Lowercase

The lowercase filter converts terms generated by a tokenizer to lowercase, making searches case-insensitive. For example, it can convert ["High", "Performance", "Vector", "Database"] to ["high", "performance", "vector", "database"].

Configuration

The lowercase filter is built into Milvus. To use it, simply specify its name in the filter section within analyzer_params.

analyzer_params = {
    "tokenizer": "standard",
    "filter": ["lowercase"],
}

Map<String, Object> analyzerParams = new HashMap<>();
analyzerParams.put("tokenizer", "standard");
analyzerParams.put("filter", Collections.singletonList("lowercase"));

analyzerParams := map[string]any{"tokenizer": "standard", "filter": []any{"lowercase"}}

use serde_json::json;

let analyzer_params = json!({
    "tokenizer": "standard",
    "filter": ["lowercase"]
});

#include <milvus/thirdparty/nlohmann/json.hpp>

nlohmann::json analyzer_params = {
    {"tokenizer", "standard"},
    {"filter", {"lowercase"}}
};

const analyzer_params = {
    "tokenizer": "standard",
    "filter": ["lowercase"],
};

using System.Collections.Generic;

Dictionary<string, object> analyzerParams = new()
{
    ["tokenizer"] = "standard",
    ["filter"] = new List<object> { "lowercase" }
};

# restful
analyzerParams='{
  "tokenizer": "standard",
  "filter": [
    "lowercase"
  ]
}'

The lowercase filter operates on the terms generated by the tokenizer, so it must be used in combination with a tokenizer.

After defining analyzer_params, you can apply them to a VARCHAR field when defining a collection schema. This allows Milvus to process the text in that field using the specified analyzer for efficient tokenization and filtering. For details, refer to Example use.

Examples

Before applying the analyzer configuration to your collection schema, verify its behavior using the run_analyzer method.

Analyzer configuration

analyzer_params = {
    "tokenizer": "standard",
    "filter": ["lowercase"],
}

Map<String, Object> analyzerParams = new HashMap<>();
analyzerParams.put("tokenizer", "standard");
analyzerParams.put("filter", Collections.singletonList("lowercase"));

analyzerParams := map[string]any{"tokenizer": "standard", "filter": []any{"lowercase"}}

use serde_json::json;

let analyzer_params = json!({
    "tokenizer": "standard",
    "filter": ["lowercase"]
});

#include <milvus/thirdparty/nlohmann/json.hpp>

nlohmann::json analyzer_params = {
    {"tokenizer", "standard"},
    {"filter", {"lowercase"}}
};

const analyzer_params = {
    "tokenizer": "standard",
    "filter": ["lowercase"],
}

using System.Collections.Generic;

Dictionary<string, object> analyzerParams = new()
{
    ["tokenizer"] = "standard",
    ["filter"] = new List<object> { "lowercase" }
};

# restful
analyzerParams='{
  "tokenizer": "standard",
  "filter": [
    "lowercase"
  ]
}'

Verification using run_analyzer

from pymilvus import (
    MilvusClient,
)

client = MilvusClient(
    uri="http://localhost:19530",
    token="root:Milvus"
)

# Sample text to analyze
sample_text = "The Lowercase Filter Ensures Uniformity In Text Processing."

# Run the standard analyzer with the defined configuration
result = client.run_analyzer(sample_text, analyzer_params)
print("Standard analyzer output:", result)

import java.util.*;
import io.milvus.v2.client.ConnectConfig;
import io.milvus.v2.client.MilvusClientV2;
import io.milvus.v2.service.vector.request.RunAnalyzerReq;
import io.milvus.v2.service.vector.response.RunAnalyzerResp;

ConnectConfig config = ConnectConfig.builder()
        .uri("http://localhost:19530")
        .token("root:Milvus")
        .build();
MilvusClientV2 client = new MilvusClientV2(config);

List<String> texts = new ArrayList<>();
texts.add("The Lowercase Filter Ensures Uniformity In Text Processing.");

