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"content": "venv\/lib\/python3.13\/site-packages\/mysql\/ai\/ml\/model.py:69: TOPIC_MODELING = \"topic_modeling\"\nvenv\/lib\/python3.13\/site-packages\/pydantic\/mypy.py:84:BASEMODEL_FULLNAME = 'pydantic.main.BaseModel'\nvenv\/lib\/python3.13\/site-packages\/pydantic\/mypy.py:86:ROOT_MODEL_FULLNAME = 'pydantic.root_model.RootModel'\nvenv\/lib\/python3.13\/site-packages\/pydantic\/mypy.py:87:MODEL_METACLASS_FULLNAME = 'pydantic._internal._model_construction.ModelMetaclass'\nvenv\/lib\/python3.13\/site-packages\/pydantic\/mypy.py:90:MODEL_VALIDATOR_FULLNAME = 'pydantic.functional_validators.model_validator'\nvenv\/lib\/python3.13\/site-packages\/pydantic\/mypy.py:1224:ERROR_EXTRA_FIELD_ROOT_MODEL = ErrorCode('pydantic-field', 'Extra field on RootModel subclass', 'Pydantic')\nvenv\/lib\/python3.13\/site-packages\/pydantic\/v1\/mypy.py:80:BASEMODEL_FULLNAME = f'{_NAMESPACE}.main.BaseModel'\nvenv\/lib\/python3.13\/site-packages\/pydantic\/v1\/mypy.py:82:MODEL_METACLASS_FULLNAME = f'{_NAMESPACE}.main.ModelMetaclass'\nvenv\/lib\/python3.13\/site-packages\/lxml\/xmlerror.pxi:1002:DTD_CONTENT_MODEL=504\nvenv\/lib\/python3.13\/site-packages\/lxml\/includes\/xmlerror.pxd:176: XML_DTD_CONTENT_MODEL = 504\nvenv\/lib\/python3.13\/site-packages\/qdrant_client\/fastembed_common.py:38: _TEXT_MODELS: set[str] = set()\nvenv\/lib\/python3.13\/site-packages\/qdrant_client\/fastembed_common.py:39: _IMAGE_MODELS: set[str] = set()\nvenv\/lib\/python3.13\/site-packages\/qdrant_client\/fastembed_common.py:40: _LATE_INTERACTION_TEXT_MODELS: set[str] = set()\nvenv\/lib\/python3.13\/site-packages\/qdrant_client\/fastembed_common.py:41: _LATE_INTERACTION_MULTIMODAL_MODELS: set[str] = set()\nvenv\/lib\/python3.13\/site-packages\/qdrant_client\/fastembed_common.py:42: _SPARSE_MODELS: set[str] = set()\nvenv\/lib\/python3.13\/site-packages\/qdrant_client\/fastembed_common.py:187: cls._TEXT_MODELS = {model.lower() for model in cls.list_text_models()}\nvenv\/lib\/python3.13\/site-packages\/qdrant_client\/fastembed_common.py:205: cls._IMAGE_MODELS = {model.lower() for model in cls.list_image_models()}\nvenv\/lib\/python3.13\/site-packages\/qdrant_client\/fastembed_common.py:223: cls._LATE_INTERACTION_TEXT_MODELS = {\nvenv\/lib\/python3.13\/site-packages\/qdrant_client\/fastembed_common.py:243: cls._LATE_INTERACTION_MULTIMODAL_MODELS = {\nvenv\/lib\/python3.13\/site-packages\/qdrant_client\/fastembed_common.py:263: cls._SPARSE_MODELS = {model.lower() for model in cls.list_sparse_models()}\nvenv\/lib\/python3.13\/site-packages\/qdrant_client\/fastembed_common.py:272:SUPPORTED_EMBEDDING_MODELS: dict[str, tuple[int, models.Distance]] = (\nvenv\/lib\/python3.13\/site-packages\/qdrant_client\/fastembed_common.py:281:SUPPORTED_SPARSE_EMBEDDING_MODELS: dict[str, dict[str, Any]] = (\nvenv\/lib\/python3.13\/site-packages\/qdrant_client\/fastembed_common.py:287:IDF_EMBEDDING_MODELS: set[str] = (\nvenv\/lib\/python3.13\/site-packages\/qdrant_client\/fastembed_common.py:297:_LATE_INTERACTION_EMBEDDING_MODELS: