# Pinecone Docs

> Official Pinecone documentation for the vector database, Assistant, inference APIs, SDKs, and building production search and AI applications.

## Docs

- [Pinecone documentation](https://docs.pinecone.io/guides/get-started/overview.md): Pinecone is the vector database for AI agents and applications, built for semantic search, knowledge retrieval, and long-term memory at scale.
- [Quickstart](https://docs.pinecone.io/guides/get-started/quickstart.md): Add Pinecone to your AI agent or app in minutes. Build a knowledge retrieval agent, use your IDE assistant, or integrate the SDK directly.
- [Agentic IDEs and CLIs](https://docs.pinecone.io/guides/get-started/ai-coding-tools.md): Use Pinecone with agentic IDEs and CLIs like Claude Code, Gemini CLI, Cursor, and more.
- [Test Pinecone at scale](https://docs.pinecone.io/guides/get-started/test-at-scale.md): Test Pinecone with a real-world dataset and semantic search workload.
- [Concepts](https://docs.pinecone.io/guides/get-started/concepts.md): Understand concepts in Pinecone and how they relate to each other.
- [Architecture](https://docs.pinecone.io/guides/get-started/database-architecture.md): Learn how Pinecone's architecture enables fast, relevant vector search at any scale.
- [Indexing overview](https://docs.pinecone.io/guides/index-data/indexing-overview.md): Understand key concepts related to indexing data in Pinecone.
- [Create an index](https://docs.pinecone.io/guides/index-data/create-an-index.md): Create indexes for full-text, semantic, lexical, and hybrid search.
- [Data modeling](https://docs.pinecone.io/guides/index-data/data-modeling.md): Learn how to structure records for efficient data retrieval and management in Pinecone.
- [Data ingestion overview](https://docs.pinecone.io/guides/index-data/data-ingestion-overview.md): Learn about the different ways to ingest data into Pinecone.
- [Upsert records](https://docs.pinecone.io/guides/index-data/upsert-data.md): Add or update records in Pinecone indexes and manage data with namespaces.
- [Import records](https://docs.pinecone.io/guides/index-data/import-data.md): Import large datasets efficiently from Amazon S3, Google Cloud Storage, or Azure Blob Storage into Pinecone serverless indexes using object storage.
- [Check data freshness](https://docs.pinecone.io/guides/index-data/check-data-freshness.md): Monitor data freshness in Pinecone using log sequence numbers and vector counts.
- [Implement multitenancy](https://docs.pinecone.io/guides/index-data/implement-multitenancy.md): Use namespaces to isolate tenant data securely.
- [Dedicated Read Nodes](https://docs.pinecone.io/guides/index-data/dedicated-read-nodes.md): Dedicated read nodes use provisioned hardware for read operations, providing predictable, low-latency performance at high query volumes.
- [Search overview](https://docs.pinecone.io/guides/search/search-overview.md): Explore full-text, semantic, lexical, and hybrid search options.
- [Full-text search](https://docs.pinecone.io/guides/search/full-text-search.md): Upsert and search typed JSON documents in Pinecone with BM25 scoring, Lucene query syntax, dense and sparse vector ranking, and metadata filters.
- [Semantic search](https://docs.pinecone.io/guides/search/semantic-search.md): Find semantically similar records using dense vectors.
- [Lexical search](https://docs.pinecone.io/guides/search/lexical-search.md): Perform sparse-vector keyword retrieval against a custom sparse encoder.
- [Hybrid search](https://docs.pinecone.io/guides/search/hybrid-search.md): Combine semantic and lexical search for better results.
- [Filter by metadata](https://docs.pinecone.io/guides/search/filter-by-metadata.md): Narrow search results with metadata filtering.
- [Rerank results](https://docs.pinecone.io/guides/search/rerank-results.md): Improve the quality of results with reranking.
- [Increase search relevance](https://docs.pinecone.io/guides/optimize/increase-relevance.md): Learn techniques to improve search result quality.
- [Increase throughput](https://docs.pinecone.io/guides/optimize/increase-throughput.md): Learn techniques to improve data operation performance and query throughput.
- [Decrease latency](https://docs.pinecone.io/guides/optimize/decrease-latency.md): Learn techniques to decrease latency for search and upsert operations.
- [Save on costs](https://docs.pinecone.io/guides/optimize/save-on-costs.md): Learn techniques to reduce spend when ingesting data, querying, and operating indexes.
- [Target an index](https://docs.pinecone.io/guides/manage-data/target-an-index.md): Target an index by host or name for data operations such as upsert and query.
- [Manage serverless indexes](https://docs.pinecone.io/guides/manage-data/manage-indexes.md): List, describe, and configure serverless indexes.
- [Manage namespaces](https://docs.pinecone.io/guides/manage-data/manage-namespaces.md): Create and manage namespaces in serverless indexes.
- [Backups overview](https://docs.pinecone.io/guides/manage-data/backups-overview.md): Learn about backups of serverless indexes in Pinecone.
- [Back up an index](https://docs.pinecone.io/guides/manage-data/back-up-an-index.md): Create backups of serverless indexes for protection
- [Restore an index](https://docs.pinecone.io/guides/manage-data/restore-an-index.md): Restore serverless indexes from backup snapshots.
- [Update records](https://docs.pinecone.io/guides/manage-data/update-data.md): Update vectors and metadata for existing records
- [Delete records](https://docs.pinecone.io/guides/manage-data/delete-data.md): Delete records by ID or metadata filter from indexes
- [Fetch records](https://docs.pinecone.io/guides/manage-data/fetch-data.md): Retrieve complete records by ID or metadata filter.
- [List record IDs](https://docs.pinecone.io/guides/manage-data/list-record-ids.md): List the IDS of records in an index namespace.
- [Understanding cost](https://docs.pinecone.io/guides/manage-cost/understanding-cost.md): Understand how costs are incurred in Pinecone, including read units (RUs), write units (WUs), storage, egress, and embedding.
- [Manage cost](https://docs.pinecone.io/guides/manage-cost/manage-cost.md): Learn strategies for managing cost in Pinecone.
- [Monitor usage and costs](https://docs.pinecone.io/guides/manage-cost/monitor-usage-and-costs.md): Monitor usage and costs for your Pinecone organization and indexes.
- [Production checklist](https://docs.pinecone.io/guides/production/production-checklist.md): Prepare your indexes for production with best practices.
- [Bring your own cloud (BYOC)](https://docs.pinecone.io/guides/production/bring-your-own-cloud.md): Deploy Pinecone in your own cloud account (AWS, GCP, or Azure), with full control over your infrastructure
- [Security overview](https://docs.pinecone.io/guides/production/security-overview.md): Understand Pinecone's security features, including authentication, encryption, and audit logs.
- [Manage roles and access](https://docs.pinecone.io/guides/production/manage-rbac.md): Assign and manage roles for users, service accounts, and API keys using the Pinecone console or the Admin API.
- [Configure SSO with Okta](https://docs.pinecone.io/guides/production/configure-single-sign-on/okta.md): Configure SAML SSO with Okta for enterprise.
- [Manage roles with Okta](https://docs.pinecone.io/guides/production/configure-single-sign-on/okta-role-management.md): Automatically assign Pinecone organization and project roles from SAML attributes with Okta.
- [SCIM provisioning with Okta](https://docs.pinecone.io/guides/production/configure-single-sign-on/okta-scim-provisioning.md): Automatically provision members and roles from Okta to Pinecone over SCIM.
- [Configure customer-managed encryption keys](https://docs.pinecone.io/guides/production/configure-cmek.md): Use customer-managed encryption keys with AWS KMS.
- [Configure Private Endpoints](https://docs.pinecone.io/guides/production/configure-private-endpoints.md): Secure Pinecone with private endpoints using AWS PrivateLink or Azure Private Link.
- [Data deletion on Pinecone](https://docs.pinecone.io/guides/production/data-deletion.md): Understand Pinecone's secure data deletion process.
- [Configure audit logs](https://docs.pinecone.io/guides/production/configure-audit-logs.md): Enable audit logging to Amazon S3 for compliance
- [Error handling](https://docs.pinecone.io/guides/production/error-handling.md): Handle errors with retry logic and best practices.
- [Monitor performance](https://docs.pinecone.io/guides/production/monitoring.md): Monitor performance metrics in the Pinecone console or with Prometheus or Datadog.
- [CI/CD with Pinecone Local and GitHub Actions](https://docs.pinecone.io/guides/production/automated-testing.md): Test Pinecone integration with CI/CD workflows.
- [Upgrade your plan](https://docs.pinecone.io/guides/organizations/manage-billing/upgrade-billing-plan.md): Upgrade to a paid plan to access advanced features and limits.
- [Change your payment method](https://docs.pinecone.io/guides/organizations/manage-billing/change-payment-method.md): Update your billing payment method.
- [Account deactivation for non-payment](https://docs.pinecone.io/guides/organizations/manage-billing/non-payment-account-deactivation.md): Understand what happens when your account is deactivated for non-payment, including data retention and how to reactivate.
- [Downgrade your plan](https://docs.pinecone.io/guides/organizations/manage-billing/downgrade-billing-plan.md): Downgrade from a paid plan to the free Starter plan.
- [Download a usage report](https://docs.pinecone.io/guides/organizations/manage-billing/download-usage-report.md): Download detailed usage and cost reports.
- [Access your invoices](https://docs.pinecone.io/guides/organizations/manage-billing/access-your-invoices.md): View and download organization billing invoices.
- [Standard trial](https://docs.pinecone.io/guides/organizations/manage-billing/standard-trial.md): Get $300 credits for 21 days with the Standard plan trial.
- [Understanding organizations](https://docs.pinecone.io/guides/organizations/understanding-organizations.md): Understand organization structure, projects, and billing.
- [Manage organization members](https://docs.pinecone.io/guides/organizations/manage-organization-members.md): Add and manage organization members and roles.
- [Manage service accounts at the organization-level](https://docs.pinecone.io/guides/organizations/manage-service-accounts.md): Create service accounts for organization-level API access.
- [Understanding projects](https://docs.pinecone.io/guides/projects/understanding-projects.md): Learn about projects, environments, and member roles.
- [Create a project](https://docs.pinecone.io/guides/projects/create-a-project.md): Create a new Pinecone project in your organization.
- [Manage projects](https://docs.pinecone.io/guides/projects/manage-projects.md): View, rename, and delete projects in your organization.
- [Manage project members](https://docs.pinecone.io/guides/projects/manage-project-members.md): Add and manage project members with role-based access control.
