mirror of https://github.com/kortix-ai/suna.git
696 lines
36 KiB
Python
696 lines
36 KiB
Python
import os
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import json
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import asyncio
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import datetime
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from typing import Optional, Dict, List, Any, AsyncGenerator
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from dataclasses import dataclass
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from agent.tools.message_tool import MessageTool
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from agent.tools.sb_deploy_tool import SandboxDeployTool
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from agent.tools.sb_expose_tool import SandboxExposeTool
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from agent.tools.web_search_tool import SandboxWebSearchTool
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from dotenv import load_dotenv
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from utils.config import config
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from agent.agent_builder_prompt import get_agent_builder_prompt
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from agentpress.thread_manager import ThreadManager
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from agentpress.response_processor import ProcessorConfig
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from agent.tools.sb_shell_tool import SandboxShellTool
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from agent.tools.sb_files_tool import SandboxFilesTool
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from agent.tools.data_providers_tool import DataProvidersTool
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from agent.tools.expand_msg_tool import ExpandMessageTool
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from agent.prompt import get_system_prompt
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from agent.custom_prompt import render_prompt_template
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from utils.logger import logger
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from utils.auth_utils import get_account_id_from_thread
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from services.billing import check_billing_status
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from agent.tools.sb_vision_tool import SandboxVisionTool
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from agent.tools.sb_image_edit_tool import SandboxImageEditTool
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from agent.tools.sb_presentation_outline_tool import SandboxPresentationOutlineTool
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from agent.tools.sb_presentation_tool_v2 import SandboxPresentationToolV2
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from services.langfuse import langfuse
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from langfuse.client import StatefulTraceClient
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from agent.gemini_prompt import get_gemini_system_prompt
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from agent.tools.mcp_tool_wrapper import MCPToolWrapper
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from agent.tools.task_list_tool import TaskListTool
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from agentpress.tool import SchemaType
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from agent.tools.sb_sheets_tool import SandboxSheetsTool
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from agent.tools.sb_web_dev_tool import SandboxWebDevTool
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load_dotenv()
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@dataclass
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class AgentConfig:
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thread_id: str
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project_id: str
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stream: bool
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native_max_auto_continues: int = 25
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max_iterations: int = 100
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model_name: str = "openrouter/moonshotai/kimi-k2"
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enable_thinking: Optional[bool] = False
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reasoning_effort: Optional[str] = 'low'
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enable_context_manager: bool = True
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agent_config: Optional[dict] = None
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trace: Optional[StatefulTraceClient] = None
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is_agent_builder: Optional[bool] = False
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target_agent_id: Optional[str] = None
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class ToolManager:
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def __init__(self, thread_manager: ThreadManager, project_id: str, thread_id: str):
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self.thread_manager = thread_manager
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self.project_id = project_id
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self.thread_id = thread_id
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def register_all_tools(self):
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self.thread_manager.add_tool(ExpandMessageTool, thread_id=self.thread_id, thread_manager=self.thread_manager)
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self.thread_manager.add_tool(MessageTool)
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self.thread_manager.add_tool(SandboxShellTool, project_id=self.project_id, thread_manager=self.thread_manager)
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self.thread_manager.add_tool(SandboxFilesTool, project_id=self.project_id, thread_manager=self.thread_manager)
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self.thread_manager.add_tool(SandboxDeployTool, project_id=self.project_id, thread_manager=self.thread_manager)
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self.thread_manager.add_tool(SandboxExposeTool, project_id=self.project_id, thread_manager=self.thread_manager)
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self.thread_manager.add_tool(SandboxWebSearchTool, project_id=self.project_id, thread_manager=self.thread_manager)
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self.thread_manager.add_tool(SandboxVisionTool, project_id=self.project_id, thread_id=self.thread_id, thread_manager=self.thread_manager)
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self.thread_manager.add_tool(SandboxImageEditTool, project_id=self.project_id, thread_id=self.thread_id, thread_manager=self.thread_manager)
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self.thread_manager.add_tool(SandboxPresentationOutlineTool, project_id=self.project_id, thread_manager=self.thread_manager)
