weknora

src/langbot/libs/weknora_api/v1/__init__.py

@@ -0,0 +1,4 @@
+from .client import AsyncWeKnoraClient
+from .errors import WeKnoraAPIError
+
+__all__ = ['AsyncWeKnoraClient', 'WeKnoraAPIError']

src/langbot/libs/weknora_api/v1/client.py

@@ -0,0 +1,172 @@
+from __future__ import annotations
+
+import httpx
+import typing
+import json
+
+from .errors import WeKnoraAPIError
+
+
+class AsyncWeKnoraClient:
+    """WeKnora API 客户端"""
+
+    api_key: str
+    base_url: str
+
+    def __init__(
+        self,
+        api_key: str,
+        base_url: str = 'http://localhost:80/api/v1',
+    ) -> None:
+        self.api_key = api_key
+        self.base_url = base_url
+
+    async def create_session(
+        self,
+        title: str = '',
+        description: str = '',
+        timeout: float = 30.0,
+    ) -> str:
+        """创建会话，返回 session_id"""
+        async with httpx.AsyncClient(
+            base_url=self.base_url,
+            trust_env=True,
+            timeout=timeout,
+        ) as client:
+            payload: dict[str, typing.Any] = {}
+            if title:
+                payload['title'] = title
+            if description:
+                payload['description'] = description
+
+            response = await client.post(
+                '/sessions',
+                headers={
+                    'X-API-Key': self.api_key,
+                    'Content-Type': 'application/json',
+                },
+                json=payload,
+            )
+
+            if response.status_code not in (200, 201):
+                raise WeKnoraAPIError(f'{response.status_code} {response.text}')
+
+            data = response.json()
+            return data['data']['id']
+
+    async def agent_chat(
+        self,
+        session_id: str,
+        query: str,
+        user: str,
+        agent_id: str = '',
+        knowledge_base_ids: list[str] | None = None,
+        web_search_enabled: bool = False,
+        timeout: float = 120.0,
+    ) -> typing.AsyncGenerator[dict[str, typing.Any], None]:
+        """
+        Agent 智能对话（SSE 流式）
+
+        响应事件类型:
+        - agent_query: Agent 开始处理
+        - thinking: 思考过程
+        - tool_call: 工具调用
+        - tool_result: 工具结果
+        - references: 知识库引用
+        - answer: 回答内容
+        - reflection: 反思
+        - session_title: 会话标题
+        - error: 错误
+        """
+        if knowledge_base_ids is None:
+            knowledge_base_ids = []
+
+        async with httpx.AsyncClient(
+            base_url=self.base_url,
+            trust_env=True,
+            timeout=timeout,
+        ) as client:
+            payload: dict[str, typing.Any] = {
+                'query': query,
+                'agent_enabled': True,
+                'channel': 'im',
+            }
+            if agent_id:
+                payload['agent_id'] = agent_id
+            if knowledge_base_ids:
+                payload['knowledge_base_ids'] = knowledge_base_ids
+            if web_search_enabled:
+                payload['web_search_enabled'] = True
+
+            async with client.stream(
+                'POST',
+                f'/agent-chat/{session_id}',
+                headers={
+                    'X-API-Key': self.api_key,
+                    'Content-Type': 'application/json',
+                },
+                json=payload,
+            ) as r:
+                async for chunk in r.aiter_lines():
+                    if r.status_code != 200:
+                        raise WeKnoraAPIError(f'{r.status_code} {chunk}')
+                    if chunk.strip() == '':
+                        continue
+                    if chunk.startswith('data:'):
+                        try:
+                            yield json.loads(chunk[5:].strip())
+                        except json.JSONDecodeError:
+                            continue
+
+    async def knowledge_chat(
+        self,
+        session_id: str,
+        query: str,
+        user: str,
+        agent_id: str = 'builtin-quick-answer',
+        knowledge_base_ids: list[str] | None = None,
+        timeout: float = 120.0,
+    ) -> typing.AsyncGenerator[dict[str, typing.Any], None]:
+        """
+        知识库 RAG 问答（SSE 流式）
+
+        响应事件类型:
+        - references: 知识库引用
+        - answer: 回答内容
+        """
+        if knowledge_base_ids is None:
+            knowledge_base_ids = []
+
+        async with httpx.AsyncClient(
+            base_url=self.base_url,
+            trust_env=True,
+            timeout=timeout,
+        ) as client:
+            payload: dict[str, typing.Any] = {
+                'query': query,
+                'channel': 'im',
+            }
+            if agent_id:
+                payload['agent_id'] = agent_id
+            if knowledge_base_ids:
+                payload['knowledge_base_ids'] = knowledge_base_ids
+
+            async with client.stream(
+                'POST',
+                f'/knowledge-chat/{session_id}',
+                headers={
+                    'X-API-Key': self.api_key,
+                    'Content-Type': 'application/json',
+                },
+                json=payload,
+            ) as r:
+                async for chunk in r.aiter_lines():
+                    if r.status_code != 200:
+                        raise WeKnoraAPIError(f'{r.status_code} {chunk}')
+                    if chunk.strip() == '':
+                        continue
+                    if chunk.startswith('data:'):
+                        try:
+                            yield json.loads(chunk[5:].strip())
+                        except json.JSONDecodeError:
+                            continue