- [Manage API keys](https://docs.pinecone.io/guides/projects/manage-api-keys.md): Create and manage API keys with custom permissions.
- [Manage service accounts at the project-level](https://docs.pinecone.io/guides/projects/manage-service-accounts.md): Enable service accounts for programmatic API access.
- [Integrate with Amazon S3](https://docs.pinecone.io/guides/operations/integrations/integrate-with-amazon-s3.md): Set up Amazon S3 integrationfor data import and audit logs.
- [Integrate with Google Cloud Storage](https://docs.pinecone.io/guides/operations/integrations/integrate-with-google-cloud-storage.md): Integrate Google Cloud Storage for bulk data import
- [Integrate with Azure Blob Storage](https://docs.pinecone.io/guides/operations/integrations/integrate-with-azure-blob-storage.md): Set up Azure Blob Storage integration for data import.
- [Manage storage integrations](https://docs.pinecone.io/guides/operations/integrations/manage-storage-integrations.md): Update and manage cloud storage integrations.
- [Use the Pinecone MCP server](https://docs.pinecone.io/guides/operations/mcp-server.md): Use Pinecone MCP server for AI agent integration.
- [Local development with Pinecone Local](https://docs.pinecone.io/guides/operations/local-development.md): Develop locally with an in-memory Pinecone emulator.
- [Understanding pod-based indexes](https://docs.pinecone.io/guides/indexes/pods/understanding-pod-based-indexes.md): Legacy documentation for Pinecone pod-based indexes. Pod indexes are no longer available to new customers as of August 2025. Serverless indexes are recommended for all new projects.
- [Migrate a pod-based index to serverless](https://docs.pinecone.io/guides/indexes/pods/migrate-a-pod-based-index-to-serverless.md): Complete guide to migrating a Pinecone pod-based index to serverless. Serverless indexes offer better performance, automatic scaling, and usage-based pricing with no minimum spend.
- [Choose a pod type and size](https://docs.pinecone.io/guides/indexes/pods/choose-a-pod-type-and-size.md): Legacy guide for selecting Pinecone pod types (s1, p1, p2) and sizes. Pod indexes are no longer available to new customers as of August 2025. Serverless indexes require no capacity planning.
- [Create a pod-based index](https://docs.pinecone.io/guides/indexes/pods/create-a-pod-based-index.md): Legacy instructions for creating Pinecone pod-based indexes. New customers cannot create pod indexes as of August 2025. See serverless index creation for current instructions.
- [Manage pod-based indexes](https://docs.pinecone.io/guides/indexes/pods/manage-pod-based-indexes.md): Legacy guide for managing Pinecone pod-based indexes. Pod indexes are no longer available to new customers as of August 2025. Serverless indexes are recommended for all new projects.
- [Scale pod-based indexes](https://docs.pinecone.io/guides/indexes/pods/scale-pod-based-indexes.md): Legacy guide for scaling Pinecone pod-based indexes. Pod indexes are no longer available to new customers as of August 2025. Serverless indexes scale automatically with no manual configuration.
- [Understanding collections](https://docs.pinecone.io/guides/indexes/pods/understanding-collections.md): Legacy documentation for Pinecone collections, a pod-only feature for creating static index snapshots. Collections are not available for serverless indexes.
- [Back up a pod-based index](https://docs.pinecone.io/guides/indexes/pods/back-up-a-pod-based-index.md): Legacy guide for backing up Pinecone pod-based indexes using collections. Collections are a pod-only feature not available for serverless indexes.
- [Restore a pod-based index](https://docs.pinecone.io/guides/indexes/pods/restore-a-pod-based-index.md): Legacy guide for restoring Pinecone pod-based indexes from collections. Pod indexes are no longer available to new customers as of August 2025.
- [API reference](https://docs.pinecone.io/reference/api/introduction.md): Pinecone REST API: Pinecone's APIs let you interact programmatically with your Pinecone account.
- [Authentication](https://docs.pinecone.io/reference/api/authentication.md): Pinecone REST API: All requests to Pinecone APIs must contain a valid API key for the target project.
- [API versioning](https://docs.pinecone.io/reference/api/versioning.md): Pinecone REST API: Pinecone's APIs are versioned to ensure that your applications continue to work as expected as the platform evolves.
- [Pinecone Database limits](https://docs.pinecone.io/reference/api/database-limits.md): Pinecone Database limits: This page describes different types of limits for Pinecone Database.
- [Known limitations](https://docs.pinecone.io/reference/api/known-limitations.md): Pinecone REST API: This page describes known limitations and feature restrictions in Pinecone.
- [Errors](https://docs.pinecone.io/reference/api/errors.md): Pinecone REST API: Pinecone uses conventional HTTP response codes to indicate the success or failure of an API request. In general, codes in the range.
- [Generate vectors](https://docs.pinecone.io/reference/api/2026-04/inference/generate-embeddings.md): Generate vector embeddings for input data. This endpoint uses Pinecone's [hosted embedding models](https://docs.pinecone.io/guides/index-data/create-an-index#embedding-models).
- [Rerank results](https://docs.pinecone.io/reference/api/2026-04/inference/rerank.md): Rerank results according to their relevance to a query.
- [List available models](https://docs.pinecone.io/reference/api/2026-04/inference/list_models.md): List the embedding and reranking models hosted by Pinecone.
- [Describe a model](https://docs.pinecone.io/reference/api/2026-04/inference/describe_model.md): Get a description of a model hosted by Pinecone.
- [Create an API key](https://docs.pinecone.io/reference/api/2026-04/admin/create_api_key.md): Create an API key for a project to authenticate Data Plane and Control Plane requests.
- [List API keys](https://docs.pinecone.io/reference/api/2026-04/admin/list_api_keys.md): List all API keys in a project.
- [Get API key details](https://docs.pinecone.io/reference/api/2026-04/admin/fetch_api_key.md): Get an API key's details, excluding its secret.
- [Update an API key](https://docs.pinecone.io/reference/api/2026-04/admin/update_api_key.md): Update an API key's name and roles.
- [Delete an API key](https://docs.pinecone.io/reference/api/2026-04/admin/delete_api_key.md): Delete an API key from a project.
- [Create a new project](https://docs.pinecone.io/reference/api/2026-04/admin/create_project.md): Create a new project.
- [List projects](https://docs.pinecone.io/reference/api/2026-04/admin/list_projects.md): List all projects in an organization.
- [Get project details](https://docs.pinecone.io/reference/api/2026-04/admin/fetch_project.md): Get a project's details.
- [Update a project](https://docs.pinecone.io/reference/api/2026-04/admin/update_project.md): Update a project's name, maximum number of Pods, or customer-managed encryption key (CMEK).
- [Delete a project](https://docs.pinecone.io/reference/api/2026-04/admin/delete_project.md): Delete a project and all its configuration; delete its indexes, assistants, backups, and collections first.
- [Create a service account](https://docs.pinecone.io/reference/api/2026-04/admin/create_service_account.md): Create a service account with optional initial role bindings; the client secret is returned only once.
- [List service accounts](https://docs.pinecone.io/reference/api/2026-04/admin/list_service_accounts.md): List service accounts in the caller's organization.
- [Get service account details](https://docs.pinecone.io/reference/api/2026-04/admin/fetch_service_account.md): Get a service account by ID; the client secret is returned only from create and rotate-secret requests.
- [Update a service account](https://docs.pinecone.io/reference/api/2026-04/admin/update_service_account.md): Update a service account's name; role bindings are managed through the role-binding endpoints.
- [Delete a service account](https://docs.pinecone.io/reference/api/2026-04/admin/delete_service_account.md): Delete a service account and its role bindings; tokens it minted are revoked within a few seconds.
- [Rotate a service account's OAuth client secret](https://docs.pinecone.io/reference/api/2026-04/admin/rotate_service_account_secret.md): Rotate a service account's OAuth client secret; the previous secret and its tokens are revoked within seconds and the new secret is returned only once.
- [Create an access token](https://docs.pinecone.io/reference/api/2026-04/admin/get_token.md): Obtain an access token for a service account using the OAuth2 client credentials flow. An access token is needed to authorize requests to the Pinecone Admin API. The host domain for OAuth endpoints is `login.pinecone.io`.
- [List users in the organization](https://docs.pinecone.io/reference/api/2026-04/admin/list_users.md): List users in the caller's organization, optionally filtered by email address.
- [Get user details](https://docs.pinecone.io/reference/api/2026-04/admin/fetch_user.md): Get a user in the caller's organization by ID.
- [Remove a user from the organization](https://docs.pinecone.io/reference/api/2026-04/admin/delete_user.md): Remove a user from the organization and revoke their role bindings; their Pinecone account is not deleted.
- [Invite a user to the organization](https://docs.pinecone.io/reference/api/2026-04/admin/create_invite.md): Invite a user to the organization by email and grant their initial role bindings.
- [List invites](https://docs.pinecone.io/reference/api/2026-04/admin/list_invites.md): List pending and expired invites in the caller's organization.
- [Get invite details](https://docs.pinecone.io/reference/api/2026-04/admin/fetch_invite.md): Get an invite in the caller's organization by ID.
- [Delete an invite](https://docs.pinecone.io/reference/api/2026-04/admin/delete_invite.md): Delete a pending or expired invite and its role bindings; to remove an accepted user, delete the user instead.
- [Resend an invite email](https://docs.pinecone.io/reference/api/2026-04/admin/resend_invite.md): Resend the invite email and extend its expiration to 7 days from now; limited to 100 emails per hour per organization.
- [Create a role binding](https://docs.pinecone.io/reference/api/2026-04/admin/create_role_binding.md): Grant a role to a principal at an organization or project scope.
- [List role bindings](https://docs.pinecone.io/reference/api/2026-04/admin/list_role_bindings.md): List role bindings in the caller's organization, optionally filtered by principal, resource, and role.
- [Get role binding details](https://docs.pinecone.io/reference/api/2026-04/admin/fetch_role_binding.md): Get a role binding in the caller's organization by ID.
- [Delete a role binding](https://docs.pinecone.io/reference/api/2026-04/admin/delete_role_binding.md): Delete a role binding; permissions are revoked when the deletion completes.
- [Pinecone SDKs overview](https://docs.pinecone.io/reference/pinecone-sdks.md): Browse official Pinecone SDKs for Python, Node.js, Java, and Go, including the version mappings between SDK releases and API versions.
- [Pinecone Python SDK](https://docs.pinecone.io/reference/sdks/python/overview.md): Install and use the Pinecone SDK for Pinecone Python SDK: auth, typed clients, and API operations. For installation instructions, usage examples, and.