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self.thread_manager.add_tool(SandboxPresentationToolV2, project_id=self.project_id, thread_manager=self.thread_manager)
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self.thread_manager.add_tool(TaskListTool, project_id=self.project_id, thread_manager=self.thread_manager, thread_id=self.thread_id)
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self.thread_manager.add_tool(SandboxSheetsTool, project_id=self.project_id, thread_manager=self.thread_manager)
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# self.thread_manager.add_tool(SandboxWebDevTool, project_id=self.project_id, thread_id=self.thread_id, thread_manager=self.thread_manager)
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if config.RAPID_API_KEY:
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self.thread_manager.add_tool(DataProvidersTool)
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# Add Browser Tool
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from agent.tools.browser_tool import BrowserTool
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self.thread_manager.add_tool(BrowserTool, project_id=self.project_id, thread_id=self.thread_id, thread_manager=self.thread_manager)
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def register_agent_builder_tools(self, agent_id: str):
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from agent.tools.agent_builder_tools.agent_config_tool import AgentConfigTool
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from agent.tools.agent_builder_tools.mcp_search_tool import MCPSearchTool
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from agent.tools.agent_builder_tools.credential_profile_tool import CredentialProfileTool
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from agent.tools.agent_builder_tools.workflow_tool import WorkflowTool
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from agent.tools.agent_builder_tools.trigger_tool import TriggerTool
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from services.supabase import DBConnection
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db = DBConnection()
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self.thread_manager.add_tool(AgentConfigTool, thread_manager=self.thread_manager, db_connection=db, agent_id=agent_id)
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self.thread_manager.add_tool(MCPSearchTool, thread_manager=self.thread_manager, db_connection=db, agent_id=agent_id)
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self.thread_manager.add_tool(CredentialProfileTool, thread_manager=self.thread_manager, db_connection=db, agent_id=agent_id)
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self.thread_manager.add_tool(WorkflowTool, thread_manager=self.thread_manager, db_connection=db, agent_id=agent_id)
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self.thread_manager.add_tool(TriggerTool, thread_manager=self.thread_manager, db_connection=db, agent_id=agent_id)
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def register_custom_tools(self, enabled_tools: Dict[str, Any]):
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self.thread_manager.add_tool(ExpandMessageTool, thread_id=self.thread_id, thread_manager=self.thread_manager)
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self.thread_manager.add_tool(MessageTool)
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self.thread_manager.add_tool(TaskListTool, project_id=self.project_id, thread_manager=self.thread_manager, thread_id=self.thread_id)
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def safe_tool_check(tool_name: str) -> bool:
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try:
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if not isinstance(enabled_tools, dict):
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return False
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tool_config = enabled_tools.get(tool_name, {})
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if not isinstance(tool_config, dict):
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return bool(tool_config) if isinstance(tool_config, bool) else False
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return tool_config.get('enabled', False)
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except Exception:
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return False
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if safe_tool_check('sb_shell_tool'):
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self.thread_manager.add_tool(SandboxShellTool, project_id=self.project_id, thread_manager=self.thread_manager)
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if safe_tool_check('sb_files_tool'):
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self.thread_manager.add_tool(SandboxFilesTool, project_id=self.project_id, thread_manager=self.thread_manager)
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if safe_tool_check('sb_deploy_tool'):
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self.thread_manager.add_tool(SandboxDeployTool, project_id=self.project_id, thread_manager=self.thread_manager)
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if safe_tool_check('sb_expose_tool'):
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self.thread_manager.add_tool(SandboxExposeTool, project_id=self.project_id, thread_manager=self.thread_manager)
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if safe_tool_check('web_search_tool'):
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self.thread_manager.add_tool(SandboxWebSearchTool, project_id=self.project_id, thread_manager=self.thread_manager)
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if safe_tool_check('sb_vision_tool'):
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self.thread_manager.add_tool(SandboxVisionTool, project_id=self.project_id, thread_id=self.thread_id, thread_manager=self.thread_manager)
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if safe_tool_check('sb_presentation_tool'):
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self.thread_manager.add_tool(SandboxPresentationOutlineTool, project_id=self.project_id, thread_manager=self.thread_manager)
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self.thread_manager.add_tool(SandboxPresentationToolV2, project_id=self.project_id, thread_manager=self.thread_manager)
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if safe_tool_check('sb_image_edit_tool'):
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self.thread_manager.add_tool(SandboxImageEditTool, project_id=self.project_id, thread_id=self.thread_id, thread_manager=self.thread_manager)
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if safe_tool_check('sb_sheets_tool'):
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self.thread_manager.add_tool(SandboxSheetsTool, project_id=self.project_id, thread_manager=self.thread_manager)
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if safe_tool_check('sb_web_dev_tool'):
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self.thread_manager.add_tool(SandboxWebDevTool, project_id=self.project_id, thread_id=self.thread_id, thread_manager=self.thread_manager)
