style: restrict line-length

2026-06-11 16:26:02 +00:00 · 2025-05-10 18:04:58 +08:00
parent b30016ed08
commit 055b389353
134 changed files with 1096 additions and 2595 deletions
--- a/pkg/provider/entities.py
+++ b/pkg/provider/entities.py
@@ -80,17 +80,13 @@ class Message(pydantic.BaseModel):

    def readable_str(self) -> str:
        if self.content is not None:
-            return (
-                str(self.role) + ': ' + str(self.get_content_platform_message_chain())
-            )
+            return str(self.role) + ': ' + str(self.get_content_platform_message_chain())
        elif self.tool_calls is not None:
            return f'调用工具: {self.tool_calls[0].id}'
        else:
            return '未知消息'

-    def get_content_platform_message_chain(
-        self, prefix_text: str = ''
-    ) -> platform_message.MessageChain | None:
+    def get_content_platform_message_chain(self, prefix_text: str = '') -> platform_message.MessageChain | None:
        """将内容转换为平台消息 MessageChain 对象

        Args:
@@ -100,9 +96,7 @@ class Message(pydantic.BaseModel):
        if self.content is None:
            return None
        elif isinstance(self.content, str):
-            return platform_message.MessageChain(
-                [platform_message.Plain(prefix_text + self.content)]
-            )
+            return platform_message.MessageChain([platform_message.Plain(prefix_text + self.content)])
        elif isinstance(self.content, list):
            mc = []
            for ce in self.content:
--- a/pkg/provider/modelmgr/modelmgr.py
+++ b/pkg/provider/modelmgr/modelmgr.py
@@ -43,16 +43,12 @@ class ModelManager:
        self.requester_dict = {}

    async def initialize(self):
-        self.requester_components = self.ap.discover.get_components_by_kind(
-            'LLMAPIRequester'
-        )
+        self.requester_components = self.ap.discover.get_components_by_kind('LLMAPIRequester')

        # forge requester class dict
        requester_dict: dict[str, type[requester.LLMAPIRequester]] = {}
        for component in self.requester_components:
-            requester_dict[component.metadata.name] = (
-                component.get_python_component_class()
-            )
+            requester_dict[component.metadata.name] = component.get_python_component_class()

        self.requester_dict = requester_dict

@@ -65,9 +61,7 @@ class ModelManager:
        self.llm_models = []

        # llm models
-        result = await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.select(persistence_model.LLMModel)
-        )
+        result = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_model.LLMModel))

        llm_models = result.all()

@@ -77,9 +71,7 @@ class ModelManager:

    async def load_llm_model(
        self,
-        model_info: persistence_model.LLMModel
-        | sqlalchemy.Row[persistence_model.LLMModel]
-        | dict,
+        model_info: persistence_model.LLMModel | sqlalchemy.Row[persistence_model.LLMModel] | dict,
    ):
        """加载模型"""

@@ -88,9 +80,7 @@ class ModelManager:
        elif isinstance(model_info, dict):
            model_info = persistence_model.LLMModel(**model_info)

-        requester_inst = self.requester_dict[model_info.requester](
-            ap=self.ap, config=model_info.requester_config
-        )
+        requester_inst = self.requester_dict[model_info.requester](ap=self.ap, config=model_info.requester_config)

        await requester_inst.initialize()

@@ -136,9 +126,7 @@ class ModelManager:
                return component.to_plain_dict()
        return None

-    def get_available_requester_manifest_by_name(
-        self, name: str
-    ) -> engine.Component | None:
+    def get_available_requester_manifest_by_name(self, name: str) -> engine.Component | None:
        """通过名称获取请求器清单"""
        for component in self.requester_components:
            if component.metadata.name == name:
--- a/pkg/provider/modelmgr/requesters/anthropicmsgs.py
+++ b/pkg/provider/modelmgr/requesters/anthropicmsgs.py
@@ -73,9 +73,7 @@ class AnthropicMessages(requester.LLMAPIRequester):
        if system_role_message:
            messages.pop(i)

