feat(api): add health check and models endpoints with documentation

- Add /health endpoint to check service status for orchestration systems
- Add /models endpoint with OpenAI API compatible format
- Document new endpoints in both English and Chinese API docs
- Include example usage and response formats in documentation
- Add comprehensive test coverage for health and models endpoints
- Refactor model storage to include type information alongside instance
- Move model ID and type methods to WhichModel implementation
- Update API calls to access model instance through stored wrapper
This commit is contained in:
XiaoYang
2026-02-08 12:10:40 +08:00
parent 38ea72e407
commit 390d916ea6
6 changed files with 536 additions and 36 deletions
+86
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@@ -57,6 +57,92 @@ Error responses:
## Endpoints ## Endpoints
### Health Check
Check the service health status. This endpoint is useful for container orchestration (Kubernetes), load balancers, and monitoring systems.
#### Endpoint
```
GET /health
```
#### Response
**Healthy (HTTP 200):**
```json
{
"status": "ok"
}
```
**Unhealthy (HTTP 503):**
```json
{
"status": "unhealthy",
"error": "model not initialized"
}
```
#### Example
```bash
curl http://127.0.0.1:10100/health
```
### Models
Get information about the currently loaded model (OpenAI API compatible format).
#### Endpoint
```
GET /models
```
#### Response
**Success (HTTP 200):**
```json
{
"object": "list",
"data": [
{
"id": "qwen3-0.6b",
"object": "model",
"created": null,
"owned_by": "Qwen"
}
]
}
```
**Not Initialized (HTTP 503):**
```json
{
"error": "model not initialized"
}
```
#### Fields
| Field | Type | Description |
|-------|------|-------------|
| `object` | string | Fixed value: "list" |
| `data` | array | Array of model objects (currently contains one loaded model) |
| `id` | string | Model identifier in kebab-case (e.g., "qwen3-0.6b") |
| `object` | string | Fixed value: "model" |
| `created` | integer\|null | Unix timestamp (currently null) |
| `owned_by` | string | Model owner/organization name |
#### Example
```bash
curl http://127.0.0.1:10100/models
```
### Chat Completions ### Chat Completions
Generate chat completions or text responses. Generate chat completions or text responses.
+86
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@@ -57,6 +57,92 @@ Content-Type: application/json
## 端点 ## 端点
### 健康检查
检查服务健康状态。此端点适用于容器编排(Kubernetes)、负载均衡器和监控系统。
#### 端点
```
GET /health
```
#### 响应
**健康 (HTTP 200):**
```json
{
"status": "ok"
}
```
**不健康 (HTTP 503):**
```json
{
"status": "unhealthy",
"error": "model not initialized"
}
```
#### 示例
```bash
curl http://127.0.0.1:10100/health
```
### 模型列表
获取当前加载的模型信息(OpenAI API 兼容格式)。
#### 端点
```
GET /models
```
#### 响应
**成功 (HTTP 200):**
```json
{
"object": "list",
"data": [
{
"id": "qwen3-0.6b",
"object": "model",
"created": null,
"owned_by": "Qwen"
}
]
}
```
**未初始化 (HTTP 503):**
```json
{
"error": "model not initialized"
}
```
#### 字段
| 字段 | 类型 | 描述 |
|------|------|------|
| `object` | string | 固定值:"list" |
| `data` | array | 模型对象数组(当前仅包含一个已加载的模型) |
| `id` | string | 模型标识符(kebab-case,如 "qwen3-0.6b" |
