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Merge pull request #843 from SuanmoSuanyangTechnology/feature/openclaw_lm

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Feature/openclaw lm
This commit is contained in:
Ke Sun
2026-04-10 18:54:09 +08:00
committed by GitHub
parent 4c2a1e6d1d 0f28d54c43
commit b8507a1df6
10 changed files with 514 additions and 16 deletions
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18
api/app/services/app_chat_service.py
View File

@@ -165,7 +165,14 @@ class AppChatService:
multimodal_service = MultimodalService(self.db, model_info)
processed_files = await multimodal_service.process_files(files)
logger.info(f"处理了 {len(processed_files)} 个文件")
# 为需要运行时上下文的工具注入上下文
for t in tools:
if hasattr(t, 'tool_instance') and hasattr(t.tool_instance, 'set_runtime_context'):
t.tool_instance.set_runtime_context(
user_id=user_id or "anonymous",
conversation_id=str(conversation_id) if conversation_id else None,
uploaded_files=processed_files or []
)
# 调用 Agent（支持多模态）
result = await agent.chat(
message=message,
@@ -413,6 +420,15 @@ class AppChatService:
processed_files = await multimodal_service.process_files(files)
logger.info(f"处理了 {len(processed_files)} 个文件")
# 为需要运行时上下文的工具注入上下文
for t in tools:
if hasattr(t, 'tool_instance') and hasattr(t.tool_instance, 'set_runtime_context'):
t.tool_instance.set_runtime_context(
user_id=user_id or "anonymous",
conversation_id=str(conversation_id) if conversation_id else None,
uploaded_files=processed_files or []
)
# 流式调用 Agent（支持多模态），同时并行启动 TTS
full_content = ""
full_reasoning = ""

18
api/app/services/draft_run_service.py
View File

@@ -640,7 +640,14 @@ class AgentRunService:
multimodal_service = MultimodalService(self.db, model_info)
processed_files = await multimodal_service.process_files(files)
logger.info(f"处理了 {len(processed_files)} 个文件，provider={provider}")
# 为需要运行时上下文的工具注入上下文
for t in tools:
if hasattr(t, 'tool_instance') and hasattr(t.tool_instance, 'set_runtime_context'):
t.tool_instance.set_runtime_context(
user_id=user_id or "anonymous",
conversation_id=str(conversation_id) if conversation_id else None,
uploaded_files=processed_files or []
)
# 7. 知识库检索
context = None
@@ -890,7 +897,14 @@ class AgentRunService:
multimodal_service = MultimodalService(self.db, model_info)
processed_files = await multimodal_service.process_files(files)
logger.info(f"处理了 {len(processed_files)} 个文件，provider={provider}")
# 为需要运行时上下文的工具注入上下文
for t in tools:
if hasattr(t, 'tool_instance') and hasattr(t.tool_instance, 'set_runtime_context'):
t.tool_instance.set_runtime_context(
user_id=user_id or "anonymous",
conversation_id=str(conversation_id) if conversation_id else None,
uploaded_files=processed_files or []
)
# 7. 知识库检索
context = None

86
api/app/services/tool_service.py
View File

@@ -34,7 +34,8 @@ BUILTIN_TOOLS = {
"JsonTool": "app.core.tools.builtin.json_tool",
"BaiduSearchTool": "app.core.tools.builtin.baidu_search_tool",
"MinerUTool": "app.core.tools.builtin.mineru_tool",
"TextInTool": "app.core.tools.builtin.textin_tool"
"TextInTool": "app.core.tools.builtin.textin_tool",
"OpenClawTool": "app.core.tools.builtin.openclaw_tool",
}
@@ -340,18 +341,18 @@ class ToolService:
return {"success": False, "message": f"测试失败: {str(e)}"}
def ensure_builtin_tools_initialized(self, tenant_id: uuid.UUID):
"""确保内置工具已初始化"""
existing = self.tool_repo.exists_builtin_for_tenant(self.db, tenant_id)
if existing:
"""确保内置工具已初始化（支持增量补充新工具）"""
builtin_config = self._load_builtin_config()
if not builtin_config:
return
# 从配置文件加载内置工具定义
builtin_config = self._load_builtin_config()
existing_classes = self.builtin_repo.get_existing_tool_classes(self.db, tenant_id)
added = False
for tool_key, tool_info in builtin_config.items():
if tool_info['tool_class'] in existing_classes:
continue
try:
# 创建工具配置
initial_status = self._determine_initial_status(tool_info)
tool_config = ToolConfig(
name=tool_info['name'],
@@ -367,7 +368,6 @@ class ToolService:
self.db.add(tool_config)
self.db.flush()
# 创建内置工具配置
builtin_config_obj = BuiltinToolConfig(
id=tool_config.id,
tool_class=tool_info['tool_class'],
@@ -375,12 +375,14 @@ class ToolService:
requires_config=tool_info.get('requires_config', False)
)
self.db.add(builtin_config_obj)
added = True
except Exception as e:
logger.error(f"初始化内置工具失败: {tool_key}, {e}")
self.db.commit()
logger.info(f"租户 {tenant_id} 内置工具初始化完成")
if added:
self.db.commit()
logger.info(f"租户 {tenant_id} 内置工具增量初始化完成")
async def get_tool_methods(self, tool_id: str, tenant_id: uuid.UUID) -> Optional[List[Dict[str, Any]]]:
"""获取工具的所有方法
@@ -458,6 +460,9 @@ class ToolService:
# 对于json_tool，根据操作类型返回相关参数
elif hasattr(tool_instance, 'name') and tool_instance.name == 'json_tool':
return self._get_json_tool_params(operation)
# 对于openclaw_tool，根据操作类型返回不同描述的参数
elif hasattr(tool_instance, 'name') and tool_instance.name == 'openclaw_tool':
return self._get_openclaw_tool_params(operation)
# 其他工具的默认处理：返回除operation外的所有参数
return [{
@@ -710,6 +715,65 @@ class ToolService:
return base_params
@staticmethod
def _get_openclaw_tool_params(operation: str) -> List[Dict[str, Any]]:
"""获取 openclaw_tool 特定操作的参数"""
if operation == "print_task":
return [
{
"name": "message",
"type": "string",
"description": "发送给 OpenClaw 的打印任务描述，将用户的原始消息原封不动地传递给 OpenClaw，禁止改写、补充或润色用户的原文",
"required": True
},
{
"name": "image_url",
"type": "string",
"description": "可选，附带的设计图片或参考图，OpenClaw 可据此生成 3D 模型",
"required": False
}
]
elif operation == "device_query":
return [
{
"name": "message",
"type": "string",
"description": "发送给 OpenClaw 的设备查询指令",
"required": True
}
]
elif operation == "image_understand":
return [
{
"name": "message",
"type": "string",
"description": "发送给 OpenClaw 的图片理解任务，应描述需要对图片做什么（如描述内容、提取文字、分析信息）",
"required": True
},
{
"name": "image_url",
"type": "string",
"description": "要分析的图片 URL 或 base64 data URI",
"required": False
}
]
else:
# general 及其他
return [
{
"name": "message",
"type": "string",
"description": "发送给 OpenClaw Agent 的任务描述，应包含完整的任务需求",
"required": True
},
{
"name": "image_url",
"type": "string",
"description": "可选，附带的图片 URL 或 base64 data URI",
"required": False
}
]
async def _get_custom_tool_methods(self, config: ToolConfig) -> List[Dict[str, Any]]:
"""获取自定义工具的方法"""
custom_config = self.custom_repo.find_by_tool_id(self.db, config.id)