app/backend/app/flow/schemas.py

"""The persisted shape of a flow, shared by the store, the API and the editor.

A flow is structure plus code: this module is the structure. Node logic for
``python`` nodes lives beside it as a plain ``.py`` file.
"""

from __future__ import annotations

import re
from typing import Any, Literal

from pydantic import BaseModel, Field, field_validator

from app.flow.messages import MessageSpec

NAME_PATTERN = re.compile(r"^[a-z][a-z0-9_]*$")


def _validate_name(value: str) -> str:
    if not NAME_PATTERN.match(value):
        raise ValueError(
            "Use lowercase letters, digits and underscores, starting with a letter"
        )
    return value


class NodeDef(BaseModel):
    """A node as stored: identity, configuration and ports.

    Deliberately no canvas position. The editor lays a flow out itself, so
    where a node sits is a fact about the drawing rather than about the flow —
    and a graph nobody can arrange is one worth keeping small.
    """

    id: str
    type: str = "python"
    title: str = ""
    params: dict[str, Any] = Field(default_factory=dict)
    requires: list[MessageSpec] = Field(default_factory=list)
    provides: list[MessageSpec] = Field(default_factory=list)
    #: Name of a shared source in the library, instead of this node's own file.
    #: Editing it edits the copy every flow using it runs.
    source_ref: str | None = None
    timeout: float | None = Field(
        default=None,
        gt=0,
        description=(
            "Seconds this node's code may run before it is stopped. This "
            "covers the first call's imports, which can be much slower than "
            "the body. Above 60 the engine may deliver its work again while "
            "it is still running."
        ),
    )

    @field_validator("id")
    @classmethod
    def _check_id(cls, value: str) -> str:
        return _validate_name(value)


class FlowInput(BaseModel):
    """A message the flow starts with rather than computes."""

    spec: MessageSpec
    initial: Any | None = None


class FlowDef(BaseModel):
    """One atomic flow."""

    name: str
    title: str = ""
    nodes: list[NodeDef] = Field(default_factory=list)
    inputs: list[FlowInput] = Field(default_factory=list)
    version: int = 1

    @field_validator("name")
    @classmethod
    def _check_name(cls, value: str) -> str:
        return _validate_name(value)


class NodeSource(BaseModel):
    """The Python source of a node."""

    code: str


Health = Literal["ok", "degraded", "down"]


class NodeStatusPublic(BaseModel):
    """Whether a node loaded, and how its connection is doing."""

    id: str
    status: str = "active"
    error: str | None = None
    health: Health = "ok"
    health_detail: str | None = None


class MessageValue(BaseModel):
    """The last payload seen on a message."""

    value: Any = None
    ts: float | None = None


class HistoryPoint(BaseModel):
    """One numeric value a message carried, and when."""

    ts: float
    value: float


class MessageHistory(BaseModel):
    """A message's recent numeric values, oldest first.

    Only numbers are recorded, so ``numeric`` tells the panel whether an empty
    series means "nothing plottable here" or "nothing has arrived yet".
    """

    message: str
    numeric: bool = False
    points: list[HistoryPoint] = Field(default_factory=list)


class FlowSummary(BaseModel):
    name: str
    title: str = ""
    node_count: int = 0
    error_count: int = 0
    has_draft: bool = False
    enabled: bool = True
    paused: bool = False
    # Its background tasks kept crashing, so the engine stopped restarting them.
    quarantined: bool = False


class FlowsPublic(BaseModel):
    data: list[FlowSummary]
    count: int


class LibraryNode(BaseModel):
    """A node source shared across flows, and who is using it."""

    name: str
    used_by: list[str] = Field(default_factory=list)


class FlowStatePublic(BaseModel):
    values: dict[str, MessageValue] = Field(default_factory=dict)
    nodes: list[NodeStatusPublic] = Field(default_factory=list)


class ModulePackage(BaseModel):
    """One package installed in the venv node code runs on."""

    name: str
    version: str


class ModulesInfo(BaseModel):
    """The venv node code imports from, and the manifest that describes it."""

    python_version: str = ""
    venv_path: str = ""
    requirements: str = ""
    packages: list[ModulePackage] = Field(default_factory=list)
    #: Whether what is installed matches the manifest.
    applied: bool = False


class ApplyRequest(BaseModel):
    """A pip manifest, one requirement per line."""

    requirements: str = ""


class ApplyResult(BaseModel):
    ok: bool
    output: str = ""


class BrainNode(BaseModel):
    """One neuron: a thing the engine talks to, or a node that only computes.

    Nodes of the same type pointing at the same outside thing — one broker
    topic, one URL, one bucket — are a single entry here, whichever flows they
    sit in. ``members`` are the ``flow.node_id`` names behind it, which is also
    what the live events are keyed by.
    """

    id: str
    label: str
    kind: str
    members: list[str] = Field(default_factory=list)
    flows: list[str] = Field(default_factory=list)
    issue: str | None = Field(
        default=None,
        description=(
            "Why this neuron cannot run, if validation found something. A "
            "failure the engine hits while running arrives over the socket "
            "instead; this is the part that is already true before anything "
            "fires, and so has to travel with the graph."
        ),
    )


class BrainEdge(BaseModel):
    """Messages carrying values from one neuron to another."""

    source: str
    target: str
    messages: list[str] = Field(default_factory=list)


class BrainGraph(BaseModel):
    """Every published flow at once, merged on what its nodes talk to."""

    nodes: list[BrainNode] = Field(default_factory=list)
    edges: list[BrainEdge] = Field(default_factory=list)


class NodeTypeInfo(BaseModel):
    """A node type the editor can offer, with its parameter schema."""

    type: str
    title: str
    description: str
    params_schema: dict[str, Any] = Field(default_factory=dict)
    has_source: bool = False
    #: Whether this type takes settings beyond the ones its schema declares.
    #: A function node's params are its author's to name, and reach `process`
    #: as whatever they put there.
    free_params: bool = False
    #: The package a connector came from; empty for the built-in types.
    plugin: str | None = None