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dij-digital/langfuse-php

Composer 安装命令:

composer require dij-digital/langfuse-php

包简介

A langfuse wrapper for PHP

关键字:

README 文档

README

This package provides a wrapper around the Langfuse API, allowing you to easily integrate Langfuse into your PHP applications. It uses as few dependencies as possible.

This package supports the following features:

Prompts

  • Get text prompts
  • Get chat prompts
  • Compile text prompts
  • Compile chat prompts
  • Create text prompts
  • Create chat prompts
  • List prompts (auto-paginated)
  • Update prompt labels
  • Fallback handling for prompt fetching errors
  • Fallback handling when no prompt is found

Ingestion

  • Create and update traces
  • Create and update spans (with nesting)
  • Create and update generations
  • Automatic traceId and parentObservationId threading
  • Sends directly to the Langfuse v2 ingestion API

Scores

  • Create scores
  • Get scores
  • List scores
  • Delete scores
  • V2 API support for scores

Requires PHP 8.3 or PHP 8.4

Install the package using Composer:

composer require dij-digital/langfuse-php

How to use this package

Setup

use DIJ\Langfuse\PHP\Langfuse;
use DIJ\Langfuse\PHP\Transporters\HttpTransporter;
use GuzzleHttp\Client;

$langfuse = new Langfuse(
    transporter: new HttpTransporter(new Client([
        'base_uri' => 'https://cloud.langfuse.com',
        'auth' => ['PUBLIC_KEY', 'SECRET_KEY'],
    ])),
    environment: 'production', // optional, defaults to 'default'
);

Prompts

// Get and compile prompts
$langfuse->prompt()->text(promptName: 'promptName')->compile(params: ['key' => 'value']);
$langfuse->prompt()->chat(promptName: 'chatName')->compile(params: ['key' => 'value']);

// List all prompts (returns a Generator that auto-paginates)
foreach ($langfuse->prompt()->list() as $prompt) {
    echo $prompt->name;
}

// Create a prompt
$langfuse->prompt()->create(promptName: 'promptName', prompt: 'text', type: PromptType::TEXT);

// Update prompt labels
$langfuse->prompt()->update(promptName: 'promptName', version: 1, labels: ['production']);

Ingestion

Every call to trace(), span(), or generation() immediately sends a request to the Langfuse ingestion API. No buffering, no flushing required.

$ingestion = $langfuse->ingestion();
Trace

A trace is the root of an observation tree.

$trace = $ingestion->trace(
    name: 'my-workflow',
    userId: 'user-456',
    input: 'user question',
);

// Update the trace (sends immediately)
$trace->update(
    output: 'final answer',
    metadata: ['duration_ms' => 1234],
);
Span

Spans group related work within a trace. Create them from a Trace or another Span -- traceId and parentObservationId are set automatically.

// Create a span from the trace
$span = $trace->span(name: 'web-search-batch');

// Nest a child span under the parent span
$childSpan = $span->span(name: 'single-search');

// Update spans when work is done
$childSpan->update(output: ['results' => 3], endTime: date('c'));
$span->update(output: ['total' => 3], endTime: date('c'));
Generation

Generations represent LLM calls. Create them from a Trace or Span -- context IDs are threaded automatically.

// Generation on a trace
$gen = $trace->generation(
    input: ['messages' => [['role' => 'user', 'content' => 'Hello']]],
    output: 'Hi there!',
    name: 'llm-call',
    model: 'gpt-4o',
    modelParameters: ['temperature' => 0.7],
    promptName: 'my-prompt',
    promptVersion: 1,
);

// Generation nested under a span
$gen = $span->generation(
    input: 'summarize this',
    output: 'summary text',
    name: 'summarize-call',
    model: 'gpt-4o',
);

// Update a generation after the LLM responds
$gen->update(
    output: 'updated response',
    metadata: ['tokens' => 150],
);
Full example
$ingestion = $langfuse->ingestion();

$trace = $ingestion->trace(
    name: 'handle-request',
    userId: 'user-789',
    input: 'What is the weather?',
);

