mirror of
https://github.com/langbot-app/LangBot.git
synced 2026-06-22 13:34:24 +00:00
huanghuoguoguo
a020ca680f
* fix(tools): harden agent runner tool runtimes * fix(tools): bootstrap Python workspaces with available interpreter * fix(tools): clear stale Python workspace env locks * fix(tools): decouple runtime from agent runner * test(tools): cover runtime hardening edge cases * fix(tools): support binary workspace file chunks
1309 lines
53 KiB
Python
1309 lines
53 KiB
Python
from __future__ import annotations
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import base64
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import json
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import os
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import langbot_plugin.api.entities.builtin.resource.tool as resource_tool
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from langbot_plugin.api.entities.events import pipeline_query
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from .. import loader
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from ..errors import ToolNotFoundError
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from .availability import is_box_backend_available
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from . import skill as skill_loader
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EXEC_TOOL_NAME = 'exec'
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READ_TOOL_NAME = 'read'
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WRITE_TOOL_NAME = 'write'
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EDIT_TOOL_NAME = 'edit'
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GLOB_TOOL_NAME = 'glob'
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GREP_TOOL_NAME = 'grep'
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_ALL_TOOL_NAMES = {EXEC_TOOL_NAME, READ_TOOL_NAME, WRITE_TOOL_NAME, EDIT_TOOL_NAME, GLOB_TOOL_NAME, GREP_TOOL_NAME}
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# Skip these dirs during grep walk to avoid noise
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_SKIP_DIRS = {'.git', 'node_modules', '__pycache__', '.venv', 'venv', '.tox', 'dist', 'build'}
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_DEFAULT_READ_MAX_LINES = 2000
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_MAX_READ_MAX_LINES = 10000
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_DEFAULT_TOOL_RESULT_MAX_BYTES = 50 * 1024
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_BOX_FILE_SCRIPT_MAX_BYTES = 2048
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_GLOB_MAX_MATCHES = 100
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_GREP_MAX_MATCHES = 200
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_GREP_MAX_FILES = 5000
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_GREP_MAX_LINE_CHARS = 500
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class NativeToolLoader(loader.ToolLoader):
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def __init__(self, ap):
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super().__init__(ap)
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self._tools: list[resource_tool.LLMTool] | None = None
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self._backend_available: bool | None = None
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async def initialize(self):
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"""Check if backend is truly available at startup."""
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self._backend_available = await self._check_backend_available()
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if self._backend_available:
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self.ap.logger.info('Native sandbox tools (exec/read/write/edit/glob/grep) are available.')
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else:
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self.ap.logger.warning(
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'Native sandbox tools (exec/read/write/edit/glob/grep) are NOT available. '
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'No sandbox backend (Docker/nsjail/E2B) is ready. '
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'The LLM will not have access to code execution or file operation tools.'
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)
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async def _check_backend_available(self) -> bool:
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"""Check if the box backend is truly available (not just the runtime)."""
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return await is_box_backend_available(self.ap)
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async def get_tools(self, bound_plugins: list[str] | None = None) -> list[resource_tool.LLMTool]:
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if not self._is_sandbox_available():
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return []
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if self._tools is None:
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self._tools = [
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self._build_exec_tool(),
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self._build_read_tool(),
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self._build_write_tool(),
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self._build_edit_tool(),
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self._build_glob_tool(),
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self._build_grep_tool(),
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]
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return list(self._tools)
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async def has_tool(self, name: str) -> bool:
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return name in _ALL_TOOL_NAMES and self._is_sandbox_available()
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async def invoke_tool(self, name: str, parameters: dict, query: pipeline_query.Query):
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if name == EXEC_TOOL_NAME:
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self.ap.logger.info(
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'exec tool invoked: '
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f'query_id={query.query_id} '
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f'parameters={json.dumps(self._summarize_parameters(parameters), ensure_ascii=False)}'
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)
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return await self._invoke_exec(parameters, query)
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if name == READ_TOOL_NAME:
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return await self._invoke_read(parameters, query)
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if name == WRITE_TOOL_NAME:
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return await self._invoke_write(parameters, query)
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if name == EDIT_TOOL_NAME:
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return await self._invoke_edit(parameters, query)
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if name == GLOB_TOOL_NAME:
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return await self._invoke_glob(parameters, query)
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if name == GREP_TOOL_NAME:
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return await self._invoke_grep(parameters, query)
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raise ToolNotFoundError(name)
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async def shutdown(self):
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pass
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async def _invoke_exec(self, parameters: dict, query: pipeline_query.Query) -> dict:
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command = str(parameters['command'])
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workdir = str(parameters.get('workdir', '/workspace') or '/workspace')
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# Validate that skill references target activated skills.
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selected_skill, _ = skill_loader.resolve_virtual_skill_path(
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self.ap,
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query,
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workdir,
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include_visible=False,
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include_activated=True,
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)
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referenced_skill_names = skill_loader.find_referenced_skill_names(command)
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if selected_skill is None and referenced_skill_names:
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if len(referenced_skill_names) > 1:
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raise ValueError('exec can target at most one activated skill package per call.')
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selected_skill = skill_loader.get_activated_skill(query, referenced_skill_names[0])
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if selected_skill is None:
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raise ValueError(
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f'Skill "{referenced_skill_names[0]}" must be activated before exec can run in its package.'
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)
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if selected_skill is not None:
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selected_skill_name = str(selected_skill.get('name', '') or '')
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if referenced_skill_names and any(name != selected_skill_name for name in referenced_skill_names):
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raise ValueError('exec can reference files from only one activated skill package per call.')
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package_root = str(selected_skill.get('package_root', '') or '').strip()
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if not package_root:
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raise ValueError(f'Activated skill "{selected_skill_name}" has no package_root.')
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# Wrap command with Python venv bootstrap if the skill has a Python project.
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# The venv is created inside the skill's mount path.
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skill_mount = f'/workspace/.skills/{selected_skill_name}'
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if skill_loader.should_prepare_skill_python_env(package_root):
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parameters = dict(parameters)
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parameters['command'] = skill_loader.wrap_skill_command_with_python_env(command, mount_path=skill_mount)
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# All exec calls (with or without skills) go through the same container
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# via execute_tool. Skills are mounted at /workspace/.skills/{name}/
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# via extra_mounts built by BoxService.
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result = await self.ap.box_service.execute_tool(parameters, query)
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result = self._normalize_exec_result(result)
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if selected_skill is not None:
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self._refresh_skill_from_disk(selected_skill)
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return result
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def _resolve_host_path(
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self,
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query: pipeline_query.Query,
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sandbox_path: str,
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*,
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include_visible: bool,
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include_activated: bool,
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) -> tuple[str, dict | None]:
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selected_skill, rewritten_path = skill_loader.resolve_virtual_skill_path(
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self.ap,
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query,
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sandbox_path,
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include_visible=include_visible,
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include_activated=include_activated,
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)
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box_service = self.ap.box_service
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host_root = selected_skill.get('package_root') if selected_skill is not None else box_service.default_workspace
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if not host_root:
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raise ValueError('No host workspace configured for file operations.')
