@@ -1,74 +1,724 @@
"""
ModelHub 提交智能体（代理模式）
用途：获取 strategyId，
ModelHub 全云端 提交智能体
部署在平台容器中，直接从内网提交验证任务
功能：
- POST /run → 触发一次完整流程（搜索→筛选→提交）
- GET /status → 查看当前状态
- GET /health → 健康检查
"""
import json
import os
import signal
import sqlite3
import threading
import time
import traceback
from datetime import datetime
from http . server import BaseHTTPRequestHandler , ThreadingHTTPServer
from urllib . parse import urlparse , parse_qs
import requests
import yaml
# ============================================================
# 配置
# ============================================================
HOST = " 0.0.0.0 "
PORT = 8080
shutdown_requested = False
STRATEGY_ID = os . getenv ( " STRATEGY_ID " , " " )
# 目标GPU
TARGET_GPU = " Iluvatar_bi-100 "
# 账号Token
TARGET_TOKEN = " f45f1aae2c094426be237c88b1085015 "
# 架构白名单
SUPPORTED_ARCH_KEYWORDS = [ ' Qwen ' , ' Qwen2 ' , ' Qwen3 ' ]
SUPPORTED_MODEL_TYPES = [
' qwen ' , ' qwen2 ' , ' qwen2_vl ' , ' qwen2_5_vl ' , ' qwen2_audio ' ,
' qwen3 ' , ' qwen3_vl ' , ' qwen3_5 ' , ' qwen3_5_moe ' ,
]
SUPPORTED_SPECIAL_ARCHS = [ ' Eagle3Speculator ' , ' LlamaForCausalLMEagle3 ' ]
MODELHUB_API = " https://modelhub.org.cn/api "
# 搜索关键词
SEARCH_KEYWORDS = [ ' qwen ' , ' Qwen2 ' , ' Qwen3 ' , ' Qwen3.5 ' , ' Llama-3 ' , ' Llama-3.1 ' , ' Mistral ' , ' DeepSeek ' ]
# ============================================================
# 全局状态
# ============================================================
state = {
' running ' : False ,
' last_run ' : None ,
' last_result ' : None ,
' logs ' : [ ] ,
}
state_lock = threading . Lock ( )
def _config ( ) - > dict :
strategy_id = os . getenv ( " STRATEGY_ID " , " " )
return {
" strategy_id " : strategy_id ,
" status " : " running " ,
def log ( msg : str ) :
ts = datetime . now ( ) . strftime ( ' % H: % M: % S ' )
line = f " [ { ts } ] { msg } "
print ( line , flush = True )
with state_lock :
state [ ' logs ' ] . append ( line )
if len ( state [ ' logs ' ] ) > 500 :
state [ ' logs ' ] = state [ ' logs ' ] [ - 300 : ]
# ============================================================
# 数据库（内存 SQLite）
# ============================================================
db_conn = None
def init_db ( ) :
global db_conn
os . makedirs ( ' /app/data ' , exist_ok = True )
db_conn = sqlite3 . connect ( ' /app/data/submit_history.db ' , check_same_thread = False )
db_conn . execute ( ''' CREATE TABLE IF NOT EXISTS submitted (
model_id TEXT, gpu TEXT, task_id TEXT, status TEXT,
submitted_at TEXT, checked_at TEXT,
PRIMARY KEY(model_id, gpu)
) ''' )
db_conn . execute ( ''' CREATE TABLE IF NOT EXISTS failed (
model_id TEXT, gpu TEXT, reason TEXT, failed_at TEXT,
PRIMARY KEY(model_id, gpu)
) ''' )
db_conn . commit ( )
def is_model_failed ( model_id : str ) - > bool :
""" 检查模型是否已知失败 """
if db_conn :
row = db_conn . execute (
' SELECT 1 FROM failed WHERE model_id=? AND gpu=? ' ,
( model_id , TARGET_GPU )
) . fetchone ( )
return row is not None
return False
def record_failed ( model_id : str , reason : str ) :
""" 记录失败的模型 """
if db_conn :
db_conn . execute (
' INSERT OR REPLACE INTO failed VALUES (?,?,?,?) ' ,
( model_id , TARGET_GPU , reason , datetime . now ( ) . isoformat ( ) )
)
db_conn . commit ( )