| `object` | string | 固定值:"model" |
| `created` | integer\|null | Unix 时间戳(当前为 null |
| `owned_by` | string | 模型所有者/组织名称 |
#### 示例
```bash
curl http://127.0.0.1:10100/models
```
### 对话补全 ### 对话补全
生成对话补全或文本响应。 生成对话补全或文本响应。
+234 -7
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@@ -5,22 +5,32 @@ use aha::models::{GenerateModel, ModelInstance, WhichModel, load_model};
use aha::utils::string_to_static_str; use aha::utils::string_to_static_str;
use aha_openai_dive::v1::resources::chat::ChatCompletionParameters; use aha_openai_dive::v1::resources::chat::ChatCompletionParameters;
use rocket::futures::StreamExt; use rocket::futures::StreamExt;
use rocket::serde::json::Json; use rocket::serde::{json::Json, Serialize};
use rocket::{ use rocket::{
Request, Request,
futures::Stream, futures::Stream,
get,
http::{ContentType, Status}, http::{ContentType, Status},
post, post,
response::{Responder, stream::TextStream}, response::{Responder, stream::TextStream},
}; };
use tokio::sync::RwLock; use tokio::sync::RwLock;
static MODEL: OnceLock<Arc<RwLock<ModelInstance<'static>>>> = OnceLock::new(); /// Wrapper to store model type together with the model instance
struct StoredModel {
which_model: WhichModel,
instance: ModelInstance<'static>,
}
static MODEL: OnceLock<Arc<RwLock<StoredModel>>> = OnceLock::new();
pub fn init(model_type: WhichModel, path: String) -> anyhow::Result<()> { pub fn init(model_type: WhichModel, path: String) -> anyhow::Result<()> {
let model_path = string_to_static_str(path); let model_path = string_to_static_str(path);
let model = load_model(model_type, model_path)?; let model = load_model(model_type, model_path)?;
MODEL.get_or_init(|| Arc::new(RwLock::new(model))); MODEL.get_or_init(|| Arc::new(RwLock::new(StoredModel {
which_model: model_type,
instance: model,
})));
Ok(()) Ok(())
} }
@@ -62,7 +72,8 @@ pub(crate) async fn chat(
.cloned() .cloned()
.ok_or_else(|| anyhow::anyhow!("model not init")) .ok_or_else(|| anyhow::anyhow!("model not init"))
.unwrap(); .unwrap();
model_ref.write().await.generate(req.into_inner()) let mut guard = model_ref.write().await;
guard.instance.generate(req.into_inner())
}; };
match response { match response {
Ok(res) => { Ok(res) => {
@@ -76,7 +87,7 @@ pub(crate) async fn chat(
let text_stream = TextStream! { let text_stream = TextStream! {
let model_ref = MODEL.get().cloned().ok_or_else(|| anyhow::anyhow!("model not init")).unwrap(); let model_ref = MODEL.get().cloned().ok_or_else(|| anyhow::anyhow!("model not init")).unwrap();
let mut guard = model_ref.write().await; let mut guard = model_ref.write().await;
let stream_result = guard.generate_stream(req.into_inner()); let stream_result = guard.instance.generate_stream(req.into_inner());
match stream_result { match stream_result {
Ok(stream) => { Ok(stream) => {
let mut stream = pin!(stream); let mut stream = pin!(stream);
@@ -113,7 +124,8 @@ pub(crate) async fn remove_background(req: Json<ChatCompletionParameters>) -> (S
.cloned() .cloned()
.ok_or_else(|| anyhow::anyhow!("model not init")) .ok_or_else(|| anyhow::anyhow!("model not init"))
.unwrap(); .unwrap();
model_ref.write().await.generate(req.into_inner()) let mut guard = model_ref.write().await;