$span = $trace->span(name: 'search-batch');

    $child = $span->span(name: 'weather-api-call');
    $child->update(output: ['temp' => 22], endTime: date('c'));

    $span->generation(
        input: 'Summarize weather data',
        output: 'It is 22 degrees and sunny.',
        name: 'summarize',
        model: 'gpt-4o',
    );

$span->update(output: ['answer' => 'It is 22 degrees.'], endTime: date('c'));
$trace->update(output: 'It is 22 degrees and sunny.');

Scores

use DIJ\Langfuse\PHP;
use DIJ\Langfuse\PHP\Enums\ScoreDataType;

// Create a score
$score = $langfuse->score()->create(
    traceId: 'trace-id-123',
    name: 'accuracy',
    value: 0.95,
    dataType: ScoreDataType::NUMERIC,
    comment: 'High accuracy score'
);

// Get a specific score (using v2 API)
$score = $langfuse->score()->get('score-id-123');

// List scores with filters (using v2 API)
$scores = $langfuse->score()->list(
    traceId: 'trace-id-123',
    dataType: ScoreDataType::NUMERIC,
    limit: 10
);

// Delete a score
$langfuse->score()->delete('score-id-123');

Architecture

Langfuse(transporter, environment?)
├── prompt()                → Prompt
│                                 ├── text()     → TextPromptResponse|FallbackPrompt
│                                 ├── chat()     → ChatPromptResponse|FallbackPrompt
│                                 ├── list()     → Generator<PromptListItem>
│                                 ├── create()   → TextPromptResponse|ChatPromptResponse
│                                 └── update()   → TextPromptResponse|ChatPromptResponse
├── ingestion()             → Ingestion
│                             ├── trace()      → Trace
│                             │                   ├── update()
│                             │                   ├── span()       → Span
│                             │                   └── generation() → Generation
│                             ├── span()       → Span
│                             │                   ├── update()
│                             │                   ├── span()       → Span
│                             │                   └── generation() → Generation
│                             └── generation() → Generation
│                                                 └── update()
└── score()                 → Score
                              ├── create()
                              ├── get()
                              ├── list()
                              └── delete()

Each trace(), span(), generation(), and update() call sends a request to the Langfuse POST /api/public/ingestion endpoint immediately. Langfuse PHP was created by Tycho Engberink and is maintained by DIJ Digital under the MIT license.

dij-digital/langfuse-php 适用场景与选型建议

dij-digital/langfuse-php 是一款 基于 PHP 开发的 Composer 扩展包,目前已累计 8.49k 次下载、GitHub Stars 达 10, 最近一次更新时间为 2025 年 06 月 24 日, 在 PHP 生态内属于活跃度较高的组件。

它主要适用于以下技术方向: 「php」 「langfuse」 等业务场景。在实际项目中,围绕这些方向常见需要落地的问题包括:接口对接、性能调优、并发安全、与既有框架(Laravel / ThinkPHP / Yii / Webman 等)的兼容适配,以及生产环境的日志埋点与稳定性保障。

我们在过去多个企业项目中使用过 dij-digital/langfuse-php 或与其功能相近的方案,如果你在选型或落地过程中遇到问题,例如 版本兼容、二次改造、私有化封装、与内部系统对接、生产 BUG 排查,欢迎联系我们协助评估。

围绕 dij-digital/langfuse-php 我们能提供哪些服务?
定制开发 / 二次开发

基于 dij-digital/langfuse-php 在你已有业务上做功能扩展、字段裁剪、UI 适配、与内部账号 / 权限 / 日志系统的深度对接。

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统计信息

  • 总下载量: 8.49k
  • 月度下载量: 0
  • 日度下载量: 0
  • 收藏数: 10
  • 点击次数: 20
  • 依赖项目数: 1
  • 推荐数: 0

GitHub 信息

  • Stars: 10
  • Watchers: 0
  • Forks: 1
  • 开发语言: PHP

其他信息

  • 授权协议: MIT
  • 更新时间: 2025-06-24