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- Added `exercise_instruction_rewrite` functionality to enhance AI-generated instructions, incorporating fields for goal, execution, preparation, and trainer notes. - Updated `ExerciseFormAiPromptContext` to include new fields and methods for instruction handling. - Enhanced the `run_exercise_form_ai_suggestion` function to support instruction rewriting and validation. - Modified API endpoints and frontend components to integrate instruction features, including a new button for AI instruction revision. - Incremented application version to 0.8.163 and updated changelog to reflect these changes, including migration details and new functionality.
115 lines
3.3 KiB
Python
115 lines
3.3 KiB
Python
"""
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Gemeinsame KI-Prompt-Laufzeit (Shinkan): DB-Lesezugriff ai_prompts + Kontext-Arten.
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Bleibt ohne Import von exercise_ai (kein Zirkel). Domänen wie exercise_ai nutzen
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load_ai_prompt_row und die Enum; Platzhalter bauen sie selbst oder über geteilte Builder.
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"""
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from __future__ import annotations
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from enum import Enum
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from typing import Any, Dict, Mapping, Optional, Tuple
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from prompt_resolver import MustacheRenderResult, render_mustache_template
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_EXERCISE_AI_SLUGS = frozenset(
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{
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"exercise_summary",
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"exercise_skill_suggestions",
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"exercise_instruction_rewrite",
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}
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)
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class AiPromptContextKind(str, Enum):
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"""
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Logischer Kontext fuer Platzhalter/Builder — erweiterbar fuer Planung/Rahmen
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ohne bestehende Slugs zu invalidieren.
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"""
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EXERCISE_FORM_AI = "exercise_form_ai"
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def context_kind_for_slug(slug: str) -> Optional[AiPromptContextKind]:
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"""Ordnet einen DB-Slug einer Kontext-Art zu, sofern registriert."""
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s = (slug or "").strip().lower()
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if s in _EXERCISE_AI_SLUGS:
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return AiPromptContextKind.EXERCISE_FORM_AI
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return None
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def load_ai_prompt_row(cur, slug: str, *, active_only: bool = True) -> Optional[Dict[str, Any]]:
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"""
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Laedt eine Zeile ai_prompts fuer Laufzeit-Orchestrierung.
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active_only=True: inaktive Prompts werden wie fehlend behandelt (503 im Aufrufer).
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"""
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if active_only:
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cur.execute(
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"""
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SELECT slug, display_name, template, output_format, active, openrouter_model
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FROM ai_prompts
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WHERE slug = %s AND active = true
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""",
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(slug,),
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)
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else:
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cur.execute(
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"""
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SELECT slug, display_name, template, output_format, active, openrouter_model
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FROM ai_prompts
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WHERE slug = %s
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""",
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(slug,),
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)
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row = cur.fetchone()
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if not row:
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return None
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d = dict(row)
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if active_only and not d.get("active", True):
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return None
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return d
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class AiPromptUnavailableError(LookupError):
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"""Kein aktiver Prompt fuer slug (oder Zeile fehlt)."""
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def __init__(self, slug: str) -> None:
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self.slug = (slug or "").strip()
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super().__init__(self.slug)
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def render_ai_prompt_template_for_row(
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row: Mapping[str, Any],
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variables: Mapping[str, str],
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) -> MustacheRenderResult:
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"""Ersetzt Platzhalter anhand einer bereits geladenen ai_prompts-Zeile (z. B. Admin-Vorschauch, inkl. inaktiv)."""
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return render_mustache_template(str(row.get("template") or ""), variables)
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def load_and_render_ai_prompt(
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cur,
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slug: str,
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variables: Mapping[str, str],
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*,
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active_only: bool = True,
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) -> Tuple[Dict[str, Any], MustacheRenderResult]:
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"""
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Laedt einen aktiven Prompt und wendet Mustache-Variablen an.
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Wirft AiPromptUnavailableError, wenn die Zeile fehlt oder (bei active_only) inaktiv ist.
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"""
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row = load_ai_prompt_row(cur, slug, active_only=active_only)
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if not row:
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raise AiPromptUnavailableError(slug)
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rr = render_ai_prompt_template_for_row(row, variables)
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return dict(row), rr
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__all__ = [
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"AiPromptContextKind",
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"AiPromptUnavailableError",
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"context_kind_for_slug",
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"load_ai_prompt_row",
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"load_and_render_ai_prompt",
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"render_ai_prompt_template_for_row",
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]
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