-        if isinstance(system_role_message, llm_entities.Message) and isinstance(
-            system_role_message.content, str
-        ):
+        if isinstance(system_role_message, llm_entities.Message) and isinstance(system_role_message.content, str):
            args['system'] = system_role_message.content

        req_messages = []
@@ -106,9 +104,7 @@ class AnthropicMessages(requester.LLMAPIRequester):
            elif isinstance(m.content, list):
                for i, ce in enumerate(m.content):
                    if ce.type == 'image_base64':
-                        image_b64, image_format = await image.extract_b64_and_format(
-                            ce.image_base64
-                        )
+                        image_b64, image_format = await image.extract_b64_and_format(ce.image_base64)

                        alter_image_ele = {
                            'type': 'image',
@@ -156,9 +152,7 @@ class AnthropicMessages(requester.LLMAPIRequester):

            for block in resp.content:
                if block.type == 'thinking':
-                    args['content'] = (
-                        '<think>' + block.thinking + '</think>\n' + args['content']
-                    )
+                    args['content'] = '<think>' + block.thinking + '</think>\n' + args['content']
                elif block.type == 'text':
                    args['content'] += block.text
                elif block.type == 'tool_use':
@@ -166,9 +160,7 @@ class AnthropicMessages(requester.LLMAPIRequester):
                    tool_call = llm_entities.ToolCall(
                        id=block.id,
                        type='function',
-                        function=llm_entities.FunctionCall(
-                            name=block.name, arguments=json.dumps(block.input)
-                        ),
+                        function=llm_entities.FunctionCall(name=block.name, arguments=json.dumps(block.input)),
                    )
                    if 'tool_calls' not in args:
                        args['tool_calls'] = []
--- a/pkg/provider/modelmgr/requesters/chatcmpl.py
+++ b/pkg/provider/modelmgr/requesters/chatcmpl.py
@@ -28,9 +28,7 @@ class OpenAIChatCompletions(requester.LLMAPIRequester):
            api_key='',
            base_url=self.requester_cfg['base_url'].replace(' ', ''),
            timeout=self.requester_cfg['timeout'],
-            http_client=httpx.AsyncClient(
-                trust_env=True, timeout=self.requester_cfg['timeout']
-            ),
+            http_client=httpx.AsyncClient(trust_env=True, timeout=self.requester_cfg['timeout']),
        )

    async def _req(
@@ -50,20 +48,11 @@ class OpenAIChatCompletions(requester.LLMAPIRequester):
        if 'role' not in chatcmpl_message or chatcmpl_message['role'] is None:
            chatcmpl_message['role'] = 'assistant'

-        reasoning_content = (
-            chatcmpl_message['reasoning_content']
-            if 'reasoning_content' in chatcmpl_message
-            else None
-        )
+        reasoning_content = chatcmpl_message['reasoning_content'] if 'reasoning_content' in chatcmpl_message else None

        # deepseek的reasoner模型
        if reasoning_content is not None:
-            chatcmpl_message['content'] = (
-                '<think>\n'
-                + reasoning_content
-                + '\n</think>\n'
-                + chatcmpl_message['content']
-            )
+            chatcmpl_message['content'] = '<think>\n' + reasoning_content + '\n</think>\n' + chatcmpl_message['content']

        message = llm_entities.Message(**chatcmpl_message)

@@ -124,10 +113,7 @@ class OpenAIChatCompletions(requester.LLMAPIRequester):
            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
-                ):
+                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)
--- a/pkg/provider/modelmgr/requesters/modelscopechatcmpl.py
+++ b/pkg/provider/modelmgr/requesters/modelscopechatcmpl.py
@@ -1,23 +1,17 @@
 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):
@@ -33,26 +27,22 @@ class ModelScopeChatCompletions(requester.LLMAPIRequester):
        self.requester_cfg = self.ap.provider_cfg.data['requester']['modelscope-chat-completions']

    async def initialize(self):
-
        self.client = openai.AsyncClient(
-            api_key="",
+            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']
-            )
+            http_client=httpx.AsyncClient(trust_env=True, timeout=self.requester_cfg['timeout']),
        )

    async def _req(
        self,
        args: dict,
    ) -> chat_completion.ChatCompletion:
-        args["stream"] = True
+        args['stream'] = True

        chunk = None

-        pending_content = ""
+        pending_content = ''

        tool_calls = []

