{
  "opencollection": "1.0.0",
  "info": {
    "name": "Pinecone Admin API Keys Vector Operations API",
    "version": "2025-10"
  },
  "request": {
    "auth": {
      "type": "bearer",
      "token": "{{bearerToken}}"
    }
  },
  "items": [
    {
      "info": {
        "name": "Vector Operations",
        "type": "folder"
      },
      "items": [
        {
          "info": {
            "name": "Get index stats",
            "type": "http"
          },
          "http": {
            "method": "POST",
            "url": "https://api.pinecone.io/describe_index_stats",
            "headers": [
              {
                "name": "X-Pinecone-Api-Version",
                "value": ""
              }
            ],
            "body": {
              "type": "json",
              "data": "{}"
            }
          },
          "docs": "Return statistics about the contents of an index, including the vector count per namespace, the number of dimensions, and the index fullness.\n\nServerless indexes scale automatically as needed, so index fullness is relevant only for pod-based indexes."
        },
        {
          "info": {
            "name": "Search with a vector",
            "type": "http"
          },
          "http": {
            "method": "POST",
            "url": "https://api.pinecone.io/query",
            "headers": [
              {
                "name": "X-Pinecone-Api-Version",
                "value": ""
              }
            ],
            "body": {
              "type": "json",
              "data": "{}"
            }
          },
          "docs": "Search a namespace using a query vector. It retrieves the ids of the most similar items in a namespace, along with their similarity scores.\n\nFor guidance, examples, and limits, see [Search](https://docs.pinecone.io/guides/search/search-overview)."
        },
        {
          "info": {
            "name": "Delete vectors",
            "type": "http"
          },
          "http": {
            "method": "POST",
            "url": "https://api.pinecone.io/vectors/delete",
            "headers": [
              {
                "name": "X-Pinecone-Api-Version",
                "value": ""
              }
            ],
            "body": {
              "type": "json",
              "data": "{}"
            }
          },
          "docs": "Delete vectors by id from a single namespace.\n\nFor guidance and examples, see [Delete data](https://docs.pinecone.io/guides/manage-data/delete-data)."
        },
        {
          "info": {
            "name": "Fetch vectors",
            "type": "http"
          },
          "http": {
            "method": "GET",
            "url": "https://api.pinecone.io/vectors/fetch",
            "headers": [
              {
                "name": "X-Pinecone-Api-Version",
                "value": ""
              }
            ],
            "params": [
              {
                "name": "ids",
                "value": "",
                "type": "query",
                "description": "The vector IDs to fetch. Does not accept values containing spaces."
              },
              {
                "name": "namespace",
                "value": "",
                "type": "query",
                "description": "The namespace to fetch vectors from. If not provided, the default namespace is used."
              }
            ]
          },
          "docs": "Look up and return vectors by ID from a single namespace. The returned vectors include the vector data and/or metadata.\n\nFor 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 query operation with `includeValues` set to `false` instead.\n\nFor guidance and examples, see [Fetch data](https://docs.pinecone.io/guides/manage-data/fetch-data)."
        },
        {
          "info": {
            "name": "Fetch vectors by metadata",
            "type": "http"
          },
          "http": {
            "method": "POST",
            "url": "https://api.pinecone.io/vectors/fetch_by_metadata",
            "headers": [
              {
                "name": "X-Pinecone-Api-Version",
                "value": ""
              }
            ],
            "body": {
              "type": "json",
              "data": "{}"
            }
          },
          "docs": "Look up and return vectors by metadata filter from a single namespace. The returned vectors include the vector data and/or metadata.\nFor guidance and examples, see [Fetch data](https://docs.pinecone.io/guides/manage-data/fetch-data)."
        },
        {
          "info": {
            "name": "List vector IDs",
            "type": "http"
          },
          "http": {
            "method": "GET",
            "url": "https://api.pinecone.io/vectors/list",
            "headers": [
              {
                "name": "X-Pinecone-Api-Version",
                "value": ""
              }
            ],
            "params": [
              {
                "name": "prefix",
                "value": "",
                "type": "query",
                "description": "The vector IDs to fetch. Does not accept values containing spaces."
