> For the complete documentation index, see [llms.txt](https://help.tellius.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://help.tellius.com/tellius-6.3/embedding-tellius/embedding-url/embedding-search/search-query-execution.md). # Search query execution Learn how to execute search queries in embedded Tellius Search using postMessage API—send queries, receive visualizations, and integrate results seamlessly. After connecting with Tellius, the embedding app will contain the Search page component from Tellius. Once the Search page is loaded in the embedding app, users can type the required query in the search box. ### **Request** After typing the query and clicking on Enter, the following postMessage (consisting of the query) will be sent from Tellius: ```json { "actionType":"SEARCH_QUERY_REQUEST", "corrId":"4y1XV", "enterKeyPress":true, "performQuery":true, "query":"show total profit" } ``` ### **Response** After receiving the result, the following postMessage will be sent from Tellius: ```json { "actionType":"SEARCH_QUERY_RESPONSE", "vizResponse":{ "vizResponseType":"kpi", "viz":{ "vizType":"kpi", "title":"Total profit", "theme":{ "vizBackground":{ "transparency":"0.9", "image":"img/test", "color":"white" }, "name":"dark", "color":"black" }, "size":{ "width":200, "height":100 }, "placement":{ "yDistance":20, "xDistance":10 }, "metadata":{ "language":"english", "format":{ "title":{ "font":{ "weight":"normal", "size":"16", "color":"#000000" }, "enabled":true }, "legend":{ "font":{ "weight":"normal", "size":"14", "color":"#78909c" }, "enabled":true }, "colorPaletteInfo":{ "colors":[ "#1565C0", "#F57F17", "#558B2F", "#BF360C", "#5E35B1", "#00838F", "#C62828", "#827717", "#E65100", "#5D4037", "#AD1457", "#6A1B9A", "#1976D2", "#F9A825", "#689F38", "#D84315", "#673AB7", "#0097A7", "#D32F2F", "#9E9D24", "#EF6C00", "#6D4C41", "#C2185B", "#7B1FA2", "#42A5F5", "#FFEB3B", "#9CCC65", "#FF8A65", "#9575CD", "#4DD0E1", "#EF5350", "#C0CA33", "#FF9800", "#8D6E63", "#EC407A", "#AB47BC", "#64B5F6", "#FFF176", "#AED581", "#FFAB91", "#B39DDB", "#80DEEA", "#E57373", "#D4E157", "#FFB74D", "#A1887F", "#F06292", "#BA68C8", "#90CAF9", "#FFF59D", "#C5E1A5", "#FFCCBC", "#D1C4E9", "#B2EBF2", "#EF9A9A", "#DCE775", "#FFCC80", "#BCAAA4", "#F48FB1", "#CE93D8" ] }, "background":{ "enableGrid":false, "color":"#FFFFFF" }, "axes":{ "yAxis":{ "enabled":true }, "xAxis":{ "enabled":true }, "font":{ "weight":"normal", "size":"14", "color":"#78909c" } } }, "dualAxis":true, "colorPalette":"401300fe-58ae-42ad-b185-ce1f4a181d73" }, "id":"5f6b92e5-6711-4c8b-841f-763cf9f7b171", "chartType":"simpleCount", "businessViewId":"bv_d5dfeeb5-9a4a-4fac-92a0-a51a07da52d9", "axes":{ "yAxis":[ { "columnName":"profit", "aggregation":"sum" } ], "isMultipleAxes":false } }, "tooltip":[ { "translatedAggregation":"sum", "originalValue":2698921, "isYAxis":true, "isXAxis":false, "isGroupBy":false, "formattedValue":"2.7M", "columnName":"profit", "alias":"profit", "aggregation":"sum" } ], "responseText":"**Total profit** is **2698921**", "possibleTransitions":[ "funnel", "detailTable", "simpleCount", "radialProgress", "viewData", "interactiveTable", "histogram", "bar", "column", "barConversion", "table" ], "possibleBucketInfo":{ "possibleBuckets":{ "measureType":{ "values":{ "tooltips":5, "measures":0 } } } }, "metadata":{ "tqlResponseRowCount":1, "totalRowCount":0, "timeTakenInMilliSeconds":244, "responseDataCount":1 }, "count":"2.7M", "columns":[ { "name":"profit", "format":{ "type":"number", "isCommaSeparated":false, "displayUnit":"default", "decimals":2 }, "datasetName":"bv_guide_query", "datasetId":"bv_d5dfeeb5-9a4a-4fac-92a0-a51a07da52d9", "aggregation":"sum" } ], "columnDetails":{ "measureType":[ { "column":{ "name":"profit", "isWeekEndDate":false, "aggregation":"sum" }, "bucket":"measures" } ], "dimensionType":[ ], "dateType":[ ] } }, "responseType":"vizResponse", "metadata":{ "witResponse":{ "query":"show total profit", "intent":"Chart", "entities":{ "businessViewId":[ { "value":{ "value":"bv_d5dfeeb5-9a4a-4fac-92a0-a51a07da52d9", "type":"string" }, "start":0, "end":0, "confidence":1 } ], "aggregatedField":[ { "value":{ "type":"aggregation", "columnStartIndexInQuery":11, "aggregationField":{ "name":"profit", "isExpression":false, "datasetName":"bv_guide_query", "datasetId":"bv_d5dfeeb5-9a4a-4fac-92a0-a51a07da52d9", "databaseTable":"bv_d5dfeeb5-9a4a-4fac-92a0-a51a07da52d9" }, "aggregation":"total" }, "start":5, "end":17, "confidence":1 } ] }, "confidence":0.9183534383773804 }, "tokens":[ { "type":"measure", "tokenString":"total profit", "suggestions":[ { "type":"measure", "tokenString":"avg profit", "suggestions":[ ], "column":{ "name":"profit" }, "aggregation":"avg" }, { "type":"measure", "tokenString":"min profit", "suggestions":[ ], "column":{ "name":"profit" }, "aggregation":"min" }, { "type":"measure", "tokenString":"max profit", "suggestions":[ ], "column":{ "name":"profit" }, "aggregation":"max" }, { "type":"measure", "tokenString":"total profit", "suggestions":[ ], "column":{ "name":"profit" }, "aggregation":"total" }, { "type":"measure", "tokenString":"marketShare profit", "suggestions":[ ], "column":{ "name":"profit" }, "aggregation":"marketShare" }, { "type":"measure", "tokenString":"sum cost", "suggestions":[ ], "column":{ "name":"cost" }, "aggregation":"sum" }, { "type":"measure", "tokenString":"sum customer_id", "suggestions":[ ], "column":{ "name":"customer_id" }, "aggregation":"sum" }, { "type":"measure", "tokenString":"sum revenue", "suggestions":[ ], "column":{ "name":"revenue" }, "aggregation":"sum" }, { "type":"measure", "tokenString":"sum store_id", "suggestions":[ ], "column":{ "name":"store_id" }, "aggregation":"sum" }, { "type":"measure", "tokenString":"sum competition_distance", "suggestions":[ ], "column":{ "name":"competition_distance" }, "aggregation":"sum" }, { "type":"measure", "tokenString":"sum store_lat", "suggestions":[ ], "column":{ "name":"store_lat" }, "aggregation":"sum" }, { "type":"measure", "tokenString":"sum store_lon", "suggestions":[ ], "column":{ "name":"store_lon" }, "aggregation":"sum" }, { "type":"measure", "tokenString":"sum store_zip", "suggestions":[ ], "column":{ "name":"store_zip" }, "aggregation":"sum" }, { "type":"measure", "tokenString":"sum age", "suggestions":[ ], "column":{ "name":"age" }, "aggregation":"sum" } ], "start":5, "end":17, "column":{ "name":"profit" }, "aggregation":"sum" } ], "suggestions":[ ], "rowsCount":1, "responseType":"viz", "original":"show total profit", "filterDescriptions":[ ], "chartType":"simpleCount", "chartTitle":"Total profit", "BVId":"bv_d5dfeeb5-9a4a-4fac-92a0-a51a07da52d9" }, "corrId":"4y1XV", "filterDescriptions":[ ] } ``` ### **Add to Vizpads** For more details on adding Search to a Vizpad, please [refer to this section](/tellius-6.3/embedding-tellius/embedding-url/embedding-vizpads/adding-a-viz-to-a-vizpad.md). --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://help.tellius.com/tellius-6.3/embedding-tellius/embedding-url/embedding-search/search-query-execution.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.