dict[str, tuple[int, models.Distance]] = (\nvenv\/lib\/python3.13\/site-packages\/qdrant_client\/fastembed_common.py:306:_IMAGE_EMBEDDING_MODELS: dict[str, tuple[int, models.Distance]] = (\nvenv\/lib\/python3.13\/site-packages\/qdrant_client\/fastembed_common.py:315:_LATE_INTERACTION_MULTIMODAL_EMBEDDING_MODELS: dict[str, tuple[int, models.Distance]] = (\nvenv\/lib\/python3.13\/site-packages\/qdrant_client\/async_qdrant_fastembed.py:39: DEFAULT_EMBEDDING_MODEL = \"BAAI\/bge-small-en\"\nvenv\/lib\/python3.13\/site-packages\/qdrant_client\/qdrant_fastembed.py:33: DEFAULT_EMBEDDING_MODEL = \"BAAI\/bge-small-en\"\nvenv\/lib\/python3.13\/site-packages\/qdrant_client\/embed\/builtin_embedder.py:8: _SUPPORTED_MODELS = (\"Qdrant\/Bm25\",)\nvenv\/lib\/python3.13\/site-packages\/qdrant_client\/grpc\/points_pb2.py:69: _globals['_INFERENCEUSAGE_MODELSENTRY']._options = None\nvenv\/lib\/python3.13\/site-packages\/qdrant_client\/grpc\/points_pb2.py:70: _globals['_INFERENCEUSAGE_MODELSENTRY']._serialized_options = b'8\\001'\nvenv\/lib\/python3.13\/site-packages\/qdrant_client\/grpc\/points_pb2.py:357: _globals['_INFERENCEUSAGE_MODELSENTRY']._serialized_start=25319\nvenv\/lib\/python3.13\/site-packages\/qdrant_client\/grpc\/points_pb2.py:358: _globals['_INFERENCEUSAGE_MODELSENTRY']._serialized_end=25384\nvenv\/lib\/python3.13\/site-packages\/qdrant_client\/grpc\/points_pb2.py:359: _globals['_MODELUSAGE']._serialized_start=25386\nvenv\/lib\/python3.13\/site-packages\/qdrant_client\/grpc\/points_pb2.py:360: _globals['_MODELUSAGE']._serialized_end=25414\nvenv\/lib\/python3.13\/site-packages\/anthropic\/resources\/messages\/messages.py:50:DEPRECATED_MODELS = {\nvenv\/lib\/python3.13\/site-packages\/anthropic\/_constants.py:20:MODEL_NONSTREAMING_TOKENS = {\ngenerate_semantics.py:14:MODEL = \"gemma3:27b-it-qat\"\ngenerate.py:364: model=ANTHROPIC_MODEL, max_tokens=4000, messages=[{\"role\": \"user\", \"content\": prompt}]\nsemantic_chunk_analyzer.py:33:ANALYSIS_MODEL = \"mistral\" # Schnell und gut für Deutsch\nvision.py:22:DEFAULT_VISION_MODEL = \"minicpm-v:latest\"\nvision.py:70:def analyze_image_ollama(image_bytes, model=DEFAULT_VISION_MODEL, prompt=None):\nvision.py:131:def analyze_document(file_path, model=DEFAULT_VISION_MODEL, store_images=False, image_dir=None):\nknowledge.py:58:DEFAULT_MODELS = {\nchat.py:21: f\"{OLLAMA_HOST}\/api\/embeddings\", json={\"model\": EMBEDDING_MODEL, \"prompt\": text}, timeout=60\nconfig.py:49:EMBEDDING_MODEL = \"mxbai-embed-large\" # 1024-dim, max ~1600 chars per chunk\nconfig.py:53:OLLAMA_CHAT_MODEL = \"gemma3:27b-it-qat\"\nconfig.py:56:ANTHROPIC_MODEL = \"claude-opus-4-5-20251101\"\nquality_test.py:22:MODELS = {\nanalyze.py:108: model=ANTHROPIC_MODEL, max_tokens=2000, messages=[{\"role\": \"user\", \"content\": prompt}]\nanalyze.py:154: model=ANTHROPIC_MODEL, max_tokens=1000, messages=[{\"role\": \"user\", \"content\": prompt}]\nanalyze.py:204: model=ANTHROPIC_MODEL, max_tokens=500, messages=[{\"role\": \"user\", \"content\": prompt}]",
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