"""Tests for ContentGenerationService - extracted from api/content.py

TDD RED phase: tests for the service that extracts the 3-stage
content generation flow (generate -> de-AI -> GEO optimize)
out of the API handler.
"""
import uuid
from unittest.mock import AsyncMock, MagicMock, patch

import pytest

from app.services.llm.base import LLMError, LLMResponse


def _make_llm_response(content: str) -> LLMResponse:
    """Helper to create LLMResponse objects for mocking."""
    return LLMResponse(content=content, model="test-model")


class TestContentGenerationService:
    """ContentGenerationService unit tests."""

    @pytest.mark.asyncio
    async def test_generate_content_basic_three_stages(self):
        """Test basic 3-stage content generation (generate -> de-AI -> GEO optimize)."""
        from app.services.content.content_generation_service import (
            ContentGenerationService,
        )

        service = ContentGenerationService()

        mock_provider = AsyncMock()
        mock_provider.chat.side_effect = [
            _make_llm_response("Raw generated content"),
            _make_llm_response("De-AIed content"),
            _make_llm_response("GEO optimized content"),
        ]

        with patch.object(service, "_get_provider", return_value=mock_provider):
            result = await service.generate_content(
                keyword="AI搜索",
                brand_name="Brand X",
                platform="wenxin",
                content_style="专业严谨",
                word_count=2000,
                run_deai=True,
                run_geo=True,
            )

        assert result is not None
        assert result["content"] == "De-AIed content"
        assert result["optimized_content"] == "GEO optimized content"
        assert result["pipeline_stages"] is not None
        assert len(result["pipeline_stages"]) == 3
        assert result["pipeline_stages"][0]["stage"] == "content_generation"
        assert result["pipeline_stages"][1]["stage"] == "deai"
        assert result["pipeline_stages"][2]["stage"] == "geo_optimization"

    @pytest.mark.asyncio
    async def test_generate_content_skip_deai(self):
        """Test generation with run_deai=False skips the de-AI stage."""
        from app.services.content.content_generation_service import (
            ContentGenerationService,
        )

        service = ContentGenerationService()

        mock_provider = AsyncMock()
        mock_provider.chat.side_effect = [
            _make_llm_response("Raw generated content"),
            _make_llm_response("GEO optimized content"),
        ]

        with patch.object(service, "_get_provider", return_value=mock_provider):
            result = await service.generate_content(
                keyword="test",
                brand_name="Brand X",
                platform="wenxin",
                run_deai=False,
                run_geo=True,
            )

        assert result["content"] == "Raw generated content"
        assert result["optimized_content"] == "GEO optimized content"
        assert len(result["pipeline_stages"]) == 2
        stage_names = [s["stage"] for s in result["pipeline_stages"]]
        assert "deai" not in stage_names

    @pytest.mark.asyncio
    async def test_generate_content_skip_geo(self):
        """Test generation with run_geo=False skips the GEO optimization stage."""
        from app.services.content.content_generation_service import (
            ContentGenerationService,
        )

        service = ContentGenerationService()

        mock_provider = AsyncMock()
        mock_provider.chat.side_effect = [
            _make_llm_response("Raw generated content"),
            _make_llm_response("De-AIed content"),
        ]

        with patch.object(service, "_get_provider", return_value=mock_provider):
            result = await service.generate_content(
                keyword="test",
                brand_name="Brand X",
                platform="wenxin",
                run_deai=True,
                run_geo=False,
            )

        assert result["content"] == "De-AIed content"
        assert result["optimized_content"] == "De-AIed content"
        assert len(result["pipeline_stages"]) == 2
        stage_names = [s["stage"] for s in result["pipeline_stages"]]
        assert "geo_optimization" not in stage_names

    @pytest.mark.asyncio
    async def test_generate_content_skip_both_stages(self):
        """Test generation with both run_deai=False and run_geo=False."""
        from app.services.content.content_generation_service import (
            ContentGenerationService,
        )

        service = ContentGenerationService()

        mock_provider = AsyncMock()
        mock_provider.chat.side_effect = [
            _make_llm_response("Raw generated content"),
        ]

        with patch.object(service, "_get_provider", return_value=mock_provider):
            result = await service.generate_content(
                keyword="test",
                brand_name="Brand X",
                platform="wenxin",
                run_deai=False,
                run_geo=False,
            )

        assert result["content"] == "Raw generated content"
        assert result["optimized_content"] == "Raw generated content"
        assert len(result["pipeline_stages"]) == 1

