Authorizations
Bearer authentication header of the form Bearer <token>, where <token> is your auth token.
Response
Successful Response
import Telnyx from 'telnyx';
const client = new Telnyx({
apiKey: 'My API Key',
});
const response = await client.ai.embeddings.similaritySearch({ bucket_name: 'bucket_name', query: 'query' });
console.log(response.data);{
"data": [
{
"document_chunk": "<string>",
"distance": 123,
"metadata": {
"source": "<string>",
"checksum": "<string>",
"embedding": "<string>",
"filename": "<string>",
"certainty": 123,
"loader_metadata": {}
}
}
]
}Perform a similarity search on a Telnyx Storage Bucket, returning the most similar num_docs document chunks to the query.
Currently the only available distance metric is cosine similarity which will return a distance between 0 and 1.
The lower the distance, the more similar the returned document chunks are to the query.
A certainty will also be returned, which is a value between 0 and 1 where the higher the certainty, the more similar the document.
You can read more about Weaviate distance metrics here: Weaviate Docs
If a bucket was embedded using a custom loader, such as intercom, the additional metadata will be returned in the
loader_metadata field.
import Telnyx from 'telnyx';
const client = new Telnyx({
apiKey: 'My API Key',
});
const response = await client.ai.embeddings.similaritySearch({ bucket_name: 'bucket_name', query: 'query' });
console.log(response.data);{
"data": [
{
"document_chunk": "<string>",
"distance": 123,
"metadata": {
"source": "<string>",
"checksum": "<string>",
"embedding": "<string>",
"filename": "<string>",
"certainty": 123,
"loader_metadata": {}
}
}
]
}Bearer authentication header of the form Bearer <token>, where <token> is your auth token.
Successful Response
Show child attributes
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