* feat: add conversation deletion endpoint (soft delete) [LET-7286]
- Add DELETE /conversations/{conversation_id} endpoint
- Filter soft-deleted conversations from list operations
- Add check_is_deleted=True to update/delete operations
Co-authored-by: Sarah Wooders <sarahwooders@users.noreply.github.com>
🤖 Generated with [Letta Code](https://letta.com)
Co-Authored-By: Letta <noreply@letta.com>
* feat: add tests, update SDK and stainless for delete conversation
- Add 5 integration tests for DELETE conversation endpoint
- Run stage-api to regenerate OpenAPI spec and SDK
- Add delete method to conversations in stainless.yml
Co-authored-by: Sarah Wooders <sarahwooders@users.noreply.github.com>
🤖 Generated with [Letta Code](https://letta.com)
Co-Authored-By: Letta <noreply@letta.com>
* test: add manager-level tests for conversation soft delete [LET-7286]
- test_delete_conversation_removes_from_list
- test_delete_conversation_double_delete_raises
- test_update_deleted_conversation_raises
- test_delete_conversation_excluded_from_summary_search
🤖 Generated with [Letta Code](https://letta.com)
Co-Authored-By: Letta <noreply@letta.com>
---------
Co-authored-by: letta-code <248085862+letta-code@users.noreply.github.com>
Co-authored-by: Letta <noreply@letta.com>
Co-authored-by: Sarah Wooders <sarahwooders@gmail.com>
624 lines
24 KiB
Python
624 lines
24 KiB
Python
from typing import TYPE_CHECKING, Dict, List, Optional
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if TYPE_CHECKING:
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pass
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# Import AgentState outside TYPE_CHECKING for @enforce_types decorator
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from sqlalchemy import delete, func, select
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from letta.errors import LettaInvalidArgumentError
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from letta.orm.agent import Agent as AgentModel
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from letta.orm.block import Block as BlockModel
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from letta.orm.blocks_conversations import BlocksConversations
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from letta.orm.conversation import Conversation as ConversationModel
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from letta.orm.conversation_messages import ConversationMessage as ConversationMessageModel
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from letta.orm.message import Message as MessageModel
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from letta.otel.tracing import trace_method
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from letta.schemas.agent import AgentState
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from letta.schemas.block import Block as PydanticBlock
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from letta.schemas.conversation import Conversation as PydanticConversation, CreateConversation, UpdateConversation
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from letta.schemas.letta_message import LettaMessage
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from letta.schemas.message import Message as PydanticMessage
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from letta.schemas.user import User as PydanticUser
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from letta.server.db import db_registry
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from letta.services.helpers.agent_manager_helper import validate_agent_exists_async
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from letta.utils import enforce_types
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class ConversationManager:
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"""Manager class to handle business logic related to Conversations."""
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@enforce_types
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@trace_method
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async def create_conversation(
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self,
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agent_id: str,
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conversation_create: CreateConversation,
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actor: PydanticUser,
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) -> PydanticConversation:
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"""Create a new conversation for an agent.
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Args:
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agent_id: The ID of the agent this conversation belongs to
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conversation_create: The conversation creation request, optionally including
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isolated_block_labels for conversation-specific memory blocks
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actor: The user performing the action
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Returns:
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The created conversation with isolated_block_ids if any were created
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"""
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async with db_registry.async_session() as session:
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# Validate that the agent exists before creating the conversation
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await validate_agent_exists_async(session, agent_id, actor)
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conversation = ConversationModel(
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agent_id=agent_id,
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summary=conversation_create.summary,
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organization_id=actor.organization_id,
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)
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await conversation.create_async(session, actor=actor)
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# Handle isolated blocks if requested
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isolated_block_ids = []
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if conversation_create.isolated_block_labels:
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isolated_block_ids = await self._create_isolated_blocks(
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session=session,
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conversation=conversation,
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agent_id=agent_id,
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isolated_block_labels=conversation_create.isolated_block_labels,
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actor=actor,
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)
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pydantic_conversation = conversation.to_pydantic()
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pydantic_conversation.isolated_block_ids = isolated_block_ids
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return pydantic_conversation
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@enforce_types
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@trace_method
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async def get_conversation_by_id(
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self,
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conversation_id: str,
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actor: PydanticUser,
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) -> PydanticConversation:
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"""Retrieve a conversation by its ID, including in-context message IDs."""