# ============================================================
# ModelScope 搜索
# ============================================================
MODELSCOPE_API = " https://modelscope.cn/api/v1 "
DOWNLOAD_MIN = 50
DOWNLOAD_MAX = 5000
SEARCH_PAGES = 5 # 每个关键词搜5页（ ）
def search_models ( keyword : str ) - > list :
""" 从 ModelScope 搜索模型（ ， ） """
url = " https://modelscope.cn/openapi/v1/models "
models = [ ]
for page in range ( 1 , SEARCH_PAGES + 1 ) :
params = {
' search ' : keyword ,
' page_size ' : 50 ,
' page_number ' : page ,
' sort ' : ' downloads ' ,
}
try :
resp = requests . get ( url , params = params , timeout = 20 ,
headers = { ' User-Agent ' : ' Mozilla/5.0 ' } )
data = resp . json ( )
if data . get ( ' success ' ) :
page_models = data . get ( ' data ' , { } ) . get ( ' models ' , [ ] )
for m in page_models :
dl = m . get ( ' downloads ' , 0 )
if DOWNLOAD_MIN < = dl < = DOWNLOAD_MAX :
models . append ( { ' id ' : m . get ( ' id ' ) , ' downloads ' : dl } )
if len ( page_models ) < 50 :
break # 最后一页，不继续
else :
break
except Exception as e :
log ( f " [ { keyword } ] page= { page } : { e } " )
break
time . sleep ( 0.3 )
log ( f " [ { keyword } ]: { len ( models ) } 个 (50<= { DOWNLOAD_MAX } ) " )
return models
class Handler ( BaseHTTPRequestHandler ) :
def do_GET ( self ) - > None :
if self . path == " /health " :
self . _send_json ( { " status " : " ok " } )
return
def check_architecture ( model_id : str ) - > tuple :
""" 检查模型架构 """
try :
cfg_url = f " { MODELSCOPE_API } /models/ { model_id } /repo?Revision=master&FilePath=config.json "
resp = requests . get ( cfg_url , timeout = 10 )
if resp . status_code == 200 :
cfg = resp . json ( )
archs = cfg . get ( ' architectures ' , [ ] )
mtype = cfg . get ( ' model_type ' , ' ' )
arch_str = str ( archs )
for special in SUPPORTED_SPECIAL_ARCHS :
if special in arch_str :
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 ( )
if ' QWEN3 ' in mid_upper or ' QWEN2 ' in mid_upper :
return True , " GGUF "
return False , " no config, not Qwen "
except Exception as e :
return True , f " check error: { e } "
if self . path == " / " :
self . _send_json ( {
" name " : " modelhub-submit-agent " ,
" config " : _config ( ) ,
def normalize_model_url ( model_url : str ) - > str :
""" 标准化 URL 格式 """
if ' /models/ ' in model_url :
return model_url
if ' modelscope.cn/ ' in model_url :
parts = model_url . split ( ' modelscope.cn/ ' )
if len ( parts ) == 2 :
return f " https://www.modelscope.cn/models/ { parts [ 1 ] } "
return model_url
# ============================================================
# 平台 API
# ============================================================
def check_platform_verify ( model_id : str ) - > dict :
""" 查询全平台验证状态 """
headers = { ' Xc-Token ' : TARGET_TOKEN , ' Accept ' : ' application/json ' }
url = f " { MODELHUB_API } /computility/models/search-by-model-id "
try :
resp = requests . get ( url , headers = headers , params = { ' modelId ' : model_id } , timeout = 10 )
data = resp . json ( )
if data . get ( ' code ' ) == 0 :
result = data . get ( ' data ' , { } ) . get ( ' verifyResult ' , { } )
return result if isinstance ( result , dict ) else { }
except Exception :
pass
return { }
def check_my_submitted ( model_id : str ) - > bool :
""" 检查自己是否已提交 """
