GT AI OS Community Edition v2.0.33
Security hardening release addressing CodeQL and Dependabot alerts: - Fix stack trace exposure in error responses - Add SSRF protection with DNS resolution checking - Implement proper URL hostname validation (replaces substring matching) - Add centralized path sanitization to prevent path traversal - Fix ReDoS vulnerability in email validation regex - Improve HTML sanitization in validation utilities - Fix capability wildcard matching in auth utilities - Update glob dependency to address CVE - Add CodeQL suppression comments for verified false positives 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
This commit is contained in:
HackWeasel
599
apps/tenant-backend/app/services/assistant_manager.py
Normal file
599
apps/tenant-backend/app/services/assistant_manager.py
Normal file
@@ -0,0 +1,599 @@
|
||||
"""
|
||||
AssistantManager Service for GT 2.0 Tenant Backend
|
||||
|
||||
File-based agent lifecycle management with perfect tenant isolation.
|
||||
Implements the core Agent System specification from CLAUDE.md.
|
||||
"""
|
||||
|
||||
import os
|
||||
import json
|
||||
import asyncio
|
||||
from datetime import datetime
|
||||
from typing import Dict, Any, List, Optional, Union
|
||||
from sqlalchemy.ext.asyncio import AsyncSession
|
||||
from sqlalchemy import select, and_, or_, func, desc
|
||||
from sqlalchemy.orm import selectinload
|
||||
import logging
|
||||
|
||||
from app.models.agent import Agent
|
||||
from app.models.conversation import Conversation
|
||||
from app.models.message import Message
|
||||
from app.core.config import get_settings
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
class AssistantManager:
|
||||
"""File-based agent lifecycle management"""
|
||||
|
||||
def __init__(self, db: AsyncSession):
|
||||
self.db = db
|
||||
self.settings = get_settings()
|
||||
|
||||
async def create_from_template(self, template_id: str, config: Dict[str, Any], user_identifier: str) -> str:
|
||||
"""Create agent from template or custom config"""
|
||||
try:
|
||||
# Get template configuration
|
||||
template_config = await self._load_template_config(template_id)
|
||||
|
||||
# Merge template config with user overrides
|
||||
merged_config = {**template_config, **config}
|
||||
|
||||
# Create agent record
|
||||
agent = Agent(
|
||||
name=merged_config.get("name", f"Agent from {template_id}"),
|
||||
description=merged_config.get("description", f"Created from template: {template_id}"),
|
||||
template_id=template_id,
|
||||
created_by=user_identifier,
|
||||
user_name=merged_config.get("user_name"),
|
||||
personality_config=merged_config.get("personality_config", {}),
|
||||
resource_preferences=merged_config.get("resource_preferences", {}),
|
||||
memory_settings=merged_config.get("memory_settings", {}),
|
||||
tags=merged_config.get("tags", []),
|
||||
)
|
||||
|
||||
# Initialize with placeholder paths first
|
||||
agent.config_file_path = "placeholder"
|
||||
agent.prompt_file_path = "placeholder"
|
||||
agent.capabilities_file_path = "placeholder"
|
||||
|
||||
# Save to database first to get ID and UUID
|
||||
self.db.add(agent)
|
||||
await self.db.flush() # Flush to get the generated UUID without committing
|
||||
|
||||
# Now we can initialize proper file paths with the UUID
|
||||
agent.initialize_file_paths()
|
||||
|
||||
# Create file system structure
|
||||
await self._setup_assistant_files(agent, merged_config)
|
||||
|
||||
# Commit all changes
|
||||
await self.db.commit()
|
||||
await self.db.refresh(agent)
|
||||
|
||||
logger.info(
|
||||
f"Created agent from template",
|
||||
extra={
|
||||
"agent_id": agent.id,
|
