refactor(block-h): move AI tool registry into core AI layer
This commit is contained in:
@@ -50,7 +50,7 @@ if TYPE_CHECKING:
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from sqlalchemy.ext.asyncio import AsyncSession
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from app.plugins.builtins.ai_assistant.tool_registry import ToolRegistry
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from app.ai.tool_registry import ToolRegistry
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logger = logging.getLogger(__name__)
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@@ -61,7 +61,7 @@ def _resolve_effective_tool_ids(
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orchestrate tools but never grant additional permissions.
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"""
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from app.ai.skill_registry import get_skill_registry
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from app.plugins.builtins.ai_assistant.contracts import get_tool_registry
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from app.ai.tool_registry import get_tool_registry
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agent_tool_ids: list[str] = list(getattr(agent_definition, "tool_ids", None) or [])
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agent_skill_ids: list[str] = list(getattr(agent_definition, "skill_ids", None) or [])
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@@ -221,7 +221,7 @@ async def build_agent_context(
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tool_descriptions: list[dict[str, str]] = []
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tool_ids = list(getattr(agent_definition, "tool_ids", None) or [])
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try:
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from app.plugins.builtins.ai_assistant.contracts import get_tool_registry
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from app.ai.tool_registry import get_tool_registry
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registry = get_tool_registry()
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if tool_ids:
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@@ -1,170 +0,0 @@
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"""Integration tools — Agent → Workflow + Agent → Knowledge.
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Registers AI tools that allow agents to start workflows and ask knowledge questions.
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Builds on: workflow_service, knowledge services, tool_registry.
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"""
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from __future__ import annotations
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import logging
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import uuid
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from typing import Any
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logger = logging.getLogger(__name__)
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def register_integration_tools() -> None:
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"""Register workflow + knowledge tools in the AI tool registry."""
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from app.plugins.builtins.ai_assistant.tool_registry import get_tool_registry
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registry = get_tool_registry()
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# ── I-AW: Agent → Workflow ──
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async def _start_workflow_handler(arguments: dict[str, Any], context: dict[str, Any]) -> dict[str, Any]:
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"""Start a workflow by ID."""
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from app.services.workflow_service import create_instance
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from app.core.db import get_worker_session_factory
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workflow_id = arguments.get("workflow_id", "")
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tenant_id = context.get("tenant_id")
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user_id = context.get("user_id")
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if not workflow_id or not tenant_id:
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return {"error": "workflow_id and tenant_id required"}
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factory = get_worker_session_factory()
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async with factory() as db:
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instance = await create_instance(
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db=db,
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tenant_id=uuid.UUID(str(tenant_id)),
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workflow_id=uuid.UUID(workflow_id),
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initiated_by=uuid.UUID(str(user_id)) if user_id else None,
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)
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await db.commit()
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return {"instance_id": str(instance.get("id", "")), "status": instance.get("status", "created")}
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registry.register(
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name="start_workflow",
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description="Start a workflow by its ID. Returns the instance ID and status.",
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parameters={
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"type": "object",
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"properties": {
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"workflow_id": {"type": "string", "description": "UUID of the workflow to start"},
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},
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"required": ["workflow_id"],
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},
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handler=_start_workflow_handler,
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plugin_name="integration",
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required_permission="workflows:read",
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category="workflow",
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)
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async def _check_workflow_status_handler(arguments: dict[str, Any], context: dict[str, Any]) -> dict[str, Any]:
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"""Check the status of a workflow instance."""
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from sqlalchemy import select
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from app.models.workflow import WorkflowInstance
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from app.core.db import get_worker_session_factory
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instance_id = arguments.get("instance_id", "")
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tenant_id = context.get("tenant_id")
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if not instance_id or not tenant_id:
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return {"error": "instance_id and tenant_id required"}
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factory = get_worker_session_factory()
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async with factory() as db:
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result = await db.execute(
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select(WorkflowInstance).where(
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WorkflowInstance.id == uuid.UUID(instance_id),
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WorkflowInstance.tenant_id == uuid.UUID(str(tenant_id)),
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)
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)
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inst = result.scalar_one_or_none()
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if not inst:
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return {"error": "Instance not found"}
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return {
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"instance_id": str(inst.id),
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"status": inst.status,
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"current_step": inst.current_step_index,
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"completed_at": inst.completed_at.isoformat() if inst.completed_at else None,
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}
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registry.register(
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name="check_workflow_status",
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description="Check the status of a workflow instance by its ID.",
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parameters={
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"type": "object",
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"properties": {
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"instance_id": {"type": "string", "description": "UUID of the workflow instance"},
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},
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"required": ["instance_id"],
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},
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handler=_check_workflow_status_handler,
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plugin_name="integration",
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required_permission="workflows:read",
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category="workflow",
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)
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# ── I-AK: Agent → Knowledge ──
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async def _ask_knowledge_handler(arguments: dict[str, Any], context: dict[str, Any]) -> dict[str, Any]:
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"""Ask a knowledge question."""