headers = { ' Xc-Token ' : TARGET_TOKEN , ' Accept ' : ' application/json ' }
url = f " { MODELHUB_API } /adapt/task/page "
try :
resp = requests . get ( url , headers = headers , params = {
' current ' : 1 , ' pageSize ' : 100 , ' onlyMine ' : ' true ' ,
' gpuType ' : TARGET_GPU , ' modelId ' : model_id ,
} , timeout = 10 )
data = resp . json ( )
if data . get ( ' code ' ) == 0 :
records = data . get ( ' data ' , { } ) . get ( ' records ' , [ ] )
for r in records :
if r . get ( ' modelId ' ) == model_id and r . get ( ' gpuType ' ) == gpu :
status = r . get ( ' status ' , ' ' )
if status in ( ' waiting ' , ' running ' , ' success ' ) :
return True
except Exception :
pass
return False
def check_queue_available ( ) - > int :
""" 查询队列可用位置 """
headers = { ' Xc-Token ' : TARGET_TOKEN , ' Accept ' : ' application/json ' }
url = f " { MODELHUB_API } /adapt/task/page "
try :
resp = requests . get ( url , headers = headers , params = {
' current ' : 1 , ' pageSize ' : 1 , ' onlyMine ' : ' true ' ,
' gpuType ' : TARGET_GPU , ' status ' : ' waiting ' ,
} , timeout = 10 )
data = resp . json ( )
if data . get ( ' code ' ) == 0 :
waiting = int ( data [ ' data ' ] . get ( ' total ' , 0 ) )
return max ( 0 , 100 - waiting )
except Exception :
pass
return - 1
def build_config_params ( ) - > str :
""" 构建 YAML 配置 - llama.cpp (支持 GGUF) """
params = {
' framework ' : ' llama.cpp ' ,
' nv_framework ' : ' llama.cpp ' ,
' api ' : ' completion ' ,
' max_tokens ' : 1024 ,
' temperature ' : 0.7 ,
' repetition_penalty ' : 1.2 ,
' top_p ' : 0.9 ,
' lang ' : ' zh ' ,
' max_model_len ' : 4096 ,
' sut_config ' : {
' gpu_num ' : 1 ,
' values ' : {
' command ' : [
' llama-server ' , ' --model ' , ' /model ' , ' --alias ' , ' llm ' ,
' --threads ' , ' 20 ' , ' --n-gpu-layers ' , ' 999 ' , ' --prio ' , ' 3 ' ,
' --min_p ' , ' 0.01 ' , ' --ctx-size ' , ' 4096 ' ,
' --host ' , ' 0.0.0.0 ' , ' --port ' , ' 8000 ' ,
' --jinja ' , ' --flash-attn ' , ' off ' ,
]
}
} ,
' ref_config ' : {
' gpu_num ' : 1 ,
' values ' : {
' command ' : [
' llama-server ' , ' --model ' , ' /model ' , ' --alias ' , ' llm ' ,
' --threads ' , ' 20 ' , ' --n-gpu-layers ' , ' 999 ' ,
' --ctx-size ' , ' 4096 ' , ' --host ' , ' 0.0.0.0 ' , ' --port ' , ' 8000 ' ,
]
}
} ,
}
return yaml . dump ( params , default_flow_style = False , allow_unicode = True , width = 1000 )
def submit_model ( model_url : str ) - > tuple :
""" 提交单个模型 """
headers = {
' Xc-Token ' : TARGET_TOKEN ,
' Accept ' : ' application/json ' ,
' Content-Type ' : ' application/json ' ,
}
url = f " { MODELHUB_API } /adapt/task/add "
payload = {
' modelAddress ' : normalize_model_url ( model_url ) ,
' taskType ' : ' text-generation ' ,
' targetGpu ' : TARGET_GPU ,
' framework ' : ' llama.cpp ' ,
' strategyId ' : STRATEGY_ID ,
' configParams ' : build_config_params ( ) ,
}
try :
resp = requests . post ( url , headers = headers , json = payload , timeout = 30 )
data = resp . json ( )
if data . get ( ' code ' ) == 0 :
task_id = data . get ( ' data ' , { } ) . get ( ' id ' )
return True , task_id , ' success '
return False , None , data . get ( ' message ' , ' unknown error ' )
except Exception as e :
return False , None , str ( e )
