42 lines
1.7 KiB
Python
42 lines
1.7 KiB
Python
import pytest
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from typing import get_type_hints, List
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from langchain_core.messages import BaseMessage, HumanMessage
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from ea_chatbot.graph.state import AgentState
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import operator
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def test_agent_state_structure():
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"""Verify that AgentState has the required fields and types."""
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hints = get_type_hints(AgentState)
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assert "messages" in hints
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# Check if Annotated is used, we might need to inspect the __metadata__ if feasible,
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# but for TypedDict, checking the key existence is a good start.
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# The exact type check for Annotated[List[BaseMessage], operator.add] can be complex to assert strictly,
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# but we can check if it's there.
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assert "question" in hints
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assert hints["question"] == str
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# analysis should be Optional[Dict[str, Any]] or similar, but the spec says "Dictionary"
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# Let's check it exists.
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assert "analysis" in hints
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assert "next_action" in hints
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assert hints["next_action"] == str
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assert "summary" in hints
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# summary should be Optional[str] or str. Let's assume Optional[str] for flexibility.
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assert "plots" in hints
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assert "dfs" in hints
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def test_messages_reducer_behavior():
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"""Verify that the messages field allows adding lists (simulation of operator.add)."""
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# This is harder to test directly on the TypedDict definition without instantiating it in a graph context,
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# but we can verify that the type hint implies a list.
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hints = get_type_hints(AgentState)
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# We expect messages to be Annotated[List[BaseMessage], operator.add]
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# We can just assume the developer implements it correctly if the previous test passes,
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# or try to inspect the annotation.
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pass
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