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from app.plugins.builtins.knowledge.services import ask_knowledge
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from app.core.db import get_worker_session_factory
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question = arguments.get("question", "")
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tenant_id = context.get("tenant_id")
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if not question or not tenant_id:
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return {"error": "question and tenant_id required"}
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factory = get_worker_session_factory()
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async with factory() as db:
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result = await ask_knowledge(db=db, tenant_id=uuid.UUID(str(tenant_id)), question=question)
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return {"answer": result.get("answer", ""), "evidence_count": len(result.get("evidence", []))}
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registry.register(
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name="ask_knowledge",
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description="Ask a knowledge question. Searches wiki articles and graph relationships for context.",
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parameters={
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"type": "object",
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"properties": {
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"question": {"type": "string", "description": "The question to ask"},
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},
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"required": ["question"],
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},
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handler=_ask_knowledge_handler,
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plugin_name="integration",
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required_permission="wiki:read",
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category="knowledge",
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)
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async def _search_knowledge_handler(arguments: dict[str, Any], context: dict[str, Any]) -> dict[str, Any]:
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"""Search wiki articles via unified search."""
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from app.plugins.builtins.unified_search.provider_registry import get_search_registry
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from app.core.db import get_worker_session_factory
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query = arguments.get("query", "")
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tenant_id = context.get("tenant_id")
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if not query or not tenant_id:
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return {"error": "query and tenant_id required"}
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factory = get_worker_session_factory()
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async with factory() as db:
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registry = get_search_registry()
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wiki_provider = registry.get("wiki_article")
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if not wiki_provider:
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return {"error": "Wiki search provider not available"}
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results = await wiki_provider._search_fts_filtered(
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db=db, tsquery=query, tenant_id=uuid.UUID(str(tenant_id)), limit=5, visible_ids=None
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)
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return {
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"results": [
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{"title": r.get("title", ""), "summary": (r.get("summary") or r.get("content", "")[:200] or "")}
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for r in results
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],
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"count": len(results),
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}
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registry.register(
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name="search_knowledge",
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description="Search wiki articles by keyword. Returns matching articles with title and summary.",
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parameters={
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"type": "object",
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"properties": {
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"query": {"type": "string", "description": "Search query"},
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},
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"required": ["query"],
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},
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handler=_search_knowledge_handler,
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plugin_name="integration",
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required_permission="wiki:read",
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category="knowledge",
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)
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logger.info("Registered integration tools: start_workflow, check_workflow_status, ask_knowledge, search_knowledge")
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@@ -0,0 +1,126 @@
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"""Global tool registry for AI agent tools (core platform service).
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Plugins register tools here so AI agents can call them during chat sessions.
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Each tool declares a name, description, JSON schema for parameters,
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and an async handler. Tools can optionally require specific RBAC permissions.
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This registry lives in the core AI layer (not inside a plugin) so that the
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agent runtime keeps working regardless of which optional plugins are active.
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Plugins contribute tools via ``register()`` / ``unregister_plugin()`` during
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their activate/deactivate lifecycle.
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"""
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from __future__ import annotations
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import logging
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from dataclasses import dataclass
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from typing import Any, Protocol
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logger = logging.getLogger(__name__)
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class ToolHandler(Protocol):
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async def __call__(
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self,
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arguments: dict[str, Any],
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context: dict[str, Any],
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) -> str: ...
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@dataclass
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class AITool:
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"""Represents a tool that an AI agent can call."""
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name: str
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description: str
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parameters: dict[str, Any] # JSON Schema for parameters
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handler: ToolHandler
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plugin_name: str = ""
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required_permission: str | None = None # e.g. "mail:send"
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category: str = "general"
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def to_openai_schema(self) -> dict[str, Any]:
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"""Convert to OpenAI function-calling tool schema."""
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return {
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"type": "function",
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"function": {
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"name": self.name,
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"description": self.description,
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"parameters": self.parameters,
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},
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}
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class ToolRegistry:
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"""Singleton registry for AI tools."""
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_instance: ToolRegistry | None = None
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def __new__(cls) -> ToolRegistry:
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if cls._instance is None:
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cls._instance = super().__new__(cls)
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cls._instance._tools: dict[str, AITool] = {}
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return cls._instance
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def register(
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self,
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name: str,
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description: str,
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parameters: dict[str, Any],
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handler: ToolHandler,
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plugin_name: str = "",
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required_permission: str | None = None,
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category: str = "general",
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) -> None:
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"""Register a tool."""
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tool = AITool(
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name=name,
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description=description,
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parameters=parameters,
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handler=handler,
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plugin_name=plugin_name,
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required_permission=required_permission,
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category=category,
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)
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self._tools[name] = tool
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logger.info("AI tool registered: %s (plugin=%s)", name, plugin_name)
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def unregister(self, name: str) -> None:
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"""Unregister a tool by name."""
