import json

# These tests are integration-like and exercise chat endpoints.
import os
from unittest.mock import MagicMock, patch

import pytest

from app import app as flask_app


@pytest.fixture
def app():
    yield flask_app


@pytest.fixture
def client(app):
    return app.test_client()


class TestChatEndpoint:
    """Test cases for the /chat endpoint"""

    @patch.dict(os.environ, {"OPENROUTER_API_KEY": "test_key"})
    @patch("src.rag.rag_pipeline.RAGPipeline")
    @patch("src.rag.response_formatter.ResponseFormatter")
    @patch("src.llm.llm_service.LLMService")
    @patch("src.search.search_service.SearchService")
    @patch("src.vector_store.vector_db.VectorDatabase")
    @patch("src.embedding.embedding_service.EmbeddingService")
    def test_chat_endpoint_valid_request(
        self,
        mock_embedding,
        mock_vector,
        mock_search,
        mock_llm,
        mock_formatter,
        mock_rag,
        client,
    ):
        """Test chat endpoint with valid request"""
        # Mock the RAG pipeline response
        mock_response = {
            "answer": ("Based on the remote work policy, employees can work " "remotely up to 3 days per week."),
            "confidence": 0.85,
            "sources": [{"chunk_id": "123", "content": "Remote work policy content..."}],
            "citations": ["remote_work_policy.md"],
            "processing_time_ms": 1500,
        }

        # Setup mock instances
        mock_rag_instance = MagicMock()
        mock_rag_instance.generate_answer.return_value = mock_response
        mock_rag.return_value = mock_rag_instance

        mock_formatter_instance = MagicMock()
        mock_formatter_instance.format_api_response.return_value = {
            "status": "success",
            "answer": mock_response["answer"],
            "confidence": mock_response["confidence"],
            "sources": mock_response["sources"],
            "citations": mock_response["citations"],
        }
        mock_formatter.return_value = mock_formatter_instance

        # Mock LLMService.from_environment to return a mock instance
        mock_llm_instance = MagicMock()
        mock_llm.from_environment.return_value = mock_llm_instance

        request_data = {
            "message": "What is the remote work policy?",
            "include_sources": True,
        }

        response = client.post("/chat", data=json.dumps(request_data), content_type="application/json")

        assert response.status_code == 200
        data = response.get_json()

        assert data["status"] == "success"
        assert "answer" in data
        assert "confidence" in data
        assert "sources" in data
        assert "citations" in data

    @patch.dict(os.environ, {"OPENROUTER_API_KEY": "test_key"})
    @patch("src.rag.rag_pipeline.RAGPipeline")
    @patch("src.rag.response_formatter.ResponseFormatter")
    @patch("src.llm.llm_service.LLMService")
    @patch("src.search.search_service.SearchService")
    @patch("src.vector_store.vector_db.VectorDatabase")
    @patch("src.embedding.embedding_service.EmbeddingService")
    def test_chat_endpoint_minimal_request(
        self,
        mock_embedding,
        mock_vector,
        mock_search,
        mock_llm,
        mock_formatter,
        mock_rag,
        client,
    ):
        """Test chat endpoint with minimal request (only message)"""
        mock_response = {
            "answer": ("Employee benefits include health insurance, " "retirement plans, and PTO."),
            "confidence": 0.78,
            "sources": [],
            "citations": ["employee_benefits_guide.md"],
            "processing_time_ms": 1200,
        }

        # Setup mock instances
        mock_rag_instance = MagicMock()
        mock_rag_instance.generate_answer.return_value = mock_response
        mock_rag.return_value = mock_rag_instance

        mock_formatter_instance = MagicMock()
        mock_formatter_instance.format_api_response.return_value = {
            "status": "success",
            "answer": mock_response["answer"],
        }
        mock_formatter.return_value = mock_formatter_instance

        mock_llm.from_environment.return_value = MagicMock()

        request_data = {"message": "What are the employee benefits?"}

        response = client.post("/chat", data=json.dumps(request_data), content_type="application/json")

        assert response.status_code == 200
        data = response.get_json()
        assert data["status"] == "success"

    def test_chat_endpoint_missing_message(self, client):
        """Test chat endpoint with missing message parameter"""
        request_data = {"include_sources": True}

        response = client.post("/chat", data=json.dumps(request_data), content_type="application/json")