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if config.RAPID_API_KEY and safe_tool_check('data_providers_tool'):
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self.thread_manager.add_tool(DataProvidersTool)
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if safe_tool_check('browser_tool'):
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from agent.tools.browser_tool import BrowserTool
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self.thread_manager.add_tool(BrowserTool, project_id=self.project_id, thread_id=self.thread_id, thread_manager=self.thread_manager)
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class MCPManager:
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def __init__(self, thread_manager: ThreadManager, account_id: str):
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self.thread_manager = thread_manager
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self.account_id = account_id
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async def register_mcp_tools(self, agent_config: dict) -> Optional[MCPToolWrapper]:
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all_mcps = []
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if agent_config.get('configured_mcps'):
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all_mcps.extend(agent_config['configured_mcps'])
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if agent_config.get('custom_mcps'):
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for custom_mcp in agent_config['custom_mcps']:
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custom_type = custom_mcp.get('customType', custom_mcp.get('type', 'sse'))
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if custom_type == 'pipedream':
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if 'config' not in custom_mcp:
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custom_mcp['config'] = {}
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if not custom_mcp['config'].get('external_user_id'):
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profile_id = custom_mcp['config'].get('profile_id')
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if profile_id:
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try:
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from pipedream import profile_service
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from uuid import UUID
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profile = await profile_service.get_profile(UUID(self.account_id), UUID(profile_id))
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if profile:
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custom_mcp['config']['external_user_id'] = profile.external_user_id
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except Exception as e:
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logger.error(f"Error retrieving external_user_id from profile {profile_id}: {e}")
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if 'headers' in custom_mcp['config'] and 'x-pd-app-slug' in custom_mcp['config']['headers']:
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custom_mcp['config']['app_slug'] = custom_mcp['config']['headers']['x-pd-app-slug']
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elif custom_type == 'composio':
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qualified_name = custom_mcp.get('qualifiedName')
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if not qualified_name:
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qualified_name = f"composio.{custom_mcp['name'].replace(' ', '_').lower()}"
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mcp_config = {
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'name': custom_mcp['name'],
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'qualifiedName': qualified_name,
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'config': custom_mcp.get('config', {}),
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'enabledTools': custom_mcp.get('enabledTools', []),
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'instructions': custom_mcp.get('instructions', ''),
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'isCustom': True,
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'customType': 'composio'
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}
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all_mcps.append(mcp_config)
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continue
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mcp_config = {
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'name': custom_mcp['name'],
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'qualifiedName': f"custom_{custom_type}_{custom_mcp['name'].replace(' ', '_').lower()}",
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'config': custom_mcp['config'],
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'enabledTools': custom_mcp.get('enabledTools', []),
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'instructions': custom_mcp.get('instructions', ''),
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'isCustom': True,
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'customType': custom_type
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}
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all_mcps.append(mcp_config)
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if not all_mcps:
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return None
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mcp_wrapper_instance = MCPToolWrapper(mcp_configs=all_mcps)
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try:
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await mcp_wrapper_instance.initialize_and_register_tools()
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updated_schemas = mcp_wrapper_instance.get_schemas()
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for method_name, schema_list in updated_schemas.items():
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for schema in schema_list:
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self.thread_manager.tool_registry.tools[method_name] = {
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"instance": mcp_wrapper_instance,
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"schema": schema
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}
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logger.info(f"⚡ Registered {len(updated_schemas)} MCP tools (Redis cache enabled)")
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return mcp_wrapper_instance
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except Exception as e:
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logger.error(f"Failed to initialize MCP tools: {e}")
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return None
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class PromptManager:
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@staticmethod
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async def build_system_prompt(model_name: str, agent_config: Optional[dict],
