Run Agent Spec configurations with CrewAI

# Create a Agent Spec agent
from pyagentspec.agent import Agent
from pyagentspec.llms.openaicompatibleconfig import OpenAiCompatibleConfig
from pyagentspec.property import FloatProperty
from pyagentspec.tools import ServerTool

subtraction_tool = ServerTool(
    name="subtraction-tool",
    description="subtract two numbers together",
    inputs=[FloatProperty(title="a"), FloatProperty(title="b")],
    outputs=[FloatProperty(title="difference")],
)

agentspec_llm_config = OpenAiCompatibleConfig(
    name="llama-3.3-70b-instruct",
    model_id="/storage/models/Llama-3.3-70B-Instruct",
    url="url.to.my.llm",
)

agentspec_agent = Agent(
    name="agentspec_tools_test",
    description="agentspec_tools_test",
    llm_config=agentspec_llm_config,
    system_prompt="Perform subtraction with the given tool.",
    tools=[subtraction_tool],
)

# Export the Agent Spec configuration
from pyagentspec.serialization import AgentSpecSerializer

agentspec_config = AgentSpecSerializer().to_json(agentspec_agent)

# Load and run the Agent Spec configuration with CrewAI
import os
os.environ["CREWAI_DISABLE_TELEMETRY"] = "true"
from crewai import Crew, Task
from pyagentspec.adapters.crewai import AgentSpecLoader

def subtract(a: float, b: float) -> float:
    return a - b

async def main():
    loader = AgentSpecLoader(tool_registry={"subtraction-tool": subtract})
    assistant = loader.load_json(agentspec_config)

    while True:
        task = Task(
            description="{user_input}",
            expected_output="A helpful, concise reply to the user.",
            agent=assistant,
            async_execution=True
        )
        crew = Crew(agents=[assistant], tasks=[task])
        user_input = input("USER >> ")
        if user_input == "exit":
            break
        response = await crew.kickoff_async(inputs={"user_input": user_input})
        print(f"AGENT >> {response}")


# anyio.run(main)
# USER >> Compute 987654321-123456789
# AGENT >> 864197532