- [Reference](https://docs.pinecone.io/reference/sdks/python/reference.md): Browse the Pinecone SDK reference for Reference: types and methods.
- [Pinecone Node.js SDK](https://docs.pinecone.io/reference/sdks/node/overview.md): Install and use the Pinecone SDK for Pinecone Node.js SDK: auth, typed clients, and API operations. For installation instructions, usage examples, and.
- [Reference](https://docs.pinecone.io/reference/sdks/node/reference.md): Browse the Pinecone SDK reference for Reference: types and methods.
- [Pinecone Java SDK](https://docs.pinecone.io/reference/sdks/java/overview.md): Install and use the Pinecone SDK for Pinecone Java SDK: auth, typed clients, and API operations. For installation instructions and usage examples, see the.
- [Reference](https://docs.pinecone.io/reference/sdks/java/reference.md): Browse the Pinecone SDK reference for Reference: types and methods.
- [OpenTelemetry support](https://docs.pinecone.io/reference/sdks/java/open-telemetry.md): Monitor Pinecone Java SDK operations with OpenTelemetry metrics, including latency breakdowns and error tracking.
- [Pinecone Go SDK](https://docs.pinecone.io/reference/sdks/go/overview.md): Install and use the Pinecone SDK for Pinecone Go SDK: auth, typed clients, and API operations. For installation instructions and usage examples, see the Go.
- [Reference](https://docs.pinecone.io/reference/sdks/go/reference.md): Browse the Pinecone SDK reference for Reference: types and methods.
- [CLI quickstart](https://docs.pinecone.io/reference/cli/quickstart.md): Pinecone CLI: The Pinecone CLI ( ) lets you manage Pinecone resources directly from your terminal.
- [CLI command reference](https://docs.pinecone.io/reference/cli/command-reference.md): CLI command reference: This document provides a complete reference for all Pinecone CLI commands.
- [CLI authentication](https://docs.pinecone.io/reference/cli/authentication.md): Pinecone CLI: This document describes how to authenticate the Pinecone CLI to manage your Pinecone resources.
- [CLI target context](https://docs.pinecone.io/reference/cli/target-context.md): Pinecone CLI: The CLI's **target context** determines which organization and project your commands operate on. You must authenticate before setting target.
- [Spark-Pinecone connector](https://docs.pinecone.io/reference/tools/pinecone-spark-connector.md): Pinecone data tools: Use the connector to efficiently create, ingest, and update vector embeddings at scale with Databricks and Pinecone.
- [List indexes](https://docs.pinecone.io/reference/api/2026-04/control-plane/list_indexes.md): List all indexes in a project.
- [Create an index](https://docs.pinecone.io/reference/api/2026-04/control-plane/create_index.md): Create a Pinecone index. This is where you specify the measure of similarity, the dimension of vectors to be stored in the index, which cloud provider you would like to deploy with, and more. To restore from a backup, set `spec.serverless.source_backup_id` and specify the target `cloud` and `region`…
- [Create an index with integrated embedding](https://docs.pinecone.io/reference/api/2026-04/control-plane/create_for_model.md): Create an index with integrated embedding. With 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/referenc…
- [Describe an index](https://docs.pinecone.io/reference/api/2026-04/control-plane/describe_index.md): Get a description of an index.
- [Delete an index](https://docs.pinecone.io/reference/api/2026-04/control-plane/delete_index.md): Delete an existing index.
- [Configure an index](https://docs.pinecone.io/reference/api/2026-04/control-plane/configure_index.md): Configure an existing index. For guidance and examples, see [Manage indexes](https://docs.pinecone.io/guides/manage-data/manage-indexes).
- [Get index stats](https://docs.pinecone.io/reference/api/2026-04/data-plane/describeindexstats.md): Return statistics about the contents of an index, including the vector count per namespace, the number of dimensions, and the index fullness.
- [List namespaces](https://docs.pinecone.io/reference/api/2026-04/data-plane/listnamespaces.md): List all namespaces in a serverless index.
- [Create a namespace](https://docs.pinecone.io/reference/api/2026-04/data-plane/createnamespace.md): Create a namespace in a serverless index.
- [Describe a namespace](https://docs.pinecone.io/reference/api/2026-04/data-plane/describenamespace.md): Describe a namespace in a serverless index, including the total number of vectors in the namespace.
- [Delete a namespace](https://docs.pinecone.io/reference/api/2026-04/data-plane/deletenamespace.md): Delete a namespace from a serverless index. Deleting a namespace is irreversible; all data in the namespace is permanently deleted.
- [Upsert records](https://docs.pinecone.io/reference/api/2026-04/data-plane/upsert.md): Upsert records into a namespace. If a new value is upserted for an existing record ID, it will overwrite the previous value.
- [Upsert text](https://docs.pinecone.io/reference/api/2026-04/data-plane/upsert_records.md): Upsert text into a namespace. Pinecone converts the text to vectors automatically using the hosted embedding model associated with the index.
- [Fetch records](https://docs.pinecone.io/reference/api/2026-04/data-plane/fetch.md): Look up and return records by ID from a single namespace. The returned records include the vector data and/or metadata. For on-demand indexes, since vector values are retrieved from object storage, fetch operations may have increased latency. If you only need metadata or IDs, consider using the quer…
- [Fetch records by metadata](https://docs.pinecone.io/reference/api/2026-04/data-plane/fetch_by_metadata.md): Look up and return records by metadata from a single namespace. The returned records include the vector data and metadata. For guidance and examples, see [Fetch data](https://docs.pinecone.io/guides/manage-data/fetch-data).
- [Update a record](https://docs.pinecone.io/reference/api/2026-04/data-plane/update.md): Update records by ID or by metadata in a namespace. Updating by ID changes the vector and/or metadata of a single record. Updating by metadata changes metadata across multiple records using a metadata filter. If a vector value is included, it will overwrite the previous value. If `set_metadata` is i…
- [Delete records](https://docs.pinecone.io/reference/api/2026-04/data-plane/delete.md): Delete records by id or by metadata from a single namespace.
- [List record IDs](https://docs.pinecone.io/reference/api/2026-04/data-plane/list.md): List the IDs of records in a single namespace of a serverless index. An optional prefix can be passed to limit the results to IDs with a common prefix.
- [Search with a vector](https://docs.pinecone.io/reference/api/2026-04/data-plane/query.md): Search a namespace using a query vector. It retrieves the ids of the most similar items in a namespace, along with their similarity scores.
- [Search with text](https://docs.pinecone.io/reference/api/2026-04/data-plane/search_records.md): 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.
- [Start import](https://docs.pinecone.io/reference/api/2026-04/data-plane/start_import.md): Start an asynchronous import of vectors from object storage into an index.
- [List imports](https://docs.pinecone.io/reference/api/2026-04/data-plane/list_imports.md): List all recent and ongoing import operations.
- [Describe an import](https://docs.pinecone.io/reference/api/2026-04/data-plane/describe_import.md): Return details of a specific import operation.
- [Cancel an import](https://docs.pinecone.io/reference/api/2026-04/data-plane/cancel_import.md): Cancel an import operation if it is not yet finished. It has no effect if the operation is already finished.
- [Create a backup of an index](https://docs.pinecone.io/reference/api/2026-04/control-plane/create_backup.md): Create a backup of an index.
- [List backups for all indexes in a project](https://docs.pinecone.io/reference/api/2026-04/control-plane/list_project_backups.md): List all backups for a project.
- [List backups for an index](https://docs.pinecone.io/reference/api/2026-04/control-plane/list_index_backups.md): When `include_deleted` is false (or omitted), `index_name` must resolve to an active index in the project. If no active index by that name exists—including the case where only deleted indexes have used the name—the API returns **404**, not an empty list. When `include_deleted` is true, the API retur…
- [Describe a backup](https://docs.pinecone.io/reference/api/2026-04/control-plane/describe_backup.md): Get a description of a backup.
- [Delete a backup](https://docs.pinecone.io/reference/api/2026-04/control-plane/delete_backup.md): Delete a backup.
- [Create an index from a backup](https://docs.pinecone.io/reference/api/2026-04/control-plane/create_index_from_backup.md): Create an index from a backup. For serverless backups, you can optionally set `read_capacity` so the restored index is created with dedicated read nodes (DRN) instead of defaulting to on-demand capacity.
- [List restore jobs](https://docs.pinecone.io/reference/api/2026-04/control-plane/list_restore_jobs.md): List all restore jobs for a project.
- [Describe a restore job](https://docs.pinecone.io/reference/api/2026-04/control-plane/describe_restore_job.md): Get a description of a restore job.
- [List collections](https://docs.pinecone.io/reference/api/2026-04/control-plane/list_collections.md): List all collections in a project. Serverless indexes do not support collections.
- [Create a collection](https://docs.pinecone.io/reference/api/2026-04/control-plane/create_collection.md): Create a Pinecone collection.    Serverless indexes do not support collections.
- [Describe a collection](https://docs.pinecone.io/reference/api/2026-04/control-plane/describe_collection.md): Get a description of a collection. Serverless indexes do not support collections.
- [Delete a collection](https://docs.pinecone.io/reference/api/2026-04/control-plane/delete_collection.md): Delete an existing collection. Serverless indexes do not support collections.
- [Create backup schedule](https://docs.pinecone.io/reference/api/2026-04/control-plane/create_backup_schedule.md): Create a recurring backup schedule for an index.
- [List backup schedules](https://docs.pinecone.io/reference/api/2026-04/control-plane/list_backup_schedules.md): List all backup schedules for an index.
- [Describe backup schedule](https://docs.pinecone.io/reference/api/2026-04/control-plane/describe_backup_schedule.md): Get details of a specific backup schedule.
- [Update backup schedule](https://docs.pinecone.io/reference/api/2026-04/control-plane/update_backup_schedule.md): Update a backup schedule.
- [Delete backup schedule](https://docs.pinecone.io/reference/api/2026-04/control-plane/delete_backup_schedule.md): Delete a backup schedule.
- [List backup schedule history](https://docs.pinecone.io/reference/api/2026-04/control-plane/list_backup_schedule_history.md): List the execution history for a backup schedule.
- [Notebooks](https://docs.pinecone.io/examples/notebooks.md): Runnable Colab notebooks covering semantic search, lexical search, hybrid search, RAG, embeddings, reranking, and data ingestion with Pinecone.
- [Sample apps](https://docs.pinecone.io/examples/sample-apps.md): Full-stack sample applications built with Pinecone: semantic search over PDFs, multi-tenant RAG with namespace isolation, multimodal search, and Assistant chat.
