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POST
/
records
/
namespaces
/
{namespace}
/
search
from pinecone import 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("docs-example")

# Search with a query text and rerank the results
# Supported only for indexes with integrated embedding
search_with_text = index.search(
    namespace="example-namespace", 
    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'
    }
)

print(search_with_text)

# Search with a query vector and rerank the results
search_with_vector = index.search(
    namespace="example-namespace", 
    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'
    }
)

print(search_with_vector)

# Search with a record ID and rerank the results
search_with_id = index.search(
    namespace="example-namespace", 
    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"] # Specified field must also be included in 'fields'
    }
)

print(search_with_id)
// npm install @pinecone-database/pinecone
import { Pinecone } from '@pinecone-database/pinecone'

const pc = new Pinecone({ apiKey: "YOUR_API_KEY" })

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

// Search with a query text and rerank the results
// Supported only for indexes with integrated embedding
const searchWithText = await namespace.searchRecords({
  query: {
    topK: 4,
    inputs: { text: 'Disease prevention' },
  },
  fields: ['chunk_text', 'category'],
  rerank: {
    model: 'bge-reranker-v2-m3',
    rankFields: ['chunk_text'],
    topN: 2,
  },
});

console.log(searchWithText);

// Search with a query vector and rerank the results
const searchWithVector = await namespace.searchRecords({
  query: {
    topK: 4,
    vector: {
      values: [0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3]
    },
    inputs: { text: 'Disease prevention' },
  },
  fields: ['chunk_text', 'category'],
  rerank: {
    query: "Disease prevention",
    model: 'bge-reranker-v2-m3',
    rankFields: ['chunk_text'],
    topN: 2,
  },
});

console.log(searchWithVector);

// Search with a record ID and rerank the results
const searchWithId = await namespace.searchRecords({
  query: {
    topK: 4,
    id: 'rec1',
  },
  fields: ['chunk_text', 'category'],
  rerank: {
    query: "Disease prevention",
    model: 'bge-reranker-v2-m3',
    rankFields: ['chunk_text'],
    topN: 2,
  },
});

console.log(searchWithId);
import io.pinecone.clients.Index;
import io.pinecone.configs.PineconeConfig;
import io.pinecone.configs.PineconeConnection;
import org.openapitools.db_data.client.ApiException;
import org.openapitools.db_data.client.model.SearchRecordsRequestRerank;
import org.openapitools.db_data.client.model.SearchRecordsResponse;
import org.openapitools.db_data.client.model.SearchRecordsVector;

import java.util.*;

public class SearchText {
    public static void main(String[] args) throws ApiException {
        PineconeConfig config = new PineconeConfig("YOUR_API_KEY");
        config.setHost("INDEX_HOST");
        PineconeConnection connection = new PineconeConnection(config);

        Index index = new Index(config, connection, "integrated-dense-java");

        String query = "Famous historical structures and monuments";
        List<String> fields = new ArrayList<>();
        fields.add("category");
        fields.add("chunk_text");
        List<String>rankFields = new ArrayList<>();
        rankFields.add("chunk_text");

        SearchRecordsRequestRerank rerank = new SearchRecordsRequestRerank()
                .query(query)
                .model("bge-reranker-v2-m3")
                .topN(2)
                .rankFields(rankFields);

        // Search with a query text and rerank the results
        // Supported only for indexes with integrated embedding
        SearchRecordsResponse searchWithText = index.searchRecordsByText(query,  "example-namespace", fields, 10, null, rerank);

        System.out.println(searchWithText);

        // Search with a query vector and rerank the results
        SearchRecordsVector queryVector = new SearchRecordsVector();
        queryVector.setValues(Arrays.asList(0.3f, 0.3f, 0.3f, 0.3f, 0.3f, 0.3f, 0.3f, 0.3f));
        SearchRecordsResponse searchWithVector = index.searchRecordsByVector(queryVector, "example-namespace", fields, 4, null, rerank);
        
        System.out.println(searchWithVector);

        // Search with a record ID and rerank the results
        SearchRecordsResponse searchWithID = index.searchRecordsById("rec1", "example-namespace", fields, 4, null, rerank);

        System.out.println(searchWithID);
    }
}
package main

import (
    "context"
    "encoding/json"
    "fmt"
    "log"