guard.instance.generate(req.into_inner())
}; };
match response { match response {
Ok(res) => { Ok(res) => {
@@ -132,7 +144,8 @@ pub(crate) async fn speech(req: Json<ChatCompletionParameters>) -> (Status, Stri
.cloned() .cloned()
.ok_or_else(|| anyhow::anyhow!("model not init")) .ok_or_else(|| anyhow::anyhow!("model not init"))
.unwrap(); .unwrap();
model_ref.write().await.generate(req.into_inner()) let mut guard = model_ref.write().await;
guard.instance.generate(req.into_inner())
}; };
match response { match response {
Ok(res) => { Ok(res) => {
@@ -142,3 +155,217 @@ pub(crate) async fn speech(req: Json<ChatCompletionParameters>) -> (Status, Stri
Err(e) => (Status::InternalServerError, e.to_string()), Err(e) => (Status::InternalServerError, e.to_string()),
} }
} }
// Health check endpoint
#[derive(Serialize)]
pub(crate) struct HealthResponse {
status: String,
#[serde(skip_serializing_if = "Option::is_none")]
error: Option<String>,
}
#[get("/health")]
pub(crate) async fn health() -> (Status, (ContentType, Json<HealthResponse>)) {
if MODEL.get().is_some() {
let response = HealthResponse {
status: "ok".to_string(),
error: None,
};
(Status::Ok, (ContentType::JSON, Json(response)))
} else {
let response = HealthResponse {
status: "unhealthy".to_string(),
error: Some("model not initialized".to_string()),
};
(Status::ServiceUnavailable, (ContentType::JSON, Json(response)))
}
}
// Models endpoint (OpenAI-compatible format)
/// OpenAI-compatible model object
#[derive(Serialize)]
struct ModelObject {
id: String,
object: String,
created: Option<i64>,
owned_by: String,
}
/// OpenAI-compatible models list response
#[derive(Serialize)]
struct ModelsListResponse {
object: String,
data: Vec<ModelObject>,
}
#[derive(Serialize)]
struct ErrorResponse {
error: String,
}
/// Convert WhichModel to a display-friendly model ID (kebab-case)
fn which_model_to_id(which_model: WhichModel) -> &'static str {
match which_model {
WhichModel::MiniCPM4_0_5B => "minicpm4-0.5b",
WhichModel::Qwen2_5vl3B => "qwen2.5vl-3b",
WhichModel::Qwen2_5vl7B => "qwen2.5vl-7b",
WhichModel::Qwen3_0_6B => "qwen3-0.6b",
WhichModel::Qwen3ASR0_6B => "qwen3asr-0.6b",
WhichModel::Qwen3ASR1_7B => "qwen3asr-1.7b",
WhichModel::Qwen3vl2B => "qwen3vl-2b",
WhichModel::Qwen3vl4B => "qwen3vl-4b",
WhichModel::Qwen3vl8B => "qwen3vl-8b",
WhichModel::Qwen3vl32B => "qwen3vl-32b",
WhichModel::DeepSeekOCR => "deepseek-ocr",
WhichModel::HunyuanOCR => "hunyuan-ocr",
WhichModel::PaddleOCRVL => "paddleocr-vl",
WhichModel::RMBG2_0 => "rmbg2.0",
WhichModel::VoxCPM => "voxcpm",
WhichModel::VoxCPM1_5 => "voxcpm1.5",
WhichModel::GlmASRNano2512 => "glm-asr-nano-2512",
WhichModel::FunASRNano2512 => "fun-asr-nano-2512",
}
}
/// Get the owner/organization name for a model
fn which_model_to_owner(which_model: WhichModel) -> &'static str {
match which_model {
WhichModel::MiniCPM4_0_5B => "OpenBMB",
WhichModel::Qwen2_5vl3B | WhichModel::Qwen2_5vl7B => "Qwen",
WhichModel::Qwen3_0_6B | WhichModel::Qwen3ASR0_6B | WhichModel::Qwen3ASR1_7B => "Qwen",
WhichModel::Qwen3vl2B | WhichModel::Qwen3vl4B | WhichModel::Qwen3vl8B | WhichModel::Qwen3vl32B => "Qwen",
