diff --git a/README.md b/README.md
index 4973023b..13f327fc 100644
--- a/README.md
+++ b/README.md
@@ -124,6 +124,7 @@ docker compose up -d
| [火山方舟](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | ✅ | 大模型聚合平台, LLMOps 平台 |
| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | ✅ | 大模型聚合平台 |
| [MCP](https://modelcontextprotocol.io/) | ✅ | 支持通过 MCP 协议获取工具 |
+| [百宝箱Tbox](https://www.tbox.cn/open) | ✅ | 蚂蚁百宝箱智能体平台，每月免费10亿大模型Token |
### TTS
diff --git a/pkg/provider/runners/tboxapi.py b/pkg/provider/runners/tboxapi.py
new file mode 100644
index 00000000..f0b1bd6a
--- /dev/null
+++ b/pkg/provider/runners/tboxapi.py
@@ -0,0 +1,205 @@
+from __future__ import annotations
+
+import typing
+import json
+import base64
+import tempfile
+import os
+
+from tboxsdk.tbox import TboxClient
+from tboxsdk.model.file import File, FileType
+
+from .. import runner
+from ...core import app
+from ...utils import image
+import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query
+import langbot_plugin.api.entities.builtin.provider.message as provider_message
+
+
+class TboxAPIError(Exception):
+ """TBox API 请求失败"""
+
+ def __init__(self, message: str):
+ self.message = message
+ super().__init__(self.message)
+
+
+@runner.runner_class('tbox-app-api')
+class TboxAPIRunner(runner.RequestRunner):
+ "蚂蚁百宝箱API对话请求器"
+
+ # 运行器内部使用的配置
+ app_id: str # 蚂蚁百宝箱平台中的应用ID
+ api_key: str # 在蚂蚁百宝箱平台中申请的令牌
+
+ def __init__(self, ap: app.Application, pipeline_config: dict):
+ """初始化"""
+ self.ap = ap
+ self.pipeline_config = pipeline_config
+
+ # 初始化Tbox 参数配置
+ self.app_id = self.pipeline_config['ai']['tbox-app-api']['app-id']
+ self.api_key = self.pipeline_config['ai']['tbox-app-api']['api-key']
+
+ # 初始化Tbox client
+ self.tbox_client = TboxClient(authorization=self.api_key)
+
+ async def _preprocess_user_message(self, query: pipeline_query.Query) -> tuple[str, list[str]]:
+ """预处理用户消息，提取纯文本，并将图片上传到 Tbox 服务
+
+ Returns:
+ tuple[str, list[str]]: 纯文本和图片的 Tbox 文件ID
+ """
+ plain_text = ''
+ image_ids = []
+
+ if isinstance(query.user_message.content, list):
+ for ce in query.user_message.content:
+ 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)
+ # 创建临时文件
+ file_bytes = base64.b64decode(image_b64)
+ try:
+ with tempfile.NamedTemporaryFile(suffix=f'.{image_format}', delete=False) as tmp_file:
+ tmp_file.write(file_bytes)
+ tmp_file_path = tmp_file.name
+ file_upload_resp = self.tbox_client.upload_file(
+ tmp_file_path
+ )
+ image_id = file_upload_resp.get("data", "")
+ image_ids.append(image_id)
+ finally:
+ # 清理临时文件
+ if os.path.exists(tmp_file_path):
+ os.unlink(tmp_file_path)
+ elif isinstance(query.user_message.content, str):
+ plain_text = query.user_message.content
+
+ return plain_text, image_ids
+
+ async def _agent_messages(
+ self, query: pipeline_query.Query
+ ) -> typing.AsyncGenerator[provider_message.Message, None]:
+ """TBox 智能体对话请求"""
+
+ plain_text, image_ids = await self._preprocess_user_message(query)
+ remove_think = self.pipeline_config['output'].get('misc', {}).get('remove-think')
+
+ try:
+ is_stream = await query.adapter.is_stream_output_supported()
+ except AttributeError:
+ is_stream = False
+
+ # 获取Tbox的conversation_id
+ conversation_id = query.session.using_conversation.uuid or None
+
+ files = None
+ if image_ids:
+ files = [
+ File(file_id=image_id, type=FileType.IMAGE)
+ for image_id in image_ids
+ ]
+
+ # 发送对话请求
+ response = self.tbox_client.chat(
+ app_id=self.app_id, # Tbox中智能体应用的ID
+ user_id=query.bot_uuid, # 用户ID
+ query=plain_text, # 用户输入的文本信息
+ stream=is_stream, # 是否流式输出
+ conversation_id=conversation_id, # 会话ID，为None时Tbox会自动创建一个新会话
+ files=files, # 图片内容
+ )
+
+ if is_stream:
+ # 解析Tbox流式输出内容，并发送给上游
+ for chunk in self._process_stream_message(response, query, remove_think):
+ yield chunk
+ else:
+ message = self._process_non_stream_message(response, query, remove_think)
+ yield provider_message.Message(
+ role='assistant',
+ content=message,
+ )
+
+ def _process_non_stream_message(self, response: typing.Dict, query: pipeline_query.Query, remove_think: bool):