- [Reference architectures](https://docs.pinecone.io/examples/reference-architectures.md): Official AWS reference architecture for building high-scale production systems with Pinecone, including Pulumi IaC, documentation, and video tutorial.
- [Model Gallery](https://docs.pinecone.io/models/overview.md): Pinecone integrations enable you to build and deploy AI applications faster and more efficiently. Integrate Pinecone with your favorite frameworks, data sources, and infrastructure providers.
- [Integrations](https://docs.pinecone.io/integrations/overview.md): Pinecone integrations enable you to build and deploy AI applications faster and more efficiently. Integrate Pinecone with your favorite frameworks, data sources, and infrastructure providers.
- [Agent Skills](https://docs.pinecone.io/integrations/agent-skills.md): Connect Pinecone and Agent Skills to ship vector search and RAG: embed, index, and query at scale with managed infrastructure.
- [Claude Code Plugin](https://docs.pinecone.io/integrations/claude-code.md): Integrate Pinecone with Claude Code Plugin for vector search, RAG, and production AI workloads.
- [Cursor Plugin](https://docs.pinecone.io/integrations/cursor.md): Integrate Pinecone with the Cursor plugin for vector search, RAG, and production AI workloads.
- [Gemini CLI Extension](https://docs.pinecone.io/integrations/gemini-cli.md): Integrate Pinecone with Gemini CLI Extension for vector search, RAG, and production AI workloads.
- [Airbyte](https://docs.pinecone.io/integrations/airbyte.md): Connect Pinecone and Airbyte to ship vector search and RAG: embed, index, and query at scale with managed infrastructure.
- [Apify](https://docs.pinecone.io/integrations/apify.md): Connect Pinecone and Apify to ship vector search and RAG: embed, index, and query at scale with managed infrastructure.
- [Aryn](https://docs.pinecone.io/integrations/aryn.md): Connect Pinecone and Aryn to ship vector search and RAG: embed, index, and query at scale with managed infrastructure.
- [Box](https://docs.pinecone.io/integrations/box.md): Connect Pinecone and Box to ship vector search and RAG: embed, index, and query at scale with managed infrastructure.
- [Confluent](https://docs.pinecone.io/integrations/confluent.md): Connect Pinecone and Confluent to ship vector search and RAG: embed, index, and query at scale with managed infrastructure.
- [Databricks](https://docs.pinecone.io/integrations/databricks.md): Connect Pinecone and Databricks to ship vector search and RAG: embed, index, and query at scale with managed infrastructure.
- [Datavolo](https://docs.pinecone.io/integrations/datavolo.md): Connect Pinecone and Datavolo to ship vector search and RAG: embed, index, and query at scale with managed infrastructure.
- [Estuary](https://docs.pinecone.io/integrations/estuary.md): Connect Pinecone and Estuary to ship vector search and RAG: embed, index, and query at scale with managed infrastructure.
- [Fleak](https://docs.pinecone.io/integrations/fleak.md): Connect Pinecone and Fleak to ship vector search and RAG: embed, index, and query at scale with managed infrastructure.
- [FlowiseAI](https://docs.pinecone.io/integrations/flowise.md): Connect Pinecone and FlowiseAI to ship vector search and RAG: embed, index, and query at scale with managed infrastructure.
- [Gathr](https://docs.pinecone.io/integrations/gathr.md): Connect Pinecone and Gathr to ship vector search and RAG: embed, index, and query at scale with managed infrastructure.
- [Matillion](https://docs.pinecone.io/integrations/matillion.md): Connect Pinecone and Matillion to ship vector search and RAG: embed, index, and query at scale with managed infrastructure.
- [Nexla](https://docs.pinecone.io/integrations/nexla.md): Connect Pinecone and Nexla to ship vector search and RAG: embed, index, and query at scale with managed infrastructure.
- [Redpanda](https://docs.pinecone.io/integrations/redpanda.md): Connect Pinecone and Redpanda to ship vector search and RAG: embed, index, and query at scale with managed infrastructure.
- [Snowflake](https://docs.pinecone.io/integrations/snowflake.md): Connect Pinecone and Snowflake to ship vector search and RAG: embed, index, and query at scale with managed infrastructure.
- [StreamNative](https://docs.pinecone.io/integrations/streamnative.md): Connect Pinecone and StreamNative to ship vector search and RAG: embed, index, and query at scale with managed infrastructure.
- [Unstructured](https://docs.pinecone.io/integrations/unstructured.md): Connect Pinecone and Unstructured to ship vector search and RAG: embed, index, and query at scale with managed infrastructure.
- [AI Engine](https://docs.pinecone.io/integrations/ai-engine.md): Connect Pinecone and AI Engine to ship vector search and RAG: embed, index, and query at scale with managed infrastructure.
- [Amazon Bedrock](https://docs.pinecone.io/integrations/amazon-bedrock.md): Connect Pinecone and Amazon Bedrock to ship vector search and RAG: embed, index, and query at scale with managed infrastructure.
- [Amazon SageMaker](https://docs.pinecone.io/integrations/amazon-sagemaker.md): Integrate Pinecone with Amazon SageMaker for vector search, RAG, and production AI workloads.
- [Cloudera AI](https://docs.pinecone.io/integrations/cloudera.md): Connect Pinecone and Cloudera AI to ship vector search and RAG: embed, index, and query at scale with managed infrastructure.
- [Context Data](https://docs.pinecone.io/integrations/context-data.md): Connect Pinecone and Context Data to ship vector search and RAG: embed, index, and query at scale with managed infrastructure.
- [Genkit](https://docs.pinecone.io/integrations/genkit.md): Connect Pinecone and Genkit to ship vector search and RAG: embed, index, and query at scale with managed infrastructure.
- [Haystack](https://docs.pinecone.io/integrations/haystack.md): Connect Pinecone and Haystack to ship vector search and RAG: embed, index, and query at scale with managed infrastructure.
- [Instill AI](https://docs.pinecone.io/integrations/instill.md): Connect Pinecone and Instill AI to ship vector search and RAG: embed, index, and query at scale with managed infrastructure.
- [LangChain](https://docs.pinecone.io/integrations/langchain.md): Connect Pinecone and LangChain to ship vector search and RAG: embed, index, and query at scale with managed infrastructure.
- [LlamaIndex](https://docs.pinecone.io/integrations/llamaindex.md): Connect Pinecone and LlamaIndex to ship vector search and RAG: embed, index, and query at scale with managed infrastructure.
- [n8n](https://docs.pinecone.io/integrations/n8n.md): Connect Pinecone and n8n to ship vector search and RAG: embed, index, and query at scale with managed infrastructure.
- [Nuclia](https://docs.pinecone.io/integrations/nuclia.md): Connect Pinecone and Nuclia to ship vector search and RAG: embed, index, and query at scale with managed infrastructure.
- [OctoAI](https://docs.pinecone.io/integrations/octoai.md): Connect Pinecone and OctoAI to ship vector search and RAG: embed, index, and query at scale with managed infrastructure.
- [VoltAgent](https://docs.pinecone.io/integrations/voltagent.md): Connect Pinecone and VoltAgent to ship vector search and RAG: embed, index, and query at scale with managed infrastructure.
- [AWS Marketplace](https://docs.pinecone.io/integrations/aws-marketplace.md): Integrate Pinecone with AWS Marketplace for vector search, RAG, and production AI workloads.
- [GitHub Copilot](https://docs.pinecone.io/integrations/github-copilot.md): Integrate Pinecone with GitHub Copilot for vector search, RAG, and production AI workloads.
- [Google Cloud Marketplace](https://docs.pinecone.io/integrations/google-cloud-marketplace.md): Integrate Pinecone with Google Cloud Marketplace for vector search, RAG, and production AI workloads.
- [Microsoft Marketplace](https://docs.pinecone.io/integrations/microsoft-marketplace.md): Integrate Pinecone with Microsoft Marketplace for vector search, RAG, and production AI workloads.
- [Pulumi](https://docs.pinecone.io/integrations/pulumi.md): Connect Pinecone and Pulumi to ship vector search and RAG: embed, index, and query at scale with managed infrastructure.
- [Terraform](https://docs.pinecone.io/integrations/terraform.md): Connect Pinecone and Terraform to ship vector search and RAG: embed, index, and query at scale with managed infrastructure.
- [Vercel](https://docs.pinecone.io/integrations/vercel.md): Connect Pinecone and Vercel to ship vector search and RAG: embed, index, and query at scale with managed infrastructure.
- [Zapier](https://docs.pinecone.io/integrations/zapier.md): Connect Pinecone and Zapier to ship vector search and RAG: embed, index, and query at scale with managed infrastructure.
- [Anyscale](https://docs.pinecone.io/integrations/anyscale.md): Connect Pinecone and Anyscale to ship vector search and RAG: embed, index, and query at scale with managed infrastructure.
- [Cohere](https://docs.pinecone.io/integrations/cohere.md): Connect Pinecone and Cohere to ship vector search and RAG: embed, index, and query at scale with managed infrastructure.
- [Voyage AI](https://docs.pinecone.io/integrations/voyage.md): Connect Pinecone and Voyage AI to ship vector search and RAG: embed, index, and query at scale with managed infrastructure.
- [Hugging Face Inference Endpoints](https://docs.pinecone.io/integrations/hugging-face-inference-endpoints.md): Integrate Pinecone with Hugging Face Inference Endpoints for vector search, RAG, and production AI workloads.
- [Jina AI](https://docs.pinecone.io/integrations/jina.md): Connect Pinecone and Jina AI to ship vector search and RAG: embed, index, and query at scale with managed infrastructure.
- [OpenAI](https://docs.pinecone.io/integrations/openai.md): Connect Pinecone and OpenAI to ship vector search and RAG: embed, index, and query at scale with managed infrastructure.
- [Twelve Labs](https://docs.pinecone.io/integrations/twelve-labs.md): Connect Pinecone and Twelve Labs to ship vector search and RAG: embed, index, and query at scale with managed infrastructure.
- [Datadog](https://docs.pinecone.io/integrations/datadog.md): Connect Pinecone and Datadog to ship vector search and RAG: embed, index, and query at scale with managed infrastructure.
- [Langtrace](https://docs.pinecone.io/integrations/langtrace.md): Connect Pinecone and Langtrace to ship vector search and RAG: embed, index, and query at scale with managed infrastructure.
- [New Relic](https://docs.pinecone.io/integrations/new-relic.md): Connect Pinecone and New Relic to ship vector search and RAG: embed, index, and query at scale with managed infrastructure.
