29 lines
1.3 KiB
Python
29 lines
1.3 KiB
Python
from langchain_core.messages import HumanMessage
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from deerflow.agents.memory.thread_prompt import build_thread_memory_prompt, format_thread_memory_for_injection
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def test_thread_memory_injection_keeps_profile_and_preferences_under_small_budget(monkeypatch):
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monkeypatch.setattr("deerflow.agents.memory.thread_prompt._count_tokens", lambda text, encoding_name="cl100k_base": len(text))
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memory = {
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"profile": {"name": "Alice", "role": "Engineer", "expertise": ["Python", "React"], "language": "en-US", "context": "Building APIs"},
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"preferences": {"tone": "technical", "verbosity": "concise", "codeStyle": "typed-first", "other": "tests first"},
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"facts": [
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{"content": "Fact one that might be trimmed", "category": "context", "confidence": 0.9},
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{"content": "Fact two that might be trimmed", "category": "context", "confidence": 0.8},
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],
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}
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result = format_thread_memory_for_injection(memory, max_tokens=140)
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assert "Profile:" in result
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assert "Preferences:" in result
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def test_build_thread_memory_prompt_does_not_raise_format_key_error():
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prompt = build_thread_memory_prompt(
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{"profile": {}, "preferences": {}, "facts": []},
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[HumanMessage(content="My name is Alice.")],
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)
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assert "Current per-thread memory" in prompt
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assert '"profile"' in prompt
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