# ============================================================
# 主流程
# ============================================================
def run_pipeline ( submit_limit : int = 2 ) :
""" 完整流程： （ ） """
init_db ( )
log ( " = " * 50 )
log ( " 开始执行流程 " )
log ( f " 目标GPU: { TARGET_GPU } " )
log ( f " 提交限制: { submit_limit } 个 " )
# 1. 搜索
log ( " \n --- 阶段1: 搜索 ModelScope --- " )
seen = set ( )
all_models = [ ]
for kw in SEARCH_KEYWORDS :
models = search_models ( kw )
for m in models :
mid = m . get ( ' id ' , ' ' )
if mid and mid not in seen :
seen . add ( mid )
all_models . append ( {
' model_id ' : mid ,
' url ' : f " https://modelscope.cn/ { mid } " ,
' downloads ' : m . get ( ' downloads ' , 0 ) ,
} )
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 } " )
# 2. 格式筛选（排除 GPTQ/AWQ， ）
log ( " \n --- 阶段2: 格式筛选 --- " )
hf_models = [ ]
format_skipped = 0
SKIP_FORMATS = [ ' GPTQ ' , ' AWQ ' ]
for m in all_models :
mid_upper = m [ ' model_id ' ] . upper ( )
skip = False
for fmt in SKIP_FORMATS :
if fmt in mid_upper :
format_skipped + = 1
log ( f " x { m [ ' model_id ' ] } : { fmt } 格式，跳过 " )
skip = True
break
if not skip :
hf_models . append ( m )
log ( f " 格式筛选: { len ( hf_models ) } 通过, { format_skipped } 跳过 (GPTQ/AWQ) " )
# 3. 架构筛选（参考检查，不做严格过滤，让平台决定兼容性）
log ( " \n --- 阶段3: 架构检查 --- " )
for m in hf_models :
ok , reason = check_architecture ( m [ ' model_id ' ] )
if not ok :
log ( f " ! { m [ ' model_id ' ] } : { reason } (仍保留) " )
time . sleep ( 0.1 )
log ( f " 架构检查: { len ( hf_models ) } 个模型进入下一阶段 " )
# 4. 筛选并提交（ ）
log ( f " \n --- 阶段4: 筛选并提交 [ { TARGET_GPU } ] --- " )
# 检查队列
available = check_queue_available ( )
if available < = 0 :
log ( f " 队列满，跳过 " )
return 0
log ( f " 队列可用: { available } " )
# 筛选
to_submit = [ ]
for m in hf_models :
model_id = m [ ' model_id ' ]
# 检查全平台验证状态
verify = check_platform_verify ( model_id )
if TARGET_GPU in verify :
continue # 已有记录，跳过
# 检查自己是否已提交
if check_my_submitted ( model_id ) :
continue
# 检查是否已知失败（避免重复提交）
if is_model_failed ( model_id ) :
continue
to_submit . append ( m )
if len ( to_submit ) > = min ( submit_limit , available ) :
break
time . sleep ( 0.2 )
log ( f " 待提交: { len ( to_submit ) } " )
# 提交
submitted = 0
for m in to_submit :
ok , task_id , msg = submit_model ( m [ ' url ' ] )
if ok :
submitted + = 1
log ( f " ✅ { m [ ' model_id ' ] } " )
db_conn . execute (
' INSERT OR REPLACE INTO submitted VALUES (?,?,?,?) ' ,
( m [ ' model_id ' ] , TARGET_GPU , str ( task_id ) , datetime . now ( ) . isoformat ( ) )
)
else :
log ( f " ❌ { m [ ' model_id ' ] } : { msg } " )
# 永久失败类型记录到 failed 表
if any ( kw in str ( msg ) for kw in [ ' 保护期 ' , ' 白名单 ' , ' 唯一性 ' ] ) :
record_failed ( m [ ' model_id ' ] , msg )
time . sleep ( 0.5 )
log ( f " 提交完成: { submitted } / { len ( to_submit ) } " )
db_conn . commit ( )
log ( f " \n { ' = ' * 50 } " )
log ( f " 流程完成，共提交 { submitted } 个模型 " )
return submitted
# ============================================================
# HTTP 服务
# ============================================================
class AgentHandler ( BaseHTTPRequestHandler ) :
def do_GET ( self ) :
parsed = urlparse ( self . path )
path = parsed . path
if path == ' /health ' :
self . _json ( { ' status ' : ' ok ' } )
elif path == ' / ' :
self . _json ( {