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is_agent_builder: bool, thread_id: str,
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mcp_wrapper_instance: Optional[MCPToolWrapper]) -> dict:
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if "gemini-2.5-flash" in model_name.lower() and "gemini-2.5-pro" not in model_name.lower():
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default_system_content = get_gemini_system_prompt()
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else:
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default_system_content = get_system_prompt()
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if "anthropic" not in model_name.lower():
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sample_response_path = os.path.join(os.path.dirname(__file__), 'sample_responses/1.txt')
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with open(sample_response_path, 'r') as file:
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sample_response = file.read()
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default_system_content = default_system_content + "\n\n <sample_assistant_response>" + sample_response + "</sample_assistant_response>"
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if is_agent_builder:
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system_content = get_agent_builder_prompt()
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elif agent_config and agent_config.get('system_prompt'):
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system_content = render_prompt_template(agent_config['system_prompt'].strip())
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else:
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system_content = default_system_content
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if agent_config and (agent_config.get('configured_mcps') or agent_config.get('custom_mcps')) and mcp_wrapper_instance and mcp_wrapper_instance._initialized:
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mcp_info = "\n\n--- MCP Tools Available ---\n"
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mcp_info += "You have access to external MCP (Model Context Protocol) server tools.\n"
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mcp_info += "MCP tools can be called directly using their native function names in the standard function calling format:\n"
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mcp_info += '<function_calls>\n'
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mcp_info += '<invoke name="{tool_name}">\n'
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mcp_info += '<parameter name="param1">value1</parameter>\n'
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mcp_info += '<parameter name="param2">value2</parameter>\n'
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mcp_info += '</invoke>\n'
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mcp_info += '</function_calls>\n\n'
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mcp_info += "Available MCP tools:\n"
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try:
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registered_schemas = mcp_wrapper_instance.get_schemas()
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for method_name, schema_list in registered_schemas.items():
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for schema in schema_list:
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if schema.schema_type == SchemaType.OPENAPI:
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func_info = schema.schema.get('function', {})
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description = func_info.get('description', 'No description available')
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mcp_info += f"- **{method_name}**: {description}\n"
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params = func_info.get('parameters', {})
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props = params.get('properties', {})
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if props:
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mcp_info += f" Parameters: {', '.join(props.keys())}\n"
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except Exception as e:
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logger.error(f"Error listing MCP tools: {e}")
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mcp_info += "- Error loading MCP tool list\n"
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mcp_info += "\n🚨 CRITICAL MCP TOOL RESULT INSTRUCTIONS 🚨\n"
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mcp_info += "When you use ANY MCP (Model Context Protocol) tools:\n"
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mcp_info += "1. ALWAYS read and use the EXACT results returned by the MCP tool\n"
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mcp_info += "2. For search tools: ONLY cite URLs, sources, and information from the actual search results\n"
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mcp_info += "3. For any tool: Base your response entirely on the tool's output - do NOT add external information\n"
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mcp_info += "4. DO NOT fabricate, invent, hallucinate, or make up any sources, URLs, or data\n"
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mcp_info += "5. If you need more information, call the MCP tool again with different parameters\n"
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mcp_info += "6. When writing reports/summaries: Reference ONLY the data from MCP tool results\n"
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mcp_info += "7. If the MCP tool doesn't return enough information, explicitly state this limitation\n"
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mcp_info += "8. Always double-check that every fact, URL, and reference comes from the MCP tool output\n"
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mcp_info += "\nIMPORTANT: MCP tool results are your PRIMARY and ONLY source of truth for external data!\n"
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mcp_info += "NEVER supplement MCP results with your training data or make assumptions beyond what the tools provide.\n"
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system_content += mcp_info
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now = datetime.datetime.now(datetime.timezone.utc)
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datetime_info = f"\n\n=== CURRENT DATE/TIME INFORMATION ===\n"
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datetime_info += f"Today's date: {now.strftime('%A, %B %d, %Y')}\n"
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datetime_info += f"Current UTC time: {now.strftime('%H:%M:%S UTC')}\n"
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datetime_info += f"Current year: {now.strftime('%Y')}\n"
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datetime_info += f"Current month: {now.strftime('%B')}\n"
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datetime_info += f"Current day: {now.strftime('%A')}\n"