        assert response.status_code == 400
        data = response.get_json()
        assert data["status"] == "error"
        assert "message parameter is required" in data["message"]

    def test_chat_endpoint_empty_message(self, client):
        """Test chat endpoint with empty message"""
        request_data = {"message": ""}

        response = client.post("/chat", data=json.dumps(request_data), content_type="application/json")

        assert response.status_code == 400
        data = response.get_json()
        assert data["status"] == "error"
        assert "non-empty string" in data["message"]

    def test_chat_endpoint_non_string_message(self, client):
        """Test chat endpoint with non-string message"""
        request_data = {"message": 123}

        response = client.post("/chat", data=json.dumps(request_data), content_type="application/json")

        assert response.status_code == 400
        data = response.get_json()
        assert data["status"] == "error"
        assert "non-empty string" in data["message"]

    def test_chat_endpoint_non_json_request(self, client):
        """Test chat endpoint with non-JSON request"""
        response = client.post("/chat", data="not json", content_type="text/plain")

        assert response.status_code == 400
        data = response.get_json()
        assert data["status"] == "error"
        assert "application/json" in data["message"]

    def test_chat_endpoint_no_llm_config(self, client):
        """Test chat endpoint with no LLM configuration"""
        with patch.dict(os.environ, {}, clear=True):
            request_data = {"message": "What is the policy?"}

            response = client.post("/chat", data=json.dumps(request_data), content_type="application/json")

            assert response.status_code == 503
            data = response.get_json()
            assert data["status"] == "error"
            assert "LLM service configuration error" in data["message"]

    @patch.dict(os.environ, {"OPENROUTER_API_KEY": "test_key"})
    @patch("src.rag.rag_pipeline.RAGPipeline")
    @patch("src.rag.response_formatter.ResponseFormatter")
    @patch("src.llm.llm_service.LLMService")
    @patch("src.search.search_service.SearchService")
    @patch("src.vector_store.vector_db.VectorDatabase")
    @patch("src.embedding.embedding_service.EmbeddingService")
    def test_chat_endpoint_with_conversation_id(
        self,
        mock_embedding,
        mock_vector,
        mock_search,
        mock_llm,
        mock_formatter,
        mock_rag,
        client,
    ):
        """Test chat endpoint with conversation_id parameter"""
        mock_response = {
            "answer": "The PTO policy allows 15 days of vacation annually.",
            "confidence": 0.9,
            "sources": [],
            "citations": ["pto_policy.md"],
            "processing_time_ms": 1100,
        }

        # Setup mock instances
        mock_rag_instance = MagicMock()
        mock_rag_instance.generate_answer.return_value = mock_response
        mock_rag.return_value = mock_rag_instance

        mock_formatter_instance = MagicMock()
        mock_formatter_instance.format_chat_response.return_value = {
            "status": "success",
            "answer": mock_response["answer"],
        }
        mock_formatter.return_value = mock_formatter_instance

        mock_llm.from_environment.return_value = MagicMock()

        request_data = {
            "message": "What is the PTO policy?",
            "conversation_id": "conv_123",
            "include_sources": False,
        }

        response = client.post("/chat", data=json.dumps(request_data), content_type="application/json")

        assert response.status_code == 200
        data = response.get_json()
        assert data["status"] == "success"

    @patch.dict(os.environ, {"OPENROUTER_API_KEY": "test_key"})
    @patch("src.rag.rag_pipeline.RAGPipeline")
    @patch("src.rag.response_formatter.ResponseFormatter")
    @patch("src.llm.llm_service.LLMService")
    @patch("src.search.search_service.SearchService")
    @patch("src.vector_store.vector_db.VectorDatabase")
    @patch("src.embedding.embedding_service.EmbeddingService")
    def test_chat_endpoint_with_debug(
        self,
        mock_embedding,
        mock_vector,
        mock_search,
        mock_llm,
        mock_formatter,
        mock_rag,
        client,
    ):
        """Test chat endpoint with debug information"""
        mock_response = {
            "answer": "The security policy requires 2FA authentication.",
            "confidence": 0.95,
            "sources": [{"chunk_id": "456", "content": "Security requirements..."}],
            "citations": ["information_security_policy.md"],
            "processing_time_ms": 1800,
            "search_results_count": 5,
            "context_length": 2048,
        }