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self._tools.pop(name, None)
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def unregister_plugin(self, plugin_name: str) -> None:
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"""Unregister all tools from a plugin."""
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to_remove = [
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name for name, tool in self._tools.items() if tool.plugin_name == plugin_name
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]
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for name in to_remove:
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self._tools.pop(name, None)
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def get(self, name: str) -> AITool | None:
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return self._tools.get(name)
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def get_all(self) -> list[AITool]:
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return list(self._tools.values())
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def get_by_names(self, names: list[str]) -> list[AITool]:
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return [self._tools[name] for name in names if name in self._tools]
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def list_for_api(self) -> list[dict[str, Any]]:
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"""Return tool list for API response."""
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return [
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{
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"name": tool.name,
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"description": tool.description,
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"parameters": tool.parameters,
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"plugin_name": tool.plugin_name,
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"required_permission": tool.required_permission,
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"category": tool.category,
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}
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for tool in self._tools.values()
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]
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def get_tool_registry() -> ToolRegistry:
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"""Get the global tool registry singleton."""
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return ToolRegistry()
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@@ -1,121 +1,19 @@
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"""Global tool registry for AI Assistant plugin tools.
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"""Compatibility shim — the tool registry moved to the core AI layer.
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Plugins can register tools that AI agents can call during chat sessions.
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Each tool declares a name, description, JSON schema for parameters,
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and an async handler. Tools can optionally require specific RBAC permissions.
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The agent runtime must not depend on this optional plugin being active,
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so ``ToolRegistry`` / ``AITool`` / ``get_tool_registry`` now live in
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``app.ai.tool_registry``. Import from here still works for existing
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plugin code; new code should import from ``app.ai.tool_registry``
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directly (or via the ai_assistant contract).
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"""
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from __future__ import annotations
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import logging
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from dataclasses import dataclass
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from typing import Any, Protocol
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from app.ai.tool_registry import ( # noqa: F401
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AITool,
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ToolHandler,
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ToolRegistry,
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get_tool_registry,
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)
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logger = logging.getLogger(__name__)
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class ToolHandler(Protocol):
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async def __call__(
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self,
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arguments: dict[str, Any],
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context: dict[str, Any],
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) -> str: ...
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@dataclass
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class AITool:
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"""Represents a tool that an AI agent can call."""
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name: str
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description: str
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parameters: dict[str, Any] # JSON Schema for parameters
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handler: ToolHandler
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plugin_name: str = ""
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required_permission: str | None = None # e.g. "mail:send"
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category: str = "general"
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def to_openai_schema(self) -> dict[str, Any]:
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"""Convert to OpenAI function-calling tool schema."""
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return {
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"type": "function",
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"function": {
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"name": self.name,
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"description": self.description,
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"parameters": self.parameters,
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},
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}
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class ToolRegistry:
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"""Singleton registry for AI tools."""
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_instance: ToolRegistry | None = None
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def __new__(cls) -> ToolRegistry:
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if cls._instance is None:
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cls._instance = super().__new__(cls)
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cls._instance._tools: dict[str, AITool] = {}
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return cls._instance
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def register(
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self,
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name: str,
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description: str,
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parameters: dict[str, Any],
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handler: ToolHandler,
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plugin_name: str = "",
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required_permission: str | None = None,
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category: str = "general",
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) -> None:
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"""Register a tool."""
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tool = AITool(
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name=name,
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description=description,
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parameters=parameters,
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handler=handler,
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plugin_name=plugin_name,
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required_permission=required_permission,
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category=category,
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)
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self._tools[name] = tool
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logger.info("AI tool registered: %s (plugin=%s)", name, plugin_name)
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def unregister(self, name: str) -> None:
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"""Unregister a tool by name."""
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self._tools.pop(name, None)
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def unregister_plugin(self, plugin_name: str) -> None:
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"""Unregister all tools from a plugin."""
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to_remove = [
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name for name, tool in self._tools.items() if tool.plugin_name == plugin_name
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]
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for name in to_remove:
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self._tools.pop(name, None)
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def get(self, name: str) -> AITool | None:
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return self._tools.get(name)
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def get_all(self) -> list[AITool]:
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return list(self._tools.values())
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def get_by_names(self, names: list[str]) -> list[AITool]:
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return [self._tools[name] for name in names if name in self._tools]
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def list_for_api(self) -> list[dict[str, Any]]:
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"""Return tool list for API response."""
|
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return [
|
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{
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"name": tool.name,
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"description": tool.description,
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"parameters": tool.parameters,
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"plugin_name": tool.plugin_name,
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"required_permission": tool.required_permission,
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"category": tool.category,
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}
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for tool in self._tools.values()
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]
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def get_tool_registry() -> ToolRegistry:
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"""Get the global tool registry singleton."""
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return ToolRegistry()
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__all__ = ["AITool", "ToolHandler", "ToolRegistry", "get_tool_registry"]
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Block a user