src/langbot/libs/weknora_api/v1/errors.py

@@ -0,0 +1,6 @@
+class WeKnoraAPIError(Exception):
+    """WeKnora API 请求失败"""
+
+    def __init__(self, message: str = ''):
+        self.message = message
+        super().__init__(self.message)

src/langbot/pkg/core/migrations/m042_weknora_api.py

@@ -0,0 +1,27 @@
+from __future__ import annotations
+
+from .. import migration
+
+
+@migration.migration_class('weknora-api-config', 42)
+class WeKnoraAPICfgMigration(migration.Migration):
+    """WeKnora API 配置迁移"""
+
+    async def need_migrate(self) -> bool:
+        """判断当前环境是否需要运行此迁移"""
+        return 'weknora-api' not in self.ap.provider_cfg.data
+
+    async def run(self):
+        """执行迁移"""
+        self.ap.provider_cfg.data['weknora-api'] = {
+            'base-url': 'http://localhost:8080/api/v1',
+            'app-type': 'agent',
+            'api-key': '',
+            'agent-id': 'builtin-smart-reasoning',
+            'knowledge-base-ids': [],
+            'web-search-enabled': False,
+            'timeout': 120,
+            'base-prompt': '请回答用户的问题。',
+        }
+
+        await self.ap.provider_cfg.dump_config()

