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Code Issues Packages Projects Releases Wiki Activity

Add ModelScope Support

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yrk
2025-04-03 16:55:14 +08:00
parent f9d07779a9
commit b09ce8296f
10 changed files with 374 additions and 2 deletions
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1
README.md
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@@ -117,6 +117,7 @@
| [阿里云百炼](https://bailian.console.aliyun.com/) | ✅ | 大模型聚合平台, LLMOps 平台 |
| [火山方舟](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | ✅ | 大模型聚合平台, LLMOps 平台 |
| [MCP](https://modelcontextprotocol.io/) | ✅ | 支持通过 MCP 协议获取工具 |
| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | ✅ | |
### TTS

1
README_EN.md
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@@ -114,6 +114,7 @@ Directly use the released version to run, see the [Manual Deployment](https://do
| [Aliyun Bailian](https://bailian.console.aliyun.com/) | ✅ | LLM gateway(MaaS), LLMOps platform |
| [Volc Engine Ark](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | ✅ | LLM gateway(MaaS), LLMOps platform |
| [MCP](https://modelcontextprotocol.io/) | ✅ | Support tool access through MCP protocol |
| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | ✅ | |
## 🤝 Community Contribution

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README_JP.md
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@@ -113,6 +113,7 @@ LangBotはBTPanelにリストされています。BTPanelをインストール
| [Aliyun Bailian](https://bailian.console.aliyun.com/) | ✅ | LLMゲートウェイ(MaaS), LLMOpsプラットフォーム |
| [Volc Engine Ark](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | ✅ | LLMゲートウェイ(MaaS), LLMOpsプラットフォーム |
| [MCP](https://modelcontextprotocol.io/) | ✅ | MCPプロトコルをサポート |
| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | ✅ | |
## 🤝 コミュニティ貢献

30
pkg/core/migrations/m039_modelscope_cfg_completion.py Normal file
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@@ -0,0 +1,30 @@
from __future__ import annotations
from .. import migration
@migration.migration_class("modelscope-config-completion", 4)
class ModelScopeConfigCompletionMigration(migration.Migration):
"""OpenAI配置迁移
"""
async def need_migrate(self) -> bool:
"""判断当前环境是否需要运行此迁移
"""
return 'modelscope-chat-completions' not in self.ap.provider_cfg.data['requester'] \
or 'modelscope' not in self.ap.provider_cfg.data['keys']
async def run(self):
"""执行迁移
"""
if 'modelscope-chat-completions' not in self.ap.provider_cfg.data['requester']:
self.ap.provider_cfg.data['requester']['modelscope-chat-completions'] = {
'base-url': 'https://api.modelscope.cn/v1',
'args': {},
'timeout': 120,
}
if 'modelscope' not in self.ap.provider_cfg.data['keys']:
self.ap.provider_cfg.data['keys']['modelscope'] = []
await self.ap.provider_cfg.dump_config()

2
pkg/core/stages/migrate.py
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@@ -12,7 +12,7 @@ from ..migrations import m020_wecom_config, m021_lark_config, m022_lmstudio_conf
from ..migrations import m026_qqofficial_config, m027_wx_official_account_config, m028_aliyun_requester_config
from ..migrations import m029_dashscope_app_api_config, m030_lark_config_cmpl, m031_dingtalk_config, m032_volcark_config
from ..migrations import m033_dify_thinking_config, m034_gewechat_file_url_config, m035_wxoa_mode, m036_wxoa_loading_message
from ..migrations import m037_mcp_config, m038_tg_dingtalk_markdown
from ..migrations import m037_mcp_config, m038_tg_dingtalk_markdown, m039_modelscope_cfg_completion
@stage.stage_class("MigrationStage")

2
pkg/provider/modelmgr/modelmgr.py
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@@ -6,7 +6,7 @@ from . import entities, requester
from ...core import app
from ...discover import engine
from . import token
from .requesters import bailianchatcmpl, chatcmpl, anthropicmsgs, moonshotchatcmpl, deepseekchatcmpl, ollamachat, giteeaichatcmpl, volcarkchatcmpl, xaichatcmpl, zhipuaichatcmpl, lmstudiochatcmpl, siliconflowchatcmpl, volcarkchatcmpl
from .requesters import bailianchatcmpl, chatcmpl, anthropicmsgs, moonshotchatcmpl, deepseekchatcmpl, ollamachat, giteeaichatcmpl, volcarkchatcmpl, xaichatcmpl, zhipuaichatcmpl, lmstudiochatcmpl, siliconflowchatcmpl, volcarkchatcmpl, modelscopechatcmpl
FETCH_MODEL_LIST_URL = "https://api.qchatgpt.rockchin.top/api/v2/fetch/model_list"

