# agents-flex

**Repository Path**: codetangxin/agents-flex

## Basic Information

- **Project Name**: agents-flex
- **Description**: Agents-Flex： 一个优雅的 LLM（大语言模型） 应用开发框架
- **Primary Language**: Unknown
- **License**: Apache-2.0
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 789
- **Created**: 2024-01-16
- **Last Updated**: 2024-01-16

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

<h4 align="right"><strong>English</strong> | <a href="./readme_zh.md">简体中文</a></h4>



# Agents-Flex is an elegant LLM Application Framework like LangChain with Java.


## Hello Word

use OpenAi LLM:

```java
 public static void main(String[] args) throws InterruptedException {

    OpenAiConfig config = new OpenAiConfig();
    config.setApiKey("sk-rts5NF6n*******");

    Llm llm = new OpenAiLlm(config);

    Prompt  prompt = new SimplePrompt("Please write a story about a little rabbit defeating a big bad wolf");
    llm.chat(prompt, (llmInstance, message) -> {
        System.out.println("--->" + message.getContent());
    });

    Thread.sleep(10000);
}
```


use Qwen LLM:

```java
 public static void main(String[] args) throws InterruptedException {

    QwenLlmConfig config = new QwenLlmConfig();
    config.setApiKey("sk-28a6be3236****");
    config.setModel("qwen-turbo");

    Llm llm = new QwenLlm(config);

    Prompt  prompt = new SimplePrompt("Please write a story about a little rabbit defeating a big bad wolf");
    llm.chat(prompt, (llmInstance, message) -> {
        System.out.println("--->" + message.getContent());
    });

    Thread.sleep(10000);
}
```


use SparkAi LLM:

```java
 public static void main(String[] args) throws InterruptedException {

    SparkLlmConfig config = new SparkLlmConfig();
    config.setAppId("****");
    config.setApiKey("****");
    config.setApiSecret("****");

    Llm llm = new SparkLlm(config);

    Prompt  prompt = new SimplePrompt("Please write a story about a little rabbit defeating a big bad wolf");
    llm.chat(prompt, (llmInstance, message) -> {
        System.out.println("--->" + message.getContent());
    });

    Thread.sleep(10000);
}
```