@@ -74,7 +64,7 @@ class ModelScopeChatCompletions(requester.LLMAPIRequester):
                            break
                    else:
                        tool_calls.append(tool_call)
-            
+
            if chunk.choices[0].finish_reason is not None:
                break

@@ -82,36 +72,41 @@ class ModelScopeChatCompletions(requester.LLMAPIRequester):

        for tc in tool_calls:
            function = chat_completion_message_tool_call.Function(
-                name=tc.function.name,
-                arguments=tc.function.arguments
+                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,
+            real_tool_calls.append(
+                chat_completion_message_tool_call.ChatCompletionMessageToolCall(
+                    id=tc.id, function=function, type='function'
                )
-            ],
-            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 (
+            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(
@@ -138,29 +133,27 @@ class ModelScopeChatCompletions(requester.LLMAPIRequester):
        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
+        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
+                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"]
+            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
+        args['messages'] = messages

        # 发送请求
        resp = await self._req(args)
@@ -180,12 +173,12 @@ class ModelScopeChatCompletions(requester.LLMAPIRequester):
        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")
+            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):
+                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)
+                    msg_dict['content'] = '\n'.join(part['text'] for part in content)
            req_messages.append(msg_dict)

        try:
@@ -204,4 +197,4 @@ class ModelScopeChatCompletions(requester.LLMAPIRequester):
        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}')
+            raise errors.RequesterError(f'请求错误: {e.message}')
--- a/pkg/provider/modelmgr/requesters/ollamachat.py
+++ b/pkg/provider/modelmgr/requesters/ollamachat.py
@@ -61,13 +61,9 @@ class OllamaChatCompletions(requester.LLMAPIRequester):

                msg['content'] = '\n'.join(text_content)
                msg['images'] = [url.split(',')[1] for url in image_urls]
-            if (
-                'tool_calls' in msg
-            ):  # LangBot 内部以 str 存储 tool_calls 的参数，这里需要转换为 dict
+            if 'tool_calls' in msg:  # LangBot 内部以 str 存储 tool_calls 的参数，这里需要转换为 dict
                for tool_call in msg['tool_calls']:
-                    tool_call['function']['arguments'] = json.loads(
-                        tool_call['function']['arguments']
-                    )
+                    tool_call['function']['arguments'] = json.loads(tool_call['function']['arguments'])
        args['messages'] = messages

        args['tools'] = []
@@ -80,9 +76,7 @@ class OllamaChatCompletions(requester.LLMAPIRequester):
        message: llm_entities.Message = await self._make_msg(resp)
        return message

-    async def _make_msg(
-        self, chat_completions: ollama.ChatResponse
-    ) -> llm_entities.Message:
+    async def _make_msg(self, chat_completions: ollama.ChatResponse) -> llm_entities.Message:
        message: ollama.Message = chat_completions.message
        if message is None:
            raise ValueError("chat_completions must contain a 'message' field")
@@ -122,10 +116,7 @@ class OllamaChatCompletions(requester.LLMAPIRequester):
            msg_dict: dict = m.dict(exclude_none=True)
            content: Any = msg_dict.get('content')
            if isinstance(content, list):
-                if all(
-                    isinstance(part, dict) and part.get('type') == 'text'
-                    for part in content
-                ):
+                if all(isinstance(part, dict) and part.get('type') == 'text' for part in content):
                    msg_dict['content'] = '\n'.join(part['text'] for part in content)
            req_messages.append(msg_dict)
        try:
--- a/pkg/provider/modelmgr/requesters/ppiochatcmpl.py
+++ b/pkg/provider/modelmgr/requesters/ppiochatcmpl.py
@@ -1,12 +1,11 @@
-
 from __future__ import annotations

 import openai

-from . import chatcmpl, modelscopechatcmpl
-from .. import requester
+from . import chatcmpl
 from ....core import app

