Upsert text into a legacy integrated index

New projects should use the Documents API. To move an existing index, see Move to the Documents API.

This page shows you how to upsert source text into a legacy integrated index created with create_index_for_model. The legacy Records API converts the text to vectors with the hosted embedding model associated with the index. For a document index with integrated embedding, see Upsert data. When you describe a legacy integrated index, its text field has the semantic_text type. Document schemas don’t use that type.

Upsert text as dense vectors

To upsert source text into a legacy integrated index, use the Upsert text operation. Pinecone converts the text to dense vectors automatically using the hosted dense embedding model associated with the index.

Specify the namespace to upsert into. If the namespace doesn’t exist, it’s created. To use the default namespace, set the namespace to "__default__".
Format your input data as records, each with the following:
- An _id field with a unique record identifier for the index namespace. id can be used as an alias for _id.
- A field with the source text to convert to a vector. This field must match the field_map specified in the index.
- Additional fields are stored as record metadata and can be returned in search results or used to filter search results.

For example, the following code converts the sentences in the chunk_text fields to dense vectors and then upserts them into example-namespace in an example index. The additional category field is stored as metadata.

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/indexes/target-an-index
index = pc.index(host="INDEX_HOST")

# Upsert records into a namespace
# `chunk_text` fields are converted to dense vectors
# `category` fields are stored as metadata
index.upsert_records(
    namespace="example-namespace",
    records=[
        {
            "_id": "rec1",
            "chunk_text": "Apples are a great source of dietary fiber, which supports digestion and helps maintain a healthy gut.",
            "category": "digestive system", 
        },
        {
            "_id": "rec2",
            "chunk_text": "Apples originated in Central Asia and have been cultivated for thousands of years, with over 7,500 varieties available today.",
            "category": "cultivation",
        },
        {
            "_id": "rec3",
            "chunk_text": "Rich in vitamin C and other antioxidants, apples contribute to immune health and may reduce the risk of chronic diseases.",
            "category": "immune system",
        },
        {
            "_id": "rec4",
            "chunk_text": "The high fiber content in apples can also help regulate blood sugar levels, making them a favorable snack for people with diabetes.",
            "category": "endocrine system",
        },
    ]
) 

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/indexes/target-an-index
const namespace = pc.index("INDEX_NAME", "INDEX_HOST").namespace("example-namespace");

// Upsert records into a namespace
// `chunk_text` fields are converted to dense vectors
// `category` is stored as metadata
await namespace.upsertRecords({ records: [
        {
            "_id": "rec1",
            "chunk_text": "Apples are a great source of dietary fiber, which supports digestion and helps maintain a healthy gut.",
            "category": "digestive system", 
        },
        {
            "_id": "rec2",
            "chunk_text": "Apples originated in Central Asia and have been cultivated for thousands of years, with over 7,500 varieties available today.",
            "category": "cultivation",
        },
        {
            "_id": "rec3",
            "chunk_text": "Rich in vitamin C and other antioxidants, apples contribute to immune health and may reduce the risk of chronic diseases.",
            "category": "immune system",
        },
        {
            "_id": "rec4",
            "chunk_text": "The high fiber content in apples can also help regulate blood sugar levels, making them a favorable snack for people with diabetes.",
            "category": "endocrine system",
        }
] });

import io.pinecone.clients.Index;
import io.pinecone.configs.PineconeConfig;
import io.pinecone.configs.PineconeConnection;
import org.openapitools.db_data.client.ApiException;

import java.util.*;

public class UpsertText {
    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");
        ArrayList<Map<String, String>> upsertRecords = new ArrayList<>();

        HashMap<String, String> record1 = new HashMap<>();
        record1.put("_id", "rec1");
        record1.put("category", "digestive system");
        record1.put("chunk_text", "Apples are a great source of dietary fiber, which supports digestion and helps maintain a healthy gut.");

        HashMap<String, String> record2 = new HashMap<>();
        record2.put("_id", "rec2");
        record2.put("category", "cultivation");
        record2.put("chunk_text", "Apples originated in Central Asia and have been cultivated for thousands of years, with over 7,500 varieties available today.");

        HashMap<String, String> record3 = new HashMap<>();
        record3.put("_id", "rec3");
        record3.put("category", "immune system");
        record3.put("chunk_text", "Rich in vitamin C and other antioxidants, apples contribute to immune health and may reduce the risk of chronic diseases.");

        HashMap<String, String> record4 = new HashMap<>();
        record4.put("_id", "rec4");
        record4.put("category", "endocrine system");
        record4.put("chunk_text", "The high fiber content in apples can also help regulate blood sugar levels, making them a favorable snack for people with diabetes.");

        upsertRecords.add(record1);
        upsertRecords.add(record2);
        upsertRecords.add(record3);
        upsertRecords.add(record4);

        index.upsertRecords("example-namespace", upsertRecords);
    }
}

package main

import (
    "context"
    "log"

    "github.com/pinecone-io/go-pinecone/v7/pinecone"
)

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/indexes/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)
	  }