' name ' : ' modelhub-submit-agent ' ,
' strategy_id ' : STRATEGY_ID ,
' status ' : ' running ' if state [ ' running ' ] else ' idle ' ,
' last_run ' : state [ ' last_run ' ] ,
' last_result ' : state [ ' last_result ' ] ,
} )
elif path == ' /test ' :
self . _json ( self . _run_connectivity_test ( ) )
elif path == ' /status ' :
self . _json ( {
' running ' : state [ ' running ' ] ,
' last_run ' : state [ ' last_run ' ] ,
' last_result ' : state [ ' last_result ' ] ,
' queue_count ' : db_conn . execute ( ' SELECT COUNT(*) FROM queue ' ) . fetchone ( ) [ 0 ] if db_conn else 0 ,
' submitted_count ' : db_conn . execute ( ' SELECT COUNT(*) FROM submitted ' ) . fetchone ( ) [ 0 ] if db_conn else 0 ,
} )
elif path == ' /logs ' :
lines = int ( parse_qs ( parsed . query ) . get ( ' lines ' , [ ' 50 ' ] ) [ 0 ] )
self . _json ( { ' logs ' : state [ ' logs ' ] [ - lines : ] } )
else :
self . _json ( { ' error ' : ' not found ' } , 404 )
def do_POST ( self ) :
parsed = urlparse ( self . path )
path = parsed . path
if path == ' /run ' :
if state [ ' running ' ] :
self . _json ( { ' error ' : ' already running ' } , 409 )
return
self . _send_json ( { " error " : " not found " } , status = 404 )
# 读取请求体
content_len = int ( self . headers . get ( ' Content-Length ' , 0 ) )
body = { }
if content_len > 0 :
body = json . loads ( self . rfile . read ( content_len ) )
def log_message ( self , fmt : str , * args : object ) - > None :
print ( f " { self . address_string ( ) } - { fmt % args } " , flush = True )
limit = body . get ( ' limit ' , 2 )
def _send_json ( self , body : dict , : int = 200 ) - > None :
payload = json . dumps ( body ) . encode ( )
self . _json ( { ' ' : ' started ' , ' gpu ' : TARGET_GPU , ' limit ' : limit } )
# 后台运行
def _run ( ) :
try :
state [ ' running ' ] = True
state [ ' last_run ' ] = datetime . now ( ) . isoformat ( )
count = run_pipeline ( submit_limit = limit )
state [ ' last_result ' ] = { ' submitted ' : count , ' success ' : True }
except Exception as e :
log ( f " 流程异常: { traceback . format_exc ( ) } " )
state [ ' last_result ' ] = { ' error ' : str ( e ) , ' success ' : False }
finally :
state [ ' running ' ] = False
threading . Thread ( target = _run , daemon = True ) . start ( )
else :
self . _json ( { ' error ' : ' not found ' } , 404 )
def _run_connectivity_test ( self ) - > dict :
""" 测试各 API 连通性 """
results = { }
# 1. ModelScope 搜索 API
try :
resp = requests . get (
' https://modelscope.cn/openapi/v1/models ' ,
params = { ' search ' : ' qwen ' , ' page_size ' : 2 , ' sort ' : ' downloads ' } ,
timeout = 10 ,
headers = { ' User-Agent ' : ' Mozilla/5.0 ' }
)
results [ ' modelscope_search ' ] = {
' status ' : resp . status_code ,
' ok ' : resp . status_code == 200 ,
' body_preview ' : resp . text [ : 200 ] if resp . status_code == 200 else resp . text [ : 100 ] ,
}
except Exception as e :
results [ ' modelscope_search ' ] = { ' ok ' : False , ' error ' : str ( e ) }
# 2. ModelScope config.json API
try :
resp = requests . get (
' https://modelscope.cn/api/v1/models/Qwen/Qwen3-8B/repo?Revision=master&FilePath=config.json ' ,
timeout = 10 ,
)
results [ ' modelscope_config ' ] = {
' status ' : resp . status_code ,
' ok ' : resp . status_code == 200 ,
