| from src.manager.agent_manager import AgentManager |
| from src.tools.default_tools.agent_cost_manager import AgentCostManager |
| __all__ = ['AgentCreator'] |
|
|
| class AgentCreator(): |
| dependencies = ["ollama==0.4.7", |
| "pydantic==2.11.1", |
| "pydantic_core==2.33.0"] |
|
|
| inputSchema = { |
| "name": "AgentCreator", |
| "description": "Creates an AI agent for you. Please make sure to invoke the created agent using the AskAgent tool.", |
| "parameters": { |
| "type": "object", |
| "properties":{ |
| "agent_name": { |
| "type": "string", |
| "description": "Name of the AI agent that is to be created. This name cannot have spaces or special characters. It should be a single word.", |
| }, |
| "base_model": { |
| "type": "string", |
| "description": "A base model from which the new agent mode is to be created. Check the available models using the AgentCostManager tool.", |
| }, |
| "system_prompt": { |
| "type": "string", |
| "description": "This is the system prompt that will be used to create the agent. It should be a string that describes the role of the agent and its capabilities." |
| }, |
| "description": { |
| "type": "string", |
| "description": "Description of the agent. This is a string that describes the agent and its capabilities. It should be a single line description.", |
| }, |
| }, |
| "required": ["agent_name", "base_model", "system_prompt", "description"], |
| } |
| } |
|
|
|
|
| def run(self, **kwargs): |
| print("Running Agent Creator") |
| agent_name = kwargs.get("agent_name") |
| base_model = kwargs.get("base_model") |
|
|
| print(f"[DEBUG] Selected Model: {base_model}") |
|
|
| system_prompt = kwargs.get("system_prompt") |
| description = kwargs.get("description") |
| model_costs = AgentCostManager().get_costs() |
| if base_model not in model_costs: |
| return { |
| "status": "error", |
| "message": f"Model {base_model} not found in the cost manager.", |
| "output": None |
| } |
| create_resource_cost = model_costs[base_model].get("create_resource_cost", 0) |
| invoke_resource_cost = model_costs[base_model].get("invoke_resource_cost", 0) |
| create_expense_cost = model_costs[base_model].get("create_expense_cost", 0) |
| invoke_expense_cost = model_costs[base_model].get("invoke_expense_cost", 0) |
| output_expense_cost = model_costs[base_model].get("output_expense_cost", 0) |
|
|
| agent_manager = AgentManager() |
| try: |
| _, remaining_resource_budget, remaining_expense_budget = agent_manager.create_agent( |
| agent_name=agent_name, |
| base_model=base_model, |
| system_prompt=system_prompt, |
| description=description, |
| create_resource_cost=create_resource_cost, |
| invoke_resource_cost=invoke_resource_cost, |
| create_expense_cost=create_expense_cost, |
| invoke_expense_cost=invoke_expense_cost, |
| output_expense_cost=output_expense_cost |
| ) |
| except ValueError as e: |
| return { |
| "status": "error", |
| "message": f"Error occurred: {str(e)}", |
| "output": None |
| } |
| |
| return { |
| "status": "success", |
| "message": "Agent successfully created", |
| "remaining_resource_budget": remaining_resource_budget, |
| "remaining_expense_budget": remaining_expense_budget |
| } |
