Merge branch 'langbot-app:master' into master

.github/workflows/lint.yml

@@ -0,0 +1,60 @@
+name: Lint
+
+on:
+  push:
+    branches:
+      - main
+      - master
+      - dev
+  pull_request:
+    types: [opened, synchronize, reopened, ready_for_review]
+
+jobs:
+  ruff:
+    name: Ruff Lint & Format
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: '3.12'
+
+      - name: Install uv
+        uses: astral-sh/setup-uv@v4
+
+      - name: Install dependencies
+        run: uv sync --dev
+
+      - name: Run ruff check
+        run: uv run ruff check src
+
+      - name: Run ruff format
+        run: uv run ruff format src --check
+
+  frontend:
+    name: Frontend Lint
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Setup Node.js
+        uses: actions/setup-node@v4
+        with:
+          node-version: '25'
+
+      - name: Install pnpm
+        uses: pnpm/action-setup@v4
+        with:
+          version: 9
+
+      - name: Install dependencies
+        working-directory: web
+        run: pnpm install
+
+      - name: Run lint
+        working-directory: web
+        run: pnpm lint

pyproject.toml

@@ -23,7 +23,7 @@ dependencies = [
     "pynacl>=1.5.0", # Required for Discord voice support
     "gewechat-client>=0.1.5",
     "lark-oapi>=1.4.15",
-    "mcp>=1.20.0",
+    "mcp>=1.25.0",
     "nakuru-project-idk>=0.0.2.1",
     "ollama>=0.4.8",
     "openai>1.0.0",

src/langbot/libs/qq_official_api/api.py

@@ -85,7 +85,6 @@ class QQOfficialClient:
             req: Quart Request 对象
         """
         try:
-            
             body = await req.get_data()
 
             print(f'[QQ Official] Received request, body length: {len(body)}')
@@ -96,7 +95,6 @@ class QQOfficialClient:
 
             payload = json.loads(body)
 
-            
             if payload.get('op') == 13:
                 validation_data = payload.get('d')
                 if not validation_data:
@@ -276,21 +274,21 @@ class QQOfficialClient:
         seed = bot_secret
         while len(seed) < target_size:
             seed *= 2
-        return seed[:target_size].encode("utf-8")
+        return seed[:target_size].encode('utf-8')
 
     async def verify(self, validation_payload: dict):
         seed = await self.repeat_seed(self.secret)
         private_key = ed25519.Ed25519PrivateKey.from_private_bytes(seed)
 
-        event_ts = validation_payload.get("event_ts", "")
+        event_ts = validation_payload.get('event_ts', '')
-        plain_token = validation_payload.get("plain_token", "")
+        plain_token = validation_payload.get('plain_token', '')
         msg = event_ts + plain_token
 
         # sign
         signature = private_key.sign(msg.encode()).hex()
 
         response = {
-            "plain_token": plain_token,
+            'plain_token': plain_token,
-            "signature": signature,
+            'signature': signature,
         }
         return response

src/langbot/libs/wecom_ai_bot_api/wecombotevent.py

@@ -36,7 +36,12 @@ class WecomBotEvent(dict):
         """
         用户名称
         """
-        return self.get('username', '') or self.get('from', {}).get('alias', '') or self.get('from', {}).get('name', '') or self.userid
+        return (
+            self.get('username', '')
+            or self.get('from', {}).get('alias', '')
+            or self.get('from', {}).get('name', '')
+            or self.userid
+        )
 
     @property
     def chatname(self) -> str:

src/langbot/pkg/api/http/controller/groups/webhooks.py

@@ -30,7 +30,6 @@ class WebhookRouterGroup(group.RouterGroup):
             适配器返回的响应
         """
         try:
-            
             runtime_bot = await self.ap.platform_mgr.get_bot_by_uuid(bot_uuid)
 
             if not runtime_bot:
@@ -39,11 +38,9 @@ class WebhookRouterGroup(group.RouterGroup):
             if not runtime_bot.enable:
                 return quart.jsonify({'error': 'Bot is disabled'}), 403
 
-            
             if not hasattr(runtime_bot.adapter, 'handle_unified_webhook'):
                 return quart.jsonify({'error': 'Adapter does not support unified webhook'}), 501
 
-            
             response = await runtime_bot.adapter.handle_unified_webhook(
                 bot_uuid=bot_uuid,
                 path=path,

src/langbot/pkg/api/http/service/bot.py

@@ -59,7 +59,16 @@ class BotService:
             adapter_runtime_values['bot_account_id'] = runtime_bot.adapter.bot_account_id
 
         # Webhook URL for unified webhook adapters (independent of bot running state)
-        if persistence_bot['adapter'] in ['wecom', 'wecombot', 'officialaccount', 'qqofficial', 'slack', 'wecomcs', 'LINE', 'lark']:
+        if persistence_bot['adapter'] in [
+            'wecom',
+            'wecombot',
+            'officialaccount',
+            'qqofficial',
+            'slack',
+            'wecomcs',
+            'LINE',
+            'lark',
+        ]:
             webhook_prefix = self.ap.instance_config.data['api'].get('webhook_prefix', 'http://127.0.0.1:5300')
             webhook_url = f'/bots/{bot_uuid}'
             adapter_runtime_values['webhook_url'] = webhook_url

src/langbot/pkg/core/stages/build_app.py

@@ -34,7 +34,6 @@ from .. import taskmgr
 from ...telemetry import telemetry as telemetry_module
 
 
-
 @stage.stage_class('BuildAppStage')
 class BuildAppStage(stage.BootingStage):
     """Build LangBot application"""

src/langbot/pkg/platform/botmgr.py

@@ -75,10 +75,17 @@ class RuntimeBot:
 
             # Only add to query pool if no webhook requested to skip pipeline
             if not skip_pipeline:
+                launcher_id = event.sender.id
+
+                if hasattr(adapter, 'get_launcher_id'):
+                    custom_launcher_id = adapter.get_launcher_id(event)
+                    if custom_launcher_id:
+                        launcher_id = custom_launcher_id
+
                 await self.ap.query_pool.add_query(
                     bot_uuid=self.bot_entity.uuid,
                     launcher_type=provider_session.LauncherTypes.PERSON,
-                    launcher_id=event.sender.id,
+                    launcher_id=launcher_id,
                     sender_id=event.sender.id,
                     message_event=event,
                     message_chain=event.message_chain,
@@ -86,7 +93,7 @@ class RuntimeBot:
                     pipeline_uuid=self.bot_entity.use_pipeline_uuid,
                 )
             else:
-                await self.logger.info(f'Pipeline skipped for person message due to webhook response')
+                await self.logger.info('Pipeline skipped for person message due to webhook response')
 
         async def on_group_message(
             event: platform_events.GroupMessage,
@@ -111,10 +118,17 @@ class RuntimeBot:
 
