627 lines
17 KiB
Python
627 lines
17 KiB
Python
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"""Data models for interacting with the LangGraph API."""
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from __future__ import annotations
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from collections.abc import Mapping, Sequence
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from dataclasses import Field
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from datetime import datetime
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from typing import (
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Any,
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ClassVar,
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Literal,
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NamedTuple,
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Protocol,
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TypeAlias,
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Union,
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)
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from typing_extensions import TypedDict
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Json = dict[str, Any] | None
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"""Represents a JSON-like structure, which can be None or a dictionary with string keys and any values."""
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RunStatus = Literal["pending", "running", "error", "success", "timeout", "interrupted"]
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"""
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Represents the status of a run:
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- "pending": The run is waiting to start.
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- "running": The run is currently executing.
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- "error": The run encountered an error and stopped.
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- "success": The run completed successfully.
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- "timeout": The run exceeded its time limit.
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- "interrupted": The run was manually stopped or interrupted.
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"""
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ThreadStatus = Literal["idle", "busy", "interrupted", "error"]
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"""
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Represents the status of a thread:
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- "idle": The thread is not currently processing any task.
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- "busy": The thread is actively processing a task.
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- "interrupted": The thread's execution was interrupted.
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- "error": An exception occurred during task processing.
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"""
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ThreadStreamMode = Literal["run_modes", "lifecycle", "state_update"]
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"""
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Defines the mode of streaming:
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- "run_modes": Stream the same events as the runs on thread, as well as run_done events.
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- "lifecycle": Stream only run start/end events.
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- "state_update": Stream state updates on the thread.
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"""
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StreamMode = Literal[
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"values",
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"messages",
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"updates",
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"events",
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"tasks",
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"checkpoints",
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"debug",
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"custom",
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"messages-tuple",
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]
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"""
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Defines the mode of streaming:
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- "values": Stream only the values.
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- "messages": Stream complete messages.
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- "updates": Stream updates to the state.
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- "events": Stream events occurring during execution.
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- "checkpoints": Stream checkpoints as they are created.
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- "tasks": Stream task start and finish events.
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- "debug": Stream detailed debug information.
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- "custom": Stream custom events.
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"""
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DisconnectMode = Literal["cancel", "continue"]
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"""
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Specifies behavior on disconnection:
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- "cancel": Cancel the operation on disconnection.
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- "continue": Continue the operation even if disconnected.
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"""
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MultitaskStrategy = Literal["reject", "interrupt", "rollback", "enqueue"]
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"""
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Defines how to handle multiple tasks:
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- "reject": Reject new tasks when busy.
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- "interrupt": Interrupt current task for new ones.
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- "rollback": Roll back current task and start new one.
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- "enqueue": Queue new tasks for later execution.
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"""
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OnConflictBehavior = Literal["raise", "do_nothing"]
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"""
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Specifies behavior on conflict:
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- "raise": Raise an exception when a conflict occurs.
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- "do_nothing": Ignore conflicts and proceed.
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"""
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OnCompletionBehavior = Literal["delete", "keep"]
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"""
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Defines action after completion:
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- "delete": Delete resources after completion.
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- "keep": Retain resources after completion.
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"""
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Durability = Literal["sync", "async", "exit"]
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"""Durability mode for the graph execution.
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- `"sync"`: Changes are persisted synchronously before the next step starts.
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- `"async"`: Changes are persisted asynchronously while the next step executes.
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- `"exit"`: Changes are persisted only when the graph exits."""
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All = Literal["*"]
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"""Represents a wildcard or 'all' selector."""
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IfNotExists = Literal["create", "reject"]
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"""
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Specifies behavior if the thread doesn't exist:
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- "create": Create a new thread if it doesn't exist.
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- "reject": Reject the operation if the thread doesn't exist.
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"""
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CancelAction = Literal["interrupt", "rollback"]
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"""
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Action to take when cancelling the run.
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- "interrupt": Simply cancel the run.
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- "rollback": Cancel the run. Then delete the run and associated checkpoints.
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"""
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AssistantSortBy = Literal[
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"assistant_id", "graph_id", "name", "created_at", "updated_at"
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]
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"""
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The field to sort by.
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"""
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ThreadSortBy = Literal["thread_id", "status", "created_at", "updated_at"]
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"""
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The field to sort by.
