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86 lines
4.4 KiB
Python
86 lines
4.4 KiB
Python
"""
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FILE: app/config.py
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DESCRIPTION: Zentrale Pydantic-Konfiguration.
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WP-20: Hybrid-Cloud Modus Support (OpenRouter/Gemini/Ollama).
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FIX: Einführung von Parametern zur intelligenten Rate-Limit Steuerung (429 Handling).
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VERSION: 0.6.7
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STATUS: Active
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DEPENDENCIES: os, functools, pathlib, python-dotenv
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"""
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from __future__ import annotations
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import os
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from functools import lru_cache
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from pathlib import Path
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from dotenv import load_dotenv
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# WP-20: Lade Umgebungsvariablen aus der .env Datei
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# override=True garantiert, dass Änderungen in der .env immer Vorrang haben.
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load_dotenv(override=True)
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class Settings:
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# --- Qdrant Datenbank ---
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QDRANT_URL: str = os.getenv("QDRANT_URL", "http://127.0.0.1:6333")
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QDRANT_API_KEY: str | None = os.getenv("QDRANT_API_KEY")
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# WP-24c v4.5.10: Harmonisierung - Unterstützt beide Umgebungsvariablen für Abwärtskompatibilität
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# COLLECTION_PREFIX hat Priorität, MINDNET_PREFIX als Fallback
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COLLECTION_PREFIX: str = os.getenv("COLLECTION_PREFIX") or os.getenv("MINDNET_PREFIX") or "mindnet_dev"
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# WP-22: Vektor-Dimension für das Embedding-Modell (nomic)
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VECTOR_SIZE: int = int(os.getenv("VECTOR_DIM", "768"))
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DISTANCE: str = os.getenv("MINDNET_DISTANCE", "Cosine")
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# --- Lokale Embeddings (Ollama & Sentence-Transformers) ---
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EMBEDDING_MODEL: str = os.getenv("MINDNET_EMBEDDING_MODEL", "nomic-embed-text")
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MODEL_NAME: str = os.getenv("MINDNET_MODEL", "sentence-transformers/all-MiniLM-L6-v2")
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# --- WP-20 Hybrid LLM Provider ---
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# Erlaubt: "ollama" | "gemini" | "openrouter"
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MINDNET_LLM_PROVIDER: str = os.getenv("MINDNET_LLM_PROVIDER", "openrouter").lower()
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# Standardwert 10000, falls nichts in der .env steht
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MAX_OLLAMA_CHARS: int = int(os.getenv("MAX_OLLAMA_CHARS", 10000))
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# Google AI Studio (2025er Lite-Modell für höhere Kapazität)
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GOOGLE_API_KEY: str | None = os.getenv("GOOGLE_API_KEY")
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GEMINI_MODEL: str = os.getenv("MINDNET_GEMINI_MODEL", "gemini-2.5-flash-lite")
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# OpenRouter Integration (Verfügbares Free-Modell 2025)
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OPENROUTER_API_KEY: str | None = os.getenv("OPENROUTER_API_KEY")
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OPENROUTER_MODEL: str = os.getenv("OPENROUTER_MODEL", "mistralai/mistral-7b-instruct:free")
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LLM_FALLBACK_ENABLED: bool = os.getenv("MINDNET_LLM_FALLBACK", "true").lower() == "true"
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# --- NEU: Intelligente Rate-Limit Steuerung ---
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# Dauer der Wartezeit in Sekunden, wenn ein HTTP 429 (Rate Limit) auftritt
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LLM_RATE_LIMIT_WAIT: float = float(os.getenv("MINDNET_LLM_RATE_LIMIT_WAIT", "60.0"))
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# Anzahl der Cloud-Retries bei 429, bevor Ollama-Fallback greift
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LLM_RATE_LIMIT_RETRIES: int = int(os.getenv("MINDNET_LLM_RATE_LIMIT_RETRIES", "3"))
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# --- WP-05 Lokales LLM (Ollama) ---
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OLLAMA_URL: str = os.getenv("MINDNET_OLLAMA_URL", "http://127.0.0.1:11434")
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LLM_MODEL: str = os.getenv("MINDNET_LLM_MODEL", "phi3:mini")
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PROMPTS_PATH: str = os.getenv("MINDNET_PROMPTS_PATH", "config/prompts.yaml")
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# --- WP-06 / WP-14 Performance & Last-Steuerung ---
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LLM_TIMEOUT: float = float(os.getenv("MINDNET_LLM_TIMEOUT", "300.0"))
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DECISION_CONFIG_PATH: str = os.getenv("MINDNET_DECISION_CONFIG", "config/decision_engine.yaml")
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BACKGROUND_LIMIT: int = int(os.getenv("MINDNET_LLM_BACKGROUND_LIMIT", "2"))
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# --- System-Pfade & Ingestion-Logik ---
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DEBUG: bool = os.getenv("DEBUG", "false").lower() == "true"
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MINDNET_VAULT_ROOT: str = os.getenv("MINDNET_VAULT_ROOT", "./vault_master")
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MINDNET_TYPES_FILE: str = os.getenv("MINDNET_TYPES_FILE", "config/types.yaml")
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MINDNET_VOCAB_PATH: str = os.getenv("MINDNET_VOCAB_PATH", "/mindnet/vault/mindnet/_system/dictionary/edge_vocabulary.md")
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CHANGE_DETECTION_MODE: str = os.getenv("MINDNET_CHANGE_DETECTION_MODE", "full")
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# --- WP-04 Retriever Gewichte ---
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RETRIEVER_W_SEM: float = float(os.getenv("MINDNET_WP04_W_SEM", "0.70"))
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RETRIEVER_W_EDGE: float = float(os.getenv("MINDNET_WP04_W_EDGE", "0.25"))
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RETRIEVER_W_CENT: float = float(os.getenv("MINDNET_WP04_W_CENT", "0.05"))
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RETRIEVER_TOP_K: int = int(os.getenv("MINDNET_WP04_TOP_K", "10"))
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RETRIEVER_EXPAND_DEPTH: int = int(os.getenv("MINDNET_WP04_EXPAND_DEPTH", "1"))
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RETRIEVER_EDGE_TYPES: str = os.getenv("MINDNET_WP04_EDGE_TYPES", "references,belongs_to,prev,next")
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@lru_cache
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def get_settings() -> Settings:
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"""Gibt die zentralen Einstellungen als Singleton zurück."""
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return Settings() |