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- Added `planning_context` to the `suggestExerciseAi` endpoint, enabling structured planning context for new exercise creation. - Updated relevant components and backend logic to handle the new planning context, enhancing the AI's exercise suggestion capabilities. - Incremented application version to 0.8.208 to reflect these changes.
109 lines
3.7 KiB
Python
109 lines
3.7 KiB
Python
"""
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Gemeinsame Pydantic-Modelle fuer Uebungs-KI-Kontext (Formularfelder → Prompt-Platzhalter).
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Keine Imports aus exercise_ai — vermeidet Zirkelimporte mit ai_prompt_job / exercise_ai.
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"""
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from __future__ import annotations
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from typing import Any, Dict, List, Optional, Sequence, Tuple
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from pydantic import BaseModel, Field
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class ExerciseFormAiFocusRow(BaseModel):
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"""Fokusbereich fuer Skill-Retrieval (ai_skill_retrieval_profiles)."""
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focus_area_id: int = Field(..., ge=1)
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is_primary: Optional[bool] = False
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class ExerciseFormAiPromptContext(BaseModel):
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"""
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Inhaltliche Eingabe fuer Uebungs-Prompts (Kurzfassung / Skills / Anleitung).
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Wird genutzt von Admin-Prompt-Vorschau und POST /exercises/ai/suggest (via Mapping).
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"""
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title: Optional[str] = ""
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goal: Optional[str] = None
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execution: Optional[str] = None
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preparation: Optional[str] = None
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trainer_notes: Optional[str] = None
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focus_hint: Optional[str] = None
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focus_areas_context: Optional[List[ExerciseFormAiFocusRow]] = None
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planning_context: Optional[Dict[str, Any]] = None
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def focus_area_tuples(self) -> Optional[List[Tuple[int, bool]]]:
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if not self.focus_areas_context:
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return None
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return [(int(x.focus_area_id), bool(x.is_primary)) for x in self.focus_areas_context]
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def has_instruction_source_text(self) -> bool:
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"""Mindestens ein Anleitungsfeld oder Titel fuer instruction_rewrite."""
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if (self.title or "").strip():
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return True
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for val in (self.goal, self.execution, self.preparation, self.trainer_notes):
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if val and str(val).strip():
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return True
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return False
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@classmethod
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def from_api_suggest(
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cls,
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*,
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title: Optional[str] = None,
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goal: Optional[str] = None,
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execution: Optional[str] = None,
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preparation: Optional[str] = None,
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trainer_notes: Optional[str] = None,
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focus_area_hint: Optional[str] = None,
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focus_areas_context: Optional[Sequence[ExerciseFormAiFocusRow]] = None,
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planning_context: Optional[Dict[str, Any]] = None,
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) -> ExerciseFormAiPromptContext:
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"""Mappt Felder aus POST /exercises/ai/suggest (focus_area_hint → focus_hint)."""
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hint = (focus_area_hint or "").strip() or None
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return cls(
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title=(title or "").strip(),
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goal=goal,
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execution=execution,
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preparation=preparation,
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trainer_notes=trainer_notes,
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focus_hint=hint,
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focus_areas_context=list(focus_areas_context) if focus_areas_context else None,
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planning_context=dict(planning_context) if planning_context else None,
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)
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@classmethod
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def from_focus_tuples(
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cls,
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*,
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title: str = "",
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goal: Optional[str] = None,
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execution: Optional[str] = None,
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preparation: Optional[str] = None,
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trainer_notes: Optional[str] = None,
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focus_hint: Optional[str] = None,
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focus_tuples: Optional[Sequence[Tuple[int, bool]]] = None,
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) -> ExerciseFormAiPromptContext:
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rows = None
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if focus_tuples:
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rows = [
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ExerciseFormAiFocusRow(focus_area_id=int(fid), is_primary=bool(prim))
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for fid, prim in focus_tuples
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]
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return cls(
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title=(title or "").strip(),
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goal=goal,
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execution=execution,
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preparation=preparation,
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trainer_notes=trainer_notes,
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focus_hint=(focus_hint or "").strip() or None,
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focus_areas_context=rows,
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)
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__all__ = [
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"ExerciseFormAiFocusRow",
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"ExerciseFormAiPromptContext",
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]
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