- [Traceloop](https://docs.pinecone.io/integrations/traceloop.md): Connect Pinecone and Traceloop to ship vector search and RAG: embed, index, and query at scale with managed infrastructure.
- [TruLens](https://docs.pinecone.io/integrations/trulens.md): Connect Pinecone and TruLens to ship vector search and RAG: embed, index, and query at scale with managed infrastructure.
- [Integration ecosystem](https://docs.pinecone.io/integrations/build-integration/integration-ecosystem.md): Understand how native Pinecone integrations are built with public SDKs and APIs, and how curated listings on the Integrations hub are reviewed for partner support.
- [Attribute usage to your integration](https://docs.pinecone.io/integrations/build-integration/attribute-usage-to-your-integration.md): Attribute Pinecone SDK and REST usage to your integration with source tags and User-Agent values so support and analytics can trace traffic to your product.
- [Connect your users to Pinecone](https://docs.pinecone.io/integrations/build-integration/connect-your-users-to-pinecone.md): Embed a Connect to Pinecone flow in your app or notebook so users can sign in, choose a project, and receive an API key without leaving your integration.
- [Contact Support](https://docs.pinecone.io/troubleshooting/contact-support.md): Troubleshoot “Contact Support” in Pinecone: Pinecone Support is available to customers on the Builder and Standard billing plans.
- [How to work with Support](https://docs.pinecone.io/troubleshooting/how-to-work-with-support.md): Troubleshoot “How to work with Support” in Pinecone: There are several best practices for working with Pinecone Support that can lead to faster resolutions.
- [Pinecone Support SLAs](https://docs.pinecone.io/troubleshooting/pinecone-support-slas.md): Troubleshoot “Pinecone Support SLAs” in Pinecone: New first-response SLAs went into effect on September 16th, 2024. See the pricing page for more details.
- [Login code issues](https://docs.pinecone.io/troubleshooting/login-code-issues.md): Troubleshoot “Login code issues” in Pinecone: If the email token you received from Pinecone is not accepted when logging in there may be a few different.
- [Custom data processing agreements](https://docs.pinecone.io/troubleshooting/custom-data-processing-agreements.md): Troubleshoot “Custom data processing agreements” in Pinecone: If you need a data processing agreement (DPA) with Pinecone you can get started by filling out.
- [Delete your organization](https://docs.pinecone.io/troubleshooting/delete-your-organization.md): Troubleshoot “Delete your organization” in Pinecone: If you want to delete your Pinecone organization entirely, you'll need to delete all projects, which.
- [Delete your account](https://docs.pinecone.io/troubleshooting/delete-your-account.md): Troubleshoot “Delete your account” in Pinecone: To delete your Pinecone account, you need to remove your user from all organizations and delete any.
- [Billing disputes and refunds](https://docs.pinecone.io/troubleshooting/billing-disputes-and-refunds.md): Troubleshoot “Billing disputes and refunds” in Pinecone: As a rule, Pinecone does not offer refunds for unused indexes. If you use a pod-based index, we.
- [Wait for index creation to be complete](https://docs.pinecone.io/troubleshooting/wait-for-index-creation.md): The Python SDK and the REST API are designed to interact with the first system during index creation but not the second.
- [Restrictions on index names](https://docs.pinecone.io/troubleshooting/restrictions-on-index-names.md): Troubleshoot “Restrictions on index names” in Pinecone: There are two main restrictions on index names in Pinecone: character restrictions and a maximum.
- [Return all vectors in an index](https://docs.pinecone.io/troubleshooting/return-all-vectors-in-an-index.md): Troubleshoot “Return all vectors in an index” in Pinecone: Pinecone is designed to find vectors that are similar to a given set of conditions, either by.
- [Embedding values changed when upserted](https://docs.pinecone.io/troubleshooting/embedding-values-changed-when-upserted.md): Troubleshoot “Embedding values changed when upserted” in Pinecone: There are two distinct cases in which you might notice that the values of your embeddings.
- [Limitations of querying by ID](https://docs.pinecone.io/troubleshooting/limitations-of-querying-by-id.md): Understand why querying by record ID can omit that ID under ANN search, and when to use fetch or metadata filters to retrieve a specific vector reliably.
- [Index creation error - missing spec parameter](https://docs.pinecone.io/troubleshooting/index-creation-error-missing-spec.md): Troubleshoot “Index creation error - missing spec parameter” in Pinecone: Using the new API, creating an index requires passing appropriate values into the.
- [Serverless index creation error - max serverless indexes](https://docs.pinecone.io/troubleshooting/index-creation-error-max-serverless.md): Troubleshoot “Serverless index creation error - max serverless indexes” in Pinecone: Each project is limited to 20 serverless indexes. Trying to create more.
- [Serverless index connection errors](https://docs.pinecone.io/troubleshooting/serverless-index-connection-errors.md): Troubleshoot “Serverless index connection errors” in Pinecone: To connect to a serverless index, you must use an updated Pinecone client. Trying to connect.
- [Error: Handshake read failed when connecting](https://docs.pinecone.io/troubleshooting/error-handshake-read-failed.md): Troubleshoot “Error: Handshake read failed when connecting” in Pinecone: When trying to connect to Pinecone server, some users may receive an error message.
- [PineconeAttribute errors with LangChain](https://docs.pinecone.io/troubleshooting/pinecone-attribute-errors-with-langchain.md): Troubleshoot “PineconeAttribute errors with LangChain” in Pinecone: When using an outdated version of LangChain, you may encounter errors like the following:
- [Error: Cannot import name 'Pinecone' from 'pinecone'](https://docs.pinecone.io/troubleshooting/error-cannot-import-name-pinecone.md): Troubleshoot “Error: Cannot import name 'Pinecone' from 'pinecone'” in Pinecone: When using an older version of the Python SDK (earlier than 3.0.0), trying.
- [Python AttributeError: module pinecone has no attribute init](https://docs.pinecone.io/troubleshooting/module-pinecone-has-no-attribute-init.md): Troubleshoot “Python AttributeError: module pinecone has no attribute init” in Pinecone: If you are using Pinecone serverless and getting the error , first.
- [Node.js Troubleshooting](https://docs.pinecone.io/troubleshooting/nodejs-troubleshooting.md): Troubleshoot “Node.js Troubleshooting” in Pinecone: There could be several reasons why a Node.js application works in development mode but not in deployment.
- [CORS Issues](https://docs.pinecone.io/troubleshooting/cors-issues.md): Troubleshoot “CORS Issues” in Pinecone: Cross-Origin Resource Sharing (CORS) is an HTTP-header based security feature that
- [Debug model vs. Pinecone recall issues](https://docs.pinecone.io/troubleshooting/debug-model-vs-pinecone-recall-issues.md): Troubleshoot “Debug model vs. Pinecone recall issues” in Pinecone: Before starting, establish an evaluation framework for your model and Pinecone recall.
- [Unable to pip install](https://docs.pinecone.io/troubleshooting/unable-to-pip-install.md): Resolve pip install issues for the Pinecone Python SDK: use pip3 on Python 3.x, choose pinecone[grpc] or plain pinecone for HTTP, and upgrade to the latest release.
- [2026 releases](https://docs.pinecone.io/release-notes/2026.md): Pinecone release notes — 2026 releases:
- [2025 releases](https://docs.pinecone.io/release-notes/2025.md): Pinecone release notes — 2025 releases:
- [2024 releases](https://docs.pinecone.io/release-notes/2024.md): Pinecone release notes — 2024 releases:
- [2023 releases](https://docs.pinecone.io/release-notes/2023.md): Pinecone release notes — 2023 releases:
- [2022 releases](https://docs.pinecone.io/release-notes/2022.md): Pinecone release notes — 2022 releases:
- [Feature availability](https://docs.pinecone.io/release-notes/feature-availability.md): Pinecone release notes — Feature availability:
- [Pinecone Assistant](https://docs.pinecone.io/guides/assistant/overview.md): Pinecone Assistant is a service that allow you to build production-grade chat and agent-based applications quickly.
- [Pinecone Assistant: SDK quickstart](https://docs.pinecone.io/guides/assistant/quickstart/sdk-quickstart.md): Use a Pinecone SDK to create an assistant, upload documents, and chat with the assistant.
- [Pinecone Assistant: n8n quickstart](https://docs.pinecone.io/guides/assistant/quickstart/n8n-quickstart.md): Create an n8n workflow to chat with documents using Pinecone Assistant and OpenAI.
- [Pricing and limits](https://docs.pinecone.io/guides/assistant/pricing-and-limits.md): Understand Pinecone Assistant pricing and service limits.
- [Create an assistant](https://docs.pinecone.io/guides/assistant/create-assistant.md): Create and deploy a Pinecone Assistant with uploaded files for context.
- [Manage assistants](https://docs.pinecone.io/guides/assistant/manage-assistants.md): View, update, and delete, and check the status of assistants.
- [Files in Pinecone Assistant](https://docs.pinecone.io/guides/assistant/files-overview.md): Understand supported file types and metadata in Pinecone Assistant.
- [Upload files](https://docs.pinecone.io/guides/assistant/upload-files.md): Upload local files to an assistant.
- [Multimodal context for assistants](https://docs.pinecone.io/guides/assistant/multimodal.md): Process images and charts in PDFs with multimodal assistants.
- [Manage files](https://docs.pinecone.io/guides/assistant/manage-files.md): List, check status, and delete files from your assistant.
- [Chat through the standard interface](https://docs.pinecone.io/guides/assistant/chat-with-assistant.md): Chat with your assistant using the standard interface and API.
- [Chat through the OpenAI-compatible interface](https://docs.pinecone.io/guides/assistant/chat-through-the-openai-compatible-interface.md): Integrate OpenAI-compatible chat interface with Pinecone Assistant.
- [Evaluation overview](https://docs.pinecone.io/guides/assistant/evaluation-overview.md): Learn about evaluating the correctness and completeness of assistant responses.
- [Evaluate answers](https://docs.pinecone.io/guides/assistant/evaluate-answers.md): Measure assistant response quality with LLM-based evaluation.
- [Context snippets overview](https://docs.pinecone.io/guides/assistant/context-snippets-overview.md): Retrieve context snippets from files uploaded to your assistant.
- [Retrieve context snippets](https://docs.pinecone.io/guides/assistant/retrieve-context-snippets.md): Access relevant context and citations from Pinecone Assistant.
- [Use an Assistant MCP server](https://docs.pinecone.io/guides/assistant/mcp-server.md): Connect AI agents to Pinecone Assistant via Model Context Protocol.
