feat: Add Comprehensive Dreadnode Data Types: Image, Audio, Video, Table, and Object3D (#48)

* Add log object support for custom data types: Image, Video, Table, Audio, and 3D Objects

* Fix ruff errors

* Fix mypy errors

* Updated potery lock

* Add missing dependency

* Fix object identification to maintain schema uniqueness while preserving storage efficiency

---------

Co-authored-by: monoxgas <monoxgas@gmail.com>

Author: rdheekonda

dreadnode/__init__.py

@@ -1,3 +1,4 @@
+from dreadnode.data_types import Audio, Image, Object3D, Table, Video
 from dreadnode.main import DEFAULT_INSTANCE, Dreadnode
 from dreadnode.metric import Metric, MetricDict, Scorer
 from dreadnode.object import Object
@@ -30,15 +31,22 @@
 __version__ = VERSION
 
 __all__ = [
+    "Audio",
     "Dreadnode",
+    "Image",
     "Metric",
     "MetricDict",
     "Object",
+    "Object3D",
+    "Run",
     "RunSpan",
     "Scorer",
     "Span",
+    "Table",
     "Task",
     "TaskSpan",
+    "Video",
+    "__version__",
     "api",
     "configure",
     "link_objects",

dreadnode/data_types/__init__.py

@@ -0,0 +1,7 @@
+from .audio import Audio
+from .image import Image
+from .object_3d import Object3D
+from .table import Table
+from .video import Video
+
+__all__ = ["Audio", "Image", "Object3D", "Table", "Video"]