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

@@ -0,0 +1,360 @@
+from __future__ import annotations
+
+import typing
+import json
+
+
+from langbot.pkg.provider import runner
+from langbot.pkg.core import app
+import langbot_plugin.api.entities.builtin.provider.message as provider_message
+import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query
+from langbot.libs.weknora_api.v1 import client, errors
+
+
+@runner.runner_class('weknora-api')
+class WeKnoraAPIRunner(runner.RequestRunner):
+    """WeKnora API 对话请求器"""
+
+    weknora_client: client.AsyncWeKnoraClient
+
+    def __init__(self, ap: app.Application, pipeline_config: dict):
+        self.ap = ap
+        self.pipeline_config = pipeline_config
+
+        valid_app_types = ['chat', 'agent']
+        if self.pipeline_config['ai']['weknora-api']['app-type'] not in valid_app_types:
+            raise errors.WeKnoraAPIError(
+                f'不支持的 WeKnora 应用类型: {self.pipeline_config["ai"]["weknora-api"]["app-type"]}'
+            )
+
+        api_key = self.pipeline_config['ai']['weknora-api'].get('api-key', '').strip()
+        if not api_key:
+            raise errors.WeKnoraAPIError(
+                'WeKnora API Key 未配置，请在流水线的 WeKnora API 配置中填入 API Key '
+                '(从 WeKnora 前端 设置 → API Keys 生成)'
+            )
+
+        base_url = self.pipeline_config['ai']['weknora-api'].get('base-url', '').strip()
+        if not base_url:
+            raise errors.WeKnoraAPIError(
+                'WeKnora Base URL 未配置，请填入服务器地址，例如 http://localhost:8080/api/v1'
+            )
+
+        self.weknora_client = client.AsyncWeKnoraClient(
+            api_key=api_key,
+            base_url=base_url,
+        )
+
+    async def _extract_plain_text(self, query: pipeline_query.Query) -> str:
+        """从用户消息中提取纯文本内容"""
+        plain_text = ''
+        if isinstance(query.user_message.content, str):
+            plain_text = query.user_message.content
+        elif isinstance(query.user_message.content, list):
+            for ce in query.user_message.content:
+                if ce.type == 'text':
+                    plain_text += ce.text
+
+        if not plain_text:
+            plain_text = self.pipeline_config['ai']['weknora-api'].get('base-prompt', '')
+
+        return plain_text
+
+    async def _ensure_session(self, query: pipeline_query.Query) -> str:
+        """确保会话存在，如果不存在则创建"""
+        session_id = query.session.using_conversation.uuid or ''
+
+        if not session_id:
+            user_tag = f'{query.session.launcher_type.value}_{query.session.launcher_id}'
+            session_id = await self.weknora_client.create_session(
+                title=f'IM Chat - {user_tag}'
+            )
+            query.session.using_conversation.uuid = session_id
+
+        return session_id
+
+    async def _agent_chat_messages(
+        self, query: pipeline_query.Query
+    ) -> typing.AsyncGenerator[provider_message.Message, None]:
+        """调用 Agent 智能对话（非流式聚合输出）"""
+        session_id = await self._ensure_session(query)
+        plain_text = await self._extract_plain_text(query)
+        user_tag = f'{query.session.launcher_type.value}_{query.session.launcher_id}'
+
+        config = self.pipeline_config['ai']['weknora-api']
+        agent_id = config.get('agent-id', 'builtin-smart-reasoning')
+        knowledge_base_ids = config.get('knowledge-base-ids', [])
+        web_search_enabled = config.get('web-search-enabled', False)
+        timeout = config.get('timeout', 120)
+
+        full_answer = ''
+        chunk = None
+
+        async for chunk in self.weknora_client.agent_chat(
+            session_id=session_id,
+            query=plain_text,
+            user=user_tag,
+            agent_id=agent_id,
+            knowledge_base_ids=knowledge_base_ids,
+            web_search_enabled=web_search_enabled,
+            timeout=timeout,
+        ):
+            self.ap.logger.debug('weknora-agent-chunk: ' + str(chunk))
+
+            response_type = chunk.get('response_type', '')
+            content = chunk.get('content', '')
+
+            if response_type == 'tool_call':
+                # 工具调用
+                tool_data = chunk.get('data', {})
+                tool_name = tool_data.get('tool_name', '')
+                if tool_name:
+                    yield provider_message.Message(
+                        role='assistant',
+                        tool_calls=[
+                            provider_message.ToolCall(
+                                id=chunk.get('id', ''),
+                                type='function',
