refactor: v1 API 统一使用 catelogid 参数替代 lctype/llmcatelogid
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docs/API.md
17
docs/API.md
@ -21,6 +21,7 @@ Base Path: `/llmage/v1`
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| 参数 | 类型 | 说明 |
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|------|------|------|
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| `catelogid` | string | 目录类型，默认 `"文生文"` |
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| `stream` | boolean | 是否启用流式输出 |
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| `off_peak` | boolean | 是否使用非高峰时段 |
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| `transno` | string | 交易流水号（不传则自动生成） |
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@ -82,7 +83,7 @@ data: [DONE]
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| 参数 | 类型 | 说明 |
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|------|------|------|
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| `model` | string | 模型名称，如 `"keling-2.1"` |
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| `llmcatelogid` | string | 目录类型，如 `"文生视频"` / `"图生视频"` |
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| `catelogid` | string | 目录类型，如 `"文生视频"` / `"图生视频"` |
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| `prompt` | string | 生成提示词 |
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### 可选参数
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@ -100,7 +101,7 @@ data: [DONE]
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```json
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{
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"model": "keling-2.1",
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"llmcatelogid": "文生视频",
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"catelogid": "文生视频",
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"prompt": "A beautiful sunset over the ocean",
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"duration": "5s",
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"resolution": "1080p"
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@ -135,7 +136,7 @@ data: [DONE]
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| 参数 | 类型 | 说明 |
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|------|------|------|
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| `model` | string | 模型名称，如 `"jimeng-4.0"` |
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| `llmcatelogid` | string | 目录类型，如 `"文生图"` / `"图生图"` |
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| `catelogid` | string | 目录类型，如 `"文生图"` / `"图生图"` |
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| `prompt` | string | 生成提示词 |
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### 可选参数
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@ -154,7 +155,7 @@ data: [DONE]
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```json
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{
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"model": "jimeng-4.0",
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"llmcatelogid": "文生图",
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"catelogid": "文生图",
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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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@ -218,7 +219,7 @@ GET /llmage/v1/tasks?taskid=task_xxx
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| 参数 | 类型 | 说明 |
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|------|------|------|
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| `lctype` | string | 按目录类型过滤 |
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| `catelogid` | string | 按目录类型过滤 |
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| `orderby` | string | 排序字段 |
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### 请求示例
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@ -247,12 +248,16 @@ GET /llmage/v1/models
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## 通用说明
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### 参数统一
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所有 v1 接口统一使用 `catelogid` 参数标识目录类型，替代原有的 `lctype` / `llmcatelogid`。
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### 认证
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所有接口需要 Bearer Token 认证，请求头中携带:
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```
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Authorization: Bearer <your_api_key>
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Authorization: Bearer ***
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```
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### 余额检查
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@ -10,7 +10,7 @@ async def gen():
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yield l
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debug_params('params_kw', params_kw)
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lctype='文生文'
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catelogid = params_kw.catelogid or '文生文'
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if params_kw.off_peak:
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off_peak = params_kw.off_peak
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if off_peak in [True, "Y" "y", 1, "1"]:
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@ -33,11 +33,11 @@ async with get_sor_context(env, 'llmage') as sor:
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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.name = ${lctype}$
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where b.name = ${catelogid}$
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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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'catelogid': catelogid,
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'model': params_kw.model or 'qwen3-max'
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})
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if len(recs) == 0:
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@ -1,12 +1,12 @@
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# OpenAI-compatible Image Generation API
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# POST /v1/image/generations
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# Required params: model, llmcatelogid
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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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# "llmcatelogid": "文生图",
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# "catelogid": "文生图",
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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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@ -36,15 +36,15 @@ 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.llmcatelogid:
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d = return_error('Missing required parameter: llmcatelogid')
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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.llmcatelogid
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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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@ -6,9 +6,9 @@ def get_time_in_seconds(datestr):
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timestamp = dt_obj.timestamp()
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return timestamp
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lctype=params_kw.lctype
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orderby=params_kw.orderby or 'model'
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rets = await get_llms_by_catelog_to_customer(catelogid=lctype, orderby=orderby)
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catelogid = params_kw.catelogid
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orderby = params_kw.orderby or 'model'
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rets = await get_llms_by_catelog_to_customer(catelogid=catelogid, orderby=orderby)
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ret = {
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"object": "list",
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"data": []
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@ -1,12 +1,12 @@
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# OpenAI-compatible Video Generation API
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# POST /v1/video/generations
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# Required params: model, llmcatelogid
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# Required params: model, catelogid
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# Optional params: prompt, image_url, duration, resolution, n, etc.
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#
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# Example request:
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# {
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# "model": "keling-2.1",
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# "llmcatelogid": "文生视频",
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# "catelogid": "文生视频",
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# "prompt": "A beautiful sunset over the ocean",
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# "duration": "5s",
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# "resolution": "1080p"
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@ -44,15 +44,15 @@ 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.llmcatelogid:
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d = return_error('Missing required parameter: llmcatelogid')
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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.llmcatelogid
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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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