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"""
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CronSortBy = Literal[
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"cron_id", "assistant_id", "thread_id", "created_at", "updated_at", "next_run_date"
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]
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"""
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The field to sort by.
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"""
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SortOrder = Literal["asc", "desc"]
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"""
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The order to sort by.
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"""
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class Config(TypedDict, total=False):
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"""Configuration options for a call."""
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tags: list[str]
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"""
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Tags for this call and any sub-calls (eg. a Chain calling an LLM).
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You can use these to filter calls.
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"""
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recursion_limit: int
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"""
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Maximum number of times a call can recurse. If not provided, defaults to 25.
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"""
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configurable: dict[str, Any]
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"""
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Runtime values for attributes previously made configurable on this Runnable,
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or sub-Runnables, through .configurable_fields() or .configurable_alternatives().
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Check .output_schema() for a description of the attributes that have been made
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configurable.
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"""
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class Checkpoint(TypedDict):
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"""Represents a checkpoint in the execution process."""
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thread_id: str
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"""Unique identifier for the thread associated with this checkpoint."""
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checkpoint_ns: str
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"""Namespace for the checkpoint; used internally to manage subgraph state."""
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checkpoint_id: str | None
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"""Optional unique identifier for the checkpoint itself."""
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checkpoint_map: dict[str, Any] | None
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"""Optional dictionary containing checkpoint-specific data."""
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class GraphSchema(TypedDict):
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"""Defines the structure and properties of a graph."""
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graph_id: str
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"""The ID of the graph."""
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input_schema: dict | None
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"""The schema for the graph input.
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Missing if unable to generate JSON schema from graph."""
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output_schema: dict | None
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"""The schema for the graph output.
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Missing if unable to generate JSON schema from graph."""
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state_schema: dict | None
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"""The schema for the graph state.
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Missing if unable to generate JSON schema from graph."""
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config_schema: dict | None
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"""The schema for the graph config.
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Missing if unable to generate JSON schema from graph."""
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context_schema: dict | None
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"""The schema for the graph context.
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Missing if unable to generate JSON schema from graph."""
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Subgraphs = dict[str, GraphSchema]
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class AssistantBase(TypedDict):
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"""Base model for an assistant."""
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assistant_id: str
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"""The ID of the assistant."""
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graph_id: str
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"""The ID of the graph."""
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config: Config
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"""The assistant config."""
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context: Context
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"""The static context of the assistant."""
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created_at: datetime
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"""The time the assistant was created."""
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metadata: Json
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"""The assistant metadata."""
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version: int
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"""The version of the assistant"""
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name: str
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"""The name of the assistant"""
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description: str | None
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"""The description of the assistant"""
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class AssistantVersion(AssistantBase):
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"""Represents a specific version of an assistant."""
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pass
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class Assistant(AssistantBase):
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"""Represents an assistant with additional properties."""
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updated_at: datetime
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"""The last time the assistant was updated."""
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class AssistantsSearchResponse(TypedDict):
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"""Paginated response for assistant search results."""
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assistants: list[Assistant]
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"""The assistants returned for the current search page."""
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next: str | None
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"""Pagination cursor from the ``X-Pagination-Next`` response header."""
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class Interrupt(TypedDict):
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"""Represents an interruption in the execution flow."""
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value: Any
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"""The value associated with the interrupt."""
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id: str
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"""The ID of the interrupt. Can be used to resume the interrupt."""
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class Thread(TypedDict):
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"""Represents a conversation thread."""
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thread_id: str
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"""The ID of the thread."""
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created_at: datetime
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"""The time the thread was created."""
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updated_at: datetime
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"""The last time the thread was updated."""
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metadata: Json
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"""The thread metadata."""
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status: ThreadStatus
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"""The status of the thread, one of 'idle', 'busy', 'interrupted'."""
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values: Json
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"""The current state of the thread."""
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interrupts: dict[str, list[Interrupt]]
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"""Mapping of task ids to interrupts that were raised in that task."""
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class ThreadTask(TypedDict):
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"""Represents a task within a thread."""
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id: str
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name: str
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error: str | None
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interrupts: list[Interrupt]
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checkpoint: Checkpoint | None
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state: ThreadState | None
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result: dict[str, Any] | None
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class ThreadState(TypedDict):
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"""Represents the state of a thread."""