207
pkg/provider/modelmgr/requesters/modelscopechatcmpl.py Normal file
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@@ -0,0 +1,207 @@
from __future__ import annotations
import asyncio
import typing
import json
import base64
from typing import AsyncGenerator
import openai
import openai.types.chat.chat_completion as chat_completion
import openai.types.chat.chat_completion_message_tool_call as chat_completion_message_tool_call
import httpx
import aiohttp
import async_lru
from .. import entities, errors, requester
from ....core import entities as core_entities, app
from ... import entities as llm_entities
from ...tools import entities as tools_entities
from ....utils import image
class ModelScopeChatCompletions(requester.LLMAPIRequester):
"""ModelScope ChatCompletion API 请求器"""
client: openai.AsyncClient
requester_cfg: dict
def __init__(self, ap: app.Application):
self.ap = ap
self.requester_cfg = self.ap.provider_cfg.data['requester']['modelscope-chat-completions']
async def initialize(self):
self.client = openai.AsyncClient(
api_key="",
base_url=self.requester_cfg['base-url'],
timeout=self.requester_cfg['timeout'],
http_client=httpx.AsyncClient(
trust_env=True,
timeout=self.requester_cfg['timeout']
)
)
async def _req(
self,
args: dict,
) -> chat_completion.ChatCompletion:
args["stream"] = True
chunk = None
pending_content = ""
tool_calls = []
resp_gen: openai.AsyncStream = await self.client.chat.completions.create(**args)
async for chunk in resp_gen:
# print(chunk)
if not chunk or not chunk.id or not chunk.choices or not chunk.choices[0] or not chunk.choices[0].delta:
continue
if chunk.choices[0].delta.content is not None:
pending_content += chunk.choices[0].delta.content
if chunk.choices[0].delta.tool_calls is not None:
for tool_call in chunk.choices[0].delta.tool_calls:
for tc in tool_calls:
if tc.index == tool_call.index:
tc.function.arguments += tool_call.function.arguments
break
else:
tool_calls.append(tool_call)
if chunk.choices[0].finish_reason is not None:
break
real_tool_calls = []
for tc in tool_calls:
function = chat_completion_message_tool_call.Function(
name=tc.function.name,
arguments=tc.function.arguments
)
real_tool_calls.append(chat_completion_message_tool_call.ChatCompletionMessageToolCall(
id=tc.id,
function=function,
type="function"
))
return chat_completion.ChatCompletion(
id=chunk.id,
object="chat.completion",
created=chunk.created,
choices=[
chat_completion.Choice(
index=0,
message=chat_completion.ChatCompletionMessage(
role="assistant",
content=pending_content,
tool_calls=real_tool_calls if len(real_tool_calls) > 0 else None
),
finish_reason=chunk.choices[0].finish_reason if hasattr(chunk.choices[0], 'finish_reason') and chunk.choices[0].finish_reason is not None else 'stop',
logprobs=chunk.choices[0].logprobs,
)
],
model=chunk.model,
service_tier=chunk.service_tier if hasattr(chunk, 'service_tier') else None,
system_fingerprint=chunk.system_fingerprint if hasattr(chunk, 'system_fingerprint') else None,
usage=chunk.usage if hasattr(chunk, 'usage') else None
) if chunk else None
return await self.client.chat.completions.create(**args)
async def _make_msg(
self,
chat_completion: chat_completion.ChatCompletion,
) -> llm_entities.Message:
chatcmpl_message = chat_completion.choices[0].message.dict()
# 确保 role 字段存在且不为 None
if 'role' not in chatcmpl_message or chatcmpl_message['role'] is None:
chatcmpl_message['role'] = 'assistant'
message = llm_entities.Message(**chatcmpl_message)
return message
async def _closure(
self,
query: core_entities.Query,
req_messages: list[dict],
use_model: entities.LLMModelInfo,
use_funcs: list[tools_entities.LLMFunction] = None,
) -> llm_entities.Message:
self.client.api_key = use_model.token_mgr.get_token()
args = self.requester_cfg['args'].copy()
args["model"] = use_model.name if use_model.model_name is None else use_model.model_name
if use_funcs:
tools = await self.ap.tool_mgr.generate_tools_for_openai(use_funcs)
if tools:
args["tools"] = tools
# 设置此次请求中的messages
messages = req_messages.copy()
# 检查vision
for msg in messages:
if 'content' in msg and isinstance(msg["content"], list):
for me in msg["content"]:
if me["type"] == "image_base64":
me["image_url"] = {
"url": me["image_base64"]
}
me["type"] = "image_url"
del me["image_base64"]
args["messages"] = messages
# 发送请求
resp = await self._req(args)
# 处理请求结果
message = await self._make_msg(resp)
return message
async def call(
self,
query: core_entities.Query,
model: entities.LLMModelInfo,
messages: typing.List[llm_entities.Message],
funcs: typing.List[tools_entities.LLMFunction] = None,
) -> llm_entities.Message:
req_messages = [] # req_messages 仅用于类内，外部同步由 query.messages 进行
for m in messages:
msg_dict = m.dict(exclude_none=True)
content = msg_dict.get("content")
if isinstance(content, list):
# 检查 content 列表中是否每个部分都是文本
if all(isinstance(part, dict) and part.get("type") == "text" for part in content):
# 将所有文本部分合并为一个字符串
msg_dict["content"] = "\n".join(part["text"] for part in content)
req_messages.append(msg_dict)
try:
return await self._closure(query=query, req_messages=req_messages, use_model=model, use_funcs=funcs)
except asyncio.TimeoutError:
raise errors.RequesterError('请求超时')
except openai.BadRequestError as e:
if 'context_length_exceeded' in e.message:
raise errors.RequesterError(f'上文过长，请重置会话: {e.message}')
else:
raise errors.RequesterError(f'请求参数错误: {e.message}')
except openai.AuthenticationError as e:
raise errors.RequesterError(f'无效的 api-key: {e.message}')
except openai.NotFoundError as e:
raise errors.RequesterError(f'请求路径错误: {e.message}')
except openai.RateLimitError as e:
raise errors.RequesterError(f'请求过于频繁或余额不足: {e.message}')
except openai.APIError as e:
raise errors.RequesterError(f'请求错误: {e.message}')