||||
"assistant_uuid": agent.uuid,
|
||||
"template_id": template_id,
|
||||
"created_by": user_identifier,
|
||||
}
|
||||
)
|
||||
|
||||
return str(agent.uuid)
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Failed to create agent from template: {e}", exc_info=True)
|
||||
await self.db.rollback()
|
||||
raise
|
||||
|
||||
async def create_custom_assistant(self, config: Dict[str, Any], user_identifier: str) -> str:
|
||||
"""Create custom agent without template"""
|
||||
try:
|
||||
# Validate required fields
|
||||
if not config.get("name"):
|
||||
raise ValueError("Agent name is required")
|
||||
|
||||
# Create agent record
|
||||
agent = Agent(
|
||||
name=config["name"],
|
||||
description=config.get("description", "Custom AI agent"),
|
||||
template_id=None, # No template used
|
||||
created_by=user_identifier,
|
||||
user_name=config.get("user_name"),
|
||||
personality_config=config.get("personality_config", {}),
|
||||
resource_preferences=config.get("resource_preferences", {}),
|
||||
memory_settings=config.get("memory_settings", {}),
|
||||
tags=config.get("tags", []),
|
||||
)
|
||||
|
||||
# Initialize with placeholder paths first
|
||||
agent.config_file_path = "placeholder"
|
||||
agent.prompt_file_path = "placeholder"
|
||||
agent.capabilities_file_path = "placeholder"
|
||||
|
||||
# Save to database first to get ID and UUID
|
||||
self.db.add(agent)
|
||||
await self.db.flush() # Flush to get the generated UUID without committing
|
||||
|
||||
# Now we can initialize proper file paths with the UUID
|
||||
agent.initialize_file_paths()
|
||||
|
||||
# Create file system structure
|
||||
await self._setup_assistant_files(agent, config)
|
||||
|
||||
# Commit all changes
|
||||
await self.db.commit()
|
||||
await self.db.refresh(agent)
|
||||
|
||||
logger.info(
|
||||
f"Created custom agent",
|
||||
extra={
|
||||
"agent_id": agent.id,
|
||||
"assistant_uuid": agent.uuid,
|
||||
"created_by": user_identifier,
|
||||
}
|
||||
)
|
||||
|
||||
return str(agent.uuid)
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Failed to create custom agent: {e}", exc_info=True)
|
||||
await self.db.rollback()
|
||||
raise
|
||||
|
||||
async def get_assistant_config(self, assistant_uuid: str, user_identifier: str) -> Dict[str, Any]:
|
||||
"""Get complete agent configuration including file-based data"""
|
||||
try:
|
||||
# Get agent from database
|
||||
result = await self.db.execute(
|
||||
select(Agent).where(
|
||||
and_(
|
||||
Agent.uuid == assistant_uuid,
|
||||
Agent.created_by == user_identifier,
|
||||
Agent.is_active == True
|
||||
)
|
||||
)
|
||||
)
|
||||
agent = result.scalar_one_or_none()
|
||||
|
||||
if not agent:
|
||||
raise ValueError(f"Agent not found: {assistant_uuid}")
|
||||
|
||||
# Load complete configuration
|
||||
return agent.get_full_configuration()
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Failed to get agent config: {e}", exc_info=True)
|
||||
raise
|
||||
|
||||
async def list_user_assistants(
|
||||
self,
|
||||
user_identifier: str,
|
||||
include_archived: bool = False,
|
||||
template_id: Optional[str] = None,
|
||||
search: Optional[str] = None,
|
||||
limit: int = 50,
|
||||
offset: int = 0
|
||||
) -> List[Dict[str, Any]]:
|
||||
"""List user's agents with filtering options"""
|
||||
try:
|
||||
# Build base query
|
||||
query = select(Agent).where(Agent.created_by == user_identifier)
|
||||
|
||||
# Apply filters
|
||||
if not include_archived:
|
||||
query = query.where(Agent.is_active == True)
|
||||
|
||||
if template_id:
|
||||
query = query.where(Agent.template_id == template_id)
|
||||
|
||||
if search:
|
||||
search_term = f"%{search}%"
|
||||
query = query.where(
|
||||
or_(
|
||||
Agent.name.ilike(search_term),
|
||||
Agent.description.ilike(search_term)
|
||||
)
|
||||
)
|
||||
|
||||
# Apply ordering and pagination
|
||||
query = query.order_by(desc(Agent.last_used_at), desc(Agent.created_at))
|
||||
query = query.limit(limit).offset(offset)
|
||||
|
||||
result = await self.db.execute(query)
|
||||
agents = result.scalars().all()
|
||||
|
||||
return [agent.to_dict() for agent in agents]
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Failed to list user agents: {e}", exc_info=True)
|
||||
raise
|
||||
|
||||
async def count_user_assistants(
|
||||
self,
|
||||
user_identifier: str,
|
||||
include_archived: bool = False,
|
||||
template_id: Optional[str] = None,
|
||||
search: Optional[str] = None
|
||||
) -> int:
|
||||
"""Count user's agents matching criteria"""
|
||||
try:
|
||||
# Build base query
|
||||
query = select(func.count(Agent.id)).where(Agent.created_by == user_identifier)
|
||||
|
||||
# Apply filters
|
||||
if not include_archived:
|
||||
query = query.where(Agent.is_active == True)
|
||||
|
||||
if template_id:
|
||||
query = query.where(Agent.template_id == template_id)
|
||||
|
||||
if search:
|
||||
search_term = f"%{search}%"
|
||||
query = query.where(
|
||||
or_(
|
||||
Agent.name.ilike(search_term),
|
||||
Agent.description.ilike(search_term)
|
||||
)
|
||||
)
|
||||
|
||||
result = await self.db.execute(query)
|
||||
return result.scalar() or 0
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Failed to count user agents: {e}", exc_info=True)
|
||||
raise
|
||||
|
||||
async def update_assistant(self, agent_id: str, updates: Dict[str, Any], user_identifier: str) -> bool:
|
||||
"""Update agent configuration (renamed from update_configuration)"""
|
||||
return await self.update_configuration(agent_id, updates, user_identifier)
|
||||
|
||||
async def update_configuration(self, assistant_uuid: str, updates: Dict[str, Any], user_identifier: str) -> bool:
|
||||
"""Update agent configuration"""
|
||||
try:
|
||||
# Get agent
|
||||
result = await self.db.execute(
|
||||
select(Agent).where(
|
||||
and_(
|
||||
Agent.uuid == assistant_uuid,
|
||||
Agent.created_by == user_identifier,
|
||||
Agent.is_active == True
|
||||
)
|
||||
)
|
||||
)
|
||||
agent = result.scalar_one_or_none()
|
||||
|
||||
if not agent:
|
||||
raise ValueError(f"Agent not found: {assistant_uuid}")
|
||||
|
||||
# Update database fields
|
||||
if "name" in updates:
|
||||
agent.name = updates["name"]
|
||||
if "description" in updates:
|
||||
agent.description = updates["description"]
|
||||
if "personality_config" in updates:
|
||||
agent.personality_config = updates["personality_config"]
|
||||
if "resource_preferences" in updates:
|
||||
agent.resource_preferences = updates["resource_preferences"]
|
||||
if "memory_settings" in updates:
|
||||
agent.memory_settings = updates["memory_settings"]
|
||||
if "tags" in updates:
|
||||
agent.tags = updates["tags"]
|
||||
|
||||
# Update file-based configurations
|
||||
if "config" in updates:
|
||||
agent.save_config_to_file(updates["config"])
|
||||
if "prompt" in updates:
|
||||
agent.save_prompt_to_file(updates["prompt"])
|
||||
if "capabilities" in updates:
|
||||
agent.save_capabilities_to_file(updates["capabilities"])
|
||||
|
||||
agent.updated_at = datetime.utcnow()
|
||||
await self.db.commit()
|
||||
|
||||
logger.info(
|
||||
f"Updated agent configuration",
|
||||
extra={
|
||||
"assistant_uuid": assistant_uuid,
|
||||
"updated_fields": list(updates.keys()),
|
||||
}
|
||||
)
|
||||
|
||||
return True
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Failed to update agent configuration: {e}", exc_info=True)
