"""Tests for universal provider support.

Tests OpenAICompatibleProvider, GoogleProvider, and LiteLLMProvider.
"""

from __future__ import annotations

import pytest

from headroom.providers import (
    GoogleProvider,
    ModelCapabilities,
    OpenAICompatibleProvider,
    create_groq_provider,
    create_lmstudio_provider,
    create_ollama_provider,
    create_together_provider,
    create_vllm_provider,
    is_litellm_available,
)


def _transformers_available() -> bool:
    """Check if transformers is available."""
    try:
        import transformers  # noqa: F401

        return True
    except ImportError:
        return False


class TestOpenAICompatibleProvider:
    """Tests for OpenAICompatibleProvider."""

    def test_init_default(self):
        """Test initialization with defaults."""
        provider = OpenAICompatibleProvider()
        assert provider.name == "openai_compatible"
        assert provider.base_url is None

    def test_init_with_config(self):
        """Test initialization with configuration."""
        provider = OpenAICompatibleProvider(
            name="custom",
            base_url="http://localhost:8080/v1",
            api_key="test-key",
        )
        assert provider.name == "custom"
        assert provider.base_url == "http://localhost:8080/v1"
        assert provider.api_key == "test-key"

    def test_supports_any_model(self):
        """Test that provider supports any model."""
        provider = OpenAICompatibleProvider()
        assert provider.supports_model("any-model") is True
        assert provider.supports_model("llama-3") is True
        assert provider.supports_model("custom-finetuned") is True

    @pytest.mark.skipif(
        not _transformers_available(),
        reason="transformers not installed - needed for HuggingFace tokenizer",
    )
    def test_get_token_counter(self):
        """Test getting token counter."""
        provider = OpenAICompatibleProvider()
        counter = provider.get_token_counter("llama-3-8b")
        assert counter is not None
        # Should be able to count tokens
        count = counter.count_text("Hello, world!")
        assert count > 0

    def test_get_context_limit_known_model(self):
        """Test context limit for known models."""
        provider = OpenAICompatibleProvider()
        # Llama 3.1 has 128K context
        limit = provider.get_context_limit("llama-3.1-8b")
        assert limit == 128000

    def test_get_context_limit_unknown_model(self):
        """Test context limit for unknown models (defaults to 128K)."""
        provider = OpenAICompatibleProvider()
        limit = provider.get_context_limit("unknown-model")
        assert limit == 128000

    def test_register_model(self):
        """Test registering a custom model."""
        provider = OpenAICompatibleProvider()
        provider.register_model(
            "my-model",
            context_window=64000,
            max_output_tokens=8192,
            input_cost_per_1m=1.0,
            output_cost_per_1m=2.0,
        )
        assert provider.get_context_limit("my-model") == 64000

    def test_estimate_cost_registered_model(self):
        """Test cost estimation for registered model."""
        provider = OpenAICompatibleProvider()
        provider.register_model(
            "priced-model",
            input_cost_per_1m=1.0,
            output_cost_per_1m=2.0,
        )
        cost = provider.estimate_cost(
            input_tokens=1000000,
            output_tokens=500000,
            model="priced-model",
        )
        assert cost == 2.0  # 1.0 + 1.0

    def test_estimate_cost_unknown_model(self):
        """Test cost estimation returns None for unknown model."""
        provider = OpenAICompatibleProvider()
        cost = provider.estimate_cost(
            input_tokens=1000,
            output_tokens=500,
            model="unknown-model",
        )
        assert cost is None


class TestModelCapabilities:
    """Tests for ModelCapabilities dataclass."""

    def test_default_values(self):
        """Test default capability values."""
        caps = ModelCapabilities(model="test-model")
        assert caps.context_window == 128000
        assert caps.max_output_tokens == 4096
        assert caps.supports_tools is True
        assert caps.supports_vision is False
        assert caps.supports_streaming is True

    def test_custom_values(self):
        """Test custom capability values."""
        caps = ModelCapabilities(
            model="custom-model",
            context_window=32000,
            max_output_tokens=16384,
            supports_tools=False,
            supports_vision=True,
            input_cost_per_1m=0.5,
            output_cost_per_1m=1.5,
        )
        assert caps.context_window == 32000
        assert caps.max_output_tokens == 16384
        assert caps.supports_tools is False
        assert caps.supports_vision is True
        assert caps.input_cost_per_1m == 0.5
        assert caps.output_cost_per_1m == 1.5


class TestGoogleProvider:
    """Tests for GoogleProvider."""

