# Requires Terraform provider v5.0.0 or later# Creates a legacy integrated index. For new indexes, declare integrated embedding# on a string field of a document index instead (provider v5.1.0 or later).resource "pinecone_index" "docs_example" { name = "docs-example" spec = { serverless = { cloud = "aws" region = "us-east-1" } } embed = { model = "multilingual-e5-large" field_map = { text = "chunk_text" } }}
Create a legacy integrated index. Legacy integrated indexes created via create-for-model require the legacy Records API.
For new work, create a document index with Create an index, declaring embed or sparse_embed on a string field to enable integrated embedding on it, and read and write the index through the Documents API. Document indexes support integrated embedding alongside full-text search on the same field, and scoring with score_by.
With this type of index, you provide source text, and Pinecone uses a hosted embedding model to convert the text automatically during upsert and search.
The response is this version’s index model, with the embedding configuration surfaced as a semantic_text field in the index schema, named after the field_map text entry. Read and write the index through the legacy Records API.
# Requires Terraform provider v5.0.0 or later# Creates a legacy integrated index. For new indexes, declare integrated embedding# on a string field of a document index instead (provider v5.1.0 or later).resource "pinecone_index" "docs_example" { name = "docs-example" spec = { serverless = { cloud = "aws" region = "us-east-1" } } embed = { model = "multilingual-e5-large" field_map = { text = "chunk_text" } }}
# Requires Terraform provider v5.0.0 or later# Creates a legacy integrated index. For new indexes, declare integrated embedding# on a string field of a document index instead (provider v5.1.0 or later).resource "pinecone_index" "docs_example" { name = "docs-example" spec = { serverless = { cloud = "aws" region = "us-east-1" } } embed = { model = "multilingual-e5-large" field_map = { text = "chunk_text" } }}
The name of the index. Resource name must be 1-45 characters long, start and end with an alphanumeric character, and consist only of lower case alphanumeric characters or '-'.
Specify the integrated embedding configuration for the legacy integrated index.
Once set the model cannot be changed, but you can later update the embedding configuration of a legacy integrated index, including field map, read parameters, or write parameters.
Refer to the model guide for available models and model details.
Custom user tags added to an index, at most 20 per index. Keys must be 80 characters or less and alphanumeric, '_', or '-'. Values must be 120 characters or less and consist of printable ASCII characters or spaces. To unset a key, set the value to be an empty string. null in responses when the index has no tags.
Schema for the behavior of Pinecone's internal metadata index. By default, all metadata is indexed; when schema is present, only fields which are present in the fields object with a filterable: true are indexed. Note that filterable: false is not currently supported.
By default the index will be created with read capacity mode OnDemand. If you prefer to allocate dedicated read nodes for your workload, you must specify mode Dedicated and additional configurations for node_type and scaling. BYOC indexes do not support OnDemand: a byoc deployment must set mode: Dedicated explicitly, since omitting read_capacity defaults to OnDemand and is rejected.
On-demand
Dedicated
Show child attributes
Example:
{ "mode": "OnDemand" }
Response
The index has successfully been created for the embedding model.
The IndexModel describes the configuration and status of a Pinecone index.
The name of the index. Resource name must be 1-45 characters long, start and end with an alphanumeric character, and consist only of lower case alphanumeric characters or '-'.
The schema of a Pinecone index. The schema defines the typed fields that documents in the index can contain, including vector fields, string fields searched by full-text search or by embeddings, and metadata fields.
Custom user tags added to an index, at most 20 per index. Keys must be 80 characters or less and alphanumeric, '_', or '-'. Values must be 120 characters or less and consist of printable ASCII characters or spaces. To unset a key, set the value to be an empty string. null in responses when the index has no tags.
Show child attributes
Example:
{ "tag0": "val0", "tag1": "val1" }
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Legacy integrated indexes created via create-for-model require the legacy Records API.\n\nFor new work, create a document index with [Create an index](https://docs.pinecone.io/reference/api/2026-07/control-plane/create_index), declaring `embed` or `sparse_embed` on a `string` field to enable integrated embedding on it, and read and write the index through the Documents API. Document indexes support integrated embedding alongside full-text search on the same field, and scoring with `score_by`.\n\nWith this type of index, you provide source text, and Pinecone uses a [hosted embedding model](https://docs.pinecone.io/guides/index-data/create-an-index#embedding-models) to convert the text automatically during [upsert](https://docs.pinecone.io/reference/api/2026-07/data-plane/upsert_records) and [search](https://docs.pinecone.io/reference/api/2026-07/data-plane/search_records).\n\nThe response is this version's index model, with the embedding configuration surfaced as a `semantic_text` field in the index `schema`, named after the `field_map` text entry. 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\\\\`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0550AE`,\"--shiki-dark\":`#569CD6`},children:` -H`}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"X-Pinecone-Api-Version: 2026-07\"`}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D7BA7D`},children:` \\\\`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0550AE`,\"--shiki-dark\":`#569CD6`},children:` -d`}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` '{`})]}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"name\": \"docs-example\",`})}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"cloud\": \"aws\",`})}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"region\": \"us-east-1\",`})}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"embed\": {`})}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"model\": \"multilingual-e5-large\",`})}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"field_map\": {\"text\": \"chunk_text\"}`})}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` }`})}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` }'`})}),`\n`]})})})]})}function MDXContent(props={}){const{wrapper:MDXLayout}={..._provideComponents(),...props.components};return MDXLayout?_jsx(MDXLayout,{...props,children:_jsx(_createMdxContent,{...props})}):_createMdxContent(props)}return{default:MDXContent};function _missingMdxReference(id,component){throw new Error(`Expected `+(component?`component`:`object`)+\" `\"+id+\"` to be defined: you likely forgot to import, pass, or provide it.\")}","frontmatter":{},"scope":{"config":{},"pageMetadata":{"openapi":"https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2026-07/db_control_2026-07.oas.yaml post /indexes/create-for-model","title":"Create a legacy integrated index","description":"Create a legacy integrated index. Legacy integrated indexes created via create-for-model require the legacy Records API.\n\nFor new work, create a document index with [Create an index](https://docs.pinecone.io/reference/api/2026-07/control-plane/create_index), declaring `embed` or `sparse_embed` on a `string` field to enable integrated embedding on it, and read and write the index through the Documents API. Document indexes support integrated embedding alongside full-text search on the same field, and scoring with `score_by`.