Search with text

INDEX_HOST="INDEX_HOST"
NAMESPACE="YOUR_NAMESPACE"
PINECONE_API_KEY="YOUR_API_KEY"

# Search with a query text and rerank the results
# Supported only for indexes with integrated embedding
curl "https://$INDEX_HOST/records/namespaces/$NAMESPACE/search" \
  -H "Accept: application/json" \
  -H "Content-Type: application/json" \
  -H "Api-Key: $PINECONE_API_KEY" \
  -H "X-Pinecone-Api-Version: 2025-10" \
  -d '{
        "query": {
            "inputs": {"text": "Disease prevention"},
            "top_k": 4,
        },
        "fields": ["category", "chunk_text"]
        "rerank": {
            "model": "bge-reranker-v2-m3",
            "top_n": 2,
            "rank_fields": ["chunk_text"] # Specified field must also be included in 'fields'
        }
     }'

# Search with a query vector and rerank the results
curl "https://$INDEX_HOST/records/namespaces/$NAMESPACE/search" \
  -H "Accept: application/json" \
  -H "Content-Type: application/json" \
  -H "Api-Key: $PINECONE_API_KEY" \
  -H "X-Pinecone-Api-Version: 2025-10" \
  -d '{
        "query": {
            "vector": {
                "values": [0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3]
            },
            "top_k": 4,
        },
        "fields": ["category", "chunk_text"]
        "rerank": {
            "query": "Disease prevention",
            "model": "bge-reranker-v2-m3",
            "top_n": 2,
            "rank_fields": ["chunk_text"] # Specified field must also be included in 'fields'
        }
     }'

# Search with a record ID and rerank the results
# Supported only for indexes with integrated embedding
curl "https://$INDEX_HOST/records/namespaces/$NAMESPACE/search" \
  -H "Accept: application/json" \
  -H "Content-Type: application/json" \
  -H "Api-Key: $PINECONE_API_KEY" \
  -H "X-Pinecone-Api-Version: 2025-10" \
  -d '{
        "query": {
            "id": "rec1",
            "top_k": 4,
        },
        "fields": ["category", "chunk_text"]
        "rerank": {
            "query": "Disease prevention",
            "model": "bge-reranker-v2-m3",
            "top_n": 2,
            "rank_fields": ["chunk_text"]
        }
     }'

{
    "result": {
        "hits": [
            {
                "_id": "rec3",
                "_score": 0.004433765076100826,
                "fields": {
                    "category": "immune system",
                    "chunk_text": "Rich in vitamin C and other antioxidants, apples contribute to immune health and may reduce the risk of chronic diseases."
                }
            },
            {
                "_id": "rec4",
                "_score": 0.0029121784027665854,
                "fields": {
                    "category": "endocrine system",
                    "chunk_text": "The high fiber content in apples can also help regulate blood sugar levels, making them a favorable snack for people with diabetes."
                }
            }
        ]
    },
    "usage": {
        "embed_total_tokens": 8,
        "read_units": 6,
        "rerank_units": 1
    }
}

POST

records

namespaces

{namespace}

INDEX_HOST="INDEX_HOST"
NAMESPACE="YOUR_NAMESPACE"
PINECONE_API_KEY="YOUR_API_KEY"

# Search with a query text and rerank the results
# Supported only for indexes with integrated embedding
curl "https://$INDEX_HOST/records/namespaces/$NAMESPACE/search" \
  -H "Accept: application/json" \
  -H "Content-Type: application/json" \
  -H "Api-Key: $PINECONE_API_KEY" \
  -H "X-Pinecone-Api-Version: 2025-10" \
  -d '{
        "query": {
            "inputs": {"text": "Disease prevention"},
            "top_k": 4,
        },
        "fields": ["category", "chunk_text"]
        "rerank": {
            "model": "bge-reranker-v2-m3",
            "top_n": 2,
            "rank_fields": ["chunk_text"] # Specified field must also be included in 'fields'
        }
     }'