             # Only add to query pool if no webhook requested to skip pipeline
             if not skip_pipeline:
+                launcher_id = event.group.id
+
+                if hasattr(adapter, 'get_launcher_id'):
+                    custom_launcher_id = adapter.get_launcher_id(event)
+                    if custom_launcher_id:
+                        launcher_id = custom_launcher_id
+
                 await self.ap.query_pool.add_query(
                     bot_uuid=self.bot_entity.uuid,
                     launcher_type=provider_session.LauncherTypes.GROUP,
-                    launcher_id=event.group.id,
+                    launcher_id=launcher_id,
                     sender_id=event.sender.id,
                     message_event=event,
                     message_chain=event.message_chain,
@@ -122,7 +136,7 @@ class RuntimeBot:
                     pipeline_uuid=self.bot_entity.use_pipeline_uuid,
                 )
             else:
-                await self.logger.info(f'Pipeline skipped for group message due to webhook response')
+                await self.logger.info('Pipeline skipped for group message due to webhook response')
 
         self.adapter.register_listener(platform_events.FriendMessage, on_friend_message)
         self.adapter.register_listener(platform_events.GroupMessage, on_group_message)

src/langbot/pkg/platform/sources/lark.py

@@ -244,7 +244,6 @@ class LarkMessageConverter(abstract_platform_adapter.AbstractMessageConverter):
 
         lb_msg_list.append(platform_message.Source(id=message.message_id, time=msg_create_time))
 
-
         if message.message_type == 'text':
             element_list = []
 
@@ -310,7 +309,11 @@ class LarkMessageConverter(abstract_platform_adapter.AbstractMessageConverter):
             ]
         elif message.message_type == 'audio':
             message_content['content'] = [
-                {'tag': 'audio', 'file_key': message_content['file_key'], "duration": message_content.get('duration',0)}
+                {
+                    'tag': 'audio',
+                    'file_key': message_content['file_key'],
+                    'duration': message_content.get('duration', 0),
+                }
             ]
 
         for ele in message_content['content']:
@@ -367,12 +370,9 @@ class LarkMessageConverter(abstract_platform_adapter.AbstractMessageConverter):
                     audio_bytes = response.file.read()
                     audio_base64 = base64.b64encode(audio_bytes).decode()
 
-
                     # Get content type from response headers
                     content_type = response.raw.headers.get('content-type', 'audio/mpeg')
 
-
-
                     mime_main = content_type.split(';')[0].strip()
                     ext = mimetypes.guess_extension(mime_main) or '.bin'
                     temp_dir = tempfile.gettempdir()
@@ -418,7 +418,6 @@ class LarkMessageConverter(abstract_platform_adapter.AbstractMessageConverter):
                 file_bytes = response.file.read()
                 file_base64 = base64.b64encode(file_bytes).decode()
 
-
                 file_format = response.raw.headers['content-type']
 
                 file_size = len(file_bytes)
@@ -453,7 +452,6 @@ class LarkMessageConverter(abstract_platform_adapter.AbstractMessageConverter):
                     )
                 )
 
-
         return platform_message.MessageChain(lb_msg_list)
 
 

src/langbot/pkg/platform/sources/telegram.py

@@ -197,6 +197,10 @@ class TelegramAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
                 }
                 if self.config['markdown_card'] is True:
                     args['parse_mode'] = 'MarkdownV2'
+
+        if message_source.source_platform_object.message.message_thread_id:
+            args['message_thread_id'] = message_source.source_platform_object.message.message_thread_id
+
         if quote_origin:
             args['reply_to_message_id'] = message_source.source_platform_object.message.id
 
@@ -231,8 +235,12 @@ class TelegramAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
                         'chat_id': message_source.source_platform_object.effective_chat.id,
                         'text': content,
                     }
+                    if message_source.source_platform_object.message.message_thread_id:
+                        args['message_thread_id'] = message_source.source_platform_object.message.message_thread_id
+
                     if quote_origin:
                         args['reply_to_message_id'] = message_source.source_platform_object.message.id
+
                     if self.config['markdown_card'] is True:
                         args['parse_mode'] = 'MarkdownV2'
 
@@ -260,6 +268,24 @@ class TelegramAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
                 # self.seq = 1  # 消息回复结束之后重置seq
                 self.msg_stream_id.pop(message_id)  # 消息回复结束之后删除流式消息id
 
+    def get_launcher_id(self, event: platform_events.MessageEvent) -> str | None:
+        if not isinstance(event.source_platform_object, Update):
+            return None
+
+        message = event.source_platform_object.message
+        if not message:
+            return None
+
+        # specifically handle telegram forum topic and private thread(not supported by official client yet but supported by bot api)
+        if message.message_thread_id:
+            # check if it is a group
+            if isinstance(event, platform_events.GroupMessage):
+                return f'{event.group.id}#{message.message_thread_id}'
+            elif isinstance(event, platform_events.FriendMessage):
+                return f'{event.sender.id}#{message.message_thread_id}'
+
+        return None
+
     async def is_stream_output_supported(self) -> bool:
         is_stream = False
         if self.config.get('enable-stream-reply', None):

src/langbot/pkg/platform/sources/wecom.py

@@ -75,13 +75,15 @@ class WecomMessageConverter(abstract_platform_adapter.AbstractMessageConverter):
         for msg in message_chain:
             if type(msg) is platform_message.Plain:
                 chunks = split_string_by_bytes(msg.text)
-                content_list.extend([
+                content_list.extend(
-                    {
+                    [
-                        'type': 'text',
+                        {
-                        'content': chunk,
+                            'type': 'text',
-                    }
+                            'content': chunk,
-                    for chunk in chunks
+                        }
-                ])
+                        for chunk in chunks
+                    ]
+                )
             elif type(msg) is platform_message.Image:
                 content_list.append(
                     {

src/langbot/pkg/platform/webhook_pusher.py

@@ -56,7 +56,7 @@ class WebhookPusher:
             # Check if any webhook responded with skip_pipeline=true
             for result in results:
                 if isinstance(result, dict) and result.get('skip_pipeline') is True:
-                    self.logger.info(f'Webhook responded with skip_pipeline=true, skipping pipeline for person message')
+                    self.logger.info('Webhook responded with skip_pipeline=true, skipping pipeline for person message')
                     return True
 
             return False
@@ -103,7 +103,7 @@ class WebhookPusher:
             # Check if any webhook responded with skip_pipeline=true
             for result in results:
                 if isinstance(result, dict) and result.get('skip_pipeline') is True:
-                    self.logger.info(f'Webhook responded with skip_pipeline=true, skipping pipeline for group message')
+                    self.logger.info('Webhook responded with skip_pipeline=true, skipping pipeline for group message')
                     return True
 
             return False

src/langbot/pkg/provider/modelmgr/requesters/seekdbembed.py

@@ -51,9 +51,10 @@ class SeekDBEmbedding(requester.ProviderAPIRequester):
                 await self.initialize()
 
             if self._embedding_function is None:
-                raise RuntimeError("SeekDB embedding function initialization failed")
+                raise RuntimeError('SeekDB embedding function initialization failed')
 
             return self._embedding_function(input_text)
         except Exception as e:
             from .. import errors
+
             raise errors.RequesterError(f'SeekDB embedding failed: {str(e)}')

src/langbot/pkg/provider/runners/localagent.py

@@ -212,13 +212,20 @@ class LocalAgentRunner(runner.RequestRunner):
                 try:
                     func = tool_call.function
 
-                    parameters = json.loads(func.arguments)
+                    if func.arguments:
+                        parameters = json.loads(func.arguments)
+                    else:
+                        parameters = {}
 
                     func_ret = await self.ap.tool_mgr.execute_func_call(func.name, parameters, query=query)
 