+                                function=provider_message.FunctionCall(
+                                    name=tool_name,
+                                    arguments=json.dumps(tool_data.get('arguments', {})),
+                                ),
+                            )
+                        ],
+                    )
+
+            elif response_type == 'answer':
+                if content:
+                    full_answer += content
+
+            elif response_type == 'error':
+                raise errors.WeKnoraAPIError(f'WeKnora 服务错误: {content}')
+
+        if chunk is None:
+            raise errors.WeKnoraAPIError('WeKnora API 没有返回任何响应，请检查网络连接和API配置')
+
+        if full_answer:
+            yield provider_message.Message(
+                role='assistant',
+                content=full_answer,
+            )
+
+    async def _chat_messages(
+        self, query: pipeline_query.Query
+    ) -> typing.AsyncGenerator[provider_message.Message, None]:
+        """调用知识库 RAG 问答（非流式聚合输出）"""
+        session_id = await self._ensure_session(query)
+        plain_text = await self._extract_plain_text(query)
+        user_tag = f'{query.session.launcher_type.value}_{query.session.launcher_id}'
+
+        config = self.pipeline_config['ai']['weknora-api']
+        agent_id = config.get('agent-id', 'builtin-quick-answer')
+        knowledge_base_ids = config.get('knowledge-base-ids', [])
+        timeout = config.get('timeout', 120)
+
+        full_answer = ''
+        chunk = None
+
+        async for chunk in self.weknora_client.knowledge_chat(
+            session_id=session_id,
+            query=plain_text,
+            user=user_tag,
+            agent_id=agent_id,
+            knowledge_base_ids=knowledge_base_ids,
+            timeout=timeout,
+        ):
+            self.ap.logger.debug('weknora-chat-chunk: ' + str(chunk))
+
+            response_type = chunk.get('response_type', '')
+            content = chunk.get('content', '')
+
+            if response_type == 'answer':
+                if content:
+                    full_answer += content
+
+            elif response_type == 'error':
+                raise errors.WeKnoraAPIError(f'WeKnora 服务错误: {content}')
+
+        if chunk is None:
+            raise errors.WeKnoraAPIError('WeKnora API 没有返回任何响应，请检查网络连接和API配置')
+
+        if full_answer:
+            yield provider_message.Message(
+                role='assistant',
+                content=full_answer,
+            )
+
+    async def _agent_chat_messages_chunk(
+        self, query: pipeline_query.Query
+    ) -> typing.AsyncGenerator[provider_message.MessageChunk, None]:
+        """调用 Agent 智能对话（流式输出）"""
+        session_id = await self._ensure_session(query)
+        plain_text = await self._extract_plain_text(query)
+        user_tag = f'{query.session.launcher_type.value}_{query.session.launcher_id}'
+
+        config = self.pipeline_config['ai']['weknora-api']
+        agent_id = config.get('agent-id', 'builtin-smart-reasoning')
+        knowledge_base_ids = config.get('knowledge-base-ids', [])
+        web_search_enabled = config.get('web-search-enabled', False)
+        timeout = config.get('timeout', 120)
+
+        pending_answer = ''
+        message_idx = 0
+        is_final = False
+        chunk = None
+
+        async for chunk in self.weknora_client.agent_chat(
+            session_id=session_id,
+            query=plain_text,
+            user=user_tag,
+            agent_id=agent_id,
+            knowledge_base_ids=knowledge_base_ids,
+            web_search_enabled=web_search_enabled,
+            timeout=timeout,
+        ):
+            self.ap.logger.debug('weknora-agent-chunk: ' + str(chunk))
+
+            response_type = chunk.get('response_type', '')
+            content = chunk.get('content', '')
+            done = chunk.get('done', False)
+
+            if response_type == 'tool_call':
+                tool_data = chunk.get('data', {})
+                tool_name = tool_data.get('tool_name', '')
+                if tool_name:
+                    message_idx += 1
+                    yield provider_message.MessageChunk(
+                        role='assistant',
+                        tool_calls=[
+                            provider_message.ToolCall(
+                                id=chunk.get('id', ''),
+                                type='function',
+                                function=provider_message.FunctionCall(
+                                    name=tool_name,
+                                    arguments=json.dumps(tool_data.get('arguments', {})),
