# pip install --upgrade pinecone
import os
from pinecone import Pinecone
pc = Pinecone(api_key=os.environ["PINECONE_API_KEY"])
# To get the host for an index, see https://docs.pinecone.io/guides/manage-data/target-an-index
index = pc.index(host="INDEX_HOST")
# Search with a query text and rerank the results
# Supported only for indexes with integrated embedding
search_with_text = index.search(
namespace="example-namespace",
inputs={"text": "Disease prevention"},
top_k=4,
fields=["category", "chunk_text"],
rerank={
"model": "bge-reranker-v2-m3",
"top_n": 2,
"rank_fields": ["chunk_text"],
},
)
for hit in search_with_text.result.hits:
print(hit.id, hit.score, hit.fields)
# Search with a query vector and rerank the results
search_with_vector = index.search(
namespace="example-namespace",
vector=[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"],
},
)
for hit in search_with_vector.result.hits:
print(hit.id, hit.score, hit.fields)
# Search with a record ID and rerank the results
search_with_id = index.search(
namespace="example-namespace",
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"],
},
)
for hit in search_with_id.result.hits:
print(hit.id, hit.score, hit.fields)
// npm install @pinecone-database/pinecone
import { Pinecone } from '@pinecone-database/pinecone';
// Reads PINECONE_API_KEY from the environment
const pc = new Pinecone();
// To get the host for an index, see https://docs.pinecone.io/guides/manage-data/target-an-index
const index = pc.index({
host: 'INDEX_HOST',
namespace: 'example-namespace',
});
// Search with a query text and rerank the results
// Supported only for indexes with integrated embedding
const searchWithText = await index.searchRecords({
query: {
inputs: { text: 'Disease prevention' },
topK: 4,
},
fields: ['category', 'chunk_text'],
rerank: {
model: 'bge-reranker-v2-m3',
topN: 2,
rankFields: ['chunk_text'],
},
});
console.log(searchWithText.result.hits);
// Search with a query vector and rerank the results
const searchWithVector = await index.searchRecords({
query: {
vector: {
values: [0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3],
},
topK: 4,
},
fields: ['category', 'chunk_text'],
rerank: {
query: 'Disease prevention',
model: 'bge-reranker-v2-m3',
topN: 2,
rankFields: ['chunk_text'],
},
});
console.log(searchWithVector.result.hits);
// Search with a record ID and rerank the results
const searchWithId = await index.searchRecords({
query: {
id: 'rec1',
topK: 4,
},
fields: ['category', 'chunk_text'],
rerank: {
query: 'Disease prevention',
model: 'bge-reranker-v2-m3',
topN: 2,
rankFields: ['chunk_text'],
},
});
console.log(searchWithId.result.hits);
package main
import (
"context"
"fmt"
"log"
"os"
"github.com/pinecone-io/go-pinecone/v7/pinecone"
)
func main() {
ctx := context.Background()
pc, err := pinecone.NewClient(pinecone.NewClientParams{
ApiKey: os.Getenv("PINECONE_API_KEY"),
})
if err != nil {
log.Fatalf("Failed to create Client: %v", err)
}
// To get the 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: %v", err)
}
fields := []string{"category", "chunk_text"}
rerankQuery := "Disease prevention"
topN := int32(2)
// Search with a query text and rerank the results
// Supported only for indexes with integrated embedding
searchWithText, err := idxConnection.SearchRecords(ctx, &pinecone.SearchRecordsRequest{
Query: pinecone.SearchRecordsQuery{
Inputs: &map[string]interface{}{
"text": "Disease prevention",
},
TopK: 4,
},
Fields: &fields,
Rerank: &pinecone.SearchRecordsRerank{
Model: "bge-reranker-v2-m3",
TopN: &topN,
RankFields: []string{"chunk_text"},
},
})
if err != nil {
log.Fatalf("Failed to search with text: %v", err)
}
for _, hit := range searchWithText.Result.Hits {
fmt.Println(hit.Id, hit.Score, hit.Fields["category"])
}
// Search with a query vector and rerank the results
searchWithVector, err := idxConnection.SearchRecords(ctx, &pinecone.SearchRecordsRequest{
Query: pinecone.SearchRecordsQuery{