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async with db_registry.async_session() as session:
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conversation = await ConversationModel.read_async(
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db_session=session,
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identifier=conversation_id,
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actor=actor,
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check_is_deleted=True,
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)
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# Get the in-context message IDs for this conversation
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message_ids = await self.get_message_ids_for_conversation(
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conversation_id=conversation_id,
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actor=actor,
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)
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# Build the pydantic model with in_context_message_ids
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pydantic_conversation = conversation.to_pydantic()
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pydantic_conversation.in_context_message_ids = message_ids
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return pydantic_conversation
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@enforce_types
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@trace_method
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async def list_conversations(
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self,
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agent_id: Optional[str],
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actor: PydanticUser,
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limit: int = 50,
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after: Optional[str] = None,
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summary_search: Optional[str] = None,
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) -> List[PydanticConversation]:
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"""List conversations for an agent (or all conversations) with cursor-based pagination.
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Args:
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agent_id: The agent ID to list conversations for (optional - returns all if not provided)
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actor: The user performing the action
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limit: Maximum number of conversations to return
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after: Cursor for pagination (conversation ID)
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summary_search: Optional text to search for within the summary field
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Returns:
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List of conversations matching the criteria
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"""
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async with db_registry.async_session() as session:
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# If summary search is provided, use custom query
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if summary_search:
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from sqlalchemy import and_
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# Build where conditions
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conditions = [
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ConversationModel.organization_id == actor.organization_id,
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ConversationModel.is_deleted == False,
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ConversationModel.summary.isnot(None),
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ConversationModel.summary.contains(summary_search),
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]
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# Add agent_id filter if provided
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if agent_id is not None:
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conditions.append(ConversationModel.agent_id == agent_id)
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stmt = select(ConversationModel).where(and_(*conditions)).order_by(ConversationModel.created_at.desc()).limit(limit)
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if after:
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# Add cursor filtering
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after_conv = await ConversationModel.read_async(
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db_session=session,
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identifier=after,
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actor=actor,
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)
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stmt = stmt.where(ConversationModel.created_at < after_conv.created_at)
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result = await session.execute(stmt)
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conversations = result.scalars().all()
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return [conv.to_pydantic() for conv in conversations]
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# Use default list logic
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conversations = await ConversationModel.list_async(
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db_session=session,
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actor=actor,
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agent_id=agent_id,
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is_deleted=False,
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limit=limit,
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after=after,
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ascending=False,
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)
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return [conv.to_pydantic() for conv in conversations]
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@enforce_types
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@trace_method
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async def update_conversation(
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self,
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conversation_id: str,
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conversation_update: UpdateConversation,
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actor: PydanticUser,
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) -> PydanticConversation:
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"""Update a conversation."""
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async with db_registry.async_session() as session:
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conversation = await ConversationModel.read_async(
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db_session=session,
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identifier=conversation_id,
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actor=actor,
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check_is_deleted=True,
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)
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# Set attributes on the model
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update_data = conversation_update.model_dump(exclude_none=True)
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for key, value in update_data.items():
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setattr(conversation, key, value)
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# Commit the update
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updated_conversation = await conversation.update_async(
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db_session=session,
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actor=actor,
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)
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return updated_conversation.to_pydantic()
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@enforce_types
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@trace_method
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async def delete_conversation(
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self,
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conversation_id: str,
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actor: PydanticUser,
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) -> None:
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"""Soft delete a conversation and hard-delete its isolated blocks."""
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async with db_registry.async_session() as session:
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conversation = await ConversationModel.read_async(
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db_session=session,
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identifier=conversation_id,
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actor=actor,
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check_is_deleted=True,
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)
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# Get isolated blocks before modifying conversation
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isolated_blocks = list(conversation.isolated_blocks)
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# Soft delete the conversation first
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conversation.is_deleted = True
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await conversation.update_async(db_session=session, actor=actor)
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# Hard-delete isolated blocks (Block model doesn't support soft-delete)
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# Following same pattern as block_manager.delete_block_async
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for block in isolated_blocks:
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# Delete junction table entry first
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await session.execute(delete(BlocksConversations).where(BlocksConversations.block_id == block.id))
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await session.flush()
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# Then hard-delete the block
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await block.hard_delete_async(db_session=session, actor=actor)
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# ==================== Message Management Methods ====================
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@enforce_types
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@trace_method
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async def get_message_ids_for_conversation(
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self,
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conversation_id: str,
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actor: PydanticUser,
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) -> List[str]:
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"""
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Get ordered message IDs for a conversation.