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values: list[dict] | dict[str, Any]
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"""The state values."""
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next: Sequence[str]
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"""The next nodes to execute. If empty, the thread is done until new input is
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received."""
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checkpoint: Checkpoint
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"""The ID of the checkpoint."""
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metadata: Json
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"""Metadata for this state"""
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created_at: str | None
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"""Timestamp of state creation"""
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parent_checkpoint: Checkpoint | None
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"""The ID of the parent checkpoint. If missing, this is the root checkpoint."""
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tasks: Sequence[ThreadTask]
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"""Tasks to execute in this step. If already attempted, may contain an error."""
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interrupts: list[Interrupt]
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"""Interrupts which were thrown in this thread."""
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class ThreadUpdateStateResponse(TypedDict):
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"""Represents the response from updating a thread's state."""
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checkpoint: Checkpoint
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"""Checkpoint of the latest state."""
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class Run(TypedDict):
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"""Represents a single execution run."""
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run_id: str
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"""The ID of the run."""
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thread_id: str
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"""The ID of the thread."""
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assistant_id: str
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"""The assistant that was used for this run."""
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created_at: datetime
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"""The time the run was created."""
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updated_at: datetime
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"""The last time the run was updated."""
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status: RunStatus
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"""The status of the run. One of 'pending', 'running', "error", 'success', "timeout", "interrupted"."""
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metadata: Json
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"""The run metadata."""
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multitask_strategy: MultitaskStrategy
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"""Strategy to handle concurrent runs on the same thread."""
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class Cron(TypedDict):
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"""Represents a scheduled task."""
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cron_id: str
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"""The ID of the cron."""
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assistant_id: str
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"""The ID of the assistant."""
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thread_id: str | None
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"""The ID of the thread."""
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end_time: datetime | None
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"""The end date to stop running the cron."""
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schedule: str
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"""The schedule to run, cron format."""
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created_at: datetime
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"""The time the cron was created."""
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updated_at: datetime
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"""The last time the cron was updated."""
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payload: dict
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"""The run payload to use for creating new run."""
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user_id: str | None
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"""The user ID of the cron."""
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next_run_date: datetime | None
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"""The next run date of the cron."""
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metadata: dict
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"""The metadata of the cron."""
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# Select field aliases for client-side typing of `select` parameters.
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# These mirror the server's allowed field sets.
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AssistantSelectField = Literal[
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"assistant_id",
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"graph_id",
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"name",
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"description",
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"config",
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"context",
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"created_at",
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"updated_at",
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"metadata",
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"version",
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]
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ThreadSelectField = Literal[
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"thread_id",
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"created_at",
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"updated_at",
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"metadata",
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"config",
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"context",
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"status",
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"values",
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"interrupts",
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]
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RunSelectField = Literal[
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"run_id",
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"thread_id",
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"assistant_id",
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"created_at",
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"updated_at",
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"status",
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"metadata",
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"kwargs",
|
||
|
|
"multitask_strategy",
|
||
|
|
]
|
||
|
|
|
||
|
|
CronSelectField = Literal[
|
||
|
|
"cron_id",
|
||
|
|
"assistant_id",
|
||
|
|
"thread_id",
|
||
|
|
"end_time",
|
||
|
|
"schedule",
|
||
|
|
"created_at",
|
||
|
|
"updated_at",
|
||
|
|
"user_id",
|
||
|
|
"payload",
|
||
|
|
"next_run_date",
|
||
|
|
"metadata",
|
||
|
|
"now",
|
||
|
|
"on_run_completed",
|
||
|
|
]
|
||
|
|
|
||
|
|
PrimitiveData = str | int | float | bool | None
|
||
|
|
|
||
|
|
QueryParamTypes = (
|
||
|
|
Mapping[str, PrimitiveData | Sequence[PrimitiveData]]
|
||
|
|
| list[tuple[str, PrimitiveData]]
|
||
|
|
| tuple[tuple[str, PrimitiveData], ...]
|
||
|
|
| str
|
||
|
|
| bytes
|
||
|
|
)
|
||
|
|
|
||
|
|
|
||
|
|
class RunCreate(TypedDict):
|
||
|
|
"""Defines the parameters for initiating a background run."""