Vector: &pinecone.SearchRecordsVector{
Values: &[]float32{0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3},
},
TopK: 4,
},
Fields: &fields,
Rerank: &pinecone.SearchRecordsRerank{
Query: &rerankQuery,
Model: "bge-reranker-v2-m3",
TopN: &topN,
RankFields: []string{"chunk_text"},
},
})
if err != nil {
log.Fatalf("Failed to search with vector: %v", err)
}
for _, hit := range searchWithVector.Result.Hits {
fmt.Println(hit.Id, hit.Score, hit.Fields["category"])
}
// Search with a record ID and rerank the results
recordId := "rec1"
searchWithId, err := idxConnection.SearchRecords(ctx, &pinecone.SearchRecordsRequest{
Query: pinecone.SearchRecordsQuery{
Id: &recordId,
TopK: 4,
},
Fields: &fields,
Rerank: &pinecone.SearchRecordsRerank{
Query: &rerankQuery,
Model: "bge-reranker-v2-m3",
TopN: &topN,
RankFields: []string{"chunk_text"},
},
})
if err != nil {
log.Fatalf("Failed to search with ID: %v", err)
}
for _, hit := range searchWithId.Result.Hits {
fmt.Println(hit.Id, hit.Score, hit.Fields["category"])
}
}
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: $PINECONE_API_KEY" \
-H "X-Pinecone-Api-Version: 2026-07" \
-d '{
"query": {
"inputs": {"text": "Disease prevention"},
"top_k": 4
},
"fields": ["category", "chunk_text"],
"rerank": {
"model": "bge-reranker-v2-m3",
"top_n": 2,
"rank_fields": ["chunk_text"]
}
}'
# Search with a query vector and rerank the results
curl "https://$INDEX_HOST/records/namespaces/$NAMESPACE/search" \
-H "Accept: application/json" \
-H "Content-Type: application/json" \
-H "Api-Key: $PINECONE_API_KEY" \
-H "X-Pinecone-Api-Version: 2026-07" \
-d '{
"query": {
"vector": {
"values": [0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3]
},
"top_k": 4
},
"fields": ["category", "chunk_text"],
"rerank": {
"query": "Disease prevention",
"model": "bge-reranker-v2-m3",
"top_n": 2,
"rank_fields": ["chunk_text"]
}
}'
# Search with a record ID and rerank the results
curl "https://$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: 2026-07" \
-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"]
}
}'
{
"namespace": "example-namespace",
"result": {
"hits": [
{
"_id": "example-record-1",
"_score": 0.9281134605407715,
"fields": {
"data": "your example text"
}
}
]
},
"usage": {
"egress_bytes": 1024,
"embed_total_tokens": 10,
"read_units": 5
}
}{
"error": {
"code": "INVALID_ARGUMENT",
"message": "No 'ids' or 'filter' provided in the document fetch request. Provide at least one document ID in 'ids', or a metadata filter in 'filter'."
},
"status": 400
}Unauthorized{
"error": {
"code": "INVALID_ARGUMENT",
"message": "No 'ids' or 'filter' provided in the document fetch request. Provide at least one document ID in 'ids', or a metadata filter in 'filter'."
},
"status": 400
}{
"error": {
"code": "INVALID_ARGUMENT",
"message": "No 'ids' or 'filter' provided in the document fetch request. Provide at least one document ID in 'ids', or a metadata filter in 'filter'."
},
"status": 400
}Search
Search with text (legacy Records API)
Search a namespace with a query text, query vector, or record ID and return the most similar records, along with their similarity scores. Optionally, rerank the initial results based on their relevance to the query.
This operation is part of the legacy Records API, which legacy integrated indexes require. For new work, create a document index with a string field that uses integrated embedding (embed or sparse_embed), and search it with the Documents API’s search_documents operation and an embed or sparse_embed scoring method.
Searching with text (inputs) is supported only for legacy integrated indexes; for any other index a text query is rejected with 400, and it is not available on BYOC indexes; reranking (rerank) is likewise unavailable on BYOC indexes. Searching with a query vector (vector) or a record ID (id) works on any index served by the vectors API.
For guidance and examples, see Search.