    "github.com/pinecone-io/go-pinecone/v4/pinecone"
)

func prettifyStruct(obj interface{}) string {
  	bytes, _ := json.MarshalIndent(obj, "", "  ")
    return string(bytes)
}

func main() {
    ctx := context.Background()

    pc, err := pinecone.NewClient(pinecone.NewClientParams{
        ApiKey: "YOUR_API_KEY",
    })
    if err != nil {
        log.Fatalf("Failed to create Client: %v", err)
    }

    // To get the unique host for an index, 
    // see https://docs.pinecone.io/guides/manage-data/target-an-index
    idxConnection, err := pc.Index(pinecone.NewIndexConnParams{Host: "INDEX_HOST", Namespace: "example-namespace"})
    if err != nil {
        log.Fatalf("Failed to create IndexConnection for Host: %v", err)
    } 

    // Search with a query text and rerank the results
    // Supported only for indexes with integrated embedding
    topN := int32(2)
    searchWithText, err := idxConnection.SearchRecords(ctx, &pinecone.SearchRecordsRequest{
        Query: pinecone.SearchRecordsQuery{
            TopK: 4,
            Inputs: &map[string]interface{}{
                "text": "Disease prevention",
            },
        },
        Rerank: &pinecone.SearchRecordsRerank{
            Model:      "bge-reranker-v2-m3",
            TopN:       &topN,
            RankFields: []string{"chunk_text"},
        },
        Fields: &[]string{"chunk_text", "category"},
    })
    if err != nil {
        log.Fatalf("Failed to search records: %v", err)
    }
    fmt.Printf(prettifyStruct(searchWithText))

    // Search with a query vector and rerank the results
    topN := int32(2)
    searchWithVector, err := idxConnection.SearchRecords(ctx, &pinecone.SearchRecordsRequest{
        Query: pinecone.SearchRecordsQuery{
            TopK: 4,
            Vector: pinecone.SearchRecordsVector{
                Values: []float32{0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3},
            },
        },
        Rerank: &pinecone.SearchRecordsRerank{
            Model:      "bge-reranker-v2-m3",
            TopN:       &topN,
            RankFields: []string{"chunk_text"},
        },
        Fields: &[]string{"chunk_text", "category"},
    })
    if err != nil {
        log.Fatalf("Failed to search records: %v", err)
    }
    fmt.Printf(prettifyStruct(resSearchWithVector))

    // Search with a query ID and rerank the results
    topN := int32(2)
    searchWithId, err := idxConnection.SearchRecords(ctx, &pinecone.SearchRecordsRequest{
        Query: pinecone.SearchRecordsQuery{
            TopK: 4,
            Id: "rec1",
        },
        Rerank: &pinecone.SearchRecordsRerank{
            Model:      "bge-reranker-v2-m3",
            TopN:       &topN,
            RankFields: []string{"chunk_text"},
        },
        Fields: &[]string{"chunk_text", "category"},
    })
    if err != nil {
        log.Fatalf("Failed to search records: %v", err)
    }
    fmt.Printf(prettifyStruct(searchWithId))
}
using Pinecone;

var pinecone = new PineconeClient("YOUR_API_KEY");

var index = pinecone.Index(host: "INDEX_HOST");

// Search with a query text and rerank the results
var searchWithText = await index.SearchRecordsAsync(
    "example-namespace",
    new SearchRecordsRequest
    {
        Query = new SearchRecordsRequestQuery
        {
            TopK = 4,
            Inputs = new Dictionary<string, object?> { { "text", "Disease prevention" } },
        },
        Fields = ["category", "chunk_text"],
        Rerank = new SearchRecordsRequestRerank
        {
            Model = "bge-reranker-v2-m3",
            TopN = 2,
            RankFields = ["chunk_text"],
        },
    }
);

Console.WriteLine(searchWithText);

// Search with a query vector and rerank the results
var searchWithVector = await index.SearchRecordsAsync(
    "example-namespace",
    new SearchRecordsRequest
    {
        Query = new SearchRecordsRequestQuery
        {
            TopK = 4,
            Vector = new SearchRecordsVector
            {
                Values = new float[] { 0.3f, 0.3f, 0.3f, 0.3f, 0.3f, 0.3f, 0.3f, 0.3f },
            },
        },
        Fields = ["category", "chunk_text"],
        Rerank = new SearchRecordsRequestRerank
        {
            Model = "bge-reranker-v2-m3",
            TopN = 2,
            RankFields = ["chunk_text"],
        },
    }
);

Console.WriteLine(searchWithVector);

