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aha/tests/test_qwen3_5_multi_format.rs
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use std::path::{Path, PathBuf};
use aha::models::{
ArtifactKind, GenerateModel, LoadSpec, ModelPaths, WhichModel,
qwen3_5::generate::Qwen3_5GenerateModel,
};
use aha_openai_dive::v1::resources::chat::ChatCompletionParameters;
use anyhow::Result;
const DEFAULT_QWEN3_5_SAFETENSORS_DIR: &str = r"D:\model_download\Qwen3.5-0.8B";
#[cfg(feature = "onnx-runtime")]
const DEFAULT_QWEN3_5_ONNX_DIR: &str = r"D:\model_download\Qwen3.5-0.8B-ONNX";
const DEFAULT_QWEN3_5_GGUF_DIRS: &[&str] = &[
r"D:\model_download\Qwen3.5-0.8B-GGUF",
r"D:\model_download\Qwen3.5-0.8B-gguf",
r"D:\model_download\Qwen3.5-2B-GGUF",
r"D:\model_download\Qwen3.5-4B-GGUF",
];
fn env_or_default(key: &str, default: &str) -> String {
std::env::var(key).unwrap_or_else(|_| default.to_string())
}
fn existing_dir(path: &str) -> bool {
let p = Path::new(path);
p.exists() && p.is_dir()
}
fn first_file_with_extension_recursive(dir: &str, extension: &str) -> Result<Option<PathBuf>> {
if !existing_dir(dir) {
return Ok(None);
}
let mut stack = vec![PathBuf::from(dir)];
let mut matches = Vec::new();
while let Some(current) = stack.pop() {
for entry in std::fs::read_dir(&current)? {
let entry = entry?;
let path = entry.path();
if path.is_dir() {
stack.push(path);
} else if path
.extension()
.is_some_and(|ext| ext.eq_ignore_ascii_case(extension))
{
matches.push(path);
}
}
}
matches.sort();
Ok(matches.into_iter().next())
}
fn resolve_gguf_path() -> Result<Option<String>> {
if let Ok(path) = std::env::var("AHA_QWEN3_5_GGUF_PATH")
&& Path::new(&path).exists()
{
return Ok(Some(path));
}
for dir in DEFAULT_QWEN3_5_GGUF_DIRS {
if let Some(path) = first_file_with_extension_recursive(dir, "gguf")? {
return Ok(Some(path.to_string_lossy().to_string()));
}
}
Ok(None)
}
fn build_text_request() -> Result<ChatCompletionParameters> {
let payload = serde_json::json!({
"model": "qwen3.5-0.8b",
"max_tokens": 8,
"messages": [
{
"role": "user",
"content": "请用一句话介绍 Rust。"
}
]
});
Ok(serde_json::from_value(payload)?)
}
#[test]
fn qwen3_5_safetensors_init_from_spec_can_generate() -> Result<()> {
let weight_dir = env_or_default(
"AHA_QWEN3_5_SAFETENSORS_DIR",
DEFAULT_QWEN3_5_SAFETENSORS_DIR,
);
if !existing_dir(&weight_dir) {
println!("skip safetensors test: dir not found, set AHA_QWEN3_5_SAFETENSORS_DIR to run");
return Ok(());
}
let spec = LoadSpec {
model: WhichModel::Qwen3_5_0_8B,
artifact: ArtifactKind::Safetensors,
paths: ModelPaths {
weight_dir: Some(weight_dir),
..Default::default()
},
};
let mut model = Qwen3_5GenerateModel::init_from_spec(&spec, None, None)?;
let response = model.generate(build_text_request()?)?;
let value = serde_json::to_value(response)?;
let choices_len = value
.get("choices")
.and_then(|choices| choices.as_array())
.map_or(0, |choices| choices.len());
assert!(choices_len > 0, "expected at least one generated choice");
Ok(())
}
#[test]
fn qwen3_5_gguf_init_from_spec_can_generate() -> Result<()> {
let Some(gguf_path) = resolve_gguf_path()? else {
println!("skip gguf test: no gguf file found, set AHA_QWEN3_5_GGUF_PATH to run explicitly");
return Ok(());
};
let spec = LoadSpec {
model: WhichModel::Qwen3_5_0_8B,
artifact: ArtifactKind::Gguf,
paths: ModelPaths {
gguf_path: Some(gguf_path),
..Default::default()
},
};
let mut model = Qwen3_5GenerateModel::init_from_spec(&spec, None, None)?;
let response = model.generate(build_text_request()?)?;
let value = serde_json::to_value(response)?;
let choices_len = value
.get("choices")
.and_then(|choices| choices.as_array())
.map_or(0, |choices| choices.len());
assert!(choices_len > 0, "expected at least one generated choice");
Ok(())
}
#[cfg(feature = "onnx-runtime")]
#[test]
fn qwen3_5_onnx_init_from_spec_can_generate() -> Result<()> {
use aha::models::common::onnx::ensure_ort_dylib_path;
