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- Replaced the previous exercise matching logic with a new multistage planning retrieval process, improving the accuracy of exercise suggestions. - Introduced LLM gates to limit LLM calls based on query length and intent application, optimizing performance and resource usage. - Updated the `compose_retrieval_phase` function to include profile preselection, enhancing the retrieval process. - Incremented version to 0.5.0 and updated changelog to reflect these significant enhancements in planning AI capabilities.
101 lines
3.9 KiB
Python
101 lines
3.9 KiB
Python
"""Tests Planungs-Übungssuche: Intent, Szenario-Pipeline, LLM-Parser."""
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from planning_exercise_suggest import resolve_planning_exercise_intent
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from planning_exercise_intent import parse_planning_query_intent_response
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from planning_exercise_llm_rank import parse_planning_exercise_rank_response
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from planning_exercise_target_pipeline import (
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SCENARIO_ADDITIVE,
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SCENARIO_PRESET_NEXT,
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classify_planning_scenario,
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compose_retrieval_phase,
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is_simple_preset_query,
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should_run_llm_intent_pipeline,
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)
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def test_resolve_planning_exercise_intent_defaults():
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assert resolve_planning_exercise_intent("", None) == "suggest_next"
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assert resolve_planning_exercise_intent(" ", "suggest_next") == "suggest_next"
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def test_resolve_planning_exercise_intent_keywords():
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assert resolve_planning_exercise_intent("Vertiefung Partner", None) == "deepen_exercise"
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assert resolve_planning_exercise_intent("nächste übung", None) == "suggest_next"
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assert resolve_planning_exercise_intent("progression graph", None) == "progression_next"
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def test_classify_planning_scenario_preset():
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assert is_simple_preset_query("Schlage mir die nächste Übung vor")
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assert classify_planning_scenario("", "suggest_next") == SCENARIO_PRESET_NEXT
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assert classify_planning_scenario("nächste übung", "suggest_next") == SCENARIO_PRESET_NEXT
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def test_classify_planning_scenario_additive():
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q = "Baut auf der Planung auf und trainiert zusätzlich Schnellkraft"
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assert classify_planning_scenario(q, "continue_plan_goal") == SCENARIO_ADDITIVE
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assert should_run_llm_intent_pipeline(q, SCENARIO_ADDITIVE, include_llm_intent=True)
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def test_should_skip_llm_for_preset():
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assert not should_run_llm_intent_pipeline("", SCENARIO_PRESET_NEXT, include_llm_intent=True)
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assert not should_run_llm_intent_pipeline(
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"nächste übung",
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SCENARIO_PRESET_NEXT,
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include_llm_intent=True,
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)
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def test_should_skip_llm_intent_short_free_search():
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from planning_exercise_target_pipeline import SCENARIO_FREE_SEARCH, should_run_llm_intent_pipeline
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assert not should_run_llm_intent_pipeline(
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"Partnerübung",
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SCENARIO_FREE_SEARCH,
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include_llm_intent=True,
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)
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def test_should_skip_llm_rank_when_intent_already_applied():
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from planning_exercise_target_pipeline import SCENARIO_ADDITIVE, should_run_llm_rank_pipeline
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hits = [{"score": 0.5}, {"score": 0.48}, {"score": 0.47}, {"score": 0.46}]
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assert not should_run_llm_rank_pipeline(
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"Baut auf dem Plan auf und trainiert zusätzlich Schnellkraft mit Partner",
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SCENARIO_ADDITIVE,
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include_llm_rank=True,
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query_intent_applied=True,
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hits=hits,
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)
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def test_compose_retrieval_phase():
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assert compose_retrieval_phase(query_intent=False, llm_rank=False) == "profile_v1"
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assert compose_retrieval_phase(query_intent=True, llm_rank=True) == "profile_v1+query_intent+llm_rank"
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assert (
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compose_retrieval_phase(profile_preselect=True, query_intent=True, llm_rank=False)
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== "profile_v1+profile_preselect+query_intent"
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)
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def test_parse_planning_query_intent_response():
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parsed = parse_planning_query_intent_response(
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'{"intent":"continue_plan_goal","scenario":"additive_constraint",'
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'"skill_hints":[{"name":"Schnellkraft","weight":1}],"emphasis":"additive",'
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'"rationale":"Zusatz Schnellkraft"}'
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)
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assert parsed.intent == "continue_plan_goal"
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assert parsed.scenario == "additive_constraint"
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assert parsed.skill_hints[0].name == "Schnellkraft"
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def test_parse_planning_exercise_rank_response_filters_ids():
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allowed = {10, 20, 30}
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ranked, reasons = parse_planning_exercise_rank_response(
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'{"ranked_ids":[20,999,20,10],"reasons":{"20":"Passt gut","999":"ignore"}}',
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allowed,
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)
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assert ranked == [20, 10]
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assert reasons[20] == "Passt gut"
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assert 999 not in reasons
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