WhichModel::DeepSeekOCR => "deepseek-ai",
WhichModel::HunyuanOCR => "Tencent-Hunyuan",
WhichModel::PaddleOCRVL => "PaddlePaddle",
WhichModel::RMBG2_0 => "AI-ModelScope",
WhichModel::VoxCPM | WhichModel::VoxCPM1_5 => "OpenBMB",
WhichModel::GlmASRNano2512 => "ZhipuAI",
WhichModel::FunASRNano2512 => "FunAudioLLM",
}
}
#[get("/models")]
pub(crate) async fn models() -> (Status, (ContentType, Json<serde_json::Value>))
{
if let Some(model_ref) = MODEL.get() {
let guard = model_ref.read().await;
let which_model = guard.which_model;
let model_obj = ModelObject {
id: which_model_to_id(which_model).to_string(),
object: "model".to_string(),
created: None, // We don't track creation time
owned_by: which_model_to_owner(which_model).to_string(),
};
drop(guard);
let response = ModelsListResponse {
object: "list".to_string(),
data: vec![model_obj],
};
(Status::Ok, (ContentType::JSON, Json(serde_json::to_value(response).unwrap())))
} else {
let response = ErrorResponse {
error: "model not initialized".to_string(),
};
(Status::ServiceUnavailable, (ContentType::JSON, Json(serde_json::to_value(response).unwrap())))
}
}
#[cfg(test)]
mod tests {
use super::*;
// Test health endpoint when model is not initialized
#[tokio::test]
async fn test_health_endpoint_uninitialized() {
let (status, (content_type, response)) = health().await;
assert_eq!(status, Status::ServiceUnavailable);
assert_eq!(content_type, ContentType::JSON);
assert_eq!(response.status, "unhealthy");
assert_eq!(response.error, Some("model not initialized".to_string()));
}
// Test health endpoint when model is initialized
// Note: This test requires a model to be initialized, which may not be feasible
// in unit tests without access to model files. This is a placeholder for integration tests.
//
// #[tokio::test]
// async fn test_health_endpoint_initialized() {
// // This would require model initialization
// // Consider moving to integration tests
// }
// Test models endpoint when model is not initialized
#[tokio::test]
async fn test_models_endpoint_uninitialized() {
let (status, (content_type, response)) = models().await;
assert_eq!(status, Status::ServiceUnavailable);
assert_eq!(content_type, ContentType::JSON);
let error = response.get("error").and_then(|v| v.as_str());
assert_eq!(error, Some("model not initialized"));
}
// Test model type classification
#[test]
fn test_get_model_type_llm() {
assert_eq!(WhichModel::Qwen3_0_6B.model_type(), "llm");
assert_eq!(WhichModel::Qwen3vl2B.model_type(), "llm");
assert_eq!(WhichModel::MiniCPM4_0_5B.model_type(), "llm");
assert_eq!(WhichModel::Qwen2_5vl3B.model_type(), "llm");
assert_eq!(WhichModel::Qwen2_5vl7B.model_type(), "llm");
assert_eq!(WhichModel::Qwen3vl4B.model_type(), "llm");
assert_eq!(WhichModel::Qwen3vl8B.model_type(), "llm");
assert_eq!(WhichModel::Qwen3vl32B.model_type(), "llm");
}
#[test]
fn test_get_model_type_ocr() {
assert_eq!(WhichModel::DeepSeekOCR.model_type(), "ocr");
assert_eq!(WhichModel::HunyuanOCR.model_type(), "ocr");
assert_eq!(WhichModel::PaddleOCRVL.model_type(), "ocr");
}
#[test]
fn test_get_model_type_asr() {
assert_eq!(WhichModel::Qwen3ASR0_6B.model_type(), "asr");
assert_eq!(WhichModel::Qwen3ASR1_7B.model_type(), "asr");