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datetime_info += "Use this information for any time-sensitive tasks, research, or when current date/time context is needed.\n"
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system_content += datetime_info
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return {"role": "system", "content": system_content}
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class MessageManager:
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def __init__(self, client, thread_id: str, model_name: str, trace: Optional[StatefulTraceClient]):
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self.client = client
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self.thread_id = thread_id
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self.model_name = model_name
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self.trace = trace
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async def build_temporary_message(self) -> Optional[dict]:
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temp_message_content_list = []
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latest_browser_state_msg = await self.client.table('messages').select('*').eq('thread_id', self.thread_id).eq('type', 'browser_state').order('created_at', desc=True).limit(1).execute()
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if latest_browser_state_msg.data and len(latest_browser_state_msg.data) > 0:
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try:
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browser_content = latest_browser_state_msg.data[0]["content"]
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if isinstance(browser_content, str):
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browser_content = json.loads(browser_content)
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screenshot_base64 = browser_content.get("screenshot_base64")
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screenshot_url = browser_content.get("image_url")
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browser_state_text = browser_content.copy()
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browser_state_text.pop('screenshot_base64', None)
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browser_state_text.pop('image_url', None)
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if browser_state_text:
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temp_message_content_list.append({
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"type": "text",
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"text": f"The following is the current state of the browser:\n{json.dumps(browser_state_text, indent=2)}"
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})
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if 'gemini' in self.model_name.lower() or 'anthropic' in self.model_name.lower() or 'openai' in self.model_name.lower():
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if screenshot_url:
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temp_message_content_list.append({
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"type": "image_url",
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"image_url": {
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"url": screenshot_url,
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"format": "image/jpeg"
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}
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})
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elif screenshot_base64:
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temp_message_content_list.append({
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"type": "image_url",
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"image_url": {
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"url": f"data:image/jpeg;base64,{screenshot_base64}",
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}
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})
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except Exception as e:
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logger.error(f"Error parsing browser state: {e}")
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latest_image_context_msg = await self.client.table('messages').select('*').eq('thread_id', self.thread_id).eq('type', 'image_context').order('created_at', desc=True).limit(1).execute()
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if latest_image_context_msg.data and len(latest_image_context_msg.data) > 0:
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try:
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image_context_content = latest_image_context_msg.data[0]["content"] if isinstance(latest_image_context_msg.data[0]["content"], dict) else json.loads(latest_image_context_msg.data[0]["content"])
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base64_image = image_context_content.get("base64")
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mime_type = image_context_content.get("mime_type")
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file_path = image_context_content.get("file_path", "unknown file")
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if base64_image and mime_type:
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temp_message_content_list.append({
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"type": "text",
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|
"text": f"Here is the image you requested to see: '{file_path}'"
|
|
})
|
|
temp_message_content_list.append({
|
|
"type": "image_url",
|
|
"image_url": {
|
|
"url": f"data:{mime_type};base64,{base64_image}",
|
|
}
|
|
})
|
|
|
|
await self.client.table('messages').delete().eq('message_id', latest_image_context_msg.data[0]["message_id"]).execute()
|
|
except Exception as e:
|
|
logger.error(f"Error parsing image context: {e}")
|
|
|
|
if temp_message_content_list:
|
|
return {"role": "user", "content": temp_message_content_list}
|
|
return None
|
|
|
|
|
|
class AgentRunner:
|
|
def __init__(self, config: AgentConfig):
|
|
self.config = config
|
|
|
|
async def setup(self):
|
|
if not self.config.trace:
|
|
self.config.trace = langfuse.trace(name="run_agent", session_id=self.config.thread_id, metadata={"project_id": self.config.project_id})
|
|
|
|
self.thread_manager = ThreadManager(
|
|
trace=self.config.trace,
|
|
is_agent_builder=self.config.is_agent_builder or False,
|
|
target_agent_id=self.config.target_agent_id,
|
|
agent_config=self.config.agent_config
|
|
)
|
|
|
|
self.client = await self.thread_manager.db.client
|
|
self.account_id = await get_account_id_from_thread(self.client, self.config.thread_id)
|
|
if not self.account_id:
|
|
raise ValueError("Could not determine account ID for thread")
|
|
|
|
project = await self.client.table('projects').select('*').eq('project_id', self.config.project_id).execute()
|
|
if not project.data or len(project.data) == 0:
|
|
raise ValueError(f"Project {self.config.project_id} not found")
|
|
|
|
project_data = project.data[0]
|
|
sandbox_info = project_data.get('sandbox', {})
|
|
if not sandbox_info.get('id'):