' body_preview ' : resp . text [ : 200 ] if resp . status_code == 200 else resp . text [ : 100 ] ,
}
except Exception as e :
results [ ' modelscope_config ' ] = { ' ok ' : False , ' error ' : str ( e ) }
# 3. ModelHub 查询 API
try :
resp = requests . get (
' https://modelhub.org.cn/api/adapt/task/page ' ,
headers = { ' Xc-Token ' : TARGET_TOKEN , ' Accept ' : ' application/json ' } ,
params = { ' current ' : 1 , ' pageSize ' : 1 , ' onlyMine ' : ' true ' } ,
timeout = 10 ,
)
data = resp . json ( )
results [ ' modelhub_query ' ] = {
' ok ' : data . get ( ' code ' ) == 0 ,
' code ' : data . get ( ' code ' ) ,
' total ' : data . get ( ' data ' , { } ) . get ( ' total ' ) ,
}
except Exception as e :
results [ ' modelhub_query ' ] = { ' ok ' : False , ' error ' : str ( e ) }
# 4. ModelHub 提交 API (dry test)
try :
resp = requests . post (
' https://modelhub.org.cn/api/adapt/task/add ' ,
headers = { ' Xc-Token ' : TARGET_TOKEN , ' Accept ' : ' application/json ' , ' Content-Type ' : ' application/json ' } ,
json = {
' modelAddress ' : ' https://www.modelscope.cn/models/Qwen/Qwen3-8B ' ,
' taskType ' : ' text-generation ' ,
' targetGpu ' : TARGET_GPU ,
' framework ' : ' llama.cpp ' ,
' strategyId ' : STRATEGY_ID ,
' configParams ' : build_config_params ( ) ,
} ,
timeout = 10 ,
)
data = resp . json ( )
results [ ' modelhub_submit ' ] = {
' ok ' : data . get ( ' code ' ) == 0 ,
' code ' : data . get ( ' code ' ) ,
' message ' : data . get ( ' message ' , ' ' ) [ : 100 ] ,
}
except Exception as e :
results [ ' modelhub_submit ' ] = { ' ok ' : False , ' error ' : str ( e ) }
return results
def _json ( self , body : dict , status : int = 200 ) :
payload = json . dumps ( body , ensure_ascii = False ) . encode ( )
self . send_response ( status )
self . send_header ( " " , " " )
self . send_header ( " " , str ( len ( payload ) ) )
self . send_header ( ' ' , ' ; charset=utf-8 ' )
self . send_header ( ' ' , str ( len ( payload ) ) )
self . end_headers ( )
self . wfile . write ( payload )
def log_message ( self , fmt , * args ) :
pass # 静默 HTTP 日志
def _handle_signal ( signum : int , _frame : object ) - > None :
# ============================================================
# 启动
# ============================================================
shutdown_requested = False
def _handle_signal ( signum , _frame ) :
global shutdown_requested
shutdown_requested = True
print ( f " received signal { signum } , shutting down " , flush = True )
log ( f " 收到信号 { signum } ，准备关闭 " )
def main ( ) - > None :
def main ( ) :
signal . signal ( signal . SIGTERM , _handle_signal )
signal . signal ( signal . SIGINT , _handle_signal )
server = ThreadingHTTPServer ( ( HOST , PORT ) , Handler )
init_db ( )
server = ThreadingHTTPServer ( ( HOST , PORT ) , AgentHandler )
server . timeout = 1
strategy_id = os . getenv ( " STRATEGY_ID " , " NOT_SET " )
print ( f " modelhub-submit-agent listening on { HOST } : { PORT } " , flush = True )
print ( f " STRATEGY_ID: { strategy_id } " , flush = True )
log ( f " 智能体启动 | { HOST } : { PORT } " )
log ( f " STRATEGY_ID: { STRATEGY_ID } " )
log ( f " 目标GPU: { TARGET_GPU } " )
# 启动后自动运行连通性测试
def _startup_test ( ) :
time . sleep ( 2 )
log ( " = " * 50 )
log ( " 连通性测试开始 " )
log ( " = " * 50 )
