from typing import Any, List
from agno.agent import Agent
from agno.models.base import Model
from agno.db.postgres import PostgresDb
from agents.agent_ids import AgentID
from db.session import db_url
def create_ibmi_agent(
id: AgentID,
name: str,
model: Model,
description: str,
instructions: str,
tools: List[Any] = None,
debug_mode: bool = False,
) -> Agent:
"""
Internal factory for creating IBM i agents with shared configuration.
This function centralizes all common Agent settings (database, history,
memory, formatting) while allowing agent-specific customization through
the parameters.
Args:
agent_id: Unique identifier from AgentID enum
name: Human-readable agent name
model: Model instance (already processed by get_model())
description: Agent description for system prompt
instructions: Detailed agent instructions
tools: List of tools available to the agent
debug_mode: Enable debug logging
Returns:
Configured Agent instance with shared IBM i agent settings
"""
return Agent(
id=id,
name=name,
model=model,
description=description,
instructions=instructions,
tools=tools,
debug_mode=debug_mode,
# -*- Default Settings -*-
markdown=True,
add_datetime_to_context=True,
# -*- Storage -*-
# Storage chat history and session state in a Postgres table
db=PostgresDb(id="agno-storage", db_url=db_url),
# --- Session settings ---
search_session_history=True,
num_history_sessions=2,
# --- Agent History ---
add_history_to_context=True,
num_history_runs=3,
# num_history_messages=2,
# --- Default tools ---
# Add a tool to read the chat history if needed
read_chat_history=True,
read_tool_call_history=True,
# --- Agent Response Settings ---
retries=3,
# -*- Memory -*-
# Enable agentic memory where the Agent can personalize responses to the user
enable_agentic_memory=True,
)
