Struct LlmClient 

pub struct LlmClient { /* private fields */ }

统一LLM客户端

这个客户端提供统一的接口来访问各种LLM服务， 使用V2架构的清晰抽象层。

示例

use llm_connector::{LlmClient, types::{ChatRequest, Message, Role}};

#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
    // 创建OpenAI客户端
    let client = LlmClient::openai("sk-...")?;

    // 创建请求
    let request = ChatRequest {
        model: "gpt-4".to_string(),
        messages: vec![Message::text(Role::User, "Hello, how are you?")],
        ..Default::default()
    };

    // 发送请求
    let response = client.chat(&request).await?;
    println!("Response: {}", response.content);

    Ok(())
}

Implementations

impl LlmClient

pub fn from_provider(provider: Arc<dyn Provider>) -> Self

从任何Provider创建客户端

pub fn openai(api_key: &str) -> Result<Self, LlmConnectorError>

创建OpenAI客户端

参数

• api_key: OpenAI API密钥

示例

use llm_connector::LlmClient;

let client = LlmClient::openai("sk-...").unwrap();

pub fn openai_with_base_url( api_key: &str, base_url: &str, ) -> Result<Self, LlmConnectorError>

创建带有自定义基础URL的OpenAI客户端

参数

• api_key: API密钥
• base_url: 自定义基础URL

示例

use llm_connector::LlmClient;

let client = LlmClient::openai_with_base_url(
    "sk-...",
    "https://api.deepseek.com"
).unwrap();

pub fn azure_openai( api_key: &str, endpoint: &str, api_version: &str, ) -> Result<Self, LlmConnectorError>

创建Azure OpenAI客户端

参数

• api_key: Azure OpenAI API密钥
• endpoint: Azure OpenAI端点
• api_version: API版本

示例

use llm_connector::LlmClient;

let client = LlmClient::azure_openai(
    "your-api-key",
    "https://your-resource.openai.azure.com",
    "2024-02-15-preview"
).unwrap();

pub fn aliyun(api_key: &str) -> Result<Self, LlmConnectorError>

创建阿里云DashScope客户端

参数

• api_key: 阿里云DashScope API密钥

示例

use llm_connector::LlmClient;

let client = LlmClient::aliyun("sk-...").unwrap();

pub fn anthropic(api_key: &str) -> Result<Self, LlmConnectorError>

创建Anthropic Claude客户端

参数

• api_key: Anthropic API密钥 (格式: sk-ant-…)

示例

use llm_connector::LlmClient;

let client = LlmClient::anthropic("sk-ant-...").unwrap();

pub fn zhipu(api_key: &str) -> Result<Self, LlmConnectorError>

创建智谱GLM客户端

参数

• api_key: 智谱GLM API密钥

示例

use llm_connector::LlmClient;

let client = LlmClient::zhipu("your-api-key").unwrap();

pub fn zhipu_openai_compatible(api_key: &str) -> Result<Self, LlmConnectorError>

创建智谱GLM客户端 (OpenAI兼容模式)

参数

• api_key: 智谱GLM API密钥

示例

use llm_connector::LlmClient;

let client = LlmClient::zhipu_openai_compatible("your-api-key").unwrap();

pub fn ollama() -> Result<Self, LlmConnectorError>

创建Ollama客户端 (默认本地地址)

示例

use llm_connector::LlmClient;

let client = LlmClient::ollama().unwrap();

pub fn ollama_with_base_url(base_url: &str) -> Result<Self, LlmConnectorError>

创建带有自定义URL的Ollama客户端

参数

• base_url: Ollama服务的URL

示例

use llm_connector::LlmClient;

let client = LlmClient::ollama_with_base_url("http://192.168.1.100:11434").unwrap();

pub fn openai_compatible( api_key: &str, base_url: &str, service_name: &str, ) -> Result<Self, LlmConnectorError>

创建OpenAI兼容服务客户端

参数

• api_key: API密钥
• base_url: 服务基础URL
• service_name: 服务名称

示例

use llm_connector::LlmClient;

// DeepSeek
let deepseek = LlmClient::openai_compatible(
    "sk-...",
    "https://api.deepseek.com",
    "deepseek"
).unwrap();