|
||
|
|
|
||
|
|
thread_id: str | None
|
||
|
|
"""The identifier of the thread to run. If not provided, the run is stateless."""
|
||
|
|
assistant_id: str
|
||
|
|
"""The identifier of the assistant to use for this run."""
|
||
|
|
input: dict | None
|
||
|
|
"""Initial input data for the run."""
|
||
|
|
metadata: dict | None
|
||
|
|
"""Additional metadata to associate with the run."""
|
||
|
|
config: Config | None
|
||
|
|
"""Configuration options for the run."""
|
||
|
|
context: Context | None
|
||
|
|
"""The static context of the run."""
|
||
|
|
checkpoint_id: str | None
|
||
|
|
"""The identifier of a checkpoint to resume from."""
|
||
|
|
interrupt_before: list[str] | None
|
||
|
|
"""List of node names to interrupt execution before."""
|
||
|
|
interrupt_after: list[str] | None
|
||
|
|
"""List of node names to interrupt execution after."""
|
||
|
|
webhook: str | None
|
||
|
|
"""URL to send webhook notifications about the run's progress."""
|
||
|
|
multitask_strategy: MultitaskStrategy | None
|
||
|
|
"""Strategy for handling concurrent runs on the same thread."""
|
||
|
|
|
||
|
|
|
||
|
|
class Item(TypedDict):
|
||
|
|
"""Represents a single document or data entry in the graph's Store.
|
||
|
|
|
||
|
|
Items are used to store cross-thread memories.
|
||
|
|
"""
|
||
|
|
|
||
|
|
namespace: list[str]
|
||
|
|
"""The namespace of the item. A namespace is analogous to a document's directory."""
|
||
|
|
key: str
|
||
|
|
"""The unique identifier of the item within its namespace.
|
||
|
|
|
||
|
|
In general, keys needn't be globally unique.
|
||
|
|
"""
|
||
|
|
value: dict[str, Any]
|
||
|
|
"""The value stored in the item. This is the document itself."""
|
||
|
|
created_at: datetime
|
||
|
|
"""The timestamp when the item was created."""
|
||
|
|
updated_at: datetime
|
||
|
|
"""The timestamp when the item was last updated."""
|
||
|
|
|
||
|
|
|
||
|
|
class ListNamespaceResponse(TypedDict):
|
||
|
|
"""Response structure for listing namespaces."""
|
||
|
|
|
||
|
|
namespaces: list[list[str]]
|
||
|
|
"""A list of namespace paths, where each path is a list of strings."""
|
||
|
|
|
||
|
|
|
||
|
|
class SearchItem(Item, total=False):
|
||
|
|
"""Item with an optional relevance score from search operations.
|
||
|
|
|
||
|
|
Attributes:
|
||
|
|
score (Optional[float]): Relevance/similarity score. Included when
|
||
|
|
searching a compatible store with a natural language query.
|
||
|
|
"""
|
||
|
|
|
||
|
|
score: float | None
|
||
|
|
|
||
|
|
|
||
|
|
class SearchItemsResponse(TypedDict):
|
||
|
|
"""Response structure for searching items."""
|
||
|
|
|
||
|
|
items: list[SearchItem]
|
||
|
|
"""A list of items matching the search criteria."""
|
||
|
|
|
||
|
|
|
||
|
|
class StreamPart(NamedTuple):
|
||
|
|
"""Represents a part of a stream response."""
|
||
|
|
|
||
|
|
event: str
|
||
|
|
"""The type of event for this stream part."""
|
||
|
|
data: dict
|
||
|
|
"""The data payload associated with the event."""
|
||
|
|
id: str | None = None
|
||
|
|
"""The ID of the event."""
|
||
|
|
|
||
|
|
|
||
|
|
class Send(TypedDict):
|
||
|
|
"""Represents a message to be sent to a specific node in the graph.
|
||
|
|
|
||
|
|
This type is used to explicitly send messages to nodes in the graph, typically
|
||
|
|
used within Command objects to control graph execution flow.
|
||
|
|
"""
|
||
|
|
|
||
|
|
node: str
|
||
|
|
"""The name of the target node to send the message to."""
|
||
|
|
input: dict[str, Any] | None
|
||
|
|
"""Optional dictionary containing the input data to be passed to the node.