|
|
# Sandbox is created lazily by tools when required. Do not fail setup
|
|
# if no sandbox is present — tools will call `_ensure_sandbox()`
|
|
# which will create and persist the sandbox metadata when needed.
|
|
logger.info(f"No sandbox found for project {self.config.project_id}; will create lazily when needed")
|
|
|
|
async def setup_tools(self):
|
|
tool_manager = ToolManager(self.thread_manager, self.config.project_id, self.config.thread_id)
|
|
|
|
if self.config.agent_config and self.config.agent_config.get('is_suna_default', False):
|
|
suna_agent_id = self.config.agent_config['agent_id']
|
|
tool_manager.register_agent_builder_tools(suna_agent_id)
|
|
|
|
if self.config.is_agent_builder:
|
|
tool_manager.register_agent_builder_tools(self.config.target_agent_id)
|
|
|
|
enabled_tools = None
|
|
if self.config.agent_config and 'agentpress_tools' in self.config.agent_config:
|
|
raw_tools = self.config.agent_config['agentpress_tools']
|
|
|
|
if isinstance(raw_tools, dict):
|
|
if self.config.agent_config.get('is_suna_default', False) and not raw_tools:
|
|
enabled_tools = None
|
|
else:
|
|
enabled_tools = raw_tools
|
|
else:
|
|
enabled_tools = None
|
|
|
|
if enabled_tools is None:
|
|
tool_manager.register_all_tools()
|
|
else:
|
|
if not isinstance(enabled_tools, dict):
|
|
enabled_tools = {}
|
|
tool_manager.register_custom_tools(enabled_tools)
|
|
|
|
async def setup_mcp_tools(self) -> Optional[MCPToolWrapper]:
|
|
if not self.config.agent_config:
|
|
return None
|
|
|
|
mcp_manager = MCPManager(self.thread_manager, self.account_id)
|
|
return await mcp_manager.register_mcp_tools(self.config.agent_config)
|
|
|
|
def get_max_tokens(self) -> Optional[int]:
|
|
if "sonnet" in self.config.model_name.lower():
|
|
return 8192
|
|
elif "gpt-4" in self.config.model_name.lower():
|
|
return 4096
|
|
elif "gemini-2.5-pro" in self.config.model_name.lower():
|
|
return 64000
|
|
elif "kimi-k2" in self.config.model_name.lower():
|
|
return 8192
|
|
return None
|
|
|
|
async def run(self) -> AsyncGenerator[Dict[str, Any], None]:
|
|
await self.setup()
|
|
await self.setup_tools()
|
|
mcp_wrapper_instance = await self.setup_mcp_tools()
|
|
|
|
system_message = await PromptManager.build_system_prompt(
|
|
self.config.model_name, self.config.agent_config,
|
|
self.config.is_agent_builder, self.config.thread_id,
|
|
mcp_wrapper_instance
|
|
)
|
|
|
|
iteration_count = 0
|
|
continue_execution = True
|
|
|
|
latest_user_message = await self.client.table('messages').select('*').eq('thread_id', self.config.thread_id).eq('type', 'user').order('created_at', desc=True).limit(1).execute()
|
|
if latest_user_message.data and len(latest_user_message.data) > 0:
|
|
data = latest_user_message.data[0]['content']
|
|
if isinstance(data, str):
|
|
data = json.loads(data)
|
|
if self.config.trace:
|
|
self.config.trace.update(input=data['content'])
|
|
|
|
message_manager = MessageManager(self.client, self.config.thread_id, self.config.model_name, self.config.trace)
|
|
|
|
while continue_execution and iteration_count < self.config.max_iterations:
|
|
iteration_count += 1
|
|
|
|