        # Setup mock instances
        mock_rag_instance = MagicMock()
        mock_rag_instance.generate_answer.return_value = mock_response
        mock_rag.return_value = mock_rag_instance

        mock_formatter_instance = MagicMock()
        mock_formatter_instance.format_api_response.return_value = {
            "status": "success",
            "answer": mock_response["answer"],
            "debug": {"processing_time": 1800},
        }
        mock_formatter.return_value = mock_formatter_instance

        mock_llm.from_environment.return_value = MagicMock()

        request_data = {
            "message": "What are the security requirements?",
            "include_debug": True,
        }

        response = client.post("/chat", data=json.dumps(request_data), content_type="application/json")

        assert response.status_code == 200
        data = response.get_json()
        assert data["status"] == "success"

    @patch.dict(os.environ, {"OPENROUTER_API_KEY": "test_key"})
    @patch("src.routes.main_routes.get_rag_pipeline")
    def test_chat_endpoint_refuses_off_corpus_questions(self, mock_get_rag_pipeline, client):
        """Test that /chat refuses to answer questions outside the corpus"""
        # Mock RAG pipeline to simulate off-corpus refusal
        mock_pipeline = MagicMock()
        mock_response = MagicMock()
        mock_response.answer = "I can only answer questions about our company policies and procedures."
        mock_response.confidence = 0.0
        mock_response.sources = []
        mock_pipeline.generate_answer.return_value = mock_response
        mock_get_rag_pipeline.return_value = mock_pipeline

        # Ask an off-corpus question
        request_data = {"message": "What is the capital of France?"}
        response = client.post("/chat", data=json.dumps(request_data), content_type="application/json")

        assert response.status_code == 200
        data = response.get_json()
        assert data["status"] == "success"
        # Should contain refusal language
        assert "I can only answer" in data["answer"] or "only answer about" in data.get("response", "")

    @patch.dict(os.environ, {"OPENROUTER_API_KEY": "test_key"})
    @patch("src.routes.main_routes.get_rag_pipeline")
    def test_chat_endpoint_limits_output_length(self, mock_get_rag_pipeline, client):
        """Test that /chat limits output length according to config"""
        # Create a response longer than typical max_response_length (1000 chars) with ellipsis to simulate truncation
        long_response_base = "This is a very long policy response that should be truncated. " * 16  # ~1024 chars
        truncated_response = long_response_base[:997] + "..."  # Simulate RAG pipeline truncation

        # Mock the RAG pipeline to return a truncated response as the actual pipeline would
        mock_pipeline = MagicMock()
        mock_response = MagicMock()
        mock_response.success = True
        mock_response.answer = truncated_response
        mock_response.confidence = 0.9
        mock_response.sources = [{"source": "policy.md", "content": "test"}]
        mock_response.processing_time = 0.5
        mock_response.context_length = 500
        mock_response.llm_provider = "test"
        mock_response.llm_model = "test"
        mock_response.search_results_count = 1
        mock_pipeline.generate_answer.return_value = mock_response
        mock_get_rag_pipeline.return_value = mock_pipeline

        request_data = {"message": "Tell me about the vacation policy in great detail"}
        response = client.post("/chat", data=json.dumps(request_data), content_type="application/json")

        assert response.status_code == 200
        data = response.get_json()
        assert data["status"] == "success"

        # Response should be truncated - check for ellipsis or reasonable length
        response_text = data.get("answer", data.get("response", ""))
        assert len(response_text) <= 1000 or response_text.endswith(
            "..."
        ), f"Response should be limited or truncated, got {len(response_text)} chars"

    @patch.dict(os.environ, {"OPENROUTER_API_KEY": "test_key"})
    @patch("src.routes.main_routes.get_rag_pipeline")
    def test_chat_endpoint_always_includes_citations(self, mock_get_rag_pipeline, client):
        """Test that /chat always includes at least one source citation"""
        # Mock RAG pipeline to return response with sources
        mock_pipeline = MagicMock()
        mock_response = MagicMock()
        mock_response.answer = "According to our policy, employees get 15 days of vacation."
        mock_response.confidence = 0.9
        mock_response.sources = [{"source": "vacation_policy.md", "content": "Vacation policy details"}]
        mock_pipeline.generate_answer.return_value = mock_response
        mock_get_rag_pipeline.return_value = mock_pipeline

        request_data = {"message": "How many vacation days do employees get?"}
        response = client.post("/chat", data=json.dumps(request_data), content_type="application/json")

        assert response.status_code == 200
        data = response.get_json()
        assert data["status"] == "success"