+
 class PPIOChatCompletions(chatcmpl.OpenAIChatCompletions):
    """欧派云 ChatCompletion API 请求器"""

@@ -17,4 +16,4 @@ class PPIOChatCompletions(chatcmpl.OpenAIChatCompletions):
    def __init__(self, ap: app.Application):
        self.ap = ap

-        self.requester_cfg = self.ap.provider_cfg.data['requester']['ppio-chat-completions']
+        self.requester_cfg = self.ap.provider_cfg.data['requester']['ppio-chat-completions']
--- a/pkg/provider/runner.py
+++ b/pkg/provider/runner.py
@@ -35,8 +35,6 @@ class RequestRunner(abc.ABC):
        self.pipeline_config = pipeline_config

    @abc.abstractmethod
-    async def run(
-        self, query: core_entities.Query
-    ) -> typing.AsyncGenerator[llm_entities.Message, None]:
+    async def run(self, query: core_entities.Query) -> typing.AsyncGenerator[llm_entities.Message, None]:
        """运行请求"""
        pass
--- a/pkg/provider/runners/dashscopeapi.py
+++ b/pkg/provider/runners/dashscopeapi.py
@@ -26,7 +26,9 @@ class DashScopeAPIRunner(runner.RequestRunner):
    app_type: str  # 应用类型
    app_id: str  # 应用ID
    api_key: str  # API Key
-    references_quote: str  # 引用资料提示（当展示回答来源功能开启时，这个变量会作为引用资料名前的提示，可在provider.json中配置）
+    references_quote: (
+        str  # 引用资料提示（当展示回答来源功能开启时，这个变量会作为引用资料名前的提示，可在provider.json中配置）
+    )

    def __init__(self, ap: app.Application, pipeline_config: dict):
        """初始化"""
@@ -42,9 +44,7 @@ class DashScopeAPIRunner(runner.RequestRunner):
        # 初始化Dashscope 参数配置
        self.app_id = self.pipeline_config['ai']['dashscope-app-api']['app-id']
        self.api_key = self.pipeline_config['ai']['dashscope-app-api']['api-key']
-        self.references_quote = self.pipeline_config['ai']['dashscope-app-api'][
-            'references_quote'
-        ]
+        self.references_quote = self.pipeline_config['ai']['dashscope-app-api']['references_quote']

    def _replace_references(self, text, references_dict):
        """阿里云百炼平台的自定义应用支持资料引用，此函数可以将引用标签替换为参考资料"""
@@ -65,9 +65,7 @@ class DashScopeAPIRunner(runner.RequestRunner):
        # 使用 re.sub() 进行替换
        return pattern.sub(replacement, text)

-    async def _preprocess_user_message(
-        self, query: core_entities.Query
-    ) -> tuple[str, list[str]]:
+    async def _preprocess_user_message(self, query: core_entities.Query) -> tuple[str, list[str]]:
        """预处理用户消息，提取纯文本，阿里云提供的上传文件方法过于复杂，暂不支持上传文件（包括图片）"""
        plain_text = ''
        image_ids = []
@@ -91,9 +89,7 @@ class DashScopeAPIRunner(runner.RequestRunner):

        return plain_text, image_ids

-    async def _agent_messages(
-        self, query: core_entities.Query
-    ) -> typing.AsyncGenerator[llm_entities.Message, None]:
+    async def _agent_messages(self, query: core_entities.Query) -> typing.AsyncGenerator[llm_entities.Message, None]:
        """Dashscope 智能体对话请求"""

        # 局部变量
@@ -151,9 +147,7 @@ class DashScopeAPIRunner(runner.RequestRunner):
            content=pending_content,
        )

-    async def _workflow_messages(
-        self, query: core_entities.Query
-    ) -> typing.AsyncGenerator[llm_entities.Message, None]:
+    async def _workflow_messages(self, query: core_entities.Query) -> typing.AsyncGenerator[llm_entities.Message, None]:
        """Dashscope 工作流对话请求"""

