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refactor: v1 API 统一使用 catelogid 参数替代 lctype/llmcatelogid

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yumoqing 2026-05-30 16:22:21 +08:00
parent f32f49fb85
commit 08bebcd257
5 changed files with 27 additions and 22 deletions
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17
docs/API.md
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@ -21,6 +21,7 @@ Base Path: `/llmage/v1`
| 参数 | 类型 | 说明 | | 参数 | 类型 | 说明 |
|------|------|------| |------|------|------|
| `catelogid` | string | 目录类型，默认 `"文生文"` |
| `stream` | boolean | 是否启用流式输出 | | `stream` | boolean | 是否启用流式输出 |
| `off_peak` | boolean | 是否使用非高峰时段 | | `off_peak` | boolean | 是否使用非高峰时段 |
| `transno` | string | 交易流水号（不传则自动生成） | | `transno` | string | 交易流水号（不传则自动生成） |
@ -82,7 +83,7 @@ data: [DONE]
| 参数 | 类型 | 说明 | | 参数 | 类型 | 说明 |
|------|------|------| |------|------|------|
| `model` | string | 模型名称，如 `"keling-2.1"` | | `model` | string | 模型名称，如 `"keling-2.1"` |
| `llmcatelogid` | string | 目录类型，如 `"文生视频"` / `"图生视频"` | | `catelogid` | string | 目录类型，如 `"文生视频"` / `"图生视频"` |
| `prompt` | string | 生成提示词 | | `prompt` | string | 生成提示词 |
### 可选参数 ### 可选参数
@ -100,7 +101,7 @@ data: [DONE]
```json ```json
{ {
"model": "keling-2.1", "model": "keling-2.1",
"llmcatelogid": "文生视频", "catelogid": "文生视频",
"prompt": "A beautiful sunset over the ocean", "prompt": "A beautiful sunset over the ocean",
"duration": "5s", "duration": "5s",
"resolution": "1080p" "resolution": "1080p"
@ -135,7 +136,7 @@ data: [DONE]
| 参数 | 类型 | 说明 | | 参数 | 类型 | 说明 |
|------|------|------| |------|------|------|
| `model` | string | 模型名称，如 `"jimeng-4.0"` | | `model` | string | 模型名称，如 `"jimeng-4.0"` |
| `llmcatelogid` | string | 目录类型，如 `"文生图"` / `"图生图"` | | `catelogid` | string | 目录类型，如 `"文生图"` / `"图生图"` |
| `prompt` | string | 生成提示词 | | `prompt` | string | 生成提示词 |
### 可选参数 ### 可选参数
@ -154,7 +155,7 @@ data: [DONE]
```json ```json
{ {
"model": "jimeng-4.0", "model": "jimeng-4.0",
"llmcatelogid": "文生图", "catelogid": "文生图",
"prompt": "A beautiful sunset over the ocean", "prompt": "A beautiful sunset over the ocean",
"size": "1024x1024", "size": "1024x1024",
"n": 1 "n": 1
@ -218,7 +219,7 @@ GET /llmage/v1/tasks?taskid=task_xxx
| 参数 | 类型 | 说明 | | 参数 | 类型 | 说明 |
|------|------|------| |------|------|------|
| `lctype` | string | 按目录类型过滤 | | `catelogid` | string | 按目录类型过滤 |
| `orderby` | string | 排序字段 | | `orderby` | string | 排序字段 |
### 请求示例 ### 请求示例
@ -247,12 +248,16 @@ GET /llmage/v1/models
## 通用说明 ## 通用说明
### 参数统一
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`。
### 认证 ### 认证
所有接口需要 Bearer Token 认证，请求头中携带: 所有接口需要 Bearer Token 认证，请求头中携带:
``` ```
Authorization: Bearer <your_api_key> Authorization: Bearer ***
``` ```
### 余额检查 ### 余额检查

6
wwwroot/v1/chat/completions/index.dspy
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@ -10,7 +10,7 @@ async def gen():
yield l yield l
debug_params('params_kw', params_kw) debug_params('params_kw', params_kw)
lctype='文生文' catelogid = params_kw.catelogid or '文生文'
if params_kw.off_peak: if params_kw.off_peak:
off_peak = params_kw.off_peak off_peak = params_kw.off_peak
if off_peak in [True, "Y" "y", 1, "1"]: if off_peak in [True, "Y" "y", 1, "1"]:
@ -33,11 +33,11 @@ async with get_sor_context(env, 'llmage') as sor:
sql = """select distinct a.* from llm a sql = """select distinct a.* from llm a
join llm_api_map m on a.id = m.llmid join llm_api_map m on a.id = m.llmid
join llmcatelog b on m.llmcatelogid = b.id join llmcatelog b on m.llmcatelogid = b.id
where b.name = ${lctype}$ where b.name = ${catelogid}$
and a.model=${model}$ and a.model=${model}$
and a.status = 'published'""" and a.status = 'published'"""
recs = await sor.sqlExe(sql, { recs = await sor.sqlExe(sql, {
'lctype': lctype, 'catelogid': catelogid,
'model': params_kw.model or 'qwen3-max' 'model': params_kw.model or 'qwen3-max'
}) })
if len(recs) == 0: if len(recs) == 0:

