Mark baumann patch 1 - #867
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- reward_model.py: Regelbasiertes + modellbasiertes Reward-Modell für Agent-Bewertung - train_agent.py: GRPO-Training mit LoRA für Qwen/Llama (CLI + API) - GRPO_TRAINING.md: Dokumentation und Schnellstart-Anleitung - pyproject.toml: uv required-version auf >=0.11.6 gesenkt (Kompatibilität)
…und Konfiguration hinzugefügt - train_agent.py: Ungenutzte Imports (annotations, dataclass, Path, load_dataset, TrainingArguments, LocalGRPOConfig) entfernt - reward_model.py: Ungenutzte TYPE_CHECKING-Imports (PreTrainedModel, PreTrainedTokenizer) entfernt - tests/unit/test_reward_model.py: 24 Unit-Tests für AgentRewardModel, create_reward_function und RewardModelWrapper - tests/unit/test_grpo_config.py: 19 Unit-Tests für ModelConfig, LoRAConfig, GRPOConfig, RewardConfig, DataConfig, TrainingConfig und Preset-Configs - Alle 43 Tests bestanden (1 skipped wegen fehlendem torch)
…A-Parameter einstellen
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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