66 lines
2.0 KiB
Rust
66 lines
2.0 KiB
Rust
use text_video_agent_client::apis::configuration::Configuration;
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use text_video_agent_client::apis::{default_api, midjourney_api, llm_api};
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#[tokio::main]
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async fn main() -> Result<(), Box<dyn std::error::Error>> {
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// 创建支持 HTTPS 的客户端
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let client = reqwest::Client::builder()
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.timeout(std::time::Duration::from_secs(30))
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.build()?;
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// 创建配置
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let config = Configuration {
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base_path: "https://bowongai-dev--text-video-agent-fastapi-app.modal.run".to_string(),
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user_agent: Some("text-video-agent-rust-client/1.0.6".to_string()),
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client,
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basic_auth: None,
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oauth_access_token: None,
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bearer_access_token: None,
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api_key: None,
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};
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println!("🚀 文本视频智能体 API 健康检查");
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println!("================================");
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println!("API 地址: {}", config.base_path);
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println!();
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// 1. 测试根路径
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println!("📍 测试根路径...");
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match default_api::root_get(&config).await {
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Ok(response) => {
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println!("✅ 根路径响应: {}", response);
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}
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Err(e) => {
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println!("❌ 根路径错误: {:?}", e);
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}
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}
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println!();
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// 2. 测试 Midjourney 健康检查
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println!("🎨 测试 Midjourney 健康检查...");
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match midjourney_api::health_check_api_mj_health_get(&config).await {
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Ok(response) => {
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println!("✅ Midjourney 健康状态: {}", response);
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}
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Err(e) => {
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println!("❌ Midjourney 健康检查错误: {:?}", e);
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}
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}
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println!();
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// 3. 测试获取支持的 LLM 模型
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println!("🧠 获取支持的 LLM 模型...");
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match llm_api::llm_supported_models(&config).await {
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Ok(response) => {
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println!("✅ 支持的模型: {}", response);
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}
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Err(e) => {
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println!("❌ 获取模型列表错误: {:?}", e);
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}
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}
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println!();
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println!("🎯 健康检查完成！");
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Ok(())
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}
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