6 Commits

55
main.py
View File

@@ -31,7 +31,7 @@ PORT = 8080
STRATEGY_ID = os.getenv("STRATEGY_ID", "") STRATEGY_ID = os.getenv("STRATEGY_ID", "")
# 目标GPU # 目标GPU
TARGET_GPU = "Iluvatar_bi-150" TARGET_GPU = "Iluvatar_bi-100"
# 账号Token # 账号Token
TARGET_TOKEN = "f45f1aae2c094426be237c88b1085015" TARGET_TOKEN = "f45f1aae2c094426be237c88b1085015"
@@ -47,7 +47,7 @@ SUPPORTED_SPECIAL_ARCHS = ['Eagle3Speculator', 'LlamaForCausalLMEagle3']
MODELHUB_API = "https://modelhub.org.cn/api" MODELHUB_API = "https://modelhub.org.cn/api"
# 搜索关键词 # 搜索关键词
SEARCH_KEYWORDS = ['qwen', 'Qwen2', 'Qwen3', 'Qwen3.5', 'Qwen1.5', 'Qwen-'] SEARCH_KEYWORDS = ['Llama-3', 'Llama-3.1', 'Llama-3.2', 'Meta-Llama', 'Llama-4']
# ============================================================ # ============================================================
# 全局状态 # 全局状态
@@ -157,7 +157,7 @@ def search_models(keyword: str) -> list:
def check_architecture(model_id: str) -> tuple: def check_architecture(model_id: str) -> tuple:
"""检查模型架构""" """检查模型是否有有效的 config.json不限架构类型"""
try: try:
cfg_url = f"{MODELSCOPE_API}/models/{model_id}/repo?Revision=master&FilePath=config.json" cfg_url = f"{MODELSCOPE_API}/models/{model_id}/repo?Revision=master&FilePath=config.json"
resp = requests.get(cfg_url, timeout=10) resp = requests.get(cfg_url, timeout=10)
@@ -165,20 +165,13 @@ def check_architecture(model_id: str) -> tuple:
cfg = resp.json() cfg = resp.json()
archs = cfg.get('architectures', []) archs = cfg.get('architectures', [])
mtype = cfg.get('model_type', '') mtype = cfg.get('model_type', '')
arch_str = str(archs) if archs or mtype:
for special in SUPPORTED_SPECIAL_ARCHS: return True, f"arch={archs} type={mtype}"
if special in arch_str: return False, "empty config"
return True, special
for kw in SUPPORTED_ARCH_KEYWORDS:
if kw in arch_str:
return True, kw
if mtype in SUPPORTED_MODEL_TYPES:
return True, mtype
return False, f"arch={archs} type={mtype}"
mid_upper = model_id.upper() mid_upper = model_id.upper()
if 'QWEN3' in mid_upper or 'QWEN2' in mid_upper: if 'LLAMA' in mid_upper:
return True, "GGUF" return True, "Llama(GGUF)"
return False, "no config, not Qwen" return False, "no config"
except Exception as e: except Exception as e:
return True, f"check error: {e}" return True, f"check error: {e}"
@@ -254,7 +247,7 @@ def check_queue_available() -> int:
def build_config_params() -> str: def build_config_params() -> str:
"""构建 YAML 配置 - 完全匹配平台自动生成的格式(只支持vllm""" """构建 YAML 配置 - vllm"""
params = { params = {
'framework': 'vllm', 'framework': 'vllm',
'nv_framework': 'vllm', 'nv_framework': 'vllm',
@@ -347,11 +340,11 @@ def run_pipeline(submit_limit: int = 2):
time.sleep(0.3) time.sleep(0.3)
log(f"搜索完成: {len(seen)} 个唯一模型, {len(all_models)} 个下载量{DOWNLOAD_MIN}-{DOWNLOAD_MAX}") log(f"搜索完成: {len(seen)} 个唯一模型, {len(all_models)} 个下载量{DOWNLOAD_MIN}-{DOWNLOAD_MAX}")
# 2. 格式筛选(排除 GGUF/GPTQ/AWQ # 2. 格式筛选(排除 GPTQ/AWQ,保留 GGUF 和 HuggingFace
log("\n--- 阶段2: 格式筛选 ---") log("\n--- 阶段2: 格式筛选 ---")
hf_models = [] hf_models = []
format_skipped = 0 format_skipped = 0
SKIP_FORMATS = ['GGUF', 'GPTQ', 'AWQ'] SKIP_FORMATS = ['GPTQ', 'AWQ']
for m in all_models: for m in all_models:
mid_upper = m['model_id'].upper() mid_upper = m['model_id'].upper()
skip = False skip = False
@@ -363,27 +356,24 @@ def run_pipeline(submit_limit: int = 2):
break break
if not skip: if not skip:
hf_models.append(m) hf_models.append(m)
log(f"格式筛选: {len(hf_models)} 通过, {format_skipped} 跳过 (GGUF/GPTQ/AWQ)") log(f"格式筛选: {len(hf_models)} 通过, {format_skipped} 跳过 (GPTQ/AWQ)")
# 3. 架构筛选(排除 Qwen3.5 在 Iluvatar 上不支持 # 3. 架构筛选(只保留有标准config.json的模型排除无效格式
log("\n--- 阶段3: 架构筛选 ---") log("\n--- 阶段3: 架构检查 ---")
arch_passed = [] arch_passed = []
arch_rejected = 0 arch_rejected = 0
SKIP_ARCHS = ['qwen3_5', 'Qwen3_5', 'Qwen3.5']
for m in hf_models: for m in hf_models:
ok, reason = check_architecture(m['model_id']) ok, reason = check_architecture(m['model_id'])
if not ok: if not ok:
arch_rejected += 1 arch_rejected += 1
log(f" x {m['model_id']}: {reason}") log(f" x {m['model_id']}: {reason}")
continue elif reason == 'GGUF':
arch_str = str(reason).upper()
if any(a.upper() in arch_str for a in SKIP_ARCHS):
arch_rejected += 1 arch_rejected += 1
log(f" x {m['model_id']}: Qwen3.5(Iluvatar不支持)") log(f" x {m['model_id']}: GGUF(无config)")
continue else:
arch_passed.append(m) arch_passed.append(m)
time.sleep(0.15) time.sleep(0.1)
log(f"架构筛选: {len(arch_passed)} 通过, {arch_rejected} 拒绝") log(f"架构检查: {len(arch_passed)} 通过, {arch_rejected} 拒绝")
# 4. 筛选并提交只针对目标GPU # 4. 筛选并提交只针对目标GPU
log(f"\n--- 阶段4: 筛选并提交 [{TARGET_GPU}] ---") log(f"\n--- 阶段4: 筛选并提交 [{TARGET_GPU}] ---")
@@ -428,8 +418,9 @@ def run_pipeline(submit_limit: int = 2):
submitted += 1 submitted += 1
log(f"{m['model_id']}") log(f"{m['model_id']}")
db_conn.execute( db_conn.execute(
'INSERT OR REPLACE INTO submitted VALUES (?,?,?,?)', 'INSERT OR REPLACE INTO submitted VALUES (?,?,?,?,?,?)',
(m['model_id'], TARGET_GPU, str(task_id), datetime.now().isoformat()) (m['model_id'], TARGET_GPU, str(task_id), 'submitted',
datetime.now().isoformat(), None)
) )
else: else:
log(f"{m['model_id']}: {msg}") log(f"{m['model_id']}: {msg}")