if let Err(err) = ensure_ort_dylib_path() {
println!("skip onnx test: {err}");
return Ok(());
}
let onnx_dir = env_or_default("AHA_QWEN3_5_ONNX_DIR", DEFAULT_QWEN3_5_ONNX_DIR);
if !existing_dir(&onnx_dir) {
println!("skip onnx test: dir not found, set AHA_QWEN3_5_ONNX_DIR to run");
return Ok(());
}
let spec = LoadSpec {
model: WhichModel::Qwen3_5_0_8B,
artifact: ArtifactKind::Onnx,
paths: ModelPaths {
onnx_path: Some(onnx_dir.clone()),
tokenizer_dir: Some(onnx_dir),
..Default::default()
},
};
let mut model = Qwen3_5GenerateModel::init_from_spec(&spec, None, None)?;
let response = model.generate(build_text_request()?)?;
let value = serde_json::to_value(response)?;
let choices_len = value
.get("choices")
.and_then(|choices| choices.as_array())
.map_or(0, |choices| choices.len());
assert!(choices_len > 0, "expected at least one generated choice");
Ok(())
}
#[cfg(feature = "onnx-runtime")]
#[test]
fn qwen3_5_onnx_image_multimodal_can_generate() -> Result<()> {
use aha::models::common::onnx::ensure_ort_dylib_path;
if let Err(err) = ensure_ort_dylib_path() {
println!("skip onnx multimodal image test: {err}");
return Ok(());
}
let onnx_dir = env_or_default("AHA_QWEN3_5_ONNX_DIR", DEFAULT_QWEN3_5_ONNX_DIR);
if !existing_dir(&onnx_dir) {
println!("skip onnx multimodal image test: dir not found");
return Ok(());
}
let spec = LoadSpec {
model: WhichModel::Qwen3_5_0_8B,
artifact: ArtifactKind::Onnx,
paths: ModelPaths {
onnx_path: Some(onnx_dir.clone()),
tokenizer_dir: Some(onnx_dir),
..Default::default()
},
};
let mut model = Qwen3_5GenerateModel::init_from_spec(&spec, None, None)?;
let image_path = std::env::current_dir()?
.join("assets")
.join("img")
.join("ocr_test1.png");
if !image_path.exists() {
println!(
"skip onnx multimodal image test: local image not found at {}",
image_path.display()
);
return Ok(());
}
let image_url = format!(
"file:///{}",
image_path.to_string_lossy().replace('\\', "/")
);
let payload = serde_json::json!({
"model": "qwen3.5-0.8b",
"max_tokens": 8,
"messages": [
{
"role": "user",
"content": [
{
"type": "image",
"image_url": {"url": image_url}
},
{
"type": "text",
"text": "识别图像中的文字"
}
]
}
]
});
let request: ChatCompletionParameters = serde_json::from_value(payload)?;
let response = model.generate(request)?;
let value = serde_json::to_value(response)?;
let choices_len = value
.get("choices")
.and_then(|choices| choices.as_array())
.map_or(0, |choices| choices.len());
assert!(
choices_len > 0,
"expected at least one generated choice for multimodal image request"
);
Ok(())
}
#[cfg(feature = "onnx-runtime")]
#[test]
fn qwen3_5_onnx_video_multimodal_is_rejected() -> Result<()> {
use aha::models::common::onnx::ensure_ort_dylib_path;
if let Err(err) = ensure_ort_dylib_path() {
println!("skip onnx multimodal video rejection test: {err}");
return Ok(());
}
let onnx_dir = env_or_default("AHA_QWEN3_5_ONNX_DIR", DEFAULT_QWEN3_5_ONNX_DIR);
if !existing_dir(&onnx_dir) {
println!("skip onnx multimodal video rejection test: dir not found");
return Ok(());
}
let spec = LoadSpec {
model: WhichModel::Qwen3_5_0_8B,
artifact: ArtifactKind::Onnx,
paths: ModelPaths {
onnx_path: Some(onnx_dir.clone()),
tokenizer_dir: Some(onnx_dir),
..Default::default()
},
};
let mut model = Qwen3_5GenerateModel::init_from_spec(&spec, None, None)?;
let payload = serde_json::json!({
"model": "qwen3.5-0.8b",
"max_tokens": 8,
"messages": [
{
"role": "user",
"content": [
{
"type": "video",
"video_url": {"url": "file://./assets/video/dummy.mp4"}
},
{
"type": "text",
"text": "描述视频内容"
}
]
}
]
});
let request: ChatCompletionParameters = serde_json::from_value(payload)?;
let err = model
.generate(request)
.expect_err("onnx backend should reject video multimodal input for now");
assert!(
err.to_string().contains("audio/video") || err.to_string().contains("video"),
"unexpected error: {err}"
);
Ok(())
}