Audios¶

Audios

class vectorai.api.audio.ViAudioClient(username, api_key, url=None)¶

Search and Encoding of Audios

search_audio(collection_name: str, audio, fields: List, metric: str = 'cosine', min_score=None, page: int = 1, page_size: int = 10, include_vector: bool = False, include_count: bool = True, asc: bool = False, return_curl: bool = False, **kwargs)¶

Search an audio field with audio using Vector Search Vector similarity search with an audio directly.

_note: audio has to be stored somewhere and be provided as audio_url, a url that stores the audio_

For example: an audio_url represents sounds that a pokemon make:

"https://play.pokemonshowdown.com/audio/cries/pikachu.mp3"

-> <Encode the audio to vector> ->

audio vector: [0.794617772102356, 0.3581121861934662, 0.21113917231559753, 0.24878688156604767, 0.9741804003715515 ...]

-> <Vector Search> ->

Search Results: {...}

Parameters

audio_url – The audio url of an audio to encode into a vector
collection_name – Name of Collection
search_fields – Vector fields to search through
approx – Used for approximate search
sum_fields – Whether to sum the multiple vectors similarity search score as 1 or seperate
page_size – Size of each page of results
page – Page of the results
metric – Similarity Metric, choose from [‘cosine’, ‘l1’, ‘l2’, ‘dp’]
min_score – Minimum score for similarity metric
include_vector – Include vectors in the search results
include_count – Include count in the search results
hundred_scale –
Whether to scale up the metric by 100

asc:
Whether to sort the score by ascending order (default is false, for getting most similar results)

search_audio_by_upload(collection_name: str, audio, fields: List, metric: str = 'cosine', min_score=None, page: int = 1, page_size: int = 10, include_vector: bool = False, include_count: bool = True, asc: bool = False, return_curl: bool = False, **kwargs)¶

Search an audio field with uploaded audio using Vector Search with an uploaded audio directly.

_note: audio has to be sent as a base64 encoded string_

Parameters

collection_name – Name of Collection
search_fields – Vector fields to search against
page_size – Size of each page of results
page – Page of the results
approx – Used for approximate search
sum_fields – Whether to sum the multiple vectors similarity search score as 1 or seperate
metric – Similarity Metric, choose from [‘cosine’, ‘l1’, ‘l2’, ‘dp’]
min_score – Minimum score for similarity metric
include_vector – Include vectors in the search results
include_count – Include count in the search results
hundred_scale – Whether to scale up the metric by 100
audio –
Audio in local file path

asc:
Whether to sort the score by ascending order (default is false, for getting most similar results)

encode_audio(collection_name: str, audio, return_curl: bool = False, **kwargs)¶

Encode encode into a vector

_note: audio has to be stored somewhere and be provided as audio_url, a url that stores the audio_

For example: an audio_url represents sounds that a pokemon make:

"https://play.pokemonshowdown.com/audio/cries/pikachu.mp3"

-> <Encode the audio to vector> ->

audio_url vector: [0.794617772102356, 0.3581121861934662, 0.21113917231559753, 0.24878688156604767, 0.9741804003715515 ...]

Parameters

audio_url – The audio url of an audio to encode into a vector
collection_name – Name of Collection

encode_audio_job(collection_name: str, audio_field: str, refresh: bool = False, return_curl: bool = False, **kwargs)¶

Encode all audios in a field into vectors

Within a collection encode the specified audio field in every document into vectors.

_note: audio has to be stored somewhere and be provided as audio_url, a url that stores the audio_

For example, an audio_url field “pokemon_cries” represents sounds that a pokemon make:

document 1 audio_url field: {"pokemon_cries" : "https://play.pokemonshowdown.com/audio/cries/pikachu.mp3"}

document 2 audio_url field: {"pokemon_cries" : "https://play.pokemonshowdown.com/audio/cries/meowth.mp3"}

-> <Encode the audios to vectors> ->

document 1 audio_url vector: {"pokemon_cries_vector_": [0.794617772102356, 0.3581121861934662, 0.21113917231559753, 0.24878688156604767, 0.9741804003715515 ...]}

document 2 audio_url vector: {"pokemon_cries_vector_": [0.8364648222923279, 0.6280597448348999, 0.8112713694572449, 0.36105549335479736, 0.005313870031386614 ...]}

Parameters

audio_field – The audio field to encode into vectors
refresh – Whether to refresh the whole collection and re-encode all to vectors
collection_name – Name of Collection