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mount_path = '/workspace'
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if not rewritten_path.startswith(mount_path):
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raise ValueError(f'Path must be under {mount_path}.')
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relative = rewritten_path[len(mount_path) :].lstrip('/')
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host_path = os.path.realpath(os.path.join(host_root, relative))
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host_root = os.path.realpath(host_root)
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if not (host_path == host_root or host_path.startswith(host_root + os.sep)):
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raise ValueError('Path escapes the workspace boundary.')
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return host_path, selected_skill
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def _resolve_skill_relative_path(
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self,
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query: pipeline_query.Query,
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sandbox_path: str,
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*,
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include_visible: bool,
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include_activated: bool,
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) -> tuple[dict, str] | None:
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selected_skill, rewritten_path = skill_loader.resolve_virtual_skill_path(
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self.ap,
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query,
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sandbox_path,
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include_visible=include_visible,
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include_activated=include_activated,
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)
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if selected_skill is None:
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return None
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mount_path = '/workspace'
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if not rewritten_path.startswith(mount_path):
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raise ValueError(f'Path must be under {mount_path}.')
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relative = rewritten_path[len(mount_path) :].lstrip('/') or '.'
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return selected_skill, relative
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def _should_use_box_workspace_files(self, selected_skill: dict | None) -> bool:
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if selected_skill is not None:
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return False
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box_service = getattr(self.ap, 'box_service', None)
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if box_service is None or not hasattr(box_service, 'execute_tool'):
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return False
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default_workspace = getattr(box_service, 'default_workspace', None)
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return bool(default_workspace and not os.path.isdir(os.path.realpath(default_workspace)))
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async def _run_workspace_file_script(self, script: str, query: pipeline_query.Query) -> dict:
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result = await self.ap.box_service.execute_tool(
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{
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'command': f"python - <<'PY'\n{script}\nPY",
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'timeout_sec': 30,
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},
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query,
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)
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if not result.get('ok'):
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return {'ok': False, 'error': result.get('stderr') or result.get('stdout') or 'Box execution failed'}
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stdout = str(result.get('stdout') or '').strip()
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try:
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return json.loads(stdout.splitlines()[-1])
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except Exception:
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return {'ok': False, 'error': stdout or 'Box file operation returned no result'}
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async def _read_workspace_via_box(self, path: str, parameters: dict, query: pipeline_query.Query) -> dict:
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offset = self._positive_int(parameters.get('offset'), default=1)
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byte_offset = self._non_negative_int(parameters.get('byte_offset'), default=0)
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max_lines = self._positive_int(
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parameters.get('limit'),
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default=_DEFAULT_READ_MAX_LINES,
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max_value=_MAX_READ_MAX_LINES,
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)
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# Box file fallback returns through exec stdout, which is already capped
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# by BoxService. Keep this payload small enough to remain valid JSON.
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max_bytes = min(
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self._positive_int(parameters.get('max_bytes'), default=_DEFAULT_TOOL_RESULT_MAX_BYTES),
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_BOX_FILE_SCRIPT_MAX_BYTES,
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)
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encoding = self._read_encoding(parameters)
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script = f"""
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import base64, json, os
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path = {json.dumps(path)}
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offset = {offset}
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byte_offset = {byte_offset}
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max_lines = {max_lines}
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max_bytes = {max_bytes}
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encoding = {json.dumps(encoding)}
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if not path.startswith('/workspace'):
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print(json.dumps({{'ok': False, 'error': 'Path must be under /workspace.'}}))
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elif not os.path.exists(path):
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print(json.dumps({{'ok': False, 'error': f'File not found: {{path}}'}}))
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elif os.path.isdir(path):
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entries = sorted(os.listdir(path))
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content = '\\n'.join(entries)
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print(json.dumps({{'ok': True, 'content': content, 'is_directory': True, 'total': len(entries), 'truncated': False}}))
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elif encoding == 'base64':
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size_bytes = os.path.getsize(path)
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with open(path, 'rb') as f:
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f.seek(byte_offset)
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data = f.read(max_bytes + 1)
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chunk = data[:max_bytes]
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has_more = len(data) > max_bytes
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print(json.dumps({{
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'ok': True,
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'content': base64.b64encode(chunk).decode('ascii'),
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'encoding': 'base64',
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'byte_offset': byte_offset,
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'length': len(chunk),
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'size_bytes': size_bytes,
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'has_more': has_more,
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'next_byte_offset': byte_offset + len(chunk) if has_more else None,
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'max_bytes': max_bytes,
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}}))
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else:
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lines = []
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output_bytes = 0
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end_line = offset - 1
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truncated = False
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next_offset = None
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with open(path, 'r', encoding='utf-8', errors='replace') as f:
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for line_number, line in enumerate(f, 1):
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if line_number < offset:
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continue
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if len(lines) >= max_lines:
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truncated = True
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next_offset = line_number
