1|# KTV Pipeline / GPU Service Inference API
2|# POST /v1/pipeline/submit
3|# catelogid 固定为 ktv_pipeline，无需传 catelogid
4|#
5|# Required params:
6|#   model: string - 模型名称，如 "ky-asr-transcribe"
7|#
8|# 各服务特定参数见 API 文档
9|#
10|# 同步服务直接返回结果：
11|# {
12|#   "taskid": "luid_xxx",
13|#   "taskstatus": "SUCCEEDED",
14|#   ...服务特定结果字段...,
15|#   "usage": {...}
16|# }
17|#
18|# 异步服务返回任务信息：
19|# {
20|#   "taskid": "luid_xxx",
21|#   "taskstatus": "PENDING"
22|# }
23|# 异步结果通过 /v1/tasks?taskid=xxx 查询
24|
25|debug_params('params_kw', params_kw)
26|
27|userid = await get_user()
28|userorgid = await get_userorgid()
29|if userid is None:
30|	debug('need login')
31|	return openai_403()
32|
33|# Validate required parameters
34|if not params_kw.model:
35|	d = return_error('Missing required parameter: model')
36|	return json_response(d, status=400)
37|
38|catelogid = 'ktv_pipeline'
39|params_kw.catelogid = catelogid
40|
41|env = request._run_ns
42|# llmid from cache (model+catelogid -> llmid)
llmid = await env.get_llmid_cached(env, params_kw.model or 'qwen3-max', 'ktv_pipeline')
if not llmid:
	debug(f'model not found: params_kw.model')
	return {{error_response}}
params_kw.llmid = llmid
59|	params_kw.llmcatelogid = catelogid
60|
61|debug(f'{params_kw.llmid=}')
62|
63|# Check balance
64|f = await checkCustomerBalance(params_kw.llmid, userid, userorgid)
65|if not f:
66|	debug(f'{userid=} balance not enough')
67|	return openai_429()
68|
69|# Generate task ID
70|if not params_kw.transno:
71|	params_kw.transno = getID()
72|
73|# Call inference
74|return await inference(request, env=env)
75|