34
pkg/provider/modelmgr/requesters/modelscopechatcmpl.yaml Normal file
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@@ -0,0 +1,34 @@
apiVersion: v1
kind: LLMAPIRequester
metadata:
name: modelscope-chat-completions
label:
en_US: ModelScope
zh_CN: 魔搭社区
spec:
config:
- name: base-url
label:
en_US: Base URL
zh_CN: 基础 URL
type: string
required: true
default: "https://api-inference.modelscope.cn/v1"
- name: args
label:
en_US: Args
zh_CN: 附加参数
type: object
required: true
default: {}
- name: timeout
label:
en_US: Timeout
zh_CN: 超时时间
type: int
required: true
default: 120
execution:
python:
path: ./modelscopechatcmpl.py
attr: ModelScopeChatCompletions

90
templates/metadata/llm-models.json
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@@ -232,6 +232,96 @@
"token_mgr": "zhipuai",
"vision_supported": true,
"tool_call_supported": true
},
{
"name": "Qwen/Qwen2.5-Coder-32B-Instruct",
"requester": "modelscope-chat-completions",
"token_mgr": "modelscope",
"tool_call_supported": true
},
{
"name": "Qwen/Qwen2.5-Coder-14B-Instruct",
"requester": "modelscope-chat-completions",
"token_mgr": "modelscope",
"tool_call_supported": true
},
{
"name": "Qwen/Qwen2.5-Coder-7B-Instruct",
"requester": "modelscope-chat-completions",
"token_mgr": "modelscope",
"tool_call_supported": true
},
{
"name": "Qwen/Qwen2.5-72B-Instruct",
"requester": "modelscope-chat-completions",
"token_mgr": "modelscope",
"tool_call_supported": true
},
{
"name": "Qwen/Qwen2.5-32B-Instruct",
"requester": "modelscope-chat-completions",
"token_mgr": "modelscope",
"tool_call_supported": true
},
{
"name": "Qwen/Qwen2.5-14B-Instruct",
"requester": "modelscope-chat-completions",
"token_mgr": "modelscope",
"tool_call_supported": true
},
{
"name": "Qwen/Qwen2.5-7B-Instruct",
"requester": "modelscope-chat-completions",
"token_mgr": "modelscope",
"tool_call_supported": true
},
{
"name": "Qwen/QwQ-32B-Preview",
"requester": "modelscope-chat-completions",
"token_mgr": "modelscope",
"tool_call_supported": true
},
{
"name": "Qwen/QwQ-32B",
"requester": "modelscope-chat-completions",
"token_mgr": "modelscope",
"tool_call_supported": true
},
{
"name": "LLM-Research/Llama-3.3-70B-Instruct",
"requester": "modelscope-chat-completions",
"token_mgr": "modelscope",
"tool_call_supported": true
},
{
"name": "LLM-Research/Meta-Llama-3.1-405B-Instruct",
"requester": "modelscope-chat-completions",
"token_mgr": "modelscope",
"tool_call_supported": true
},
{
"name": "LLM-Research/Meta-Llama-3.1-8B-Instruct",
"requester": "modelscope-chat-completions",
"token_mgr": "modelscope",
"tool_call_supported": true
},
{
"name": "LLM-Research/Meta-Llama-3.1-70B-Instruct",
"requester": "modelscope-chat-completions",
"token_mgr": "modelscope",
"tool_call_supported": true
},
{
"name": "mistralai/Ministral-8B-Instruct-2410",
"requester": "modelscope-chat-completions",
"token_mgr": "modelscope",
"tool_call_supported": true
},
{
"name": "deepseek-ai/DeepSeek-V3-0324",
"requester": "modelscope-chat-completions",
"token_mgr": "modelscope",
"tool_call_supported": true
}
]
}

8
templates/provider.json
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@@ -31,6 +31,9 @@
],
"volcark": [
"xxxxxxxx"
],
"modelscope": [
"xxxxxxxx"
]
},
"requester": {
@@ -95,6 +98,11 @@
"args": {},
"base-url": "https://ark.cn-beijing.volces.com/api/v3",
"timeout": 120
},
"modelscope-chat-completions": {
"base-url": "https://api-inference.modelscope.cn/v1",
"args": {},
"timeout": 120
}
},
"model": "gpt-4o",