# OpenAI-compatible Image Generation API
# POST /v1/image/generations
# Required params: model, catelogid
# Optional params: prompt, image_url, n, size, style, quality, etc.
#
# Example request:
# {
#     "model": "jimeng-4.0",
#     "catelogid": "t2i",
#     "prompt": "A beautiful sunset over the ocean",
#     "size": "1024x1024",
#     "n": 1
# }
#
# Response format depends on the upstream model (sync returns image data, async returns task info)


debug_params('params_kw', params_kw)

userid = await get_user()
userorgid = await get_userorgid()
if userid is None:
    debug('need login')
    return openai_403()

# Validate required parameters
if not params_kw.model:
    d = return_error('Missing required parameter: model')
    return json_response(d, status=400)

if not params_kw.catelogid:
    d = return_error('Missing required parameter: catelogid')
    return json_response(d, status=400)

if not params_kw.prompt:
    d = return_error('Missing required parameter: prompt')
    return json_response(d, status=400)

lctype = params_kw.catelogid

env = request._run_ns
llmid = await env.get_llmid_cached(env, params_kw.model, lctype)
if not llmid:
	debug(f'{params_kw.model=} not found for catalog {lctype}')
	return openai_400()
params_kw.llmid = llmid
params_kw.llmcatelogid = lctype

debug(f'{params_kw.llmid=}')

# Check balance
f = await checkCustomerBalance(params_kw.llmid, userid, userorgid)
if not f:
    debug(f'{userid=} balance not enough')
    return openai_429()

# Generate task ID and attach to params
if not params_kw.transno:
    params_kw.transno = getID()

# Call inference (image generation can be sync or async depending on model config)
return await inference(request, env=env)