"""
Unit tests for Pydantic models.
"""

import pytest
from pydantic import ValidationError

from src.models import (
    Extraction,
    ExtractionExample,
    ExtractRequest,
    BatchExtractRequest,
    ExtractMetadata,
    ExtractResponse,
    HealthResponse,
)


def test_extraction_basic():
    e = Extraction(extraction_class="topic", extraction_text="meeting")
    assert e.extraction_class == "topic"
    assert e.attributes is None


def test_extraction_with_attributes():
    e = Extraction(
        extraction_class="emotion",
        extraction_text="stressed",
        attributes={"valence": "negative"},
    )
    assert e.attributes["valence"] == "negative"


def test_extraction_example():
    ex = ExtractionExample(
        text="sample text",
        extractions=[
            Extraction(extraction_class="topic", extraction_text="sample"),
        ],
    )
    assert len(ex.extractions) == 1


def test_extract_request_minimal():
    req = ExtractRequest(text="Hello world")
    assert req.text == "Hello world"
    assert req.task_id is None
    assert req.model_id is None


def test_extract_request_full():
    req = ExtractRequest(
        text="Test text",
        task_id="triage",
        task_prompt="Extract entities",
        model_id="gemini-2.5-flash",
        extraction_passes=2,
        max_workers=5,
        max_char_buffer=500,
    )
    assert req.extraction_passes == 2
    assert req.max_workers == 5


def test_extract_request_rejects_empty_text():
    with pytest.raises(ValidationError):
        ExtractRequest(text="")


def test_extract_request_rejects_oversized_text():
    with pytest.raises(ValidationError):
        ExtractRequest(text="a" * 50_001)


def test_extract_request_rejects_invalid_passes():
    with pytest.raises(ValidationError):
        ExtractRequest(text="test", extraction_passes=10)


def test_batch_extract_request():
    batch = BatchExtractRequest(
        requests=[
            ExtractRequest(text="doc 1"),
            ExtractRequest(text="doc 2"),
        ]
    )
    assert len(batch.requests) == 2


def test_batch_extract_request_rejects_empty():
    with pytest.raises(ValidationError):
        BatchExtractRequest(requests=[])


def test_extract_metadata():
    meta = ExtractMetadata(
        model_id="gemini-2.5-flash",
        duration_ms=150.5,
        char_count=42,
    )
    assert meta.token_count is None
    assert meta.duration_ms == 150.5


def test_extract_response():
    resp = ExtractResponse(
        extractions=[
            Extraction(extraction_class="topic", extraction_text="AI"),
        ],
        metadata=ExtractMetadata(
            model_id="gemini-2.5-flash",
            duration_ms=100,
            char_count=20,
        ),
    )
    assert len(resp.extractions) == 1
    assert resp.metadata.model_id == "gemini-2.5-flash"


def test_health_response_defaults():
    h = HealthResponse()
    assert h.status == "ok"
    assert h.version == "0.1.0"
    assert h.sidecar == "langextract"