\n\nWith this type of index, you provide source text, and Pinecone uses a [hosted embedding model](https://docs.pinecone.io/guides/index-data/create-an-index#embedding-models) to convert the text automatically during [upsert](https://docs.pinecone.io/reference/api/2026-07/data-plane/upsert_records) and [search](https://docs.pinecone.io/reference/api/2026-07/data-plane/search_records).\n\nThe response is this version's index model, with the embedding configuration surfaced as a `semantic_text` field in the index `schema`, named after the `field_map` text entry. Read and write the index through the legacy Records API.\n\nFor guidance and examples, see [Create an index](https://docs.pinecone.io/guides/index-data/create-an-index#integrated-embedding).","href":"/reference/api/2026-07/control-plane/create_for_model"}}}},"mdxExtracts":{"tableOfContents":[],"codeExamples":{"request":{"type":"RequestExample","children":[{"filename":"Python","html":"\u003cpre class=\"shiki shiki-themes github-light-default dark-plus\" style=\"background-color:#ffffff;--shiki-dark-bg:#0B0C0E;color:#1f2328;--shiki-dark:#D4D4D4\" language=\"python\">\u003ccode language=\"python\" numberOfLines=\"15\">\u003cspan class=\"line\">\u003cspan style=\"color:#6E7781;--shiki-dark:#6A9955\"># pip install --upgrade pinecone\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#CF222E;--shiki-dark:#C586C0\">import\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\"> os\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#CF222E;--shiki-dark:#C586C0\">from\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\"> pinecone \u003c/span>\u003cspan style=\"color:#CF222E;--shiki-dark:#C586C0\">import\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\"> Pinecone\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">pc \u003c/span>\u003cspan style=\"color:#CF222E;--shiki-dark:#D4D4D4\">=\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\"> Pinecone(\u003c/span>\u003cspan style=\"color:#953800;--shiki-dark:#9CDCFE\">api_key\u003c/span>\u003cspan style=\"color:#CF222E;--shiki-dark:#D4D4D4\">=\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">os.environ[\u003c/span>\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\">\"PINECONE_API_KEY\"\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">])\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">index_model \u003c/span>\u003cspan style=\"color:#CF222E;--shiki-dark:#D4D4D4\">=\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\"> pc.indexes.create_for_model(\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#953800;--shiki-dark:#9CDCFE\"> name\u003c/span>\u003cspan style=\"color:#CF222E;--shiki-dark:#D4D4D4\">=\u003c/span>\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\">\"docs-example\"\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">,\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#953800;--shiki-dark:#9CDCFE\"> cloud\u003c/span>\u003cspan style=\"color:#CF222E;--shiki-dark:#D4D4D4\">=\u003c/span>\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\">\"aws\"\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">,\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#953800;--shiki-dark:#9CDCFE\"> region\u003c/span>\u003cspan style=\"color:#CF222E;--shiki-dark:#D4D4D4\">=\u003c/span>\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\">\"us-east-1\"\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">,\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#953800;--shiki-dark:#9CDCFE\"> embed\u003c/span>\u003cspan style=\"color:#CF222E;--shiki-dark:#D4D4D4\">=\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">{\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\"> \"model\"\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">: \u003c/span>\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\">\"multilingual-e5-large\"\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">,\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\"> \"field_map\"\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">: {\u003c/span>\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\">\"text\"\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">: \u003c/span>\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\">\"chunk_text\"\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">},\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\"> },\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">)\u003c/span>\u003c/span>\n\u003c/code>\u003c/pre>"},{"filename":"JavaScript","html":"\u003cpre class=\"shiki shiki-themes github-light-default dark-plus\" style=\"background-color:#ffffff;--shiki-dark-bg:#0B0C0E;color:#1f2328;--shiki-dark:#D4D4D4\" language=\"javascript\">\u003ccode language=\"javascript\" numberOfLines=\"15\">\u003cspan class=\"line\">\u003cspan style=\"color:#6E7781;--shiki-dark:#6A9955\">// npm install @pinecone-database/pinecone\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#CF222E;--shiki-dark:#C586C0\">import\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\"> { \u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#9CDCFE\">Pinecone\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\"> } \u003c/span>\u003cspan style=\"color:#CF222E;--shiki-dark:#C586C0\">from\u003c/span>\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\"> '@pinecone-database/pinecone'\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">;\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#6E7781;--shiki-dark:#6A9955\">// Reads PINECONE_API_KEY from the environment\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#CF222E;--shiki-dark:#569CD6\">const\u003c/span>\u003cspan style=\"color:#0550AE;--shiki-dark:#4FC1FF\"> pc\u003c/span>\u003cspan style=\"color:#CF222E;--shiki-dark:#D4D4D4\"> =\u003c/span>\u003cspan style=\"color:#CF222E;--shiki-dark:#569CD6\"> new\u003c/span>\u003cspan style=\"color:#8250DF;--shiki-dark:#DCDCAA\"> Pinecone\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">();\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#CF222E;--shiki-dark:#569CD6\">const\u003c/span>\u003cspan style=\"color:#0550AE;--shiki-dark:#4FC1FF\"> indexModel\u003c/span>\u003cspan style=\"color:#CF222E;--shiki-dark:#D4D4D4\"> =\u003c/span>\u003cspan style=\"color:#CF222E;--shiki-dark:#C586C0\"> await\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#9CDCFE\"> pc\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">.\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#9CDCFE\">indexes\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">.\u003c/span>\u003cspan style=\"color:#8250DF;--shiki-dark:#DCDCAA\">createForModel\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">({\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#1F2328;--shiki-dark:#9CDCFE\"> name:\u003c/span>\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\"> 'docs-example'\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">,\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#1F2328;--shiki-dark:#9CDCFE\"> cloud:\u003c/span>\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\"> 'aws'\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">,\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#1F2328;--shiki-dark:#9CDCFE\"> region:\u003c/span>\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\"> 'us-east-1'\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">,\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#1F2328;--shiki-dark:#9CDCFE\"> embed:\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\"> {\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#1F2328;--shiki-dark:#9CDCFE\"> model:\u003c/span>\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\"> 'multilingual-e5-large'\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">,\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#1F2328;--shiki-dark:#9CDCFE\"> fieldMap:\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\"> { \u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#9CDCFE\">text:\u003c/span>\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\"> 'chunk_text'\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\"> },\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\"> },\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">});\u003c/span>\u003c/span>\n\u003c/code>\u003c/pre>"},{"filename":"Go","html":"\u003cpre