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5cdae671d5
Close 3 integration gaps between the ported Sandbox system and Agent V2: 1. Fix _invoke_tool_in_sandbox to use SandboxBashSession context manager API correctly (keyword args, bash_tool, ToolReference), with graceful fallback to direct invocation when DifyCli binary is unavailable. 2. Inject sandbox into run_context via _resolve_sandbox_context() in WorkflowBasedAppRunner — automatically creates a sandbox when a tenant has an active sandbox provider configured. 3. Register SandboxLayer in both advanced_chat and workflow app runners for proper sandbox lifecycle cleanup on graph end. Also: make SkillInitializer non-fatal when no skill bundle exists, add node_id to ExecutionContext for sandbox session scoping. Made-with: Cursor
38 lines
1.3 KiB
Python
38 lines
1.3 KiB
Python
from __future__ import annotations
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import logging
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from core.sandbox.sandbox import Sandbox
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from core.skill import SkillAttrs
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from core.skill.skill_manager import SkillManager
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from .base import SandboxInitializeContext, SyncSandboxInitializer
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logger = logging.getLogger(__name__)
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class SkillInitializer(SyncSandboxInitializer):
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"""Ensure ``sandbox.attrs[BUNDLE]`` is populated for downstream consumers.
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In the draft path ``DraftAppAssetsInitializer`` already sets the
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bundle on attrs from the in-memory build result, so this initializer
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becomes a no-op. In the published path no prior initializer sets
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it, so we fall back to ``SkillManager.load_bundle()`` (Redis/S3).
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"""
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def initialize(self, sandbox: Sandbox, ctx: SandboxInitializeContext) -> None:
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if sandbox.attrs.has(SkillAttrs.BUNDLE):
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return
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try:
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bundle = SkillManager.load_bundle(
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ctx.tenant_id,
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ctx.app_id,
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ctx.assets_id,
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)
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sandbox.attrs.set(SkillAttrs.BUNDLE, bundle)
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except FileNotFoundError:
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logger.debug("No skill bundle found for app %s, skipping skill initialization", ctx.app_id)
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except Exception:
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logger.warning("Failed to load skill bundle for app %s, skipping", ctx.app_id, exc_info=True)
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