import pytest
from unittest.mock import MagicMock, patch
from langchain_core.messages import AIMessage
from ea_chatbot.graph.nodes.summarizer import summarizer_node
from ea_chatbot.graph.state import AgentState

@pytest.fixture
def mock_llm():
    with patch("ea_chatbot.graph.nodes.summarizer.get_llm_model") as mock_get_llm:
        mock_llm_instance = MagicMock()
        mock_get_llm.return_value = mock_llm_instance
        yield mock_llm_instance

def test_summarizer_node_success(mock_llm):
    """Test that summarizer_node invokes LLM with correct inputs and returns messages."""
    state = {
        "question": "What is the total count?",
        "plan": "1. Run query\n2. Sum results",
        "code_output": "The total is 100",
        "messages": []
    }
    
    mock_llm.invoke.return_value = AIMessage(content="The final answer is 100.")
    
    result = summarizer_node(state)
    
    # Verify LLM was called
    assert mock_llm.invoke.called
    
    # Verify result structure
    assert "messages" in result
    assert len(result["messages"]) == 1
    assert isinstance(result["messages"][0], AIMessage)
    assert result["messages"][0].content == "The final answer is 100."

def test_summarizer_node_empty_state(mock_llm):
    """Test handling of empty or minimal state."""
    state = {
        "question": "Empty?",
        "messages": []
    }
    
    mock_llm.invoke.return_value = AIMessage(content="No data provided.")
    
    result = summarizer_node(state)
    
    assert "messages" in result
    assert result["messages"][0].content == "No data provided."