        # Should have citations in sources array
        assert "sources" in data
        assert len(data["sources"]) > 0

        # Response text should contain citation markers or sources should be populated
        response_text = data.get("answer", data.get("response", ""))
        has_citation_in_text = "[Source:" in response_text or "[source:" in response_text
        has_sources_array = len(data.get("sources", [])) > 0

        assert (
            has_citation_in_text or has_sources_array
        ), "Response must include citations either in text or sources array"


class TestChatHealthEndpoint:
    """Test cases for the /chat/health endpoint"""

    @pytest.fixture(autouse=True)
    def _clear_app_config(self, app):
        # Clear any mock state that might persist between tests
        # Clear app cache to ensure clean state
        app.config["RAG_PIPELINE"] = None
        app.config["INGESTION_PIPELINE"] = None
        app.config["SEARCH_SERVICE"] = None

    @patch.dict(os.environ, {"OPENROUTER_API_KEY": "test_key"})
    @patch("src.llm.llm_service.LLMService.from_environment")
    @patch("src.rag.rag_pipeline.RAGPipeline.health_check")
    def test_chat_health_healthy(self, mock_health_check, mock_llm_service, client):
        """Test chat health endpoint when all services are healthy"""
        mock_health_data = {
            "pipeline": "healthy",
            "components": {
                "search_service": {"status": "healthy"},
                "llm_service": {"status": "healthy"},
                "vector_db": {"status": "healthy"},
            },
        }
        mock_health_check.return_value = mock_health_data
        # Return a simple object instead of MagicMock to avoid serialization issues
        mock_llm_service.return_value = object()

        response = client.get("/chat/health")

        assert response.status_code == 200
        data = response.get_json()
        assert data["status"] == "success"

    @patch.dict(os.environ, {"OPENROUTER_API_KEY": "test_key"})
    @patch("src.llm.llm_service.LLMService.from_environment")
    @patch("src.rag.rag_pipeline.RAGPipeline.health_check")
    def test_chat_health_degraded(self, mock_health_check, mock_llm_service, client):
        """Test chat health endpoint when services are degraded"""
        mock_health_data = {
            "pipeline": "degraded",
            "components": {
                "search_service": {"status": "healthy"},
                "llm_service": {"status": "degraded", "warning": "High latency"},
                "vector_db": {"status": "healthy"},
            },
        }
        mock_health_check.return_value = mock_health_data
        # Return a simple object instead of MagicMock to avoid serialization issues
        mock_llm_service.return_value = object()

        response = client.get("/chat/health")

        assert response.status_code == 200
        data = response.get_json()
        assert data["status"] == "success"

    def test_chat_health_no_llm_config(self, client):
        """Test chat health endpoint with no LLM configuration"""
        with patch.dict(os.environ, {}, clear=True):
            response = client.get("/chat/health")

            assert response.status_code == 503
            data = response.get_json()
            assert data["status"] == "error"
            assert "LLM" in data["message"] and "configuration error" in data["message"]

    @patch.dict(os.environ, {"OPENROUTER_API_KEY": "test_key"})
    @patch("src.llm.llm_service.LLMService.from_environment")
    @patch("src.rag.rag_pipeline.RAGPipeline.health_check")
    @patch("src.routes.main_routes.get_rag_pipeline")
    def test_chat_health_unhealthy(self, mock_get_rag_pipeline, mock_health_check, mock_llm_service, client):
        """Test chat health endpoint when services are unhealthy"""
        mock_health_data = {
            "pipeline": "unhealthy",
            "components": {
                "search_service": {
                    "status": "unhealthy",
                    "error": "Database connection failed",
                },
                "llm_service": {"status": "unhealthy", "error": "API unreachable"},
                "vector_db": {"status": "unhealthy"},
            },
        }
        mock_health_check.return_value = mock_health_data
        # Return a simple object instead of MagicMock to avoid serialization issues
        mock_llm_service.return_value = object()

        # Create a mock pipeline that has the health_check method
        mock_pipeline = MagicMock()
        mock_pipeline.health_check.return_value = mock_health_data
        mock_get_rag_pipeline.return_value = mock_pipeline

        response = client.get("/chat/health")

        assert response.status_code == 503
        data = response.get_json()
        assert data["status"] == "success"  # Still returns success, but 503 status code