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Returns message IDs ordered by position in the conversation.
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Only returns messages that are currently in_context.
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"""
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async with db_registry.async_session() as session:
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query = (
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select(ConversationMessageModel.message_id)
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.where(
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ConversationMessageModel.conversation_id == conversation_id,
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ConversationMessageModel.organization_id == actor.organization_id,
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ConversationMessageModel.in_context == True,
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ConversationMessageModel.is_deleted == False,
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)
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.order_by(ConversationMessageModel.position)
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)
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result = await session.execute(query)
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return list(result.scalars().all())
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@enforce_types
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@trace_method
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async def get_messages_for_conversation(
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self,
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conversation_id: str,
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actor: PydanticUser,
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) -> List[PydanticMessage]:
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"""
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Get ordered Message objects for a conversation.
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Returns full Message objects ordered by position in the conversation.
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Only returns messages that are currently in_context.
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"""
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async with db_registry.async_session() as session:
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query = (
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select(MessageModel)
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.join(
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ConversationMessageModel,
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MessageModel.id == ConversationMessageModel.message_id,
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)
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.where(
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ConversationMessageModel.conversation_id == conversation_id,
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ConversationMessageModel.organization_id == actor.organization_id,
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ConversationMessageModel.in_context == True,
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ConversationMessageModel.is_deleted == False,
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)
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.order_by(ConversationMessageModel.position)
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)
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result = await session.execute(query)
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return [msg.to_pydantic() for msg in result.scalars().all()]
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@enforce_types
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@trace_method
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async def add_messages_to_conversation(
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self,
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conversation_id: str,
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agent_id: str,
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message_ids: List[str],
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actor: PydanticUser,
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starting_position: Optional[int] = None,
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) -> None:
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"""
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Add messages to a conversation's tracking table.
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Creates ConversationMessage entries with auto-incrementing positions.
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Args:
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conversation_id: The conversation to add messages to
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agent_id: The agent ID
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message_ids: List of message IDs to add
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actor: The user performing the action
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starting_position: Optional starting position (defaults to next available)
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"""
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if not message_ids:
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return
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async with db_registry.async_session() as session:
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# Get starting position if not provided
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if starting_position is None:
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query = select(func.coalesce(func.max(ConversationMessageModel.position), -1)).where(
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ConversationMessageModel.conversation_id == conversation_id,
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ConversationMessageModel.organization_id == actor.organization_id,
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)
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result = await session.execute(query)
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max_position = result.scalar()
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# Use explicit None check instead of `or` to handle position=0 correctly
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if max_position is None:
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max_position = -1
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starting_position = max_position + 1
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# Create ConversationMessage entries
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for i, message_id in enumerate(message_ids):
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conv_msg = ConversationMessageModel(
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conversation_id=conversation_id,
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agent_id=agent_id,
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message_id=message_id,
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position=starting_position + i,
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in_context=True,
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organization_id=actor.organization_id,
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)
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session.add(conv_msg)
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await session.commit()
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@enforce_types
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@trace_method
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async def update_in_context_messages(
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self,
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conversation_id: str,
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in_context_message_ids: List[str],
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actor: PydanticUser,
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) -> None:
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"""
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Update which messages are in context for a conversation.
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Sets in_context=True for messages in the list, False for others.
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Also updates positions to preserve the order specified in in_context_message_ids.
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This is critical for correctness: when summarization inserts a summary message
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that needs to appear before an approval request, the positions must reflect
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the intended order, not the insertion order.