# Search with a query vector and rerank the results
curl "https://$INDEX_HOST/records/namespaces/$NAMESPACE/search" \
  -H "Accept: application/json" \
  -H "Content-Type: application/json" \
  -H "Api-Key: $PINECONE_API_KEY" \
  -H "X-Pinecone-Api-Version: 2025-10" \
  -d '{
        "query": {
            "vector": {
                "values": [0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3]
            },
            "top_k": 4,
        },
        "fields": ["category", "chunk_text"]
        "rerank": {
            "query": "Disease prevention",
            "model": "bge-reranker-v2-m3",
            "top_n": 2,
            "rank_fields": ["chunk_text"] # Specified field must also be included in 'fields'
        }
     }'

# Search with a record ID and rerank the results
# Supported only for indexes with integrated embedding
curl "https://$INDEX_HOST/records/namespaces/$NAMESPACE/search" \
  -H "Accept: application/json" \
  -H "Content-Type: application/json" \
  -H "Api-Key: $PINECONE_API_KEY" \
  -H "X-Pinecone-Api-Version: 2025-10" \
  -d '{
        "query": {
            "id": "rec1",
            "top_k": 4,
        },
        "fields": ["category", "chunk_text"]
        "rerank": {
            "query": "Disease prevention",
            "model": "bge-reranker-v2-m3",
            "top_n": 2,
            "rank_fields": ["chunk_text"]
        }
     }'

{
    "result": {
        "hits": [
            {
                "_id": "rec3",
                "_score": 0.004433765076100826,
                "fields": {
                    "category": "immune system",
                    "chunk_text": "Rich in vitamin C and other antioxidants, apples contribute to immune health and may reduce the risk of chronic diseases."
                }
            },
            {
                "_id": "rec4",
                "_score": 0.0029121784027665854,
                "fields": {
                    "category": "endocrine system",
                    "chunk_text": "The high fiber content in apples can also help regulate blood sugar levels, making them a favorable snack for people with diabetes."
                }
            }
        ]
    },
    "usage": {
        "embed_total_tokens": 8,
        "read_units": 6,
        "rerank_units": 1
    }
}

INDEX_HOST="INDEX_HOST"
NAMESPACE="YOUR_NAMESPACE"
PINECONE_API_KEY="YOUR_API_KEY"

# Search with a query text and rerank the results
# Supported only for indexes with integrated embedding
curl "https://$INDEX_HOST/records/namespaces/$NAMESPACE/search" \
  -H "Accept: application/json" \
  -H "Content-Type: application/json" \
  -H "Api-Key: $PINECONE_API_KEY" \
  -H "X-Pinecone-Api-Version: 2025-10" \
  -d '{
        "query": {
            "inputs": {"text": "Disease prevention"},
            "top_k": 4,
        },
        "fields": ["category", "chunk_text"]
        "rerank": {
            "model": "bge-reranker-v2-m3",
            "top_n": 2,
            "rank_fields": ["chunk_text"] # Specified field must also be included in 'fields'
        }
     }'

# Search with a query vector and rerank the results
curl "https://$INDEX_HOST/records/namespaces/$NAMESPACE/search" \
  -H "Accept: application/json" \
  -H "Content-Type: application/json" \
  -H "Api-Key: $PINECONE_API_KEY" \
  -H "X-Pinecone-Api-Version: 2025-10" \
  -d '{
        "query": {
            "vector": {
                "values": [0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3]
            },
            "top_k": 4,
        },
        "fields": ["category", "chunk_text"]
        "rerank": {
            "query": "Disease prevention",
            "model": "bge-reranker-v2-m3",
            "top_n": 2,
            "rank_fields": ["chunk_text"] # Specified field must also be included in 'fields'
        }
     }'

# Search with a record ID and rerank the results
# Supported only for indexes with integrated embedding
curl "https://$INDEX_HOST/records/namespaces/$NAMESPACE/search" \
  -H "Accept: application/json" \
  -H "Content-Type: application/json" \
  -H "Api-Key: $PINECONE_API_KEY" \
  -H "X-Pinecone-Api-Version: 2025-10" \
  -d '{
        "query": {
            "id": "rec1",
            "top_k": 4,
        },
        "fields": ["category", "chunk_text"]
        "rerank": {
            "query": "Disease prevention",
            "model": "bge-reranker-v2-m3",
            "top_n": 2,
            "rank_fields": ["chunk_text"]
        }
     }'

