# Building a Lexical Search Query

Lexical Search, or Classic Search, is a fundamental approach to retrieve information based on keyword, integer, float, date etc. value matching. This search operates by assessing the similarity of a collection documents to a query document. It then selects the documents with the top scores and return their id's to the user. 

## Running the Lexical (Classic) Search Query in DSL Syntax

{% tabs %}
{% tab title="Python" %}
{% code lineNumbers="true" %}

```python
query = {
        "query": {
            "bool": {
                "must": [
                    {"term": {"name": "John"}}
                ]
            }
        }
    }
results = hyperspace_client.dsl_search(query,
                                   size=10,                 
                                   collection_name=collection_name)
```

{% endcode %}
{% endtab %}

{% tab title="Java" %}
{% code lineNumbers="true" %}

```java
String queryJson =
                    "{" +
                    "  \"query\": {" +
                    "    \"bool\": {" +
                    "      \"must\": [" +
                    "        {" +
                    "          \"term\":{" +
                    "            \"name\":\"John\"" +
                    "           }" +
                    "        }" +
                    "      ]" +
                    "    }" +
                    "  }" +
                    "}";
JsonObject query = JsonParser.parseString(queryJson).getAsJsonObject();
Object response = client.dslSearch(collectionName, 10, query));
```

{% endcode %}
{% endtab %}

{% tab title="JavaScript" %}

<pre class="language-javascript" data-line-numbers><code class="lang-javascript">let size = 10;
let query = {
<strong>    "query": {
</strong>        "bool": {
            "must": [
                {"term": {"name": "John"}}
            ]
        }
    }
}
await hyperspaceClient.dslSearch(collectionName, size, query)
</code></pre>

{% endtab %}
{% endtabs %}

Where <mark style="color:purple;">query</mark> is your query logic, see example below.

{% tabs %}
{% tab title="Python" %}
{% code lineNumbers="true" %}

```python
query = {
  "query": {
    "function_score": {
      "query": {
        "bool": {
          "must": [
            {
              "term": {
                "genres": "genres_value"
              }
            },
            {
              "term": {
                "adult": "adult_value"
              }
            },
            {
              "bool": {
                "must_not": [
                  {
                    "term": {
                      "title": "title_value"
                    }
                  }
                ]
              }
            }
          ],
          "should": [
            {
              "range": {
                "rating": {
                  "gt": 7.0
                }
              }
            }
          ]
        }
      },
      "boost_mode": "multiply",
      "boost": 2.0
    }
  }
}
```

{% endcode %}
{% endtab %}

{% tab title="Java" %}
{% code lineNumbers="true" %}

```java
String queryJson =" { " + 
"    \"function_score\": { " + 
"      \"query\": { " + 
"        \"bool\": { " + 
"          \"must\": [ " + 
"            { " + 
"              \"term\": { " + 
"                \"genres\": \"genres_value\" " + 
"              } " + 
"            }, " + 
"            { " + 
"              \"term\": { " + 
"                \"adult\": \"adult_value\" " + 
"              } " + 
"            }, " + 
"            { " + 
"              \"bool\": { " + 
"                \"must_not\": [ " + 
"                  { " + 
"                    \"term\": { " + 
"                      \"title\": \"title_value\" " + 
"                    } " + 
"                  } " + 
"                ] " + 
"             } " + 
"            } " + 
"          ], " + 
"          \"should\": [ " + 
"            { " + 
"              \"range\": { " + 
"                \"rating\": { " + 
"                  \"gt\": 7.0 " + 
"                } " + 
"              } " + 
"            } " + 
"          ] " + 
"        } " + 
"      }, " + 
"      \"boost_mode\": \"multiply\", " + 
"      \"boost\": 2.0 " + 
"    } " + 
"  } " + 
"} " + 
JsonObject query = JsonParser.parseString(queryJson).getAsJsonObject();
Object response = client.dslSearch(collectionName, 10, query));
```

{% endcode %}
{% endtab %}

{% tab title="JavaScript" %}
{% code lineNumbers="true" %}

```javascript
let query = {
  "query": {
    "function_score": {
      "query": {
        "bool": {
          "must": [
            {
              "term": {
                "genres": "genres_value"
              }
            },
            {
              "term": {
                "adult": "adult_value"
              }
            },
            {
              "bool": {
                "must_not": [
                  {
                    "term": {
                      "title": "title_value"
                    }
                  }
                ]
              }
            }
          ],
          "should": [
            {
              "range": {
                "rating": {
                  "gt": 7.0
                }
              }
            }
          ]
        }
      },
      "boost_mode": "multiply",
      "boost": 2.0
    }
  }
};
```

{% endcode %}
{% endtab %}
{% endtabs %}


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.hyper-space.io/hyperspace-docs/flows/setting-up/building-and-running-queries/building-a-lexical-search-query.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
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.