- [Upgrade your plan](https://docs.pinecone.io/guides/assistant/admin/upgrade-billing-plan.md): Upgrade to a paid plan to access advanced features and limits.
- [Change your payment method](https://docs.pinecone.io/guides/assistant/admin/change-payment-method.md): Update billing payment method for your organization.
- [Downgrade your plan](https://docs.pinecone.io/guides/assistant/admin/downgrade-billing-plan.md): Downgrade from a paid plan to the free Starter plan.
- [Download a usage report](https://docs.pinecone.io/guides/assistant/admin/download-usage-report.md): Export organization usage and cost reports.
- [Access your invoices](https://docs.pinecone.io/guides/assistant/admin/access-your-invoices.md): View and download billing invoices from Pinecone.
- [Security overview](https://docs.pinecone.io/guides/assistant/admin/security-overview.md): Understand Pinecone's security features, including authentication, encryption, and audit logs.
- [Manage roles and access](https://docs.pinecone.io/guides/assistant/admin/manage-rbac.md): Assign and manage roles for users, service accounts, and API keys using the Pinecone console or the Admin API.
- [Configure SSO with Okta](https://docs.pinecone.io/guides/assistant/admin/configure-sso-with-okta.md): Enable SSO authentication using Okta integration.
- [Configure audit logs](https://docs.pinecone.io/guides/assistant/admin/configure-audit-logs.md): Track user and API actions with audit log configuration.
- [Organizations overview](https://docs.pinecone.io/guides/assistant/admin/organizations-overview.md): Understand organization structure, projects, and billing.
- [Monitor usage and cost](https://docs.pinecone.io/guides/assistant/admin/monitor-spend-and-usage.md): Set monthly spend alerts and monitor usage across your organization.
- [Manage organization members](https://docs.pinecone.io/guides/assistant/admin/manage-organization-members.md): Invite and control organization member access levels.
- [Manage service accounts at the organization-level](https://docs.pinecone.io/guides/assistant/admin/manage-organization-service-accounts.md): Create service accounts for organization-level API access.
- [Projects overview](https://docs.pinecone.io/guides/assistant/admin/projects-overview.md): Learn about projects, roles, and collaboration.
- [Create a project](https://docs.pinecone.io/guides/assistant/admin/create-a-project.md): Create a new Pinecone project in your organization.
- [Manage projects](https://docs.pinecone.io/guides/assistant/admin/manage-projects.md): View, rename, and delete projects in your organization.
- [Manage project members](https://docs.pinecone.io/guides/assistant/admin/manage-project-members.md): Add and manage team members in your project.
- [Manage API keys](https://docs.pinecone.io/guides/assistant/admin/manage-api-keys.md): Create and manage API keys with custom permissions.
- [Manage service accounts at the project-level](https://docs.pinecone.io/guides/assistant/admin/manage-project-service-accounts.md): Enable programmatic access with project-level service accounts.
- [Assistant API reference](https://docs.pinecone.io/reference/api/assistant/introduction.md): Pinecone REST API: Use the Assistant API to upload documents, ask questions, and receive responses that reference your documents.
- [Authentication](https://docs.pinecone.io/reference/api/assistant/authentication.md): Pinecone REST API: All requests to the Pinecone Assistant API must contain a valid API key for the target project.
- [Pinecone Assistant limits](https://docs.pinecone.io/reference/api/assistant/assistant-limits.md): Pinecone REST API:
- [List assistants](https://docs.pinecone.io/reference/api/2026-04/assistant/list_assistants.md): List of all assistants in a project.
- [Create an assistant](https://docs.pinecone.io/reference/api/2026-04/assistant/create_assistant.md): Create an assistant. This is where you specify the underlying training model, which cloud provider you would like to deploy with, and more.
- [Check assistant status](https://docs.pinecone.io/reference/api/2026-04/assistant/describe_assistant.md): Get the status of an assistant.
- [Update an assistant](https://docs.pinecone.io/reference/api/2026-04/assistant/update_assistant.md): Update an existing assistant. You can modify the assistant's instructions.
- [Delete an assistant](https://docs.pinecone.io/reference/api/2026-04/assistant/delete_assistant.md): Delete an existing assistant.
- [List Files](https://docs.pinecone.io/reference/api/2026-04/assistant/list_files.md): List all files in an assistant, with an option to filter files with metadata.
- [Upload a file](https://docs.pinecone.io/reference/api/2026-04/assistant/upload_file.md): Upload a file to the specified assistant.
- [Upsert a file](https://docs.pinecone.io/reference/api/2026-04/assistant/upsert_file.md): Create or replace a file in the specified assistant. If a file with the given `assistant_file_id` already exists, it will be replaced with the new file. If it doesn't exist, a new file will be created with that identifier.
- [Describe a file](https://docs.pinecone.io/reference/api/2026-04/assistant/describe_file.md): [Get the current status and metadata of a file](https://docs.pinecone.io/guides/assistant/manage-files#get-the-status-of-a-file) uploaded to an assistant.
- [Delete a file](https://docs.pinecone.io/reference/api/2026-04/assistant/delete_file.md): [Delete an uploaded file](https://docs.pinecone.io/guides/assistant/manage-files#delete-a-file) from an assistant.
- [List operations](https://docs.pinecone.io/reference/api/2026-04/assistant/list_operations.md): List all operations for an assistant. Returns operations that are in progress, as well as recently completed or failed operations. Both successful and failed operations are retained for 30 days after completion. Use the `operation_type` and `status` query parameters to filter results.
- [Describe an operation](https://docs.pinecone.io/reference/api/2026-04/assistant/describe_operation.md): Get the status of an operation.
- [Chat with an assistant](https://docs.pinecone.io/reference/api/2026-04/assistant/chat_assistant.md): Chat with an assistant and get back citations in structured form.
- [Chat through an OpenAI-compatible interface](https://docs.pinecone.io/reference/api/2026-04/assistant/chat_completion_assistant.md): Chat with an assistant. This endpoint is based on the OpenAI Chat Completion API, a commonly used and adopted API.
- [Evaluate an answer](https://docs.pinecone.io/reference/api/2026-04/assistant/metrics_alignment.md): Evaluate the correctness and completeness of a response from an assistant or a RAG system. The correctness and completeness are evaluated based on the precision and recall of the generated answer with respect to the ground truth answer facts. Alignment is the harmonic mean of correctness and complet…
- [Retrieve context from an assistant](https://docs.pinecone.io/reference/api/2026-04/assistant/context_assistant.md): Retrieve context snippets from an assistant to use as part of RAG or any agentic flow.
- [Create an API key](https://docs.pinecone.io/reference/api/2026-04/admin-assistant/create_api_key.md): Create an API key for a project to authenticate Data Plane and Control Plane requests.
- [List API keys](https://docs.pinecone.io/reference/api/2026-04/admin-assistant/list_api_keys.md): List all API keys in a project.
- [Get API key details](https://docs.pinecone.io/reference/api/2026-04/admin-assistant/fetch_api_key.md): Get an API key's details, excluding its secret.
- [Update an API key](https://docs.pinecone.io/reference/api/2026-04/admin-assistant/update_api_key.md): Update an API key's name and roles.
- [Delete an API key](https://docs.pinecone.io/reference/api/2026-04/admin-assistant/delete_api_key.md): Delete an API key from a project.
- [Create a new project](https://docs.pinecone.io/reference/api/2026-04/admin-assistant/create_project.md): Create a new project.
- [List projects](https://docs.pinecone.io/reference/api/2026-04/admin-assistant/list_projects.md): List all projects in an organization.
- [Get project details](https://docs.pinecone.io/reference/api/2026-04/admin-assistant/fetch_project.md): Get a project's details.
- [Update a project](https://docs.pinecone.io/reference/api/2026-04/admin-assistant/update_project.md): Update a project's name, maximum number of Pods, or customer-managed encryption key (CMEK).
- [Delete a project](https://docs.pinecone.io/reference/api/2026-04/admin-assistant/delete_project.md): Delete a project and all its configuration; delete its indexes, assistants, backups, and collections first.
- [Create an access token](https://docs.pinecone.io/reference/api/2026-04/admin-assistant/get_token.md): Obtain an access token for a service account using the OAuth2 client credentials flow. An access token is needed to authorize requests to the Pinecone Admin API. The host domain for OAuth endpoints is `login.pinecone.io`.
- [Pinecone Assistant architecture](https://docs.pinecone.io/reference/architecture/assistant-architecture.md): Pinecone Assistant architecture: This page describes the architecture for Pinecone Assistant.
- [Assistant examples](https://docs.pinecone.io/examples/assistant.md): Notebooks and sample apps for Pinecone Assistant: quickstart, context snippets, and a full-stack chat UI.
- [2026 releases](https://docs.pinecone.io/assistant-release-notes/2026.md): Pinecone release notes — 2026 releases:
- [2025 releases](https://docs.pinecone.io/assistant-release-notes/2025.md): Pinecone release notes — 2025 releases:
- [2024 releases](https://docs.pinecone.io/assistant-release-notes/2024.md): Pinecone release notes — 2024 releases:
- [2023 releases](https://docs.pinecone.io/assistant-release-notes/2023.md): Pinecone release notes — 2023 releases:
- [2022 releases](https://docs.pinecone.io/assistant-release-notes/2022.md): Pinecone release notes — 2022 releases:
- [Feature availability](https://docs.pinecone.io/assistant-release-notes/feature-availability.md): Pinecone release notes — Feature availability:
- [Pinecone Nexus](https://docs.pinecone.io/guides/nexus/overview.md): Pinecone Nexus is the knowledge engine for agents. It compiles your data into queryable knowledge once, then serves grounded, cited answers to agents on every call.
- [Nexus quickstart](https://docs.pinecone.io/guides/nexus/quickstart.md): Deploy Nexus in your own cloud, then create a context and query it.
- [Nexus key concepts](https://docs.pinecone.io/guides/nexus/concepts.md): Contexts, manifests, artifacts, sessions, and the Query API, and how they fit together.
- [How Nexus works](https://docs.pinecone.io/guides/nexus/how-it-works.md): How Nexus distills curated artifacts for retrieval, then answers with code over a retrieval SDK.
- [Context design](https://docs.pinecone.io/guides/nexus/context-design.md): The manifest, the information stack (chunks, artifacts, and edges), and the artifact-kind reference.
- [Curation](https://docs.pinecone.io/guides/nexus/how-curation-works.md): The write path that turns sources into chunks and artifacts, incrementally, driven by the manifest.