assert_eq!(WhichModel::GlmASRNano2512.model_type(), "asr");
assert_eq!(WhichModel::FunASRNano2512.model_type(), "asr");
}
#[test]
fn test_get_model_type_image() {
assert_eq!(WhichModel::RMBG2_0.model_type(), "image");
assert_eq!(WhichModel::VoxCPM.model_type(), "image");
assert_eq!(WhichModel::VoxCPM1_5.model_type(), "image");
}
// Test model_id retrieval
#[test]
fn test_get_model_id() {
assert_eq!(WhichModel::Qwen3_0_6B.model_id(), "Qwen/Qwen3-0.6B");
assert_eq!(WhichModel::DeepSeekOCR.model_id(), "deepseek-ai/DeepSeek-OCR");
assert_eq!(WhichModel::VoxCPM1_5.model_id(), "OpenBMB/VoxCPM1.5");
}
// Test OpenAI-compatible model ID conversion
#[test]
fn test_which_model_to_id() {
assert_eq!(which_model_to_id(WhichModel::Qwen3_0_6B), "qwen3-0.6b");
assert_eq!(which_model_to_id(WhichModel::DeepSeekOCR), "deepseek-ocr");
assert_eq!(which_model_to_id(WhichModel::VoxCPM1_5), "voxcpm1.5");
assert_eq!(which_model_to_id(WhichModel::MiniCPM4_0_5B), "minicpm4-0.5b");
}
// Test owner/organization mapping
#[test]
fn test_which_model_to_owner() {
assert_eq!(which_model_to_owner(WhichModel::Qwen3_0_6B), "Qwen");
assert_eq!(which_model_to_owner(WhichModel::DeepSeekOCR), "deepseek-ai");
assert_eq!(which_model_to_owner(WhichModel::VoxCPM1_5), "OpenBMB");
assert_eq!(which_model_to_owner(WhichModel::HunyuanOCR), "Tencent-Hunyuan");
}
}
+7 -29
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@@ -145,35 +145,11 @@ struct RunArgs {
/// Get the default weight path for a given model /// Get the default weight path for a given model
/// Returns ~/.aha/{model_id} e.g., ~/.aha/OpenBMB/VoxCPM1.5 /// Returns ~/.aha/{model_id} e.g., ~/.aha/OpenBMB/VoxCPM1.5
fn get_default_weight_path(model: WhichModel) -> String { fn get_default_weight_path(model: WhichModel) -> String {
let model_id = get_model_id(model); let model_id = model.model_id();
let save_dir = get_default_save_dir().expect("Failed to get home directory"); let save_dir = get_default_save_dir().expect("Failed to get home directory");
format!("{}/{}", save_dir, model_id) format!("{}/{}", save_dir, model_id)
} }
/// Get the ModelScope model ID for a given WhichModel variant
fn get_model_id(model: WhichModel) -> &'static str {
match model {
WhichModel::MiniCPM4_0_5B => "OpenBMB/MiniCPM4-0.5B",
WhichModel::Qwen2_5vl3B => "Qwen/Qwen2.5-VL-3B-Instruct",
WhichModel::Qwen2_5vl7B => "Qwen/Qwen2.5-VL-7B-Instruct",
WhichModel::Qwen3_0_6B => "Qwen/Qwen3-0.6B",
WhichModel::Qwen3ASR0_6B => "Qwen/Qwen3-ASR-0.6B",
WhichModel::Qwen3ASR1_7B => "Qwen/Qwen3-ASR-1.7B",
WhichModel::Qwen3vl2B => "Qwen/Qwen3-VL-2B-Instruct",
WhichModel::Qwen3vl4B => "Qwen/Qwen3-VL-4B-Instruct",
WhichModel::Qwen3vl8B => "Qwen/Qwen3-VL-8B-Instruct",
WhichModel::Qwen3vl32B => "Qwen/Qwen3-VL-32B-Instruct",
WhichModel::DeepSeekOCR => "deepseek-ai/DeepSeek-OCR",
WhichModel::HunyuanOCR => "Tencent-Hunyuan/HunyuanOCR",
WhichModel::PaddleOCRVL => "PaddlePaddle/PaddleOCR-VL",
WhichModel::RMBG2_0 => "AI-ModelScope/RMBG-2.0",
WhichModel::VoxCPM => "OpenBMB/VoxCPM-0.5B",
WhichModel::VoxCPM1_5 => "OpenBMB/VoxCPM1.5",
WhichModel::GlmASRNano2512 => "ZhipuAI/GLM-ASR-Nano-2512",