10
wwwroot/v1/image/generations/index.dspy
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@ -1,12 +1,12 @@
# OpenAI-compatible Image Generation API # OpenAI-compatible Image Generation API
# POST /v1/image/generations # POST /v1/image/generations
# Required params: model, llmcatelogid # Required params: model, catelogid
# Optional params: prompt, image_url, n, size, style, quality, etc. # Optional params: prompt, image_url, n, size, style, quality, etc.
# #
# Example request: # Example request:
# { # {
# "model": "jimeng-4.0", # "model": "jimeng-4.0",
# "llmcatelogid": "文生图", # "catelogid": "文生图",
# "prompt": "A beautiful sunset over the ocean", # "prompt": "A beautiful sunset over the ocean",
# "size": "1024x1024", # "size": "1024x1024",
# "n": 1 # "n": 1
@ -36,15 +36,15 @@ if not params_kw.model:
d = return_error('Missing required parameter: model') d = return_error('Missing required parameter: model')
return json_response(d, status=400) return json_response(d, status=400)
if not params_kw.llmcatelogid: if not params_kw.catelogid:
d = return_error('Missing required parameter: llmcatelogid') d = return_error('Missing required parameter: catelogid')
return json_response(d, status=400) return json_response(d, status=400)
if not params_kw.prompt: if not params_kw.prompt:
d = return_error('Missing required parameter: prompt') d = return_error('Missing required parameter: prompt')
return json_response(d, status=400) return json_response(d, status=400)
lctype = params_kw.llmcatelogid lctype = params_kw.catelogid
env = request._run_ns env = request._run_ns
async with get_sor_context(env, 'llmage') as sor: async with get_sor_context(env, 'llmage') as sor:

4
wwwroot/v1/models/index.dspy
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@ -6,9 +6,9 @@ def get_time_in_seconds(datestr):
timestamp = dt_obj.timestamp() timestamp = dt_obj.timestamp()
return timestamp return timestamp
lctype=params_kw.lctype catelogid = params_kw.catelogid
orderby = params_kw.orderby or 'model' orderby = params_kw.orderby or 'model'
rets = await get_llms_by_catelog_to_customer(catelogid=lctype, orderby=orderby) rets = await get_llms_by_catelog_to_customer(catelogid=catelogid, orderby=orderby)
ret = { ret = {
"object": "list", "object": "list",
"data": [] "data": []

10
wwwroot/v1/video/generations/index.dspy
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@ -1,12 +1,12 @@
# OpenAI-compatible Video Generation API # OpenAI-compatible Video Generation API
# POST /v1/video/generations # POST /v1/video/generations
# Required params: model, llmcatelogid # Required params: model, catelogid
# Optional params: prompt, image_url, duration, resolution, n, etc. # Optional params: prompt, image_url, duration, resolution, n, etc.
# #
# Example request: # Example request:
# { # {
# "model": "keling-2.1", # "model": "keling-2.1",
# "llmcatelogid": "文生视频", # "catelogid": "文生视频",
# "prompt": "A beautiful sunset over the ocean", # "prompt": "A beautiful sunset over the ocean",
# "duration": "5s", # "duration": "5s",
# "resolution": "1080p" # "resolution": "1080p"
@ -44,15 +44,15 @@ if not params_kw.model:
d = return_error('Missing required parameter: model') d = return_error('Missing required parameter: model')
return json_response(d, status=400) return json_response(d, status=400)
if not params_kw.llmcatelogid: if not params_kw.catelogid:
d = return_error('Missing required parameter: llmcatelogid') d = return_error('Missing required parameter: catelogid')
return json_response(d, status=400) return json_response(d, status=400)
if not params_kw.prompt: if not params_kw.prompt:
d = return_error('Missing required parameter: prompt') d = return_error('Missing required parameter: prompt')
return json_response(d, status=400) return json_response(d, status=400)
lctype = params_kw.llmcatelogid lctype = params_kw.catelogid
env = request._run_ns env = request._run_ns
async with get_sor_context(env, 'llmage') as sor: async with get_sor_context(env, 'llmage') as sor: