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Cleanup: Remove temporary debug files

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Krümel Branko
2025-12-07 20:46:22 +01:00
parent 9c01bc0607
commit 2fd60fdfd5
2 changed files with 0 additions and 3 deletions
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2
probe.txt
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Version: 1.16.1
Dir: ['DEFAULT_BATCH_SIZE', 'DEFAULT_EMBEDDING_MODEL', '_FASTEMBED_INSTALLED', '__annotate_func__', '__class__', '__del__', '__delattr__', '__dict__', '__dir__', '__doc__', '__eq__', '__firstlineno__', '__format__', '__ge__', '__getattribute__', '__getstate__', '__gt__', '__hash__', '__init__', '__init_subclass__', '__le__', '__lt__', '__module__', '__ne__', '__new__', '__reduce__', '__reduce_ex__', '__repr__', '__setattr__', '__sizeof__', '__static_attributes__', '__str__', '__subclasshook__', '__weakref__', '_client', '_embed_documents', '_embed_models', '_embed_models_strict', '_embedding_model_name', '_get_model_params', '_get_or_init_model', '_get_or_init_sparse_model', '_inference_inspector', '_init_options', '_model_embedder', '_points_iterator', '_resolve_query', '_resolve_query_batch_request', '_resolve_query_request', '_scored_points_to_query_responses', '_sparse_embed_documents', '_sparse_embedding_model_name', '_validate_collection_info', 'add', 'batch_update_points', 'clear_payload', 'close', 'cloud_inference', 'cluster_collection_update', 'cluster_status', 'collection_cluster_info', 'collection_exists', 'count', 'create_collection', 'create_full_snapshot', 'create_payload_index', 'create_shard_key', 'create_shard_snapshot', 'create_snapshot', 'delete', 'delete_collection', 'delete_full_snapshot', 'delete_payload', 'delete_payload_index', 'delete_shard_key', 'delete_shard_snapshot', 'delete_snapshot', 'delete_vectors', 'embedding_model_name', 'facet', 'get_aliases', 'get_collection', 'get_collection_aliases', 'get_collections', 'get_embedding_size', 'get_fastembed_sparse_vector_params', 'get_fastembed_vector_params', 'get_sparse_vector_field_name', 'get_vector_field_name', 'grpc_collections', 'grpc_points', 'http', 'info', 'init_options', 'list_full_snapshots', 'list_image_models', 'list_late_interaction_multimodal_models', 'list_late_interaction_text_models', 'list_shard_snapshots', 'list_snapshots', 'list_sparse_models', 'list_text_models', 'local_inference_batch_size', 'migrate', 'overwrite_payload', 'query', 'query_batch', 'query_batch_points', 'query_points', 'query_points_groups', 'recover_current_peer', 'recover_shard_snapshot', 'recover_snapshot', 'recreate_collection', 'remove_peer', 'retrieve', 'scroll', 'search_matrix_offsets', 'search_matrix_pairs', 'set_model', 'set_payload', 'set_sparse_model', 'sparse_embedding_model_name', 'update_collection', 'update_collection_aliases', 'update_vectors', 'upload_collection', 'upload_points', 'upsert']

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sig.txt
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(self, collection_name: str, query: int | str | uuid.UUID | qdrant_common_pb2.PointId | list[float] | list[list[float]] | qdrant_client.http.models.models.SparseVector | qdrant_client.http.models.models.NearestQuery | qdrant_client.http.models.models.RecommendQuery | qdrant_client.http.models.models.DiscoverQuery | qdrant_client.http.models.models.ContextQuery | qdrant_client.http.models.models.OrderByQuery | qdrant_client.http.models.models.FusionQuery | qdrant_client.http.models.models.RrfQuery | qdrant_client.http.models.models.FormulaQuery | qdrant_client.http.models.models.SampleQuery | numpy.ndarray[tuple[Any, ...], numpy.dtype[numpy.bool | numpy.int8 | numpy.int16 | numpy.int32 | numpy.int64 | numpy.uint8 | numpy.uint16 | numpy.uint32 | numpy.uint64 | numpy.float16 | numpy.float32 | numpy.float64 | numpy.longdouble]] | qdrant_client.http.models.models.Document | qdrant_client.http.models.models.Image | qdrant_client.http.models.models.InferenceObject | None = None, using: str | None = None, prefetch: qdrant_client.http.models.models.Prefetch | list[qdrant_client.http.models.models.Prefetch] | None = None, query_filter: qdrant_client.http.models.models.Filter | qdrant_common_pb2.Filter | None = None, search_params: qdrant_client.http.models.models.SearchParams | points_pb2.SearchParams | None = None, limit: int = 10, offset: int | None = None, with_payload: bool | Sequence[str] | qdrant_client.http.models.models.PayloadSelectorInclude | qdrant_client.http.models.models.PayloadSelectorExclude | points_pb2.WithPayloadSelector = True, with_vectors: bool | Sequence[str] = False, score_threshold: float | None = None, lookup_from: qdrant_client.http.models.models.LookupLocation | points_pb2.LookupLocation | None = None, consistency: Annotated[int, Strict(strict=True)] | qdrant_client.http.models.models.ReadConsistencyType | None = None, shard_key_selector: Annotated[int, Strict(strict=True)] | Annotated[str, Strict(strict=True)] | List[Annotated[int, Strict(strict=True)] | Annotated[str, Strict(strict=True)]] | qdrant_client.http.models.models.ShardKeyWithFallback | None = None, timeout: int | None = None, **kwargs: Any) -> qdrant_client.http.models.models.QueryResponse