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Args:
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conversation_id: The conversation to update
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in_context_message_ids: List of message IDs in the desired order
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actor: The user performing the action
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"""
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async with db_registry.async_session() as session:
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# Get all conversation messages for this conversation
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query = select(ConversationMessageModel).where(
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ConversationMessageModel.conversation_id == conversation_id,
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ConversationMessageModel.organization_id == actor.organization_id,
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ConversationMessageModel.is_deleted == False,
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)
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result = await session.execute(query)
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conv_messages = result.scalars().all()
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# Build lookup dict
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conv_msg_dict = {cm.message_id: cm for cm in conv_messages}
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# Update in_context status AND positions
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in_context_set = set(in_context_message_ids)
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for conv_msg in conv_messages:
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conv_msg.in_context = conv_msg.message_id in in_context_set
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# Update positions to match the order in in_context_message_ids
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# This ensures ORDER BY position returns messages in the correct order
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for position, message_id in enumerate(in_context_message_ids):
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if message_id in conv_msg_dict:
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conv_msg_dict[message_id].position = position
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await session.commit()
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@enforce_types
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@trace_method
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async def list_conversation_messages(
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self,
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conversation_id: str,
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actor: PydanticUser,
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limit: Optional[int] = 100,
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before: Optional[str] = None,
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after: Optional[str] = None,
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reverse: bool = False,
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group_id: Optional[str] = None,
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include_err: Optional[bool] = None,
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) -> List[LettaMessage]:
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"""
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List all messages in a conversation with pagination support.
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Unlike get_messages_for_conversation, this returns ALL messages
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(not just in_context) and supports cursor-based pagination.
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Args:
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conversation_id: The conversation to list messages for
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actor: The user performing the action
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limit: Maximum number of messages to return
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before: Return messages before this message ID
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after: Return messages after this message ID
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reverse: If True, return messages in descending order (newest first)
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group_id: Optional group ID to filter messages by
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include_err: Optional boolean to include error messages and error statuses
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Returns:
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List of LettaMessage objects
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"""
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async with db_registry.async_session() as session:
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# Build base query joining Message with ConversationMessage
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query = (
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select(MessageModel)
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.join(
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ConversationMessageModel,
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MessageModel.id == ConversationMessageModel.message_id,
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)
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.where(
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ConversationMessageModel.conversation_id == conversation_id,
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ConversationMessageModel.organization_id == actor.organization_id,
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ConversationMessageModel.is_deleted == False,
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)
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)
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# Filter by group_id if provided
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if group_id:
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query = query.where(MessageModel.group_id == group_id)
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# Handle cursor-based pagination
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if before:
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# Get the position of the cursor message
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cursor_query = select(ConversationMessageModel.position).where(
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ConversationMessageModel.conversation_id == conversation_id,
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ConversationMessageModel.message_id == before,
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)
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cursor_result = await session.execute(cursor_query)
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cursor_position = cursor_result.scalar_one_or_none()
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if cursor_position is not None:
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query = query.where(ConversationMessageModel.position < cursor_position)
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if after:
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# Get the position of the cursor message
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cursor_query = select(ConversationMessageModel.position).where(
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ConversationMessageModel.conversation_id == conversation_id,
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ConversationMessageModel.message_id == after,
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)
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cursor_result = await session.execute(cursor_query)
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cursor_position = cursor_result.scalar_one_or_none()
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if cursor_position is not None:
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query = query.where(ConversationMessageModel.position > cursor_position)
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# Order by position
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if reverse:
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query = query.order_by(ConversationMessageModel.position.desc())
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else:
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query = query.order_by(ConversationMessageModel.position.asc())
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# Apply limit
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if limit is not None:
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query = query.limit(limit)
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result = await session.execute(query)
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messages = [msg.to_pydantic() for msg in result.scalars().all()]
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# Convert to LettaMessages (reverse=False keeps sub-messages in natural order)
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return PydanticMessage.to_letta_messages_from_list(
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messages, reverse=False, include_err=include_err, text_is_assistant_message=True
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)
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|
# ==================== Isolated Blocks Methods ====================
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|
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async def _create_isolated_blocks(
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self,
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session,
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conversation: ConversationModel,
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agent_id: str,
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isolated_block_labels: List[str],
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actor: PydanticUser,
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) -> List[str]:
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"""Create conversation-specific copies of blocks for isolated labels.
