greatmengqi
edf345cd72
- Freeze all config models (AppConfig + 15 sub-configs) with frozen=True - Purify from_file() — remove 9 load_*_from_dict() side-effect calls - Replace mtime/reload/push/pop machinery with single ContextVar + init_app_config() - Delete 10 sub-module globals and their getters/setters/loaders - Migrate 50+ consumers from get_*_config() to get_app_config().xxx - Expand DeerFlowContext: app_config + thread_id + agent_name (frozen dataclass) - Wire into Gateway runtime (worker.py) and DeerFlowClient via context= parameter - Remove sandbox_id from runtime.context — flows through ThreadState.sandbox only - Middleware/tools access runtime.context directly via Runtime[DeerFlowContext] generic - resolve_context() retained at server entry points for LangGraph Server fallback
63 lines
2.1 KiB
Python
63 lines
2.1 KiB
Python
import logging
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import yaml
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from langchain_core.messages import ToolMessage
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from langchain_core.tools import tool
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from langgraph.prebuilt import ToolRuntime
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from langgraph.types import Command
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from deerflow.config.paths import get_paths
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logger = logging.getLogger(__name__)
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@tool
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def setup_agent(
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soul: str,
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description: str,
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runtime: ToolRuntime,
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) -> Command:
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"""Setup the custom DeerFlow agent.
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Args:
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soul: Full SOUL.md content defining the agent's personality and behavior.
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description: One-line description of what the agent does.
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"""
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agent_name: str | None = runtime.context.agent_name
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try:
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paths = get_paths()
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agent_dir = paths.agent_dir(agent_name) if agent_name else paths.base_dir
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agent_dir.mkdir(parents=True, exist_ok=True)
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if agent_name:
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# If agent_name is provided, we are creating a custom agent in the agents/ directory
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config_data: dict = {"name": agent_name}
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if description:
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config_data["description"] = description
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config_file = agent_dir / "config.yaml"
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with open(config_file, "w", encoding="utf-8") as f:
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yaml.dump(config_data, f, default_flow_style=False, allow_unicode=True)
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soul_file = agent_dir / "SOUL.md"
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soul_file.write_text(soul, encoding="utf-8")
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logger.info(f"[agent_creator] Created agent '{agent_name}' at {agent_dir}")
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return Command(
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update={
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"created_agent_name": agent_name,
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"messages": [ToolMessage(content=f"Agent '{agent_name}' created successfully!", tool_call_id=runtime.tool_call_id)],
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}
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)
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except Exception as e:
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import shutil
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if agent_name and agent_dir.exists():
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# Cleanup the custom agent directory only if it was created but an error occurred during setup
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shutil.rmtree(agent_dir)
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logger.error(f"[agent_creator] Failed to create agent '{agent_name}': {e}", exc_info=True)
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return Command(update={"messages": [ToolMessage(content=f"Error: {e}", tool_call_id=runtime.tool_call_id)]})
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