dreadnode/data_types/audio.py

@@ -0,0 +1,186 @@
+import io
+import typing as t
+from pathlib import Path
+
+import numpy as np
+import soundfile as sf  # type: ignore  # noqa: PGH003
+from pydub import AudioSegment  # type: ignore  # noqa: PGH003
+
+from dreadnode.data_types.base_data_type import BaseDataType
+
+AudioDataType: t.TypeAlias = str | Path | np.ndarray[t.Any, t.Any] | bytes | AudioSegment
+
+
+class Audio(BaseDataType):
+    """
+    Audio media type for Dreadnode logging.
+
+    Supports:
+    - Local file paths (str or Path)
+    - Numpy arrays with sample rate
+    - Raw bytes
+    - Pydub AudioSegment object
+    """
+
+    def __init__(
+        self,
+        data: AudioDataType,
+        sample_rate: int | None = None,
+        caption: str | None = None,
+        format: str | None = None,
+    ):
+        """
+        Initialize an Audio object.
+
+        Args:
+            data: The audio data, which can be:
+                - A path to a local audio file (str or Path)
+                - A numpy array (requires sample_rate)
+                - Raw bytes
+                - A pydub AudioSegment
+            sample_rate: Required when using numpy arrays
+            caption: Optional caption for the audio
+            format: Optional format to use (default is wav for numpy arrays)
+        """
+        self._data = data
+        self._sample_rate = sample_rate
+        self._caption = caption
+        self._format = format
+
+    def to_serializable(self) -> tuple[t.Any, dict[str, t.Any]]:
+        """
+        Serialize the audio data to bytes and return with metadata.
+        Returns:
+            A tuple of (audio_bytes, metadata_dict)
+        """
+        audio_bytes, format_name, sample_rate, duration = self._process_audio_data()
+        metadata = self._generate_metadata(format_name, sample_rate, duration)
+        return audio_bytes, metadata
+
+    def _process_audio_data(self) -> tuple[bytes, str, int | None, float | None]:
+        """
+        Process the audio data and return bytes, format, sample rate, and duration.
+        Returns:
+            A tuple of (audio_bytes, format_name, sample_rate, duration)
+        """
+        if isinstance(self._data, (str, Path)) and Path(self._data).exists():
+            return self._process_file_path()
+        if isinstance(self._data, np.ndarray):
+            return self._process_numpy_array()
+        if isinstance(self._data, bytes):
+            return self._process_raw_bytes()
+        if isinstance(self._data, AudioSegment):
+            return self._process_pydub_audio_segment()
+        raise TypeError(f"Unsupported audio data type: {type(self._data)}")
+
+    def _process_file_path(self) -> tuple[bytes, str, int | None, float | None]:
+        """
+        Process audio from file path. Obtain sample rate and duration using soundfile.
+        Returns:
+            A tuple of (audio_bytes, format_name, sample_rate, duration)
+        """
+        path_str = str(self._data)
+        audio_bytes = Path(path_str).read_bytes()
+        format_name = self._format or Path(path_str).suffix.lstrip(".").lower() or "wav"
+        sample_rate = self._sample_rate
+        duration = None
+        with sf.SoundFile(path_str) as f:
+            sample_rate = sample_rate or f.samplerate
+            duration = f.frames / f.samplerate
+
+        return audio_bytes, format_name, sample_rate, duration
+
+    def _process_numpy_array(self) -> tuple[bytes, str, int | None, float | None]:
+        """
+        Process numpy array to WAV using soundfile.
+        Returns:
+            A tuple of (audio_bytes, format_name, sample_rate, duration)
+        """
+        if self._sample_rate is None:
+            raise ValueError('Argument "sample_rate" is required when using numpy arrays.')
+
+        buffer = io.BytesIO()
+        format_name = self._format or "wav"
+        sf.write(buffer, self._data, self._sample_rate, format=format_name)
+        buffer.seek(0)
+        audio_bytes = buffer.read()
+
+        if isinstance(self._data, np.ndarray):
+            duration = len(self._data) / float(self._sample_rate)
+        else:
+            raise TypeError("Invalid data type for numpy array processing.")
+
+        return audio_bytes, format_name, self._sample_rate, duration
+
+    def _process_raw_bytes(self) -> tuple[bytes, str, int | None, float | None]:
+        """
+        Process raw bytes. Format is determined by the provided format argument.
+        Returns:
+            A tuple of (audio_bytes, format_name, sample_rate, duration)
+        """
+        format_name = self._format or "wav"
+        if not isinstance(self._data, bytes):
+            raise TypeError("Raw bytes are expected for this processing method.")
+        return self._data, format_name, self._sample_rate, None
+
+    def _process_pydub_audio_segment(self) -> tuple[bytes, str, int | None, float | None]:
+        """
+        Process pydub AudioSegment to bytes.
+        Returns:
+            A tuple of (audio_bytes, format_name, sample_rate, duration)
+        """
+
+        if not isinstance(self._data, AudioSegment):
+            raise TypeError("AudioSegment is expected for this processing method.")
+
+        sample_rate = self._data.frame_rate
+
+        buffer = io.BytesIO()
+        format_name = self._format or "wav"
+        self._data.export(buffer, format=format_name)
+        buffer.seek(0)
+        audio_bytes = buffer.read()
+
+        # PyDUB provides duration in milliseconds, convert to seconds for consistency
+        duration = len(self._data) / 1000.0
+
+        return audio_bytes, format_name, sample_rate, duration
+
+    def _generate_metadata(
+        self, format_name: str, sample_rate: int | None, duration: float | None
+    ) -> dict[str, str | int | float | None]:
+        """
+        Generate metadata for the audio data.
+        Returns:
+            A dictionary of metadata
+        """
+        metadata: dict[str, str | int | float | None] = {
+            "extension": format_name.lower(),
+            "x-python-datatype": "dreadnode.Audio.bytes",
+        }
+
+        if isinstance(self._data, (str, Path)):
+            metadata["source-type"] = "file"
+            metadata["source-path"] = str(self._data)
+        elif isinstance(self._data, np.ndarray):
+            metadata["source-type"] = "numpy.ndarray"
+        elif isinstance(self._data, bytes):
+            metadata["source-type"] = "bytes"
+        elif isinstance(self._data, AudioSegment):
+            metadata["source-type"] = "pydub.AudioSegment"
+
+        if sample_rate is not None:
+            metadata["sample-rate"] = sample_rate
+
+        if duration is not None:
+            metadata["duration"] = duration
+
+        # Add pydub-specific metadata if available
+        if isinstance(self._data, AudioSegment):
+            metadata["channels"] = self._data.channels
+            metadata["sample-width"] = self._data.sample_width
+
+        if self._caption:
+            metadata["caption"] = self._caption
+
+        return metadata

dreadnode/data_types/base_data_type.py

@@ -0,0 +1,17 @@
+import typing as t
+from abc import ABC, abstractmethod
+
+
+class BaseDataType(ABC):
+    """Base class for all data types that can be logged with Dreadnode."""
+
+    @abstractmethod
+    def to_serializable(self) -> tuple[t.Any, dict[str, t.Any]]:
+        """
+        Convert the media type to a serializable format.
+
+        Returns:
+            Tuple of (data, metadata) where:
+                - data: The serialized data
+                - metadata: Additional metadata for this data type
+        """