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break
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line_bytes = len(line.encode('utf-8'))
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if output_bytes + line_bytes > max_bytes:
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truncated = True
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next_offset = line_number
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break
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lines.append(line.rstrip('\\n'))
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output_bytes += line_bytes
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end_line = line_number
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print(json.dumps({{
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'ok': True,
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'content': '\\n'.join(lines),
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'truncated': truncated,
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'start_line': offset,
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'end_line': end_line,
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'next_offset': next_offset,
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'max_lines': max_lines,
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'max_bytes': max_bytes,
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}}))
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""".strip()
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return await self._run_workspace_file_script(script, query)
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async def _write_workspace_via_box(
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self,
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path: str,
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content: str,
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parameters: dict,
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query: pipeline_query.Query,
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) -> dict:
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encoding, mode = self._write_options(parameters)
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script = f"""
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import base64, json, os
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path = {json.dumps(path)}
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content = {json.dumps(content)}
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encoding = {json.dumps(encoding)}
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mode = {json.dumps(mode)}
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if not path.startswith('/workspace'):
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print(json.dumps({{'ok': False, 'error': 'Path must be under /workspace.'}}))
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else:
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os.makedirs(os.path.dirname(path) or '/workspace', exist_ok=True)
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if encoding == 'base64':
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try:
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data = base64.b64decode(content, validate=True)
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except Exception as exc:
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print(json.dumps({{'ok': False, 'error': f'invalid base64 content: {{exc}}'}}))
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else:
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with open(path, 'ab' if mode == 'append' else 'wb') as f:
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f.write(data)
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print(json.dumps({{'ok': True, 'path': path}}))
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else:
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with open(path, 'a' if mode == 'append' else 'w', encoding='utf-8') as f:
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f.write(content)
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print(json.dumps({{'ok': True, 'path': path}}))
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""".strip()
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return await self._run_workspace_file_script(script, query)
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async def _edit_workspace_via_box(
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self,
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path: str,
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old_string: str,
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new_string: str,
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query: pipeline_query.Query,
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) -> dict:
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script = f"""
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import json, os
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path = {json.dumps(path)}
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old_string = {json.dumps(old_string)}
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new_string = {json.dumps(new_string)}
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if not path.startswith('/workspace'):
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print(json.dumps({{'ok': False, 'error': 'Path must be under /workspace.'}}))
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elif not os.path.isfile(path):
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print(json.dumps({{'ok': False, 'error': f'File not found: {{path}}'}}))
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else:
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with open(path, 'r', encoding='utf-8', errors='replace') as f:
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content = f.read()
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count = content.count(old_string)
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if count == 0:
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print(json.dumps({{'ok': False, 'error': 'old_string not found in file.'}}))
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elif count > 1:
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print(json.dumps({{'ok': False, 'error': f'old_string matches {{count}} locations; provide a more unique string.'}}))
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else:
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with open(path, 'w', encoding='utf-8') as f:
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f.write(content.replace(old_string, new_string, 1))
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print(json.dumps({{'ok': True, 'path': path}}))
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""".strip()
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return await self._run_workspace_file_script(script, query)
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async def _glob_workspace_via_box(self, path: str, pattern: str, query: pipeline_query.Query) -> dict:
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script = f"""
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import json, os
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from pathlib import Path
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path = {json.dumps(path)}
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pattern = {json.dumps(pattern)}
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skip_dirs = {json.dumps(sorted(_SKIP_DIRS))}
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if not path.startswith('/workspace'):
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print(json.dumps({{'ok': False, 'error': 'Path must be under /workspace.'}}))
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elif not os.path.isdir(path):
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print(json.dumps({{'ok': False, 'error': f'Path is not a directory: {{path}}'}}))
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else:
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base = Path(path)
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hits = [
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item for item in base.rglob(pattern)
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if not any(part in skip_dirs for part in item.parts)
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]
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hits.sort(key=lambda item: item.stat().st_mtime if item.exists() else 0, reverse=True)
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shown = hits[:{_GLOB_MAX_MATCHES}]
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matches = []
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output_bytes = 0
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truncated_by_bytes = False
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for item in shown:
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rel = os.path.relpath(str(item), path)
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sandbox_path = os.path.join(path, rel).replace(os.sep, '/')
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entry_bytes = len(sandbox_path.encode('utf-8')) + (1 if matches else 0)
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if output_bytes + entry_bytes > {_DEFAULT_TOOL_RESULT_MAX_BYTES}:
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truncated_by_bytes = True
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break
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matches.append(sandbox_path)
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output_bytes += entry_bytes
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print(json.dumps({{
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'ok': True,
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'matches': matches,
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'preview': '\\n'.join(matches),
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'total': len(hits),
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'truncated': len(hits) > len(matches) or truncated_by_bytes,
