from langchain_core.messages import HumanMessage

from deerflow.agents.memory.thread_prompt import build_thread_memory_prompt, format_thread_memory_for_injection


def test_thread_memory_injection_keeps_profile_and_preferences_under_small_budget(monkeypatch):
    monkeypatch.setattr("deerflow.agents.memory.thread_prompt._count_tokens", lambda text, encoding_name="cl100k_base": len(text))
    memory = {
        "profile": {"name": "Alice", "role": "Engineer", "expertise": ["Python", "React"], "language": "en-US", "context": "Building APIs"},
        "preferences": {"tone": "technical", "verbosity": "concise", "codeStyle": "typed-first", "other": "tests first"},
        "facts": [
            {"content": "Fact one that might be trimmed", "category": "context", "confidence": 0.9},
            {"content": "Fact two that might be trimmed", "category": "context", "confidence": 0.8},
        ],
    }

    result = format_thread_memory_for_injection(memory, max_tokens=140)
    assert "Profile:" in result
    assert "Preferences:" in result


def test_build_thread_memory_prompt_does_not_raise_format_key_error():
    prompt = build_thread_memory_prompt(
        {"profile": {}, "preferences": {}, "facts": []},
        [HumanMessage(content="My name is Alice.")],
    )
    assert "Current per-thread memory" in prompt
    assert '"profile"' in prompt