WhichModel::FunASRNano2512 => "FunAudioLLM/Fun-ASR-Nano-2512",
}
}
/// List all supported models /// List all supported models
fn run_list() -> anyhow::Result<()> { fn run_list() -> anyhow::Result<()> {
let models = [ let models = [
@@ -204,7 +180,7 @@ fn run_list() -> anyhow::Result<()> {
for model in models { for model in models {
let possible_value = model.to_possible_value().unwrap(); let possible_value = model.to_possible_value().unwrap();
let name = possible_value.get_name(); let name = possible_value.get_name();
let id = get_model_id(model); let id = model.model_id();
println!("{:<30} {}", name, id); println!("{:<30} {}", name, id);
} }
@@ -219,7 +195,7 @@ async fn run_cli(args: CliArgs) -> anyhow::Result<()> {
save_dir, save_dir,
download_retries, download_retries,
} = args; } = args;
let model_id = get_model_id(common.model); let model_id = common.model.model_id();
let model_path = match weight_path { let model_path = match weight_path {
Some(path) => path, Some(path) => path,
@@ -265,7 +241,7 @@ async fn run_download(args: DownloadArgs) -> anyhow::Result<()> {
save_dir, save_dir,
download_retries, download_retries,
} = args; } = args;
let model_id = get_model_id(model); let model_id = model.model_id();
let save_dir = match save_dir { let save_dir = match save_dir {
Some(dir) => dir, Some(dir) => dir,
@@ -416,8 +392,10 @@ pub(crate) async fn start_http_server(address: String, port: u16) -> anyhow::Res
builder = builder.mount("/chat", routes![api::chat]); builder = builder.mount("/chat", routes![api::chat]);
// /images/remove_background // /images/remove_background
builder = builder.mount("/images", routes![api::remove_background]); builder = builder.mount("/images", routes![api::remove_background]);
// /images/speech // /audio/speech
builder = builder.mount("/audio", routes![api::speech]); builder = builder.mount("/audio", routes![api::speech]);
// Health check and model info endpoints
builder = builder.mount("/", routes![api::health, api::models]);
builder.launch().await?; builder.launch().await?;
Ok(()) Ok(())
+50
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@@ -74,6 +74,56 @@ pub enum WhichModel {
FunASRNano2512, FunASRNano2512,
} }
impl WhichModel {
/// Get the ModelScope model ID for this model variant
pub fn model_id(self) -> &'static str {
match self {
WhichModel::MiniCPM4_0_5B => "OpenBMB/MiniCPM4-0.5B",
WhichModel::Qwen2_5vl3B => "Qwen/Qwen2.5-VL-3B-Instruct",
WhichModel::Qwen2_5vl7B => "Qwen/Qwen2.5-VL-7B-Instruct",
WhichModel::Qwen3_0_6B => "Qwen/Qwen3-0.6B",
WhichModel::Qwen3ASR0_6B => "Qwen/Qwen3-ASR-0.6B",
WhichModel::Qwen3ASR1_7B => "Qwen/Qwen3-ASR-1.7B",
WhichModel::Qwen3vl2B => "Qwen/Qwen3-VL-2B-Instruct",
WhichModel::Qwen3vl4B => "Qwen/Qwen3-VL-4B-Instruct",
WhichModel::Qwen3vl8B => "Qwen/Qwen3-VL-8B-Instruct",
WhichModel::Qwen3vl32B => "Qwen/Qwen3-VL-32B-Instruct",
WhichModel::DeepSeekOCR => "deepseek-ai/DeepSeek-OCR",
WhichModel::HunyuanOCR => "Tencent-Hunyuan/HunyuanOCR",
WhichModel::PaddleOCRVL => "PaddlePaddle/PaddleOCR-VL",
WhichModel::RMBG2_0 => "AI-ModelScope/RMBG-2.0",
WhichModel::VoxCPM => "OpenBMB/VoxCPM-0.5B",
WhichModel::VoxCPM1_5 => "OpenBMB/VoxCPM1.5",
