45 lines
1.9 KiB
Python
45 lines
1.9 KiB
Python
from pathlib import Path
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from didactopus.config import load_config
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from didactopus.learner_session import build_graph_grounded_session
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from didactopus.learner_session_demo import run_learner_session_demo
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from didactopus.model_provider import ModelProvider
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from didactopus.ocw_skill_agent_demo import load_ocw_skill_context
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def test_build_graph_grounded_session_uses_grounded_steps() -> None:
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root = Path(__file__).resolve().parents[1]
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context = load_ocw_skill_context(root / "skills" / "ocw-information-entropy-agent")
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provider = ModelProvider(load_config(root / "configs" / "config.example.yaml").model_provider)
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payload = build_graph_grounded_session(
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context=context,
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provider=provider,
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learner_goal="Help me connect Shannon entropy and channel capacity.",
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learner_submission="Entropy measures uncertainty because unlikely outcomes carry more information, but one limitation is that idealized source models may not match physical systems.",
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language="es",
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)
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assert payload["study_plan"]["steps"]
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assert payload["primary_concept"]["supporting_lessons"]
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assert payload["evaluation"]["verdict"] in {"acceptable", "needs_revision"}
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assert len(payload["turns"]) == 6
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assert payload["output_language"] == "es"
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assert any("Grounding fragments" in turn["content"] or "Concept:" in turn["content"] for turn in payload["turns"])
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def test_run_learner_session_demo_writes_output(tmp_path: Path) -> None:
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root = Path(__file__).resolve().parents[1]
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payload = run_learner_session_demo(
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root / "configs" / "config.example.yaml",
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root / "skills" / "ocw-information-entropy-agent",
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tmp_path / "session.json",
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)
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assert (tmp_path / "session.json").exists()
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assert (tmp_path / "session.html").exists()
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assert (tmp_path / "session.txt").exists()
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assert payload["practice_task"]
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assert payload["evaluation"]["aggregated"]
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assert payload["output_language"] == "en"
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