"""Hand-written fakes for narrow application-owned ports (ADR-0016)."""

import asyncio
from collections.abc import Sequence
from dataclasses import dataclass, field

from src.application.ingestion.models import SparseVector


@dataclass
class FakeObjectStorage:
    """In-memory `ObjectStorage`. `fail_next` simulates one upload failure."""

    objects: dict[str, bytes] = field(default_factory=dict)
    fail_next: bool = False

    async def put_object(self, *, key: str, data: bytes, content_type: str) -> None:
        if self.fail_next:
            self.fail_next = False
            raise OSError("simulated object storage failure")
        self.objects[key] = data


@dataclass
class FakeDenseEmbedder:
    """A scripted `DenseEmbedder`. Returns a fixed-dimension zero vector per
    text by default; `fail_next` simulates one batch failure.
    """

    name: str
    dimensions: int = 4
    model_version: str = "fake-dense-v1"
    calls: list[list[str]] = field(default_factory=list)
    fail_next: bool = False
    delay_seconds: float = 0.0
    """Simulates a slow provider call, e.g. to exercise timeout handling."""

    async def embed_batch(self, texts: Sequence[str]) -> list[list[float]]:
        self.calls.append(list(texts))
        if self.delay_seconds:
            await asyncio.sleep(self.delay_seconds)
        if self.fail_next:
            self.fail_next = False
            raise RuntimeError("simulated embedder failure")
        return [[0.0] * self.dimensions for _ in texts]


@dataclass
class FakeSparseEmbedder:
    """A scripted `SparseEmbedder`. Returns an empty sparse vector per text."""

    name: str = "sparse"
    model_version: str = "fake-sparse-v1"
    calls: list[list[str]] = field(default_factory=list)
    fail_next: bool = False

    def embed_batch(self, texts: Sequence[str], *, query: bool = False) -> list[SparseVector]:
        self.calls.append(list(texts))
        if self.fail_next:
            self.fail_next = False
            raise RuntimeError("simulated embedder failure")
        return [SparseVector(indices=[], values=[]) for _ in texts]