POST
https://{index_host}
/
query
# pip install "pinecone[grpc]"
from pinecone.grpc import PineconeGRPC as Pinecone

pc = Pinecone(api_key="YOUR_API_KEY")

# To get the unique host for an index, 
# see https://docs.pinecone.io/guides/manage-data/target-an-index
index = pc.Index(host="INDEX_HOST")

index.query(
    namespace="example-namespace",
    vector=[0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3],
    filter={
        "genre": {"$eq": "documentary"}
    },
    top_k=3,
    include_values=True
)

{
  "matches":[
    {
      "id": "vec3",
      "score": 0,
      "values": [0.3,0.3,0.3,0.3,0.3,0.3,0.3,0.3]
    },
    {
      "id": "vec2",
      "score": 0.0800000429,
      "values": [0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2]
    },
    {
      "id": "vec4",
      "score": 0.0799999237,
      "values": [0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4]
    }
  ],
  "namespace": "example-namespace",
  "usage": {"read_units": 6}
}

# pip install "pinecone[grpc]"
from pinecone.grpc import PineconeGRPC as Pinecone

pc = Pinecone(api_key="YOUR_API_KEY")

# To get the unique host for an index, 
# see https://docs.pinecone.io/guides/manage-data/target-an-index
index = pc.Index(host="INDEX_HOST")

index.query(
    namespace="example-namespace",
    vector=[0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3],
    filter={
        "genre": {"$eq": "documentary"}
    },
    top_k=3,
    include_values=True
)

{
  "matches":[
    {
      "id": "vec3",
      "score": 0,
      "values": [0.3,0.3,0.3,0.3,0.3,0.3,0.3,0.3]
    },
    {
      "id": "vec2",
      "score": 0.0800000429,
      "values": [0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2]
    },
    {
      "id": "vec4",
      "score": 0.0799999237,
      "values": [0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4]
    }
  ],
  "namespace": "example-namespace",
  "usage": {"read_units": 6}
}

Authorizations

​
Api-Key
string
header
required

An API Key is required to call Pinecone APIs. Get yours from the console.

Body

application/json

The request for the query operation.

Response

200
application/json

A successful response.

The response for the query operation. These are the matches found for a particular query vector. The matches are ordered from most similar to least similar.