yangzheli
59c4a3f0a4
* feat(agent): add update_agent tool for in-chat custom-agent self-updates (#2616) Custom agents had no built-in way to persist updates to their own SOUL.md / config.yaml from a normal chat — `setup_agent` was only bound during the bootstrap flow, so when the user asked the agent to refine its description or personality, the agent would shell out via bash/write_file and the edits landed in a temporary sandbox/tool workspace instead of `{base_dir}/agents/{agent_name}/`. Changes: - New `update_agent` builtin tool with partial-update semantics (only the fields you pass are written) and atomic temp-file + os.replace writes so a failed update never corrupts existing SOUL.md / config.yaml. - Lead agent now binds `update_agent` in the non-bootstrap path whenever `agent_name` is set in the runtime context. Default agent (no agent_name) and bootstrap flow are unchanged. - New `<self_update>` system-prompt section is injected for custom agents, instructing them to use `update_agent` — and explicitly NOT bash / write_file — to persist self-updates. - Tests: 11 new cases in `tests/test_update_agent_tool.py` covering validation (missing/invalid agent_name, unknown agent, no fields), partial updates (soul-only, description-only, skills=[] vs omitted), no-op detection, atomic-write safety, and AgentConfig round-tripping; plus 2 new cases in `tests/test_lead_agent_prompt.py` covering the self-update prompt section. - Docs: updated backend/CLAUDE.md builtin tools list and tools.mdx (en/zh) with the new tool description. * feat(agent): isolate custom agents per user Store custom agent definitions under the effective user, keep legacy agents readable until migration, and cover API/tool/migration behavior with tests. Co-authored-by: Cursor <cursoragent@cursor.com> * feat: consistent write/delete targets & add --user-id to migration --------- Co-authored-by: Cursor <cursoragent@cursor.com>
80 lines
3.0 KiB
Python
80 lines
3.0 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.agents_config import validate_agent_name
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from deerflow.config.paths import get_paths
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from deerflow.runtime.user_context import get_effective_user_id
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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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skills: list[str] | None = None,
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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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skills: Optional list of skill names this agent should use. None means use all enabled skills, empty list means no skills.
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"""
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agent_name: str | None = runtime.context.get("agent_name") if runtime.context else None
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agent_dir = None
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is_new_dir = False
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try:
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agent_name = validate_agent_name(agent_name)
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paths = get_paths()
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if agent_name:
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# Custom agents are persisted under the current user's bucket so
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# different users do not see each other's agents.
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user_id = get_effective_user_id()
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agent_dir = paths.user_agent_dir(user_id, agent_name)
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else:
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# Default agent (no agent_name): SOUL.md lives at the global base dir.
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agent_dir = paths.base_dir
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is_new_dir = not agent_dir.exists()
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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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if skills is not None:
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config_data["skills"] = skills
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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 is_new_dir and agent_dir is not None and agent_dir.exists():
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# Cleanup the custom agent directory only if it was newly created during this call
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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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