              },
              {
                "name": "limit",
                "value": "",
                "type": "query",
                "description": "Max number of IDs to return per page."
              },
              {
                "name": "paginationToken",
                "value": "",
                "type": "query",
                "description": "Pagination token to continue a previous listing operation."
              },
              {
                "name": "namespace",
                "value": "",
                "type": "query",
                "description": "The namespace to list vectors from. If not provided, the default namespace is used."
              }
            ]
          },
          "docs": "List the IDs of vectors in a single namespace of a serverless index. An optional prefix can be passed to limit the results to IDs with a common prefix.\n\nReturns up to 100 IDs at a time by default in sorted order (bitwise \"C\" collation). If the `limit` parameter is set, `list` returns up to that number of IDs instead. Whenever there are additional IDs to return, the response also includes a `pagination_token` that you can use to get the next batch of IDs. When the response does not include a `pag"
        },
        {
          "info": {
            "name": "Update a vector",
            "type": "http"
          },
          "http": {
            "method": "POST",
            "url": "https://api.pinecone.io/vectors/update",
            "headers": [
              {
                "name": "X-Pinecone-Api-Version",
                "value": ""
              }
            ],
            "body": {
              "type": "json",
              "data": "{}"
            }
          },
          "docs": "Update a vector in a namespace. If a value is included, it will overwrite the previous value. If a `set_metadata` is included, the values of the fields specified in it will be added or overwrite the previous value.\n\nFor guidance and examples, see [Update data](https://docs.pinecone.io/guides/manage-data/update-data)."
        },
        {
          "info": {
            "name": "Upsert vectors",
            "type": "http"
          },
          "http": {
            "method": "POST",
            "url": "https://api.pinecone.io/vectors/upsert",
            "headers": [
              {
                "name": "X-Pinecone-Api-Version",
                "value": ""
              }
            ],
            "body": {
              "type": "json",
              "data": "{}"
            }
          },
          "docs": "Upsert vectors into a namespace. If a new value is upserted for an existing vector ID, it will overwrite the previous value.\n\nFor guidance, examples, and limits, see [Upsert data](https://docs.pinecone.io/guides/index-data/upsert-data)."
        },
        {
          "info": {
            "name": "Upsert text",
            "type": "http"
          },
          "http": {
            "method": "POST",
            "url": "https://api.pinecone.io/records/namespaces/:namespace/upsert",
            "headers": [
              {
                "name": "X-Pinecone-Api-Version",
                "value": ""
              }
            ],
            "params": [
              {
                "name": "namespace",
                "value": "",
                "type": "path",
                "description": "The namespace to upsert records into."
              }
            ],
            "body": {
              "type": "json",
              "data": "{}"
            }
          },
          "docs": "Upsert text into a namespace. Pinecone converts the text to vectors automatically using the hosted embedding model associated with the index.\n\nUpserting text is supported only for [indexes with integrated embedding](https://docs.pinecone.io/guides/index-data/create-an-index#embedding-models).\n\nFor guidance, examples, and limits, see [Upsert data](https://docs.pinecone.io/guides/index-data/upsert-data)."
        },
        {
          "info": {
            "name": "Search with text",
            "type": "http"
          },
          "http": {
            "method": "POST",
            "url": "https://api.pinecone.io/records/namespaces/:namespace/search",
            "headers": [
              {
                "name": "X-Pinecone-Api-Version",
                "value": ""
              }
            ],
            "params": [
              {
                "name": "namespace",
                "value": "",
                "type": "path",
                "description": "The namespace to search."
              }
            ],
            "body": {
              "type": "json",
              "data": "{}"
            }
          },
          "docs": "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. \n\nSearching with text is supported only for indexes with [integrated embedding](https://docs.pinecone.io/guides/index-data/indexing-overview#vector-embedding). Searching with a query vector or record ID is supported for all indexes. \n\nFor guidance and examples, see [Search](https://d"
        }
      ]
    }
  ],
  "bundled": true
}