"""Tests for fusionagi.gpu.tensor_attention."""

import pytest

from fusionagi.gpu.backend import get_backend, reset_backend
from fusionagi.gpu.tensor_attention import (
    attention_consensus,
    cross_claim_attention,
)


@pytest.fixture(autouse=True)
def _use_numpy():
    reset_backend()
    get_backend(force="numpy")
    yield
    reset_backend()


class TestAttentionConsensus:
    def test_empty(self):
        result = attention_consensus([], "query")
        assert result["head_scores"] == []
        assert result["consensus_score"] == 0.0

    def test_single_head(self):
        result = attention_consensus(
            [["the sky is blue"]],
            "what color is the sky",
        )
        assert len(result["head_scores"]) == 1
        assert isinstance(result["consensus_score"], float)

    def test_multiple_heads(self):
        result = attention_consensus(
            [
                ["the sky is blue", "water is wet"],
                ["security is important"],
                ["cost should be minimized"],
            ],
            "what should we do about the project",
        )
        assert len(result["head_scores"]) == 3
        assert 0.0 <= result["consensus_score"] <= 1.0

    def test_with_weights(self):
        result = attention_consensus(
            [["claim a"], ["claim b"]],
            "query",
            head_weights=[2.0, 0.5],
        )
        assert len(result["head_scores"]) == 2

    def test_empty_claims(self):
        result = attention_consensus(
            [[], []],
            "query",
        )
        assert len(result["head_scores"]) == 2
        assert result["head_scores"] == [0.0, 0.0]


class TestCrossClaimAttention:
    def test_empty(self):
        result = cross_claim_attention([])
        assert result["similarity_matrix"] == []
        assert result["conflict_pairs"] == []

    def test_single(self):
        result = cross_claim_attention(["only one claim"])
        assert result["similarity_matrix"] == []

    def test_two_claims(self):
        result = cross_claim_attention(["claim one", "claim two"])
        assert len(result["similarity_matrix"]) == 2
        assert len(result["similarity_matrix"][0]) == 2

    def test_self_similarity_high(self):
        result = cross_claim_attention(["same text", "same text"])
        sim = result["similarity_matrix"]
        assert sim[0][0] > 0.9
        assert sim[1][1] > 0.9

    def test_conflict_detection(self):
        result = cross_claim_attention([
            "the project is very safe and reliable",
            "completely unrelated topic about food and cooking",
        ])
        assert isinstance(result["conflict_pairs"], list)