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from src.budget_manager import BudgetManager
from src.agent_manager import AgentManager
__all__ = ['AskAgent']
class AskAgent():
dependencies = ["ollama==0.4.7",
"pydantic==2.11.1",
"pydantic_core==2.33.0"]
inputSchema = {
"name": "AskAgent",
"description": "Asks an AI agent a question and gets a response. The agent must be created using the AgentCreator tool before using this tool.",
"parameters": {
"type": "object",
"properties": {
"agent_name": {
"type": "string",
"description": "Name of the AI agent that is to be asked a question. This name cannot have spaces or special characters. It should be a single word.",
},
"prompt": {
"type": "string",
"description": "This is the prompt that will be used to ask the agent a question. It should be a string that describes the question to be asked.",
}
},
"required": ["agent_name", "prompt"],
}
}
def run(self, **kwargs):
print("Asking agent a question")
agent_name = kwargs.get("agent_name")
prompt = kwargs.get("prompt")
agent_manger = AgentManager()
budget_manager = BudgetManager()
try:
agent = agent_manger.get_agent(agent_name=agent_name)
except ValueError as e:
return {
"status": "error",
"message": f"Error occurred: {str(e)}",
"output": None
}
agent_costs = agent.get_costs()
agent_question_cost = agent_costs["invoke_cost"]
print("Agent question cost", agent_question_cost)
if not budget_manager.can_spend(agent_question_cost):
return {
"status": "error",
"message": f"Do not have enough budget to ask the agent a question. Asking the agent costs {agent_question_cost} but only {budget_manager.get_current_remaining_budget()} is remaining",
"output": None
}
agent_response = agent.ask_agent(prompt=prompt)
print("Agent response", agent_response)
return {
"status": "success",
"message": "Agent has replied to the given prompt",
"output": agent_response,
}
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