    @pytest.mark.asyncio
    async def test_generate_content_with_knowledge_context(self):
        """Test that knowledge_context is passed through to the generation prompt."""
        from app.services.content.content_generation_service import (
            ContentGenerationService,
        )

        service = ContentGenerationService()

        mock_provider = AsyncMock()
        mock_provider.chat.side_effect = [
            _make_llm_response("Raw content"),
            _make_llm_response("De-AIed"),
            _make_llm_response("Optimized"),
        ]

        with patch.object(service, "_get_provider", return_value=mock_provider):
            result = await service.generate_content(
                keyword="test keyword",
                brand_name="Brand X",
                platform="wenxin",
                knowledge_context="Some knowledge base content",
            )

        # The first call to provider.chat should include the knowledge context
        first_call_args = mock_provider.chat.call_args_list[0]
        messages = first_call_args[0][0]
        # Verify knowledge context appears in the rendered messages
        all_content = " ".join(str(m) for m in messages)
        assert "Some knowledge base content" in all_content

    @pytest.mark.asyncio
    async def test_generate_content_saves_to_database(self):
        """Test that generated content is saved to database when db and user_id are provided."""
        from app.services.content.content_generation_service import (
            ContentGenerationService,
        )

        service = ContentGenerationService()

        mock_provider = AsyncMock()
        mock_provider.chat.side_effect = [
            _make_llm_response("Raw content"),
            _make_llm_response("De-AIed"),
            _make_llm_response("Optimized"),
        ]
        mock_db = AsyncMock()

        with patch.object(service, "_get_provider", return_value=mock_provider):
            result = await service.generate_content(
                keyword="test",
                brand_name="Brand X",
                platform="wenxin",
                db=mock_db,
                user_id="test-user-123",
                org_id=str(uuid.uuid4()),
            )

        # Verify db.add was called (Content + ContentVersion)
        assert mock_db.add.call_count == 2
        mock_db.commit.assert_called_once()

    @pytest.mark.asyncio
    async def test_generate_content_no_db_no_save(self):
        """Test that when db is not provided, no database operations occur."""
        from app.services.content.content_generation_service import (
            ContentGenerationService,
        )

        service = ContentGenerationService()

        mock_provider = AsyncMock()
        mock_provider.chat.side_effect = [
            _make_llm_response("Raw"),
            _make_llm_response("De-AIed"),
            _make_llm_response("Optimized"),
        ]

        with patch.object(service, "_get_provider", return_value=mock_provider):
            result = await service.generate_content(
                keyword="test",
                brand_name="Brand X",
                platform="wenxin",
            )

        # No content_id when db is not provided
        assert result.get("content_id") is None

    @pytest.mark.asyncio
    async def test_generate_content_llm_error_propagates(self):
        """Test that LLMError from the provider propagates correctly."""
        from app.services.content.content_generation_service import (
            ContentGenerationService,
        )

        service = ContentGenerationService()

        mock_provider = AsyncMock()
        mock_provider.chat.side_effect = LLMError(
            "API rate limit", provider="openai"
        )

        with patch.object(service, "_get_provider", return_value=mock_provider):
            with pytest.raises(LLMError, match="API rate limit"):
                await service.generate_content(
                    keyword="test",
                    brand_name="Brand X",
                    platform="wenxin",
                )

    @pytest.mark.asyncio
    async def test_get_knowledge_context_with_ids(self):
        """Test _get_knowledge_context retrieves context when knowledge_base_ids are provided."""
        from app.services.content.content_generation_service import (
            ContentGenerationService,
        )

        service = ContentGenerationService()
        mock_db = AsyncMock()

        mock_rag = MagicMock()
        mock_rag.search = AsyncMock(return_value=[
            {"content": "Knowledge chunk 1", "document_title": "Doc A"},
            {"content": "Knowledge chunk 2", "document_title": "Doc B"},
        ])

        with patch(
            "app.services.knowledge.rag_service.RAGService",
            return_value=mock_rag,
        ):
            context = await service._get_knowledge_context(
                db=mock_db,
                brand_name="Brand X",
                knowledge_base_ids=["kb-1"],
                target_keyword="test keyword",
            )

        assert "Knowledge chunk 1" in context
        assert "Knowledge chunk 2" in context
        assert "Doc A" in context