- [Queries](https://docs.pinecone.io/guides/nexus/how-queries-work.md): The query runtime that gathers evidence and composes a grounded, cited answer.
- [Query tracing](https://docs.pinecone.io/guides/nexus/query-tracing.md): Trace any query to see the steps, retrieval code, tokens, and cost behind its answer.
- [MCP server](https://docs.pinecone.io/guides/nexus/mcp-server.md): Query your Pinecone Nexus contexts from any Model Context Protocol client, such as Claude Desktop, over Streamable HTTP.
- [Nexus BYOC overview](https://docs.pinecone.io/guides/nexus/byoc/overview.md): What Nexus bring your own cloud is, how it relates to Database BYOC, and its architecture.
- [Data residency and limits](https://docs.pinecone.io/guides/nexus/byoc/reference.md): Where your data lives and travels in Nexus BYOC, plus authentication, encryption, cluster footprint, and limitations.
- [Deploy Nexus BYOC](https://docs.pinecone.io/guides/nexus/byoc/deploy.md): Install and operate Pinecone Nexus in your own cloud account.
- [Pinecone Nexus API](https://docs.pinecone.io/reference/api/nexus/introduction.md): Programmatic access to Nexus: manage contexts and sources, curate, and query with KnowQL.
- [Authentication](https://docs.pinecone.io/reference/api/nexus/authentication.md): Authenticate to the Nexus API with your Pinecone API key, sent directly or exchanged for a short-lived session token.
- [Current identity (whoami)](https://docs.pinecone.io/reference/api/nexus/get_identity.md)
- [Exchange a Pinecone API key for a session token](https://docs.pinecone.io/reference/api/nexus/login.md)
- [Get the active project](https://docs.pinecone.io/reference/api/nexus/get_project.md)
- [Project-wide task stats](https://docs.pinecone.io/reference/api/nexus/get_project_task_stats.md): Aggregate task counters across the whole project (all contexts), broken down by state and workflow. The per-context equivalent is `GET /contexts/{slug}/tasks/stats`.
- [List contexts (newest first, with stats)](https://docs.pinecone.io/reference/api/nexus/list_contexts.md)
- [Create a context](https://docs.pinecone.io/reference/api/nexus/create_context.md): The context is created empty and is not queryable until you import sources and curate them (curate is explicit — there is no auto-curate). Optionally seed a `manifest`. A `work` context is the exception: it is queryable from day zero and is built from traces of work rather than source documents.
- [Get a context](https://docs.pinecone.io/reference/api/nexus/get_context.md)
- [Update a context](https://docs.pinecone.io/reference/api/nexus/update_context.md): All fields optional; absent leaves untouched. Empty string clears description/guide; `{}` clears the manifest back to defaults. A supplied manifest is validated against the manifest schema.
- [Delete a context (and its Pinecone indexes)](https://docs.pinecone.io/reference/api/nexus/delete_context.md)
- [Run the Design-flow explore agent (propose a manifest)](https://docs.pinecone.io/reference/api/nexus/explore_context.md): Inspects the uploaded source and proposes manifest-template matches, returned in the task's `output` (see `ExploreOutput`). Persists nothing on the index — review the proposal, then apply it via the manifest update + a forced curate. Body is optional.
- [Fork a context (copy manifest into a fresh target)](https://docs.pinecone.io/reference/api/nexus/fork_context.md): Copies the source context's manifest and lifecycle metadata onto an **already-created** target context in the same project, so the target's query and curate gates pass. It does not create the target — create it first with `POST /contexts`. The target's index stays empty until curated. The source mus…
- [Trigger an on-demand self-tuning optimize](https://docs.pinecone.io/reference/api/nexus/optimize_context.md): Tunes the manifest from real query traffic and chains a forced re-curate. A body is required but every field in it is optional, so `{}` is valid — and a no-op when no `candidate_queries` are supplied. The context must have been curated, and only one optimize runs at a time.
- [Estimate the token + time cost of curating the in-progress manifest](https://docs.pinecone.io/reference/api/nexus/profile_context.md): Spins up the `profile` runtime to estimate the token + time cost of curating the sources under the in-progress manifest (sent in the request body), returned as the task's `output` (see `ProfileEstimateOutput`). Persists nothing; the console polls it for the Design-page cost box. Body is optional.
- [Per-context task statistics](https://docs.pinecone.io/reference/api/nexus/get_context_task_stats.md)
- [Import source documents from a project connector](https://docs.pinecone.io/reference/api/nexus/import_context_sources.md): Pull source documents from a linked project connector (Box, ...) into the context. Supply either `folder` or `files`. Stages the source only — curate explicitly before querying.
- [Upload a source file or archive](https://docs.pinecone.io/reference/api/nexus/upload_context_source.md): One file per request, max 2 GiB. Archives (`.zip`, `.tar`, `.tar.gz`, `.tgz`) are expanded by the import runtime. Stages the source only — it does not index anything. Curate explicitly with `POST /contexts/{slug}/curate` before querying.
- [List the source file tree (root)](https://docs.pinecone.io/reference/api/nexus/list_source_files.md)
- [Flat manifest of source files (path, size, last_modified)](https://docs.pinecone.io/reference/api/nexus/get_source_manifest.md): Flat source-object inventory used to render the source page without walking the tree. Excludes the `_inbox/` staging directory.
- [Source file/dir/size counts](https://docs.pinecone.io/reference/api/nexus/get_source_stats.md): Aggregate counts. Under preview mode the response also carries the per-context quota (`max_files_per_context`, `max_bytes_per_context`, `used_files`, `used_bytes`); those fields are absent otherwise.
- [Delete a source file](https://docs.pinecone.io/reference/api/nexus/delete_source_file.md)
- [List the source file tree under a path](https://docs.pinecone.io/reference/api/nexus/list_source_files_by_path.md)
- [Read a source file (raw bytes)](https://docs.pinecone.io/reference/api/nexus/read_source_file.md)
- [List the built-in manifest templates](https://docs.pinecone.io/reference/api/nexus/list_manifest_templates.md): The catalog the console seeds new contexts from.
- [Get the context's manifest](https://docs.pinecone.io/reference/api/nexus/get_context_manifest.md): The context's pinned manifest document. A context with no pinned manifest returns `{}` — the runtime fills defaults. Writes go through the `manifest` field on `PUT /contexts/{slug}`.
- [Get the curation ledger](https://docs.pinecone.io/reference/api/nexus/get_curation_ledger.md): The full ledger: per-source hashes, edges, corpus groups, chunk-id lineage, version pin, reclaim intents, pointers, and glossary. This pays an O(corpus) chunk-id-lineage read — use `GET /contexts/{slug}/curate/version/pin` on the per-turn path.
- [(Re)build the context's index from its sources](https://docs.pinecone.io/reference/api/nexus/curate_context.md): Curate the staged sources under the active manifest. **Required before querying** — there is no auto-curate. Body is optional. Set `force: true` to do a full rebuild (use after editing the manifest); the default is an incremental curate. Search contexts only — a work context builds via `work`/`groom…
- [Drop named sources from the index + ledger](https://docs.pinecone.io/reference/api/nexus/delete_curated_sources.md)
- [List curated knowledge (root)](https://docs.pinecone.io/reference/api/nexus/list_knowledge.md)
- [Knowledge file/dir/size counts](https://docs.pinecone.io/reference/api/nexus/get_knowledge_stats.md)
- [List curated knowledge under a path](https://docs.pinecone.io/reference/api/nexus/list_knowledge_by_path.md)
- [Read a curated knowledge file (raw bytes)](https://docs.pinecone.io/reference/api/nexus/read_knowledge_file.md)
- [List the selectable query models](https://docs.pinecone.io/reference/api/nexus/list_models.md): The model catalog the `model` field on `POST /query` draws from. Returns the default model, every catalog entry, the tier → model-id map, per-phase defaults, and the curate-capable model ids. Only entries with `available: true` are selectable (others are coming soon and rejected with `400`).
- [Run one KnowQL query turn](https://docs.pinecone.io/reference/api/nexus/query.md): Send `ask` (the natural-language question) and, when starting a new session, a `scope` of 1–10 contexts. Continue an existing session with `session_id` or `previous_query_id`. Scoped search contexts must be curated (work contexts are queryable immediately), and a scope may not mix work and search co…
- [List project-wide query sessions (newest first)](https://docs.pinecone.io/reference/api/nexus/list_sessions.md)
- [Fetch one query (turn)](https://docs.pinecone.io/reference/api/nexus/get_query.md)
- [Get a session with its queries (conversation order)](https://docs.pinecone.io/reference/api/nexus/get_session.md)
- [Delete a session and its queries](https://docs.pinecone.io/reference/api/nexus/delete_session.md)
- [Cancel an in-progress query turn](https://docs.pinecone.io/reference/api/nexus/cancel_query.md): Idempotent — an already-terminal query is returned unchanged. On success the turn's `status` becomes `cancelled`.
- [Stream a query turn's events (SSE)](https://docs.pinecone.io/reference/api/nexus/stream_query_events.md): Server-sent event stream of the turn's events as they land — the same `type`-named events POST /query emits with `stream: true`, but as a standalone, resumable subscription. Reconnect with `Last-Event-ID` to replay from where the stream dropped.
- [Record thumbs-up/down feedback on a query turn](https://docs.pinecone.io/reference/api/nexus/create_query_feedback.md)
- [Fetch the recorded trace for a query turn](https://docs.pinecone.io/reference/api/nexus/get_query_trace.md): The per-turn debug trace (steps, tool calls, strategy, cost, rollup). Trace persistence is unconditional — every turn lands a trace blob — so this is available once the turn is terminal.
- [List tasks (project-wide, paginated)](https://docs.pinecone.io/reference/api/nexus/list_tasks.md)
- [Get a task (with steps)](https://docs.pinecone.io/reference/api/nexus/get_task.md)
- [Cancel/terminate a task](https://docs.pinecone.io/reference/api/nexus/cancel_task.md): Body is optional. Max body 1 MiB.
- [Live token + runtime stats for a task](https://docs.pinecone.io/reference/api/nexus/get_task_stats.md)
- [List a task's working-directory files](https://docs.pinecone.io/reference/api/nexus/list_task_files.md)
- [Delete a task file](https://docs.pinecone.io/reference/api/nexus/delete_task_file.md)
- [List a task's files under a path](https://docs.pinecone.io/reference/api/nexus/list_task_files_by_path.md)
- [Stat a task file](https://docs.pinecone.io/reference/api/nexus/get_task_file_metadata.md)
- [Read a task file (raw bytes)](https://docs.pinecone.io/reference/api/nexus/read_task_file.md): Serves from the live container while the task runs, and from the archived blob store afterwards. This is how a finished pack's `<slug>.context.zip` is downloaded.