# 1. ModelScope 搜索
try :
resp = requests . get (
' https://modelscope.cn/openapi/v1/models ' ,
params = { ' search ' : ' qwen ' , ' page_size ' : 2 , ' sort ' : ' downloads ' } ,
timeout = 10 , headers = { ' User-Agent ' : ' Mozilla/5.0 ' }
)
if resp . status_code == 200 :
data = resp . json ( )
models = data . get ( ' data ' , { } ) . get ( ' models ' , [ ] )
log ( f " [ModelScope搜索] ✅ status= { resp . status_code } models= { len ( models ) } " )
for m in models [ : 2 ] :
log ( f " { m . get ( ' id ' ) } downloads= { m . get ( ' downloads ' ) } " )
else :
log ( f " [ModelScope搜索] ❌ status= { resp . status_code } body= { resp . text [ : 100 ] } " )
except Exception as e :
log ( f " [ModelScope搜索] ❌ error= { e } " )
# 2. ModelScope config.json
try :
resp = requests . get (
' https://modelscope.cn/api/v1/models/Qwen/Qwen3-8B/repo?Revision=master&FilePath=config.json ' ,
timeout = 10
)
if resp . status_code == 200 :
cfg = resp . json ( )
log ( f " [ModelScope配置] ✅ arch= { cfg . get ( ' architectures ' ) } type= { cfg . get ( ' model_type ' ) } " )
else :
log ( f " [ModelScope配置] ❌ status= { resp . status_code } " )
except Exception as e :
log ( f " [ModelScope配置] ❌ error= { e } " )
# 3. ModelHub 查询
try :
resp = requests . get (
' https://modelhub.org.cn/api/adapt/task/page ' ,
headers = { ' Xc-Token ' : TARGET_TOKEN , ' Accept ' : ' application/json ' } ,
params = { ' current ' : 1 , ' pageSize ' : 1 , ' onlyMine ' : ' true ' } ,
timeout = 10
)
data = resp . json ( )
if data . get ( ' code ' ) == 0 :
log ( f " [ModelHub查询] ✅ total= { data [ ' data ' ] . get ( ' total ' ) } " )
else :
log ( f " [ModelHub查询] ❌ code= { data . get ( ' code ' ) } msg= { data . get ( ' message ' , ' ' ) [ : 80 ] } " )
except Exception as e :
log ( f " [ModelHub查询] ❌ error= { e } " )
# 4. ModelHub 提交
try :
resp = requests . post (
' https://modelhub.org.cn/api/adapt/task/add ' ,
headers = { ' Xc-Token ' : TARGET_TOKEN , ' Accept ' : ' application/json ' , ' Content-Type ' : ' application/json ' } ,
json = {
' modelAddress ' : ' https://www.modelscope.cn/models/Qwen/Qwen3-8B ' ,
' taskType ' : ' text-generation ' , ' targetGpu ' : TARGET_GPU ,
' framework ' : ' llama.cpp ' , ' strategyId ' : STRATEGY_ID ,
' configParams ' : build_config_params ( ) ,
} , timeout = 10
)
data = resp . json ( )
log ( f " [ModelHub提交] code= { data . get ( ' code ' ) } msg= { data . get ( ' message ' , ' ' ) [ : 80 ] } " )
except Exception as e :
log ( f " [ModelHub提交] ❌ error= { e } " )
log ( " = " * 50 )
log ( " 连通性测试完成 " )
log ( " = " * 50 )
# 开始正式提交流程
log ( " \n 自动触发提交流程... " )
try :
state [ ' running ' ] = True
state [ ' last_run ' ] = datetime . now ( ) . isoformat ( )
count = run_pipeline ( submit_limit = 2 )
state [ ' last_result ' ] = { ' submitted ' : count , ' success ' : True }
except Exception as e :
log ( f " 流程异常: { traceback . format_exc ( ) } " )
state [ ' last_result ' ] = { ' error ' : str ( e ) , ' success ' : False }
finally :
state [ ' running ' ] = False
threading . Thread ( target = _startup_test , daemon = True ) . start ( )
while not shutdown_requested :
server . handle_request ( )
server . server_close ( )
log ( " 智能体已关闭 " )
if __name__ == " " :
if __name__ == ' ' :
main ( )
