content.';
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CREATE TABLE IF NOT EXISTS "email_sync_status" (
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"id" UUID NOT NULL PRIMARY KEY,
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"last_sync_date" TIMESTAMPTZ,
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"last_message_uid" INT NOT NULL DEFAULT 0,
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"message_count" INT NOT NULL DEFAULT 0,
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"consecutive_failures" INT NOT NULL DEFAULT 0,
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"last_failure_date" TIMESTAMPTZ,
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"updated_at" TIMESTAMPTZ NOT NULL DEFAULT CURRENT_TIMESTAMP,
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"account_id" UUID NOT NULL REFERENCES "email_accounts" ("id") ON DELETE CASCADE
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);
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COMMENT ON TABLE "email_sync_status" IS 'Tracks sync progress and state per email account.';"""
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async def downgrade(db: BaseDBAsyncClient) -> str:
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return """
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DROP TABLE IF EXISTS "user_memories";
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DROP TABLE IF EXISTS "email_accounts";
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DROP TABLE IF EXISTS "emails";
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DROP TABLE IF EXISTS "email_sync_status";"""
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MODELS_STATE = (
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|
||||
)
|
||||
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