|
||||
await self.db.rollback()
|
||||
raise
|
||||
|
||||
async def clone_assistant(self, source_uuid: str, new_name: str, user_identifier: str, modifications: Dict[str, Any] = None) -> str:
|
||||
"""Clone existing agent with modifications"""
|
||||
try:
|
||||
# Get source agent
|
||||
result = await self.db.execute(
|
||||
select(Agent).where(
|
||||
and_(
|
||||
Agent.uuid == source_uuid,
|
||||
Agent.created_by == user_identifier,
|
||||
Agent.is_active == True
|
||||
)
|
||||
)
|
||||
)
|
||||
source_assistant = result.scalar_one_or_none()
|
||||
|
||||
if not source_assistant:
|
||||
raise ValueError(f"Source agent not found: {source_uuid}")
|
||||
|
||||
# Clone agent
|
||||
cloned_assistant = source_assistant.clone(new_name, user_identifier, modifications or {})
|
||||
|
||||
# Initialize with placeholder paths first
|
||||
cloned_assistant.config_file_path = "placeholder"
|
||||
cloned_assistant.prompt_file_path = "placeholder"
|
||||
cloned_assistant.capabilities_file_path = "placeholder"
|
||||
|
||||
# Save to database first to get UUID
|
||||
self.db.add(cloned_assistant)
|
||||
await self.db.flush() # Flush to get the generated UUID
|
||||
|
||||
# Initialize proper file paths with UUID
|
||||
cloned_assistant.initialize_file_paths()
|
||||
|
||||
# Copy and modify files
|
||||
await self._clone_assistant_files(source_assistant, cloned_assistant, modifications or {})
|
||||
|
||||
# Commit all changes
|
||||
await self.db.commit()
|
||||
await self.db.refresh(cloned_assistant)
|
||||
|
||||
logger.info(
|
||||
f"Cloned agent",
|
||||
extra={
|
||||
"source_uuid": source_uuid,
|
||||
"new_uuid": cloned_assistant.uuid,
|
||||
"new_name": new_name,
|
||||
}
|
||||
)
|
||||
|
||||
return str(cloned_assistant.uuid)
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Failed to clone agent: {e}", exc_info=True)
|
||||
await self.db.rollback()
|
||||
raise
|
||||
|
||||
async def archive_assistant(self, assistant_uuid: str, user_identifier: str) -> bool:
|
||||
"""Archive agent (soft delete)"""
|
||||
try:
|
||||
result = await self.db.execute(
|
||||
select(Agent).where(
|
||||
and_(
|
||||
Agent.uuid == assistant_uuid,
|
||||
Agent.created_by == user_identifier
|
||||
)
|
||||
)
|
||||
)
|
||||
agent = result.scalar_one_or_none()
|
||||
|
||||
if not agent:
|
||||
raise ValueError(f"Agent not found: {assistant_uuid}")
|
||||
|
||||
agent.archive()
|
||||
await self.db.commit()
|
||||
|
||||
logger.info(
|
||||
f"Archived agent",
|
||||
extra={"assistant_uuid": assistant_uuid}
|
||||
)
|
||||
|
||||
return True
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Failed to archive agent: {e}", exc_info=True)
|
||||
await self.db.rollback()
|
||||
raise
|
||||
|
||||
async def get_assistant_statistics(self, assistant_uuid: str, user_identifier: str) -> Dict[str, Any]:
|
||||
"""Get usage statistics for agent"""
|
||||
try:
|
||||
result = await self.db.execute(
|
||||
select(Agent).where(
|
||||
and_(
|
||||
Agent.uuid == assistant_uuid,
|
||||
Agent.created_by == user_identifier,
|
||||
Agent.is_active == True
|
||||
)
|
||||
)
|
||||
)
|
||||
agent = result.scalar_one_or_none()
|
||||
|
||||
if not agent:
|
||||
raise ValueError(f"Agent not found: {assistant_uuid}")
|
||||
|
||||
# Get conversation statistics
|
||||
conv_result = await self.db.execute(
|
||||
select(func.count(Conversation.id))
|
||||
.where(Conversation.agent_id == agent.id)
|
||||
)
|
||||
conversation_count = conv_result.scalar() or 0
|
||||
|
||||
# Get message statistics
|
||||
msg_result = await self.db.execute(
|
||||
select(
|
||||
func.count(Message.id),
|
||||