class=\"shiki shiki-themes github-light-default dark-plus\" style=\"background-color:#ffffff;--shiki-dark-bg:#0B0C0E;color:#1f2328;--shiki-dark:#D4D4D4\" language=\"go\">\u003ccode language=\"go\" numberOfLines=\"35\">\u003cspan class=\"line\">\u003cspan style=\"color:#CF222E;--shiki-dark:#569CD6\">package\u003c/span>\u003cspan style=\"color:#953800;--shiki-dark:#4EC9B0\"> main\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#CF222E;--shiki-dark:#C586C0\">import\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\"> (\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\"> \"\u003c/span>\u003cspan style=\"color:#953800;--shiki-dark:#CE9178\">context\u003c/span>\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\">\"\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\"> \"\u003c/span>\u003cspan style=\"color:#953800;--shiki-dark:#CE9178\">fmt\u003c/span>\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\">\"\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\"> \"\u003c/span>\u003cspan style=\"color:#953800;--shiki-dark:#CE9178\">log\u003c/span>\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\">\"\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\"> \"\u003c/span>\u003cspan style=\"color:#953800;--shiki-dark:#CE9178\">os\u003c/span>\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\">\"\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\"> \"\u003c/span>\u003cspan style=\"color:#953800;--shiki-dark:#CE9178\">github.com/pinecone-io/go-pinecone/v7/pinecone\u003c/span>\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\">\"\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">)\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#CF222E;--shiki-dark:#569CD6\">func\u003c/span>\u003cspan style=\"color:#8250DF;--shiki-dark:#DCDCAA\"> main\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">() {\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#1F2328;--shiki-dark:#9CDCFE\"> ctx\u003c/span>\u003cspan style=\"color:#CF222E;--shiki-dark:#D4D4D4\"> :=\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#9CDCFE\"> context\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">.\u003c/span>\u003cspan style=\"color:#8250DF;--shiki-dark:#DCDCAA\">Background\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">()\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#1F2328;--shiki-dark:#9CDCFE\"> pc\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">, \u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#9CDCFE\">err\u003c/span>\u003cspan style=\"color:#CF222E;--shiki-dark:#D4D4D4\"> :=\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#9CDCFE\"> pinecone\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">.\u003c/span>\u003cspan style=\"color:#8250DF;--shiki-dark:#DCDCAA\">NewClient\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">(\u003c/span>\u003cspan style=\"color:#953800;--shiki-dark:#4EC9B0\">pinecone\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">.\u003c/span>\u003cspan style=\"color:#953800;--shiki-dark:#4EC9B0\">NewClientParams\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">{\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#1F2328;--shiki-dark:#9CDCFE\"> ApiKey\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">: \u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#9CDCFE\">os\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">.\u003c/span>\u003cspan style=\"color:#8250DF;--shiki-dark:#DCDCAA\">Getenv\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">(\u003c/span>\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\">\"PINECONE_API_KEY\"\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">),\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\"> })\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#CF222E;--shiki-dark:#C586C0\"> if\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#9CDCFE\"> err\u003c/span>\u003cspan style=\"color:#CF222E;--shiki-dark:#D4D4D4\"> !=\u003c/span>\u003cspan style=\"color:#0550AE;--shiki-dark:#569CD6\"> nil\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\"> {\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#1F2328;--shiki-dark:#9CDCFE\"> log\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">.\u003c/span>\u003cspan style=\"color:#8250DF;--shiki-dark:#DCDCAA\">Fatalf\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">(\u003c/span>\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\">\"Failed to create Client: \u003c/span>\u003cspan style=\"color:#CF222E;--shiki-dark:#9CDCFE\">%v\u003c/span>\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\">\"\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">, \u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#9CDCFE\">err\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">)\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\"> }\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#1F2328;--shiki-dark:#9CDCFE\"> idx\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">, \u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#9CDCFE\">err\u003c/span>\u003cspan style=\"color:#CF222E;--shiki-dark:#D4D4D4\"> :=\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#9CDCFE\"> pc\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">.\u003c/span>\u003cspan style=\"color:#8250DF;--shiki-dark:#DCDCAA\">CreateIndexForModel\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">(\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#9CDCFE\">ctx\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">, \u003c/span>\u003cspan style=\"color:#CF222E;--shiki-dark:#D4D4D4\">\u0026#x26;\u003c/span>\u003cspan style=\"color:#953800;--shiki-dark:#4EC9B0\">pinecone\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">.\u003c/span>\u003cspan style=\"color:#953800;--shiki-dark:#4EC9B0\">CreateIndexForModelRequest\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">{\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#1F2328;--shiki-dark:#9CDCFE\"> Name\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">: \u003c/span>\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\">\"docs-example\"\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">,\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#1F2328;--shiki-dark:#9CDCFE\"> Cloud\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">: \u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#9CDCFE\">pinecone\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">.\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#9CDCFE\">CloudAWS\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">,\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#1F2328;--shiki-dark:#9CDCFE\"> Region\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">: \u003c/span>\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\">\"us-east-1\"\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">,\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#1F2328;--shiki-dark:#9CDCFE\"> Embed\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">: \u003c/span>\u003cspan style=\"color:#953800;--shiki-dark:#4EC9B0\">pinecone\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">.\u003c/span>\u003cspan style=\"color:#953800;--shiki-dark:#4EC9B0\">CreateIndexForModelEmbed\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">{\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#1F2328;--shiki-dark:#9CDCFE\"> Model\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">: \u003c/span>\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\">\"multilingual-e5-large\"\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">,\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#1F2328;--shiki-dark:#9CDCFE\"> FieldMap\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">: \u003c/span>\u003cspan style=\"color:#CF222E;--shiki-dark:#569CD6\">map\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">[\u003c/span>\u003cspan style=\"color:#CF222E;--shiki-dark:#4EC9B0\">string\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">]\u003c/span>\u003cspan style=\"color:#CF222E;--shiki-dark:#569CD6\">interface\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">{}{\u003c/span>\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\">\"text\"\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">: \u003c/span>\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\">\"chunk_text\"\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">},\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\"> },\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\"> })\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#CF222E;--shiki-dark:#C586C0\"> if\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#9CDCFE\"> err\u003c/span>\u003cspan style=\"color:#CF222E;--shiki-dark:#D4D4D4\"> !