    @pytest.mark.asyncio
    async def test_get_knowledge_context_empty_ids(self):
        """Test _get_knowledge_context returns empty string when no IDs provided."""
        from app.services.content.content_generation_service import (
            ContentGenerationService,
        )

        service = ContentGenerationService()
        mock_db = AsyncMock()

        context = await service._get_knowledge_context(
            db=mock_db,
            brand_name="Brand X",
            knowledge_base_ids=[],
            target_keyword="test",
        )

        assert context == ""

    @pytest.mark.asyncio
    async def test_get_knowledge_context_rag_failure_returns_empty(self):
        """Test _get_knowledge_context returns empty string when RAG search fails."""
        from app.services.content.content_generation_service import (
            ContentGenerationService,
        )

        service = ContentGenerationService()
        mock_db = AsyncMock()

        mock_rag = MagicMock()
        mock_rag.search = AsyncMock(side_effect=Exception("RAG service down"))

        with patch(
            "app.services.knowledge.rag_service.RAGService",
            return_value=mock_rag,
        ):
            context = await service._get_knowledge_context(
                db=mock_db,
                brand_name="Brand X",
                knowledge_base_ids=["kb-1"],
                target_keyword="test",
            )

        assert context == ""

    @pytest.mark.asyncio
    async def test_generate_content_passes_correct_prompt_variables(self):
        """Test that the service passes correct variables to each prompt template stage."""
        from app.services.content.content_generation_service import (
            ContentGenerationService,
        )

        service = ContentGenerationService()

        mock_provider = AsyncMock()
        mock_provider.chat.side_effect = [
            _make_llm_response("Raw content"),
            _make_llm_response("De-AIed content"),
            _make_llm_response("Optimized content"),
        ]

        with patch.object(service, "_get_provider", return_value=mock_provider):
            with patch(
                "app.services.content.content_generation_service.CONTENT_GENERATOR_TEMPLATE"
            ) as mock_gen_template, patch(
                "app.services.content.content_generation_service.DEAI_TEMPLATE"
            ) as mock_deai_template, patch(
                "app.services.content.content_generation_service.GEO_OPTIMIZER_TEMPLATE"
            ) as mock_geo_template:
                mock_gen_template.render.return_value = [
                    {"role": "user", "content": "gen prompt"}
                ]
                mock_deai_template.render.return_value = [
                    {"role": "user", "content": "deai prompt"}
                ]
                mock_geo_template.render.return_value = [
                    {"role": "user", "content": "geo prompt"}
                ]

                await service.generate_content(
                    keyword="AI搜索",
                    brand_name="Brand X",
                    platform="微信公众号",
                    content_style="专业严谨",
                    word_count=3000,
                    knowledge_context="Some context",
                )

                # Verify CONTENT_GENERATOR_TEMPLATE.render called with correct variables
                gen_call_kwargs = mock_gen_template.render.call_args[0][0]
                assert gen_call_kwargs["topic_title"] == "AI搜索"
                assert gen_call_kwargs["target_keyword"] == "AI搜索"
                assert gen_call_kwargs["target_platform"] == "微信公众号"
                assert gen_call_kwargs["content_style"] == "专业严谨"
                assert gen_call_kwargs["word_count"] == "3000"
                assert gen_call_kwargs["brand_name"] == "Brand X"
                assert gen_call_kwargs["knowledge_context"] == "Some context"

                # Verify DEAI_TEMPLATE.render called with the generated content
                deai_call_kwargs = mock_deai_template.render.call_args[0][0]
                assert deai_call_kwargs["original_content"] == "Raw content"

                # Verify GEO_OPTIMIZER_TEMPLATE.render called with de-AIed content
                geo_call_kwargs = mock_geo_template.render.call_args[0][0]
                assert geo_call_kwargs["original_content"] == "De-AIed content"
                assert geo_call_kwargs["target_keywords"] == "AI搜索"
                assert geo_call_kwargs["target_platform"] == "微信公众号"

    @pytest.mark.asyncio
    async def test_generate_content_default_parameters(self):
        """Test that default parameter values are applied correctly."""
        from app.services.content.content_generation_service import (
            ContentGenerationService,
        )

        service = ContentGenerationService()

        mock_provider = AsyncMock()
        mock_provider.chat.side_effect = [
            _make_llm_response("Raw"),
            _make_llm_response("De-AIed"),
            _make_llm_response("Optimized"),
        ]

        with patch.object(service, "_get_provider", return_value=mock_provider):
            result = await service.generate_content(
                keyword="test",
                brand_name="Brand X",
            )

        # Defaults: platform="通用", content_style="专业严谨", word_count=2000
        # run_deai=True, run_geo=True
        assert result is not None
        assert len(result["pipeline_stages"]) == 3