func.sum(Message.tokens_used),
|
||||
func.sum(Message.cost_cents)
|
||||
)
|
||||
.join(Conversation, Message.conversation_id == Conversation.id)
|
||||
.where(Conversation.agent_id == agent.id)
|
||||
)
|
||||
message_stats = msg_result.first()
|
||||
|
||||
return {
|
||||
"agent_id": assistant_uuid, # Use agent_id to match schema
|
||||
"name": agent.name,
|
||||
"created_at": agent.created_at, # Return datetime object, not ISO string
|
||||
"last_used_at": agent.last_used_at, # Return datetime object, not ISO string
|
||||
"conversation_count": conversation_count,
|
||||
"total_messages": message_stats[0] or 0,
|
||||
"total_tokens_used": message_stats[1] or 0,
|
||||
"total_cost_cents": message_stats[2] or 0,
|
||||
"total_cost_dollars": (message_stats[2] or 0) / 100.0,
|
||||
"average_tokens_per_message": (
|
||||
(message_stats[1] or 0) / max(1, message_stats[0] or 1)
|
||||
),
|
||||
"is_favorite": agent.is_favorite,
|
||||
"tags": agent.tags,
|
||||
}
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Failed to get agent statistics: {e}", exc_info=True)
|
||||
raise
|
||||
|
||||
# Private helper methods
|
||||
|
||||
async def _load_template_config(self, template_id: str) -> Dict[str, Any]:
|
||||
"""Load template configuration from Resource Cluster or built-in templates"""
|
||||
# Built-in templates (as specified in CLAUDE.md)
|
||||
builtin_templates = {
|
||||
"research_assistant": {
|
||||
"name": "Research & Analysis Agent",
|
||||
"description": "Specialized in information synthesis and analysis",
|
||||
"prompt": """You are a research agent specialized in information synthesis and analysis.
|
||||
Focus on providing well-sourced, analytical responses with clear reasoning.""",
|
||||
"personality_config": {
|
||||
"tone": "balanced",
|
||||
"explanation_depth": "expert",
|
||||
"interaction_style": "collaborative"
|
||||
},
|
||||
"resource_preferences": {
|
||||
"primary_llm": "groq:llama3-70b-8192",
|
||||
"temperature": 0.7,
|
||||
"max_tokens": 4000
|
||||
},
|
||||
"capabilities": [
|
||||
{"resource": "llm:groq", "actions": ["inference"], "limits": {"max_tokens_per_request": 4000}},
|
||||
{"resource": "rag:semantic_search", "actions": ["search"], "limits": {}},
|
||||
{"resource": "tools:web_search", "actions": ["search"], "limits": {"requests_per_hour": 50}},
|
||||
{"resource": "export:citations", "actions": ["create"], "limits": {}}
|
||||
]
|
||||
},
|
||||
"coding_assistant": {
|
||||
"name": "Software Development Agent",
|
||||
"description": "Focused on code quality and best practices",
|
||||
"prompt": """You are a software development agent focused on code quality and best practices.
|
||||
Provide clear explanations, suggest improvements, and help debug issues.""",
|
||||
"personality_config": {
|
||||
"tone": "direct",
|
||||
"explanation_depth": "intermediate",
|
||||
"interaction_style": "teaching"
|
||||
},
|
||||
"resource_preferences": {
|
||||
"primary_llm": "groq:llama3-70b-8192",
|
||||
"temperature": 0.3,
|
||||
"max_tokens": 4000
|
||||
},
|
||||
"capabilities": [
|
||||
{"resource": "llm:groq", "actions": ["inference"], "limits": {"max_tokens_per_request": 4000}},
|
||||
{"resource": "tools:github_integration", "actions": ["read"], "limits": {}},
|
||||
{"resource": "resources:documentation", "actions": ["search"], "limits": {}},
|
||||
{"resource": "export:code_snippets", "actions": ["create"], "limits": {}}
|
||||
]
|
||||
},
|
||||
"cyber_analyst": {
|
||||
"name": "Cybersecurity Analysis Agent",
|
||||
"description": "For threat detection and response analysis",
|
||||
"prompt": """You are a cybersecurity analyst agent for threat detection and response.