- [List the project's linked connectors](https://docs.pinecone.io/reference/api/nexus/list_connectors.md)
- [Get a connector](https://docs.pinecone.io/reference/api/nexus/get_connector.md)
- [Unlink a connector](https://docs.pinecone.io/reference/api/nexus/delete_connector.md)
- [Link a connector with an API key](https://docs.pinecone.io/reference/api/nexus/create_connector.md)
- [Browse a connector's folders/files](https://docs.pinecone.io/reference/api/nexus/list_connector_items.md)
- [List a context's connectors (with per-context enabled flag)](https://docs.pinecone.io/reference/api/nexus/list_context_connectors.md)
- [Start the OAuth link flow for a provider](https://docs.pinecone.io/reference/api/nexus/start_connector_oauth.md): Returns an `authorize_url` for the user to open in a browser. The connector is persisted by the provider's OAuth redirect callback once the user approves access.
- [Enable or disable a connector for a context](https://docs.pinecone.io/reference/api/nexus/update_context_connector.md)
- [2026 releases](https://docs.pinecone.io/nexus-release-notes/2026.md): Pinecone Nexus release notes for 2026.
- [Feature availability](https://docs.pinecone.io/nexus-release-notes/feature-availability.md): Feature availability phases for Pinecone Nexus.
- [Pinecone Marketplace](https://docs.pinecone.io/guides/marketplace/overview.md): Pinecone Marketplace is a no-code platform for creating, publishing, and operating knowledge applications powered by Pinecone.
- [Marketplace quickstart](https://docs.pinecone.io/guides/marketplace/quickstart.md): Pick a template, connect a folder of documents, and publish your first Pinecone Marketplace knowledge application.
- [Marketplace concepts](https://docs.pinecone.io/guides/marketplace/concepts.md): Core concepts in Pinecone Marketplace: knowledge applications, deployments, templates, manifests, KAT, layouts, and components.
- [Marketplace pricing and limits](https://docs.pinecone.io/guides/marketplace/pricing-and-limits.md): How Pinecone Marketplace usage is billed and what limits apply.
- [Templates overview](https://docs.pinecone.io/guides/marketplace/templates-overview.md): How Pinecone Marketplace templates work, what they define, and how operators customize a deployment after creating it from a template.
- [Template catalog](https://docs.pinecone.io/guides/marketplace/template-catalog.md): The bundled vertical templates available in Pinecone Marketplace.
- [Create a deployment](https://docs.pinecone.io/guides/marketplace/create-a-deployment.md): Create a new deployment in Pinecone Marketplace from a vertical template.
- [Configure operating parameters](https://docs.pinecone.io/guides/marketplace/configure-operating-parameters.md): Tune the system prompt and response behavior of a Pinecone Marketplace knowledge application.
- [Configure layouts](https://docs.pinecone.io/guides/marketplace/configure-layouts.md): Choose the consumer layout for a Pinecone Marketplace knowledge application.
- [Configure components](https://docs.pinecone.io/guides/marketplace/configure-components.md): Enable visual components in a Pinecone Marketplace knowledge application.
- [Connectors overview](https://docs.pinecone.io/guides/marketplace/connectors-overview.md): How Pinecone Marketplace connectors ingest documents, keep them in sync with source systems, and let operators add manually uploaded files.
- [Knowledge Agent Toolkit (KAT) overview](https://docs.pinecone.io/guides/marketplace/kat-overview.md): How the Knowledge Agent Toolkit orchestrates multi-domain knowledge applications in Pinecone Marketplace, including manifests, disambiguation, slot filling, and guardrails.
- [Multi-domain routing](https://docs.pinecone.io/guides/marketplace/multi-domain-routing.md): How KAT routes queries across multiple knowledge bases in a Pinecone Marketplace deployment.
- [Publish a deployment](https://docs.pinecone.io/guides/marketplace/publish-a-deployment.md): How to publish a Pinecone Marketplace deployment so end users can use it.
- [Manage versions and rollback](https://docs.pinecone.io/guides/marketplace/manage-versions-and-rollback.md): Use versioned publishing in Pinecone Marketplace to ship safer changes and roll back when needed.
- [Evaluations](https://docs.pinecone.io/guides/marketplace/evaluations.md): How Pinecone Marketplace evaluates a knowledge application on every publish.
- [Analytics and event logs](https://docs.pinecone.io/guides/marketplace/analytics-and-event-logs.md): Monitor end-user activity, refusals, and feedback for a Pinecone Marketplace deployment.
- [Deployer authentication](https://docs.pinecone.io/guides/marketplace/deployer-auth.md): How operators sign in to Pinecone Marketplace.
- [Consumer authentication](https://docs.pinecone.io/guides/marketplace/consumer-auth-overview.md): Choose how end users sign in to a Pinecone Marketplace knowledge application: link access or Google sign-in.
- [End user guide](https://docs.pinecone.io/guides/marketplace/end-user/overview.md): What a Pinecone Marketplace knowledge application is and how to sign in to one.
- [Ask questions](https://docs.pinecone.io/guides/marketplace/end-user/ask-questions.md): Get the most out of a Pinecone Marketplace knowledge application by asking clear, specific questions.
- [Understand answers](https://docs.pinecone.io/guides/marketplace/end-user/citations.md): Read citations, work with visual components, export and share answers, and give feedback in a Pinecone Marketplace knowledge application.
- [Pinecone Marketplace API](https://docs.pinecone.io/reference/api/marketplace/introduction.md): Programmatic access to Pinecone Marketplace deployments, templates, connectors, versions, and analytics.
- [Authentication](https://docs.pinecone.io/reference/api/marketplace/authentication.md): Authenticate to the Pinecone Marketplace API.
- [Deployments](https://docs.pinecone.io/reference/api/marketplace/deployments.md): Create and manage Pinecone Marketplace deployments programmatically.
- [Templates](https://docs.pinecone.io/reference/api/marketplace/templates.md): List the vertical templates available in Pinecone Marketplace.
- [Connectors](https://docs.pinecone.io/reference/api/marketplace/connectors.md): Manage source connectors for Pinecone Marketplace deployments.
- [Versions and publishing](https://docs.pinecone.io/reference/api/marketplace/versions.md): Programmatically publish, list, and roll back Pinecone Marketplace deployment versions.
- [Evaluations](https://docs.pinecone.io/reference/api/marketplace/evaluations.md): Trigger and retrieve Pinecone Marketplace evaluation results.
- [Events and analytics](https://docs.pinecone.io/reference/api/marketplace/events.md): Read deployment events and analytics counters from Pinecone Marketplace.

## OpenAPI Specs

- [nexus_2026-07.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2026-07/nexus_2026-07.oas.yaml)
- [inference_2026-04.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2026-04/inference_2026-04.oas.yaml)
- [db_data_2026-04.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2026-04/db_data_2026-04.oas.yaml)
- [db_control_2026-04.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2026-04/db_control_2026-04.oas.yaml)
- [oauth_2026-04.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2026-04/oauth_2026-04.oas.yaml)
- [assistant_data_2026-04.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2026-04/assistant_data_2026-04.oas.yaml)
- [assistant_control_2026-04.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2026-04/assistant_control_2026-04.oas.yaml)
- [admin_2026-04.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2026-04/admin_2026-04.oas.yaml)
- [db_data_2026-01.alpha.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2026-01.alpha/db_data_2026-01.alpha.oas.yaml)
- [db_control_2026-01.alpha.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2026-01.alpha/db_control_2026-01.alpha.oas.yaml)
- [assistant_evaluation_2026-04.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2026-04/assistant_evaluation_2026-04.oas.yaml)
- [db_data_2025-04.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2025-04/db_data_2025-04.oas.yaml)
- [db_data_2025-10.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2025-10/db_data_2025-10.oas.yaml)
- [db_control_2025-10.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2025-10/db_control_2025-10.oas.yaml)
- [assistant_data_2025-10.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2025-10/assistant_data_2025-10.oas.yaml)
- [assistant_control_2025-10.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2025-10/assistant_control_2025-10.oas.yaml)
- [db_data_2025-01.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2025-01/db_data_2025-01.oas.yaml)
- [data_2024-04.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2024-04/data_2024-04.oas.yaml)
- [data_2024-07.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2024-07/data_2024-07.oas.yaml)
- [db_data_2024-10.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2024-10/db_data_2024-10.oas.yaml)
- [inference_2025-10.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2025-10/inference_2025-10.oas.yaml)
- [assistant_evaluation_2025-10.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2025-10/assistant_evaluation_2025-10.oas.yaml)
- [oauth_2025-10.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2025-10/oauth_2025-10.oas.yaml)
- [admin_2025-10.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2025-10/admin_2025-10.oas.yaml)
- [admin_2025-04.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2025-04/admin_2025-04.oas.yaml)
- [assistant_data_2025-01.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2025-01/assistant_data_2025-01.oas.yaml)
- [assistant_data_2025-04.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2025-04/assistant_data_2025-04.oas.yaml)
- [db_control_2025-04.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2025-04/db_control_2025-04.oas.yaml)
- [control_2024-04.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2024-04/control_2024-04.oas.yaml)
- [control_2024-07.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2024-07/control_2024-07.oas.yaml)
- [inference_2024-10.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2024-10/inference_2024-10.oas.yaml)
- [db_control_2024-10.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2024-10/db_control_2024-10.oas.yaml)
- [inference_2025-01.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2025-01/inference_2025-01.oas.yaml)
- [db_control_2025-01.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2025-01/db_control_2025-01.oas.yaml)
- [assistant_evaluation_2025-01.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2025-01/assistant_evaluation_2025-01.oas.yaml)
- [assistant_control_2025-01.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2025-01/assistant_control_2025-01.oas.yaml)
- [inference_2025-04.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2025-04/inference_2025-04.oas.yaml)
- [assistant_evaluation_2025-04.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2025-04/assistant_evaluation_2025-04.oas.yaml)
- [assistant_control_2025-04.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2025-04/assistant_control_2025-04.oas.yaml)
- [oauth_2025-04.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2025-04/oauth_2025-04.oas.yaml)
- [pinecone](https://docs.pinecone.io/pinecone.json)
- [data_plane_api](https://docs.pinecone.io/data_plane_api.json)
- [control_plane_api](https://docs.pinecone.io/control_plane_api.json)