// Search with a query ID and rerank the results
var searchWithId = await index.SearchRecordsAsync(
    "example-namespace",
    new SearchRecordsRequest
    {
        Query = new SearchRecordsRequestQuery
        {
            TopK = 4,
            Id = "rec1",
        },
        Fields = ["category", "chunk_text"],
        Rerank = new SearchRecordsRequestRerank
        {
            Model = "bge-reranker-v2-m3",
            TopN = 2,
            RankFields = ["chunk_text"],
        },
    }
);

Console.WriteLine(searchWithId);
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: 2025-04" \
  -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: 2025-04" \
  -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: 2025-04" \
  -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': 0.004399413242936134,
                      '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': 0.0029235430993139744,
                      '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}}
{
  "result": { 
    "hits": [ 
      {
        "_id": "rec3",
        "_score": 0.004399413242936134,
        "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": 0.0029235430993139744,
        "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": { 
    "readUnits": 6, 
    "embedTotalTokens": 8,
    "rerankUnits": 1 
  }
}
class SearchRecordsResponse {
    result: class SearchRecordsResponseResult {
        hits: [class Hit {
            id: rec3
            score: 0.004399413242936134
            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.}
            additionalProperties: null
        }, class Hit {
            id: rec4
            score: 0.0029235430993139744
            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.}
            additionalProperties: null
        }]
        additionalProperties: null
    }
    usage: class SearchUsage {
        readUnits: 6
        embedTotalTokens: 13
        rerankUnits: 1
        additionalProperties: null
    }
    additionalProperties: null
}
{
  "result": {
    "hits": [
      {
        "_id": "rec3",
        "_score": 0.004399413242936134,
        "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": 0.0029235430993139744,
        "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": {
    "read_units": 6,
    "embed_total_tokens": 8,
    "rerank_units": 1
  }
}
{
    "result": {
        "hits": [
            {
                "_id": "rec3",
                "_score": 0.13741668,
                "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": "rec1",
                "_score": 0.0023413408,
                "fields": {
                    "category": "digestive system",
                    "chunk_text": "Apples are a great source of dietary fiber, which supports digestion and helps maintain a healthy gut."
                }
            }
        ]
    },
    "usage": {
        "read_units": 6,
        "embed_total_tokens": 5,
        "rerank_units": 1
    }
}
{
    "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
    }
}
from pinecone import 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("docs-example")

# Search with a query text and rerank the results
# Supported only for indexes with integrated embedding
search_with_text = index.search(
    namespace="example-namespace", 
    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'
    }
)

print(search_with_text)

# Search with a query vector and rerank the results
search_with_vector = index.search(
    namespace="example-namespace", 
    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'
    }
)

print(search_with_vector)

# Search with a record ID and rerank the results
search_with_id = index.search(
    namespace="example-namespace", 
    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"] # Specified field must also be included in 'fields'
    }
)

print(search_with_id)
// npm install @pinecone-database/pinecone
import { Pinecone } from '@pinecone-database/pinecone'

const pc = new Pinecone({ apiKey: "YOUR_API_KEY" })

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

// Search with a query text and rerank the results
// Supported only for indexes with integrated embedding
const searchWithText = await namespace.searchRecords({
  query: {
    topK: 4,
    inputs: { text: 'Disease prevention' },
  },
  fields: ['chunk_text', 'category'],
  rerank: {
    model: 'bge-reranker-v2-m3',
    rankFields: ['chunk_text'],
    topN: 2,
  },
});

console.log(searchWithText);

// Search with a query vector and rerank the results
const searchWithVector = await namespace.searchRecords({
  query: {
    topK: 4,
    vector: {
      values: [0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3]
    },
    inputs: { text: 'Disease prevention' },
  },
  fields: ['chunk_text', 'category'],
  rerank: {
    query: "Disease prevention",
    model: 'bge-reranker-v2-m3',
    rankFields: ['chunk_text'],
    topN: 2,
  },
});

console.log(searchWithVector);

// Search with a record ID and rerank the results
const searchWithId = await namespace.searchRecords({
  query: {
    topK: 4,
    id: 'rec1',
  },
  fields: ['chunk_text', 'category'],
  rerank: {
    query: "Disease prevention",
    model: 'bge-reranker-v2-m3',
    rankFields: ['chunk_text'],
    topN: 2,
  },
});

console.log(searchWithId);
import io.pinecone.clients.Index;
import io.pinecone.configs.PineconeConfig;
import io.pinecone.configs.PineconeConnection;
import org.openapitools.db_data.client.ApiException;
import org.openapitools.db_data.client.model.SearchRecordsRequestRerank;
import org.openapitools.db_data.client.model.SearchRecordsResponse;
import org.openapitools.db_data.client.model.SearchRecordsVector;

import java.util.*;

public class SearchText {
    public static void main(String[] args) throws ApiException {
        PineconeConfig config = new PineconeConfig("YOUR_API_KEY");
        config.setHost("INDEX_HOST");
        PineconeConnection connection = new PineconeConnection(config);