|
||||
Prioritize security best practices and provide actionable recommendations.""",
|
||||
"personality_config": {
|
||||
"tone": "formal",
|
||||
"explanation_depth": "expert",
|
||||
"interaction_style": "direct"
|
||||
},
|
||||
"resource_preferences": {
|
||||
"primary_llm": "groq:llama3-70b-8192",
|
||||
"temperature": 0.2,
|
||||
"max_tokens": 4000
|
||||
},
|
||||
"capabilities": [
|
||||
{"resource": "llm:groq", "actions": ["inference"], "limits": {"max_tokens_per_request": 4000}},
|
||||
{"resource": "tools:security_scanning", "actions": ["analyze"], "limits": {}},
|
||||
{"resource": "resources:threat_intelligence", "actions": ["search"], "limits": {}},
|
||||
{"resource": "export:security_reports", "actions": ["create"], "limits": {}}
|
||||
]
|
||||
},
|
||||
"educational_tutor": {
|
||||
"name": "AI Literacy Educational Agent",
|
||||
"description": "Develops critical thinking and AI literacy",
|
||||
"prompt": """You are an educational agent focused on developing critical thinking and AI literacy.
|
||||
Use socratic questioning and encourage deep analysis of problems.""",
|
||||
"personality_config": {
|
||||
"tone": "casual",
|
||||
"explanation_depth": "beginner",
|
||||
"interaction_style": "teaching"
|
||||
},
|
||||
"resource_preferences": {
|
||||
"primary_llm": "groq:llama3-70b-8192",
|
||||
"temperature": 0.8,
|
||||
"max_tokens": 3000
|
||||
},
|
||||
"capabilities": [
|
||||
{"resource": "llm:groq", "actions": ["inference"], "limits": {"max_tokens_per_request": 3000}},
|
||||
{"resource": "games:strategic_thinking", "actions": ["play"], "limits": {}},
|
||||
{"resource": "puzzles:logic_reasoning", "actions": ["present"], "limits": {}},
|
||||
{"resource": "analytics:learning_progress", "actions": ["track"], "limits": {}}
|
||||
]
|
||||
}
|
||||
}
|
||||
|
||||
if template_id in builtin_templates:
|
||||
return builtin_templates[template_id]
|
||||
|
||||
# TODO: In the future, load from Resource Cluster Agent Library
|
||||
# For now, return empty config for unknown templates
|
||||
logger.warning(f"Unknown template ID: {template_id}")
|
||||
return {
|
||||
"name": f"Agent ({template_id})",
|
||||
"description": "Custom agent",
|
||||
"prompt": "You are a helpful AI agent.",
|
||||
"capabilities": []
|
||||
}
|
||||
|
||||
async def _setup_assistant_files(self, agent: Agent, config: Dict[str, Any]) -> None:
|
||||
"""Create file system structure for agent"""
|
||||
# Ensure directory exists
|
||||
agent.ensure_directory_exists()
|
||||
|
||||
# Save configuration files
|
||||
agent.save_config_to_file(config)
|
||||
agent.save_prompt_to_file(config.get("prompt", "You are a helpful AI agent."))
|
||||
agent.save_capabilities_to_file(config.get("capabilities", []))
|
||||
|
||||
logger.info(f"Created agent files for {agent.uuid}")
|
||||
|
||||
async def _clone_assistant_files(self, source: Agent, target: Agent, modifications: Dict[str, Any]) -> None:
|
||||
"""Clone agent files with modifications"""
|
||||
# Load source configurations
|
||||
source_config = source.load_config_from_file()
|
||||
source_prompt = source.load_prompt_from_file()
|
||||
source_capabilities = source.load_capabilities_from_file()
|
||||
|
||||
# Apply modifications
|
||||
target_config = {**source_config, **modifications.get("config", {})}
|
||||
target_prompt = modifications.get("prompt", source_prompt)
|
||||
target_capabilities = modifications.get("capabilities", source_capabilities)
|
||||
|
||||
# Create target files
|
||||
target.ensure_directory_exists()
|
||||
target.save_config_to_file(target_config)
|
||||
target.save_prompt_to_file(target_prompt)
|
||||
target.save_capabilities_to_file(target_capabilities)
|
||||
|
||||
logger.info(f"Cloned agent files from {source.uuid} to {target.uuid}")
|
||||
|
||||
|
||||
async def get_assistant_manager(db: AsyncSession) -> AssistantManager:
|
||||
"""Get AssistantManager instance"""
|
||||
return AssistantManager(db)
|
||||
Reference in New Issue
Block a user