+ if response.get('errorCode') != "0":
+ raise TboxAPIError(f'Tbox API 请求失败: {response.get("errorMsg", "")}')
+ payload = response.get('data', {})
+ conversation_id = payload.get('conversationId', '')
+ query.session.using_conversation.uuid = conversation_id
+ thinking_content = payload.get('reasoningContent', [])
+ result = ""
+ if thinking_content and not remove_think:
+ result += f'\n{thinking_content[0].get("text", "")}\n\n'
+ content = payload.get('result', [])
+ if content:
+ result += content[0].get('chunk', '')
+ return result
+
+ def _process_stream_message(self, response: typing.Generator[dict], query: pipeline_query.Query, remove_think: bool):
+ idx_msg = 0
+ pending_content = ''
+ conversation_id = None
+ think_start = False
+ think_end = False
+ for chunk in response:
+ if chunk.get('type', '') == 'chunk':
+ """
+ Tbox返回的消息内容chunk结构
+ {'lane': 'default', 'payload': {'conversationId': '20250918tBI947065406', 'messageId': '20250918TB1f53230954', 'text': '️'}, 'type': 'chunk'}
+ """
+ # 如果包含思考过程，拼接
+ if think_start and not think_end:
+ pending_content += '\n\n'
+ think_end = True
+
+ payload = chunk.get('payload', {})
+ if not conversation_id:
+ conversation_id = payload.get('conversationId')
+ query.session.using_conversation.uuid = conversation_id
+ if payload.get('text'):
+ idx_msg += 1
+ pending_content += payload.get('text')
+ elif chunk.get('type', '') == 'thinking' and not remove_think:
+ """
+ Tbox返回的思考过程chunk结构
+ {'payload': '{"ext_data":{"text":"日期"},"event":"flow.node.llm.thinking","entity":{"node_type":"text-completion","execute_id":"6","group_id":0,"parent_execute_id":"6","node_name":"模型推理","node_id":"TC_5u6gl0"}}', 'type': 'thinking'}
+ """
+ payload = json.loads(chunk.get('payload', '{}'))
+ if payload.get('ext_data', {}).get('text'):
+ idx_msg += 1
+ content = payload.get('ext_data', {}).get('text')
+ if not think_start:
+ think_start = True
+ pending_content += f'\n{content}'
+ else:
+ pending_content += content
+ elif chunk.get('type', '') == 'error':
+ raise TboxAPIError(
+ f'Tbox API 请求失败: status_code={chunk.get("status_code")} message={chunk.get("message")} request_id={chunk.get("request_id")} '
+ )
+
+ if idx_msg % 8 == 0:
+ yield provider_message.MessageChunk(
+ role='assistant',
+ content=pending_content,
+ is_final=False,
+ )
+
+ # Tbox不返回END事件，默认发一个最终消息
+ yield provider_message.MessageChunk(
+ role='assistant',
+ content=pending_content,
+ is_final=True,
+ )
+
+ async def run(self, query: pipeline_query.Query) -> typing.AsyncGenerator[provider_message.Message, None]:
+ """运行"""
+ msg_seq = 0
+ async for msg in self._agent_messages(query):
+ if isinstance(msg, provider_message.MessageChunk):
+ msg_seq += 1
+ msg.msg_sequence = msg_seq
+ yield msg
diff --git a/pyproject.toml b/pyproject.toml
index 28f50b05..564211c8 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -64,7 +64,8 @@ dependencies = [
"qdrant-client (>=1.15.1,<2.0.0)",
"langbot-plugin==0.1.3b1",
"asyncpg>=0.30.0",
- "line-bot-sdk>=3.19.0"
+ "line-bot-sdk>=3.19.0",
+ "tboxsdk>=0.0.10",
]
keywords = [
"bot",
diff --git a/templates/metadata/pipeline/ai.yaml b/templates/metadata/pipeline/ai.yaml
index b37c753b..2b69806c 100644
--- a/templates/metadata/pipeline/ai.yaml
+++ b/templates/metadata/pipeline/ai.yaml
@@ -23,6 +23,10 @@ stages:
label:
en_US: Local Agent
zh_Hans: 内置 Agent
+ - name: tbox-app-api
+ label:
+ en_US: Tbox App API
+ zh_Hans: 蚂蚁百宝箱平台 API
- name: dify-service-api
label:
en_US: Dify Service API
@@ -82,6 +86,26 @@ stages:
type: knowledge-base-selector
required: false
default: ''
+ - name: tbox-app-api
+ label:
+ en_US: Tbox App API
+ zh_Hans: 蚂蚁百宝箱平台 API
+ description:
+ en_US: Configure the Tbox App API of the pipeline
+ zh_Hans: 配置蚂蚁百宝箱平台 API
+ config:
+ - name: api-key
+ label:
+ en_US: API Key
+ zh_Hans: API 密钥
+ type: string
+ required: true
+ - name: app-id
+ label:
+ en_US: App ID
+ zh_Hans: 应用 ID
+ type: string
+ required: true
- name: dify-service-api
label:
en_US: Dify Service API