                     # Handle return value content
                     tool_content = None
-                    if isinstance(func_ret, list) and len(func_ret) > 0 and isinstance(func_ret[0], provider_message.ContentElement):
+                    if (
+                        isinstance(func_ret, list)
+                        and len(func_ret) > 0
+                        and isinstance(func_ret[0], provider_message.ContentElement)
+                    ):
                         tool_content = func_ret
                     else:
                         tool_content = json.dumps(func_ret, ensure_ascii=False)

src/langbot/pkg/provider/runners/n8nsvapi.py

@@ -68,15 +68,16 @@ class N8nServiceAPIRunner(runner.RequestRunner):
 
         return plain_text
 
-    async def _process_stream_response(self, response: aiohttp.ClientResponse) -> typing.AsyncGenerator[
+    async def _process_stream_response(
-        provider_message.Message, None]:
+        self, response: aiohttp.ClientResponse
+    ) -> typing.AsyncGenerator[provider_message.Message, None]:
         """处理流式响应——支持部分 JSON 和多个 JSON 对象在同一 chunk 的情况"""
-        full_content = ""
+        full_content = ''
         chunk_idx = 0
         is_final = False
         message_idx = 0
 
-        buffer = ""
+        buffer = ''
         decoder = json.JSONDecoder()
 
         async for raw_chunk in response.content.iter_chunked(1024):
@@ -129,7 +130,7 @@ class N8nServiceAPIRunner(runner.RequestRunner):
                     preview = chunk_str[:200]
                 except Exception:
                     preview = '<unavailable>'
-                self.ap.logger.warning(f"Failed to process chunk: {e}; chunk preview: {preview}")
+                self.ap.logger.warning(f'Failed to process chunk: {e}; chunk preview: {preview}')
 
         # 流结束后，尝试解析残余 buffer
         if buffer:
@@ -151,7 +152,7 @@ class N8nServiceAPIRunner(runner.RequestRunner):
                     )
             except Exception as e:
                 preview = buffer[:200]
-                self.ap.logger.warning(f"Failed to parse remaining buffer: {e}; buffer preview: {preview}")
+                self.ap.logger.warning(f'Failed to parse remaining buffer: {e}; buffer preview: {preview}')
 
     async def _call_webhook(self, query: pipeline_query.Query) -> typing.AsyncGenerator[provider_message.Message, None]:
         """调用n8n webhook"""
@@ -165,7 +166,7 @@ class N8nServiceAPIRunner(runner.RequestRunner):
         # 准备请求数据
         payload = {
             # 基本消息内容
-            'chatInput' :plain_text,  # 考虑到之前用户直接用的message model这里添加新键
+            'chatInput': plain_text,  # 考虑到之前用户直接用的message model这里添加新键
             'message': plain_text,
             'user_message_text': plain_text,
             'conversation_id': query.session.using_conversation.uuid,
@@ -217,57 +218,49 @@ class N8nServiceAPIRunner(runner.RequestRunner):
 
             # 调用webhook
             async with aiohttp.ClientSession() as session:
-                    if is_stream:
+                if is_stream:
-                        # 流式请求
+                    # 流式请求
-                        async with session.post(
+                    async with session.post(
-                                self.webhook_url,
+                        self.webhook_url, json=payload, headers=headers, auth=auth, timeout=self.timeout
-                                json=payload,
+                    ) as response:
-                                headers=headers,
+                        if response.status != 200:
-                                auth=auth,
+                            error_text = await response.text()
-                                timeout=self.timeout
+                            self.ap.logger.error(f'n8n webhook call failed: {response.status}, {error_text}')
-                        ) as response:
+                            raise Exception(f'n8n webhook call failed: {response.status}, {error_text}')
+
+                        # 处理流式响应
+                        async for chunk in self._process_stream_response(response):
+                            yield chunk
+                else:
+                    async with session.post(
+                        self.webhook_url, json=payload, headers=headers, auth=auth, timeout=self.timeout
+                    ) as response:
+                        try:
+                            async for chunk in self._process_stream_response(response):
+                                output_content = chunk.content if chunk.is_final else ''
+                        except:
+                            # 非流式请求（保持原有逻辑）
                             if response.status != 200:
                                 error_text = await response.text()
                                 self.ap.logger.error(f'n8n webhook call failed: {response.status}, {error_text}')
                                 raise Exception(f'n8n webhook call failed: {response.status}, {error_text}')
 
-                            # 处理流式响应
+                            # 解析响应
-                            async for chunk in self._process_stream_response(response):
+                            response_data = await response.json()
-                                yield chunk
+                            self.ap.logger.debug(f'n8n webhook response: {response_data}')
-                    else:
-                        async with session.post(
-                                self.webhook_url,
-                                json=payload,
-                                headers=headers,
-                                auth=auth,
-                                timeout=self.timeout
-                        ) as response:
-                            try:
-                                async for chunk in self._process_stream_response(response):
-                                    output_content = chunk.content if chunk.is_final else ''
-                            except:
-                                # 非流式请求（保持原有逻辑）
-                                if response.status != 200:
-                                    error_text = await response.text()
-                                    self.ap.logger.error(f'n8n webhook call failed: {response.status}, {error_text}')
-                                    raise Exception(f'n8n webhook call failed: {response.status}, {error_text}')
 
-                                # 解析响应
+                            # 从响应中提取输出
-                                response_data = await response.json()
+                            if self.output_key in response_data:
-                                self.ap.logger.debug(f'n8n webhook response: {response_data}')
+                                output_content = response_data[self.output_key]
+                            else:
+                                # 如果没有指定的输出键，则使用整个响应
+                                output_content = json.dumps(response_data, ensure_ascii=False)
 
-                                # 从响应中提取输出
+                        # 返回消息
-                                if self.output_key in response_data:
+                        yield provider_message.Message(
-                                    output_content = response_data[self.output_key]
+                            role='assistant',
-                                else:
+                            content=output_content,
-                                    # 如果没有指定的输出键，则使用整个响应
+                        )
-                                    output_content = json.dumps(response_data, ensure_ascii=False)
-
-                            # 返回消息
-                            yield provider_message.Message(
-                                role='assistant',
-                                content=output_content,
-                            )
         except Exception as e:
             self.ap.logger.error(f'n8n webhook call exception: {str(e)}')
             raise N8nAPIError(f'n8n webhook call exception: {str(e)}')

src/langbot/pkg/provider/tools/loaders/mcp.py

@@ -194,7 +194,7 @@ class RuntimeMCPSession:
 
             async def func(*, _tool=tool, **kwargs):
                 if not self.session:
-                    raise Exception("MCP session is not connected")
+                    raise Exception('MCP session is not connected')
 
                 result = await self.session.call_tool(_tool.name, kwargs)
                 if result.isError:
@@ -202,7 +202,7 @@ class RuntimeMCPSession:
                     for content in result.content:
                         if content.type == 'text':
                             error_texts.append(content.text)
-                    raise Exception("\n".join(error_texts) if error_texts else "Unknown error from MCP tool")
+                    raise Exception('\n'.join(error_texts) if error_texts else 'Unknown error from MCP tool')
 
                 result_contents: list[provider_message.ContentElement] = []
                 for content in result.content:
@@ -221,8 +221,8 @@ class RuntimeMCPSession:
             self.functions.append(
                 resource_tool.LLMTool(
                     name=tool.name,
-                    human_desc=tool.description or "",
+                    human_desc=tool.description or '',
-                    description=tool.description or "",
+                    description=tool.description or '',
                     parameters=tool.inputSchema,
                     func=func,
                 )
@@ -338,13 +338,10 @@ class MCPLoader(loader.ToolLoader):
         """
         uuid_ = server_config.get('uuid')
         if not uuid_:
-            self.ap.logger.warning(
+            self.ap.logger.warning('Server UUID is None for MCP server, maybe testing in the config page.')
-                'Server UUID is None for MCP server, maybe testing in the config page.'
-            )
             uuid_ = str(uuid_module.uuid4())
             server_config['uuid'] = uuid_
 