    // Upsert records into a namespace
    // `chunk_text` fields are converted to dense vectors
    // `category` is stored as metadata
	records := []*pinecone.IntegratedRecord{
        {
            "_id": "rec1",
            "chunk_text": "Apples are a great source of dietary fiber, which supports digestion and helps maintain a healthy gut.",
            "category": "digestive system", 
        },
        {
            "_id": "rec2",
            "chunk_text": "Apples originated in Central Asia and have been cultivated for thousands of years, with over 7,500 varieties available today.",
            "category": "cultivation",
        },
        {
            "_id": "rec3",
            "chunk_text": "Rich in vitamin C and other antioxidants, apples contribute to immune health and may reduce the risk of chronic diseases.",
            "category": "immune system",
        },
        {
            "_id": "rec4",
            "chunk_text": "The high fiber content in apples can also help regulate blood sugar levels, making them a favorable snack for people with diabetes.",
            "category": "endocrine system",
        },
	}

	err = idxConnection.UpsertRecords(ctx, records)
	if err != nil {
		log.Fatalf("Failed to upsert vectors: %v", err)
	}
}

# To get the unique host for an index,
# see https://docs.pinecone.io/guides/indexes/target-an-index
INDEX_HOST="INDEX_HOST"
NAMESPACE="YOUR_NAMESPACE"
PINECONE_API_KEY="YOUR_API_KEY"

# Upsert records into a namespace
# `chunk_text` fields are converted to dense vectors
# `category` is stored as metadata
curl "https://$INDEX_HOST/records/namespaces/$NAMESPACE/upsert" \
  -H "Content-Type: application/x-ndjson" \
  -H "Api-Key: $PINECONE_API_KEY" \
  -H "X-Pinecone-Api-Version: 2026-07" \
  -d '{"_id": "rec1", "chunk_text": "Apples are a great source of dietary fiber, which supports digestion and helps maintain a healthy gut.", "category": "digestive system"}
      {"_id": "rec2", "chunk_text": "Apples originated in Central Asia and have been cultivated for thousands of years, with over 7,500 varieties available today.", "category": "cultivation"}
      {"_id": "rec3", "chunk_text": "Rich in vitamin C and other antioxidants, apples contribute to immune health and may reduce the risk of chronic diseases.", "category": "immune system"}
      {"_id": "rec4", "chunk_text": "The high fiber content in apples can also help regulate blood sugar levels, making them a favorable snack for people with diabetes.", "category": "endocrine system"}'

Upsert text as sparse vectors

To upsert source text into a legacy integrated index, use the Upsert text operation. Pinecone converts the text to sparse vectors automatically using the hosted sparse embedding model associated with the index.

Specify the namespace to upsert into. If the namespace doesn’t exist, it’s created. To use the default namespace, set the namespace to "__default__".
Format your input data as records, each with the following:
- An _id field with a unique record identifier for the index namespace. id can be used as an alias for _id.
- A field with the source text to convert to a vector. This field must match the field_map specified in the index.
- Additional fields are stored as record metadata and can be returned in search results or used to filter search results.

For example, the following code converts the sentences in the chunk_text fields to sparse vectors and then upserts them into example-namespace in an example index. The additional category and quarter fields are stored as metadata.

import time

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/indexes/target-an-index
index = pc.index(host="INDEX_HOST")

# Upsert records into a namespace
# `chunk_text` fields are converted to sparse vectors
# `category` and `quarter` fields are stored as metadata
index.upsert_records(
    namespace="example-namespace",
    records=[
        { 
            "_id": "vec1", 
            "chunk_text": "AAPL reported a year-over-year revenue increase, expecting stronger Q3 demand for its flagship phones.", 
            "category": "technology",
            "quarter": "Q3"
        },
        { 
            "_id": "vec2", 
            "chunk_text": "Analysts suggest that AAPL's upcoming Q4 product launch event might solidify its position in the premium smartphone market.", 
            "category": "technology",
            "quarter": "Q4"
        },
        { 
            "_id": "vec3", 
            "chunk_text": "AAPL's strategic Q3 partnerships with semiconductor suppliers could mitigate component risks and stabilize iPhone production.",
            "category": "technology",
            "quarter": "Q3"
        },
        { 
            "_id": "vec4", 
            "chunk_text": "AAPL may consider healthcare integrations in Q4 to compete with tech rivals entering the consumer wellness space.", 
            "category": "technology",
            "quarter": "Q4"
        }
    ]
)

time.sleep(10) # Wait for the upserted vectors to be indexed

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/indexes/target-an-index
const namespace = pc.index("INDEX_NAME", "INDEX_HOST").namespace("example-namespace");