=\u003c/span>\u003cspan style=\"color:#0550AE;--shiki-dark:#569CD6\"> nil\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\"> {\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#1F2328;--shiki-dark:#9CDCFE\"> log\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">.\u003c/span>\u003cspan style=\"color:#8250DF;--shiki-dark:#DCDCAA\">Fatalf\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">(\u003c/span>\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\">\"Failed to create index: \u003c/span>\u003cspan style=\"color:#CF222E;--shiki-dark:#9CDCFE\">%v\u003c/span>\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\">\"\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">, \u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#9CDCFE\">err\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">)\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\"> }\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#1F2328;--shiki-dark:#9CDCFE\"> fmt\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">.\u003c/span>\u003cspan style=\"color:#8250DF;--shiki-dark:#DCDCAA\">Println\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">(\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#9CDCFE\">idx\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">.\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#9CDCFE\">Name\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">, \u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#9CDCFE\">idx\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">.\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#9CDCFE\">Host\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">)\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">}\u003c/span>\u003c/span>\n\u003c/code>\u003c/pre>"},{"filename":"Terraform","html":"\u003cpre class=\"shiki shiki-themes github-light-default dark-plus\" style=\"background-color:#ffffff;--shiki-dark-bg:#0B0C0E;color:#1f2328;--shiki-dark:#D4D4D4\" language=\"hcl\">\u003ccode language=\"hcl\" numberOfLines=\"18\">\u003cspan class=\"line\">\u003cspan style=\"color:#6E7781;--shiki-dark:#6A9955\"># Requires Terraform provider v5.0.0 or later\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#6E7781;--shiki-dark:#6A9955\"># Creates a legacy integrated index. For new indexes, declare integrated embedding\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#6E7781;--shiki-dark:#6A9955\"># on a string field of a document index instead (provider v5.1.0 or later).\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#953800;--shiki-dark:#4EC9B0\">resource\u003c/span>\u003cspan style=\"color:#0550AE;--shiki-dark:#4FC1FF\"> \"pinecone_index\"\u003c/span>\u003cspan style=\"color:#0550AE;--shiki-dark:#4FC1FF\"> \"docs_example\"\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\"> {\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#1F2328;--shiki-dark:#9CDCFE\"> name\u003c/span>\u003cspan style=\"color:#CF222E;--shiki-dark:#D4D4D4\"> =\u003c/span>\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\"> \"docs-example\"\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#1F2328;--shiki-dark:#9CDCFE\"> spec\u003c/span>\u003cspan style=\"color:#CF222E;--shiki-dark:#D4D4D4\"> =\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\"> {\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#1F2328;--shiki-dark:#9CDCFE\"> serverless\u003c/span>\u003cspan style=\"color:#CF222E;--shiki-dark:#D4D4D4\"> =\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\"> {\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#1F2328;--shiki-dark:#9CDCFE\"> cloud\u003c/span>\u003cspan style=\"color:#CF222E;--shiki-dark:#D4D4D4\"> =\u003c/span>\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\"> \"aws\"\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#1F2328;--shiki-dark:#9CDCFE\"> region\u003c/span>\u003cspan style=\"color:#CF222E;--shiki-dark:#D4D4D4\"> =\u003c/span>\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\"> \"us-east-1\"\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\"> }\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\"> }\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#1F2328;--shiki-dark:#9CDCFE\"> embed\u003c/span>\u003cspan style=\"color:#CF222E;--shiki-dark:#D4D4D4\"> =\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\"> {\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#1F2328;--shiki-dark:#9CDCFE\"> model\u003c/span>\u003cspan style=\"color:#CF222E;--shiki-dark:#D4D4D4\"> =\u003c/span>\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\"> \"multilingual-e5-large\"\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#1F2328;--shiki-dark:#9CDCFE\"> field_map\u003c/span>\u003cspan style=\"color:#CF222E;--shiki-dark:#D4D4D4\"> =\u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\"> {\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#1F2328;--shiki-dark:#9CDCFE\"> text\u003c/span>\u003cspan style=\"color:#CF222E;--shiki-dark:#D4D4D4\"> =\u003c/span>\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\"> \"chunk_text\"\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\"> }\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\"> }\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#1F2328;--shiki-dark:#D4D4D4\">}\u003c/span>\u003c/span>\n\u003c/code>\u003c/pre>"},{"filename":"curl","html":"\u003cpre class=\"shiki shiki-themes github-light-default dark-plus\" style=\"background-color:#ffffff;--shiki-dark-bg:#0B0C0E;color:#1f2328;--shiki-dark:#D4D4D4\" language=\"shellscript\">\u003ccode language=\"shellscript\" numberOfLines=\"15\">\u003cspan class=\"line\">\u003cspan style=\"color:#1F2328;--shiki-dark:#9CDCFE\">PINECONE_API_KEY\u003c/span>\u003cspan style=\"color:#CF222E;--shiki-dark:#D4D4D4\">=\u003c/span>\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\">\"YOUR_API_KEY\"\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#953800;--shiki-dark:#DCDCAA\">curl\u003c/span>\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\"> \"https://api.pinecone.io/indexes/create-for-model\"\u003c/span>\u003cspan style=\"color:#CF222E;--shiki-dark:#D7BA7D\"> \\\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#0550AE;--shiki-dark:#569CD6\"> -H\u003c/span>\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\"> \"Api-Key: \u003c/span>\u003cspan style=\"color:#1F2328;--shiki-dark:#9CDCFE\">$PINECONE_API_KEY\u003c/span>\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\">\"\u003c/span>\u003cspan style=\"color:#CF222E;--shiki-dark:#D7BA7D\"> \\\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#0550AE;--shiki-dark:#569CD6\"> -H\u003c/span>\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\"> \"Content-Type: application/json\"\u003c/span>\u003cspan style=\"color:#CF222E;--shiki-dark:#D7BA7D\"> \\\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#0550AE;--shiki-dark:#569CD6\"> -H\u003c/span>\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\"> \"X-Pinecone-Api-Version: 2026-07\"\u003c/span>\u003cspan style=\"color:#CF222E;--shiki-dark:#D7BA7D\"> \\\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#0550AE;--shiki-dark:#569CD6\"> -d\u003c/span>\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\"> '{\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\"> \"name\": \"docs-example\",\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\"> \"cloud\": \"aws\",\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\"> \"region\": \"us-east-1\",\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\"> \"embed\": {\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\"> \"model\": \"multilingual-e5-large\",\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\"> \"field_map\": {\"text\": \"chunk_text\"}\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\"> }\u003c/span>\u003c/span>\n\u003cspan class=\"line\">\u003cspan style=\"color:#0A3069;--shiki-dark:#CE9178\"> }'\u003c/span>\u003c/span>\n\u003c/code>\u003c/pre>"}],"attributes":[]}}},"jsLinks":["/_mintlify/custom/pinecone/345ae6b85c58f0d4/console-iframe.js","/_mintlify/custom/pinecone/7865d5d28c64c1ee/script.js","/_mintlify/custom/pinecone/4d30bdf131035051/inkeep.js"],"openApiReferenceData":{"operation":{"tags":["Manage Indexes"],"summary":"Create a legacy integrated index","description":"Create a legacy integrated index. Legacy integrated indexes created via create-for-model require the legacy Records API.