-
         name = server_config['name']
         uuid = server_config['uuid']
         mode = server_config['mode']

src/langbot/pkg/rag/knowledge/services/embedder.py

@@ -37,7 +37,7 @@ class Embedder(BaseService):
         embeddings_list: list[list[float]] = []
 
         for i in range(0, len(chunks), MAX_BATCH_SIZE):
-            batch = chunks[i:i + MAX_BATCH_SIZE]
+            batch = chunks[i : i + MAX_BATCH_SIZE]
             batch_embeddings = await embedding_model.provider.requester.invoke_embedding(
                 model=embedding_model,
                 input_text=batch,

src/langbot/pkg/vector/mgr.py

@@ -55,12 +55,7 @@ class VectorDBManager:
                     user = pgvector_config.get('user', 'postgres')
                     password = pgvector_config.get('password', 'postgres')
                     self.vector_db = PgVectorDatabase(
-                        self.ap,
+                        self.ap, host=host, port=port, database=database, user=user, password=password
-                        host=host,
-                        port=port,
-                        database=database,
-                        user=user,
-                        password=password
                     )
                 self.ap.logger.info('Initialized pgvector database backend.')
 

src/langbot/pkg/vector/vdbs/milvus.py

@@ -10,7 +10,7 @@ from langbot.pkg.core import app
 class MilvusVectorDatabase(VectorDatabase):
     """Milvus vector database implementation"""
 
-    def __init__(self, ap: app.Application, uri: str = "milvus.db", token: str = None, db_name: str = None):
+    def __init__(self, ap: app.Application, uri: str = 'milvus.db', token: str = None, db_name: str = None):
         """Initialize Milvus vector database
 
         Args:
@@ -34,9 +34,9 @@ class MilvusVectorDatabase(VectorDatabase):
                 self.client = MilvusClient(uri=self.uri, token=self.token, db_name=self.db_name)
             else:
                 self.client = MilvusClient(uri=self.uri, db_name=self.db_name)
-            self.ap.logger.info(f"Connected to Milvus at {self.uri}")
+            self.ap.logger.info(f'Connected to Milvus at {self.uri}')
         except Exception as e:
-            self.ap.logger.error(f"Failed to connect to Milvus: {e}")
+            self.ap.logger.error(f'Failed to connect to Milvus: {e}')
             raise
 
     @staticmethod
@@ -70,15 +70,11 @@ class MilvusVectorDatabase(VectorDatabase):
         """
         index_params = IndexParams()
         index_params.add_index(
-            field_name="vector",
+            field_name='vector',
-            index_type="AUTOINDEX",
+            index_type='AUTOINDEX',
-            metric_type="COSINE",
+            metric_type='COSINE',
-        )
-        await asyncio.to_thread(
-            self.client.create_index,
-            collection_name=collection,
-            index_params=index_params
         )
+        await asyncio.to_thread(self.client.create_index, collection_name=collection, index_params=index_params)
 
     async def _get_or_create_collection_internal(self, collection: str, vector_size: int = None):
         """Internal method to get or create a Milvus collection with proper configuration.
@@ -94,9 +90,7 @@ class MilvusVectorDatabase(VectorDatabase):
             return collection
 
         # Check if collection exists
-        has_collection = await asyncio.to_thread(
+        has_collection = await asyncio.to_thread(self.client.has_collection, collection_name=collection)
-            self.client.has_collection, collection_name=collection
-        )
 
         if not has_collection:
             # Default dimension if not specified (for backward compatibility)
@@ -104,24 +98,26 @@ class MilvusVectorDatabase(VectorDatabase):
                 vector_size = 1536
 
             fields = [
-                FieldSchema(name="id", dtype=DataType.VARCHAR, is_primary=True, max_length=255),
+                FieldSchema(name='id', dtype=DataType.VARCHAR, is_primary=True, max_length=255),
-                FieldSchema(name="vector", dtype=DataType.FLOAT_VECTOR, dim=vector_size),
+                FieldSchema(name='vector', dtype=DataType.FLOAT_VECTOR, dim=vector_size),
-                FieldSchema(name="text", dtype=DataType.VARCHAR, max_length=65535),
+                FieldSchema(name='text', dtype=DataType.VARCHAR, max_length=65535),
-                FieldSchema(name="file_id", dtype=DataType.VARCHAR, max_length=255),
+                FieldSchema(name='file_id', dtype=DataType.VARCHAR, max_length=255),
-                FieldSchema(name="chunk_uuid", dtype=DataType.VARCHAR, max_length=255),
+                FieldSchema(name='chunk_uuid', dtype=DataType.VARCHAR, max_length=255),
             ]
 
-            schema = CollectionSchema(fields=fields, description="LangBot knowledge base vectors")
+            schema = CollectionSchema(fields=fields, description='LangBot knowledge base vectors')
 
             await asyncio.to_thread(
                 self.client.create_collection,
                 collection_name=collection,
                 schema=schema,
-                metric_type="COSINE",
+                metric_type='COSINE',
             )
 
             await self._ensure_vector_index(collection)
-            self.ap.logger.info(f"Created Milvus collection '{collection}' with dimension={vector_size}, index=AUTOINDEX")
+            self.ap.logger.info(
+                f"Created Milvus collection '{collection}' with dimension={vector_size}, index=AUTOINDEX"
+            )
         else:
             # Ensure index exists for existing collection
             await self._ensure_index_if_missing(collection)
@@ -137,11 +133,8 @@ class MilvusVectorDatabase(VectorDatabase):
             collection: Normalized collection name
         """
         try:
-            indexes = await asyncio.to_thread(
+            indexes = await asyncio.to_thread(self.client.list_indexes, collection_name=collection)
-                self.client.list_indexes,
+            if 'vector' not in indexes:
-                collection_name=collection
-            )
-            if "vector" not in indexes:
                 await self._ensure_vector_index(collection)
                 self.ap.logger.info(f"Created index for existing Milvus collection '{collection}'")
         except Exception as e:
@@ -184,39 +177,30 @@ class MilvusVectorDatabase(VectorDatabase):
         data = []
         for i, vector_id in enumerate(ids):
             entry = {
-                "id": vector_id,
+                'id': vector_id,
-                "vector": embeddings_list[i],
+                'vector': embeddings_list[i],
             }
             # Add metadata fields
             if metadatas and i < len(metadatas):
                 metadata = metadatas[i]
                 # Add common metadata fields
-                if "text" in metadata:
+                if 'text' in metadata:
-                    entry["text"] = metadata["text"]
+                    entry['text'] = metadata['text']
-                if "file_id" in metadata:
+                if 'file_id' in metadata:
-                    entry["file_id"] = metadata["file_id"]
+                    entry['file_id'] = metadata['file_id']
-                if "uuid" in metadata:
+                if 'uuid' in metadata:
-                    entry["chunk_uuid"] = metadata["uuid"]
+                    entry['chunk_uuid'] = metadata['uuid']
             data.append(entry)
 
