長度

length 篩選器會移除不符合指定長度要求的標記，讓您能夠控制在文字處理過程中保留的標記長度。

設定

length 過濾器是 Milvus 中的自訂過濾器，可透過在過濾器設定中設定 `"type": "length" ` 來指定。您可以在 `analyzer_params ` 中將其設定為字典，以定義長度限制。

analyzer_params = {
    "tokenizer": "standard",
    "filter":[{
        "type": "length", # Specifies the filter type as length
        "max": 10, # Sets the maximum token length to 10 characters
    }],
}

import java.util.Collections;
import java.util.HashMap;
import java.util.Map;

Map<String, Object> analyzerParams = new HashMap<>();
analyzerParams.put("tokenizer", "standard");
analyzerParams.put("filter",
        Collections.singletonList(new HashMap<String, Object>() {{
            put("type", "length");
            put("max", 10);
        }}));

analyzerParams := map[string]any{"tokenizer": "standard",
    "filter": []any{map[string]any{
        "type": "length",
        "max":  10,
    }}}

let analyzer_params = serde_json::json!({
    "tokenizer": "standard",
    "filter": [
        {
            "type": "length",
            "max": 10
        }
    ]
});

nlohmann::json analyzer_params = {
    {"tokenizer", "standard"},
    {"filter", {
        {{"type", "length"}, {"max", 10}}
    }}
};

const analyzer_params = {
    "tokenizer": "standard",
    "filter":[{
        "type": "length", // Specifies the filter type as length
        "max": 10, // Sets the maximum token length to 10 characters
    }],
};

using System.Collections.Generic;

var analyzerParams = new Dictionary<string, object>
{
    ["tokenizer"] = "standard",
    ["filter"] = new object[]
    {
        new Dictionary<string, object>
        {
            ["type"] = "length", // Specifies the filter type as length
            ["max"] = 10 // Sets the maximum token length to 10 characters
        }
    }
};

# restful
analyzerParams='{
  "tokenizer": "standard",
  "filter": [
    {
      "type": "length",
      "max": 10
    }
  ]
}'

length 篩選器接受以下可配置參數。

參數	說明
max	設定最大標記長度。超過此長度的標記將被移除。

length 過濾器是針對分詞器所產生的術語進行處理，因此必須與分詞器搭配使用。有關 Milvus 中可用的分詞器清單，請參閱「標準分詞器」及其相關頁面。

定義完analyzer_params 後，您可在定義集合架構時將其套用至VARCHAR 欄位。這使Milvus能使用指定的分析器處理該欄位中的文字，以實現高效的分詞與過濾。詳細資訊請參閱「使用範例」。

範例

在將分析器設定套用至您的集合架構之前，請先使用 `run_analyzer ` 方法驗證其運作行為。

分析器設定

analyzer_params = {
    "tokenizer": "standard",
    "filter":[{
        "type": "length", # Specifies the filter type as length
        "max": 10, # Sets the maximum token length to 10 characters
    }],
}

import java.util.Collections;
import java.util.HashMap;
import java.util.Map;

Map<String, Object> analyzerParams = new HashMap<>();
analyzerParams.put("tokenizer", "standard");
analyzerParams.put("filter",
        Collections.singletonList(new HashMap<String, Object>() {{
            put("type", "length");
            put("max", 10);
        }}));

analyzerParams := map[string]any{"tokenizer": "standard",
    "filter": []any{map[string]any{
        "type": "length",
        "max":  10,
    }}}

let analyzer_params = serde_json::json!({
    "tokenizer": "standard",
    "filter": [
        {
            "type": "length",
            "max": 10
        }
    ]
});

nlohmann::json analyzer_params = {
    {"tokenizer", "standard"},
    {"filter", {
        {{"type", "length"}, {"max", 10}}
    }}
};

const analyzer_params = {
    "tokenizer": "standard",
    "filter":[{
        "type": "length", // Specifies the filter type as length
        "max": 10, // Sets the maximum token length to 10 characters
    }],
};

using System.Collections.Generic;

var analyzerParams = new Dictionary<string, object>
{
    ["tokenizer"] = "standard",
    ["filter"] = new object[]
    {
        new Dictionary<string, object>
        {
            ["type"] = "length", // Specifies the filter type as length
            ["max"] = 10 // Sets the maximum token length to 10 characters
        }
    }
};

# restful
analyzerParams='{
  "tokenizer": "standard",
  "filter": [
    {
      "type": "length",
      "max": 10
    }
  ]
}'

使用以下方式進行驗證run_analyzer

from pymilvus import (
    MilvusClient,
)

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

# Sample text to analyze
sample_text = "The length filter allows control over token length requirements for 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 length filter allows control over token length requirements for 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 length filter allows control over token length requirements for 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("Standard analyzer output:", token.Text)
    }
}

use milvus::v2::error::Result;
use milvus::v2::prelude::*;

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

let sample_text = "The length filter allows control over token length requirements for text processing.";
let result = client
    .run_analyzer(
        RunAnalyzerRequest::builder()
            .texts(vec![sample_text])
            .analyzer_params(analyzer_params)
            .build()?,
    )
    .await?;

println!("Standard analyzer output: {:?}", result);

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

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 length filter allows control over token length requirements for 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",
});

// Sample text to analyze
const sample_text = "The length filter allows control over token length requirements for text processing.";

// Run the standard analyzer with the defined configuration
const result = await client.runAnalyzer({
    text: sample_text,
    analyzer_params: analyzer_params
});
console.log("Standard analyzer output:", result);

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

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

// Sample text to analyze
var sampleText = "The length filter allows control over token length requirements for text processing.";

// Run the standard analyzer with the defined configuration
RunAnalyzerResp result = await client.RunAnalyzerAsync(new RunAnalyzerReq
{
    AnalyzerParams = analyzerParams,
    Texts = new[] { sampleText }
});
Console.WriteLine("Standard analyzer output: " + string.Join(", ", result.Results.SelectMany(r => r.Tokens).Select(t => t.Token)));

export CLUSTER_ENDPOINT="http://localhost:19530"
export TOKEN="root:Milvus"

curl --request POST \
--url "${CLUSTER_ENDPOINT}/v2/vectordb/common/run_analyzer" \
--header "Authorization: Bearer ${TOKEN}" \
--header "Content-Type: application/json" \
--header "Request-Timeout: 10" \
-d '{
    "text": ["The length filter allows control over token length requirements for text processing."],
    "analyzerParams": "{\"tokenizer\": \"standard\", \"filter\": [{\"type\": \"length\", \"max\": 10}]}"
}'

預期輸出

['The', 'length', 'filter', 'allows', 'control', 'over', 'token', 'length', 'for', 'text', 'processing']