\n\nFor new work, create a document index with [Create an index](https://docs.pinecone.io/reference/api/2026-07/control-plane/create_index), declaring `embed` or `sparse_embed` on a `string` field to enable integrated embedding on it, and read and write the index through the Documents API. Document indexes support integrated embedding alongside full-text search on the same field, and scoring with `score_by`.\n\nWith this type of index, you provide source text, and Pinecone uses a [hosted embedding model](https://docs.pinecone.io/guides/index-data/create-an-index#embedding-models) to convert the text automatically during [upsert](https://docs.pinecone.io/reference/api/2026-07/data-plane/upsert_records) and [search](https://docs.pinecone.io/reference/api/2026-07/data-plane/search_records).\n\nThe response is this version's index model, with the embedding configuration surfaced as a `semantic_text` field in the index `schema`, named after the `field_map` text entry. 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Must be `dense_vector`.","type":"string","enum":["dense_vector"],"isRequired":true,"uniqueKey":"schema.fields.additionalProperties.oneOf.0.type","typeLabel":"enum\u003cstring>"},"dimension":{"example":1536,"description":"The number of dimensions in the dense vectors stored in this field.","type":"integer","format":"int32","minimum":1,"maximum":20000,"isRequired":true,"uniqueKey":"schema.fields.additionalProperties.oneOf.0.dimension","typeLabel":"integer\u003cint32>"},"metric":{"example":"cosine","description":"The distance metric used for similarity search.\n\nPossible values: `cosine`, `dotproduct`, or `euclidean`.","x-enum":["cosine","dotproduct","euclidean"],"type":"string","isRequired":true,"uniqueKey":"schema.fields.additionalProperties.oneOf.0.metric","typeLabel":"string"},"description":{"oneOf":[{"description":"Optional description for this field, at most 256 bytes. `null` in responses when none was set.","type":"string","maxLength":256,"uniqueKey":"schema.fields.additionalProperties.oneOf.0.description.oneOf.0","typeLabel":"string"},{"description":"Optional description for this field, at most 256 bytes. `null` in responses when none was set.","type":"null","maxLength":256,"uniqueKey":"schema.fields.additionalProperties.oneOf.0.description.oneOf.1","typeLabel":"null"}],"uniqueKey":"schema.fields.additionalProperties.oneOf.0.description","typeLabel":"string | null"}},"additionalProperties":false,"uniqueKey":"schema.fields.additionalProperties.oneOf.0","typeLabel":"Dense vector · object"},{"type":"object","title":"Sparse vector","description":"The configuration of a single field in the index schema.\n\nMost fields carry a `type` property that identifies the field type:\n\n- `dense_vector`: Fixed-dimension floating-point vectors for ANN search.\n- `sparse_vector`: Sparse vectors for keyword or hybrid search.\n- `semantic_text`: The embedded text field of a legacy integrated index created via create-for-model.\n- `string`: String field for full-text search, integrated embedding (`embed` / `sparse_embed`), or metadata filtering.\n- `string_list`: String array field.\n- `float`: Numeric field.\n- `integer`: Legacy numeric field from older indexes (pre-dating float normalization). Will not appear in new indexes.\n- `boolean`: Boolean field.\n\nFields in older indexes may omit `type` entirely. These are legacy metadata fields from before typed schemas were introduced.","required":["type"],"example":{"type":"sparse_vector"},"properties":{"type":{"description":"Identifies this as a sparse vector field. Must be `sparse_vector`.","type":"string","enum":["sparse_vector"],"isRequired":true,"uniqueKey":"schema.fields.additionalProperties.oneOf.1.type","typeLabel":"enum\u003cstring>"},"description":{"oneOf":[{"description":"Optional description for this field, at most 256 bytes. `null` in responses when none was set.","type":"string","maxLength":256,"uniqueKey":"schema.fields.additionalProperties.oneOf.1.description.oneOf.0","typeLabel":"string"},{"description":"Optional description for this field, at most 256 bytes. `null` in responses when none was set.","type":"null","maxLength":256,"uniqueKey":"schema.fields.additionalProperties.oneOf.1.description.oneOf.1","typeLabel":"null"}],"uniqueKey":"schema.fields.additionalProperties.oneOf.1.description","typeLabel":"string | null"}},"additionalProperties":false,"uniqueKey":"schema.fields.additionalProperties.oneOf.1","typeLabel":"Sparse vector · object"},{"type":"object","title":"Semantic text","description":"The configuration of a single field in the index schema.\n\nMost fields carry a `type` property that identifies the field type:\n\n- `dense_vector`: Fixed-dimension floating-point vectors for ANN search.\n- `sparse_vector`: Sparse vectors for keyword or hybrid search.\n- `semantic_text`: The embedded text field of a legacy integrated index created via create-for-model.\n- `string`: String field for full-text search, integrated embedding (`embed` / `sparse_embed`), or metadata filtering.\n- `string_list`: String array field.\n- `float`: Numeric field.\n- `integer`: Legacy numeric field from older indexes (pre-dating float normalization). Will not appear in new indexes.\n- `boolean`: Boolean field.\n\nFields in older indexes may omit `type` entirely. These are legacy metadata fields from before typed schemas were introduced.","required":["type","model"],"example":{"model":"multilingual-e5-large","type":"semantic_text"},"properties":{"type":{"description":"Identifies this as a semantic text field. Must be `semantic_text`.","type":"string","enum":["semantic_text"],"isRequired":true,"uniqueKey":"schema.fields.additionalProperties.oneOf.2.type","typeLabel":"enum\u003cstring>"},"model":{"example":"multilingual-e5-large","description":"The hosted embedding model that embeds the field's text.","type":"string","isRequired":true,"uniqueKey":"schema.fields.additionalProperties.oneOf.2.model","typeLabel":"string"},"description":{"oneOf":[{"description":"The field's description, or `null` when none was set.","type":"string","maxLength":256,"uniqueKey":"schema.fields.additionalProperties.oneOf.2.description.oneOf.0","typeLabel":"string"},{"description":"The field's description, or `null` when none was set.","type":"null","maxLength":256,"uniqueKey":"schema.fields.additionalProperties.oneOf.2.description.oneOf.1","typeLabel":"null"}],"uniqueKey":"schema.fields.additionalProperties.oneOf.2.description","typeLabel":"string | null"},"dimension":{"oneOf":[{"example":1024,"description":"The dimension of the vectors the model produces. `null` for models that produce sparse vectors.","type":"integer","format":"int32","uniqueKey":"schema.fields.additionalProperties.oneOf.2.dimension.oneOf.0","typeLabel":"integer\u003cint32>"},{"example":1024,"description":"The dimension of the vectors the model produces. `null` for models that produce sparse vectors.","type":"null","format":"int32","uniqueKey":"schema.fields.additionalProperties.oneOf.2.dimension.oneOf.1","typeLabel":"null"}],"uniqueKey":"schema.fields.additionalProperties.oneOf.2.dimension","typeLabel":"integer\u003cint32> | null"},"metric":{"example":"cosine","description":"The distance metric the index uses.