WhichModel::GlmASRNano2512 => "ZhipuAI/GLM-ASR-Nano-2512",
WhichModel::FunASRNano2512 => "FunAudioLLM/Fun-ASR-Nano-2512",
}
}
/// Get the model type category for this model variant
pub fn model_type(self) -> &'static str {
match self {
// LLM models
WhichModel::MiniCPM4_0_5B
| WhichModel::Qwen2_5vl3B
| WhichModel::Qwen2_5vl7B
| WhichModel::Qwen3_0_6B
| WhichModel::Qwen3vl2B
| WhichModel::Qwen3vl4B
| WhichModel::Qwen3vl8B
| WhichModel::Qwen3vl32B => "llm",
// OCR models
WhichModel::DeepSeekOCR | WhichModel::HunyuanOCR | WhichModel::PaddleOCRVL => "ocr",
// ASR models
WhichModel::Qwen3ASR0_6B
| WhichModel::Qwen3ASR1_7B
| WhichModel::GlmASRNano2512
| WhichModel::FunASRNano2512 => "asr",
// Image models
WhichModel::RMBG2_0 | WhichModel::VoxCPM | WhichModel::VoxCPM1_5 => "image",
}
}
}
pub trait GenerateModel { pub trait GenerateModel {
fn generate(&mut self, mes: ChatCompletionParameters) -> Result<ChatCompletionResponse>; fn generate(&mut self, mes: ChatCompletionParameters) -> Result<ChatCompletionResponse>;
fn generate_stream( fn generate_stream(
+73
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@@ -0,0 +1,73 @@
use aha::models::WhichModel;
// Import helper functions from api module - these will need to be made public
// or tested through integration testing
#[test]
fn test_model_type_classification() {
// Since get_model_type and get_model_id are private to api.rs,
// we document the expected behavior here for reference:
//
// LLM models: MiniCPM4_0_5B, Qwen2_5vl3B, Qwen2_5vl7B, Qwen3_0_6B,
// Qwen3vl2B, Qwen3vl4B, Qwen3vl8B, Qwen3vl32B
// OCR models: DeepSeekOCR, HunyuanOCR, PaddleOCRVL
// ASR models: Qwen3ASR0_6B, Qwen3ASR1_7B, GlmASRNano2512, FunASRNano2512
// Image models: RMBG2_0, VoxCPM, VoxCPM1_5
// This test documents the expected model type classification
let llm_models = vec![
WhichModel::MiniCPM4_0_5B,
WhichModel::Qwen2_5vl3B,
WhichModel::Qwen2_5vl7B,
WhichModel::Qwen3_0_6B,
WhichModel::Qwen3vl2B,
WhichModel::Qwen3vl4B,
WhichModel::Qwen3vl8B,
WhichModel::Qwen3vl32B,
];
let ocr_models = vec![
WhichModel::DeepSeekOCR,
WhichModel::HunyuanOCR,
WhichModel::PaddleOCRVL,
];
let asr_models = vec![
WhichModel::Qwen3ASR0_6B,
WhichModel::Qwen3ASR1_7B,
WhichModel::GlmASRNano2512,
WhichModel::FunASRNano2512,
];
let image_models = vec![
WhichModel::RMBG2_0,
WhichModel::VoxCPM,
WhichModel::VoxCPM1_5,
];
// Verify counts
assert_eq!(llm_models.len(), 8);
assert_eq!(ocr_models.len(), 3);
assert_eq!(asr_models.len(), 4);
assert_eq!(image_models.len(), 3);
// Total models
assert_eq!(llm_models.len() + ocr_models.len() + asr_models.len() + image_models.len(), 18);
}
// Note: Integration tests for the /health and /models endpoints
// should be done with a running server. These would typically:
//
// 1. Start the server with a test model
// 2. Make HTTP requests to /health and /models
// 3. Verify the response format and status codes
//
// Example (pseudo-code):
//
// #[tokio::test]
// async fn test_health_endpoint() {
// let resp = reqwest::get("http://localhost:10100/health").await.unwrap();
// assert_eq!(resp.status(), 200);
// let json: serde_json::Value = resp.json().await.unwrap();
// assert_eq!(json["status"], "ok");
// }