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Args:
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session: The database session
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conversation: The conversation model (must be created but not yet committed)
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agent_id: The agent ID to get source blocks from
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isolated_block_labels: List of block labels to isolate
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|
actor: The user performing the action
|
|
|
|
Returns:
|
|
List of created block IDs
|
|
|
|
Raises:
|
|
LettaInvalidArgumentError: If a block label is not found on the agent
|
|
"""
|
|
# Get the agent with its blocks
|
|
agent = await AgentModel.read_async(db_session=session, identifier=agent_id, actor=actor)
|
|
|
|
# Map of label -> agent block
|
|
agent_blocks_by_label = {block.label: block for block in agent.core_memory}
|
|
|
|
created_block_ids = []
|
|
for label in isolated_block_labels:
|
|
if label not in agent_blocks_by_label:
|
|
raise LettaInvalidArgumentError(
|
|
f"Block with label '{label}' not found on agent '{agent_id}'",
|
|
argument_name="isolated_block_labels",
|
|
)
|
|
|
|
source_block = agent_blocks_by_label[label]
|
|
|
|
# Create a copy of the block with a new ID using Pydantic schema (which auto-generates ID)
|
|
new_block_pydantic = PydanticBlock(
|
|
label=source_block.label,
|
|
description=source_block.description,
|
|
value=source_block.value,
|
|
limit=source_block.limit,
|
|
metadata=source_block.metadata_,
|
|
read_only=source_block.read_only,
|
|
)
|
|
|
|
# Convert to ORM model
|
|
block_data = new_block_pydantic.model_dump(to_orm=True, exclude_none=True)
|
|
new_block = BlockModel(**block_data, organization_id=actor.organization_id)
|
|
await new_block.create_async(session, actor=actor)
|
|
|
|
# Create the junction table entry
|
|
blocks_conv = BlocksConversations(
|
|
conversation_id=conversation.id,
|
|
block_id=new_block.id,
|
|
block_label=label,
|
|
)
|
|
session.add(blocks_conv)
|
|
created_block_ids.append(new_block.id)
|
|
|
|
return created_block_ids
|
|
|
|
@enforce_types
|
|
@trace_method
|
|
async def get_isolated_blocks_for_conversation(
|
|
self,
|
|
conversation_id: str,
|
|
actor: PydanticUser,
|
|
) -> Dict[str, PydanticBlock]:
|
|
"""Get isolated blocks for a conversation, keyed by label.
|
|
|
|
Args:
|
|
conversation_id: The conversation ID
|
|
actor: The user performing the action
|
|
|
|
Returns:
|
|
Dictionary mapping block labels to their conversation-specific blocks
|
|
"""
|
|
async with db_registry.async_session() as session:
|
|
conversation = await ConversationModel.read_async(
|
|
db_session=session,
|
|
identifier=conversation_id,
|
|
actor=actor,
|
|
check_is_deleted=True,
|
|
)
|
|
return {block.label: block.to_pydantic() for block in conversation.isolated_blocks}
|
|
|
|
@enforce_types
|
|
@trace_method
|
|
async def apply_isolated_blocks_to_agent_state(
|
|
self,
|
|
agent_state: "AgentState",
|
|
conversation_id: str,
|
|
actor: PydanticUser,
|
|
) -> "AgentState":
|
|
"""Apply conversation-specific block overrides to an agent state.
|
|
|
|
This method modifies the agent_state.memory to replace blocks that have
|
|
conversation-specific isolated versions.
|
|
|
|
Args:
|
|
agent_state: The agent state to modify (will be modified in place)
|
|
conversation_id: The conversation ID to get isolated blocks from
|
|
actor: The user performing the action
|
|
|
|
Returns:
|
|
The modified agent state (same object, modified in place)
|
|
"""
|
|
from letta.schemas.memory import Memory
|
|
|
|
# Get conversation's isolated blocks
|
|
isolated_blocks = await self.get_isolated_blocks_for_conversation(
|
|
conversation_id=conversation_id,
|
|
actor=actor,
|
|
)
|
|
|
|
if not isolated_blocks:
|
|
return agent_state
|
|
|
|
# Override agent's blocks with conversation-specific blocks
|
|
memory_blocks = []
|
|
for block in agent_state.memory.blocks:
|
|
if block.label in isolated_blocks:
|
|
memory_blocks.append(isolated_blocks[block.label])
|
|
else:
|
|
memory_blocks.append(block)
|
|
|
|
# Create new Memory with overridden blocks
|
|
agent_state.memory = Memory(
|
|
blocks=memory_blocks,
|
|
file_blocks=agent_state.memory.file_blocks,
|
|
agent_type=agent_state.memory.agent_type,
|
|
git_enabled=agent_state.memory.git_enabled,
|
|
)
|
|
|
|
return agent_state
|