RunAnalyzerResp resp = client.runAnalyzer(RunAnalyzerReq.builder()
        .texts(texts)
        .analyzerParams(analyzerParams)
        .build());
List<RunAnalyzerResp.AnalyzerResult> results = resp.getResults();

import (
    "context"
    "fmt"

    "github.com/milvus-io/milvus/client/v3/milvusclient"
)

ctx := context.Background()

client, err := milvusclient.New(ctx, &milvusclient.ClientConfig{
    Address: "http://localhost:19530",
    APIKey:  "root:Milvus",
})
if err != nil {
    fmt.Println(err.Error())
    // handle error
}

texts := []string{"The Lowercase Filter Ensures Uniformity In Text Processing."}
option := milvusclient.NewRunAnalyzerOption(texts...).
    WithAnalyzerParams(analyzerParams)

result, err := client.RunAnalyzer(ctx, option)
if err != nil {
    fmt.Println(err.Error())
    // handle error
}

for _, r := range result {
    for _, token := range r.Tokens {
        fmt.Println(token.Text)
    }
}

use milvus::v2::prelude::*;

let config = ConnectConfig::new().uri("http://localhost:19530").token("root:Milvus");
let client = ClientV2::new(&config).await?;

let response = client
    .run_analyzer(
        RunAnalyzerRequest::builder()
            .texts(["The Lowercase Filter Ensures Uniformity In Text Processing."])
            .analyzer_params(analyzer_params)
            .build()?,
    )
    .await?;

for result in response.results() {
    for token in result.get_tokens() {
        println!("Standard analyzer output: {}", token.get_text());
    }
}

#include "milvus/MilvusClientV2.h"
#include <string>
#include <iostream>

auto client = milvus::MilvusClientV2::Create();

milvus::ConnectParam connect_param{"http://localhost:19530", "root:Milvus"};
auto status = client->Connect(connect_param);
if (!status.IsOk()) {
    std::cout << status.Message() << std::endl;
}

std::string text = "The Lowercase Filter Ensures Uniformity In Text Processing.";
auto request = milvus::RunAnalyzerRequest()
                       .AddText(text)
                       .WithAnalyzerParams(analyzer_params);

milvus::RunAnalyzerResponse response;
status = client->RunAnalyzer(request, response);
if (!status.IsOk()) {
    std::cout << status.Message() << std::endl;
}

import { MilvusClient } from '@zilliz/milvus2-sdk-node';

const client = new MilvusClient({
  address: 'http://localhost:19530',
  token: "root:Milvus",
});

const sample_text = 'The Lowercase Filter Ensures Uniformity In Text Processing.';
const result = await client.runAnalyzer({
  text: sample_text,
  analyzer_params,
});
const tokens = result.results.flatMap(r => r.tokens.map(t => t.token));
console.log('Standard analyzer output:', tokens);

using System;
using Milvus.Client.V2;
using Milvus.Client.V2.Requests.Utility;
using Milvus.Client.V2.Responses.Utility;
using Milvus.Client.V2.Types;

MilvusClientV2 client = new(new ConnectConfig
{
    Uri = "http://localhost:19530",
    ApiKey = "root:Milvus"
});

// Sample text to analyze
string sampleText = "The Lowercase Filter Ensures Uniformity In Text Processing.";

// Run the standard analyzer with the defined configuration
RunAnalyzerResp result = await client.RunAnalyzerAsync(new RunAnalyzerReq
{
    AnalyzerParams = analyzerParams,
    Texts = [sampleText]
});

foreach (AnalyzerResult r in result.Results)
{
    foreach (AnalyzerToken t in r.Tokens)
    {
        Console.WriteLine($"Standard analyzer output: {t.Token}");
    }
}

curl --request POST \
  --url "http://localhost:19530/v2/vectordb/common/run_analyzer" \
  --header "Authorization: Bearer root:Milvus" \
  --header "Content-Type: application/json" \
  --data-raw '{
    "analyzerParams": "{\"tokenizer\": \"standard\", \"filter\": [\"lowercase\"]}",
    "text": ["The Lowercase Filter Ensures Uniformity In Text Processing."]
  }'

Expected output

['the', 'lowercase', 'filter', 'ensures', 'uniformity', 'in', 'text', 'processing']