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97 lines
4.6 KiB
Python
97 lines
4.6 KiB
Python
from typing import List, Optional
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from openai.types.chat.chat_completion_message_tool_call import ChatCompletionMessageToolCall as OpenAIToolCall
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from sqlalchemy import BigInteger, FetchedValue, ForeignKey, Index, event, text
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from sqlalchemy.orm import Mapped, Session, mapped_column, relationship
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from letta.orm.custom_columns import MessageContentColumn, ToolCallColumn, ToolReturnColumn
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from letta.orm.mixins import AgentMixin, OrganizationMixin
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from letta.orm.sqlalchemy_base import SqlalchemyBase
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from letta.schemas.letta_message_content import MessageContent
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from letta.schemas.letta_message_content import TextContent as PydanticTextContent
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from letta.schemas.message import Message as PydanticMessage
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from letta.schemas.message import ToolReturn
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from letta.settings import settings
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class Message(SqlalchemyBase, OrganizationMixin, AgentMixin):
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"""Defines data model for storing Message objects"""
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__tablename__ = "messages"
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__table_args__ = (
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Index("ix_messages_agent_created_at", "agent_id", "created_at"),
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Index("ix_messages_created_at", "created_at", "id"),
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Index("ix_messages_agent_sequence", "agent_id", "sequence_id"),
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)
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__pydantic_model__ = PydanticMessage
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id: Mapped[str] = mapped_column(primary_key=True, doc="Unique message identifier")
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role: Mapped[str] = mapped_column(doc="Message role (user/assistant/system/tool)")
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text: Mapped[Optional[str]] = mapped_column(nullable=True, doc="Message content")
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content: Mapped[List[MessageContent]] = mapped_column(MessageContentColumn, nullable=True, doc="Message content parts")
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model: Mapped[Optional[str]] = mapped_column(nullable=True, doc="LLM model used")
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name: Mapped[Optional[str]] = mapped_column(nullable=True, doc="Name for multi-agent scenarios")
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tool_calls: Mapped[List[OpenAIToolCall]] = mapped_column(ToolCallColumn, doc="Tool call information")
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tool_call_id: Mapped[Optional[str]] = mapped_column(nullable=True, doc="ID of the tool call")
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step_id: Mapped[Optional[str]] = mapped_column(
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ForeignKey("steps.id", ondelete="SET NULL"), nullable=True, doc="ID of the step that this message belongs to"
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)
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otid: Mapped[Optional[str]] = mapped_column(nullable=True, doc="The offline threading ID associated with this message")
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tool_returns: Mapped[List[ToolReturn]] = mapped_column(
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ToolReturnColumn, nullable=True, doc="Tool execution return information for prior tool calls"
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)
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group_id: Mapped[Optional[str]] = mapped_column(nullable=True, doc="The multi-agent group that the message was sent in")
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sender_id: Mapped[Optional[str]] = mapped_column(
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nullable=True, doc="The id of the sender of the message, can be an identity id or agent id"
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)
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# Monotonically increasing sequence for efficient/correct listing
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sequence_id: Mapped[int] = mapped_column(
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BigInteger,
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server_default=FetchedValue(),
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unique=True,
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nullable=False,
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)
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# Relationships
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organization: Mapped["Organization"] = relationship("Organization", back_populates="messages", lazy="selectin")
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step: Mapped["Step"] = relationship("Step", back_populates="messages", lazy="selectin")
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# Job relationship
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job_message: Mapped[Optional["JobMessage"]] = relationship(
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"JobMessage", back_populates="message", uselist=False, cascade="all, delete-orphan", single_parent=True
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)
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@property
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def job(self) -> Optional["Job"]:
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"""Get the job associated with this message, if any."""
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return self.job_message.job if self.job_message else None
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def to_pydantic(self) -> PydanticMessage:
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"""Custom pydantic conversion to handle data using legacy text field"""
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model = self.__pydantic_model__.model_validate(self)
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if self.text and not model.content:
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model.content = [PydanticTextContent(text=self.text)]
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# If there are no tool calls, set tool_calls to None
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if len(self.tool_calls) == 0:
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model.tool_calls = None
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return model
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# listener
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@event.listens_for(Message, "before_insert")
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def set_sequence_id_for_sqlite(mapper, connection, target):
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# TODO: Kind of hacky, used to detect if we are using sqlite or not
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if not settings.letta_pg_uri_no_default:
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session = Session.object_session(target)
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if not hasattr(session, "_sequence_id_counter"):
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# Initialize counter for this flush
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max_seq = connection.scalar(text("SELECT MAX(sequence_id) FROM messages"))
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session._sequence_id_counter = max_seq or 0
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session._sequence_id_counter += 1
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target.sequence_id = session._sequence_id_counter
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