+                                ),
+                            )
+                        ],
+                    )
+
+            elif response_type == 'answer':
+                message_idx += 1
+                if content:
+                    pending_answer += content
+
+                if done:
+                    is_final = True
+
+                # 每 8 个 chunk 输出一次，或最终输出
+                if message_idx % 8 == 0 or is_final:
+                    yield provider_message.MessageChunk(
+                        role='assistant',
+                        content=pending_answer,
+                        is_final=is_final,
+                    )
+
+            elif response_type == 'error':
+                raise errors.WeKnoraAPIError(f'WeKnora 服务错误: {content}')
+
+        if chunk is None:
+            raise errors.WeKnoraAPIError('WeKnora API 没有返回任何响应，请检查网络连接和API配置')
+
+        # 确保最终消息已发出
+        if not is_final and pending_answer:
+            yield provider_message.MessageChunk(
+                role='assistant',
+                content=pending_answer,
+                is_final=True,
+            )
+
+    async def _chat_messages_chunk(
+        self, query: pipeline_query.Query
+    ) -> typing.AsyncGenerator[provider_message.MessageChunk, None]:
+        """调用知识库 RAG 问答（流式输出）"""
+        session_id = await self._ensure_session(query)
+        plain_text = await self._extract_plain_text(query)
+        user_tag = f'{query.session.launcher_type.value}_{query.session.launcher_id}'
+
+        config = self.pipeline_config['ai']['weknora-api']
+        agent_id = config.get('agent-id', 'builtin-quick-answer')
+        knowledge_base_ids = config.get('knowledge-base-ids', [])
+        timeout = config.get('timeout', 120)
+
+        pending_answer = ''
+        message_idx = 0
+        is_final = False
+        chunk = None
+
+        async for chunk in self.weknora_client.knowledge_chat(
+            session_id=session_id,
+            query=plain_text,
+            user=user_tag,
+            agent_id=agent_id,
+            knowledge_base_ids=knowledge_base_ids,
+            timeout=timeout,
+        ):
+            self.ap.logger.debug('weknora-chat-chunk: ' + str(chunk))
+
+            response_type = chunk.get('response_type', '')
+            content = chunk.get('content', '')
+            done = chunk.get('done', False)
+
+            if response_type == 'answer':
+                message_idx += 1
+                if content:
+                    pending_answer += content
+
+                if done:
+                    is_final = True
+
+                if message_idx % 8 == 0 or is_final:
+                    yield provider_message.MessageChunk(
+                        role='assistant',
+                        content=pending_answer,
+                        is_final=is_final,
+                    )
+
+            elif response_type == 'error':
+                raise errors.WeKnoraAPIError(f'WeKnora 服务错误: {content}')
+
+        if chunk is None:
+            raise errors.WeKnoraAPIError('WeKnora API 没有返回任何响应，请检查网络连接和API配置')
+
+        if not is_final and pending_answer:
+            yield provider_message.MessageChunk(
+                role='assistant',
+                content=pending_answer,
+                is_final=True,
+            )
+
+    async def run(self, query: pipeline_query.Query) -> typing.AsyncGenerator[provider_message.Message, None]:
+        """运行请求"""
+        app_type = self.pipeline_config['ai']['weknora-api']['app-type']
+
+        if await query.adapter.is_stream_output_supported():
+            msg_idx = 0
+            if app_type == 'agent':
+                async for msg in self._agent_chat_messages_chunk(query):
+                    msg_idx += 1
+                    msg.msg_sequence = msg_idx
+                    yield msg
+            elif app_type == 'chat':
+                async for msg in self._chat_messages_chunk(query):
+                    msg_idx += 1
+                    msg.msg_sequence = msg_idx
+                    yield msg
+            else:
+                raise errors.WeKnoraAPIError(
+                    f'不支持的 WeKnora 应用类型: {app_type}'
+                )
+        else:
+            if app_type == 'agent':
+                async for msg in self._agent_chat_messages(query):
+                    yield msg
+            elif app_type == 'chat':
+                async for msg in self._chat_messages(query):
+                    yield msg
+            else:
+                raise errors.WeKnoraAPIError(
+                    f'不支持的 WeKnora 应用类型: {app_type}'
+                )

