# Search the top K semantically similar records ### Search the top K semantically similar records If you have defined indices, you can query Epsilla with natural language questions. The question will be embedded using the same model as the index definition: {% tabs %} {% tab title="Python" %} ```python status_code, response = db.query( table_name="MyTable", # The name of the table to query against. query_index="Index", # The index name to query against. query_text="Where can I find a serene environment, ideal for relaxation and introspection?", # The query question. limit=2, # The top K result to return. response_fields=["Doc"], # (Optional) which fields to be included in # the response. If not provided, will include # all fields in the table. filter="ID < 6 AND Doc <> 'London'", # (Optional) a boolean expression for filtering # out the results. with_distance=True # (Optional) include the distance or not in # the response. Default is False. When given # as True, each matched record will have a # @distance field returned. ) print(response) ``` Response example: ``` { 'message': 'Query search successfully.', 'result': [ { '@distance': 0.4707561135292053, 'Doc': 'The library was a quiet haven, filled with the scent of old books and the soft rustling of pages.', 'ID': 3 }, { '@distance': 0.47871750593185425, 'Doc': 'High in the mountains, the air was crisp and clear, revealing breathtaking views of the valley below.', 'ID': 4 } ], 'statusCode': 200 } ``` {% endtab %} {% tab title="JavaScript" %} ```javascript const query = await db.query( 'MyTable', // The name of the table to query against. { queryIndex: 'Index', // The index name to query against. query: 'Where can I find a serene environment, ideal for relaxation and introspection?', // The query question. limit: 2, // The top K result to return. response: ["Doc"], // (Optional) which fields to be included in // the response. If not provided, will include // all fields in the table. filter: 'ID < 6 AND Doc <> \'London\'', // (Optional) filter: a boolean expression for filtering // out the results. withDistance: true // (Optional) include the distance or not in // the response. Default is False. When given // as true, each matched record will have a // @distance field returned. } ); console.log(JSON.stringify(query, undefined, 2)); ``` Response example: ``` { "statusCode": 200, "message": "Query search successfully.", "result": [ { "@distance": 0.4707561135292053, "Doc": "The library was a quiet haven, filled with the scent of old books and the soft rustling of pages.", "ID": 3 }, { "@distance": 0.47871750593185425, "Doc": "High in the mountains, the air was crisp and clear, revealing breathtaking views of the valley below.", "ID": 4 } ] } ``` {% endtab %} {% endtabs %} If there is only one embedding field, the query field parameter can be omitted. Below is an example with minimum required parameters: {% tabs %} {% tab title="Python" %} ```python status_code, response = db.query( table_name="MyTable", query_text="Where can I find a serene environment, ideal for relaxation and introspection?", limit=2 ) ``` {% endtab %} {% tab title="JavaScript" %} ```javascript const query = await db.query( 'MyTable', { query: "Where can I find a serene environment, ideal for relaxation and introspection?", limit: 2 } ); ``` {% endtab %} {% endtabs %} If you brought in your own embedding vectors via vector fields, you can query by providing the target vector: {% tabs %} {% tab title="Python" %} ```python status_code, response = db.query( table_name="MyTable", # The name of the table to query against. query_field="Embedding", # The embedding field name to query against. query_vector=[0.35, 0.55, 0.47, 0.94], # The embedded vector from the question. limit=2, # The top K result to return. response_fields=["Doc"], # (Optional) which fields to be included in # the response. If not provided, will include # all fields in the table. filter="ID < 6 AND Doc <> 'London'", # (Optional) a boolean expression for filtering # out the results. with_distance=True # (Optional) include the distance or not in # the response. Default is False. When given # as True, each matched record will have a # @distance field returned. ) print(response) ``` Response example: ``` { 'statusCode': 200, 'message': 'Query search successfully.', 'result': [ { '@distance': 0.0001000004049274139, 'Doc': 'The library was a quiet haven, filled with the scent of old books and the soft rustling of pages.' }, { '@distance': 0.2176999747753143, 'Doc': 'The garden was blooming with vibrant flowers, attracting butterflies and bees with their sweet nectar.' } ] } ``` {% endtab %} {% tab title="JavaScript" %} ```javascript const query = await db.query( 'MyTable', // The name of the table to query against. { queryField: 'Embedding', // The embedding field name to query against. queryVector: [0.35, 0.55, 0.47, 0.94], // The embedded vector from the question. limit: 2, // The top K result to return. response: ["Doc"], // (Optional) which fields to be included in // the response. If not provided, will include // all fields in the table. filter: 'ID < 6 AND Doc <> \'London\'', // (Optional) filter: a boolean expression for filtering // out the results. withDistance: true // (Optional) include the distance or not in // the response. Default is False. When given // as true, each matched record will have a // @distance field returned. } ); console.log(JSON.stringify(query, undefined, 2)); ``` Response example: ``` { "statusCode": 200, "message": "Query search successfully.", "result": [ { "@distance": 0.0001000004049274139, "Doc": "The library was a quiet haven, filled with the scent of old books and the soft rustling of pages." }, { "@distance": 0.2176999747753143, "Doc": "The garden was blooming with vibrant flowers, attracting butterflies and bees with their sweet nectar." } ] } ``` {% endtab %} {% endtabs %} {% hint style="info" %} If there is only one embedding field, the query field parameter can be omitted. {% endhint %} #### Filter Expression Epsilla supports filter expression in search that is compatible with SQL. The following operators are supported: | Operator | Description | | -------- | ----------------------------------------------------- | | + | Add | | - | Subtract | | \* | Multiply | | / | Divide | | % | Modulo | | = | Equal to | | > | Greater than | | < | Less than | | >= | Greater than or equal to | | <= | Less than or equal to | | <> | Not equal to | | AND | TRUE if all the conditions separated by AND is TRUE | | NOT | TRUE if the condition afterward is NOT TRUE | | OR | TRUE if any of the conditions separated by OR is TRUE | A string literal needs to be surrounded by single quotes. Refer to a field of the record directly by the field name. Providing an empty filter is same as not providing the filter at all (all records will pass the evaluation). #### Filter on @distance Epsilla supports filter the result by the distance. For example, use the following filter condition to only return the matching results that have a semantic similarity distance less than 0.5: ``` "filter": "@distance < 0.5" ``` @distance can be combined and nested with all the other filter condition operators.