{
    "result": {
        "hits": [
            {
                "_id": "rec3",
                "_score": 0.004433765076100826,
                "fields": {
                    "category": "immune system",
                    "chunk_text": "Rich in vitamin C and other antioxidants, apples contribute to immune health and may reduce the risk of chronic diseases."
                }
            },
            {
                "_id": "rec4",
                "_score": 0.0029121784027665854,
                "fields": {
                    "category": "endocrine system",
                    "chunk_text": "The high fiber content in apples can also help regulate blood sugar levels, making them a favorable snack for people with diabetes."
                }
            }
        ]
    },
    "usage": {
        "embed_total_tokens": 8,
        "read_units": 6,
        "rerank_units": 1
    }
}

Authorizations

Api-Key

string

header

required

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

Headers

X-Pinecone-Api-Version

string

default:2025-10

required

Required date-based version header

Path Parameters

namespace

string

required

The namespace to search.

Body

application/json

A search request for records in a specific namespace.

query

object

required

Show child attributes

query.top_k

integer<int32>

required

The number of similar records to return.

Example:

10

query.filter

object

The filter to apply. You can use vector metadata to limit your search. See Understanding metadata.

query.inputs

object

Example:

{ "text": "chunk_text" }

query.vector

object

Show child attributes

query.vector.values

number<float>[]

This is the vector data included in the request.

query.vector.sparse_values

number<float>[]

The sparse embedding values.

Example:

[0.1, 0.2, 0.3]

query.vector.sparse_indices

integer<int32>[]

The sparse embedding indices.

Required range: x >= 0

Example:

[10, 3, 156]

query.id

string

The unique ID of the vector to be used as a query vector.

Maximum string length: 512

Example:

"example-vector-1"

query.match_terms

object

Specifies which terms must be present in the text of each search hit based on the specified strategy. The match is performed against the text field specified in the integrated index field_map configuration.

Terms are normalized and tokenized into single tokens before matching, and order does not matter.

Example:

"match_terms": {"terms": ["animal", "CHARACTER", "donald Duck"], "strategy": "all"} will tokenize to ["animal", "character", "donald", "duck"], and would match "Donald F. Duck is a funny animal character" but would not match "A duck is a funny animal".

Match terms filtering is supported only for sparse indexes with integrated embedding configured to use the pinecone-sparse-english-v0 model.

Show child attributes

query.match_terms.strategy

string

The strategy for matching terms in the text. Currently, only all is supported, which means all specified terms must be present.

query.match_terms.terms

string[]

A list of terms that must be present in the text of each search hit based on the specified strategy.

Example:

{
  "strategy": "all",
  "terms": ["animal", "CHARACTER", "donald Duck"]
}

fields

string[]

The fields to return in the search results. If not specified, the response will include all fields.

Example:

["chunk_text"]

rerank

object

Parameters for reranking the initial search results.

Show child attributes

rerank.model

string

required

The name of the reranking model to use.

Example:

"bge-reranker-v2-m3"

rerank.rank_fields

string[]

required

The field(s) to consider for reranking. If not provided, the default is ["text"].

The number of fields supported is model-specific.

Example:

["chunk_text", "title"]

rerank.top_n

integer<int32>

The number of top results to return after reranking. Defaults to top_k.

Example:

5

rerank.parameters

object

Additional model-specific parameters. Refer to the model guide for available model parameters.

Example:

{ "truncate": "END" }

rerank.query

string

The query to rerank documents against. If a specific rerank query is specified, it overwrites the query input that was provided at the top level.

Example:

"What is the capital of France?"

Response

A successful search namespace response.

The records search response.

result

object

required

Show child attributes

result.hits

object[]

required

The hits for the search document request.

Show child attributes

result.hits._id

string

required

The record id of the search hit.

result.hits._score

number<float>

required

The similarity score of the returned record.

result.hits.fields

object

required

The selected record fields associated with the search hit.

usage

object

required

Show child attributes

usage.read_units

integer<int32>

required

The number of read units consumed by this operation.

Required range: x >= 0

Example:

5

usage.embed_total_tokens

integer<int32>

The number of embedding tokens consumed by this operation.

Required range: x >= 0

Example:

2

usage.rerank_units

integer<int32>

The number of rerank units consumed by this operation.

Required range: x >= 0

Example:

1

Search with a vector Start import

⌘I

APIs

Database

Inference

Admin

SDKs

CLI

Tools

Authorizations

Headers

Path Parameters

Body

Response