# Multimedia search Multimedia search uses **images, video, audio and other multimedia formats as a search input** to perform vector similarity search via the `near_media` operator. :::callout{intent="tip" title="Image search"} For image-only search using `near_image`, see the dedicated [Image search](image.md) page. The `near_media` operator shown here provides a unified interface for multiple media types. ::: :::accordion{title="How to configure Weaviate to use multimedia search?"} **Configure multimedia search** To use images, video, or audio as search inputs, configure a multi-modal vectorizer integration that supports these media types for your collection. For example, Google's `multi2vec-google` with the `gemini-embedding-2` model supports image, video, and audio inputs. See the [model provider integrations](../model-provider-integrations/index.md) page for available options. **Collection configuration** The collection must be configured with the appropriate media fields. For example: ```python {10-15} from weaviate.classes.config import Configure, Property, DataType client.collections.delete("MediaExample") client.collections.create( name="MediaExample", properties=[ Property(name="title", data_type=DataType.TEXT), Property(name="mediaType", data_type=DataType.TEXT), ], vector_config=Configure.Vectors.multi2vec_google_gemini( model="gemini-embedding-2", text_fields=["title"], # video_fields=["video"], # image_fields=["image"], ), ) ``` ::: ## By local file path Use the `near_media` operator to search by providing a file path to a video. :::code-group{sync="languages"} ```python title="Python" {3-4,9-10} from pathlib import Path from weaviate.classes.query import NearMediaType collection = client.collections.use("MediaExample") response = collection.query.near_media( media=Path("./videos/dog.mp4"), media_type=NearMediaType.VIDEO, return_properties=["title", "mediaType"], limit=5, ) for obj in response.objects: print(obj.properties) ``` ::: ## By base64 representation You can also provide a base64-encoded video string: :::code-group{sync="languages"} ```python title="Python" {4-5,10-11} import base64 from weaviate.classes.query import NearMediaType with open("./videos/butterfly.mp4", "rb") as f: video_base64 = base64.b64encode(f.read()).decode("utf-8") collection = client.collections.use("MediaExample") response = collection.query.near_media( media=video_base64, media_type=NearMediaType.VIDEO, return_properties=["title", "mediaType"], limit=5, ) for obj in response.objects: print(obj.properties) ``` ::: ## Set a maximum distance Set a maximum `distance` to filter results and return the distance metadata: :::code-group{sync="languages"} ```python title="Python" {12-13} import base64 from weaviate.classes.query import MetadataQuery, NearMediaType with open("./videos/cat.mp4", "rb") as f: video_base64 = base64.b64encode(f.read()).decode("utf-8") collection = client.collections.use("MediaExample") response = collection.query.near_media( media=video_base64, media_type=NearMediaType.VIDEO, distance=0.8, # Maximum accepted distance return_metadata=MetadataQuery(distance=True), return_properties=["title", "mediaType"], limit=5, ) for obj in response.objects: print(f"{obj.properties} - Distance: {obj.metadata.distance}") ``` ::: ## With a filter Combine near media searches with filters to narrow results: :::code-group{sync="languages"} ```python title="Python" {13} import base64 from weaviate.classes.query import NearMediaType from weaviate.classes.query import Filter with open("./videos/dog.mp4", "rb") as f: video_base64 = base64.b64encode(f.read()).decode("utf-8") collection = client.collections.use("MediaExample") response = collection.query.near_media( media=video_base64, media_type=NearMediaType.VIDEO, filters=Filter.by_property("mediaType").equal("animals"), return_properties=["title", "mediaType"], limit=5, ) for obj in response.objects: print(obj.properties) ``` ::: ## Other media types The `near_media` operator supports other media types such as audio. Set the `media_type` parameter to the appropriate `NearMediaType` value: :::code-group{sync="languages"} ```python title="Python" {7-8} import base64 from weaviate.classes.query import NearMediaType collection = client.collections.use("MediaExample") response = collection.query.near_media( media=Path("./audio/dog.wav"), media_type=NearMediaType.AUDIO, return_properties=["title", "mediaType"], limit=5, ) for obj in response.objects: print(obj.properties) ``` ::: ## Supported media types The `NearMediaType` enum supports the following media types. Available types depend on the vectorizer module and model used. | Media type | Enum value | Description | | :--------- | :---------------------- | :--------------------------------------------------------------------- | | Audio | `NearMediaType.AUDIO` | Audio files (e.g., `.wav`, `.mp3`) | | Image | `NearMediaType.IMAGE` | Image files (e.g., `.jpg`, `.png`). See also [Image search](image.md). | | Video | `NearMediaType.VIDEO` | Video files (e.g., `.mp4`, `.avi`) | | Depth | `NearMediaType.DEPTH` | Depth map data | | Thermal | `NearMediaType.THERMAL` | Thermal image data | | IMU | `NearMediaType.IMU` | Inertial measurement unit data | :::callout{intent="note" title="Model support"} Not all models support all media types. For example, `gemini-embedding-2` supports image, video, and audio. Check your model provider's documentation for supported modalities. ::: ## Further resources - [How-to: Query & Search - Image search](image.md) - [How-to: Query & Search - Vector similarity search](similarity.md) - [Model provider integrations - Google multimodal embeddings](../model-provider-integrations/google-embeddings-multimodal.md) ## Questions and feedback Have a question or feedback? 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