{
  "opencollection": "1.0.0",
  "info": {
    "name": "MyScale SQL (ClickHouse HTTP) Interface",
    "version": "1.0"
  },
  "request": {
    "auth": {
      "type": "basic",
      "username": "{{username}}",
      "password": "{{password}}"
    }
  },
  "items": [
    {
      "info": {
        "name": "Query",
        "type": "folder"
      },
      "items": [
        {
          "info": {
            "name": "Ping / health check",
            "type": "http"
          },
          "http": {
            "method": "GET",
            "url": "https://{{clusterHost}}:8443/"
          },
          "docs": "GET the root of the HTTP interface; returns 'Ok.' when the cluster is reachable."
        },
        {
          "info": {
            "name": "Create table with vector index",
            "type": "http"
          },
          "http": {
            "method": "POST",
            "url": "https://{{clusterHost}}:8443/",
            "body": {
              "type": "text",
              "data": "CREATE TABLE IF NOT EXISTS default.articles\n(\n    id UInt64,\n    title String,\n    content_vector Array(Float32),\n    CONSTRAINT cons_vec_len CHECK length(content_vector) = 768,\n    VECTOR INDEX article_idx content_vector TYPE HNSWFLAT('metric_type=Cosine')\n)\nENGINE = MergeTree ORDER BY id"
            }
          },
          "docs": "Execute DDL over the ClickHouse HTTP interface to create a table with a VECTOR INDEX."
        },
        {
          "info": {
            "name": "Insert rows",
            "type": "http"
          },
          "http": {
            "method": "POST",
            "url": "https://{{clusterHost}}:8443/?query=INSERT%20INTO%20default.articles%20FORMAT%20JSONEachRow",
            "body": {
              "type": "text",
              "data": "{\"id\": 1, \"title\": \"example\", \"content_vector\": [0.1, 0.2, 0.3]}"
            }
          },
          "docs": "Insert data by sending an INSERT ... FORMAT statement; the rows go in the request body."
        },
        {
          "info": {
            "name": "Vector similarity search (distance)",
            "type": "http"
          },
          "http": {
            "method": "POST",
            "url": "https://{{clusterHost}}:8443/?default_format=JSON",
            "body": {
              "type": "text",
              "data": "SELECT id, title, distance(content_vector, [0.1, 0.2, 0.3]) AS dist\nFROM default.articles\nORDER BY dist ASC\nLIMIT 10"
            }
          },
          "docs": "Run a vector similarity search in SQL using the distance() function ordered by distance."
        }
      ]
    }
  ]
}