// Upsert records into a namespace
// `chunk_text` fields are converted to sparse vectors
// `category` and `quarter` fields are stored as metadata
await namespace.upsertRecords({ records: [
    { 
        "_id": "vec1", 
        "chunk_text": "AAPL reported a year-over-year revenue increase, expecting stronger Q3 demand for its flagship phones.", 
        "category": "technology",
        "quarter": "Q3"
    },
    { 
        "_id": "vec2", 
        "chunk_text": "Analysts suggest that AAPL's upcoming Q4 product launch event might solidify its position in the premium smartphone market.", 
        "category": "technology",
        "quarter": "Q4"
    },
    { 
        "_id": "vec3", 
        "chunk_text": "AAPL's strategic Q3 partnerships with semiconductor suppliers could mitigate component risks and stabilize iPhone production.",
        "category": "technology",
        "quarter": "Q3"
    },
    { 
        "_id": "vec4", 
        "chunk_text": "AAPL may consider healthcare integrations in Q4 to compete with tech rivals entering the consumer wellness space.", 
        "category": "technology",
        "quarter": "Q4"
    }
] });

import io.pinecone.clients.Index;
import io.pinecone.configs.PineconeConfig;
import io.pinecone.configs.PineconeConnection;
import org.openapitools.db_data.client.ApiException;

import java.util.*;

public class UpsertText {
    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-sparse-java");
        ArrayList<Map<String, String>> upsertRecords = new ArrayList<>();

        HashMap<String, String> record1 = new HashMap<>();
        record1.put("_id", "rec1");
        record1.put("category", "digestive system");
        record1.put("chunk_text", "Apples are a great source of dietary fiber, which supports digestion and helps maintain a healthy gut.");

        HashMap<String, String> record2 = new HashMap<>();
        record2.put("_id", "rec2");
        record2.put("category", "cultivation");
        record2.put("chunk_text", "Apples originated in Central Asia and have been cultivated for thousands of years, with over 7,500 varieties available today.");

        HashMap<String, String> record3 = new HashMap<>();
        record3.put("_id", "rec3");
        record3.put("category", "immune system");
        record3.put("chunk_text", "Rich in vitamin C and other antioxidants, apples contribute to immune health and may reduce the risk of chronic diseases.");

        HashMap<String, String> record4 = new HashMap<>();
        record4.put("_id", "rec4");
        record4.put("category", "endocrine system");
        record4.put("chunk_text", "The high fiber content in apples can also help regulate blood sugar levels, making them a favorable snack for people with diabetes.");

        upsertRecords.add(record1);
        upsertRecords.add(record2);
        upsertRecords.add(record3);
        upsertRecords.add(record4);

        index.upsertRecords("example-namespace", upsertRecords);
    }
}

package main

import (
    "context"
    "log"

    "github.com/pinecone-io/go-pinecone/v7/pinecone"
)

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/indexes/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)
	  }

    // Upsert records into a namespace
    // `chunk_text` fields are converted to sparse vectors
    // `category` and `quarter` fields are stored as metadata
	records := []*pinecone.IntegratedRecord{
		{
			"_id":        "vec1",
			"chunk_text": "AAPL reported a year-over-year revenue increase, expecting stronger Q3 demand for its flagship phones.",
			"category":   "technology",
			"quarter":    "Q3",
		},
		{
			"_id":        "vec2",
			"chunk_text": "Analysts suggest that AAPL's upcoming Q4 product launch event might solidify its position in the premium smartphone market.",
			"category":   "technology",
			"quarter":    "Q4",
		},
		{
			"_id":        "vec3",
			"chunk_text": "AAPL's strategic Q3 partnerships with semiconductor suppliers could mitigate component risks and stabilize iPhone production.",
			"category":   "technology",
			"quarter":    "Q3",
		},
		{
			"_id":        "vec4",
			"chunk_text": "AAPL may consider healthcare integrations in Q4 to compete with tech rivals entering the consumer wellness space.",
			"category":   "technology",
			"quarter":    "Q4",
		},
	}

	err = idxConnection.UpsertRecords(ctx, records)
	if err != nil {
		log.Fatalf("Failed to upsert vectors: %v", err)
	}
}

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

curl  "https://$INDEX_HOST/records/namespaces/$NAMESPACE/upsert" \
    -H "Content-Type: application/x-ndjson" \
    -H "Api-Key: $PINECONE_API_KEY" \
    -H "X-Pinecone-Api-Version: 2026-07" \
    -d '{ "_id": "vec1", "chunk_text": "AAPL reported a year-over-year revenue increase, expecting stronger Q3 demand for its flagship phones.", "category": "technology", "quarter": "Q3" }
      { "_id": "vec2", "chunk_text": "Analysts suggest that AAPL'\''s upcoming Q4 product launch event might solidify its position in the premium smartphone market.", "category": "technology", "quarter": "Q4" }
      { "_id": "vec3", "chunk_text": "AAPL'\''s strategic Q3 partnerships with semiconductor suppliers could mitigate component risks and stabilize iPhone production.", "category": "technology", "quarter": "Q3" }
      { "_id": "vec4", "chunk_text": "AAPL may consider healthcare integrations in Q4 to compete with tech rivals entering the consumer wellness space.", "category": "technology", "quarter": "Q4" }'

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Legacy

Upsert text into a legacy integrated index

Upsert text as dense vectors

Upsert text as sparse vectors

​Upsert text as dense vectors

​Upsert text as sparse vectors

Upsert text as dense vectors

Upsert text as sparse vectors