POST
/
records
/
namespaces
/
{namespace}
/
search
# pip install --upgrade pinecone
import os
from pinecone import Pinecone
pc = Pinecone(api_key=os.environ["PINECONE_API_KEY"])
# To get the host for an index, see https://docs.pinecone.io/guides/manage-data/target-an-index
index = pc.index(host="INDEX_HOST")
# Search with a query text and rerank the results
# Supported only for indexes with integrated embedding
search_with_text = index.search(
namespace="example-namespace",
inputs={"text": "Disease prevention"},
top_k=4,
fields=["category", "chunk_text"],
rerank={
"model": "bge-reranker-v2-m3",
"top_n": 2,
"rank_fields": ["chunk_text"],
},
)
for hit in search_with_text.result.hits:
print(hit.id, hit.score, hit.fields)
# Search with a query vector and rerank the results
search_with_vector = index.search(
namespace="example-namespace",
vector=[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"],
},
)
for hit in search_with_vector.result.hits:
print(hit.id, hit.score, hit.fields)
# Search with a record ID and rerank the results
search_with_id = index.search(
namespace="example-namespace",
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"],
},
)
for hit in search_with_id.result.hits:
print(hit.id, hit.score, hit.fields)
// npm install @pinecone-database/pinecone
import { Pinecone } from '@pinecone-database/pinecone';
// Reads PINECONE_API_KEY from the environment
const pc = new Pinecone();
// To get the host for an index, see https://docs.pinecone.io/guides/manage-data/target-an-index
const index = pc.index({
host: 'INDEX_HOST',
namespace: 'example-namespace',
});
// Search with a query text and rerank the results
// Supported only for indexes with integrated embedding
const searchWithText = await index.searchRecords({
query: {
inputs: { text: 'Disease prevention' },
topK: 4,
},
fields: ['category', 'chunk_text'],
rerank: {
model: 'bge-reranker-v2-m3',
topN: 2,
rankFields: ['chunk_text'],
},
});
console.log(searchWithText.result.hits);
// Search with a query vector and rerank the results
const searchWithVector = await index.searchRecords({
query: {
vector: {
values: [0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3],
},
topK: 4,
},
fields: ['category', 'chunk_text'],
rerank: {
query: 'Disease prevention',
model: 'bge-reranker-v2-m3',
topN: 2,
rankFields: ['chunk_text'],
},
});
console.log(searchWithVector.result.hits);
// Search with a record ID and rerank the results
const searchWithId = await index.searchRecords({
query: {
id: 'rec1',
topK: 4,
},
fields: ['category', 'chunk_text'],
rerank: {
query: 'Disease prevention',
model: 'bge-reranker-v2-m3',
topN: 2,
rankFields: ['chunk_text'],
},
});
console.log(searchWithId.result.hits);
package main
import (
"context"
"fmt"
"log"
"os"
"github.com/pinecone-io/go-pinecone/v7/pinecone"
)
func main() {
ctx := context.Background()
pc, err := pinecone.NewClient(pinecone.NewClientParams{
ApiKey: os.Getenv("PINECONE_API_KEY"),
})
if err != nil {
log.Fatalf("Failed to create Client: %v", err)
}
// To get the 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: %v", err)
}
fields := []string{"category", "chunk_text"}
rerankQuery := "Disease prevention"
topN := int32(2)
// Search with a query text and rerank the results
// Supported only for indexes with integrated embedding
searchWithText, err := idxConnection.SearchRecords(ctx, &pinecone.SearchRecordsRequest{
Query: pinecone.SearchRecordsQuery{
Inputs: &map[string]interface{}{
"text": "Disease prevention",
},
TopK: 4,
},
Fields: &fields,
Rerank: &pinecone.SearchRecordsRerank{
Model: "bge-reranker-v2-m3",
TopN: &topN,
RankFields: []string{"chunk_text"},
},
})
if err != nil {
log.Fatalf("Failed to search with text: %v", err)
}
for _, hit := range searchWithText.Result.Hits {
fmt.Println(hit.Id, hit.Score, hit.Fields["category"])
}
// Search with a query vector and rerank the results
searchWithVector, err := idxConnection.SearchRecords(ctx, &pinecone.SearchRecordsRequest{
Query: pinecone.SearchRecordsQuery{
Vector: &pinecone.SearchRecordsVector{
Values: &[]float32{0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3},
},
TopK: 4,
},
Fields: &fields,
Rerank: &pinecone.SearchRecordsRerank{
Query: &rerankQuery,
Model: "bge-reranker-v2-m3",
TopN: &topN,
RankFields: []string{"chunk_text"},
},
})
if err != nil {
log.Fatalf("Failed to search with vector: %v", err)
}
for _, hit := range searchWithVector.Result.Hits {
fmt.Println(hit.Id, hit.Score, hit.Fields["category"])
}
// Search with a record ID and rerank the results
recordId := "rec1"