\n\nPossible values: `cosine`, `dotproduct`, or `euclidean`.","x-enum":["cosine","dotproduct","euclidean"],"type":"string","uniqueKey":"schema.fields.additionalProperties.oneOf.2.metric","typeLabel":"string"},"write_parameters":{"oneOf":[{"example":{"input_type":"passage"},"description":"Model-specific parameters applied at write time, such as `input_type`.","type":"object","uniqueKey":"schema.fields.additionalProperties.oneOf.2.write_parameters.oneOf.0","typeLabel":"object"},{"example":{"input_type":"passage"},"description":"Model-specific parameters applied at write time, such as `input_type`.","type":"null","uniqueKey":"schema.fields.additionalProperties.oneOf.2.write_parameters.oneOf.1","typeLabel":"null"}],"uniqueKey":"schema.fields.additionalProperties.oneOf.2.write_parameters","typeLabel":"object | null"},"read_parameters":{"oneOf":[{"example":{"input_type":"query"},"description":"Model-specific parameters applied at query time, such as `input_type`.","type":"object","uniqueKey":"schema.fields.additionalProperties.oneOf.2.read_parameters.oneOf.0","typeLabel":"object"},{"example":{"input_type":"query"},"description":"Model-specific parameters applied at query time, such as `input_type`.","type":"null","uniqueKey":"schema.fields.additionalProperties.oneOf.2.read_parameters.oneOf.1","typeLabel":"null"}],"uniqueKey":"schema.fields.additionalProperties.oneOf.2.read_parameters","typeLabel":"object | null"}},"uniqueKey":"schema.fields.additionalProperties.oneOf.2","typeLabel":"Semantic text · object"},{"type":"object","title":"String","description":"The configuration of a single field in the index schema.\n\nMost fields carry a `type` property that identifies the field type:\n\n- `dense_vector`: Fixed-dimension floating-point vectors for ANN search.\n- `sparse_vector`: Sparse vectors for keyword or hybrid search.\n- `semantic_text`: The embedded text field of a legacy integrated index created via create-for-model.\n- `string`: String field for full-text search, integrated embedding (`embed` / `sparse_embed`), or metadata filtering.\n- `string_list`: String array field.\n- `float`: Numeric field.\n- `integer`: Legacy numeric field from older indexes (pre-dating float normalization). Will not appear in new indexes.\n- `boolean`: Boolean field.\n\nFields in older indexes may omit `type` entirely. These are legacy metadata fields from before typed schemas were introduced.","required":["type"],"example":{"full_text_search":{"language":"en","stemming":false,"stop_words":false},"store_text":true,"type":"string"},"properties":{"type":{"description":"Identifies this as a string field. Must be `string`.","type":"string","enum":["string"],"isRequired":true,"uniqueKey":"schema.fields.additionalProperties.oneOf.3.type","typeLabel":"enum\u003cstring>"},"description":{"oneOf":[{"description":"Optional description for this field. `null` when none was set.","type":"string","uniqueKey":"schema.fields.additionalProperties.oneOf.3.description.oneOf.0","typeLabel":"string"},{"description":"Optional description for this field. `null` when none was set.","type":"null","uniqueKey":"schema.fields.additionalProperties.oneOf.3.description.oneOf.1","typeLabel":"null"}],"uniqueKey":"schema.fields.additionalProperties.oneOf.3.description","typeLabel":"string | null"},"full_text_search":{"description":"Full-text search configuration. Present when the field is indexed for full-text search.","type":"object","properties":{"language":{"example":"en","description":"The language used for text analysis. Defaults to `en`.","default":"en","type":"string","isRequired":true,"uniqueKey":"schema.fields.additionalProperties.oneOf.3.full_text_search.language","typeLabel":"string"},"stemming":{"description":"Whether stemming is applied during text analysis.","type":"boolean","isRequired":true,"uniqueKey":"schema.fields.additionalProperties.oneOf.3.full_text_search.stemming","typeLabel":"boolean"},"stop_words":{"description":"Whether stop words are filtered during text analysis. Only `true` if `stemming: true`.","type":"boolean","isRequired":true,"uniqueKey":"schema.fields.additionalProperties.oneOf.3.full_text_search.stop_words","typeLabel":"boolean"},"ngram":{"description":"Character n-gram tokenization configuration. Present only when the field is configured for n-gram substring matching.","type":"object","properties":{"min_gram":{"example":2,"description":"Minimum n-gram length.","type":"integer","isRequired":true,"uniqueKey":"schema.fields.additionalProperties.oneOf.3.full_text_search.ngram.min_gram","typeLabel":"integer"},"max_gram":{"example":3,"description":"Maximum n-gram length.","type":"integer","isRequired":true,"uniqueKey":"schema.fields.additionalProperties.oneOf.3.full_text_search.ngram.max_gram","typeLabel":"integer"},"prefix_only":{"description":"Whether only prefix n-grams anchored at the start of the token are generated.","type":"boolean","isRequired":true,"uniqueKey":"schema.fields.additionalProperties.oneOf.3.full_text_search.ngram.prefix_only","typeLabel":"boolean"}},"required":["min_gram","max_gram","prefix_only"],"additionalProperties":false,"uniqueKey":"schema.fields.additionalProperties.oneOf.3.full_text_search.ngram","typeLabel":"object"}},"required":["language","stemming","stop_words"],"additionalProperties":false,"uniqueKey":"schema.fields.additionalProperties.oneOf.3.full_text_search","typeLabel":"object"},"store_text":{"example":true,"description":"Whether the field's text is stored. `true` means the text is stored and indexed for full-text search; `false` means it is embedded without being stored.","type":"boolean","uniqueKey":"schema.fields.additionalProperties.oneOf.3.store_text","typeLabel":"boolean"},"embed":{"example":{"dimension":1024,"metric":"cosine","model":"llama-text-embed-v2","read_parameters":{"truncate":"END"},"write_parameters":{"truncate":"END"}},"description":"The dense embedding configuration of a `string` field, as resolved when the index was created: the values set in the create request, with every omitted one filled from the model's defaults. Present when the field was created with `embed`.","type":"object","properties":{"model":{"example":"llama-text-embed-v2","description":"The hosted dense embedding model that embeds the field's text and the query text of `embed` scoring methods.","type":"string","isRequired":true,"uniqueKey":"schema.fields.additionalProperties.oneOf.3.embed.model","typeLabel":"string"},"dimension":{"example":1024,"description":"The dimension of the embedding vectors.","type":"integer","format":"int32","isRequired":true,"uniqueKey":"schema.fields.additionalProperties.oneOf.3.embed.dimension","typeLabel":"integer\u003cint32>"},"metric":{"example":"cosine","description":"The distance metric used for similarity search.