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'truncated_by': 'bytes' if truncated_by_bytes else ('matches' if len(hits) > len(matches) else None),
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}}))
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""".strip()
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return await self._run_workspace_file_script(script, query)
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|
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async def _grep_workspace_via_box(
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self,
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path: str,
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pattern: str,
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include: str | None,
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query: pipeline_query.Query,
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) -> dict:
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script = f"""
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import json, os, re
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from pathlib import Path
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path = {json.dumps(path)}
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pattern = {json.dumps(pattern)}
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include = {json.dumps(include)}
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skip_dirs = {json.dumps(sorted(_SKIP_DIRS))}
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try:
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regex = re.compile(pattern)
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except re.error as exc:
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print(json.dumps({{'ok': False, 'error': f'Invalid regex: {{exc}}'}}))
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else:
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if not path.startswith('/workspace'):
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print(json.dumps({{'ok': False, 'error': 'Path must be under /workspace.'}}))
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elif not os.path.exists(path):
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print(json.dumps({{'ok': False, 'error': f'Path not found: {{path}}'}}))
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|
else:
|
|
base = Path(path)
|
|
if base.is_file():
|
|
files = [base]
|
|
else:
|
|
files = []
|
|
for item in base.rglob(include or '*'):
|
|
if any(part in skip_dirs for part in item.parts):
|
|
continue
|
|
if item.is_file():
|
|
files.append(item)
|
|
if len(files) >= {_GREP_MAX_FILES}:
|
|
break
|
|
|
|
matches = []
|
|
output_bytes = 0
|
|
truncated_by = None
|
|
for fp in files:
|
|
try:
|
|
handle = fp.open('r', encoding='utf-8', errors='ignore')
|
|
except OSError:
|
|
continue
|
|
with handle:
|
|
for lineno, line in enumerate(handle, 1):
|
|
if regex.search(line):
|
|
if base.is_file():
|
|
file_path = path
|
|
else:
|
|
rel = os.path.relpath(str(fp), path)
|
|
file_path = os.path.join(path, rel).replace(os.sep, '/')
|
|
content = line.rstrip()
|
|
line_truncated = False
|
|
if len(content) > {_GREP_MAX_LINE_CHARS}:
|
|
content = content[:{_GREP_MAX_LINE_CHARS}] + '... [truncated]'
|
|
line_truncated = True
|
|
entry = {{'file': file_path, 'line': lineno, 'content': content}}
|
|
entry_bytes = len(json.dumps(entry, ensure_ascii=False).encode('utf-8')) + 1
|
|
if output_bytes + entry_bytes > {_DEFAULT_TOOL_RESULT_MAX_BYTES}:
|
|
truncated_by = 'bytes'
|
|
break
|
|
if line_truncated and truncated_by is None:
|
|
truncated_by = 'line'
|
|
matches.append(entry)
|
|
output_bytes += entry_bytes
|
|
if len(matches) >= {_GREP_MAX_MATCHES}:
|
|
truncated_by = truncated_by or 'matches'
|
|
break
|
|
if truncated_by == 'bytes' or len(matches) >= {_GREP_MAX_MATCHES}:
|
|
break
|
|
if truncated_by == 'bytes' or len(matches) >= {_GREP_MAX_MATCHES}:
|
|
break
|
|
|
|
print(json.dumps({{
|
|
'ok': True,
|
|
'matches': matches,
|
|
'total': len(matches),
|
|
'truncated': truncated_by is not None,
|
|
'truncated_by': truncated_by,
|
|
}}))
|
|
""".strip()
|
|
return await self._run_workspace_file_script(script, query)
|
|
|
|
async def _invoke_read(self, parameters: dict, query: pipeline_query.Query) -> dict:
|
|
path = parameters['path']
|
|
self.ap.logger.info(f'read tool invoked: query_id={query.query_id} path={path}')
|
|
skill_request = self._resolve_skill_relative_path(
|
|
query,
|
|
path,
|
|
include_visible=True,
|
|
include_activated=True,
|
|
)
|
|
if skill_request is not None and hasattr(self.ap.box_service, 'read_skill_file'):
|
|
selected_skill, relative = skill_request
|
|
host_path = self._resolve_skill_host_path(selected_skill, relative)
|
|
if host_path and os.path.exists(host_path):
|
|
if os.path.isdir(host_path):
|
|
return self._build_directory_result(os.listdir(host_path))
|
|
return self._read_text_file_preview(host_path, parameters)
|
|
|
|
try:
|
|
result = await self.ap.box_service.read_skill_file(selected_skill['name'], relative)
|
|
return self._build_read_result_from_text(str(result.get('content', '')), parameters)
|
|
except Exception:
|
|
try:
|
|
result = await self.ap.box_service.list_skill_files(selected_skill['name'], relative)
|
|
entries = [entry['name'] for entry in result.get('entries', [])]
|
|
return self._build_directory_result(entries)
|
|
except Exception as exc:
|
|
return {'ok': False, 'error': str(exc)}
|
|
|
|
host_path, selected_skill = self._resolve_host_path(
|
|
query,
|
|
path,
|
|
include_visible=True,
|
|
include_activated=True,
|
|
)
|
|
if self._should_use_box_workspace_files(selected_skill):
|
|
return await self._read_workspace_via_box(path, parameters, query)
|
|
if not os.path.exists(host_path):
|
|
return {'ok': False, 'error': f'File not found: {path}'}
|
|
if os.path.isdir(host_path):
|
|
entries = os.listdir(host_path)
|
|
return self._build_directory_result(entries)
|
|
return self._read_text_file_preview(host_path, parameters)
|
|
|
|
async def _invoke_write(self, parameters: dict, query: pipeline_query.Query) -> dict:
|
|
path = parameters['path']
|
|
content = parameters['content']
|
|
self.ap.logger.info(f'write tool invoked: query_id={query.query_id} path={path} length={len(content)}')
|
|
encoding, _mode = self._write_options(parameters)
|
|
skill_request = self._resolve_skill_relative_path(
|
|
query,
|
|
path,
|
|
include_visible=False,
|
|
include_activated=True,
|
|
)
|
|
if skill_request is not None and hasattr(self.ap.box_service, 'write_skill_file'):
|
|
if encoding != 'text':
|
|
return {'ok': False, 'error': 'base64 writes to skill packages are not supported.'}
|
|
selected_skill, relative = skill_request
|
|
await self.ap.box_service.write_skill_file(selected_skill['name'], relative, content)
|
|
await self.ap.skill_mgr.reload_skills()
|
|
return {'ok': True, 'path': path}
|
|
|
|
host_path, selected_skill = self._resolve_host_path(
|
|
query,
|
|
path,
|
|
include_visible=False,
|
|
include_activated=True,
|
|
)
|
|
if self._should_use_box_workspace_files(selected_skill):
|
|
return await self._write_workspace_via_box(path, content, parameters, query)
|
|
os.makedirs(os.path.dirname(host_path), exist_ok=True)
|
|
try:
|
|
self._write_host_file(host_path, content, parameters)
|
|
except ValueError as exc:
|
|
return {'ok': False, 'error': str(exc)}
|
|
self._refresh_skill_from_disk(selected_skill)
|
|
return {'ok': True, 'path': path}
|
|
|
|
async def _invoke_edit(self, parameters: dict, query: pipeline_query.Query) -> dict:
|
|
path = parameters['path']
|
|
old_string = parameters['old_string']
|
|
new_string = parameters['new_string']
|
|
self.ap.logger.info(
|
|
f'edit tool invoked: query_id={query.query_id} path={path} '
|
|
f'old_len={len(old_string)} new_len={len(new_string)}'
|
|
)
|
|
skill_request = self._resolve_skill_relative_path(
|
|
query,
|
|
path,
|
|
include_visible=False,
|
|
include_activated=True,
|
|
)
|
|
if (
|
|
skill_request is not None
|
|
and hasattr(self.ap.box_service, 'read_skill_file')
|
|
and hasattr(self.ap.box_service, 'write_skill_file')
|
|
):
|
|
selected_skill, relative = skill_request
|
|
try:
|
|
result = await self.ap.box_service.read_skill_file(selected_skill['name'], relative)
|
|
except Exception:
|
|
return {'ok': False, 'error': f'File not found: {path}'}
|
|
content = result.get('content', '')
|
|
count = content.count(old_string)
|
|
if count == 0:
|
|
return {'ok': False, 'error': 'old_string not found in file.'}
|
|
if count > 1:
|
|
return {'ok': False, 'error': f'old_string matches {count} locations; provide a more unique string.'}
|
|
new_content = content.replace(old_string, new_string, 1)
|
|
await self.ap.box_service.write_skill_file(selected_skill['name'], relative, new_content)
|
|
await self.ap.skill_mgr.reload_skills()
|
|
return {'ok': True, 'path': path}
|
|
|
|
host_path, selected_skill = self._resolve_host_path(
|
|
query,
|
|
path,
|
|
include_visible=False,
|
|
include_activated=True,
|
|
)
|
|
if self._should_use_box_workspace_files(selected_skill):
|
|
return await self._edit_workspace_via_box(path, old_string, new_string, query)
|
|
if not os.path.isfile(host_path):
|
|
return {'ok': False, 'error': f'File not found: {path}'}
|
|
with open(host_path, 'r', encoding='utf-8', errors='replace') as f:
|
|
content = f.read()
|
|
count = content.count(old_string)
|
|
if count == 0:
|
|
return {'ok': False, 'error': 'old_string not found in file.'}
|
|
if count > 1:
|
|
return {'ok': False, 'error': f'old_string matches {count} locations; provide a more unique string.'}
|
|
new_content = content.replace(old_string, new_string, 1)
|
|
with open(host_path, 'w', encoding='utf-8') as f:
|
|
f.write(new_content)
|
|
self._refresh_skill_from_disk(selected_skill)
|
|
return {'ok': True, 'path': path}
|
|
|
|
def _refresh_skill_from_disk(self, selected_skill: dict | None) -> None:
|
|
if selected_skill is None:
|
|
return
|
|
|
|
skill_mgr = getattr(self.ap, 'skill_mgr', None)
|
|
if skill_mgr is None:
|
|
return
|
|
|
|
refresh_skill = getattr(skill_mgr, 'refresh_skill_from_disk', None)
|
|
if callable(refresh_skill):
|
|
refresh_skill(selected_skill.get('name', ''))
|
|
|
|
def _is_sandbox_available(self) -> bool:
|
|
"""Check if sandbox backend is available.
