30a5846219
* fix: make tool argument behavior discoverable The write_file tool already supported append=false by default with append=true for end-of-file writes, but the parsed docstring did not describe append in the model-facing schema. This records the overwrite default and append path in the tool description, adds resilient schema regression coverage, and keeps backend sandbox docs aligned. The regression now also checks that every public parameter in the existing tool schema test matrix has a description. Enabling docstring parsing on setup_agent and update_agent fills the two existing gaps with their existing Args docs instead of duplicating descriptions elsewhere. Constraint: Issue #2831 asks for a small docstring/schema discoverability fix without changing runtime file-writing behavior Rejected: Changing write_file defaults | would alter existing overwrite semantics and broaden the fix beyond schema discoverability Rejected: Exact phrase assertions | too brittle for future docstring rewording while testing the same behavior Confidence: high Scope-risk: narrow Directive: Keep model-facing tool parameters documented through parsed docstrings or equivalent schema descriptions Tested: cd backend && uv run pytest tests/test_setup_agent_tool.py tests/test_update_agent_tool.py tests/test_tool_args_schema_no_pydantic_warning.py tests/test_sandbox_tools_security.py::test_str_replace_and_append_on_same_path_should_preserve_both_updates -q Tested: cd backend && uv run ruff check packages/harness/deerflow/sandbox/tools.py packages/harness/deerflow/tools/builtins/setup_agent_tool.py packages/harness/deerflow/tools/builtins/update_agent_tool.py tests/test_tool_args_schema_no_pydantic_warning.py Not-tested: Full backend test suite Co-authored-by: OmX <omx@oh-my-codex.dev> * Fix the lint error --------- Co-authored-by: OmX <omx@oh-my-codex.dev> Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
87 lines
3.3 KiB
Python
87 lines
3.3 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.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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from deerflow.tools.types import Runtime
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logger = logging.getLogger(__name__)
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def _get_runtime_user_id(runtime: Runtime) -> str:
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context_user_id = runtime.context.get("user_id") if runtime.context else None
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if context_user_id:
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return str(context_user_id)
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return get_effective_user_id()
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@tool(parse_docstring=True)
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def setup_agent(
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soul: str,
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description: str,
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runtime: Runtime,
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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_runtime_user_id(runtime)
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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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