// Moonshot
let moonshot = LlmClient::openai_compatible(
    "sk-...",
    "https://api.moonshot.cn",
    "moonshot"
).unwrap();

// LongCat (OpenAI format)
let longcat = LlmClient::openai_compatible(
    "ak_...",
    "https://api.longcat.chat/openai",
    "longcat"
).unwrap();

pub fn longcat_anthropic(api_key: &str) -> Result<Self, LlmConnectorError>

创建LongCat Anthropic格式客户端

LongCat的Anthropic端点使用Bearer认证而不是标准的x-api-key认证

参数

• api_key: LongCat API密钥 (格式: ak_…)

示例

use llm_connector::LlmClient;

let client = LlmClient::longcat_anthropic("ak_...").unwrap();

pub fn longcat_anthropic_with_config( api_key: &str, base_url: Option<&str>, timeout_secs: Option<u64>, proxy: Option<&str>, ) -> Result<Self, LlmConnectorError>

创建带有自定义配置的LongCat Anthropic客户端

pub fn volcengine(api_key: &str) -> Result<Self, LlmConnectorError>

创建火山引擎（Volcengine）客户端

火山引擎使用 OpenAI 兼容的 API 格式，但端点路径不同

参数

• api_key: 火山引擎 API 密钥 (UUID 格式)

示例

use llm_connector::LlmClient;

let client = LlmClient::volcengine("26f962bd-450e-4876-bc32-a732e6da9cd2").unwrap();

pub fn volcengine_with_config( api_key: &str, base_url: Option<&str>, timeout_secs: Option<u64>, proxy: Option<&str>, ) -> Result<Self, LlmConnectorError>

创建带有自定义配置的火山引擎客户端

pub fn tencent(api_key: &str) -> Result<Self, LlmConnectorError>

创建腾讯云混元（Tencent Hunyuan）客户端

腾讯云混元使用 OpenAI 兼容的 API 格式

参数

• api_key: 腾讯云混元 API 密钥 (格式: sk-…)

示例

use llm_connector::LlmClient;

let client = LlmClient::tencent("sk-YMiR2Q7LNWVKVWKivkfPn49geQXT27OZXumFkSS3Ef6FlQ50").unwrap();

pub fn tencent_with_config( api_key: &str, base_url: Option<&str>, timeout_secs: Option<u64>, proxy: Option<&str>, ) -> Result<Self, LlmConnectorError>

创建带有自定义配置的腾讯云混元客户端

pub fn moonshot(api_key: &str) -> Result<Self, LlmConnectorError>

创建 Moonshot（月之暗面）客户端

Moonshot 使用 OpenAI 兼容的 API 格式

参数

• api_key: Moonshot API 密钥 (格式: sk-…)

示例

use llm_connector::LlmClient;

let client = LlmClient::moonshot("sk-...").unwrap();

pub fn moonshot_with_config( api_key: &str, base_url: Option<&str>, timeout_secs: Option<u64>, proxy: Option<&str>, ) -> Result<Self, LlmConnectorError>

创建带有自定义配置的 Moonshot 客户端

pub fn deepseek(api_key: &str) -> Result<Self, LlmConnectorError>

创建 DeepSeek 客户端

DeepSeek 使用 OpenAI 兼容的 API 格式，支持推理模型

参数

• api_key: DeepSeek API 密钥 (格式: sk-…)

示例

use llm_connector::LlmClient;

let client = LlmClient::deepseek("sk-...").unwrap();

pub fn deepseek_with_config( api_key: &str, base_url: Option<&str>, timeout_secs: Option<u64>, proxy: Option<&str>, ) -> Result<Self, LlmConnectorError>

创建带有自定义配置的 DeepSeek 客户端

pub fn openai_with_config( api_key: &str, base_url: Option<&str>, timeout_secs: Option<u64>, proxy: Option<&str>, ) -> Result<Self, LlmConnectorError>

创建带有自定义配置的OpenAI客户端

pub fn aliyun_with_config( api_key: &str, base_url: Option<&str>, timeout_secs: Option<u64>, proxy: Option<&str>, ) -> Result<Self, LlmConnectorError>

创建带有自定义配置的Aliyun客户端

pub fn aliyun_international( api_key: &str, region: &str, ) -> Result<Self, LlmConnectorError>