\n\nPossible values: `cosine`, `dotproduct`, or `euclidean`.","x-enum":["cosine","dotproduct","euclidean"],"type":"string","isRequired":true,"uniqueKey":"schema.fields.additionalProperties.oneOf.3.embed.metric","typeLabel":"string"},"write_parameters":{"example":{"truncate":"END"},"description":"The model-specific parameters applied when embedding document text, as resolved at creation: the parameters set in the create request merged with the model's defaults.","type":"object","uniqueKey":"schema.fields.additionalProperties.oneOf.3.embed.write_parameters","typeLabel":"object"},"read_parameters":{"example":{"truncate":"END"},"description":"The model-specific parameters applied when embedding the query text of `embed` scoring methods, as resolved at creation: the parameters set in the create request merged with the model's defaults.","type":"object","uniqueKey":"schema.fields.additionalProperties.oneOf.3.embed.read_parameters","typeLabel":"object"}},"required":["model","dimension","metric"],"uniqueKey":"schema.fields.additionalProperties.oneOf.3.embed","typeLabel":"object"},"sparse_embed":{"example":{"model":"pinecone-sparse-english-v0","read_parameters":{"truncate":"END"},"write_parameters":{"truncate":"END"}},"description":"The learned-sparse embedding configuration of a `string` field, as resolved when the index was created: the values set in the create request, with every omitted one filled from the model's defaults. Present when the field was created with `sparse_embed`. Sparse embeddings have no dimension or metric.","type":"object","properties":{"model":{"example":"pinecone-sparse-english-v0","description":"The hosted sparse embedding model that embeds the field's text and the query text of `sparse_embed` scoring methods.","type":"string","isRequired":true,"uniqueKey":"schema.fields.additionalProperties.oneOf.3.sparse_embed.model","typeLabel":"string"},"write_parameters":{"example":{"truncate":"END"},"description":"The model-specific parameters applied when embedding document text, as resolved at creation: the parameters set in the create request merged with the model's defaults.","type":"object","uniqueKey":"schema.fields.additionalProperties.oneOf.3.sparse_embed.write_parameters","typeLabel":"object"},"read_parameters":{"example":{"truncate":"END"},"description":"The model-specific parameters applied when embedding the query text of `sparse_embed` scoring methods, as resolved at creation: the parameters set in the create request merged with the model's defaults.","type":"object","uniqueKey":"schema.fields.additionalProperties.oneOf.3.sparse_embed.read_parameters","typeLabel":"object"}},"required":["model"],"uniqueKey":"schema.fields.additionalProperties.oneOf.3.sparse_embed","typeLabel":"object"},"filterable":{"description":"Whether this field is indexed for metadata filtering. Present only on a string field with no search configuration.","type":"boolean","uniqueKey":"schema.fields.additionalProperties.oneOf.3.filterable","typeLabel":"boolean"}},"uniqueKey":"schema.fields.additionalProperties.oneOf.3","typeLabel":"String · object"},{"type":"object","title":"String array","description":"The configuration of a single field in the index schema.\n\nMost fields carry a `type` property that identifies the field type:\n\n- `dense_vector`: Fixed-dimension floating-point vectors for ANN search.\n- `sparse_vector`: Sparse vectors for keyword or hybrid search.\n- `semantic_text`: The embedded text field of a legacy integrated index created via create-for-model.\n- `string`: String field for full-text search, integrated embedding (`embed` / `sparse_embed`), or metadata filtering.\n- `string_list`: String array field.\n- `float`: Numeric field.\n- `integer`: Legacy numeric field from older indexes (pre-dating float normalization). Will not appear in new indexes.\n- `boolean`: Boolean field.\n\nFields in older indexes may omit `type` entirely. These are legacy metadata fields from before typed schemas were introduced.","required":["type"],"example":{"filterable":true,"type":"string_list"},"properties":{"type":{"description":"Identifies this as a string array field. Must be `string_list`.","type":"string","enum":["string_list"],"isRequired":true,"uniqueKey":"schema.fields.additionalProperties.oneOf.4.type","typeLabel":"enum\u003cstring>"},"description":{"oneOf":[{"description":"Optional description for this field. `null` when none was set.","type":"string","uniqueKey":"schema.fields.additionalProperties.oneOf.4.description.oneOf.0","typeLabel":"string"},{"description":"Optional description for this field. `null` when none was set.","type":"null","uniqueKey":"schema.fields.additionalProperties.oneOf.4.description.oneOf.1","typeLabel":"null"}],"uniqueKey":"schema.fields.additionalProperties.oneOf.4.description","typeLabel":"string | null"},"filterable":{"description":"Whether this field is indexed for metadata filtering.","type":"boolean","uniqueKey":"schema.fields.additionalProperties.oneOf.4.filterable","typeLabel":"boolean"}},"uniqueKey":"schema.fields.additionalProperties.oneOf.4","typeLabel":"String array · object"},{"type":"object","title":"Float","description":"The configuration of a single field in the index schema.\n\nMost fields carry a `type` property that identifies the field type:\n\n- `dense_vector`: Fixed-dimension floating-point vectors for ANN search.\n- `sparse_vector`: Sparse vectors for keyword or hybrid search.\n- `semantic_text`: The embedded text field of a legacy integrated index created via create-for-model.\n- `string`: String field for full-text search, integrated embedding (`embed` / `sparse_embed`), or metadata filtering.\n- `string_list`: String array field.\n- `float`: Numeric field.\n- `integer`: Legacy numeric field from older indexes (pre-dating float normalization). Will not appear in new indexes.\n- `boolean`: Boolean field.\n\nFields in older indexes may omit `type` entirely. These are legacy metadata fields from before typed schemas were introduced.","required":["type"],"example":{"type":"float"},"properties":{"type":{"description":"Identifies this as a float field. Must be `float`.","type":"string","enum":["float"],"isRequired":true,"uniqueKey":"schema.fields.additionalProperties.oneOf.5.type","typeLabel":"enum\u003cstring>"},"description":{"oneOf":[{"description":"Optional description for this field. `null` when none was set.","type":"string","uniqueKey":"schema.fields.additionalProperties.oneOf.5.description.oneOf.0","typeLabel":"string"},{"description":"Optional description for this field. `null` when none was set.","type":"null","uniqueKey":"schema.fields.additionalProperties.oneOf.5.description.oneOf.1","typeLabel":"null"}],"uniqueKey":"schema.fields.additionalProperties.oneOf.5.description","typeLabel":"string | null"},"filterable":{"description":"Whether this field is indexed for metadata filtering.","type":"boolean","uniqueKey":"schema.fields.additionalProperties.oneOf.5.filterable","typeLabel":"boolean"}},"uniqueKey":"schema.fields.additionalProperties.oneOf.5","typeLabel":"Float · object"},{"type":"object","title":"Integer","description":"The configuration of a single field in the index schema.\n\nMost fields carry a `type` property that identifies the field type:\n\n- `dense_vector`: Fixed-dimension floating-point vectors for ANN search.\n- `sparse_vector`: Sparse vectors for keyword or hybrid search.\n- `semantic_text`: The embedded text field of a legacy integrated index created via create-for-model.\n- `string`: String field for full-text search, integrated embedding (`embed` / `sparse_embed`), or metadata filtering.\n- `string_list`: String array field.\n- `float`: Numeric field.\n- `integer`: Legacy numeric field from older indexes (pre-dating float normalization). Will not appear in new indexes.\n- `boolean`: Boolean field.\n\nFields in older indexes may omit `type` entirely. These are legacy metadata fields from before typed schemas were introduced.","required":["type"],"example":{"filterable":true,"type":"integer"},"properties":{"type":{"description":"Identifies this as an integer field. Must be `integer`.","type":"string","enum":["integer"],"isRequired":true,"uniqueKey":"schema.fields.additionalProperties.oneOf.6.type","typeLabel":"enum\u003cstring>"},"description":{"oneOf":[{"description":"Optional description for this field. `null` when none was set.","type":"string","uniqueKey":"schema.fields.additionalProperties.oneOf.6.description.oneOf.0","typeLabel":"string"},{"description":"Optional description for this field. `null` when none was set.","type":"null","uniqueKey":"schema.fields.additionalProperties.oneOf.6.description.oneOf.1","typeLabel":"null"}],"uniqueKey":"schema.fields.additionalProperties.oneOf.6.description","typeLabel":"string | null"},"filterable":{"description":"Whether this field is indexed for metadata filtering.","type":"boolean","uniqueKey":"schema.fields.additionalProperties.oneOf.6.filterable","typeLabel":"boolean"}},"uniqueKey":"schema.fields.additionalProperties.oneOf.6","typeLabel":"Integer · object"},{"type":"object","title":"Boolean","description":"The configuration of a single field in the index schema.