        Index index = new Index(config, connection, "integrated-dense-java");

        String query = "Famous historical structures and monuments";
        List<String> fields = new ArrayList<>();
        fields.add("category");
        fields.add("chunk_text");
        List<String>rankFields = new ArrayList<>();
        rankFields.add("chunk_text");

        SearchRecordsRequestRerank rerank = new SearchRecordsRequestRerank()
                .query(query)
                .model("bge-reranker-v2-m3")
                .topN(2)
                .rankFields(rankFields);

        // Search with a query text and rerank the results
        // Supported only for indexes with integrated embedding
        SearchRecordsResponse searchWithText = index.searchRecordsByText(query,  "example-namespace", fields, 10, null, rerank);

        System.out.println(searchWithText);

        // Search with a query vector and rerank the results
        SearchRecordsVector queryVector = new SearchRecordsVector();
        queryVector.setValues(Arrays.asList(0.3f, 0.3f, 0.3f, 0.3f, 0.3f, 0.3f, 0.3f, 0.3f));
        SearchRecordsResponse searchWithVector = index.searchRecordsByVector(queryVector, "example-namespace", fields, 4, null, rerank);
        
        System.out.println(searchWithVector);

        // Search with a record ID and rerank the results
        SearchRecordsResponse searchWithID = index.searchRecordsById("rec1", "example-namespace", fields, 4, null, rerank);

        System.out.println(searchWithID);
    }
}
package main

import (
    "context"
    "encoding/json"
    "fmt"
    "log"

    "github.com/pinecone-io/go-pinecone/v4/pinecone"
)

func prettifyStruct(obj interface{}) string {
  	bytes, _ := json.MarshalIndent(obj, "", "  ")
    return string(bytes)
}

func main() {
    ctx := context.Background()

    pc, err := pinecone.NewClient(pinecone.NewClientParams{
        ApiKey: "YOUR_API_KEY",
    })
    if err != nil {
        log.Fatalf("Failed to create Client: %v", err)
    }

    // To get the unique host for an index, 
    // see https://docs.pinecone.io/guides/manage-data/target-an-index
    idxConnection, err := pc.Index(pinecone.NewIndexConnParams{Host: "INDEX_HOST", Namespace: "example-namespace"})
    if err != nil {
        log.Fatalf("Failed to create IndexConnection for Host: %v", err)
    } 

    // Search with a query text and rerank the results
    // Supported only for indexes with integrated embedding
    topN := int32(2)
    searchWithText, err := idxConnection.SearchRecords(ctx, &pinecone.SearchRecordsRequest{
        Query: pinecone.SearchRecordsQuery{
            TopK: 4,
            Inputs: &map[string]interface{}{
                "text": "Disease prevention",
            },
        },
        Rerank: &pinecone.SearchRecordsRerank{
            Model:      "bge-reranker-v2-m3",
            TopN:       &topN,
            RankFields: []string{"chunk_text"},
        },
        Fields: &[]string{"chunk_text", "category"},
    })
    if err != nil {
        log.Fatalf("Failed to search records: %v", err)
    }
    fmt.Printf(prettifyStruct(searchWithText))

    // Search with a query vector and rerank the results
    topN := int32(2)
    searchWithVector, err := idxConnection.SearchRecords(ctx, &pinecone.SearchRecordsRequest{
        Query: pinecone.SearchRecordsQuery{
            TopK: 4,
            Vector: pinecone.SearchRecordsVector{
                Values: []float32{0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3},
            },
        },
        Rerank: &pinecone.SearchRecordsRerank{
            Model:      "bge-reranker-v2-m3",
            TopN:       &topN,
            RankFields: []string{"chunk_text"},
        },
        Fields: &[]string{"chunk_text", "category"},
    })
    if err != nil {
        log.Fatalf("Failed to search records: %v", err)
    }
    fmt.Printf(prettifyStruct(resSearchWithVector))