searchWithId, err := idxConnection.SearchRecords(ctx, &pinecone.SearchRecordsRequest{
Query: pinecone.SearchRecordsQuery{
Id: &recordId,
TopK: 4,
},
Fields: &fields,
Rerank: &pinecone.SearchRecordsRerank{
Query: &rerankQuery,
Model: "bge-reranker-v2-m3",
TopN: &topN,
RankFields: []string{"chunk_text"},
},
})
if err != nil {
log.Fatalf("Failed to search with ID: %v", err)
}
for _, hit := range searchWithId.Result.Hits {
fmt.Println(hit.Id, hit.Score, hit.Fields["category"])
}
}
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: $PINECONE_API_KEY" \
-H "X-Pinecone-Api-Version: 2026-07" \
-d '{
"query": {
"inputs": {"text": "Disease prevention"},
"top_k": 4
},
"fields": ["category", "chunk_text"],
"rerank": {
"model": "bge-reranker-v2-m3",
"top_n": 2,
"rank_fields": ["chunk_text"]
}
}'
# Search with a query vector and rerank the results
curl "https://$INDEX_HOST/records/namespaces/$NAMESPACE/search" \
-H "Accept: application/json" \
-H "Content-Type: application/json" \
-H "Api-Key: $PINECONE_API_KEY" \
-H "X-Pinecone-Api-Version: 2026-07" \
-d '{
"query": {
"vector": {
"values": [0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3]
},
"top_k": 4
},
"fields": ["category", "chunk_text"],
"rerank": {
"query": "Disease prevention",
"model": "bge-reranker-v2-m3",
"top_n": 2,
"rank_fields": ["chunk_text"]
}
}'
# Search with a record ID and rerank the results
curl "https://$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: 2026-07" \
-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"]
}
}'
{
"namespace": "example-namespace",
"result": {
"hits": [
{
"_id": "example-record-1",
"_score": 0.9281134605407715,
"fields": {
"data": "your example text"
}
}
]
},
"usage": {
"egress_bytes": 1024,
"embed_total_tokens": 10,
"read_units": 5
}
}{
"error": {
"code": "INVALID_ARGUMENT",
"message": "No 'ids' or 'filter' provided in the document fetch request. Provide at least one document ID in 'ids', or a metadata filter in 'filter'."
},
"status": 400
}Unauthorized{
"error": {
"code": "INVALID_ARGUMENT",
"message": "No 'ids' or 'filter' provided in the document fetch request. Provide at least one document ID in 'ids', or a metadata filter in 'filter'."
},
"status": 400
}{
"error": {
"code": "INVALID_ARGUMENT",
"message": "No 'ids' or 'filter' provided in the document fetch request. Provide at least one document ID in 'ids', or a metadata filter in 'filter'."
},
"status": 400
}# pip install --upgrade pinecone
import os
from pinecone import Pinecone
pc = Pinecone(api_key=os.environ["PINECONE_API_KEY"])
# To get the host for an index, see https://docs.pinecone.io/guides/manage-data/target-an-index
index = pc.index(host="INDEX_HOST")
# Search with a query text and rerank the results
# Supported only for indexes with integrated embedding
search_with_text = index.search(
namespace="example-namespace",
inputs={"text": "Disease prevention"},
top_k=4,
fields=["category", "chunk_text"],
rerank={
"model": "bge-reranker-v2-m3",
"top_n": 2,
"rank_fields": ["chunk_text"],
},
)
for hit in search_with_text.result.hits:
print(hit.id, hit.score, hit.fields)
# Search with a query vector and rerank the results
search_with_vector = index.search(
namespace="example-namespace",
vector=[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"],
},
)
for hit in search_with_vector.result.hits:
print(hit.id, hit.score, hit.fields)
# Search with a record ID and rerank the results
search_with_id = index.search(
namespace="example-namespace",
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"],
},
)
for hit in search_with_id.result.hits:
print(hit.id, hit.score, hit.fields)
// npm install @pinecone-database/pinecone
import { Pinecone } from '@pinecone-database/pinecone';
// Reads PINECONE_API_KEY from the environment
const pc = new Pinecone();
// To get the host for an index, see https://docs.pinecone.io/guides/manage-data/target-an-index
const index = pc.index({
host: 'INDEX_HOST',
namespace: 'example-namespace',
});
// Search with a query text and rerank the results
// Supported only for indexes with integrated embedding
const searchWithText = await index.searchRecords({
query: {
inputs: { text: 'Disease prevention' },
topK: 4,
},
fields: ['category', 'chunk_text'],
rerank: {
model: 'bge-reranker-v2-m3',
topN: 2,
rankFields: ['chunk_text'],
},
});
console.log(searchWithText.result.hits);
// Search with a query vector and rerank the results
const searchWithVector = await index.searchRecords({
query: {
vector: {
values: [0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3],
},
topK: 4,
},