|
|
|
|
This checks the cached backend availability from initialization,
|
|
not just whether the box_service process is running.
|
|
"""
|
|
return bool(self._backend_available)
|
|
|
|
def _build_exec_tool(self) -> resource_tool.LLMTool:
|
|
return resource_tool.LLMTool(
|
|
name=EXEC_TOOL_NAME,
|
|
human_desc='Execute a command in an isolated environment',
|
|
description=(
|
|
'Run shell commands in an isolated execution environment. '
|
|
'Use this tool for bash commands, Python execution, and exact calculations over '
|
|
'user-provided data. Activated skill packages are addressable under '
|
|
'/workspace/.skills/<skill-name>; when running inside one, set workdir to that path. '
|
|
'To create a new skill package, prepare it under /workspace first, then use register_skill.'
|
|
),
|
|
parameters={
|
|
'type': 'object',
|
|
'properties': {
|
|
'command': {
|
|
'type': 'string',
|
|
'description': 'Shell command to execute.',
|
|
},
|
|
'workdir': {
|
|
'type': 'string',
|
|
'description': 'Working directory for the command. Defaults to /workspace.',
|
|
'default': '/workspace',
|
|
},
|
|
'timeout_sec': {
|
|
'type': 'integer',
|
|
'description': 'Execution timeout in seconds. Defaults to 30.',
|
|
'default': 30,
|
|
'minimum': 1,
|
|
},
|
|
'env': {
|
|
'type': 'object',
|
|
'description': 'Optional environment variables for the execution.',
|
|
'additionalProperties': {'type': 'string'},
|
|
'default': {},
|
|
},
|
|
'description': {
|
|
'type': 'string',
|
|
'description': 'Brief description of what this command does, for logging and audit.',
|
|
},
|
|
},
|
|
'required': ['command'],
|
|
'additionalProperties': False,
|
|
},
|
|
func=lambda parameters: parameters,
|
|
)
|
|
|
|
def _build_read_tool(self) -> resource_tool.LLMTool:
|
|
return resource_tool.LLMTool(
|
|
name=READ_TOOL_NAME,
|
|
human_desc='Read a file from the workspace',
|
|
description=(
|
|
'Read the contents of a file at the given path under /workspace. '
|
|
'Visible skill packages can be inspected through /workspace/.skills/<skill-name>/... .'
|
|
),
|
|
parameters={
|
|
'type': 'object',
|
|
'properties': {
|
|
'path': {
|
|
'type': 'string',
|
|
'description': 'Absolute path to the file (must be under /workspace).',
|
|
},
|
|
'offset': {
|
|
'type': 'integer',
|
|
'description': '1-indexed line number to start reading from. Defaults to 1.',
|
|
'default': 1,
|
|
'minimum': 1,
|
|
},
|
|
'limit': {
|
|
'type': 'integer',
|
|
'description': f'Maximum number of lines to return. Defaults to {_DEFAULT_READ_MAX_LINES}.',
|
|
'default': _DEFAULT_READ_MAX_LINES,
|
|
'minimum': 1,
|
|
'maximum': _MAX_READ_MAX_LINES,
|
|
},
|
|
'max_bytes': {
|
|
'type': 'integer',
|
|
'description': (
|
|
f'Maximum bytes of file content to return. Defaults to {_DEFAULT_TOOL_RESULT_MAX_BYTES}.'
|
|
),
|
|
'default': _DEFAULT_TOOL_RESULT_MAX_BYTES,
|
|
'minimum': 1,
|
|
'maximum': _DEFAULT_TOOL_RESULT_MAX_BYTES,
|
|
},
|
|
'encoding': {
|
|
'type': 'string',
|
|
'description': 'Return text by default, or base64 for binary byte-range reads.',
|
|
'enum': ['text', 'base64'],
|
|
'default': 'text',
|
|
},
|
|
'byte_offset': {
|
|
'type': 'integer',
|
|
'description': '0-indexed byte offset used when encoding is base64. Defaults to 0.',
|
|
'default': 0,
|
|
'minimum': 0,
|
|
},
|
|
},
|
|
'required': ['path'],
|
|
'additionalProperties': False,
|
|
},
|
|
func=lambda parameters: parameters,
|
|
)
|
|
|
|
def _build_write_tool(self) -> resource_tool.LLMTool:
|
|
return resource_tool.LLMTool(
|
|
name=WRITE_TOOL_NAME,
|
|
human_desc='Write a file to the workspace',
|
|
description=(
|
|
'Create or overwrite a file at the given path under /workspace with the provided content. '
|
|
'Activated skill packages can be modified through /workspace/.skills/<skill-name>/... . '
|
|
'For new skills, write files under /workspace and then call register_skill.'
|
|
),
|
|
parameters={
|
|
'type': 'object',
|
|
'properties': {
|
|
'path': {
|
|
'type': 'string',
|
|
'description': 'Absolute path to the file (must be under /workspace).',
|
|
},
|
|
'content': {
|
|
'type': 'string',
|
|
'description': 'Text content, or base64 content when encoding is base64.',
|
|
},
|
|
'encoding': {
|
|
'type': 'string',
|
|
'description': 'Write content as text by default, or decode it from base64 for binary files.',
|
|
'enum': ['text', 'base64'],
|
|
'default': 'text',
|
|
},
|
|
'mode': {
|
|
'type': 'string',
|
|
'description': 'Overwrite the file by default, or append to it.',
|
|
'enum': ['overwrite', 'append'],
|
|
'default': 'overwrite',
|
|
},
|
|
},
|
|
'required': ['path', 'content'],
|
|
'additionalProperties': False,
|
|
},
|
|
func=lambda parameters: parameters,
|
|
)
|
|
|
|
def _build_edit_tool(self) -> resource_tool.LLMTool:
|
|
return resource_tool.LLMTool(
|
|
name=EDIT_TOOL_NAME,
|
|
human_desc='Edit a file in the workspace',
|
|
description=(
|
|
'Perform an exact string replacement in a file under /workspace. '
|
|
'The old_string must appear exactly once in the file. Activated skill packages '
|
|
'can be edited through /workspace/.skills/<skill-name>/... . '
|
|
'For new skills, edit files under /workspace and then call register_skill.'
|
|
),
|
|
parameters={
|
|
'type': 'object',
|
|
'properties': {
|
|
'path': {
|
|
'type': 'string',
|
|
'description': 'Absolute path to the file (must be under /workspace).',
|
|
},
|
|
'old_string': {
|
|
'type': 'string',
|
|
'description': 'The exact string to find and replace.',
|
|
},
|
|
'new_string': {
|
|
'type': 'string',
|
|
'description': 'The replacement string.',
|
|
},
|
|
},
|
|
'required': ['path', 'old_string', 'new_string'],
|
|
'additionalProperties': False,
|
|
},
|
|
func=lambda parameters: parameters,
|
|
)
|
|
|
|
def _build_glob_tool(self) -> resource_tool.LLMTool:
|
|
return resource_tool.LLMTool(
|
|
name=GLOB_TOOL_NAME,
|
|
human_desc='Find files matching a glob pattern',
|
|
description=(
|
|
'Find files matching a glob pattern under /workspace. '
|
|
'Supports ** for recursive matching (e.g. **/*.py). '
|
|
'Results are sorted by modification time (newest first). '
|
|
'Visible and activated skill packages can be searched through /workspace/.skills/<skill-name>/...'