         # Insert data into Milvus
-        await asyncio.to_thread(
+        await asyncio.to_thread(self.client.insert, collection_name=collection, data=data)
-            self.client.insert,
-            collection_name=collection,
-            data=data
-        )
 
         # Load collection for searching (Milvus requires this)
-        await asyncio.to_thread(
+        await asyncio.to_thread(self.client.load_collection, collection_name=collection)
-            self.client.load_collection,
-            collection_name=collection
-        )
 
         self.ap.logger.info(f"Added {len(ids)} embeddings to Milvus collection '{collection}'")
 
-    async def search(
+    async def search(self, collection: str, query_embedding: list[float], k: int = 5) -> Dict[str, Any]:
-        self, collection: str, query_embedding: list[float], k: int = 5
-    ) -> Dict[str, Any]:
         """Search for similar vectors in Milvus collection
 
         Args:
@@ -231,10 +215,7 @@ class MilvusVectorDatabase(VectorDatabase):
         await self.get_or_create_collection(collection)
 
         # Perform search
-        search_params = {
+        search_params = {'metric_type': 'COSINE', 'params': {}}
-            "metric_type": "COSINE",
-            "params": {}
-        }
 
         results = await asyncio.to_thread(
             self.client.search,
@@ -242,7 +223,7 @@ class MilvusVectorDatabase(VectorDatabase):
             data=[query_embedding],
             limit=k,
             search_params=search_params,
-            output_fields=["text", "file_id", "chunk_uuid"]
+            output_fields=['text', 'file_id', 'chunk_uuid'],
         )
 
         # Convert results to Chroma-compatible format
@@ -253,30 +234,24 @@ class MilvusVectorDatabase(VectorDatabase):
 
         if results and len(results) > 0:
             for hit in results[0]:
-                ids.append(hit.get("id", ""))
+                ids.append(hit.get('id', ''))
-                distances.append(hit.get("distance", 0.0))
+                distances.append(hit.get('distance', 0.0))
 
                 # Build metadata from entity fields
-                entity = hit.get("entity", {})
+                entity = hit.get('entity', {})
                 metadata = {}
-                if "text" in entity:
+                if 'text' in entity:
-                    metadata["text"] = entity["text"]
+                    metadata['text'] = entity['text']
-                if "file_id" in entity:
+                if 'file_id' in entity:
-                    metadata["file_id"] = entity["file_id"]
+                    metadata['file_id'] = entity['file_id']
-                if "chunk_uuid" in entity:
+                if 'chunk_uuid' in entity:
-                    metadata["uuid"] = entity["chunk_uuid"]
+                    metadata['uuid'] = entity['chunk_uuid']
                 metadatas.append(metadata)
 
         # Return in Chroma-compatible format (nested lists)
-        result = {
+        result = {'ids': [ids], 'distances': [distances], 'metadatas': [metadatas]}
-            "ids": [ids],
-            "distances": [distances],
-            "metadatas": [metadatas]
-        }
 
-        self.ap.logger.info(
+        self.ap.logger.info(f"Milvus search in '{collection}' returned {len(ids)} results")
-            f"Milvus search in '{collection}' returned {len(ids)} results"
-        )
         return result
 
     async def delete_by_file_id(self, collection: str, file_id: str) -> None:
@@ -290,14 +265,8 @@ class MilvusVectorDatabase(VectorDatabase):
         await self.get_or_create_collection(collection)
 
         # Delete entities matching the file_id
-        await asyncio.to_thread(
+        await asyncio.to_thread(self.client.delete, collection_name=collection, filter=f'file_id == "{file_id}"')
-            self.client.delete,
+        self.ap.logger.info(f"Deleted embeddings from Milvus collection '{collection}' with file_id: {file_id}")
-            collection_name=collection,
-            filter=f'file_id == "{file_id}"'
-        )
-        self.ap.logger.info(
-            f"Deleted embeddings from Milvus collection '{collection}' with file_id: {file_id}"
-        )
 
     async def delete_collection(self, collection: str):
         """Delete a Milvus collection
@@ -310,14 +279,10 @@ class MilvusVectorDatabase(VectorDatabase):
         self._collections.discard(collection)
 
         # Check if collection exists before attempting deletion
-        has_collection = await asyncio.to_thread(
+        has_collection = await asyncio.to_thread(self.client.has_collection, collection_name=collection)
-            self.client.has_collection, collection_name=collection
-        )
 
         if has_collection:
-            await asyncio.to_thread(
+            await asyncio.to_thread(self.client.drop_collection, collection_name=collection)
-                self.client.drop_collection, collection_name=collection
-            )
             self.ap.logger.info(f"Deleted Milvus collection '{collection}'")
         else:
             self.ap.logger.warning(f"Milvus collection '{collection}' not found")

src/langbot/pkg/vector/vdbs/pgvector_db.py

@@ -1,19 +1,18 @@
 from __future__ import annotations
-import asyncio
 from typing import Any, Dict
 from sqlalchemy import create_engine, text, Column, String, Text
-from sqlalchemy.orm import declarative_base, sessionmaker, Session
+from sqlalchemy.orm import declarative_base
 from sqlalchemy.ext.asyncio import create_async_engine, AsyncSession, async_sessionmaker
 from pgvector.sqlalchemy import Vector
 from langbot.pkg.vector.vdb import VectorDatabase
 from langbot.pkg.core import app
-import uuid
 
 Base = declarative_base()
 
 
 class PgVectorEntry(Base):
     """SQLAlchemy model for pgvector entries"""
+
     __tablename__ = 'langbot_vectors'
 
     id = Column(String, primary_key=True)
@@ -31,11 +30,11 @@ class PgVectorDatabase(VectorDatabase):
         self,
         ap: app.Application,
         connection_string: str = None,
-        host: str = "localhost",
+        host: str = 'localhost',
         port: int = 5432,
-        database: str = "langbot",
+        database: str = 'langbot',
-        user: str = "postgres",
+        user: str = 'postgres',
-        password: str = "postgres"
+        password: str = 'postgres',
     ):
         """Initialize pgvector database
 
@@ -54,14 +53,10 @@ class PgVectorDatabase(VectorDatabase):
         if connection_string:
             self.connection_string = connection_string
         else:
-            self.connection_string = (
+            self.connection_string = f'postgresql+psycopg://{user}:{password}@{host}:{port}/{database}'
-                f"postgresql+psycopg://{user}:{password}@{host}:{port}/{database}"
-            )
 
-        self.async_connection_string = self.connection_string.replace(
+        self.async_connection_string = self.connection_string.replace('postgresql://', 'postgresql+asyncpg://').replace(
-            "postgresql://", "postgresql+asyncpg://"
+            'postgresql+psycopg://', 'postgresql+asyncpg://'
-        ).replace(
-            "postgresql+psycopg://", "postgresql+asyncpg://"
         )
 
         self.engine = None
@@ -75,35 +70,25 @@ class PgVectorDatabase(VectorDatabase):
         """Initialize database connection and create tables"""
         try:
             # Create async engine for async operations
-            self.async_engine = create_async_engine(
+            self.async_engine = create_async_engine(self.async_connection_string, echo=False, pool_pre_ping=True)
-                self.async_connection_string,
+            self.AsyncSessionLocal = async_sessionmaker(self.async_engine, class_=AsyncSession, expire_on_commit=False)
-                echo=False,
-                pool_pre_ping=True
-            )
-            self.AsyncSessionLocal = async_sessionmaker(
-                self.async_engine,
-                class_=AsyncSession,
-                expire_on_commit=False
-            )
 