    // Search with a query ID and rerank the results
    topN := int32(2)
    searchWithId, err := idxConnection.SearchRecords(ctx, &pinecone.SearchRecordsRequest{
        Query: pinecone.SearchRecordsQuery{
            TopK: 4,
            Id: "rec1",
        },
        Rerank: &pinecone.SearchRecordsRerank{
            Model:      "bge-reranker-v2-m3",
            TopN:       &topN,
            RankFields: []string{"chunk_text"},
        },
        Fields: &[]string{"chunk_text", "category"},
    })
    if err != nil {
        log.Fatalf("Failed to search records: %v", err)
    }
    fmt.Printf(prettifyStruct(searchWithId))
}
using Pinecone;

var pinecone = new PineconeClient("YOUR_API_KEY");

var index = pinecone.Index(host: "INDEX_HOST");

// Search with a query text and rerank the results
var searchWithText = await index.SearchRecordsAsync(
    "example-namespace",
    new SearchRecordsRequest
    {
        Query = new SearchRecordsRequestQuery
        {
            TopK = 4,
            Inputs = new Dictionary<string, object?> { { "text", "Disease prevention" } },
        },
        Fields = ["category", "chunk_text"],
        Rerank = new SearchRecordsRequestRerank
        {
            Model = "bge-reranker-v2-m3",
            TopN = 2,
            RankFields = ["chunk_text"],
        },
    }
);

Console.WriteLine(searchWithText);

// Search with a query vector and rerank the results
var searchWithVector = await index.SearchRecordsAsync(
    "example-namespace",
    new SearchRecordsRequest
    {
        Query = new SearchRecordsRequestQuery
        {
            TopK = 4,
            Vector = new SearchRecordsVector
            {
                Values = new float[] { 0.3f, 0.3f, 0.3f, 0.3f, 0.3f, 0.3f, 0.3f, 0.3f },
            },
        },
        Fields = ["category", "chunk_text"],
        Rerank = new SearchRecordsRequestRerank
        {
            Model = "bge-reranker-v2-m3",
            TopN = 2,
            RankFields = ["chunk_text"],
        },
    }
);

Console.WriteLine(searchWithVector);

// Search with a query ID and rerank the results
var searchWithId = await index.SearchRecordsAsync(
    "example-namespace",
    new SearchRecordsRequest
    {
        Query = new SearchRecordsRequestQuery
        {
            TopK = 4,
            Id = "rec1",
        },
        Fields = ["category", "chunk_text"],
        Rerank = new SearchRecordsRequestRerank
        {
            Model = "bge-reranker-v2-m3",
            TopN = 2,
            RankFields = ["chunk_text"],
        },
    }
);

Console.WriteLine(searchWithId);
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: 2025-04" \
  -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: 2025-04" \
  -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: 2025-04" \
  -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': 0.004399413242936134,
                      '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': 0.0029235430993139744,
                      '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}}
{
  "result": { 
    "hits": [ 
      {
        "_id": "rec3",
        "_score": 0.004399413242936134,
        "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": 0.0029235430993139744,
        "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": { 
    "readUnits": 6, 
    "embedTotalTokens": 8,
    "rerankUnits": 1 
  }
}
class SearchRecordsResponse {
    result: class SearchRecordsResponseResult {
        hits: [class Hit {
            id: rec3
            score: 0.004399413242936134
            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.}
            additionalProperties: null
        }, class Hit {
            id: rec4
            score: 0.0029235430993139744
            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.}
            additionalProperties: null
        }]
        additionalProperties: null
    }
    usage: class SearchUsage {
        readUnits: 6
        embedTotalTokens: 13
        rerankUnits: 1
        additionalProperties: null
    }
    additionalProperties: null
}
{
  "result": {
    "hits": [
      {
        "_id": "rec3",
        "_score": 0.004399413242936134,
        "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": 0.0029235430993139744,
        "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": {
    "read_units": 6,
    "embed_total_tokens": 8,
    "rerank_units": 1
  }
}
{
    "result": {
        "hits": [
            {
                "_id": "rec3",
                "_score": 0.13741668,
                "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": "rec1",
                "_score": 0.0023413408,
                "fields": {
                    "category": "digestive system",
                    "chunk_text": "Apples are a great source of dietary fiber, which supports digestion and helps maintain a healthy gut."
                }
            }
        ]
    },
    "usage": {
        "read_units": 6,
        "embed_total_tokens": 5,
        "rerank_units": 1
    }
}
{
    "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.

Path Parameters

namespace
string
required

The namespace to search.

Body

application/json

A search request for records in a specific namespace.

query
object
required

.

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.

Response

A successful search namespace response.

The records search response.

result
object
required
usage
object
required