fields: ['category', 'chunk_text'],
rerank: {
query: 'Disease prevention',
model: 'bge-reranker-v2-m3',
topN: 2,
rankFields: ['chunk_text'],
},
});
console.log(searchWithVector.result.hits);
// Search with a record ID and rerank the results
const searchWithId = await index.searchRecords({
query: {
id: 'rec1',
topK: 4,
},
fields: ['category', 'chunk_text'],
rerank: {
query: 'Disease prevention',
model: 'bge-reranker-v2-m3',
topN: 2,
rankFields: ['chunk_text'],
},
});
console.log(searchWithId.result.hits);
package main
import (
"context"
"fmt"
"log"
"os"
"github.com/pinecone-io/go-pinecone/v7/pinecone"
)
func main() {
ctx := context.Background()
pc, err := pinecone.NewClient(pinecone.NewClientParams{
ApiKey: os.Getenv("PINECONE_API_KEY"),
})
if err != nil {
log.Fatalf("Failed to create Client: %v", err)
}
// To get the 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: %v", err)
}
fields := []string{"category", "chunk_text"}
rerankQuery := "Disease prevention"
topN := int32(2)
// Search with a query text and rerank the results
// Supported only for indexes with integrated embedding
searchWithText, err := idxConnection.SearchRecords(ctx, &pinecone.SearchRecordsRequest{
Query: pinecone.SearchRecordsQuery{
Inputs: &map[string]interface{}{
"text": "Disease prevention",
},
TopK: 4,
},
Fields: &fields,
Rerank: &pinecone.SearchRecordsRerank{
Model: "bge-reranker-v2-m3",
TopN: &topN,
RankFields: []string{"chunk_text"},
},
})
if err != nil {
log.Fatalf("Failed to search with text: %v", err)
}
for _, hit := range searchWithText.Result.Hits {
fmt.Println(hit.Id, hit.Score, hit.Fields["category"])
}
// Search with a query vector and rerank the results
searchWithVector, err := idxConnection.SearchRecords(ctx, &pinecone.SearchRecordsRequest{
Query: pinecone.SearchRecordsQuery{
Vector: &pinecone.SearchRecordsVector{
Values: &[]float32{0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3},
},
TopK: 4,
},
Fields: &fields,
Rerank: &pinecone.SearchRecordsRerank{
Query: &rerankQuery,
Model: "bge-reranker-v2-m3",
TopN: &topN,
RankFields: []string{"chunk_text"},
},
})
if err != nil {
log.Fatalf("Failed to search with vector: %v", err)
}
for _, hit := range searchWithVector.Result.Hits {
fmt.Println(hit.Id, hit.Score, hit.Fields["category"])
}
// Search with a record ID and rerank the results
recordId := "rec1"
searchWithId, err := idxConnection.SearchRecords(ctx, &pinecone.SearchRecordsRequest{
Query: pinecone.SearchRecordsQuery{
Id: &recordId,
TopK: 4,
},
Fields: &fields,
Rerank: &pinecone.SearchRecordsRerank{
Query: &rerankQuery,
Model: "bge-reranker-v2-m3",
TopN: &topN,
RankFields: []string{"chunk_text"},
},
})
if err != nil {
log.Fatalf("Failed to search with ID: %v", err)
}
for _, hit := range searchWithId.Result.Hits {
fmt.Println(hit.Id, hit.Score, hit.Fields["category"])
}
}
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: $PINECONE_API_KEY" \
-H "X-Pinecone-Api-Version: 2026-07" \
-d '{
"query": {
"inputs": {"text": "Disease prevention"},
"top_k": 4
},
"fields": ["category", "chunk_text"],
"rerank": {
"model": "bge-reranker-v2-m3",
"top_n": 2,
"rank_fields": ["chunk_text"]
}
}'
# Search with a query vector and rerank the results
curl "https://$INDEX_HOST/records/namespaces/$NAMESPACE/search" \
-H "Accept: application/json" \
-H "Content-Type: application/json" \
-H "Api-Key: $PINECONE_API_KEY" \
-H "X-Pinecone-Api-Version: 2026-07" \
-d '{
"query": {
"vector": {
"values": [0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3]
},
"top_k": 4
},
"fields": ["category", "chunk_text"],
"rerank": {
"query": "Disease prevention",
"model": "bge-reranker-v2-m3",
"top_n": 2,
"rank_fields": ["chunk_text"]
}
}'
# Search with a record ID and rerank the results
curl "https://$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: 2026-07" \
-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"]
}
}'
Authorizations
Headers
Required date-based version header
Path Parameters
The namespace to search.
Body
application/json
A search request for records in a specific namespace, for the legacy Records API's search_records operation.
The query to search with. Set top_k and one of inputs, vector, or id.
Show child attributes
Show child attributes
The fields to return in the search results. If not specified, the response will include all fields.
Example:
["chunk_text"]
Parameters for reranking the initial search results.
Show child attributes
Show child attributes
Response
A successful search namespace response.
The records search response.
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