|
|
),
|
|
parameters={
|
|
'type': 'object',
|
|
'properties': {
|
|
'pattern': {
|
|
'type': 'string',
|
|
'description': 'Glob pattern, e.g. **/*.py or src/**/*.ts',
|
|
},
|
|
'path': {
|
|
'type': 'string',
|
|
'description': 'Directory to search in (must be under /workspace, default: /workspace)',
|
|
'default': '/workspace',
|
|
},
|
|
},
|
|
'required': ['pattern'],
|
|
'additionalProperties': False,
|
|
},
|
|
func=lambda parameters: parameters,
|
|
)
|
|
|
|
def _build_grep_tool(self) -> resource_tool.LLMTool:
|
|
return resource_tool.LLMTool(
|
|
name=GREP_TOOL_NAME,
|
|
human_desc='Search file contents with regex',
|
|
description=(
|
|
'Search file contents with regex pattern under /workspace. '
|
|
'Returns matching lines with file path and line number. '
|
|
'Visible and activated skill packages can be searched through /workspace/.skills/<skill-name>/...'
|
|
),
|
|
parameters={
|
|
'type': 'object',
|
|
'properties': {
|
|
'pattern': {
|
|
'type': 'string',
|
|
'description': 'Regex pattern to search for',
|
|
},
|
|
'path': {
|
|
'type': 'string',
|
|
'description': 'File or directory to search (must be under /workspace, default: /workspace)',
|
|
'default': '/workspace',
|
|
},
|
|
'include': {
|
|
'type': 'string',
|
|
'description': 'Only search files matching this glob (e.g. *.py)',
|
|
},
|
|
},
|
|
'required': ['pattern'],
|
|
'additionalProperties': False,
|
|
},
|
|
func=lambda parameters: parameters,
|
|
)
|
|
|
|
async def _invoke_glob(self, parameters: dict, query: pipeline_query.Query) -> dict:
|
|
pattern = parameters['pattern']
|
|
path = str(parameters.get('path', '/workspace') or '/workspace')
|
|
self.ap.logger.info(f'glob tool invoked: query_id={query.query_id} pattern={pattern} path={path}')
|
|
|
|
host_path, selected_skill = self._resolve_host_path(
|
|
query,
|
|
path,
|
|
include_visible=True,
|
|
include_activated=True,
|
|
)
|
|
if self._should_use_box_workspace_files(selected_skill):
|
|
return await self._glob_workspace_via_box(path, pattern, query)
|
|
|
|
if not os.path.isdir(host_path):
|
|
return {'ok': False, 'error': f'Path is not a directory: {path}'}
|
|
|
|
from pathlib import Path
|
|
|
|
base = Path(host_path)
|
|
hits = list(base.rglob(pattern))
|
|
|
|
# Filter out skipped directories
|
|
hits = [h for h in hits if not any(skip in h.parts for skip in _SKIP_DIRS)]
|
|
|
|
# Sort by mtime, newest first
|
|
hits.sort(key=lambda p: p.stat().st_mtime if p.exists() else 0, reverse=True)
|
|
|
|
total = len(hits)
|
|
shown = hits[:_GLOB_MAX_MATCHES]
|
|
|
|
# Convert back to sandbox paths
|
|
sandbox_paths = []
|
|
output_bytes = 0
|
|
truncated_by_bytes = False
|
|
for h in shown:
|
|
rel = os.path.relpath(str(h), host_path)
|
|
sandbox_path = os.path.join(path, rel)
|
|
entry_bytes = len(sandbox_path.encode('utf-8')) + (1 if sandbox_paths else 0)
|
|
if output_bytes + entry_bytes > _DEFAULT_TOOL_RESULT_MAX_BYTES:
|
|
truncated_by_bytes = True
|
|
break
|
|
sandbox_paths.append(sandbox_path)
|
|
output_bytes += entry_bytes
|
|
|
|
return {
|
|
'ok': True,
|
|
'matches': sandbox_paths,
|
|
'preview': '\n'.join(sandbox_paths),
|
|
'total': total,
|
|
'truncated': total > len(sandbox_paths) or truncated_by_bytes,
|
|
'truncated_by': 'bytes' if truncated_by_bytes else ('matches' if total > len(sandbox_paths) else None),
|
|
}
|
|
|
|
async def _invoke_grep(self, parameters: dict, query: pipeline_query.Query) -> dict:
|
|
pattern = parameters['pattern']
|
|
path = str(parameters.get('path', '/workspace') or '/workspace')
|
|
include = parameters.get('include')
|
|
self.ap.logger.info(f'grep tool invoked: query_id={query.query_id} pattern={pattern} path={path}')
|
|
|
|
import re
|
|
from pathlib import Path
|
|
|
|
try:
|
|
regex = re.compile(pattern)
|
|
except re.error as e:
|
|
return {'ok': False, 'error': f'Invalid regex: {e}'}
|
|
|
|
host_path, selected_skill = self._resolve_host_path(
|
|
query,
|
|
path,
|
|
include_visible=True,
|
|
include_activated=True,
|
|
)
|
|
if self._should_use_box_workspace_files(selected_skill):
|
|
return await self._grep_workspace_via_box(path, pattern, include, query)
|
|
|
|
if not os.path.exists(host_path):
|
|
return {'ok': False, 'error': f'Path not found: {path}'}
|
|
|
|
base = Path(host_path)
|
|
|
|
if base.is_file():
|
|
files = [base]
|
|
else:
|
|
files = self._grep_walk(base, include)
|
|
|
|
matches = []
|
|
output_bytes = 0
|
|
truncated_by = None
|
|
for fp in files:
|
|
try:
|
|
handle = fp.open('r', encoding='utf-8', errors='ignore')
|
|
except OSError:
|
|
continue
|
|
with handle:
|
|
for lineno, line in enumerate(handle, 1):
|
|
if regex.search(line):
|
|
rel = os.path.relpath(str(fp), host_path)
|
|
sandbox_path = os.path.join(path, rel)
|
|
content, line_truncated = self._truncate_grep_line(line.rstrip())
|
|
entry = {
|
|
'file': sandbox_path,
|
|
'line': lineno,
|
|
'content': content,
|
|
}
|
|
entry_bytes = len(json.dumps(entry, ensure_ascii=False).encode('utf-8')) + 1
|
|
if output_bytes + entry_bytes > _DEFAULT_TOOL_RESULT_MAX_BYTES:
|
|
truncated_by = 'bytes'
|
|
break
|
|
if line_truncated and truncated_by is None:
|
|
truncated_by = 'line'
|
|
matches.append(entry)
|
|
output_bytes += entry_bytes
|
|
if len(matches) >= _GREP_MAX_MATCHES:
|
|
truncated_by = truncated_by or 'matches'
|
|
break
|
|
if truncated_by == 'bytes' or len(matches) >= _GREP_MAX_MATCHES:
|
|
break
|
|
if truncated_by == 'bytes' or len(matches) >= _GREP_MAX_MATCHES:
|
|
break
|
|
|
|
return {
|
|
'ok': True,
|
|
'matches': matches,
|
|
'total': len(matches),
|
|
'truncated': truncated_by is not None,
|
|
'truncated_by': truncated_by,
|
|
}
|
|
|
|
@staticmethod
|
|
def _grep_walk(root, include: str | None) -> list:
|
|
"""Walk dir tree for grep, skipping junk dirs."""