|
||
|
|
|
||
|
|
If None, the node will be called with no input."""
|
||
|
|
|
||
|
|
|
||
|
|
class Command(TypedDict, total=False):
|
||
|
|
"""Represents one or more commands to control graph execution flow and state.
|
||
|
|
|
||
|
|
This type defines the control commands that can be returned by nodes to influence
|
||
|
|
graph execution. It lets you navigate to other nodes, update graph state,
|
||
|
|
and resume from interruptions.
|
||
|
|
"""
|
||
|
|
|
||
|
|
goto: Send | str | Sequence[Send | str]
|
||
|
|
"""Specifies where execution should continue. Can be:
|
||
|
|
|
||
|
|
- A string node name to navigate to
|
||
|
|
- A Send object to execute a node with specific input
|
||
|
|
- A sequence of node names or Send objects to execute in order
|
||
|
|
"""
|
||
|
|
update: dict[str, Any] | Sequence[tuple[str, Any]]
|
||
|
|
"""Updates to apply to the graph's state. Can be:
|
||
|
|
|
||
|
|
- A dictionary of state updates to merge
|
||
|
|
- A sequence of (key, value) tuples for ordered updates
|
||
|
|
"""
|
||
|
|
resume: Any
|
||
|
|
"""Value to resume execution with after an interruption.
|
||
|
|
Used in conjunction with interrupt() to implement control flow.
|
||
|
|
"""
|
||
|
|
|
||
|
|
|
||
|
|
class RunCreateMetadata(TypedDict):
|
||
|
|
"""Metadata for a run creation request."""
|
||
|
|
|
||
|
|
run_id: str
|
||
|
|
"""The ID of the run."""
|
||
|
|
|
||
|
|
thread_id: str | None
|
||
|
|
"""The ID of the thread."""
|
||
|
|
|
||
|
|
|
||
|
|
class _TypedDictLikeV1(Protocol):
|
||
|
|
"""Protocol to represent types that behave like TypedDicts
|
||
|
|
|
||
|
|
Version 1: using `ClassVar` for keys."""
|
||
|
|
|
||
|
|
__required_keys__: ClassVar[frozenset[str]]
|
||
|
|
__optional_keys__: ClassVar[frozenset[str]]
|
||
|
|
|
||
|
|
|
||
|
|
class _TypedDictLikeV2(Protocol):
|
||
|
|
"""Protocol to represent types that behave like TypedDicts
|
||
|
|
|
||
|
|
Version 2: not using `ClassVar` for keys."""
|
||
|
|
|
||
|
|
__required_keys__: frozenset[str]
|
||
|
|
__optional_keys__: frozenset[str]
|
||
|
|
|
||
|
|
|
||
|
|
class _DataclassLike(Protocol):
|
||
|
|
"""Protocol to represent types that behave like dataclasses.
|
||
|
|
|
||
|
|
Inspired by the private _DataclassT from dataclasses that uses a similar protocol as a bound.
|
||
|
|
"""
|
||
|
|
|
||
|
|
__dataclass_fields__: ClassVar[dict[str, Field[Any]]]
|
||
|
|
|
||
|
|
|
||
|
|
class _BaseModelLike(Protocol):
|
||
|
|
"""Protocol to represent types that behave like Pydantic `BaseModel`."""
|
||
|
|
|
||
|
|
model_config: ClassVar[dict[str, Any]]
|
||
|
|
__pydantic_core_schema__: ClassVar[Any]
|
||
|
|
|
||
|
|
def model_dump(
|
||
|
|
self,
|
||
|
|
**kwargs: Any,
|
||
|
|
) -> dict[str, Any]: ...
|
||
|
|
|
||
|
|
|
||
|
|
_JSONLike: TypeAlias = None | str | int | float | bool
|
||
|
|
_JSONMap: TypeAlias = Mapping[
|
||
|
|
str, Union[_JSONLike, list[_JSONLike], "_JSONMap", list["_JSONMap"]]
|
||
|
|
]
|
||
|
|
|
||
|
|
Input: TypeAlias = (
|
||
|
|
_TypedDictLikeV1 | _TypedDictLikeV2 | _DataclassLike | _BaseModelLike | _JSONMap
|
||
|
|
)
|
||
|
|
|
||
|
|
Context: TypeAlias = Input
|