             # Create sync engine for table creation
-            sync_connection_string = self.connection_string.replace(
+            sync_connection_string = self.connection_string.replace('postgresql+asyncpg://', 'postgresql+psycopg://')
-                "postgresql+asyncpg://", "postgresql+psycopg://"
-            )
             self.engine = create_engine(sync_connection_string, echo=False)
 
             # Create pgvector extension and tables
             with self.engine.connect() as conn:
                 # Enable pgvector extension
-                conn.execute(text("CREATE EXTENSION IF NOT EXISTS vector"))
+                conn.execute(text('CREATE EXTENSION IF NOT EXISTS vector'))
                 conn.commit()
 
             # Create tables
             Base.metadata.create_all(self.engine)
 
-            self.ap.logger.info(f"Connected to PostgreSQL with pgvector")
+            self.ap.logger.info('Connected to PostgreSQL with pgvector')
         except Exception as e:
-            self.ap.logger.error(f"Failed to connect to PostgreSQL: {e}")
+            self.ap.logger.error(f'Failed to connect to PostgreSQL: {e}')
             raise
 
     async def get_or_create_collection(self, collection: str):
@@ -144,24 +129,20 @@ class PgVectorDatabase(VectorDatabase):
                         id=vector_id,
                         collection=collection,
                         embedding=embeddings_list[i],
-                        text=metadata.get("text", ""),
+                        text=metadata.get('text', ''),
-                        file_id=metadata.get("file_id", ""),
+                        file_id=metadata.get('file_id', ''),
-                        chunk_uuid=metadata.get("uuid", "")
+                        chunk_uuid=metadata.get('uuid', ''),
                     )
                     session.add(entry)
 
                 await session.commit()
-                self.ap.logger.info(
+                self.ap.logger.info(f"Added {len(ids)} embeddings to pgvector collection '{collection}'")
-                    f"Added {len(ids)} embeddings to pgvector collection '{collection}'"
-                )
             except Exception as e:
                 await session.rollback()
-                self.ap.logger.error(f"Error adding embeddings to pgvector: {e}")
+                self.ap.logger.error(f'Error adding embeddings to pgvector: {e}')
                 raise
 
-    async def search(
+    async def search(self, collection: str, query_embedding: list[float], k: int = 5) -> Dict[str, Any]:
-        self, collection: str, query_embedding: list[float], k: int = 5
-    ) -> Dict[str, Any]:
         """Search for similar vectors using cosine distance
 
         Args:
@@ -177,7 +158,7 @@ class PgVectorDatabase(VectorDatabase):
         async with self.AsyncSessionLocal() as session:
             try:
                 # Use cosine distance for similarity search
-                from sqlalchemy import select, func
+                from sqlalchemy import select
 
                 # Query for similar vectors
                 stmt = (
@@ -186,7 +167,7 @@ class PgVectorDatabase(VectorDatabase):
                         PgVectorEntry.text,
                         PgVectorEntry.file_id,
                         PgVectorEntry.chunk_uuid,
-                        PgVectorEntry.embedding.cosine_distance(query_embedding).label('distance')
+                        PgVectorEntry.embedding.cosine_distance(query_embedding).label('distance'),
                     )
                     .filter(PgVectorEntry.collection == collection)
                     .order_by(PgVectorEntry.embedding.cosine_distance(query_embedding))
@@ -204,25 +185,17 @@ class PgVectorDatabase(VectorDatabase):
                 for row in rows:
                     ids.append(row.id)
                     distances.append(float(row.distance))
-                    metadatas.append({
+                    metadatas.append(
-                        "text": row.text or "",
+                        {'text': row.text or '', 'file_id': row.file_id or '', 'uuid': row.chunk_uuid or ''}
-                        "file_id": row.file_id or "",
+                    )
-                        "uuid": row.chunk_uuid or ""
-                    })
 
-                result_dict = {
+                result_dict = {'ids': [ids], 'distances': [distances], 'metadatas': [metadatas]}
-                    "ids": [ids],
-                    "distances": [distances],
-                    "metadatas": [metadatas]
-                }
 
-                self.ap.logger.info(
+                self.ap.logger.info(f"pgvector search in '{collection}' returned {len(ids)} results")
-                    f"pgvector search in '{collection}' returned {len(ids)} results"
-                )
                 return result_dict
 
             except Exception as e:
-                self.ap.logger.error(f"Error searching pgvector: {e}")
+                self.ap.logger.error(f'Error searching pgvector: {e}')
                 raise
 
     async def delete_by_file_id(self, collection: str, file_id: str) -> None:
@@ -239,8 +212,7 @@ class PgVectorDatabase(VectorDatabase):
                 from sqlalchemy import delete
 
                 stmt = delete(PgVectorEntry).where(
-                    PgVectorEntry.collection == collection,
+                    PgVectorEntry.collection == collection, PgVectorEntry.file_id == file_id
-                    PgVectorEntry.file_id == file_id
                 )
                 await session.execute(stmt)
                 await session.commit()
@@ -250,7 +222,7 @@ class PgVectorDatabase(VectorDatabase):
                 )
             except Exception as e:
                 await session.rollback()
-                self.ap.logger.error(f"Error deleting from pgvector: {e}")
+                self.ap.logger.error(f'Error deleting from pgvector: {e}')
                 raise
 
     async def delete_collection(self, collection: str):
@@ -266,16 +238,14 @@ class PgVectorDatabase(VectorDatabase):
             try:
                 from sqlalchemy import delete
 
-                stmt = delete(PgVectorEntry).where(
+                stmt = delete(PgVectorEntry).where(PgVectorEntry.collection == collection)
-                    PgVectorEntry.collection == collection
-                )
                 await session.execute(stmt)
                 await session.commit()
 
                 self.ap.logger.info(f"Deleted pgvector collection '{collection}'")
             except Exception as e:
                 await session.rollback()
-                self.ap.logger.error(f"Error deleting pgvector collection: {e}")
+                self.ap.logger.error(f'Error deleting pgvector collection: {e}')
                 raise
 
     async def close(self):

src/langbot/pkg/vector/vdbs/seekdb.py

@@ -3,10 +3,8 @@ from __future__ import annotations
 import asyncio
 from typing import Any, Dict, List
 
-import sqlalchemy
 
 from langbot.pkg.core import app
-from langbot.pkg.entity.persistence import model as persistence_model
 from langbot.pkg.vector.vdb import VectorDatabase
 
 try:
@@ -87,14 +85,16 @@ class SeekDBVectorDatabase(VectorDatabase):
         self._collections: Dict[str, Any] = {}
         self._collection_configs: Dict[str, HNSWConfiguration] = {}
 