|
|
results = []
|
|
for item in root.rglob(include or '*'):
|
|
if any(skip in item.parts for skip in _SKIP_DIRS):
|
|
continue
|
|
if item.is_file():
|
|
results.append(item)
|
|
if len(results) >= _GREP_MAX_FILES:
|
|
break
|
|
return results
|
|
|
|
@staticmethod
|
|
def _resolve_skill_host_path(selected_skill: dict, relative: str) -> str | None:
|
|
package_root = str(selected_skill.get('package_root', '') or '').strip()
|
|
if not package_root:
|
|
return None
|
|
|
|
host_root = os.path.realpath(package_root)
|
|
host_path = os.path.realpath(os.path.join(host_root, relative))
|
|
if not (host_path == host_root or host_path.startswith(host_root + os.sep)):
|
|
raise ValueError('Path escapes the skill package boundary.')
|
|
return host_path
|
|
|
|
def _normalize_exec_result(self, result: dict) -> dict:
|
|
normalized = dict(result)
|
|
stdout = str(normalized.get('stdout') or '')
|
|
stderr = str(normalized.get('stderr') or '')
|
|
stdout, stdout_capped = self._truncate_text_to_bytes_with_flag(stdout, _DEFAULT_TOOL_RESULT_MAX_BYTES)
|
|
stderr, stderr_capped = self._truncate_text_to_bytes_with_flag(stderr, _DEFAULT_TOOL_RESULT_MAX_BYTES)
|
|
normalized['stdout'] = stdout
|
|
normalized['stderr'] = stderr
|
|
normalized['stdout_truncated'] = bool(normalized.get('stdout_truncated') or stdout_capped)
|
|
normalized['stderr_truncated'] = bool(normalized.get('stderr_truncated') or stderr_capped)
|
|
|
|
if stdout and stderr:
|
|
preview_raw = f'stdout:\n{stdout}\n\nstderr:\n{stderr}'
|
|
else:
|
|
preview_raw = stdout or stderr
|
|
preview, preview_capped = self._truncate_text_to_bytes_with_flag(preview_raw, _DEFAULT_TOOL_RESULT_MAX_BYTES)
|
|
normalized['preview'] = preview
|
|
normalized['truncated'] = bool(
|
|
normalized['stdout_truncated'] or normalized['stderr_truncated'] or preview_capped
|
|
)
|
|
if preview_capped and not normalized.get('truncated_by'):
|
|
normalized['truncated_by'] = 'bytes'
|
|
return normalized
|
|
|
|
def _build_directory_result(self, entries: list[str]) -> dict:
|
|
sorted_entries = sorted(str(entry) for entry in entries)
|
|
content = '\n'.join(sorted_entries)
|
|
preview = self._truncate_text_to_bytes(content, _DEFAULT_TOOL_RESULT_MAX_BYTES)
|
|
truncated = preview != content
|
|
return {
|
|
'ok': True,
|
|
'content': preview,
|
|
'is_directory': True,
|
|
'total': len(sorted_entries),
|
|
'truncated': truncated,
|
|
'truncated_by': 'bytes' if truncated else None,
|
|
}
|
|
|
|
def _read_text_file_preview(self, host_path: str, parameters: dict) -> dict:
|
|
if self._read_encoding(parameters) == 'base64':
|
|
return self._read_binary_file_chunk(host_path, parameters)
|
|
|
|
offset = self._positive_int(parameters.get('offset'), default=1)
|
|
max_lines = self._positive_int(
|
|
parameters.get('limit'),
|
|
default=_DEFAULT_READ_MAX_LINES,
|
|
max_value=_MAX_READ_MAX_LINES,
|
|
)
|
|
max_bytes = self._positive_int(
|
|
parameters.get('max_bytes'),
|
|
default=_DEFAULT_TOOL_RESULT_MAX_BYTES,
|
|
max_value=_DEFAULT_TOOL_RESULT_MAX_BYTES,
|
|
)
|
|
lines: list[str] = []
|
|
output_bytes = 0
|
|
end_line = offset - 1
|
|
truncated = False
|
|
truncated_by: str | None = None
|
|
next_offset: int | None = None
|
|
|
|
with open(host_path, 'r', encoding='utf-8', errors='replace') as f:
|
|
for line_number, line in enumerate(f, 1):
|
|
if line_number < offset:
|
|
continue
|
|
if len(lines) >= max_lines:
|
|
truncated = True
|
|
truncated_by = 'lines'
|
|
next_offset = line_number
|
|
break
|
|
|
|
line_bytes = len(line.encode('utf-8'))
|
|
if output_bytes + line_bytes > max_bytes:
|
|
truncated = True
|
|
truncated_by = 'bytes'
|
|
next_offset = line_number
|
|
break
|
|
|
|
lines.append(line.rstrip('\n'))
|
|
output_bytes += line_bytes
|
|
end_line = line_number
|
|
|
|
if not lines and truncated_by == 'bytes':
|
|
content = (
|
|
f'[Line {next_offset or offset} exceeds the {self._format_size(max_bytes)} read limit. '
|
|
'Use exec with a byte-range command for this line, or read a different offset.]'