\n\nMost fields carry a `type` property that identifies the field type:\n\n- `dense_vector`: Fixed-dimension floating-point vectors for ANN search.\n- `sparse_vector`: Sparse vectors for keyword or hybrid search.\n- `semantic_text`: The embedded text field of a legacy integrated index created via create-for-model.\n- `string`: String field for full-text search, integrated embedding (`embed` / `sparse_embed`), or metadata filtering.\n- `string_list`: String array field.\n- `float`: Numeric field.\n- `integer`: Legacy numeric field from older indexes (pre-dating float normalization). Will not appear in new indexes.\n- `boolean`: Boolean field.\n\nFields in older indexes may omit `type` entirely. These are legacy metadata fields from before typed schemas were introduced.","required":["type"],"example":{"type":"boolean"},"properties":{"type":{"description":"Identifies this as a boolean field. Must be `boolean`.","type":"string","enum":["boolean"],"isRequired":true,"uniqueKey":"schema.fields.additionalProperties.oneOf.7.type","typeLabel":"enum\u003cstring>"},"description":{"oneOf":[{"description":"Optional description for this field. `null` when none was set.","type":"string","uniqueKey":"schema.fields.additionalProperties.oneOf.7.description.oneOf.0","typeLabel":"string"},{"description":"Optional description for this field. `null` when none was set.","type":"null","uniqueKey":"schema.fields.additionalProperties.oneOf.7.description.oneOf.1","typeLabel":"null"}],"uniqueKey":"schema.fields.additionalProperties.oneOf.7.description","typeLabel":"string | null"},"filterable":{"description":"Whether this field is indexed for metadata filtering.","type":"boolean","uniqueKey":"schema.fields.additionalProperties.oneOf.7.filterable","typeLabel":"boolean"}},"uniqueKey":"schema.fields.additionalProperties.oneOf.7","typeLabel":"Boolean · object"},{"type":"object","title":"Legacy metadata","description":"The configuration of a single field in the index schema.\n\nMost fields carry a `type` property that identifies the field type:\n\n- `dense_vector`: Fixed-dimension floating-point vectors for ANN search.\n- `sparse_vector`: Sparse vectors for keyword or hybrid search.\n- `semantic_text`: The embedded text field of a legacy integrated index created via create-for-model.\n- `string`: String field for full-text search, integrated embedding (`embed` / `sparse_embed`), or metadata filtering.\n- `string_list`: String array field.\n- `float`: Numeric field.\n- `integer`: Legacy numeric field from older indexes (pre-dating float normalization). Will not appear in new indexes.\n- `boolean`: Boolean field.\n\nFields in older indexes may omit `type` entirely. These are legacy metadata fields from before typed schemas were introduced.","required":["filterable"],"example":{"filterable":true},"properties":{"filterable":{"description":"Whether this field is indexed for metadata filtering.","type":"boolean","isRequired":true,"uniqueKey":"schema.fields.additionalProperties.oneOf.8.filterable","typeLabel":"boolean"}},"additionalProperties":false,"uniqueKey":"schema.fields.additionalProperties.oneOf.8","typeLabel":"Legacy metadata · object"}],"uniqueKey":"schema.fields.additionalProperties","typeLabel":"Dense vector · object | Sparse vector · object | Semantic text · object | String · object | String array · object | Float · object | Integer · object | Boolean · object | Legacy metadata · object"},"isRequired":true,"uniqueKey":"schema.fields","typeLabel":"object"}},"required":["fields"],"isRequired":true,"uniqueKey":"schema","typeLabel":"object"},"deletion_protection":{"description":"Whether [deletion protection](http://docs.pinecone.io/guides/manage-data/manage-indexes#configure-deletion-protection) is enabled/disabled for the index.\n\nPossible values: `disabled` or `enabled`.","default":"disabled","x-enum":["disabled","enabled"],"type":"string","isRequired":true,"uniqueKey":"deletion_protection","typeLabel":"string"},"private_host":{"example":"semantic-search-c01b5b5.svc.private.us-west1-gcp.pinecone.io","description":"The private endpoint URL of an index.","type":"string","uniqueKey":"private_host","typeLabel":"string"},"read_capacity":{"oneOf":[{"type":"object","title":"On-demand","description":"Response containing read capacity configuration","required":["mode","status"],"example":{"mode":"OnDemand","status":{"state":"Ready"}},"properties":{"mode":{"description":"The mode of the index. Possible values: `OnDemand` or `Dedicated`. Defaults to `OnDemand`. If set to `Dedicated`, `dedicated.node_type`, and `dedicated.scaling` must be specified.","type":"string","isRequired":true,"uniqueKey":"read_capacity.oneOf.0.mode","typeLabel":"string"},"status":{"description":"The current status of factors affecting the read capacity of a serverless index","type":"object","properties":{"state":{"description":"The `state` describes the overall status of factors relating to the read capacity of an index.\n\nAvailable values:\n- `Ready` is the state most of the time\n- `Scaling` if the number of replicas or shards has been recently updated by calling the [configure index endpoint](https://docs.pinecone.io/reference/api/2026-07/control-plane/configure_index)\n- `Migrating` if the index is being migrated to a new `node_type`\n- `Error` if there is an error with the read capacity configuration. In that case, see `error_message` for more details.","x-enum":["Ready","Scaling","Migrating","Error"],"type":"string","isRequired":true,"uniqueKey":"read_capacity.oneOf.0.status.state","typeLabel":"string"},"current_replicas":{"oneOf":[{"description":"The number of replicas. Each replica has dedicated compute resources and data storage. Increasing this number will increase the total throughput of the index. `null` for `OnDemand` indexes and for a `Dedicated` index that has not finished provisioning.","type":"integer","format":"int32","uniqueKey":"read_capacity.oneOf.0.status.current_replicas.oneOf.0","typeLabel":"integer\u003cint32>"},{"description":"The number of replicas. Each replica has dedicated compute resources and data storage. Increasing this number will increase the total throughput of the index. `null` for `OnDemand` indexes and for a `Dedicated` index that has not finished provisioning.","type":"null","format":"int32","uniqueKey":"read_capacity.oneOf.0.status.current_replicas.oneOf.1","typeLabel":"null"}],"uniqueKey":"read_capacity.oneOf.0.status.current_replicas","typeLabel":"integer\u003cint32> | null"},"current_shards":{"oneOf":[{"description":"The number of shards. Each shard has dedicated storage. Increasing shards alleviates index fullness. `null` for `OnDemand` indexes and for a `Dedicated` index that has not finished provisioning.","type":"integer","format":"int32","uniqueKey":"read_capacity.oneOf.0.status.current_shards.oneOf.0","typeLabel":"integer\u003cint32>"},{"description":"The number of shards. Each shard has dedicated storage. Increasing shards alleviates index fullness. `null` for `OnDemand` indexes and for a `Dedicated` index that has not finished provisioning.","type":"null","format":"int32","uniqueKey":"read_capacity.oneOf.0.status.current_shards.oneOf.1","typeLabel":"null"}],"uniqueKey":"read_capacity.oneOf.0.status.current_shards","typeLabel":"integer\u003cint32> | null"},"error_message":{"description":"An optional error message indicating any issues with your read capacity configuration","type":"string","uniqueKey":"read_capacity.oneOf.0.status.error_message","typeLabel":"string"}},"required":["state"],"isRequired":true,"uniqueKey":"read_capacity.oneOf.0.status","typeLabel":"object"}},"additionalProperties":false,"uniqueKey":"read_capacity.oneOf.0","typeLabel":"On-demand · object"},{"type":"object","title":"Dedicated","description":"Response containing read capacity configuration","required":["mode","dedicated","status"],"example":{"dedicated":{"manual":{"replicas":2,"shards":2},"node_type":"t1","scaling":"Manual"},"mode":"Dedicated","status":{"current_replicas":2,"current_shards":2,"state":"Ready"}},"properties":{"mode":{"description":"The mode of the index. 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