yumoqing
6890af7638
删除已在 ahserver/ServerEnv 预加载的模块: json, datetime, getID, debug, curDateString, timestampstr, get_sor_context, time, DictObject, partial, FileStorage, os 删除模块内部 import: from llmage.utils import get_llmusage_by_id, read_ioinfo_content 同步将 get_llmusage_by_id, read_ioinfo_content 加入 load_llmage() 导出, dspy 中通过 ServerEnv 全局调用。
74 lines
2.1 KiB
Plaintext
74 lines
2.1 KiB
Plaintext
# OpenAI-compatible Image Generation API
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# POST /v1/image/generations
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# Required params: model, catelogid
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# Optional params: prompt, image_url, n, size, style, quality, etc.
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#
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# Example request:
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# {
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# "model": "jimeng-4.0",
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# "catelogid": "t2i",
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# "prompt": "A beautiful sunset over the ocean",
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# "size": "1024x1024",
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# "n": 1
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# }
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#
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# Response format depends on the upstream model (sync returns image data, async returns task info)
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debug_params('params_kw', params_kw)
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userid = await get_user()
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userorgid = await get_userorgid()
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if userid is None:
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debug('need login')
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return openai_403()
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# Validate required parameters
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if not params_kw.model:
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d = return_error('Missing required parameter: model')
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return json_response(d, status=400)
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if not params_kw.catelogid:
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d = return_error('Missing required parameter: catelogid')
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return json_response(d, status=400)
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if not params_kw.prompt:
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d = return_error('Missing required parameter: prompt')
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return json_response(d, status=400)
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lctype = params_kw.catelogid
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env = request._run_ns
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async with get_sor_context(env, 'llmage') as sor:
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# Look up llm by model name and catalog type through llm_api_map
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sql = """select distinct a.* from llm a
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join llm_api_map m on a.id = m.llmid
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join llmcatelog b on m.llmcatelogid = b.id
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where (b.id = ${lctype}$ OR b.name = ${lctype}$)
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and a.model=${model}$
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and a.status = 'published'"""
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recs = await sor.sqlExe(sql, {
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'lctype': lctype,
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'model': params_kw.model
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})
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if len(recs) == 0:
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debug(f'{params_kw.model=} not found for catalog {lctype}')
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return openai_400()
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params_kw.llmid = recs[0].id
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params_kw.llmcatelogid = lctype
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debug(f'{params_kw.llmid=}')
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# Check balance
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f = await checkCustomerBalance(params_kw.llmid, userid, userorgid)
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if not f:
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debug(f'{userid=} balance not enough')
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return openai_429()
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# Generate task ID and attach to params
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if not params_kw.transno:
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params_kw.transno = getID()
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# Call inference (image generation can be sync or async depending on model config)
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return await inference(request, env=env)
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