-        self._escape_table = str.maketrans({
+        self._escape_table = str.maketrans(
-            '\x00': '',
+            {
-            '\\': '\\\\',
+                '\x00': '',
-            '"': '\\"',
+                '\\': '\\\\',
-            '\n': '\\n',
+                '"': '\\"',
-            '\r': '\\r',
+                '\n': '\\n',
-            '\t': '\\t',
+                '\r': '\\r',
-        })
+                '\t': '\\t',
+            }
+        )
 
     async def _get_or_create_collection_internal(self, collection: str, vector_size: int = None) -> Any:
         """Internal method to get or create a collection with proper configuration."""
@@ -133,8 +133,10 @@ class SeekDBVectorDatabase(VectorDatabase):
     def _clean_metadata(self, meta: Dict[str, Any]) -> Dict[str, Any]:
         """SeekDB metadata doesn't support \\ and ", insert will error 3104"""
         return {
-            k: v.translate(self._escape_table) if isinstance(v, str)
+            k: v.translate(self._escape_table)
-            else v if v is None or isinstance(v, (int, float, bool))
+            if isinstance(v, str)
+            else v
+            if v is None or isinstance(v, (int, float, bool))
             else str(v)
             for k, v in meta.items()
             if v is not None
@@ -145,11 +147,7 @@ class SeekDBVectorDatabase(VectorDatabase):
         return await self._get_or_create_collection_internal(collection)
 
     async def add_embeddings(
-        self,
+        self, collection: str, ids: List[str], embeddings_list: List[List[float]], metadatas: List[Dict[str, Any]]
-        collection: str,
-        ids: List[str],
-        embeddings_list: List[List[float]],
-        metadatas: List[Dict[str, Any]]
     ) -> None:
         """Add vector embeddings to the specified collection.
 

tests/unit_tests/config/test_env_override.py

@@ -23,6 +23,7 @@ def _apply_env_overrides_to_config(cfg: dict) -> dict:
     Returns:
         Updated configuration dictionary
     """
+
     def convert_value(value: str, original_value: Any) -> Any:
         """Convert string value to appropriate type based on original value
 
@@ -90,11 +91,7 @@ class TestEnvOverrides:
 
     def test_simple_string_override(self):
         """Test overriding a simple string value"""
-        cfg = {
+        cfg = {'api': {'port': 5300}}
-            'api': {
-                'port': 5300
-            }
-        }
 
         # Set environment variable
         os.environ['API__PORT'] = '8080'
@@ -108,12 +105,7 @@ class TestEnvOverrides:
 
     def test_nested_key_override(self):
         """Test overriding nested keys with __ delimiter"""
-        cfg = {
+        cfg = {'concurrency': {'pipeline': 20, 'session': 1}}
-            'concurrency': {
-                'pipeline': 20,
-                'session': 1
-            }
-        }
 
         os.environ['CONCURRENCY__PIPELINE'] = '50'
 
@@ -126,14 +118,7 @@ class TestEnvOverrides:
 
     def test_deep_nested_override(self):
         """Test overriding deeply nested keys"""
-        cfg = {
+        cfg = {'system': {'jwt': {'expire': 604800, 'secret': ''}}}
-            'system': {
-                'jwt': {
-                    'expire': 604800,
-                    'secret': ''
-                }
-            }
-        }
 
         os.environ['SYSTEM__JWT__EXPIRE'] = '86400'
         os.environ['SYSTEM__JWT__SECRET'] = 'my_secret_key'
@@ -148,12 +133,7 @@ class TestEnvOverrides:
 
     def test_underscore_in_key(self):
         """Test keys with underscores like runtime_ws_url"""
-        cfg = {
+        cfg = {'plugin': {'enable': True, 'runtime_ws_url': 'ws://localhost:5400/control/ws'}}
-            'plugin': {
-                'enable': True,
-                'runtime_ws_url': 'ws://localhost:5400/control/ws'
-            }
-        }
 
         os.environ['PLUGIN__RUNTIME_WS_URL'] = 'ws://newhost:6000/ws'
 
@@ -165,12 +145,7 @@ class TestEnvOverrides:
 
     def test_boolean_conversion(self):
         """Test boolean value conversion"""
-        cfg = {
+        cfg = {'plugin': {'enable': True, 'enable_marketplace': False}}
-            'plugin': {
-                'enable': True,
-                'enable_marketplace': False
-            }
-        }
 
         os.environ['PLUGIN__ENABLE'] = 'false'
         os.environ['PLUGIN__ENABLE_MARKETPLACE'] = 'true'
@@ -185,14 +160,7 @@ class TestEnvOverrides:
 
     def test_ignore_dict_type(self):
         """Test that dict types are ignored"""
-        cfg = {
+        cfg = {'database': {'use': 'sqlite', 'sqlite': {'path': 'data/langbot.db'}}}
-            'database': {
-                'use': 'sqlite',
-                'sqlite': {
-                    'path': 'data/langbot.db'
-                }
-            }
-        }
 
         # Try to override a dict value - should be ignored
         os.environ['DATABASE__SQLITE'] = 'new_value'
@@ -207,13 +175,7 @@ class TestEnvOverrides:
 
     def test_ignore_list_type(self):
         """Test that list/array types are ignored"""
-        cfg = {
+        cfg = {'admins': ['admin1', 'admin2'], 'command': {'enable': True, 'prefix': ['!', '！']}}
-            'admins': ['admin1', 'admin2'],
-            'command': {
-                'enable': True,
-                'prefix': ['!', '！']
-            }
-        }
 
         # Try to override list values - should be ignored
         os.environ['ADMINS'] = 'admin3'
@@ -232,11 +194,7 @@ class TestEnvOverrides:
 
     def test_lowercase_env_var_ignored(self):
         """Test that lowercase environment variables are ignored"""
-        cfg = {
+        cfg = {'api': {'port': 5300}}
-            'api': {
-                'port': 5300
-            }
-        }
 
         os.environ['api__port'] = '8080'
 
@@ -249,11 +207,7 @@ class TestEnvOverrides:
 
     def test_no_double_underscore_ignored(self):
         """Test that env vars without __ are ignored"""
-        cfg = {
+        cfg = {'api': {'port': 5300}}
-            'api': {
-                'port': 5300
-            }
-        }
 
         os.environ['APIPORT'] = '8080'
 
@@ -266,11 +220,7 @@ class TestEnvOverrides:
 
     def test_nonexistent_key_ignored(self):
         """Test that env vars for non-existent keys are ignored"""
-        cfg = {
+        cfg = {'api': {'port': 5300}}
-            'api': {
-                'port': 5300
-            }
-        }
 
         os.environ['API__NONEXISTENT'] = 'value'
 
@@ -283,11 +233,7 @@ class TestEnvOverrides:
 
     def test_integer_conversion(self):
         """Test integer value conversion"""
-        cfg = {
+        cfg = {'concurrency': {'pipeline': 20}}
-            'concurrency': {
-                'pipeline': 20
-            }
-        }
 
         os.environ['CONCURRENCY__PIPELINE'] = '100'
 
@@ -300,18 +246,7 @@ class TestEnvOverrides:
 
     def test_multiple_overrides(self):
         """Test multiple environment variable overrides at once"""
-        cfg = {
+        cfg = {'api': {'port': 5300}, 'concurrency': {'pipeline': 20, 'session': 1}, 'plugin': {'enable': False}}
-            'api': {
-                'port': 5300
-            },
-            'concurrency': {
-                'pipeline': 20,
-                'session': 1
-            },
-            'plugin': {
-                'enable': False
-            }
-        }
 
         os.environ['API__PORT'] = '8080'
         os.environ['CONCURRENCY__PIPELINE'] = '50'

tests/unit_tests/plugin/test_plugin_component_filtering.py

@@ -1,6 +1,5 @@
 """Test plugin list filtering by component kinds."""
 