can_run, message, subscription = await check_billing_status(self.client, self.account_id)
|
|
if not can_run:
|
|
error_msg = f"Billing limit reached: {message}"
|
|
yield {
|
|
"type": "status",
|
|
"status": "stopped",
|
|
"message": error_msg
|
|
}
|
|
break
|
|
|
|
latest_message = await self.client.table('messages').select('*').eq('thread_id', self.config.thread_id).in_('type', ['assistant', 'tool', 'user']).order('created_at', desc=True).limit(1).execute()
|
|
if latest_message.data and len(latest_message.data) > 0:
|
|
message_type = latest_message.data[0].get('type')
|
|
if message_type == 'assistant':
|
|
continue_execution = False
|
|
break
|
|
|
|
temporary_message = await message_manager.build_temporary_message()
|
|
max_tokens = self.get_max_tokens()
|
|
|
|
generation = self.config.trace.generation(name="thread_manager.run_thread") if self.config.trace else None
|
|
try:
|
|
response = await self.thread_manager.run_thread(
|
|
thread_id=self.config.thread_id,
|
|
system_prompt=system_message,
|
|
stream=self.config.stream,
|
|
llm_model=self.config.model_name,
|
|
llm_temperature=0,
|
|
llm_max_tokens=max_tokens,
|
|
tool_choice="auto",
|
|
max_xml_tool_calls=1,
|
|
temporary_message=temporary_message,
|
|
processor_config=ProcessorConfig(
|
|
xml_tool_calling=True,
|
|
native_tool_calling=False,
|
|
execute_tools=True,
|
|
execute_on_stream=True,
|
|
tool_execution_strategy="parallel",
|
|
xml_adding_strategy="user_message"
|
|
),
|
|
native_max_auto_continues=self.config.native_max_auto_continues,
|
|
include_xml_examples=True,
|
|
enable_thinking=self.config.enable_thinking,
|
|
reasoning_effort=self.config.reasoning_effort,
|
|
enable_context_manager=self.config.enable_context_manager,
|
|
generation=generation
|
|
)
|
|
|
|
if isinstance(response, dict) and "status" in response and response["status"] == "error":
|
|
yield response
|
|
break
|
|
|
|
last_tool_call = None
|
|
agent_should_terminate = False
|
|
error_detected = False
|
|
full_response = ""
|
|
|
|
try:
|
|
if hasattr(response, '__aiter__') and not isinstance(response, dict):
|
|
async for chunk in response:
|
|
if isinstance(chunk, dict) and chunk.get('type') == 'status' and chunk.get('status') == 'error':
|
|
error_detected = True
|
|
yield chunk
|
|
continue
|
|
|
|
if chunk.get('type') == 'status':
|
|
try:
|
|
metadata = chunk.get('metadata', {})
|
|
if isinstance(metadata, str):
|
|
metadata = json.loads(metadata)
|
|
|
|
if metadata.get('agent_should_terminate'):
|
|
agent_should_terminate = True
|
|
|
|
content = chunk.get('content', {})
|
|
if isinstance(content, str):
|
|
content = json.loads(content)
|
|
|
|
if content.get('function_name'):
|
|
last_tool_call = content['function_name']
|
|
elif content.get('xml_tag_name'):
|
|
last_tool_call = content['xml_tag_name']
|
|
|
|
except Exception:
|
|
pass
|
|
|
|
if chunk.get('type') == 'assistant' and 'content' in chunk:
|
|
try:
|
|
content = chunk.get('content', '{}')
|
|
if isinstance(content, str):
|
|
assistant_content_json = json.loads(content)
|
|
else:
|
|
assistant_content_json = content
|
|
|
|
assistant_text = assistant_content_json.get('content', '')
|
|