        # 局部变量
@@ -216,9 +210,7 @@ class DashScopeAPIRunner(runner.RequestRunner):
            content=pending_content,
        )

-    async def run(
-        self, query: core_entities.Query
-    ) -> typing.AsyncGenerator[llm_entities.Message, None]:
+    async def run(self, query: core_entities.Query) -> typing.AsyncGenerator[llm_entities.Message, None]:
        """运行"""
        if self.app_type == 'agent':
            async for msg in self._agent_messages(query):
--- a/pkg/provider/runners/difysvapi.py
+++ b/pkg/provider/runners/difysvapi.py
@@ -26,10 +26,7 @@ class DifyServiceAPIRunner(runner.RequestRunner):
        self.pipeline_config = pipeline_config

        valid_app_types = ['chat', 'agent', 'workflow']
-        if (
-            self.pipeline_config['ai']['dify-service-api']['app-type']
-            not in valid_app_types
-        ):
+        if self.pipeline_config['ai']['dify-service-api']['app-type'] not in valid_app_types:
            raise errors.DifyAPIError(
                f'不支持的 Dify 应用类型: {self.pipeline_config["ai"]["dify-service-api"]["app-type"]}'
            )
@@ -48,16 +45,10 @@ class DifyServiceAPIRunner(runner.RequestRunner):
        ):
            return resp_text

-        if (
-            self.pipeline_config['ai']['dify-service-api']['thinking-convert']
-            == 'original'
-        ):
+        if self.pipeline_config['ai']['dify-service-api']['thinking-convert'] == 'original':
            return resp_text

-        if (
-            self.pipeline_config['ai']['dify-service-api']['thinking-convert']
-            == 'remove'
-        ):
+        if self.pipeline_config['ai']['dify-service-api']['thinking-convert'] == 'remove':
            return re.sub(
                r'<details style="color:gray;background-color: #f8f8f8;padding: 8px;border-radius: 4px;" open> <summary> Thinking... </summary>.*?</details>',
                '',
@@ -65,18 +56,13 @@ class DifyServiceAPIRunner(runner.RequestRunner):
                flags=re.DOTALL,
            )

-        if (
-            self.pipeline_config['ai']['dify-service-api']['thinking-convert']
-            == 'plain'
-        ):
+        if self.pipeline_config['ai']['dify-service-api']['thinking-convert'] == 'plain':
            pattern = r'<details style="color:gray;background-color: #f8f8f8;padding: 8px;border-radius: 4px;" open> <summary> Thinking... </summary>(.*?)</details>'
            thinking_text = re.search(pattern, resp_text, flags=re.DOTALL)
            content_text = re.sub(pattern, '', resp_text, flags=re.DOTALL)
            return f'<think>{thinking_text.group(1)}</think>\n{content_text}'

-    async def _preprocess_user_message(
-        self, query: core_entities.Query
-    ) -> tuple[str, list[str]]:
+    async def _preprocess_user_message(self, query: core_entities.Query) -> tuple[str, list[str]]:
        """预处理用户消息，提取纯文本，并将图片上传到 Dify 服务

        Returns:
@@ -90,9 +76,7 @@ class DifyServiceAPIRunner(runner.RequestRunner):
                if ce.type == 'text':
                    plain_text += ce.text
                elif ce.type == 'image_base64':
-                    image_b64, image_format = await image.extract_b64_and_format(
-                        ce.image_base64
-                    )
+                    image_b64, image_format = await image.extract_b64_and_format(ce.image_base64)
                    file_bytes = base64.b64decode(image_b64)
                    file = ('img.png', file_bytes, f'image/{image_format}')
                    file_upload_resp = await self.dify_client.upload_file(
@@ -106,9 +90,7 @@ class DifyServiceAPIRunner(runner.RequestRunner):

        return plain_text, image_ids

-    async def _chat_messages(
-        self, query: core_entities.Query
-    ) -> typing.AsyncGenerator[llm_entities.Message, None]:
+    async def _chat_messages(self, query: core_entities.Query) -> typing.AsyncGenerator[llm_entities.Message, None]:
        """调用聊天助手"""
        cov_id = query.session.using_conversation.uuid or ''