-from datetime import datetime
 from unittest.mock import AsyncMock, MagicMock
 import pytest
 
@@ -31,16 +30,7 @@ async def test_plugin_list_filter_by_component_kinds():
                     }
                 }
             },
-            'components': [
+            'components': [{'manifest': {'manifest': {'kind': 'Tool', 'metadata': {'name': 'tool1'}}}}],
-                {
-                    'manifest': {
-                        'manifest': {
-                            'kind': 'Tool',
-                            'metadata': {'name': 'tool1'}
-                        }
-                    }
-                }
-            ]
         },
         {
             'debug': False,
@@ -53,15 +43,8 @@ async def test_plugin_list_filter_by_component_kinds():
                 }
             },
             'components': [
-                {
+                {'manifest': {'manifest': {'kind': 'KnowledgeRetriever', 'metadata': {'name': 'retriever1'}}}}
-                    'manifest': {
+            ],
-                        'manifest': {
-                            'kind': 'KnowledgeRetriever',
-                            'metadata': {'name': 'retriever1'}
-                        }
-                    }
-                }
-            ]
         },
         {
             'debug': False,
@@ -73,16 +56,7 @@ async def test_plugin_list_filter_by_component_kinds():
                     }
                 }
             },
-            'components': [
+            'components': [{'manifest': {'manifest': {'kind': 'Command', 'metadata': {'name': 'cmd1'}}}}],
-                {
-                    'manifest': {
-                        'manifest': {
-                            'kind': 'Command',
-                            'metadata': {'name': 'cmd1'}
-                        }
-                    }
-                }
-            ]
         },
         {
             'debug': False,
@@ -94,16 +68,7 @@ async def test_plugin_list_filter_by_component_kinds():
                     }
                 }
             },
-            'components': [
+            'components': [{'manifest': {'manifest': {'kind': 'EventListener', 'metadata': {'name': 'listener1'}}}}],
-                {
-                    'manifest': {
-                        'manifest': {
-                            'kind': 'EventListener',
-                            'metadata': {'name': 'listener1'}
-                        }
-                    }
-                }
-            ]
         },
         {
             'debug': False,
@@ -116,23 +81,9 @@ async def test_plugin_list_filter_by_component_kinds():
                 }
             },
             'components': [
-                {
+                {'manifest': {'manifest': {'kind': 'KnowledgeRetriever', 'metadata': {'name': 'retriever2'}}}},
-                    'manifest': {
+                {'manifest': {'manifest': {'kind': 'Tool', 'metadata': {'name': 'tool2'}}}},
-                        'manifest': {
+            ],
-                            'kind': 'KnowledgeRetriever',
-                            'metadata': {'name': 'retriever2'}
-                        }
-                    }
-                },
-                {
-                    'manifest': {
-                        'manifest': {
-                            'kind': 'Tool',
-                            'metadata': {'name': 'tool2'}
-                        }
-                    }
-                }
-            ]
         },
     ]
 
@@ -187,16 +138,7 @@ async def test_plugin_list_filter_no_filter():
                     }
                 }
             },
-            'components': [
+            'components': [{'manifest': {'manifest': {'kind': 'Tool', 'metadata': {'name': 'tool1'}}}}],
-                {
-                    'manifest': {
-                        'manifest': {
-                            'kind': 'Tool',
-                            'metadata': {'name': 'tool1'}
-                        }
-                    }
-                }
-            ]
         },
         {
             'debug': False,
@@ -209,15 +151,8 @@ async def test_plugin_list_filter_no_filter():
                 }
             },
             'components': [
-                {
+                {'manifest': {'manifest': {'kind': 'KnowledgeRetriever', 'metadata': {'name': 'retriever1'}}}}
-                    'manifest': {
+            ],
-                        'manifest': {
-                            'kind': 'KnowledgeRetriever',
-                            'metadata': {'name': 'retriever1'}
-                        }
-                    }
-                }
-            ]
         },
     ]
 
@@ -267,15 +202,8 @@ async def test_plugin_list_filter_empty_result():
                 }
             },
             'components': [
-                {
+                {'manifest': {'manifest': {'kind': 'KnowledgeRetriever', 'metadata': {'name': 'retriever1'}}}}
-                    'manifest': {
+            ],
-                        'manifest': {
-                            'kind': 'KnowledgeRetriever',
-                            'metadata': {'name': 'retriever1'}
-                        }
-                    }
-                }
-            ]
         },
     ]
 
@@ -321,16 +249,7 @@ async def test_plugin_list_filter_plugin_without_components():
                     }
                 }
             },
-            'components': [
+            'components': [{'manifest': {'manifest': {'kind': 'Tool', 'metadata': {'name': 'tool1'}}}}],
-                {
-                    'manifest': {
-                        'manifest': {
-                            'kind': 'Tool',
-                            'metadata': {'name': 'tool1'}
-                        }
-                    }
-                }
-            ]
         },
         {
             'debug': False,
@@ -342,7 +261,7 @@ async def test_plugin_list_filter_plugin_without_components():
                     }
                 }
             },
-            'components': []
+            'components': [],
         },
     ]
 

web/src/i18n/locales/en-US.ts

@@ -121,7 +121,8 @@ const enUS = {
     webhookHint:
       'Webhooks allow LangBot to push person and group message events to external systems',
     actions: 'Actions',
-    apiKeyCreatedMessage: 'Please copy this API key.',
+    apiKeyCreatedMessage:
+      'Please copy this API key, if the button is invalid, please copy manually.',
     none: 'None',
   },
   notFound: {

web/src/i18n/locales/ja-JP.ts

@@ -123,7 +123,8 @@ const jaJP = {
     webhookHint:
       'Webhook を使用すると、LangBot は個人メッセージとグループメッセージイベントを外部システムにプッシュできます',
     actions: 'アクション',
-    apiKeyCreatedMessage: 'この API キーをコピーしてください。',
+    apiKeyCreatedMessage:
+      'この API キーをコピーしてください。もしボタンが無効な場合は手動でコピーしてください。',
     none: 'なし',
   },
   notFound: {

web/src/i18n/locales/zh-Hans.ts

@@ -114,7 +114,7 @@ const zhHans = {
     noWebhooks: '暂无 Webhook',
     webhookHint: 'Webhook 允许 LangBot 将个人消息和群消息事件推送到外部系统',
     actions: '操作',
-    apiKeyCreatedMessage: '请复制此 API 密钥。',
+    apiKeyCreatedMessage: '请复制此 API 密钥，若按钮无效，请手动复制。',
     none: '无',
   },
   notFound: {

web/src/i18n/locales/zh-Hant.ts

@@ -114,7 +114,7 @@ const zhHant = {
     noWebhooks: '暫無 Webhook',
     webhookHint: 'Webhook 允許 LangBot 將個人訊息和群組訊息事件推送到外部系統',
     actions: '操作',
-    apiKeyCreatedMessage: '請複製此 API 金鑰。',
+    apiKeyCreatedMessage: '請複製此 API 金鑰，若按鈕無效，請手動複製。',
     none: '無',
   },
   notFound: {