Search for documents

POST 
/ai/embeddings/similarity-search

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.

application/json

Body

required

bucket_name Bucket Name (string)required
query Query (string)required
num_of_docs Num Of Docs (integer)

Default value: 3

200: Successful Response

application/json

• Schema
• Example (from schema)

Schema

data

object[]

required

Array [

document_chunk Document Chunk (string)required

distance Distance (number)required

metadata

object

required

source Source (string)required

checksum Checksum (string)required

embedding Embedding (string)required

filename Filename (string)required

certainty Certainty (number)

loader_metadata object

]

{
  "data": [
    {
      "document_chunk": "string",
      "distance": 0,
      "metadata": {
        "source": "string",
        "checksum": "string",
        "embedding": "string",
        "filename": "string",
        "certainty": 0,
        "loader_metadata": {}
      }
    }
  ]
}

422: Validation Error

application/json

• Schema
• Example (from schema)

Schema

detail

object[]

Array [

loc

object[]

required

Array [

anyOf

• MOD1
• MOD2

string

integer

]

msg Message (string)required

type Error Type (string)required

]

{
  "detail": [
    {
      "loc": [
        "string",
        0
      ],
      "msg": "string",
      "type": "string"
    }
  ]
}

Request samples

• cURL

---

curl -L 'https://api.telnyx.com/v2/ai/embeddings/similarity-search' \
-H 'Content-Type: application/json' \
-H 'Accept: application/json' \
-H 'Authorization: Bearer <TOKEN>' \
-d '{
  "bucket_name": "string",
  "query": "string",
  "num_of_docs": 3
}'

Response samples

• 200
• 422

---

{
  "data": [
    {
      "document_chunk": "string",
      "distance": 0,
      "metadata": {
        "source": "string",
        "checksum": "string",
        "embedding": "string",
        "filename": "string",
        "certainty": 0,
        "loader_metadata": {}
      }
    }
  ]
}

{
  "detail": [
    {
      "loc": [
        "string",
        0
      ],
      "msg": "string",
      "type": "string"
    }
  ]
}