@@ -151,9 +133,7 @@ class DifyServiceAPIRunner(runner.RequestRunner):
                    if chunk['data']['node_type'] == 'answer':
                        yield llm_entities.Message(
                            role='assistant',
-                            content=self._try_convert_thinking(
-                                chunk['data']['outputs']['answer']
-                            ),
+                            content=self._try_convert_thinking(chunk['data']['outputs']['answer']),
                        )
            elif mode == 'basic':
                if chunk['event'] == 'message':
@@ -166,9 +146,7 @@ class DifyServiceAPIRunner(runner.RequestRunner):
                    basic_mode_pending_chunk = ''

        if chunk is None:
-            raise errors.DifyAPIError(
-                'Dify API 没有返回任何响应，请检查网络连接和API配置'
-            )
+            raise errors.DifyAPIError('Dify API 没有返回任何响应，请检查网络连接和API配置')

        query.session.using_conversation.uuid = chunk['conversation_id']

@@ -217,9 +195,7 @@ class DifyServiceAPIRunner(runner.RequestRunner):
                pending_agent_message += chunk['answer']
            else:
                if pending_agent_message.strip() != '':
-                    pending_agent_message = pending_agent_message.replace(
-                        '</details>Action:', '</details>'
-                    )
+                    pending_agent_message = pending_agent_message.replace('</details>Action:', '</details>')
                    yield llm_entities.Message(
                        role='assistant',
                        content=self._try_convert_thinking(pending_agent_message),
@@ -227,9 +203,7 @@ class DifyServiceAPIRunner(runner.RequestRunner):
                pending_agent_message = ''

                if chunk['event'] == 'agent_thought':
-                    if (
-                        chunk['tool'] != '' and chunk['observation'] != ''
-                    ):  # 工具调用结果，跳过
+                    if chunk['tool'] != '' and chunk['observation'] != '':  # 工具调用结果，跳过
                        continue

                    if chunk['tool']:
@@ -258,23 +232,17 @@ class DifyServiceAPIRunner(runner.RequestRunner):

                        yield llm_entities.Message(
                            role='assistant',
-                            content=[
-                                llm_entities.ContentElement.from_image_url(image_url)
-                            ],
+                            content=[llm_entities.ContentElement.from_image_url(image_url)],
                        )
                if chunk['event'] == 'error':
                    raise errors.DifyAPIError('dify 服务错误: ' + chunk['message'])

        if chunk is None:
-            raise errors.DifyAPIError(
-                'Dify API 没有返回任何响应，请检查网络连接和API配置'
-            )
+            raise errors.DifyAPIError('Dify API 没有返回任何响应，请检查网络连接和API配置')

        query.session.using_conversation.uuid = chunk['conversation_id']

-    async def _workflow_messages(
-        self, query: core_entities.Query
-    ) -> typing.AsyncGenerator[llm_entities.Message, None]:
+    async def _workflow_messages(self, query: core_entities.Query) -> typing.AsyncGenerator[llm_entities.Message, None]:
        """调用工作流"""

        if not query.session.using_conversation.uuid:
@@ -315,10 +283,7 @@ class DifyServiceAPIRunner(runner.RequestRunner):
                continue

            if chunk['event'] == 'node_started':
-                if (
-                    chunk['data']['node_type'] == 'start'
-                    or chunk['data']['node_type'] == 'end'
-                ):
+                if chunk['data']['node_type'] == 'start' or chunk['data']['node_type'] == 'end':
                    continue

                msg = llm_entities.Message(
@@ -349,9 +314,7 @@ class DifyServiceAPIRunner(runner.RequestRunner):

                yield msg

-    async def run(
-        self, query: core_entities.Query
-    ) -> typing.AsyncGenerator[llm_entities.Message, None]:
+    async def run(self, query: core_entities.Query) -> typing.AsyncGenerator[llm_entities.Message, None]:
        """运行请求"""
        if self.pipeline_config['ai']['dify-service-api']['app-type'] == 'chat':
            async for msg in self._chat_messages(query):
--- a/pkg/provider/runners/localagent.py
+++ b/pkg/provider/runners/localagent.py
@@ -12,15 +12,11 @@ from .. import entities as llm_entities
 class LocalAgentRunner(runner.RequestRunner):
    """本地Agent请求运行器"""