创建Aliyun国际版客户端

pub fn aliyun_private( api_key: &str, base_url: &str, ) -> Result<Self, LlmConnectorError>

创建Aliyun专有云客户端

pub fn aliyun_with_timeout( api_key: &str, timeout_secs: u64, ) -> Result<Self, LlmConnectorError>

创建带有自定义超时的Aliyun客户端

pub fn anthropic_with_config( api_key: &str, base_url: Option<&str>, timeout_secs: Option<u64>, proxy: Option<&str>, ) -> Result<Self, LlmConnectorError>

创建带有自定义配置的Anthropic客户端

pub fn anthropic_vertex( project_id: &str, location: &str, access_token: &str, ) -> Result<Self, LlmConnectorError>

创建Anthropic Vertex AI客户端

pub fn anthropic_bedrock( region: &str, access_key: &str, secret_key: &str, ) -> Result<Self, LlmConnectorError>

创建Anthropic AWS Bedrock客户端

pub fn anthropic_with_timeout( api_key: &str, timeout_secs: u64, ) -> Result<Self, LlmConnectorError>

创建带有自定义超时的Anthropic客户端

pub fn zhipu_with_config( api_key: &str, openai_compatible: bool, base_url: Option<&str>, timeout_secs: Option<u64>, proxy: Option<&str>, ) -> Result<Self, LlmConnectorError>

创建带有自定义配置的Zhipu客户端

pub fn zhipu_with_timeout( api_key: &str, timeout_secs: u64, ) -> Result<Self, LlmConnectorError>

创建带有自定义超时的Zhipu客户端

pub fn zhipu_enterprise( api_key: &str, base_url: &str, ) -> Result<Self, LlmConnectorError>

创建Zhipu企业版客户端

pub fn ollama_with_config( base_url: &str, timeout_secs: Option<u64>, proxy: Option<&str>, ) -> Result<Self, LlmConnectorError>

创建带有自定义配置的Ollama客户端

pub fn provider_name(&self) -> &str

获取提供商名称

pub async fn chat( &self, request: &ChatRequest, ) -> Result<ChatResponse, LlmConnectorError>

发送聊天完成请求

参数

• request: 聊天请求

返回

聊天响应

示例

use llm_connector::LlmClient;
use llm_connector::types::{ChatRequest, Message};

#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
    let client = LlmClient::openai("sk-...")?;

    let request = ChatRequest {
        model: "gpt-4".to_string(),
        messages: vec![Message::user("Hello!")],
        ..Default::default()
    };

    let response = client.chat(&request).await?;
    println!("Response: {}", response.content);

    Ok(())
}

pub async fn models(&self) -> Result<Vec<String>, LlmConnectorError>

获取可用模型列表

返回

模型名称列表

示例

use llm_connector::LlmClient;

#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
    let client = LlmClient::openai("sk-...")?;

    let models = client.models().await?;
    for model in models {
        println!("Available model: {}", model);
    }

    Ok(())
}

pub fn provider(&self) -> &dyn Provider

获取底层提供商的引用 (用于特殊功能访问)

示例

use llm_connector::LlmClient;

let client = LlmClient::openai("sk-...").unwrap();
let provider = client.provider();

// 可以进行类型转换以访问特定提供商的功能

pub fn as_ollama(&self) -> Option<&OllamaProvider>

尝试将客户端转换为OllamaProvider

返回

如果底层Provider是OllamaProvider，返回Some引用，否则返回None

示例

use llm_connector::LlmClient;

let client = LlmClient::ollama()?;
if let Some(_ollama) = client.as_ollama() {
    // 可以访问 Ollama 特定的功能
}

pub fn as_openai(&self) -> Option<&OpenAIProvider>

尝试将客户端转换为OpenAIProvider

pub fn as_aliyun(&self) -> Option<&AliyunProvider>

尝试将客户端转换为AliyunProvider

pub fn as_anthropic(&self) -> Option<&AnthropicProvider>

尝试将客户端转换为AnthropicProvider

pub fn as_zhipu(&self) -> Option<&ZhipuProvider>

尝试将客户端转换为ZhipuProvider

Trait Implementations

impl Clone for LlmClient

fn clone(&self) -> Self

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for LlmClient

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.