    @pytest.fixture
    def provider(self):
        """Create Google provider."""
        return GoogleProvider()

    def test_name(self, provider):
        """Test provider name."""
        assert provider.name == "google"

    def test_supports_gemini_models(self, provider):
        """Test support for Gemini models."""
        assert provider.supports_model("gemini-2.0-flash") is True
        assert provider.supports_model("gemini-1.5-pro") is True
        assert provider.supports_model("gemini-1.5-flash") is True

    def test_not_supports_other_models(self, provider):
        """Test non-support for other models."""
        assert provider.supports_model("gpt-4o") is False
        assert provider.supports_model("claude-3") is False

    def test_get_token_counter(self, provider):
        """Test getting token counter."""
        counter = provider.get_token_counter("gemini-2.0-flash")
        assert counter is not None
        count = counter.count_text("Hello, world!")
        assert count > 0

    def test_get_context_limit_gemini_2(self, provider):
        """Test context limit for Gemini 2.0."""
        limit = provider.get_context_limit("gemini-2.0-flash")
        # LiteLLM returns 1048576 (2^20), fallback returns 1000000
        assert limit in (1000000, 1048576)  # ~1M tokens

    def test_get_context_limit_gemini_1_5_pro(self, provider):
        """Test context limit for Gemini 1.5 Pro (2M!)."""
        limit = provider.get_context_limit("gemini-1.5-pro")
        # LiteLLM returns 2097152 (2^21), fallback returns 2000000
        assert limit in (2000000, 2097152)  # ~2M tokens!

    def test_estimate_cost(self, provider):
        """Test cost estimation."""
        cost = provider.estimate_cost(
            input_tokens=1000000,
            output_tokens=500000,
            model="gemini-2.0-flash",
        )
        assert cost is not None
        # 1M input * $0.10 + 0.5M output * $0.40 = $0.10 + $0.20 = $0.30
        assert abs(cost - 0.30) < 0.01

    def test_openai_compatible_url(self):
        """Test OpenAI-compatible URL."""
        url = GoogleProvider.get_openai_compatible_url("test-key")
        assert "generativelanguage.googleapis.com" in url


class TestProviderFactoryFunctions:
    """Tests for provider factory functions."""

    def test_create_ollama_provider(self):
        """Test creating Ollama provider."""
        provider = create_ollama_provider()
        assert provider.name == "ollama"
        assert provider.base_url == "http://localhost:11434/v1"

    def test_create_ollama_provider_custom_url(self):
        """Test creating Ollama provider with custom URL."""
        provider = create_ollama_provider("http://192.168.1.100:11434/v1")
        assert provider.base_url == "http://192.168.1.100:11434/v1"

    def test_create_together_provider(self):
        """Test creating Together provider."""
        provider = create_together_provider()
        assert provider.name == "together"
        assert "together.xyz" in provider.base_url

    def test_create_groq_provider(self):
        """Test creating Groq provider."""
        provider = create_groq_provider()
        assert provider.name == "groq"
        assert "groq.com" in provider.base_url

    def test_create_vllm_provider(self):
        """Test creating vLLM provider."""
        provider = create_vllm_provider("http://localhost:8000/v1")
        assert provider.name == "vllm"
        assert provider.base_url == "http://localhost:8000/v1"

    def test_create_lmstudio_provider(self):
        """Test creating LM Studio provider."""
        provider = create_lmstudio_provider()
        assert provider.name == "lmstudio"
        assert provider.base_url == "http://localhost:1234/v1"


class TestLiteLLMProvider:
    """Tests for LiteLLM provider."""

    def test_is_litellm_available(self):
        """Test checking LiteLLM availability."""
        result = is_litellm_available()
        assert isinstance(result, bool)

    @pytest.mark.skipif(
        not is_litellm_available(),
        reason="LiteLLM not installed",
    )
    def test_create_litellm_provider(self):
        """Test creating LiteLLM provider."""
        from headroom.providers import create_litellm_provider

        provider = create_litellm_provider()
        assert provider.name == "litellm"

    @pytest.mark.skipif(
        not is_litellm_available(),
        reason="LiteLLM not installed",
    )
    def test_litellm_supports_any_model(self):
        """Test LiteLLM supports any model."""
        from headroom.providers import create_litellm_provider

        provider = create_litellm_provider()
        assert provider.supports_model("gpt-4o") is True
        assert provider.supports_model("claude-3-sonnet") is True
        assert provider.supports_model("any-model") is True

    @pytest.mark.skipif(
        not is_litellm_available(),
        reason="LiteLLM not installed",
    )
    def test_litellm_list_providers(self):
        """Test listing LiteLLM providers."""
        from headroom.providers import LiteLLMProvider

        providers = LiteLLMProvider.list_supported_providers()
        assert "openai" in providers
        assert "anthropic" in providers
        assert "ollama" in providers