"""Shared test fakes (no network, deterministic)."""
from __future__ import annotations

from typing import Any

from app.config import Settings
from app.rag.llm import LLMError


class FakeEmbedder:
    """Duck-typed stand-in for :class:`app.rag.llm.LLMClient` (see the
    ``Embedder`` protocol in :mod:`app.rag.importer`).

    Returns deterministic vectors of *dim* dimensions; records every call
    so tests can assert batching behaviour. ``chat`` is the deterministic
    ``lite``-model stand-in (phase 30): it returns
    ``"Summary of <first token of the user content>"`` and raises
    :class:`LLMError` when the content contains the sentinel word
    ``SUMMARY-BLOWUP`` (drives the importer's fail-soft summary path).
    ``content`` may be a string or a phase-122 multimodal part list
    (``dict[str, Any]`` messages, the ``LLMClient.chat`` shape) — the
    text-summary body above is string-only; a subclass handling the
    multimodal image description (task 03's vision mock) overrides
    ``chat``.
    """

    def __init__(self, dim: int = 768) -> None:
        self.dim = dim
        self.settings = Settings(_env_file=None)  # pyright: ignore[reportCallIssue]
        self.embed_batches = 0
        self.calls: list[list[str]] = []
        self.chat_calls: list[list[dict[str, str]]] = []

    async def embed(self, texts: list[str]) -> list[list[float]]:
        self.calls.append(list(texts))
        self.embed_batches += 1
        return [[0.01 * (i % 97) for i in range(self.dim)] for _ in texts]

    async def embed_one(self, text: str) -> list[float]:
        """The retrieval/probe convenience path — delegates to :meth:`embed`
        (satisfies the phase-41 pre-sync model probe)."""
        (vec,) = await self.embed([text])
        return vec

    async def chat(
        self, messages: list[dict[str, Any]], model: str | None = None
    ) -> str:
        self.chat_calls.append(list(messages))
        user = next((m["content"] for m in messages if m.get("role") == "user"), "")
        if "SUMMARY-BLOWUP" in user:
            raise LLMError("simulated lite-model failure (SUMMARY-BLOWUP sentinel)")
        first = user.split()
        return "Summary of " + (first[0] if first else "<empty>")