|
|
)
|
|
else:
|
|
content = '\n'.join(lines)
|
|
|
|
return {
|
|
'ok': True,
|
|
'content': content,
|
|
'truncated': truncated,
|
|
'truncated_by': truncated_by,
|
|
'start_line': offset,
|
|
'end_line': end_line,
|
|
'next_offset': next_offset,
|
|
'max_lines': max_lines,
|
|
'max_bytes': max_bytes,
|
|
}
|
|
|
|
def _read_binary_file_chunk(self, host_path: str, parameters: dict) -> dict:
|
|
byte_offset = self._non_negative_int(parameters.get('byte_offset'), default=0)
|
|
max_bytes = self._positive_int(
|
|
parameters.get('max_bytes'),
|
|
default=_DEFAULT_TOOL_RESULT_MAX_BYTES,
|
|
max_value=_DEFAULT_TOOL_RESULT_MAX_BYTES,
|
|
)
|
|
size_bytes = os.path.getsize(host_path)
|
|
with open(host_path, 'rb') as f:
|
|
f.seek(byte_offset)
|
|
data = f.read(max_bytes + 1)
|
|
chunk = data[:max_bytes]
|
|
has_more = len(data) > max_bytes
|
|
return {
|
|
'ok': True,
|
|
'content': base64.b64encode(chunk).decode('ascii'),
|
|
'encoding': 'base64',
|
|
'byte_offset': byte_offset,
|
|
'length': len(chunk),
|
|
'size_bytes': size_bytes,
|
|
'has_more': has_more,
|
|
'next_byte_offset': byte_offset + len(chunk) if has_more else None,
|
|
'max_bytes': max_bytes,
|
|
}
|
|
|
|
def _write_host_file(self, host_path: str, content: str, parameters: dict) -> None:
|
|
encoding, mode = self._write_options(parameters)
|
|
if encoding == 'base64':
|
|
try:
|
|
data = base64.b64decode(content, validate=True)
|
|
except Exception as exc:
|
|
raise ValueError(f'invalid base64 content: {exc}') from exc
|
|
with open(host_path, 'ab' if mode == 'append' else 'wb') as f:
|
|
f.write(data)
|
|
return
|
|
with open(host_path, 'a' if mode == 'append' else 'w', encoding='utf-8') as f:
|
|
f.write(content)
|
|
|
|
@staticmethod
|
|
def _read_encoding(parameters: dict) -> str:
|
|
return 'base64' if parameters.get('encoding') == 'base64' else 'text'
|
|
|
|
@staticmethod
|
|
def _write_options(parameters: dict) -> tuple[str, str]:
|
|
encoding = 'base64' if parameters.get('encoding') == 'base64' else 'text'
|
|
mode = 'append' if parameters.get('mode') == 'append' else 'overwrite'
|
|
return encoding, mode
|
|
|
|
def _build_read_result_from_text(self, content: str, parameters: dict) -> dict:
|
|
offset = self._positive_int(parameters.get('offset'), default=1)
|
|
max_lines = self._positive_int(
|
|
parameters.get('limit'),
|
|
default=_DEFAULT_READ_MAX_LINES,
|
|
max_value=_MAX_READ_MAX_LINES,
|
|
)
|
|
max_bytes = self._positive_int(
|
|
parameters.get('max_bytes'),
|
|
default=_DEFAULT_TOOL_RESULT_MAX_BYTES,
|
|
max_value=_DEFAULT_TOOL_RESULT_MAX_BYTES,
|
|
)
|
|
all_lines = content.splitlines()
|
|
start_index = offset - 1
|
|
if start_index >= len(all_lines) and all_lines:
|
|
return {'ok': False, 'error': f'Offset {offset} is beyond end of file ({len(all_lines)} lines total)'}
|
|
output_lines: list[str] = []
|
|
output_bytes = 0
|
|
truncated = False
|
|
truncated_by: str | None = None
|
|
next_offset: int | None = None
|
|
for index, line in enumerate(all_lines[start_index:], start_index + 1):
|
|
if len(output_lines) >= max_lines:
|
|
truncated = True
|
|
truncated_by = 'lines'
|
|
next_offset = index
|
|
break
|
|
line_bytes = len(line.encode('utf-8')) + (1 if output_lines else 0)
|
|
if output_bytes + line_bytes > max_bytes:
|
|
truncated = True
|
|
truncated_by = 'bytes'
|
|
next_offset = index
|
|
break
|
|
output_lines.append(line)
|
|
output_bytes += line_bytes
|
|
|
|
end_line = offset + len(output_lines) - 1
|
|
return {
|
|
'ok': True,
|
|
'content': '\n'.join(output_lines),
|
|
'truncated': truncated,
|
|
'truncated_by': truncated_by,
|
|
'start_line': offset,
|
|
'end_line': end_line,
|
|
'next_offset': next_offset,
|
|
'max_lines': max_lines,
|
|
'max_bytes': max_bytes,
|
|
}
|
|
|
|
@staticmethod
|
|
def _positive_int(value, *, default: int, max_value: int | None = None) -> int:
|
|
try:
|
|
parsed = int(value)
|
|
except (TypeError, ValueError):
|
|
parsed = default
|
|
if parsed <= 0:
|
|
parsed = default
|
|
if max_value is not None:
|
|
parsed = min(parsed, max_value)
|
|
return parsed
|
|
|
|
@staticmethod
|
|
def _non_negative_int(value, *, default: int) -> int:
|
|
try:
|
|
parsed = int(value)
|
|
except (TypeError, ValueError):
|
|
parsed = default
|
|
return parsed if parsed >= 0 else default
|
|
|
|
@staticmethod
|
|
def _truncate_grep_line(line: str) -> tuple[str, bool]:
|
|
if len(line) <= _GREP_MAX_LINE_CHARS:
|
|
return line, False
|
|
return f'{line[:_GREP_MAX_LINE_CHARS]}... [truncated]', True
|
|
|
|
@staticmethod
|
|
def _truncate_text_to_bytes(text: str, max_bytes: int) -> str:
|
|
return NativeToolLoader._truncate_text_to_bytes_with_flag(text, max_bytes)[0]
|
|
|
|
@staticmethod
|
|
def _truncate_text_to_bytes_with_flag(text: str, max_bytes: int) -> tuple[str, bool]:
|
|
data = text.encode('utf-8')
|
|
if len(data) <= max_bytes:
|
|
return text, False
|
|
truncated = data[:max_bytes]
|
|
while truncated and (truncated[-1] & 0xC0) == 0x80:
|
|
truncated = truncated[:-1]
|
|
return truncated.decode('utf-8', errors='ignore'), True
|
|
|
|
@staticmethod
|
|
def _format_size(bytes_count: int) -> str:
|
|
if bytes_count < 1024:
|
|
return f'{bytes_count}B'
|
|
return f'{bytes_count / 1024:.1f}KB'
|
|
|
|
def _summarize_parameters(self, parameters: dict) -> dict:
|
|
summary = dict(parameters)
|
|
cmd = str(summary.get('command', '')).strip()
|
|
if len(cmd) > 400:
|
|
cmd = f'{cmd[:397]}...'
|
|
summary['command'] = cmd
|
|
|
|
env = summary.get('env')
|
|
if isinstance(env, dict):
|
|
summary['env_keys'] = sorted(str(key) for key in env.keys())
|
|
del summary['env']
|
|
|
|
return summary
|