models.py

• Pfad: /var/www/scripts/pipeline/knowledge/models.py
• Namespace: pipeline
• Zeilen: 40 | Größe: 865 Bytes
• Geändert: 2025-12-25 15:50:37 | Gescannt: 2025-12-31 10:22:15

Code Hygiene Score: 100

• Dependencies: 100 (25%)
• LOC: 100 (20%)
• Methods: 100 (20%)
• Secrets: 100 (15%)
• Classes: 100 (10%)
• Magic Numbers: 100 (10%)

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Dependencies 3

• extends Enum
• use dataclasses.dataclass
• use enum.Enum

Klassen 3

• KnowledgeLevel class Zeile 7
• KnowledgeType class Zeile 15
• ModelConfig class Zeile 25

Code

"""Datenmodelle für Wissensextraktion."""

from dataclasses import dataclass
from enum import Enum


class KnowledgeLevel(Enum):
    """Ebene der Wissensextraktion."""

    PAGE = "page"
    SECTION = "section"
    DOCUMENT = "document"


class KnowledgeType(Enum):
    """Typ des extrahierten Wissens."""

    ENTITY = "entity"
    SEMANTIC = "semantic"
    ONTOLOGY = "ontology"
    TAXONOMY = "taxonomy"


@dataclass
class ModelConfig:
    """Konfiguration für LLM-Modell."""

    provider: str  # 'ollama' oder 'anthropic'
    model_name: str
    temperature: float = 0.3
    max_tokens: int = 2000


# Standard-Modellkonfigurationen
DEFAULT_MODELS = {
    "ollama": ModelConfig("ollama", "gemma3:27b-it-qat"),
    "anthropic": ModelConfig("anthropic", "claude-3-haiku-20240307"),
    "anthropic_opus": ModelConfig("anthropic", "claude-opus-4-5-20251101"),
}