68c0985482
- Refactored OIDC flow to implement PKCE, state/nonce validation, and BFF pattern. - Centralized configuration in Settings class (DEV_MODE, FRONTEND_URL, OIDC_REDIRECT_URI). - Updated auth routers to use conditional secure cookie flags based on DEV_MODE. - Modernized and cleaned up test suite by removing legacy Streamlit tests. - Fixed linting errors and unused imports across the backend.
76 lines
3.0 KiB
Python
76 lines
3.0 KiB
Python
import pytest
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from unittest.mock import MagicMock, patch
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from langchain_core.messages import HumanMessage, AIMessage
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from ea_chatbot.graph.nodes.query_analyzer import query_analyzer_node, QueryAnalysis
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@pytest.fixture
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def mock_state_with_history():
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return {
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"messages": [
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HumanMessage(content="Show me the 2024 results for Florida"),
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AIMessage(content="Here are the results for Florida in 2024...")
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],
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"question": "What about in New Jersey?",
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"analysis": None,
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"next_action": "",
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"summary": "The user is asking about 2024 election results."
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}
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@patch("ea_chatbot.graph.nodes.query_analyzer.get_llm_model")
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@patch("ea_chatbot.graph.nodes.query_analyzer.QUERY_ANALYZER_PROMPT")
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def test_query_analyzer_uses_history_and_summary(mock_prompt, mock_get_llm, mock_state_with_history):
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"""Test that query_analyzer_node passes history and summary to the prompt."""
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mock_llm_instance = MagicMock()
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mock_get_llm.return_value = mock_llm_instance
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mock_structured_llm = MagicMock()
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mock_llm_instance.with_structured_output.return_value = mock_structured_llm
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mock_structured_llm.invoke.return_value = QueryAnalysis(
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data_required=["2024 results", "New Jersey"],
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unknowns=[],
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ambiguities=[],
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conditions=[],
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next_action="plan"
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)
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query_analyzer_node(mock_state_with_history)
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# Verify that the prompt was formatted with the correct variables
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mock_prompt.format_messages.assert_called_once()
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kwargs = mock_prompt.format_messages.call_args[1]
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assert kwargs["question"] == "What about in New Jersey?"
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assert "summary" in kwargs
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assert kwargs["summary"] == mock_state_with_history["summary"]
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assert "history" in kwargs
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# History should contain the messages from the state
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assert len(kwargs["history"]) == 2
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assert kwargs["history"][0].content == "Show me the 2024 results for Florida"
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@patch("ea_chatbot.graph.nodes.query_analyzer.get_llm_model")
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def test_query_analyzer_context_window(mock_get_llm):
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"""Test that query_analyzer_node only uses the last 6 messages (3 turns)."""
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messages = [HumanMessage(content=f"Msg {i}") for i in range(10)]
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state = {
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"messages": messages,
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"question": "Latest question",
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"analysis": None,
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"next_action": "",
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"summary": "Summary"
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}
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mock_llm_instance = MagicMock()
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mock_get_llm.return_value = mock_llm_instance
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mock_structured_llm = MagicMock()
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mock_llm_instance.with_structured_output.return_value = mock_structured_llm
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mock_structured_llm.invoke.return_value = QueryAnalysis(
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data_required=[], unknowns=[], ambiguities=[], conditions=[], next_action="plan"
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)
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with patch("ea_chatbot.graph.nodes.query_analyzer.QUERY_ANALYZER_PROMPT") as mock_prompt:
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query_analyzer_node(state)
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kwargs = mock_prompt.format_messages.call_args[1]
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# Should only have last 6 messages
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assert len(kwargs["history"]) == 6
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assert kwargs["history"][0].content == "Msg 4"
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