feat: implement mvp with email-first login flow and langgraph architecture

tests/test_researcher_search_tools.py

@@ -0,0 +1,62 @@
+import pytest
+from unittest.mock import MagicMock, patch
+from langchain_core.messages import AIMessage
+from langchain_openai import ChatOpenAI
+from langchain_google_genai import ChatGoogleGenerativeAI
+from ea_chatbot.graph.nodes.researcher import researcher_node
+
+@pytest.fixture
+def base_state():
+    return {
+        "question": "Who won the 2024 election?",
+        "messages": [],
+        "summary": ""
+    }
+
+@patch("ea_chatbot.graph.nodes.researcher.get_llm_model")
+def test_researcher_binds_openai_search(mock_get_llm, base_state):
+    """Test that OpenAI LLM binds 'web_search' tool."""
+    mock_llm = MagicMock(spec=ChatOpenAI)
+    mock_get_llm.return_value = mock_llm
+    
+    mock_llm_with_tools = MagicMock()
+    mock_llm.bind_tools.return_value = mock_llm_with_tools
+    mock_llm_with_tools.invoke.return_value = AIMessage(content="OpenAI Search Result")
+    
+    result = researcher_node(base_state)
+    
+    # Verify bind_tools called with correct OpenAI tool
+    mock_llm.bind_tools.assert_called_once_with([{"type": "web_search"}])
+    assert result["messages"][0].content == "OpenAI Search Result"
+
+@patch("ea_chatbot.graph.nodes.researcher.get_llm_model")
+def test_researcher_binds_google_search(mock_get_llm, base_state):
+    """Test that Google LLM binds 'google_search' tool."""
+    mock_llm = MagicMock(spec=ChatGoogleGenerativeAI)
+    mock_get_llm.return_value = mock_llm
+    
+    mock_llm_with_tools = MagicMock()
+    mock_llm.bind_tools.return_value = mock_llm_with_tools
+    mock_llm_with_tools.invoke.return_value = AIMessage(content="Google Search Result")
+    
+    result = researcher_node(base_state)
+    
+    # Verify bind_tools called with correct Google tool
+    mock_llm.bind_tools.assert_called_once_with([{"google_search": {}}])
+    assert result["messages"][0].content == "Google Search Result"
+
+@patch("ea_chatbot.graph.nodes.researcher.get_llm_model")
+def test_researcher_fallback_on_bind_error(mock_get_llm, base_state):
+    """Test that researcher falls back to basic LLM if bind_tools fails."""
+    mock_llm = MagicMock(spec=ChatOpenAI)
+    mock_get_llm.return_value = mock_llm
+    
+    # Simulate bind_tools failing (e.g. model doesn't support it)
+    mock_llm.bind_tools.side_effect = Exception("Not supported")
+    mock_llm.invoke.return_value = AIMessage(content="Basic Result")
+    
+    result = researcher_node(base_state)
+    
+    # Should still succeed using the base LLM
+    assert result["messages"][0].content == "Basic Result"
+    mock_llm.invoke.assert_called_once()