IBM watsonx Orchestrate

import asyncio
import sys
import traceback

from beeai_framework.adapters.watsonx_orchestrate.agents import WatsonxOrchestrateAgent
from beeai_framework.errors import FrameworkError
from examples.helpers.io import ConsoleReader


async def main() -> None:
    reader = ConsoleReader()

    agent = WatsonxOrchestrateAgent(
        # To find your instance URL, visit IBM watsonx Orchestrate -> Settings -> API Details
        # Example: https://api.eu-de.watson-orchestrate.cloud.ibm.com/instances/aaaaaa-bbbb-cccc-dddd-eeeeeeeee
        instance_url="YOUR_INSTANCE_URL",
        # To find agent's ID, visit IBM watsonx Orchestrate -> Select any existing agent -> copy the last part of the URL ()
        # Example: 1xfa8c27-6d0f-4962-9eb5-4e1c0b8073d8
        agent_id="YOUR_AGENT_ID",
        # Auth type, typically IAM (hosted version) or JWT for custom deployments
        auth_type="iam",
        # To find your API Key, visit IBM watsonx Orchestrate -> Settings -> API Details -> Generate API Key
        api_key="YOUR_API_KEY",
    )
    for prompt in reader:
        response = await agent.run(prompt)
        reader.write("Agent 🤖 : ", response.last_message.text)


if __name__ == "__main__":
    try:
        asyncio.run(main())
    except FrameworkError as e:
        traceback.print_exc()
        sys.exit(e.explain())

from beeai_framework.adapters.watsonx_orchestrate import WatsonxOrchestrateServer, WatsonxOrchestrateServerConfig
from beeai_framework.agents.requirement import RequirementAgent
from beeai_framework.backend import ChatModel
from beeai_framework.memory import UnconstrainedMemory
from beeai_framework.serve.utils import LRUMemoryManager
from beeai_framework.tools.weather import OpenMeteoTool


def main() -> None:
    llm = ChatModel.from_name("ollama:granite4:micro")
    agent = RequirementAgent(llm=llm, tools=[OpenMeteoTool()], memory=UnconstrainedMemory(), role="a weather agent")

    config = WatsonxOrchestrateServerConfig(port=8080, host="0.0.0.0", api_key=None)  # optional
    # use LRU memory manager to keep limited amount of sessions in the memory
    server = WatsonxOrchestrateServer(config=config, memory_manager=LRUMemoryManager(maxsize=100))
    server.register(agent)

    # start an API with /chat/completions endpoint which is compatible with Watsonx Orchestrate
    server.serve()


if __name__ == "__main__":
    main()