full_response += assistant_text
|
|
if isinstance(assistant_text, str):
|
|
if '</ask>' in assistant_text or '</complete>' in assistant_text or '</web-browser-takeover>' in assistant_text:
|
|
if '</ask>' in assistant_text:
|
|
xml_tool = 'ask'
|
|
elif '</complete>' in assistant_text:
|
|
xml_tool = 'complete'
|
|
elif '</web-browser-takeover>' in assistant_text:
|
|
xml_tool = 'web-browser-takeover'
|
|
|
|
last_tool_call = xml_tool
|
|
|
|
except json.JSONDecodeError:
|
|
pass
|
|
except Exception:
|
|
pass
|
|
|
|
yield chunk
|
|
else:
|
|
error_detected = True
|
|
|
|
if error_detected:
|
|
if generation:
|
|
generation.end(output=full_response, status_message="error_detected", level="ERROR")
|
|
break
|
|
|
|
if agent_should_terminate or last_tool_call in ['ask', 'complete', 'web-browser-takeover']:
|
|
if generation:
|
|
generation.end(output=full_response, status_message="agent_stopped")
|
|
continue_execution = False
|
|
|
|
except Exception as e:
|
|
error_msg = f"Error during response streaming: {str(e)}"
|
|
if generation:
|
|
generation.end(output=full_response, status_message=error_msg, level="ERROR")
|
|
yield {
|
|
"type": "status",
|
|
"status": "error",
|
|
"message": error_msg
|
|
}
|
|
break
|
|
|
|
except Exception as e:
|
|
error_msg = f"Error running thread: {str(e)}"
|
|
yield {
|
|
"type": "status",
|
|
"status": "error",
|
|
"message": error_msg
|
|
}
|
|
break
|
|
|
|
if generation:
|
|
generation.end(output=full_response)
|
|
|
|
asyncio.create_task(asyncio.to_thread(lambda: langfuse.flush()))
|
|
|
|
|
|
async def run_agent(
|
|
thread_id: str,
|
|
project_id: str,
|
|
stream: bool,
|
|
thread_manager: Optional[ThreadManager] = None,
|
|
native_max_auto_continues: int = 25,
|
|
max_iterations: int = 100,
|
|
model_name: str = "openrouter/moonshotai/kimi-k2",
|
|
enable_thinking: Optional[bool] = False,
|
|
reasoning_effort: Optional[str] = 'low',
|
|
enable_context_manager: bool = True,
|
|
agent_config: Optional[dict] = None,
|
|
trace: Optional[StatefulTraceClient] = None,
|
|
is_agent_builder: Optional[bool] = False,
|
|
target_agent_id: Optional[str] = None
|
|
):
|
|
effective_model = model_name
|
|
if model_name == "openrouter/moonshotai/kimi-k2" and agent_config and agent_config.get('model'):
|
|
effective_model = agent_config['model']
|
|
logger.info(f"Using model from agent config: {effective_model} (no user selection)")
|
|
elif model_name != "openrouter/moonshotai/kimi-k2":
|
|
logger.info(f"Using user-selected model: {effective_model}")
|
|
else:
|
|
logger.info(f"Using default model: {effective_model}")
|
|
|
|
config = AgentConfig(
|
|
thread_id=thread_id,
|
|
project_id=project_id,
|
|
stream=stream,
|
|
native_max_auto_continues=native_max_auto_continues,
|
|
max_iterations=max_iterations,
|
|
model_name=effective_model,
|
|
enable_thinking=enable_thinking,
|
|
reasoning_effort=reasoning_effort,
|
|
enable_context_manager=enable_context_manager,
|
|
agent_config=agent_config,
|
|
trace=trace,
|
|
is_agent_builder=is_agent_builder,
|
|
target_agent_id=target_agent_id
|
|
)
|
|
|
|
runner = AgentRunner(config)
|
|
async for chunk in runner.run():
|
|
yield chunk |