src/langbot/templates/metadata/pipeline/ai.yaml

@@ -47,6 +47,10 @@ stages:
             label:
               en_US: Langflow API
               zh_Hans: Langflow API
+          - name: weknora-api
+            label:
+              en_US: WeKnora API
+              zh_Hans: WeKnora API
       - name: expire-time
         label:
           en_US: Conversation expire time (seconds)
@@ -653,3 +657,97 @@ stages:
         type: json
         required: false
         default: '{}'
+  - name: weknora-api
+    label:
+      en_US: WeKnora API
+      zh_Hans: WeKnora API
+    description:
+      en_US: Configure the WeKnora API of the pipeline
+      zh_Hans: 配置 WeKnora API
+    config:
+      - name: base-url
+        label:
+          en_US: Base URL
+          zh_Hans: 基础 URL
+        description:
+          en_US: The base URL of the WeKnora server (with /api/v1)
+          zh_Hans: WeKnora 服务器的基础 URL（包含 /api/v1）
+        type: string
+        required: true
+        default: 'http://localhost:8080/api/v1'
+      - name: api-key
+        label:
+          en_US: API Key
+          zh_Hans: API 密钥
+        description:
+          en_US: The API key for WeKnora, generated from WeKnora frontend Settings → API Keys
+          zh_Hans: WeKnora 的 API 密钥，从 WeKnora 前端 设置 → API Keys 生成
+        type: string
+        required: true
+        default: ''
+      - name: app-type
+        label:
+          en_US: App Type
+          zh_Hans: 应用类型
+        type: select
+        required: true
+        default: agent
+        options:
+          - name: agent
+            label:
+              en_US: Agent (Smart Reasoning)
+              zh_Hans: Agent（智能推理）
+          - name: chat
+            label:
+              en_US: Chat (Knowledge Base RAG)
+              zh_Hans: 聊天（知识库 RAG）
+      - name: agent-id
+        label:
+          en_US: Agent ID
+          zh_Hans: 智能体 ID
+        description:
+          en_US: The Agent ID to use. Built-in agents include builtin-quick-answer, builtin-smart-reasoning, builtin-data-analyst
+          zh_Hans: 要使用的智能体 ID。内置智能体：builtin-quick-answer、builtin-smart-reasoning、builtin-data-analyst
+        type: string
+        required: true
+        default: 'builtin-smart-reasoning'
+      - name: knowledge-base-ids
+        label:
+          en_US: Knowledge Base IDs
+          zh_Hans: 知识库 ID 列表
+        description:
+          en_US: List of WeKnora knowledge base IDs to use (one per line)
+          zh_Hans: 要使用的 WeKnora 知识库 ID 列表（每行一个）
+        type: array
+        required: false
+        default: []
+      - name: web-search-enabled
+        label:
+          en_US: Enable Web Search
+          zh_Hans: 启用网络搜索
+        description:
+          en_US: Whether to enable web search in agent mode
+          zh_Hans: 在 Agent 模式下是否启用网络搜索
+        type: boolean
+        required: false
+        default: false
+      - name: timeout
+        label:
+          en_US: Timeout
+          zh_Hans: 超时时间
+        description:
+          en_US: Request timeout in seconds
+          zh_Hans: 请求超时时间（秒）
+        type: integer
+        required: false
+        default: 120
+      - name: base-prompt
+        label:
+          en_US: Base Prompt
+          zh_Hans: 基础提示词
+        description:
+          en_US: Default prompt when user message is empty (e.g. only images)
+          zh_Hans: 当用户消息为空（例如仅图片）时使用的默认提示词
+        type: string
+        required: false
+        default: '请回答用户的问题。'