-    async def run(
-        self, query: core_entities.Query
-    ) -> typing.AsyncGenerator[llm_entities.Message, None]:
+    async def run(self, query: core_entities.Query) -> typing.AsyncGenerator[llm_entities.Message, None]:
        """运行请求"""
        pending_tool_calls = []

-        req_messages = (
-            query.prompt.messages.copy() + query.messages.copy() + [query.user_message]
-        )
+        req_messages = query.prompt.messages.copy() + query.messages.copy() + [query.user_message]

        # 首次请求
        msg = await query.use_llm_model.requester.invoke_llm(
@@ -45,9 +41,7 @@ class LocalAgentRunner(runner.RequestRunner):

                    parameters = json.loads(func.arguments)

-                    func_ret = await self.ap.tool_mgr.execute_func_call(
-                        query, func.name, parameters
-                    )
+                    func_ret = await self.ap.tool_mgr.execute_func_call(query, func.name, parameters)

                    msg = llm_entities.Message(
                        role='tool',
@@ -60,9 +54,7 @@ class LocalAgentRunner(runner.RequestRunner):
                    req_messages.append(msg)
                except Exception as e:
                    # 工具调用出错，添加一个报错信息到 req_messages
-                    err_msg = llm_entities.Message(
-                        role='tool', content=f'err: {e}', tool_call_id=tool_call.id
-                    )
+                    err_msg = llm_entities.Message(role='tool', content=f'err: {e}', tool_call_id=tool_call.id)

                    yield err_msg

--- a/pkg/provider/session/sessionmgr.py
+++ b/pkg/provider/session/sessionmgr.py
@@ -23,10 +23,7 @@ class SessionManager:
    async def get_session(self, query: core_entities.Query) -> core_entities.Session:
        """获取会话"""
        for session in self.session_list:
-            if (
-                query.launcher_type == session.launcher_type
-                and query.launcher_id == session.launcher_id
-            ):
+            if query.launcher_type == session.launcher_type and query.launcher_id == session.launcher_id:
                return session

        session_concurrency = self.ap.instance_config.data['concurrency']['session']
--- a/pkg/provider/tools/loader.py
+++ b/pkg/provider/tools/loader.py
@@ -45,9 +45,7 @@ class ToolLoader(abc.ABC):
        pass

    @abc.abstractmethod
-    async def invoke_tool(
-        self, query: core_entities.Query, name: str, parameters: dict
-    ) -> typing.Any:
+    async def invoke_tool(self, query: core_entities.Query, name: str, parameters: dict) -> typing.Any:
        """执行工具调用"""
        pass

--- a/pkg/provider/tools/loaders/mcp.py
+++ b/pkg/provider/tools/loaders/mcp.py
@@ -43,15 +43,11 @@ class RuntimeMCPSession:
            env=self.server_config['env'],
        )

-        stdio_transport = await self.exit_stack.enter_async_context(
-            stdio_client(server_params)
-        )
+        stdio_transport = await self.exit_stack.enter_async_context(stdio_client(server_params))

        stdio, write = stdio_transport

-        self.session = await self.exit_stack.enter_async_context(
-            ClientSession(stdio, write)
-        )
+        self.session = await self.exit_stack.enter_async_context(ClientSession(stdio, write))

        await self.session.initialize()

@@ -66,25 +62,19 @@ class RuntimeMCPSession:

        sseio, write = sse_transport

-        self.session = await self.exit_stack.enter_async_context(
-            ClientSession(sseio, write)
-        )
+        self.session = await self.exit_stack.enter_async_context(ClientSession(sseio, write))

        await self.session.initialize()

    async def initialize(self):
-        self.ap.logger.debug(
-            f'初始化 MCP 会话: {self.server_name} {self.server_config}'
-        )
+        self.ap.logger.debug(f'初始化 MCP 会话: {self.server_name} {self.server_config}')

        if self.server_config['mode'] == 'stdio':
            await self._init_stdio_python_server()
        elif self.server_config['mode'] == 'sse':
            await self._init_sse_server()
        else:
-            raise ValueError(
-                f'无法识别 MCP 服务器类型: {self.server_name}: {self.server_config}'
-            )
+            raise ValueError(f'无法识别 MCP 服务器类型: {self.server_name}: {self.server_config}')

        tools = await self.session.list_tools()

@@ -132,9 +122,7 @@ class MCPLoader(loader.ToolLoader):
        self._last_listed_functions = []

    async def initialize(self):
-        for server_config in self.ap.instance_config.data.get('mcp', {}).get(
-            'servers', []
-        ):
+        for server_config in self.ap.instance_config.data.get('mcp', {}).get('servers', []):
            if not server_config['enable']:
                continue
            session = RuntimeMCPSession(server_config['name'], server_config, self.ap)
@@ -155,9 +143,7 @@ class MCPLoader(loader.ToolLoader):
    async def has_tool(self, name: str) -> bool:
        return name in [f.name for f in self._last_listed_functions]

-    async def invoke_tool(
-        self, query: core_entities.Query, name: str, parameters: dict
-    ) -> typing.Any:
+    async def invoke_tool(self, query: core_entities.Query, name: str, parameters: dict) -> typing.Any:
        for server_name, session in self.sessions.items():
            for function in session.functions:
                if function.name == name:
--- a/pkg/provider/tools/loaders/plugin.py
+++ b/pkg/provider/tools/loaders/plugin.py
@@ -48,9 +48,7 @@ class PluginToolLoader(loader.ToolLoader):
                    return function, plugin.plugin_inst
        return None, None

-    async def invoke_tool(
-        self, query: core_entities.Query, name: str, parameters: dict
-    ) -> typing.Any:
+    async def invoke_tool(self, query: core_entities.Query, name: str, parameters: dict) -> typing.Any:
        try:
            function, plugin = await self._get_function_and_plugin(name)
            if function is None:
--- a/pkg/provider/tools/toolmgr.py
+++ b/pkg/provider/tools/toolmgr.py
@@ -28,9 +28,7 @@ class ToolManager:
            await loader_inst.initialize()
            self.loaders.append(loader_inst)

-    async def get_all_functions(
-        self, plugin_enabled: bool = None
-    ) -> list[entities.LLMFunction]:
+    async def get_all_functions(self, plugin_enabled: bool = None) -> list[entities.LLMFunction]:
        """获取所有函数"""
        all_functions: list[entities.LLMFunction] = []

@@ -39,9 +37,7 @@ class ToolManager:

        return all_functions

-    async def generate_tools_for_openai(
-        self, use_funcs: list[entities.LLMFunction]
-    ) -> list:
+    async def generate_tools_for_openai(self, use_funcs: list[entities.LLMFunction]) -> list:
        """生成函数列表"""
        tools = []

@@ -58,9 +54,7 @@ class ToolManager:

        return tools

-    async def generate_tools_for_anthropic(
-        self, use_funcs: list[entities.LLMFunction]
-    ) -> list:
+    async def generate_tools_for_anthropic(self, use_funcs: list[entities.LLMFunction]) -> list:
        """为anthropic生成函数列表

        e.g.
@@ -95,9 +89,7 @@ class ToolManager:

        return tools

-    async def execute_func_call(
-        self, query: core_entities.Query, name: str, parameters: dict
-    ) -> typing.Any:
+    async def execute_func_call(self, query: core_entities.Query, name: str, parameters: dict) -> typing.Any:
        """执行函数调用"""

        for loader in self.loaders: